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This study investigates the gap between switching intentions and actual switching behaviors among customers, addressing a gap in previous research that focused on either intentions or behaviors in isolation.

A sample of 376 survey responses from retail bank customers in China were obtained through an online survey and subsequently analyzed using the Macro PROCESS.

The results indicate that factors such as reputation, pricing, service failures and competitors’ advertising significantly influence switching intentions. However, only reputation directly impacts actual switching behavior. A notable intention-behavior gap exists, with switching costs moderating this relationship by reducing the likelihood of intentions leading to actual switching.

This study contributes to the literature by incorporating both intentions and behaviors into a single model. It provides new insights into the intention-behavior discrepancy and highlights the moderating role of switching costs, offering a more comprehensive understanding of consumer switching dynamics.

As opposed to conventional promotional methods, Word-of-Mouth (WOM) communication, especially when negative, significantly shapes customers’ repurchase decisions and preferences. Therefore, this study aims to examine the interplay between negative WOM and bank service failures, with a focus on the mediating role of customer switching intentions and the moderating role of switching costs in this relationship.

Using an online semi-structured questionnaire survey, a dataset comprising 411 responses was gathered from retail bank customers in China. This dataset was subsequently analyzed using SPSS PROCESS.

Consistent with the social exchange theory, our study revealed a significant relationship between service failure and both bank customers’ intention to switch and negative WOM communication. Additionally, we observed that switching intentions significantly influence negative WOM communications, acting as a mediator between service failures and negative WOM. Furthermore, our findings indicated that switching costs moderate the direct effect of service failures on negative WOM and moderate the indirect effect of service failures on negative WOM through switching intentions.

This study provides significant policy implications aimed at minimizing bank service failures and subsequent negative WOM communications among bank customers.

This study empirically investigates the role of service failures in promoting negative WOM communication, demonstrating a partial mediation effect of switching intentions in this relationship. Moreover, the study highlights that switching costs moderate service failures’ impact on customers’ switching intentions.

Gas transmission pipelines are at constant risk of gas leakage or fire due to various atmospheric environments, corrosion on pipe metal surfaces and other external factors. This study aims to reduce the human and financial risks associated with gas transmission by regularly monitoring pipeline performance, controlling situations and preventing disasters.

Facility managers can monitor the status of gas transmission lines in real-time by integrating sensor information into a building information modeling (BIM) 3D model. Using the Monitoring Panel plugin, coded in C# programming language and operated through Navisworks software, the model provides up-to-date information on pipeline safety and performance.

By collecting project information on the BIM and installing critical sensors, this approach allows facility manager to observe the real-time safety status of gas pipelines. If any risks of gas leakage or accidents are identified by the sensors, the BIM model quickly shows the location of the incident, enabling facility managers to make the best decisions to reduce financial and life risks. This intelligent gas transmission pipeline approach changes traditional risk management and inspection methods, minimizing the risk of explosion and gas leakage in the environment.

This research distinguishes itself from related work by integrating sensor data into a BIM model for real-time monitoring and providing facility managers with up-to-date safety information. By leveraging intelligent gas transmission pipelines, the system enables quick identification and location of potential hazards, reducing financial and human risks associated with gas transmission.

This paper aims at developing a multi-objective mathematical model of circular economy that integrates key concept of leasing as a strategy in addition to reuse, refurbishing, primary recycling, secondary recycling and disposal.

This paper proposes multi-objective fuzzy mixed integer linear programming mathematical model considering multi-product, multi-echelon and multi-capacitated concepts of the circular economy. The three objectives of the proposed model, namely, economic, environmental and social are solved simultaneously using constraint approach to obtain balanced trade-off between the objective functions. The model is validated by solving a case study from the literature. The proposed model is made pragmatic for industrial application by considering multi-external suppliers multi-customer zones, multi-disassembly centers, multi-collection centers and multi-refurbishing centers and accounting for purchasing, processing, transportation, set-up costs and capacity constraints at the same time.

The results show that the leasing of the products improves the economic function in addition to the known environmental improvements. The proposed model also shows that the circular economy can generate the jobs for the unskilled people at different locations.

The proposed model can be further improved by considering the non-linearity due to economy of scale at various centers and in transportation. The model can be further extended to make it multi-period model.

The proposed model of circular economy can be used by the organizations as a policy tool to decide the optimum number of collection centers, disassembly centers, refurbishing centers, recycling centers and disposal centers and their optimum locations and allocations. The organizations can also trade-off among economic, environmental and social benefits of their proposed decisions in circular economy.

The originality of the proposed mathematical model is consideration of leasing as a strategy to have better control over the supply chain for circularity; considering the training of unskilled people for backward supply chain jobs and accounting for primary recycling and secondary recycling separately for economical computation.

This study conducts a systematic review to analyze the impact of blockchain technology and smart contracts on digital entrepreneurial finance and venture funding. It aims to investigate how these technologies can transform business operations, offering enhanced transparency, security and efficiency in various financial contexts.

A systematic literature review was conducted following PRISMA guidelines to assess the effectiveness of blockchain and smart contracts in generating business value. The study used the Scopus database to identify relevant articles published between 2015 and 2023. Quantitative and qualitative analyses were performed on the data using IRAMUTEQ software and Bibliometrix tool, both based in the “R” programming language.

The study reveals significant potential for blockchain and smart contracts to disrupt traditional venture funding models by automating contract execution and reducing administrative costs. Blockchain’s secure, decentralized ledger offers advantages in peer-to-peer transactions and risk mitigation, particularly in supply chain management and international trade. However, challenges related to scalability, energy consumption and regulatory compliance were also identified.

Despite the contributions, systematic review of the literature has limitations. Only articles in English, published in journals, were considered for this research, omitting, for example, conference articles and research in other languages, which may also contain relevant information.

The study contributes to the existing literature by synthesizing recent advancements in blockchain and smart contract applications within entrepreneurial finance. It highlights the transformative potential of these technologies while addressing their limitations and offering insights into future research directions. The findings provide valuable implications for academics, practitioners and policymakers interested in leveraging blockchain for financial innovation.

This study provides a comprehensive overview of the research landscape of Kansei engineering (KE) within the domain of emotional clothing design. It explores the pivotal technologies, challenges and potential future directions of KE, offering application methodologies and theoretical underpinnings to support emotional clothing design.

This study briefly introduces KE, outlining its overarching research methodologies and processes. This framework lays the groundwork for advancing research in clothing Kansei. Subsequently, by reviewing literature from both domestic and international sources, this research initially explores the application of KE in the design and evaluation of clothing products as well as the development of intelligent clothing design systems from the vantage point of designers. Second, it investigates the role of KE in the customization of online clothing recommendation systems and the optimization of retail environments, as perceived by consumers. Finally, with the research methodologies of KE as a focal point, this paper discusses the principal challenges and opportunities currently confronting the field of clothing Kansei research.

At present, studies in the domain of clothing KE have achieved partial progress, but there are still some challenges to be solved in the concept, technical methods and area of application. In the future, multimodal and multisensory user Kansei acquisition, multidimensional product deconstruction, artificial intelligence (AI) enabling KE research and clothing sales environment Kansei design will become new development trends.

This study provides significant directions and concepts in the technology, methods and application types of KE, which is helpful to better apply KE to emotional clothing design.

In response to the complex external structure of high-precision aviation plugs, which makes it difficult to search outside the hole and adjust inside the hole during automated assembly. This paper aims to propose an assembly framework that combines multi-agent search and variable parameter compliant control to solve this problem.

First, a multi-agent search strategy (MAS) based on Gaussian Mixture Model and Deep Q-Network was proposed to optimize displacement direction and actions, thereby improving search speed and success rate. Then, a variable parameter admittance control method (RL-VPA) based on dual delay depth deterministic policy gradient (TD3) was proposed, which dynamically optimized the internal parameters of the admittance controller and adopted state space discretization to improve convergence speed and assembly efficiency.

Compared to spiral search and single-agent search, the average search success rate has improved by approximately 10% and 6.6%. Compared to fixed admittance control and other RL-based methods, the average assembly success rate has increased by approximately 38.6%, 22% and 8.6%. Compared with the training results of the model without state discretization, it was found that state discretization helps the model converge quickly. To verify the generalization ability of the assembly framework, experiments were conducted on three different pin counts of aviation plugs, the assembly success rate reached 86.7%, all of which showed good assembly results. Finally, combining state space discretization to reduce the impact of environmental noise, improve training effectiveness and convergence speed.

MAS has been proposed to optimize displacement direction and action, improving search speed and success rate. RL-VPA is designed to dynamically optimize the internal parameters of the admittance controller, enhancing the robustness and generalization ability of the model. Additionally, state space discretization is combined to improve training effectiveness and convergence speed.

This paper aims to investigate the relationship between uncertainty and corporate cash holdings with the moderating role of political connections.

We employ fixed effects estimation on a panel dataset of 669 Vietnamese listed firms over the 2010–2020 period, with one- and two-way standard error clustering. We conduct various robustness tests, including two-stage least squares/instrumental variable and generalized method of moments regressions, alternative cash holding measure, and additional controls for macroeconomic conditions and ownership types.

The effect of uncertainty on cash holdings is weakened for firms with political connections relative to those without the connections. Although general firms depend on cash flows to adjust their cash holding behavior when uncertainty increases, our findings suggest that politically connected firms do not rely on internal cash flows to accumulate cash when confronted high uncertainty.

Our findings on the role of political connections in moderating the relationship between cash holding and economic policy uncertainty have practical implications for policymaking. Since political connections serve as a buffer for a firm’s liquidity, firms may want to seek those connections, which can, in turn, lead to increasing informal costs and unfair business environment.

This is the first study investigating the role of political connections to the nexus of cash, cash flow and uncertainty, providing novel evidence regarding the less dependence on internal cash flows to save cash by politically connected firms. Second, the paper enriches the literature on the motives of cash holdings by proposing a modified agency view in the context of weak investor protection. Therefore, our findings strengthen the explanation for the positive effect of uncertainty on firms’ cash holdings in emerging markets.

The research aims to explore the influence mechanism of peer feedback and users' knowledge contribution behavior. This study draws on the social identity theory and considers social identity as a mediating factor into the research framework.

This paper collected users' activity data of 142,191 ideas submitted by 76,647 users from the MIUI community between October 2010 and May 2018 via Python software, and data were processed using Stata 16.0.

The results indicate that knowledge feedback and social feedback positively influence users' knowledge contribution (quantity and quality), respectively. User's cognitive identity positively mediates the relationship between peer feedback and knowledge contribution behavior, affective identity positively mediates the relationship between peer feedback and knowledge contribution behavior, while evaluative identity positively mediates the relationship between peer feedback and knowledge contribution quality, but there is no mediating effect between peer feedback and knowledge contribution quantity.

This study advances knowledge management by highlighting peer feedback on online innovation communities. By demonstrating the significant mediating effect of social identity, this study empirically clarifies the relationships of peer feedback (knowledge feedback and social feedback) to specific dimensions of knowledge contribution, thereby providing managerial guidance to the online innovation community on incentivizing and managing user interaction to foster the innovation development of firms.

The purpose of this paper is to test if the digital economy improves the quality of life of our residents. Furthermore, if this finding is confirmed, what would be the mechanism behind its effect? Does the impact of the digital economy on quality of life vary according to its level of development?

A comprehensive index of the digital economy, income gap and quality of life was constructed empirically based on data from 220 cities in China from 2011–2020. A multi-dimensional empirical analysis was conducted in this paper.

The analysis of the pathways of action shows that narrowing the income gap is an important mechanism through which the digital economy actively contributes to the quality of life. The results of the threshold model show that the “marginal effect” of the digital economy on quality of life is non-linear and increasing. The results show that after a series of robustness tests, including instrumental variables, the digital economy still significantly enhances people’s quality of life.

This paper reveals the intrinsic link between the digital economy and quality of life and provides a theoretical basis for further improving people’s well-being.

Encouraging the development of the digital economy is a useful way to improve the quality of life by narrowing the income gap.

Data analysis of the digital economy from 2011–2020 in China to get an insight into what would be the mechanism behind the digital economy improving the quality of life of our residents.