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This paper attempts to demystify the technique of causal path modeling for the non‐specialists by presenting aspects of its value for social science and management research and by illustrating common misunderstandings about its attributes. Special emphasis is placed on the real world validity of causal relationships depicted in causal path models and on the information that the data‐fitting properties of causal path models provide regarding this issue. Causal path models that are based on research in antecedents of career success are used to illustrate the points that are made. It is stressed that the validity of causal relationships depicted in causal path models is subject to exactly the same methodological restrictions as the validity of causality claims that are made without the use of causal path modeling; and that the purpose of using quantitative techniques in causal path modeling is not to improve certainty on causality direction.

The purpose of this research is to show a preliminary examination of the effects of the development of the causal model of the strategy in the implementation of the Balanced Scorecard. Studies on the Balanced Scorecard adoption show that many organizations that adopted the Balanced Scorecard did not develop a causal model of their strategy. The study seeks to examine the differences in Balanced Scorecard implementation of adopters who developed a causal model of their strategy and those who did not.

Mailed survey was used to collect the data.

It was found that Balanced Scorecard adopters who did not develop a causal model of their strategy experienced specific problems more than those who developed a causal model of their strategy. It affected the outcomes and ease of implementation of the Balanced Scorecard.

The small number of responses obtained in this study due to the relatively recent adoption of the Balanced Scorecard in Malaysia limits the generalizability of this study. However, it does provide insights on the hypotheses to be examined in future studies.

The findings of this survey suggest that the successful implementation of the Balanced Scorecard requires that organizations develop and articulate a causal model of their strategy.

This study is probably the first attempt to examine the role of causal model development in effective implementation of the Balanced Scorecard.

Construction fall-from-height accidents are not only caused by a single factor but also by the risk coupling between two or more factors. The purpose of this paper is to quantitatively analyze the risk coupling relationships between multiple factors and identify critical factors in construction fall-from-height accidents.

A cause analysis framework was established from the perspective of human, machine, material, management and environmental factors. The definition, the classification and the process of risk coupling were proposed. The data from 824 historical accident reports from 2011 to 2021 were collected on government websites. A risk coupling analysis model was constructed to quantitatively analyze the risk coupling relationships of multiple factors based on the N-K model. The results were classified using K-means clustering analysis.

The results indicated that the greater the number of causal factors involved in risk coupling, the higher the risk coupling value and the higher the risk of accidents. However, specific risk coupling combinations occurred when the number of their coupling factors was not large. Human, machine and material factors were determined to be the critical factors when risk coupling between them tended to pose a greater risk of accidents.

This study established a cause analysis framework from five aspects and constructed a theoretical model to quantitatively analyze multi-factor coupling. Several suggestions were proposed for construction units to manage accident risks more effectively by controlling the number of factors and paying more attention to critical factors coupling and management and environmental factors.

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.

Authors analyze a business model (BM) based on organizational performance. BMs are strategic tools used to achieve high performance. This study is based on two characteristics of causal complexity: conjunction and equifinality. Authors also examine the applicability of causal asymmetry in the relationship between BMs and organizational performance.

Generally, the relationship between BM elements and organizational performance is analyzed using a correlational approach. This relationship is marked by causal complexity, which cannot be analyzed via such approach. Authors applied a fuzzy-set qualitative comparative analysis with data from three time-periods and two performance variables for pharmaceutical firms.

Qualitative comparative analysis revealed that high performance resulted from configurations (combinations) of BM elements and not from the effects of individual elements. In addition, multiple configurations are available for achieving high performance. Causal asymmetry was observed in the configuration of the BM elements for high and low performances.

Using qualitative comparative analysis of data sets from three time-periods in the context of the pharmaceutical industry BM, authors integrated the theoretical constructs of causal complexity, namely conjunction, equifinality and causal asymmetry.

Findings related to conjunctions will help managers shift their focus from individual BM elements to combinations of BM elements. Additionally, the findings related to equifinality and causal asymmetry will allow flexibility in designing their company’s BM according to the resource constraints their company faces.

This was one of the first few studies on BMs using the twin indicators of the organizational performance relationship and causal complexity.

Purpose – The chapter provides an exposition both of Hayek's causal theory of the mind (especially as applied to intentionality) and of Popper's critique of causal theories, argues that Hayek fails successfully to rebut Popper's critique, and shows how the dispute between Hayek and Popper is relevant to controversies in contemporary philosophy of mind.

Methodology/approach –The chapter elucidates Hayek's ideas and Popper's by situating them within the history of the mind/body problem and comparing them to the views of contemporary philosophers like Fred Dretske, Jerry Fodor, and Hilary Putnam.

Findings – Popper's critique has yet to be answered, either by Hayek or by contemporary causal theorists.

Originality/value of the chapter –The chapter calls attention to some important but neglected ideas of Hayek and Popper and examines some of their as-yet-unpublished writings.

Mediating effects are often tested using hierarchical multiple regression (HMR) procedures. Typical of the HMR-based strategies is the very frequently cited and widely used procedure described by Baron and Kenny (1986). Unfortunately, there are several important problems with it. More specifically, as we demonstrate below, it: (a) is of virtually no value for buttressing claims of mediating effects for data from non-experimental research; (b) produces erroneous inferences about the existence of mediating effects for misspecified mediation models; and (c) is incapable of providing credible evidence of such effects in a large proportion of cases, even for properly specified mediation models. We detail a number of important implications of our analyses.

Although we have improved identification of and access to evidence-based interventions for addressing student problem behavior, teacher use of these practices remains low. In this chapter, we examine teachers’ causal attributions for student problem behavior and their implications for use of effective school-based behavioral interventions and supports. Attribution theory and research suggest that causal attributions strongly influence how individuals (e.g., teachers) perceive and respond to the problem behavior of others (e.g., students). Teacher perception regarding problem behavior and appropriate responses to it can be a significant barrier to the adoption and sustained implementation of empirically supported practices. In light of these factors, causal attribution theory and research can be used as a framework for better understanding and even changing teacher beliefs related to acceptance, implementation, and sustained use of effective behavior management practices. In this chapter, we make the case for cultivating an understanding of teachers’ causal attributions of student problem behavior and considering implications of causal attributions in future research. We explore how such research endeavors can potentially positively impact teacher implementation of effective school-based behavioral interventions and supports.

The lack of systematic methods for reducing the complex reality has hampered many of the contributions that processual research might have produced. This paper presents a methodology for processual strategy research that offers a systematic approach for causal explanation across complex sequences of events and enables theorization about underlying causal mechanisms driving the processes. In addition, a comparative analysis of two organizational decline and turnaround processes is presented in order to illuminate how the methodology is able to generate a substantial advancement in knowledge by indicating the causal mechanisms underlying the decline and turnaround processes. The findings show that the turnaround is produced by four causal mechanisms that cumulatively and interdependently work against the mechanism of decline.