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This study aims to discover the factors which influence user satisfaction levels and their continuous use intention (CUI) of academic library social media, and then considers how to promote and improve further work on library social media to reduce user churn and increase user satisfaction.

An updated DeLone and McLean information systems success (D&M ISS) model and the expectation confirmation model for information systems continuance (ECM-ISC) with new variables of emotions are used to examine the factors which influence user satisfaction levels and CUI of academic library social media through 445 questionnaires. Partial least squares structural equation modelling was used to analyse the data and presented in tables.

The results show that information quality, system quality and emotions affect user satisfaction and CUI, and reveal that emotions can affect that most obviously.

The WeChat public platform is mainly used in China, so the study only focuses on Chinese academic libraries. There are still limitations on the settings of observed variables which cannot cover all the causes of users’ positive and negative emotions. In addition, although the respondents of this questionnaire can represent academic library users, 445 samples are still fairly low in contrast to the great number of academic library WeChat public platform users.

This study integrates ECM-ISC and D&M ISS models, adds positive and negative emotions as new variables, to broaden the application scope of these models, and demonstrates the applicability of these two models in the fields of researching academic library social media, expanding and deepening related theories above. This also provides practical reference for academic libraries on how to improve user satisfaction and CUI of academic library social media and academic library WeChat public platforms, promoting the development of academic library social media.

Challenges associated with ensuring the accuracy and reliability of cost estimation of highway construction bid items are of significant interest to state highway transportation agencies. Even with the existing research undertaken on the subject, the problem of inaccurate estimation of highway bid items still exists. This paper aims to assess the accuracy of the cost estimation methods employed in the selected studies to provide insights into how well they perform empirically. Additionally, this research seeks to identify, synthesize and assess the impact of the factors affecting highway unit prices because they affect the total cost of highway construction costs.

This paper systematically searched, selected and reviewed 105 papers from Scopus, Google Scholar, American Society of Civil Engineers (ASCE), Transportation Research Board (TRB) and Science Direct (SD) on conceptual cost estimation of highway bid items. This study used content and nonparametric statistical analyses to determine research trends, identify, categorize the factors influencing highway unit prices and assess the combined performance of conceptual cost prediction models.

Findings from the trend analysis showed that between 1983 and 2019 North America, Asia, Europe and the Middle East contributed the most to improving highway cost estimation research. Aggregating the quantitative results and weighting the findings using each study's sample size revealed that the average error between the actual and the estimated project costs of Monte-Carlo simulation models (5.49%) performed better compared to the Bayesian model (5.95%), support vector machines (6.03%), case-based reasoning (11.69%), artificial neural networks (12.62%) and regression models (13.96%). This paper identified 41 factors and was grouped into three categories, namely: (1) factors relating to project characteristics; (2) organizational factors and (3) estimate factors based on the common classification used in the selected papers. The mean ranking analysis showed that most of the selected papers used project-specific factors more when estimating highway construction bid items than the other factors.

This paper contributes to the body of knowledge by analyzing and comparing the performance of highway cost estimation models, identifying and categorizing a comprehensive list of cost drivers to stimulate future studies in improving highway construction cost estimates.

This study aims to review the status quo, current state of research, research hot themes and research gaps in sustainable facilities management (SFM) in the built environment (BE) through an extant literature review.

To map and analyze knowledge paths in the context of SFM research, a sequential explanatory mixed-method review involving bibliometric and content analysis was used to help identify current research trends, research hot themes and knowledge gaps. The Scopus search engine was used to find 169 relevant articles. For a better understanding of the literature accumulated, a bibliometric analysis was carried out by using VOSviewer to reveal current research themes, the status quo and current state of research as well as research gaps.

Through the literature review and content analysis, the current research themes on SFM revealed from the study include green building technologies, assessment methods of SFM, smart buildings and building information modeling. The research hot themes in SFM include smart buildings and green building technologies, green buildings (GB), architectural and building designs in the university sector, assessment methods in buildings and decision-making and the adoption of asset and facility management in the university sector. Indoor air pollution, intelligent buildings, climate change, maintenance, environmental management, facilities, historic preservation, environmental performance, energy management, etc. are the research gaps identified from the study, and these serve as potential areas for future research studies under SFM. It was recognized that facilities managers are increasingly involved with sustainability policies within their organizations and are developing sustainability agendas to keep up with the changing nature of the facilities management (FM) profession.

The findings of this study hold relevance to the FM practice, as the integration of SFM by facilities managers can lead to waste reduction, decreased operating expenses and reduced energy consumption. In addition, occupants of sustainable buildings experience improved conditions that contribute to better health and productivity, thus boosting their overall well-being. Consistent with the themes of smart buildings and green technologies, revealed to be the hot themes in the SFM research scope, properties with sustainable features can command higher rental rates and property values, appealing to a broader range of stakeholders. SFM practices in universities can aid in saving money from reduced facility operational costs and improve the image of institutions while creating better indoor environments for students and staff. The analyses of countries involved in research can open doors for the establishment of research groups and the development of collaboration between universities in different countries researching similar topics of interest.

The geographical scope of this study is not limited and, therefore, encourages broad applicability of the findings to the global sustainable BE.