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The successful implementation of hospital projects (HPs) tends to confront sundry challenges in the planning and construction (P&C) phases due to their complexity and particularity. Employing key performance indicators (KPIs) facilitates the monitoring of HPs to advance their successful delivery. This study aims to comprehensively investigate the KPIs for hospital planning and construction (HPC).

The KPIs for HPC were identified through a systematic review. Then a comprehensive assessment of these KPIs was performed utilizing a meta-analysis method. In this process, basic statistical analysis, subgroup analysis, sensitive analysis and publication bias analysis were performed.

Results indicate that all 27 KPIs identified from the literature are significant for executing HPs in P&C phases. Also, some unconventional performance indicators are crucial for implementing HPs, such as “Project monitoring effectiveness” and “Industry innovation and synergy,” as their high significance is reflected in this study. Despite the fact that the findings of meta-analysis are more trustworthy than those of individual studies, a high heterogeneity still exists in the findings. It highlights the inherent uncertainty in the construction industry. Hence, this study applied subgroup analysis to explore the underlying factors causing the high level of heterogeneity and used sensitive analysis to assess the robustness of the findings.

There is no consensus among the prior studies on KPIs for HPC specifically and their degree of significance. Additionally, few reviews in this field have focused on the reliability of the results. This study comprehensively assesses the KPIs for HPC and explores the variability and robustness of the results, which provides a multi-dimensional perspective for practitioners and the research community to investigate the performance of HPs during the P&C stages.

Practitioners have reported a minimal and non-use of building information modelling (BIM), especially in small and medium-sized organisations and BIM infant construction industries. This development calls for a reappraisal of organisations’ strength in capabilities required for BIM uptake towards the target of global construction digitalisation. This study aims to assess the BIM Level 2 uptake capability of organisations in a BIM infant construction industry and identify the underlying interactions between the capability criteria.

The study used a multivariable analysis of fifteen descriptors identified from the people, process, policy, finance and technology domain. Data collection was done in the BIM infant construction industry in Nigeria. Verification of the descriptors and an evaluation of BIM uptake capability in organisations was done. Seventy-three responses were received within the selected context, and data analysis was done with mean weighting and exploratory factor analysis. Maximum Likelihood extraction and Direct Oblimin rotation were used.

Factor analysis revealed three factors that explained 53.28% of the total variance in the BIM Level 2 uptake capability of construction organisations. The factors are workforce capacity and continuous development, an affinity for innovation and strength in physical and operational facilities.

This study provides an overarching and insightful discussion on BIM uptake capability and construction digitalisation with evidence from a BIM-infant construction industry.

The findings of this study are a piece of valuable empirical evidence on Level 2 BIM uptake capability. This empirical situation analysis will inform the advocacy for the advancement of BIM and enhanced utilisation of building information. Evidence on the capability performance of the BIM infant industry has been revealed.

The outcome is expected to stir debate on the preparedness of organisations to further exploit the benefits of BIM in the BIM infant construction industry. Examination of the capability for a particular phase of BIM is scanty in the literature.

Although research on job insecurity (JI) and its relationship with employee performance has increased in recent years, results are mixed and inconclusive. The objectives of this paper are to explore 1) the conceptualizations of JI, 2) the relationship between JI and different performance dimensions, 3) the theoretical perspectives used to explain the JI–performance relationship and 4) the mechanisms and contextual boundaries that affect the JI–performance relationship.

Following the PRISMA guidelines, the authors systematically searched for peer-reviewed empirical studies published before July 2021 in Web of Science and Scopus. The authors analyzed 81 empirical studies published on the conceptualization of job insecurity, its relationship with employee performance, and what mechanisms and contingency factors are studied. The authors used thematic analysis to analyze the articles.

Results of this review show that the quantitative cognitive dimension is dominant in extant JI literature. Furthermore, in-role performance and OCB were most often investigated in relation to the four dimensions of job insecurity, drawing from a range of theoretical perspectives to explain this relationship. Moreover, a variety of mechanisms and contextual factors on individual, individual work-related, individual-level attitudes and job-level characteristics have found to play a role in this relationship.

This study has a number of limitations. The first pertains to the exclusion of articles in languages other than English and non-peer reviewed papers. It is possible that the search strategy used may not have identified other studies that may have met the established criteria in order to be included in our research. However, this method was chosen to guarantee the quality of the included articles in this study and in line with previous meta-analyses and literature reviews (De Witte et al., 2016; Sverke et al., 2019). Second, one selection criteria focused on how performance was assessed in the studies incorporated in this literature review. The authors excluded studies that addressed performance from the perspective of the organization (i.e. studies that measured performance at the organizational level). The authors herewith might have excluded studies that focused on one or multiple job insecurity constructs, but the authors herewith included studies that were comparable in terms of performance indicator outcomes. Future studies could expand the search by investigating, as a next step, the impact on organizational performance. Finally, since the focus of this literature review was on the relationship between job insecurity and performance indicators, including the mechanisms and boundary conditions that affect this relationship, the authors did not include focus on how job insecurity can be influenced (Shoss, 2017), and herewith lack information on the predictors side of job insecurity. However, by narrowing the authors focus to mediators and moderators, the authors were able to come up with an extensive list of factors that impact the job insecurity–performance relationship and herewith provide fruitful areas for future research. Future studies could expand these findings by providing an overview of predictors of different job insecurity constructs, to see whether there are potential different predictors of job insecurity conceptualizations (Jiang and Lavaysse, 2018).

The study review contributes to the systematization of the current empirical evidence on this area of research. This is especially important and enables room to take an additional step toward understanding the consequences of job insecurity on performance. Specifically, it is important for organizations and policymakers to be aware of the different conceptualizations of job insecurity that exist and how they impact employee performance. In addition, an overview of potential mechanisms and boundary conditions that affect this relationship provides insights as to how organizations can intervene to affect reactions to job insecurity.

The study findings are relevant and may be of interest to decision makers in organizations and national authorities that must have information on quality concerning the effects of job insecurity on performance.

Based on these findings the authors show the impact of the different conceptualizations of job insecurity and how they affect job performance. In addition, the authors provide recommendations for future studies how to better handle the integration of different conceptualizations and measures of job insecurity and its different approaches.

The purpose of this study is to analyse Benidorm, San Sebastián, Gijón, Málaga, Tenerife Island and Santander smart tourist destinations (STDs) as a touristic model and example to follow by other destinations in Spain and all over the world.

To fulfil the stated objective, this study follows several phases that introduce and classify a set of measures implemented by the six Spanish smart destinations to be designed as a STD.

Findings suggest that being a STD requires a high cost, and this is only accessible to big destinations with enough resources. Of the 50 Spanish provinces, eight are STDs, and these are localised in coastal areas. Obviously, this challenge is not within the reach of any Spanish city. Moreover, findings of the current study prove that the six Spanish smart destinations have a good air accessibility through their six airports, but the accessibility in a STD is not just physical; this must provide digital accessibility to tourists through destination marketing organisation’s website and app that will supply them with information on a wide range of services, including accommodations, tourist attractions, restaurants, public transport, museums and monuments’ locations, amongst many others.

From a resident point of view, a STD cannot be only focused on a technological and tourism context; a STD also requires knowing and meeting the needs of local residents and having a voice in decision-making processes. Hence, this study shows a new perspective on STDs that will benefit the literature on STDs.

Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.

This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.

Four domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.

This paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

This article presents a novel case study that analyzes the applicability of DoE in the curling sport in order to improve their own performance and the performance of its athletes. Specifically, this study analyzes the most important factors to increase accuracy and precision in the draw game with curlers' opinions. It was decided to use the “Last Stone Draw (LSD)’ as an appropriate play situation.

Specifically, this study analyzes most important factors to increase accuracy and precision in the draw game with curlers opinions from the German Curling association. Three research techniques were used in this study: case study, interviews and a well-designed experiment. The analysis through the use of DoE includes a measurement system analysis, an initial variance test between two players, a screening and a characterization experiment.

The results obtained from DoE suggest that the factors routine, stress, release, balance, and the previous play situation have a substantial impact on the score of the player's draw game. However, no factor has a statistically significant impact on the average distance to the center of the target. Moreover, the DoE analysis also concludes that the accuracy and precision of the player's performance is not affected equally by all analyzed factors, but they turn into highly significant when examining their relationship to the other factors.

The findings of this study can be beneficial to other sports events in improving the performance. Moreover, DoE has proved to be an invaluable tool for many people in the German Curling Association in understanding the factors which influence the curlers performance and also factors which do not affect the curlers performance.

This research attempts to contribute to the existing sports management literature by identifying a way in which DoE can be an effective tool in non-manufacturing settings for identification of most important factors which influence the curling performance.

This study aims to explore the effect of digitalization on the promotion of enterprise R&D cooperation, and it analyzes the microimpact mechanism and boundary conditions of enterprise digitalization on enterprise R&D cooperation.

Based on survey data sourced from the World Bank Enterprise Surveys of the business environment of Chinese enterprises in 2012, this study applies multiple regression methods to test theoretical hypotheses.

Enterprise digitalization positively affects the breadth and intensity of enterprise R&D cooperation. Employees’ digital literacy plays an intermediary role between enterprise digitalization and enterprise R&D cooperation. The subordinate attributes of enterprises weaken the positive relationship between enterprise digitalization and the breadth and intensity of enterprise R&D cooperation. The shareholding of state-owned enterprises reinforces the positive relationship between digitalization and the intensity of enterprise R&D cooperation. However, such shareholding shows no significant regulatory effect on digitalization and the breadth of enterprise R&D cooperation.

Focusing on the digital transformation of the enterprise, this study discusses its impact mechanism on enterprise R&D cooperation, including the impact on the intensity and breadth of R&D cooperation. The study further examines the regulatory effect of organizational inertia on enterprise digital and R&D cooperation from two aspects: resource rigidity and routine rigidity. It emphasizes the significance of the digital literacy of employees in enterprise digitalization and discusses the micromechanism of enterprise digitalization and enterprise R&D cooperation.

The construction industry has been traditionally referred to as slow when it comes to technological transformation. This study aims to investigate and present a scorecard of the construction industry in the past decade, the paper adopted Bibliometrics. The study identified the various digital transformation (DT) aspects in the construction industry and future research directions are also identified.

To achieve the aim of this research, an inductive approach was adopted through a grounded theory strategy. Secondary data was retrieved from the Scopus database and analysed using Biblioshiny and VOSviewer. The data was retrieved through specific keywords related to the study focus.

The study also proposed a balanced flow model for DT discussion in the construction industry. DT in the construction industry disrupts every aspect of the industry, albeit at different rates due to the existing barriers; hence, the study identified areas that require further research. It, thus, provides a theoretical and practical basis for researchers and practitioners alike.

The study reviewed the DT research discuss in the construction industry. It is worthy of note that this is the first study that analyses the DT of the construction industry in the past decade.

Building Information Modeling (BIM) capabilities have been studied at the individual, project, organizational, and even industry levels to ensure the realization of BIM value in the architectural, engineering, construction, and operation industry. However, limited research has focused on a project owner organization perspective to investigate owner BIM capabilities that are required to ensure effective project management and delivery. This present study aims to propose an indicator framework to evaluate owner BIM capabilities at the organizational level.

Leveraging the existing literature on BIM capabilities and synthesizing insights from the resource-based view and information technology capabilities research, this study conceptualizes the BIM capabilities of project owner organizations and offers a framework of indicators for measurement. Semi-structured interviews with BIM experts and a questionnaire survey were conducted to identify key indicators affecting owner BIM capabilities. A six-dimensional structural equation model with 29 indicators was then established.

The findings highlight the multidimensionality of owner BIM capabilities and show that process capabilities play a crucial role in enhancing owner BIM capabilities, while technical capabilities are considered as the least important aspect.

The study sheds light on the key role of project owner organizations in ensuring BIM value and suggests that project owners focus more on the organizational processes of introducing BIM in managing projects.

This study reconceptualizes owner BIM capabilities drawing on the idea of resource-based view and information technology capabilities and highlights the important dimensions and indicators of owner BIM capabilities at the organizational level.

This chapter conceptualises a link between Industrial Revolution 4.0 (IR 4.0), big data, data science and sustainable tourism.

The author adopts a grounded theory and conceptual approach to endeavour in this exploratory research.

The outcome shows a significant rise of big data in the tourism sector under three major dimensions, i.e. business, governance and research. And, some exemplary evidence of institutions promoting the use of big data and data science for sustainable tourism has been discussed.

The conceptualised interlinkage of concepts like IR 4.0, big data, data science and sustainable development provides a valuable knowledge resource to policy-makers, researchers, businesses and students.