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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.

The notion of configuration – that the whole is best understood from a systemic perspective and should be viewed as a constellation of interconnected elements – is arguably one of the central ideas of organization studies. Yet, this idea also remains one of the field’s least understood aspects. In this volume and its introduction, we outline a new perspective for understanding configuration. Our starting point is the emergence of set theoretic configurational methods, and especially Qualitative Comparative Analysis (QCA), which provides novel ways for analyzing configurations. Our volume goes beyond introducing a new method to the fields of management and organization, as these methods furthermore offer an opportunity to rethink our understanding of the field and to develop different ways of theorizing the rich complexity of relationships that characterize organizational life. In this introduction, we introduce some of the key themes that differentiate the approach taken here from previous work on organizational configurations and provide evidence for the emerging renaissance of the configurational approach in organizational theory and research.

Purpose: Case studies are detailed empirical investigations into a complex entity that emphasize the uniqueness of the case and are valuable for making a theoretical contribution. We aim to reveal the types of theoretical contributions case study research can make to the field of strategy and management and explore how case study design can create the opportunities for making a theoretical contribution.

Methodology/Approach: The dynamic capability approach focuses on the firm-specific processes through which firms integrate, build, or reconfigure resources. A comprehensive review of case studies in this field is conducted in five search engines, resulting in a data set of 13 in-depth case studies.

Findings: We demonstrate that using case studies to extend and refine theory enhances knowledge in the field of dynamic capabilities. In strategy and management research, case studies identify and refine constructs and their relationships, develop and confirm propositions, and embed constructs within a larger set of relationships. We reveal that sampling strategy, research setting, and multiple lenses are aspects of case study design that create opportunities for making a theoretical contribution.

Practical Implications: We suggest that case study researchers strategically and purposefully sample cases, vary the setting conditions, or draw upon numerous research fields to make a theoretical contribution.

Originality/Value of Paper: Going beyond the current discussion, we show that case studies have the potential to extend and refine theory. We shed new light on how dynamic capabilities can benefit from case study research by discovering the antecedents that shape the development of capabilities and determining the boundary conditions of the dynamic capabilities approach.

Construction is a highly dynamic environment with numerous interacting factors that affect construction processes and decisions. Uncertainty is inherent in most aspects of construction engineering and management, and traditionally, it has been treated as a random phenomenon. However, there are many types of uncertainty that are not naturally modelled by probability theory, such as subjectivity, ambiguity and vagueness. Fuzzy logic provides an approach for handling such uncertainties. However, fuzzy logic alone has some limitations, including its inability to learn from data and its extensive reliance on expert knowledge. To address these limitations, fuzzy logic has been combined with other techniques to create fuzzy hybrid techniques, which have helped solve complex problems in construction. In this chapter, a background on fuzzy logic in the context of construction engineering and management applications is presented. The chapter provides an introduction to uncertainty in construction and illustrates how fuzzy logic can improve construction modelling and decision-making. The role of fuzzy logic in representing uncertainty is contrasted with that of probability theory. Introductory material is presented on key definitions, properties and methods of fuzzy logic, including the definition and representation of fuzzy sets and membership functions, basic operations on fuzzy sets, fuzzy relations and compositions, defuzzification methods, entropy for fuzzy sets, fuzzy numbers, methods for the specification of membership functions and fuzzy rule-based systems. Finally, a discussion on the need for fuzzy hybrid modelling in construction applications is presented, and future research directions are proposed.

Introduced into the literature a decade ago, grit originally defined as perseverance and passion for long-term goals has stimulated considerable research on positive effects primarily in the academic and military contexts, as well as attracted widespread media attention. Despite recent criticism regarding grit’s construct and criterion-related validity, research on grit has begun to spill over into the work context as well. In this chapter, the authors provide an overview of the initial theoretical foundations of grit as a motivational driver, and present newer conceptualizations on the mechanisms of grit’s positive effects rooted in goal-setting theory. Furthermore, the authors also draw attention to existing shortcomings of the current definition and measurement of grit, and their implications for its scientific and practical application. After establishing a theoretical understanding, the authors discuss the potential utility of grit for human resource management, related to staffing and recruitment, development and training, and performance management systems as well as performance evaluations. The authors conclude this chapter with a discussion of necessary and potential future research, and consider the practical implications of grit in its current state.

This focal chapter deals with the understanding of important ethical theories used in executive moral reasoning such as teleology, deontology, distributive justice and corrective justice, virtue ethics versus ethics of trust, from the perspectives of intrinsic versus instrumental good, moral worth versus moral obligation, and moral conscience versus moral justification. Ethical and moral reasoning will power executives to identify, explore, and resolve corporate moral dilemma, especially in the wake of emerging gray market areas where good and evil, right or wrong, just or unjust, and truth and falsehood cannot be easily distinguished. We focus on developing corporate skills of awareness of ethical values and moral imperatives in current otherwise highly commoditized and turbulent human, market, and corporate situations. The challenges of morality are multifaceted and diverse. Professionals usually have self-discipline and self-regulation abilities, ego strength, and social skills. Morality in the professions is not concerned with the issues of rudimentary socialization; rather, the issues involve deciding between conflicting values, where each value represents something good in itself. There are problems in both knowing what is right, good, true, and just on the one hand, and on the other hand, in doing what is right and avoiding wrong, doing good and avoiding evil, and being fair and just while avoiding being unfair and unjust. Several contemporary cases will illustrate the challenging dimensions of ethical and moral reasoning, moral judgment and moral justification embedded in executive decision processes, and corporate growth and profitability ventures.

This chapter points out that the use of a wide range of theoretical paradigms in marketing research requires researchers to use a broad range of methodologies. As an aid in doing so, the chapter argues for the use of case study research (CSR), defines CSR, and describes several CSR theories and methods that are useful for describing, explaining, and forecasting processes occurring in business-to-business (B2B) contexts. The discussion includes summaries of six B2B case studies spanning more than 60 years of research. This chapter advocates embracing the view that learning and reporting objective realities of B2B processes is possible using CSR methods. CSR methods in the chapter include using multiple interviews (2 + ) separately of multiple persons participating in B2B processes, direct research and participant observation, decision systems analysis, degrees-of-freedom analysis, ethnographic-decision-tree-modeling, content analysis, and fuzzy-set qualitative comparative analysis (fs/QCA.com). The discussion advocates rejecting the dominant logic of attempting to describe and explain B2B processes by arms-length fixed-point surveys that usually involve responses from one executive per firm with no data-matching of firms in specific B2B relationships – such surveys lack details and accuracy necessary for understanding, describing, and forecasting B2B processes.

Research in entrepreneurship is increasingly exploring how archetypes, taxonomies, typologies, and configurations can help scholars understand complex entrepreneurial phenomena. We illustrate the potential for set-theoretic methods to inform this literature by offering best practices regarding how qualitative comparative analysis (QCA) can be used to explore research questions of interest to entrepreneurship scholars. Specifically, we introduce QCA, document how this approach has been used in management research, and provide step-by-step guidance to empower scholars to use this family of methods. We put a particular emphasis on the analytical procedures and offer solutions to dealing with potential pitfalls when using QCA-based methods and highlight opportunities for future entrepreneurship research.