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In this chapter, we explore the relationship between organizational complexity and firm-level innovation. We define and operationalize a new construct, experienced complexity, which is the extent to which the organizational environment makes it challenging for decision makers to do their jobs effectively. We distinguish experienced complexity from structural complexity, which is the elements of the organization, such as the number of reporting lines or integrating mechanisms, that are deliberately put in place to help the organization deliver on its objectives, and we argue that structural complexity correlates positively with firm-level innovation, while experienced complexity correlates negatively with innovation. Using a novel dataset combining survey and objective data on 209 large firms, we find support for our arguments.

This chapter addresses the challenges associated with temporary organising under conditions of institutional complexity. The authors draw on findings from an in-depth case study of a megaproject initiated to reshape healthcare in Sweden. At the centre of this transformation was the construction of a new, ‘world-class’ hospital to replace the former (historical and renowned) university hospital. The authors posit that organising such projects is largely a matter of creating, responding to, and re-creating temporal institutional complexity. Thus, their study identifies four distinct response strategies – innovating, partial decoupling, avoiding, and surfing – on which project actors relied when dealing with the multiplicity of temporal institutional requirements. The authors propose a model for explaining how these strategies affected the temporal institutional complexity faced by the project. Their chapter adds to the literature on temporary organisations by highlighting the nature and dynamics of temporal institutional complexity and by revealing how inter-institutional temporary organisations cope with such complexity.

Organizations today operate in highly dynamic environments and are becoming more complex. Helping their organizations master this complexity is a major leadership challenge. To better understand how managers’ behaviors aggravate or reduce complexity, we reviewed 1,400 responses to a proprietary organizational complexity survey. Analysis identified specific managers’ behaviors that contribute to perceived complexity. We draw from these findings, literature on complex adaptive systems, and our consulting experiences to identify specific strategies managers can use to make it simpler for people to get things done, and even to “master” complexity by turning it into a source of strategic advantage.

Globalization introduces new challenges related to increased levels of diversity and complexity that organizations cannot meet without capable global leaders. Such leaders are currently lacking, so a theory-based approach to global leader development is needed. A critical intermediary outcome that enables competent global leadership performance is global leader self-complexity, defined by the number of unique leader identities contained within a leader's self-concept (self-differentiation) and the extent to which the identities are integrated with the leader's sense of self (self-integration). This research aims to generate and test a theory of the development of global leader self-complexity through identity construction during international experiences. In Study 1, I gathered qualitative data through retrospectively interviewing 27 global leaders about identity-related changes following their international experiences. Using a grounded theory approach, I developed a theoretical model of global leader identity construction during international experiences, which I empirically tested using quantitative data in Study 2. Specifically, I tested the hypothesized relationships through structural equation modeling with cross-sectional survey data from a sample of 610 global leaders. Findings from both studies indicate global leader identity construction during international experiences primarily occurs through interacting with locals and local culture over a sustained period, motivated by appreciation of cultural differences and resulting in increased global leader self-complexity. These results advance understanding of the global leader self-complexity construct (i.e., what develops) and global leader development processes (i.e., how it develops). Additionally, the findings have practical implications for global leader development initiatives.

The conclusions summarize the main empirical evidence that emerged in the book and put forward final reflections and some recommendations for scholars and policymakers. First, the reader is reminded that the book focuses on how a desirable and ambitious agenda that contemplates a progress-oriented policy system is feasible when confronted with the challenges of its implementation and the related problem of coordination between the goals it postulates. The purpose of the concluding chapter is to extrapolate the findings from the individual analyses and synthesize them into a single interpretative proposal centered on two analytical pillars. The first is the analysis and management of the complexity generated by wickedness, through the reconstruction of types of complexity and consequences that the policymaker must acquire in terms of problem setting. The second is the analysis of the skills needed to manage said complexity, distinguishing between linear and nonlinear skills. These are the skills that the policymaker must acquire in terms of problem-solving. Both problem setting and problem solving are summarized in some final recommendations on what to do to improve the feasibility and effectiveness of sustainable development policies: the pragmatic culture of government and some supporting institutional tools, the importance of training as a lever of change, and the building of knowledge infrastructures in terms of evidence-based policymaking.

The purpose of this chapter is to contextualize mixed findings in the self-complexity literature. Self-complexity (when individuals' identity meanings do not overlap) theoretically buffers negative outcomes associated with distressing experiences, like identity non-verification (perceptions that others see individuals differently than individuals see themselves). However, research on self-complexity overlooks the social context in which these processes occur. Here, the author argues that multiplexity (when individuals are connected in two or more role relationships) provides meaningful context that influences whether self-complexity functions as a buffer. This leads to two competing arguments: (1) multiplexity enhances the self-complexity buffering effect and (2) multiplexity undermines the self-complexity buffering effect.

Using egocentric network survey data from 314 US adults, the author ran four regression models (two for the friend identity, two for the coworker identity). These models test whether self-complexity moderates the effect of non-verification on distress when individuals do (or do not) have multiplex ties in which they are close friends with their coworkers.

Multiplex ties amplify the buffering effect of self-complexity when non-verification occurs in the coworker identity, but multiplex ties weaken the buffering effect of self-complexity when non-verification occurs in the friend identity.

This work supports the idea that the benefits associated with self-complexity are conditional on social context as well as identity context. Future research should consider these realities when examining how identity and buffering processes relate to wellbeing.

This work integrates social network analysis and identity theory to reconcile mixed findings in the literature on self-complexity.

Financial analysts' forecasts serve as a proxy for market earnings expectations, and research provides mixed evidence of the relation between financial analysts' expertise and forecast accuracy. The judgment and decision-making (J/DM) literature suggests that those with more expertise will not perform better when tasks exhibit either extremely high or extremely low complexity. Expertise is expected to contribute to superior performance for tasks between these two extremes. Using archival data, this research examines the effect of analysts' expertise on forecasting performance by taking into consideration the forecasting task's complexity. Results indicate that expertise is not an explanatory factor for forecast accuracy when the forecasting task's complexity is extremely high or low. However, when task complexity falls between these two extremes, expertise is a significant explanatory variable of forecast accuracy. Both results are consistent with our expectations.

This paper develops a practice approach to institutional ambidexterity. In doing so, it first explores the ‘promise’ of institutional ambidexterity as a concept to address shortcomings with the treatment of complexity in institutional theory. However, we argue that this is an empty promise because ambidexterity remains an organizational level construct that neither connects to the institutional level, or to the practical actions and interactions within which individuals enact institutions. We therefore suggest a practice approach that we develop into a conceptual framework for fulfilling the promise of institutional ambidexterity. The second part of the paper outlines what a practice approach is and the variation in practice-based insights into institutional ambidexterity that we might expect in contexts of novel or routine institutional complexity. Finally, the paper concludes with a research agenda that highlights the potential of practice to extend institutional theory through new research approaches to well-established institutional theory questions, interests and established-understandings.

Organizations desire more accurate cost systems as competition increases, and consequently increase cost system complexity, as cost systems with greater complexity are potentially more accurate than simpler systems. However, even complex systems are prone to impactful inaccuracies, for example, due to design or calculation issues, that can adversely affect decision-making and firm performance. The authors investigate whether and the extent to which cost system complexity and competition decrease managers’ attribution of cost-system-driven adverse firm effects to the cost system. The authors find greater cost system complexity (by inspiring greater confidence in the cost system) and higher competition (by providing a plausible external cause) decrease managers’ attribution of cost-system-driven adverse firm effects to the cost system. With both greater cost system complexity and higher competition, managers observing signals of material cost inaccuracies are potentially the least likely to attribute cost-system-driven adverse firm effects to the cost system.

Managing complex construction projects is a challenging task because it involves multiple factors and decision-making processes. A systematic evaluation of these complex factors is imperative for achieving project success. As most of these factors are qualitative or intangible in nature, decision makers often rely on subjective judgements when comparing and evaluating them. The hybrid techniques that integrate fuzzy set theory and the analytic hierarchy process (AHP) are able to deal with such problems. This chapter discusses various hybrid techniques of the fuzzy AHP and presents an application of these techniques to the evaluation of transportation project complexity, which is essential for prioritising resource allocation and assessing project performance. Project complexity can be quantified and visualised effectively with the application of the fuzzy AHP. This chapter enhances the understanding of construction project complexity and fuzzy hybrid computing in construction engineering and management. Future research should address the calibration of fuzzy membership functions in pairwise comparisons for each individual decision maker and develop computational tools for solving optimisation problems in the constrained fuzzy AHP. In the area of construction project complexity, future research should investigate how scarce resources are allocated to better manage complex projects and how appropriate resource allocation improves their performance.