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In light of Bangladesh’s economy, the goal of this study is to examine the “Twin Deficit Hypothesis (TDH),” which refers to a link between the budget deficit and the current account deficit. This study used yearly time series data from 1980 to 2020 to investigate the phenomena.

A multivariate autoregressive distributive lag (ARDL) model has been presented for empirical investigation, with the ARDL bound test investigating the co-integration between the inadequacies. As some of the variables in the bound test lack co-integration, the study adds a multivariate vector autoregressive (VAR) model later on.

With evidence of the result, the study supports the validation of twin deficit hypothesis in Bangladesh economy since both current account deficit and fiscal deficit affects each other significantly whereas Granger causality test confirms that fiscal deficit causes current account deficit but not the other way around.

The government should maintain a restrictive monetary policy in order to stabilize the current account deficit.

The novelty of this study is the incorporation of inflation, real exchange rate and GDP per capital to TDH that together form the basis for a macroeconomic snapshot of the economy.

This paper aims to investigate the impact of selected macro-economic variables like real effective exchange rate (REER), GDP, inflation (INF), the volume of trade (TR) and money supply (M2) on-budget deficit (BD) in Bangladesh over the period of 1980–2018.

By using secondary data, the paper uses the Vector Error Correction Model (VECM) and Granger Causality test. Johansen’s cointegration test is used to examine the long-run relationship among the variables under study.

Johansen’s cointegration test result shows that there exists a positive long-run relationship of selected macroeconomic variables (real effective exchange rate, inflation, the volume of trade and money supply) with the budget deficit, whereas GDP has a negative one. The short-run results from the VECM show that GDP, inflation and money supply have a negative relationship with the budget deficit. The Granger Causality test results reveal unidirectional causal relationships running from BD to REER; TR to BD; M2 to BD; GDP to REER; M2 to REER; INF to GDP; GDP to TR; M2 to GDP and bidirectional causal relationship between GDP and BD; TR and REER; M2 and TR.

Bangladesh has been experiencing a budget deficit since 1972 due to a decline in sources of revenue. This study contributes to the empirical debate on the causal nexus between macroeconomic variables and budget deficits by employing VECM and Granger Causality approaches.

This paper aims to explore the underlying intention behind using blockchain technology (BLCT) in the agri-food supply chain (AFSC). This is achieved by using a conceptual framework based on technology acceptance models that considers various factors influencing user behavior toward implementing this technology in their practices.

The conceptual framework developed is empirically validated using structural equation modeling (SEM). A total of 258 respondents from agri-food domain in India were involved in this survey, and their responses were analyzed through SEM to validate our conceptual framework.

The findings state that food safety and security, traceability, transparency and cost highly influence the intention to use BLCT. Decision-makers of the AFSCs are more inclined to embrace BLCT if they perceive the usefulness of the technology as valuable and believe it will enhance their productivity.

This study contributes to the existing literature by providing thorough examination of the variables that influence the intention to adopt BLCT within the AFSC. The insights aim to benefit industry decision-makers, supply chain practitioners and policymakers in their decision-making processes regarding BLCT adoption in the AFSC.

This study investigates how decision-makers’ perceptions of BLCT influence their intention to use it in AFSCs, as well as the impact of the different underlying factors deemed valuable in the adoption process of this technology.

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.

A digital supply chain (DSC) positively enhances circular economy (CE) practices. However, what factors and conditions lead to the implementation of DSC for transitioning toward CE is not yet clear. Therefore, this study aims at identifying and subsequently analyzing the antecedents of DSC for CE.

The study identifies major antecedents of DSC for CE to achieve sustainability objectives through literature review and expert opinions. In this study, 19 potential antecedents of DSCs for CE are established from the literature and suggestions from industry professionals. A trapezoidal fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is applied quantitatively to investigate the antecedents identified.

Conducted in the context of Indian automobile manufacturing industry, the findings of the study reflect that advanced information sharing arrangement, effective government policies for DSC and CE implementation and digitalizing the supply chains are the top three potential antecedents of DSC for a CE.

In the existing literature, few studies are specific to investigating the DSC and CE paradigm. The present study will help organizations develop a practical and integrated strategic approach that will foster DSC through improved knowledge of CE.

The recent coronavirus disease 2019 (COVID-19) pandemic poses numerous challenges to supply chains. This pandemic is quite unique when compared to previous epidemic disruptions and has had a severe impact on supply chains. As a result, the operational challenges (OCs) caused by COVID-19 are still unknown among practitioners and academics. It is critical to comprehensively document current OCs so that firms can plan and implement strategies to overcome them. Consequently, this study systematically identifies and ranks COVID-19-related OCs.

This study uses an integrated methodology combining expert interviews and the best-worst method (BWM) to analyze the results. The data have been collected from the electronics industry of Bangladesh, an emerging economy. This study also conducts a sensitivity analysis to check the robustness of the results.

The results reveal 23 COVID-19-related OCs under five categories: sourcing, production and inventory management, demand management and distribution, return management and after-sales service, and supply chain-wide challenges. The quantitative investigation reveals that overstock in finished goods inventory, low end-customer demands, order cancellations from dealers and retailers, high inventory holding costs and lack of transportation are the top five OCs.

The findings will help practitioners to understand the OCs and allow them to prepare for future major disruptions and formulate long-term strategies for operations during and after the COVID-19 pandemic.

This study contributes to the literature on supply chain complexity and challenges by considering a major pandemic outbreak. Moreover, the study also contributes to the knowledge on emerging economies, which have been largely neglected in the current literature.

The recent pandemic caused by coronavirus disease 2019 (COVID-19) has significantly impacted the operational performances of pharmaceutical supply chains (SCs), especially in emerging economies that are critically vulnerable due to their inadequate resources. Finding the possible barriers that continue to impede the sustainable performance of SCs in the post-COVID-19 era has become essential. This study aims to investigate and analyze the barriers to achieving sustainability in the pharmaceutical SC of an emerging economy in a bid to help decision-makers recognize the most influential barriers.

To achieve the goals, two decision-making tools are integrated to analyze the most critical barriers: interpretive structural modeling (ISM) and the matrix of cross-impact multiplications applied to classification (MICMAC). In contrast to other multi-criteria decision-making (MCDM) approaches, ISM develops a hierarchical decision tool for decision-makers and cluster analysis of the barriers using the MICMAC method based on their driving and dependency powers.

The findings reveal that the major barriers are in a four-level hierarchical relationship where “Insufficient SC strategic plans to ensure agility during crisis” acts as the most critical barrier, followed by “Poor information structure among SC contributors,” and “Inadequate risk management policy under pandemic.” Finally, the MICMAC analysis validates the findings from the ISM approach.

This study provides meaningful insights into barriers to achieving sustainability in pharmaceutical SCs in the post-COVID-19 era. The study can help pharmaceutical SC practitioners to better understand what can go wrong in post-COVID-19, and develop actionable strategies to ensure sustainability and resilience in practitioners' SCs.

The purpose of this study is to present a systematic review of the online service failure (OSF) literature and conduct an exhaustive analysis of academic research on this emerging research area.

The current study has adopted a structured systematic literature review approach to synthesize and assess the OSF literature. Further, the study uses the Theory-Context-Characteristics-Methodology (TCCM) framework to propose future research directions in the OSF domain.

This systematic review shows that OSF research is still developing and remains mainly incoherent. Further, the study develops a conceptual framework integrating the frequently reported antecedents, mediators, moderator and consequences in the extant literature. This review also synthesizes the theoretical perspectives adopted for this domain.

The study followed specific inclusion and exclusion criteria to shortlist articles. Further, articles published only in the English language were considered. Hence, the findings of this review cannot be generalized to all OSF literature.

This systematic review has classified antecedents into customers' and service providers' roles which will enable online service providers to understand all sets of factors driving OSF. It also synthesizes and presents service recovery strategies and emphasizes the role of online customer support to fix OSF.

The OSF literature is still developing and remains highly incoherent, suggesting that a synthesized review is needed. This study has systematically reviewed and synthesized the OSF literature to study its development over time and proposes a framework which provides a comprehensive understanding of OSF.