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The purpose of this paper is to develop a structural relationship model to study the relationship between causes and effects of poor communication and information exchange in construction projects using Smart-PLS.

The first method of this research is to identify the causes and effects factors of poor communication in construction projects from the extant of literature. The data used to develop the model was collected using a questionnaire survey, which targeted construction practitioners in the Malaysian construction industry. A five-point Likert type scale was used to rate the significance of the factors. The factors were classified under their relevant construct/group using exploratory factor analysis. A hypothetical model was developed and then transformed into Smart-PLS in which the hypothetical model suggested that each group of the cause factors has a direct impact on the effect groups. The hypothesis was tested using t-values and p-values. The model was assessed for its inner and outer components and achieved the threshold criterion. Further, the model was verified by engaging 14 construction experts to verify its applicability in the construction project setting.

The study developed a structural equation model to clarify the relationships between causes and effects of poor communication in construction projects. The model explained the degree of relationships among causes and effects of poor communication in construction projects.

The published academic and non-academic literature introduced many studies on the issue of communication including the definitions, importance, barriers to effective communication and means of poor communication. However, these studies ended up only on the general issue of communication lacking an in-depth investigation of the causes and effects of poor communication in the construction industry. The study implemented advanced structural modeling to study the causes and effects. The questionnaire, the data and concluding results fill the identified research gap of this study. The addressed issue is also of interest because communication is considered one of the main knowledge areas in construction management.

The reverse logistics supply chain (RLSC) for demolition waste management (DWM) is a complex process that inherits significant interdependent risks. However, studies on the RLSC have not explicitly identified the risks of its inter-relationships by disentangling their effects on operational performance. Accordingly, this paper aims to identify and assess the inter-dependencies of the risks in the RLSC to improve quality-related operational performance.

A sequential exploratory mixed-method research approach, consisting of qualitative and quantitative methods, was employed. The qualitative approach involved 25 semi-structured interviews, whereas the 18 subsequent structured interviews were conducted with stakeholders in the entire RLSC as part of the quantitative method. These were used to identify the cause and effect relationships of the identified risks. The data were analysed using thematic analysis, and the Bayesian belief network (BBN) technique was used to develop a conceptual risk model.

In total 20 risks in four RLSC sub-processes, namely, dismantling and on-site process, off-site resource recovery process, marketing of secondary products and residue disposal, emerged. Among cause and effect relationships of identified risk factors, inferior quality of secondary products was found to have the strongest relationship with customer satisfaction. Under-pricing of dismantling job, improper landfill operations and inadequacy of landfill levy are independent risks that initiate other risks down the supply chain. The aggregate effects of these risks affect customer dissatisfaction of the end-product, as well as health and safety risks in on-site, off-site and residue disposal.

This study only identify the cause and effect relationships of the identified risks within the RLSC for DWM operations. It has not targeted a specific construction material or any secondary production, which could be practiced through a case study in future research.

The results encourage the investigation of RLSC process quality by maintaining the relationship between recycler and customer to enable a safe workplace environment. Hence, the role of relevant practitioners and government is inseparable in supporting decision-making. Future research could discuss the impact of those inter-related risks in relation to time- or cost-related operational performance criteria.

This study contributes to the field through presenting the first major study on the identification and assessment of the inter-dependencies of the risks in the RLSC in South Australia. The RLSC process mapping had been identified as a tactical and operational management approach. However, the risk management process is a strategic management approach. Therefore, the integration of both process mapping and the risk management approaches in one platform is germane to construction management research.

Claims are increasingly becoming a norm in construction projects and thus an area that is attracting interventions through researches. This paper aims to establish causes–effects relationship of claims in construction projects.

This is correlation study type of study that attempts to establish causes–effects relationship of claims in construction projects. Significant causes and effects of construction claims were determined using one-sample t-test. To establish the relationship, the significant causes and effects of construction claims were correlated using bivariate correlation analysis.

Among the significant causes, variations, change of scope of the project and delay in completion of works have high level of significant positive relationship with five to six other causes and positive relationship with multiple effects ranging from five to six. Besides, among significant effects, delay in completion and delivering of construction projects, poor contractual relationship among parties and extension of time have significant positive relationship with multiple causes.

The findings of this study are limited to causes-causes relationship and causes–effects relationship of claims in construction projects. This means effects–effects relationship was not covered that could be an important area to investigate as some of causes and effects are at times termed interchangeably.

With reference to previous studies which have focused on determining the causes and effects of construction claims, the findings of the current study have specific contribution on claims management as it divulges the causes of constructions claims that have multiplier effects to the project as a result of their linkage.

The paper unveils causes of claims with multiplier effects to construction projects for project participants to devise strategies to minimize and consequently eliminate them.

This paper aims to share key ideas forwarded in the five-book series focused on the Intelligent Social Change Journey (ISCJ) reflecting the latest research in the Consciousness Series supported by the Mountain Quest Institute and collaborators. This review is based on five separate books released as Part I (Laying the Groundwork), Part II (Learning from the Past), Part III (Learning in the Present), Part IV (Co-Creating the Future) and Part V (Living the Future) of The Profundity and Bifurcation of Change.

Reflecting the consilience approach taken by this in-depth research, the review of ideas provided in this paper tap into a deep array of research in knowledge and learning, with specific reference to recent neuroscience understanding that is emerging, and looks to psychology, physics, cell biology, systems and complexity, cognitive theory, social theory and spirituality for their contributions. The five books are heavily referenced (look to the larger work for these references) and, considering the individual as an intelligent complex adaptive learning system (Bennet et al., 2015b), entangle materials from science to philosophy, facts to psychology, management to poetry and words to pictures. This much shorter review can only partially represent this approach.

At this point in the history of humanity ? in the midst of a conscious expansion of our human capacity and understanding ? the rules are changing. As we move away from predictable patterns susceptible to logic, we are increasingly reliant on our ?gut? instinct, an internal sense of knowing that can tap into the intuitional plane. Yet, this knowing can only serve us if we ?know? what to do with it, how to act. Development of our mental faculties is essential to acting. We are on a developmental journey of the body, mind and heart, moving from the heaviness of cause-and-effect linear extrapolations, to the fluidity of co-evolving with our environment, to the lightness of breathing our thought and feelings into reality. Grounded in development of our mental faculties, these are phase changes, each building on and expanding previous learning in our movement toward intelligent activity.

This review lays the groundwork for the ISCJ, exploring consciousness through the lens of the cause-and-effect logic of Phase 1 (Learning from the Past), the co-evolving of Phase 2 (Learning in the Present) and the creative leap of Phase 3 (Co-Creating the Future). This research connects the expansion of consciousness to development of the human knowledge system.

In implementing Six Sigma and/or Lean Six Sigma, a practitioner often faces a dilemma of how to select the subset of root causes from a superset of all possible potential causes, popularly known as root cause analysis (RCA). Generally one resorts to the cause and effect diagram for this purpose. However, the practice adopted for identification of root causes is in many situations quite arbitrary and lacks a systematic, structured approach based on the rigorous data driven statistical analysis. This paper aims at developing a methodology for validation of potential causes to root causes to aid practitioners.

Discussion has been made on various methods for identification and validation of potential causes to root causes with the help of a few real life examples for effective Lean Six Sigma implementation.

The cause and effect diagram is the frequently adopted method for identifying potential causes out of a host of methods available for such identification. The method of validation depends on the practitioners’ knowledge on the relationship between cause and effect and controllability of the causes.

The roadmap thus evolved for the validation of root causes will be of great value to the practitioners as it is expected to help them understand the ground reality in an unambiguous manner resulting in a superior strategy for cause validation and corrective actions.

The purpose of this paper is to develop the strategy map (SM) of an Iranian automotive industry and the causal and effects relations of the SM’s variables though fourth generation of balanced scorecard (BSC) and fuzzy DEMATEL (decision-making trial and evaluation laboratory) technique.

This research has employed a fuzzy DEMATEL approach in order to find cause and effect relations. At first step, CSFs in Company A’s SM were determined. Then four experts’ views of Company A’s strategic planning department were gathered and calculated by fuzzy set theory.

Results showed the important role of customer perspective in supporting and achieving the organization’s vision which ultimately will lead to fulfillment of the financial objective of the company through satisfied customers. In other words, the dominant approach to logic of SM design in Company A and the obtained results from this research indicate, Company A can achieve strategic result with a more prominent role of customer and financial perspective, through employing the enabler perspective, i.e. learning and growth perspective.

Current study is limited to Iranian automotive industry. So, the strategic planning managers and future researchers shall consider their own company’s strategic structures for developing their SM.

To the best of knowledge of the authors, it is the first attempt, particularly in the context of Iran, aimed at using fourth generation of BSC and fuzzy DEMATEL technique in an automotive industry which led to the confirmation that these two approaches can jointly be employed for the identifying cause and effect relations in SM and clarification and easy understanding of it. This proposed research structure can be a suitable base for the development of SM in other companies.

The purpose of this paper was to assess the causal relationship(s) between moral hazard and adverse selection of public–private partnership (PPP) construction projects. Structural equation modelling (SEM) was used to explore the cause and effect relationship between moral hazard and adverse selection problems in PPP construction projects in Ghana. The study produced a framework to predict, estimate and depict the complex causal relationships (i.e. the directionality) between moral hazard and adverse selection.

To test the proposed framework, a quantitative methodology was used, in which, data were collected using research questionnaires that targeted a sample of 280 PPP stakeholders in Ghana. In total, 210 useable questionnaires were retrieved, representing a response rate of 75 per cent.

The interrelationships between the eight causes and the nine effects of moral hazard and adverse selection were established using the model. The tested framework showed the degree of association and isolation of the unobserved variables on the indicator factors. Confirmatory factor analysis (CFA) was used to evaluate the fit of items to latent constructs. Because the fit of each model was good and the item loadings were adequate, it was assumed that the indicators of the different variables factors were fitting. Furthermore, a diagnostic fit analysis was conducted using the robust maximum likelihood method to test the statistical significance of the parameter estimates.

This novel research is one of the few studies investigating the causal relationships between moral hazard and adverse selection of PPP construction projects. The research concluded with future studies that seek to validate the model developed in other countries and/or other industries.

The research findings will serve as a guide for construction stakeholders in the PPP sector on the causes and effects of adverse selection and moral hazard and how to mitigate these.

Industry 4.0 is regarded as a modern industrial phase wherein convergence between horizontal and vertical production systems, along with their interactions, would enable industries to obtain excellent industrial efficiency. This research thus explores the barriers relevant to Industry 4.0 and their cause and effect relations using the decision-making trial and evaluation laboratory (DEMATEL) technique, and this will assist in the implementation of Industry 4.0 in manufacturing industries.

A comprehensive literature review is carried out to outline the barriers for the Industry 4.0 implementation. The investigative techniques used in this research were conducted utilizing a questionnaire as an instrument for collecting data. The data collected were analysed using the method DEMATEL.

The findings indicate that key barriers to implementing Industry 4.0 include their cause and effect relationships. Reported “implementation costs” have been a critical barrier for Industry 4.0 implementation. Prioritization of barriers and their cause and effect relationships was achieved so that decision-makers could concentrate on overcoming such barriers for Industry 4.0 implementation.

The research is intended to assist executives in recognizing the barriers to Industry 4.0 implementation in their manufacturing industries. Furthermore, the strong functional and empirical importance of emerging and digital manufacturing technologies ensures that understanding the necessary barriers to implementation is important.

This is one of the first few empirical studies in the field of Indian manufacturing industries that uses the DEMATEL method framework as a foundation for recognizing cause-effect interactions among the barriers that affect Industry 4.0.

Green Lean concepts offer methods for managing manufacturing organizations with the goal of improving organizational performance. Green Lean practices are good options to increase the environmental and operational performance of manufacturing industries. However, there are some barriers to implement Green Lean in manufacturing industries. This paper aims to identify these barriers by reviewing the literature and analyze inter-relationships amongst selected barriers.

This paper deals with the identification of barriers to the adoption of Green Lean practices in manufacturing industries. Using the DEMATEL approach and using the insights of experts, a cause and effect relationship diagram was generated through which the effect of barriers was analyzed.

Twelve barriers were categorized in terms of cause and effect, and the interrelationships of barriers were also analyzed. Threshold value is calculated as 0.134 and the values lower than a were eliminated to obtain the digraph. “Resistance to change,” “lack of top management commitment” and “lack of training to employees” are the most prominent barriers on the basis of their prominent score.

Analysis in the research is highly dependent on expert judgments and opinions may be biased. However, the initial matrix obtained from the experts is hindered by the ambiguity about some relationships. But this can be improved by using fuzzy and grey set theories. The barriers used for the analysis are not from a specific type of manufacturing industry.

The findings will help the manufacturing organizations to simplify the most important barriers, the least significant barriers and the relationships between these barriers. This Berlin knowledge will enable administrators to increase awareness of the barriers in Green Lean implementation. “The top management commitment” and “government support” are most important for the removal of barriers to Green Lean strategies.

Very few scholars have used the DEMATEL approach to examine the sequence of the barriers to Green Lean implementation. The present study attempts to incorporate the DEMATEL model to assess the sequence of barriers to the implementation of Green Lean. This study investigates the degree of influence of barriers on each other and categorizes the barriers into cause and effect groups. This study is also intended to pave the way for future research in the path of the elimination of barriers to Green Lean strategies.