scientific theory case study

Scientific Management Theory: Definition, History, Principles, Examples, and FAQs

Table of Contents

What is Scientific Management Theory?

Scientific management theory, also known as Taylorism, is a management approach aimed at improving economic efficiency and labor productivity. Developed by Frederick W. Taylor (1856-1915), it applies scientific methods to analyze workflows and optimize production processes.

By conducting research, collecting data, and applying the scientific method, managers can identify the most efficient ways to complete tasks. Taylor emphasized the importance of training workers to maximize their efficiency, leading to higher productivity.

The core principles include selecting methods based on science, assigning tasks based on worker aptitudes, monitoring performance, and properly dividing the workload.

It has significantly impacted management practices , focusing on evidence-based approaches and setting clear expectations for employees. By implementing scientific management, organizations can achieve greater efficiency and productivity.

A Brief History of Scientific Management Theory

The history of scientific management theory dates back to the early 20th century and is credited to Frederick Winslow Taylor (1856-1915). In 1911, Taylor published his groundbreaking book titled “Principles of Scientific Management,” where he outlined the fundamental principles of this management approach.

Taylor, often referred to as the “Father of Scientific Management,” worked at various companies, including Bethlehem Steel, where he observed the need for more efficient work processes.

His key contributions involved conducting time and motion studies to identify the most effective ways of performing tasks. Taylor’s approach focused on replacing traditional “rule of thumb” methods with scientific methods to achieve economic efficiency and increase productivity. His ideas revolutionized management practices, emphasizing specialization , training, and optimizing workflows.

Today, his legacy lives on as scientific management continues to influence modern organizational strategies, prioritizing evidence-based and systematic approaches to improve efficiency and productivity in various industries.

Also Read: What is Participative Management?

Studies in Scientific Management Theory

Taylor’s scientific management is based on the following studies. These four studies are fundamental components of scientific management theory.

Motion Study

This study involves carefully observing how workers perform tasks to identify and eliminate unnecessary movements. By streamlining work processes and optimizing movements , it aims to enhance efficiency and productivity in the workplace.

In a time study, the precise time required to complete a specific task is determined. This helps in organizing work activities, assigning duties effectively, and creating efficient work schedules, ultimately reducing idle time and maximizing productivity.

Fatigue Study

The focus of this study is on researching and addressing employee fatigue and exhaustion. By determining appropriate working hours and breaks, it ensures that employees are well-rested and energized, leading to increased productivity and improved well-being.

Rate Setting

Rate setting involves establishing differential piece wages based on workers’ performance. Efficient workers who meet or exceed standards are rewarded with higher pay, providing an incentive for productivity and linking pay directly to output achieved.

Principles of Scientific Management Theory

Let’s explore the principles of management by F.W. Taylor.

Science, not the Rule of Thumb

Scientific management emphasizes the use of proven scientific methods instead of relying on traditional and arbitrary rules of thumb. By carefully analyzing work processes and tasks through scientific observation and measurement, managers can identify the most efficient and effective methods to achieve optimal results.

Harmony, Not Discord

Scientific management promotes cooperation and harmony between workers and management. Instead of adversarial relationships, the focus is on creating a work environment where both parties work together towards shared goals. This fosters a positive and productive atmosphere, leading to improved morale and teamwork.

Mental Revolution

A mental revolution is required to adopt scientific management principles fully. Both workers and management must shift their mindset towards embracing the benefits of scientific approaches to work. This entails accepting change, continuous improvement, and open communication between all levels of the organization.

Related : What is Equity Principle?

Cooperation, not Individualism

Scientific management encourages cooperation among workers and discourages individualism. By working together as a team, employees can accomplish tasks more efficiently and achieve higher productivity. Teamwork also fosters a sense of camaraderie and mutual support within the organization .

Development of Every Person to His Greatest Efficiency

Scientific management aims to develop each individual worker to reach their highest potential. This involves selecting employees based on their skills and aptitudes, providing appropriate training, and creating opportunities for personal growth and advancement. By maximizing each person’s efficiency, the overall productivity of the organization can be significantly enhanced.

Contribution of Scientific Management Theory

The followings are the key contributions of Taylor’s scientific management approach.

Application of scientific methods to analyze and improve work processes.
Emphasis on efficiency and productivity through optimized work methods.
Introduction of time and motion studies to reduce waste and streamline tasks.
Focus on training and development to enhance worker skills and performance.
Promotion of cooperation and teamwork between workers and management.

Limitations of Scientific Management Approach

Taylor’s management approach also has some limitations.

Overemphasis on technical efficiency, neglecting human aspects of work.
Standardization of tasks may lead to monotonous and demotivated workers.
Ignored the social and psychological needs of workers.
Employee resistance and opposition to being treated as mere cogs in a machine.

Contributors to Scientific Management Approach

Throughout history, different thinkers have contributed to scientific management schools. They include:

Related : D efinitions of Management by Different Scholars

Frederick Winslow Taylor (1856 – 1915) : Known as the “Father of Scientific Management,” he developed the principles of scientific management and emphasized the use of scientific methods to optimize efficiency and productivity.
Henry L. Gantt (1861 – 1919) : An industrial and mechanical engineer, he introduced Gantt charts as a visual tool for project management and played a significant role in promoting scientific management principles.
Frank Gilbreth (1868 – 1924) : Efficiency and industrial engineering expert, he focused on motion studies to improve work processes and efficiency.
Lillian Gilbreth (1878 – 1972): Efficiency expert and psychologist, she contributed to motion studies and studied individual psychology within organizations.
Harrington Emerson (1853 – 1931) : An efficiency engineer and management consultant, he developed “Efficiency Management” based on scientific principles and functional management.
Morris L. Cooke (1872 – 1960) : A practitioner of scientific management, he worked closely with Taylor and implemented these principles in various industries.
Carl G. Barth (1860 – 1939) : An engineer and mathematician, he advocated for the use of scientific methods in industrial operations.
Sanford E. Thompson (1867 – 1949): An academic and practitioner, he focused on efficiency through time studies and tool development in collaboration with Taylor.

Examples of Scientific Management Theory

Let’s look at some organizations at how they have implemented scientific management theory in their workplace. These examples prove that this management approach is still relevant in today’s business landscape.

McDonald’s:

McDonald’s is a well-known fast-food restaurant chain that has implemented scientific management theory in its operations. The company uses time and motion studies to analyze and optimize its food preparation processes, ensuring that tasks are completed efficiently and with minimal waste. By standardizing procedures, training employees, and using efficient equipment, McDonald’s achieves consistency in food quality and service across its numerous locations worldwide.

Amazon, a global e-commerce giant, utilizes scientific management principles in its fulfillment centers to enhance efficiency. The company employs time studies to determine the most efficient picking and packing processes for its vast inventory of products. Amazon also utilizes technology, such as robots and automated conveyor systems, to optimize the movement of goods within its fulfillment centers, reducing the time it takes to fulfill customer orders.

Ford Motor Company:

Ford Motor Company, founded by Henry Ford, adopted scientific management principles in its automobile manufacturing processes. The company introduced assembly line techniques, breaking down car production into specific tasks to maximize efficiency and reduce production time. This innovation revolutionized the automobile industry, enabling Ford to mass-produce vehicles at a faster rate and at a more affordable price, making cars accessible to a broader population.

Also Read: 8 Pros and 6 Cons of Workforce Diversity in the Workplace

Time Study Vs. Motion Study

Motion study involves observing and analyzing how workers move while performing tasks. It aims to identify and eliminate unnecessary movements to streamline work processes. The focus is on optimizing the physical movements of personnel and machinery.

On the other hand, time study determines the precise time required to complete a specific task. It helps in organizing work activities, assigning duties, and establishing efficient schedules. The primary goal is to reduce idle time and improve overall efficiency by optimizing the time taken to complete tasks.

In summary, motion study deals with movement optimization, while time study focuses on task time optimization.

Scientific Management Theory: FAQs

Let’s look at some frequently asked questions (FAQs) about Taylor’s scientific management theory.

Scientific management theory is a management approach developed by Federick W. Taylor that aims to increase efficiency and productivity in the workplace through scientific means.

What is Taylorism?

Taylorism, also known as scientific management, is a management approach that aims to improve productivity and efficiency by using scientific methods to analyze and optimize work processes. It emphasizes standardizing tasks, training workers for specific jobs, and rewarding performance based on output. Taylorism seeks to replace outdated “rule of thumb” methods with evidence-based practices to achieve economic efficiency in organizations.

What are the Components of Scientific Management Theory?

Components of scientific management include – time study, motion study, fatigue study, and rate setting.

What are the Principles of Scientific Management Theory?

Principles of scientific management theory include – Science, not the Rule of Thumb, Harmony, Not Discord, Mental Revolution, Cooperation, not Individualism, and Development of Every Person to His Greatest Efficiency.

What is Time Study?

Time study is a technique used in scientific management to determine the precise time required to complete a specific task. It involves observing and measuring each element of the task, then organizing them into an optimal sequence. Time study helps in setting efficient work schedules and reducing idle time, leading to increased productivity.

What is Motion Study?

Motion study is a scientific management technique used to analyze how operators move while performing tasks. It aims to identify and eliminate unnecessary motion to streamline work processes and optimize movement. By studying and improving the motions involved in a task, motion study enhances productivity and reduces fatigue and inefficiencies.

Sujan Chaudhary is a BBA graduate. He loves to share his business knowledge with the rest of the world. While not writing, he will be found reading and exploring the world.

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4 Business Ideas That Changed the World: Scientific Management

A roundtable conversation on Taylorism and how it shapes management still today.

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In 1878, a machinist at a Pennsylvania steelworks noticed that his crew was producing much less than he thought they could. With stopwatches and time-motion studies, Frederick Winslow Taylor ran experiments to find the optimal way to make the most steel with lower labor costs. It was the birth of a management theory, called scientific management or Taylorism.

Critics said Taylor’s drive for industrial efficiency depleted workers physically and emotionally. Resentful laborers walked off the job. The U.S. Congress held hearings on it. Still, scientific management was the dominant management theory 100 years ago in October of 1922, when Harvard Business Review was founded.

It spread around the world, fueled the rise of big business, and helped decide World War II. And today it is baked into workplaces, from call centers to restaurant kitchens, gig worker algorithms, and offices. Although few modern workers would recognize Taylorism, and few employers would admit to it.

4 Business Ideas That Changed the World is a special series from HBR IdeaCast . Each week, an HBR editor talks to world-class scholars and experts on the most influential ideas of HBR’s first 100 years, such as disruptive innovation, shareholder value, and emotional intelligence.

Discussing scientific management with HBR senior editor Curt Nickisch are:

Nancy Koehn , historian at Harvard Business School
Michela Giorcelli , economic historian at UCLA
Louis Hyman , work and labor historian at Cornell University

Latest in this series

This article is about business history.

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Operations and supply chain management

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What is Scientific Management Theory? Scientific Management Theory In A Nutshell

Scientific Management Theory was created by Frederick Winslow Taylor in 1911 as a means of encouraging industrial companies to switch to mass production. With a background in mechanical engineering, he applied engineering principles to workplace productivity on the factory floor. Scientific Management Theory seeks to find the most efficient way of performing a job in the workplace.

Component	Description
Definition	Scientific Management Theory is a management approach that focuses on optimizing work processes by applying scientific methods to identify the most efficient way to perform tasks and allocate resources. It emphasizes the use of data and systematic analysis to improve productivity.
Origin	Developed by Frederick Winslow Taylor in the late 19th and early 20th centuries, Scientific Management Theory emerged during the Industrial Revolution as a response to the need for increased efficiency in manufacturing and production processes.
Principles	– : Scientific management involves breaking down tasks into smaller, measurable elements to determine the most efficient way to perform them. This often includes time and motion studies to identify optimal work methods. – : Taylor advocated for standardizing work methods and tools to eliminate variability and increase predictability. – : Employees should be selected based on their skills and abilities, matching them to specific job roles. – : Providing training and development to workers to ensure they can perform tasks optimally. – : Introducing performance-based incentive systems to motivate workers to achieve higher productivity.
Importance	Scientific Management Theory played a significant role in shaping modern management practices by introducing systematic approaches to work processes, data-driven decision-making, and the concept of efficiency in organizations.
Benefits	– : Scientific management aims to eliminate waste and inefficiency, leading to higher productivity. – : Improved efficiency often results in reduced production costs. – : The use of data and scientific analysis helps in making informed management decisions. – : It enhances the productivity and performance of both workers and organizations.
Drawbacks	– : Critics argue that scientific management can lead to dehumanization of work and an excessive focus on efficiency at the expense of worker well-being. – : Workers may resist the rigid and highly standardized work methods imposed by scientific management. – : Some argue that scientific management is most suitable for repetitive, manual tasks and may not apply to knowledge work or creative industries. – : The rigid approach may not accommodate changing circumstances or evolving job roles.
Contemporary Relevance	While some aspects of Scientific Management Theory have evolved, elements such as process optimization, data-driven decision-making, and the pursuit of efficiency continue to influence modern management practices.
Applications	Scientific Management Theory has historically been applied in manufacturing and production industries, including automotive assembly lines and manufacturing plants. However, its principles have also been adapted and applied in service industries and healthcare to optimize processes and improve efficiency.
Examples	– : Henry Ford applied principles of scientific management to automotive manufacturing, revolutionizing the production process and making cars more affordable. – : Fast food restaurants use standardized processes and workflows, influenced by scientific management principles, to ensure consistency and efficiency in food preparation. – : Call centers often employ time and motion studies and standardized scripts to improve the efficiency of customer service operations. – : Many manufacturing facilities continue to use scientific management principles to optimize production lines and reduce costs.

Table of Contents

Understanding Scientific Management Theory

In the early 20th century, there was also a general belief that workers were lazy and inefficient.

Taylor argued that the remedy for inefficiency was to be found in systematic management – there was no use trying to recruit men who had extraordinary work ethics.

Taylor was one of the first to look at productivity from a scientific standpoint, believing in universal laws that governed labor productivity and efficiency.

For this reason, “Taylorism” is often referred to as one of the first forms of scientific management .

Taylor’s classic assumptions about workers

Taylor’s belief that workers were only motivated by money provides the basis for several classic assumptions:

Workers find their work unenjoyable and have a natural tendency to slack off in a process he called natural soldiering. To counter this tendency, they must be closely monitored and controlled.
To increase worker investment in their job, it should be broken down into bite-sized actions.
Training should be provided to all employees to create a standardized way of working.
Workers should be paid based on how much they produce (piece rate). Taylor argued that this would create a win-win scenario where the employee would earn more money and the business would maximize its profits.

The four core principles of Scientific Management Theory

Taylor was perhaps a product of his time, viewing employee labor as an extension of machine labor.

He was also a strong proponent of autocratic leadership , which an increasing number of modern companies are shying away from.

However, his principles of scientific management are still relevant today.

Here is a look at each principle:

Select methods backed by science

Businesses should avoid giving workers the freedom to perform their jobs in any way they see fit.

The scientific method must be used to identify the single, most efficient way of doing the job.

Assign workers to jobs that match their aptitude

Instead of assigning workers to jobs at random, assign them to roles where their unique capabilities will allow them to work at peak efficiency.

Monitor worker performance

Monitor efficiency and ensure that necessary instruction is given on how to maintain productivity.

Divide the workload between management and staff

Here, roles and responsibilities should clearly be defined.

Management should train workers and workers should implement lessons learned.

Examples of modern companies employing Scientific Management Theory

Although slightly outdated, scientific management theory is useful in highly competitive industries where labor costs need to be kept as low as possible.

Example organizations include:

Amazon Case Study

where warehouse staff are paid on a piece-rate basis according to their level of productivity.

The company has also recently introduced patented wristbands that track employee performance in real-time.

McDonald’s Case Study

The homogenization of McDonald’s restaurants worldwide has meant that processes have had to become extremely refined.

The procedure for everything from making a burger to mopping the floor is the same – regardless of geographic location.

These processes are ultra-efficient and are broken down into actionable steps, which is a core component of Taylorism.

The aviation industry case study

Scientific management theory has played a pivotal role in the evolution of airport and airline management – a competitive, time-sensitive, and heavily regulated industry that requires companies to manage a multitude of different tasks.

Air New Zealand, for example, applied scientific management theory to its staff allocation and rostering systems over thirteen years between 1986 and 1999. Primarily, scientific management was used to address two core problems:

The tours-of-duty (ToD) planning problem – where a sequence of flights must be constructed to crew the flight schedule. These sequences can comprise one-day periods of work but also encompass longer sequences spanning consecutive days with multiple flights and rest periods, and
The rostering problem – where the airline has to match the ToD plan to individual employees to form a line of work (LoW) over a specific rostering period. In the process, airlines have to consider the employee’s skills or qualifications, employment contract conditions, operational rostering agreements, and any scheduled leave.

The role of management and crew

In aviation, the interaction of these problems can be considered from both the point of view of management and crew.

The management of Air New Zealand prefers maximum productivity and minimum-cost solutions that do not break laws and ensure all the work is performed.

They are also focused on the operational robustness of the schedule vis-à-vis sensitivity to disruptions.

For the Air New Zealand crew, on the other hand, the key concern is the quality of the solution.

What defines quality varies from one cohort to the next. Some consider the fair distribution of work to be important, while others hope to avoid arduous work patterns.

The importance of solving the aircrew-scheduling problem

Since aircraft and their associated crew are among the most expensive costs for an airline, their efficient utilization is vital to the company’s success and profitability.

Lured by the potential to reduce costs, history is littered with airlines who tried and failed to develop effective optimization methods.

But it was not until the 1980s that computational power became sufficiently advanced to solve the ToD problem.

Development of the model

In collaboration with the University of Auckland, Air New Zealand developed a total of 8 optimization-based systems. These systems, which were incorporated into the company’s database environment, solved all aspects of the planning and scheduling process across domestic and international routes.

One particular characteristic of these systems was that they presented solutions that exploited the rules. That is, the solutions were within the bounds of the law, made sense from a financial point of view, and were also beneficial for crew productivity and safety.

Air New Zealand also collaborated with NASA in its pioneering research on measuring fatigue, with the results subsequently added to the ToD systems as additional rules and constraints.

In dollar terms, scientific management theory allowed the airline to reduce the amount of money it spent on hotels, meals, and other expenses for crew who traveled overseas. The cost of constructing and maintaining the crewing system has also decreased over time.

Despite the company’s airline fleet and route structure increasing in size and complexity, the number of people Air New Zealand needed to employ to solve scheduling problems dropped from 27 in 1987 to just 15 in 2000.

At the time, conservative estimates put the total cost saving of the initiative at 15.655 million NZD per annum .

Key takeaways

Scientific Management Theory is a theory of management that seeks to analyze and synthesize workflow to improve labor productivity.
Scientific Management Theory was originally based on the assumption that workers were only motivated by money and is heavily geared toward autocratic leadership styles. Nevertheless, it is still relevant to modern organizations.
Scientific Management Theory is particularly effective in industries with a high prevalence of menial or repetitive tasks where costs need to be minimized. Examples include Amazon and McDonald’s.

Key Highlights

Origin and Background: Scientific Management Theory was developed by Frederick Winslow Taylor in 1911. It aimed to improve industrial productivity through the application of engineering principles to the workplace. Taylor believed in finding the most efficient ways of performing tasks.
Worker Perceptions: In the early 20th century, there was a perception that workers were lazy and inefficient. Taylor’s theory aimed to address this by optimizing work processes.
Efficiency and Systematic Management: Taylor believed that inefficiency could be addressed through systematic management rather than relying on recruiting individuals with extraordinary work ethics. He emphasized the need for scientific analysis to identify the most efficient ways of performing tasks.
Taylorism: Taylor’s approach is often referred to as Taylorism. He believed in universal laws governing labor productivity and efficiency, and he introduced principles to optimize work processes.
Assumptions About Workers: Taylor’s classic assumptions included that workers found work unenjoyable, had a tendency to slack off (natural soldiering), and needed close monitoring and control. He believed in breaking down tasks into manageable actions and providing standardized training.
Piece-Rate Payment: Taylor advocated for paying workers based on their production, creating a win-win situation where employees earned more and businesses maximized profits.
Core Principles: Taylor’s principles include selecting methods based on science, matching workers to suitable roles, monitoring worker performance, and clearly defining roles and responsibilities between management and staff.
Modern Relevance: Although Taylorism is outdated in some aspects, its principles are still relevant, especially in industries where labor costs need to be minimized. Examples include Amazon and McDonald’s.
Amazon Case Study: Amazon uses piece-rate payment for warehouse staff based on productivity and employs real-time performance tracking technology.
McDonald’s Case Study: McDonald’s homogenized processes globally, ensuring consistency and efficiency in tasks like burger preparation and cleaning.
Aviation Industry Case Study (Air New Zealand): The aviation industry has applied Scientific Management Theory to crew scheduling and planning, achieving cost savings and efficiency improvements.
Air New Zealand’s Collaboration: Air New Zealand collaborated with the University of Auckland and NASA to develop optimization-based systems for crew scheduling, reducing costs and increasing efficiency.
Benefits of Scientific Management: The theory has been successful in optimizing processes, reducing costs, improving efficiency, and aligning worker capabilities with tasks.
Application and Limitations: Scientific Management Theory is effective in industries with repetitive tasks but may not fully accommodate the complexities of modern work environments.
Autocratic Leadership: Taylor’s approach is associated with autocratic leadership , which may not align with modern leadership trends emphasizing empowerment and collaboration.
Key Takeaways: Scientific Management Theory focuses on improving labor productivity through systematic analysis of work processes. It’s applicable in industries where repetitive tasks require optimization, and its principles are still relevant today.

Related Concepts	Description	When to Apply
	by Frederick Taylor emphasizes improving labor productivity through systematic analysis of tasks, workflow optimization, and incentive systems. Key principles include time studies and standardization.	– When analyzing workflows to boost productivity. – When implementing performance measurement systems. – When designing incentive structures to motivate workers. – When fostering a culture of continuous improvement. – When optimizing resource allocation and cost management. – When aligning organizational structure with strategic objectives. – When addressing resistance to change and driving organizational reforms. – When improving operational efficiency and customer satisfaction. – When enhancing decision-making processes. – When preparing for career advancement or transitions.
	advocates for scientific principles in management, aiming to maximize efficiency. It involves dividing tasks, standardizing processes, and hierarchical supervision.	– When streamlining operational processes. – When designing job roles to boost productivity. – When implementing performance measurement systems. – When training managers in scientific management principles. – When evaluating organizational structures. – When fostering a culture of accountability and transparency. – When aligning management practices with strategic objectives. – When addressing employee concerns related to change. – When benchmarking performance against industry standards. – When promoting a culture of continuous improvement.
	analyze work processes to identify inefficiencies and improve productivity. It involves observing tasks, measuring time, and optimizing workflows.	– When analyzing work processes to identify bottlenecks. – When designing workstations or layouts. – When allocating resources efficiently. – When implementing new technologies or automation. – When evaluating the impact of changes in work procedures. – When fostering a culture of continuous improvement. – When aligning time and motion study findings with strategic objectives. – When benchmarking performance against industry standards. – When training employees in time management techniques. – When promoting a culture of accountability and transparency.
	focuses on optimizing resource utilization and minimizing waste to enhance performance. It involves strategies like process optimization and automation.	– When analyzing workflows for streamlining. – When implementing performance measurement systems. – When training employees in lean principles. – When investing in technology solutions. – When conducting cost-benefit analyses. – When benchmarking performance against industry peers. – When fostering a culture of efficiency and productivity. – When aligning efficiency efforts with strategic objectives. – When addressing resistance to change. – When communicating the benefits of efficiency maximization.
	defines best practices to ensure consistency and quality. It involves documenting procedures and implementing quality control measures.	– When documenting standard operating procedures (SOPs). – When training employees on standardized work processes. – When implementing quality control measures. – When conducting regular audits or inspections. – When communicating changes to work processes. – When integrating standardization with continuous improvement initiatives. – When benchmarking performance against industry benchmarks. – When fostering a culture of accountability. – When aligning standardization efforts with strategic objectives. – When addressing resistance to standardization initiatives.
	emphasizes hierarchical structures, rules, and procedures to ensure organizational efficiency and stability. It focuses on clear division of labor, formalized communication channels, and adherence to established norms.	– When establishing clear roles and responsibilities within an organization. – When formalizing communication channels and decision-making processes. – When ensuring compliance with regulations and policies. – When promoting consistency and reliability in organizational operations. – When addressing issues related to accountability and transparency. – When managing complex projects or tasks with multiple stakeholders. – When implementing quality control measures and performance metrics. – When fostering a culture of discipline and adherence to established procedures. – When aligning organizational structure with strategic objectives and market demands. – When addressing resistance to change or challenges related to organizational inertia.
	focuses on the psychological aspects of work and the importance of interpersonal relationships in organizational performance. It emphasizes employee satisfaction, motivation, and social needs fulfillment.	– When improving employee morale and job satisfaction. – When fostering teamwork and collaboration within teams or departments. – When addressing interpersonal conflicts or communication breakdowns. – When promoting a positive organizational culture and work environment. – When designing reward and recognition programs to motivate employees. – When conducting employee engagement surveys and feedback sessions. – When implementing leadership development programs to enhance managerial skills. – When promoting diversity and inclusion initiatives within the organization. – When aligning organizational goals with employee aspirations and values. – When addressing turnover or retention issues through improved people management practices.
	focuses on minimizing waste and maximizing value in organizational processes. It involves principles such as continuous improvement, respect for people, and customer focus.	– When identifying and eliminating non-value-added activities in workflows. – When improving efficiency and reducing lead times in production or service delivery. – When empowering employees to contribute ideas for process improvement. – When implementing visual management tools to monitor performance and progress. – When fostering a culture of continuous learning and adaptation to change. – When aligning operations with customer needs and preferences. – When addressing quality issues or defects through root cause analysis and corrective actions. – When optimizing inventory management and supply chain operations. – When training employees in lean principles and problem-solving techniques. – When benchmarking performance against industry leaders and best practices in lean management.
	focuses on continuous improvement and customer satisfaction through systematic approaches to quality assurance. It involves principles such as customer focus, process improvement, and employee involvement.	– When implementing quality control measures to meet customer expectations. – When conducting root cause analysis and corrective actions to address quality issues. – When fostering a culture of quality and excellence throughout the organization. – When training employees in quality management principles and techniques. – When establishing quality improvement teams to drive process optimization. – When implementing performance measurement systems to monitor quality metrics. – When aligning quality management efforts with strategic objectives and customer needs. – When promoting a culture of accountability and responsibility for quality outcomes. – When benchmarking performance against industry standards and best practices in quality management. – When addressing resistance to change or challenges related to organizational culture transformation.
	explores the dynamics of individual and group behavior within organizations. It examines factors influencing employee motivation, job satisfaction, and performance.	– When analyzing factors contributing to employee motivation and engagement. – When assessing organizational culture and its impact on employee behavior. – When designing leadership development programs to enhance managerial effectiveness. – When addressing interpersonal conflicts or communication breakdowns in teams. – When implementing change management initiatives to support organizational transformation. – When conducting performance evaluations and feedback sessions. – When promoting diversity and inclusion initiatives within the organization. – When aligning organizational structure and processes with employee needs and preferences. – When addressing turnover or retention issues through improved people management practices. – When benchmarking organizational behavior metrics against industry benchmarks and best practices.
	applies psychological principles to workplace settings to enhance employee well-being and organizational performance. It involves areas such as personnel selection, training, and job design.	– When designing recruitment and selection processes to identify top talent. – When conducting job analyses and designing work roles to maximize employee satisfaction and productivity. – When implementing training and development programs to enhance employee skills and competencies. – When assessing organizational culture and climate to identify areas for improvement. – When conducting performance appraisals and feedback sessions to support employee growth and development. – When addressing issues related to job stress, burnout, or work-life balance. – When promoting diversity and inclusion initiatives within the organization. – When aligning organizational policies and practices with legal and ethical standards. – When addressing employee grievances or concerns through effective conflict resolution techniques. – When benchmarking employee satisfaction and engagement metrics against industry standards and best practices.

What are the 4 Principles of Scientific Management?

The core principles of Scientific Management are:

What is the example of scientific management theory?

Cases of scientific management comprise companies like Amazon and McDonald’s, which have made defined business processes for inventory and fulfillment (Amazon) and fast food (McDonald’s) the core strengths of their organizations.

McDonald’s Case Study

Connected Management Frameworks

Change Management

Kotter’s 8-Step Change Model

McKinsey’s Seven Degrees

McKinsey 7-S Model

Lewin’s Change Management

ADKAR Model

Force-Field Analysis

Business Innovation Matrix

Posci Change Management

More Resources

About The Author

Gennaro Cuofano

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Open access
Published: 27 June 2011

The case study approach

Sarah Crowe 1 ,
Kathrin Cresswell 2 ,
Ann Robertson 2 ,
Guro Huby 3 ,
Anthony Avery 1 &
Aziz Sheikh 2

BMC Medical Research Methodology volume 11 , Article number: 100 ( 2011 ) Cite this article

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The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Peer Review reports

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Yin RK: Case study research, design and method. 2009, London: Sage Publications Ltd., 4

Google Scholar

Keen J, Packwood T: Qualitative research; case study evaluation. BMJ. 1995, 311: 444-446.

Article CAS PubMed PubMed Central Google Scholar

Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J, et al: Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009, 6 (10): 1-11.

Article Google Scholar

Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, et al: The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO). 2008, [ http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf ]

Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T, et al: Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010, 41: c4564-

Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P, the Patient Safety Education Study Group: Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010, 15: 4-10. 10.1258/jhsrp.2009.009052.

Article PubMed Google Scholar

van Harten WH, Casparie TF, Fisscher OA: The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002, 60 (1): 17-37. 10.1016/S0168-8510(01)00187-7.

Stake RE: The art of case study research. 1995, London: Sage Publications Ltd.

Sheikh A, Smeeth L, Ashcroft R: Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002, 52 (482): 746-51.

PubMed PubMed Central Google Scholar

King G, Keohane R, Verba S: Designing Social Inquiry. 1996, Princeton: Princeton University Press

Doolin B: Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998, 13: 301-311. 10.1057/jit.1998.8.

George AL, Bennett A: Case studies and theory development in the social sciences. 2005, Cambridge, MA: MIT Press

Eccles M, the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG): Designing theoretically-informed implementation interventions. Implementation Science. 2006, 1: 1-8. 10.1186/1748-5908-1-1.

Article PubMed Central Google Scholar

Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A: Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005, 365 (9456): 312-7.

Sheikh A, Panesar SS, Lasserson T, Netuveli G: Recruitment of ethnic minorities to asthma studies. Thorax. 2004, 59 (7): 634-

CAS PubMed PubMed Central Google Scholar

Hellström I, Nolan M, Lundh U: 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005, 4: 7-22. 10.1177/1471301205049188.

Som CV: Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005, 18: 463-477. 10.1108/09513550510608903.

Lincoln Y, Guba E: Naturalistic inquiry. 1985, Newbury Park: Sage Publications

Barbour RS: Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?. BMJ. 2001, 322: 1115-1117. 10.1136/bmj.322.7294.1115.

Mays N, Pope C: Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000, 320: 50-52. 10.1136/bmj.320.7226.50.

Mason J: Qualitative researching. 2002, London: Sage

Brazier A, Cooke K, Moravan V: Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008, 7: 5-17. 10.1177/1534735407313395.

Miles MB, Huberman M: Qualitative data analysis: an expanded sourcebook. 1994, CA: Sage Publications Inc., 2

Pope C, Ziebland S, Mays N: Analysing qualitative data. Qualitative research in health care. BMJ. 2000, 320: 114-116. 10.1136/bmj.320.7227.114.

Cresswell KM, Worth A, Sheikh A: Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010, 10 (1): 67-10.1186/1472-6947-10-67.

Article PubMed PubMed Central Google Scholar

Malterud K: Qualitative research: standards, challenges, and guidelines. Lancet. 2001, 358: 483-488. 10.1016/S0140-6736(01)05627-6.

Article CAS PubMed Google Scholar

Yin R: Case study research: design and methods. 1994, Thousand Oaks, CA: Sage Publishing, 2

Yin R: Enhancing the quality of case studies in health services research. Health Serv Res. 1999, 34: 1209-1224.

Green J, Thorogood N: Qualitative methods for health research. 2009, Los Angeles: Sage, 2

Howcroft D, Trauth E: Handbook of Critical Information Systems Research, Theory and Application. 2005, Cheltenham, UK: Northampton, MA, USA: Edward Elgar

Book Google Scholar

Blakie N: Approaches to Social Enquiry. 1993, Cambridge: Polity Press

Doolin B: Power and resistance in the implementation of a medical management information system. Info Systems J. 2004, 14: 343-362. 10.1111/j.1365-2575.2004.00176.x.

Bloomfield BP, Best A: Management consultants: systems development, power and the translation of problems. Sociological Review. 1992, 40: 533-560.

Shanks G, Parr A: Positivist, single case study research in information systems: A critical analysis. Proceedings of the European Conference on Information Systems. 2003, Naples

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Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

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Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100

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What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Case study examples
Research question	Case study
What are the ecological effects of wolf reintroduction?	Case study of wolf reintroduction in Yellowstone National Park
How do populist politicians use narratives about history to gain support?	Case studies of Hungarian prime minister Viktor Orbán and US president Donald Trump
How can teachers implement active learning strategies in mixed-level classrooms?	Case study of a local school that promotes active learning
What are the main advantages and disadvantages of wind farms for rural communities?	Case studies of three rural wind farm development projects in different parts of the country
How are viral marketing strategies changing the relationship between companies and consumers?	Case study of the iPhone X marketing campaign
How do experiences of work in the gig economy differ by gender, race and age?	Case studies of Deliveroo and Uber drivers in London

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

Provide new or unexpected insights into the subject
Challenge or complicate existing assumptions and theories
Propose practical courses of action to resolve a problem
Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

Exemplify a theory by showing how it explains the case under investigation
Expand on a theory by uncovering new concepts and ideas that need to be incorporated
Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Normal distribution
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Ecological validity

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

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Case Study Methods and Examples

By Janet Salmons, PhD Manager, Sage Research Methods Community

What is Case Study Methodology ?

Case studies in research are both unique and uniquely confusing. The term case study is confusing because the same term is used multiple ways. The term can refer to the methodology, that is, a system of frameworks used to design a study, or the methods used to conduct it. Or, case study can refer to a type of academic writing that typically delves into a problem, process, or situation.

Case study methodology can entail the study of one or more "cases," that could be described as instances, examples, or settings where the problem or phenomenon can be examined. The researcher is tasked with defining the parameters of the case, that is, what is included and excluded. This process is called bounding the case , or setting boundaries.

Case study can be combined with other methodologies, such as ethnography, grounded theory, or phenomenology. In such studies the research on the case uses another framework to further define the study and refine the approach.

Case study is also described as a method, given particular approaches used to collect and analyze data. Case study research is conducted by almost every social science discipline: business, education, sociology, psychology. Case study research, with its reliance on multiple sources, is also a natural choice for researchers interested in trans-, inter-, or cross-disciplinary studies.

The Encyclopedia of case study research provides an overview:

The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case.

It is unique given one characteristic: case studies draw from more than one data source. Case studies are inherently multimodal or mixed methods because this they use either more than one form of data within a research paradigm, or more than one form of data from different paradigms.

A case study inquiry could include multiple types of data:

multiple forms of quantitative data sources, such as Big Data + a survey

multiple forms of qualitative data sources, such as interviews + observations + documents

multiple forms of quantitative and qualitative data sources, such as surveys + interviews

Case study methodology can be used to achieve different research purposes.

Robert Yin , methodologist most associated with case study research, differentiates between descriptive , exploratory and explanatory case studies:

Descriptive : A case study whose purpose is to describe a phenomenon. Explanatory : A case study whose purpose is to explain how or why some condition came to be, or why some sequence of events occurred or did not occur. Exploratory: A case study whose purpose is to identify the research questions or procedures to be used in a subsequent study.

Robert Yin’s book is a comprehensive guide for case study researchers!

You can read the preface and Chapter 1 of Yin's book here . See the open-access articles below for some published examples of qualitative, quantitative, and mixed methods case study research.

Mills, A. J., Durepos, G., & Wiebe, E. (2010). Encyclopedia of case study research (Vols. 1-0). Thousand Oaks, CA: SAGE Publications, Inc. doi: 10.4135/9781412957397

Yin, R. K. (2018). Case study research and applications (6th ed.). Thousand Oaks: SAGE Publications.

Open-Access Articles Using Case Study Methodology

As you can see from this collection, case study methods are used in qualitative, quantitative and mixed methods research.

Ang, C.-S., Lee, K.-F., & Dipolog-Ubanan, G. F. (2019). Determinants of First-Year Student Identity and Satisfaction in Higher Education: A Quantitative Case Study. SAGE Open. https://doi.org/10.1177/2158244019846689

Abstract. First-year undergraduates’ expectations and experience of university and student engagement variables were investigated to determine how these perceptions influence their student identity and overall course satisfaction. Data collected from 554 first-year undergraduates at a large private university were analyzed. Participants were given the adapted version of the Melbourne Centre for the Study of Higher Education Survey to self-report their learning experience and engagement in the university community. The results showed that, in general, the students’ reasons of pursuing tertiary education were to open the door to career opportunities and skill development. Moreover, students’ views on their learning and university engagement were at the moderate level. In relation to student identity and overall student satisfaction, it is encouraging to state that their perceptions of studentship and course satisfaction were rather positive. After controlling for demographics, student engagement appeared to explain more variance in student identity, whereas students’ expectations and experience explained greater variance in students’ overall course satisfaction. Implications for practice, limitations, and recommendation of this study are addressed.

Baker, A. J. (2017). Algorithms to Assess Music Cities: Case Study—Melbourne as a Music Capital. SAGE Open. https://doi.org/10.1177/2158244017691801

Abstract. The global Mastering of a Music City report in 2015 notes that the concept of music cities has penetrated the global political vernacular because it delivers “significant economic, employment, cultural and social benefits.” This article highlights that no empirical study has combined all these values and offers a relevant and comprehensive definition of a music city. Drawing on industry research,1 the article assesses how mathematical flowcharts, such as Algorithm A (Economics), Algorithm B (Four T’s creative index), and Algorithm C (Heritage), have contributed to the definition of a music city. Taking Melbourne as a case study, it illustrates how Algorithms A and B are used as disputed evidence about whether the city is touted as Australia’s music capital. The article connects the three algorithms to an academic framework from musicology, urban studies, cultural economics, and sociology, and proposes a benchmark Algorithm D (Music Cities definition), which offers a more holistic assessment of music activity in any urban context. The article concludes by arguing that Algorithm D offers a much-needed definition of what comprises a music city because it builds on the popular political economy focus and includes the social importance of space and cultural practices.

Brown, K., & Mondon, A. (2020). Populism, the media, and the mainstreaming of the far right: The Guardian’s coverage of populism as a case study. Politics. https://doi.org/10.1177/0263395720955036

Abstract. Populism seems to define our current political age. The term is splashed across the headlines, brandished in political speeches and commentaries, and applied extensively in numerous academic publications and conferences. This pervasive usage, or populist hype, has serious implications for our understanding of the meaning of populism itself and for our interpretation of the phenomena to which it is applied. In particular, we argue that its common conflation with far-right politics, as well as its breadth of application to other phenomena, has contributed to the mainstreaming of the far right in three main ways: (1) agenda-setting power and deflection, (2) euphemisation and trivialisation, and (3) amplification. Through a mixed-methods approach to discourse analysis, this article uses The Guardian newspaper as a case study to explore the development of the populist hype and the detrimental effects of the logics that it has pushed in public discourse.

Droy, L. T., Goodwin, J., & O’Connor, H. (2020). Methodological Uncertainty and Multi-Strategy Analysis: Case Study of the Long-Term Effects of Government Sponsored Youth Training on Occupational Mobility. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 147–148(1–2), 200–230. https://doi.org/10.1177/0759106320939893

Abstract. Sociological practitioners often face considerable methodological uncertainty when undertaking a quantitative analysis. This methodological uncertainty encompasses both data construction (e.g. defining variables) and analysis (e.g. selecting and specifying a modelling procedure). Methodological uncertainty can lead to results that are fragile and arbitrary. Yet, many practitioners may be unaware of the potential scale of methodological uncertainty in quantitative analysis, and the recent emergence of techniques for addressing it. Recent proposals for ‘multi-strategy’ approaches seek to identify and manage methodological uncertainty in quantitative analysis. We present a case-study of a multi-strategy analysis, applied to the problem of estimating the long-term impact of 1980s UK government-sponsored youth training. We use this case study to further highlight the problem of cumulative methodological fragilities in applied quantitative sociology and to discuss and help develop multi-strategy analysis as a tool to address them.

Ebneyamini, S., & Sadeghi Moghadam, M. R. (2018). Toward Developing a Framework for Conducting Case Study Research . International Journal of Qualitative Methods . https://doi.org/10.1177/1609406918817954

Abstract. This article reviews the use of case study research for both practical and theoretical issues especially in management field with the emphasis on management of technology and innovation. Many researchers commented on the methodological issues of the case study research from their point of view thus, presenting a comprehensive framework was missing. We try representing a general framework with methodological and analytical perspective to design, develop, and conduct case study research. To test the coverage of our framework, we have analyzed articles in three major journals related to the management of technology and innovation to approve our framework. This study represents a general structure to guide, design, and fulfill a case study research with levels and steps necessary for researchers to use in their research.

Lai, D., & Roccu, R. (2019). Case study research and critical IR: the case for the extended case methodology. International Relations , 33 (1), 67-87. https://doi.org/10.1177/0047117818818243

Abstract. Discussions on case study methodology in International Relations (IR) have historically been dominated by positivist and neopositivist approaches. However, these are problematic for critical IR research, pointing to the need for a non-positivist case study methodology. To address this issue, this article introduces and adapts the extended case methodology as a critical, reflexivist approach to case study research, whereby the case is constructed through a dynamic interaction with theory, rather than selected, and knowledge is produced through extensions rather than generalisation. Insofar as it seeks to study the world in complex and non-linear terms, take context and positionality seriously, and generate explicitly political and emancipatory knowledge, the extended case methodology is consistent with the ontological and epistemological commitments of several critical IR approaches. Its potential is illustrated in the final part of the article with reference to researching the socioeconomic dimension of transitional justice in Bosnia and Herzegovina.

Lynch, R., Young, J. C., Boakye-Achampong, S., Jowaisas, C., Sam, J., & Norlander, B. (2020). Benefits of crowdsourcing for libraries: A case study from Africa . IFLA Journal. https://doi.org/10.1177/0340035220944940

Abstract. Many libraries in the Global South do not collect comprehensive data about themselves, which creates challenges in terms of local and international visibility. Crowdsourcing is an effective tool that engages the public to collect missing data, and it has proven to be particularly valuable in countries where governments collect little public data. Whereas crowdsourcing is often used within fields that have high levels of development funding, such as health, the authors believe that this approach would have many benefits for the library field as well. They present qualitative and quantitative evidence from 23 African countries involved in a crowdsourcing project to map libraries. The authors find benefits in terms of increased connections between stakeholders, capacity-building, and increased local visibility. These findings demonstrate the potential of crowdsourced approaches for tasks such as mapping to benefit libraries and similarly positioned institutions in the Global South in multifaceted ways.

Mason, W., Morris, K., Webb, C., Daniels, B., Featherstone, B., Bywaters, P., Mirza, N., Hooper, J., Brady, G., Bunting, L., & Scourfield, J. (2020). Toward Full Integration of Quantitative and Qualitative Methods in Case Study Research: Insights From Investigating Child Welfare Inequalities. Journal of Mixed Methods Research, 14 (2), 164-183. https://doi.org/10.1177/1558689819857972

Abstract. Delineation of the full integration of quantitative and qualitative methods throughout all stages of multisite mixed methods case study projects remains a gap in the methodological literature. This article offers advances to the field of mixed methods by detailing the application and integration of mixed methods throughout all stages of one such project; a study of child welfare inequalities. By offering a critical discussion of site selection and the management of confirmatory, expansionary and discordant data, this article contributes to the limited body of mixed methods exemplars specific to this field. We propose that our mixed methods approach provided distinctive insights into a complex social problem, offering expanded understandings of the relationship between poverty, child abuse, and neglect.

Rashid, Y., Rashid, A., Warraich, M. A., Sabir, S. S., & Waseem, A. (2019). Case Study Method: A Step-by-Step Guide for Business Researchers . International Journal of Qualitative Methods . https://doi.org/10.1177/1609406919862424

Abstract. Qualitative case study methodology enables researchers to conduct an in-depth exploration of intricate phenomena within some specific context. By keeping in mind research students, this article presents a systematic step-by-step guide to conduct a case study in the business discipline. Research students belonging to said discipline face issues in terms of clarity, selection, and operationalization of qualitative case study while doing their final dissertation. These issues often lead to confusion, wastage of valuable time, and wrong decisions that affect the overall outcome of the research. This article presents a checklist comprised of four phases, that is, foundation phase, prefield phase, field phase, and reporting phase. The objective of this article is to provide novice researchers with practical application of this checklist by linking all its four phases with the authors’ experiences and learning from recently conducted in-depth multiple case studies in the organizations of New Zealand. Rather than discussing case study in general, a targeted step-by-step plan with real-time research examples to conduct a case study is given.

VanWynsberghe, R., & Khan, S. (2007). Redefining Case Study. International Journal of Qualitative Methods, 80–94. https://doi.org/10.1177/160940690700600208

Abstract. In this paper the authors propose a more precise and encompassing definition of case study than is usually found. They support their definition by clarifying that case study is neither a method nor a methodology nor a research design as suggested by others. They use a case study prototype of their own design to propose common properties of case study and demonstrate how these properties support their definition. Next, they present several living myths about case study and refute them in relation to their definition. Finally, they discuss the interplay between the terms case study and unit of analysis to further delineate their definition of case study. The target audiences for this paper include case study researchers, research design and methods instructors, and graduate students interested in case study research.

Istanbul as a regional computational social science hub

Experiments and quantitative research.

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Annotated Bibliography
Analyzing a Scholarly Journal Article
Group Presentations
Dealing with Nervousness
Using Visual Aids
Grading Someone Else's Paper
Types of Structured Group Activities
Group Project Survival Skills
Leading a Class Discussion
Multiple Book Review Essay
Reviewing Collected Works
Writing a Case Analysis Paper
Writing a Case Study
About Informed Consent
Writing Field Notes
Writing a Policy Memo
Writing a Reflective Paper
Writing a Research Proposal
Generative AI and Writing
Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I. Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II. Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III. Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE: The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV. Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V. Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009; Kratochwill, Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education . Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 : General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 : One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 : The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 : The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 : It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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BMC Med Res Methodol

The case study approach

Sarah crowe.

1 Division of Primary Care, The University of Nottingham, Nottingham, UK

Kathrin Cresswell

2 Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Ann Robertson

3 School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

Anthony Avery

Aziz sheikh.

Introduction

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables Tables1, 1 , ,2, 2 , ,3 3 and and4) 4 ) and those of others to illustrate our discussion[ 3 - 7 ].

Example of a case study investigating the reasons for differences in recruitment rates of minority ethnic people in asthma research[ 3 ]

Minority ethnic people experience considerably greater morbidity from asthma than the White majority population. Research has shown however that these minority ethnic populations are likely to be under-represented in research undertaken in the UK; there is comparatively less marginalisation in the US.

To investigate approaches to bolster recruitment of South Asians into UK asthma studies through qualitative research with US and UK researchers, and UK community leaders.

Single intrinsic case study

Centred on the issue of recruitment of South Asian people with asthma.

In-depth interviews were conducted with asthma researchers from the UK and US. A supplementary questionnaire was also provided to researchers.

Framework approach.

Barriers to ethnic minority recruitment were found to centre around:

1. The attitudes of the researchers' towards inclusion: The majority of UK researchers interviewed were generally supportive of the idea of recruiting ethnically diverse participants but expressed major concerns about the practicalities of achieving this; in contrast, the US researchers appeared much more committed to the policy of inclusion.

2. Stereotypes and prejudices: We found that some of the UK researchers' perceptions of ethnic minorities may have influenced their decisions on whether to approach individuals from particular ethnic groups. These stereotypes centred on issues to do with, amongst others, language barriers and lack of altruism.

3. Demographic, political and socioeconomic contexts of the two countries: Researchers suggested that the demographic profile of ethnic minorities, their political engagement and the different configuration of the health services in the UK and the US may have contributed to differential rates.

4. Above all, however, it appeared that the overriding importance of the US National Institute of Health's policy to mandate the inclusion of minority ethnic people (and women) had a major impact on shaping the attitudes and in turn the experiences of US researchers'; the absence of any similar mandate in the UK meant that UK-based researchers had not been forced to challenge their existing practices and they were hence unable to overcome any stereotypical/prejudicial attitudes through experiential learning.

Example of a case study investigating the process of planning and implementing a service in Primary Care Organisations[ 4 ]

Health work forces globally are needing to reorganise and reconfigure in order to meet the challenges posed by the increased numbers of people living with long-term conditions in an efficient and sustainable manner. Through studying the introduction of General Practitioners with a Special Interest in respiratory disorders, this study aimed to provide insights into this important issue by focusing on community respiratory service development.

To understand and compare the process of workforce change in respiratory services and the impact on patient experience (specifically in relation to the role of general practitioners with special interests) in a theoretically selected sample of Primary Care Organisations (PCOs), in order to derive models of good practice in planning and the implementation of a broad range of workforce issues.

Multiple-case design of respiratory services in health regions in England and Wales.

Four PCOs.

Face-to-face and telephone interviews, e-mail discussions, local documents, patient diaries, news items identified from local and national websites, national workshop.

Reading, coding and comparison progressed iteratively.

1. In the screening phase of this study (which involved semi-structured telephone interviews with the person responsible for driving the reconfiguration of respiratory services in 30 PCOs), the barriers of financial deficit, organisational uncertainty, disengaged clinicians and contradictory policies proved insurmountable for many PCOs to developing sustainable services. A key rationale for PCO re-organisation in 2006 was to strengthen their commissioning function and those of clinicians through Practice-Based Commissioning. However, the turbulence, which surrounded reorganisation was found to have the opposite desired effect.

2. Implementing workforce reconfiguration was strongly influenced by the negotiation and contest among local clinicians and managers about "ownership" of work and income.

3. Despite the intention to make the commissioning system more transparent, personal relationships based on common professional interests, past work history, friendships and collegiality, remained as key drivers for sustainable innovation in service development.

It was only possible to undertake in-depth work in a selective number of PCOs and, even within these selected PCOs, it was not possible to interview all informants of potential interest and/or obtain all relevant documents. This work was conducted in the early stages of a major NHS reorganisation in England and Wales and thus, events are likely to have continued to evolve beyond the study period; we therefore cannot claim to have seen any of the stories through to their conclusion.

Example of a case study investigating the introduction of the electronic health records[ 5 ]

Healthcare systems globally are moving from paper-based record systems to electronic health record systems. In 2002, the NHS in England embarked on the most ambitious and expensive IT-based transformation in healthcare in history seeking to introduce electronic health records into all hospitals in England by 2010.

To describe and evaluate the implementation and adoption of detailed electronic health records in secondary care in England and thereby provide formative feedback for local and national rollout of the NHS Care Records Service.

A mixed methods, longitudinal, multi-site, socio-technical collective case study.

Five NHS acute hospital and mental health Trusts that have been the focus of early implementation efforts.

Semi-structured interviews, documentary data and field notes, observations and quantitative data.

Qualitative data were analysed thematically using a socio-technical coding matrix, combined with additional themes that emerged from the data.

1. Hospital electronic health record systems have developed and been implemented far more slowly than was originally envisioned.

2. The top-down, government-led standardised approach needed to evolve to admit more variation and greater local choice for hospitals in order to support local service delivery.

3. A range of adverse consequences were associated with the centrally negotiated contracts, which excluded the hospitals in question.

4. The unrealistic, politically driven, timeline (implementation over 10 years) was found to be a major source of frustration for developers, implementers and healthcare managers and professionals alike.

We were unable to access details of the contracts between government departments and the Local Service Providers responsible for delivering and implementing the software systems. This, in turn, made it difficult to develop a holistic understanding of some key issues impacting on the overall slow roll-out of the NHS Care Record Service. Early adopters may also have differed in important ways from NHS hospitals that planned to join the National Programme for Information Technology and implement the NHS Care Records Service at a later point in time.

Example of a case study investigating the formal and informal ways students learn about patient safety[ 6 ]

There is a need to reduce the disease burden associated with iatrogenic harm and considering that healthcare education represents perhaps the most sustained patient safety initiative ever undertaken, it is important to develop a better appreciation of the ways in which undergraduate and newly qualified professionals receive and make sense of the education they receive.
To investigate the formal and informal ways pre-registration students from a range of healthcare professions (medicine, nursing, physiotherapy and pharmacy) learn about patient safety in order to become safe practitioners.
Multi-site, mixed method collective case study.
: Eight case studies (two for each professional group) were carried out in educational provider sites considering different programmes, practice environments and models of teaching and learning.
Structured in phases relevant to the three knowledge contexts:
	Documentary evidence (including undergraduate curricula, handbooks and module outlines), complemented with a range of views (from course leads, tutors and students) and observations in a range of academic settings.

	Policy and management views of patient safety and influences on patient safety education and practice. NHS policies included, for example, implementation of the National Patient Safety Agency's , which encourages organisations to develop an organisational safety culture in which staff members feel comfortable identifying dangers and reporting hazards.

	The cultures to which students are exposed i.e. patient safety in relation to day-to-day working. NHS initiatives included, for example, a hand washing initiative or introduction of infection control measures.


1. Practical, informal, learning opportunities were valued by students. On the whole, however, students were not exposed to nor engaged with important NHS initiatives such as risk management activities and incident reporting schemes.
2. NHS policy appeared to have been taken seriously by course leaders. Patient safety materials were incorporated into both formal and informal curricula, albeit largely implicit rather than explicit.
3. Resource issues and peer pressure were found to influence safe practice. Variations were also found to exist in students' experiences and the quality of the supervision available.
The curriculum and organisational documents collected differed between sites, which possibly reflected gatekeeper influences at each site. The recruitment of participants for focus group discussions proved difficult, so interviews or paired discussions were used as a substitute.

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table (Table5), 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Definitions of a case study

Author	Definition
Stake[ ]	(p.237)
Yin[ , , ]	(Yin 1999 p. 1211, Yin 1994 p. 13)

	•
	• (Yin 2009 p18)
Miles and Huberman[ ]	(p. 25)
Green and Thorogood[ ]	(p. 284)
George and Bennett[ ]	(p. 17)"

These are however not necessarily mutually exclusive categories. In the first of our examples (Table (Table1), 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables Tables2, 2 , ,3 3 and and4) 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 - 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table (Table2) 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables Tables2 2 and and3, 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table (Table4 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table (Table6). 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

Example of epistemological approaches that may be used in case study research

Characteristics	Criticisms	Key references
Involves questioning one's own assumptions taking into account the wider political and social environment.	It can possibly neglect other factors by focussing only on power relationships and may give the researcher a position that is too privileged.	Howcroft and Trauth[ ] Blakie[ ] Doolin[ , ]
Interprets the limiting conditions in relation to power and control that are thought to influence behaviour.		Bloomfield and Best[ ]
Involves understanding meanings/contexts and processes as perceived from different perspectives, trying to understand individual and shared social meanings. Focus is on theory building.	Often difficult to explain unintended consequences and for neglecting surrounding historical contexts	Stake[ ] Doolin[ ]
Involves establishing which variables one wishes to study in advance and seeing whether they fit in with the findings. Focus is often on testing and refining theory on the basis of case study findings.	It does not take into account the role of the researcher in influencing findings.	Yin[ , , ] Shanks and Parr[ ]

How are case studies conducted?

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table Table7 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

Example of a checklist for rating a case study proposal[ 8 ]

	Clarity: Does the proposal read well?
	Integrity: Do its pieces fit together?
	Attractiveness: Does it pique the reader's interest?
	The case: Is the case adequately defined?
	The issues: Are major research questions identified?
	Data Resource: Are sufficient data sources identified?
	Case Selection: Is the selection plan reasonable?
	Data Gathering: Are data-gathering activities outlined?
	Validation: Is the need and opportunity for triangulation indicated?
	Access: Are arrangements for start-up anticipated?
	Confidentiality: Is there sensitivity to the protection of people?
	Cost: Are time and resource estimates reasonable?

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table (Table3), 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table (Table1) 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table Table3) 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 - 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table (Table2 2 )[ 4 ].

Analysing, interpreting and reporting case studies

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table (Table1 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table (Table3 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table (Table4 4 )[ 6 ].

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table Table3, 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table (Table4), 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table Table8 8 )[ 8 , 18 - 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table (Table9 9 )[ 8 ].

Potential pitfalls and mitigating actions when undertaking case study research

Potential pitfall	Mitigating action
Selecting/conceptualising the wrong case(s) resulting in lack of theoretical generalisations	Developing in-depth knowledge of theoretical and empirical literature, justifying choices made
Collecting large volumes of data that are not relevant to the case or too little to be of any value	Focus data collection in line with research questions, whilst being flexible and allowing different paths to be explored
Defining/bounding the case	Focus on related components (either by time and/or space), be clear what is outside the scope of the case
Lack of rigour	Triangulation, respondent validation, the use of theoretical sampling, transparency throughout the research process
Ethical issues	Anonymise appropriately as cases are often easily identifiable to insiders, informed consent of participants
Integration with theoretical framework	Allow for unexpected issues to emerge and do not force fit, test out preliminary explanations, be clear about epistemological positions in advance

Stake's checklist for assessing the quality of a case study report[ 8 ]

1. Is this report easy to read?

2. Does it fit together, each sentence contributing to the whole?

3. Does this report have a conceptual structure (i.e. themes or issues)?

4. Are its issues developed in a series and scholarly way?

5. Is the case adequately defined?

6. Is there a sense of story to the presentation?

7. Is the reader provided some vicarious experience?

8. Have quotations been used effectively?

9. Are headings, figures, artefacts, appendices, indexes effectively used?

10. Was it edited well, then again with a last minute polish?

11. Has the writer made sound assertions, neither over- or under-interpreting?

12. Has adequate attention been paid to various contexts?

13. Were sufficient raw data presented?

14. Were data sources well chosen and in sufficient number?

15. Do observations and interpretations appear to have been triangulated?

16. Is the role and point of view of the researcher nicely apparent?

17. Is the nature of the intended audience apparent?

18. Is empathy shown for all sides?

19. Are personal intentions examined?

20. Does it appear individuals were put at risk?

Conclusions

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2288/11/100/prepub

Acknowledgements

Yin RK. Case study research, design and method. 4. London: Sage Publications Ltd.; 2009. [ Google Scholar ]
Keen J, Packwood T. Qualitative research; case study evaluation. BMJ. 1995; 311 :444–446. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Sheikh A, Halani L, Bhopal R, Netuveli G, Partridge M, Car J. et al. Facilitating the Recruitment of Minority Ethnic People into Research: Qualitative Case Study of South Asians and Asthma. PLoS Med. 2009; 6 (10):1–11. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Pinnock H, Huby G, Powell A, Kielmann T, Price D, Williams S, The process of planning, development and implementation of a General Practitioner with a Special Interest service in Primary Care Organisations in England and Wales: a comparative prospective case study. Report for the National Co-ordinating Centre for NHS Service Delivery and Organisation R&D (NCCSDO) 2008. http://www.sdo.nihr.ac.uk/files/project/99-final-report.pdf
Robertson A, Cresswell K, Takian A, Petrakaki D, Crowe S, Cornford T. et al. Prospective evaluation of the implementation and adoption of NHS Connecting for Health's national electronic health record in secondary care in England: interim findings. BMJ. 2010; 41 :c4564. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Pearson P, Steven A, Howe A, Sheikh A, Ashcroft D, Smith P. the Patient Safety Education Study Group. Learning about patient safety: organisational context and culture in the education of healthcare professionals. J Health Serv Res Policy. 2010; 15 :4–10. doi: 10.1258/jhsrp.2009.009052. [ PubMed ] [ CrossRef ] [ Google Scholar ]
van Harten WH, Casparie TF, Fisscher OA. The evaluation of the introduction of a quality management system: a process-oriented case study in a large rehabilitation hospital. Health Policy. 2002; 60 (1):17–37. doi: 10.1016/S0168-8510(01)00187-7. [ PubMed ] [ CrossRef ] [ Google Scholar ]
Stake RE. The art of case study research. London: Sage Publications Ltd.; 1995. [ Google Scholar ]
Sheikh A, Smeeth L, Ashcroft R. Randomised controlled trials in primary care: scope and application. Br J Gen Pract. 2002; 52 (482):746–51. [ PMC free article ] [ PubMed ] [ Google Scholar ]
King G, Keohane R, Verba S. Designing Social Inquiry. Princeton: Princeton University Press; 1996. [ Google Scholar ]
Doolin B. Information technology as disciplinary technology: being critical in interpretative research on information systems. Journal of Information Technology. 1998; 13 :301–311. doi: 10.1057/jit.1998.8. [ CrossRef ] [ Google Scholar ]
George AL, Bennett A. Case studies and theory development in the social sciences. Cambridge, MA: MIT Press; 2005. [ Google Scholar ]
Eccles M. the Improved Clinical Effectiveness through Behavioural Research Group (ICEBeRG) Designing theoretically-informed implementation interventions. Implementation Science. 2006; 1 :1–8. doi: 10.1186/1748-5908-1-1. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Netuveli G, Hurwitz B, Levy M, Fletcher M, Barnes G, Durham SR, Sheikh A. Ethnic variations in UK asthma frequency, morbidity, and health-service use: a systematic review and meta-analysis. Lancet. 2005; 365 (9456):312–7. [ PubMed ] [ Google Scholar ]
Sheikh A, Panesar SS, Lasserson T, Netuveli G. Recruitment of ethnic minorities to asthma studies. Thorax. 2004; 59 (7):634. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Hellström I, Nolan M, Lundh U. 'We do things together': A case study of 'couplehood' in dementia. Dementia. 2005; 4 :7–22. doi: 10.1177/1471301205049188. [ CrossRef ] [ Google Scholar ]
Som CV. Nothing seems to have changed, nothing seems to be changing and perhaps nothing will change in the NHS: doctors' response to clinical governance. International Journal of Public Sector Management. 2005; 18 :463–477. doi: 10.1108/09513550510608903. [ CrossRef ] [ Google Scholar ]
Lincoln Y, Guba E. Naturalistic inquiry. Newbury Park: Sage Publications; 1985. [ Google Scholar ]
Barbour RS. Checklists for improving rigour in qualitative research: a case of the tail wagging the dog? BMJ. 2001; 322 :1115–1117. doi: 10.1136/bmj.322.7294.1115. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Mays N, Pope C. Qualitative research in health care: Assessing quality in qualitative research. BMJ. 2000; 320 :50–52. doi: 10.1136/bmj.320.7226.50. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Mason J. Qualitative researching. London: Sage; 2002. [ Google Scholar ]
Brazier A, Cooke K, Moravan V. Using Mixed Methods for Evaluating an Integrative Approach to Cancer Care: A Case Study. Integr Cancer Ther. 2008; 7 :5–17. doi: 10.1177/1534735407313395. [ PubMed ] [ CrossRef ] [ Google Scholar ]
Miles MB, Huberman M. Qualitative data analysis: an expanded sourcebook. 2. CA: Sage Publications Inc.; 1994. [ Google Scholar ]
Pope C, Ziebland S, Mays N. Analysing qualitative data. Qualitative research in health care. BMJ. 2000; 320 :114–116. doi: 10.1136/bmj.320.7227.114. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Cresswell KM, Worth A, Sheikh A. Actor-Network Theory and its role in understanding the implementation of information technology developments in healthcare. BMC Med Inform Decis Mak. 2010; 10 (1):67. doi: 10.1186/1472-6947-10-67. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
Malterud K. Qualitative research: standards, challenges, and guidelines. Lancet. 2001; 358 :483–488. doi: 10.1016/S0140-6736(01)05627-6. [ PubMed ] [ CrossRef ] [ Google Scholar ]
Yin R. Case study research: design and methods. 2. Thousand Oaks, CA: Sage Publishing; 1994. [ Google Scholar ]
Yin R. Enhancing the quality of case studies in health services research. Health Serv Res. 1999; 34 :1209–1224. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Green J, Thorogood N. Qualitative methods for health research. 2. Los Angeles: Sage; 2009. [ Google Scholar ]
Howcroft D, Trauth E. Handbook of Critical Information Systems Research, Theory and Application. Cheltenham, UK: Northampton, MA, USA: Edward Elgar; 2005. [ Google Scholar ]
Blakie N. Approaches to Social Enquiry. Cambridge: Polity Press; 1993. [ Google Scholar ]
Doolin B. Power and resistance in the implementation of a medical management information system. Info Systems J. 2004; 14 :343–362. doi: 10.1111/j.1365-2575.2004.00176.x. [ CrossRef ] [ Google Scholar ]
Bloomfield BP, Best A. Management consultants: systems development, power and the translation of problems. Sociological Review. 1992; 40 :533–560. [ Google Scholar ]
Shanks G, Parr A. Proceedings of the European Conference on Information Systems. Naples; 2003. Positivist, single case study research in information systems: A critical analysis. [ Google Scholar ]

Art Meets Science

‘The Starry Night’ Accurately Depicts a Scientific Theory That Wasn’t Described Until Years After van Gogh’s Death

Researchers say that the iconic painting’s swirling sky lines up with Kolmogorov’s theory of turbulence, suggesting that the artist was a careful observer of the world around him

Julia Binswanger

Daily Correspondent

Vincent van Gogh ’s The Starry Night (1889), which features a sky of swirling blue hues streaked with bright gold, is one of the most famous paintings in art history. Now, new research shows that the bold brushstrokes match up with patterns of a scientific theory that wasn’t described until many years later.

The Dutch artist created the masterpiece from a psychiatric facility, which he had checked into after experiencing hallucinations and severing part of his ear. While the work is sometimes interpreted as an expression of his mental health challenges, a new study in the journal Physics of Fluids suggests that it also aligns with Kolmogorov’s theory of turbulence , which describes patterns of fluid dynamics.

Andrey Kolmogorov was a Russian mathematician who identified the way in which energy moves through water or air: Large swirls or “eddies” break into smaller eddies in a predictable way. This type of movement, called turbulent flow, can be seen in “moving water, ocean currents, blood flow, billowing storm clouds and plumes of smoke,” as CNN ’s Katie Hunt writes.

“Imagine you are standing on a bridge, and you watch the river flow. You will see swirls on the surface, and these swirls are not random,” co-author Yongxiang Huang, a scholar of fluid dynamics at China’s Xiamen University, tells CNN. “They arrange themselves in specific patterns, and these kinds of patterns can be predicted by physical laws.”

Huang’s team measured the swirls and brushstrokes in The Starry Night and used van Gogh’s color choices to estimate the sky’s movement. They found that 14 of the swirling shapes in the painting align with Kolmogorov’s theory. (Measurements of the small brush strokes also matched up with a concept called Batchelor’s scaling, which describes how energy moves in small-scale turbulence.)

Van Gogh couldn’t have known about Kolmogorov’s theory when he created The Starry Night , as he died 13 years before the mathematician was born. Instead, the researchers think he was able to successfully capture the sky’s turbulence because he was a talented artist and a meticulous observer of nature.

“[ The Starry Night ] reveals a deep and intuitive understanding of natural phenomena,” says Huang in a statement . “Van Gogh’s precise representation of turbulence might be from studying the movement of clouds and the atmosphere or an innate sense of how to capture the dynamism of the sky.”

Of course, applying physical laws to a 19th-century painting that doesn’t move is challenging. Researchers also don’t know whether van Gogh’s accurate portrayal of turbulence was simply a coincidence.

However, Adam Frank , an astrophysicist at the University of Rochester who was not involved in the study, tells NBC News ’ Ellison Barber that art and science both have the ability to capture truths about the world.

“I don’t think this is a coincidence. I think that van Gogh was responding intuitively, emotionally, to what he was seeing in the sky, and was therefore sort of recapturing those patterns that a detailed mathematical analysis would also find,” Frank says. “What he was doing was capturing in the language of painting, what would later be captured in the very beautiful language of mathematics.”

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Julia Binswanger is a freelance arts and culture reporter based in Chicago. Her work has been featured in WBEZ, Chicago magazine, Rebellious magazine and PC magazine.

Modelling the Interaction Between Incumbents and New Entrants with a Game Theory Approach: A Case Study of Public Transportation

Original Research
Open access
Published: 22 September 2024
Volume 5 , article number 895 , ( 2024 )

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Ali Amiramini Kahrizeh 1 ,
Amir Karbassi Yazdi 2 ,
Peter Wanke 3 ,
Yong Tan 4 &
Thomas Hanne 5

The transformative influence of new entrants on industries and heightened competition underscores their significance. Mature companies, threatened by their entry, deploy multiple incentives to forestall market penetration. Conversely, consumers embrace fresh participants, creating a dichotomy in reactions. This has spawned escalated conflicts between mature firms and newcomers, rooted in the latter's market entry. This study navigates this landscape by delving into the strategies, preferences, and priorities of these actors, seeking stable equilibrium and reconciliation points for these conflicts. Employing thematic analysis, it distills options, feasible scenarios, and relative preferences of each stakeholder. These insights undergo scrutiny via the GMCR + decision support model. Among 21 conceivable scenarios, the study unveils three equilibria and a semi-stable state, suggesting mature companies recalibrate their stance to explore synergies with new entrants. This research offers a panoramic perspective on the intricate interactions between mature companies and new entrants, transcending the narrow confines of entry barriers.

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Introduction

Several industries have been affected by the growth of the "sharing economy," most notably hotels (Airbnb) and taxis (Uber, Lyft, and Sidecar) [ 36 ]. Today's socio-economic and environmental problems can be solved through the sharing economy. Even so, some are skeptical about the tangible benefits of the sharing economy for society [ 19 ]. The disruptive nature of the sharing economy has posed significant challenges for incumbent players [ 8 ]. There is a belief that this business model will threaten incumbents across the economy [ 36 ]. Existing firms, often referred to as incumbents or incumbent firms, have adapted or developed their own innovations to address disruptions caused by new market entrants, new technologies, or changes in consumer behavior [ 39 ].

A disruptive business model based on technological innovation leaves incumbent firms with two options to fend off new entrants: strengthening their existing business model or adopting the new business model exclusively [ 26 ]. Uber's impact on existing businesses remains a contentious issue. Is the disruption that the sharing economy will bring to society a genuine threat to incumbents, or is it being overestimated? [ 19 ]. Apart from this debate, several countries have suspended Uber's operations, and concerns about security and safety mechanisms for accommodation-sharing businesses have cast doubt on the growth potential of this economy [ 36 ].

Are traditional jobs threatened by the expansion of the "sharing economy"? In recent years, this debate has revolved around taxi services, where digital platforms such as Uber have intensified competition. Uber does not own any cars; rather, it matches passengers with self-employed drivers and profits from each ride by taking a cut. Few inventions have generated more controversy since their inception in 2010. In Europe, taxi drivers have protested, and courts have either banned or restricted its usage. The number of drivers partnering with Uber has surged in the U.S. [ 3 ]. In Iran's taxi industry, following Uber's business model and innovating in its position, led to a transformation in the taxi industry's business model. This coincided with the development of internet infrastructure and resulted in increased user acceptance due to enhanced security, reliability, and accessibility. Taxi drivers suddenly faced reduced profits and a saturated market that disrupted their monopoly, causing conflicts with newcomers. One of the most contentious cases has been taxi drivers' complaints against internet-based taxis. Taxi drivers have cited various reasons to oppose the launch of these technological platforms. According to industry officials and drivers, these internet-based transportation platforms have disrupted market order and harmed their business by illegitimately lowering fares. An alternative approach to the interaction between incumbents and new entrants might involve designing a conflict resolution model instead of solely focusing on price and non-price mechanisms.

The strategic behavior of a decision-maker (DM) in a conflict will influence the strategic behavior of other DMs based on their interests. To resolve conflicts and promote cooperation, it is essential to accurately identify the interests of DMs and to simulate the dynamic evolution of decision-making behaviors [ 24 ]. The use of game theory to resolve conflicts over complex environmental issues among multiple DMs allows for a more realistic simulation of stakeholders' interest-based decision-making behavior [ 9 ].

A longstanding research topic in economics literature is the evaluation of the impacts on incumbents of potential or actual competition. Studies by Chang & Sokol [ 5 ] primarily focus on the effects of entry on incumbents' business outcomes, often considering revenues or profits. Recent research has examined how emerging business models of disruptive innovation, such as Uber's impact on taxi drivers [ 3 ], 4 , 7 , 19 or Airbnb's impact on hotels [ 38 , 40 ], affect incumbents in traditional markets. These papers predominantly discuss the impact of disruptive innovators on revenues and incumbents' price responses. However, the conflict between incumbents and new entrants has not been addressed in previous articles. Therefore, this article identifies DMs and their decision sets, determines all feasible states, illustrates possible state transitions using a graph model, ranks relative preferences, identifies equilibrium points, and provides strategic guidance for resolving transboundary conflicts. As a result, this study aims to identify strategies, guidelines, and appropriate policies to resolve this conflict.

This paper contributes to previous studies and offers several significant insights. From a managerial and policy perspective, it examines how incumbents can respond to the disruption caused by the sharing economy. Furthermore, it analyzes incumbents' strategies in response to the entry of a disruptive innovator using GMCR (Graph Model for Conflict Resolution). Notably, there have been no previous studies using GMCR in this context. The paper makes various important contributions to the existing literature. It provides managerial and policy implications on how incumbents affected by the disruption of the sharing economy should respond. Additionally, it explores the strategies of incumbents in response to the entry of a disruptive innovator using GMCR, marking one of the few studies to utilize GMCR in this area. Given that most of the industry is under government control, this research aims to determine whether government intervention is beneficial for the industry. Specifically, it investigates whether government intervention in balancing different types of taxi services is advantageous, or if the market should determine pricing and competitiveness. This research provides insights into the effectiveness of government intervention versus market-driven approaches by comparing countries that regulate prices with those that allow the market to set them.

The paper is structured into five parts. After the introduction in Section One, which outlines the contributions, research objectives, and research gap, Section Two presents the literature review, highlighting previous research. Part Three illustrates the models and research procedure. Part Four delves into data analysis, covering modeling, actors and their possible options, extraction and refinement of feasible situations, preferences and prioritization of actors, model analysis, equilibrium points, and analysis of one-sided movements of actors, along with coalition analysis. The final part, Part Five, engages in a discussion and conclusion, summarizing the research's results.

Literature Review

This research is centered around the competition between New Entrants and Incumbents. The relevant literature is discussed below to clarify our contribution. The competition between New Entrants and incumbents has captured the attention of numerous scholars. For instance, Chang and Sokol [ 5 ] evaluated the strategies of incumbent hotels in response to Airbnb's entry, examining both price and non-price responses. The authors employed a fixed-effect model to estimate variables such as hotel occupancy rate, price, investment in service quality, and hotel revenues. Results indicated that low-quality hotels engage in price competition with Airbnb, while premium hotels may opt to differentiate their products, attract end customers, and charge higher prices. Berger et al. [ 3 ] documented the effects of Uber on the employment and earnings of taxi drivers in U.S. cities. Their findings revealed that the labor supply of self-employed taxi drivers increased by nearly 50 percent on average following Uber's introduction. Kim et al. [ 19 ] provided insights into how Uber transformed the traditional taxi industry in New York. Through a time-series regression model, they examined variables such as the number of taxi trips, the average daily revenue of taxi drivers, and occupancy rates. The results demonstrated that incumbent taxi drivers proactively responded to the disruptive threat posed by Uber's entry, resulting in significant benefits for consumers who could now hail taxis from a broader area in New York.

Ren et al. [ 29 ] delved into the strategies incumbents adopt in response to a primary rival's exit. They considered variables such as product variety at each store and market structures. Their formal model and empirical study revealed that after the exit of a rival, the survivor aims to expand both its product and geographic presence by increasing store-level product variety and opening new stores. This expansion strategy involves simultaneously filling market gaps and preempting attractive locations to discourage potential new entrants. Du et al. [ 10 ] introduced a strategic mental model to analytically characterize the effects of incumbent repositioning costs and decision biases on firms' equilibrium strategies and profits. Their findings indicated that while biases are detrimental for firms individually, both the entrant and incumbent can achieve higher profits when biased, compared to when neither party is biased. Specifically, if the entrant is biased in estimating the incumbent's repositioning ability and the incumbent is aware of this bias, the entrant's performance is negatively impacted.

Islami et al. [ 18 ] examined the relationship between industry barriers that hinder new entrants entering a competitive market and the increased profitability of incumbents. Variables considered in the study included economies of scale, product differentiation of incumbents, capital requirements of non-incumbents, switching costs, access to distribution channels, cost disadvantages independent of size, government policy, and the profitability of incumbents. The findings indicated that industry barriers contribute to increased profitability for incumbents and act as obstacles for potential rivals entering the market. Whelan [ 37 ] extended the entry deterrence literature by investigating the coordination of advertising and pricing in markets with consumption externalities, utilizing a stochastic success function. The findings revealed that the fixed cost of entry that challengers must bear and the consumption externality parameter influences an incumbent's ability to deter entry through coordinated advertising.

Chang and Sokol [ 5 ] utilize the number of Airbnb listings in the Taiwanese market to examine the price and non-price responses by hotels within the framework of traditional industrial organization. Similarly, Zervas et al. [ 40 ] explore Airbnb’s staggered entries into Texas and their impact on hotel prices. Farronato and Fradkin [ 13 ] structurally estimate the parameters of a model of consumer utility and supplier costs following Airbnb’s entry into 46 cities in the United States. In their 2011 publication, Yan and Guizani discuss various theoretical methods and provide examples commonly employed in this area of research. Rahman et al. [ 28 ] propose an MEC-based sharing economy system that utilizes Blockchain and off-chain frameworks for the storage of immutable ledgers. By utilizing the AI infrastructure we propose, a future smart city can offer cyber-physical sharing economy services through the use of IoT data. The use of smart contracts enables the framework to provide intricate spatio-temporal services worldwide, eliminating the need for a central verification authority. During the Hajj in both 2019 and 2020, we envision comprehensive testing of different sharing economy scenarios on a large scale.

Zhang et al. [ 42 ] apply the existing institutional legitimacy literature to gain insights into the intricate process of forming new institutional legitimacy within the context of a disruptive sharing economy. The primary objective of their study is to develop a comprehensive framework to elucidate the myriad factors involved in shaping and influencing the process of legitimacy formation. To investigate the institutional legitimacy issues associated with Uber, a leading tech start-up in the sharing economy, we applied deep-learning techniques to news articles published between 2009 and 2016. The initial results indicate that the legitimacy of sharing economy disruption is not constant and varies depending on the time frame and geographical region. Zhou and Wan [ 43 ] conducted a study to examine the extent of the disruptive power that the mobile digital sharing economy has on the road freight logistics industry. The advent of new information technologies, including the mobile internet, mobile payment methods, and GPS, has revolutionized the way platforms operate. These technologies allow platforms to effortlessly connect freight shippers with carriers, leveraging the convenience and mobility offered by smartphones.

In our study, we conduct empirical research to examine the impact of the emergence of mobile digital freight matching platforms in the United States on the profitability and stock performance of two specific types of incumbent road freight logistics companies: freight arrangement companies (including freight forwarders and brokers) and trucking companies (including freight carriers). Since mobile digital freight matching platforms primarily connect small and mid-sized trucking companies with shipping demand, it is anticipated that these platforms will bring direct competition to traditional freight arrangement companies and indirect competition to large trucking companies. This, in turn, may pose operational challenges for both types of established companies. Si et al. [ 32 ] explore the connection between disruptive innovation and the sharing economy. They aim to comprehensively examine the intricate mechanisms underlying a business project centered around disruptive innovation and its ability to successfully generate, distribute, and acquire value within the context of the sharing economy. The focus of their analysis is on the specific case of bike sharing in China. By utilizing an elaborate case study, they comprehensively explore the process, underlying mechanisms, and relationships among disruptive innovation, business models, bike-sharing businesses, and value creation in the sharing economy. The concept of bike sharing is a perfect fit for the theory of disruptive innovation. Its combination of affordability and exceptional convenience has resulted in swift growth and progress in China. The failures of bike-sharing companies can be attributed to their lack of improvement in products and services, as well as their inability to establish a successful business model that effectively creates, delivers, and captures value. Various factors have impeded the sustainable development of bike-sharing companies, including strategic decision-making, internal management problems, external conflicts, and uncivilized consumer behaviors. These methods include cooperative games, Nash equilibria, and allocation games, which explore the dynamics of competition versus cooperation. For a comprehensive overview of the previous research in this area, please refer to Table 1 .

Research Methodology

Due to the complexity and multifaceted nature of the problem, the chosen approach in this research is the method of constructing the problem. The problem structuring method is a novel approach within operations research [ 22 ] that serves to address complex problems. This method empowers actors to unveil the problem's structure, identify potential outcomes and consequences for each decision, and understand the responsibilities and implications of subsequent choices [ 25 ]. Within the realm of problem structuring methods, various tools and techniques exist, one of which is game theory. Among these methods, one of the most prominent is [ 11 ].

Game theory is a discipline that investigates human decision-making within situations of interaction or conflicts of interest with others. In essence, game theory delves into the study of conflicts and cooperation among rational players [ 16 ]. The theory revolves around examining the strategic interactions and collective decisions of multiple actors, yielding outcomes that might not have been intended by any single participant. Game theory's applications include explaining events as games, predicting game outcomes, or offering recommendations for achieving improved results [ 27 ]. In this study, game theory is employed to elucidate the problem and address the posed questions, aligning with the nature of the stakeholders' issue.

With the proliferation of conflicts in both number and diversity, various models have emerged within the realm of game theory. Depending on factors such as the number of participants, the available choices, and whether actors' preferences are quantifiable or relative, these models fall into two categories: quantitative methods (numeric preferences) and non-quantitative methods (relative preferences) [ 2 ]. Traditional game theory models such as normal or extended forms are employed for game modeling and analysis [ 34 ]. However, real-world decision-makers and their choices typically exhibit significant diversity, and preferences often tend to be qualitative and relative. As a result, for scenarios of this kind, classical models used in quantitative methods may not effectively analyze the situation. Thus, non-quantitative methods are harnessed for game modeling and analysis in such contexts [ 2 ].

In the current problem, given the significant number of actors and the extensive array of options at their disposal, coupled with the challenge of unquantifiable actor preferences, the utilization of the graph model is better suited to elucidate the problem. This model presents a comprehensive approach aimed at analyzing strategic conflicts in the real world. Each strategic conflict is viewed as a decision-making issue wherein diverse scenarios and situations encompass distinct preferences for each decision-maker [ 33 ]. To this end, the GMCR + software has been employed to model and analyze game outcomes based on the graph model. The requisite data for the problem were amassed from documents, articles, reports, and news articles from various news agencies. Using the content analysis method, the options available to each actor, potential situations, and the relative preferences of each actor were extracted. Content analysis stands as a systematic technique for dissecting text-based information in a standardized manner, enabling researchers to derive insights from textual data [ 35 ].

In the initial phase of this study, gather qualitative information by conducting stakeholder surveys, expert interviews, reviewing scholarly articles, and analyzing industry reports. To gain a thorough understanding of market dynamics, it is imperative to employ a wide variety of sources. For the development of scenarios and the analysis of GMCR + , create comprehensive scenarios based on the designated themes. The GMCR + model should be utilized to simulate a range of strategic interactions and conflicts. Analyzing the scenarios allows for the identification of both stable equilibria and semi-stable states. Take the time to understand and evaluate the findings from the GMCR + analysis. Present practical strategies for established businesses to reevaluate and refine their approaches, and assess potential intersections and opportunities for cooperation with recent arrivals.

The steps involved in modeling this problem align with the graph-based approach. Adhering to the definitions and concepts elucidated within the graph model, the conflict between established and newcomer companies is framed as a game. Commencing with the delineation of the actors and their respective strategies, the process filters out infeasible combinations, eventually revealing actor preferences. The analysis subsequently delves into stable scenarios, equilibrium points, coalitions, and a multi-faceted resolution of results. Figure 2 visually outlines the modeling and analysis process for the conflict within the graph framework. GMCR's process of conflict modeling and analysis encompasses two core stages: modeling and analysis [ 17 ]. In the initial stage, through an examination of conflict history and, if necessary, consultations with experts, actors, and their forthcoming choices—encompassing an array of players' selections and strategies—are defined [ 23 ]. Post-identification of the actors and their available options, potential conflict scenarios are established.

The total number of conflict scenarios is determined using the formula 2n, where n represents the overall count of potential options across all actors. Notably, not all conceivable situations are viable. To ascertain possible situations, those that lack practical feasibility are excluded from the scenario set. An essential consideration is that while the actors' potential options may not inherently align with their interests, achieving equilibrium necessitates their inclusion. The identification of such situations can be achieved through three methods: detecting two mutually exclusive pairs, identifying the presence of at least one option, and recognizing interdependencies between the options. Once potential conflict scenarios are determined, they are prioritized using various methodologies such as option weighting, option prioritization, and direct ranking [ 6 ].

The second phase in graph models involves determining equilibrium states and analyzing the resulting outcomes. Equilibrium states signify the most probable potential resolutions of the conflict and do not inherently imply fairness or optimality for all participants. In essence, equilibrium isn't necessarily the most advantageous point for everyone; rather, it's a circumstance where an actor lacks motivation to depart from. An actor's decision to remain in or leave a situation unilaterally hinges on various factors, such as their propensity for risk-taking or risk-aversion, as well as the depth of their understanding of other participants. With this perspective, several solution concepts, which are various approaches to check the stability of each actor, have been proposed. Noteworthy among these concepts are:

Nash Stability : This concept signifies a scenario where a given actor cannot improve their situation unilaterally, assuming the strategies of other actors remain unchanged [ 1 ].

Beyond General Rationality : In this approach, an actor considers not only their own unilateral improvement options but also accounts for other actors. They decide to shift their situation only if their move wouldn't enable competitors to transition them into a worse state [ 14 ].

Beyond Symmetric Rationality : Here, it's assumed that the actor can respond after their competitors. Sustainability aligned with symmetric rationality implies that an actor doesn't gain from any unilateral improvements, as each of their moves is countered by rivals, leaving them no better off [ 14 ].

Consecutive Stability : In this context, when the situation evolves, the actor views competitors as rational entities and, beyond contemplating their unilateral improvements, also considers their own move. Sequential stability indicates a situation where an individual's unilateral enhancements are counteracted by at least one rival's unilateral improvement [ 15 ].

Constrained Movement Stability : An actor envisions h steps into the future [ 14 ].

Far-Sighted Stability : A specific state within limited movement stability wherein the parameter h approaches infinity. An actor embracing foresight stability has an extensive horizon when deciding to maintain their current situation or transition to a new one [ 21 ]. Each definition of stability characterizes a distinct type of behavioral trait. Consequently, each participant can be stable within any given scenario based on one or more solution concepts, depending on their own behavioral characteristics. Table 2 elucidates the diverse sustainability concepts along with the associated behavioral attributes for each concept. Figure 1 visually outlines the research process.

Research procedure (Authors made)

Table 2 illustrates how diverse solution concepts can analyze various actors with distinct behavioral traits, encompassing a range from cautious and conservative individuals to strategic and active participants, as well as those with forward-looking perspectives and those with shorter-term views. If a situation is deemed stable for all decision-makers according to one or more stability definitions, it is termed an equilibrium point within the game, offering a plausible solution to the conflict. Given that different solution concepts reflect a variety of conceivable behavioral attributes for decision-makers, the more a situation is identified as a point of balance across multiple solution concepts, the higher the likelihood it will be embraced by decision-makers. Consequently, this increased recognition enhances the potential for its practical realization within the real world.

Data Analysis

In this section, according to the steps mentioned in Fig. 2 , we will model and analyze the actors' conflict.

Impossible situations in GMCR + software (Authors made)

The process of conflict modeling and analysis in GMCR encompasses two primary stages of modeling and analysis [ 31 ]. In the initial stage, historical conflict review and, when necessary, consultations with experts and actors, including discussions about their forthcoming options—comprising an array of players' selections and strategies [ 30 ]—inform the process. Post-identification of the actors and their potential options, potential conflict scenarios are pinpointed. The total count of conflict scenarios arises from the formula 2n, where n signifies the overall number of possible options within the entire participant set. It's important to note that not all conceivable situations are feasible. To identify viable situations, those that lack real-world feasibility are culled from the set of scenarios. An essential consideration is that while the feasible options for the actors may not inherently align with their interests, achieving equilibrium remains crucial. These situations can be identified using three methods: identification of two mutually exclusive pairs, recognition of the presence of at least one option, and acknowledgment of interdependencies among the options. After determining feasible conflict scenarios, these situations are prioritized using distinct methodologies such as option weighting, option prioritization, and direct ranking. Within this section, adhering to the aforementioned steps, we proceed to model the conflict between established and newcomer companies.

The GMCR + uses theme analysis ideas innovatively. This combination enables a quantitative examination of qualitative insights, identifying stable equilibria and semi-stable states among plausible possibilities. The report provides a detailed analysis of potential consequences and considers multiple scenarios. The in-depth scenario analysis offers a comprehensive understanding of the competitive environment through a broad spectrum of strategic interactions and possible equilibria. Strategic alignment and conflict resolution offer several avenues for established businesses to adjust their tactics and coexist with new competitors. Market entry research focuses on defensive actions by established corporations.

Groups and Individuals Involved : These are the decision-makers who have conflict strategies and preferences.

Options for Decision-Makers : These are the available choices, which are interchangeable. Decision-makers may reject options. Conflict scenarios or configurations are determined by the choices of the decision-makers. Each scenario represents a conflict situation.

Achievable Situations : These are represented by constraints and option interactions. Desirability determines the ranking of situations for each decision-maker, and preferences can be represented by rankings or utility values.

Feasibility of Transition : This is determined by the constraints dictating the course of conflicts. The possibilities and strategic interactions of decision-makers establish these rules.

Stability Evaluation

We must evaluate the stability of each scenario to identify which ones are likely to last. Well-recognized stability concepts include Nash stability, generic meta-rationality, symmetric meta-rationality, and sequential stability.

Equilibria refer to stable states determined by selected ideas and pertain to the settlement of conflicts. Decision-makers establish alliances to accomplish objectives, examining the influence of coalitions on the dynamics and outcomes of conflicts. The strength of preferences enhances the analysis. Analyzing the progression of conflicts requires studying the modifications that occur over time and the strategic adjustments made by decision-makers.

Actors and Possible Options of Each of Them

In the initial phase, following the methodology outlined in the methodology section, the actors and their corresponding options were identified. While selecting actors and delineating their potential options, it is important to recognize that not all stakeholders play a role in the conflict; those unable to take action are excluded as conflict actors. Conversely, the options available to each actor encompass practical actions that the respective player can implement in reality. These options do not encompass the entirety of an actor's interests. In essence, an actor might be interested in undertaking a specific action but may lack the practical means to execute it. Consequently, this action isn't considered as an option for that actor. The actors were classified into three distinct categories: newcomers, taxi drivers, and the government. This classification is grounded in the distinctive attributes of each actor. Within this study, new entrants are represented by companies, and owing to their analogous upcoming choices, they are grouped under the newcomers category. A mature company, conversely, refers to an established entity currently operational in the industry. In this study, Taxirani serves as a representative example of a mature company. The government, as an entity, bears the responsibility of exercising sovereignty within the realm of policy formulation.

Extraction and Refinement of Feasible Situations

As indicated in Table 3 , a total of 8 options are available to the actors. Considering that each option may or may not be included in the strategy of the corresponding actor, theoretically, 28 or 256 combinations emerge for all conceivable game scenarios. However, it's important to note that not all of these combinations are feasible. Their occurrence in reality is limited, meaning that their realization in actual circumstances is implausible. Factors such as preferences and priorities of the actors contribute to this, making the realization of certain scenarios unlikely. Thus, before proceeding to subsequent stages, it is essential to identify and eliminate impossible scenarios.

These impossible situations are influenced by constraints and limitations that need to be applied to the game. These include:

Existence of at Least One Option : This stipulation mandates that each player must select at least one of their possible actions. For example, newcomers must choose from the options presented in Table 3 .

Two-by-Two Incompatible Options : By implementing this condition, combinations in which certain options cannot coexist are removed from the potential combinations.

Dependency Between Options : This condition introduces conditional relationships where the occurrence or absence of one option depends on the occurrence or absence of other options.

Upon the application of the constraints listed in Table 4 , infeasible combinations are removed, thereby reducing the count of potential situations to 21, as depicted in Table 5 . Each entry in this table signifies a specific situation. Within each situation, an actor's decision to choose an option is denoted by "Y" (Yes), while the absence of a choice is indicated by "N" (No). Figure 2 provides a visualization of the impossible scenarios within the GMCR + software.

Lastly, following the application of the constraints outlined in Table 5 , unviable combinations were eliminated, resulting in a reduction of the potential situations to 21, as outlined in Table 6 . Significantly, this table encapsulates distinct situations. Within each situation, an actor's decision to opt for a specific choice is denoted by "Y" (Yes), while the absence of a choice is marked by "N" (No).

Moving forward in the modeling process, the next step involves determining the potential transitions that each actor can make between various states, with a focus on defining irreversible movements. The nature of reversibility in a movement hinges on the answer to the fundamental question: if an actor transitions from an ideal state A to an ideal state B, is it feasible for them to revert back to state A subsequently? For a visual representation of the actors' reversibility within each option, please refer to Fig. 3 .

Reversibility of actors in each option (Authors made)

Preferences and Prioritization of Actors

The final stage of modeling involves determining feasible priorities and preferences for each actor. In the realm of game theory, multiple methods exist for establishing actors' preferences, encompassing direct ranking, strategy prioritization, and strategy weighting. For this purpose, the option prioritization approach was employed. Data gleaned from document analysis, individual interviews, and group discussions with various stakeholders in the subject were subjected to content analysis. Subsequently, based on this analysis, the political preferences of each participant were deduced, as delineated in Table 6 . Preferences attributed to each actor can be classified as unconditional, conditional, or a combination of both. Unconditional preferences are indicated through connecting terms like "opposite (*)," "conjunction (&)," or "disjunction (or)," whereas conditional preferences are linked through the usage of "if." The policy preferences of the actors, categorized by available options, are illustrated in Tables 6 , 7 , and 8 .

Upon inputting these preferences into the software, the prioritization of prevailing scenarios for all actors across various situations is established in accordance with Table 9 .

Model Analysis

Following the ranking and determination of priorities, and in anticipation of predicting the ultimate outcomes of the game, the model is subjected to analysis. This analysis encompasses stability assessment, examination of unilateral movements by actors, and coalition analysis, and concludes with formulating policy recommendations.

Equilibrium Points

To achieve a state of equilibrium in the conflict, it's necessary to first determine stable states for each actor. A stable state refers to a condition where an actor has no incentive to deviate or leave [ 20 ]. If all actors find themselves in stable states, this collectively constitutes an equilibrium state. The attainment of equilibrium states in the conflict involves different approaches, contingent upon actors' attitudes and perspectives. As revealed by the outcomes in Table 10 , out of the 21 possible states, there exist 3 equilibrium states and one semi-stable state among the actors' various states. This analysis is elaborated as follows:

Situation 14 : According to the Nash, GMR, SMR, SEQ, and SIM logics, detailed features of which are outlined in Table 3 , this represents the equilibrium state of the game. Here, the government amends the legislation for public transportation development while refraining from intervening in setting fare rates for new entrants and taxi companies. Taxi companies, recognizing the existing scenario, choose not to oppose it and instead cooperate with newcomers in aspects related to traffic planning and the initiation of services such as ride requests, cargo transport, parcel delivery, and student transportation. Newcomers, to secure a taxi fleet, contribute 30% of the commission per trip as city fees to the municipality. This state primarily benefits taxi drivers and new companies.

Situation 20 : Similarly, based on Nash, GMR, SMR, SEQ, and SIM logics, this is another equilibrium state in the game. It closely resembles situation 14, with the distinction that taxi companies strive to equalize fare rates while newcomers remain indifferent to innovative technological advancements. This configuration holds substantial priority for taxi drivers and new companies, albeit it may not hold a commensurate priority for the government.

Situation 21 : Aligned with Nash, GMR, SMR, SEQ, and SIM logics, this also marks an equilibrium state in the game. Analogous to situation 20, the difference lies in newcomers actively innovating and developing technological services to enhance passenger and driver safety. Alongside being stable, this situation is recognized as a coalition equilibrium, resulting in an elevated priority for taxi companies. Consequently, this holds high significance for taxi drivers and new companies, while again potentially falling lower on the priority scale for the government.

State 19 : This state is semi-stable, achieving equilibrium solely based on GMR and SEQ logics. Here, the government revises the public transportation development legislation without intervening in fare determination for new entrants and taxi companies. Taxi companies do not raise objections to the existing setup and collaborate with newcomers in aspects pertaining to traffic planning and the inception of services. Within this state, new entrants exhibit indifference towards attracting a taxi fleet. Notably, this situation provides greater benefits to taxi drivers than newcomers and the government.

The outcomes derived from analyzing the stability of potential actor states using the Nash, GMR, SMR, SEQ, and SIM logic calculations demonstrate that in all four equilibrium scenarios, taxi drivers do not oppose the current situation. Instead, they prefer collaborating with newcomers on traffic planning and service initiation for various purposes. Meanwhile, the government refrains from intervening in the fare-setting process for both newcomers and established taxi companies.

Analysis of One-Sided Movements of Actors

Through the assessment of the stability of each actor within the scope of the potential conflict situations, it becomes possible to discern unilateral changes and improvements that actors can achieve. This delineates the capacity of each player to shift the game's outcome from one state to another through individual actions, unilaterally and without relying on the actions of other players. These transformative actions are depicted in both a tree format (Fig. 4 ) and a graph format (Fig. 5 ).

Tree diagram of actors' unilateral movements and improvements (Authors made)

A graph of the actors' unilateral movements and improvements (Authors made)

The illustrated outcomes of individual movements and enhancements (depicted in Fig. 6 ) showcase bold lines to signify unilateral improvements and lighter lines to denote unilateral movements. The various colors correspond to distinct actions of different actors. For instance, referring to the above figure, managers can transition from state 14 to state 15 through either a unilateral move or a unilateral enhancement from state 8 to state 14. Notably, it is evident that state 20 offers no advantage when compared to the other states.

The graph of the unilateral improvements of the actors (Authors made)

Coalition Analysis

Another analysis that can be conducted based on the obtained results is coalition analysis, which seeks to ascertain whether the establishment of a coalition among actors could potentially lead to a new equilibrium state with greater priority. If such a coalition fails to produce an equilibrium state that holds higher priority for the actors involved, the existing stable equilibrium retains its status. Figure 6 depicts the graphical representation of unilateral improvements undertaken by the actors.

The results of the coalition analysis indicate the absence of a coalition between the actors in situations 14 and 20. Considering that a coalition between actors fails to yield an equilibrium state of greater priority for them, the existing stable equilibrium remains unchanged. As evident from the analysis, the number of improvement moves is fewer in situation 21 compared to the others. Therefore, it can be inferred that situation 21, aside from its stability, is also recognized as a coalition equilibrium. From this perspective, it holds a higher priority for taxi companies, albeit without a high priority for the government.

The academic literature has paid little attention to the distinguishing characteristics of established corporations and emerging competitors. This tool is invaluable for gaining a deeper understanding of the implementation of tactics in diverse contexts. This approach facilitates a comprehensive analysis of strategic decisions, offering a novel perspective compared to traditional methodologies. The approach I utilize integrates multiple disciplines to provide a comprehensive perspective on strategy. Through this integration, it unveils crucial insights that transcend particular theoretical frameworks.

Fresh arrivals often offer innovative solutions and novel concepts, attracting customers in search of state-of-the-art products. Mature organizations are frequently compelled to innovate or enhance their value propositions due to the disruptive impact of these innovations, leading to heightened competition and a disruption of the status quo. Increased market fragmentation is a common outcome when new competitors enter the market. If consumers begin to prefer the offerings of new competitors, established enterprises may experience a decrease in both market share and profitability. Established organizations often employ diverse strategies to mitigate the risks presented by new market participants. Potential strategies could involve capitalizing on economies of scale, enhancing product attributes, optimizing customer loyalty initiatives, and implementing price adjustments. Additionally, certain corporations may endeavor to erect barriers to entry by employing legal tactics, safeguarding their intellectual property, or forging strategic alliances. According to the report, established businesses should consider seeking avenues for collaboration with recent entrants, rather than solely focusing on defensive measures. Generally, the introduction of new competitors is advantageous for consumers, as it can lead to joint ventures, acquisitions, or partnerships. Typically, competition results in improved pricing, services, and products. The readiness of customers to embrace new rivals demonstrates the necessity for established enterprises to maintain flexibility and adapt to the evolving demands of their clientele. As consumers actively search for optimal value and innovation, established enterprises prioritize the preservation of their market standing. With the rise of new competitors, this rivalry has the potential to escalate into fierce competition for both market share and customer loyalty. The themes present in this work provide a nuanced outlook on the intricacies of the market and the tensions that arise between established enterprises and emerging contenders.

The GMCR + (Graph Model for Conflict Resolution) decision support model proves to be highly beneficial in examining and illustrating possible strategic scenarios and outcomes. The investigation revealed a total of twenty-one situations, out of which three equilibria and one semi-stable condition were discovered. These findings suggest that by being open to change and potential partnerships with newcomers, established businesses can attain stable and mutually advantageous results. It is advisable for established businesses to contemplate adjusting their tactics in order to leverage potential synergies and counter new rivals. This could encompass examining joint ventures, allocating resources towards innovation, and adopting more versatile company models. Furthermore, mature organizations should engage in active interaction with new competitors rather than merely reacting to market fluctuations. This could involve joint development of innovative products and technology, making financial investments in other companies, or forging strategic alliances. It is imperative for well-established businesses to prioritize understanding and fulfilling shifting customer demands. To ensure continued relevance and competitiveness, they should strive to better align their offerings with consumer preferences. Applying theme analysis in this context is new. The integration of theme analysis in GMCR + is particularly creative, as it enables the quantitative examination of qualitative understanding, identifying stable equilibria and semi-stable states among plausible possibilities.

The report thoroughly analyzes 21 scenarios and their consequences, covering a wide range of strategic interactions and equilibria. Among these scenarios, three stable equilibria and one semi-stable state were identified. Strategic alignment and conflict resolution offer various options for established businesses to adapt to new competitors. Traditional studies on market entry barriers often focus on defensive strategies employed by established companies. In contrast, this study explores collaboration and synergies between established businesses and recent arrivals. Collaborative methods are encouraged as an alternative to defensive posturing, fostering innovation and growth. This research offers a broader perspective than traditional analyses of market entry barriers. It considers the wider effects of new competitors on market dynamics, customer preferences, and the strategic responses of established businesses. This comprehensive approach enhances the understanding of the industry. The study covers multiple aspects and includes all key industry players, providing well-rounded conclusions and suggestions.

This research delved into the analysis of the competitive behavior between mature and new companies, highlighting the pivotal role of government in legislative matters. Given the nature of the problem faced by stakeholders, game theory was employed to elucidate the issue and address the raised inquiries. Owing to the challenge of quantifying certain upcoming options and actor preferences in the real world, the graph model was utilized as a problem-solving approach. Data crucial to this endeavor was sourced from documents, articles, reports, and news agencies. By employing thematic analysis on actors' upcoming options, feasible situations, and relative preferences, the results of the games were analyzed through the use of GMCR + software.

Results stemming from the analysis of stability for feasible states among actors, grounded in Nash, GMR, SMR, SEQ, and SIM logic calculations, reveal that out of 21 feasible states, 3 equilibrium states (14, 20, 21) and one semi-stable state (19) exist among the different states of the actors. The semi-stable state 19 only exists based on GMR and SEQ logics. Situations 14, 20, and 21 exhibit stability across all logics. In these situations, no actor can improve their position through unilateral actions given fixed strategies by other players (Nash equilibrium). The actors do not gain from any individual behavior (SEQ equilibrium). Actors won't be placed in worse conditions by competitors if they decide to change their situation (GMR equilibrium). Additionally, none of the actors are confined by competitors' strategies (SIM equilibrium). Furthermore, foreseeable behaviors of the actors against competitors are stable (SEQ & SIM balance), which remain stable over the long term (SMR balance).

In all four equilibrium scenarios, taxi drivers show no resistance to the current situation and exhibit a preference for collaboration with newcomers and startups involved in car requests, cargo transportation, parcel delivery, and student services. Meanwhile, the government amends public transportation development laws but refrains from interfering in determining route fares for newcomers and taxi companies. Situation 21, apart from being stable, is recognized as a coalition equilibrium, thereby affording a higher priority to traditional taxi companies over internet-based ones.

Based on the findings derived from the stability analysis of actors' possible situations using Nash, GMR, SMR, SEQ, and SIM logic calculations, taxi drivers are recommended to adopt a cooperative stance with newcomers within the framework of traffic and air pollution plans. Collaborating with other startups for car requests, cargo transportation, parcel delivery, and student services, in exchange for commissions, is also advised. Additionally, matching fare rates with internet companies can help augment demand. This research aimed to conceptually elucidate the interaction between mature and newcomer companies in the intra-city transportation sector using the graph model. Future research could enhance these findings through qualitative investigations, while further development of the model in industries where mature companies face challenges can offer valuable comparative insights.

Data Availability

The data that support the findings of this study are available from the corresponding author upon request.

Abraham L. A game of competition for risk. 2023. ArXiv Preprint ArXiv:2305.18941 .

Aghmashhadi AH, Zahedi S, Kazemi A, Fürst C, Cirella GT. Conflict analysis of physical industrial land development policy using game theory and graph model for conflict resolution in Markazi Province. Land. 2022;11(4):501.

Article Google Scholar

Berger T, Chen C, Frey CB. Drivers of disruption? Estimating the Uber effect. Eur Econ Rev. 2018;110:197–210.

Chang H-H. The economic effects of Uber on taxi drivers in Taiwan. J Compet Law Econ. 2017;13(3):475–500.

Chang H, Sokol DD. How incumbents respond to competition from innovative disruptors in the sharing economy—The impact of Airbnb on hotel performance. Strateg Manag J. 2022;43(3):425–46.

Chen L, Xu H, Pedrycz W. Conflict analysis based on a novel three-way decisions graph model for conflict resolution method under hesitant fuzzy environment. Inf Fus. 2023;101936.

Cramer J, Krueger AB. Disruptive change in the taxi business: the case of Uber. Am Econ Rev. 2016;106(5):177–82.

Distelmans M, Scheerlinck I. Institutional strategies in the ridesharing economy: A content analysis based on Uber’s example. Sustainability. 2021;13(14):8037.

Dowlatabadi N, Banihabib ME, Roozbahani A, Randhir TO. Enhanced GMCR model for resolving conflicts in a transboundary wetland. Sci Total Environ. 2020;744: 140816.

Du X, Li M, Wu B. Incumbent repositioning with decision biases. Strateg Manage J. 2019;40(12):1984–2010.

Erol I, Ar IM, Peker I, Searcy C. Alleviating the impact of the Barriers to circular economy adoption through blockchain: An investigation using an integrated MCDM-based QFD with hesitant fuzzy linguistic term sets. Comput Ind Eng. 2022;165: 107962.

Fang L, Hipel KW, Kilgour DM. Interactive decision making: The graph model for conflict resolution, vol. 11. John Wiley & Sons; 1993.

Google Scholar

Farronato C, Fradkin A. The welfare effects of peer entry: the case of Airbnb and the accommodation industry. Am Econ Rev. 2022;112(6):1782–817.

Guan G, Liang Z. A stochastic Nash equilibrium portfolio game between two DC pension funds. Insur Math Econ. 2016;70:237–44.

Article MathSciNet Google Scholar

Hipel KW, Fang L, Kilgour DM. The graph model for conflict resolution: reflections on three decades of development. Group Decis Negot. 2020;29:11–60.

Ho E, Rajagopalan A, Skvortsov A, Arulampalam S, Piraveenan M. Game Theory in defence applications: a review. Sensors. 2022;22(3):1032.

Huang L, Zhen L, Wang J, Zhang X. Blockchain implementation for circular supply chain management: evaluating critical success factors. Ind Mark Manage. 2022;102:451–64.

Islami X, Islami V, Topuzovska Latkovikj M, Mulloli E. Barriers hindering the entry of new firms to the competitive market and profitability of incumbents. Manage J Contemp Manage Issues. 2019;24(2):121–43.

Kim K, Baek C, Lee J-D. Creative destruction of the sharing economy in action: the case of Uber. Transp Res Part A Policy Pract. 2018;110:118–27.

Lippert B, von Ondarza N, Perthes V. Politik-SWP-Deutsches SW. European strategic autonomy: actors, issues, conflicts of interests, 2019.

Martini E. A quintuple helix model for foresight: Analyzing the developments of digital technologies in order to outline possible future scenarios. Front Sociol. 2023;7:1102815.

Midgley G, Cavana RY, Brocklesby J, Foote JL, Wood DRR, Ahuriri-Driscoll A. Towards a new framework for evaluating systemic problem structuring methods. Eur J Oper Res. 2013;229(1):143–54.

Mittal A, Scholten L, Kapelan Z. A review of serious games for urban water management decisions: current gaps and future research directions. Water Res. 2022;215: 118217.

Nazari S, Ahmadi A, Rad SK, Ebrahimi B. Application of non-cooperative dynamic game theory for groundwater conflict resolution. J Environ Manage. 2020;270: 110889.

Nordström M. AI under great uncertainty: implications and decision strategies for public policy. AI & Soc. 2022;37(4):1703–14.

Osiyevskyy O, Dewald J. Explorative versus exploitative business model change: the cognitive antecedents of firm-level responses to disruptive innovation. Strateg Entrep J. 2015;9(1):58–78.

Peng J, Zhang Q. Construction group conflict under resource overlap: a game theory approach. Eng Constr Arch Manage. 2023.

Rahman MA, Rashid MM, Hossain MS, Hassanain E, Alhamid MF, Guizani M. Blockchain and IoT-based cognitive edge framework for sharing economy services in a smart city. IEEE Access. 2019;7:18611–21.

Ren CR, Hu Y, Cui TH. Responses to rival exit: product variety, market expansion, and preexisting market structure. Strateg Manag J. 2019;40(2):253–76.

Roungas B, Bekius F, Meijer S. The game between game theory and gaming simulations: design choices. Simul Gaming. 2019;50(2):180–201.

Shahbaznezhadfard M, Yousefi S, Hipel KW, Hegazy T. Dynamic-based graph model for conflict resolution: systems thinking adaptation to solve real-world conflicts. In 20th International Conference on Group Decision and Negotiation, 2020.

Si S, Chen H, Liu W, Yan Y. Disruptive innovation, business model and sharing economy: the bike-sharing cases in China. Manag Decis. 2021;59(11):2674–92.

Tang M, Liao H. A graph model for conflict resolution with inconsistent preferences among large-scale participants. Fuzzy Optim Decis Mak. 2022;1–24.

Traulsen A, Glynatsi NE. The future of theoretical evolutionary game theory. Philos Trans R Soc B. 2023;378(1876):20210508.

Vears DF, Gillam L. Inductive content analysis: a guide for beginning qualitative researchers. Focus Health Prof Educ Multi-Discip J. 2022;23(1):111–27.

Wallsten, S. The competitive effects of the sharing economy: how is Uber changing taxis. Technol Policy Inst. 2015;22(3).

Whelan A. Entry deterrence, coordinating advertising and pricing in markets with consumption externalities. BE J Theor Econ. 2018;19(2):20170058.

MathSciNet Google Scholar

Xie KL, Kwok L. The effects of Airbnb’s price positioning on hotel performance. Int J Hosp Manag. 2017;67:174–84.

Zach FJ, Nicolau JL, Sharma A. Disruptive innovation, innovation adoption and incumbent market value: the case of Airbnb. Ann Tour Res. 2020;80: 102818.

Zervas G, Proserpio D, Byers JW. The rise of the sharing economy: estimating the impact of Airbnb on the hotel industry. J Mark Res. 2017;54(5):687–705.

Zhang Y, Guizani M, editors. Game theory for wireless communications and networking. CRC Press; 2011.

Zhang N, Kien SS, Lee GW. The institutional legitimacy of disruptive start-ups in sharing economy. In PACIS, 2018. p. 343.

Zhou Z, Wan X. Does the sharing economy technology disrupt incumbents? Exploring the influences of mobile digital freight matching platforms on road freight logistics firms. Prod Oper Manag. 2022;31(1):117–37.

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Hurricane tracker, severe weather, radar & maps, news & features, winter center, news / weather news, turbulent skies of vincent van gogh’s ‘the starry night’ align with a scientific theory, study finds.

The dappled starlight and swirling clouds of Vincent van Gogh’s “The Starry Night” are thought to reflect the artist’s tumultuous state of mind. A new analysis by physicists suggests the artist had an intuitive understanding of the mathematical structure of turbulent flow.

By Katie Hunt, CNN

Published Sep 19, 2024 2:35 PM PDT | Updated Sep 19, 2024 3:33 PM PDT

The Starry Night (June 1889) by van Gogh is pictured. (Photo credit: Art Images/Getty Images via CNN Newsource)

Editor's note: Sign up for CNN’s Wonder Theory science newsletter. Explore the universe with news on fascinating discoveries, scientific advancements and more .

(CNN) — The dappled starlight and swirling clouds of Vincent van Gogh’s “The Starry Night” are thought to reflect the artist’s tumultuous state of mind when he painted the work in 1889.

Now, a new analysis by physicists based in China and France suggests the artist had a deep, intuitive understanding of the mathematical structure of turbulent flow .

As a common natural phenomenon observed in fluids — moving water, ocean currents, blood flow, billowing storm clouds and plumes of smoke — turbulent flow is chaotic, as larger swirls or eddies, form and break down into smaller ones.

It may appear random to the casual observer, but turbulence nonetheless follows a cascading pattern that can be studied and, at least partially, explained using mathematical equations.

“Imagine you are standing on a bridge, and you watch the river flow. You will see swirls on the surface, and these swirls are not random. They arrange themselves in specific patterns, and these kinds of patterns can be predicted by physical laws,” said Yongxiang Huang, lead author of the study that published Tuesday in the scientific journal Physics of Fluids. Huang is a researcher at State Key Laboratory of Marine Environmental Science & College of Ocean and Earth Sciences at Xiamen University in southeastern China.

The researchers studied the 14 whirls or eddies in van Gogh's celebrated painting. (Photo credits: Yinxiang Ma via CNN Newsource)

“The Starry Night” is an oil-on-canvas painting that, the study noted, depicts a view just before sunrise from the east-facing window of the artist’s asylum room at Saint-Rémy-de-Provence in southern France. Van Gogh had admitted himself to an asylum there after mutilating his left ear .

Using a digital image of the painting, Huang and his colleagues examined the scale of its 14 main whirling shapes to understand whether they aligned with physical theories that describe the transfer of energy from large- to small-scale eddies as they collide and interact with one another.

‘The Starry Night’ and turbulence theories

The atmospheric motion of the painted sky cannot be directly measured, so Huang and his colleagues precisely measured the brushstrokes and compared the size of the brushstrokes to the mathematical scales expected from turbulence theories. To gauge physical movement, they used the relative brightness or luminance of the varying paint colors.

They discovered that the sizes of the 14 whirls or eddies in “The Starry Night,” and their relative distance and intensity, follow a physical law that governs fluid dynamics known as Kolmogorov’s theory of turbulence .

In the 1940s, Soviet mathematician Andrey Kolmogorov described a mathematical relationship between the fluctuations in a flow’s speed and the rate at which its energy dissipates.

Huang and the team also found that the paint, at the smallest scale, mixes around with some background swirls and whirls in a fashion predicted by turbulence theory, following a statistical pattern known as Batchelor’s scaling. Batchelor’s scaling mathematically represents how small particles, such as drifting algae in the ocean or pieces of dust in the wind, are passively mixed around by turbulent flow.

“This is cool. Indeed this is the type of statistics you would expect from algae blooms being swept around by ocean currents, or dust and particulates in the air,” said James Beattie, a postdoctoral researcher in the department of astrophysical sciences at Princeton University in New Jersey, in an email. Beattie wasn’t involved in this study but has conducted similar research on the artwork.

“In my paper, I only ever really looked at the large (swirls in the painting), so I didn’t see this second relation,” he said, referring to the Batchelor’s scaling.

‘An amazing coincidence’

Of course, Huang said, van Gogh would not have been aware of such equations but likely he spent a lot of time observing turbulence in nature.

The team also studied the clouds in the painting "Chain Pier, Brighton," created by British artist John Constable in 1826-7. (Photo credit: De Agostini/Getty Images via CNN Newsource)

“I think this physical relationship must be embedded in his mind so that’s why when he made this famous ‘Starry Night’ painting, it mimics the real flow,” Huang said.

Beattie agreed: “It’s an amazing coincidence that Van Gogh’s beautiful painting shares many of the same statistics as turbulence,” he said.

“This makes some sense — the models have been constructed to try to capture the statistics of eddies and swirls on multiple scales, each swirl communicating with other swirls through the turbulent cascade. In some sense, Van Gogh painted something that represents this phenomenon, so why shouldn’t there be some convergence between the theoretical models and the statistics of Van Gogh’s swirls?”

The study team performed the same analysis and detected the same phenomenon in two other images, one a painting, “ Chain Pier, Brighton ,” created by British artist John Constable in 1826-7, and the other a photograph of Jupiter’s Great Red Spot , taken by NASA’s Voyager 1 spacecraft on March 5, 1979.

“Unlike ‘The Starry Night,’ this painting lacks well-defined swirling patterns, but the clouds are rich of structures with different scales, resembling those frequently seen in the sky,” the study noted of Constable’s artwork.

On display at the Museum of Modern Art in New York, “The Starry Night” is an enormously popular work of art that has been recreated in Lego bricks , drones and dominoes .

Huang said that scientists had long struggled to describe turbulent flow in fluid dynamics in a way that would allow them to predict the phenomenon and that a complete explanation remains a prevailing mystery of physics. A thorough understanding would help with weather forecasting, flight turbulence and many other processes, he said.

This image of Jupiter's Great Red Spot taken by NASA's Voyager 1 in 1979 also shows turbulent flow, according to the study. (Photo credit: NASA Goddard Space Flight Center via CNN Newsource)

“Even after more than 100 years (of) study, we even don’t know how to define this complex phenomenon,” Huang said. “It’s extremely important, but it’s extremely difficult.”

The fact that “The Starry Night” matched statistical models of turbulence even though the artwork doesn’t actually move could suggest that the statistical methods and tools are less precise than scientists may have thought, Beattie said.

The painting can’t be precisely measured because it’s “actually not turbulence. … (I)t has no kinetic energy,” he said.

However, Beattie said that he was a huge fan of the work of art and that it reflected universality and the beauty of turbulence.

“I deeply love the fact that I can take my understanding of the turbulence in the plasma between galaxies and apply it to the turbulence between stars, between Earth and the Sun or in our own lakes, oceans and atmosphere,” he said.

“What I take away from studies like this is that (van Gogh) captured some of this universality in the beautiful (‘Starry Night’),” Beattie added. “And I think people know this. They know that something wonderful has been embedded in this painting and we are drawn to it.”

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Frederick Winslow Taylor is widely regarded as the pioneer of scientific management theory. Developed in the early 20th century, Taylor's principles aimed to revolutionise industrial practices by emphasising systematic efficiency and productivity. This blog post explores the core tenets of Taylor's theory and their significance in the context of organisational success.Learn more by watching ...
What is Scientific Management Theory? A Complete Guide
Scientific management theory, also known as Taylorism, is a management approach aimed at improving economic efficiency and labor productivity. Developed by Frederick W. Taylor (1856-1915), it applies scientific methods to analyze workflows and optimize production processes. By conducting research, collecting data, and applying the scientific ...
4 Business Ideas That Changed the World: Scientific Management
Case Study: Mass Production and the Beginnings of Scientific Management, by Thomas K. McCraw; ... It was the birth of a management theory… called scientific management or Taylorism. And Taylor ...
Toward Developing a Framework for Conducting Case Study Research
So they consider using case study for theory building, theory testing, hypothesis building, hypothesis testing, and description. We have considered these purposes in ... (1998). The scientific theory-building process: A primer using the case of TQM. Journal of operations Management, 16, 321-339. Crossref. Google Scholar. Huberman M., Miles M ...
What is Scientific Management Theory? Scientific Management Theory In A
Scientific Management Theory was created by Frederick Winslow Taylor in 1911 as a means of encouraging industrial companies to switch to mass production. With a background in mechanical engineering, he applied engineering principles to workplace productivity on the factory floor. ... Amazon Case Study: Amazon uses piece-rate payment for ...
The theory contribution of case study research designs
The objective of this paper is to highlight similarities and differences across various case study designs and to analyze their respective contributions to theory. Although different designs reveal some common underlying characteristics, a comparison of such case study research designs demonstrates that case study research incorporates different scientific goals and collection and analysis of ...
The case study approach
The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design ...
What Is a Scientific Theory?
Guided by the prestigious Stanford Encyclopedia of Philosophy [13], we learn that there are three different ways of looking at a scientific theory: the syntactic, the semantic, and the pragmatic. Wade Savage distinguishes these philosophical perspectives as follows [14]. The syntactic view that a scientific theory is an axiomatized collection of phrases or postulates has been challenged by the ...
The Relevance of Taylor's Scientific Management in the Modern Era
The relevance o f scientific management and equity theory . in ... Survey and Case Study Findings, 101-118. ... Many regard Taylor as the founding father of management studies and scientific ...
A Necessary Dialogue: Theory in Case Study Research
Theory might relate to case study in a number of ways. First, there is theory of the case which informs how the case is constructed and selected. Second, theory for the case: here cases might test or apply theory. The researcher might begin with the theory and see how the case does or does not fit.
PDF Comparing the Five Approaches
grounded theory, and a holistic view of how a culture-sharing group works results in an ethnography. An in-depth study of a bounded system or a case (or several cases) becomes a case study. The general structures of the written report may be used in designing a journal-article-length study. However, because of the numerous steps in
Case Study Method: A Step-by-Step Guide for Business Researchers
Some famous books about case study methodology (Merriam, 2002; Stake, 1995; Yin, 2011) provide useful details on case study research but they emphasize more on theory as compared to practice, and most of them do not provide the basic knowledge of case study conduct for beginners (Hancock & Algozzine, 2016). This article is an attempt to bridge ...
Case Study Methodology of Qualitative Research: Key Attributes and
A case study is one of the most commonly used methodologies of social research. This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate ...
What Is a Case Study?
Revised on November 20, 2023. A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research. A case study research design usually involves qualitative methods, but quantitative methods are ...
Case Study Methods and Examples
The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case. It is unique given one characteristic: case studies draw from more than one data source. Case studies are inherently multimodal or mixed ...
Writing a Case Study
The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case ...
Theory vs. Hypothesis: Basics of the Scientific Method
Theory vs. Hypothesis: Basics of the Scientific Method. Written by MasterClass. Last updated: Jun 7, 2021 • 2 min read. Though you may hear the terms "theory" and "hypothesis" used interchangeably, these two scientific terms have drastically different meanings in the world of science.
The case study approach
A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5), the ...
Building Theories from Case Study Research
This paper describes the process of inducting theory using case studies—from specifying the research questions to reaching closure. Some features of the process, such as problem definition and construct validation, are similar to hypothesis-testing research. Others, such as within-case analysis and replication logic, are unique to the inductive, case-oriented process. Overall, the process ...
'The Starry Night' Accurately Depicts a Scientific Theory That Wasn't
Vincent van Gogh's The Starry Night (1889), which features a sky of swirling blue hues streaked with bright gold, is one of the most famous paintings in art history. Now, new research shows that ...
Modelling the Interaction Between Incumbents and New ...
Game theory is a discipline that investigates human decision-making within situations of interaction or conflicts of interest with others. In essence, game theory delves into the study of conflicts and cooperation among rational players . The theory revolves around examining the strategic interactions and collective decisions of multiple actors ...
Turbulent skies of Vincent Van Gogh's 'The Starry Night ...
A new study suggests Vincent van Gogh showed a deep, intuitive understanding of the mathematical structure of turbulence in his painting "The Starry Night."
Turbulent skies of Vincent Van Gogh's 'The Starry Night' align with a
The swirling clouds of van Gogh's "The Starry Night" are thought to reflect the artist's tumultuous state of mind. A new analysis suggests the artist had an understanding of the ...

Scientific Management Theory: Definition, History, Principles, Examples, and FAQs

What is Scientific Management Theory?

A Brief History of Scientific Management Theory

Studies in Scientific Management Theory

Motion Study

Fatigue Study

Rate Setting

Principles of Scientific Management Theory

Science, not the Rule of Thumb

Harmony, Not Discord

Mental Revolution

Cooperation, not Individualism

Development of Every Person to His Greatest Efficiency

Contribution of Scientific Management Theory

Limitations of Scientific Management Approach

Contributors to Scientific Management Approach

Examples of Scientific Management Theory

McDonald’s:

Ford Motor Company:

Time Study Vs. Motion Study

Scientific Management Theory: FAQs

What is Taylorism?

What are the Components of Scientific Management Theory?

What are the Principles of Scientific Management Theory?

What is Time Study?

What is Motion Study?

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4 Business Ideas That Changed the World: Scientific Management

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What is Scientific Management Theory? Scientific Management Theory In A Nutshell

Understanding Scientific Management Theory

Taylor’s classic assumptions about workers

The four core principles of Scientific Management Theory

Examples of modern companies employing Scientific Management Theory

McDonald’s Case Study

The aviation industry case study

The role of management and crew

The importance of solving the aircrew-scheduling problem

Development of the model

Key takeaways

Key Highlights

What are the 4 Principles of Scientific Management?

What is the example of scientific management theory?

Connected Management Frameworks

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Gennaro Cuofano

The case study approach

Introduction

What is a case study?

What are case studies used for?

How are case studies conducted?

Defining the case

Selecting the case(s)

Collecting the data

Analysing, interpreting and reporting case studies

What are the potential pitfalls and how can these be avoided?

Conclusions

Pre-publication history

Acknowledgements

Author information

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The Relevance of Taylor's Scientific Management in the Modern Era

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