Big data is expected to drive the new digital transformation of society, government, and business. The proportion of firms implementing and utilizing big data, however, is not high. There are many challenges and obstacles related to firm adoption of big data. The purpose of this study is to identify the factors influencing the adoption of big data among Korean firms using the technology-organization-environment (TOE) framework. The results of the analytic hierarchy process (AHP) and regression analysis from data collected from 50 experts and 226 companies, respectively, are as follows: the benefits from big data, technological capabilities, financial investment competence, and data quality and integration are perceived by the experts and the firms as the strongest determinants of adoption. Management support for big data, security and privacy, and government support and policy are also influential factors of firm big data adoption.

This paper provides a comprehensive analysis of recent advancements in additive manufacturing, a transformative approach to industrial production that allows for the layer-by-layer construction of complex parts directly from digital models. Focusing specifically on Directed Energy Deposition, it begins by clarifying the fundamental principles of metal additive manufacturing as defined by International Organization of Standardization and American Society for Testing and Materials standards, with an emphasis on laser- and powder-based methods that are pivotal to Directed Energy Deposition. It explores the critical process mechanisms that can lead to defect formation in the manufactured parts, offering in-depth insights into the factors that influence these outcomes. Additionally, the unique mechanisms of defect formation inherent to Directed Energy Deposition are examined in detail. The review also covers the current landscape of process evaluation and non-destructive testing methods essential for quality assurance, including both traditional and contemporary in situ monitoring techniques, with a particular focus given to advanced machine-vision-based methods for geometric analysis. Furthermore, the integration of process monitoring, multiphysics simulation models, and data analytics is discussed, charting a forward-looking roadmap for the development of Digital Twins in Laser–Powder-based Directed Energy Deposition. Finally, this review highlights critical research gaps and proposes directions for future research to enhance the accuracy and efficiency of Directed Energy Deposition systems.

Digital technologies play a vital role in daily human life and significantly influence human attitudes toward the adoption of new and attractive lifestyles. The internet has been widely accepted in every modern society, and the act of purchasing products or services over the internet, known as online/internet shopping, has revolutionized business. This study was designed using the technology acceptance model and theory of reasoned action. This study identified important factors such as perceived awareness of security, perceived usefulness, personal innovativeness, and perceived ease of use in purchasing, together with the effects of these factors on online purchasing intentions and the mediating role of consumer attitudes toward online purchasing. The results show that the identified factors are positively and significantly related to consumer intentions and attitudes toward online purchasing. This study has the potential to guide online retailers and managers in expanding online purchasing platforms and in increasing their responsiveness to the need to restructure business models according to new technological developments.

Oil and gas (O&G) supply chain management (SCM) is complex because it deals with different geographic locations to manage demand and supply, transportation, inventory, and distribution. Blockchain technology has created an interesting research gap in the SCM domain, and this study is designed to describe the relevancy of blockchain technology for O&G SCM. SCM is based on agile and lean supply chains (SCs). Agile SC focuses on increasing flexibility and responsiveness to gain competitive advantages, and lean SC is based on eliminating waste and processes to improve firm performance. This study is an initial effort to propose a framework that suggests the implication of blockchain for O&G by providing an overview of O&G SCM. Data were collected from SC managers of O&G companies, and we analyzed the impact of agile and lean SCs on firm performance. The results indicate that agile SC is highly important for O&G industries in comparison to lean SC. This study proposes the key requirements of agile SC and how blockchain can uplift agile SC technology with state-of-the-art properties such as data-driven management, information sharing, data privacy, cyber-security, transparency, smart contracts, visibility, traceability, and reliability, which boost SC agility as well as firm performance.