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Competitive tendering in South Africa is often associated with procurement based on the lowest fee tendered. Previous research on this topic did not provide in-depth examinations of how pricing within consulting engineering companies was affected by competitive tendering nor did it illuminate the extent to which professional services were impacted by competitive tendering. This paper aims to examine the implications of competitive tendering on pricing and delivery of consulting engineering services in South Africa.

A survey research strategy with a questionnaire as the research instrument elicited qualitative data from 28 experienced consulting engineers in South Africa. Thematic analysis was used to analyse qualitative data from the questionnaires.

Three key themes were identified, namely: considerations when determining consulting engineering fees on competitively tendered projects; the impact of reduced fees due to competitive tendering on the delivery of consulting engineering services; and interventions to prevent unsustainably “low” professional fees. Many consulting engineers in South Africa still determine fees using fee scales, while other considerations include resources, project complexity, risk, etc. Most participants asserted that design optimisation/value engineering, training, meetings and construction monitoring were adversely impacted by “low” fees.

This paper provides in-depth qualitative feedback from experienced consulting engineers (most having more than 20 years’ experience) on a topical issue in the South African construction industry. Thematic analysis was a novel method of analysis that was not used previously in this area of study.

This paper aims at understanding the differences between user profiles in collaborative consumption (CC) platforms in order to improve their management approaches and set up customized strategies. Particularly, the authors investigate the emerging role of prosumers and their influence on the active participation and growth of CC platforms. Moreover, the authors study user experience to help promoting users' recommendation and offering intention.

The sample includes responses from 6,388 users of CC platforms across the EU. The data were collected through the European Commission's Flash Eurobarometer survey 467 and analyzed through a partial least squares structural equation modeling (PLS-SEM) and a fuzzy set qualitative comparative analysis (fsQCA).

The PLS-SEM findings suggest that prosumers are more likely than consumers to recommend and offer services through CC platforms. Furthermore, previous experience using platforms positively affects the switch from consumers to prosumers. The fsQCA suggests that only economic advantages affect the switchover decision.

This study deepens the hitherto unexplored prosumer role in CC platforms and its antecedents and drivers.

The main limitations concern the generalizability outside of the EU, the unbalanced coverage of sectors and the number of moderator variables.

Prosumers act as golden actors because they contribute to enlarge both the customer base (through recommendations) and the provider base (through offering intention). Hence, managers should focus on prosumers' experiences to increase the critical mass and positive externalities of CC platforms.

This study helps understand the importance of the role of prosumers in the growth of CC platforms. The study provides more robust results through a cross-country and mixed-method research.

This study aims to carry out a systematic literature review (SLR) on the integration of Lean, Industry 4.0 and the supply chain or the Lean Supply Chain (LSC) 4.0. The research analyses the current research on the LSC 4.0 concept in an increasingly digitalised world. The authors present the benefits, motivations, critical success factors and challenges of integrating the LSC with Industry 4.0 technologies within this emerging area of research.

An SLR is carried out on how Lean can be integrated with Supply Chain 4.0. Using the search strings of “Lean Supply Chain 4.0,” “Lean Supply Chain Management 4.0” and “Lean Supply Chain Digitalisation,” a review of published literature was carried out via searches on academic databases.

Industry 4.0 has a synergistic effect on the LSC and, depending on the technology and sector applied in, can complement and enhance the LSC. Similarly, the LSC is a precursor for digitalisation. There are considerable implications in the LSC 4.0 for green and sustainable processes.

Organisations can use this study to understand what the LSC 4.0 means to industry, the benefits and motivating factors for implementation, the critical success factors (CSFs) to implementation and the challenges for implementation.

This study adds to state of the art around the LSC 4.0 and future directions in this nascent research area. This study will aid organisations in understanding how Lean, supply chain management and Industry 4.0 can be integrated.

This study aims to investigate the impact of the 2013 privatization of Nigeria’s energy sector on the technical performance of the Benin Electricity Distribution Company (BEDC) and its workforce.

This study used a questionnaire-based approach, and 196 participants were randomly selected. Analytical tools included standard deviation, Spearman rank correlation and regression analysis.

Before privatization, the energy sector, managed by the power holding company of Nigeria, suffered from inefficiencies in fault detection, response and billing. However, privatization improved resource utilization, replaced outdated transformers and increased operational efficiency. However, in spite of these improvements, BEDC faces challenges, including unstable voltage generation and inadequate staff welfare. This study also highlighted a lack of experience among the trained workforce in emerging electricity technologies such as the smart grid.

This study’s focus on BEDC may limit its generalizability to other energy companies. It does not delve into energy sector privatization’s broader economic and policy implications.

The positive outcomes of privatization, such as improved resource utilization and infrastructure investment, emphasize the potential benefits of private ownership and management. However, voltage generation stability and staff welfare challenges call for targeted interventions. Recommendations include investing in voltage generation enhancement, smart grid infrastructure and implementing measures to enhance employee well-being through benefit plans.

Energy sector enhancements hold positive social implications, uplifting living standards and bolstering electricity access for households and businesses.

This study contributes unique insights into privatization’s effects on BEDC, offering perspectives on preprivatization challenges and advancements. Practical recommendations aid BEDC and policymakers in boosting electricity distribution firms’ performance within the privatization context.

Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return.

An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews.

This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction.

The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment worth evaluation. Results of the study could assist practitioners in overcoming limitations associated with BIM investment and economic evaluations in the construction industry.

Due to the uniqueness of individual construction projects, identifying the dominant risk factors is needed for risk mitigation in ongoing and future projects. This study aims to identify the dominant construction supply chain risk (CSCR) factors, based on studies conducted between 2002 and 2022.

The study adopts the preferred reporting items for systematic reviews and meta-analysis (PRISMA) procedure to identify, screen and select relevant articles in order to provide a bibliography and annotation of the prevalent risks in the supply chains. A descriptive analysis of the findings then follows.

The study’s findings have highlighted the three most prevalent risks in the construction supply chain (poor communication across project teams, changes in foreign currency rate, unfavorable climate conditions) as reported in literature, that project teams need to pay closer attention to and take proactive steps to mitigate.

Due to limitations imposed by the chosen research methodology, tools, time frame and article availability, the study was unable to examine all CSCR-related papers.

The results will serve as a useful roadmap for risk/supply chain managers in the construction industry to take strategically proactive steps towards allocating resources for CSCR mitigation efforts.

Context-specific research on the impact of social and cultural risks on the construction supply chain would be beneficial, due to emerging social network risk factors and the complex socio-cultural settings.

There is presently no study that has reviewed extant studies to identify and compile the dominant risk factors (DRFs) associated with the supply chain of construction projects for ranking in the supply chain risk management process.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

The importance of robotics and automation (R&A) in delivering a safe built environment cannot be overemphasised. This is because R&A systems can execute a hazardous job function that the construction workforce may not execute. Based on this knowledge, this study aims to present the result of an assessment of the impediments to the deployment of R&A for a safe and healthy construction environment.

This study adopted a post-positivist philosophical stance, using a quantitative research approach and a questionnaire administered to construction professionals in South Africa. The data gathered were analysed using frequency, percentage, mean item score, Kruskal–Wallis H-test, exploratory factor analysis and partial least square structural equation modelling (SEM).

This study revealed that the impediments to the deployment of R&A could be grouped into: industry, technology, human and cost-related factors. However, SEM assessment showed that only the industry, human and cost-related factors would significantly impact attaining specific health and safety-related outcomes.

The findings offer valuable benefits to construction organisations as the careful understanding of the identified impeding factors can help lead to better deployment of R&A and the attainment of its inherent safety benefits.

This study attempts to fill the gap in the shortage of literature exploring the deployment of R&A for a safe construction environment, particularly in developing countries like South Africa, where such studies are non-existent. This paper, therefore, offers a theoretical backdrop for future works on R&A deployment, particularly in developing countries where such a study has not been explored.

The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.

In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.

Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.

The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.

This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.

This paper aims to explore the research field of digital transformation in small and medium enterprises (SMEs), considering the importance of SMEs in the economic development of countries.

Considering the contributions of researchers and the challenges of SMEs to transform their business models, in this paper, the authors conducted a scientometric analysis using CiteSpace that included 448 documents indexed in Scopus.

The authors appreciated the growth in the number of publications that have studied the digital transformation process in SMEs, showing a niche of researchers interested in the flourishing research topic. Likewise, the authors identified the intention of SMEs to adopt digital technologies such as artificial intelligence, big data, cloud computing, data analytics, electronic commerce and the Internet of Things.

This paper is a valuable resource for academics and researchers in information systems, decision-makers in digital transformation in SMEs and governmental organisations concerned with digital technologies adoption in SMEs to achieve digital transformation and increase competitiveness and productivity.

This study used CiteSpace to conduct a scientometric analysis to explore how researchers have focused on frameworks and maturity models for measuring SME readiness, the impact of Industry 4.0 on SMEs, guides for helping managers evaluate their Industry 4.0 positioning, the development and implementation of digital business strategies for SMEs, the presentation of cases of SMEs that have driven digital transformation and future research opportunities.