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The proponents of cash waqf speak highly about its huge potential for mobilizing the third sector of the economy to fund the socio-economic development agenda. However, the under-collection issue has been characterizing the cash waqf movement globally. This study aims to examine how understanding the distinct cash waqf donating behavior across different generations has the potential to address the problem.

This study extends the theory of planned behavior by adding religiosity and knowledge variables into the standard model, using the partial least square structural equation modeling. A survey is conducted on 684 respondents representing the main provinces in Indonesia and four major generations (Baby Boomers [BB], Generations X, Y and Z).

Religiosity, Knowledge, Attitude, Subjective Norms and Perceived Behavioral Control directly or indirectly affect cash waqf intention. The effect is contingent on the characteristics of generations.

This study covers only the Indonesian case with limited coverage of the more heterogeneous provinces in the country. The sample distribution for BB can also be enlarged.

Cash waqf institutions (government and private) should apply the dynamic segmenting strategy, where the diversification of the promotion, marketing, awareness and approaches are contingent on the different characteristics of each generation.

To the best of the authors’ knowledge, this is the first study evaluating the intergenerational determinants of Intention toward cash waqf, particularly in Indonesia.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

The purpose of this paper is to assess the feasibility of analytical models, specifically the radial basis function method, Akbari–Ganji method and Gaussian method, in conjunction with the finite element method. The aim is to examine the impact of processing parameters on temperature history.

Through analytical investigation and finite element simulation, this research examines the influence of processing parameters on temperature history. Simufact software with a thermomechanical approach was used for finite element simulation, while radial basis function, Akbari–Ganji and Gaussian methods were used for analytical modeling to solve the heat transfer differential equation.

The accuracy of both finite element and analytical methods was validated with about 90%. The findings revealed direct relationships between thermal conductivity (from 100 to 200), laser power (from 400 to 800 W), heat source depth (from 0.35 to 0.75) and power absorption coefficient (from 0.4 to 0.8). Increasing the values of these parameters led to higher temperature history. On the other hand, density (from 7,600 to 8,200), emission coefficient (from 0.5 to 0.7) and convective heat transfer (from 35 to 90) exhibited an inverse relationship with temperature history.

The application of analytical modeling, particularly the utilization of the Akbari–Ganji, radial basis functions and Gaussian methods, showcases an innovative approach to studying directed energy deposition. This analytical investigation offers an alternative to relying solely on experimental procedures, potentially saving time and resources in the optimization of DED processes.

We explore how sustainable management education (SME) can help prepare future leaders to manage crises effectively. Precisely, the intricacies of articulating moral and economic imperatives for businesses in a manner that engages students in sustainable behavior are a serious challenge for SME. We study how to integrate reminders of moral and economic imperatives in a socially responsible investment (SRI) stock-picking simulation created for SME.

Adopting an experimental design, we analyzed how the reminders affected the average environment social governance (ESG) integration in the portfolios of 127 graduate students in finance over a twelve-week period.

Our results show how essential it is to balance the two imperatives. The highest level of sustainable investment is attained when utilizing both reminders.

Our findings have practical implications for implementing and organizing SME in business schools to educate responsible leaders who are able to effectively manage crises. Learning responsible management is most effective when students are exposed to the inherent tension between moral and economic imperatives. Hence, our findings corroborate the win-win conception of SME.

No management decision study has experimentally measured the effects of SME practices on students' actual behavior. Our research fills this gap by complementing previous studies on the effectiveness of teaching practices, first by drawing on behavioral sciences and measuring changes in students' actual sustainability behavior and second by introducing moral and economic imperatives into an innovative teaching resource (TR) dedicated to SME.

The efficiency of each of an organization’s individual workers determines its effectiveness. The study aims to explore the relationship between human resource management (HRM) practices and organizational effectiveness with employee performance as a mediating variable.

Data were collected from 800 police officers in the Greater Accra and Tema regions. The data were supported by the hypothesized relationship. Construct reliability and validity was established through confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

The results show that career planning and employee performance were significantly related. Self-managed teams and employee performance were shown to be nonsignificantly related. Similarly, performance management and employee performance were shown to be nonsignificantly related. Employee performance significantly influenced organizational effectiveness. The results further indicate that employee performance mediates the relationship between HRM practices and organizational effectiveness.

The generalizability of the findings will be constrained due to the research’s police service focus and cross-sectional data.

The study’s findings will serve as valuable pointers for the police administration in the adoption, design and implementation of well-articulated and proactive HRM practices to improve the abilities, skills, knowledge and motivation of officer’s to inordinately enhance the effectiveness of the service.

By evidencing empirically that employee performance mediates the relationship between HRM practice and organizational effectiveness, the study extends the literature.

This study aims to examine the role of hope and hate in political leaders’ messages in influencing liberals versus conservatives’ social-distancing behavior during the COVID-19 pandemic. Given the increasing political partisanship across the world today, using the appropriate message framing has important implications for social and public policy.

The authors use two Natural Language Processing (NLP) methods – a pretrained package (HateSonar) and a classifier built to implement our supervised neural network-based model architecture using RoBERTa – to analyze 61,466 tweets by each US state’s governor and two senators with the goal of examining the association between message factors invoking hate and hope and increased or decreased social distancing from March to May 2020. The authors examine individuals’ social-distancing behaviors (the amount of nonessential driving undertaken) using data from 3,047 US counties between March 13 and May 31, 2020, as reported by Google COVID-19 Community Mobility Reports and the New York Times repository of COVID-19 data.

The results show that for conservative state leaders, the use of hate increases nonessential driving of state residents. However, when these leaders use hope in their speech, nonessential driving of state residents decreases. For liberal state leaders, the use of hate displays a directionally different result as compared to their conservative counterparts.

Amid the emergence of new analytic techniques and novel data sources, the findings demonstrate that the use of global positioning systems data and social media analysis can provide valuable and precise insights into individual behavior. They also contribute to the literature on political ideology and emotion by demonstrating the use of specific emotion appeals in targeting specific consumer segments based on their political ideology.

The findings have significant implications for policymakers and public health officials regarding the importance of considering partisanship when developing and implementing public health policies. As partisanship continues to increase, applying the appropriate emotion appeal in messages will become increasingly crucial. The findings can help marketers and policymakers develop more effective social marketing campaigns by tailoring specific appeals given the political identity of the consumer.

Using Neural NLP methods, this study identifies the specific factors linking social media messaging from political leaders and increased compliance with health directives in a partisan population.

Although user stickiness has been studied for several years in the field of live e-commerce, little attention has been paid to the effects of streamer attributes on user stickiness in this field. Rooted in the stimulus-organism-response (S-O-R) theory, this study investigated how streamer attributes influence user stickiness.

The authors obtained 496 valid samples from Chinese live e-commerce users and explored the formation of user stickiness using partial least squares-structural equation modeling (PLS-SEM). Artificial neural network (ANN) was used to capture linear and non-linear relationships and analyze the normalized importance ranking of significant variables, supplementing the PLS-SEM results.

The authors found that attractiveness and similarity positively impacted parasocial interaction (PSI). Expertise and trustworthiness positively impacted perceived information quality. Moreover, streamer-brand preference mediated the relationship between PSI and user stickiness, as well as the relationship between perceived information quality and user stickiness. Compared to PLS-SEM, the predictive ability of ANN was more robust. Further, the results of PLS-SEM and ANN both showed that attractiveness was the strongest predictor of user stickiness.

This study explained how streamer attributes affect user stickiness and provided a reference value for future research on user behavior in live e-commerce. The exploration of the linear and non-linear relationships between variables based on ANN supplements existing research. Moreover, the results of this study have implications for practitioners on how to improve user stickiness and contribute to the development of the livestreaming industry.

The present research attempts to show the contribution of emotional intelligence and servant leadership climate to individual adaptive performance. The authors intend to explain the relations between the emotional intelligence of employees as well as of manager and the employee's adaptive performance. Moreover, this research assesses the significance of the mediating role of “servant leadership” climate in the relationship between the emotional intelligence of the manager and the employee's adaptive performance.

This research uses the quantitative research method and is included in explanatory research. Data collection used several informants for each organization. Data were collected using a sample of 57 managers and 204 team members spread over 24 companies belonging to different sectors of activity.

Employees' emotional intelligence directly influences individual adaptive performance. There is a direct influence of manager's emotional intelligence on individual adaptive performance. Then, there is an indirect influence of emotional intelligence on individual adaptive performance through the mediation of servant leadership climate.

The novelty of this research is in its effort to observe the multilevel mediation of servant leadership climate with other variables developed in the research model. No previous studies have found a relationship between employee and manager's emotional intelligence and individual adaptive performance.