This research assesses the adoption of artificial intelligence (AI)-based batch order picking in a warehouse, focusing on benefits, challenges, and critical success factors. Using customer order data and simulation, the study employs a quantitative approach, combining mathematical and statistical estimations with qualitative examinations centered on interviews with the warehouse staff, its Enterprise Resource Planning (ERP) developer, and the AI developer. The findings of this mixed-method study reveal that the AI-based order-picking system (AI-based system) has improved order-picking efficiency by reducing travel distance and time. Nevertheless, challenges hinder maximum utilization of the system. In addition, the research highlights critical success factors and other benefits of adopting the system tailored to warehouse management. Understanding the lessons learned in this research is essential for businesses seeking to adopt AI to enhance their efficiency.

Femvertising, a progressive advertising approach, combines product promotion with empowering messages for women. Recent trends, especially in feminine hygiene, have shifted towards such empowering narratives, moving away from traditional stigmatized portrayals of women. This research investigates how femvertising impacts consumer perceptions in feminine hygiene advertising. Focusing on transformational versus informational advertising, we examine femvertising's effects on purchase behavior together with the role of perceived authenticity, and the impact of consumers' construal level mindset. The findings from four experimental studies reveal that transformational messages significantly boost purchase behavior more than informational ones. Key to this effect is the alignment of message framing with the consumer's construal level and the mediating role of perceived authenticity. These results provide critical insights for brands using femvertising strategies, emphasizing the importance of authentic, resonant messages aligned with the target audience's mindset.

Digital transformation represents a compelling opportunity for manufacturing companies to enhance their competitiveness. This transformative journey offers myriad possibilities, including improved connectivity between workers and machines, as well as seamless machine-to-machine interactions. However, many manufacturing companies encounter challenges when attempting to implement digital transformation effectively. The process of digital transformation is often slow, and most companies find themselves in the early stages of adoption, grappling with the ambiguity surrounding the associated technologies. A systematic approach for the implementation of digital transformation is still elusive for many manufacturing companies. The number of studies exploring digital transformation is increasingly growing, encompassing various sectors and domains. However, within the manufacturing sector, there remains a need for further research and clarity on systematic implementation approaches. To address these issues, this research undertakes a comprehensive analysis to identify the critical factors that influence digital transformation in the manufacturing sector. The objective of this research is to identify the factors that drive the success of digital transformation in manufacturing companies while also uncovering factors that, when neglected, could lead to failure. Through a systematic literature review, this research identifies 11 critical factors. These factors serve as the basis for developing the ARTO model, a structured framework comprising four distinct categories: "Awareness-related factors," "Readiness-related factors," "Technology Selection-related factors," and "Operations-related factors." Moreover, this research incorporates expert perspectives gathered through a survey to refine the ARTO model. This study offers the ARTO model and digital transformation definition as practical tools for successfully implementing digital transformation in manufacturing companies, while also delineating the intricate relationships among the crucial factors. By shedding light on the factors underpinning digital transformation in the manufacturing sector, this research contributes to the ongoing discourse and facilitates more effective adoption of digital transformation strategies.

The era of digitization coincides with a growing interest in social and environmental sustainability. Management scholars, therefore, turned their attention to the intersection of both trends, seeking a better understanding of how firms can manage digital sustainability. Business models are a central element in the strategic management of digital sustainability. Due to the diverse roots in the digitization literature, the sustainability literature and the business model literature, previous work on digital-sustainable business models is highly fragmented. We, therefore, develop a strategic management framework and conduct an integrative literature review to synthesize fragmented insights, covering 134 studies published between 2007 and 2023 in leading academic journals. Examining the synthesized body of knowledge from the lens of affordances and our framework's inclusive strategic management perspective, we then identify promising avenues for further strategy research. Among others, future research should examine complementarities and conflicts between the three business model dimensions (value propositions, value creation and delivery processes, value capture mechanisms), between multiple options within each dimension, between different digital technologies, between various digital affordances, between digitalization and sustainability and between the outcomes of the triple-bottom-line. More efforts should also be directed towards the antecedents and boundary conditions of digital-sustainable business models and towards questions of generalizability, especially towards generalizable theoretical mechanisms. Our framework, synthesis and research agenda support strategy scholars in advancing our understanding of business models for digital sustainability.

Diversity in femvertising-advertising that empowers women through inclusive representation-has gained significant traction in recent times. Yet consumer perceptions of its authenticity and effectiveness remain underexplored. This study examines the impact of diverse representation in femvertising on brand attitudes, purchase intentions, and consumer behavior. Findings from four experimental studies reveal that diversity enhances brand perceptions and purchase intentions, mediated by perceived brand authenticity. However, political orientation moderates these effects; liberals respond more positively to diverse advertisements while conservatives prefer homogeneous representations. These insights highlight the importance of authenticity in femvertising and the potential risks of tokenism and political polarization. The research contributes to advertising knowledge by incorporating intersectionality, examining behavioral outcomes, and addressing the ideological divide in consumer responses. Practical implications suggest that brands should balance diversity with authenticity to foster inclusivity without alienating key audiences. Future research should explore the optimal level of diversity, long-term effects on brand loyalty, and the role of AI-driven personalization in diverse advertising.

With returns imposing a growing burden on retail supply chains, major e-commerce platforms are increasingly implementing size recommendations to curb returns. Based on a fit valence and fit reference framework, we test whether customers using the size finder are more likely or less likely to return products. We use confidential data from a major fashion e-commerce platform in Sweden that introduced a size finder based on customer-supplied information on weight, build, hips, waist, shoulders, leg-to-torso length, and body shape. In a sample of 496,365 items ordered by 75,707 customers from 113 countries between July 2015 to April 2022, those using the size finder are 0.65% more likely to return an item. The findings are robust to a variety of econometrics tests. Furthermore, machine learning analysis based on gradient boosted trees shows that size finder is among the least important features in predicting returns. However, for each unit quarterly increase in the use of the size finder with purchased items, the customer lifetime value (CLV) increases by 7.51% in the next quarter and 5.53% in the subsequent quarter. Post-hoc interviews with executives in the e-commerce sector demonstrated that, when implementing size recommendation tools, managers in fashion retailers must weigh a small increase in returns against higher CLV from repeat customers.

AbstractPurpose – Island entrepreneurship is a relatively new research direction within entrepreneurship research. Mostpreviousresearch hasfocused on empiricalstudiesin specific island contexts. The purpose of this article isto (1)investigate how island entrepreneurship has been explored, (2) develop a theoretical foundation forconceptualising island entrepreneurship through the lens of entrepreneurial ecosystems theory and (3)propose a set of future research directions to advance the field

Design/methodology/approach – This article employs a literature review methodology, analysing 89 articlesthrough text analysis. The analysis identified 18 interrelated categories and then organised them into seven overarching themes.

Findings – Many studies highlight the key role of collective action and cooperation as prerequisites forentrepreneurial success. The main finding is that the entrepreneurial ecosystems approach can serve as anumbrella for addressing various research gaps, complex contexts and settings influencing entrepreneurialinteractions, resource use and the type of local institutions that either support or hamper entrepreneurialactivities on islands. This approach generates new knowledge to promote actionable entrepreneurial solutionsand policies for islands.

Originality/value – The paper’s originality lies in applying the entrepreneurial ecosystems approach to thespecific context of island entrepreneurship. It offers a holistic perspective that addresses previouslyunderexplored complexities, such as interactions between entrepreneurs, resource usage and the role of localinstitutions on islands.

Purpose - This study proposes a distinct ecosystem orchestration concept, with the idea to address some of the technology and value proposition uncertainties that can occur during the birth phase of an innovation ecosystem linked to its actor's relation with each other as well as policymakers and customers. In order to better explain the proposed orchestration concept, Mobility as a Service (MaaS), a technological and social complex, innovative ecosystem, was chosen. Design/methodology/approach - The suggested touring orchestrating model emerges by utilizing multiple case study analyses, focusing on ecosystem construct, orchestration mechanism, and various actors of five selected mobility as service use cases, each presenting one category with unique characteristics. The analysis is complemented by a multi-vocal literature review (MLR) of secondary data. Findings - The study findings reveal substantial barriers to successful collaboration between innovation ecosystem actors, using traditional ways of orchestrating the ecosystem due to competition and unwillingness to invest for the benefit of others or risk of losing their customer base to competitors by joining a MaaS ecosystem, particularly when a new actor as orchestrator is onboarded. Additionally, there is a need to increase incentives and to enhance offerings in order to generate demand and attract stakeholders toward a new innovation ecosystem like MaaS. Research limitations/implications - Most of the models reviewed in this study are predominantly successful examples of mobility as a service originating from northern Europe and the Baltic region, potentially shaped by the characteristics of these markets. This regional focus represents a limitation of the study. Furthermore, the study's conceptual nature and lack of practical testing and empirical data support are additional limitations which could be addressed in future research through empirical investigation. The results of this study could assist in shaping future research and contribute to the development of more effective orchestration models and stakeholder management frameworks for managing innovation ecosystems across different industry contexts. Practical implications - The proposed touring orchestration model (TOM) provides insights not only for the actors in transportation industry but also for providers in other industries; on how to manage uncertainties and risks tied to technology and value proposition while advancing seamless cross-firm collaboration with other market actors during the formation of an innovation ecosystem. It can also facilitate the emergence of unexplored cross-industry business models by leveraging various data-sharing frameworks. The proposed model can also streamline processes and lower costs for policymakers in encouraging transportation and mobility providers to participate in MaaS, as it reduces risks and can offer greater financial advantages for these stakeholders. Originality/value - The findings of this study enhance the evolving ecosystem literature by exploring orchestration amid technological and value proposition uncertainties. Additionally, this study contributes to the expanding research on MaaS business models and ecosystem orchestration by leveraging data as a service-sharing model.

Entrepreneurs often encounter challenges during their entrepreneurial journeys that may lead to disengagement from their business ventures. While the concept of disengagement has been extensively studied in the human resource management literature, there remains a relative lack of understanding regarding entrepreneurial disengagement. This study, grounded in the psychological theory of engagement and the job demands-resources (JD-R) theory, focuses on physical disengagement and investigates whether emotional disengagement precedes it. Moreover, recognizing the significance of entrepreneurs' comprehension of their team vision, we hypothesize that team vision serves as an antecedent to both emotional and physical disengagement. Specifically, we investigate whether emotional disengagement mediates the relationship between team vision and physical disengagement. Building on JD-R theory, we examine the moderating roles of family emotional support and social networks' emotional support in this mediation relationship. Our findings, utilizing data obtained from 184 entrepreneurs in the UK, indicate that emotional disengagement fully mediates the relationship between team vision and physical disengagement. Interestingly, our results suggest that while social networks' emotional support moderates this mediation relationship, family emotional support does not. These insights carry significant theoretical and managerial implications for understanding and addressing entrepreneurial disengagement.

There is a growing recognition that firms increase their collaboration breadth by opening their boundaries to more innovation partners, sourcing and integrating complementary knowledge, skills, and resources and, in turn, improving their innovation performance. However, not all firms benefit equally from collaboration breadth. We argue that the literature has not considered important contingency factors that can mitigate such benefits. This paper enhances understanding of the relationship between collaboration breadth and innovation performance by contending, and empirically confirming, that the magnitude and direction of this association depend on the type of constraints the firm faces. Drawing on organizational learning theory, it is argued that firms encountering financial, knowledge, and institutional innovation constraints will compromise the effects of their openness. The empirical findings suggest that innovative firms face challenges balancing trade-offs between a broad collaboration network and high financial, knowledge, and institutional constraints.