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Research has highlighted the cognitive nature of the business model intended as a cognitive representation describing a business’ value creation and value capture activities. Although the content of the business model has been extensively investigated from this perspective, less attention has been paid to the business model’s causal structure – that is the pattern of cause-effect relations that, in top managers’ or entrepreneurs’ understandings, link value creation and value capture activities. Building on the strategic cognition literature, this paper argues that conceptualizing and analysing business models as cognitive maps can shed light on four important properties of a business model’s causal structure: the levels of complexity, focus and clustering that characterize the causal structure and the mechanisms underlying the causal links featured in that structure. I use examples of business models drawn from the literature as illustrations to describe these four properties. Finally, I discuss the value of a cognitive mapping approach for augmenting extant theories and practices of business model design.

This study aims to draw on the complexity theory and uses a non-an asymmetrical method – fuzzy-set qualitative comparative analysis (fsQCA) to test the core tenets of complexity theory, namely, asymmetry, equifinality and causal complexity and valence reversals or conjunction with a focus on testing the relationships between service quality, customer satisfaction and loyalty. Case outcome forecasting accuracy rather than relationships are tested in asymmetric testing.

Both symmetrical (structural equation modelling or SEM) and non-symmetrical (fsQCA) methods were used to test the proposed relationships (symmetrical testing) and case outcome forecasting accuracy (asymmetric testing). The former was used as a comparison. The study setting was in Australian airports. The data were collected from departure passengers.

The results from SEM and fsQCA differ substantially. The former provides very simplistic findings of variable directional relationships; whereas the latter presents asymmetrical, equifinal and conjunctional relationships regarding service quality, customer satisfaction and behavioural intentions. These findings support the core tenets of the complexity theory.

The study findings conform to the complexity theory that indicates relationships between variables can be nonlinear and the same causes can produce different effects. The findings suggest the outcomes of interest often result from combined antecedent conditions rather than a single causal factor. The study confirms that asymmetrical thinking relies on Boolean algebra and set theory principles.

This study uses both symmetrical and asymmetrical methods to reveal the nuanced information about the relationship that has been tested primarily using symmetrical methods.

The purpose of this paper is to propose a data-driven scheme for identifying critical project complexity dimensions and establishing the trade-off across multiple project performance criteria.

This paper adopts a hybrid approach using Bayesian Belief Networks (BBNs) and Artificial Neural Networks (ANNs). The output of the ANN model is used as input to the BBN model for prioritizing project complexity dimensions relative to multiple project performance criteria. The proposed process is demonstrated through a real application in the construction industry.

With a number of nonlinear interactions involved within and across project complexity and performance, it is not feasible to model and assess the strength of these interactions using conventional techniques. The proposed process helps in effectively mapping a “multidimensional complexity” space to a “multidimensional performance” space and makes use of data from past projects for operationalizing this mapping scheme by means of ANNs. This obviates the need for developing a parametric model that is both challenging and computationally cumbersome. The mapping function can be used for generating all possible scenarios required for the development of a data-driven BBN model.

This paper introduces a data-driven process for operationalizing the mapping of project complexity to project performance within a network setting of interacting complexity dimensions and performance criteria. The results of the application study manifest the importance of capturing the interdependency across project complexity and performance. Ignoring the underlying interdependencies and relying exclusively on conventional correlation-based techniques may lead to making suboptimal decisions.

Qualitative Comparative Analysis (QCA) is a promising, powerful method that is increasingly used for IS research. However, the Information Systems (IS) discipline still lacks a shared understanding of how to conduct and report QCA. This paper introduces the fundamental concepts of QCA, summarizes the status quo, and derives recommendations for future research.

A descriptive literature review in major IS outlets summarizes how and why QCA has been used in the IS discipline, critically evaluates the status quo, and derives recommendations for future QCA studies.

The literature review reveals 32 empirical research articles in major IS journals that have used the QCA method. Articles applied QCA to a broad range of research topics at the individual and organizational levels, mainly as a standalone analysis for theory development, elaboration and testing. The authors also provide evidence that most published IS research articles do not take full advantage of the potential QCA, such as analyzing necessary causal conditions or testing the robustness of QCA results. The authors provide seven actionable recommendations for future IS research using QCA.

The literature review assesses the status quo of QCA’s application in the IS discipline and provides specific recommendations on how IS researchers can leverage the full potential of QCA.

This study aims to examine the entrepreneurship profiles of migrants and refugees relying on a neo-configurational approach that increases understanding of causal complexity, equifinality and causal asymmetry patterns to high entrepreneurial intentions in the two groups.

Using a fuzzy set qualitative comparative analysis method, the authors analysed 52 respondents – migrants and refugees. The findings show the existence of equifinality in which different configurations can lead to high and low entrepreneurial intentions, underlying that traumatic experiences have a major role in entrepreneurial intention. It also demonstrates that core conditions are associated with refugee’s configurations and causal asymmetry. The cross-sectional character of this research impedes the searching for a better causal relationship. The lack of studies that approach the subject of refugees makes it challenging to develop a robust theory in this sense.

The paper highlights five main configurations – two related to migrants’ profile and three related to refugees’ profile – that enable expanding the current knowledge and practices to better customize practices to increase entrepreneurial intention.

To the best of the authors’ knowledge, this is the first research using a configurational approach to explore migrant and refugee entrepreneurship intention profiles.

Technology‐based new ventures (TNVs) – which rely on entrepreneurial activities based on science and technology applications in newly created organizations to be successful – are important to current economic growth and innovation. Past research has looked at the importance of networks and social capital to TNV performance. Yet these studies rarely provide theoretical predictions of the attributes of network ties. This paper aims to bring TNV theory up to date with respect to twenty‐first century adaptation and complexity conditions.

The paper draws on new developments in complexity science (specifically scalability and scale‐free theories) and long‐standing first principles of efficacious adaptation to develop TNV‐relevant theory offering an alternative perspective on the impact of network ties on the performance of TNV.

It is argued that TNVs can achieve superior performance by developing and building moderate numbers of short‐term (and thereby weak) network ties. The theorizing calls for a new research agenda pertaining to TNVs, which are delineated. The paper also develops four propositions as part of setting forth an agenda for future research.

The paper updates the entrepreneurship and social network literatures by reshaping them with respect to the nonlinear order‐creation dynamics of complexity theory and scale‐free dynamics of econophysics. It focuses on the aspects of network theory that are especially likely to set in motion the complex adaptive systems dynamics essential to TNV performance. Therefore, the conceptual framework contributes to TNVs as a guide to achieving higher performance, effectiveness, and longevity in a rapidly changing world.

The purpose of this paper is to empirically study the necessary and sufficient antecedents of customer loyalty to logistics service providers (LSPs). Despite the abundance of loyalty studies, few studies have empirically examined the complex causal relationships between loyalty and its antecedents using the appropriate research methods.

The study uses fuzzy sets qualitative comparison analysis (FsQCA) to uncover the antecedents and antecedent configurations of customer loyalty. This study examined the necessity and sufficiency of five antecedents (operational collaboration, strategic collaboration, trust, service satisfaction and price satisfaction) and on five dimensions of loyalty (repurchase intension, switching costs, exclusiveness, referrals and overall loyalty). This study developed six research hypotheses based on existing literature and tested them empirically in a manufacturing context. This study compared results from FsQCA with regression analysis.

The findings reveal that only a few antecedent configurations lead to customer loyalty, including a combination of strategic and operational collaboration, bundling of service offerings and combining competitive price with strategic collaboration. Further, the absence of trust negatively affects loyalty, but the presence of trust does not lead to loyalty.

This study contributes to business to business literature by demonstrating how to use FsQCA analysis to test the presence of equifinality, conjunction and causal asymmetry of complex relationships. This study applies FsQCA between antecedent factors and customer loyalty. Furthermore, we demonstrate how to compare and integrate FsQCA with conventional regression analysis which is based on correlation-bounded logic.

This study shows that no single antecedents that can generate loyalty, yet, few antecedent configurations work better than others: collaborating at both strategic and operational level with your partner has the highest impact on loyalty. Another configuration that leads to loyalty is to combine competitive prices with strategic collaboration, which particularly stimulates repurchase decisions. Price is are not sufficient enough to lead to customer loyalty.

This study applied a novel analysis to uncover necessary and sufficient conditions that conventional methods such as regression analysis and structural equation modelling have limited power.

Purpose – This chapter examines the potential of qualitative comparative analysis (QCA) for strategy research.

Methodology/approach – We introduce the set-theoretic framework of QCA and provide an overview of recent methodological developments.

Findings – We utilize a variety of examples relevant to strategy research to illustrate the action steps and key concepts involved in conducting a QCA study.

Originality/value of paper – We develop examples from core research areas in strategic management to illustrate QCA's potential for examining issues of causality and diversity in strategy research, and in settings involving medium-N samples. We conclude by emphasizing that QCA offers an alternative mode of inquiry to open and redirect important lines of strategy research.

This study aims to investigate the configurations that drive employee service recovery. Rather than analyzing the net effects of individual antecedents of service recovery, which is the common approach in the literature, this study uses a configurational approach to investigate how five antecedents (customer service orientation, rewards, teamwork, empowerment and customer service training) combine to yield employee adaptive and proactive service recovery behaviors.

The study collects responses from 90 frontline employees through an online survey. Building on configurational theory, the authors developed and empirically validated four research propositions by using a fuzzy-set qualitative comparative analysis.

Three equifinal configurations of managerial practices result in either employee proactive or adaptive service recovery behaviors. Two of these three configurations result in both adaptive and proactive behaviors. In addition, the findings show that two out of the three configurations that lead to proactive behavior in service recovery also lead to the simultaneous existence of proactive and adaptive behaviors in service recovery. None of the sufficient configurations require the presence of all managerial practices. These results underscore that managers do not have to act on every single managerial intervention area to promote service recovery.

The study advances the knowledge on the antecedents of employee behavior in service recovery by investigating how these antecedents combine to yield different recipes for developing either employee adaptive or proactive behavior in service recovery.

The findings provide insights for managers into the different combinations of practices that can be used to develop employee proactive or adaptive behavior in service recovery.

To the best of the authors’ knowledge, this is the first study that relies on a configurational approach to understand the combinations of managerial practices that result in employee proactive and adaptive behaviors in service recovery.

In literature, it is recognized that there is no universal set of critical success factors (CSFs) applicable to all projects. The goal of this research is to validate a theoretical model which considers that CSFs’ influence on project success (PS) is configurational, that CSFs combine to influence PS.

The authors proposed a theoretical framework which operationalizes CSFs considering contingency and institutional theories' terms, as external contingencies, organizational resources and project strategies, which influence PS. The framework is validated through a qualitative approach on 18 social projects implemented by nongovernmental organizations (NGOs). Based on the conducted semistructured interviews with NGO managers or project managers, 91 instances when CSFs combine to influence PS were identified.

The dominant path reveals the combination of CSFs in terms of strategies adopted to face contingencies (70 instances), another as resources which moderate managers' strategies (14 instances), and in seven instances positive contingencies and resources combine and influence the PS. The results reveal that CSFs combine in reactive and dynamic ways to influence PS.

The research contributes to the vast literature on projects' success by adopting a different perspective. Configurational theory explains project management and projects' complexity better than the traditional approaches, which have a rather correlational perspective.