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This study aims to investigate the association between cognitive moral development (CMD) and unethical pro-organizational behaviour (UPB) by taking purchasing employees as research subjects. The moderating effect of perceived leader’s UPB is also explored.

Data were collected through a two-stage questionnaire survey on purchasing employees in companies across a spectrum of industries in Taiwan, and 492 purchasing employees were analysed in the study.

Research findings reveal that employees at the conventional level of CMD are more likely to conduct UPB than those at the pre-conventional and post-conventional levels. Perceived leader’s UPB will moderate the association between CMD and UPB. Employees’ UPB is strongly associated with their CMD when they perceive their leaders as being likely to perform UPB.

Although a variety of factors influencing UPB have been proposed in the literature, none of them have analysed the association between CMD and UPB. However, CMD is one important factor affecting ethical decision-making. The present study can promote further understanding of the role of CMD in UPB and contribute to a growing body of research on CMD and UPB.

This study aims to analyze the determinants influencing Chinese manufacturing companies in implementing lean manufacturing (LM).

The determinants to be explored in this study consist of technological, organizational and environmental (TOE) dimensions. A questionnaire survey was conducted on Chinese manufacturing companies, and 208 samples were analyzed.

The findings show that the relative advantage of LM and organizational support have significantly positive effects on Chinese manufacturing firms’ adoption of LM. The complexity of LM, quality of human resources, organizational readiness, customer pressure, international situation, governmental support and environmental uncertainty do not have significant effects.

This paper contributes to the literature by using the TOE model to explore the factors influencing LM adoption in the Chinese manufacturing industry.

The purpose of this study is to examine the factors that affect managers’ ethical decision-making in export-oriented readymade garments in Bangladesh.

This is an empirical study based on the quantitative approach undertaking a cross-sectional survey method where a convenience sampling technique was applied. The analysis was done using partial least square structural equation model applying Smart-PLS version 3.0.

This study confirmed that all the components of cognitive appraisal processes, including perceived severity, perceived vulnerability, response efficacy and self-efficacy, have a significant influence on attitude. Attitude, in turn, mediates the relationship between these variables and the behavioural intention of ethical practice, except for perceived vulnerability. Besides, moral obligation is found to mediate the relationship between attitude, self-efficacy and the behavioural intention of ethical decision-making. The study also found that ethical climate and subjective norms have a direct influence on behavioural intention. Furthermore, behavioural intention, ethical climate and self-efficacy are positively related to actual decision-making behaviour. However, this study did not find any direct effect of subjective norms on moral obligation.

The organization should include an emphasis on building ethical culture and setting an ethical code of conduct within the organization to sustain ethical practice within employees. However, the practitioner should work on enhancing self-efficacy to curb unethical practices by individuals.

This research contributes to the management of garments manufacturers by a practical and theoretical understanding of what influences the ethical behavioural decision-making process. Valuable guidelines are provided on the ethical decision-making process in the garments manufacturing companies for future researchers.

Well-being is an important dimension of human life but plays a controversial role in organizations, especially in different working environments. This study aims to explore the role of well-being in work from home (WFH) context, and its consequence on job outcomes among accountants in a fast-developing country, Vietnam.

A quantitative study is conducted with the data from Vietnamese accountants who had to work from home during the pandemic time. Partial least squares structural equation modeling method is applied to analyze the data.

The results show a direct and significant relationship of WFH with the employees’ well-being and job satisfaction (JS). Well-being fully mediates the influence of home-based work and JS on job performance.

This study generates valuable knowledge and practical implication in organizational policies and initiatives that aim to enhance employees’ well-being and promote positive job outcomes in the context of remote work. Organization employers should take their employees’ well-being as a key factor and consider it in personnel policy to enhance their work performance.

While many companies begin to promote ethically produced products, much remains to be known about consumers' buying intention toward these products. This paper attempts to integrate the theory of planned behavior and the Hunt–Vitell theory of marketing ethics to explore the buying intention toward ethically produced food products in a developing economy.

Data were collected through a questionnaire survey in Bangladesh. Structural equation modeling technique was used to test the research model.

Research findings showed that deontological evaluation and teleological evaluation have significantly positive effects on perceived behavioral control and subjective norm. Perceived behavioral control, subjective norm, attitude, hedonic and utilitarian value have significantly positive effects on buying intention toward ethically produced foods.

The results are practically and theoretically meaningful because the integrated model holds well explanatory power to predict consumers' intention toward buying ethical foods and thereby understand consumers' ethical decision-makings.

The purpose of this paper is to study the factors influencing the adoption of RFID technology and the relation between RFID technology adoption and supply chain performance for logistics companies.

Determinants of RFID technology adoption are analyzed from the technological, organizational and environmental perspectives. Supply chain performance measurements consist of financial and non‐financial indices. Data were collected by means of delivering questionnaires to logistics service providers in China. A total of 574 logistics companies were analyzed.

Logistics companies' willingness to adopt RFID technology are significantly influenced by the explicitness and accumulation of technology, organizational encouragement for innovation, quality of human resources, and governmental support. There is a positive association between the willingness to adopt RFID technology and supply chain performance for logistics service providers.

As a single‐country and single‐industry study, the current research may be limited in its generalizability.

The growth of China's economy hinges to a large extent on the ability of the logistics industry to operate efficiently and effectively in the global supply chain system. China's logistics service providers need to adopt more efficient logistics technologies to provide better supply chain services for their customers. This paper provides some suggestions for governmental officials, logistics companies, and RFID technology providers in advancing the application of RFID in supply chains.

This paper may be the first empirical research in analyzing the adoption of RFID technology and its association with supply chain performance in the logistics industry, especially for China's logistics industry.

The emerging markets have been witnessing a remarkable revival of rotating savings and credit associations (ROSCAs) serving as alternative informal financing and investment platforms, also known as savings-based finance (SBF) in Turkey. The purpose of this study is to present the SBF model mathematically, analyse the performance of the SBF sector and propose a new Sharīʿah-compliant SBF model for the acquisition of durables.

The paper thoroughly reviews the concept and practice of ROSCA across the globe, mathematically models and empirically analyses the performance of Turkish SBF companies using a unique data set.

The study formulates a two-person SBF model and proposes a Mudarabah-Wakalah hybrid model with a new investment feature. It is found that the concept of ROSCA is being operationalized in 105 countries across the globe under different names with slight business model modifications. The research also reveals that the demand for financing of durables in Turkey significantly increased in recent years with the demand for housing is twice greater compared to vehicles. Most importantly, a strong significant inter- and intra-comovement is observed between these durables implying that the success of the sector in one segment has attracted the customers to other SBF products. It shows that the SBF institutions can effectively serve as the alternative financing houses for pooling savings and financing the durables, and they have strong potential to capture a larger financial market share in Turkey and even globally.

The study constructs mathematical models and proposes a new investment wing to an existing SBF wealth fund.

This study aims to investigate the evolvement of the concept and practice of the Rotating Savings and Credit Association (ROSCA) from informal fund collection for indivisible durables to real property acquisition under the interest-free SBF model by analyzing the previously conducted research that focused on the concept in terms of names, forms, and natures.

A PRISMA-compliant systematic literature review is adopted to ascertain the most relevant studies from various sources and analyze the extracted data or items to accomplish the research objective. Besides, bibliometric network, thematic, and statistical analysis are also applied to bolster the findings acquired from the systematic review. Furthermore, this study mathematically formulates and introduces the customized PRISMA systematic flowchart.

The results reveal that the concept of ROSCA has evolved over the years from informal to formal, micro to macro, individual to institutional, social to business, and fund collection for purchasing household items to real property acquisition since 1962. In this process, the focus area of the research has been shifted from characteristics, operation, and economics to law; source of funds, and history to social; benefits and contribution to digital, risk, and savings behaviour. It is noticed that the majority of the study are Africa-centric, followed by Asia; academic discussion on the ROSCA covers most of the social and economic arena, except the real property acquisition aspect. However, the SBF concept fills up this gap by introducing a real-property-acquisition-centric ROSCA model. The authors provide future agendas regarding focus areas that researchers may consider to develop the SBF concept.

The study focuses on the evolvement of a savings-based model. No study concentrates on the evolution process of the model from ROSCA to SBF; in fact, no conspicuous academic study is found regarding the systematic review of ROSCA in the literature archive.

The purpose of this study is to propose the time series decomposition approach to analyze and predict the failure data of the repairable systems.

This study employs NHPP to model the failure data. Initially, Nelson's graph method is employed to estimate the mean number of repairs and the MCRF value for the repairable system. Second, the time series decomposition approach is employed to predict the mean number of repairs and MCRF values.

The proposed method can analyze and predict the reliability for repairable systems. It can analyze the combined effect of trend‐cycle components and the seasonal component of the failure data.

This study only adopts simulated data to verify the proposed method. Future research may use other real products' failure data to verify the proposed method. The proposed method is superior to ARIMA and neural network model prediction techniques in the reliability of repairable systems.

Results in this study can provide a valuable reference for engineers when constructing quality feedback systems for assessing current quality conditions, providing logistical support, correcting product design, facilitating optimal component‐replacement and maintenance strategies, and ensuring that products meet quality requirements.

The time series decomposition approach was used to model and analyze software aging and software failure in 2007. However, the time series decomposition approach was rarely used for modeling and analyzing the failure data for repairable systems. This study proposes the time series decomposition approach to analyze and predict the failure data of the repairable systems and the proposed method is better than the ARIMA model and neural networks in predictive accuracy.

Analyzing and forecasting reliability is increasingly important for enterprises. An accurate product reliability forecasting model cannot only learn and track a product's reliability and operational performance, but can also offer useful information that allows managers to take follow‐up actions to improve the product's quality and cost. The Generalized Autoregressive Conditional Heteroskedastic (GARCH) model is already extensively used to analyze and forecast time series data. However, the GARCH model has not been used to analyze and forecast the failure data of repairable systems. Based on these concerns, this study proposes the GARCH model to analyze and forecast the field failure data of repairable systems.

This paper proposes the GARCH model to analyze and forecast the field failure data of repairable systems. Empirical results from electronic systems designed and manufactured by suppliers of the Chrysler Corporation are presented and discussed.

The proposed method can analyze and forecast failure data for repairable systems. Not only can this method analyze failure data volatility, it can also forecast the future failure data of repairable systems.

Advanced progress in the field of reliability prediction estimation can benefit engineers or management authorities by providing important decision support tools in which the prediction accuracy suggests financial and business outcomes as well as other outcome application results.