Managerial control mechanisms and their influence on project performance: an investigation of the moderating role of complexity risk

Abstract

PurposeDespite the efforts of project managers and the widespread use of project management methodologies, most of the projects remain unfulfilling in terms of delivering targeted performance. This for most part can be attributed to the inability of an organization to implement control mechanisms and ineffective management of complexity risk. Keeping in view the aforementioned problem, the objective of this study is to investigate the association between control modes and project performance. Moreover, this study also examines the moderating role of complexity risk on the association among various control modes and project performance.Design/methodology/approachThe data were collected from 171 construction projects through a postal questionnaire survey. Partial least squares structural equation modeling was utilized for testing the hypothesized relationships of the research model.FindingsThis study found significant positive relation between formal and informal control mechanisms and project performance. It is found that complexity risk significantly moderates the relationship between control modes and project performance. The results indicate that complexity risk positively moderates the relationship between outcome control and clan control with project performance. Furthermore, complexity risks negatively moderates the relationship between behavior control and project performance. However, the association between self-control and project performance is found insignificant in the presence of complexity risk.Originality/valueThis study is the first attempt to study the relationship of control mechanisms, complexity risk and project performance in the construction industry.

Public procurement of engineering services: the influence of task characteristics on organisational control

“…In Table 6, the control modes for both phases suggested by the expanded model and the procurement model (Eriksson, 2006;Eriksson and Laan, 2007) are outlined. Thus, in accordance with Kirsch et al (2010) and Maqsoom et al (2020), applying the empirical data to the expanded model and the procurement model (Eriksson, 2006;Eriksson and Laan, 2007) illustrates that social control is optimal when uncertainty is perceived high.…”

“…However, risk is argued having a known probability, whereas uncertainty is argued having an unknown probability (ibid). In addition, risk has been used as a moderator between control modes and performance (Maqsoom et al, Das and Teng, 2001;Liu, 2015;Maqsoom et al, 2020), whereas it is argued that uncertainty should affect the choice of control modes (e.g. Gencturk and Aulakh, 1995;Schilke and Lumineau, 2018;Lin et al, 2019;Yang et al, 2022), thus a task characteristic (antecedent) and not a moderator.…”

Effect of customer cooperative behavior on reverse logistics outsourcing performance in the construction industry – A partial least squares structural equation modeling approach

“…Acceptable R 2 values depend on the research disciplines (Hair et al , 2016). Studies in the construction management field follow the suggestions of Chin (1998) that R 2 values of 0.19, 0.33 or 0.67 are considered weak, moderate or substantial, respectively (Maqsoom et al , 2020; Wang et al , 2019). The three dimensions of cooperative behavior (commitment, cooperation and planning) produced an R 2 value of 0.54, indicating that 54.0% of variance in RLOP was explained by the cooperative behavior.…”

“…PLS-SEM is appropriate when the research goal focuses on maximization of the explained variance in the endogenous constructs, identification of important “driver” constructs or extension of a theory (Hair et al , 2011). PLS-SEM can work efficiently with small sample sizes and address the non-normal data distribution problem to produce robust results (Hair et al , 2011; Maqsoom et al , 2020; Wang et al , 2019). In this research, PLS-SEM was selected to test the conceptual model for three reasons.…”

Management control structures and performance implications in international construction joint ventures: critical survey and conceptual framework

“…Their poor performance could be connected to key challenges in the complex interorganizational relationships – for example, the control structures available for use (Wang et al , 2017; Han et al , 2019). Studies have shown that with management control, firms can improve performance (Ghauri et al , 2013; Maqsoom et al , 2020), manage risks effectively (Bing and Tiong, 1999), bring to success strategic goals (Yan and Gray, 2001b) and exploit completive advantage (Ozorhon et al , 2010b). Thus, management control acts as a significant determinant of performance in ICJVs.…”