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This study aims to examine the factors that affect individuals’ intentions of participating in waqf-based crowdfunding model in Kuwait.

This study adopted the unified theory of acceptance and use of technology (UTAUT) model. The data were collected by online questionnaire survey based on 419 donors in waqf institutions in Kuwait. The data were analysed using the partial least squares structural equation modelling technique.

The results illustrate that performance expectancy, effort expectancy, social influence and facilitating condition positively affect behavioural intention towards waqf-based crowdfunding projects.

The paper presents an alternative source for waqf institutions to raise capital to develop waqf assets in majority and minority Muslim countries. The findings of this study hold significant implications for government officials and policymakers.

To the best of the authors’ knowledge, this paper is the first to explore waqf crowdfunding in Kuwait using the UTAUT model. There needs to be more research on waqf-giving behaviour in Kuwait, particularly concerning crowdfunding, which has become more popular recently. Thus, this paper aims to address this gap and contribute new insights to the field.

Truck-sharing stands out as an impactful strategy for minimizing emissions and optimizing the streamlined transport of goods. This study seeks to address a gap in understanding by investigating the barriers shippers face in adopting truck-sharing services.

This study employs the innovation resistance theory to examine a range of potential barriers. A total of seven potential barriers are included in the investigation. Survey data from Bangladeshis are analyzed using an artificial neural network.

The barriers, ranked in importance, include image, tradition, value, usage, risk, psychological ownership and privacy concerns. Thus, psychological barriers (image and tradition) mostly underpin resistance to change, showing that the issue is more rooted in shippers' perceptions than operations. Also, they often do not find a financial cause to use truck-sharing services. Usage barriers, explicitly addressing the practical application of truck-sharing services, have now assumed the third position, underscoring their significance in overcoming the barriers.

The findings provide valuable insights for policymakers to reconsider their approaches in addressing the most formidable truck-sharing barriers.

This insight holds implications for shippers and transport companies, offering strategic guidance to optimize their engagement with and support for such services.

To the best of our knowledge, this study examines shippers' reluctance to adopt truck-sharing services in a developing country.

Be that as it may, BC is computationally costly, has restricted versatility and brings about critical transmission capacity upward and postpones, those seems not to be fit with Internet of Things (IoT) setting. A lightweight scalable blockchain (LSB) which is improved toward IoT necessities is suggested by the authors and investigates LSB within brilliant house setup like an agent model to enable more extensive IoT apps. Less asset gadgets inside brilliant house advantage via any unified chief which lays out common units for correspondence also cycles generally approaching and active solicitations.

Federated learning and blockchain (BC) have drawn in huge consideration due to the unchanging property and the relevant safety measure and protection benefits. FL and IoT safety measures’ difficulties can be conquered possibly by BC.

LSB accomplishes fragmentation through shaping any overlaid web with more asset gadgets mutually deal with a public BC and federated learning which assures complete protection also security.

This overlaid is coordinated as without error bunches and reduces extra efforts, also batch leader will be with answer to handle commonly known BCs. LSB joins some of advancements which also includes computations related to lesser weighing agreement, optimal belief also throughput regulatory body.

This paper aims to examine the impact of board gender diversity on the likelihood of financial distress in 90 Jordanian companies listed on the Amman Stock Exchange from 2010 to 2021.

To examine the hypotheses, this study used the panel logistic regression. In addition, this study used the two-staged Heckman regression model as a robust check. To proxy for the financial distress, the 2005 version of Altman’s Z-score for emerging markets was used.

The results indicate that female directors can reduce the likelihood of financial distress in Jordanian listed companies. These findings align with previous literature that highlights the benefits of female directors on corporate boards.

To the best of the authors’ knowledge, this study is the first to examine the impact of board gender diversity on financial distress in Jordan and the Middle East and highlights several practical implications. It emphasizes the need for policymakers to develop regulations that promote gender diversity on corporate boards as a strategy to enhance stability and prevent financial distress. For corporate managers, incorporating more women into board roles could strengthen decision-making and risk management. Regulators are advised to support these changes through improved governance codes. In addition, increasing female board participation could enhance corporate responsibility, reduce bankruptcy risks and boost overall economic stability, benefiting society at large.

This paper aims to develop an optimization model to enhance pipeline assembly performance. It focuses on predicting the pipeline’s assembly pose while ensuring compliance with clamp constraints.

The assembly pose of the pipeline is quantitatively assessed by a proposed indicator based on joint defects. The assembly interference between the pipeline and assembly boundary is characterized quantitatively. Subsequently, an analytical mapping relationship is established between the assembly pose and assembly interference. A digital fitting model, along with a novel indicator, is established to discern the fit between the pipeline and clamp. Using the proposed indicators as the optimization objective and penalty term, an optimization model is established to predict the assembly pose based on the reinforced particle swarm optimization, incorporating a proposed adaptive inertia weight.

The optimization model demonstrates robust search capability and rapid convergence, effectively minimizing joint defects while adhering to clamp constraints. This leads to enhanced pipeline assembly efficiency and the achievement of a one-time assembly process.

The offset of the assembly boundary and imperfections in pipeline manufacturing may lead to joint defects during pipeline assembly, as well as failure in the fit between the pipeline and clamp. The assembly pose predicted by the proposed optimization model can effectively reduce the joint defects and satisfy clamp constraints. The efficiency of pipeline modification and assembly has been significantly enhanced.

This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.

Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.

The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.

The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.

Driven by the rapid expansion of online retail and the surge in livestream commerce, the impact of different livestream mode on brand and platform performance has become a critical issue. This paper analyzes the impact of artificial intelligence (AI) and key opinion leader (KOL) livestream on the profitability of brands and the platform, incorporating the effects of horizontal interactions to identify the optimal livestream mode.

This paper develops a model of a platform supply chain involving two brands and a platform, where each brand independently decides whether to utilize KOL or AI livestream. Applying Stackelberg game approach, the study derives equilibria for various livestream scenarios, identifying the optimal livestream mode for both parties. Additionally, the model is extended to incorporate asymmetric market potential and network externality to evaluate their impact on a brand’s choice of livestream mode.

Several interesting and important results are derived in this paper. Firstly, it is found that AI livestream enables brands to leverage network externality and mitigate the market disadvantage, thereby gaining a competitive advantage. Secondly, while KOL livestream promotes trust, the medium KOL commission rates could cause brands to be trapped in a prisoner’s dilemma, and excessively high commission rates may render them less profitable. Thirdly, the KOL commission rate, network externality intensity, horizontal interactions and market disadvantage are critical determinants influencing a brand’s choice of livestream mode.

This study is the first to investigate the effects of horizontal interactions, asymmetric market potential and asymmetric network externality on livestream mode selection by brands within a platform supply chain. The research provides valuable insights into optimizing livestream strategies to enhance brand profitability.

Drawing on conservation of resources (COR) theory, this study examined the effect of developmental human resource (HR) practices on employee workplace procrastination and investigated the mediation effect of boredom at work and the moderation effects of exploitative leadership and self-leadership.

Data were collected from 443 employees across companies in China. Hypotheses were tested using hierarchical regression analysis and indirect effect testing via bootstrapping in SPSS and Mplus.

This study found that developmental HR practices were negatively related to employee workplace procrastination and that boredom at work mediated the relationship between developmental HR practices and employee workplace procrastination. Moreover, exploitative leadership strengthened the negative relationship between developmental HR practices and boredom at work, whereas self-leadership weakened the positive relationship between boredom at work and employee workplace procrastination. The indirect relationship between developmental HR practices and employee workplace procrastination through boredom at work was moderated by exploitative leadership and self-leadership.

This study extended the literature on the antecedents of employee workplace procrastination. Moreover, by investigating the mediation effect of boredom at work, this study extended the underlying mechanism by which developmental HR practices affect subsequent employee outcomes. Finally, by testing the moderation effect of exploitative leadership and self-leadership, respectively, this study offered insights into the boundary conditions resultant from developmental HR practices.

The purpose of this study is to develop and assess the effects of unified theory of acceptance and use of technology (UTAUT 2) constructs – effort expectancy (EE), social influence (SI) and hedonic motivation (HM) – on behavioural intention (BI), as well as the impact of innovation resistance theory (IRT) constructs – usage barrier (UB) and tradition barrier (TB) – on innovation resistance (IR) behavior in the context of digital zakat payment in Aceh. In addition, this study also examines how knowledge of fiqh zakat influences both BI and IR.

This was a quantitative study including 350 Acehnese persons who paid zakat online. This research used a Likert scale, and the sampling technique was purposive sampling applied for the Acehnese people. The research respondents were civil servants, private employees, BUMN employees (employees of State-Owned Enterprises), merchants, restaurant owners, professionals and other occupations who had paid professional zakat through a digital system mechanism. The data were analysed using partial least squares structural equation modelling.

This research found that the constructs built through the theory of UTAUT 2 explained the position of the EE variable, which had a significant effect on BI. On the other hand, the variable of SI and HM did not significantly affect BI in digital zakat payment. This finding demonstrated that BI significantly influenced actual usage (AU). UB and TB had no impact on IR, according to the theoretical framework developed by IRT. Yet, the knowledge about the fiqh zakat (KFZ) significantly affected the AU. In terms of the moderation role, the KFZ variable moderated the relationship between BI and AU. However, the KFZ variable did not moderate the relationship between IR and AU.

This research had limitations and could still be investigated further by involving a larger sample. This study does not include all UTAUT 2 and IRT constructs, but only involves UTAUT 2 and IRT constructs based on the phenomenon of digital zakat paying behavior in the people of Aceh.

This research had a managerial contribution and an evaluation of the use of digital zakat collection services in Aceh and zakat management institutions in various countries. The existence of significant EE should be a reference for zakat institutions to produce continuous payment applications with a higher level of convenience in the future. In addition, the government should encourage more organised fiqh zakat education in society to plan a more optimal zakat collection. The reason for this is that KFZ has been shown to moderate zakat intentions towards actual digital zakat payment behaviour.

The results of this study were then accommodated by the government to design a digital zakat collection system so that it resulted in optimising the collected zakat funds. The greater the zakat funds collected, the greater the economic impact and social resilience of the community was in the midst of the post-covid and global crisis.

This research provided an essential value in the aspect of collecting zakat funds, especially in the study of the behaviour of paying zakat digitally. The theory of planned behaviour predominated in earlier studies that investigated zakat-paying behaviour. Yet, this research was even more focused as it used the constructs of UTAUT 2 and IRT theory and applied the involvement of a moderator variable like fiqh zakat knowledge that was barely discussed.

The digital disruptions have provided alternative methods of monetary transactions. Despite the digital wave, cash as a payment option has regained its position. The purpose of this research is to investigate behavioral intentions of mobile wallet (m-wallet) users. The paper explores the dynamics of perception, behavioral intention motivation and satisfaction of m-wallet users.

The authors have used a self-administered questionnaire for data collection. A total of 506 responses were analysed using confirmatory factor analysis in conjunction with Structural Equation Modeling, ensuring the validity and reliability of the insights into the behavioral dynamics of m-wallet users.

The research highlights the direct impact of perceived security on m-wallet users' perceptions, which subsequently influence both direct and indirect behavioral intentions. Moreover, satisfaction emerged as a significant determinant directly shaping behavioral intentions.

This study contributes significantly to the existing literature by offering a comprehensive understanding of the factors driving m-wallet adoption and usage intentions, thereby equipping stakeholders and policymakers with the necessary tools to devise effective strategies to promote mobile payment technologies in North India. The study employs a multifaceted model that incorporates six key elements, providing a comprehensive understanding of the complex interrelationships among these variables.