The research aims to investigate the potential impact of Artificial Intelligence (AI) on the digital supply chain in light of extant literature on the Decision-Oriented Information (DOI) theory and the Technology-Oriented Enterprise (TOE) framework. The research further attempts to unpack the strategic implications of AI integration in supply chain management, and its association with operational excellence and business model innovation. The study is exploratory and employs a mixed-methods approach. We develop propositions that examine the decision-making processes within AI-enhanced supply chains based on an analysis of concepts central to the DOI theory. We also employ the TOE framework to develop further propositions regarding the technological infrastructure required for AI implementation. Empirical case studies encompassing AI applications in different industries (e.g. manufacturing, healthcare, and pharmaceuticals) are presented to gain a broad perspective of the impact of AI on the digital supply chain. AI technologies inherently make supply chains more agile, transparent, and responsive. Machine Learning algorithms allow for more accurate forecasting and demand management under conditions of supply chain risk and volatility. Robotics and automation, allow for greater flexibility and efficiency in executing operations and logistics. Additionally, the successful implementation of AI is heavily contingent on the organization’s current level of technological infrastructure and its alignment with its current and future business objectives. Furthermore, the DOI theory and TOE framework may serve as a blueprint for how one could evaluate AI implementation beyond the scope of supply chain management.

This research aims to investigate the impact of digital transformation on the operational efficiency, customer experience, competitive advantage, organizational performance, and risk management in Jordanian Islamic banks. A descriptive analytical method was used, collecting primary data from a survey of 68 employees across four Islamic banks. Statistical tools, including linear regression and correlation, were used for data analysis and hypothesis testing. The findings revealed that digital transformation significantly influences the operational efficiency, competitive advantage, customer experience, organizational performance, and risk management of Islamic banks at a significance level of α ≤ 0.05. While digital transformation generally enhanced operational outcomes and customer experience, it also increased exposure to risks such as electronic attacks, fraud, and privacy concerns. The results highlight the importance of integrating digital transformation in Islamic banking while employing robust risk management strategies. These findings provide insights for policymakers, bank managers, and researchers in formulating strategic initiatives for digital transformation in the banking sector. The research contributes to the literature by focusing on the role of digital transformation in Islamic banking, a less-explored area in academic studies. This research also presents valuable implications for practice, specifically for banks and regulators to balance the potential of digital transformation with the associated risks.

Safety risk and operational efficiency in sustainable coal supply was an issue in the coal distribution supply chain. An online survey evaluating safety hazards, operational effectiveness, logistic service providers, and sustainable supply chain management was completed by 89 consumers of coal logistic service providers. In contrast, this study aimed to evaluate the operational effectiveness and safety concerns of a sustainable coal supply chain managed by the logistic service providers on the Barito River. In addition to using path analysis, quantitative research methods were also applied to calculate and process the questionnaire data, producing a value that determined the weight of each vendor, criterion, and sub-criterion. It showed several positive and significant influences connected to the safety of sustainable supply chain management, the operational efficiency of logistic service providers, supply chain management, and security risks for the providers. Therefore, it was essential to unite the positive influences on the logistic flow to secure the coal supply chain activities on the Barito River. This research would have theoretical and practical applications, adding to the advancement of science through its applications. Such knowledge would affect the safety risk and operational efficiency of sustainable supply chain management through the logistic service providers on the Barito River, Central Kalimantan.

The research analyses the impact of non-interest income on the performance of 26 Vietnamese commercial banks in the period of 2008 - 2017 by the Generalized Method of Moments (GMM) method. The research results show that: (i) The average non-interest income ratio of Vietnamese commercial banks is only 8.32%, a significantly low level compared with the interest income ratio of more than 90% of the total income of the banks; (ii) Non-interest income has a positive impact on the performance of Vietnamese commercial banks in the research period. The research results assist in confirming the trend of diversifying non-credit activities to increase non-interest income ratio of Vietnamese commercial banks.

This research aims to explore the impact of AI-induced anxiety on the adoption of mobile payment services in supply chain firms, viewed through the lens of Mental Accounting Theory. In an era driven by technological advancement, supply chain companies' use of mobile payment services has arisen as a crucial problem. This study is the first to investigate the complicated links between AI-induced anxiety, perceived utility, and the adoption rate of mobile payment systems using the Mental Accounting Theory as a theoretical framework. The study employs a quantitative research approach, using Smart PLS for regression analysis, and gathers its data from major supply chain business players. Our analysis offered important insights into the many aspects influencing the adoption of mobile payment services in supply chain companies. The acceptance rate was shown to be adversely connected with AI-induced anxiety and integration expenses, posing obstacles for businesses seeking to embrace mobile payment systems. In contrast, characteristics such as perceived utility, usability, confidence in security, and backing from upper management were positively connected with adoption rates. These findings provide not only theoretical contributions to the current research, but also concrete advice for supply chain practitioners seeking to exploit mobile payment systems for operational and strategic advantage.

This article analyzes the impact of internal control on the performance of pharmaceutical companies, providing additional empirical evidence on the effects of internal control on performance. The research method used includes surveys through questionnaires distributed among pharmaceutical companies to assess internal control and each element of internal control of these firms. Quantitative research was carried out with SPSS 25 software. The results show that monitoring, information and communication are the factors that have the strongest impacts on the performance of pharmaceutical companies. This can be explained that, for pharmaceutical companies, good monitoring and information and good tradition will positively affect the effectiveness of internal control in particular and the performance of the business. Based on the research results, the author proposes some recommendations to improve the effectiveness of internal control, thereby contributing to improve the performance of pharmaceutical enterprises.