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In the scope of the immense growth of corporate frauds and scandals, reporting unethical practices could be considered as an important mechanism to control them and ultimately improve organizational quality. To this end, this study proposes the conceptual framework comprising the enablers impacting employees' tendencies and behaviors to reporting misdemeanor in the workplace.

Systematic review of literature has been carried out. To understand the complexities among various enablers and to analyze their driving power and contingencies, a modified total interpretive structural modeling (TISM) approach has been adopted.

The findings indicate that enablers such as moral identity (MI) and job satisfaction (JS) having higher driving power (come at the bottom of the hierarchy) are relatively more important. Furthermore, perceived personal cost (PC), moral courage (MC), self-efficacy (SE) and anger have high dependent power of factors. Finally, the paper provides two paths that can lead to whistleblower's ethical decision.

A conceptual framework delivered in this paper requires to test against the field data. However, the conceptual understanding of driving enablers paves the way to top management in recruiting and hiring people in the workplace.

This study represents the first attempt to apply TISM for whistleblowing phenomenon. It provides a comprehensive conceptual framework in order to address the relative importance of various individual enablers in developing reporting tendencies against misdemeanors.

The manufacturing industry is one of the most disrupted systems as a result of the global spread of the Covid-19 pandemic. Manufacturing firms are looking for strategies and policies to deal with the situation while also meeting customer demands. This study aims to discuss and analyze the barriers that have impacted manufacturing systems during this period.

The barriers and performance measures were extracted from the extant literature and further discussed with academic and industry experts. Based on the response of experts, a list of ten barriers and five performance measures were selected for further analysis. The interpretive ranking process (IRP) is applied to analyze the inter-relationship among the barriers with respect to performance variables. The cross-interaction matrices and the dominance profile are created to prioritize the barriers. Based on dominance value, an IRP-based manufacturing barrier evaluation model is developed for validation.

The impact of the pandemic on the manufacturing industry is analyzed through the list of barriers and a structured ranking model is proposed. The research findings of the study indicate that “Financial constraints” is the most influential barrier to manufacturing due to the outbreak of Covid-19, followed by “Government imposed restrictions” and “Setbacks in logistics services.”

The ranking of barriers and developed interpretive ranking process model would be helpful for practitioners and policymakers to formulate strategies for manufacturing organizations to deal with the pandemic situation. The finding can be beneficial as it promotes similar studies in other sectors.

This study contributes to the manufacturing sector by developing a contextual relationship among the set of identified barriers against various performance measures. As per the author's knowledge, this is the first study that provides a relationship and ranking of manufacturing barriers due to the outbreak of Covid-19.

Since Industry 4.0 (I4.0) is a new idea in Bangladesh, this study supports I4.0 adoption. Companies struggle to implement I4.0 and fully profit from the fourth industrial revolution’s digital transformation due to its novelty. Although barriers to I4.0 adoption are thoroughly studied, the literature has hardly examined the many aspects that are crucial for I4.0 adoption in Bangladesh’s Ready-Made Garment (RMG) industry. So, the purpose of this study is to investigate the barriers of adopting I4.0 in relation to Bangladesh’s RMG industries to enhance the adoption of I4.0 by developing a framework. Ultimately, the goal of this research is to improve the adoption of I4.0 in Bangladesh.

Through a comprehensive analysis of the existing research, this paper aims to reveal the barriers that must be overcome for I4.0 to be adopted. For evaluating those barriers, a decision analysis framework based on the combination of Delphi technique and Decision-Making Trial and Evaluation Laboratory (DEMATEL) method has been developed. The use of DEMATEL has led to a ranking model of those barriers and a map of how the barriers are connected to each other.

The findings reveal that “I4.0 training”, “Lack of Motivation” and “Resistance to Change” are the most significant barriers for adopting Industry 4.0 in RMG sector of Bangladesh based on their prominence scores.

These findings will help the people who make decisions in the RMG industry of Bangladesh, such as company owners, managers and the executive body, come up with a plan for putting I4.0 practices into place successfully. The decision-making framework developed in this research can be utilized by the RMG industry of Bangladesh and other similar industries in developing countries to figure out how important each barrier is for them and how to get rid of them in order of importance.

As far as the authors are aware, there has not been a comprehensive study of the barriers inhibiting the adoption of I4.0 within the scope of Bangladeshi RMG industry. This work is the first to uncover these barriers and analyze them using the combination of Delphi technique and DEMATEL.

In the recent dynamic market, supply chain disruptions are rapidly increasing with varied customer demand, technological changes, uncertain pandemic events etc. To overcome the unexpected disruptions, supply chain of each business should be resilient and pharmaceutical supply chain (PSC) is no exception. Motivated by the challenges and unexpected pandemic disruptions, this paper aims to examine the performance indicators (PIs) of the resilient PSC and to predict the resilience level for a certain time period in the context of Bangladesh.

The aim of this paper presents a structured framework based on the Delphi method, fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and system dynamics (SD). The proposed methodology was validated using expert's inputs from the relevant field in Bangladesh. This study reveals the influential relationships of indicators and resilience level using fuzzy DEMATEL and SD to improve the resiliency.

Findings revealed that “Supply chain risk orientation”, “Visibility”, “Flexibility”, “Agility in supply chain” and “Collaboration” are the top five influential performance indicators for resilient PSC. The cause and effect relationship found that “IT capability”, “Flexibility”, “Supply chain network design”, “Resource availability”, “Supply chain risk orientation” and “Velocity” were in cause category which play a vital role for establishing resilient supply chain. SD approach has developed a model for predicting the resilience level of the supply chain.

This work is one of the initial contributions in the literature that has targeted on the identification and analysis of the significant PIs and predicting the resilience level of the PSC.