This essay describes tenets of complexity theory including the precept that within the same set of data X relates to Y positively, negatively, and not at all. A consequence to this first precept is ...that reporting how X relates positively to Y with and without additional terms in multiple regression models ignores important information available in a data set. Performing contrarian case analysis indicates that cases having low X with high Y and high X with low Y occur even when the relationship between X and Y is positive and the effect size of the relationship is large. Findings from contrarian case analysis support the necessity of modeling multiple realities using complex antecedent configurations. Complex antecedent configurations (i.e., 2 to 7 features per recipe) can show that high X is an indicator of high Y when high X combines with certain additional antecedent conditions (e.g., high A, high B, and low C)—and low X is an indicator of high Y as well when low X combines in other recipes (e.g., high A, low R, and high S), where A, B, C, R, and S are additional antecedent conditions. Thus, modeling multiple realities—configural analysis—is necessary, to learn the configurations of multiple indicators for high Y outcomes and the negation of high Y. For a number of X antecedent conditions, a high X may be necessary for high Y to occur but high X alone is almost never sufficient for a high Y outcome.
This editorial suggests moving beyond relying on the dominant logic of multiple regression analysis (MRA) toward thinking and using algorithms in advancing and testing theory in accounting, consumer ...research, finance, management, and marketing. The editorial includes an example of testing an MRA model for fit and predictive validity. The same data used for the MRA is used to conduct a fuzzy-set qualitative comparative analysis (fsQCA). The editorial reviews a number of insights by prominent scholars including Gerd Gigerenzer's treatise that “Scientists' tools are not neutral.” Tools impact thinking and theory crafting as well theory testing. The discussion may be helpful for early career scholars unfamiliar with David C. McClelland's brilliance in data analysis and in introducing business research scholars to fsQCA as an alternative tool for theory development and data analysis.
Under the “Metrics” link, Google.com/scholar ranks the top twenty journals by impact in 16 subcategories of “business, economics, and management” (e.g., accounting and taxation, economics, finance, ...marketing, strategic management, tourism and hospitality). This editorial describes bad practices appearing in the majority of published articles in the twenty leading journals within all of these 16 subcategories. Unfortunately, bad practices appear in most articles in the Journal of Business Research—even though the JBR is first in marketing and seventh in strategic management in the Google journal h5 impact rankings. Most of the articles in most of the journals in finance, management, marketing, and organizational studies include empirical positivistic methods and findings—and each of these empirical articles likely includes three-to-ten or more bad practices that this editorial describes. The editorial includes how to design-in good practices in theory, data collection procedures, analysis, and interpretations to avoid these bad practices. Given that bad practices in research are ingrained in the career training of scholars in sub-disciplines of business/management (e.g., through reading articles exhibiting bad practices usually without discussions of the severe weaknesses in these studies and by research courses stressing the use of regression analysis and structural equation modeling), this editorial is likely to have little impact. However, scholars and executives supporting good practices should not lose hope. The relevant literature includes a few brilliant contributions that can serve as beacons for eliminating the current pervasive bad practices and for performing highly competent research.
•We provide a step-by-step guide on employing fsQCA based on an already published study.•Performing contrarian case analysis and testing for predictive validity is highly recommended.•FsQCA can be ...used together with variance-based methods (e.g., SEM).•Existing studies can be extended and complemented through fsQCA.
The increasing interest in fuzzy-set Qualitative Comparative Analysis (fsQCA) in Information Systems and marketing raises the need for a tutorial paper that discusses the basic concepts and principles of the method, provide answers to typical questions that editors, reviewers, and authors would have when dealing with a new tool of analysis, and practically guide researchers on how to employ fsQCA. This article helps the reader to gain richer information from their data and understand the importance of avoiding shallow information‐from‐data reporting. To this end, it proposes a different research paradigm that includes asymmetric, configurational‐focused case‐outcome theory construction and somewhat precise outcome testing. This article offers a detailed step-by-step guide on how to employ fsQCA by using as an example an already published study. We analyze the same dataset and present all the details in each step of the analysis to guide the reader onto how to employ fsQCA. The article discusses differences between fsQCA and variance-based approaches and compares fsQCA with those from structured equation modelling. Finally, the article offers a summary of thresholds and guidelines for practice, along with a discussion on how existing papers that employ variance-based methods are extendable and complemented through fsQCA.
This article describes why and how to end bad science practices and shallow information‐from‐data reporting by embracing a seemingly minor but quite a radically different research paradigm that ...includes asymmetric, configurational‐focused case‐outcome theory construction and somewhat precise outcome testing. This radically different paradigm provides accurate point or interval estimates of case‐outcomes. As an illustration of this paradigm, the exposition in this article includes an elaboration based on additional analyses of data in research appearing in a recent issue of this journal.
•Research across disciplines provide principles/tools for in mitigating disasters.•Symmetric theory and NHTS are detrimental to advancing science.•Natural experiment do not include the requirements ...of a “true experiment.”•An estimate of 2.1 million U.S. deaths from COVID-19 may be overly conservative.•Intervention performance marks to COVID-19 by nations include Sweden: F; U.S: F.
This essay applies the “ultimate broadening of the concept of marketing” for designing and implementing interventions in public laws and policy, national and local regulations, and everyday lives of individuals. The ultimate broadening of the concept of marketing: Marketing is any activity, message, emotion, or behavior by someone, firm, organization, government, community, or brand executed consciously or nonconsciously that may stimulate an observable or non-observable activity, emotion, attitude, belief, or thought by someone else, group, organization, firm or community. The broadening definition applies to the current interventions by national and state/provincial governments as well as healthcare facilities, medical science facilities, firms, and individuals to mitigate and eliminate the impact of the COVID-19 pandemic. Framing interventions as experiments is helpful in improving the quality of their designs, implementing them successfully, and validly interpreting their effectiveness. In January and February 2020, a few nations were exemplars for accurately forecasting the coming disaster of COVID-19 as a cause of illness and death and in designing/implementing effective mitigating strategies: Denmark, Finland, Republic of Korea, New Zealand, Norway, and Vietnam. While the COVID-19 prevention intervention tests now being run for several promising vaccines are true experiments, the researchers analyzing the data from these interventions may need prompting to examine the efficacy of each vaccine tested by modeling demographic subgroups for the members in the treatment and placebo groups in the randomized control trials.
ABSTRACT
The study here applies qualitative comparative analysis (QCA) in an examination of data from 15 societies varying in their degree of market integration (MI) and participation in world ...religions (WRs); the data are available in Henrich et al. (2010b). The findings here provide a more nuanced coverage of the influences of cultural causal recipes on fairness and punishment in exchanges with strangers than “net effect” explanations. The coverage here explains how acts of fairness and punishment are contingent on several alternative paths including both low as well as high levels of MI and WR. Contrary to conclusions by Henrich et al. (2010a), depending on additional ingredients in cultural recipes, a society does not need to achieve MI and adoption of a WR to be fair and punish unfairness.
The theorization of emotion receives considerable attention in contemporary tourism literature. Remarkably, existing studies largely ignore the operationalization of emotion in tourism research. ...Drawing on extant knowledge from psychology, marketing, and tourism literatures, this article describes methodological and theoretical concerns and provides guidance for selecting highly useful-for-the-context (HUFTC) emotion measures. To help researchers choose HUFTC measures, this study proposes a new model: Emotionapps. The article here highlights the need for tourism researchers to account for the complexities in measuring emotions and how such measurement impacts theory construction.
Corrupt behavior presents major challenges for organizations in a wide range of settings. This article embraces a complexity theoretical perspective to elucidate the causal patterns of factors ...underlying consumers' unethical judgments. This study examines how causal conditions of four distinct domains combine into configurational causes of unethical judgments of two frequent forms of corrupt consumer behavior: shoplifting and fare dodging. The findings of fuzzy-set Qualitative Comparative Analyses indicate alternative, consistently sufficient "recipes" for the outcomes of interest. This study extends prior work on the topic by offering new insights into the interplay and the interconnected structures of multiple causal factors and by describing configurational causes of consumers' ethical evaluations of corrupt behaviors. This knowledge may support practitioners and policy makers to develop education and control approaches to thwart corrupt consumer behaviors.
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