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There is a limited number of research work on critical success factors (CSFs) in public construction projects in Saudi Arabia. In response to this knowledge gap, the objective of this paper is to assess the impact of CSFs on the government construction projects in Saudi Arabia. The success factors are investigated from a broader consideration of failure criteria, from consideration of most effectiveness in successful project completion and also from consideration of the impact of implementing control processes for successful project completion.

This study has analysed the impact of success factors on construction projects in Saudi Arabia using a descriptive methodology. An exhaustive literature survey is undertaken to identify the success and failure factors related to government construction projects in Saudi Arabia. The survey data are sorted out and analysed by cost, schedule, technical, context and finance dimensions of the projects based on project types, engineering complexity, size, modality, jurisdictional control and funding approach. To evaluate the influence of success factors implementation, qualitative data were collected in a survey via a web-based questionnaire that was sent to officials working and occupying a responsible position in national project guidelines organizations and in government construction organizations in Saudi Arabia. In all, 28 CSFs were identified, ranked and evaluated for their impact on project success. The four identified factors belong to process categories of construction projects, nine factors belong to management of construction projects and 15 success factors are identified for impact assessment of implementation in construction projects.

The study's findings have identified and ranked the top five CSFs that significantly influence project outcomes, including meeting time targets, adhering to financial budgets, delivering desired outcomes for all stakeholders, effectively managing risks and assembling the appropriate team while optimizing resource allocation. Additionally, the research indicates that hindrances to projects primarily stem from execution, economic, human and political factors. The study advocates for strict controls over incomplete engineering designs and advises against contractors independently handling design work to ensure project success. Additionally, addressing contractors' qualifications and financial matters is crucial for project success. By highlighting these CSFs and challenges, the research provides actionable insights to enhance project management practices in the construction industry.

This study is limited to the infrastructure projects constructed by governmental bodies with the participation of officials from government organizations. Further study, including private projects and officials working on private projects, may be needed to generalized the research outcome.

Numerous studies have investigated CSFs in construction projects, but few have examined their relevance to Saudi Arabian government projects. This study aims to fill this gap by identifying key CSFs specific to Saudi Arabian public sector construction projects and assessing their impact on project success. It advocates for stringent controls in the Saudi Arabian construction sector, emphasizing the importance of preventing incomplete or altered engineering designs by contractors to increase the success rate of public sector projects. This research offers practical insights to stakeholders, advancing project management practices in Saudi Arabia's construction sector for improved outcomes and resource utilization.

Infrastructure forms a basis for the operations and sustainability of the modern society. This paper aims to recognize value creation from the infrastructure procurement ecosystem perspective to achieve those goals. The pursuit of enhancing value creation involves an examination of infrastructure procurement challenges, boundaries as well as boundary spanners that facilitate effective knowledge transfer and interaction.

The qualitative study is based on content analysis of 25 thematic interviews. Data was transcribed and coded via Atlas.ti software.

Infrastructure procurement value creation challenges appear complex and related to boundaries that hamper collaboration, coordination and knowledge sharing. Our results show that these boundaries locate within and between different levels of procurement ecosystem. Therefore, value creation in infrastructure procurement requires boundary spanners for leveraging knowledge sharing and interaction. Artifacts, discussion, processes and brokers as identified boundary spanners are strongly nested and interrelated in the industry. Special attention should be given to supporting individuals to act as brokers, since they play the key roles in trust building, culture steering and usage of other boundary spanners.

Promoting value creation in infrastructure procurement helps to achieve socio-economic development goals.

This study offers a unique perspective on value creation in the context of infrastructure by adopting an ecosystem lens and examining boundary crossing mechanisms. The results support future development of collaboration and knowledge sharing practices fostering procurement productivity.

This study explores whether targeted microcredit can effectively alleviate households’ multidimensional relative poverty (MdRP) in rural China in the new era following the poverty elimination campaign and discusses it from a gendered perspective.

This study applies a fixed-effects model, propensity score matching (PSM) and two-stage instrumental variable method to two-period panel data collected from 611 households in rural western China in 2018 and 2021 to explore the effects, mechanisms and heterogenous performance of targeted microcredit on households’ MdRP in the new era.

(i) Targeted microcredit can alleviate MdRP among rural households in the new era, mainly by reducing income and opportunity inequality. (ii) Targeted microcredit can promote women’s empowerment, mainly by enhancing their social participation, thereby helping alleviate households’ MdRP. The effect of the targeted microcredit on MdRP is more significant in medium-educated women households and non-left-behind women households. (iii) The MdRP alleviation effect is stronger in villages with a high degree of digitalization.

Learn from the experience of targeted microcredit. Accurately identify poor groups and integrate loan design into financial health and women empowerment. Particularly, pay attention to less-educated and left-behind women households and strengthen coordination between targeted microcredit and digital village strategies.

This study clarifies the effect of targeted microcredit on women’s empowerment and households’ MdRP alleviation in the new era. It also explores its various effects on households with different female characteristics and regional digitalization levels, providing ideas for optimizing microcredit.

Our study centered on activity-based workspaces (ABWs), unassigned open-plan configurations where users’ activities determine the workplace. These workspaces are conceived and shaped by accommodation professionals (APs) like managers and architects and are loaded with their ideas, ideals, norms and values; therefore, they are normative and hegemonic. Previous research has largely failed to consider how APs’ spatial conceptions materialize in the workplace. To address this omission, we adopted a narrative approach to study APs’ impact during the conceptualization stage.

The data were collected via a 10-year at-home ethnographic study at a Dutch university, including observations, interviews, documents and reports. Studying the researchers’ organization allowed for a longitudinal research approach and participative observations. The data focused on the narrative techniques of APs when establishing an ABW.

In introducing ABWs, APs resorted to two principal narrative strategies. Firstly, the ABW concept was lauded as a solution to a host of existing problems. Yet, in the face of shortcomings, lecturers were often blamed.

Despite the considerable influence of APs on both the physical layout of workspaces and the nature of academic labor, there is little insight into their conceptions of the academic workspace. Our research contributes a novel perspective by revealing how APs’ workspace conceptions drive the narratives that underpin the roll-out of ABWs and how they construct narratives of success and failure.

This study aims to explore how sustainable business models (SBM) can be developed within agri-innovation systems (AIS) and emphasize an integration of the two with a systemic understanding for reducing food loss and value loss in postharvest agri-food supply chain.

This study conducted longitudinal qualitative research in a developing country with food loss challenges in the postharvest supply chain. This study collected data through multiple rounds of fieldwork, interviews and focus groups over four years. Thematic analysis and “sensemaking” were used for inductive data analysis to generate rich contextual knowledge by drawing upon the lived realities of the agri-food supply chain actors.

First, this study finds that the value losses are varied in the supply chain, encompassing production value, intrinsic value, extrinsic value, market value, institutional value and future food value. This happens through two cumulative effects including multiplier losses, where losses in one model cascade into others, amplifying their impact and stacking losses, where the absence of data stacks or infrastructure pools hampers the realisation of food value. Thereafter, this study proposes four strategies for moving from the loss-incurring current business model to a networked SBM for mitigating losses. This emphasises the need to redefine ownership as stewardship, enable formal and informal beneficiary identification, strengthen value addition and build capacities for empowering communities to benefit from networked SBM with AIS initiatives. Finally, this study puts forth ten propositions for future research in aligning AIS with networked SBM.

This study contributes to understanding the interplay between AIS and SBM; emphasising the integration of the two to effectively address food loss challenges in the early stages of agri-food supply chains. The identified strategies and research propositions provide implications for researchers and practitioners seeking to accelerate sustainable practices for reducing food loss and waste in agri-food supply chains.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

The energy performance gap (EPG) in building construction has been one of the major barriers to the realization of environmental and economic sustainability in the built environment. Although there have been a few studies addressing this issue, studying this topic with a special focus on the project delivery process has been almost overlooked. Hence, this study aims to address the EPG in building construction through the lens of collaborative and life cycle-based project delivery.

In order to realize the objective of this study, the development of a theoretical framework based on the literature review was followed by a qualitative study in which 21 semi-structured interviews were conducted with Finnish project professionals representing clients, design/planning experts, constructors and building operation/maintenance experts to explore their views on the topic under study.

The findings reveal the project delivery-related causes of EPG in building construction. Moreover, the obtained results present a collaborative and life cycle-based delivery model that integrates project and product (i.e. building) life cycles, and it is compatible with all types of contractual frameworks in building construction projects.

Although the findings of this study significantly contribute to theory and practice in the field of collaborative and sustainable construction project delivery, it is acknowledged that these findings are based on Finnish professionals’ input, and expanding this research to other regions is a potential area for further studies. Moreover, the developed model, although validated in Finland, needs to be tested in a broader context as well to gain wider generalizability.

The obtained results reveal the significance and impact of collaborative and life cycle-based project development and delivery on the realization of environmentally sustainable building construction.

Megaprojects stimulate and challenge public opinion across countries, generating extensive reactions from citizens. Given their ability to attract public attention, they may also influence public participation in collective choices and political decision-making. These issues are relevant for evaluating projects, but are unfortunately rarely discussed in the managerial literature. This study aims to open up a debate on social issues and how they could be taken into account within management studies.

This study carried out a systematic review of the literature on the social impact of megaprojects to identify different research areas related to the evaluation of megaprojects from a social perspective.

This study identified three different research areas related to the evaluation of megaprojects from a social perspective: the role of power and social issues; infrastructure and social space; and stakeholder engagement and endorsement.

This paper underlines the need to go beyond current understanding of the social impacts of megaprojects and calls for a more interdisciplinary research agenda.

This paper aims to challenge the view of Sweden’s climate leadership by problematizing its domestic climate adaptation governance and highlighting the need for a more holistic view of adaptation. The paper highlights aspects that are troublesome for not only the built environment along coastlines but also the future of Sweden’s standing as a climate leader. The paper concludes with recommendations addressing the key areas of climate adaptation fragmentation in Sweden and calls for a more holistic view of adaptation, and one that takes into account resources, collaboration and coherence of governance vision.

The paper is a comprehensive analysis of internal governance processes in climate change adaptation. It is based on an extensive literature review and semi-structured interviews at the local level – i.e. municipalities – who have the primary responsibility for adaptation to climate change in Sweden.

Findings point to three-fold concerns. First, there is a lack of clarity on roles and responsibilities in adaptation among municipalities, regions and governmental agencies. Second, the gap between available finance and actual needs for climate change adaptation presents a major challenge when channels and pathways are not clear either. Finally, some adaptation strategies on both the local and national scales may be maladaptive in the long term.

Sweden consistently ranks highly in different climate performance indices and has acquired an international reputation as a climate leader. The paper challenges this narrative. Through a closer look the paper’s findings reveal a more fragmented picture of climate adaptation governance in the country with a myriad of unresolved questions and ad hoc solutions, where adaptation challenges are more pronounced and manifest in the built environment along the coastlines.

Using intersectionality and introducing newer developments from critical cross-cultural management studies, this paper aims to discuss how diversity is applicable to changing cultural contexts.

The paper is a conceptual paper built upon relevant empirical research findings from critical cross-cultural management studies.

By applying intersectionality as a conceptual lens, this paper underscores the practical and conceptual limitations of the business case for diversity, in particular in a culturally diverse international business (IB) setting. Introducing newer developments from critical cross-cultural management studies, the authors identify the need to investigate and manage diversity across distinct categories, and as intersecting with culture, context and power.

This paper builds on previous empirical research in critical cross-cultural management studies using intersectionality as a conceptual lens and draws implications for diversity management in an IB setting from there. The authors add to the critique of the business case by showing its failures of identifying and, consequently, managing diversity, equality/equity and inclusion (DEI) in IB settings.

Organizations (e.g. MNEs) are enabled to clearly see the limitations of the business case and provided with a conceptual lens for addressing DEI issues in a more contextualized and intersectional manner.

This paper introduces intersectionality, as discussed and applied in critical cross-cultural management studies, as a conceptual lens for outlining the limitations of the business case for diversity and for promoting DEI in an IB setting in more complicated, realistic and relevant ways.