Delay is the leading challenge in completing Engineering, Procurement, and Construction (EPC) projects. Delay can cause excess costs, which reduces company profits. The relationship between subcontractors and the main contractor is a critical factor that can support the success of an EPC project. The problematic financial condition of the main contractor can cause delay in payments to subcontractors. This research will set a model that combines the system dynamics and earned value method to describe the impact of subcontractor advance payments on project performance. The system dynamics method is used to model and analyze the impact of interactions between variables affecting project performance, while the earned value method is applied to quantitatively evaluate project performance and forecast schedule and cost outcomes. These two methods are used complementarily to achieve a holistic understanding of project dynamics and to optimize decision-making. The designed model selects the optimum scenario for project time and costs. The developed model comprises project performance, costs, cash flow, and performance forecasting sub-models. The novelty in this research is a new model for optimizing project implementation time and costs, adding payment rate variables to subcontractors and subcontractor performance rates. The designed model can provide additional information to assist project managers in making decisions.

The transportation sector is currently experiencing a significant transformation due to the influence of digital technologies, which are revolutionizing travel, goods transportation, and interactions with transportation systems. This study delves into the possibilities and obstacles presented by digital transformation in the realm of sustainable transportation. Moreover, it identifies the most effective methods for implementing digital transformation in this sector. Furthermore, our analysis sheds light on the potential impacts of digital transformation on sustainable development and environmental performance indicators within transportation systems. We discover that digital transformation can contribute to reduced greenhouse gas emissions, improved air quality, and increased resource efficiency, among other benefits. Nevertheless, we emphasize the potential risks and uncertainties associated with digital transformation, including concerns regarding data privacy, security, and ethics. Collectively, our research provides valuable insights into the opportunities and challenges presented by digital transformation in sustainable transportation. It also identifies best practices for successfully implementing digital transformation in this sector. The implications of our findings are significant for policymakers, businesses, and other stakeholders who aspire to drive the future of sustainable transportation through digital transformation.

Background: In the context of organizational innovation frameworks, knowledge plays a crucial role in sparking new ideas and bolstering innovation capabilities. Insights gathered from various sources can act as a catalyst for generating fresh concepts and pushing boundaries. Moreover, the effectiveness of innovation within an organization can be influenced by factors like employee retention and strategies in human resource management, which can either enhance or hinder the correlation between knowledge accumulation and innovation outcomes. The employee innovation performance involves a series of tasks carried out by individuals who not only possess knowledge and skills but also demonstrate consistency, active involvement in decision-making, intrinsic motivation, and a flair for innovation. Objective: This study endeavors to provide valuable insights into how non-standard service relationships, psychological contracts, and knowledge sharing practices can collectively impact and drive innovation in the green manufacturing sector. Arrangement: In the investigation of employee innovation performance within the development of the green manufacturing industry, the focus will be on exploring non-standard service relationships, psychological contracts, and knowledge sharing. These three specific facets play a pivotal role in shaping the innovation landscape in organizations operating within the realm of sustainable manufacturing. The arrangement of this study will begin by examining the impact of non-standard service relationships on employee innovation performance. By dissecting unconventional service models and their correlation with innovation behaviors, we aim to uncover novel insights that can fuel sustainable innovation practices in the green manufacturing sector. Method: The study adopts a quantitative methodology to collect data, concentrating on a group of employees across eight distinct outsourcing firms. This selection results in a comprehensive sample of 299 participants. For the analysis and manipulation of the data, the research utilizes Sructural Equation Modeling (SEM) based on Partial Least Squares (PLS) software. This choice facilitates a meticulous and structured analysis of the data gathered, ensuring precision in the research findings. Results: The research findings reveal a significant and positive influence of psychological contracts on the propensity for knowledge sharing among employees. This suggests that organizations that emphasize establishing strong psychological contracts are likely to nurture a work environment conducive to the free exchange of knowledge and ideas, thus promoting a culture of collaboration and continuous improvement. Additionally, the data points to a noteworthy positive correlation between the act of knowledge sharing and the ability of an organization to offer unique, non-standard services. This underscores the role of knowledge sharing as a catalyst for innovation, indicating that organizations encouraging such exchanges are in a better position to innovate and provide services that adapt to the changing demands of customers and stakeholders. Conclusion: The research underscores the critical but nuanced role of knowledge sharing in driving employee innovation, especially when contrasted with its pronounced impact on developing non-standard services. It highlights the necessity for organizations to create environments conducive to the free exchange of ideas, fostering innovation. The findings also reveal the significant influence of innovative service offerings and strong psychological contracts on boosting employee creativity and service quality, respectively. For the green manufacturing sector, these insights stress the importance of robust psychological contracts and an innovation-centric culture. Emphasizing trust, open communi

Purpose: The purpose of this paper is to explore the impact of Artificial Intelligence on the performance of Indian Banks in terms of financial metrics. The study focused specifically on the NIFTY Bank Index. The paper also advocates that a greater transparency in disclosing AI related information in a Bank’s annual report is required even if it is voluntary. Design/Methodology/Approach: The paper uses a mixed method approach where quantitative and qualitative analysis is combined. A dynamic panel data model is used to understand the impact of AI of Return on Equity (RoE) of 12 Indian Banks in the NIFTY Bank Index over a five-year period. In addition to that, Content analysis of annual reports of banks was conducted to examine AI related disclosure and transparency. Findings: The paper highlights that the integration of Artificial Intelligence (AI) significantly influences the financial performance of sample banks of India. Return on Equity the specific parameter positively influenced with adoption of AI. The profitability of banks is positively impacted by reduced errors and improved operational efficiency. The content analysis of annual reports of the banks indicates different approach for AI disclosure where some banks give detailed information and some are not transparent about AI initiatives. The findings suggest that a higher level of transparency could enhance confidence of all stakeholders. Theoretical Implications: The positive relation between adoption of AI and financial performance, specifically ROE, gives a foundation for academic research to explore the dynamics of emerging technology and financial systems. The study can be extended to explore the impact on other performance indicators in different sectors. Practical Implications: The findings of this study emphasize the importance of transparent AI related disclosures. A detailed reporting about integration of AI helps in enhanced stakeholders’ confidence in case of banking industry. The regulatory framework of banks may also consider making mandatory AI disclosure practices to ensure due accountability to maximize the benefits of AI in banking.

The purpose of this study is to investigate customer satisfaction with quality of service known as SERVQUAL improvement or service quality competitiveness in emerging markets. Using Indonesian government medical care as an example the author examines the satisfaction of patients. Information and data were collected through a survey of 399 BPJS users in Indonesia. All data were analyzed using Smart PLS. This study demonstrates that there is a negative value associated with the five-dimensional gap. As a result, the care provided to BPJS patients is below par. Specifically, the sensitivity dimension has the largest disparity at 0.15, while the physical evidence dimension has the smallest at 0.49. In order to raise the level of service provided, it may be necessary to take direct measures or examine tangible evidence. This study develops the relationship between different quality service models. There appears to be a substantial increase in the body of literature in the area of service quality, allowing for constant updates and the incorporation of the lessons learned from the experiences of the departed. These revised guidelines are intended to aid SERVQUAL study participants. The study gives practical support to academics and practitioners in directing service quality improvement through the use of data collected from large-scale surveys of patients and medical professionals as doctors in Indonesia.

Organisational competitiveness hinges on the strategic integration of digital transformation (DT), emerging skills (ES), and organizational health (OH) to foster sustainable performance. Despite the pivotal role of these variables, limited research investigates their interplay in Micro, Small, and Medium Enterprises (MSMEs) in Indonesia. This study addresses this gap by empirically examining how MSMEs navigate challenges and opportunities amid the digital transformation landscape. Specifically, the research probes the intermediary function of the synergistic integration between DT and ES, influencing organisational performance (OP) moderated by OH. Utilizing a validated questionnaire, a three-month convenience sample involved 120 MSME managers. Partial least squares structural equation modelling analysis was employed to assess hypotheses. Findings indicate a significant relationship between DT, ES, and OH, with DT influencing OP. Interestingly, ES alone does not impact OP. Structural equation modelling reveals OH as a mediating variable between DT, ES, and OP. While the proposed model is preliminary, offering avenues for further research, this study underscores the importance of emerging skills in the MSME sector, contributing to a nuanced understanding of organisational competitiveness dynamics.