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This study investigates the possible curvilinear relationship between operational interdependency and supply chain performance as well as the contingency effect of supply chain disruptions, in terms of disruption orientation and disruption impact.

Path analysis was employed to test the hypotheses using the data collected from Chinese manufacturers.

The results confirm an inverted U-shape effect of operational interdependency. As level of buyer-supplier operational dependency increase, the supply chain performance is enhanced. However, the benefits of operational interdependency diminish beyond a certain point. Additionally, the findings of this study show the disruption orientations positively moderate the relationship between interdependency and performance, whereas the effect of disruption impact is not significant.

The findings of this study provide an explanation to the theoretical gap about the equivocal results of the effect of dependency, which provide new insights into the literature regarding buyer-supplier relationships. Furthermore, this paper identifies the moderating role of supply chain disruption in the relationship between operational interdependency and supply chain performance, which provide further explanation about the mixed results of the effect of dependency. The results confirmed that supply chain disruption orientation positively moderate the relationship between operational interdependency and supply chain performance.

In the realm of construction education, the investigation of immersive learning and extended reality (XR) technologies has experienced a surge in recent times. Nevertheless, there remains a notable lack of comprehension surrounding the most efficient ways to integrate these technologies into tailored teaching approaches for vocational construction training. This research study aims to pinpoint the key factors that construction vocational education and training (VET) providers must consider when introducing XR technologies into their training schemes.

This study conducted an in-depth literature review to develop an initial framework to summarise training, technology and institutional factors influencing the educational-technology integration of XR technologies in VET. In addition, this study utilised a Delphi technique, including semi-structured group discussions and two rounds of online follow-up questionnaires, to capture VET experts’ judgements on the importance of decision-making criteria.

This study has identified the critical factors to be considered in the VET sector when adopting XR technologies. Findings revealed institutional factors were the most important criteria for participants, followed by training and technology factors.

The current decision-making process focuses on selecting XR technologies rather than evaluating their performance after implementation. Therefore, more research is needed to monitor the implementation of this technology in curricula from a senior management perspective. This will help to understand the cost and value factors related to the value proposition of XR technologies in courses.

To ensure the success and long-term viability of the technology-curriculum interface, it is important to consider factors such as the availability of technical and educational support, data security and cost-effectiveness. It is also crucial to focus on ease of use and content development that emphasises instruction to create engaging content for learners.

The potential impact of this study is underpinned by two facts: (1) it constitutes the first effort made in the field to comprehensively elicit VET expert judgements in relation to XR technologies, and (2) it offers decision-making criteria that are at play in seeking to take advantage of high-cost technologies that are rapidly evolving. While there is no simple checklist for XR implementation, this study takes a step further to identify significant factors influencing XR integration in vocational construction training.

Despite large bodies of research related to the impacts of e-commerce on last-mile logistics and sustainability, there has been limited effort to evaluate urban freight using an equity lens. Therefore, this study proposes a modeling framework that enables researchers and planners to estimate the baseline equity performance of a major e-commerce platform and evaluate equity impacts of possible urban freight management strategies. The study also analyzes the sensitivity of various operational decisions to mitigate bias in the analysis.

The model adapts empirical methodologies from activity-based modeling, transport equity evaluation, and residential freight trip generation (RFTG) to estimate person- and household-level delivery demand and cargo van traffic exposure in 41 U.S. Metropolitan Statistical Areas (MSAs).

Evaluating 12 measurements across varying population segments and spatial units, the study finds robust evidence for racial and socio-economic inequities in last-mile delivery for low-income and, especially, populations of color (POC). By the most conservative measurement, POC are exposed to roughly 35% more cargo van traffic than white populations on average, despite ordering less than half as many packages. The study explores the model’s utility by evaluating a simple scenario that finds marginal equity gains for urban freight management strategies that prioritize line-haul efficiency improvements over those improving intra-neighborhood circulations.

Presents a first effort in building a modeling framework for more equitable decision-making in last-mile delivery operations and broader city planning.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

This study introduces a comprehensive bibliometric analysis of the foreign direct investment (FDI) literature by multinational corporations (MNCs) focusing on emerging economies to identify the most influential authors, journals and articles in FDI research and reveals the fields' conceptual and intellectual structures. The purpose of this paper is to address these issues.

The study analyzed 533 articles published between 1974 and 2020 in 226 academic journals indexed in the Web of Science (WoS) and Scopus databases. We used the R language for statistical computing to map author collaboration, co-word and develop a conceptual and intellectual map of the field.

The results show that, although the FDI literature has many authors, few dominate the field. The International Business Review (IBR) and International Journal of Emerging Markets (IJoEM) are the main sources of the publications. Moreover, bibliometric laws show that our dataset follows the Lotka law of scientific productivity and Bradford law of scattering, identifying the core journals. Finally, FDI by MNCs in emerging economies research is divided into four sub-research themes related to (1) FDI determinants, (2) entry mode, (3) MNCs and FDI performance and (4) the internationalization process.

The current article provides several starting points for practitioners and researchers investigating FDI. It contributes to broadening the vision of the field and offers recommendations for future studies.

The role of customers has moved from reactive to proactive, and they require more control over digital touchpoints. The quest for authenticity is their response to the dark side of interactive marketing – forms of faking, manipulation and exploitation. Authenticity becomes a key topic in interactive marketing as it reflects how customers assess digital touchpoints. However, there is a lack of comprehensive knowledge of authenticity in the interactive environment.

This article consolidates the authenticity studies in various digital touchpoints using the entity-referent correspondence framework. This research employs bibliometric analysis and thematic analysis of 103 articles in the last 15 years.

Five research clusters are identified: (1) human, (2) brand-generated content, (3) user-generated content, (4) branded platforms and (5) new technologies-based touchpoints (artificial intelligence, augmented reality and virtual reality). Most interactive marketing studies focus on human and content authenticity, and new technologies-based touchpoints lack comprehensive conceptualization. The review synthesizes the types of authenticity used in each touchpoint and highlights the importance of true-to-creator-self and true-to-customer-self in customer evaluation. We further propose a research framework with four antecedent groups and outcomes.

Our research supports managers by highlighting the type of authenticity prioritized in each touchpoint's development.

To answer the call from interactive marketing researchers, this research highlights the distinct definitions of authenticity at various digital touchpoints rather than looking at the overall brand. Trends, gaps and future research agenda of the authenticity concept in technology adoption and customer behavior are discussed.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

For almost half a century, society has been aware of the existence of a glass ceiling, a term that describes the invisible barriers that hinder women’s access to power positions despite having equal or greater qualifications, skills and merits than their male counterparts. Nowadays, although there are signs of slow progress, women are still underrepresented in the upper echelons of large corporations and the risk of reversing the progress made in gender parity has increased because of the effects of the COVID-19 pandemic. This paper contributes to previous literature by analysing the impact that the uncertainty and cognitive effects associated with COVID-19 in 2020 had on the presence of women on the board of directors and whether this impact has been moderated by the regulatory and policy system on gender quotas in place at the time.

To test the authors' research hypotheses, the authors selected the major global companies worldwide with economic-financial and non-financial information available in the Thomson Reuters EIKON database over the 2015–2020 period. As a result, the authors' final sample is made up of 1,761 companies from 52 countries with different institutional settings that constitute an unbalanced data panel of 8,963 observations. The nature of the dependent variables requires the use of logistic regressions. The models incorporate the terms to control for any unobservable heterogeneity and the error term. Any endogeneity issues were addressed by considering the explanatory variables with a time lag.

The authors find that almost 30% of the companies downsized their boards in 2020. This decision resulted in more female than male directors being made redundant, causing a reversal in the fulfilment of gender quotas focussed on ensuring balanced boards with a female presence of 40% or more. This effect was enhanced in countries with hard-law regulation because the penalty for non-compliance with gender quotas had led to a significant increase in the size of these bodies in previous years through the inclusion of the required number of female directors. In contrast, the reduction in board size in soft-law countries does not differ from that in laissez-faire countries, lacking any moderating effect or impact on the number of female board members dismissed as a result of the pandemic.

This paper aims to contribute to current knowledge by analysing the impact that the countries' regulatory and normative systems on gender parity on boards of directors have had on the decisions made in relation to leadership positions, moderating the effects of the COVID-19 pandemic on gender equality at a global level.

Drawing on legitimacy and upper-echelon theory, this paper aims to investigate the moderating role of corporate governance in the relationship between corporate social performance (CSP) and board gender diversity (BGD).

Using Morgan Stanley Capital International measures of social and governance performance, the authors use 2,950 firm-year observations from US companies for the years 2016–2020 to show that good performance on social issues drives BGD.

The panel data model indicates that the relationship between CSP and BGD is strengthened when firms display robust corporate governance.

This study contributes to the extant literature through empirical consideration of CSP as a predictor of BGD, a relationship that has rarely been examined. It further highlights the significant role of corporate governance in ensuring that women have access to corporate boards. Discussion and findings highlight that social performance and governance may significantly contribute to the diversity of socially cognizant boards.

Agricultural land loss is a severe issue that Australia faces, along with many other countries. Myriad research studies have discussed the reasons for such land loss, including urban sprawl as the main factor and factor's repercussions. However, there is a knowledge gap in understanding the impact of dwelling type on farming land reduction. Also, there is an application gap, particularly in the local context. The purpose of this study is to discover the effect of differing dwelling types (compact and non-compact) in metropolitan areas with a growing population (such as Craigieburn) toward potentially noticeable agricultural land loss.

This paper aims to fill these research and practice gaps through a case study using a mixed methods approach. A quantitative analysis was conducted of housing types, the types' growth and agricultural land area taken up by those different housing types over 18 years. Thematic analysis of policies, strategies, schemes and codes relevant to the case study enabled a better understanding of practice gaps.

The study revealed a significant loss of agricultural land. Separate housing was found to be the main culprit due to the number of houses and the area the houses require, thus exhibiting the lack of practical guidelines to prevent the houses' overdevelopment. The findings enabled the identification of opportunities for better practice through government intervention and potential industry alterations.

Previous literature has primarily explored the issues associated with urban sprawl and the sprawl's unsustainability. This research paper offers a more targeted insight into one of the key factors leading to urban sprawl: the types of dwellings being constructed.