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This study aims to empirically examine the relationships among perceived environmental uncertainty (EV), the level of knowledge distance (KD) and the impact of value network on firm performance.

The quantitative analysis is based on data from 243 Chinese companies with engineering, procurement and construction (EPC) business in the context of the COVID-19 pandemic.

The two dimensions of value network [network centrality (NC) and network openness (NO)] have a different impact on firm performance [financial performance (FP) and market performance (MP)]. NC has a positive impact on FP, but not on MP. NO has a positive effect on MP, but not on FP. A reduced KD mediates the relationship between value network and firm performance. Moreover, it fully mediates the relationship between NC and MP, NO and FP. Finally, during the COVID-19 pandemic, only EV has a moderating effect on KD and MP.

This study is limited in terms of data set because it relies on a limited amount of cross-sectional data from one specific country. Therefore, researchers are encouraged to test the proposed propositions further.

The present findings suggest that EPC professionals should pay more attention to the EV, which may be impacted by policy, technology and the economy. This research has actionable implications for the reform of EPC in the construction industry, and practical recommendations for EPC firms to improve their corporate performance.

The results measure the complementary effects of both dimensions of value network (NC and NO) on two distinct aspects of firm performance (MP and FP) and assess the moderating effect of EV and KD in the context of the COVID-19 pandemics.

This study has a twofold goal. First, we examined perceptions of organizational politics as viewed by the academic staff in a public university. Second, we tested the potential mediating effect of perceptions of politics on the relationship between social capital and work outcomes. We surveyed 142 junior and senior faculty members of a large public Israeli university and tested several competing models. Major results, based on Structural Equations Model (SEM) analysis, indicate that the mediating model has several advantages over the direct effect model. In addition, a revised, mixed model provided additional advantages. The models are compared and discussed. Finally, implications of the findings and recommendations for future studies on internal politics and social capital in academia and beyond are suggested.

Prediction problems raised in uncertain environments require different solution approaches such as grey prediction models, which consider uncertainty in information and also enable the use of small data sets. The purpose of this paper is to investigate the comparative performances of grey prediction models (GM) and Markov chain integrated grey models in a demand prediction problem.

The modeling process of grey models is initially described, and then an integrated model called the Grey-Markov model is presented for the convenience of applications. The analyses are conducted on a monthly demand prediction problem to demonstrate the modeling accuracies of the GM (1,1), GM (2,1), GM (1,1)-Markov, and GM (2,1)-Markov models.

Numerical results reveal that the Grey-Markov model based on GM (2,1) achieves better prediction performance than the other models.

It is thought that the methodology and the findings of the study will be a significant reference for both academics and executives who struggle with similar demand prediction problems in their fields of interest.

The novelty of this study comes from the fact that the GM (2,1)-Markov model has been first used for demand prediction. Furthermore, the GM (2,1)-Markov model represents a relatively new approach, and this is the second paper that addresses the GM (2,1)-Markov model in any area.

Ontology and Linked Data (LD) are the two prominent web technologies that have emerged in the recent past. Both of them are at the center of Semantic Web and its applications. Researchers and developers from both academia and business are actively working in these areas. The increasing interest in these technologies promoted the growth of LD sets and ontologies on the web. The purpose of this paper is to investigate the possible relationships between them. The effort is to investigate the possible roles that ontologies may play in further empowering the LD. In a similar fashion, the author also studies the possible roles that LD may play to empower ontologies.

The work is mainly carried out by exploring the ontology- and LD-based real-world systems, and by reviewing the existing literature.

The current work reveals, in general, that both the technologies are interdependent and have lots to offer to each other for their faster growth and meaningful development. Specifically, anything that we can do with LD, we can do more by adding an ontology to it.

The author envisions that the current work, in the one hand, will help in boosting the successful implementation and the delivery of semantic applications; on the other hand, it will also become a food for the future researchers in further investigating the relationships between the ontologies and LD.

So far, as per the author’s knowledge, there are very little works that have attempted in exploring the relationships between the ontologies and LD. In this work, the author illustrates the real-world systems that are based on ontology and LD, discusses the issues and challenges and finally illustrates their interdependency discussing some of the ongoing research works.

The production of sleeve grouting in prefabricated construction is routinely plagued by a variety of factors, and lack of mass data and complex environmental conditions over time make problems inevitable. Thus, a dynamic risk control system is a valuable support for the successful completion of the sleeve grouting process. This study aims to develop an entropy-based sleeve grouting risk dynamic control system.

First, static risk assessment was conducted through the structured interview survey using the entropy weight method, followed by a dynamic risk control technique, where indicators were simulated through system dynamics containing causal loop diagrams and stock-and-flow diagrams.

Finally, three types of risk control models, namely, “tortuous type”, “stable type” and “peak loop type”, were developed in the entropy-based sleeve grouting risk dynamic control system and simulated using system dynamics in a real case.

Compared to traditional sleeve grouting risk management, the developed system enabled dynamic control over time.

Since the first automated container terminal (ACT) was introduced at Europe Container Terminals Delta Terminal in Port Rotterdam back in the year 1992, a lot of research had been done to improve the management of ACT. However, up until recently, the number of literature available still appeared scarce. Hence, this paper aims to review the collection of literature about ACT to generate an exhaustive summary to answer the formulated review question in this study.

Preferred reporting items for systematic reviews and meta-analyses to narrow down the search parameters of literature retrieved so that only relevant articles were only selected. The systematic literature reviews were applied to analyse the content of the articles retrieved to determine its journal ranking, research findings and timeline of publications.

The adoption of ACT technology by container terminal operators could increase the terminal efficiency in productivity, cost reduction and environmental sustainability. Owing to global environmental awareness, the research trend of container terminal field and container terminal operator in the terminal design is much more environmentally friendly oriented.

The limited numbers of experts in the management of ACT are causing challenges in data collections.

The analysis of the global ACT trend could help academicians and industrial investors to review the revolution timeline of maritime technology in port and shipping that is happening rapidly.

The analysis of timeline and collective literature leads to the propose of the conceptual framework to determine the relationship between increased productivity, cost reduction and environmentally sustainable.

The purpose of this study is to explore the association between eating patterns, social identity and the well-being of adolescents via a mixed methods study of Chinese teenagers. The specific research questions presented in this study are as follows: What is the relationship between social eating and well-being? How is the relationship between social eating and well-being mediated by social identity?

This study is based on a sequential mixed methods study, including interviews with 16 teenage–parent dyads, and a large-scale survey of over 1,000 teenagers on their eating patterns, conducted with the support of public schools. A model that tests relationships among social eating, social identity and subjective well-being is developed and tested.

The results show that dining with family members leads to improved subjective well-being for teenagers, through a partial mediator of stronger family identity. However, dining with peers is not found to influence subjective well-being.

The privileged position of family meals demonstrated through this study may be an artifact of the location of this study in one Chinese city. Further research is needed related to the connections among social identity, objective well-being and the social patterns of teenagers’ food consumption behavior.

To improve the subjective well-being of teenagers, families, public policy-makers and food marketers should support food consumption patterns that promote family meals.

While many food-related consumer studies focus on the individual, social and environmental influences of food choices of adolescents, few studies address how eating patterns affect overall well-being. These results reinforce the importance of understanding the effect of the social context of teenagers’ eating patterns on health and well-being.

This paper aims to present the result of a scientometric analysis conducted using studies on high-performance computing in computational modelling. This was done with a view to showcasing the need for high-performance computers (HPC) within the architecture, engineering and construction (AEC) industry in developing countries, particularly in Africa, where the use of HPC in developing computational models (CMs) for effective problem solving is still low.

An interpretivism philosophical stance was adopted for the study which informed a scientometric review of existing studies gathered from the Scopus database. Keywords such as high-performance computing, and computational modelling were used to extract papers from the database. Visualisation of Similarities viewer (VOSviewer) was used to prepare co-occurrence maps based on the bibliographic data gathered.

Findings revealed the scarcity of research emanating from Africa in this area of study. Furthermore, past studies had placed focus on high-performance computing in the development of computational modelling and theory, parallel computing and improved visualisation, large-scale application software, computer simulations and computational mathematical modelling. Future studies can also explore areas such as cloud computing, optimisation, high-level programming language, natural science computing, computer graphics equipment and Graphics Processing Units as they relate to the AEC industry.

The study assessed a single database for the search of related studies.

The findings of this study serve as an excellent theoretical background for AEC researchers seeking to explore the use of HPC for CMs development in the quest for solving complex problems in the industry.