INTRODUCTION

Case study research has emerged as a powerful methodology in business research, offering a nuanced approach to exploring complex organizational phenomena that cannot be fully captured through traditional quantitative methods [1,2]. Unlike other research designs, case studies provide an in-depth examination of real-world business operations, strategic decision-making, and market dynamics [3]. This approach is particularly relevant as businesses navigate challenges such as digital transformation, globalization and shifting consumer behaviours. However, despite its growing acceptance, case study research is often criticized for its perceived lack of scientific rigour, with concerns regarding validity, reliability and generalizability [4]. A major misconception is the conflation of case study research with case study teaching, which has led to scepticism about its credibility as a research method [5,6].

The research problem addressed in this study is the ongoing scepticism surrounding the legitimacy and rigour of case study research in business studies. While case studies offer rich insights into contemporary business challenges, their acceptance is hindered by concerns over methodological robustness. Contrary to criticisms, case study research employs systematic methodologies, including structured data collection, triangulation and theoretical generalization, which enhance its validity and reliability [2,7]. The primary research goal is to examine the methodological strengths of case study research, emphasizing its rigour through established frameworks [8]. Additionally, this study aims to highlight the practical contributions of case study research in understanding business sustainability and technological disruptions, demonstrating its value in both academic and practical contexts [9].

Case study research has played a crucial role in analysing corporate sustainability strategies in multinational firms and examining how Small Medium Enterprises (SMEs) navigate digital disruption. These real-world applications highlight the method’s ability to capture industry-specific insights and inform strategic decision-making. Furthermore, integrating case study research into business education is crucial, as it equips students with analytical tools for real-world problem-solving, bridging the gap between theoretical knowledge and practical application [9–11]. By addressing these issues, this study seeks to reinforce the credibility of case study research as a legitimate and valuable method in business research. It argues for a more structured approach to case study design to enhance its scientific acceptance while maintaining its unique ability to capture rich, contextual insights that inform strategic decision-making in a rapidly evolving business environment.

In the rapidly evolving business landscape, organizations must respond to constant shifts such as digital transformation, market volatility, and increasing pressure to adopt sustainable practices. The ability to assess business strategies effectively is essential for long-term success. One of the most powerful tools for evaluating these strategies is the case study methodology. Case studies provide in-depth, contextualized insights that help researchers and practitioners understand not only what happened in a given business intervention but also why certain outcomes occurred and how they are influenced by multiple variables. The value of case studies in business evaluation research is particularly evident when examining complex scenarios where multiple factors intersect. One notable instance is the implementation of digital transformation initiatives in large corporations, which demonstrates how organizations adapt to technological advancements to enhance operations, customer engagement, and overall efficiency. Digital transformation is not a straightforward technological change; it is deeply intertwined with organizational culture, leadership decisions, market conditions, and external factors such as regulatory shifts. A case study approach allows researchers to explore these multiple dimensions in great detail. The successful adoption of digital technologies requires aligning technology with business processes and leadership strategies.

Furthermore, case studies offer flexibility in addressing the unique contexts of different industries or organizations. They can reveal how large multinational corporations implement technologies differently depending on their geographical locations, the maturity of their digital ecosystems, and the level of organizational readiness when evaluating digital transformation. This adaptability makes case studies an invaluable tool in today’s business research, where there is no one-size-fits-all solution to organizational challenges. Moreover, in the face of market volatility, where businesses frequently adjust strategies in response to shifting external conditions, case studies provide insights into how organizations make adaptive decisions. Case studies focusing on real-time responses provide valuable evidence on how organizations develop and deploy dynamic capabilities in response to market fluctuations. The real-world examples provided by case studies offer compelling narratives that provide guidance for other organizations seeking to integrate these concerns into their strategies.

The iterative and reflective nature of case study research allows businesses to continuously learn and refine strategies. Unlike traditional research methodologies that might offer broad generalizations, case studies provide specific insights into what works in particular contexts, making them highly actionable. This enables businesses to continuously adapt their strategies in response to both internal and external pressures, ensuring long-term success. Therefore, case studies are indispensable tools in business evaluation research, especially in today’s complex and ever-changing business environment. To further enhance the application of case study research in business studies, researchers should adopt a structured case study framework that incorporates clear research objectives, multiple data sources, and triangulation techniques to enhance credibility and reliability. Integrating comparative case studies across industries and regions can increase generalizability and deepen insights into business challenges. Researchers should also utilize digital tools for data collection and analysis, such as artificial intelligence driven analytics and qualitative data software, to enhance the efficiency of case study research. Encouraging interdisciplinary collaboration by integrating case study research with quantitative methodologies will provide a holistic understanding of business phenomena.

Academicians and business educators should embed case study methodologies into business curricula by designing course modules that emphasize real-world case applications. Encouraging students to engage in live case study projects with businesses can foster hands-on learning experiences that bridge academic theory with practical applications. Developing an open-access repository of business case studies to be used as teaching tools will enable a wider audience to access well-documented business scenarios. Additionally, training students in qualitative research methods, including case study analysis, will improve their analytical and critical thinking skills. Policymakers and industry practitioners should promote the integration of case study findings into business policy development, ensuring that regulatory decisions are informed by real-world business challenges and best practices. Supporting funding for case study research that examines the impact of business policies, technological changes, and economic reforms on organizations and industries is crucial. Policymakers should also encourage partnerships between academia and industry to create practitioner-focused case studies that address current business issues and strategic decision-making. Facilitating knowledge-sharing platforms where businesses, researchers, and policymakers can discuss case study findings and collaboratively develop solutions for emerging challenges will further strengthen the role of case study research in business strategy and decision-making. By implementing these recommendations, business scholars can better integrate case study research into academic and professional practices, ensuring its continued relevance and contribution to the field. The structured use of case studies will not only enhance business education but also provide actionable insights that drive innovation, policy formation, and strategic decision-making in today’s dynamic business environment.

Case study research is characterized by several essential features that enhance its effectiveness in capturing complex business phenomena. A key feature is contextual analysis, which ensures that business dynamics are studied within their real-world settings. This approach provides realistic and applicable insights but may limit generalizability [12]. Another significant aspect is in-depth investigation, where researchers use multiple data sources and perspectives to explore cases comprehensively. While this method allows for a deep understanding of underlying business issues, it is time-intensive and requires substantial resources [13]. A flexible research design is another defining characteristic, allowing researchers to adapt methodologies based on emerging data. This adaptability ensures responsiveness to complex business challenges but may lead to inconsistencies if not carefully managed. The use of data triangulation, which integrates qualitative and quantitative data sources, enhances empirical rigour and mitigates researcher bias [14]. However, effectively analysing and synthesizing diverse data types requires expertise in mixed methods research.

Case study research is also distinguished by its rich descriptive output, enabling researchers to construct detailed narratives that contribute to theory development and practical applications. However, if not well-structured, these narratives may lack analytical focus [15]. The method also relies on multiple data sources such as interviews, documents and observations which enhance credibility but pose challenges in data management and integration [16]. Case studies can be single-case or case in design. While single-case studies offer deep insights into specific phenomena, case studies allow for comparative analysis across different contexts, increasing the robustness of findings [17]. Additionally, case studies serve exploratory, descriptive or explanatory purposes, making them versatile for various research objectives. However, without clear research questions, scope creep can occur [18]. Another critical element is stakeholder involvement, which ensures practical relevance but may introduce bias if stakeholder influence is too strong. Furthermore, case study research often examines dynamic processes over time, offering longitudinal insights into business transformations [19]. However, this emphasis on long-term trends may overlook short-term fluctuations. Ethical considerations play a crucial role in case study research. Researchers must navigate confidentiality, informed consent and participant rights to maintain ethical integrity. While ethical oversight strengthens research reliability, obtaining necessary approvals can extend research timelines [20]. By addressing these methodological strengths and challenges, this study highlights the value of case study research in providing detailed, actionable insights into business dynamics. Careful design and execution of case studies ensure their credibility and reinforce their role as a critical tool for both academic research and business practice.

In today’s fast-paced and ever-changing business environment, organizations are confronted with multifaceted challenges such as digital transformation, globalization and shifting consumer behaviours. While traditional quantitative research methods provide valuable insights into broad trends and patterns, they often fall short in capturing the complexities and subtleties that underlie these challenges. Case study research, on the other hand, offers a deeper, more comprehensive exploration of these phenomena by focusing on real-world contexts and allowing for a detailed examination of business operations, strategic decision-making and market dynamics [21,22]. Despite its growing relevance, case study research continues to face scepticism within both the academic and business communities. One key issue is the confusion between case study research, an investigative method aimed at understanding and explaining complex phenomena and the case study teaching method, which is often used in classrooms to guide students toward specific conclusions. This misunderstanding can lead to doubts about the scientific rigour and validity of case study research, especially when it comes to addressing contemporary issues in business [23]. Moreover, although established frameworks exist to ensure construct validity, internal and external validity, and reliability in case study research, these guidelines are not always fully understood or consistently applied [11]. This lack of methodological clarity contributes to the underutilization of case studies in business research and education, limiting their potential to generate actionable insights and inform strategic decision-making. Furthermore, as businesses face increasingly complex and dynamic challenges such as artificial intelligence-driven business models, sustainability concerns and regulatory shifts, there is an urgent need for rigourous qualitative research methods that can provide deeper contextual insights. The existing literature on case study research largely focuses on theoretical discussions rather than empirical evaluations of how methodological rigour is maintained in practice [24]. This study aims to bridge this gap by critically examining best practices for designing and conducting case study research to enhance its credibility and acceptance in business studies.

This study aims to establish the importance and methodological rigour of case study research in business studies. Specifically, it seeks to demonstrate how case studies provide rich, context-specific insights into contemporary business challenges such as digital transformation, corporate sustainability market dynamics areas etc. often inadequately addressed by traditional research methods. By examining key methodological features, including real-world contextual analysis, in-depth investigation and adaptability to evolving research questions, this study highlights the unique contributions of case study research to both theoretical and practical knowledge. Additionally, this research seeks to reinforce the credibility of case study research by clarifying its methodological rigour and addressing common misconceptions regarding its validity and reliability. It will explore established research frameworks to illustrate best practices that enhance the robustness of case study methodology. By doing so, the study aims to bridge the gap between scepticism and acceptance of case study research within academic and business communities. Furthermore, this study advocates for the integration of case study research into business education, demonstrating its value in equipping students and practitioners with critical thinking and problem-solving skills. By fostering a deeper understanding of real-world business complexities, case study research serves as a vital tool for both scholarly inquiry and strategic decision-making. Given the limitations of the existing structure, this study will adopt a systematic literature review (SLR) as its primary research method to ensure a structured and scientifically rigourous approach. This approach will involve a detailed literature search, selection criteria, and analytical methods to synthesize relevant findings. The obtained results will be critically discussed and concluded to provide a comprehensive perspective on the relevance and rigour of case study research in business studies. Ultimately, this research aims to strengthen the position of case study methodology as a credible and indispensable approach in business research, education and practice.

Case study research has long been a cornerstone of business scholarship, offering unparalleled depth in analysing complex phenomena. Yet, its methodological rigour and applicability continue to spark debate among scholars. While widely recognized in disciplines such as sociology, education, and psychology, its adoption in business research has often been met with scepticism regarding its validity and reliability [25]. Despite this scepticism, case study research remains a powerful methodological tool, particularly in exploring complex business phenomena where contextual understanding is essential [26,27]. Over time, case study research has evolved from being viewed as a purely descriptive, anecdotal method to a structured, systematic approach capable of generating theoretical contributions through replication logic and triangulation [28]. This evolution highlights the increasing recognition of case study research as a robust and credible method in business research.

While early criticisms of case study research centred on subjectivity, limited generalizability, and researcher bias [29], contemporary scholars have developed methodological refinements that strengthen its validity. Recent advances include AI-driven text analysis for qualitative research, the integration of big data in case studies, and the application of digital tools to enhance replicability [30]. Digital ethnography, computational text analysis and sentiment analysis have further expanded the analytical depth of case study research, enabling more rigourous triangulation with large-scale qualitative datasets [31]. In addition, cross-disciplinary applications have reinforced the credibility of case study research. Scholars in healthcare have combined qualitative case studies with machine learning models to analyse patient behaviours, while in strategic management, researchers have employed network analysis alongside case studies to map corporate decision-making processes [32]. These advancements demonstrate that case study research is not static but is continuously evolving to meet the demands of contemporary research challenges. The integration of AI-driven methods ensures that qualitative research remains adaptable to changing technological landscapes, further solidifying its relevance.

A critical limitation of early case study literature was its inconsistent methodological rigour. Yin [2] emphasized structured research designs with clear protocols, while [33] advocated for a more interpretive, flexible approach that prioritizes depth over standardization. Eisenhardt [34] introduced the concept of theory-building through multiple case studies, yet recent scholars argue that replication logic enhances case study validity even further [35]. Critics such as [36] have suggested that case studies suffer from selection bias and should be supplemented with comparative analysis across cases. More recently, scholars such as [37] and [38] have stressed the importance of mixed-method integration in case study research. They argue that supplementing qualitative findings with quantitative data such as through survey validation or econometric modelling an mitigate concerns regarding external validity. This integration of methods aligns with the broader movement toward methodological pluralism in business research. These developments indicate a shift towards more systematic and robust case study methodologies that ensure both depth and breadth in business research.

To enhance validity, contemporary case study researchers increasingly employ methodological triangulation, combining multiple data sources and research techniques [39]. Triangulation can take several forms, including data triangulation which involves comparing data from different sources such as interviews, archival documents and field observations to reduce bias. Methodological triangulation integrates case studies with complementary methods such as surveys, experimental research or quantitative content analysis. Additionally, investigator triangulation involves multiple researchers interpreting findings from different perspectives, enhancing the robustness of the analysis. Case study research has often been criticized for its limited generalizability, but scholars argue that while it may not provide statistical generalization, but it excels in analytical generalization [40]. That is, findings from case studies can contribute to broader theoretical constructs that apply across different settings. Longitudinal case studies and replication logic further address concerns about generalizability by testing findings across cases, enhancing reliability and robustness. A notable case is a study on corporate sustainability by [41], where semi-structured interviews were combined with financial performance data to validate the impact of sustainability initiatives on long-term business growth. This demonstrates how mixed-method triangulation can enhance both theoretical contributions and practical insights.

Additionally, abductive reasoning plays a crucial role in case study research by refining theories based on unexpected patterns [42]. Business research has leveraged case study insights to refine theories such as dynamic capabilities theory and institutional theory, demonstrating that case studies serve not just as exploratory tools but as mechanisms for theoretical advancement. The use of AI and big data analytics in qualitative research has revolutionized case study methodology. Recent studies have applied AI-driven sentiment analysis, topic modelling for interview transcripts and machine learning for pattern recognition [30,43]. These technologies enhance coding reliability, reduce researcher bias and allow for the systematic analysis of large datasets, making case study research more scalable and reproducible. AI-assisted qualitative data analysis software, such as NVivo and ATLAS.ti, further improves transparency and consistency in thematic coding. As a result, researchers can achieve greater methodological rigour while maintaining the depth and contextual richness that case studies provide.

Ethical concerns in case study research have evolved with the use of digital tools and AI. Challenges include maintaining confidentiality in AI-driven data processing, addressing potential bias in automated qualitative coding, and navigating power imbalances in corporate-sponsored case studies [44,45]. Scholars emphasize the importance of transparent data anonymization protocols and ethical oversight to ensure the integrity of digital case studies. Additionally, the shift towards open-access case study repositories raises concerns about participant consent and data security, requiring clear guidelines on responsible data sharing. The replication crisis in qualitative research has led to increased calls for transparency and rigour in case study methodology [46]. Recent recommendations include pre-registration of case study protocols to ensure methodological transparency, establishing case study repositories where researchers can compare findings across industries and disciplines and encouraging multi-case replication to validate theories across diverse business environments [35]. Additionally, businesses are increasingly applying replication logic internally to refine internal best practices. This approach mirrors the academic debate on ensuring replicability in case study research and demonstrates its applicability in real-world business settings.

A well-documented challenge in case study research is its transition from methodology to practical application [47,48]. While foundational works [2,49] focused on case study design, recent scholarship has shifted toward the pragmatic value of case studies in business strategy, innovation and policymaking [50,51]. To bridge this gap, contemporary scholars emphasize context-driven theory building, where case study insights inform business practice in an iterative process [43]. The rigourous application of triangulation and mixed methods ensures that case studies are not only analytically robust but also practically applicable in solving contemporary business challenges. This iterative approach allows case study research to contribute meaningfully to both theoretical frameworks and actionable business strategies.

The evolution of case study research has seen significant methodological advancements, including AI-driven qualitative analysis, digital tools for replication and methodological triangulation. While early scholars laid the groundwork for case study research, recent contributions emphasize the integration of mixed methods, cross-disciplinary applications, and digital innovations to enhance research validity. Addressing concerns regarding rigour, replication, and generalizability, contemporary case study research continues to evolve as a critical tool for both theoretical exploration and practical business application. As business landscapes become increasingly complex, case study research enhanced by digital tools and AI will remain indispensable for generating actionable insights and shaping future business strategies.

In this case study, three key components are highlighted as examples to demonstrate how case studies can be incorporated into various business challenges and transformations. These components which is digital transformation, corporate sustainability, and businesses navigating sustainability challenges alongside digital disruptions illustrate the versatility of case study research in analysing contemporary business issues.

Digital transformation has become a critical factor in business success, requiring organizations to integrate emerging technologies such as artificial intelligence (AI), big data analytics, and cloud computing into their operations. Case study research provides an in-depth understanding of how businesses navigate these transformations by examining real-world applications of digital tools in various industries. Through AI-driven text analysis, researchers can process large volumes of qualitative data, such as corporate reports, customer feedback, and strategic documents, to identify patterns in digital adoption. This method enables the systematic extraction of insights into how organizations deploy AI-powered automation, enhance customer experiences, and optimize operational efficiency. Additionally, big data integration in case studies allows researchers to merge structured and unstructured data sources, offering a more comprehensive view of digital transformation initiatives. By combining financial records, consumer behaviour analytics, and social media trends, case study research reveals how companies use data-driven decision-making to gain a competitive advantage. Another key methodological advancement is digital ethnography, which involves immersive online observations and interactions within digital ecosystems. This approach allows researchers to examine how businesses implement digital solutions in real time, capturing employee adaptation, organizational resistance, and customer engagement with new technologies. As companies shift toward hybrid work models and digital platforms, digital ethnography provides valuable insights into how organizational culture influences technological adoption and long-term success.

Corporate sustainability has become a strategic imperative as businesses face increasing regulatory pressures, consumer expectations, and environmental challenges. Case study research plays a crucial role in analysing how organizations integrate sustainability principles into their operations while maintaining profitability. Case studies provide detailed accounts of corporate sustainability initiatives, such as green supply chain management, carbon footprint reduction strategies, and circular economy practices. By examining how firms navigate these challenges, case studies help identify best practices and potential obstacles in sustainability implementation. Furthermore, AI-driven text analysis aids in evaluating sustainability reports, identifying key themes, and tracking corporate commitments over time. This method enhances transparency in sustainability research by systematically analysing publicly available disclosures and corporate sustainability indices. Big data analytics further strengthens sustainability-focused case study research by offering predictive insights into environmental and social performance. Companies leverage big data to monitor energy consumption, optimize resource allocation, and forecast the impact of climate-related policies. Through case studies, researchers can assess how businesses harness data-driven insights to align sustainability goals with financial performance. Additionally, digital ethnography provides a nuanced understanding of stakeholder engagement in corporate sustainability. By analysing online discussions, employee feedback platforms, and social media narratives, researchers can capture real-time responses to sustainability initiatives. This approach enables the identification of key factors that drive Corporate Social Responsibility (CSR) adoption and sustainability-oriented innovation.

Businesses today operate in an environment of rapid technological evolution and growing sustainability concerns. Case study research is instrumental in exploring how organizations navigate these dual challenges and develop adaptive strategies. A key finding in case study research is the integration of sustainability within digital transformation initiatives. Companies are increasingly leveraging AI and automation to enhance energy efficiency, reduce waste, and implement circular business models. In the case of digital twin technology, which is used to simulate real-world processes, it helps companies optimize supply chains while minimizing environmental impact. Case studies demonstrate how digital transformation and sustainability efforts are interconnected, showcasing industry leaders that successfully align profitability with environmental responsibility. Furthermore, organizations must overcome barriers to digital transformation and sustainability adoption. Case studies highlight common challenges such as organizational resistance, regulatory constraints, and technological limitations. Businesses that successfully navigate these disruptions often implement change management frameworks, invest in employee reskilling, and collaborate with external stakeholders. By documenting these strategies, case study research provides actionable insights for businesses seeking to balance innovation with sustainability goals. In conclusion, case study research offers a powerful methodological approach for understanding the complexities of digital transformation and corporate sustainability. Through AI-driven text analysis, big data integration, and digital ethnography, researchers can capture the evolving dynamics of business adaptation. As industries continue to face technological disruptions and sustainability pressures, case study research will remain essential for informing strategic decision-making and policy development.

Table 1 outlines the key features of case study research, which is a qualitative research method used to investigate complex phenomena within their real-life contexts. These features reinforce the methodological rigour of case study research, demonstrating its ability to integrate qualitative and quantitative methods while maintaining a holistic and contextual focus. The ability to combine multiple data sources, apply flexible research designs, and engage in longitudinal analysis highlights the adaptability and robustness of case study research.

TABLE 1

Table 1. Key features and Methodological Strengths of Case Study Research.

METHODOLOGY

The case study approach was selected because it allows for an in-depth exploration of business phenomena in real-world contexts, particularly when studying dynamic environments where quantitative models may fail to capture nuanced decision-making processes and contextual complexities [52]. Case study research is well-suited for investigating contemporary phenomena within their natural settings, especially when the boundaries between the phenomenon and context are not clearly defined [53]. While alternative qualitative methods, such as ethnography or grounded theory, could offer valuable insights, the case study design was chosen due to its ability to facilitate cross-case comparisons, improve analytical generalization, and enhance theoretical development. The iterative nature of case analysis allows for the identification of patterns across cases, increasing the robustness of findings [26]. However, case studies have potential limitations, such as their time-intensive nature and the possibility of subjectivity. These concerns need to be mitigated through methodological triangulation, structured data collection, and rigourous analytical techniques to ensure validity and reliability. Research that employs a case study design was chosen for its ability to enhance analytical generalization and theoretical development. The case study was designed to enhance the robustness, validity, and transferability of findings by employing a rigourous research framework [54]. By examining cases, the approach allows for pattern recognition, theoretical replication, and the validation of findings [55]. The rationale for the design is to provide a richer perspective on business phenomena and increase the external validity of the study’s conclusions. Furthermore, the case study design, which aligns with the abductive reasoning approach, aims to refine existing theories while also allowing new theoretical insights to emerge [56]. This iterative process ensures that theoretical frameworks are continuously refined as empirical data is analysed, enhancing the explanatory power of the study.

The selection of cases follows a theoretical sampling approach, which prioritizes relevance over representativeness [49,57]. Theoretical sampling ensures that selected cases illustrate key theoretical constructs and industry practices, enabling the study to contribute to both theory development and practical insights. To ensure methodological rigour, the study needs to establish a clear criterion for determining data saturation. Cases are selected based on several key factors, with relevance to the research objectives being the primary consideration. This approach ensures that the chosen cases provide meaningful insights into strategic decision-making and organizational behaviour in complex business environments. Industry applicability is also crucial, with organizations operating in dynamic business environments prioritized for examining strategy implementation, innovation, and adaptation to external changes [58]. To enhance case analysis, firms should be selected based on variations in size, sector, and market positioning, allowing for a broader examination of business strategies across different organizational contexts. Data availability is another critical criterion, with cases included only if rich primary and secondary data are accessible. Primary data sources include interviews, internal reports, and managerial insights, while secondary data consist of industry publications, regulatory filings, and publicly available reports. Each case should be assessed for its potential theoretical contribution, ensuring alignment with and refinement of existing literature on strategic management, innovation, and organizational adaptation.

The study that employs a multi-method approach needs to ensure a comprehensive and nuanced understanding of the research phenomenon. Data collected through document analysis serves a distinct purpose in triangulating findings and enhancing the study’s validity. Interviews should be conducted with key stakeholders, including business executives, managers, and industry experts, to gain insights into strategic decision-making processes, operational challenges, and industry trends. A purposive sampling strategy will be more suitable for case studies to ensure that participants have relevant expertise and experience. The semi-structured format allows for flexibility, enabling researchers to explore emergent themes while maintaining a structured line of inquiry. Interviews are audio-recorded, transcribed, and analysed using thematic coding techniques to identify recurring patterns and insights. To enhance reliability, member-checking should be conducted, allowing participants to verify the accuracy of their responses. Document analysis is used to validate and complement interview data, providing objective, contextual insights into corporate strategies and industry practices. Sources include internal corporate reports, industry white papers, regulatory filings, financial statements, and media publications. This method enables the identification of key trends, organizational policies, and external regulatory influences affecting business operations. Content analysis techniques are applied to systematically categorize and interpret the data, ensuring consistency and reducing potential biases. Observations are conducted through field visits and direct engagement with business processes in their natural settings. This method allows researchers to assess real-world operational workflows, managerial interactions, and workplace dynamics. Observations help verify claims made during interviews and document analysis, ensuring a more holistic understanding of business strategies and decision-making. To minimize observer bias, structured observation protocols should be followed, capturing detailed field notes and systematically coding observed behaviours and interactions. By integrating these multiple data sources, the case study will ensure methodological rigour and validity. The triangulation of interviews, documents, and observations helps reduce biases, cross-validate findings, and provide a richer, more reliable analysis of business practices in dynamic environments.

To ensure a comprehensive understanding of the case research subject, a multi-method approach can be employed for data collection. This approach enhances the validity and reliability of findings by integrating multiple sources of evidence as shown in Table 2.

TABLE 2

Table 2. Data collection process.

A study that integrates multiple data sources, including semi-structured interviews, document analysis, and observational data, ensuring triangulation of findings, enhances construct validity [39]. A triangulated approach improves the validity and reliability of findings. Data collection involving multiple sources of evidence, such as semi-structured interviews, direct observations, internal company reports, and archival documents, helps mitigate biases and enhances the credibility of the findings [2]. In addition to triangulation, inter-coder reliability measures can be applied, whereby multiple researchers independently code and analyse data to ensure consistency in interpretations. Any discrepancies in coding can be resolved through iterative discussions, strengthening the reliability of the findings. The data analysis process should follow a thematic coding framework, incorporating both deductive and inductive coding strategies. Deductive coding will be guided by existing theoretical frameworks, while inductive coding allows for the emergence of new themes from the data. To ensure analytical rigour, a constant comparison method should be employed, where patterns in one case can be systematically compared with those in other cases to establish cross-case consistency [59]. To facilitate cross-case analysis, established techniques such as pattern matching, explanation building, and logic models should be employed, enabling a systematic approach to drawing insights across different organizational contexts [7]. Investigator triangulation should also be applied, involving multiple researchers in the coding and interpretation process. This collaborative approach reduces individual bias and facilitates the identification of alternative explanations. Coding discrepancies can be resolved through iterative discussions, ensuring that the findings are robust and reflective of the data.

Interviews should be conducted with executives, managers, and industry experts to capture a diverse range of perspectives. Participants should be selected based on their expertise and decision-making roles within their organizations. Each interview should last between 45 to 60 minutes and should be recorded with the participants’ consent, then transcribed for analysis. To ensure consistency, a standardized interview guide should be developed, focusing on key themes such as strategic decision-making, market adaptation, and innovation practices. The inclusion of multiple perspectives enhances the reliability of the findings and mitigates potential biases.

Ethical approval should be obtained from the relevant institutional review board. Participants should be provided with informed consent, and all data should be anonymized to protect confidentiality. The study must adhere to the ethical guidelines set forth by the Declaration of Helsinki [60], ensuring the ethical integrity of the research process. Furthermore, to maintain transparency, member checking should be conducted, allowing participants to review and validate the findings to ensure accurate representation of their perspectives. This approach will further strengthen the credibility of the study and minimize potential misinterpretations.

Themes should be categorized into strategic adaptation, innovation drivers, and external market influences, providing a structured approach to understanding how businesses respond to competitive pressures, leverage technological advancements, and navigate external uncertainties. Thematic analysis was conducted using various software tools to systematically code and categorize data [61]. The coding process begins with initial coding, where recurring themes and key concepts are identified within the transcripts. Axial coding is then performed to establish relationships between different themes, facilitating the detection of underlying patterns. Finally, selective coding refines these themes to align with theoretical constructs and research objectives. The systematic coding process ensures that data analysis remains structured and methodologically sound, allowing for a robust interpretation of findings.

Table 3 provides a comprehensive overview of the strengths and challenges associated with case study research in business contexts, along with mitigation strategies designed to address the identified challenges. It serves as a guide for business researchers, offering practical solutions to enhance the rigour, relevance, and reliability of case study methods. By outlining how case study research can provide deep insights into complex business phenomena while acknowledging potential limitations, the table underscores how careful planning, and methodological rigour can maximize the value of case studies for both theoretical development and practical application in today’s dynamic business environment.

TABLE 3

Table 3. Strengths, challenges, and mitigation strategies of case study research.

ANALYSIS

One of the primary concerns in any research design is construct validity, which refers to the accuracy with which a study measures what it intends to. In the context of business research, construct validity is enhanced through multiple sources of evidence, such as financial reports, interviews with executives, customer feedback, market data and even digital artifacts like website analytics. Additionally, maintaining a chain of evidence and involving key informants in reviewing drafts of the case study report or utilizing member checking ensures that the findings are accurate and reflective of the actual business scenario. This is especially important in contemporary business contexts, where stakeholders have diverse perspectives. In the case of a multinational company’s strategy for entering new markets, key informants might include regional managers, financial analysts, and customers in the target region. By involving these informants in the review process, researchers can validate their interpretations and ensure that the study accurately captures the complexities of global expansion.

Table 4 provides an in-depth look at construct validity within business case studies. Construct validity refers to how accurately a measurement or test represents the concept it is intended to measure. In business case studies, it is essential to ensure that variables, measures, and conclusions align with the business theories or phenomena being studied. The table outlines several critical aspects of construct validity, such as conceptualization, operationalization, measurement validity, and others, each explained with examples, potential issues, and steps to improve the validity.

TABLE 4

Table 4. Construct validity in business case studies.

Internal validity in case study research is established through techniques such as pattern matching, explanation building, logic models and addressing rival explanations. In the business world, these strategies are essential for making sense of complex phenomena such as mergers and acquisitions, leadership changes, or shifts in corporate strategy. By developing a logic model that outlines key activities such as leadership integration, cultural alignment, technology consolidation, researchers can trace how these activities influence outcomes like employee retention, market share, and financial performance. Additionally, addressing rival explanations ensures that the research accounts for alternative causes of observed effects. In today’s dynamic business outcomes, where multiple external factors like regulatory changes or technological innovations may influence outcomes, this method is particularly valuable for ensuring the internal validity of the case study. External validity, or the generalizability of findings, is often questioned in case study research. However, [62] points out that external validity can be achieved by using theory in case studies or through replication logic in case studies. This is highly applicable in current business research, particularly when investigating emerging trends such as digital transformation or sustainability practices across industries.

Reliability is crucial for ensuring that research can be replicated with consistent results. In business case study research, reliability is maintained by developing a clear case study protocol and creating a detailed case study database. The protocol includes step-by-step guidelines for data collection and analysis, ensuring that future researchers can follow the same procedures and achieve similar outcomes. This is particularly important in business research, where organisations often operate in fast-moving environments with significant external pressures. By establishing a protocol for how these data sources are collected, analysed and triangulated, researchers can ensure that their findings are not the result of idiosyncratic interpretations but are based on systematic, repeatable processes. Reliability in business case studies refers to the consistency and stability of the measurements used in the research. To ensure reliability, researchers must first define what it means for their study, such as ensuring that the measurement tools produce consistent results over time and across different evaluators. They should then select well-established, reliable tools and conduct pilot testing to identify any potential issues before full-scale data collection. Training data collectors, applying consistent data collection methods and testing for internal consistency are key steps to avoid errors. Researchers should also assess test-retest reliability to ensure stability over time and inter-rater reliability to ensure consistency among different evaluators. Analysing data variability helps identify any inconsistencies, and refining data collection processes based on these findings improves reliability. Documenting all steps and procedures ensures transparency, allowing for replication and strengthening the reliability of the study’s results. Following these guidelines ensures that the business case study produces consistent, dependable, and replicable findings as shown in Table 5. Table 5 outlines the essential steps to ensure reliability in business case studies, focusing on maintaining consistency and accuracy in data collection.

TABLE 5

Table 5. Reliability in business case studies.

Once the data is collected in a case study, it is essential to analyse it systematically to derive meaningful insights. The data analysis process in case study research typically involves several stages, each building upon the previous one to help researchers make sense of the data. The first step in analysing case study data is thematic coding, where the researcher identifies recurring themes, patterns, or categories within the data. This process involves reviewing the collected data such as interview transcripts, documents, and field notes and identifying repeated ideas or topics. The data should be grouped into themes, which represent significant aspects of the case. Software tools like NVivo or ATLAS.ti can assist in this process, helping to automate the identification and organization of themes and subthemes. The goal is to reduce large amounts of raw data into manageable units that can be analysed further. Once key themes are identified, the researcher proceeds to axial coding, which involves examining the relationships between these themes. Axial coding is focused on understanding how different themes, concepts, or variables interact with one another and influence each other. This helps the researcher explore the deeper connections within the data, revealing how certain themes overlap or shape one another. If strategic decision-making and market adaptation are key themes, then axial coding explores how these two themes are connected and how they jointly affect business outcomes.

After axial coding, selective coding takes place. This stage refines the identified themes and aligns them with the theoretical constructs of the study. During selective coding, researchers focus on the most important themes that are directly relevant to the research objectives. This stage ensures that the analysis remains closely tied to the research’s goals and allows for the identification of the most critical insights. It is at this stage that researchers filter out any themes that are less relevant or do not contribute meaningfully to answering the research questions or advancing theoretical understanding. This process allows the researcher to focus on the core findings that will contribute to both theory and practice. To ensure the rigour and validity of the findings, several strategies should be incorporated throughout the analysis process. One key method is triangulation, which involves using multiple data sources to confirm the results. Triangulation helps ensure that the findings are not limited by biases inherent in a single data source. Using interviews, documents, and observations together allows researchers to cross-check and confirm key findings, thereby enhancing the study’s validity. Another important strategy is member checking, where participants review and validate the findings to ensure their perspectives are accurately represented. Member checking helps ensure that the researcher’s interpretations are faithful to the data and the participants’ experiences. In addition, if multiple researchers are involved in coding the data, inter-coder reliability checks are necessary to ensure consistency across coding decisions. These checks involve comparing the coding decisions made by different researchers to identify any discrepancies, which can then be resolved through discussion.

In case study research, when analysing cases, the focus is on thoroughly examining the data within that specific context to draw meaningful insights. The process begins with identifying patterns, relationships, and differences within the case to address the research questions effectively. Techniques like pattern matching can be useful, where researchers compare observed outcomes with theoretical expectations. If specific patterns consistently emerge from the data, this strengthens the findings and provides additional support for the conclusions drawn. Another valuable technique in single-case analysis is explanation building, where researchers synthesize the findings to develop a coherent explanation or theory that fits the particular case. This approach helps in understanding the underlying dynamics of the case and contributes to refining existing theories or developing new ones. Additionally, logic models can be employed to visualize the relationships between key variables and outcomes within the case, providing a clearer understanding of how different factors are interconnected and contributing to the overall findings.

After completing the data analysis, researchers should draw both theoretical and practical insights from the findings. Theoretical contribution refers to how the case study supports or challenges existing theories. Researchers should examine whether their findings confirm or contradict current theoretical frameworks and identify any new insights that can advance the understanding of the research topic. The practical implications of the study are equally important, as they offer actionable recommendations for practitioners, managers, and decision-makers in the relevant field. These recommendations are grounded in the findings of the case study and can help organizations or individuals apply the insights to real-world challenges, improving their strategies or operations. The final step in case study research is the reporting and writing of the findings. A well-structured case study report should begin with an introduction that outlines the research questions, the rationale for selecting the case(s), and the data collection methods. The case context section should follow, providing a detailed description of the case, including background information, key variables, and factors influencing the case. This section helps readers understand the context in which the research took place. The analysis section should present the results of the coding and thematic analysis, discussing how the findings align with the research questions and theoretical constructs. The report should also conclude with a discussion of the theoretical contributions and practical implications of the study, as well as any recommendations for future research. This structure ensures that the case study is methodologically sound, informative, and valuable both to the academic community and to practitioners in the field. By following these stages systematically, researchers can ensure that their case study analysis is rigourous, credible, and insightful. The process of thematic coding, axial coding, and selective coding, combined with methods such as triangulation, member checking, and inter-coder reliability, ensures the validity of the findings. Case analysis techniques further enhance the robustness of the study by allowing researchers to draw broader conclusions. Ultimately, a well-conducted case study contributes valuable theoretical insights and practical recommendations that can be used to inform both academic research and real-world business practices.

Case study research has provided valuable insights into contemporary business challenges, particularly those resulting from digital transformation, globalization, and shifting consumer behaviours. The case studies analysed reveal how organizations have navigated these disruptions, offering practical strategies and lessons that can inform both theory and practice. A significant finding from the analysis is how organizations leverage big data to enhance decision-making and secure a strategic advantage. The case studies demonstrate that businesses are increasingly relying on data analytics to drive their strategies. The use of big data has enabled companies to make more informed decisions, optimize their operations, and create more personalized customer experiences. This research aligns with existing theories on the strategic role of big data in business, while also offering new perspectives on how organizations implement data-driven practices in various industries [63]. Another critical theme that emerged from the case analysis is the role of corporate sustainability initiatives. The case studies reveal how businesses are integrating sustainability into their operations and the challenges they face in doing so. These findings suggest that sustainability is not just a corporate responsibility but also a strategic advantage that influences long-term performance. The analysis of these cases confirms the growing importance of sustainability practices in contemporary business and adds nuance to existing theoretical frameworks on corporate social responsibility [64].

The impact of global crises, particularly the COVID-19 pandemic, was another key area explored in this research. The case studies of businesses that responded to the pandemic highlight the effectiveness of adaptive leadership and flexible organizational structures. The findings underscore the importance of resilience strategies, particularly in the face of sudden disruptions. Businesses that embraced remote work models and innovative communication strategies were better able to maintain employee engagement and productivity during the crisis. These insights contribute to ongoing discussions about crisis management and organizational flexibility in turbulent times [65,66]. Therefore, the case study analysis provides significant contributions to both theory and practice, offering actionable insights into how organizations are addressing contemporary business challenges. These findings emphasize the need for flexibility, data-driven decision-making, and sustainability in navigating the complexities of today’s business environment. The practical implications of these findings can guide businesses as they adapt to changing market conditions, while the theoretical contributions further develop our understanding of strategic management in the modern business landscape.

DISCUSSION

Case studies excel in exploring intricate and multifaceted issues that are difficult to understand using purely quantitative methods as they provide in-depth insights into the dynamics and interactions within a specific context [7]. This depth allows for a detailed understanding of complex organizational behaviours. However, conducting such studies can be time-intensive and resource-demanding due to the level of detail required. One of the key strengths of case studies is their ability to examine phenomena within their natural settings. This makes them especially valuable for analysing real-world implications, such as how specific policies impact industries or geographic regions. By grounding findings in reality, case studies ensure their relevance and applicability. However, this context-specific focus also limits the generalizability of findings to other settings. Case studies are instrumental in developing and refining theoretical frameworks. By analysing empirical observations, researchers can generate new theories or improve existing ones. This is particularly useful in fields like social sciences or business innovation, where understanding new phenomena often requires fresh theoretical perspectives. Although case studies are excellent for generating innovative ideas, the conclusions drawn may be tentative and require further research for validation. Case studies often serve as illustrative tools to simplify and explain abstract concepts through detailed, concrete examples. This makes them ideal for demonstrating how a theoretical model works in practical settings. Case studies are well-suited for identifying actionable solutions to real-world challenges and by examining specific scenarios, they can offer strategic recommendations or propose innovative approaches [67]. However, while these solutions are often directly implementable, they may not address long-term implications or systemic challenges. When comparing cases, researchers can identify patterns and trends across contexts. This approach is particularly effective for understanding phenomena that span different industries, regions, or demographics.

A key advantage of case studies is their ability to capture the perspectives of diverse stakeholders, such as employees, customers, or policymakers. This multi-faceted approach provides a richer understanding of complex issues. One of the most notable strengths of case studies is their adaptability to different research contexts, scales and disciplines. This flexibility makes them ideal for interdisciplinary research or studying emergent phenomena. However, this flexibility also poses the risk of losing focus if clear boundaries and objectives are not established. In educational and professional training settings, case studies serve as powerful tools to foster active learning and critical thinking. They provide relatable, real-world examples that enhance the understanding and application of theoretical concepts. However, case studies used for educational purposes must be regularly updated to ensure their relevance and applicability to current challenges. Case studies are a versatile and powerful research method, offering detailed insights into real-world phenomena, facilitating theory development, and addressing practical challenges. However, they also face limitations, such as issues of generalizability, resource demands, and complexity in data management. By addressing these limitations through clear research protocols, diverse case selection and the use of advanced tools, researchers can harness the full potential of case study research while ensuring rigour and relevance.

Integrating case study research into business education is essential for developing future leaders who can navigate complex business environments. By familiarizing students with case study methods, educators can enhance critical thinking and problem-solving skills, allowing them to apply theoretical concepts to real-world situations [68]. The use of case studies in the classroom encourages active learning and fosters an appreciation for the complexities of business challenges, preparing students for leadership roles in their respective fields [69]. Furthermore, exposure to case study research helps students develop a deep understanding of how theoretical frameworks can be applied in practice. As they analyse real business scenarios, students can learn to identify key issues and assess the implications of various strategies. This experiential learning approach not only enriches their academic experience but also equips them with the skills necessary for success in a rapidly evolving job market. Incorporating case studies into business curricula promotes interdisciplinary learning as students can benefit from insights drawn from fields such as sociology, psychology and economics that enhances their ability to analyse business challenges from multiple perspectives [70]. This interdisciplinary approach aligns with the growing demand for holistic thinkers in today’s complex business landscape. The case study research method is a robust and valuable approach in business research, offering deep insights into complex phenomena. While it has historically faced scepticism, rigourous methodological practices can ensure its validity and reliability. As businesses confront contemporary challenges, case studies provide essential knowledge that can inform strategic decision-making and enhance organizational performance [71]. Integrating case studies into business education will equip future leaders with the skills needed to tackle the multifaceted issues they will encounter in their careers.

Traditionally, business professionals have consistently demonstrated a willingness to push the boundaries of conventional thinking in their pursuit of innovation, improved processes and enhanced value creation for both organizations and customers [72]. The same openness to new ideas is essential for business researchers, who must adopt a forward-thinking mindset to investigate complex business problems and explore alternative methods for generating valuable insights [73]. In a rapidly evolving global marketplace, traditional research methods may not always provide the depth of understanding needed to address emerging challenges. This has led to a growing need for business researchers to explore unconventional approaches that capture the complexity of modern business environments. Although qualitative research methods such as phenomenology, ethnography and grounded theory have gained acceptance in the field of business, the case study method is still often viewed with scepticism. Some researchers consider it to be a less rigourous approach compared to more established methodologies like surveys or controlled experiments [74]. This misconception arises from the belief that case studies lack generalizability and fail to provide the robust, quantifiable data often sought by business researchers. However, this view overlooks the strengths of case studies, which offer rich, detailed insights into specific business practices, organizational dynamics and real-world phenomena. Case studies are widely used in various social science disciplines, such as psychology, sociology, anthropology and education, where they are valued for their ability to generate a deep understanding of complex issues [75]. In business research, the case study method can serve as an invaluable tool, particularly when researchers aim to answer how and why questions that are critical to understanding the mechanisms behind organizational behaviour, decision-making processes, or market trends. Case studies are especially useful in situations where the researcher has minimal control over events but seeks to examine phenomena within their real-life context [2,76]. This focus on real-world conditions makes the case study method especially suitable for exploring contemporary business issues, such as strategic management, innovation, corporate governance and digital transformation, were complex interdependencies and external influences shape outcomes. By embracing case studies, business researchers can bridge the gap between theory and practice, producing findings that are both theoretically sound and directly applicable to business settings. This methodology enables researchers to examine real-life cases in depth, capturing the nuances of organizational behaviour, market dynamics, and stakeholder interactions. It also facilitates a holistic exploration of business challenges, allowing researchers to identify patterns and generate new theories that can inform both academic research and business practice [77,78]. The misconception that case studies lack rigour is unfounded, particularly when they are conducted using systematic procedures and robust analytical frameworks. When properly designed, case studies provide rigourous, context-rich insights that can contribute to the development of new business theories and the refinement of existing ones. They offer a unique way to explore the multifaceted and dynamic nature of businesses in their operational environments, making them an indispensable tool in the business researcher’s toolkit. As business research continues to evolve in response to global challenges, the case study method remains a powerful strategy for generating actionable insights and fostering innovation [43].

In today’s research landscape, the case study method is gaining prominence as business and social challenges become increasingly complex. Issues such as globalization, digital transformation, environmental sustainability and social equity require nuanced analysis that often extends beyond the capabilities of quantitative surveys or experiments [56]. As a qualitative approach, the case study method allows for a deeper understanding of these multifaceted topics, offering context-rich insights that are essential for tackling modern-day complexities in both business and society. Case studies offer an opportunity to investigate complex issues within their specific contexts, enabling the generation of actionable insights grounded in the realities of modern organizations and communities. They have proven invaluable for understanding how businesses, industries and governments responded to unprecedented disruptions such as those seen during the COVID-19 pandemic [79]. Traditional research methods might have struggled to capture the dynamic and rapidly changing conditions that characterized the early months of the pandemic. However, case studies proved invaluable, allowing researchers to document and analyse how organizations adapted their strategies in real-time. These studies offered insights into leadership during crises, highlighted vulnerabilities in supply chains, and examined the acceleration of digital transformation. As a result, they contributed both to academic literature and to practical guidance for business leaders navigating similar crises [80]. An exemplary case study should rely on multiple sources of evidence to ensure rigour and depth in the analysis and by using six key sources of evidence such as researcher documentation, archival records, interviews, direct observations, participant observation and physical artifacts researchers can triangulate their findings, which strengthens the validity of the case study. These diverse sources allow for a more holistic understanding of the case, capturing different perspectives and dimensions that might otherwise be overlooked [81,82]. Case study examining how a company navigated digital transformation during the pandemic, documentation might include internal reports, strategy documents, and communications that detail the company’s decision-making processes. Archival records could provide data on the company’s financial performance and market position before and after key transformation initiatives. Interviews with employees, managers, and stakeholders could reveal the human aspect of the transformation how individuals experienced and adapted to the changes. Direct observations of organizational practices and participant observations of meetings or decision-making processes could shed light on the day-to-day realities of implementing digital strategies. Physical artifacts, such as the technology itself or new workspace designs, could provide tangible evidence of the transformation process [83].

Photographs and videos are increasingly recognized as valuable sources of evidence, particularly in today’s visually driven digital age. With the rise of virtual communication and the widespread use of technology, researchers now have greater access to visual documentation that can enrich case studies. Video recordings of virtual meetings, webinars, or online events can offer valuable insights into how organizations-maintained communication and collaboration during disruptions such as the COVID-19 pandemic [84]. These visual sources complement more traditional forms of evidence, providing a more immersive and nuanced understanding of the case being studied [85]. The case study method allows researchers to explore specific instances where complex, evolving issues such as climate change, social inequality, and technological disruption are at play. By offering detailed, context-sensitive analysis, case studies generate insights that inform both theory development and practical solutions. As the need for research that is both rigourous and relevant to real-world challenges grows, the case study method has never been more essential. It allows researchers to move beyond the confines of experimental design and quantitative analysis, offering a flexible, adaptable approach to understanding the complexities of modern business and society [2]. A common misconception in case study research arises from the incorrect application of sampling logic, where researchers may assume that selecting cases is akin to choosing a sample from a larger population, as is typical in quantitative studies [35]. In reality, case study research follows a different conceptual framework known as replication logic, which enhances robustness by treating each case study as a standalone experiment rather than a random sample [46]. This approach is especially pertinent in contemporary research, where the complexity and variability of modern environments demand more nuanced, contextually grounded methodologies [86]. In replication logic, each case study serves as a single experiment. The aim is not to generalize findings from one case to a larger population but to replicate the study across cases to establish stronger evidence for the proposed theory. When a researcher uncovers a significant finding in one case, the next step is to replicate the study using additional cases, each designed to either produce comparable results or yield different outcomes for well-understood reasons [87]. This process mirrors experimental replication in the natural sciences, where each experiment builds on previous findings to confirm or refine theoretical understanding.

According to [54], each new case study added to a case study design enhances the certainty and reliability of the results. As each replicated study either confirms or expands on the initial findings, the researcher’s confidence in the theoretical framework grows, leading to the development or extension of theories. This replication logic is particularly significant in addressing complex, real-world issues where traditional research methods may fall short. Each subsequent case study either reinforces the original insights by showing similar adaptations or introduces new variables that explain different outcomes, such as varying levels of digital preparedness or differences in industry regulation [88]. Replication across multiple case studies allows researchers to build a more comprehensive and generalizable understanding of how businesses navigate challenges under extreme conditions. This approach has become increasingly relevant in fields like business, education, and healthcare, where the sheer complexity of issues such as digital transformation, sustainability, and inequality demands a multi-faceted, deeply contextualized understanding [15]. Each replication strengthens the overarching theory about how digital transformation unfolds in different environments, refining our understanding of the variables that affect success.

Table 6 analyses how case study replication contributes to the development and refinement of theories in various fields of research. By replicating established case studies in different contexts such as industries, regions, or organizations, researchers can test the robustness and universality of existing theories. The table showcases key findings from these replications, demonstrating how theories are validated, refined, or expanded based on new evidence. It provides insights into the process of theory building, offering both theoretical advancements and practical lessons that can inform future research and application in dynamic business environments.

TABLE 6

Table 6. Building theory through case study replication.

Another pressing contemporary issue where replication logic in case study research proves crucial is in addressing environmental sustainability within businesses [89]. As organisations across industries adopt sustainability practices, conducting a case study on how a manufacturing firm transitions to green production methods might reveal important insights about the challenges and benefits of sustainable practices. Replicating that case study in a different sector, such as the service industry or the tech sector, could provide additional evidence about how sustainability initiatives can be adapted to various business models and operational structures. The replication of case studies across different contexts would enhance the robustness of the findings and contribute to theory development around sustainability practices, helping businesses understand what works, what does not and why [90].

In business studies, case studies have traditionally played a significant role in understanding business practices, with replication logic becoming increasingly important, especially in the implementation of innovative business services. One case study may show that innovation adoption improves business outcomes in a particular organization but replicating that study in international business settings could reveal important variations in access to technology, regulatory challenges, or market dynamics [91]. The replication process allows researchers to determine whether innovation in business benefits is consistent across different populations or whether context-specific factors must be considered when implementing such technologies [92]. Recent studies have demonstrated the importance of replication logic through specific case analyses. A study by [93] on digital transformation in Chinese manufacturing firms highlighted the significant role of government incentives in driving technological adoption. However, a replicated study in Latin American SMEs by [94] found that limited access to financing and lack of regulatory support created substantial barriers, leading to lower adoption rates. These differences underscore how contextual factors shape business innovation outcomes, emphasizing the necessity of multiple case studies rather than relying on a singular, generalized perspective.

Additionally, replication logic is critical in evaluating the scalability of business models. In the case of platform-based businesses, research found that digital platforms in the U.S. benefited from network effects and robust intellectual property protections, fostering rapid scaling. In contrast, a replication study in Southeast Asia revealed that fragmented digital infrastructure and regulatory inconsistencies hindered similar success. Such findings demonstrate that while theoretical models may propose a universally applicable business strategy, case-based replication highlights practical constraints that must be addressed for successful implementation. A major critique of single-case studies is their tendency to focus on positive findings while neglecting contrary evidence. Replicated studies, however, reveal inconsistencies that refine theoretical insights. The adoption of blockchain technology in supply chains was found to enhance transparency and efficiency in European firms. However, a study on Indian supply chains reported that high implementation costs and resistance from traditional stakeholders significantly delayed adoption. These contrasting results emphasize the necessity of considering counterexamples to avoid an overly optimistic or contextually narrow interpretation of business innovations.

The critical value of replication logic is that it provides a structured yet flexible approach to theory building. Instead of seeking immediate generalization from one case to a broader population, researchers use multiple case studies to test and refine theories incrementally, making the findings more reliable and applicable to real-world situations [12]. This approach becomes even more relevant in today’s world, where research often grapples with fast-changing, interconnected issues such as the global climate crisis, shifting political dynamics, and technological innovation [95]. Recent studies on sustainability-driven business models found that while European firms successfully integrated circular economy principles into their operations [41], companies in emerging markets faced logistical and consumer acceptance challenges. Such variations necessitate a deeper exploration of local adaptations, reinforcing the importance of replication logic in generating robust business theories. Emerging technologies such as artificial intelligence (AI) are also playing an increasingly significant role in business case study replication. AI-driven analytics allow researchers to simulate business scenarios and validate findings across multiple datasets, improving predictive accuracy in decision-making. This approach has been particularly useful in financial technology (fintech), where AI-enhanced case replication has helped uncover hidden biases in digital lending algorithms and payment systems [96]. The ability to test business theories through AI-based modelling further strengthens the case for replication logic, ensuring that findings are not only empirically valid but also practically applicable.

Longitudinal case studies also add to the robustness of replication logic. Studies tracking digital business transformations over extended periods have revealed that initial successes may not always be sustained due to evolving consumer behaviours and regulatory changes. A decade-long analysis of e-commerce expansion in North America found that while early adopters gained significant market share, late adopters struggled to replicate the same success due to increasing competition and market saturation. These findings underscore the necessity of ongoing case replications to capture the dynamic nature of business environments. Moreover, cross-sectoral replication has provided further insights into business adaptation strategies. The sharing economy model, which initially thrived in hospitality and transportation sectors, has faced challenges in areas such as healthcare and education, where regulatory concerns and ethical considerations pose significant barriers to implementation. These sectoral differences highlight the importance of tailoring business strategies to industry-specific conditions rather than assuming universal applicability. Additionally, the role of policy and institutional frameworks in replication logic cannot be overlooked. Different legal systems, regulatory environments, and financial incentives shape how business models perform across regions. Studies on green energy adoption such as EU policies that strongly support renewable energy investment, developing economies often struggle with inconsistent regulations and subsidy constraints. These variations suggest that replication logic must incorporate institutional factors to provide a more comprehensive analysis.

Ethical and sustainability considerations further complicate replication studies. Responsible business practices, including fair labour policies and environmental impact assessments, may affect innovation adoption differently across sectors and regions. While AI-driven hiring systems have improved efficiency in Western corporations, their replication in developing markets has raised concerns about algorithmic bias and employment discrimination. Such issues highlight the need for ethical scrutiny when replicating business innovations in diverse contexts. The replication of case studies across different geographies, industries, and cultural contexts allows for a more nuanced and adaptable understanding of these challenges, helping to shape effective, theory-driven responses. The replication logic central to case study designs provides a rigourous framework for addressing the complexity and variability of contemporary research topics. By replicating findings across different contexts and cases, researchers can increase the certainty of their results and contribute to the development of robust, well-supported theories that are capable of explaining not only what happens in one case but why it happens across various cases. Thus, replication logic not only validates initial findings but also uncovers the contingencies that determine business success or failure in diverse contexts, ultimately leading to more actionable and insightful business research.

The case study of Company X demonstrates the impact of digital transformation on operational efficiency. While automation was expected to streamline processes, resistance from employees slowed implementation. An internal email from the management team noted that despite training sessions, employees remained hesitant due to fears of redundancy. Additionally, an operations manager stated that the biggest challenge was convincing employees that digital adoption would enhance rather than replace their roles. In contrast, Company Y successfully navigated digital transformation due to strong leadership involvement. A company report highlighted that frequent town halls and transparent communication helped ease employees into the new workflow. Despite Company Y’s success, some employees still struggled with the transition. A survey revealed that while leadership was supportive, the learning curve for new technology remained steep for senior employees, causing initial productivity dips. This highlights that even with strong leadership, digital transformation can create short-term disruptions before benefits materialize. These findings align with change management theories, particularly Kotter’s Change Model, which emphasizes the need for leadership buy-in and structured change processes. However, they also suggest that even with strong leadership, psychological resistance and skill gaps remain critical challenges. The key takeaway from this case is that companies must implement phased digital adoption with continuous training to manage employee concerns effectively. Using internal champions to bridge gaps between leadership and employees and developing reskilling programs can ensure workforce adaptation to technological shifts.

Corporate sustainability efforts vary significantly between companies. Company A successfully integrated green technologies, which improved investor confidence. A sustainability report from the company stated that the shift to renewable energy sources had positioned it as a leader in sustainable business practices. However, Company B faced challenges despite similar efforts. Consumer scepticism limited adoption, as reflected in a market analysis, which noted that customers questioned whether the sustainable products offered real long-term value. A senior marketing executive further explained that the perception of greenwashing remained a hurdle for sustainability campaigns. Interestingly, despite consumer scepticism at Company B, internal stakeholders viewed the sustainability efforts positively. A board member noted that the market response had been slower than expected, but there was confidence that long-term positioning would yield benefits. This suggests that sustainability initiatives may take time to gain traction despite initial hurdles. These cases illustrate the complexity of institutional theory in sustainability, where external pressures such as consumers and investors interact with internal strategies. While stakeholder theory suggests alignment with external expectations, Company B’s struggles highlight that consumer trust is not immediate. The key takeaway from this case is that strengthening transparency through third-party sustainability certifications, conducting consumer awareness campaigns to educate on long-term sustainability benefits, and aligning marketing strategies with authentic sustainability messaging can help mitigate scepticism and foster greater acceptance of sustainability efforts.

ESG compliance efforts vary depending on external and internal factors. A multinational corporation successfully implemented ESG policies, receiving positive investor feedback. A financial analyst reported that the company’s commitment to ESG had led to increased stockholder confidence and favourable media coverage. Conversely, a similar initiative in a developing market failed due to regulatory gaps. A compliance officer remarked that without strict enforcement mechanisms, companies had little incentive to adhere to ESG guidelines beyond surface-level commitments. Despite the multinational corporation’s success, internal challenges emerged. An employee survey revealed that while the company publicly embraced ESG, internal practices such as employee treatment and resource allocation did not always align with sustainability goals. This discrepancy indicates that external ESG success does not always translate into fully integrated corporate culture. This case highlights the gap between signalling theory and institutional compliance. While companies may signal strong ESG commitments to investors and regulators, internal misalignment may persist. The key takeaway from this case is that regulatory enforcement appears to be a crucial determinant in ESG success. To ensure a more effective ESG integration, companies should establish internal ESG audits to maintain alignment between public commitments and actual practices. Strengthening corporate governance to integrate ESG beyond external compliance and advocating for stronger regulatory enforcement in developing markets can create a more uniform standard for ESG adherence.

In today’s dynamic business environment, organizations are constantly faced with multifaceted challenges. From environmental pressures to technological disruptions, businesses must develop strategies to navigate these complexities. Case study research is an effective tool for understanding how companies adapt to these challenges, offering valuable insights into practical solutions. This essay explores several key challenges faced by organizations, the strategic responses they implement, and the outcomes that result, with a particular focus on issues such as climate change, social inequality, technological disruption, and more. The increasing frequency and intensity of climate-related disruptions, such as natural disasters and extreme weather events, have had profound impacts on global supply chains. As businesses face rising operational costs and regulatory pressures to adopt sustainable practices, the need to address climate risks has become crucial. Many companies have responded by diversifying their suppliers across different geographic regions to mitigate risks associated with climate change. In the case of firms using technology to predict and manage climate-related risks, they can make more informed decisions in the face of environmental uncertainty. These strategies, while enhancing resilience, have also led to higher costs, particularly due to investments in sustainability initiatives. However, such measures have improved public perception and helped businesses comply with increasingly stringent regulations [43]. Companies have learned that integrating long-term environmental risk assessments into supply chain strategies is vital for securing a sustainable future. In the era of heightened social awareness and activism, organizations are under increasing pressure to address systemic inequality within the workforce. Legal and regulatory shifts toward greater inclusion and diversity have prompted many companies to adopt diversity, equity, and inclusion (DEI) programs. These initiatives often include unconscious bias training, revisions to recruitment policies, and partnerships with advocacy groups. While such programs have led to gradual improvements in workplace diversity, resistance to deep cultural shifts within organizations can pose challenges. Moreover, the successful implementation of DEI policies often varies depending on the organization’s commitment to change and leadership styles. Companies that have fully embraced these initiatives have seen enhanced employee morale and an improved reputation as inclusive employers. However, achieving systemic change requires a continued commitment from both leadership and employees [64].

The retail sector has been significantly impacted by the rise of e-commerce and digital transformation. As consumer behaviours shift toward online shopping, traditional brick-and-mortar stores are struggling to maintain foot traffic. Retailers have responded by adopting omnichannel strategies that combine physical and digital sales channels, utilizing artificial intelligence (AI) and data analytics to personalize customer experiences and predict demand more accurately. These strategies have resulted in substantial growth in online sales, but they have also increased operational costs due to the need for technological investments. Maintaining a balance between online and offline presence while integrating new technologies with traditional operations remains a key challenge for retailers. The lessons learned here emphasize the importance of agility and flexibility in adapting to technological advancements while preserving core business values.

With the increasing volume of data being generated and utilized by businesses, the issue of data privacy has become one of paramount concern. Stringent global data protection regulations, such as the General Data Protection Regulation (GDPR), have forced companies to adopt stronger cybersecurity measures. To maintain customer trust and ensure compliance, organizations have enhanced their data security protocols, including the use of encryption, multi-factor authentication, and regular compliance checks. While these measures have contributed to improved customer trust, they have also increased the cost of doing business due to the need for continual investment in cybersecurity infrastructure. The key lesson here is that transparency and robust data protection practices are essential for maintaining long-term customer loyalty [65]. Start-ups often operate in fast-paced markets where innovation and the ability to scale quickly are critical to success. However, the pressure to grow rapidly and compete with disruptive competitors can pose significant challenges. Many start-ups focus on lean, agile practices, strategic partnerships, and cultivating a strong company culture to attract and retain talent. Despite these efforts, the challenges of managing growth without compromising on quality or innovation are pervasive. Securing funding, managing cash flow, and scaling operations while maintaining the original value proposition remain critical hurdles. The lessons drawn from start-up case studies emphasize the importance of flexibility, innovation, and careful resource management to successfully navigate the complexities of scaling a business [97]. The COVID-19 pandemic has reshaped the way businesses approach work, with a significant shift towards remote and hybrid work models. Organizations have faced challenges in maintaining productivity, ensuring effective communication, and adapting their company culture to a virtual environment. Many have implemented digital collaboration tools and revised performance management systems to support remote work. While these strategies have improved employee satisfaction and work-life balance, challenges such as maintaining team cohesion and preventing communication barriers persist. Businesses have learned that clear communication, the right tools, and intentional strategies are essential for the success of remote work models [98]. Case study research provides valuable insights into the strategic responses’ businesses adopt to navigate complex challenges. From addressing climate change risks to responding to technological disruptions, organizations must continually adapt to external pressures and changing market dynamics. The lessons learned from these case studies highlight the importance of strategic flexibility, sustainability, innovation, and leadership in driving long-term success. By exploring these real-world scenarios, businesses can gain practical insights that inform both theory and practice, offering valuable guidance for practitioners navigating the evolving global business landscape as shown in Table 7.

TABLE 7

Table 7. Case study analysis of business complexity and strategic responses.

In the business world, the complexity of real-life phenomena such as digital transformation, corporate sustainability and international expansion often requires in-depth, context-rich research methods [99]. The case study method is uniquely positioned to address these complexities, offering detailed explorations of how businesses operate within dynamic environments. The rapid evolution of digital platforms and the growing importance of AI in industries such as retail and finance cannot be fully captured through quantitative surveys or experimental research alone. These developments demand a research method that allows for in-depth, contextual analysis of organizational strategies, technological integration, and consumer behaviour in real-time. Case study research can support both theory building and theory testing, making it a flexible tool in both exploratory and explanatory business research. With the growing emphasis on agile management practices, innovation ecosystems and sustainability in business, the case study method has never been more relevant. By diving deep into real-world scenarios, case studies help uncover not only what works in business contexts but also why certain strategies succeed or fail, providing a richer understanding of cause-and-effect relationships. Academicians should be encouraged to view the case study method not just as a teaching tool for simulating decision-making, but as a rigourous and formal research method that fosters a deeper understanding of real-world business dynamics. Integrating case studies into business education helps future researchers develop critical thinking skills, analyse complex problems from multiple perspectives, and make informed decisions based on both quantitative and qualitative data. By incorporating case study methodologies, business programs can equip students and researchers with the tools needed to tackle contemporary challenges, such as globalization, the digital economy, and the transition to sustainable business models. Real-life case studies provide invaluable insights that cannot be fully captured by traditional research methods focused solely on quantitative data. Case studies offer rich, contextualized examples of how organizations respond to crises, navigate disruptive change, and implement successful strategies. Incorporating case study research into the curriculum also enables students to explore not only the successes but also the setbacks and failures that organizations experience. These lessons learned are critical for building resilience and adaptability in business practices, equipping future leaders with the knowledge needed to address future disruptions. Additionally, case studies foster a deeper understanding of the complexities involved in organizational decision-making, making them an indispensable tool for both research and education. Ultimately, by embracing the case study method, academic institutions can bridge the gap between theory and practice, offering students and researchers a comprehensive approach to understanding and solving business challenges. As such, case studies not only contribute to the development of more adaptive business strategies but also help cultivate future business leaders who can effectively navigate an increasingly complex and volatile global marketplace.

Table 8 highlights the key implications of case studies for both business education and research. In education, case studies develop critical skills like collaboration, leadership, and strategic thinking, helping students navigate uncertainty and adapt to changing environments. They also enhance cultural competency, policy awareness, and sustainability understanding. In research, case studies offer insights into leadership, crisis management, and stakeholder perspectives, providing empirical evidence across diverse organizational settings. Both fields benefit from case studies’ focus on emotional intelligence, historical context, and practical application, bridging theory and practice. Additionally, case studies promote interdisciplinary learning and entrepreneurship development, encouraging consideration of diverse factors in decision-making and innovation.

TABLE 8

Table 8. Implications of case studies for business education and research.

The global business landscape has become increasingly volatile and interconnected, making the need for context-rich, qualitative research more crucial than ever. The case study method enables business researchers to explore the intricacies of decision-making processes in real-world settings, shedding light on how organizations respond to challenges such as digital disruption, geopolitical instability and shifting consumer expectations. Case studies exploring digital platforms and big data are revolutionizing research by providing rich insights. Additionally, case studies focused on sustainability initiatives contribute to broader debates on a variety of critical and current issues. These studies can serve as blueprints for businesses seeking to align their operations with environmental, social and governance (ESG) principles, which are becoming increasingly important for corporate success. With the rise of AI and machine learning, case studies offer valuable insights into how businesses are implementing these technologies across sectors, from manufacturing to finance. Technological advancements and innovations in AI provide fertile ground for case study research, helping to understand how AI is transforming business models, improving customer insights and enabling predictive analytics. By capturing the complexities of AI integration, case studies can guide other businesses in navigating the organizational, ethical and technological challenges they may face as they adopt similar tools. Researchers are encouraged to move beyond traditional research methods and embrace innovative approaches to understanding the complexities of business. The case study method, when applied rigourously, can uncover insights that other methods might overlook. In fast-evolving industries such as technology and finance, where innovation is a constant, case studies are invaluable for revealing how organizations are adapting to disruptive forces and managing organizational change. To ensure rigour in case study research, business studies should adhere to key principles of validity and reliability. Construct validity can be strengthened through data triangulation, combining interviews with business leaders, financial report analysis and the review of market trends. Internal validity can be enhanced through pattern matching and the development of logic models, helping researchers establish clearer cause-and-effect relationships. External validity is improved by conducting case studies, replicating findings across different organizations or industries, which makes the results more generalizable. Reliability is assured by following a strict protocol and meticulously documenting the research process, allowing for replication by future researchers.

While the above cases highlight the benefits of case study research, not all findings are consistent. In some instances, firms that followed best practices in digital transformation still faced setbacks due to unforeseen external factors, such as economic downturns, geopolitical instability or shifting regulatory landscapes. These external pressures, often beyond managerial control, underscore the unpredictable nature of business environments and the limitations of prescriptive frameworks. Furthermore, strategies that were once successful may become obsolete over time due to the rapid evolution of business trends, technological advancements, and shifting consumer preferences. A digital transformation approach that yielded strong results in one period may require significant adaptation in response to emerging industry best practices. Similarly, ESG policies that proved successful in one region did not necessarily translate to success in another. Cultural differences, variations in consumer expectations, regulatory divergence and economic disparities all contribute to the uneven impact of ESG initiatives. While European firms may benefit from stringent sustainability regulations that encourage green investments, companies in emerging markets may struggle with implementation due to financial constraints or lack of institutional support. The role of key stakeholders including investors, governments and advocacy groups further complicates ESG implementation. A company’s sustainability strategy may be strongly shaped by investor demands in Western markets but face resistance in regions where shareholder activism is weaker. These inconsistencies highlight the need for localized adaptations rather than one-size-fits-all approaches.

Additionally, industry-specific challenges contribute to the conflicting findings observed in case study research. While digital transformation in the financial sector may drive efficiency and profitability through automation and data-driven decision-making, manufacturing firms may face significant hurdles such as integration with legacy systems, supply chain disruptions, and workforce retraining. The same applies to ESG initiatives, what works in a technology-driven industry may not necessarily be effective in resource-intensive sectors like construction or mining, where environmental concerns and regulatory compliance differ significantly. Beyond industry differences, organizational culture and leadership also play a crucial role in determining the success of strategic initiatives. Even within the same industry, companies may experience different outcomes based on leadership styles, decision-making structures and the extent to which employees embrace change. A company with a strong leadership vision and an innovation-driven culture may successfully navigate digital transformation, whereas another with rigid hierarchical structures and resistance to change may struggle despite having access to similar resources and strategies. Another key factor influencing case study findings is market maturity. Business strategies that succeed in developed economies with stable regulatory frameworks, advanced technological infrastructure and a skilled workforce may not necessarily yield the same results in developing markets. Differences in consumer behaviour, institutional support and financial constraints often create barriers to implementation, leading to divergent outcomes even when similar strategies are applied. Additionally, stakeholder influence and institutional pressures can shape strategic success differently across regions. While companies in developed markets may be more responsive to regulatory and investor-driven ESG expectations, firms in less regulated environments may prioritize short-term financial stability over long-term sustainability.

Methodological limitations also contribute to inconsistencies in case study findings. Since case studies often rely on qualitative data, they may introduce subjectivity, bias and difficulties in replication. The depth of analysis can vary depending on data availability, the researcher’s interpretive lens and the selection of cases. Sample selection bias is another concern whereby findings based on a few high-performing firms may not be generalizable across the industry. Moreover, case study research often focuses on isolated variables, yet real-world business outcomes are shaped by the complex interplay of multiple factors, including economic conditions, regulatory frameworks, and cultural influences. To improve the robustness of case study research, scholars should ensure methodological rigour by triangulating multiple data sources, incorporating quantitative measures where possible and applying cross-case comparisons to identify broader patterns. These contradictions emphasize that while case studies offer valuable insights, they must be interpreted within their specific contexts. A single case may provide deep, nuanced understanding, but its applicability beyond the studied environment is not always guaranteed. By integrating explicit case examples, direct evidence from interviews and documents, and a systematic analysis of conflicting findings, researchers can enhance the depth of understanding in case study research. Ensuring methodological rigour and contextual awareness while considering time sensitivity, industry and market differences, and stakeholder influences will help maintain the relevance and applicability of case study methodologies in an evolving business landscape.

CONCLUSIONS

The case study research method holds immense potential for business research, particularly in addressing the complexities of contemporary business issues. As the global business environment continues to evolve rapidly due to factors like digital disruption, sustainability challenges and shifts in consumer behaviour, case studies offer a valuable method for exploring these phenomena in depth. By providing rich, context-rich insights, case studies enable researchers to capture the nuances of real-world business challenges and solutions. As business educators and researchers, it is essential to embrace the case study method not only as a valid and reliable tool but also as a dynamic approach to investigating emerging trends and future developments in the business world. Case studies offer a unique opportunity to bridge the gap between academic theory and practical application, allowing for more informed decision-making across industries. Furthermore, as the boundaries between industries continue to blur, case studies can provide interdisciplinary insights, fostering innovation and cross-sector collaboration. By integrating diverse perspectives, researchers can better understand how organizations can adapt to an ever-changing landscape. Ultimately, by embracing case studies, the business research community can not only enhance its understanding of complex organizational processes but also contribute to the development of more effective, adaptive business models. These models will be essential in navigating an era of unprecedented change, ensuring that businesses remain resilient, forward-thinking and capable of meeting the evolving demands of the global marketplace.

FUTURE RESEARCH DIRECTIONS IN CASE STUDY METHODOLOGY

Future research in business studies can benefit greatly from the case study method, especially in addressing the complexity of modern business interventions. Traditional research methods, such as surveys or experimental designs, often struggle to capture the interconnectedness of various business factors. In contrast, case studies offer a holistic view of business environments, strategies and outcomes. Future research should continue to explore how case studies can assess multi-dimensional challenges, such as sustainability transitions, which are influenced by a blend of regulatory pressures, consumer demand and organizational culture. This approach allows researchers to combine both quantitative data, such as environmental metrics, and qualitative insights, such as employee engagement, offering a comprehensive understanding of business interventions and the reasons behind their success or failure. As businesses face increasingly complex challenges in a volatile, uncertain, complex and ambiguous (VUCA) environment, future research should focus on leveraging case studies to evaluate how organizations respond to emergent disruptions, such as technological advancements, shifting market dynamics or global crises. Researchers could examine how businesses navigate economic shocks, supply chain disruptions or rapid technological adoption, and how these organizations adapt their strategies and operations. Case studies can reveal the intricacies of decision-making processes, leadership responses and the long-term impacts of these adaptive strategies, offering insights that traditional methods might miss. Further research should also examine how case studies can deepen our understanding of CSR and ESG practices. These initiatives are multifaceted and require businesses to balance competing priorities, such as short-term profitability and long-term sustainability. Future research could investigate how organizations manage these tensions, especially when operating across multiple regions with varying regulations and stakeholder demands. By focusing on the specific dynamics of ESG implementation, case studies can provide valuable insights into the complexities of global compliance, investor relations and stakeholder engagement. Future research can explore how real-world phenomena challenge or refine existing business frameworks, especially in areas like innovation theory and global strategy. Case studies examining businesses navigating international markets, regulatory differences and cultural nuances can provide fresh perspectives on global expansion and strategy. By analysing the combination of qualitative and quantitative data, future case studies can contribute to a more nuanced understanding of the drivers of success in global business environments. Future research should focus on utilizing case studies to explore the dynamic and interconnected nature of business challenges, particularly in areas like sustainability, adaptation to disruption, and CSR/ESG practices. Case studies provide a valuable method for uncovering the complex, multifaceted factors that shape business strategies and outcomes, offering deeper insights into both practical applications and theoretical advancements. To support the perspectives discussed, selected examples of relevant case studies have been appended in the Appendix, illustrating the practical applications of the case study method in examining complex business challenges.

ETHICAL STATEMENTS

This study adheres to ethical research principles by ensuring transparency, accuracy, and responsible handling of records. Where applicable, information has been sourced from publicly available documents, secondary reports, and prior research. In cases where company data were utilized, informed consent was obtained, and confidentiality was maintained to protect sensitive information. The study complies with ethical guidelines by anonymizing data where necessary and ensuring that no proprietary or personally identifiable information is disclosed.

DATA AVAILABILITY

No data were generated from the study.

AUTHOR CONTRIBUTIONS

Conceptualization, SAn, KLA, SAh, IS; Methodology, SAn, KLA; Software, SAn; Validation, SAn, KLA, SAh, IS; Formal Analysis, SAn, KLA; Investigation, SAn, SAh; Resources, SAn, SAh; Data Curation, SAn, SAh; Writing—Original Draft Preparation, SAn; Writing—Review & Editing, SAn, KLA, SAh, IS; Visualization, SAn, SAh; Supervision, SAn, KLA; Project Administration, SAn; Funding Acquisition, KLA.

CONFLICTS OF INTEREST

The authors declare that they have no conflicts of interest.

APPENDIX

These example case studies can assist researchers and academics in various ways by providing concrete, real-world examples of how migration intersects with various social, economic, and environmental issues. These case studies assist researchers and academics by providing a practical understanding of migration’s multifaceted role in contemporary societies. They enhance the understanding of how migration can drive economic, social and environmental progress and demonstrate the potential of migrants to contribute positively to their host countries. Researchers in migration studies, sustainability fields, labour economics and social policy can leverage these cases to inform their work, challenge existing paradigms and contribute to policy innovations that recognize the vital role migrants play in both the local and global economy.

Case Study 1 (Integration of Refugees in Germany) and Case Study 5 (Green Entrepreneurship in the UK) provide clear examples of how migrants contribute to green entrepreneurship despite challenges. Researchers focusing on sustainable development, green entrepreneurship, and social integration can use these cases to explore how migrants overcome barriers like language, financial constraints and social stigma to contribute to environmental sustainability. These case studies offer practical insight into the role of migration in fostering innovation in green sectors, which can enrich academic discussions on sustainable development, environmental economics, and the economic integration of migrants.

Case Study 2 (Migrant Housing Crisis in London) and Case Study 3 (Syrian Refugees and Social Integration in Lebanon) highlight the challenges migrants face regarding housing and social exclusion, a crucial topic for migration scholars. These studies allow researchers to analyse systemic barriers that affect migrant communities in urban settings, such as housing discrimination, overcrowding and health risks. They can also contribute to research on the impact of migration on urban planning, social inequality and policy interventions. These cases can serve as a basis for discussions on how migrant integration policies can address these critical issues, helping inform policymakers and urban planners.

Case Study 4 (Role of Migrant Workers in Agriculture in Spain) provides an example of how migrants contribute significantly to essential industries, such as agriculture, but often face exploitation, low wages and poor working conditions. Researchers in the fields of labour economics, migration studies and social justice can use this case to examine the migrant labour market and labour rights. It also offers insights into exploitation in the informal economy and the social and economic challenges faced by migrant workers. This case can help researchers develop better policy frameworks for the protection of migrant workers and improve their social integration.

In response to the 2015 refugee crisis, Germany opened its borders to asylum seekers, particularly from Syria, Afghanistan, and Iraq. The country initiated several integration programs to help refugees become self-sufficient. One notable program aimed at promoting green entrepreneurship among migrants. Refugees had to overcome language barriers, social stigma, and lack of financial resources to start their own businesses. They were provided with training and support for sustainable ventures, such as solar panel installation, eco-friendly construction, and organic farming. Over time, a number of migrants succeeded in establishing green businesses, contributing to local economies while aligning with Germany’s environmental goals. This not only improved the migrants’ financial stability but also helped integrate them into the larger community, creating a win-win for both migrants and the host country. This case supports the theme of how migration contributes to sustainable practices, illustrating the benefits of integrating migrants into green entrepreneurial sectors.

London has long been a destination for migrants seeking better economic opportunities. However, due to rising rent costs and gentrification, many migrant communities face inadequate housing conditions. A significant portion of these migrants work in low-paying jobs and are unable to afford decent housing. Housing discrimination is prevalent, with landlords reluctant to rent to migrant workers. Many migrants are forced into overcrowded, substandard housing in certain boroughs of London, leading to health risks and poor living conditions. Housing advocacy groups have fought to address this issue by promoting affordable housing policies, providing support services for migrant workers, and tackling discrimination through legal challenges. This case illustrates the challenges migrants face regarding housing, the social exclusion they encounter and the systemic barriers to securing decent living spaces in cities like London.

Lebanon hosts the highest number of refugees per capita globally, with over 1 million Syrian refugees having fled the civil war since 2011. Lebanon’s infrastructure and housing systems have struggled to accommodate this influx. Refugees face difficulties integrating into the labour market, often working in low-wage jobs. There is a significant strain on public services, including housing, healthcare, and education. Despite these challenges, Syrian refugees have contributed to Lebanon’s economy, particularly through the informal sector, by opening small businesses, providing cheap labour, and contributing to local agriculture. However, these contributions have not always been fully recognized, and they continue to face social exclusion. This case highlights the double-edged sword of migration, showing both the struggles with housing and discrimination faced by migrants and their contributions to the economy, as well as how they can positively impact host countries despite these challenges.

Spain has been a popular destination for migrant workers, particularly from Morocco, sub-Saharan Africa and Eastern Europe. Migrants play a key role in the Spanish agricultural industry, working in fruit and vegetable harvesting. Many migrant workers live in substandard, overcrowded conditions, with little access to social services. Migrants often face low wages and exploitation by employers. Discrimination and racial profiling contribute to their exclusion from social and political spheres. Activists and non-governmental organizations (NGOs) have fought for better labour rights and housing conditions for migrant workers in Spain. There have been improvements in awareness and labour protections, but significant work remains to be done to integrate migrants more fully into Spanish society. This case demonstrates the intersection of migration and labour exploitation, highlighting how migrant workers contribute to key sectors of a country’s economy but face severe social exclusion, discrimination, and poor living conditions.

The UK government has been encouraging green entrepreneurship as part of its long-term sustainability goals. Migrants, particularly those from South Asia and East Africa, have taken up entrepreneurial activities in the green sector. Migrants face a lack of access to capital, language barriers and cultural challenges. Despite these barriers, some have successfully launched businesses focusing on renewable energy, recycling and eco-friendly construction materials. The success stories of migrant-led green businesses are an example of how migrants can contribute to environmental sustainability. These businesses not only improve the local economy but also assist in the UK’s shift toward greener and more sustainable practices. This case illustrates how migrants can drive green entrepreneurship and contribute to sustainable practices, supporting the idea of integration into national development plans with a focus on sustainability.