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Drawing on the affect transfer and stakeholder theories, this study aims to examine how the performance of a sports team that a firm owns or sponsors may affect the firm’s market value. It explicates that a sports team wins (loses) in the field raises the public’s positive (negative) affect, which can spill over to the associated firm.

Based on a sample of publicly listed firms in Chinese stock exchanges that are owners or sponsors of soccer teams that competed in the National soccer league of China during 2004–2017, the authors find good support for the hypotheses.

The findings reveal that a firm’s cumulative abnormal return is positively related to its soccer team’s winning and negatively related to the team’s losing, and these relationships are moderated by both firm and match characteristics. By showing a relationship between sports team’s performance and associated firm’s market value, executives need cautions when their firms want to own or sponsor sports team. However, owned sports team’s winning could be a good strategy to improve a firm’s market value.

This study enriches the spillover literature and deepens the understanding of spillover effect. It provides evidence for the concept of affect transfer and broadens its application scope.

This paper aims to investigate the way in which blockchain technology is likely to influence future supply chain practices and policies.

A systematic review of both academic and practitioner literature was conducted. Multiple accounts of blockchain adoption within industry were also consulted to gain further insight.

While blockchain technologies remain in their infancy, they are gaining momentum within supply chains, trust being the predominant factor driving their adoption. The value of such technologies for supply chain management lies in four areas: extended visibility and traceability, supply chain digitalisation and disintermediation, improved data security and smart contracts. Several challenges and gaps in understanding and opportunities for further research are identified by this research. How a blockchain-enabled supply chain should be configured has also been explored from a design perspective.

This systematic review focuses on the diffusion of blockchain technology within supply chains, and great care was taken in selecting search terms. However, the authors acknowledge that their choice of terms may have excluded certain blockchain articles from this review.

This paper offers valuable insight for supply chain practitioners into how blockchain technology has the potential to disrupt existing supply chain provisions as well as a number of challenges to its successful diffusion.

The paper debates the poential social and economic impact brought by blockchain.

This paper is one of the first studies to examine the current state of blockchain diffusion within supply chains. It lays a firm foundation for future research.

A number of governments are making building information modeling (BIM) a mandatory requirement for all public works construction projects. While main contractors may be ready to comply with such requirements, the supply chain as whole may be vulnerable as lower-tier suppliers may not be able to adopt BIM. There is currently no objective approach to assessing BIM maturity; hence, this paper aims to develop a new approach to determine suppliers’ current vision and execution-based capabilities to exploit BIM and their capacity to reach a higher maturity level.

Based on UK Government BIM maturity levels, the authors exploit a unique data set made available by a main contractor, to determine a data-driven approach, using K-means, to assess the capabilities and vision of its supply base.

The authors find a direct comparison between our suggested K-means clusters and the UK Government’s BIM maturity levels. However, in interrogating specific cases, the authors find that using a subjective approach would have wrongly categorized certain companies. The authors also determine what capability and strategic developments are required for companies to move to a higher level.

The method aligns with the existing UK BIM maturity model and enhances the model by determining the likelihood of a supplier in progressing to a higher level of maturity. The research was with a single case company, exploiting their existing survey instrument and data. A more comprehensive study could be adopted with a generic survey questionnaire.

The research may be exploited by companies to take a strategic approach to assess suppliers in BIM adoption and to establish supplier development mechanisms.

The data-driven approach avoids ambiguity of categories and mis-categorizing suppliers.

It is greatly important to select the parameters for support vector machines (SVM), which is usually determined by cross-validation. However, the cross-validation is very time-consuming and complicated to create good parameters for SVM. The parameter tuning issue can be solved in the optimization framework. The paper aims to discuss these issues.

In this paper, the authors propose a novel variant of particle swarm optimization (PSO) for the selection of parameters in SVM. The proposed algorithm is denoted as PSO-TS (PSO algorithm with team-search strategy), which is with team-based local search strategy and dynamic inertia factor. The ultimate design purpose of the strategy is to realize that the algorithm can be suitable for different problems with good balance between exploration and exploitation and efficiently control the inertia of the flight. In PSO-TS, the particles accomplish the assigned tasks according to different topology and detailedly search the achieved and potential regions. The authors also theoretically analyze the behavior of PSO-TS and demonstrate they can share the different information from their neighbors to maintain diversity for efficient search.

The validation of PSO-TS is conducted over a widely used benchmark functions and applied to tuning the parameters of SVM. The experimental results demonstrate that the proposed algorithm can tune the parameters of SVM efficiently.

The developed method is original.

The purpose of this paper is to evaluate electronic logistics marketplaces (ELMs), especially closed systems based on long‐term relationships between shippers and carriers. It aims to establish likely operational models and investigate their relationship with tailored logistics.

Multiple case‐studies with shippers, carriers and technology providers, involving interviews, process mapping, work‐shops and system demonstrations.

Key attributes in relation to processes, relationships and technology are identified. Finding reveal that the ELM business model is still at its infancy stage but with huge potential for growth in optimizing supply chain networks, and enabling the provision of tailored logistics.

Business‐to‐business electronic marketplaces are becoming more common in practice. By characterizing the different operational models, decision makers in logistics can identify which structure is best suited for their particular application. The paper confirms the existence of three distinct ELM structures, while also specifying their key attributes. It provides a foundation for future research in this developing field.

Research on ELMs is scarce. The paper establishes fundamentals of the operational models available to support closed ELM and provides insights on how different closed ELMs are structured, what they do and how they impact tailored logistics.

The purpose of this paper is to investigate empirically how information and communication technologies (ICT) can contribute to reduction of CO₂ emissions in road freight transport and to identify opportunities for further improvements.

This research adopts a multiple case study approach with three leading UK grocery retailers as exemplars of fast-moving consumer goods retailers, conducted using multiple data collection techniques including interviews, system demonstrations, onsite observations and the use of archive information.

ICT solutions have a direct positive impact on CO₂ emissions reduction but opportunities to further reduce CO₂ emissions are perceived as lying beyond retailers’ own distribution networks. These opportunities are not fully utilised due to the complexities of collaborative ICT provisions and retailers’ reluctance to share information with competitors.

A limitation of the study is that it is exploratory and only three cases were examined. Even though these three retailers represent over 60 per cent of the UK grocery retail sector, other retailers may deploy significantly different ICT applications.

The research provides an overarching insight for businesses on how to leverage the existing and emerging information technologies for environmental and economic benefits.

While sustainability issues have received increasing attention recently, the role of ICT in freight transport for CO₂ emissions reduction has not been investigated in depth and its impact is largely unknown. This research advances understanding about how ICT contributes CO₂ emissions reductions and provides a framework for further investigation.

This paper seeks to analyse and propose how e‐business can be coupled with different logistics strategies to achieve customized logistics sustainability (CLS).

In this paper, a conceptual model for CLS has been developed and, using four cases from industry, the model is further enhanced and validated.

Three main streams in supply chains, namely collaboration, dissolution, and innovation, are identified in a customised logistics domain. In each of the three streams, e‐business and relationship configurations are discussed in detail. Using four case examples, the research presented in this paper demonstrates how e‐business performance has hindered or improved the performance of customised logistics provision. A performance measurement (PM) system (efficacy, effectiveness and efficiency (E³) to evaluate the CLS has been proposed.

The E³ PM system development in this paper is based on current research on performance in the literature. Using the case examples, the application of E³ has been explored. Further research on testing E³ as a good PM system in supply chains using empirical data is desirable.

The paper attempts to provide a guiding framework for practitioners on how to align and design different e‐business linkages with different customers.

There has been considerable research on how e‐business can be deployed by a focal company in supply chains in order to support its B2B collaboration with key customers and suppliers. There is little research on e‐business's potential in dealing with dynamic, unpredictable and sometimes sporadic customer demands. The research presented in this paper attempts to fill this gap by proposing a structured model incorporating different logistics streams, and a PM system for CLS.

Hospitableness lies in the center of hospitality services. With the infusion of artificial intelligence (AI) technology in the hospitality industry, managers are concerned about how AI influences service hospitableness. Previous research has examined the consequences of AI technology based on customers’ assessment while ignoring the key players in service hospitableness – frontline employees (FLEs). This study aims to reveal how AI technology empowers FLEs physically, mentally and emotionally, facilitating hospitableness provision.

As the starting point, the instrument for AI-enabled service attributes was designed based on previous literature, hotel FLE interviews, expert panel and a pilot survey, and then validated using survey data. After that, a paired supervisor-employee sample was recruited in 15 hotels, and 342 valid questionnaires covering the constructs were obtained.

Factor analyses and measurement model evaluation suggest that the four factors, including anthropomorphic, entertainment, functional and information attributes, explain the construct of AI-enabled service attributes well, with high reliability and validity. Additionally, anthropomorphic, functional and information attributes of AI technology have been found to enable FLEs physically, mentally and emotionally, which further lead to increased service hospitableness. The entertainment attributes do not significantly reduce physical and mental fatigue but lead to positive emotions of FLEs significantly. Additionally, psychological job demand moderates the effects of AI-enabled service attributes on physical fatigue.

Practical implications can be made for AI technology application and hospitableness provision, in terms of AI technology analysis, job design and employee workload management.

This research contributes to understanding AI-enabled service attributes and their consequences, extends the conservation of resources theory to AI application context and promotes the research on service hospitableness.

The main purpose of this paper is to investigate the vibration isolation performance of a quasi-zero stiffness (QZS) metastructure by employing the band gap (BG) mechanism.

The metastructure QZS characteristic was investigated through static analysis by numerical simulation. Based on that, the BG mechanism is primarily used in this article to investigate the wave propagation characteristics of this structure. The model's dispersion relation is then examined using theoretical (perturbation method) and finite element techniques. The dynamic response of the finite-size systems and experimental analysis is used to confirm the vibration mitigation property under investigation. Finally, the model's ability to absorb energy was examined and contrasted with a traditional model.

The analytical analysis reveals the dispersion curve and the effect of the nonlinear parameter on the curve shifting. The dispersion curve in the finite element method (FEM) result depicts five complete BGs within the range of 0–1,000 Hz, and the BG width accounted for 67.4% of the frequency concerned (0–1,000 Hz). Eigenmodes of the dispersion curves were analyzed to investigate the BG formation mechanisms. The dependence of BG opening and closure on structure parameters was also studied. Finally, the energy absorption property of the QZS metastructure was evaluated by comparing it with a classical model. The QZS structure absorbs 4.08 J/Kg compared to the 3.69 J/Kg absorbed by the classical model, which reveals that the QZS demonstrates better energy absorption performance. Based on the BG mechanism, it is clear that this model is an excellent vibration isolator, and the study reveals the frequencies at which complete vibration mitigation is achieved. As a result, this model could be a promising candidate for vibration mitigation engineering structures and energy absorption.

The tough vibration issue, which is primarily experienced in mechanical equipment, will be resolved in this study. This study provides a precise understanding of the QZS metastructure's isolation of vibration, including the frequencies at which this isolation occurs.