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This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.

This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.

The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.

This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.

By harnessing technology developments such as Internet-of-Things (IoT)-enabled intelligent sensors and immersive virtual reality (VR) experiences, facility managers can access real-time, precise information on thermal comfort-related indicators through virtual facility models. While prior research studies have developed key technologies for improving the understanding of thermal comfort and its impact on the occupants’ well-being and productivity, there remain areas yet to be explored, especially in relation to integrating both real-time data from multimodal IoT-enabled smart sensors and VR technologies. Hence, this study demonstrates the potential of integrating IoT and VR technologies for real-time thermal comfort assessment and visualization as well as user interaction with HVAC systems to enhance thermal comfort.

To develop the proposed integrated analytical framework in this paper, various steps were implemented. First, four multimodal IoT-enabled sensing stations were created and installed to collect real-time thermal comfort-related data (i.e. temperature and relative humidity). Second, a VR environment was developed using the Unity engine to offer an immersive experience. Third, the real-time data from the IoT-enabled sensing stations was integrated into the VR environment by transmitting it to the cloud via the MQTT protocol server, and various programming scripts were developed to provide multiple functionalities to the users, including visualizing the thermal comfort along the entire indoor space as well as interacting with and controlling the cooling and heating HVAC systems. Fourth, the applicability and effectiveness of the developed framework was validated and evaluated by 92 participants using a survey questionnaire.

The obtained survey results validated the importance and effectiveness of the developed framework on various aspects including graphical satisfaction, spatial presence, involvement, experienced realism, low-to-no cybersickness and overall application satisfaction, among others. More specifically, the findings reflected that the participants’ average scores for graphical satisfaction, sense of spatial presence, involvement and experienced realism were 4.69, 4.61, 4.71 and 4.53 out of 5, respectively. Hence, the results showed that the visualization capabilities of the developed framework serve as a powerful feature that enables a comprehensive visualization of thermal comfort variations across the entire room/office space. Also, the results showed that there were no statistically significant differences between the responses of participants with prior VR experience with those from participants with limited-to-no prior VR experience, thus further highlighting the usefulness of the proposed technology not only for experienced users but also for users from different skills and background.

This research has the potential to revolutionize the way built environments are managed and interacted with, where facility managers can monitor, assess and visualize thermal comfort in real-time as well as interact with the HVAC systems and control multimodal IoT devices in the real-world from a distance through virtual facility models. The proposed framework’s ability to provide dynamic and continuously updated assessments of thermal conditions in real-time positions it as a valuable tool for prompt adjustments to optimize occupants’ comfort levels. Ultimately, the proposed framework provides an intuitive and immersive platform to manage thermal comfort, thus promoting healthier, more productive and eco-friendly indoor environments.

Although trust is generally taken as a fundamental factor in influencing relational behavior in contractor–subcontractor collaboration, the determination of an optimal level of trust is still lacking. Trust with an optimal tipping point that matches dependence best is considered the optimal trust to improve relational behavior between general contractors and subcontractors. To fill the knowledge gap, this study explores how combinations of trust and dependence trigger relational behavior between general contractors and subcontractors through a configurational approach.

Questionnaires were administered to 228 middle management and technical staff members of the general contractor. The data were analyzed using fuzzy-set qualitative comparative analysis (fsQCA), and the inductive analytic method allowed researchers to explore configurations of different dimensions and levels of dependence and trust.

Necessity analysis results indicated that neither dependence nor trust was a necessary condition for facilitating relational behavior. Through sufficiency analysis, four configurations of optimal trust matched with dependence were identified in contractor–subcontractor collaboration. Even if contractors rely only on subcontractors for resources, the optimal trust between contractors and subcontractors should include both institution- and cognition-based trust. In the event that contractor–subcontractor collaboration involves relational dependence, both affect- and cognition-based trust are necessary for the optimal trust.

This study enhances existing research by delving deeper into a nuanced understanding of optimal trust in dependence scenarios, and enriches project governance theory by uncovering the internal transmission of relational governance. Practically, this study offers general contractors guidance on how to establish optimal trust strategies based on the dual dependence level with subcontractors, which can facilitate subcontractors' relational behavior, and ultimately improve contractor–subcontractor collaboration performance.

Based on dual information asymmetry, the two-stage segmented compensation mechanism for technological innovation of civilian enterprises’ participation in military (CEPIM) has been discussed.

On the basis of the traditional principal-agent problems, the incentive compatibility condition is introduced as well as the hybrid incentive compensation model is established, to solve optimal solution of the compensation parameters under the dynamic contract condition and the validity is verified by numerical simulation.

The results show that: (1) The two-stage segmented compensation mechanism has the functions of “self-selection” and “stimulus to the strong”, (2) It promotes the civilian enterprises to obtain more innovation benefit compensation through the second stage, (3) There is an inverted U-shaped relationship between government compensation effectiveness and the innovation ability of compensation objects and (4) The “compensable threshold” and “optimal compensation threshold” should be set, respectively, to assess the applicability and priority of compensation.

In this paper, through numerical simulation, the optimal solution for two-stage segmented compensation, segmented compensation coefficient, expected returns for all parties and excess expected returns have been verified under various information asymmetry. The results show that the mechanism of two-stage segmented compensation can improve the expected returns for both civilian enterprises and the government. However, under dual information asymmetry, for innovation ability of the intended compensation candidates, a “compensation threshold” should be set to determine whether the compensation should be carried out, furthermore an “optimal compensation threshold” should be set to determine the compensation priority.

This paper introduces a formal risk interdependency framework to model cascading effects in collaborative systems. By characterizing risk causal chains and propagation chains, the framework aims to provide decision-makers with a structured tool to systematically identify, analyze, and prevent cascading risks in interconnected networks.

The framework, named the danger-risk-consequence chain, defines core components – danger, stake, risk, condition, and consequence – alongside their causal and propagation relationships, which form the basis for risk characterization. The framework is applied through a use case in the construction supply chain to demonstrate its capacity to model cascading risks.

The framework uncovers risk propagation chains that lead to cascading effects and formalizes the state evolution of these effects within collaborative systems. Through the use case, it demonstrates practical value by enabling stakeholders to visualize interrelated risks, detect vulnerabilities early, and implement targeted mitigation measures to enhance resilience against cascading disruptions.

This study presents a novel approach to modeling cascading effects by integrating risk causality and propagation into a formalized framework. In contrast to previous research, which offers static risk definitions for risk characterization, this framework contributes to risk management theory by providing a structured method for understanding and modeling interdependencies.

Although researchers have long recognized the importance of participating organizations’ (POs) relational behavior for mega construction projects (MCPs) performance, relational behavior may not be executed by POs without effective leadership from project owners. However, little is known about the mechanisms linking owners’ leadership styles to POs’ relational behavior. This study draws on full range leadership theory and role theory to examine the relationships between owners’ leadership styles (i.e. transformational and transactional) and relational behavior. POs’ role orientations (i.e. normative and economic) are considered as potential mediators.

Data were collected from 175 managers deeply involved in MCPs. Hierarchical regression model and bootstrapping methods were performed on the data to examine the direct effects of owners’ leadership on POs’ relational behavior and the mediating effects of POs’ role orientations.

The results revealed that both owners’ transformational and transactional leadership positively affect POs’ relational behavior, despite the former being higher than the latter, and indirectly influence relational behavior via POs’ normative and economic role orientation, respectively.

This study provides a clear picture of how owners’ leadership can motivate POs’ relational behavior to achieve high-quality inter-organizational relationships in MCPs. The findings can guide owners’ top manager selection by prioritizing those with transformational leadership, which is beneficial to achieving high-level relational behavior of POs. The results also imply that owners should pay greater attention to cultivating POs’ normative role orientation by encouraging teamwork and open communication to enhance their implementation of relational behavior.

Unlike previous research focusing more on intra-organizational leader–follower relationship within one PO, this study is one of the first to empirically confirm owners’ leadership as a critical antecedent of POs’ relational behavior, thus enhancing the theoretical understanding of inter-organizational relationship management in MCPs. Based on role theory, this study considers a novel organizational psychology mechanism, i.e. POs’ role orientations, as the mediator to unravel how owners’ leadership affects POs’ relational behavior, which was rarely invoked in MCP leadership literature.

The contractors’ consummate performance behavior is the key to achieving the project’s value added, but existing research has paid little attention to how to stimulate this behavior. Based on contractual functions and regulatory focus theory, this study examined how the allocation of contractual functions and the contractors’ regulatory focus affect their consummate performance behaviors. At the same time, considering the important position of guanxi between owner and contractor, this study also examined the moderating effect of guanxi on the relationship between the contractors’ regulatory focus and consummate performance behaviors.

This study first constructs a conceptual model that incorporates contractual functions (control, coordination and adaptation), contractors’ regulatory focus (promotion focus, prevention focus) and the effect of guanxi on contractors’ consummate performance behavior. Next, partial least squares structural equation modeling is used to analyze the survey data of 297 Chinese construction project professionals.

This study has the following four findings. First, contractual control has a negative effect on contractors’ promotion focus but a positive effect on their prevention focus. Contractual coordination and adaptation have a positive effect on contractors’ promotion focus but a negative effect on their prevention focus. Second, contractors’ promotion focus has a positive effect on their consummate performance behaviors, while their prevention focus has a negative effect on such behaviors. Third, both of contractors’ promotion focus and prevention focus play a mediating role in the relationship between contractual functions and their consummate performance behaviors. Finally, guanxi plays a moderating role in the relationship between contractors’ regulatory focus and their consummate performance behaviors.

Theoretically, this study enriches the research on the antecedents of contractors’ regulatory focus and extends the literature on contractual and guanxi management in construction projects. In practice, this study can provide guidance for improving contractors’ consummate performance behaviors and reasonable allocation of contractual functions.

The rapid development and widespread application of artificial intelligence tools have raised concerns about how designers are embracing these technologies. This study investigates the factors influencing designers' behavioral intention to use and disclose the use of generative artificial intelligence.

A quantitative research approach was employed, designing a structured questionnaire based on Self-Determination Theory to assess the impact of various psychological and social dimensions. The questionnaire included dimensions such as autonomy, competence, relatedness, social influence, value fit and social innovativeness. A Partial Least Squares Structural Equation Modeling analysis was conducted on 309 valid responses from diverse design fields.

Competence and relatedness are significant factors influencing designers' continuance intention to use generative artificial intelligence. Although autonomy does not significantly affect continuance intention, it plays a crucial role in the decision to disclose artificial intelligence participation. Social influence and value fit significantly shape autonomy, competence and relatedness, while the impact of social innovativeness is relatively limited.

This study clarifies the factors influencing designers' continuance intention and disclosure of generative artificial intelligence tools from both individual and social dimensions, enhancing the understanding of the relationship between designers and generative artificial intelligence tools. It provides valuable insights for the development of artificial intelligence technology and the future trends in the design industry, offering significant theoretical and practical value.

Relationship conflict between the owners and contractors is inevitable, which could induce negative consequences. Yet, the existing literature mostly focused on its direct effects on project performance and ignored the process by which relationship conflict gradually deteriorates cooperation as well as corresponding managerial approaches. Given the fact that relationship conflict originates from interdependent tasks, the proposed theoretical model is intended to measure relational behavior as an instant outcome of relationship conflict, and explore the buffering role of contract enforcement approach.

This paper develops the conceptual model based on the literature review. Then the questionnaire survey was conducted. The dyadic data obtained from 168 Chinese construction project professionals were analyzed by the Partial Least squares Structural Equation Modeling (PLS-SEM) technique.

The results show that relational behavior partially mediates the link between relationship conflict and project performance. Besides, three types of contract enforcement approaches are found to differentially change the negative link between relationship conflict and relational behavior. Rigid contract enforcement can worsen the adverse effects of relationship conflict on relational behavior, whereas flexible contract enforcement can alleviate these negative effects. The level of mitigation hinges on whether compromising behaviors or obliging behaviors are chosen.

The study extends the knowledge of conflict theory and contract theory in the construction field. Based on the proposed conceptual model and PLS-SEM results, this study contributes to the understanding of relationship conflict’s consequences between the owners and contractors and enriches conflict management approaches in the construction field.

This paper aims to understand the scholarly contributions to mobile advertising by analyzing the publishing trend from 2001 to 2022 from the documents indexed in the Scopus database.

A total of 348 documents were selected for analysis published between 2001 and 2022. The garnered data was examined using a bibliometric domain mapping analysis technique using computer-aided software R and VOSviewer and manually exploring the articles.

The results of this study discover the most prolific authors in the mobile advertising domain and other seminal works carried out by productive researchers in the field of mobile advertising. The journals in which most instrumental research studies have been published are also identified. Moreover, the co-citation, bibliometric coupling and co-occurrence analysis of literature are also carried out to draw themes concerning mobile advertising research that have been identified and categorized.

This research analyzed a singular, exclusive database, “Scopus,” which limited the sectoral scope of publications. Since the present research uses bibliometric analysis, these studies cannot conduct sentiment analysis of the chosen studies.

Marketing professionals looking after technological advancements may use this study to understand the broad scope of mobile advertising applicability across diverse domains and discuss the trade-offs that may address significant bottlenecks in mobile advertising applications.

To the best of the authors’ knowledge, this paper is one of the latest attempts in recent times to understand the research work in mobile advertising using a bibliometric domain analysis approach.