Blockchain adoption: A study of cognitive factors underpinning decision making

E-commerce operations and technology perceptions in promoting farmers' adoption of green production technologies: Evidence from rural China

Agricultural green production is vital for ensuring product quality, safety, and mitigating environmental issues. E-commerce operations have emerged as a key driver of green production transformation. Based on a sample of 704 farm households in Jiangsu Province, this study employs a two-way fixed-effects model, Propensity Score Matching (PSM), Instrumental Variable Probit (IVProbit), and Extended Regression Model (ERM) to address endogeneity, alongside stepwise regression to test the mediating role of technology cognition. The results show that e-commerce operations significantly and positively influence the adoption of green production technologies among farmers, with technology cognition acting as a positive mediator. The impact of e-commerce on technology adoption varied across different age groups and geographical terrains, with older farmers and those in plain regions benefiting the most. Additionally, e-commerce played a crucial role in the adoption of green technologies, particularly in the use of organic fertilizers. To promote the broader adoption of green technologies among farmers, it is recommended that governments strengthen e-commerce support systems, enhance technical training for farmers, improve the inclusivity of e-commerce platforms, and address gaps in the availability of green production technologies.

Barriers to blockchain adoption in the seaport industry: A fuzzy DEMATEL analysis

Blockchain technology, marked as a disruptive force across various sectors, including seaport logistics, faces challenges and obstacles that impede its effective adoption. We aim to empirically identify the significant barriers impeding blockchain adoption in the seaport industry and elucidate the interconnected relationships between these impediments. Utilizing the Fuzzy Decision-Making Trial and Evaluation Laboratory Analysis (Fuzzy DEMATEL) technique, we quantify the cause-and-effect relationships between various barriers to blockchain adoption. Structured interviews involving 18 experts were conducted, collecting both qualitative interview data and quantitative data. The nature of ports and the maritime industry did not seem to be accurately reflected in the literature about blockchain adoption, presenting several new findings in this study. Four primary obstacles were identified: 1) Lack of management support and commitment. 2) Issues in supply chain collaboration, communication and coordination. 3) Resistance from and lack of involvement of external stakeholders. 4) The high cost. Furthermore, cost was reaffirmed as a significant factor influencing blockchain adoption. We enhance existing literature by revealing the interdependencies among identified barriers and offers insights for policymakers and industry practitioners. We aim to foster successful blockchain integration in the seaport industry, improving its sustainability performance. During this research, it has been acknowledged by the business sector that the effective employment of business process re-engineering (BPR) and the strategic implementation of blockchain technology are crucial strategies to surmount the obstacles that have impeded the extensive integration of blockchain within port operations.

The acceleration of blockchain technology adoption in Taiwan

This study explores the factors influencing the intention to adopt blockchain technology and the alignment between respondents' work characteristics and blockchain technology. It addresses the lack of attention from previous literature on these factors in the context of blockchain adoption, especially amidst the recent blockchain hype. By integrating Task-Technology Fit (TTF) and a modified version of the Unified Theory of Acceptance and Use of Technology (UTAUT), this study employs a questionnaire survey. The results demonstrate that the alignment between blockchain and work characteristics significantly impacts performance expectations and the recognition of opportunities, thereby influencing the intention to adopt blockchain. Furthermore, factors such as effort expectancy, social influence, facilitating conditions, and perceived policy uncertainty influence adoption intention by identifying opportunities. Exposure to blockchain-related knowledge reinforces the relationships mentioned above. Additionally, digital natives display greater confidence in blockchain's potential to enhance work performance than digital immigrants. These study findings offer valuable insights and strategies for blockchain technology providers and provide a comprehensive survey for individuals and professionals interested in embracing or understanding the dynamics of blockchain adoption.

Adoption of Blockchain Technology: Exploring the Factors Affecting Organizational Decision

Blockchain (BCT) is an emerging technology that promises many benefits for organizations, for instance, disintermediation, data security, data transparency, a single version of the truth, and trust among trading partners. Despite its multiple benefits, the adoption rate of BCT among organizations has not reached a significantly high level worldwide, thus requiring further research in this space. The present study addresses this issue in the Australian context. There is a knowledge gap in what specific factors, among the plethora of factors reported in the extant literature, affect the organizational adoption of BCT in Australia. To fill this gap, the study uses the qualitative interpretative research approach along with the technology-organization-environment (TOE) framework as a theoretical lens. The data was mainly drawn from the literature review and semi-structured interviews of the decision-makers and senior IT people from the BCT adopter and potential adopter organizations in Australia. According to the findings, perceived information transparency, perceived risks, organization innovativeness, organization learning capability, standards uncertainty, and competition intensity influence organizational adoption of BCT in Australia. These factors are exclusively identified in this study. The study also validates the influence of perceived benefits and perceived compatibility on BCT adoption that are reported in the past studies. Practically, these findings are helpful for the Australian government and public and private organizations to develop better policies and make informed decisions for the organizational adoption of BCT. The findings would guide decision-makers to think about the adoption of BCT strategically. The study also has theoretical implications explained in the discussion section.

A Novel Credible Carbon Footprint Traceability System for Low Carbon Economy Using Blockchain Technology

To achieve the goal of carbon neutrality, many countries have established regional carbon emission trading markets and tried to build a low-carbon economic system. At present, the implementation of carbon emission trading and low-carbon economic systems faces many challenges such as manipulation, corruption, opacity, lack of trust, and lack of data tracking means. The application of blockchain technology can perfectly solve the above problems. However, the data recorded on a blockchain are often multi-type and heterogeneous, and users at different levels such as regulators, enterprises, and consumers have different requirements for data types and granularity. This requires a quick and trustworthy method for monitoring the carbon footprint of enterprises and products. In this paper, the carbon footprint traceability of enterprises and products is taken as an application scenario, and the distributed traceability concept of "traceability off the chain and verification on the chain" is adopted. By reconstructing the pointer of the file structure of the distributed storage, an interactive traceability structure supporting type filtering is constructed, which enables fast retrieval and locating of carbon emission data in the mixed data on the chain. The experimental results show that using the interactive traceability structure that supports type filtering for traceability not only releases the computing power of full nodes but also greatly improves the traceability efficiency of the long-span transaction chain. The proposed carbon footprint traceability system can rapidly trace and track data on an enterprise's and a product's carbon footprint, as well as meet the needs of users at all levels for traceability. It also offers more advantages when handling large amounts of data requests.