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PurposeLimited use of Internet of Things (IoT) technology on construction sites has restricted its value in the construction industry. To propel its widespread application, this paper explores the influencing factors and action paths of construction companies' IoT technology adoption behavior.Design/methodology/approachFirst, literature research, technology adoption theories, and semi-structured expert interviews were employed to build the adoption model. Second, a questionnaire survey was conducted among Chinese construction contractors to collect empirical data. Third, the structural equation model method and regression analysis were used to test the adoption model. Finally, the findings were further validated with interviews, case studies, and field observations.FindingsExternal environmental pressure (EEP), perceived benefit (PB), top management support (TMS), company resource readiness (CRR), adoption intention (AI), and perceived compatibility (PCA) have a direct positive impact on adoption behavior (AB). In contrast, perceived cost (PC) and perceived complexity (PCL) exert a direct negative impact on AB. The EEP, PB, and PC are critical factors affecting AB, whereas AI is strongly affected by CRR and TMS. Besides, AI plays a part mediating role in the relationship between seven factors and AB. Company size and nature positively moderate AI's positive effect on AB.Originality/valueThis paper contributes to the knowledge of IoT technology adoption behavior in the construction sector by applying the technology adoption theories. Exploring the implementation barriers and drivers of IoT technology in construction sites from the perspective of organizational technology adoption behavior and introducing moderating variables to explain adoption behavior are innovations of this paper. The findings can help professionals better understand the IoT technology adoption barriers and enhance construction companies' adoption awareness, demand, and ability. This work also provides a reference for understanding the impact mechanism of the adoption behavior of other innovative technologies in construction.

The aim of this study is to define and clarify the idea of improving management effectiveness within Indian construction companies. We conducted an online survey with an Indian construction company and used correlation analysis to thoroughly examine how both external and internal factors affect management effectiveness. The survey includes demographic questions, ratings on a scale of 1 to 5 for management aspects, ratings on a similar scale for internal and external factors, and ratings on a similar scale for potential improvement suggestions. With the help of descriptive statistics and frequencies, the mean efficiency values were calculated using SPSS and Excel to analyse the collected data. To establish links between the variables and the effectiveness of the company, correlation analysis was also carried out. The primary conclusions of the study highlight the critical importance of focussing on employee relations, meticulous tracking of work output, integration of technology, and adherence to established protocols as key factors in improving management effectiveness. The research also reveals significant problems with the management system, such as a preference for sanctions over incentives. It establishes that internal and external factors have equal weight in influencing management effectiveness, emphasising the need for an all-encompassing strategy that is flexible enough to support long-term advancement in construction company management practices.

In recent years, China’s construction companies have placed increasing emphasis on technological innovation and have invested significant resources in it. How the input-output performance of these resources needs to be clarified. The purpose of this study is to understand the differences and variations in the input-output performance of China’s listed construction companies in terms of technological innovation by measuring their technological innovation efficiency (TIE), which can inform their technological innovation decisions. A data envelopment analysis (DEA) based Malmquist productivity index (MPI) model was constructed to measure the TIE of 48 China’s listed construction companies from 2015 to 2020. The study has the following findings. Firstly, the overall TIE of listed construction companies decreased by 0.4% per year on average during the study period, which needs further improvement. Secondly, the changes of TIE in different sub-sectors were different. The TIE of companies in the sectors of building decoration, infrastructure construction and mining, metallurgical, and petrochemical engineering increased by 10.7%, 3.7%, and 9.5% annually, respectively. Thirdly, the TIE varies among different companies with 23 companies increasing and 25 companies declining. For most companies, the management level was the main factor restricting TIE’s improvement.

Purpose Capital structure decisions are important decisions for any business activity because they have considerable influence on the worth and cost of companies. Most previous studies in Ethiopia were primarily focused on identifying and measuring problems in banking sectors and other sectors and paying little attention to the construction sector. The purpose of this study is mainly to fill the gap by examining the effects of capital structure on the profitability of construction firms in Ethiopia. Design/methodology/approach To test hypotheses of the study, time series secondary data were gathered from the sample of 30 grade one construction companies in Ethiopia during the 2011–2015 period. To examine the correlation among capital structures and its determinants, random effect multiple regression models were used. Findings From the regression outcomes, the study indicates that capital structure measured by debt to equity and long-term debt to total assets has a significant positive correlation with return on equity (ROE) and return on assets (ROA) of sampled construction companies. However, the capital structure measured by debt to assets has a significant negative correlation with ROE and ROA of sampled construction companies in Ethiopia. Originality/value This paper is the author’s original work and assures that the paper was not undertaken anywhere and is also not published in any journal before.

The construction sector plays an important role in environmental sustainable development and the green economy. Green technology innovation in the construction sector can improve the energy, cost, and environmental performance of the industry. The lagging effects of influential factors for green technology innovation have yet to be fully understood. This study aims to explore the process of green technology innovation in large construction companies based on the innovation value chain theory and through a system dynamics (SD) approach. The results revealed the dynamic interaction between various influencing factors of green technology innovation in the construction industry. The effects of different knowledge bases and market shares show heterogeneity when the influencing factors are considered as an integrated system. The study helps researchers and practitioners gain a better understanding of the nature of green technology innovation from a systematic view. Suggestions are provided for decision-makers and practitioners to better manage green technology innovation.

A method for predicting the financial status of construction companies after a medium-to-long-term period can help stakeholders in large construction projects make decisions to select an appropriate company for the project. This study compares the performances of various prediction models. It proposes an appropriate model for predicting the financial distress of construction companies considering three, five, and seven years ahead of the prediction point. To establish the prediction model, a financial ratio was selected, which was adopted in existing studies on medium-to-long-term predictions in other industries, as an additional input variable. To compare the performances of the prediction models, single-machine learning and ensemble models’ performances were compared. The comprehensive performance comparison of these models was based on the average value of the prediction performance and the results of the Friedman test. The comparison result determined that the random subspace (RS) model exhibited the best performance in predicting the financial status of construction companies after a medium-to-long-term period. The proposed model can be effectively employed to help large-scale project stakeholders avoid damage caused by the financial distress of construction companies during the project implementation process.

The world has been implementing Building Information Modelling (BIM) successfully to construction projects from small to large scale. In Vietnam and many other countries, BIM is also widely applied in different fields of the construction industry. However, there are still many problems that need to be solved. One of those is to determine the necessary BIM competencies, thereby develop BIM personnel recruitment standards. The article identifies the competencies as well as evaluates their importance when supporting the recruitment of BIM personnel in construction enterprises in Vietnam. Through survey forms such as survey on online recruitment, expert interviews, and survey forms, the study is conducted with Likert scale, relative importance index (RII) for result analysis and ranking the importance of BIM competency for three distinct group of positions in Vietnam. With this result, the authors hope that the study will be an important reference, contributing to the development and concretization of the required competency criteria in the recruitment of BIM personnel in Vietnam and other similar countries.

Small and medium-sized construction companies (SMCCs) typically lack the international experience of their large counterparts. International construction projects often are more uncertain than domestic projects, which can pique SMCCs’ interest or necessity for external benchmarks of best practices. This study aims to provide a three-phased risk-management benchmark framework for the internationalization of SMCCs. The first-phase benchmarking evaluates how well companies prepare to undertake business abroad and what capabilities they should improve upon based on comparative data from 41 SMCCs. The second-phase benchmarking provides risk information from 49 international subcontract projects that must be managed for SMCCs. In the last phase, the benchmark delivers subcontractor risk-response strategies through the analysis of 134 international-contractual cases. Additionally, the three illustrative cases show that the benchmark framework and metrics are quite helpful for decision-makers and SMCC practitioners in evaluating and responding to their international construction project risks.

Unethical behavior is one of the grand challenges facing international construction companies (ICCs) to move toward sustainable development when operating on an international basis. The ethics and compliance program (ECP) has played a significant role in addressing illegal and unethical behavior and avoiding liability in multinational companies. However, there have been few studies on the current status, major barriers, and best solutions to ECP adoption in ICCs. To fill this gap, an international questionnaire was conducted; 87 valid samples of Chinese ICCs located in 44 countries were filtered out for in-depth analysis. The survey results showed that only 36.8% of responding ICCs exercised compliance functions through the compliance department. The top five recognized barriers hampering ECP adoption were “lack of related laws and regulations”, “insufficient support from the government”, “lack of authorization to the compliance department”, “shortage of compliance professionals”, and “lack of case studies”. There was no disagreement about the barriers’ rankings among organizations of different firm ownerships, sizes, and locations, except the variable “great institutional distance”. Results also revealed the top five best solutions to help ICCs overcome the identified barriers. The findings would enhance the understanding of industry practitioners and policymakers, hence helping them address corresponding solutions to boost ECP adoption and promote the sustainable development of ICCs.

Purpose Building information modeling (BIM) is vital in the performance improvement of contracting firms. Thus, there is a need to stimulate its implementation in the construction sector with a view to meeting the competitive demands of the industry. However, there have been very few studies on BIM implementation among contracting firms in Nigeria. Hence, this study aims to examine the current BIM uptake among Nigerian contracting firms, assess the barriers to BIM implementation and examine the ways of improving BIM implementation within these contracting firms. Design/methodology/approach A questionnaire survey was conducted on contracting firms (comprising small-, medium- and large-sized firms) in Lagos, Nigeria. The obtained data were analyzed using both descriptive and inferential statistics. These included percentage, mean score, standard deviation, the Kruskal–Wallis test and factor analysis. Findings This study revealed the current state of BIM implementation among contracting firms in Nigeria in terms of their knowledge of BIM, their usage of BIM as well as the BIM software adopted. Furthermore, the study identified 25 barriers to BIM implementation in contracting firms and identified 15 ways to improve BIM implementation in contracting firms. The relative importance of both the identified barriers and the ways for improving BIM implementation was gauged among contracting firms comprising small-, medium- and large-sized firms. The result of the Kruskal–Wallis test revealed that, except for two (out of 25) identified barriers, and one (out of 15) identified ways of improving BIM implementation in contracting firms, there is no significant statistical difference in the perceptions of the three respondents’ groups. The result of the factor analysis categorized the identified 25 barriers into seven main factors. Practical implications This study provides empirical evidence on the barriers to BIM implementation and the ways of improving its implementation among contracting firms, thereby providing a better insight of the Nigerian construction industry’s BIM environment. Originality/value This study’s findings can positively inform the decisions of construction stakeholders to formulate strategies capable of improving BIM implementation in the construction industry at large.