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This study aims to investigate how configurations of boundary objects (BOs) support innovation teams in developing innovative product concepts. Specifically, it explores the effectiveness of different artefact configurations in facilitating collaboration and bridging knowledge boundaries during the concept development process.

The research is based on data from ten undergraduate innovation teams working with an industry partner in a creative industry. Six categories of BOs are identified, which serve as tools for collaboration. The study applies fsQCA (fuzzy-set qualitative comparative analysis) to analyse the configurations employed by the teams to bridge knowledge boundaries and support the development of innovative product concepts.

The findings of the study reveal two distinct groups of configurations: product envisioning and product design. The configurations within the “product envisioning” group support the activities of visioning and pivoting, enabling teams to innovate the product concept by altering the product vision. On the other hand, the configurations within the “product design” group facilitate experimenting, modelling and prototyping, allowing teams to design the attributes of the innovative product concept while maintaining the product vision.

This research contributes to the field of innovation by providing insights into the role of BOs and their configurations in supporting innovation teams during concept development. The results suggest that configurations of “product envisioning” support bridging semantic knowledge boundaries, while configurations within “product design” bridge pragmatic knowledge boundaries. This understanding contributes to the broader field of knowledge integration and innovation in design contexts.

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 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.

Previous literature has identified human resources as a key source of competitive advantage in organizations of all sizes. However, Small and Medium-sized Enterprises (SMEs) face difficulty in comprehensively implementing all recommended Human Resource Management (HRM) functions. In this study, we shed light on the field of HRM in SMEs by focusing on the context of Greek Small and Medium-sized Hotels (SMHs), which represent a dominant private sector employer across the country.

Using a fuzzy-set qualitative comparative analysis (fsQCA) and 34 in-depth interviews with SMHs' owners/managers, we explore the HRM conditions leading to high levels of performance, while taking into consideration the influence of internal key determinants.

We uncover three alternative successful HRM strategies that maximize business performance, namely the Compensation-based performers, the HRM developers and the HRM investors. Each strategy fits discreet organizational characteristics related to company size, ownership type and organizational structure.

To the best of the authors' knowledge this is among the first empirical studies that examine different and equifinal performance-enhancing configurations of HRM practices in SMHs.

Numerous design methods are available to facilitate digital innovation processes in user interface design. Nonetheless, little guidance exists on their appropriate selection within the design process based on specific situations. Consequently, design novices with limited design knowledge face challenges when determining suitable methods. Thus, this paper aims to support design novices by guiding the situational selection of design methods.

Our research approach includes two phases: i) we adopted a taxonomy development method to identify dimensions of design methods by reviewing 292 potential design methods and interviewing 15 experts; ii) we conducted focus groups with 25 design novices and applied fuzzy-set qualitative comparative analysis to describe the relations between the taxonomy's dimensions.

We developed a novel taxonomy that presents a comprehensive overview of design conditions and their associated design methods in innovation processes. Thus, the taxonomy enables design novices to navigate the complexities of design methods needed to design digital innovation. We also identify configurations of these conditions that support the situational selections of design methods in digital innovation processes of user interface design.

The study’s contribution to the literature lies in the identification of both similarities and differences among design methods, as well as the investigation of sufficient condition configurations within the digital innovation processes of user interface design. The taxonomy helps design novices to navigate the design space by providing an overview of design conditions and the associations between methods and these conditions. By using the developed taxonomy, design novices can narrow down their options when selecting design methods for their specific situations.

The COVID-19 pandemic and recent disruptive events are affecting firms’ operations and supply chain networks on a large scale, causing disturbances in supply, demand, production and logistics activities. Although supply chain resilience (SCR) research has received large attention in recent years, the purpose of this paper is to offer an original contribution by exploring how complex configurations and interactions between SCR strategies and capacities can lead to resilience.

This study investigates the configurations of SCR strategies and capacities using a fuzzy-set qualitative comparative analysis.

First, the findings reveal different SCR strategy configurations through the lens of absorptive, reactive and restorative capacities to achieve resilience. Second, this study applies the contingent resource-based view (CRBV) perspective to interpret how organizations can achieve resilience before, during and after a disruptive event. Third, it offers an analysis of different groups of organizations, based on the adoption of different SCR strategies and capacities.

This study identifies a set of equifinal SCR strategies and capacity configurations that can be implemented to cope with a disruptive event and lead to resilience. It also enriches the research addressing the consecutive phases of SCR investments, developing the CRBV perspective. In our results, five solutions describe organizations that invest in absorptive capacities, representing an ex ante readiness.

This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

The purpose is to explore how the configurations resulting from the interplay of last mile logistics practices and firm characteristics are associated with firm performance in an omni-channel context.

Drawing on configuration theory (CT), the authors use fuzzy-set qualitative comparative analysis (fsQCA) to analyze data on 72 Swedish omni-channel retailers.

Four configurations are identified—store-oriented small and medium-sized enterprises (SME's), online-oriented SME's, large store-oriented retailers and large online-oriented retailers. The results show that while offering a wide range of delivery options is necessary to achieve high performance, it is not sufficient, and that returns and fulfilment should be simultaneously considered. For instance, large high-performers leverage their stores and warehouses for fulfilment and returns in an integrated way irrespective of sales channel-mix. However, SME's appear to focus on fulfilment simplicity with less-costly delivery alternatives, where store-oriented SME's leverage stores and the online-oriented counterparts leverage warehouses. Consequently, the authors develop a configurational taxonomy and discuss a set of recipes which provide insights for researchers and practitioners.

The study provides a more comprehensive understanding of the pathways to success, and potential pitfalls, in the last mile logistics context.

This study applies a novel methodology in the field, namely fsQCA, to explore the paths to competitive advantage. It covers a wide range of stages in the LM including back-end fulfilment, delivery and returns. It also provides insight into the logistics practices of both SME's and large omni-channel retailers.

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.

This empirical study uses herd behavior model to explore the role of anchor investors in ensuring fundraising success and overfunding of crowdfunded ventures.

Qualitative comparative analysis (QCA) is applied to find the configurational patterns describing how anchor investors' information disclosure leads to successful financing and overfunding.

Even when the anchor investor's resume is not detailed or the anchor investor has little experience in entrepreneurial investment, success or overfunding can be achieved, provided the anchor investor is a corporation rather than an individual. For individual anchor investors, a detailed resume matters. Overfunding can be achieved even when an individual anchor investor makes a small relative investment, if this small relative investment is compensated for by a detailed resume. Experience in entrepreneurial investment is crucial when individual anchor investors have few previous investments. Regardless of the anchor investor's identity, investment in absolute terms is crucial for crowdfunding success when experience in entrepreneurial investment is low. Such experience must be extensive if the anchor investor's resume is not detailed.

Both entrepreneurs and crowdfunding platforms can benefit from the findings in relation to the design of campaigns that use anchor investors' informational cues to achieve success and overfunding.

The study examines the importance of anchor investors' information disclosure in digital crowdfunding environments, differentiating between individual and corporate anchor investors.

本實證研究使用羊群行為模型, 去探究錨定投資者在確保眾籌活動可達成功籌資以及過多籌資方面所扮演的角色。

研究人員以定性比較分析法、去找出描述錨定投資者的資訊公佈如何帶來成功融資和過多籌資的配置模式。

研究結果顯示、只要錨定投資者不是個人、而是一間公司, 則即使他們的履歷不詳盡, 又或他們對企業投資的經驗淺薄, 也無礙籌資或過多籌資的成功完成。如錨定投資者為個人, 則詳盡的履歷會影響甚鉅。即使個人錨定投資者相對而言參與少量的投資, 但若這少量的投資給他們詳盡的履歷所彌補的話, 則過多籌資仍可成功達到。若個別錨定投資者原有的投資量不多的話, 則企業投資的經驗至為重要。不管錨定投資者的身份是什麼, 若他們對企業投資所持的經驗淺薄, 則按絕對值計算的投資額對眾籌能否成功至為重要。若錨定投資者的履歷不詳盡, 則這種經驗必須是豐富廣泛的。

本研究區分了個人錨定投資者與公司錨定投資者兩者對眾籌的影響, 就此而研究在數碼的眾籌環境裡, 錨定投資者信息公佈的重要性。

研究結果可幫助企業家和群眾募資平台去設計可使用錨定投資者的資訊提示來達至成功眾籌和過多籌資的活動。