Behavioural intention to adopt blockchain for a transparent and effective taxing system

Towards measuring SMEs performance amid the COVID-19 outbreak: exploring the impact of integrated supply chain drivers

Purpose

This study aims to explore supply chain disruptions during the COVID-19 pandemic in the small and medium enterprise (SME) sector in Oman. This study analyzes the impact on selected supply chain drivers – facilities, inventory, transportation and sourcing. It further intends to explore whether the supply chain challenges faced by the SME sector in Oman impact their overall performance.

Design/methodology/approach

This study follows the quantitative technique of structural equation modeling to examine the proposed hypotheses. Data were collected electronically from SME managers/owners/entrepreneurs. All items were adopted and measured using a five-point Likert scale. One hundred and four complete and usable responses were received and considered.

Findings

The data was analyzed using SPSS and PLS statistical software. The model has been supported empirically, and the results showed a significant relationship between supply chain drivers and SMEs’ overall performance in Oman, except for supply chain inventory. The results have demonstrated that the COVID-19 pandemic has affected the SMEs’ supply chain drivers in Oman and, consequently, their overall performance.

Practical implications

The results of this research can drive the development and implementation of a supply chain management strategy. This research will help policymakers induce the performance of SMEs affected by the COVID-19 pandemic. It would further enhance strategic sourcing and supplier performance considering the developed practices associated with the resource-based view.

Originality/value

The originality of the current study lies in its ability to empirically test two models within the Omani SMEs context while considering the supply chain drivers as a single variable or dividing it into four separate independent variables. This study would provide a preview for scholars for such empirical investigation and serve as a reference for policymakers and practitioners to maintain a management system of crises that may protect the SME supply chain drivers.

Classifications of Sustainable Factors in Blockchain Adoption: A Literature Review and Bibliometric Analysis

Blockchain is a cutting-edge technology that is transforming and reshaping many industries. Hence, the adoption of Blockchain is becoming an increasingly significant topic. The number of publications discussing the potential of Blockchain adoption has been expanding significantly. In addition, not enough attention has been given to Blockchain adoption in the software development industry. As a result, a systematic overview to investigate the research trends in this area is needed. This study uses a Scientometric analysis and critical review to examine the evolution of Blockchain adoption research on the Web of Science Principal Collection. In addition, a systematic literature review (SLR) was conducted to identify gaps in Blockchain adoption research and the top reasons for adopting Blockchain with the intention of proposing a sustainable adoption framework. This study extends the body of knowledge by discussing the most influential countries, authors, organizations, publication themes, and most cited publications on Blockchain adoption research. Additionally, this study identifies the 30 relevant studies from the Web of Science and Scopus, including their industries, countries, methods, and respondent sample size, and the top 18 adoption factors among them. Consequently, this study proposes a suitable Blockchain adoption framework based on these top 18 factors. Finally, this study’s aim and unique contribution is to serve as an initial launching point for upcoming Blockchain adoption in software development industry research.

Blockchain technology adoption in government organizations: a systematic literature review

Purpose

Blockchain technology is spreading its roots and growing rapidly. With the advancement of blockchain technology, government organizations are focusing toward adopting blockchain technology. The purpose of this study is to identify the factors that affect the adoption of blockchain technology and provide a conceptual framework to adopt blockchain technology in government organizations.

Design/methodology/approach

To answer the research questions, this study has used systematic literature review (SLR). For achieving the quality and transparent process, this study has applied the PRISMA framework in the SLR.

Findings

With the help of SLR, this study has identified 72 factors that influence the adoption of blockchain technology. After critically examining the factors, this study has developed the conceptual framework for the adoption of blockchain technology in government organizations with four factors of the unified theory of acceptance and use of technology model and four additional factors, i.e. facilitating conditions, social influence, effort expectancy, performance expectancy, trust, transparency, cost and security.

Research limitations/implications

To perform SLR, this study has used two databases: Web of Science and Google Scholar; future studies can consider other databases. This study has provided the framework but not validated it; future studies can use structural equation modeling and artificial neural network to validate the framework.

Practical implications

This study helps to provide insights about blockchain technology and help government and policymakers to take decisions for the adoption of blockchain technology and in determining the future action plan.

Originality/value

Few studies are available in the literature that have used SLR to identify blockchain technology adoption in government organizations.

Drivers of digital transformation adoption: A weight and meta-analysis

The advent of the global pandemic has accelerated the growing need for product and service transformation, highlighting the emerging importance of technology and creating the opportunity to update the digital transformation (DT) domain through empirical-quantitative research. This weight and meta-analysis enabled the synthesis and integration of previous literature on the scope of individual DT adoption, evaluating the state of the art and filling a void on the subject. Athwart 88 studies and 99 datasets by international sources, our results demonstrate that attitude and satisfaction are relevant predictors of behavioral intentions and promising outcomes, including compatibility and personal innovativeness. Behavioral intentions, satisfaction, and habit are the best predictors for DT use. Usefulness and ease of use are critical for DT adoption intention and use, being moderated by individualism, as a cultural factor, human capital, and knowledge-technology, as innovation indicators. We present a conceptual model of promising and best predictors for future research on DT individual adoption.

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An update of digital transformation (DT) through a weight and meta-analysis.

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Contribution to DT literature by surpassing biases and limitations of size estimates.

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Identification of promising and best predictors for further DT adoption research.

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Behavioral intentions, satisfaction, and habit are best predictors for DT use.

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Usefulness and ease of use are pivotal, being moderated by culture and innovation.