recommendations for using the case study method in international business research

Methodological challenges and insights for future international business research

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• Published: 12 December 2022
• Volume 54 , pages 219–232, ( 2023 )

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• Herman Aguinis 1 ,
• Donald Bergh 2 &
• José F. Molina-Azorin 3  

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Given the diverse, interdisciplinary, and multilevel nature of international business (IB) research, it is critical to address methodological challenges prior to data collection. Thus, we suggest that an ounce of methodological prevention is worth a pound of cure . We describe the following challenges: (1) researching an important and relevant issue; (2) making meaningful theoretical progress; (3) recognizing, anticipating, and resolving dilemmas in research design and execution decisions; (4) integrating quantitative and qualitative research by using mixed methods; and (5) reducing the “distal proxy fallacy” through measurement error management. We then offer specific and actionable recommendations and implementation guidelines for authors, journal editors, and reviewers for addressing each of these methodological challenges with the overall goal of advancing IB theory.

Compte tenu de la nature interdisciplinaire, multi-niveaux et diverse de la recherche en affaires internationales ( International Business  – IB), il est essentiel de relever les défis méthodologiques avant la collecte des données. Ainsi, nous suggérons qu' une once de prévention méthodologique vaut une livre de remède. Nous décrivons les défis suivants: (1) effectuer de la recherche sur une question importante et pertinente; (2) faire des progrès théoriques significatifs; (3) reconnaître, anticiper et résoudre les dilemmes dans la conception et l'exécution de la recherche; (4) intégrer la recherche quantitative et qualitative en utilisant des méthodes mixtes; et (5) réduire l’idée fausse relative au proxy distal (Distal Proxy Fallacy) par la gestion des erreurs de mesure. Nous proposons ensuite aux auteurs, rédacteurs en chef et évaluateurs des recommandations spécifiques et actionnables ainsi que des instructions de mise en œuvre pour relever chacun de ces défis méthodologiques, et ce dans le but général de faire progresser la théorie de l'IB.

Dada la naturaleza diversa, interdisciplinaria y multinivel de la investigación sobre negocios internacionales (IB por sus iniciales en inglés), es esencial abordar los retos metodológicos desde antes de la recolección de datos. Por ello, sugerimos que un gramo de prevención metodológica vale más que una libra de cura. Describimos los siguientes retos: (1) investigar un tema importante y relevante; (2) lograr un progreso teórico significativo; (3) reconocer, anticipar y resolver los dilemas en el diseño de la investigación y las decisiones de ejecución; (4) integrar la investigación cuantitativa y cualitativa mediante el uso de métodos mixtos; y (5) reducir la “falacia de la distancia entre constructos y sus proxies” mediante la gestión de los errores de medición. A continuación, ofrecemos recomendaciones específicas y prácticas, así como directrices de aplicación para los autores, los editores de revistas y los revisores, para abordar cada uno de estos retos metodológicos con el objetivo general de hacer avanzar la teoría de negocios internacionales.

Dada a natureza diversa, interdisciplinar e multinível da pesquisa em negócios internacionais (IB), é fundamental abordar desafios metodológicos anteriores à coleta de dados. Assim, sugerimos que um grama de prevenção metodológica vale um quilo de cura. Descrevemos os seguintes desafios: (1) pesquisar uma questão importante e relevante; (2) fazer progresso teórico significativo; (3) reconhecer, antecipar e resolver dilemas em decisões de desenho e execução da pesquisa; (4) integrar pesquisas quantitativas e qualitativas usando métodos mistos; e (5) reduzir a falácia da distância da proxy por meio do gerenciamento de erros de mensuração. Em seguida, oferecemos recomendações específicas e acionáveis bem como diretrizes de implementação para autores, editores de periódicos e revisores para abordar cada um desses desafios metodológicos com o objetivo geral de avançar a teoria em IB.

鉴于国际商务 (IB) 研究多样化、跨学科和多层次的性质, 在数据收集之前解决方法论的挑战至关重要。因此, 我们建议, 一盎司的方法论的预防胜过一磅的治疗。我们描述了以下的挑战: (1) 研究一个重要且相关的问题; (2) 取得有意义的理论进展; (3) 识别、预测和解决研究设计和执行决策中的困境; (4) 采用混合方法整合定量和定性研究; (5) 通过测量误差管理来减少“远端代理谬误”。然后, 为了推进 IB 理论这个总体目标, 我们为作者、期刊编辑和审稿人提供了具体且可操作的建议和实施指南, 以解决这些方法论挑战中的每一个挑战。

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Introduction

Many theories and much of the research conducted in the field of international business (IB) are closely related to theories originating in macro-foundational (e.g., economics, sociology) and well as micro-foundational (e.g., psychology) disciplines (Buckley, Doh, & Benischke, 2017 ). Similarly, as documented in the edited volume Research Methods in International Business (Eden, Nielsen, & Verbeke, 2020 ), IB researchers rely on methodological approaches originating in a wide variety of fields. The reason is that IB research addresses transnational operations, multinational firm strategies, and the behavior of individuals within these settings (i.e., micro-foundations of many of the choices and decisions and their relations to organizational outcomes). Thus, IB research examines not only different levels of analysis, but also interactions among these macro-, meso-, and micro-levels given that it encompasses business (e.g., accounting, finance, management, marketing) as well as other disciplines (e.g., economics, political science, psychology).

Given the diversity regarding disciplines and levels of analysis, contemporary IB research faces two broad challenges, which also serve as opportunities: (a) quicker access to massive amounts of both numerical and text-based data (e.g., firm websites, social media sites), and (b) new software and data-analytic developments. Certainly, these developments are not specific to IB research alone but are also happening in other fields such as management, medicine, and engineering.

Despite its interdisciplinary and multilevel orientation, and the emergence of new challenges and opportunities, we believe that an important constant across IB research domains is that an ounce of methodological prevention is worth a pound of cure (cf. Aguinis & Vandenberg, 2014 ). Stated differently, although it may be possible to improve a study and its contributions to IB theory by conducting additional analyses, it is difficult, if not impossible, to turn a methodologically inferior study into a methodologically sound one if certain issues were not addressed prior to data collection . In fact, these problems are often the cause of desk-rejection decisions. Accordingly, the specific methodological challenges we address – and associated solutions that constitute features of sound methodology – refer to the pre-data collection stages of research.

Clearly, we are not the first to discuss methodological challenges in IB (e.g., Eden et al., 2020 ; Nielsen, Eden, et al., 2020a ; see Bergh, 2021 , for a review). In fact, articles published in Journal of International Business Studies ( JIBS ) have addressed how to make IB research more reproducible and trustworthy (Aguinis, Cascio, & Ramani, 2017 ), how to improve the use of and take more advantage of qualitative methods (Birkinshaw, Brannen, & Tung, 2011 ), and how to gain new insights from the unique features of social network analysis (Cuypers, Ertug, Cantwell, Zaheer, & Kilduff, 2020 ), among many others. Indeed, most JIBS volumes feature at least one article addressing some methodological matter (Bergh, 2021 ). In addition, some of the challenges we describe in our article are not necessarily unique to IB research. For example, Shaver ( 2021 ) highlighted methodological challenges in strategic management research such as the need to strengthen causal inferences and the use of multi-method approaches for advancing theory, which are issues we address in our article. But, these and other challenges are particularly relevant and, moreover, exacerbated in IB research because of the field’s diversity regarding disciplines and particular interest in developing and testing theory about different levels as well as relations between levels (e.g., individuals and firms, firms and industries, individuals and culture).

Within the framework that an ounce of methodological prevention is worth a pound of cure, our article makes value-added contributions given four features. First, complementing past specific methodological contributions published in JIBS, rather than focusing on a specific approach or technique, we discuss broad challenges that are relevant and applicable for IB theory advancements more generally. Accordingly, we offer insights for a broad range of IB researchers – not just those interested in a particular method or relying on a particular ontological perspective. Second, most of our recommendations and specific courses of action can be implemented concurrently or separately. Thus, best-in-kind IB research and theory advancements will result from the implementation of as many of these sound practices as possible. Third, we offer insights and recommendations on how to achieve best-in-kind IB methodology specifically based on lessons learned from the organizational research literature. Clearly, not all organizational research is directly relevant to IB. However, we point to methodological bridges between IB and organizational research because we believe that making IB’s methodological borders more permeable is likely to result in benefits not only for IB but also for adjacent fields such as organizational behavior, strategic management studies, human resource management, and entrepreneurship (Aguinis & Gabriel, 2022 ). A benefit of building such bridges is that scholars from fields outside of IB may find it relevant and attractive to submit their research for publication consideration in JIBS and other IB journals, thereby increasing the diversity of perspectives. Finally, the challenges and solutions we offer are particularly relevant and useful for IB research given its heterogeneity regarding substantive domains, levels of analysis, and methodological and ontological orientations and we illustrate this feature using examples from across several IB domains.

Methodological challenges and features of sound IB methodology

We focus on the following five challenges. As a preview, a summary of challenges and recommendations as well as implementation guidelines on how to address these challenges to achieve sound methodology are included in Table 1 .

Researching an important and relevant issue : How can IB researchers identify and study issues of importance not only for theory but also for practice and policy-making?

Making meaningful theoretical progress : How can IB researchers accelerate theoretical progress?

Recognizing, anticipating, and resolving dilemmas in research design and execution decisions : How can IB researchers solve dilemmas and tradeoffs when designing and executing empirical research?

Integrating quantitative and qualitative research by using mixed methods : How can IB researchers integrate, rather than stack, quantitative and qualitative methods by using mixed methods?

Reducing the “distal proxy fallacy” through measurement error management : How can IB researchers reduce the distance between constructs and their proxies when creating measures and use Cronbach’s alpha and other approaches for narrowing this gap?

Researching an important and relevant issue

There is a documented disconnect between the knowledge that IB academics are producing and the knowledge that managers and policy-makers are consuming (Grøgaard, Sartor, & Rademaker, 2022 ). As noted by Grøgaard et al., ( 2022 : 1512), “it is common to find only a cursory consideration of a study’s practical implications in the discussion section of published IB papers… most published research seems to be primarily intended for an academic audience.” We believe that an important reason for this so-called research-practice gap is that, frankly, our research often does not address important and relevant issues for society. It is very encouraging that JIBS now includes a Societal Impact Advisory Committee (SIAC), whose mission is to support authors, editors, reviewers, and users of IB knowledge in strengthening the discussion of the societal impact of research (Tung, 2023 ). Specifically, SIAC’s role is to strengthen articles’ (a) practical implications for business or society (i.e., policy or practice) and/or (b) have impact on stakeholders beyond shareholders.

Clearly, not all IB research is supposed to have direct and immediate application and there is a need to produce research that will lead to basic and theoretical knowledge without direct and short-term applicability. But, we also believe that if the bulk of IB research falls into that category, then IB is unlikely to achieve our collective and lofty goal expressed in the mission of the Academy of International Business, which is “dedicated to promoting impactful research, improving business education and practice, and collaborating with leaders in policy and interdisciplinary research” (Academy of International Business, 2022 ). In fact, there is a close association between the Academy of international Business (AIB) and the World Investment Report (WIR) produced by the United Nations Conference on Trade and Development (UNCTAD), and this is the reason why the annual AIB meetings include a plenary session devoted to the publication and discussion of each year’s WIR.

How can IB researchers identify and study issues of importance for both theory and practice? We offer two features of sound IB methodology to answer this question. First, there is a need to address important questions. For junior researchers, this can be accomplished by becoming exposed to many ideas and topics. One way of doing so is to be involved in as many research projects as possible (beginning in graduate school) and volunteering as a reviewer for conferences. More experienced scholars can volunteer as reviewers for journals and, eventually, as editorial board members. But, exposure to other research and other researchers is only the first step. It is also important to engage in “bridging” activities with the world of IB practice (Grøgaard et al., 2022 ; Shapiro, Kirkman, & Courtney, 2007 ). Consider the following three possibilities likely to result in researching important and relevant issues: (a) becoming involved in senior managerial decision-making by serving on boards of directors and leadership positions in global organizations, (b) serving as an instructor in executive education courses, and (c) spending a sabbatical in business practice either as a translator of existing research or researcher on teams including both researchers and practitioners.

Second, consider conducting research with a practical and possibly policy-making end in mind (Aguinis & Vandenberg, 2014 ). This can be accomplished by adopting a design-science approach as proposed by Simon ( 1996 [1969]). This approach to doing research involves understanding the present, but also aims to create better futures. For example, in the field of medicine, a design-science approach involves restoring health to a patient suffering from cancer. In the case of IB, as just two examples, a design-science approach may involve producing knowledge to improve the effectiveness of a firm’s global talent management system, or producing knowledge aimed at improving the effectiveness of firms’ entry strategy in a different country. Sound IB methodology based on a design-science approach means studying dependent variables that are of interest to decision-makers (e.g., the attraction and retention of global talent, effective foreign market entry) and independent variables that can be changed by instituting new practices and policies (e.g., improved use of recruiting websites, improved practices regarding cross-cultural management). Although leading to new knowledge, if independent variables are outside of the control of decision-makers and policy-makers, it is unlikely that the resulting knowledge will be of use to them.

Making Meaningful Theoretical Progress

There are important challenges in IB regarding the way we usually test our theories and the overall slow degree of theory advancement. For example, one challenge is the lack of precision in hypothesis testing, given that the majority of hypotheses simply predict that an increase in one variable will covary with an increase or decrease in another. This type of hypothesis is common and two illustrations of hypotheses tested in recently published JIBS articles are the following: 1

Hypothesis 1:

The extent of women representation on the board of directors is positively related to corporate social performance.

Hypothesis 2:

An initial public offering has a positive effect on the pace at which small- and medium-sized enterprises establish new foreign subsidiaries.

These are broad and general relations that can often be easily confirmed given a sufficiently large sample size (Edwards & Christian, 2014 ). As a second illustrative challenge about the need to make meaningful theoretical progress, hypothesizing after results are known (i.e., HARKing) systematically capitalizes on chance. HARKing not only delays, but also derails, theory advancements (Aguinis et al., 2017 ; Murphy & Aguinis, 2019 ). For example, cherry-picking involves searching through data involving alternative measures or samples to find the results that offer the strongest possible support for a particular hypothesis. Another particularly pernicious form of HARKing is question trolling , which involves searching through data involving several different constructs and measures to find seemingly notable results worth writing about.

What does sound IB methodology look like if we would like to make meaningful theoretical progress? We offer two complementary courses of action. First, there is a need to develop theories with hypotheses that are more precise in describing the nature of the effect rather than merely stating that an effect or relation will differ from zero or that higher/lower values on variable X are related to higher/lower values on variable Y . In other words, sound IB methodology exposes theories to stringent tests that put them at genuine risk of falsification. To do so, the wording of hypotheses can be such that they include lower and upper bounds for effects (e.g., based on previous research or meta-analyses), non-nil effects, zones of indifference for effects, competitive predictions (i.e., strong inference), and a “good enough” belt for effects. To return to Hypothesis 1 above, a more precise hypothesis leading to improved theory might be the following:

Hypothesis 1a:

The presence of [precise number or proportion] of women on the board results in an increase of corporate social performance of [specific] %.

In addition, it is important for hypotheses to specify the functional form of the predicted relation between variables. For example, the nature of the relation could be linear or curvilinear, in which case the prediction should also include the location of the inflection point. To follow-up on this same example, a more precise version of the same hypothesis would be the following:

Hypothesis 1b:

The presence of [precise number or proportion] of women on the board results in an inflection point such that its impact on corporate social performance becomes [asymptotic or negative].

On a related note, results of hypothesis testing should go beyond simply reporting p values and include effect-size estimates and their confidence intervals, as well as an interpretation of the meaning and significance of the reported effect for theory and practice (Meyer, van Witteloostuijn, & Beugelsdijk, 2017 ).

Second, sound IB methodology ideally allows for inferences about causal relations. Shaver ( 2021 ) highlighted research design choices that can help advance causal identification, noting that a recent trend in the field of strategic management studies is to conduct experiments. Moreover, field experiments are also becoming more popular because they provide opportunities to identify previously unconsidered relations or examine existing relations in new ways (Eden, 2017 ; Withers & Li, 2021 ). Research design weaknesses and unclear causal relations are the #3 and #4 most frequent methodological challenges reported by authors of JIBS articles, respectively (Aguinis, Ramani, & Cascio, 2020 ). But, although randomized experiments are the gold standard for science (Lonati, Quiroga, Zehnder, & Antonakis, 2018 ), they are difficult, if not impossible, in many IB domains because of the inability to manipulate variables such as internationalization decisions, risk assessments, or buy-or-build decisions for large multinational enterprises. Also, regarding micro-foundations of IB, although some managers may be willing to participate in experiments involving simulations or vignette studies, there are concerns about external validity. Nevertheless, sound IB research can provide stronger evidence about causal relations by incorporating design features that have the potential to turn what otherwise might be a nonexperimental study into a quasi-experiment (Grant & Wall, 2009 ). As yet another feature of sound IB methodology to address causality, latent class tools such as latent profile analysis can be used to identify groups of firms (or group of individuals, teams, or industries) at different levels of the predictors and subsequently use this distinction as a manipulation to evaluate whether the outcome variables differ in the expected direction between the groups.

We also recommend addressing endogenous threats in research design to anticipate misleading conclusions about causal relations. This topic has received attention in IB research, spanning sampling decisions, experimental design variations, matching models, instrumental variables, 2-stage analytical techniques, and longitudinal data structures (see Li, Ding, Hu, & Wan, 2021 ; Reeb, Sakakibara, & Mahmood, 2012 ). We highlight two additional issues. First, all approaches to causal identification have limitations, so there is a need to develop a cumulative body of research that includes a plurality of approaches (as we explain further below). In addition, we call on IB researchers to attend to alternative theoretical mechanisms to help rule out competing explanations. Second, we recommend that IB researchers report quantitative evidence of possible omitted variable bias by implementing the “Impact Threshold of Confounding Variables” (ITCV) procedure (Busenbark, Yoon, Gamache, & Withers, 2022 ). This test provides insights into how omitted variables can directly bias causal inference. Specifically, it provides information on (a) the minimum correlation an omitted variable would need to have with both an explanatory variable and the dependent variable to invalidate a finding and (b) how many cases (and the overall percentage) of a predictor variable would need to be replaced with a value of zero for the coefficient of interest to become statistically non-significant. If the correlational value in (a) is larger than any others in a study relative to both the independent and dependent variables and if the number (percentage) of cases in (b) needed to become zero is outside the likelihood of chance, then the researcher can conclude that omitted variables pose little risk to the relationship. Overall, ITCV is a sensitivity analysis that provides objective information about the likelihood of omitted variable bias.

Recognizing, Anticipating, and Solving Dilemmas in Research Design and Execution Decisions

The availability of data regarding transnational operations, multinational firm strategies, and the behavior of individuals within these settings (i.e., micro-foundations of many of the choices and decisions and their relations to organizational outcomes) is going through a major transformation. Specifically, records of these topics are now available through “big data” sources that give IB researchers quick access to massive amounts of information. In addition, IB researchers also have access to increasingly sophisticated and new analytical techniques that allow them to parse and glean insights previously unimaginable. These trends, and others, represent significant opportunities for IB researchers to “take advantage of untapped sources of information and to re-analyze currently available data” (Aguinis et al., 2020 : 1593). However, these developments also led Nielsen, Eden, et al. ( 2020 : 32) to warn that “[t]echnology is a powerful aid in research, but IB scholars should strive for methodological parsimony.” We agree, noting that as exciting as recent methodological developments may seem, they have implications that IB researchers need to understand and leverage in their research agendas. Indeed, a reminder of tradeoffs in research design choices is warranted.

Clearly, social science research is imperfect. To help understand the origins of the inevitable challenges in a social science such as IB, and how we can possibly address them, it is instructive to review the classic article by McGrath ( 1981 ). He identified intractable tradeoffs and how we can learn to live with them. Our discussion in this section provides additional justification for Nielsen et al.'s ( 2020b ) observation that “[R]igor requires a holistic approach that integrates multiple methodological elements together in a way that best suits the entire research design….rigor in IB research need[s] to be recalibrated to acknowledge the importance of building in triangulation to strengthen research designs [italics added], a strategy that we found has received little explicit recognition so far” (Nielsen, Welch, et al., 2020 : 1492)

Applying what he called the “dilemmatic approach,” McGrath argued that the research process includes a series of interlocking decisions in which scholars try to maximize several conflicting desiderata. Research choices involve a series of mutually incompatible goals, leading McGrath to assert that there is no “one true method or set of methodological choices that will guarantee success…no one ‘best’ strategy or set of choices…all research strategies and methods are seriously flawed” (McGrath, 1981 : 179). Several important tradeoffs, or dilemmas, exist. We draw attention to these matters to improve our understanding of the limitations in how knowledge is created and how we can help contribute despite the vulnerabilities in our own work.

First, starting with the most general, there are different types of research designs that can be arranged into four groups including (1) field studies and field experiments, (2) laboratory experiments and experimental simulations, (3) judgment tasks and sample surveys, and (4) formal theory and computer simulations. McGrath then noted that these four can be evaluated relative to two dimensions: obtrusive versus unobtrusive and universal versus particular. Based on this categorization, he identified “three horns” that pertain to each group of methodological strategies: (a) generalizability with respect to populations; (b) precision with respect to measurement, manipulation, and control; and (c) realism of context. These horns represent opposing or conflicting features afflicting empirical research which  a single study cannot maximize all three at the same time. McGrath explained that “the research strategy domain is a three-horned dilemma, and every research strategy either avoids two horns by an uneasy compromise but gets impaled, to the hilt, on the third horn; or grabs the dilemma boldly by one horn, maximizing on it, but at the same time ‘sitting down’ (with some pain) on the other two horns” (McGrath, 1981 : 184). The strength of one research strategy is the weakness of another. McGrath opined in a summary, “[ i]t is not possible, in principle, to do an unflawed study, or fantasize, if you will, about lying in clover; but be prepared to awake on a bed of horns” (McGrath, 1981 : 186). The implication is that knowledge development within a research stream needs a plurality of research strategies to develop insights that span the three horns. If a research stream has developed using the same research strategies, then all the studies suffer from the same general weaknesses. Methods that compensate for each other’s vulnerabilities offer the most promise for advancing theory (Bergh, Boyd, Byron, Gove, & Ketchen, 2022 ). Researchers might therefore position the strengths of their strategies relative to others that have already appeared within their chosen literature.

Second, research designs also involve dilemmas, especially between information, noise, and uncertainty. In particular, tradeoffs exist between scope (i.e., amount of information in the problem) and precision (i.e., amount of noise in the information). For example, if a particular design reduces uncertainty to help gain precision, such as through controls within an experiment, then it reduces the possible combinations of events and observations that can occur. In turn, there is less information that can be yielded from the variables, meaning that we find out less about our studied relations. In addition, as mentioned earlier, randomized experiments may not be the answer. Although they are useful for untangling relations that may have causal connections, they suffer from important logistical challenges, they do not necessarily address all threats to internal validity, and by the very nature of experimental manipulation they might exaggerate the size of effects. McGrath depicted these tradeoffs as conflicts between standardization to gain precision by reducing noise and generalizability to gain confidence in strength and robustness.

So, IB researchers are left to accept the harsh reality that no single study is perfect and each has built-in flaws. If the scope of our studies is wide and we employ big data sources with apparently little or no constraints, we may be tempted to conclude that we have captured their topic fully. However, we accept noise, suffer a lack of measurement precision, and learn only a little about something very large. Alternatively, if we reduce noise by cutting scope, we learn more about less. The implications are stark: when making design choices, IB researchers face conflicts between information and noise through the tradeoffs between scope and precision. Thus, big data and other technological developments may not be the panacea that some suggest they are.

Overall, McGrath’s insights help us understand research design and execution decisions: the research process “teems” with dilemmas involving two or even three contradictory objectives and there is no single solution that allows all three objectives to be accomplished simultaneously. We cannot conduct flawless research and, therefore, combining a plurality of strategies and designs is the way to overcome or at least lessen the inherent limitations in each. Indeed, McGrath exhorted researchers to consider multiple methods approaches: “The dilemmas can be handled by… bowling them over with multiple methods… multiple designs… multiple strategies, to gain information about the research problems of concern… ‘good research’—using flawed methods well, and in effective combinations—can help us accrue ‘knowledge’ … that are of both theoretical and practical concern” (McGrath, 1981 : 209–210).

Integrating Quantitative and Qualitative Research by using Mixed Methods

Based on an examination of empirical studies published in JIBS over its entire 50-year lifetime, Nielsen, Welch, et al. ( 2020 ) reported that most articles (86.7%) used quantitative methods. So, although the IB community has been a pioneer in fostering the use of mixed-methods research (Hurmerinta-Peltomäki & Nummela, 2006 ), this methodological approach is clearly underutilized. We reached this same conclusion after reviewing the references lists of the 35 mixed-methods studies published in JIBS from 2000 to 2019 identified by Nielsen, Welch, et al. ( 2020 ). Specifically, we found that only four studies actually included some methodological reference to mixed methods. As noted in the previous section about dilemmas in research decisions, combining research strategies may help overcome inherent and unavoidable limitations and tradeoffs. Moreover, IB methodology can improve its soundness by using mixed methods because of its role in producing responsible research (Tsui & McKiernan, 2022 ): research that is simultaneously (a) rigorous and credible and (b) relevant and useful for society.

With regards to rigorous and credible research, the main premise of mixed methods is that the use of quantitative and qualitative approaches in combination provides a better understanding of phenomena compared to either approach by itself. But, this combination should not be a simple stacking of separate quantitative and qualitative components. Rather, the key point is to take advantage of the full potential of mixed methods by integration. In fact, integration is the central defining characteristic of mixed methods research. It is this specific and unique feature that prompted Fetters and Freshwater ( 2015 ) to conclude that 1 + 1 = 3, reflecting on the idea that conducting mixed methods using a fully integrated approach yields a whole greater than the sum of the individual quantitative and qualitative parts.

An important feature of sound mixed-methods studies is transparency about precisely how integration has been achieved. Specifically, Fetters, Curry and Creswell ( 2013 ) described three possible types of integration: (a) study design (i.e., examining integration in three basic mixed methods designs: exploratory sequential, explanatory sequential, and convergent); (b) methods (i.e., considering four approaches: connecting, building, merging, and embedding); and (c) interpretation and reporting (e.g., integration through narrative and data transformation).

Together with recommendations on how to achieve better integration, O’Cathain ( 2010 ) provided a set of criteria for evaluating the quality of mixed methods studies, and Fabregues and Molina-Azorin ( 2017 ) reviewed the literature about quality in mixed methods and summarized available criteria. For example, some of these criteria include (a) planning quality (i.e., the extent to which the study plan is feasible and the purpose(s) and rationale for using mixed methods are appropriate), (b) design quality (i.e., the extent to which the mixed methods design is described in detail, suitable for the research question(s) and employs quantitative and qualitative methods that complement each other), and (c) methods and data quality (i.e., the extent to which sampling, data collection, analysis and integration of the qualitative and quantitative parts are appropriate, rigorous, and described with transparency) (Creswell & Plano Clark, 2018 ).

As mentioned above, using mixed methods research can help integrate rigor and relevance. Specifically in IB, Buckley et al. ( 2017 ) proposed a redirection of research toward grand challenges, emphasizing methodological implications: the need of phenomena-based research, the use of interdisciplinary research methods, the application of multilevel research, and the use of research involving interactions among business, government, and society in a global environment. Mixed methods are well positioned to address each of these challenges. In addition, involvement of stakeholders (e.g., managers, NGOs, policy-makers) in the research process, as well as the dissemination of research results, is a key aspect for relevant research. A mixed methods approach, through the qualitative part, may facilitate this involvement with the goal of identifying and addressing key research problems and questions regarding grand societal challenges.

Reducing the “Distal Proxy Fallacy” through Measurement Error Management

Challenges about measurement have been reported by 73% of authors of JIBS articles (Aguinis et al., 2020 ). This result should not be surprising given that some of the most central measures in the field such as the Kogut and Singh’s ( 1988 ) cultural distance index have resulted in significant debate and disagreement (Beugelsdijk, Kostova, Kunst, Spadafora, & van Essen, 2018 ; Cuypers, Ertug, Heugens, Kogut, & Zou, 2018 ). Other sources of IB measurement challenges include non-equivalence of data sources owing to cross-cultural settings and translations from one language to another. These and other sources of error direct attention to important needs: (a) Critically assessing the fit between theoretical constructs and their empirical proxies, and (b) ensuring the appropriateness of measures. For example, IB researchers often “retrofit” a construct to fit a data source that is available to them, and as a result, may introduce error into their measurement. We offer several recommendations to address these needs.

First, we suggest that researchers pay particularly careful attention to the meaning and definition of constructs. Podsakoff, MacKenzie, and Podsakoff ( 2016 ) argued that a lack of conceptual clarity can lead to a cascade of problems, not least of which is measurement error, and provided several recommendations in the form of a four-step process for developing conceptual definitions that can lead to a closer relation between IB constructs and their proxies:

Identify potential attributes of the construct and/or collect a representative set of definitions. Such activities encompass searching dictionaries, surveying the literature, interviewing subject-matter experts, consulting focus-groups, and case studies.

Organize the potential attributes by theme and identify any necessary and sufficient ones.

Develop a preliminary definition of the construct.

Refine the definition by introducing greater clarity and parsimony.

Second, we typically use a variety of procedures to assess the validity and reliability of our measures to understand whether they reflect their intended underlying constructs and how consistently they do so. While construct validity in IB research has been examined elsewhere (Aguinis et al., 2020 ), less attention has been devoted to reliability (e.g., consistency of scores across items in a scale, consistency of variables across databases). We propose that the “distal proxy fallacy” in IB research can be fruitfully addressed by paying more careful attention to how we manage measurement error through recognizing that there is not a “one size fits all” approach to knowing the extent to which measures are reliable (e.g., scores do not fluctuate due to random or measurement error).

More specifically, reliability is typically assessed using Cronbach’s alpha (CA; Cronbach, 1951 ). In fact, Cho and Kim noted that CA may be “regarded as the best available reliability coefficient because so many researchers use it in practice” ( 2015 : 208). Moreover, CA levels of 0.70 have become institutionalized as evidence to confirm the reliability of measures (Lance, Butts, & Michels, 2006 ). We used the Business Source Ultimate database with the phrases “Cronbach alpha” and “ Journal of International Business Studies ” and, not surprisingly, found 87 hits in the past decade alone. However, CA is often “not the most accurate reliability coefficient (i.e., it is overused)” (Cho, 2016 : 642). Its accuracy hinges on satisfying several conditions which, if violated, result in “estimates of reliability that are too small, making measures look less reliable than they actually are” (McNeish, 2018 : 412). Indeed, several scholars have examined the history, conditions, and assumptions of CA (Cho, 2016 ; Cho & Kim, 2015 ; Schmidt & Hunter, 1996 ) and concluded that it may have more limited application than IB researchers usually recognize. We review these matters to guide future IB research on when it is, and is not appropriate, to select CA, and when we should use a different reliability estimate.

First, CA requires “tau equivalence” among items of a scale, which occurs when items are linearly related and differ only by a constant. In other words, tau equivalence means that all items of a scale contribute equally to the total scale score, which is an assumption likely unmet in most IB measures ranging from cultural distance to innovation and liabilities of outsidership – just to mention a few. Second, scale items should be on a continuous scale and normally distributed – another assumption likely violated in most IB research. For example, the assumption that firm performance is normally distributed is untenable in most industries and especially in the context of international firms. Third, the errors of the terms should not covary (uncorrelated errors) (McNeish, 2018 ). In addition, the unquestioned used of CA is based on several misconceptions, including that CA was first developed by Cronbach (it was not), CA equals reliability (i.e., it is an imperfect index of one specific source of error only), reliability can be improved by deleting items, CA is deemed sufficient if it is greater than or equal to 0.70, and CA is the best choice among all reliability coefficients (Cho & Kim, 2015 ). Overall, the use of CA should not be an “unconditional and automatic choice for reliability estimation” (Cho & Kim, 2015 : 219). Thus, IB research should not rely on CA without careful justification because the requirements for CA are often difficult to satisfy and the information it yields is often misleading.

Fortunately, IB researchers have several alternatives to CA. Cho and Kim recommended structural equation modeling (SEM)-based reliability estimates, especially when the data include a multiple-factor structure. In addition, McNeish ( 2018 ) identified alternatives including omega coefficients and coefficient H. Each of these alternatives offers strengths and weaknesses and can be used based on specific design and measurement conditions. Because SEM may not be suitable for all situations, we focus our attention on reliability estimates other than CA.

Omega coefficients are especially attractive to IB research, in particular because they are best for “congeneric scales…where items vary in how strongly they are related to the construct being measured (i.e., in a factor analysis setting, the loadings would not be assumed to be equal). In other words, where tau equivalence is not assumed” (McNeish, 2018 : 416). For example, when examining the reliability of the Kogut–Singh cultural distance index, confidence in a CA value would require that the items meet tau equivalence, otherwise omega becomes the more accurate estimate. Alternatively, the multiple dimensional element may invite Cho and Kim’s SEM reliability-based estimates instead (e.g. Cuypers et al., 2020 ). Surprisingly, these issues have received less attention than one would expect for such an important and central index used across so many IB domains and theories.

In addition, three variations of omega exist, including omega hierarchical, omega total, and Revelle’s omega total. Each applies to different settings. Coefficient H may be the most applicable to IB research, as it provides an alternative that researchers can use if they are interested in creating a scale with optimally weighted items. This approach, also known as maximal reliability, occurs when “each item contributes different amounts of information to the overall scale score (instead of each item being given the same weight with unit weighting)” (McNeish, 2018 : 417).

Concluding remarks

IB researchers rely on theories and methodological approaches originating in a wide variety of micro- and macro-fields given IB’s interdisciplinary and multilevel nature. As a result, methodological challenges faced by IB researchers are quite diverse. However, in spite of the apparent differences, we see a common way to address pervasive methodological challenges, improve methodological soundness, and accelerate theoretical progress: An ounce of methodological prevention is worth a pound of cure. In other words, it is critical to anticipate and address methodological challenges prior to data collection . We described IB challenges and proposed solutions regarding the following issues: (1) researching an important and relevant issue, (2) making meaningful theoretical progress, (3) recognizing and solving dilemmas in research design and execution decisions, (4) integrating quantitative and qualitative research by using mixed methods, and (5) reducing the distal proxy fallacy through measurement error management. We offered specific and actionable recommendations for addressing each of these challenges with the goal of producing sound methodology. Irrespective of substantive domain, all scholars share the ambition to improve the understanding of IB phenomena including transnational operations, multinational firm strategies, and the behavior of individuals within these settings. Accordingly, we offered insights for a broad range of IB researchers – not just those interested in a particular methodological or ontological approach. We hope the concurrent implementation of these recommendations will be useful for authors as well as journal editors and reviewers given our collective and lofty goal of advancing IB theory, its application, and societal impact.

Most readers will recognize the customary manner in which these hypotheses are formulated and we therefore do not see the need to “point fingers” by revealing their sources. But, we make this information available upon request.

Academy of International Business. 2022. About AIB . Retrieved 20 September, 2022, from https://www.aib.world/about/ .

Aguinis, H., Cascio, W. F., & Ramani, R. S. 2017. Science’s reproducibility and replicability crisis: International business is not immune. Journal of International Business Studies, 48(6): 653–663.

Article   Google Scholar  

Aguinis, H., & Gabriel, K. P. 2022. International business studies: Are we really so uniquely complex? Journal of International Business Studies. . https://doi.org/10.1057/s41267-021-00462-x .

Aguinis, H., Ramani, R. S., & Cascio, W. F. 2020. Methodological practices in international business research: An after-action review of challenges and solutions. Journal of International Business Studies, 51(9): 1593–1608.

Aguinis, H., & Vandenberg, R. J. 2014. An ounce of prevention is worth a pound of cure: Improving research quality before data collection. Annual Review of Organizational Psychology and Organizational Behavior, 1(1): 569–595.

Bergh, D. 2021. Book review: Research methods in international business. Journal of International Business Studies, 52(6): 1225–1228.

Bergh, D. D., Boyd, B. K., Byron, K., Gove, S., & Ketchen, D. J. 2022. What constitutes a methodological contribution? Journal of Management, 48(7): 1835–1848.

Beugelsdijk, S., Kostova, T., Kunst, V. E., Spadafora, E., & Van Essen, M. 2018. Cultural distance and firm internationalization: A meta-analytical review and theoretical implications. Journal of Management, 44(1): 89–130.

Birkinshaw, J., Brannen, M. Y., & Tung, R. L. 2011. From a distance and generalizable to up close and grounded: Reclaiming a place for qualitative methods in international business research. Journal of International Business Studies, 42(5): 573–581.

Buckley, P. J., Doh, J. P., & Benischke, M. H. 2017. Towards a renaissance in international business research? Big questions, grand challenges, and the future of IB scholarship. Journal of International Business Studies, 48(9): 1045–1064.

Busenbark, J. R., Yoon, H., Gamache, D. L., & Withers, M. C. 2022. Omitted variable bias: Examining management research with the impact threshold of a confounding variable (ITCV). Journal of Management, 48(1): 17–48.

Cho, E. 2016. Making reliability reliable: A systematic approach to reliability coefficients. Organizational Research Methods, 19(4): 651–682.

Cho, E., & Kim, S. 2015. Cronbach’s coefficient alpha: Well known but poorly understood. Organizational Research Methods, 18(2): 207–230.

Creswell, J. W., & Plano Clark, V. P. 2018. Designing and conducting mixed methods research (3rd ed.). Sage.

Google Scholar  

Cronbach, L. J. 1951. Coefficient alpha and the internal structure of tests. Psychometrika, 16(3): 297–334.

Cuypers, I. R., Ertug, G., Heugens, P. P., Kogut, B., & Zou, T. 2018. The making of a construct: Lessons from 30 years of the Kogut and Singh cultural distance index. Journal of International Business Studies, 49(9): 1138–1153.

Cuypers, I. R., Ertug, G., Cantwell, J., Zaheer, A., & Kilduff, M. 2020. Making connections: Social networks in international business. Journal of International Business Studies, 51(5): 714–736.

Eden, D. 2017. Field experiments in organizations. Annual Review of Organizational Psychology and Organizational Behavior, 9(1): 91–122.

Eden, L., Nielsen, B. B., & Verbeke, A. (Eds.). 2020. Research Methods in international business, JIBS Special Collections . Palgrave Macmillan.

Edwards, J. R., & Christian, M. S. 2014. Using accumulated knowledge to calibrate theoretical propositions. Organizational Psychology Review, 4(3): 279–291.

Fabregues, S., & Molina-Azorin, J. F. 2017. Addressing quality in mixed methods research: A review and recommendations for a future agenda. Quality and Quantity, 51(6): 2847–2863.

Fetters, M. D., Curry, L. A., & Creswell, J. W. 2013. Achieving integration in mixed methods designs. Principles and practices. Health Services Research, 48(6): 2134–2156.

Fetters, M. D., & Freshwater, D. 2015. The 1+1=3 integration challenge. Journal of Mixed Methods Research, 9(2): 115–117.

Grant, A. M., & Wall, T. D. 2009. The neglected science and art of quasi-experimentation: Why-to, when-to, and how-to advice for organizational researchers. Organizational Research Methods, 12(4): 653–686.

Grøgaard, B., Sartor, M. A., & Rademaker, L. 2022. What merits greater scholarly attention in international business? Journal of International Business Studies, 53(7): 1508–1518.

Hurmerinta-Peltomäki, L., & Nummela, N. 2006. Mixed methods in international business research: A value-added perspective. Management International Review, 46(4): 439–459.

Kogut, B., & Singh, H. 1988. The effect of national culture on the choice of entry mode. Journal of International Business Studies, 19(3): 411–432.

Lance, C. E., Butts, M. M., & Michels, L. C. 2006. The sources of four commonly reported cutoff criteria: What did they really say? Organizational Research Methods, 9(2): 202–220.

Li, J., Ding, H., Hu, Y., & Wan, G. 2021. Dealing with dynamic endogeneity in international business research. Journal of International Business Studies, 52(3): 339–362.

Lonati, S., Quiroga, B. F., Zehnder, C., & Antonakis, J. 2018. On doing relevant and rigorous experiments: Review and recommendations. Journal of Operations Management, 64(1): 19–40.

McGrath, J. E. 1981. Dilemmatics: The study of research choices and dilemmas. American Behavioral Scientist, 25(2): 179–210.

McNeish, D. 2018. Thanks coefficient alpha, we’ll take it from here. Psychological Methods, 23(3): 412–433.

Meyer, K., van Witteloostuijn, A., & Beugelsdijk, S. 2017. What is in a p ? Reassessing best practices for conducting and reporting hypothesis-testing research. Journal of International Business Studies, 48(5): 535–551.

Murphy, K. R., & Aguinis, H. 2019. HARKing: How badly can cherry picking and question trolling produce bias in published results? Journal of Business and Psychology, 34(1): 1–17.

Nielsen, B. B., Eden, L., & Verbeke, A. 2020a. Research methods in international business: Challenges and advances. In L. Eden, B. B. Nielsen, & A. Verbeke (Eds.), Research methods in international business, JIBS Special Collections : 3–41. Palgrave Macmillan.

Chapter   Google Scholar  

Nielsen, B. B., Welch, C., Chidlow, A., Miller, S. R., Aguzzoli, R., Gardner, E., Karafyllia, M., & Pegoraro, D. 2020b. Fifty years of methodological trends in JIBS: Why future IB research needs more triangulation. Journal of International Business Studies, 51(9): 1478–1499.

O’Cathain, A. 2010. Assessing the quality of mixed methods research: Towards a comprehensive framework. In A. Tashakkori, & C. Teddlie (Eds.), Sage handbook of mixed methods in social & behavioral research : 531–555 (2nd ed.). Sage.

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. 2016. Recommendation for creating better concept definitions in the organizational, behavioral, and social sciences. Organizational Research Methods, 19(2): 159–203.

Reeb, D., Sakakibara, M., & Mahmood, I. P. 2012. From the editors: Endogeneity in international business research. Journal of International Business Studies, 43(3): 211–218.

Schmidt, F. L., & Hunter, J. E. 1996. Measurement error in psychological research: Lessons from 26 research scenarios. Psychological Methods, 1(2): 199–223.

Shapiro, D. L., Kirkman, B. L., & Courtney, H. G. 2007. Perceived causes and solutions of the translation problem in management research. Academy of Management Journal, 50(2): 249–266.

Shaver, J. M. 2021. Evolution of quantitative research methods in strategic management. In I. M. Duhaime, M. A. Hitt, & M. A. Lyles (Eds.), Strategic management: State of the field and its future : 83–97. Oxford University Press.

Simon, H. 1996, 1969. The sciences of the artificial (3rd edition). MIT Press.

Tsui, A. S., & McKiernan, P. 2022. Understanding scientific freedom and scientific responsibility in business and management research. Journal of Management Studies, 59(6): 1604–1627.

Tung, R. L. 2023. To make JIBS matter for a better world. Journal of International Business Studies . https://doi.org/10.1057/s41267-022-00569-9 https://link.springer.com/article/10.1057/s41267-022-00569-9

Withers, M. C., & Li, C. H. 2021. Natural experiments in business research methods. In Bergh, D. D (Ed) The Oxford research encyclopedia of business and management. https://doi.org/10.1093/acrefore/9780190224851.013.302

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Acknowledgements

We thank Journal of International Business Studies ( JIBS ) Editor-in-Chief Rosalie L. Tung, Sjoerd Beugelsdijk, and a JIBS anonymous reviewer for highly constructive feedback on previous versions of our article.

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Aguinis, H., Bergh, D. & Molina-Azorin, J.F. Methodological challenges and insights for future international business research. J Int Bus Stud 54 , 219–232 (2023). https://doi.org/10.1057/s41267-022-00578-8

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Research methods in international business: The challenge of complexity

Lorraine eden.

1 Department of Management, Mays Business School, Texas A&M University, TAMU 4221, College Station, TX 77843-4221 USA

Bo Bernhard Nielsen

2 Discipline of International Business, The University of Sydney Business School, Abercrombie Building H70, Corner Abercrombie Street and Codrington St, Darlington, NSW 2006 Australia

3 Department of Strategy and Innovation, Copenhagen Business School, Kilevej 14, 2000 Frederiksberg, Denmark

International business (IB) research is designed to explore and explain the inherent complexity of international business, which arises from the multiplicity of entities, multiplexity of interactions, and dynamism of the global economic system. To analyze this complexity, IB scholars have developed four research lenses: difference, distance, diversity, and disparity. These four lenses on complexity have created not only unique research opportunities for IB scholarship but also unique research methodological challenges. We therefore view complexity as the underlying cause of the unique methodological challenges facing international business research. We offer several recommendations to help IB scholars embrace this complexity and conduct reliable, interesting, and practically relevant research.

Résumé

La recherche en international business (IB) est conçue pour explorer et expliquer la complexité inhérente aux affaires internationales qui découle de la multiplicité des entités, de la multiplexité des interactions et du dynamisme du système économique mondial. Pour analyser cette complexité, les chercheurs en IB ont développé quatre optiques de recherche - différence, distance, diversité et disparité - qui créent non seulement des opportunités de recherche uniques pour les chercheurs en IB, mais aussi des défis méthodologiques uniques de recherche. Par conséquent, nous considérons la complexité comme la cause sous-jacente des défis méthodologiques uniques auxquels est confrontée la recherche en international business . Nous proposons plusieurs recommandations pour aider les chercheurs en IB à appréhender cette complexité et à mener des recherches fiables, intéressantes et pertinentes sur le plan pratique.

La investigación en negocios internacionales está diseñada para explorar y explicar la complejidad inherente a los negocios internacionales, la cual surge de la multiplicidad de entidades, multiplejidad de interacciones y dinamismos del sistema económico global. Para analizar esta complejidad, los académicos de negocios internacionales han desarrollado cuatro lentes de investigación -diferencia, distancia, diversidad y disparidad- que crean no solamente oportunidades de investigación únicas para el conocimiento académico de negocios internacionales, pero también retos metodológicos de investigación únicos. Por lo tanto, vemos la complejidad como la causa subyacente de los retos metodológicos únicos enfrentados en la investigación de negocios internacionales . Ofrecemos varias recomendaciones para ayudar a los académicos de negocios internacionales a adoptar esta complejidad y llevar a cabo investigaciones confiables, interesantes y prácticamente relevantes.

A pesquisa em negócios internacionais (IB) é projetada para explorar e explicar a complexidade inerente aos negócios internacionais, que surge da multiplicidade de entidades, multiplexidade de interações e dinamismo do sistema econômico global. Para analisar essa complexidade, acadêmicos de IB desenvolveram quatro lentes de pesquisa - diferença, distância, diversidade e disparidade - que criam não apenas oportunidades de pesquisa exclusivas para a pesquisa em IB, mas também exclusivos desafios metodológicos de pesquisa. Portanto, vemos a complexidade como a causa subjacente dos desafios metodológicos únicos enfrentados pela pesquisa em negócios internacionais . Oferecemos várias recomendações para ajudar acadêmicos de IB a abraçar essa complexidade e conduzir pesquisas confiáveis, interessantes e relevantes na prática.

抽象

国际商务(IB)研究旨在探索和解释由实体多样性、互动多元复杂性和全球经济体系动态性引起的国际商业内在的复杂性。为了分析这种复杂性, IB学者开发了四个研究视角, 即差异、距离、多样化和不均衡视角, 这不仅为IB理论创造了独特的研究机会, 而且带来研究方法上独特的挑战。我们因此将复杂性视为国际商务研究所面临的独特的方法论挑战的根本原因。我们提出了一些建议, 以帮助IB学者拥抱这种复杂性并进行可靠的、有趣的和切实的研究。

INTRODUCTION

It is a well-accepted fact that high-quality research methods are a necessary building block for strong scholarship in international business (IB) research. Many scholars have written about the methodological challenges that can bedevil scholarship in IB and other disciplines and have recommended best practices for dealing with these challenges. For example, see the wide variety of methodology challenges discussed in Eden, Nielsen and Verbeke ( 2020 ) and recent papers by Aguinis and co-authors (Aguinis, Cascio & Ramani, 2017 ; Aguinis, Hill & Bailey, 2019 ; Aguinis, Ramani & Alabduljader, 2018 ; Bergh, Sharp, Aguinis & Li, 2017 ).

The new JIBS Point article by Aguinis, Ramani and Cascio ( 2020 ) follows in this tradition, providing a useful analysis of the “four most pervasive contemporary methodological choices faced by international business (IB) researchers.” Our interest lies in the unique aspects of IB research and thus our paper is designed to serve as a Counterpoint and complement to their JIBS Point article. We argue that IB research questions are designed to explore and explain the inherent complexity of the global economy, which is generated by three factors: multiplicity of entities (i.e., number and variety of actors, industries, countries, institutions, etc.), multiplexity of interactions (i.e., number and variety of ties or relationships among these entities), and dynamism over time (i.e., changing nature of the international business system). To analyze the complexity of the IB system, scholars have developed four lenses of research, which we refer to as the “four D’s” (difference, distance, diversity, and disparity). These four lenses on complexity have created unique research opportunities for IB scholars but have also presented unique research methodology problems. We therefore argue that complexity is the underlying cause of the unique methodological problems facing international business research.

Our Counterpoint article first highlights Aguinis et al.’s ( 2020 ) helpful advice for improving the quality of IB research and discusses some of the article’s limitations. We then turn to developing our thesis on the complexity of IB research, the four research lenses that can be used to analyze complexity, their resulting methodological problems, and proposed methodology solutions.

A BRIEF ASSESSMENT OF AGUINIS ET AL. ( 2020 )

Contributions.

Aguinis et al.’s ( 2020 ) article on challenges and recommended best practices in IB research methodology is a welcome addition to the literature on this topic. The authors identified the most pervasive methodological challenges faced by IB researchers by counting the self-reported research methodology problems in the 43 empirical articles published in the 2018 volume of the Journal of International Business Studies ( JIBS ). Using this method, Aguinis et al. ( 2020 ) identified four methodological challenges (percentage of JIBS articles in brackets): psychometrically deficient measures (73%), idiosyncratic samples or contexts (62%), less-than-ideal research designs (62%), and insufficient evidence about causal relations (8%). The authors explored each challenge and proposed some solutions.

The most frequently mentioned challenge (in almost three-quarters of the JIBS articles) was that the measures used were psychometrically deficient; i.g., the measures did not fully capture the construct or were not sufficiently reliable. Aguinis et al. ( 2020 ) proposed three solutions. IB scholars should: (1) determine whether the measure has been used previously to represent a different construct and, if so, demonstrate why their conceptualization is appropriate; (2) specify whether the construct is reflective or formative and, depending on the answer, apply the appropriate analytical technique; and (3) use multiple indicators to measure the construct.

The second and third challenges were reported in identical percentages of JIBS papers (62.2%), suggesting that JIBS authors coupled the two challenges together. Examples of the second challenge, idiosyncratic samples or contexts, included testing IB theories in a single country or market or during a particular time period. Solutions proposed by Aguinis et al. ( 2020 ) were to (1) treat the sample as an opportunity to go deeper, rather than as a limitation, and (2) choose unique or extreme samples or contexts. The third challenge, less-than-ideal research designs, involved questions such as multiple levels of analysis and common method variance. Recommended solutions were to (1) use Big Data to create unique insights and (2) leverage Big Data techniques to re-analyze currently available data.

The fourth challenge, insufficient evidence to infer causal relations, was reported by very few JIBS authors. Those who mentioned this issue referenced comments regarding distinguishing causality from correlation and the inability of current research methods to answer causality. To address this issue, Aguinis et al. ( 2020 ) proposed that JIBS authors use (1) quasi-experimental designs and (2) necessary-conditions analysis.

Limitations

The JIBS Point article by Aguinis et al. ( 2020 ) addresses important methodological issues. The article, however, suffers from at least three limitations, which we discuss below.

First, only one year of JIBS (2018) empirical articles was analyzed. While there is no reason to think that 2018 was an outlier year, there would have been several benefits to analyzing a longitudinal dataset. Longitudinal data allow for a more informed discussion of the limitations over time (and hence potential changes/evolutions) and provide potentially deeper insights into the importance of these limitations.

Table  1 provides some information on the general types of research methods employed by JIBS authors during the first 50 years of the journal. Of the 1265 empirical articles, nearly 30% (372 articles) were published in the most recent decade (2010–2019). Most of these 372 articles (86%) used quantitative methods (archival or survey); another 9% used qualitative methods; and the remainder (5%) used mixed methods. Clearly evident over the 50-year time period are the shifts in the relative importance of different research methods. Notable has been the growing importance of archival methods, which almost doubled from 37% as a proportion of all JIBS empirical papers in the 1970s to 62% in the 2010s, and the decline of survey methods, which fell by almost half (from 40% to 24%) of empirical papers over the same years. Papers using qualitative methods fell from 16% in the 1970s to a low of 3% in the 1990s and have now rebounded to 9% in the 2010s.

Table 1

Distribution of JIBS articles by research methodology, 1970–2019.

Source : Authors’ calculations based on data provided by Nielsen et al. ( 2020 )

Italicized numbers represent share of the total

a This table only includes JIBS publications using quantitative, qualitative, or mixed methods. The table excludes articles that are, for example, conceptual, theoretical, or editorial in nature.

It is therefore possible that examining one year rather than several years may have affected the relative shares of methods used and the resulting methodological challenges, or at least the frequencies of reports, identified in Aguinis et al. ( 2020 ). For example, the relatively low percentage given to challenge #4 (inference of causality) may have been due to the few survey papers in JIBS that year. Following the example of Brutus, Aguinis, and Wassmer ( 2013 ), which according to the authors was influential for their article methodologically, we conclude that at least five and preferably 10 years of data would have been helpful for understanding why JIBS authors identified particular research challenges and not others.

A second limitation is that the method used by Aguinis et al. ( 2020 ) was counting self-reports by JIBS authors. This is problematic for several reasons. First, the simple yardstick used (counting zero or one for whether the authors of a JIBS article mentioned a methods problem or not) is a coarse measure and not very informative. For example, it would have been useful to know whether, after having listed a methodological problem, the JIBS authors also explained whether and how they tried (or did not try) to address the problem. Second, the JIBS authors’ own assessment of the problem would have been helpful. Did they see the methodological challenge as material (i.e., could it have substantially affected the outcome of the paper) and, if so, did they assess what the likely impact would have been? Third, perhaps the JIBS authors may have gone further and identified in their paper why they had not addressed the challenge (e.g., they saw the issue as non-material, appropriate data did not exist at this point in time, or there was no method available to handle this particular problem). Fourth, a deeper analysis could have looked at whether there really was a problem or not, in other words, did the JIBS authors list too many or too few problems? Lastly, JIBS authors know they are expected to have a Discussion section where they discuss the limitations of their paper (e.g., Aguinis and his co-authors also follow this convention). Were the JIBS authors simply “checking the box” in their Limitations section? In sum, a comprehensive analysis of the research methodology problems in current JIBS articles would have benefitted from a much deeper assessment of the original JIBS articles. Given the focus on a single year and resulting limited number of articles (43), the “case study” approach (Aguinis et al., 2020 ) to analyzing JIBS methodological challenges falls somewhat short of meeting its goals.

A third and perhaps the most important limitation of Aguinis et al. ( 2020 ) from our perspective is that their four identified core research methodology issues are not unique to IB research. While the percentages may differ across disciplines (see their discussion regarding Brutus et al.’s ( 2013 ) assessment of management journal articles), the identified methodological problems and proposed solutions appear to be common across business and psychology journals rather than unique to IB research. The authors acknowledge this, noting that they used JIBS as a case study: “Secondly, our focus on recent JIBS articles is not intended to target this journal, or more broadly, the field of IB. For example, authors of articles published in Academy of Management Journal (AMJ), Strategic Management Journal (SMJ), Journal of Management (JOM), and Journal of Applied Psychology (JAP) have identified some of the challenges also referred to by JIBS authors” (Aguinis et al., 2020 ).

Self-reports by JIBS authors in 2018, as identified in Aguinis et al. ( 2020 ), suggest that IB research currently faces four major methodological challenges: measures, samples, research design, and causality. We applaud the authors’ efforts to address these important issues but have some concerns about the methods used in their paper and the lack of adequate attention to contextual influences resulting from the complexity of IB phenomena. Moreover, some of their challenges and solutions appear to be “micro” in nature, focusing on issues that may present major problems for scholars engaged in predominantly quantitative (survey) studies with particular psychometric properties (e.g., reflective versus formative measures and multiple versus single indicators to measure constructs). We conclude that their article makes a valuable contribution but should be treated with caution and recommend that IB scholars read both the JIBS Point and Counterpoint articles together.

Other Studies

For comparison purposes, we searched for other studies that have used methods similar to Aguinis et al. ( 2020 ) and Brutus et al. ( 2013 ) to identify methodology challenges relevant to IB research. We highlight two below and also acknowledge Andersen and Skaates ( 2004 ).

Peterson ( 2004 ) examined the research methods used in 124 international management (IM) articles published in three journals ( JIBS , AMJ, and Administrative Sciences Quarterly (ASQ) ) between 1990 and 1999. His analysis identified five methodological concerns in IM research: (1) non-representative or within-country samples, (2) limited data sources (only one or two countries), (3) lack of author diversity (one or two authors from the same country), (4) lack of examination of cross-cultural/national differences, and (5) excessive reliance on one research method (typically correlations and regressions), so that neither causality and nuances could be addressed. His proposed five solutions, respectively, were: (1) samples drawn from the whole country, (2) larger sample populations with more countries over at least 5–10 years, (3) cross-national research teams that meet periodically, (4) the use of standardized survey and research methods across countries, and (5) the use of multiple (mixed) research methods.

A second comparative study is Coviello and Jones ( 2004 ), which used content analysis to examine 55 articles on international entrepreneurship (IE) published in ten business journals (including JIBS ) between 1989 and 2002. The authors assessed the articles in terms of four methods issues: (1) time frame and content, (2) sample, (3) data collection and analysis, and (4) cross-national equivalence. Their key criticisms were that most articles involved static cross-country or cross-industry comparisons, had inconsistent definitions and measures of key variables, used idiosyncratic samples that led to results that were difficult to generalize, and did not capture complex processes well. Coviello and Jones ( 2004 ) argued that these methodological problems were inherent in the complexities involved in doing IE research. The authors concluded that IE scholars needed to take a multidisciplinary approach, adopt dynamic research designs that integrated positivist and interpretivist methodologies, and incorporate time as a key dimension.

Both Peterson ( 2004 ) and Coviello and Jones ( 2004 ) highlight similar complexities involved in doing IB research, despite their focus on different disciplines (management vs. entrepreneurship). Both articles stress that core methodological problems are caused by differences and diversities in cultures and contexts that are dynamic not static in nature. We concur with their assessment and go further to argue below that complexity is the underlying source of the unique methodological challenges faced by international business scholars .

THE COMPLEXITY OF IB RESEARCH

We of course agree with Aguinis et al. ( 2020 ) that IB researchers face many methodological problems and choices. Our interest lies, however, less in the commonalities of these problems with other disciplines and more with the unique methodological concerns that are specifically “IB”; i.e., caused by research questions and cross-border contexts typically studied by IB scholars and published in JIBS , some of which are highlighted in Peterson ( 2004 ) and Coviello and Jones ( 2004 ).

Complexity in IB Research

We start with a simple metaphor explaining why IB is different from mainstream disciplines like management and psychology. Eden ( 2008 ) suggested that a helpful way to understand IB research is to conceptualize a matrix where the columns are the disciplines or functional areas of business (e.g., management, entrepreneurship, finance) and the rows are the topics typically covered in these disciplines (e.g., markets, firm strategy, performance, international). IB research can therefore be viewed as the “international” row that cuts across the “discipline” columns.

Eden ( 2008 ) argued that JIBS researchers are boundary-spanners; they emphasize the adjective “international” over the noun of their particular discipline or university department. Implicit in this approach is the insight that IB researchers are not only engaged in studying business in cross-border contexts but also in cross-cultural and cross-disciplinary contexts. The domain of IB research is, in effect, a big umbrella covering the international/cross-border aspects of all business disciplines. Thus, IM and IE can be viewed as subfields of IB (see also discussions in Eden, Dai and Li ( 2010 ) on IM and IB and in Verbeke & Ciravegna ( 2018 ) on IE and IB).

The variety and breadth of research topics in the IB domain is therefore huge, ambitious, and challenging (Table  2 ). As a result, there is an inherent complexity to IB research that is different from domestically focused scholarship, and the research methodology challenges faced by IB researchers should not be simply conflated with methodological issues facing scholars in mainstream disciplines.

Table 2

The domain of international business studies.

Source : Eden ( 2008 : 3)

We believe there are three key sources to the complexity of IB research, which we illustrate in Figure ​ Figure1: 1 : multiplicity, multiplexity, and dynamism. The first source of complexity is the multiplicity (i.e., the number and variety) of entities (e.g., actors, industries, countries, contexts, cultures, institutions) in the global economic system. While often pictured as a dyad (home versus foreign), in reality most IB studies involve multiple actors in multiple countries in multiple contexts. Multiplicity creates both opportunities and problems for IB research; see, for example, the discussions in Buckley and Casson ( 2001 ), Peterson ( 2004 ), Coviello and Jones ( 2004 ), and Teagarden, Von Glinow and Mellahi ( 2018 ).

The complexity of international business research.

Multiplicity, which Buckley and Casson ( 2001 ) refer to as “combinatorial complexity”, can be addressed in many ways. Buckley and Casson recommend using parsimony and simplifying, rational-actor techniques such as real options and game theory; they provide several examples of how these techniques can be used to analyze problems such as mode of entry and location choice. Applying rational-actor economics to multiplicity has clear benefits but also some costs (Samuels, 1995 ). Other possible approaches focus more on how cross-border activities exacerbate the joint challenges of managing bounded rationality, unreliability, and investments in specific assets. Here conceptual tools from comparative institutional analysis and empirical tools such as fuzzy-set qualitative comparative analysis, as well as a variety of multi-level analysis tools, can be helpful (see Eden et al. ( 2020 ) for discussions of appropriate techniques).

The second factor contributing to complexity of the global economy and thus of IB research is the multiplexity of interactions (the number and variety of relationships and interdependencies) among these entities, which Buckley and Casson ( 2001 ) refer to as “organic complexity.” IB scholars have studied multiplexity for many years in contexts such as the MNE’s inter- and intra-organizational networks, buyer–supplier networks using lean production technologies, and international strategic alliances (Cuypers, Ertug, Cantwell, Zaheer & Kilduff, 2020 ). Multiplexity is created when there are “networks of networks” (D’Agostino & Scala, 2014 ), generating systemic problems such as cross-level effects, feedback loops, diffusion, and contagion. See, for example, Cardillo et al.’s ( 2013 ) analysis of the multiplexity of the international air transportation network and Gemmetto et al.’s ( 2016 ) study of the relationships and interdependencies of world trade flows; both papers use network theory to analyze the multiplexity of cross-border flows.

Buckley and Casson ( 2001 ) argues that rational actor approaches can be used to address multiplexity, pointing to information costs, dynamic optimization, real options, and game theory as appropriate techniques for handling the dynamism of the IB system. Other approaches to multiplexity include fuzzy-set qualitative comparative analysis, multi-level analysis techniques, and qualitative research (Eden et al., 2020 ; D’Agostino & Scala, 2014 ; Ferriani, Fonti & Corrado, 2012 ).

The third factor generating complexity for IB research is the global economy’s inherent dynamism (dynamics over time). By dynamism, we mean the various ways that time and history can affect a system such as trends, hysteresis, business cycles, crises, and other instabilities. The dynamism of the international business system generates risk, uncertainty, volatility, and ambiguity, providing both challenges and opportunities for decision-makers. Many scholars have stressed the importance of history and time to IB research (e.g., Jones & Khanna, 2006 ; Coviello & Jones, 2004 ; Eden, 2009 ). Bringing dynamism into IB research can be done using a variety of research methods, including longitudinal case studies, real options approaches, event studies, and event history analysis. Each of these approaches also raises its own methodology challenges, some of which are discussed in Eden et al. ( 2020 ).

Four Research Lenses on Complexity

To analyze the complexity of the international business system, IB scholars have developed four research lenses, which we refer to as the “four D’s” (difference, distance, diversity, and disparity) and illustrate in Figure ​ Figure1. 1 . The first – “Difference” – involves the relatively simple matter of comparing how “here” is different from “there” (e.g., cross-border comparisons of domestic with foreign). Early research in IB (e.g., the Ownership-Location-Internalization (OLI) paradigm) focused on the differences that businesses faced when they crossed national borders and one still regularly hears IB research referred to as “cross-border” or “cross-cultural” studies. The focus of “Difference” is on the border as a metaphor for separating “here” (the known or us) from “there” (the unknown or them). Research on topics varying from offshore production to liability of foreignness to insiders and outsiders all share this crossing-a-border “Difference” lens.

“Distance” became a second important research lens for IB scholars after the introduction of new datasets and metrics that could be used to measure the cultural and institutional distances between countries. Early users of Hofstede’s ( 1980 ) cultural dimensions, for example, explored the impact of cultural distance on foreign mode of entry (e.g., Kogut & Singh, 1988 ). Distance studies, using these new datasets and metrics, have been a dominant theme of IB research for nearly 30 years (see reviews in Beugelsdijk, Ambos & Nell ( 2018 ) and Maseland, Dow & Steel ( 2018 )).

“Diversity” – the third “D” – is a newer focus of IB researchers interested in exploring, for example, varieties of capitalism and variations within and across countries (see also Stahl, Tung, Kostova & Zellmer-Bruhn, 2016 ). Diversity pays attention to the multiplicity of actors and networks and the multiplexity of their interactions. Diversity is inherent in multiplexity and may involve new research metrics and methods. Dai, Eden and Beamish ( 2013 ), for example, show how Coulombe’s Law can be used to calculate the dynamic exposure faced by a foreign subsidiary surrounded by multiple war zones of different sizes at different distances and points of time. Peterson, Arregle and Martin ( 2012 ) provides a useful introduction to multilevel models that can be used to analyze diversity issues.

We believe that the fourth “D” – “Disparity” – is on the horizon and will become an important topic for IB researchers in the 2020s and 2030s. The call for IB researchers to engage more with global societal challenges (Buckley, Doh & Benischke, 2017 ), the growing importance of the new group Responsible Research in Business and Management ( http://www.rrbm.network ), and the launch of the Journal of International Business Policy , all suggest more attention is being paid by IB scholars to the massive inequalities that exist across and within countries. The current global pandemic caused by COVID-19 is likely to exacerbate these cross-country disparities. We predict that more IB research in the future will examine the role that international business plays in society, in both ameliorating and exacerbating disparity and inequality, bringing their own research methodology challenges (Schlegelmilch & Szöcs, 2020 ; Crane, Henriques & Husted, 2018 ).

We therefore conclude that complexity – generated by the multiplicity of entities, multiplexity of interactions, and dynamism of the global economy - is the underlying cause of the unique methodological challenges facing international business research. The four lenses on complexity – difference, distance, diversity, and disparity – offer unique research challenges and opportunities for IB scholars and, as a result, have also presented them with unique research methodology problems, to which we now turn.

COPING WITH THE COMPLEXITY OF IB RESEARCH

We view complexity as the keyword that best captures IB research; that is, what it means to put the adjective “international” together with the noun “business” in the matrix that defines the “IB” field. Below we discuss the implications of complexity for the methodology challenges facing IB scholars. We organize these challenges according to the timeline of a typical IB research process, building on Nielsen, Eden and Verbeke ( 2020 ): (1) problem definition and research question, (2) research design and data collection, and (3) data analysis and interpretation of results. In each phase, we focus on the complexity issues that are prevalent and/or unique to IB research, the methodology challenges they pose, and recommend possible solutions (see Figure ​ Figure1 1 ).

Phase 1: Problem Definition and Research Question

In Phase 1, the researcher or research team must identify and define the problem and question(s) that will drive the project. Here, we see at least three methodological challenges.

Defining the research problem

IB requires attention to both the similarities and differences between and across domestic and foreign operations at multiple levels of analysis (e.g., firm, industry, country). Isolating the international (cross-border) aspects of a study requires a deep understanding of domestic and foreign environments. Thus, both the multiplicity of actors and multiplexity of interactions create complexity in defining the research problem. We suggest that looking at the research problem through the lenses of the “four D’s” (difference, distance, diversity, and disparity) can provide an fruitful avenue for attending to the complex set of issues across multiple contextual dimensions, including setting, unit, location, and time.

The (non)equivalency of concepts and theories used in different contexts

Much IB research involves applying “standard” theories (e.g., internalization, transaction cost economics, resource-based view) to particular types of firms. However, the assumptions of these theories and their applicability are likely to vary across countries. IB scholars need to identify and account explicitly for contextual influences and their potential impacts on the design and interpretation of outcomes of their study. Contextual issues are critical for determining the boundaries within which particular theories may be applicable. Studies of state ownership, for example, may yield very different results when the state-owned multinationals are from China, Norway or Brazil, given the different institutional contexts of these countries. Once again, an explicit focus on the sources of complexity may help IB researchers discern how, why, where, and when concepts and theories are equivalent (or not) in different contexts.

Promising too much and delivering too little

While most scholars start with a “big” research question (e.g., how distance or diversity affects a particular MNE strategy), in practice, their empirical study is much more narrowly defined. IB scholars may end up overestimating the generalizability of their results, leading to exaggerated claims that “promise too much.” Selection of the research question should drive the data collection and choice of methodology stages, and the way the results are reported and interpreted, not the other way around.

Phase 2: Research Design and Data Collection

In the second stage where researchers are engaged in research design and data collection, there are at least three core methodological challenges.

Appropriateness of the sample

IB scholars typically prefer to use data from secondary sources such as national and international (e.g., US and UN) statistical agencies and private firms (e.g., Thomson Reuters, Standard & Poor’s). However, particularly in developing countries, such data sources are either not available or are often of questionable quality. Moreover, IB researchers often assume implicitly that all sampled entities within-country share the same characteristics, with differences existing only across countries. This assumption may be wishful thinking as differences within countries (especially between rural and city areas in developing countries) may be larger than across countries, as noted by Peterson ( 2004 ). When the samples are inadequate, of course, the results will be problematic. Aguinis et al. ( 2020 ) identified idiosyncratic samples and contexts as a methodological concern in 62% of their sampled JIBS articles. We contend that a stronger focus on understanding the types of complexity during data collection may help prevent inadequate sampling in IB studies.

Appropriateness of the sample size

Typically, studies that examine the impact of independent variable X on the dependent variable Y must hold constant other variables that can also affect Y. Less attention is paid, however, to X itself. In an international context differences in X across countries may have many facets. For example, studying the influence of institutional distance (X) on the MNE’s mode of entry choice (Y) requires unbundling institutional distance into different components, which may warrant a large sample size or more careful sample selection.

Avoiding non-sampling errors

Large multi-country datasets constructed from responses to governmental and private surveys are attractive to IB researchers because these datasets offer the opportunity to test IB research questions on much larger cross-country and cross-cultural samples. These datasets however can be problematic for IB research. First, more often the “breadth” (number of countries and number of constructs) of multi-country/culture surveys far exceeds their “depth” (number of years). Many may be single year surveys, raising reliability issues. Second, multi-country datasets – even when constructed with care – may be prone to non-sampling errors. Low measure reliability, for example, can arise from differences in assessment methods used “on the ground” across countries. Differences in how various cultures understand different constructs (e.g., what “gender equality” means) are also a problem. To this end, Chidlow, Ghauri, Yeniyurt and Cavusgil ( 2015 ) reported that establishment of translation equivalence in cross-cultural studies remains sparse with regards to whether (a) the instrument used to collect the required data is translated appropriately across different cultures and (b) the data collection procedures are comparable across different cultures. A third challenge is that IB researchers may be either unaware (or choose to ignore) changes in methods and sources used by national and international agencies to collect and publish their datasets. Lacking in-depth knowledge of a dataset raises the likelihood of its misuse and misinterpretation of the results.

In sum, non-sampling errors may bedevil IB research simply because IB research questions do not “travel well” cross-nationally and cross-culturally due to multiplicity, multiplexity, and dynamism. One solution to the problem of possible measurement non-equivalence is to test for this issue before using the datasets. Nielsen et al. ( 2020 ) provides examples of statistical methods that can test for measurement equivalence on a cross-national/cultural basis. Aguinis et al. ( 2020 ) provides more generic examples of how data collection and research design challenges may be dealt with; for example, they focus on the potential virtues of Big Data, though such approaches should be used carefully so they do not confound rather than resolve non-sampling errors in IB research.

Phase 3: Data Analysis and Interpretation of Results

IB scholars also face special issues when they are engaged in data analysis and interpretation of results. We briefly discuss three research methodology challenges which can be added to the more general issue of establishing causality (across contexts, levels, and time) raised by Aguinis et al. ( 2020 ).

Addressing anomalies and inconsistencies

Outliers and other anomalies and inconsistencies may be more prevalent in multi-country than in single country studies due to the complexity of IB research. Rare events and asymmetric, long-tailed distributions may be more prevalent in international settings, necessitating research methods designed to handle these anomalies (Andriani & McKelvey, 2007 ). For instance, ignoring the “elephant in the room” (e.g., the dominance of one country such as China or the United States in a multi-country dataset) can lead to erroneous conclusions based on Gaussian averages (e.g., about the average scale and scope of internationalization). Moreover, as datasets span multiple countries and contexts – often relying on combining data sources from different entities and countries – the likelihood of errors due to anomalies and inconsistencies in data collection methods, cleaning, and handling, including translational and equivalence issues, increases. IB researchers must take appropriate steps to correct for such biases, for example, by using investigator triangulation  ex ante  during data collection and  ex post  during analysis and reporting (Nielsen et al., 2020 ).

Choosing the level(s) of theory, data, and analysis

IB studies, as we have stressed above, involve multiplicity and multiplexity. They are typically not only multi-country and multi-context but also multi-level. Employees are nested (and may be cross-nested) within subunits of an MNE (e.g., parent, regional headquarters, plants, branches, subsidiaries); the MNE itself is cross-nested within multiple national and institutional contexts depending on its global footprint. Thus, studying an MNE – let alone a comparison across MNEs – is an exercise in studying and understanding multi-level heterogeneity (individual, plant, firm, industry, country) as well as cross-nested embeddedness at each of these levels (Nielsen & Nielsen, 2010 ). Not surprisingly, determining the “right” level or levels of theory, data, and analysis needed to address a particular research question is not easy. An extension of this research problem arises from ecological fallacies where a construct developed for use at one level of analysis (e.g., country) is used at a different level (e.g., firm), without attention paid to the possible consequences. The “four D’s” may provide useful lenses through which to examine the multiplicity and multiplexity inherent in issues of levels of theory, data, and analysis, that give rise to additional layers of interdependence and nesting.

Avoiding personal bias in interpreting and reporting results

We all “see through our own lenses.” IB researchers, given their interest in the four D’s, are likely to be more contextually aware than domestically focused but are still likely to suffer from personal and institutional biases. Working with diverse teams of scholars from other countries, cultures, and disciplines can help reduce the influence of personal biases. Multi-country/cultural research teams can also provide benefits to IB research by improving the ability of concepts and theories to “travel” across countries, as argued in Peterson ( 2004 ).

CONCLUSION: WORDS TO LIVE BY

We agree with Aguinis et al. ( 2020 ) that IB scholarship suffers from methodological challenges. IB research, by its nature, involves a high degree of complexity generated by the multiplicity, multiplexity, and dynamism of the global economy. IB scholars can use the four D’s (difference, distance, diversity, and disparity) as useful lenses for understanding and analyzing this complexity. Complexity, of course, is one of the reasons that so many scholars study IB research questions but it also brings a set of methodological challenges unique to IB research.

We end with four pieces of advice that we hope provide useful guidance for IB researchers. We note that these guiding principles are complementary to the solutions proposed in Aguinis et al. ( 2020 ) and to our methodology recommendations above.

Learn to Live with (and Embrace) Complexity in Research Design

Complexity is a word that strikes fear and dread into the heart of most researchers; the more complex the problem, the more difficult the research tasks that lie ahead. We argue that IB researchers must learn to live with (and embrace) complexity. They must be comfortable with the multiplicity, multiplexity, and dynamism that characterize the global economy. Deconstructing a research question to examine its complexity through the lens of one or more of the four D’s (difference, distance, diversity, and disparity) is, we argue, critically important for developing interesting, useful, and impactful research. Using these lenses can help the IB researcher understand how multiple parameters affect his or her variable(s) of interest, often in non-linear and interdependent ways. As a result, relying on secondary data sources and conventional research methods such as OLS regression are likely to be insufficient or inappropriate to understand the complexity of IB research. Rather, embracing complexity naturally leads to more experimental research designs, as well as mixed methods, and/or multilevel analyses. Research designs that explicitly acknowledge complexity are likely to better answer the “big” questions that IB faces now and in the future.

Use Triangulation Actively to Increase Rigor and Relevance

Looking at a phenomenon or issue from multiple angles – not the least methodological – can address the biases, errors, and limitations introduced by any single approach (Denzin, 1978 ; Jick, 1979 ). Most of the IB-specific challenges we have raised above can be directly addressed by incorporating various types of triangulation strategies into the research design. For instance, theoretical triangulation may lead to new research questions by juxtaposing different theoretical perspectives. Similarly, data source and data collection triangulation may be seen as “an opportunity to go deeper, rather than as a limitation” (Aguinis et al., 2020 ) while also increasing sample reliability and reducing non-equivalence biases. Analytical triangulation helps ensure validity and reliability of results by comparing and contrasting results using multiple analytical techniques. Investigator triangulation may reduce personal biases in both data collection, analysis, and interpretation processes (Nielsen et al., 2020 ). Indeed, we would argue that the four D’s (difference, distance, diversity, and disparity) may best be attended to by carefully building triangulation into the research design process.

Exercise Due Diligence and Good Judgment

IB researchers should spend time, up front, understanding their research question and their unit of analysis, mapping and graphing the hypothesized relationships among their variables, and taking account of previously theorized relationships. Investment in building a thorough understanding of the research problem will help point the way to the most appropriate research method(s) and technique(s) for tackling the problem. Rules of thumb as to what constitutes an “acceptable” methodological approach are a poor substitute for the due diligence necessary to enable the researcher to exercise his or her good scholarly judgment. This piece of advice also requires IB researchers to have a good command of the available different research methods, of where they work well and where they do not.

Engage in Ethical and Responsible Research Practices

There have been many articles on best practices in responsible research, including several by Herman Aguinis that are particularly appropriate for IB researchers (Aguinis et al., 2017 , 2018 , 2019 ; Bergh et al., 2017 ). In addition, Anne Tsui and colleagues have been actively encouraging business and management scholars to join RRBM (Responsible Research in Business and Management; https://www.rrbm.network ) and adopt RRBM best practices for their research. The editors of JIBS have also led the way for many years in articulating best ethical and responsible practices for IB research, e.g., through the AIB Journals Code of Ethics, JIBS editorials at https://www.palgrave.com/gp/journal/41267/volumes-issues/editorials , and the new JIBS Special Collections books, in particular, Research Methods in International Business (Eden et al., 2020 ). We conclude that “ethical” and “responsible” are good words to live by. Words that when practiced by the global community of IB scholars will build knowledge for a more prosperous, just, and sustainable world.

ACKNOWLEDGEMENTS

We thank Alain Verbeke and Stewart Miller for helpful comments on earlier drafts of this paper.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Accepted by Alain Verbeke, Editor-in-Chief, 4 September 2020. This article was single-blind reviewed.

Contributor Information

Lorraine Eden, Email: ude.umat@nedel .

Bo Bernhard Nielsen, Email: [email protected] .

• Aguinis H, Cascio WF, Ramani RS. Science’s reproducibility and replicability crisis: International business is not immune. Journal of International Business Studies. 2017; 48 (6):653–663. doi: 10.1057/s41267-017-0081-0. [ CrossRef ] [ Google Scholar ]
• Aguinis H, Hill NS, Bailey JR. Best practices in data collection and preparation: Recommendations for reviewers, editors, and authors. Organizational Research Methods. 2019 doi: 10.1177/1094428119836485. [ CrossRef ] [ Google Scholar ]
• Aguinis H, Ramani RS, Alabduljader N. What you see is what you get? Enhancing methodological transparency in management research. Academy of Management Annals. 2018; 12 (1):83–110. doi: 10.5465/annals.2016.0011. [ CrossRef ] [ Google Scholar ]
• Aguinis H, Ramani RS, Cascio WF. Methodological practices in international business research: An after-action review of challenges and solutions. Journal of International Business Studies. 2020 doi: 10.1057/s41267-020-00353-7. [ CrossRef ] [ Google Scholar ]
• Andersen PH, Skaates MA. Ensuring validity in qualitative international business research. In: Marschan-Piekkari R, Welch C, editors. Handbook of qualitative research methods for international business. Cheltenham: Edward Elgar; 2004. pp. 464–485. [ Google Scholar ]
• Andriani P, McKelvey B. Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws. Journal of International Business Studies. 2007; 38 :1212–1230. doi: 10.1057/palgrave.jibs.8400324. [ CrossRef ] [ Google Scholar ]
• Bergh DD, Sharp BM, Aguinis H, Li M. Is there a credibility crisis in strategic management research? Evidence on the reproducibility of findings. Strategic Organization. 2017; 15 (3):423–436. doi: 10.1177/1476127017701076. [ CrossRef ] [ Google Scholar ]
• Beugelsdijk S, Ambos B, Nell PC. Conceptualizing and measuring distance in international business research: Recurring questions and best practice guidelines. Journal of International Business Studies. 2018; 49 (9):1113–1137. doi: 10.1057/s41267-018-0182-4. [ CrossRef ] [ Google Scholar ]
• Brutus S, Aguinis H, Wassmer U. Self-reported limitations and future directions in scholarly reports: Analysis and recommendations. Journal of Management. 2013; 39 (1):48–75. doi: 10.1177/0149206312455245. [ CrossRef ] [ Google Scholar ]
• Buckley PJ, Casson M. Strategic complexity in international business. In: Rugman AM, Brewer TL, editors. The Oxford handbook of international business. 1. Oxford: Oxford University Press; 2001. pp. 88–126. [ Google Scholar ]
• Buckley PJ, Doh JP, Benischke MH. Towards a renaissance in international business research? Big questions, grand challenges, and the future of IB scholarship. Journal of International Business Studies. 2017; 48 (9):1045–1064. doi: 10.1057/s41267-017-0102-z. [ CrossRef ] [ Google Scholar ]
• Cardillo A, Gomez-Gardenes J, Zanin M, Romance M, Popo D, del Pozo F, Boccaletti S. Emergence of network features from multiplexity. Scientific Reports, Nature Research. 2013; 3 (1344):1–6. doi: 10.1038/srep013441. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chidlow A, Ghauri P, Yeniyurt S, Cavusgil ST. Establishing rigor in mail-survey procedures in international business research. Journal of World Business. 2015; 50 (1):26–35. doi: 10.1016/j.jwb.2014.01.004. [ CrossRef ] [ Google Scholar ]
• Coviello NE, Jones MV. Methodological issues in international entrepreneurship research. Journal of Business Venturing. 2004; 19 (4):485–508. doi: 10.1016/j.jbusvent.2003.06.001. [ CrossRef ] [ Google Scholar ]
• Crane A, Henriques I, Husted BW. Quants and poets: Advancing methods and methodologies in business and society research. Business and Society. 2018; 57 (1):3–25. doi: 10.1177/0007650317718129. [ CrossRef ] [ Google Scholar ]
• Cuypers IRP, Ertug G, Cantwell J, Zaheer A, Kilduff M. Making connections: Social networks in international business. Journal of International Business Studies. 2020; 51 :714–736. doi: 10.1057/s41267-020-00319-9. [ CrossRef ] [ Google Scholar ]
• D’Agostino G, Scala A, editors. Networks of networks: The last frontier of complexity. Cham: Springer; 2014. [ Google Scholar ]
• Dai L, Eden L, Beamish P. Place, space, and geographic exposure: Foreign subsidiary survival in conflict zones. Journal of International Business Studies. 2013; 44 (6):554–578. doi: 10.1057/jibs.2013.12. [ CrossRef ] [ Google Scholar ]
• Denzin, N. K. (Ed.) 1978. Triangulation: A case for methodological evaluation and combination. In Sociological methods: A sourcebook (pp. 339–357). New York, NY: McGraw-Hill.
• Eden L. Letter from the editor-in-chief. Journal of International Business Studies. 2008; 39 (1):1–7. doi: 10.1057/palgrave.jibs.8400336. [ CrossRef ] [ Google Scholar ]
• Eden L. Letter from the Editor-in-Chief: Time in international business. Journal of International Business Studies. 2009; 40 (4):535–538. doi: 10.1057/jibs.2009.5. [ CrossRef ] [ Google Scholar ]
• Eden L, Dai L, Li D. International business, international management, international strategy: What’s in a name ? International Studies of Management and Organization. 2010; 40 (4):54–68. doi: 10.2753/IMO0020-8825400405. [ CrossRef ] [ Google Scholar ]
• Eden L, Nielsen BB, Verbeke A, editors. Research methods in international business. JIBS Special Collections. London: Palgrave Macmillan; 2020. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Ferriani S, Fonti F, Corrado R. The social and economic bases of network multiplexity: Exploring the emergence of multiplex ties. Strategic Organization. 2012; 11 (1):7–34. doi: 10.1177/1476127012461576. [ CrossRef ] [ Google Scholar ]
• Gemmetto V, Squartini T, Picciolo F, Ruzzenenti F, Garlaschelli D. Multiplicity and multireciprocity in directed multiplexes. Physical Review. 2016; 94 (042316):1–20. doi: 10.1103/physreve.94.042316. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hofstede G. Culture’s consequences: International differences in work-related values. Beverly Hills: Sage; 1980. [ Google Scholar ]
• Jick TD. Mixing qualitative and quantitative methods: Triangulation in action. Administrative Science Quarterly. 1979; 24 (4):602–611. doi: 10.2307/2392366. [ CrossRef ] [ Google Scholar ]
• Jones G, Khanna T. Bringing history (back) into international business. Journal of International Business Studies. 2006; 37 (4):453–468. doi: 10.1057/palgrave.jibs.8400198. [ CrossRef ] [ Google Scholar ]
• Kogut B, Singh H. The effect of national culture on the choice of entry mode. Journal of International Business Studies. 1988; 19 (3):411–432. doi: 10.1057/palgrave.jibs.8490394. [ CrossRef ] [ Google Scholar ]
• Maseland R, Dow D, Steel P. The Kogut and Singh national cultural distance index: Time to start using it as a springboard rather than a crutch. Journal of International Business Studies. 2018; 49 (9):1154–1166. doi: 10.1057/s41267-018-0183-3. [ CrossRef ] [ Google Scholar ]
• Nielsen BB, Nielsen S. A multilevel approach to understanding the multinationality–performance relationship. In: Devinney TM, Pedersen T, Tihanyi L, editors. The past, present and future of international business and management. Bingley: Emerald Group Publishing Limited; 2010. pp. 527–557. [ Google Scholar ]
• Nielsen BB, Eden L, Verbeke A. Research methods in international business: Challenges and advances. In: Eden L, Nielsen BB, Verbeke A, editors. Research methods in international business, JIBS Special Collections. London: Palgrave Macmillan; 2020. pp. 3–41. [ Google Scholar ]
• Nielsen BB, Welch C, Chidlow A, Miller S, Aguzzoli R, Gardner E, Karafyllia M, Pegoraro D. 50 years of methodological trends in JIBS : Why future IB research needs more triangulation. Journal of International Business Studies. 2020 doi: 10.1057/s41267-020-00372-4. [ CrossRef ] [ Google Scholar ]
• Peterson MF, Arregle J-L, Martin X. Multilevel models in international business research. Journal of International Business Studies. 2012; 43 (5):451–457. doi: 10.1057/jibs.2011.59. [ CrossRef ] [ Google Scholar ]
• Peterson RB. Empirical research in international management: A critique and future agenda. In: Marschan-Piekkari R, Welch C, editors. Handbook of qualitative research methods for international business. Cheltenham: Edward Elgar; 2004. pp. 25–55. [ Google Scholar ]
• Samuels WJ. Some thoughts on multiplicity. Journal of Economic Methodology. 1995; 2 (2):287–291. doi: 10.1080/13501789500000020. [ CrossRef ] [ Google Scholar ]
• Schlegelmilch BB, Szöcs I. Rethinking business responsibility in a global context. Cham: Springer; 2020. [ Google Scholar ]
• Stahl GK, Tung RL, Kostova T, Zellmer-Bruhn M. Widening the lens: Rethinking distance, diversity, and foreignness in international business research through positive organizational scholarship. Journal of International Business Studies. 2016; 47 (6):621–630. doi: 10.1057/jibs.2016.28. [ CrossRef ] [ Google Scholar ]
• Teagarden MB, Von Glinow MA, Mellahi K. Contextualizing international business research: Enhancing rigor and relevance. Journal of World Business. 2018; 53 (3):303–306. doi: 10.1016/j.jwb.2017.09.001. [ CrossRef ] [ Google Scholar ]
• Verbeke A, Ciravegna L. International entrepreneurship research versus international business research: A false dichotomy? Journal of International Business Studies. 2018; 49 (4):387–394. doi: 10.1057/s41267-018-0154-8. [ CrossRef ] [ Google Scholar ]

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In This Article Expand or collapse the "in this article" section Case Study Methods in International Relations

Introduction, textbooks and monographs.

• What Is a Case Study?
• Case Study Design
• Case Studies and Understanding Concepts
• Case Studies, Theory Testing, and Theory Generation
• Case Studies and Causality
• Case Studies and Process-Tracing
• Case Studies and Interpretive Research

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Case Study Methods in International Relations by Christopher K. Lamont LAST REVIEWED: 29 November 2017 LAST MODIFIED: 29 November 2017 DOI: 10.1093/obo/9780199743292-0225

Case studies are perhaps the most widely used research design in international relations (IR). Across the discipline’s subfields of security studies, international political economy, foreign policy analysis, and international political theory, case studies have become ubiquitous. As such, it is not surprising that case studies have been the subject of debate as to what constitutes a case study, how to conduct or design case studies, the potential contribution of case studies to general, or case specific, knowledge in the field of IR, and of course, how to evaluate case studies. To be sure, debates on case study research in IR mirror the field’s methodological pluralism and broader debates on methodology. Case studies have been widely used by interpretivist and positivist scholars of IR alike. It is for this reason that literature on case study design contains scholarship that on the one hand aims to emphasize how case study design, and case selection strategies, can help generalize findings beyond specific cases to literature on the other hand that emphasizes the historic, contextual and descriptive richness of case studies. However, it will become apparent in this bibliography that most scholarship that deals explicitly with the case study method has done so from a positivist perspective on the social sciences. Indeed, each methodological standpoint advances distinct claims as to the purpose and contribution of case studies to IR. Therefore, as we will see in the overview of scholarship presented here within this bibliography, early methodological literature on case studies in IR, political science, and comparative politics, attempted to evaluate the utility, or contribution, of case studies along the lines of the extent to which case studies could contribute to causal explanation and generalizability. However, it is also the case that today, as in the past, IR scholarship that utilizes case study design cuts across both methodological traditions as not all scholars of IR deploy case studies for the purpose of explanation. Indeed, although there has been much discussion in the literature on case study design with an aim to maximize causal inference within the positivist tradition, this bibliography will highlight scholarship on case studies that includes both positivist debates on causality, inference, and generalization, and scholarship that embraces case studies as a means of producing deeper context-dependent knowledge on a given topic, notion, or concept. The first sections will present general texts and journals on case study research relevant to IR. The following texts are general textbooks or monographs on case study research design and methods. While there is a growing body of methodological scholarship that focuses on case studies in the social science that makes reference to research in IR, most of the texts below have a broader disciplinary focus. This is because debates over case study methods have tended to center around wider philosophy of social science debates on causal inference and the study of the social world.

In recent years the growing popularity of case studies in international relations (IR) has coincided with a growth in textbooks and monographs that examine case study methods. These range from broad texts on research methods in the social sciences ( Blatter and Haverland 2012 , Burton 2000 ) that sometimes contain collections of essays on case study design and research ( Gomm, et al. 2000 ) or provide examples of case studies drawn from a wide range of cognate disciplines ( Yin 2004 ). For scholars of IR, the most discipline-specific broader text is Case Studies and Theory Development in the Social Sciences ( George and Bennett 2005 ), while Qualitative Methods in International Relations ( Klotz and Prakash 2008 ) also contains contributions that explicitly address case study methods, or methods such as process tracing, that are relevant to case study research. Also of note are texts that provide readers with guidance on how to conduct case studies ( Thomas 2016 , Yin 2014 ). An example of a text that both reflects on case study methods and also provides practical how-to guidance is Case Study Research ( Gerring 2017 ).

Blatter, Joachim, and Markus Haverland. Designing Case Studies: Explanatory Approaches in Small-N Research . New York: Palgrave Macmillan, 2012.

DOI: 10.1057/9781137016669

This text presents an overview of case study methods that makes the case for a pluralist case study epistemology. Blatter and Haverland explore case study design in the context of co-variational analysis, causal process tracing, and congruence analysis.

Burton, Dawn. Research Training for Social Scientists . London: SAGE, 2000.

DOI: 10.4135/9780857028051

This is a broad text on research methods in the social sciences that contains specific chapters relevant to case study research that provide a basic introduction to case study research. See in particular chapter 16, which sets out uses of case studies in social science research.

George, Alexander L., and Andrew Bennett. Case Studies and Theory Development in the Social Sciences . Cambridge, MA: MIT, 2005.

This text provides an in-depth assessment of case study research design for researchers whose focus is on designing case studies for theory testing. While the first part of the book provides an in-depth overview of social science debates on the merits of case studies, the second part provides a guide for researchers to conduct case study research. This text draws upon examples from both international relations and political science research.

Gerring, John. Case Study Research: Principles and Practices . 2d ed. Cambridge, UK: Cambridge University Press, 2017.

This textbook provides an overview of case study research design that primarily addresses strategies for maximizing causal inference in case study research, but also provides an overview of descriptive case studies. This text contains a practical guide to doing case study research and analyzing findings.

Gomm, Roger, Martyn Hammersley, and Peter Foster, eds. Case Study Methods: Key Issues, Key Texts . London: SAGE, 2000.

This is a general collection of essays that addresses core elements of case study design and research. It contains numerous contributions on case studies and generalizability and case studies and theory. The latter includes a contribution by Harry Eckstein on case study research in political science.

Klotz, Audie, and Deepa Prakash, eds. Qualitative Methods in International Relations: A Pluralist Guide . New York: Palgrave MacMillan, 2008.

This volume contains numerous useful contributions relevant to case study methods that range from Klotz’s chapter on case selection to a contribution on process tracing by Jeffrey Checkel.

Thomas, Garry. How to Do Your Case Study . 2d ed. London: SAGE, 2016.

This is an accessible guide for case study research whose primary audience is students. It begins with defining case studies and strategies for case design before presenting a practical guide to carrying out case study research.

Yin, Robert K. The Case Study Anthology . London: SAGE, 2004.

This collection of essays includes examples of case studies drawn from IR, political science, sociology, and other related disciplines.

Yin, Robert K. Case Study Research: Design and Methods . 5th ed. London: SAGE, 2014.

This textbook provides a comprehensive overview of case study research. Starting from providing definitions for case studies, this textbook goes on to provide a practical guide for students to conduct their own case studies.

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What the Case Study Method Really Teaches

• Nitin Nohria

Seven meta-skills that stick even if the cases fade from memory.

It’s been 100 years since Harvard Business School began using the case study method. Beyond teaching specific subject matter, the case study method excels in instilling meta-skills in students. This article explains the importance of seven such skills: preparation, discernment, bias recognition, judgement, collaboration, curiosity, and self-confidence.

During my decade as dean of Harvard Business School, I spent hundreds of hours talking with our alumni. To enliven these conversations, I relied on a favorite question: “What was the most important thing you learned from your time in our MBA program?”

• Nitin Nohria is the George F. Baker Jr. Professor at Harvard Business School and the former dean of HBS.

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Designing and Conducting Case Studies in International Business Research

2004, Handbook of Qualitative Research Methods for International Business

5. Designing and Conducting Case Studies in International Business Research Pervez Ghauri INTRODUCTION A case study is not a methodological choice, but rather a choice of object to be studied. Case studies can be both quantitative and qualitative. In this chapter, I deal ...

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The Qualitative Report

Tiia Vissak

Pervez Ghauri

Qualitative case study research has frequently been criticised for being less systematic and objective than other approaches. Ambiguity in the way case studies are selected, empirically conducted and analysed, often exists and can hinder the positive dissemination of research. This paper aims to outline how case study research can be undertaken using the example of the authors' current case study research into interfirm services linkages between UK multinational subsidiaries and local firms in China and Korea. A particular emphasis is placed on the analysis of case studies and the benefits of computer aided qualitative data analysis software (CAQDAS). An integrative approach is taken through the use of Nvivo software. It is argued that the use of Nvivo can help researchers systematise and order data, enabling a more thorough and reliable analysis. If qualitative case study research is to become more accepted and publishable, its transparency must be improved. The use of a standardized type of data analysis software may go some way towards helping researchers achieve this goal.

Handbook of Qualitative Research Methods for International Business

Paul Matthyssens

SAGE Research Methods Foundations [online]

Mark N K Saunders , Bill Lee

Despite having a relatively recent history compared to other social sciences, the business and management field has proliferated into a number of largely independent disciplines. These include: accounting; corporate governance; entrepreneurship; finance; human resource management; international business and international management; leadership; management and business history; marketing and retail; operations and logistics; organizational behaviour; public management and governance; and strategy. Each of these disciplines has its own methodological predilections and as a corollary, a view of what constitutes a case study, where case studies should feature in a research project and the relative usefulness of case study research. Given this breadth of disciplines, only a provisional definition of a case study will be provided at this point; namely, a case study is research into a phenomenon, organization, process, or event that is studied as a unit of analysis that is interesting in its own right. Rather than attempting to summarise all that has been written about case studies across the management disciplines, this entry will elaborate upon thinking around this definition using the metaphor of a kaleidoscope.

David E Gray

Yhonier Gonzalez

Raymond Obeng

Albert Mills

The Journal of Agricultural Sciences - Sri Lanka

rohitha rosairo

We receive a large number of manuscripts for possible publication in this journal. In reviewing them, we find that the bulk of them are from the area of crop sciences, livestock production and allied fields that have used experiments as the research strategy. The minority that falls in to the areas of agribusiness, agricultural economics and extension have used survey strategy. There is a lack of utilizing other research strategies in current research. Research has to be commenced with a clear direction and a clearly identified study process. These are primarily provided by its research strategy (Wedawatta, 2011). There are numerous strategies that a researcher can adopt to achieve the objectives of a particular research study. Some common research strategies are; experiment, survey, archival analysis, ethnography, action research, narrative inquiry, and the case study. This paper explains what a case study is and outlines the components of a case study. The Nature of a Case Study Yin (2003) defines case study as 'an empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident'. A phenomenon and context are not always distinguishable in real-life situations. Therefore, a case study uses a large number of variables of interest than data points; and essentially relies on multiple sources of evidence for data triangulation. A historical viewpoint on case study strategy is presented in Tellis (1997). According to Yin (2003), case studies can be exploratory, explanatory or descriptive. Research in social sciences deals with interactions between institutions and human behaviour. These can be best studied in real-life settings and contexts. Sometimes an inquiry may be undertaken on an individual organization with a limited or a narrow population. These suggest qualitative investigations which are assessments of attitudes, opinions and behaviour (Kothari and Garg, 2018). These qualitative investigations are characteristic with the case study strategy. Whilst often been identified as interpretivist, case studies can also be used in positivistic research (Saunders et al. 2012).

EmmsMt Ntuli

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