Purpose This study examines how robot-related social and humanlike cues shape consumers' perceived morality and perceived ethics of service robots, and how these appraisals impact trust and intention to use. Design/methodology/approach A total of 257 usable surveys were collected from diners who have engaged with a service robot at a fine dining restaurant. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings A robot's perceived mind of its own and social presence significantly influenced consumers' perceived morality and perceived ethics. Perceived ethics and social presence significantly influenced trust, while perceived morality and mind of its own exhibited nonsignificant effects on trust. Trust strongly predicted intention to use. Mediation analysis confirmed the intermediary effects of trust between social presence, perceived ethics and intention to use. Practical implications The findings suggest that managers should balance robot autonomy with predictability, prioritize ethical transparency over simulated moral reasoning, design social presence carefully and treat trust-building as an operational process involving reliability, service recovery and escalation protocols. Originality/value The study contributes to service robot research by distinguishing perceived morality as consumers' attribution of moral capacity from perceived ethics as consumers' evaluation of ethical conduct. It further shows that moral and ethical appraisals do not translate into trust in identical ways, highlighting the need to understand service robot acceptance through moral cognition, ethical evaluation and trust formation.
Purpose When e-commerce platforms engage in Internet of Things (IoT) services and operate agency sales businesses, how to choose centralized or decentralized organizational structures for private label (PL) encroachment. Design/methodology/approach In this study, we develop a game-theoretic model to analyze the impact of centralized versus decentralized organizational structures of platforms on investment in their own-brand IoT products. Findings We find that under a centralized structure, the platform invests in PL IoT products with lower functionality than the national brand (NB) to mitigate internal competition. In contrast, under decentralization, the IoT division may invest in PL IoT products with higher or lower functionality than the NB. The platform prefers a decentralized structure only when competition is low and unit IoT service fee is high. Interestingly, PL IoT encroachment benefits the manufacturer under both structures. Furthermore, we extended our analysis to incorporate subscription-based charging mode, organizational decision before encroachment decision, sequential pricing, wholesale pricing model and encroachment costs associated with IoT technology. Originality/value Our results offer novel insights into the strategic interplay between organizational design and brand competition for e-commerce platforms.
Purpose This study examines how digital transformation (DT) affects environmental, social, and governance (ESG) performance and whether exploitative and explorative DT contribute differently under the UK's post- Task Force on Climate-related Financial Disclosures (TCFD) regime. Design/methodology/approach Grounded in Ambidexterity Theory and Dynamic Capability Theory (DCT), the study constructs firm-level DT and ESG measures from unstructured annual and sustainability disclosures using a Natural Language Processing (NLP)–Entropy framework. Panel data for Financial Times Stock Exchange (FTSE)-listed non-financial firms (2020–2024) are analysed using fixed-effects regressions with firm-clustered standard errors. Mediation tests evaluate CSR and total factor productivity (TFP) as capability-based mechanisms. Findings DT is positively associated with ESG performance. Both exploitative and explorative DT exhibit significant positive relationships with ESG, indicating that ambidextrous digitalisation supports sustainability improvements. Mediation via CSR and TFP is statistically weak, suggesting that the DT–ESG linkage is not transmitted through these proxies within the study horizon and may operate primarily through direct digital mechanisms. Research limitations/implications The study focuses on FTSE non-financial firms and a five-year window, which may constrain generalisability and the detection of longer-run capability maturation. Future work should extend the time horizon, employ alternative capability measures, and apply stronger causal identification designs. Practical implications Firms can improve ESG outcomes by pursuing both exploitative and explorative digital initiatives, while policymakers can reinforce gains by strengthening disclosure quality and digital reporting infrastructures. Originality/value The study integrates digital ambidexterity and DCT, introduces an NLP–Entropy measurement approach for DT and ESG, and provides evidence from a disclosure-intensive UK setting.
Purpose Artificial intelligence (AI) can be used to automate repetitive business processes, enhance employee capabilities and augment managerial decision-making across industries. However, many organisations struggle to translate AI initiatives into sustained strategic value. This gap between AI's potential and realised outcomes highlights the need to understand how organisations harness AI to generate business value, which this paper addresses. Design/methodology/approach We conducted a two-phase qualitative study of Transport and Logistics (T&L) organisations grounded in dynamic capabilities theory and its microfoundations. The first phase involved a systematic review of practitioner (grey) literature to examine AI applications, capabilities, processes and benefits across five T&L organisations. Phase 2 triangulated and refined these insights through key informant interviews. Findings The results indicate that T&L organisations adopt both generic AI technologies (e.g. chatbots, virtual assistants) and industry-specific AI-enabled systems (e.g. autonomous guided vehicles in warehouses, robotic forklifts and collaborative robots). When these AI assets are combined with specific microfoundations, such as AI skills, organisational routines and governance processes, they enable organisations to develop AI-based dynamic capabilities to sense, respond and transform transport, warehousing and delivery operations. These capabilities contribute to workers' safety, operational efficiency, customer experience and environmental sustainability. Originality/value The study contributes a model and propositions that explain how AI-based dynamic capabilities, underpinned by sociotechnical microfoundations enable organisations to gain operational and environmental advantages, offering guidance for managers embarking on an AI exploration journey.
Purpose This study investigates how different dimensions of power advantage and digital intelligence combine to shape green supply chain (GSC) efficiency. Design/methodology/approach Using data from 140 Chinese listed manufacturing enterprises over the period 2015–2023, this study applies dynamic qualitative comparative analysis (QCA) to comprehensively examine the configurations associated with GSC efficiency. Findings Four configurations can lead to high GSC efficiency: market synergy management, organizational change leading, ecological network empowerment and professional authority allocation. The sufficiency of the four configurations exhibits limited temporal variation as policy and market conditions evolve. The first three configurations show greater empirical relevance among high-end equipment manufacturing enterprises, whereas the fourth configuration is more relevant among enterprises outside this industry and those located in non-key environmental protection cities. Additionally, configurations leading to low GSC efficiency result from mismatches and imbalances among antecedent conditions and are not symmetric with those leading to high GSC efficiency. Originality/value Drawing on power-dependence theory and complex systems theory, this study develops a configurational framework that treats market, technology and network power advantages, digital-intelligent equipment, digital-intelligent executives and fintech as antecedent conditions and GSC efficiency as the outcome. The findings contribute to deepening the understanding of power structures and provide a theoretical reference for constructing GSC systems in the digital intelligence era.
