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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 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.