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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.

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.

This paper aims to develop a system dynamics (SD) model to identify causal relationships among the elements of failure modes and effects analysis (FMEA), i.e. failure modes, effects and causes.

A causal loop diagram (CLD) has been developed based on the results obtained from interdependencies and correlations analysis among the FMEA elements through applying the integrated approach of FMEA-quality function deployment (QFD) developed by Shaker et al. (2019). The proposed model was examined in a steel manufacturing company to identify and model the causes and effects relationships among failure modes, effects and causes of a roller-transmission system.

Findings indicated interactions among the most significant failure modes, effects and causes. Moreover, corrective actions defined to eliminate or relieve critical failure causes. Consequently, production costs decreased, and the production rate increased due to eliminated/decreased failure modes.

The application of CLD illustrates causal relationships among FMEA elements in a more effective way and results in a more precise recognition of the root causes of the potential failure modes and their easy elimination/decrease. Therefore, applying the proposed approach leads to a better analysis of the interactions among FMEA elements, decreased system's failure rate and increased system availability.

The literature review indicated a few studies on the application of SD methodology in the maintenance area, and no study was performed on the causal interactions among FMEA elements through an FMEA-QFD based SD approach. Although the interactions of these elements are significant and helpful in risks ranking, researchers fail to investigate them sufficiently.

The purpose of this paper is to investigate whether first level measures in the Balanced Scorecard (BSC) declaring a cause-effect relationship by design are composite indices of lower measures, and if they converge into a single factor as is traditionally accepted in the BSC literature.

This study reports results of a quantitative case study that focusses on an Ontario (Canada) community hospital that has been using the BSC.

The results of this study challenge the cause-effect assumption of the BSC, particularly in a cascading context, and suggest that a lack of attention of how composite indices of lower measures converge into a single higher level measure may be the reason for ineffective use of the BSC.

The BSC is a dynamic tool; as such there are several measures that have a very short history, thus limiting the observations available to be used in statistical models.

A key recommendation for practice that emerges from this study is the need to test if lower level metrics do merge naturally in the upper level measure of the BSC; if not, the upper level measure might not be linked to other measures rendering the BSC ineffective in the context of causality.

Although several studies have argued in favour of the cause-effect relationship of the BSC, none of those found in the literature have paid attention to the way in which first level measures are constructed. This may explain why certain measures are linked, while others are not, to those that are calculated as composite indices of several lower level indicators.

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.

In the last four years, since Volume I of this Bibliography first appeared, there has been an explosion of literature in all the main functional areas of business. This wealth of material poses problems for the researcher in management studies — and, of course, for the librarian: uncovering what has been written in any one area is not an easy task. This volume aims to help the librarian and the researcher overcome some of the immediate problems of identification of material. It is an annotated bibliography of management, drawing on the wide variety of literature produced by MCB University Press. Over the last four years, MCB University Press has produced an extensive range of books and serial publications covering most of the established and many of the developing areas of management. This volume, in conjunction with Volume I, provides a guide to all the material published so far.

The research aims at addressing the way in which linkages based on qualitative causality could be preferred in designing a balanced scorecard (BSC), by applying a cost-benefit judgment with respect to the complexity of defining strong, statistically reliable cause-and-effect relations among performance measures.

The authors review the way in which cause-and-effect relations across the BSC have been developed based on a case study of BSC implemented in an Italian bank collecting data by in-depth interviews and company’s internal archives.

The research reveals how the ambiguity, or “blurred nature”, of strategic linkages is recognized in the empirical setting of an bank, facing a highly uncertain and complex environment and how the orthodox tools of strategy maps and explicit cause-and-effect linkages prescribed by the theoretical literature are avoided by the human actors. Despite these omissions, the BSC is nevertheless effective. As the case shows, it generated a “democracy” where individuals and departments communicate, commit and collaborate in an effort to implement strategy. The research also shows the role of the BSC in heightening the importance and awareness of performance evaluation among the actors.

The research provides practitioners with insights into how to design and manage cause-and-effect relationships in BSC. In particular, evidence is provided that finality linkages in BSC may be successful in use and predictive capabilities, according with expectations and purposes of the organization’s “climate of control”, in a context in which the cost-benefit philosophy in implementing BSC is followed.

The paper addresses an issue of practical relevance in the implementation of BSC showing a discrepancy between theoretical and practical meaning of causality. Besides the research highlights, the extent to which linkages across the BSC perspectives (and related measures and variables) can only be based on individual assumptions about the means to an end and based on qualitative assertions (finality).

Scanning both the academic and popular business literature of the last 40 years puzzles the alert reader. The variety of prescriptions of how to be successful (effective, performing, etc.) 1 Organizational performance, organizational success and organizational effectiveness will be used interchangeably throughout this paper.1 in business is hardly comprehensible: “Being close to the customer,” Total Quality Management, corporate social responsibility, shareholder value maximization, efficient consumer response, management reward systems or employee involvement programs are but a few of the slogans introduced as means to increase organizational effectiveness. Management scholars have made little effort to integrate the various performance-enhancing strategies or to assess them in an orderly manner.

This study classifies organizational strategies by the importance each strategy attaches to different constituencies in the firm’s environment. A number of researchers divide an organization’s environment into various constituency groups and argue that these groups constitute – as providers and recipients of resources – the basis for organizational survival and well-being. Some theoretical schools argue for the foremost importance of responsiveness to certain constituencies while stakeholder theory calls for a – situation-contingent – balance in these responsiveness levels. Given that maximum responsiveness levels to different groups may be limited by an organization’s resource endowment or even counterbalanced, the need exists for a concurrent assessment of these competing claims by jointly evaluating the effect of the respective behaviors towards constituencies on performance. Thus, this study investigates the competing merits of implementing alternative business philosophies (e.g. balanced versus focused responsiveness to constituencies). Such a concurrent assessment provides a “critical test” of multiple, opposing theories rather than testing the merits of one theory (Carlsmith, Ellsworth & Aronson, 1976).

In the high tolerance level applied for this study (be among the top 80% of the industry) only a handful of organizations managed to sustain such a balanced strategy over the whole observation period. Continuously monitoring stakeholder demands and crafting suitable responsiveness strategies must therefore be a focus of successful business strategies. While such behavior may not be a sufficient explanation for organizational success, it certainly is a necessary one.

Several variables can affect work stress. This study aims to model the cause-and-effect relationships among different variables that can predict work stress based on one of the most important fuzzy multicriteria decision-making methods used to investigate the cause-and-effect relationships among variables.

This study was conducted in 2020, including 17 experts in safety management, occupational health and work psychology, based on the fuzzy decision-making trial and evaluation laboratory method as a robust approach to identify the cause-and-effect relationships among different variables.

Shift work, lack of job satisfaction, mental health, mental overload, fatigue, job security, sleep disorders, environmental discomfort, work pressure, job knowledge (this could mean expertise/level of qualifications/familiarity with the job), work complexity and role conflict were found to be the most significant variables affecting work stress. Moreover, the cause-and-effect model of relationships among variables showed that shift work and lack of job satisfaction are root causes, and mental health, fatigue, mental workload, sleep disorder and environmental discomfort are direct causes.

Although the results of this study demonstrate that work stress can be influenced by 12 different variables, the modeling results show that some variables, such as shift work and lack of job satisfaction, can directly or indirectly impact other variables and thus result in work stress.

Contemporary literature reveals that, to date, the poultry livestock sector has not received sufficient research attention. This particular industry suffers from unstructured supply chain practices, lack of awareness of the implications of the sustainability concept and failure to recycle poultry wastes. The current research thus attempts to develop an integrated supply chain model in the context of poultry industry in Bangladesh. The study considers both sustainability and supply chain issues in order to incorporate them in the poultry supply chain. By placing the forward and reverse supply chains in a single framework, existing problems can be resolved to gain economic, social and environmental benefits, which will be more sustainable than the present practices.

The theoretical underpinning of this research is ‘sustainability’ and the ‘supply chain processes’ in order to examine possible improvements in the poultry production process along with waste management. The research adopts the positivist paradigm and ‘design science’ methods with the support of system dynamics (SD) and the case study methods. Initially, a mental model is developed followed by the causal loop diagram based on in-depth interviews, focus group discussions and observation techniques. The causal model helps to understand the linkages between the associated variables for each issue. Finally, the causal loop diagram is transformed into a stock and flow (quantitative) model, which is a prerequisite for SD-based simulation modelling. A decision support system (DSS) is then developed to analyse the complex decision-making process along the supply chains.

The findings reveal that integration of the supply chain can bring economic, social and environmental sustainability along with a structured production process. It is also observed that the poultry industry can apply the model outcomes in the real-life practices with minor adjustments. This present research has both theoretical and practical implications. The proposed model’s unique characteristics in mitigating the existing problems are supported by the sustainability and supply chain theories. As for practical implications, the poultry industry in Bangladesh can follow the proposed supply chain structure (as par the research model) and test various policies via simulation prior to its application. Positive outcomes of the simulation study may provide enough confidence to implement the desired changes within the industry and their supply chain networks.