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Managing resources is crucial for firms to gain competitive advantages and succeed, particularly for startups with limited resources. It is important to understand how digital startups in general and digital academic spin-offs (ASOs) in particular may orchestrate their resources to optimize value. This paper integrates the resource-based perspective with digital entrepreneurship to analyze the resource configurations leading to success of digital ASOs.

The paper adopts an inductive approach and applies qualitative comparative analysis (QCA) on a longitudinal dataset of digital ASOs to identify the resource configurations for a successful outcome.

The authors' paper identifies two main paths to success among digital ASOs, consisting of five distinct resource configurations. The first path is termed “market exploiters” that operate in favorable market conditions where specific technological resources and research collaboration resources are lacking. The second path involves “technology explorers” that combines both technological and commercial resources to achieve success.

By outlining distinct pathways to the success of digital ASOs, this paper contributes to the digital academic entrepreneurship literature and the resource-based view of entrepreneurial firms. The paper also suggests implications for policymakers and managers in managing resources for the success of digital ventures.

By exploring the resource configurations leading to the success of ASOs commercializing digital technologies, the paper shows that favorable market conditions and complementary resource configurations can be alternative pathways to success.

The main objective of this paper is to study the optimal system for series systems with mixed standby (including cold standby, warm standby and hot standby) components.

The paper deals with the reliability and availability characteristics of four different series system configurations. The failure time of the operative, hot standby and warm standby are assumed to be exponentially distributed with parameters λ, λ, and α respectively. The repair time distribution of each server is also exponentially distributed with parameter μ.

The mean time to failure, MTTF_i, and the steady‐state availability A_i(∞) for four configurations are examined and comparisons made. For all four configurations, the configurations are ranked based on: MTTF_i, A_i(∞), and C_i/B_i where B_i is either MTTF_i or A_i(∞). Obviously, the system with height MTTF_i and A_i(∞), do not need frequent maintenance, i.e. less maintenance.

Numerical results for the cost/benefit measure have been obtained for all configurations. It is interesting to note first that the optimal configuration using the cost/MTTF_i measure is configuration 4. Next the optimal configuration using the cost/A_i(∞) measure is configuration 2.

The purpose of this paper is to research the impact of hybrid series‐parallel and parallel‐series system configurations on system performances based on system reliability and to develop a configuration model to meet the requirement of reconfigurable manufacturing system (RMS).

Based on the criterion of system reliability, a RMS configuration model is presented – the hybrid parallel‐series model with waiting system characteristics. The configuration model is evaluated from reliability, productivity, and cost by combining system engineering theory, Boolean algebra methodology with statistical analysis theory. The model reliability has been used to ameliorate by adopting the integrated algorithm based on Shrama and Misra optimization algorithm.

The need for application of this method and model – some constraints must be limited, the hybrid parallel‐series configuration is superior and the integrated algorithm is effective to RMS system configuration.

Cost constraints, equipment weight constraints, and function independency of equipment are main limitations.

The model and method have been used to ameliorate the reconfigurable automobile parts product line in SH automobile motor company of Shanghai. The operation result illustrates the validity of this configuration model and algorithm.

The new RMSs configuration model has been proposed. The new algorithm is proposed to ameliorate and optimize a reconfigurable product line with the integrated algorithm based on Shrama and Misra algorithm. The actual running effect is significant.

This paper contains a generalization of the existing theory of Garden of Eden configurations in tessellation automata. We consider spaces of at most two dimensions but with transition functions having arbitrarily large neighborhoods. A configuration c is said to be Garden of Eden of degree n just in case there is no configuration from which c can arise in n time steps; c is Garden of Eden of minimal degree n just in case there is no smaller m such that c is Garden of Eden of degree m. Necessary and sufficient conditions for the existence of Garden of Eden configurations of higher degree (and of degree 1) are established. Results are obtained relating decision procedures for Garden of Eden configurations of degree one to decision procedures for Garden of Eden configurations of higher degree.

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 examine the cost/benefit (C/B) analysis of four configurations for a repairable system with two primary components/units and one standby.

The four configurations are set to the status of the detection and switching failure of standby, as well as the possible reboot of failed units. The time to failure for each of the primary and standby is assumed to follow an exponential distribution. The time to repair and the time to reboot is assumed to have a k‐stage Erlang distribution. The paper develops the explicit expressions of the mean time to failure (or MTTF) and the steady‐state availability (or A) for four various configurations and performed some comparative analysis. Based on the C/B criterion, comparisons are made for specific values of distribution parameters and of the costs of the units. The four various configurations for a repairable system are ranked by using MTTF, A and C/B, where B is either MTTF or A.

Although it is uncertain which configuration is the optimal one among the four ones, the paper provides much comparative information to manager and manufacturers. Managers can use these results to choose the best configuration according to the used data of parameters and selections of the weight of MTTF or Cost/MTTF.

This paper shows a comparative analysis for a two‐unit online repairable system with one standby under four different configurations. It is the first discussion of comparable work on reliability and availability models for redundant repairable systems in which the units are characterized by detection, switching failure and reboot.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.

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).

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.

The growing literature on complementarities has drawn attention to how the effects of different organizational structures, practices, and institutions are interdependent. Rather than one best way of organizing, complementarities suggest that the effectiveness of one organizational element may be dependent on the presence or absence of another particular element. Consequently, organizational arrangements often display “multiple equilibria” or what is known as equifinality, whereby multiple pathways may lead to the same or similar outcomes. While being a source of theoretical innovation, the configurational nature of complementarities has posed a number of challenges. This chapter reviews the emerging literature on complementarities to identify a series of conceptual challenges related to understanding complementarities as organizational configurations, and examines the methodological challenges in studying how such elements combine to produce joint effects on performance. The chapter argues that new set-theoretic methods using Qualitative Comparative Analysis (QCA) may present a very useful methodological alternative to studying complementarities. The chapter illustrates this potential by re-analyzing past work by Aoki, Jackson, and Miyajima (2007) on relationships between ownership structure, board structure, and employment practices of listed firms in Japan to show evidence of complementarities associated with hybrid configurations that combine market and relational forms of organization.