Digitalization supports business model innovations that reconcile economic and environmental benefits in various ways. Yet, the variety of sustainability-advancing, digitally enabled business model innovation (SDBMI) has not been explored systematically. We believe that acknowledging the heterogeneity of SDBMI can help both scholars and practitioners to better understand this important topic. Our editorial, therefore, goes beyond outlining the motivation for the special issue and introducing the featured articles. We also develop a typology of SDBMI and illustrate the eight archetypes that constitute this typology with industry examples. Finally, we propose a research agenda to guide future research on SDBMI. .

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.

The increasing complexity of organized cybercrime, fueled by rapid technological advancements and global interconnectedness, challenges traditional criminological theories and fragmented policy responses. This study conducts a comprehensive literature review using both systematic and snowballing methods across two databases. From a review of 92 articles, the study identifies: (1) major journal publications in organized cybercrime, (2) major theoretical foundations employed by academic research in organized cybercrime, and (3) significant gaps in current theoretical frameworks and practical interventions, particularly concerning informal governance structures, ideological cohesion, and technological enablers that sustain cybercriminal ecosystems. The study proposes (4) an organized cybercrime ecosystem framework, drawing on criminology, institutional theory, technology adoption models, and socio-technical perspectives, and (5) targeted intervention strategies to disrupt the operational logic of organized cybercrime. Theoretical and managerial implications, along with important limitations and avenues for future empirical research, are discussed at the end of the paper.

The rapid advancement of IoT technologies has enabled new forms of data flow among devices, people, and organizations. This has brought about the emergence of innovative business models with increasingly sophisticated value propositions. This study develops a typology and progression framework for IoT business models, highlighting how value creation and capture evolve as firms integrate IoT technologies. Based on a systematic literature review and multiple case studies, the present research identifies three distinct business model archetypes-namely, connectivity, servitization, and data ecosystems. Each archetype is characterized by specific mechanisms of value creation and capture. The resulting framework provides insights into support firms seeking to align IoT investments with their capabilities and market positioning. By offering a structured view of business model sophistication, this study contributes to the theoretical understanding of IoT business models, business model sophistication, and data ecosystems, while also informing managerial practice.

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.

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.