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Concerns regarding the dysfunctional behaviours of public officials have sparked renewed interest in public service ethics and spirituality. While national and organizational systems have been established to eliminate dysfunctional behaviours such as corruption, sexual harassment and misuse of confidential information, the practice continues to have a demoralizing impact on developing countries. The study aims to intend to investigate the empirical relation between the application of spirituality and ethics in reducting dysfunctional behaviours within Ghana's Public Sector.

The study conducted a qualitative case analysis that utilized 28 semi-structured interviews and four focus groups. Interviews and group discussions with public sector staff, managers and policymakers were used to collect qualitative data. This approach facilitated an in-depth investigation into their views on dysfunctional actions and the possible impact of workplace spirituality and ethics in the Ghanaian public service.

The study uncovered a persistent recurrence of dysfunctional behaviours, such as fraudulent activities, resource misuse, unofficial work and inappropriate use of official time. There was uncertainty regarding the effectiveness of integrating ethics and spirituality to curtail dysfunctional behaviours. Nevertheless, the results supported adopting spiritual and ethical rejuvenation in the public service as a universal solution to overcome these behaviours.

This study enhances comprehension of dysfunctional behaviours in Ghana's public service by providing insights into how spirituality and ethics can transform it. The potentials of workplace spirituality and ethics can lead to a strong public service that embodies accountability, integrity and effectiveness, thereby serving as a pivotal device for Ghana's holistic advancement.

Libraries are currently undergoing a significant transformation, emerging as dynamic advocates for environmental sustainability, surpassing their conventional roles as mere repositories of knowledge. In today’s world, dominated by the growing climate crisis, these evolving institutions are poised to play a pivotal role in addressing climate change. However, they confront a range of challenges, including the need to establish sustainable operations, provide accessible climate information, engage diverse audiences and uphold ethical standards.

The research methodology used for this study involves an extensive review of literature. The authors analyze existing studies concerning green libraries and their role as catalysts for climate change action globally. This analysis draws from a variety of scholarly sources, encompassing articles, books and reports, to provide a comprehensive overview of the subject.

The findings indicate that despite the aforementioned challenges, libraries in developed countries worldwide have demonstrated noteworthy success through initiatives such as green building projects, community engagement programs, collaborative partnerships, expansion of digital resources, innovative climate literacy initiatives and a commitment to ethical stewardship. These achievements serve as a source of inspiration, fostering hope and spurring action as libraries empower communities to embrace environmental stewardship. They showcase the potential of libraries as catalysts for positive environmental change.

The originality and value of this research lie in its insights into the potential of green libraries initiative as a catalyst for climate change action. Ultimately, this study opens the door to untold literary exploration, revolutionizing the art of green library capacity in the ever-evolving technological landscape. To augment their impact, libraries are encouraged to broaden the scope of their climate education initiatives, expand their digital resources, cultivate strategic collaborations, prioritize ethical responsibility and implement thorough evaluation and communication practices.

This paper aims to assess the overall social housing development, point out factors affecting it and propose some policy implications for social housing development.

The research investigated investors, credit institutions and officials involved in social housing development. Bac Ninh province currently has 51 social housing projects that have been and are being implemented. The hypothetical regression model has seven latent variables and is tested by the criteria through the SPSS25.0 software.

There are 29 factors belonging to seven groups affecting housing development. Their impact rates range from 3.47% to 30.25%.

The study has only identified the factors affecting social housing development but has not undertaken an in-depth assessment of its development status and forecast for the future. Therefore, this gap needs to be further studied. The proposed research method could also be applied when researching social housing developments in other countries around the world.

To develop social housing to meet the needs of the real estate market, it is necessary to improve the policies that have the strongest impact first. Then, it is necessary to improve the factors with a smaller impact.

The study proposes policy implications for faster housing development for low-income people that improve their living standards.

To the best of the authors’ knowledge, the paper has studied for the first time social housing development and the factors affecting it. The paper also shows the level of their impact so that priority policies can be applied to each factor.

The purpose of this paper is examining how financial inclusion can be enhanced in rural and remote areas in emerging economies through the adoption of Financial technologies. The study examines the direct influence of technological characteristics, facilitating conditions, trust and perceived risk on adoption of FinTech. Furthermore, the study examines the mediating effects of facilitating conditions and moderating effects of education level in adoption of FinTech.

The study employed quantitative research design. Stratified and simple random sampling were employed to identify areas in which respondents will be collected. Drop and Pick method was further employed to collect 275 valid and reliable responses. Structural equation modeling was used to analyze the data and assess the reliability and validity of the measurement model. Structural model analysis was employed to examine the hypothesized relationship.

The results show that compatibility, complexity agent trust, perceived risk and facilitating have significant influence on adoption of FinTech. Furthermore, the findings show that facilitating conditions mediate the relationship between all technological characteristics and FinTech adoption except the relationship between compatibility and FinTech. The study also has found that education level moderates the relationship between observability and FinTech adoption as well as trialability and FinTech adoption.

This study employed cross-sectional research-based techniques in collecting data for analyzing the hypothesized relationship. However, the drawback of cross-sectional may impact the findings of this study over a long time. Therefore, future studies must consider conducting longitudinal studies which may collect data over some time for analysis of the FinTech adoption. Furthermore, the generalization of these findings should be considered carefully by other countries which are not economically similar to Tanzania and developed countries. This also provides room for future studies to examine the same area in countries with different economic development.

This study contributes to knowledge into two folds: First there is limited knowledge on adoption of FinTech in emerging economies; the study addresses the knowledge gap by providing empirical findings which will help scholar. Furthermore, less studies have examined the moderating effects of facilitating condition in adoption of technology. This study addresses the knowledge gap by examining the moderating influence of moderating influence of facilitating conditions. Also, this study provides empirical findings which will help policymakers to implement strategy that will speed-up financial inclusion in rural and isolated areas in emerging economies.

Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

This study evaluates the moderating role of work-based social supports (i.e. supervisor support and co-worker support) in the relationship between job insecurity and job burnout among hospitality employees in Malaysia. Besides, the direct effect between job insecurity and job burnout is examined.

The cross-sectional data of this study were based on a total of 220 self-administered questionnaires that have been completed by hospitality employees from three different states in Malaysia. Respondents were recruited based on a snowball sampling approach. The data were collected during the COVID-19 pandemic, which was from October 2020 to January 2021.

Partial least square-structural equation modeling (PLS-SEM) was performed via SmartPLS software. The finding confirmed that job insecurity significantly intensifies employees' job burnout. Supervisor support and co-worker support were found to moderate the link between job insecurity and burnout. As anticipated, the relationship between job insecurity and job burnout increased when supervisor support is low. But high co-worker support was found to strengthen the impact of job insecurity on job burnout instead of the reverse.

This study supplements the existing literature by clarifying which sources of work-based social support (i.e. co-worker support or supervisor) is more salient in alleviating the adverse impact of job insecurity on job burnout during the COVID-19 pandemic among hospitality employees in Malaysia.

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

The development of green manufacturing has become essential to achieve sustainable development and modernize the nation’s manufacturing and production capacity without increasing nonrenewable resource consumption and pollution. This study investigates the effect of green industrial practices on technical efficiency for Thai manufacturers.

The study uses stochastic frontier analysis (SFA) to estimate the stochastic frontier production function (SFPF) and inefficiency effects model, as pioneered by Battese and Coelli (1995).

This study shows that, on average, Thai manufacturing firms have experienced declining returns-to-scale production and relatively low technical efficiency. However, it is estimated that Thai manufacturing firms with a green commitment obtained the highest technical efficiency, followed by those with green activity, green systems and green culture levels, compared to those without any commitment to green manufacturing practices. Finally, internationalization and skill development can significantly improve technical efficiency.

Green industry policy mixes will be vital for driving structural reforms toward a more environmentally friendly and sustainable economic system. Furthermore, circular economy processes can promote firms' production efficiency and resource use.

To the best of the authors' knowledge, this study is the first to investigate the effect of green industry practices on the technical efficiency of Thai manufacturing enterprises. This study also encompasses analyses of the roles of internationalization, innovation and skill development.

The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.

In this chapter, we explore the ethical dilemmas commonly faced in community development projects, providing guidance for practitioners and policy makers. We delve into various challenges, from resource allocation to managing diverse stakeholder needs, using ethical theories and real-world case studies, including examples from the Ecuadorian Amazon Rainforest, Haiti Earthquake relief, and an Indigenous education program in Australia. We emphasize the importance of ethical decision-making, showcasing the potential impacts of choices on communities and individuals. Practical strategies are presented to maintain ethical integrity, such as transparent communication and accountability mechanisms, enabling stakeholders to navigate dilemmas with sensitivity and uphold ethical standards. This chapter serves as a valuable guide for those involved in community development, fostering sustainable and equitable initiatives that empower communities and drive positive transformation.