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The purpose of this paper is to present a model for building information modelling (BIM) implementation at small and medium-sized construction contractor organisations (SMOs). The proposed BIM adoption model assesses BIM implementation benefits, costs and challenges faced by SMOs. Correlation between BIM adoption in SMOs and the associated impacting factors, including knowledge support and BIM adoption motivation, is captured through the model.

A literature review of BIM adoption in construction was first presented. Research data, collected from 80 SMOs in Australia through a conducted survey, are then analysed. Descriptive analysis and structural equation modelling were used to investigate SMOs’ understanding of BIM, and to qualify the correlations among the proposed latent variables impacting BIM implementation at SMOs, respectively. Additionally, this study used χ² test to compare differences between BIM users and non-BIM users regarding BIM understanding, interested applications and attitudes towards implementation benefits and challenges.

Potential benefits associated with BIM implementation are a major motivation factor when it comes to BIM adoption at SMOs. In addition, existing staff’s capability in using BIM tools positively affects the establishment of an organisational knowledge-support system, which determines the decision of adopting BIM eventually. Ultimately, there is a need for further emphasis on staff engagement in the implementation process.

The results presented in this paper are applicable to SMOs in the building sector of construction. BIM implementation at organisations involved in non-building activities, including civil works and infrastructure, needs to be assessed in the future.

The results indicate that rather than placing the focus mainly on benefits of BIM implementation, successful implementation of BIM in practice requires adequate effort to assess implementation problems, establish knowledge support and engage staff in using BIM.

Results of this study provide an insight into the adoption challenges of BIM in SMOs, given that the focus of previous studies has been mostly placed on BIM adoption in architectural firms and large contractors.

Previous research has identified factors that enable lean change to be sustained. What remains unknown is how the interaction effects amongst these factors vary as lean change programmes mature. When are particular factors at their most influential?

Using a data and investigator triangulated qualitative research strategy, this paper tests an a priori model of change sustainability factors. In phase one, the research reveals the influence and significance of the model's change sustainability factors within 13 manufacturers. In phase two, four factors (Leadership, Political, Individual and Managerial) were selected for in-depth case study analyses in three manufacturers.

These point to when in the lean change, certain factors have the most influence on its sustainability. The Leadership factor and political factor are essential at the beginning and remain influential throughout. Employees' individual commitment (Individual factor) is significant in sustaining the change but it is at its most influential in the later stages. The Managerial factor (management approach) is influential in the mature stages of the programme.

Recognising where to put maximum focus during a lean change programme as it matures is crucial for management.

Sustaining lean change has not been studied from the perspective of what factors need to be emphasised at different stages in the programme for successful maturity to occur. Through empirical validation, this study helps address this knowledge gap.

Interesting because – Researchers have found that the majority of lean implementations fail – changes to structures and working practices are made only to see the gains dissipate. Previous research has suggested that multiple factors including leadership, culture and politics influence the change towards a lean organisation. While studies have shown that such factors play a role, what has not been studied is the time, that is, when the factors influence the change process. This study investigated when 11 factors have the most influence on lean implementation. Theoretical value – The study extends the state-of-the-art understanding of implementation of lean in organisations by adding a time element. It is found that in order to have a change that is sustainable, that is, lasting at least 18 months, factors that indicate the importance to the organisation are influential during the entire implementation process. This includes how central the change is to the organisation, the influence of leadership that sets vision and goals, and the implementation methods. Factors that can set things in motion such as the influence of important stakeholders are important at the beginning of the implementation process but then decline in influence over time. While factors that seem to have to do more with how companies operate have less influence at the start but become more influential over time. These include employees' commitment, the managerial style and approach, the organisational policies and structure, and the organisational culture. Practical value – Introducing lean into an organisation and gaining its sustained benefits is often not successful. While factors have previously been identified that influence the success of lean implementation, this study provides additional practical insight. It helps manufacturers be more effective by pinpointing which factors should be focused on during the various stages of the implementation process.

This study aims to detect the influential factors and their respective variables that affect the effectiveness or demand-driven level of the industrial parks in Iran. A hybrid procedure is sought to be developed, which embraces both qualitative and quantitative methodologies to identify the aforementioned factors and variables.

This study is incorporated with both qualitative and quantitative methodologies. To implement the qualitative approach, the researchers used focus groups and the related literature. The quantitative methodology has been carried out via a reliable questionnaire that obtained the viewpoints of 700 experts. The reliability of the designed questionnaire has been investigated through Cronbach’s alpha coefficient. By conducting several one-sample t-tests, it was confirmed that the identified factors and variables are significantly influential on the effectiveness of Iran’s industrial parks. The Kruskal–Wallis statistical test was used to determine the priorities of the factors. This research also used a multi-criteria decision-making method, namely, the weighted aggregates sum product assessment (WASPAS) to rank 15 industrial parks of Khorasan province in Iran according to the identified factors.

Comprehensive analyses have been conducted on the identified factors. Results indicate that the infrastructural facilities factor has the highest priority when it comes to affecting the effectiveness of the industrial parks. After that, industrial land and internal factors take the second and the third positions in terms of importance. A total of 15 industrial parks of the aforementioned province have been ranked by the WASPAS. The ranking offered by the WASPAS has been approved by the experts.

Based on the literature investigations, the authors were convinced that there is a scarcity of studies investigating the influential factors that affect the effectiveness or demand-driven level of industrial parks (especially in Iran). Hence, this research has been conducted to propose a procedure equipped with quantitative and qualitative techniques that detect these important factors and their subordinate variables. By means of the developed procedure of this research, it is possible to locate future industrial parks, plan for establishment of future industrial areas and plan for development of current industrial parks.

Outsourcings always affect crucial supply chain functions concerning flexibility and cost. During the decision to outsource and consider third-party logistics service provider selection, decision-makers need to pay more attention to certain critical outsourcing factors such as coordination, integration and cooperation as these key factors are essential to improve overall supply chain performance. The main purpose of this work is to identify the inter-relations among outsourcing decision factors to highlight the most important and influential factors that should be considered and carefully thought through when making outsourcing sustainable decisions.

A two-phased methodology has been used in this study. In the first phase, outsourcing decision factors are identified from existing literature and validated by decision-makers from industry and academia. To understand the influential strength and build a sustainable model, the decision-making trial and evaluation laboratory method is used. A courier company in the UAE is considered for implementation.

All identified and validated factors are segregated into two categories (cause and effect). The result shows that the most influential factors are developing strategic alliances, uncertainty and risk mitigation and deficiency of internal resources for a service.

There are several insights for industry managers and practitioners. The results of the study may help practitioners and logistics managers to make the logistics service sustainable and more efficient for businesses.

This study focusses on a courier company to understand the interdependencies among outsourcing decision factors; this is unique in this field of literature.

This paper aims to identify key factors driving auditors’ adoption of Generalized Audit Software (GAS) in a large developing country, Indonesia, through the lens of the technology, organization and environment (TOE) framework.

Results of this study are based on semi-structured in-depth interviews conducted in Indonesia with audit firms of varying sizes.

Key study findings included the identification of highly influential adoption factors, especially environmental factors, such as availability of information technology-skilled auditors in the local market, client needs and expectations and client size. This study has also identified factors, not identified in previous research, as being influential including the importance of GAS availability in a range of languages and the necessity of a supportive professional and regulatory environment.

This study makes several contributions to the literature including that it identifies new influential factors in the TOE framework. This framework has not been widely applied in auditing research and looks beyond the individual perspective to that of the organization as a whole. Moreover, the present study takes a developing country perspective and examines a range of audit firms. In contrast, most studies to date in the area have taken a Western focus and have concentrated on large audit firms. Additionally, this study provides an in-depth analysis through the use of semi-structured interviews, whereas prior studies have relied on surveys.

The purpose of the study was to discover the relative importance of influencing factors toward booking a cruise vacation. Based on a review of literature, this study focused on exploring the relative importance of six influential factors in cruise customers’ decision-making process: cruise vacation price, cruise duration, distance from the cruise port, itineraries, environmental friendliness of cruise line and cruise online reviews.

The complexity of cruise customers’ decision-making process for involving these six attributes with several levels was examined with choice-based conjoint (CBC) analysis. CBC was selected due to its realistic approach to purchase decisions, in the form of trade-offs. The online survey collected data anonymously. The survey was distributed through Amazon’s Mechanical Turk (Mturk) platform. The sample consisted of 450 cruise customers, who had experienced a cruise vacation before.

The findings of the study showed that online reviews were the most influential attribute for cruise customers in their cruise decision, followed very closely by the environmental friendliness of the cruise line. The next influential factor was the duration of the cruise vacation, which was followed by distance from the cruise port, cruise itinerary and cruise vacation price. The best and the worst cruise vacation profiles were generated based on the CBC analysis.

The findings of this study provide some insights with regard to cruise customers’ importance about influencing factors when deciding on a cruise vacation.

The research provides insides in understanding the influential factors at the last stage of cruise customers’ decision-making process. In this regard, cruise industry can pay more attention in promoting the attributes of a cruise offer as influential factors. Additionally, the findings of this study contribute to the general knowledge about cruise customers’ decision-making process.

The main purpose of this paper is to propose a new approach to determine the project activities weight factors using data envelopment analysis. Afterward, the model is applied in Mobarkeh Steel Company as a case study. Accordingly, the project schedule and plans can be written on the basis of the gained weight factors.

This study proposed an approach to determine the weights of activities using Data Envelopment Analysis. This approach consists of four phases. In the first phase, project activities are extracted based on the work breakdown structure. In the second phase, the parameters affecting the importance of activities are determined through a review of the related literature and based on the experts' opinions. In the third phase, the proper data envelopment analysis model is chosen and the inputs and outputs are signified. Then, the activities' weights are determined based on the efficiency numbers. Finally, the model is solved for the case of Isfahan Mobarakeh Steel Company.

The proposed method aimed to calculate the project activities weight factor. Thus, influential parameters on project activities importance include activity duration, activity cost, activity importance which includes successors and predecessors, activity difficulty which includes skill related (education and experience), safety, communication rate, intellectual effort, physical effort, unfavorable work conditions and work related hazards, have been recognized. Then, Projects' data were extracted from the organizational expert's opinions and recorded data in documents. Thereupon, applying DEA, the activities weight factor were calculated based on the efficiency numbers. The results show that the model is applicable and has promising benefits in real-world problems.

Planning is one the most fundamental steps of project management. The ever-growing business environment demands for more complex projects with larger number of activities wants more efficient project managers. Organizational resources are limited; therefore, activities planning is a critical from the perspectives of both managers and researchers. Knowing the importance of the activities can help to manage activities more efficient and to allocate time, budget, cost and other resources more accurate. Different elements such as cost, time, complexity, and difficulty can affect the activity weight factor. In this study, the proposed approach aims to determine the weights of activities using Data Envelopment Analysis.

Existing literature suggests that construction worker safety could be optimized using emerging technologies. However, the application of safety technologies in the construction industry is limited. One reason for the constrained adoption of safety technologies is the lack of empirical information for mitigating the risk of a failed adoption. The purpose of this paper is to fill the research gap through identifying key factors that predict successful adoption of safety technologies.

In total, 26 key technology adoption predictors were identified and classified using a combination of literature review and an expert panel. The level of influence for each identified safety technology adoption predictor was assessed and ranked using the Relative Importance Index. Analysis of variance was performed as well to assess the potential difference in perceived level of importance for the predictors when the study participants were clustered according to work experience and company size.

Statistical analysis indicates that 12 out of the 26 predictors identified are highly influential regarding technology adoption decision-making in construction. Technology reliability, effectiveness and durability were ranked as the most influential predictors. The participants who work for small companies and who had less than ten years of experience rated individual- and technology-related predictors significantly lower than the experienced participants working for medium and large companies.

The present study provides construction researchers and practitioners with valuable information regarding safety technology predictors and their magnitude, both of which are essential elements of a successful safety technology adoption process. Improved technology adoption can enhance workplace safety and minimize worker injuries, providing substantial benefits to the construction industry.

This study contributes to technology adoption knowledge by identifying and quantifying the influential predictors of safety technologies in relation to different organizational contexts. The study informs the need to develop an integrated conceptual model for safety technology adoption.

Nobody concerned with political economy can neglect the history of economic doctrines. Structural changes in the economy and society influence economic thinking and, conversely, innovative thought structures and attitudes have almost always forced economic institutions and modes of behaviour to adjust. We learn from the history of economic doctrines how a particular theory emerged and whether, and in which environment, it could take root. We can see how a school evolves out of a common methodological perception and similar techniques of analysis, and how it has to establish itself. The interaction between unresolved problems on the one hand, and the search for better solutions or explanations on the other, leads to a change in paradigma and to the formation of new lines of reasoning. As long as the real world is subject to progress and change scientific search for explanation must out of necessity continue.

Water pipes degrade over time for a variety of pipe-related, soil-related, operational, and environmental factors. Hence, municipalities are necessitated to implement effective maintenance and rehabilitation strategies for water pipes based on reliable deterioration models and cost-effective inspection programs. In the light of foregoing, the paramount objective of this research study is to develop condition assessment and deterioration prediction models for saltwater pipes in Hong Kong.

As a perquisite to the development of condition assessment models, spherical fuzzy analytic hierarchy process (SFAHP) is harnessed to analyze the relative importance weights of deterioration factors. Afterward, the relative importance weights of deterioration factors coupled with their effective values are leveraged using the measurement of alternatives and ranking according to the compromise solution (MARCOS) algorithm to analyze the performance condition of water pipes. A condition rating system is then designed counting on the generalized entropy-based probabilistic fuzzy C means (GEPFCM) algorithm. A set of fourth order multiple regression functions are constructed to capture the degradation trends in condition of pipelines overtime covering their disparate characteristics.

Analytical results demonstrated that the top five influential deterioration factors comprise age, material, traffic, soil corrosivity and material. In addition, it was derived that developed deterioration models accomplished correlation coefficient, mean absolute error and root mean squared error of 0.8, 1.33 and 1.39, respectively.

It can be argued that generated deterioration models can assist municipalities in formulating accurate and cost-effective maintenance, repair and rehabilitation programs.