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Citizen engagement can promote value creation in urban development projects. This potential stems from the granting of decision-making authority to citizens, labeled citizen enfranchisement in this study. Citizens are focal stakeholders of urban development projects and enfranchisement grants them an explicit say on such projects. Despite this potential for enhanced value creation, there remains limited understanding about how project organizations enfranchise stakeholders in the front end of urban development projects.

In this research, we designed a multiple-case study to analyze two novel citizen engagement processes in Northern-European cities. In these processes, citizens were enfranchised in ideating, designing, and making selections on urban development projects. We followed a multimethod approach to data collection. The collected datasets include document data, interview data and observation data.

Our findings demonstrated a distribution and redistribution of decision-making authority throughout the phases of the citizen engagement processes. Citizens’ voices were amplified throughout the project front end, although episodes of decision-making authority held by the cities took place periodically as well. By granting explicit decision-making authority to citizens, citizen enfranchisement facilitated a more democratic urban development process, promoting value creation.

In contrast to the earlier research, the findings of our study illustrate citizen engagement taking place at so-called higher levels of stakeholder engagement. In particular, our study reveals a granting of de facto decision-making authority to citizens, also known as citizen enfranchisement. These findings contribute to the earlier research on stakeholder engagement in projects, where the influence of stakeholder engagement has often been considered symbolic or limited.

The United Nations' Sustainable Development Goal of ensuring healthy lives and promoting well-being for people of all ages underscores the vital role of public healthcare facilities (PHFs) in delivering essential healthcare services. However, these facilities often suffer from inadequate maintenance, exacerbated by the insufficient implementation of maintenance strategies. Recognizing the importance of PHFs in enhancing healthcare services, this paper investigates the Critical Success Factors (CSFs) in the maintenance strategies of PHFs in South Africa.

Through semi-structured interviews with nineteen purposively selected maintenance personnel from the Limpopo Department of Health (DoH), this study identified and analyzed the CSFs to enhance maintenance operations in PHFs. Thematic content analysis was employed to derive key insights from the collected data.

The study's findings highlight adequate maintenance planning and effective leadership as the two overarching CSFs in the maintenance of PHFs. These factors play a pivotal role in addressing challenges that hinder the current maintenance team from meeting maintenance requirements to the satisfaction of both staff and patients within PHFs.

The study offers valuable insights for policymakers to improve the effectiveness of maintenance operations in PHFs. By addressing the identified CSFs, policymakers can enhance maintenance operations in PHFs, positively impacting healthcare service delivery and the well-being of both staff and patients.

This study aims to develop and apply a process model for prioritizing and selecting basic research projects in developing countries.

Basic research is mainly funded by governments and since, unlike technological research, it does not have clear business goals, its prioritization is one of the complicated issues in formulating science and technology policy. Adopting a design science research methodology, the authors chose a general framework for project portfolio selection as an appropriate artifact for solving this problem. By customizing it for two specific features of this study, i.e. national scale of the problem and the basic nature of research proposals, the authors developed the proposed framework for solving the problem of priority setting.

The process for selecting basic research proposals consists of several steps, which can be categorized into eight steps including strategic decisions, preparation, pre-screening, evaluating individual proposals, screening, portfolio selection and monitoring. This study emphasizes the necessity of defining goals that can be evaluated for the national basic research portfolio, as a key strategic decision. Evaluating individual proposals is a peer-review-based process. In contrast, portfolio selection is done through a zero-one linear programming model. The validity of the proposed framework has been confirmed based on the data obtained from the Iran National Science Foundation.

To the best of the authors’ knowledge, in this research, for the first time, a mathematical model for prioritizing basic research at the national level has been presented, which effectively contributes to policymaking regarding the development of an optimum national research portfolio.

The purpose of this study is to examine the role of social presence in enhancing positive behaviors in the virtual reality (VR)-based wine tourism context through an innovative approach.

Two sequential experimental studies were conducted to test proposed hypotheses using Web and head-mounted display (HMD) VR formats. Specifically, Study 1 probed the influence of social presence on mental imagery, which subsequently impacted destination visit intention, drinking intent and memorable experience. Study 2 used a field experiment to explore the boundary effects of environmental cues (nature versus social) on social presence and a series of behavioral intentions using an HMD format.

The findings represent one of the first efforts to unravel the influence of social presence on positive behaviors through mental imagery and the moderating role of environmental cues.

This research enhances the understanding of wine tourism, drawing upon social presence theory and stimulus-organism-response framework.

The outcomes provide valuable insights for wine tourism marketers in developing innovative marketing strategies by addressing the usage of social presence and environmental cues in a VR setting.

To the best of the authors’ knowledge, this study is the first to enrich the existing knowledge of wine tourism by exploring the role of social presence and environmental cues in both Web and HMD VR formats.

Short-term rentals (STRs) (like Airbnb) are reshaping social behaviour, notably in gastronomy, altering how people dine while travelling. This study delves into revenue management, examining the impact of seasonality and dining options near guests’ Airbnb. Machine Learning analysis of Airbnb data suggests owners enhance revenue strategies by adjusting prices seasonally, taking nearby food amenities into account.

This study analysed 220 Airbnb establishments from Madrid, Spain, using consistent monthly price data from Seetransparent and environment variables from MapInfo GIS. The Machine Learning algorithm calculated average prices, determined seasonal prices, applied factor analysis to categorise months and used cluster analysis to identify tourism-dwelling typologies with similar seasonal behaviour, considering nearby supermarkets/restaurants by factors such as proximity and availability of food options.

The findings reveal seasonal variations in three groups, using Machine Learning to improve revenue management: Group 1 has strong autumn-winter patterns and fewer restaurants; Group 2 shows higher spring seasonality, likely catering to tourists, and has more restaurants, while Group 3 has year-round stability, fewer supermarkets and active shops, potentially affecting local restaurant dynamics. Food establishments in these groups may need to adapt their strategies accordingly to capitalise on these seasonal trends.

Current literature lacks information on how seasonality, rental housing and proximity to amenities are interconnected. The originality of this study is to fill this gap by enhancing the STR price predictive model through a Machine Learning study. By examining seasonal trends, rental housing dynamics, and the proximity of supermarkets and restaurants to STR properties, the research enhances our understanding and predictions of STR price fluctuations, particularly in relation to the availability and demand for food options.

This study aims to develop an overall project success (OPS) model by investigating the mediation impact of value management (VM) implementation between VM critical success factors (CSFs) and OPS as well as the moderation impact of VM CSFs between VM implementation and OPS.

In total, 335 structured questionnaires were administered to relevant stakeholders in the study area. The research used a partial least square structural equation modeling (PLS-SEM) to model the relationship among VM implementation, CSFs and OPS.

The results revealed that there is an indirect positive and significant correlation among the variables. The model prediction analysis also significantly impacted with 59.9% on OPS by setting VM implementation as a mediator variable and 61% by setting VM CSFs as a moderation variable.

This research work will serve as a guide or benchmark for decision-makers who want to use VM to improve the success of their building projects.

This study fills the knowledge gap by identifying and emphasizing the impact of VM CSFs and activities on OPS.

Project bundling is an innovative practice that groups or bundles several infrastructure projects into a single contract. While project bundling has various benefits, agencies are facing some challenges when bundling their projects, including properly assessing the feasibility (or infeasibility) of project delivery methods (PDMs) of interest. More specifically, project owners face the challenge of properly selecting between traditional and alternative PDMs for their bundled projects. Although some research efforts were devoted to providing guidelines in relation to different aspects related to project bundling, no previous study was conducted to help project owners performing PDMs-related feasibility analysis for bundled projects, which differ from normal, singly delivered projects. To fill this knowledge gap, this paper develops a decision-support tool that assists agencies in deciding whether they should select a traditional or alternative PDM (i.e. whether to go with the Design-Bid-Build (DBB) PDM or not) for their bundled projects.

An analytical methodology comprised of four main steps was followed in this paper. First, an expert survey was developed and distributed to industry experts to quantify the importance of 25 project bundling objectives. Second, principal component analysis was used to determine the weights for the different project bundling objectives. Third, a series of statistical tests was implemented to identify different feasibility tiers. Fourth, a user-friendly decision-support tool was developed, and its capabilities were demonstrated.

The results showed that six tiers exist to classify the feasibility (or infeasibility) of traditional PDMs (i.e. the DBB method) for bundled projects. The research outcomes have also reflected that the following five project bundling objectives contribute the most to making traditional PDMs (i.e. the DBB method) more feasible for bundled projects: (1) Having well-defined design features; (2) Requiring prior knowledge or experience with similar project size and scope; (3) Completing the overall project on schedule; (4) Keeping rate of expenditures within cash flow plan; and (5) Acquiring specific legislative, regulatory and jurisdictional requirements early on.

This research adds to the body of knowledge by equipping agencies and project owners with a decision-support system that helps them identify whether traditional or alternative PDMs are more appropriate for the specific objectives of their bundling program(s). By making the right PDM decision, project owners can enhance their bundling practices (especially in relation to the PDM proper selection) and ultimately the performance of their bundled projects.

This study aims to systematically examine 69 secondary studies to understand trends and implications in sustainability in higher education (SHE), addressing gaps in secondary studies, which often lack comprehensive thematic overviews that hinder future directions.

This tertiary study uses meticulous thematic coding to unveil overarching themes and future research directions across seven SHE areas: institutional frameworks, campus operations, education, research, outreach and collaborations, campus experiences and assessment and reporting.

The analysis reveals challenges higher education institutions (HEIs) face in integrating sustainability, highlighting the need for a holistic approach. Barriers such as awareness deficits and resistance to change emphasize the importance of interdisciplinary research. Emphasizing holistic integration and innovation is vital for seamlessly embedding sustainability within HEIs.

Key future research themes include holistic approaches to sustainability integration, leadership for sustainable change and innovative pedagogical approaches. Additionally, it is important to explore transdisciplinary approaches in sustainability research and the role of research centers and funding in addressing sustainability challenges.

This study provides a comprehensive overview of SHE, offering insights for researchers and practitioners, and serves as a resource for advancing sustainable educational practices.

This chapter discusses how the real options theory can be useful for understanding the adoption of human resources management (HRM) practices. The authors review how the real options theory has provided insights into the processes through which firms manage uncertainties involved in the adoption of HRM practices. The authors offer propositions for future HRM research from the real options perspective. The authors contend that analyzing HRM practice adoptions through the lens of real options theory can enhance our understanding of the mechanisms through which firms choose which HRM practices to adopt and how they adjust the timing, scale, and methods of investment in these practices. Specifically, the authors suggest that differences in information relevant to valuation of HRM options are the source of distinct choices of HRM options across firms. Finally, the authors propose advancing knowledge on HRM practice adoptions by using a portfolio of options approach, as well as considering factors like competitors, path dependence, and switching options.

The accuracy of budgeting is important to fulfilling its various roles. The aim of this study is to examine perceptions of budgeting accuracy in UK universities and to identify and understand the factors that influence them.

A mixed methods research design comprising a questionnaire survey (84 responses, = 51.5%) and 42 semi-structured, qualitative interviews is employed.

The findings reveal that universities tend to be conservative in their budgeting, although previous financial difficulties, the attitude of the governing body and the need to convince lenders that finances are being managed competently might lead to a greater emphasis on a “realistic” rather than cautious budget. Stepwise multiple regression identified four significantly negative influences on perceived budgeting accuracy: the difficulty of forecasting student numbers; difficulties associated with allowing unspent balances to be carried forward; taking a relatively long time to prepare the budget; and the institution’s level of financial surplus. The interviews are drawn upon to both explain and elaborate on the statistical findings. Forecasting student numbers and associated fee income emerges as a particularly challenging and complex issue.

Our regression analysis is cross-sectional and therefore based on correlations. Furthermore, the research could be developed by investigating the views of other parties as well as repeating the study in both the UK and overseas.

Implications for university management follow from the four factors identified as significant influences upon budget accuracy. These include involving the finance department in estimating student numbers, removing or controlling the carry forward of unspent funds, and reducing the length of the budget cycle.

The first study to examine the factors that influence the perceived accuracy of universities’ budgeting, this paper also advances understanding of budgeting accuracy more generally.