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In successfully meeting city and metropolitan growth, sustainable development is compulsory. Sustainability is a must-focus for any project, particularly for large and mega rail infrastructure. This paper aims to investigate to what degree social, environmental and economic factors influence the government when planning sustainable rail infrastructure projects. To respond to such a matter, this paper focuses on two Australian mega-rail projects: the South West Rail Link (SWRL) and the Mernda Rail Extension (MRE).

As the basis of an experimental evaluation framework strengths, weaknesses, opportunities and threats (SWOT) and factor analysis were used. These two methods were specifically selected as comparative tools for SWRL and SWRL projects, to measure their overall sustainability effect.

Using factor analysis, in the MRE, the factors of network capacity, accessibility, employment and urban planning were seen frequently throughout the case study. However, politics and economic growth had lower frequencies throughout this case study. This difference between the high-weighted factors is likely a key element that determined the SWRL to be more sustainable than the MRE. The SWOT analysis showed the strengths the MRE had over the SWRL such as resource use and waste management, and natural habitat preservation. These two analyses have shown that overall, calculating the sustainability levels of a project can be subjective, based on the conditions surrounding various analysis techniques.

This paper first introduces SWRL and MRE projects followed by a discussion about their overall sustainable development. Both projects go beyond the traditional megaprojects' goal of improving economic growth by developing and enhancing infrastructure. Globally, for such projects, sustainability measures are now considered alongside the goal of economic growth. Second, SWOT and factor analysis are undertaken to further evaluate the complexity of such projects. This includes their overall sustainable development vision alignment with environmental, economic and social factors.

The purpose of this paper is to examine the evolution of the literature on technology transfer and culture, identifying the main contents of the current body of knowledge encompassing culture and technology transfer (TT), thus contributing to a better understanding of the relationship between TT and culture based on bibliometric and multivariate statistical analyses of the relevant body of literature.

Data for this study were collected from the Web of Science (WoS) Core Collection database. Based on a bibliometric analysis and in-depth empirical review of major TT subjects, supported by multivariate statistical analyses, over 200 articles were systematically reviewed. The use of these methods decreases biases since it adds rigor to the subjective evaluation of the relevant literature base.

The exploratory analysis of the articles shows that first, culture is an important topic for TT in the literature; second, the publication data demonstrate a great dynamism regarding the different contexts in which culture is covered in the TT literature and third, in the last couple of years the interest of stimulating a TT culture in the context of universities has continuously grown.

This study focuses on culture in the context of TT and identifies the main contents of the body of knowledge in the area. Based on this first insight, obtained through more detailed bibliometric and multivariate analyses, it is now important to develop and validate a theory on TT culture, emphasizing the dimensions of organizational culture, entrepreneurial culture and a culture of openness that fosters economic and societal spillovers, and to link those dimensions to the performance of TT activities.

From the practical point of view, managers in companies and universities should be aware of the importance of identifying those dimensions of culture that contribute most to the success of their TT activities.

Despite several literature reviews on the TT topic, no studies focusing specifically on culture in the context of TT have been developed. Therefore, given the multifaceted nature of the research field, this study aims to expand and to deepen the analysis of the TT literature by focusing on culture as an important and commonly cited element influencing TT performance.

This study aims to modify the human factors analysis and classification system (HFACS) to make it suitable for collapse accident analysis in construction. Based upon the modified HFACS, distribution patterns of causal factors across multiple levels were discerned among causal factors of various stakeholders at construction sites. It explored the correlations between two causal factors from different levels and further determined causation paths from two perspectives of level and stakeholder.

The main research framework consisted of data collection, coding and analysis. Collapse accident reports were collected with adequate causation information. The modified HFACS was utilized for coding causal factors across all five levels in each case. A hybrid approach with two perspectives of level and stakeholder was proposed for frequency analysis, correlation analysis and path identification between causal factors.

Eight causal factors from external organizations at the fifth level were added to the original HFACS. Level-based correlation analyses and path identification provided safety managers with a holistic view of inter-connected causal factors across five levels. Stakeholder-based correlation analyses between causal factors from the fifth level and its non-adjacent levels were implemented based on client, government and third parties. These identified paths were useful for different stakeholders to develop specific safety plans for avoiding construction collapse accidents.

This paper fulfils an identified need to modify and utilize the HFACS model for correlation analysis and path identification of causal factors resulting in collapse accidents, which can provide opportunities for tailoring preventive and protective measures at construction sites.

With the aim to provide a global view of factors affecting mark-up size on construction projects, this study performs a meta-analytical review of the relevant studies over the past 20 years.

The analytical process involved the identification and evaluation of the importance of critical factors affecting mark-up size on construction projects, and the assessment of the generalisability of findings of the meta-analysis. A random-effects model was adopted in the statistical meta-analysis.

The results show that there are 23 critical factors, and the top five factors are: (1) competitiveness of other bidders; (2) number of bidders; (3) relationship and past experience with client; (4) experience on similar project; and (5) project size. A heterogeneity test further shows that there is no statistically significant heterogeneity across the studies, reinforcing the generalisability of the findings to a global context.

The list of critical factors from a global perspective should form a good basis for future efforts in bidding model development.

The research findings have practical implications to both construction clients and contractors in formulating their contracting practices and strategies.

This is the first meta-analysis of a sizeable collection of replicated studies on factors affecting mark-up size on construction projects in the literature.

Though daycare centres are built to facilitate children's social and physical growth, divergent stakeholder perceptions yield conflicts while managing risks for each space due to the minimal guidelines in the Republic of Korea. Due to the unclearly defined knowledge and experience gap between representative stakeholders, teachers have difficulties in operating it with high satisfaction. This study therefore was conducted to systematically identify which parts of performance should be increased to preferentially increase end-user satisfaction in limited resources.

This research conducted quantitative analysis gradually. Importance–performance analysis (IPA) grasped the perceptions of construction practitioners and end-users after identifying space composition and representative risks of daycare centres. Based on the factors influencing perception differences, principal component analysis and structural equation modelling (SEM) were conducted to determine which space improves the performance preferentially to increase overall end-user satisfaction.

As the utilisation of indoor spaces increases after COVID-19, improvement of indoor spaces except for indoor playroom is necessary, especially, advancement of the quality of teachers' rooms.

Outputs by reflecting the end-user experiences support to understand which spaces are managed from the limited resources.

Theoretical framework for daycare centre was established in Korea where guidelines were insufficient, and differences in perception of each risk of stakeholders were identified. Moreover, gradual statistical analysis was set to construct end-user-focused centres by extracting where the performance of space should be improved in prior.

The purpose of this paper is to investigate the relationship between total productive maintenance (TPM) practices and operational performance (OP) in soft drinks manufacturing industry, Ethiopia.

In this study acceptability and implementation of five TPM practices (i.e., dependent factors: autonomous maintenance (AUT); safety, health and environment (SHE); education and training (EDT); focused improvement; and planned maintenance (PLM)) in soft drinks manufacturing industry have been elaborated to ascertain the benefits accrued as a result of successful TPM practices (i.e., independent variables) on OP (i.e., dependent variables). A self-administered survey seven-point Likert scale questionnaire was used for primary data collection. By using simple random sampling technique a total of 100 useable responses resulted in a 66.66 per cent response rate. Descriptive (mean, standard deviation) and inferential statistics (factor analysis, correlation, simple and multiple regression analysis) analysis were performed using Statistical Package for Social Sciences (SPSS) software (version-28) to identify the relationship and effect of TPM practices on OP. Five hypotheses were developed and tested.

Results show that four of the TPM practices were positively and significantly correlated with OP. Aggregate TPM shows positive and significant correlation with OP. Four hypotheses results revealed that the AUT; SHE; EDT and PLM practices have positive and significant relationship with OP and significantly improve OP. The results also show that the TPM practices have positive and significant relationship with OP and significantly improve cost effectiveness, product quality, on-time delivery and volume flexibility.

The benefits gained by TPM practices in selected soft drinks manufacturing industry have been highlighted, that could be genuine source of motivation to other companies to go in for TPM program. This research contributes to the literature by examining the contingency of various TPM enabling factors in the context of the Ethiopian soft drinks manufacturing sector, and it, therefore, provides direction to increase the success rate of TPM implementation. Study offers academics and practitioners a better understanding of the relationship and effect of the TPM practices on the OPs. Thus, practitioners will be able to make better and more effective decisions about the implementation of TPM practices for better OP results.

The relationship between the five factors TPM practices and OP has not yet been studied or reported in the case of soft drink manufacturing industry. The questionnaire manner and items developed, factor considered in this study, sampling method, deeply statistical data analysis techniques used, soft drink manufacturing industry, developing country like Ethiopia make this study unique and revealed the gap identification in this area. The study has contributed to the TPM literature with a better understanding of the five TPM practices and their association with a soft drink manufacturing industry OP that will provide valuable knowledge to top-management of manufacturing companies, to refine their current TPM practices and subsequently improve OP.

This paper aims to establish the most underlying factors causing construction projects delay from the most applicable.

The paper conducted survey of experts using systematic review of vast body of literature which revealed 23 common factors affecting construction delay. Consequently, this study carried out reliability analysis, ranking using the significance index measurement of delay parameters (SIDP), correlation analysis and factor analysis. From the result of factor analysis, this study grouped a specific underlying factor into three of the six applicable factors that correlated strongly with construction project delay.

The paper finds all factors from the reliability test to be consistent. It suggests project quality control, project schedule/program of work, contractors’ financial difficulties, political influence, site conditions and price fluctuation to be the six most applicable factors for construction project delay, which are in the top 25% according to the SIDP score and at the same time are strongly associated with construction project delay.

This paper is recommending that prospective research should use a qualitative and inductive approach to investigate whether any new, not previously identified, underlying factors that impact construction projects delay can be discovered as it followed an inductive research approach.

The paper includes implications for the policymakers in the construction industry in Nigeria to focus on measuring the key suppliers’ delivery performance as late delivery of materials by supplier can result in rescheduling of work activities and extra time or waiting time for construction workers as well as for the management team at site. Also, construction stakeholders in Nigeria are encouraged to leverage the amount of data produced from backlog of project schedules, as-built drawings and models, computer-aided designs (CAD), costs, invoices and employee details, among many others through the aid of state-of-the-art data driven technologies such as artificial intelligence or machine learning to make key business decisions that will help drive further profitability. Furthermore, this study suggests that these stakeholders use climatological data that can be obtained from weather observations to minimize impact of bad weather during construction.

This paper establishes the three underlying factors (late delivery of materials by supplier, poor decision-making and Inclement or bad weather) causing construction projects delay from the most applicable.

Although knowledge based on business intelligence (BI) is crucial, few studies have explored the core of BI knowledge; this study explores this topic.

The authors collected 1,306 articles and 54,020 references from the Web of Science (WoS) database and performed co-citation analysis to explore the core knowledge of BI; 52 highly cited articles were identified. The authors also performed factor and cluster analyses to organize this core knowledge and compared the results of these analyses.

The factor analysis based on the co-citation matrix revealed seven key factors of the core knowledge of BI: big data analytics, BI benefits and success, organizational capabilities and performance, information technology (IT) acceptance and measurement, information and business analytics, social media text analytics, and the development of BI. The cluster analysis revealed six categories: IT acceptance and measurement, BI success and measurement, organizational capabilities and performance, big data-enabled business value, social media text analytics, and BI system (BIS) and analytics. These results suggest that numerous research topics related to big data are emerging.

The core knowledge of BI revealed in this study can help researchers understand BI, save time, and explore new problems. The study has three limitations that researchers should consider: the time lag of co-citation analysis, the difference between two analytical methods, and the changing nature of research over time. Researchers should consider these limitations in future studies.

This study systematically explores the extent to which scholars of business have researched and understand BI. To the best of the authors’ knowledge, this is one of the first studies to outline the core knowledge of BI and identify emerging opportunities for research in the field.

Numerous attempts at installing six sigma (SS) have faced challenges and fallen short of the desired success. Thus, it becomes vital to identify the critical factors and characteristics that play a pivotal role in achieving successful adoption. In this study the research has aimed to highlight that a considerable number of corporate SS initiatives, around 60%, fail primarily due to the improper incorporation of essential elements and flawed assumptions.

To validate the influence of critical success factors (CSFs) on SS accomplishment, the study employed a research design combining exploratory and mixed-methods approaches. A Likert-scale questionnaire was utilized, and a simple random sampling method was employed to gather data. Out of the 2,325 potential participants approached, 573 responses were received, primarily from Germany, the United Kingdom and Sweden. The analysis focused on 260 completed questionnaires and statistical methods including structural equation modeling (SEM), exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) were utilized for data analysis.

The study acknowledged four essential components of CSFs that are imperative for sustaining the success of SS: (1) Competence of belt System employees; (2) Project management skills; (3) Organizational economic capability and (4) Leadership commitment and engagement. These factors were identified as significant contributors to the maintenance of SS’s success.

The practical implications of this research imply that institutions, practitioners, and researchers can utilize the four identified factors to foster the sustainable deployment of SS initiatives. By incorporating these factors, organizations can enhance the effectiveness and longevity of their SS practices.

The investigation's originality lies in its contribution to assessing CSFs in SS deployment within the European automobile industry, utilizing a mixed-methods research design supplemented by descriptive statistics.