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This research proposes and examines a theoretical model grounded in anthropomorphism theory considering the curvilinear and linear relationships between service robot anthropomorphism and consumer usage intention and explores the mediating effect of perceived risk.

To examine the developed model, two complementary studies are designed. In Study 1, multi-time data of 511 participants show that service robot anthropomorphism inverts U-shaped (curvilinear) relationship on consumer usage intention and perceived risk mediates this curvilinear relationship. In Study 2, multi-source data of 460 volunteers are used to confirm the findings of Study 1 and examine that consumer empathy moderates the complex nonlinear effect of service robot anthropomorphism on perceived risk, and the indirect curvilinear effect of service robot anthropomorphism on consumer usage intention through perceived risk.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

Although numerous signal modalities are available for emotion recognition, audio and visual modalities are the most common and predominant forms for human beings to express their emotional states in daily communication. Therefore, how to achieve automatic and accurate audiovisual emotion recognition is significantly important for developing engaging and empathetic human–computer interaction environment. However, two major challenges exist in the field of audiovisual emotion recognition: (1) how to effectively capture representations of each single modality and eliminate redundant features and (2) how to efficiently integrate information from these two modalities to generate discriminative representations.

A novel key-frame extraction-based attention fusion network (KE-AFN) is proposed for audiovisual emotion recognition. KE-AFN attempts to integrate key-frame extraction with multimodal interaction and fusion to enhance audiovisual representations and reduce redundant computation, filling the research gaps of existing approaches. Specifically, the local maximum–based content analysis is designed to extract key-frames from videos for the purpose of eliminating data redundancy. Two modules, including “Multi-head Attention-based Intra-modality Interaction Module” and “Multi-head Attention-based Cross-modality Interaction Module”, are proposed to mine and capture intra- and cross-modality interactions for further reducing data redundancy and producing more powerful multimodal representations.

Extensive experiments on two benchmark datasets (i.e. RAVDESS and CMU-MOSEI) demonstrate the effectiveness and rationality of KE-AFN. Specifically, (1) KE-AFN is superior to state-of-the-art baselines for audiovisual emotion recognition. (2) Exploring the supplementary and complementary information of different modalities can provide more emotional clues for better emotion recognition. (3) The proposed key-frame extraction strategy can enhance the performance by more than 2.79 per cent on accuracy. (4) Both exploring intra- and cross-modality interactions and employing attention-based audiovisual fusion can lead to better prediction performance.

The proposed KE-AFN can support the development of engaging and empathetic human–computer interaction environment.

This study investigates the impact of supply chain governance (SCG, which includes relational governance and contractual governance) on supply chain resilience (SCR) using the information processing theory. Moreover, the study also examines the mediating role of information processing capability and the moderating role of digital technology (DT) deployment.

A total of 288 questionnaires were collected from the Chinese manufacturing industry, and hierarchical regression was used to empirically test the proposed model.

This study reveals that SCG positively impacts SCR. Moreover, information processing capability plays a mediating role between SCG and SCR. Furthermore, the breadth of DT deployment positively moderates the effect of relational governance on information processing capability, and the depth of DT deployment positively moderates the effects of both relational governance and contractual governance on information processing capability.

This study offers a novel perspective that helps to understand the importance of the supply chain-wide information acquired by SCG in respect of improving SCR. Furthermore, this article extends the application of information processing theory by providing empirical evidence of the mediating role of information processing capability and elucidating the moderating role of DT deployment.

The purpose of this study is to advance the understanding of resource orchestration in inter-firm partnerships that appropriately configure and align strategic cross-firm supply chain resources and capabilities generating synergies to deliver superior performance.

Applying the resource orchestration logic, supported by the relational view of competitive advantage, the study draws from an empirical analysis of survey data from 152 top-level executives of US manufacturing firms to investigate the effect of leveraging and coherently combining cross-firm supply chain resources with capabilities on operational performance.

The study underscores the view that appropriately orchestrated combinations of key partnership resources and capabilities as mechanisms for marketing strategy implementation, enhance performance. Specifically, research results suggest that complementary inter-firm resources and lean align, and similarly idiosyncratic resources and agility align synergistically to deliver superior operational performance outcomes. The results also accent partnership responses to intense competition, enabling enhanced operational performance. The findings thus enrich the understanding of the resource orchestration logic and strategy, making important theoretical contributions.

As is typical in marketing and strategy research, the study research design has a cross-sectional framework, thus limiting insights on the resource orchestration dynamics that can otherwise be generated using a longitudinal design. Also, the resource orchestration stream is still nascent. Further research is needed to delineate the orchestration mechanisms that deliver on performance outcomes, especially in supply chains.

A key insight for supply chain and marketing managers is that close-knit inter-firm partnerships are critical for accessing idiosyncratic and complementary resources that can be configured and symbiotically aligned with market-facing agility and lean capabilities, respectively, to deliver market value. Proactive partnerships, especially in highly competitive and disruptive environments, enable mobilizing cross-firm resources and building appropriate matching combinations with capabilities to deliver on operational performance.

The study, guided by theory, advances the understanding of how key cross-firm resources and capabilities deliver performance gains. The key to competitive advantage and enhanced performance outcomes may lie in acquiring, leveraging and deploying appropriately matched resource-capability combinations. The present study investigates this proposition within the context of supply chain partnerships, focusing on cross-firm resources and capabilities.

The growing focus on socially responsible supply chain management (SRSCM) has made it crucial to extend corporate social responsibility (CSR) to upstream suppliers. Drawing on resource dependence theory, this study aims to examine how supplier dependence upon socially responsible buyers impacts suppliers' CSR performance and how this relationship is moderated by network prominence and demand uncertainty.

The proposed hypotheses are tested using regression analysis with Heckman's two-stage model and a dyadic supply chain dataset constructed based on publicly traded Chinese firms between 2008 and 2016. This time window is selected due to a one-year lag of the dependent variable and the change in evaluation methods of the database providing CSR performance in 2018.

The empirical results indicate that supplier dependence upon socially responsible buyers is positively associated with suppliers' CSR performance. However, this positive relationship is attenuated when suppliers occupy a prominent position in the network or when they face high demand uncertainty.

This study extends knowledge about the role of relationship dependence in implementing SRSCM by highlighting its positive impact on suppliers' CSR. Thus, this study contributes to the buyer–supplier relationship literature and the power and relationship dependence literature. This study further advances the understanding of the factors that influence suppliers' behavior by exploring the moderating roles of network prominence and demand uncertainty. The results have several practical implications for managers and policymakers.

Global supply chains are increasingly becoming more prone to high-impact disruptions, which has been fairly evident with the coronavirus disease 2019 (COVID-19) pandemic. The capacity to address disruptions is essential for the survival of any organization. Coping with increasing complexity and uncertainties requires a systemic view of supply chains. Furthermore, a comprehensive understanding of the governance structure and timely decision-making are critical in times of disruptions. Although several aspects of supply chain resilience (SCRES) are broadly studied in the literature, the relationship between supply chain orientation (SCO), decentralization in decision-making and SCRES is an understudied area.

This study takes a longitudinal approach to address this research gap with a comprehensive meta-analytic review to explore the relationships between the constructs of interest through the lenses of contingency and dynamic capability theories. Furthermore, 2 surveys with sample sizes of 250 and 200 were conducted with supply chain professionals to test the research framework before and after the pandemic to compare the findings.

Structural Equation Modeling (SEM) analysis indicates a positive relationship between SCO and decentralization and between decentralization and SCRES. The post-COVID-19 analysis further validates the influence of agility, collaboration and situational awareness related to decentralization and resilience. More importantly, capabilities have a higher impact on resilience during the pandemic than before.

The results entreat organizations to attain decentralized decision-making vis-à-vis dedicated functional teams charged with reacting timely to disruptions. The teams should be empowered to leverage their knowledge and experiences regardless of their position in the hierarchy.

Although SCRES is an active research stream, the structural aspects of SCRES and its relationship with SCO are understudied. Therefore, this research puts forth a research framework and empirically tests hypotheses that frame the relationship between SCO, decentralization and resilience outcomes in pre- and post-COVID environments.

Despite the escalating significance and intricate nature of supply chains, there has been limited scholarly attention devoted to exploring the cognitive processes that underlie supply chain management. Drawing on cognitive-behavioral theory, the authors propose a moderated-mediation model to investigate how paradoxical leadership impacts manufacturing supply chain resilience.

By conducting a two-wave study encompassing 164 supply chain managers from Chinese manufacturing firms, the authors employ partial least squares structural equation modeling (PLS-SEM) to empirically examine and validate the proposed hypotheses.

The findings indicate that managers' paradoxical cognition significantly affects supply chain resilience, with supply chain ambidexterity acting as a mediating mechanism. Surprisingly, the study findings suggest that big data analytics negatively moderate the effect of paradoxical cognition on supply chain ambidexterity and supply chain resilience, while positively moderating the effect of supply chain ambidexterity on supply chain resilience.

These findings shed light on the importance of considering cognitive factors and the potential role of big data analytics in enhancing manufacturing supply chain resilience, which enriches the study of behavioral operations.

The results offer managerial guidance for leaders to use paradoxical cognition frames and big data analytics properly, offering theoretical insight for future research in manufacturing supply chain resilience.

This is the first empirical research examining the impact of paradoxical leadership on supply chain resilience by considering the role of big data analytics and supply chain ambidexterity.

This study aims to investigate the contribution of blockchain technology to supply chain risk management and its impact on performance among Indian manufacturing companies.

Drawing on a resource-based view, dynamic capability and system of systems theory, this study examines the direct relationships between blockchain, supply chain risk management and supply chain performance. The authors validate the mediating effects of three supply chain risk management components, namely supply risk management, demand risk management and cyber security management, on financial transaction reliability and information reliability. Data were collected from 204 Indian manufacturing companies that have adopted blockchain technology.

The results demonstrate that companies adopting blockchain technology have experienced positive outcomes in managing supply chain-related risks, financial transaction reliability and information reliability. These findings provide valuable guidance to managers, highlighting blockchain as a competitive advantage for supply chain management.

To the best of the authors’ knowledge, no previous research on blockchain-based risk management capabilities has been conducted.

This study aims to investigate the impact of sustainable innovation and disruptive innovation on sustainable supply chain performance of manufacturing firms in Malaysia. The study also examined the moderating role of supply chain clockspeed in the relationship between sustainable innovation, disruptive innovation and sustainable supply chain performance.

The data were collected from 231 respondents in manufacturing firms in Malaysia. The data were analyzed using the partial least square-based structural equation modelling (PLS-SEM) technique.

The findings revealed that sustainable innovation and disruptive innovation had a significant and positive effect on sustainable supply chain performance. Supply chain clockspeed moderated the relationship between sustainable innovation and sustainable supply chain performance. The findings also identified that there was no moderating effect on the relationship between disruptive innovation and sustainable supply chain performance.

This study merely focuses on sustainable supply chain performance in Malaysian manufacturing firms. Samples from manufacturing firms in Malaysia were used in the current study, and the outcomes may vary for different nations.

To increase the firm’s commercial success, it is necessary to promote sustainable supply chain practices, including supply chain clockspeed, sustainable innovation and disruptive innovation.

This study adds to the body of knowledge by explaining the positive influence of sustainable innovation and disruptive innovation on sustainable supply chain performance in Malaysian manufacturing firms while also emphasizing the moderating role of supply chain clockspeed in this relationship. The contribution of this study could enable managers to develop sustainable supply chain performance in the manufacturing sector, based on sustainable innovation, disruptive innovation and supply chain clockspeed.

This study offers insight on the impact of virtual team projects (VTPs) of varying types (global vs domestic teams, technology vs non-tech projects) on competency and anxiety outcomes during the COVID-19 pandemic.

Paired-sample t-tests and ANOVA tests were performed on student survey responses pre- and post-engagement of different VTPs.

The results demonstrated positive effects of VTPs on intercultural sensitivity (ISS), computer self-efficacy, perceived ease of use of online learning and COVID-19 anxiety. ISS (“interaction confidence”) improved more for students in the global vs. domestic teams and technology-related outcomes (CSE, PEU and computer anxiety) and ISS (“respect for cultural differences”) improved more for students that participated in tech projects, whereas COVID-19 anxiety lessened more for those that participated in non-tech projects.

The study expands understanding of the Technology Acceptance Model and provides insight into the ISS literature showing that VTPs could be a worthwhile pedagogical approach for improving student competencies and anxiety during times of academic disruption, but that project type can influence these changes.