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Current developments in the FinTech payment industry have shown a rapid revolution in Industry 4.0, and understanding the factors affecting individual acceptance of facial recognition payment (FRP) is crucial. Hence, this study aims to evaluate the benefits and risks of FRP system adoption in Malaysia.

The perceived risks and benefits framework is adopted as the foundation in this study to examine the various risks and benefits that users perceive, along with the trust factor, to study the relationships between these variables. Data were collected via an online questionnaire, and the hypotheses were tested using Partial Least Squares analysis on 277 responses.

The results revealed that perceived risk is a significant predictor of users' intention to use the FRP system. Privacy risk and financial risk significantly influence perceived risks, while security risk does not. Although convenience, perceived ease of use and perceived trust positively influence perceived benefits, perceived benefits do not significantly influence adoption intention. Moreover, perceived trust negatively affects perceived risks while positively affecting both perceived benefits and adoption intention. Additionally, personal innovativeness moderates the relationship between perceived risks and the intention to use the FRP system.

This study helps policymakers and service providers understand individuals’ concerns and expectations regarding FRP systems. It aids practitioners in developing strategies to build trust, address innovativeness differences and mitigate risks, serving as a roadmap for integrating these systems into Malaysia's financial landscape.

This study distinguishes itself from prior research by evaluating FRP system adoption in Malaysia through the lens of perceived risks and benefits framework. It also explores personal innovativeness as a moderator, examining its impact on the relationship between usage intention and perceived risks and benefits. Additionally, it highlights perceived trust as a crucial factor influencing individuals' intention to adopt FRPs.

To meet environmental performance (EP) goals, this study aims to identify the complex interaction between green Industrial Internet of Things (GIIoT), circular economic practices (CEPs) and dynamic capabilities (DC). This study analyzes how technological, operational and cultural compatibilities enhance GIIoT adoption.

Data were collected from diverse Chinese manufacturing firms (n = 339) through a quantitative survey. The research model was proposed, and hypotheses were tested using structural equation modeling. Moreover, the robustness of the structural model is further tested using Fuzzy Set Qualitative Comparative Analysis and importance performance map analysis.

The empirical results indicate that higher organizational compatibilities boost GIIoT adoption and EP. DC was assessed as a higher-order construct to examine its mediation of GIIoT adoption and EP. DC positively mediates GIIoT adoption-EP. Similarly, CEP’s positive impact on EP, partially mediating the relationship between GIIoT adoption and EP, has also been proved.

This research bridges current understanding and contributes useful insights for fostering environmental sustainability inside manufacturing firms and advances the theoretical understanding of technology adoption, sustainable development and dynamic capacity theory. It illuminates the way forward to harmonize and successfully integrate technology, CEP and EP. This research advances the area and gives decision-makers practical advice for creating sustainable and technologically sophisticated organizations.

We aim to investigate the impact of different story types on small fashion business brand trust and purchase intention, guided by signaling theory. We investigate two potential moderators – product aesthetic judgment (i.e. consumers’ responses to the aesthetic aspects of a product) and underdog positioning (i.e. brand’s positioning as a loser that is not a leader in the marketplace and has only a small market share but puts efforts into creating valuable products) – that may influence consumers’ responses to a story.

We developed video stimuli that tell business stories to empirically compare two story types bringing brand trust: identity-focused and product-focused stories. We conducted two experimental studies and tested six hypotheses with 302 datasets. Study 1 compared eco-friendly storytelling with product-focused storytelling, considering perceived product aesthetic judgment as the moderator. Study 2 repeated the experiment with a founder story and a product-focused story, considering the perceived underdog as the moderator.

The findings suggest that the influence of eco-friendly storytelling, compared to product-focused storytelling, on higher purchase intention is fully mediated by brand trust. Consumers’ perceived product aesthetic judgments toward an eco-friendly product can positively moderate the storytelling effect and brand trust. However, founder storytelling did not bring higher brand trust and, consequently, had no significant impact on purchase intention. Similarly, the perceived underdog did not moderate this relationship.

The study is novel as it is one of the first to compare story types based on story contents, whereas previous studies have focused on story delivery. Especially, we explored which story types and contents effectively build brand trust for small businesses, a critical factor for their success. Based on the extant literature, we categorized story types into identity-focused stories and product-focused stories based on contents. We hypothesized and concluded that an identity-focused story can be more effective in eliciting consumer responses. Furthermore, we confirm the critical role of brand trust as a mediator in bringing about purchase intention through eco-friendly storytelling.

Drawing on broaden and build theory and the job demands–resources (JD–R) perspective, this study aims to test a moderated mediation model to explain the mediating effect of knowledge sharing behavior and the moderating role of perceived organizational obstruction on the dynamics of work engagement and creative effort.

Data from 497 banking service employees constitute the sample of the study, and PROCESS macro in Statistical Package for the Social Sciences (SPSS) was used to test the hypotheses.

The positive impact of work engagement on creative effort is mediated by knowledge sharing behavior and the direct effect of work engagement on creative effort and the mediating effect of knowledge sharing behavior are contingent on perceived organizational obstruction. These effects were weaker for employees who experienced high perceived organizational obstruction.

This work unfolds how and when work engagement impacts the creative efforts of banking sector employees, highlighting when engaged work matters the most. It provides bidirectional richness at the intersection of knowledge management and creativity literature by focusing on the banking industry of a developing country.

Project-based temporary organizations, as an efficient organizational form for the execution of complex and innovative tasks, encounter challenges in fostering the effectiveness of inter-organizational cooperation within their temporary, uncertain, and dynamic nature. Although change-oriented organizational citizenship behaviors are recognized for promoting organizational relationships and performance in changing contexts, research in temporary organizational settings remains sparse. This study diverges from the majority concentrating on change-oriented behaviors on intra-organizational leader-employee relations and behaviors, aiming to propose a dynamic adaptive capacity of organizational leaders and explore how leadership capabilities and organizational climate shape their change-oriented organizational citizenship behaviors at inter-organizational level.

Developing a person-organization fit model tailored for complex and dynamic organizational settings, using survey data from 225 leaders with project cooperative experience and structural equation modeling for empirical analysis.

This study reveals the direct positive influences of organizational leaders’ dynamic adaptive capacity on their changed-oriented organizational citizenship behaviors. And, change self-efficacy, as a mediating psychological trait, enhances the positive relation between dynamic adaptive capacity and changed-oriented organizational citizenship behaviors. The findings also highlight person-organization interactions, where organizational justice, acting as a situational and moderating factor, has a positive yet disruptive effect on the relationship between dynamic adaptive capacity, change self-efficacy, and changed-oriented organizational citizenship behaviors.

This research enriches the mechanisms linking dynamic managerial capability in organizational leadership to citizenship behaviors at the micro-level, providing valuable insights for the management and development of temporary cross-organizational cooperation.

The new teleworking conditions imposed by extreme events such as the COVID-19 pandemic blur the border between home and official working space, amplifying the conflicting demands of family and work life experienced by employees across national cultures. Drawing on conservation of resources (COR) theory, this study explores cross-national variances in the underlying mechanism of how family–work conflict (FWC) affects employees’ operational and marketing productivity in the global epidemic-induced teleworking context.

This study conducts a large-scale and cross-national survey of 710 remote employees who worked from home partially or fully during the COVID-19 outbreak across three countries: the USA, the UK and Vietnam.

The results show that FWC drives affective commitment, leading to greater employees’ operational and marketing productivity when teleworking. We also find distinct moderating effects of organizational factors (i.e. task control) and employees’ psychological factors (i.e. emotional exhaustion) on the FWC–operational productivity link across the three countries. Moreover, centralization positively moderates the effect of operational productivity on marketing productivity in the teleworking context in Vietnam, while it is not the case in the USA and the UK.

This study fills a gap in the literature by revealing cross-national differences in the underlying mechanism of the FWC effects on employees’ operational and marketing productivity in the pandemic-induced teleworking conditions. It extends extant studies in the work–family literature by introducing affective commitment as an important mediator in translating the negative consequences of FWC to operational and marketing productivity gain in crisis-driven teleworking across national cultures. We also provide insights into the distinct moderating roles of task control and emotional exhaustion in determining the FWC effect on operational productivity as well as that of centralization in driving marketing productivity. The findings have substantive implications for teleworking design and management to improve employee productivity across different national settings.

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.

The proposed model aims to tackle the data quality issues in multivariate time series caused by missing values. It preserves data set integrity by accurately imputing missing data, ensuring reliable analysis outcomes.

The Conv-DMSA model employs a combination of self-attention mechanisms and convolutional networks to handle the complexities of multivariate time series data. The convolutional network is adept at learning features across uneven time intervals through an imputation feature map, while the Diagonal Mask Self-Attention (DMSA) block is specifically designed to capture time dependencies and feature correlations. This dual approach allows the model to effectively address the temporal imbalance, feature correlation and time dependency challenges that are often overlooked in traditional imputation models.

Extensive experiments conducted on two public data sets and a real project data set have demonstrated the adaptability and effectiveness of the Conv-DMSA model for imputing missing data. The model outperforms baseline methods by significantly reducing the Root Mean Square Error (RMSE) metric, showcasing its superior performance. Specifically, Conv-DMSA has been found to reduce RMSE by 37.2% to 63.87% compared to other models, indicating its enhanced accuracy and efficiency in handling missing data in multivariate time series.

The Conv-DMSA model introduces a unique combination of convolutional networks and self-attention mechanisms to the field of missing data imputation. Its innovative use of a diagonal mask within the self-attention block allows for a more nuanced understanding of the data’s temporal and relational aspects. This novel approach not only addresses the existing shortcomings of conventional imputation methods but also sets a new standard for handling missing data in complex, multivariate time series data sets. The model’s superior performance and its capacity to adapt to varying levels of missing data make it a significant contribution to the field.

This paper aims to provide a full introduction, new classification, comparison and investigation of the challenges as well as applications of layerless 3D printing, which is one of the industry 4.0 pioneers.

Given the significance and novelty of uniform 3D printing, more than 250 publications were collected and reviewed in an unbiased and clear manner.

As a result, the majority of uniform parts printed in polymer form are known up to this point. In a novel division for better researchers’ comprehension, uniform printing systems were classified into three categories: oxygen inhibition (OI), liquid lubrication (LL) and photon penetration (PP), and each was thoroughly investigated. Furthermore, these three approaches were evaluated in terms of printing speed, precision and accuracy, manufacturing scale and cost.

The parameters of each approach were compared independently, and then a practical comparison was conducted among these three approaches. Finally, a variety of technologies, opportunities, challenges and advantages of each significant method, as well as a future outlook for layerless rapid prototyping, are presented.

This study aims to propose a cloud platform architecture considering information sharing based on blockchain to realize the security and convenience of enterprise information sharing in the automotive supply chain.

A bilateral matching model considering enterprises information contribution stimulates information sharing and improves the efficiency and quality of supply and demand matching. Three smart contracts are used to complete the information sharing process and match supply and demand in the automotive supply chain.

The system is tested on the local Ganache private chain, and the decentralized web page is designed based on the architecture prototype.

Solve the problem of information island in automobile supply chain.