Glenn Charles Parry

The personalisation–privacy paradox captures the tension between using personal data for personalised services and respecting individuals’ privacy. This study adopts a holistic research framework to clarify the paradox’s core challenges, evaluate existing solutions, and examining a user-centric approach. First, a systematic literature review across information systems, marketing, and management reveals that current solutions often prioritise privacy, framing the paradox as a “dilemma” rather than a persistent tension between privacy and personalisation. Personal Data Stores (PDS) are identified as a technical solution to managing the paradox: decentralising data control, enabling users to determine precisely what they share and thereby reducing privacy risks; and unlocking richer personalisation by integrating multiple data sources and facilitating transparent data markets.  A survey empirically tests user perception of PDS, showing that individuals who understand the approach believe it mitigates their privacy concerns without compromising service customisation. These findings suggest that PDS offer a dual response, rather compromise, allowing firms to manage the paradox.

This Special Issue editorial summarizes the multifaceted implications of Distributed Ledger Technologies (DLT), particularly blockchain, emphasizing the necessity of integrating temporality and contextuality into understanding their impacts. It synthesizes contributions from various empirical studies that reveal blockchain's role as a strategic enabler in addressing organizational and supply chain challenges, such as fostering trust and enhancing efficiency. However, each paper in this Special Issue underscores that the efficacy of blockchain is contingent upon contextual factors— ranging from technological readiness to cultural norms. By linking the concepts of temporality and context, this Special Issue sheds light on how varying circumstances shape the adoption and effectiveness of DLT applications. Key themes include the interaction of technological innovation with socioeconomic and political landscapes, the conditional nature of trust built through blockchain, and the necessity for contextual sensitivity in implementation strategies. Collectively, these contributions affirm that successful DLT integration is not merely a technological challenge, but a dynamic process influenced by a network of variables, requiring careful management of timing and contextual forces. The findings advocate for a nuanced understanding of DLT as a socially embedded infrastructure that holds potential for mitigating global challenges when aligned with appropriate values, policies, and practices.

Blockchain technology has been praised as a means to improve collaboration within and beyond the value chain. Key features, such as transparency and the immutability of data in a blockchain, lead to higher quality and enhanced product lifetime, improved circularity, and, ultimately, more reliable supply and cheaper offerings. Nevertheless, the promises of blockchain technology are not mirrored in reality. Based on a multiple-embedded case study from the wind turbine industry, this paper sheds light on how various paradoxes on the individual, intra-, and inter-organizational levels hamper the successful implementation of blockchain technology. Unlike general B2B collaboration challenges, these paradoxes are rooted in blockchain's technological architecture—particularly its decentralization, immutability, and trustless nature—which introduce tensions that are both temporal and contextual. These paradoxes are both identifiable on the contextual level (the setting in which blockchain technology is implemented) and on the temporal level (the impact of both prior experiences and the perception of future commitments and collaboration). Theoretically, the paper provides a more nuanced perspective on the existing literature on blockchain technology, which has traditionally been marked by transaction-cost-based frames of understanding while emphasizing the role of individuals and organizations in blockchain adoption. The presented analysis also has managerial implications in terms of the essential need to understand blockchain as more than a mere (software) implementation exercise.

The reliable fixed-charge facility location problem extends the fixed-cost facility location problem by incorporating facility unreliability. This paper addresses a novel capacitated version of the reliable fixed-charge facility location problem, where the failure probability of each facility is site-dependent, differing from existing literature models. Additionally, facilities are assumed to have limited capacity for demand allocation, with the option to increase capacity to a predetermined value in case of supply chain disruptions. To solve this problem, we develop a non-linear mixed-integer programming formulation and present its linear version. Given the NP-hard nature of the problem, we propose a novel Relax-and-Fix heuristic for its solution. We evaluate the efficiency of the proposed algorithm by solving a variety of experimental instances with different network sizes. Results demonstrate that the Relax-and-Fix heuristic improves upper bounds for problem instances and achieves this within a shorter computational time. Furthermore, sensitivity analysis is conducted on capacity and failure probabilities, and relevant results are presented.

Additive Manufacturing (AM), an innovative technology, plays a pivotal role in localising supply chains, with the integration of digital technologies further enhancing production flexibility and system resilience. However, AM increases digitalisation in the supply chain, which brings a range of cybersecurity vulnerabilities. Consequently, a comprehensive risk assessment framework is necessary to assist decision-makers considering AM systems. Prior research has employed Composite Indicators (CIs) for risk evaluation, aggregating sub-indicators to assess risks. However, the approach to determining suitable weights for these sub-indicators presents notable limitations such as limited discriminant power, non-unique outcome, subjective assumption on weight preference. To solve the limitation in determining the weight, this paper introduces a multi-level (three-stage) risk assessment model based on the Multiplicative Non-Parametric Approach. This model provides a thorough evaluation of threats within AM systems, considers both individual and industrial perspectives, and determines the global weights of each sub-indicator. The empirical analysis demonstrates that the proposed multi-level model effectively identifies appropriate weights for the sub-indicators, resulting in outcomes that closely align with the original assessment results. The model's performance improves as the number of analysis stages increases, reaching its peak in the final stage of analysis. ARTICLE HISTORY

Green innovation is essential for sustainable development worldwide. This study investigates how university engagement, coupled with the Artificial Intelligence (AI) capabilities of industrial actors, enhances regional green innovation performance within the framework of Regional Innovation Systems (RIS) theory. Using a longitudinal dataset of 31 Chinese provinces from 2008 to 2019 and employing a dynamic panel analysis with the GMM estimator, the results show that university embeddedness in regional innovation networks significantly increases green innovation performance. Contrary to previous studies , our research shows that within RIS, absorptive capacity plays a more critical role than AI in enhancing the effectiveness of knowledge transfer and exploitation, highlighting the primacy of human and organisational factors over technological tools alone. This research advances RIS theory by highlighting the critical role of university-embedded networks and systemic interactions among heterogeneous actors, demonstrating higher-order returns from knowledge exchange beyond dyadic partnerships, and enriching the understanding of the integration of AI into RIS frameworks.

Purpose – Product returns in omnichannel retail are wasteful and generate significant financial and environmental impact. Returns systems often suffer from low efficiency and effectiveness. Innovative technology and service solutions are proposed by an increasing number of startups, with many enabling new more effective and sustainable pathways for returned products to be sold again whilst conserving product value. Design/methodology/approach – By adopting an engaged research approach involving close dialogue with retailers as well as technology and returns service providers, this paper explores the implications of adopting these innovations and the outcomes for retailers and suppliers, employees, and consumers. Using the lens of the retail technology adoption framework by Shankar et al. (2021), this paper investigates how innovation in technology and process can enable alternative pathways for consumer product returns. Some offer added value to consumers, and many reduce waste and allow retailers to conserve the value of returned products.

Findings – Retailers increasingly take control of secondary markets to increase the retained value of returned products, shorten pathways to resale, and increase resale rates. Peer-to-peer returns, “trying whilst the courier waits,” and the returns ecosystem approach all optimize returns management, impacting both the forward and reverse logistics of retail.

Research limitations/implications – The study focused on fashion items, but offers relevance for household items, furniture, sports equipment, and other items with similar characteristics. Originality/value – This paper suggests extending the retail technology adoption framework to include the aspect of value conservation, in addition to the existing value-adding and commoditising features. The new pathways enable retailers to address the challenges of high returns rates, financial pressure, whilst reducing environmental impact.

To understand the slow adoption of blockchain technology by organisations, we conduct a systematic literature review of adoption factors using a mixed-methods approach. Using thematic analysis, 880 factors are identified and grouped into 29 themes, which offer a comprehensive overview of the literature. Using statistical analysis, the identified factors are dissected into technological (T), organisational (O), and environmental (E) dimensions (the TOE framework). Themes are further classified as barriers (B), enablers (En), and ambiguous (A) to describe a firm's readiness for blockchain adoption (the BEnA framework). We emphasise the multidi-mensionality of adoption factors across the TOE dimensions and the conditionality of adoption enablers across the BEnA dimensions. Analysis of research trends shows that recent blockchain adoption literature has focused on elaborating upon existing research themes (involution) rather than on developing new themes (evolution). Based on our analyses, we propose future research directions, including scrutinising the interdependence and multidimensionality of blockchain adoption factors, further examining factors with conditional or unclear effects on adoption, and broadening the contextual, temporal, and theoretical aspects of blockchain adoption research. Highlights: • Identified 880 factors and 29 themes of blockchain adoption by organisations. • Developed multidimensional theoretical frameworks to analyse factors and themes. • Adoption barriers are mostly unambiguous, while enablers are often conditional.

Business model frameworks provide a useful lens through which to examine how organisations can create social and economic value.

 Work is based on an original request from practitioners to provide insight that will help in the creation of a business that supports ex-offenders through employment and training

 The social challenge of reforming prisoners for society, and economic challenge of finding skilled committed employees is addressed simultaneously by social enterprises (SE)

 Using a business model framework this paper gives insight into how organisations undertake SE work to deliver social and economic value.

 Five diverse case examples are provided, giving insight into different Social Enterprise organisational forms: charities, not-for profit, government owned, private and limited companies.

 Business Model based analysis shows how an SEs hybrid structure has dual value propositions, creating both social and economic value using under-valued human resource