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The International Labour Organization’s (ILO) sustainable compact is evident for many labor-intensive industries in emerging economies. This study aims to develop a sustainable human resource (HR) practice model for a labor-intensive industry from the evidence of the Bangladeshi ready-made garments (RMG) sector.

The study tests the factors identified from the literature for model validation. A total of 22 HR function items were used in a survey of 800 randomly selected respondents from the RMG sector in Bangladesh. The factor analysis (both exploratory and confirmatory) techniques were applied to explore and validate the model.

The study findings reveal that the factory management and policymakers should focus on sustainable HR practices for the betterment of a labor-intensive industry. In detail, the staffing function involves strategic HR planning, recruitment and selection and perfect employee placement; training and development functions entail proper organizational orientation, various training and development programs and employees’ career management and growth; the motivation function necessitates job design, fairness in the appraisal, practicing good organizational citizenship behavior with sound rewarding system and compensation packages; and finally, the maintenance function entails healthy and safe working environment, good communication and relationship management.

The study is original in developing a sustainable HR practice model with the alignment of ILO’s three inter-linked sustainability compact for a labor-intensive industry from an emerging economy perspective. The study’s outcomes will be a torchbearer for any labor-intensive industry’s sustainable HR practice from an emerging economy across the globe.

The study aimed to develop a disruptive production process innovation model from an emerging economy's agro-based dairy farming perspective based on the case of a Bangladeshi model dairy farm named Central Cattle Breeding and Dairy Farm (CBBDF), Savar, Dhaka.

The study used qualitative in-depth interviews, participants and document observation. Around 20 key informants were purposefully selected from the case organization.

The findings propose two different models for disruptive production process innovation toward sustainable agribusiness dairy farming from an emerging economy perspective and the modified process model from traditional dairy farms to modern dairy based on the stakeholders' (such as consumers, owners, managers and government) demand.

This study is the first attempt to develop a disruptive production process innovation and technology model for the dairy industry and its stakeholders' responsibilities from the experience of an emerging economy. The value of the research is in identifying factors under traditional dairy farming that need to be reduced and eliminated, and the factors under society, health concerns and value-added to existing farms need to be raised as per the global industry standard.

This study investigates the effectiveness of trade unions in preserving and promoting the rights of the worker, and being their voice in ensuring safe working conditions as part of the firms’ CSR activities.

Data were collected from employees, managers, and owners of ready-made garments firms in Bangladesh. An open-ended survey instrument was used and distributed widely. Analysis of the 200 responses was undertaken using the qualitative narrative technique.

The findings show that, unlike traditional labor-management relations, in Bangladesh managers tend to have a more favorable attitude towards unions than employees do. The strong political links between the factory owners and the unions’ leadership raise questions about whose interest the unions represent.

The authors highlight how adopting a CSR agenda can help unions make better representations on behalf of their members. This, in turn, can enhance the workforce’s efficiency and help strengthen the sector to develop processes to help face disruptions like those experienced during the COVID-19 pandemic.

The study is unique in addressing the role of unions in promoting CSR activities in emerging economies, where the formal institutional application remains limited. The study’s findings can help explain some of the sector’s challenges.

This study aims to identify the intention to purchase Halal food products amongst non-Muslim consumers in Malaysia, moderated by the acculturation effect.

A structured close-ended questionnaire was used to gather data through the random distribution of 397 non-Muslim consumers from the Alumni network of several private higher education institutions in Malaysia.

The collected data was analyzed through the structural equation modelling technique using partial least squares with SmartPLS 3.0. The result indicated that attitude, subjective norms and perceived behavioral control were positively influenced by the purchase decision of Halal food products amongst non-Muslim consumers in Malaysia. Apart from that, the acculturation effect moderates the relationship between attitude and intention to purchase.

This finding will contribute to academics, Halal food makers and government in understanding the Halal food purchase intention amongst non-Muslim consumers in Malaysia.

The outcome of this study can be used as an input for Halal entrepreneurship in terms of marketing and operation strategy. On the government aspect, this study also provides an implication on national public policy and strategic economic planning in developing overall national Halal policy.

The social harmonization amongst the multiple races in Malaysia is partially contributed through the acculturation effect. The acculturation effect has been reflected through the food choice decision amongst Malaysian, despite of different religious belief and home culture background.

Research in studying Halal food purchase intention amongst non-Muslim consumers are scarce. This research is able to reinforce the theory of planned behavior model in dealing with Halal food choice decisions, taking into consideration of acculturation effect.

The purpose of this paper is to provide an initial empirical insight into the mediating role of quality performance on the association between six specific organisational factors (top management support, employee involvement, employee empowerment, reward and recognition, training and customer focus) and competitive advantage.

A survey questionnaire was used to collect data from 179 garment organisations in a developing country, Bangladesh.

The results show that quality performance mediates the association between three specific organisational factors (top management support, employee involvement and reward and recognition) and competitive advantage. In addition, a fourth organisational factor, employee empowerment, exhibited a direct association with competitive advantage.

The findings provide managers of developing economies with an important insight into the critical role of quality in achieving competitive advantage. In line with the resources-based view, the findings suggest that managers should deploy their limited resources to focus on providing top management support for, encourage employee involvement in and provide adequate rewards and recognition in respect to quality initiatives.

The present paper aims to conduct a comprehensive scientific mapping of exchange rate forecasting, highlighting trends, developments, and methodological changes. This will provide research scholars, researchers, and policymakers valuable insights to facilitate predictions.

The researchers performed a bibliometric analysis of exchange rate forecasting using a scientific search method on the Scopus database from 1991 to 2022. They applied a web interface program called Biblioshiny, part of the Bibliometric package built in R by Aria and Cuccurullo (2017). VOSviewer was used to identify the most influential journals, authors, countries, articles, citations, and co-citations from 1,602 documents.

The conceptual and intellectual framework of the papers under review provided an in-depth and comprehensive analysis of the domain. The research outcomes provided essential information on the subject matter, highlighting the need for further investigation. The study’s findings demonstrate the evolution of the theory of forecasting exchange rates reflecting continuous developments in the methodologies applied to forecast the exchange rates.

The scientific mapping of the present study’s bibliometric analysis is limited to the Scopus database because of its comprehensive coverage of high-quality journals and predefined structures compatible with Bibliometrix software.

The study provides considerable insight into forecasting exchange rates and their interlinkages. By outlining the social and intellectual structure of the field, it directs upcoming scholars about the relevant topics, contexts and potential collaborations emerging in this field. The study also reveals the critical concerns in the area and leads to potential research opportunities.

The study sheds light on emerging trends and approaches to forecasting exchange rates and will provide valuable information and insights to policymakers, economists, investors and decision-makers in the financial sector. It will contribute to prioritising research in overlooked areas and support the formulation of effective policies.

This study contributes significantly by bringing together disparate literature on exchange rate forecasting, highlighting important journals, authors and documents, and examining the recent studies on the foreign exchange rate.

By combining the notion of prospect theory with advanced machine learning algorithms, this study aims to predict whether financial institutions (FIs) adopt a reactive stance when they perceive climate change as a risk, consequently leading to the adoption of environmental, social and governance (ESG) practices to avoid this risk. Prospect theory assumes that decision-makers react quickly when decisions are framed as a risk or threat rather than as an opportunity.

We used a sample of 168 FIs across 27 countries and seven regions over the period 2003–2020. To conduct our empirical investigation, we compared the prediction accuracy of various machine learning algorithms.

Our findings suggest that out of 12 machine learning algorithms, AdaBoost, Gradient Boosting and XGBoost have the most precision in predicting whether FIs react to climate change risk in adopting ESG practices. This study also tested the overall climate change risk and risks associated with physical, opportunity and regulatory shocks of climate change. We observed that risks associated with physical and regulatory shocks significantly impact the adoption of ESG practices, supporting prospect theory predictions.

The insights of this study provide important implications for policymakers. Specifically, policymakers must take into account the risk posed by climate change in the corporate decision-making process, as it directly influences a firm’s adoption of corporate actions (ESG practices).

To the best of our knowledge, this is the first study to investigate the firm-level climate change risk and adoption of ESG practices from a prospect theory perspective using novel machine learning algorithms.

The pandemic crisis has resulted in global chaos that had caused massive disruption to the supply chain. The pharmaceutical industry, in particular, has been working tirelessly to ensure that they can cater to the people who need them. With restrictions being imposed to prevent the spread of the COVID-19 virus, the movement of raw materials required has been affected, thus creating the need for the procurement function to be innovative. This study proposes the application of Industry 4.0 concepts into the procurement activities of an organization to make it more resilient and efficient.

To study the intensity of the challenges, Total Interpretive Structural Modelling is used alongside the “Matrice des Impacts Croises Multiplication Appliquee a un Classement” (MICMAC) technique.

Resilience can be achieved through the collaboration between the organization and its network of suppliers. This is however easier said than done. High and unclear investments have been identified as the challenge that is taking a toll on all technological investments in the pandemic era. The study also shows that organizational inertia which is present in established and structured firms are a deterrent as well.

This study is based on the application of procurement 4.0 to ensure that pharmaceutical supply chains stay least affected since they are essentials. This study using a multi-criteria decision-making approach to prioritize the challenges. This will help practitioners make decisions faster.