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When encountering novel technology, customers often use the term “cool” to express their thoughts; therefore, coolness has become crucial for launching service robots. However, research on the impact mechanism of “coolness” is lacking. This study explored the relationship between delight and behavioral intention regarding the coolness of service robots in the food and beverage industry while discussing the mediating roles of utilitarian and hedonic values.

Questionnaires were distributed online with links to the survey posted on restaurant discussion boards on Facebook and online community platforms such as Dcard. In total, 540 responses were deemed valid. The hypotheses were tested using the partial least squares structural equation modeling method.

The results indicate that coolness positively impacted both utilitarian and hedonic values and that both perceived values positively impacted delight. Moreover, coolness does not directly impact delight but must be mediated by perceived value to be effective.

Increasing customer perceptions of the coolness of service robots is recommended. Moreover, regarding customer revisits, utilitarian value services can delight customers more effectively than hedonic value services.

The stimulus-organism-response model was used to identify the relationships among coolness, perceived value, delight and behavioral intention. Moreover, the authors investigated the impact of coolness on utilitarian and hedonic values. These findings are significant for the development of smart restaurants and provide a critical reference for exploring service robots.

Accurately evaluating fluid flow behaviors and determining permeability for deforming porous media is time-consuming and remains challenging. This paper aims to propose a novel machine-learning method for the rapid estimation of permeability of porous media at different deformation stages constrained by hydro-mechanical coupling analysis.

A convolutional neural network (CNN) is proposed in this paper, which is guided by the results of finite element coupling analysis of equilibrium equation for mechanical deformation and Boltzmann equation for fluid dynamics during the hydro-mechanical coupling process [denoted as Finite element lattice Boltzmann model (FELBM) in this paper]. The FELBM ensures the Lattice Boltzmann analysis of coupled fluid flow with an unstructured mesh, which varies with the corresponding nodal displacement resulting from mechanical deformation. It provides reliable label data for permeability estimation at different stages using CNN.

The proposed CNN can rapidly and accurately estimate the permeability of deformable porous media, significantly reducing processing time. The application studies demonstrate high accuracy in predicting the permeability of deformable porous media for both the test and validation sets. The corresponding correlation coefficients (R²) is 0.93 for the validation set, and the R² for the test set A and test set B are 0.93 and 0.94, respectively.

This study proposes an innovative approach with the CNN to rapidly estimate permeability in porous media under dynamic deformations, guided by FELBM coupling analysis. The fast and accurate performance of CNN underscores its promising potential for future applications.

The adoption of social procurement, the emerging practice of using a firm's spending power to generate social value, requires buying firms to navigate conflicts of institutional logics. Adopting an institutional work perspective, this study aims to investigate how buying firms change their existing procurement institutions to adopt and advance social procurement.

The authors conducted an in-depth case study of a social procurement initiative in the UK. This case study comprised of 16 buying firms that were actively participating in the social procurement initiative at the time of data collection (2020–2021). The data were largely captured through a set of 41 semi-structured interviews.

Four types of institutional work were observed: reducing institutional conflicts, crossing institutional boundaries, legitimising institutional change and spreading the new institutional logic. These different types of institutional work appeared in a sequential way.

This study contributes to various strands of literature investigating the role of procurement in generating value and benefits within societies, adopting an institutional lens to investigate the buying firms' purposeful actions to change procurement institutions. Secondly, this study complements the existing literature investigating the conflicts of institutional logics by illustrating the ways firms address such institutional conflicts when adopting and advancing social procurement. Finally, this work contributes to the recently emerging research on institutional work that examines the creation and establishment of new institutions by considering the existing procurement institutions in the examination of institutional work.

The adoption of emerging information and communication technologies in construction project teams has engendered numerous virtual spaces, characterized by communication visibility and content persistence. As a result, the knowledge exchanged in these virtual spaces serves as a team’s digital resources. However, the extant literature mostly takes a process-based approach to examine the impact of knowledge sharing, thus failing to fully comprehend the process of converting digital resources into performance, resulting in a gap in the literature.

This study employs team resource-based theory to construct a theoretical model and develop hypotheses. Specifically, knowledge integration capability and team efficacy are hypothesized as two types of critical capabilities that mediate the links between knowledge sharing (quantity and quality) in virtual spaces and management performance. Data from 128 middle and senior construction project managers were collected to test the proposed theoretical model.

The results suggest that relationships between knowledge sharing (quantity and quality) and project management performance are both mediated by knowledge integration capability. Moreover, team efficacy could only partially translate knowledge sharing quantity into performance and couldn’t transform knowledge sharing quality into performance. Besides, knowledge integration is found to strengthen the link between knowledge sharing quantity and performance but weaken the relationship between knowledge sharing quality and performance.

This study explores how knowledge shared in virtual spaces could be leveraged for improving management performance in construction project teams. The findings in this study enhance the understanding of knowledge sharing in digital environments and afford important insights into transforming digital resources into performance within construction project teams.

This paper investigates the role of institutional pressures (IPs) and supply chain integration (SCI) in driving the adoption of circular economy (CE) practices. It is hypothesised that, responding to IPs, firms might adopt higher levels of SCI in the attempt to implement CE practices.

A research model is developed and tested on a cross-sectional sample of 150 multi-national enterprises (MNEs). Textual content from corporate sustainability reports is used to measure the constructs of interest through an advanced coding approach.

Findings show that IPs are driving the adoption of CE practices primarily through the mediation of SCI; the prominent roles of coercive regulatory pressures (CRPs) and normative pressures (NPs) are also highlighted. CRPs influence on CE practices is partially mediated by SCI, with NPs influence being fully mediated by it.

The study shows that SCI is a key mechanism that lies in between IPs and CE practices; as such, organisations interested in implementing CE practices need to be aware of requirements for achieving higher levels of SCI.

This empirical study is the first large scale analysis that conceptualises how MNE-driven supply chains adopt CE practices. The study empirically validates the model and identifies research avenues in supply chain management (SCM) research to support the adoption of CE practices.

This paper takes the Shanghai-Shenzhen-Hong Kong Stock Connect as a quasi-natural experiment and investigates the impact of capital market liberalization on the corporate debt maturity structure. It also aims to provide some policy implications for corporate debt financing and further liberalization of the capital market in China.

Employing the exogenous event of Shanghai-Shenzhen-Hong Kong Stock Connect and using the data of Chinese A-share firms from 2010 to 2020, this study constructs a difference-in-differences model to examine the relationship between capital market liberalization and corporate debt maturity structure. To validate the results, this study performed several robustness tests, including the parallel test, the placebo test, the Heckman two-stage regression and the propensity score matching.

This paper finds that capital market liberalization has significantly increased the proportion of long-term debt of target firms. Further analyses suggest that the impact of capital market liberalization on the debt maturity structure is more pronounced for firms with lower management ownership and non-Big 4 audit. Channel tests show that capital market liberalization improves firms’ information environment and curbs self-interested management behavior.

This research provides empirical evidence for the consequences of capital market liberalization and enriches the literature on the determinants of corporate debt maturity structure. Further this study makes a reference for regulators and financial institutions to improve corporate financing through the governance role of capital market liberalization.

This study delves into the nuanced relationship between financial constraints, ownership structures (state-owned and foreign) and innovation engagement within China’s A-share market, aiming to uncover how these dynamics vary across different industries and regional contexts.

By retrieving data from various datasets in China (2010–2022), this study analyzed the effectiveness of each variable, employing various dimensions to reflect innovation engagement among Chinese listed companies. Meanwhile, for the measurement of financial constraints, this study tested all four typical ones and opted for the KZ Index, as it is the most suitable for China’s A-share market. Then, by fixing the industry and year effects, the study examined the main and moderating effects. At last, in order to address endogeneity issues and capture the dynamic nature of innovation activities, this study follow the suggestion of Khatib (2024) and employed the two-step system Generalized Method of Moments (GMM) estimation.

The results demonstrate that while the government has introduced many policies to promote innovation, state-owned ownership does not consistently enhance innovation engagement as expected, especially when firms are in financial dilemma. Particularly, in Hi-tech industries, foreign ownership demonstrates greater interest and confidence in the innovation capabilities of China’s A-share market. Findings also reveal significant regional heterogeneity in the moderating role of ownership structures. While state-owned and foreign ownerships have a buffering effect against financial constraints in the eastern and western regions, but this effect is notably different in the middle part, even though it is China’s political heartland.

The findings offer a different insight for policymakers and corporate strategists, suggesting that targeted financial and regulatory policies that leverage specific ownership structures can foster innovation in different ways, particularly in financially constrained environments. However, how to stimulate innovation vitality in the middle part of China still requires further research.

Road transport networks might face the most significant transformation in the following decades, mostly due to the anticipated introduction of Connected and Automated Vehicles (CAVs). The introduction of connectivity and automation will be realised gradually. There are distinctive levels of automation starting from single-dimension automated functionalities, such as regulating the vehicle’s longitudinal behaviour via Adaptive Cruise Control (ACC) systems. Although the technological readiness level is undeniably far from full vehicle automation, there are already commercially available lower-level automated vehicles. The penetration rate of vehicles equipped with Advanced Driver Assistance Systems (ADAS) such as ACC or Cooperative-ACC is constantly increasing bringing new driving behaviours into existing infrastructure, especially on motorways. Lately, several experiments have been conducted with platoons of ACC and CACC-equipped vehicles aiming to study the characteristics and properties of the traffic flow composed by them. This chapter aims to gather the most significant efforts on the topic and present the recent status of research and policy. The impact analysis presented within this chapter is multi-dimensional spanning from traffic flow oscillations and string stability, traffic safety to driving behaviour, energy consumption, and policy, all factors where automation has the potential to contribute to a more sustainable transport system. Investigations through analytical approaches and simulation studies are discussed as well, in comparison to empirical insights, attempting to generalise experimental conclusions. At the end of this chapter, the reader should have a clear view of the existing and potential benefits of CAVs but also the existing and future challenges they can bring.

An emerging body of literature has pinpointed the role of supply chain structure in influencing the extent to which supply chain members disclose information about their internal practices and performance. Nevertheless, empirical research investigating the effects of firm-level relational embeddedness on network-level transparency still lags. Drawing on social network analysis, this research examines the effect of relational embeddedness on supply chain transparency and the contingent role of digitalization in the context of environmental, social and governance (ESG) information disclosure.

In their empirical analysis, the authors collected secondary data from the Bloomberg database about 2,229 firms and 14,007 ties organized in 107 extended supply chains. The authors employed supplier and customer concentration metrics to measure relational embeddedness and performed multiple econometric models to test the hypothesis.

The authors found a positive effect of supplier concentration on supply chain transparency, but the effect of customer concentration was not significant. Additionally, the digitalization of focal firms reinforced the impact of supplier concentration on supply chain transparency.

The study findings contribute by underscoring the critical effect of relational embeddedness on supply chain transparency, extending prior literature on social network analysis, providing compelling evidence for the intersection of digitalization and supply chain management, and drawing important implications for practices.

This paper aims to propose a real-time evolutionary multi-objective semi-analytical inverse kinematics (IK) algorithm (EMSA-IK) for solving the multi-objective IK of redundant manipulators.

Within EMSA-IK, the parameterization method is applied to reduce the number of optimization variables of the evolutionary algorithm and calculate semi-analytical solutions that meet high target pose accuracy. The original evolutionary algorithm is improved with the proposed adaptive search sub-space strategy so that the improved evolutionary algorithm can be used to efficiently perform global search within the parametric joint space to obtain the global optimal parametric joint angles that satisfy multi-objective constraints.

Ablation experiments show the effectiveness of the improved strategy used for evolutionary algorithms. Comparative experiments on different manipulators demonstrate the advantages of EMSA-IK in terms of generalizability and balancing multiple objectives, for example, motion continuity, joint limits and obstacle avoidance. Real-world experiments further validate the effectiveness of the proposed algorithm for real-time application.

The semi-analytical IK solution that simultaneously satisfies high target pose accuracy and multi-objective constraints can be obtained in real time. Compared to existing semi-analytical IK algorithms, the proposed algorithm achieves obstacle avoidance for the first time. The proposed algorithm demonstrates superior generalizability, applicable to not only redundant manipulators with revolute joints but also those with prismatic joints.