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This chapter acknowledges the difficulties in the empirical study of social ventures – broadly defined as market-driven ventures that produce social change – that arise from the vast differences among social venture firms in terms of missions, goals, identities, strategies, and structures. In an effort to improve research in this area and advance the field of social entrepreneurship, the authors advocate approaching social ventures from a configurational perspective.

This chapter begins with a discussion of what social ventures are and why organizational configurations – sets of firms that are similar across key characteristics – may be an appropriate perspective to utilize. Then, two methods – cluster analysis and set-theoretic analysis – are discussed in detail as ways to approach the study of social venture configurations. Details include descriptions of the techniques, instructions for use, examples, and limitations for each.

This chapter identifies research opportunities using configurations approaches in social venture research. Substantial possibilities for multilevel and temporally based research are discussed in depth.

A configurational approach can address the incongruence and non-findings in current social venture research and offers new opportunities for future research.

Product configuration is considered as one of the most successful applications of knowledge‐based approaches in the past decade. Knowledge‐based configurations can be classified into three different approaches, namely, rule‐based, model‐based and case‐based approaches. Past research has mainly focused on the development of reasoning techniques for mapping requirements to configurations. Despite the success of certain conventional approaches, the acquisition of configuration knowledge is usually done manually. This paper aims to explore fundamental issues in product configuration system, and propose a novel approach based on data mining techniques to automatically discover configuration knowledge in constraint‐based configurations.

Given a set of product data comprising product requirements specification and configuration information, the paper adopted an association rule mining algorithm to discover useful patterns between requirement specification and product components, as well as the correlation among product components. A configuration was developed which takes XML‐based requirement specification as input and bases on a constraint knowledge base to produce product configuration as output consisting of a list of selected components and the structure and topology of the product. Three modules are developed, namely product data modelling, configuration knowledge generation and product configuration generation module. The proposed approach is implemented in the configuration knowledge generation module. The configuration generation module realizes a resolution of constraint satisfaction problem to generate the output configuration.

The significance and effectiveness of the proposed approach is demonstrated by its incorporation in our configuration system prototype. A case study was conducted and experimental results show that the approach is promising in finding constraints with given sufficient data.

Novel knowledge generation approach is proposed to assist constraint generation for Constraint‐based product configuration system.

The purpose of this paper is to provide a structured overview of the application of the configuration approach in the context of new and small ventures.

The paper surveys the empirical literature in the leading entrepreneurship journals from 1994 to 2006.

There are a small, but significant number of studies that deal with the empirical identification and examination of new venture types. However, researchers are just beginning to tap the potential of the configuration approach. More specifically, configuration analyses are still rather heterogeneous, and no study deals with the identification of development configuration in the context of new ventures yet.

Since the configuration approach has already delivered interesting results in research on new ventures, we might see additional studies based on this approach in the future. However, there are practical and theoretical considerations to be taken into account.

An awareness of the existence of different types of start‐ups can lead to more informed decisions in new venture management.

This literature review identifies and structures empirical configuration research in the context of new and small ventures. Also, awareness for future research opportunities is raised.

This chapter shows how configurational approaches can be a valuable inquiring system for examining and understanding complex messy phenomena in the area of digital business strategy in turbulent environments such as digital ecodynamics. Digital ecodynamics is defined as the holistic confluence among environmental turbulence, dynamic capabilities, and IT systems – and their fused dynamic interactions unfolding as an ecosystem. With fuzzy-set qualitative comparative analysis (fsQCA) we analyze firm-level field survey data and describe how IT systems, organizational dynamic capability and environmental turbulence simultaneously combine to result in multiple configurations, which have different causal structures to produce competitive firm performance. This equifinality shows how configurational approaches can create new practical insights in digital ecodynamics by suggesting multiple strategic options from which organizations can choose the best solution that fits their context.

The purpose of this paper is to propose a three-staged approach to configuration change management that uses a combination of complexity analysis, data visualization, and algorithmic validation to assist in validating configuration changes.

In order to accomplish the above purpose, the authors conducted a review of existing configuration management practices. This was followed by an in-depth case study of the configuration management practices of a major automotive OEM. The primary means of data collection for the case study were interviews, ethnographic study, and document analysis. Based on the results of the case study, a set of support tools is proposed to assist in the configuration management process.

Through the case study, the authors identified that the OEM used a configuration management method that largely represented the rule-based reasoning methods identified in the literature review. In addition, many of the associated challenges are present, primarily, the difficulty in making changes to the rule system and evaluating the changes.

The primary limitation is that the case study was based on a single OEM. However, the results are in line with other practices identified in the literature review. Therefore, it is expected that the findings and recommendations should hold true in other applications.

A set of configuration management tools and associated requirements are identified and defined that could be used to assist companies in the automotive industry, and perhaps others, in managing their option changes as they continue to move towards full mass customization of products.

The proposed approach for configuration management has not been seen in any other organization. The value of this paper is in the effectiveness of the proposed approach in assisting in the configuration change management process.

Configuration systems are used as a means for efficient design of customer tailored product service systems (PSS). In PSS configuration, mapping customer needs with optimal configuration of PSS components have become much more challenging, because more knowledge with personalization aspects has to be considered. However, the extant techniques are hard to be applied to acquire personalized configuration rules. The purpose of this paper is to extract the configuration rule knowledge in symbolism formulation from historical data.

Customer characteristics (CCs) are defined and introduced into the construction of configuration rules. Personalized PSS configuration rules (PCRs) are thereby proposed to collect and represent more knowledge. An approach combining Local Cluster Neural Network and Rulex algorithm is proposed to extract rule knowledge from historical data.

The personalized configuration rules with CCs are able to alleviate the burden of customers in expressing functional requirements. Furthermore, in the long-term relationship with a customer in PSS realization, PSS offerings can be reconfigured according to the changing CCs with the guide of PCRs.

The contribution of this paper lies in introducing the attribute of CCs into the antecedents of PCRs and proposing the neural networks-based approach to extracting the rule knowledge from historical data.

The purpose of this paper is to explore the impact of configuration on supply network capability. It was believed that a configuration perspective might provide new insights on the capability and performance of supply networks, a gap in the literature, and provide a basis for the development of tools to aid their analysis and design.

The methodology involved the development of a configuration definition and mapping approach extending established strategic and firm level constructs to the network operational level. The resulting tools were tested and refined in a series of case studies across a range of sectors and value chain models. Supply network capability assessments, from the perspective of the focal firm, were then compared with their configuration profiles.

The configuration mapping tools were found to give new insights into the structure of supply networks and allow comparisons to be made across sectors and business models through the use of consistent and quantitative methods and common presentation. They provide the foundations for linking configuration to capability and performance, and contribute to supply network design and development by highlighting the intrinsic capabilities associated with different configurations.

Although multiple case networks have been investigated, the configuration exemplars remain suggestive models. The research suggests that a re‐evaluation of operational process excellence models is needed, where the link between process maturity and performance may require a configuration context.

Advantages of particular configurations have been identified with implications for supply network development and industrial policy.

The paper seeks to develop established strategic management configuration concepts to the analysis and design of supply networks by providing a robust operational definition of supply network configuration and novel tools for their mapping and assessment.

This study aims to bridge the gap in understanding the effects of organizational culture on supply chain integration (SCI) by examining the relationships between organizational cultures and SCI. The extant studies investigating the antecedents of SCI focus mainly on environments, interfirm relationships and other firm-level factors. These studies generally overlook the role of organizational culture. The few studies that do examine the effects of organizational culture on SCI show inconsistent findings.

By placing organizational culture within the competing value framework (CVF), this study establishes a conceptual model for the relationships between organizational culture and SCI. The study uses both a contingency approach and a configuration approach to examine these proposed relationships using data collected from 317 manufacturers across ten countries.

The contingency results indicate that both development and group culture are positively related to all three dimensions of SCI. However, rational culture is positively related only to internal integration, and hierarchical culture is negatively related to both internal and customer integration. The configuration approach identifies four profiles of organizational culture: the Hierarchical, Flexible, Flatness and Across-the-Board profiles. The Flatness profile shows the highest levels of development, group and rational cultures and the lowest level of hierarchical culture. The Flatness profile also achieves the highest levels of internal, customer and supplier integration.

This study is subject to several limitations. In theoretical terms, this study does not resolve all of the inconsistencies in the relationship between organizational culture and SCI. In terms of methodology, this study uses cross-sectional data from high-performance manufacturers. Such data cannot provide strong causal explanations, but only broad and general findings.

This study reminds managers to consider organizational culture when they implement SCI. The study also provides clues to help managers in assessing and adjusting organizational culture as necessary for SCI.

This study makes two theoretical contributions. First, by examining the relationships between organizational culture and SCI in a new context, the findings of the study provide additional evidence to reconcile the previously inconsistent findings on this subject. Second, by departing from the previous practice of investigating only particular dimensions of organizational culture, this study adopts a combined contingency and configuration approach to address both the individual and synergistic effects of all dimensions of organizational culture. This more comprehensive approach deepens our understanding of the relationship between organizational culture and SCI.

The purpose of this paper is to explore and compare causal recipes for high performance among young Indian and UK firms in high-tech industries.

The traditional configuration approach suggests using the leadership, strategy, structure, and environment domains to identify configurations. In response to calls to improve causal linkages, and drawing on work on start-ups’ configurations, entrepreneurial orientation is used with these four domains to identify configurations. Fuzzy-set qualitative comparative analysis is used to analyze data collected via questionnaires from 70 Indian and 21 UK young firms.

In all five configurations identified in UK context, firms adopt high external integration, and employ inorganic development strategies, exhibit high internal integration, or do not operate in a highly competitive industry. These firms carve out niches, enjoy strong linkages with supply chain partners, and have strong enough reputations that their environment is not highly competitive. Although employees are told what to do, autonomy is provided on how to do it. Among the nine Indian configurations, a large number of managers with high-growth experience is absent in eight, high internal integration is lacking in six, and high external integration is missing in five. These firms employ alternative recipes for success, as discussed in the paper.

Comparing configurations in the Indian and UK contexts, the paper highlights similarities and differences across configurations, and that founders devise alternate pathways to achieve high performance. It also notes changes in relationships among variables across configurations.

Entrepreneurship education (EE) is critical for developing the skills of tomorrow's entrepreneurs and leaders. While significant research examines the content, student learning processes and outcomes, less studied are the entrepreneurship educators and their pedagogical preferences. Following a cognitive process model of decision-making, this study explores how self-efficacy, philosophy of teaching, entrepreneurship training and teaching experience influence entrepreneurship educator preferences to follow either a teacher-centric or a student-centric approach. This study also includes gender in a secondary analysis of the relationships.

The data were collected from 289 entrepreneurship educators in 2021, and fuzzy-set comparative qualitative analysis (fsQCA) was used to obtain configurations of conditions (causal recipes) that lead to teacher-centric or student-centric model. A secondary analysis explores whether there are different configurations of conditions when gender is added to the analysis.

The results of our fsQCA analysis reveal multiple configurations of conditions (causal recipes) that result in a preference for either a teacher-centric or student-centric approach to teaching entrepreneurship. The authors find that teaching experience is the main condition for the teacher-centric model, while self-efficacy and entrepreneurship training are the main conditions for the pathways leading to student-centric model. The fsQCA results also show that the configurations are affected when gender is taken into account in the analysis.

This study, one of the first of its kind, uses a configurational approach to examine pathways that contribute to the teaching preferences of entrepreneurship educators. This paper uses self-efficacy, teaching philosophy, teaching experience and entrepreneurship training as conditions to identify multiple unique pathways that result in either a teacher-centric or student-centric pedagogical model in EE. Notably, differences by gender are also found in this study.