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This study applies asymmetric rather than conventional symmetric analysis to advance theory in occupational psychology. The study applies systematic case-based analyses to model complex relations among conditions (i.e., configurations of high and low scores for variables) in terms of set memberships of managers. The study uses Boolean algebra to identify configurations (i.e., recipes) reflecting complex conditions sufficient for the occurrence of outcomes of interest (e.g., high versus low financial job stress, job strain, and job satisfaction). The study applies complexity theory tenets to offer a nuanced perspective concerning the occurrence of contrarian cases – for example, in identifying different cases (e.g., managers) with high membership scores in a variable (e.g., core self-evaluation) who have low job satisfaction scores and when different cases with low membership scores in the same variable have high job satisfaction. In a large-scale empirical study of managers (n = 928) in four (contextual) segments of the farm industry in New Zealand, this study tests the fit and predictive validities of set membership configurations for simple and complex antecedent conditions that indicate high/low core self-evaluations, job stress, and high/low job satisfaction. The findings support the conclusion that complexity theory in combination with configural analysis offers useful insights for explaining nuances in the causes and outcomes to high stress as well as low stress among farm managers. Some findings support and some are contrary to symmetric relationship findings (i.e., highly significant correlations that support main effect hypotheses).

The study here responds to the view that the crucial problem in strategic management (research) is firm heterogeneity – why firms adopt different strategies and structures, why heterogeneity persists, and why competitors perform differently. The present study applies complexity theory tenets and a “neo-configurational perspective” of Misangyi et al. (2016) in proposing complex antecedent conditions affecting complex outcome conditions. Rather than examining variable directional relationships using null hypotheses statistical tests, the study examines case-based conditions using somewhat precise outcome tests (SPOT). The complex outcome conditions include firms with high financial performances in declining markets and firms with low financial performances in growing markets – the study focuses on seemingly paradoxical outcomes. The study here examines firm strategies and outcomes for separate samples of cross-sectional data of manufacturing firms with headquarters in one of two nations: Finland (n = 820) and Hungary (n = 300). The study includes examining the predictive validities of the models. The study contributes conceptual advances of complex firm orientation configurations and complex firm performance capabilities configurations as mediating conditions between firmographics, firm resources, and the two final complex outcome conditions (high performance in declining markets and low performance in growing markets). The study contributes by showing how fuzzy-logic computing with words (Zadeh, 1966) advances strategic management research toward achieving requisite variety to overcome the theory-analytic mismatch pervasive currently in the discipline (Fiss, 2007, 2011) – thus, this study is a useful step toward solving the crucial problem of how to explain firm heterogeneity.

This chapter elaborates on the usefulness of embracing complexity theory, modeling outcomes rather than directionality, and modeling complex rather than simple outcomes in strategic management. Complexity theory includes the tenet that most antecedent conditions are neither sufficient nor necessary for the occurrence of a specific outcome. Identifying a firm by individual antecedents (i.e., noninnovative vs. highly innovative, small vs. large size in sales or number of employees, or serving local vs. international markets) provides shallow information in modeling specific outcomes (e.g., high sales growth or high profitability) – even if directional analyses (e.g., regression analysis, including structural equation modeling) indicate that the independent (main) effects of the individual antecedents relate to outcomes directionally – because firm (case) anomalies almost always occur to main effects. Examples: a number of highly innovative firms have low sales while others have high sales and a number of noninnovative firms have low sales while others have high sales. Breaking-away from the current dominant logic of directionality testing – null hypothesis significance testing (NHST) – to embrace somewhat precise outcome testing (SPOT) is necessary for extracting highly useful information about the causes of anomalies – associations opposite to expected and “statistically significant” main effects. The study of anomalies extends to identifying the occurrences of four-corner strategy outcomes: firms doing well in favorable circumstances, firms doing badly in favorable circumstances, firms doing well in unfavorable circumstances, and firms doing badly in unfavorable circumstances. Models of four-corner strategy outcomes advance strategic management beyond the current dominant logic of directional modeling of single outcomes.

Recognizing Gigerenzer’s (1991) dictum that scientists’ tools are not neutral (tools-in-use influence theory formulation as well as data interpretation), this chapter reports theory and examines data in ways that transcend the dominant logics for variable-based and case-based analyses. The theory and data analysis tests key propositions in complexity theory: (1) no single antecedent condition is a sufficient or necessary indicator of a high score in an outcome condition; (2) a few of many available complex configurations of antecedent conditions are sufficient indicators of high scores in an outcome condition; (3) contrarian cases occur, that is, low scores in a single antecedent condition associates with both high and low scores for an outcome condition for different cases; (4) causal asymmetry occurs, that is, accurate causal models for high scores for an outcome condition are not the mirror opposites of causal models for low scores for the same outcome condition. The study tests and supports these propositions in the context of customer assessments (n = 436) of service facets and service-outcome evaluations for assisted temporary-transformations of self via beauty salon and spa treatments. The findings contribute to advancing a nuanced theory of how customers’ service evaluations relate to their assessments of overall service quality and intentions to use the service. The findings support the need for service managers to be vigilant in fine-tuning service facets and service enactment to achieve the objective of high customer retention.

This chapter shows how to construct and test case-based macro models. The chapter makes use of national data to examine influences on quality-of-life of national cultures as complex wholes and entrepreneurship activities in Brazil, Russia, India, China, Germany, and the United States (the six focal nations) plus Denmark (a small-size, economically developed, nation). The study tests McClelland’s (1961) and more recent scholars’ proposition that some cultural configurations nurture entrepreneur startups, while other cultures are biased toward thwarting startups. The study applies complexity theory to develop and empirically test a general theory of cultures’, entrepreneurship’s, and innovation’s impact on quality-of-life across nations. Because culture represents a complex whole of attitudes, beliefs, values, and behavior, the study applies a set-theoretic approach to theory development and testing of alternative cultural configurations. Each of 28 economical developed and developing nations is scored for the level of the national cultures for each of six focal countries. The study selected for the study enables multi-way comparisons of culture-entrepreneurship-innovation-QOL among large- and small-sized developing and developed nations. The findings graphically present the complex national cultural configuration (x-axis) with entrepreneur nurture/thwart (y-axis) of the 28 nations compared to the six focal nations. The findings also include recognizing national cultures (e.g., Switzerland, the United States) nurturing entrepreneurial behavior versus other national cultures (e.g., Brazil and India) thwarting entrepreneurial behavior. The study concludes with a call to recognize the implicit shift in culturally implicit thinking and behavior necessary for advancing national platforms designed to successfully nurture entrepreneurship. Entrepreneur strategy implications include the observation that actions nurturing firm start-ups by nations low in entrepreneurship will unlikely to be successful without reducing such nations’ high levels of corruption.

This paper aims to apply complexity theory tenets to deepen understanding, explanation and prediction of how configurations of national cultures and need motivations influence national entrepreneurial and innovation behavior and nations’ quality-of-life (QOL). Also, the study examines whether or not high national ethical behavior is sufficient for indicating nations high in quality-of-life.

Applying core tenets of complexity theory, the study constructs asymmetric, case-based (nations), explanations and predictive models of cultures’ consequences (via Schwartz’s seven value dimensions) and implicit need motivations (via McClelland’s three need motivations) indicating national entrepreneur and innovation activities and subsequent national quality-of-life and ethical behavior. The study includes testing configurational models empirically for predictive accuracy. The empirical examination is for a set of data for 24 nations in Asia, Europe, North and South America and the South Pacific.

The findings confirm the usefulness of applying complexity theory to learn how culture and motivation configurations support versus have negative consequences on nations’ entrepreneurship, innovation and human well-being. Nurturing of entrepreneur activities supports the nurturing of enterprise innovation activity and their joint occurrence indicates nations achieving high quality-of-life. The findings advance the perspective that different sets of cultural value configurations indicate nations high versus low in entrepreneur and innovation activities.

High entrepreneur activities without high innovation activity are insufficient for achieving high national quality-of-life. Achieving high ethical behavior supports high quality-of-life.

This study is one of the first to apply complexity theory tenets in the field of entrepreneurship research. The study here advances the perspective that case-based asymmetric modeling of recipes is necessary to explain and predict entrepreneur activities and outcomes rather than examining whether variable relationships are statistically significant from zero.

Using data from 104 countries over a six-year period (2009-2014), this study proposes a value-added predictor in service industries based on the eight indicators of the prosperity index, namely economy, entrepreneurship and opportunity, governance, education, health, safety and security, personal freedom and social capital.

The fuzzy-set qualitative comparative analysis (fsQCA) and complexity theory, a relatively novel approach for developing and testing the conceptual model, are used for asymmetric modelling of value added in service industries, and the predictive validity of proposed configural model is tested.

Apart from advancing method and theory, this study simulates causal conditions (i.e. recipes) leading to both high and low scores of the value added of services. The configural conditions indicating a high/low level of value added in service industries can be used as a guiding strategy for marketers, investors and policy makers.

An analysis of worldwide data provides complex models demonstrating both how to regulate country conditions to achieve a high value-added score and select a foreign country for investment that offers a high level of value-added service.

The introductory chapter 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.

“Country-collectors” (CCs) are defined here as international leisure travelers who have visited 6 +  countries within the five most recent calendar years primarily to pursue leisure activities. The study here contributes by offering an early workbench model of antecedents, paths, and outcomes of country-collectors’ evaluations and behavior toward countries as place-brands competing for such visitors. This study reports findings from a large-scale omnibus survey in three large Japanese cities (total n = 1,200). Key findings support the model and the following conclusions. Generally, country-collectors represent a small share of a nation’s adult population (less than 5%) but over 40% of the total leisure trips abroad; country-collectors are classifiable into distinct sub-segments according to the country place-brands that they visit; CC sub-segments, less frequent international leisure travelers, and stay-in-country travelers and non-travelers each offer unique assessments of competing countries as place-brands. National place-brand strategists planning a marketing campaign to influence a given nation’s residents to visit a specific destination (e.g., persuading Japanese nationals to visit the United States) may increase the campaign’s effectiveness by using this workbench model. The study offers a blueprint of how to appraise strengths and weaknesses of competing national place-brands among realized and potential visitors in specific national markets.

The purpose of this paper is to use tenets of the complexity theory in order to study the effect of various determinants of firm’s performance, such as CEO’s compensation and age, for the case of 72 insurance companies.

The authors identify the asymmetries in the data set by creating quantiles and using contrarian analysis. Instead of ignoring this information and use a main effects approach, all the available information in the data set is taken into account. For this purpose, the authors use qualitative comparative analysis to find alternative equifinal routes toward high firm performance.

Five configurations are found which lead to high performance. Every one of the five configurations is found to be sufficient but not necessary for high firm performance.

The research findings contribute to a better understanding of the determinants of firm’s performance taking into account the asymmetries in the data set. The authors identify alternative paths toward high firm performance, which could be vital information for the decision maker inside a firm.