Blockchain-based systems are increasingly encouraged to prevent counterfeiting, yet literature emphasizes on challenges and adoption perceptions at the supply chain level over designing actionable solutions. Addressing this gap, the present study adopts a Design Science Research (DSR) process to propose a blockchain-enabled counterfeit prevention solution that integrates a Proof-of-Lightweight-Voting (PoLV) consensus to enhance traceability, security, and transparency while achieving low energy consumption, high transaction throughput, and efficient node-commit latency for scalable adoption. By implementing the Stimulus–Organism–Response framework, the solution integrate self-efficacy and trust as key drivers of behavioral intention toward blockchain adoption, reflecting how confidence in decentralized self-service technologies strengthens supply chain actor engagement. Results of the study advance the technology adoption and digital supply chain literature by: (i) proposing a supply-chain-inclusive, lightweight blockchain solution to prevent counterfeit; (ii) elevating self-efficacy from an individual-level construct to a multi-level capability shaping collective adoption and usage; and (iii) integrating two interrelated forms of trust that condition blockchain adoption. The solution provides practitioner guidelines for upstream and downstream supply chain actors to combat counterfeiting.

Digital technology diffusion is reshaping innovation across supply chain dynamics and ecosystem partners. Prior work often looks at one firm or uniform settings, missing how technology diffusion need to be orchestrated by ecosystem leader across diverse suppliers and other actors. To address this gap, this study employs an exploratory case study of the intelligent vehicle ecosystem, focusing on an original equipment manufacturer (OEM) and six supply chain partners. Although positioned in the supply chain, these actors influence the wider ecosystem thereby affecting technology diffusion beyond dyadic ties. Drawing on 35 interviews, observations, and secondary data, the research advances the technology diffusion and innovation ecosystem literatures in three ways. First, it highlights the evolving role of focal actor as ecosystem leader, demonstrating their progression from transformational to collaborative and ultimately empowering roles across different phases of digital technology diffusion. Second, it identifies three orchestration mechanisms, namely knowledge orchestration, incentive aligned orchestration, and market driven orchestration, and specifies when each should be deployed in response to partner-specific requirements. Third, it offers a novel perspective on how ecosystem leaders shift value propositions to include both core and peripheral partners. From a practical standpoint, the study offers OEMs actionable guidance to diagnose their diffusion context and select appropriate orchestration mechanism. It also provides policymakers with insights for designing targeted instruments that strengthen digital diffusion and support sustainable industrial growth.

Many firms set ambitious sustainability goals but these are frequently “displaced” by proxy goals that are easier to track and measure. However, the specific types of goal conflicts that follow from this displacement are poorly understood. We conducted a case study of circular innovation initiatives at a global MedTech company and identified three types of goal conflicts: inclination conflict, insufficiency conflict, and estimation conflict, along with the organizational processes aimed at reducing the negative impact of these conflicts. Our study contributes to the circular economy and organizational goal theory literatures by uncovering how goal displacement and goal conflict influence outcomes of circular innovation initiatives. By linking these dynamics to strategic decision-making in the front end of innovation, where new circular innovation initiatives are established, we demonstrate how business strategies can help align organizational goals with long-term sustainability ambitions, thereby helping companies deal with trade-offs, rebound effects, and regulatory pressure.

Sustainable value creation (SVC), while increasingly prioritized, remains challenging for large manufacturing firms because it requires balancing environmental responsibility, economic performance, and social well-being. Meeting these expectations demands a clear understanding of regulatory requirements, market dynamics, and environmental conditions in a cost-effective and reliable manner. Open data (OD) or Open Governmental Data (OGD), referring to publicly accessible and reusable free datasets, offers a potential solution that industrial firms can draw upon to support strategic and operational decisions. Although few studies acknowledge the benefits of OD, there is limited understanding of how firms actually use it in practice for SVC. To address this gap, this study identifies seven industrial practices, spanning strategic and economic imperatives, social-environmental responsibility, and regulatory and operational activities, through which large manufacturers leverage OD to improve SVC. The analysis is based on 27 in-depth interviews from 11 leading Indian manufacturing firms, complemented by a validatory focus group. The study contributes theoretically to sustainability and OD literature by demonstrating how OD supports all three dimensions of sustainability and extends its influence beyond firm boundaries to shape sustainability performance across supply chains. It also offers managerial guidance on integrating OD-based practices to report progress towards SDGs. For policymakers, the study provides insights to strengthen the design and relevance of OD platforms, ensuring better alignment between OD providers and industrial users.

Twin transition, the concurrent development of digitalization practices and circular practices, are believed to be the key to firm performance. However, empirical evidence is currently scarce regarding the effect of twin transition on firm performance and the complementary practices that enable and realize it. This study draws on a survey of 188 Swedish manufacturing firms and employs PLS structural equation modelling to test the hypothesis. The results indicate that firm performance can be improved through digitalization practices but with circular practices as a mediator. Moreover, our results show a significant and positive moderation effect of supply chain orchestration and supply chain business model innovation as complementary mechanisms for enabling and realizing the process. This implies time sequencing between the two twin transition dimensions. These results carry theoretical implications for twin transition research and circular economy literatures. The results also provide novel managerial insights by showing that digital investments must be coupled with early orchestration of supply chain partners and aligned business model innovation to effectively scale circular practices and realize performance benefits.

Twin transition, the simultaneous advancement of technology and circular practices, poses an under-operationalized challenge for industrial firms, particularly in balancing the pace of both dimensions. As a result, twin transition often remains a strategic aspiration rather than an actionable practice. To address this gap, we propose a route optimization model that operationalizes twin transition. Framed within a Socio-Techno-Ecological Systems perspective and developed using design science research, it mandates reduced CO₂ emissions as the default optimization criterion while allowing configurable parameters (i.e., distance, time, and cost). By integrating genetic algorithm with machine-learning techniques, the model enhances adaptive performance in real-time. Achieving 97.7% prediction accuracy with random-forest classifier, the model is validated on established datasets to ensure generalizability. By continuously processing real-time inputs on traffic, road conditions, environmental data, and regulatory constraints, it can improve route safety, efficiency, and compliance. This study aligns technological progress with environmental objectives and societal expectations and offers both theoretical and managerial contributions by helping industrial firms reduce CO₂ emissions, strengthen supply-chain resilience, and accelerate circularity implementation.

This research investigates the complex career dynamics of dual-career women, focusing on the interrelationships among self-efficacy, career salience, and task accomplishment. The study examines these relationships while considering dyadic cohesion and flexible work options as moderating factors. Utilising a sample of 175 dual-career women with continuous career trajectories, the research employs structural equation modelling to analyse these relationships. The findings reveal that self-efficacy significantly influences task accomplishment, mediated positively by career salience. Furthermore, dyadic cohesion and flexible work options serve to strengthen these relationships. Grounded in Social Cognitive Career Theory (SCCT), the study explores how psychological and social factors impact task accomplishment underscoring the significance of sustainable careers and informing flexible organisational policies supporting dual-career women that enhance gender parity in the workforce. Our study reinforces human resource development’s (HRD) pivotal role in enabling career sustainability by aligning individual aspirations with inclusive organisational practices. It contributes to HRD literature by linking self-efficacy and career salience with supportive work environments for dual-career women. 

This study explores how governmental and regional investments in the digital economy foster the emergence of new industries and the region's sustainable competitiveness. In particular, we focus on the creation of the big data comprehensive pilot zone (BDCPZ) in China that serves as a proxy for digital economy advancement initiatives. Employing a quasi-experimental design and a panel dataset from 31 Chinese provinces (2009–2020), this study uses the difference-in-differences approach to evaluate the impact of BDCPZ on the region's competitiveness. Our findings show that enhanced digital economy advancement significantly boosts the creation of new industries, such as the creative industry. This study advances understanding by linking economic development and the business environment and conducting a heterogeneity analysis to identify the most influential characteristics for new industry creation. These characteristics are categories that fall under regional ecosystems—including talent mobility, innovation culture, and financial institutions—and act as mediators of this relationship, offering valuable insights for stakeholders to enhance regional sustainable competitiveness and innovation.Managerial relevance statement: This study offers valuable managerial insights for managers, policymakers, and industrial networks to apply in practice. By understanding the importance of regional talent mobility and strong innovation culture, managers in traditional engineering firms can experiment with novel strategies like rotational mobilizing programs to increase agility and diversify into creative sectors. Policymakers can support these efforts in three ways: by incentivizing digital economy advancements like automation, application of emerging technologies through tax breaks and grants; by establishing cross-sector innovation hubs where traditional industries collaborate with tech startups and creative enterprises; and by focusing on training and reskilling programs. Finally, industrial networks, i.e. consultancy networks drive strategy and collaboration, are encouraged to educate financial institutions on how to assess creative industry projects and facilitate talent mobility by linking traditional engineering firms with SMEs and startups to acquire valuable cross-sector experience, foster innovation, and contribute to the development of new industries.