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This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

This study aims to explore the transformative potential of digital twins (DTs) in the construction industry by addressing challenges and bridging the technology adoption gap. Focusing on construction offices, on-site environments and their interface, the research identifies key success factors for DT implementation. Emphasizing practical applications, the study foresees a substantial impact on project management, highlighting the pivotal role of DTs in reshaping the construction sector.

We reviewed 30 variables within the DT literature, classifying investigations into three main domains: on-site environments, office environments and site-office interface in construction projects. We employed a questionnaire to examine variables, with collected data analyzed using SmartPLS version 4 software. Confirmatory analysis and structural equation modeling rigorously assessed the model’s reliability, validity and predictive utility.

The study identifies 11 critical factors crucial for successfully implementing DTs in construction projects, emphasizing contributions from office-related (ORF), site-related (SRF) and office-site-related factors (OSRF). Notably, impactful contributions from ORF affirm its pivotal role. The research sheds light on specific aspects within construction offices, on-site environments and their interface, providing valuable insights for industry stakeholders, policymakers and researchers.

Despite discussions on DT’s potential, a research gap exists in addressing essential factors for its effective application in monitoring and optimizing construction projects throughout their lifecycle. This study fills this gap by identifying and categorizing these factors, enhancing the knowledge base for successful DT assimilation and emphasizing the need for practitioners to understand key factors crucial for its integration into construction processes.

While research on sustainability reporting in the construction industry has already provided comprehensive findings, the purpose of this paper is to answer the question of how construction companies anchor the topic of sustainability in their strategic and operative management control practices. The implementation of sustainable business models and sustainability strategies requires proper management control instruments or mechanisms that support the transformation process or make it possible in the first place.

A qualitative content analysis based on deductive and inductive procedures was conducted. 39 sustainability reports published by the largest construction companies in the EU were examined.

Valuable insights are provided by showing which control instruments and mechanisms are used to improve corporate sustainability performance as well as how these are linked systematically. The results show that the focus is on strategic planning, cultural and administrative controls, while short-term targets, which could set out the path to achieving the long-term sustainability goals set, are often not reported. Strategic stakeholder theory and legitimacy theory provide explanations for the use of management control practices identified.

Previous studies often focus on selected single control practices and miss holistic approaches for investigating corporate sustainability in construction companies. Furthermore, theoretical perspectives with instrumental and socio/political views on corporate sustainability help us explain the control practices applied. Moreover, practitioners, standard setters and legislators can use the findings for sustainability management or for developing standards and legislation.

The chapter explored integrating smart construction techniques in achieving stealth construction objectives, emphasising the development of building cross-sections, visibility management, energy transmission optimisation, and countermeasure implementation. It delved into the multifaceted aspects of smart construction towards achieving stealth construction goals, including environmental protection, enhanced construction safety, accelerated construction duration, cost-effectiveness, and aesthetic considerations. Furthermore, the chapter underscores the importance of leveraging innovative approaches and advanced technologies to meet the evolving demands of stealth construction projects and pave the way for sustainable, safe, and aesthetically pleasing built environments.

This paper aims to understand the impact of intellectual capital components (human, structural and relational capital) on business internationalization through exports, analyzing the Colombian manufacturing sector.

A binomial logistic regression model was used in which the export propensity was the dependent variable. The explanatory variables consisted of the human capital, including training and managerial characteristics; the structural capital, including innovation, intellectual property, certifications and management and the relational capital, encompassing relationships with other companies, public entities and the domestic market. The Survey of Development and Technological Innovation - EDIT - Industry 2018, carried out by the National Administrative Department of Statistics of Colombia, was used to collect data from 7,529 companies in 24 manufacturing subsectors.

The research findings suggest that there is a positive relationship between internationalization and human capital (postgraduate, university and school training), with structural capital (innovation in organizational processes, ownership of patents, software rights, industrial rights, trademark registration, obtaining intellectual property rights, complexity in design, process certifications, compliance with technical requirements and the existence of production goals) and with relational capital (confidentiality agreements with other companies and contracts with the international public sector).

This article contributes to the literature generating knowledge on the relationship between intellectual capital and the internationalization of Colombian industrial companies. It will also have managerial and social implications serving as input for the decision-making process of firms undergoing internationalization, and for policymakers.

The motivation to participate in crowdsourcing (CS) platforms is an emerging challenge. Although researchers and practitioners have focused on crowd motivation in the past, the results obtained through such practices have not been satisfactory. Researchers have left unexplored research areas related to CS pillars, such as the evolution of the crowd’s primary motivations, seekers applying effective policies and incentives, platform design challenges and addressing task complexity using the synchronicity of the crowd. Researchers are now more inclined to address these issues by focusing on sustaining the crowd’s motivation; however, sustaining the crowd’s motivation has many challenges.

To fill this gap, this study conducted a systematic literature review (SLR) to investigate and map the challenges and factors affecting sustained motivation during CS with the overcoming implications. Studies that satisfied the inclusion criteria were published between 2010 and 2021.

Important sustainable factors are extracted using the grounded theory that has sustained participation and the factors' cohesion leads to the identification of challenges that the pillars of CS face. Crowds being the most vital part of CS contests face the challenge of engagement. The results reported the factors that affect the crowd’s primary and post-intentions, perceived value of incentives and social and communal interaction. Seekers face the challenge of knowledge and understanding; the results identify the reason behind the crowd’s demotivation and the impact of theories and factors on the crowd's psychological needs which helped in sustaining participation. Similarly, the platforms face the challenge of being successful and demanding, the results identify the latest technologies, designs and features that seekers proclaim and need the platforms designer's attention. The identified task challenges are completion and achievement; the authors have identified the impact of trait of task and solving mechanisms that have sustained participation.

The study identifies, explores and summarizes the challenges on CS pillars researchers are facing now to sustain contributions by keeping participants motivated during online campaigns. Similarly, the study highlights the implication to overcome the challenges by identifying and prioritizing the areas concerning sustainability through the adoption of innovative methods or policies that can guarantee sustained participation.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.