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Research focusing on psychological capital (PsyCap) has been mainly conducted at the individual level. However, recent research has expanded investigations to the collective level with a greater focus on team-level PsyCap. Although, as demonstrated by recent systematic reviews and meta-analyses, the relationships between individual-level PsyCap and the desirable/undesirable outcomes are fairly established in the literature, less is known about such relationships for team-level PsyCap. One of these important, yet least investigated, research areas is the research stream that focuses on the relationship between team-level PsyCap and the outcomes of health, Well-Being, and safety. This chapter aims to highlight the role of individual-level PsyCap as an important predictor of employees’ health, Well-Being, and safety outcomes, but also to go beyond that to provide insights into the potential role of team-level PsyCap in predicting such outcomes at both individual and team levels. To do so, the chapter first draws upon relevant theories to discuss the empirical research findings focusing on the relationship between individual-level PsyCap and the outcomes of health, Well-Being, and safety. It then focuses on team-level PsyCap from theoretical, conceptualization, and operationalization perspectives and provides insights into how team-level PsyCap might be related to health, Well-Being, and safety outcomes at both individual and team levels. Thus, this chapter proposes new research directions in an area of PsyCap that has been left unexplored.

Although researchers have carried out considerable work on organizational citizenship behavior (OCB), the questions of whether and how adopting a positive leadership style leads subordinate employees to engage in interpersonal citizenship behavior (ICB) remain, thus far, unanswered. To address this research gap, this study aimed to uncover the possible underlying mediation mechanism.

Partial least squares structural equation modeling (PLS-SEM) was used to test the research model using data collected by means of a three-wave online survey with 166 respondents.

The results indicated that the organization-based self-esteem (OBSE) of subordinate employees mediated the effect of supervisors using a positive leadership style on subordinates engaging in person-focused ICB.

The importance of positive leadership is revealed in the finding of a self-consistency-based positive spillover effect, according to which the use of a positive leadership style directly benefits subordinates by enhancing their OBSE. This subsequently motivates them to engage in person-focused ICB, which benefits their coworkers. Thus, a positive leadership style creates a positive dynamic in the workplace.

Ascorbic acid, a water-soluble antioxidant, is an essential component of the human diet and is known for its potent antioxidant properties against several diseases. In recent years, there has been increasing interest in the development of nonenzymatic sensors due to their simplicity, efficiency and excellent selectivity. The aim of this study is to present a selective and sensitive method for the detection of ascorbic acid in aqueous system using a new electrochemical non-enzymatic sensor based on a gold nanoparticles Au-NPs-1,3-di(4-bromophényl)-5-tert-butyl-1,3,5-triazinane (DBTTA) composite.

Using the square wave voltammetry (SWV) technique, a series of Au-NPs-DBTTA composites were successfully developed and investigated. First, DBTTA was synthesized via the condensation of tert-butylamine and a4-bromoaniline. The structure obtained was identified by IR, 1H NMR and 13C NMR analysis. A glassy carbon electrode (GCE) was modified with 10–1 M DBTTA dissolved in an aqueous solution by cyclic voltammetry in the potential range of 1–1.4 V. Au-NPs were then deposited on the DBTTA/GCE by a chronoamperometric technique. SWV was used to study the electrochemical behavior of the modified electrode (DBTTA/Au-NPs/GCEs). To observe the effect of nanoparticles, ascorbic acid in a buffer solution was analyzed by SWV at the modified electrode with and without gold nanoparticles (Au-NPs).

The DBTTA/Au-NPs/GCE showed better electroanalytical results. The detection limit of 10–5 M was obtained and the electrode was proportional to the logarithm of the AA concentration in the range of 5 × 10⁻³ M to 1 × 10⁻¹ with very good correlation parameters.

It was also found that the elaborated sensor exhibited reproducibility and excellent selectivity against interfering molecules such as uric acid, aspartic acid and glucose. The proposed sensor was tested for the recognition of AA in orange, and satisfactory results were obtained.

This study investigates user preferences for motivational features aligned with self-determination theory (SDT), emphasizing autonomy, relatedness, and competency. The study seeks to identify the most appealing and effective motivational features in AI-driven mobile apps for fostering autonomy, promoting relatedness, and enhancing feelings of competency in the context of reading comprehension.

Employing a mixed-methods research design based on the self-determination theory, the study used triangulation of methods to enhance the research findings' quality, completeness, validity, and understanding.

Both qualitative and quantitative findings showed similarities in the emphasis on personalization, progress tracking, social interaction, gamification, differences in specific feature preferences, and nuanced recommendations, highlighting the importance of a comprehensive and user-centric development approach.

The study design and sample size might constrain the statistical power and generalizability of the results. The study used a convenience sample of students from one school.

The synthesis of findings suggests the need for a comprehensive development strategy that incorporates both the commonalities and nuanced recommendations from qualitative and quantitative data. Combining the strengths of both findings, a holistic user-centric approach that integrates personalization, progress tracking, social interaction, and gamification is crucial for effective app development. Recognizing that individual preferences may vary, developers should consider tailoring features to accommodate a range of user needs, as indicated by qualitative and quantitative insights.

This comprehensive approach contributes to advancing knowledge in AI-driven mobile applications and their impact on student motivation and reading comprehension in the Philippine context. Also, it provides valuable insights for designers and developers, contributing to creating engaging and user-friendly platforms that enhance reading comprehension skills.

The present study seeks to examine the impact of ethical leadership on employees’ voice behavior and internal whistleblowing in organizations. Specifically, the study investigates the mediating role of moral emotions in the link between ethical leadership and employees’ reporting behaviors such as voice behavior and internal whistleblowing.

This research utilized a sample of 200 employees from various private companies in Pakistan, gathering data via questionnaires to validate the hypotheses. We employed Structural Equation Modeling (SEM) to evaluate the model and conducted a mediation analysis using 5,000 bootstrap samples.

This research found that ethical leadership positively impacts employees' moral emotions, encouraging them to voice concerns and report misdeeds. Additionally, the study affirms a direct and positive connection between ethical leadership and employees' reporting behaviors, including voice behavior and internal whistleblowing.

The findings of the study emphasized the development of ethical leadership in organizations by highlighting the critical role of ethical leadership in enhancing moral emotions, voice behavior, and whistleblowing in organizations. It highlights the necessity of promoting moral behavior to enhance organizational effectiveness and the need for ethical leaders to foster an open environment in organizations that encourages whistle bellowing and reporting of unethical practices in organizations.

The current paper extends knowledge of ethical leadership based on the social cognitive theory of morality by considering that moral emotions serve as a strong motivational cognition between ethical leadership and reporting behaviors. Particularly, by examining the mediating role of moral emotion, this study provides a deeper understanding of the underlying mechanism through which ethical leadership influences reporting behaviors of employees at workplace.

Notwithstanding their potential benefits especially for individuals with low health literacy, users are still somewhat skeptical about the reliability of healthcare chatbots. The present study aims to address this challenge by investigating strategies to enhance users’ cognitive and emotional trust in healthcare chatbots. Particularly, this study aims to understand the effects of chatbot design cues in increasing trust and future chatbot use intention for low health literacy users.

We conducted two experimental studies with a final sample of 327 (Study 1) and 241 (Study 2). Three different chatbots were developed (Chatbot design: Bot vs Male-doctor vs Female-doctor). Participants were asked to have a medical consultation with the chatbot. Participants self-reported their health literacy scores. The PROCESS model 7 was used to analyze the hypotheses.

The results showed that the female-doctor cues elicited greater cognitive and emotional trust, whereas the male-doctor cues only led to greater cognitive trust (vs bot-like cues). Importantly, this study found that users’ health literacy is a significant moderating factor in shaping cognitive and emotional trust. The results indicated that both the female and male-doctor cues’ positive effects on cognitive trust were significant for those with lower levels of health literacy. Furthermore, the positive effect of the female-doctor cues on emotional trust was also significant only for those whose health literacy level was low. The increased cognitive and emotional trust led to greater future intention to use the chatbot, confirming significant moderated mediation effects.

Despite the strong economic and educational benefits of healthcare chatbots for low health literacy users, studies examining how healthcare chatbot design cues affect low health literate users surprisingly remained scarce. The results of this study suggest that healthcare chatbots can be a promising technological intervention to narrow the health literacy gap when aligned with appropriate design cues.

The study aims to investigate how attribution theory in the context of pricing strategies can help tourism destinations recover from the negative impacts of the COVID-19 pandemic.

The study adopted a qualitative research design using semi-structured interviews to address the lack of research in this area. Interview participants included tourists and tourism customers. The interview responses were then analyzed using “Nvivo” qualitative data analysis software to identify critical themes regarding applying attribution theory to pricing strategies.

The findings revealed that tourists prefer bundled and hedonic pricing strategies that integrate the service providers' pricing strategies' locus of control, stability and controllability. Tourists do not favor dual pricing strategies unless the reasons for price controllability or stability are justified. Tourists also prefer the controllable pay-what-you-want pricing strategy. Although tourists accept dynamic pricing, certain conditions related to price locus, stability and controllability must be met.

The research shows tourists prefer pricing strategies that give them control and flexibility, like bundled packages and pay-what-you-want models. Service providers should integrate pricing strategies that transparent costs and justify price fluctuations. While dynamic pricing is accepted if necessitated by external factors, tourists are wary of unnecessary price changes. Providers can build trust and satisfaction by explaining pricing rationale and offering controllable options like bundles.

The study contributes to the theory by applying attribution theory to the context of pricing strategies in tourism. It also provides innovative recommendations for tourism managers on how to use pricing strategies after the COVID-19 pandemic. The findings offer new insights that extend beyond previous research.

Project portfolio benefit (PPB) evaluation is crucial for project portfolio management decisions. However, PPB is complex in composition and affected by synergy and ambidexterity. Ignoring these characteristics can result in inaccurate assessments, impeding the management and optimization of benefit. Considering the above complexity of PPB evaluation, this study aims to propose a refined PPB evaluation model to provide decision support for organizations.

A back propagation neural network optimized via genetic algorithm and pruning algorithm (P-GA-BPNN) is constructed for PPB evaluation. First, the benefit evaluation criteria are established. Second, the inputs and expected outputs for model training and testing are determined. Then, based on the optimization of BPNN via genetic algorithm and pruning algorithm, a PPB evaluation model is constructed considering the impacts of ambidexterity and synergy on PPB. Finally, a numerical example was applied to validate the model.

The results indicate that the proposed model can be used for effective PPB evaluation. Moreover, it shows superiority in terms of MSE and fitting effect through extensive comparative experiments with BPNN, GA-BPNN, and SVM models. The robustness of the model is also demonstrated via data random disturbance experiment and 10-cross-validation. Therefore, the proposed model could serve as a valuable decision-making tool for PPB management.

This study extends prior research by integrating the impacts of synergy and ambidexterity on PPB when conducting PPB evaluation, which facilitates to manage and enhance PPB. Besides, the structural redundancy of existing assessment methods is solved through the dynamic optimization of the network structure via the pruning algorithm, enhancing the effectiveness of PPB decision-making tools.

In order to improve the efficiency and reliability of simulation analysis for composite riveting structures in engineering products, a comparative study was conducted on different forms of riveting simulation methods.

Five different rivent simulation models were established using the finite element method, including rigid element CE, flexible element Rbe3 and beam element, and their results were future compared and analyzed.

Under the given technical parameters, the simulation method of Rbe3 (with holes) + beam can meet the analysis requirements of complex engineering products in terms of the rationality of rivet load distribution, calculation error and relatively efficient modeling.

This study proposes a simulation method for the riveting structure of carbon fiber composite materials for engineering applications. This method can satisfy the simulation analysis requirements of transportation vehicles in terms of modeling time, computational efficiency and accuracy. The research can provide technical support for the riveting process and mechanical analysis between carbon fiber composite components in transportation products.

In this study, the authors investigate whether supply chain (SC) strategies (lean or agile) improve or hinder the supply chain transparency (SCT) and what factors affect this relation.

The authors measure the level of SC strategy using natural language processing based on the annual financial reports of listed firms. Secondary data analysis is conducted on various databases encompassing 1,241 listed firms in China from 2011 to 2020. Additional tests are performed to assess the robustness of the results, and alternative explanations are duly considered.

The authors find that firms with an advanced level of SC strategy perform better on SCT. Furthermore, the authors observe that Agile SC strategy and Lean SC strategy have different effects on SCT over a firm’s life cycle. Agile SC strategy (the ratio of the proportion of Agile SC strategy word frequency divided by the proportion of Lean SC strategy word frequency greater than 1) has a significantly positive effect on SCT in the maturity stage; Lean SC strategy (the ratio less than 1) has a positive effect on SCT in the growth and decline stages. An increase in online media coverage negatively moderates the impact of the SC strategy (frequency of Lean and Agile SC strategy-related keywords) on SCT in the maturity stage. An increase in government environmental subsidies positively moderates the impact of SC strategy on SCT in the maturity and decline stages. Additionally, an increase in industrial competition intensity positively moderates the impact of the SC strategy on SCT in the decline stage.

The authors' study contributes to the Operations and Supply Chain Management (OSCM) literature by revealing the positive impact of SC strategy on SCT with objective secondary data. Additionally, the authors examine the moderating effects of moderators over the lifecycle of a firm on this relationship in an emerging market context. The authors' findings offer valuable guidance to companies operating in diverse market environments, providing actionable insights to strengthen their SC strategies and enhance SCT.