The oil and gas (O&G) sector depends on information analysis, making digital transformation vital. Industry-specific factors like environmental, regulatory, operational, and security challenges shape its tech adoption. This paper identifies and examines the barriers and drivers of digital transformation in O&G through a literature review and expert insights, leading to a questionnaire assessment. Interpretive Structural Modeling (ISM) was employed to create a structural model that illustrates the interactions between these barriers, helping experts understand how to achieve digitization within the industry. The questionnaire analysis identified the key barriers based on their RII values: “Experiments requiring significant time for validation of new technologies”, “Technical complexities of new technologies”, “Security concerns”, “Insufficient strategies”, and “Organizational culture and resistance to change”. The ISM indicated that the “Technical complexities of new technologies” and the “Lack of readily deployable technologies” are the most influential barriers. Addressing these is crucial for O&G companies to unlock digitalization potential.

Purpose: The oil and gas construction projects in Saudi Arabia are commonly impacted by the frequent occurrence of change orders. Therefore, this study aims at determining the factors influencing change orders in the oil and gas construction projects in Saudi Arabia.Design/methodology/approach: Firstly, the factors are extracted by examining the literature and further refined through experts' feedback. Twenty-one factors were identified in this manner. Thirdly, the factors are prioritized using a questionnaire survey. Responses from 162 professionals have been collected through surveys and ranked using the significance index. The correlation between factor rankings between classes is assessed using Spearman's correlation coefficient. Lastly, using principal component analysis, a change order-related factors conceptual model is developed.Findings: The five most significant factors were identified and ranked in a general manner or per the category involved. Four main types were involved: project management team (PMT), consultants, contractors and clients. Moreover, a change order-related factors model is proposed. The factors are grouped under four main groups: project definition and planning factors, project stakeholder-related factors, project execution-related factors and project performance and control factors.Originality/value: Despite the vast factor-related literature in Saudi Arabia. Nevertheless, there has never been a study that investigates the factors influencing change orders in oil and gas projects in Saudi Arabia before. This study not only identifies the change order-related factors but also proposes a model that captures the importance of these factors. This model can aid project professionals in mitigating the impact of the most critical factors encountered during the various phases of the project.

Numerous technoeconomic factors have had a considerable impact on the industrial and service sectors. The best uses of production and service resources have been a main research area. Capacity planning, which aims at the optimum utilization of resources, has attracted a lot of scholarly attention. To the best of our knowledge, however, there has never been a scientometric analysis published on this subject; as a result, the goal of this article is to provide the first such analysis. The goal of this study is to gain a thorough structural view of the background and important facets of capacity expansion and planning research. The Web of Science database, VOSviewer, and CiteSpace software are used to give an overview. Our research indicates that after the year 2000, the publication rate increased significantly. Applications for capacity planning can be divided into eight main groups based on the authors' keyword analysis. We also list both well-known and underutilized modeling and solution methods. Recent applications, research trends, and some omissions are highlighted in this study. Leading contributing countries, institutions, and the most common research outlets are mapped and analyzed. Finally, some potential future research topics are suggested