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The objective of this paper is to develop a comprehensive model of supply chain and supply chain decision‐making complexity that provides an understanding of the drivers of supply chain complexity and strategies to manage supply chain and supply chain decision‐making complexity and outcomes.

Grounded theory methodology is employed to build a theory of supply chain and supply chain decision‐making complexity and develop propositions related to antecedents, moderators, and outcomes of supply chain complexity. In addition, extensive literature review and informal interactions with a number of supply chain professionals have been used to validate the theory.

In addition to identifying the antecedents of supply chain complexity, the authors explore strategic, human cognitive ability, and tactical moderators for managing supply chain complexity.

The comprehensive framework presented in the paper builds a theory of supply chain and supply chain decision‐making complexity that is grounded in empirical data. The research also incorporates disparate findings, constructs from multi‐disciplinary research on supply chain complexity and provides future research directions.

The research helps practitioners better understand the sources and outcomes of supply chain complexity and how to manage it. Various strategies to moderate the impact of supply chain complexity are presented.

An integrated, comprehensive theory of supply chain complexity is proposed along with definitions of supply chain complexity and supply chain decision‐making complexity. The proposed model is rooted in actual practice and supported by the existing literature.

The purpose of this paper is to investigate how management attention and supply chain complexity affect the decision-making process and cost estimation accuracy of supply chain design (SCD) decisions.

The research follows an embedded case study design. Through the lens of the behavioural theory of the firm, the SCD decision process and realised outcomes are investigated through longitudinal data collection across ten embedded cases with varying degrees of supply chain decision-making complexity and management attention.

The findings suggest that as supply chain decision-making complexity increases, cost estimation accuracy decreases. The extent to which supply chain decision-making complexity is readily recognised influences the selection of strategies for information search and analysis and, thus, impacts resulting cost estimation errors. The paper further shows the importance of management attention for cost estimation accuracy, especially management attention based on conflicting goals induce behaviours that improve estimation ability.

A framework proposing a balance between supply chain decision-making complexity and management attention in SCD decisions is proposed. However, as an embedded case study the research would benefit from replication to externally validate results.

The method used in this study can identify how supply chain complexity is related to cost estimation errors and how management attention is associated with behaviours that improve cost estimation accuracy, indicating the importance of management attention in complex supply chain decision-making.

We conduct an experiment asking participants to choose to purchase either a traditional or hybrid car to examine how federal-state conformity of tax incentives impacts the decisions of taxpayers. We also examine perceptions of taxpayers surrounding federal-state conformity. Consistent with theory related to the effects of information environment and using an experiment in which taxpayers are asked to evaluate tax incentives related to a purchase decision between a traditional and hybrid car, we find that conformity is a significant factor in increasing the propensity to take advantage of the tax incentive. Specifically, we find that participants with simple and conforming federal-state incentives are more likely to take advantage of the tax incentive than with complex and conforming federal-state incentives. In addition, the effects of conformity between federal and state incentives suggest that participant perceptions of the federal system were heavily influenced by the actions of the state.

The purpose of this paper is to contribute to solving the complexity problem as increased complexity is a main reason why projects fail to reach their goals, and it is unclear what complexity is.

Conceptual development integrating theories of materiality, teleology, and complexity, decision-making theory, communication theory, coordination theory, and qualitative, quantitative and participatory approaches are used in this paper.

To understand complexity, it is necessary to develop a material-systemic process approach and to distinguish structured from unstructured complexity. The social actors construct a complex material-systemic process between themselves and nature to handle unwieldy outer nature. The material-systemic approach reveals how materiel life-world arenas are developed through increased complexity and specialization. Handling complexity is possible by materiality in general and structural material in special, the interplay between inner time (planning) and outer time (production), and between human subjects and an underlying coordination mechanism. It is a systematic organizational blockade that reproduces internal complexity as unstructured and incomprehensible complexity.

The practical models of organizing are tested to the highest degree in construction industry. It is a task to try and examine the models in other types of projects.

The paper offers a proposal to a theoretical solution to the complexity problem going back to the roots in Enlightenment and shows at the same time through practical models how increased complexity may be the most important productive force in future projects.

The purpose of this paper is to highlight how systems thinking contributes to decision making in uncertain contexts that are characteristic of service systems. Based on the assumption that service systems face complex conditions, the paper posits that systems thinking may support the understanding of key issues in service management.

This paper proposes an interpretation of complexity in the context of service systems, which highlights the perspective change that occurs when a systems approach is adopted. The offered conceptual perspective is then brought to an operational level, in spite of the complexity of the decisions driving a viable system, by modelling a service system as a network of agents, resources, processes and decisions through the use of fuzzy logic. The paper reviews service management research streams, and takes a deeper look at the concepts of service systems and complex service systems. The paper then proceeds to discuss how systems thinking contributes to service management by proposing a systems interpretation of complexity.

Service management theories and models may be enhanced by integrating prevailing approaches, based on a quantitative and mechanistic view of service systems dynamics, with systems thinking‐based meta‐models that can be used in better understanding service exchanges. The findings of the paper also show how the integration of an engineering approach can be insightful to the understanding of service systems; adopting a Viable Systems Approach (VSA) as a meta‐model can be useful in fully comprehending market behaviour in uncertain conditions.

The originality of this paper lies in exploring the contribution of systems thinking, in particular of the Viable Systems Approach (VSA), to service management and decision making.

While previous health-care-related hybridity research has focused on macro- and micro-level investigations, this paper aims to study hybridization at the organizational level, with a specific focus on decision-making. The authors investigate how new politico-economic expectations toward a university hospital as a hybrid organization become internalized via organizational decision-making, resulting in the establishment of a new business collaboration and innovation-oriented unit.

The authors employed a social systems theoretical framework to explore organizational decision-making processes involved in the establishment of the new hybrid hospital unit. Drawing on 15 interviews and nine organizational documents, the authors describe and analyze three decision-making cycles using the concepts of complexity, decision and justification.

The findings reveal the challenging nature of decision-making during hybridization, as decisions regarding unprecedented organizational structures and activities cannot be justified by traditional decision premises. The authors show that decision-makers use a combination of novel justification strategies, namely, justification by problems, by examples and by obligations, to legitimize decisions oriented at non-traditional activities. Further, the analysis reveals how expectations of several societal systems, i.e. health care, education, science, law, economy and politics, are considered in decision-making taking place in hybrid organizations.

The study draws attention to the complexity of decision-making in a hybrid context and highlights the role of justification strategies in partially reducing complexity by concealing the paradoxical nature of decision-making and ensuring the credibility of resulting decisions. Also, the study presents a move beyond the dualism inherent in many previous hybridity studies by illustrating the involvement of several societal systems in hybridization.

Noting the scarcity of complexity techniques applied to modelling social systems, this paper attempts to formulate a conceptual model of decision‐making behaviour within the information systems evaluation (ISE) task, against the backdrop of complexity theory.

Complexity theory places an emphasis on addressing how dynamic non‐linear systems can be represented and modelled utilising computational tools and techniques to draw out inherent system dynamics. In doing so, the use of fuzzy cognitive mapping (FCM) and morphological analysis (MA) (hence a fuzzy‐morphological approach), is applied to empirical case study data, to elucidate the inherent behavioural and systems issues involved in ISE decision making within a British manufacturing organisation.

The paper presents results of applying a combined FCM and MA approach to modelling complexity within management decision making in the ISE task: both in terms of a cognitive map of the key decision criteria; a matrix of constraint criteria; and a synthesised model that provides an indication of the linkages between technology management factors and organisational imperatives and goals. These findings show the usefulness of viewing the topic in complexity science terms (emergent behaviour, non‐linearity and chaotic response).

This research is limited in applying the given technique to a single case study organisation in the UK manufacturing sector, where the sample size is limited. Since this is the first time that such a combined MA‐FCM technique has been used in this field known to the authors, future research needs to validate and explore the implications of this approach in a wider context (multiple organisations and viewpoints).

The paper highlights the need for those involved in analysing managerial decision making to include aspects of complexity theory in their evaluations – namely uncovering inherent inter‐relationships that may exist between stakeholders, processes and systems. In doing so, expanding the manager's understanding of how to achieve congruence between driving forces and factors, which may exhibit non‐linear, chaotic or feedback behaviour.

The given research brings together both artificial intelligence and operational research techniques, applied in the socio‐technical milieu of information systems evaluation, within the context of complexity theory, in order to describe the rich detail within the ISE decision‐making task.

The purpose of the paper is to develop a theoretical framework with testable propositions discussing the role of counterfactual thinking in fostering accurate decision-making in groups and preventing catastrophes, being mediated by information searching, sharing, task conflict and conflict management mechanisms, moderated by task complexity, cognitive complexity, cognitive closure and tolerance of ambiguity.

A theoretical framework is formulated and propositions are postulated involving independent, mediating, moderating and dependent variables.

This paper recommends a helpful framework for understanding of how counterfactual thinking affects information searching, sharing and decision-making accuracy in groups, thereby preventing catastrophes.

The proposed framework might be of assistance in managing complex group decision-making and information sharing in organizations. Decision-makers may become aware that activating counterfactual mind-set enables them to search for critical information facilitating accurate decision-making in groups leading to catastrophe prevention.

This paper adds value to the field of counterfactual thinking theory applied to group decision-making. Moreover, the paper provides a novel framework for group decision-making which sheds light on pertinent variables, which can either ameliorate or exacerbate the accuracy of decision-making by information searching and sharing in groups under varying context of high/low task complexity. The ramifications of task conflict, conflict management mechanisms, team diversity and size are explored alongside the moderating role of cognitive complexity, cognitive closure and tolerance for ambiguity.

This paper aims to examine the relationship between the characteristics of strategic decision-making team’s mental model and its performance. The authors propose that the relationship between mental models and performance is two-way, rather than one-way. Thus, performance feedback should, in turn, influence strategic behavior and future performance by either triggering or hindering the learning process.

The authors conduct the research in the setting of a simulation experiment. A longitudinal data set was collected from 36 teams functioning as strategic decision makers over three periods.

This study provides support for the positive impacts of both the complexity and centrality of a team’s mental model on its performance. The authors also find that positive performance feedback reduces changes in complexity and centrality of team mental models due to cognitive inertia.

The study contributes to the literature by investigating the specific mechanisms that underlie mental model evolution. Different from the existing studies on team mental models that mainly focus on similarity of these shared cognitive structures, this study examines another two characteristics of team mental model, complexity and centrality, that are more relevant to the strategic decision-making process but has not been extensively studied in the team literature. In addition, this study reveals that performance feedback has different effects on team mental models depending on the referents – past performance or social comparison – which advances the understanding of the learning effects of performance feedback.

Complexity has been called the 21st-century supply chain (SC) challenge. Most SC managers view it as a necessary evil, ever-present, costly and tough to manage, and few prioritize it. Still, anecdotes suggest some leverage it to drive operational excellence. This study aims to explore how they do it, delving into the development of a complexity management capability, under what circumstances it emerges and its effect on competitiveness.

To better understand why, and how, companies develop (or not) a distinctive SC complexity management capability, this study employed an inductive study of 10 leading European companies, each operating a complex SC.

Although SC complexity raises costs, increases disruptions and makes decision-making difficult, few companies have made complexity management a priority. Among those, most focus on reducing or absorbing complexity to improve operational excellence. A few invest to develop a distinctive SC complexity management capability. They manage complexity for market success. The interaction among competitive pressures, managerial attitudes and investments delineate a dynamic capability development process.

Despite extensive research on complexity drivers, the tools used to manage SC complexity and the impact of SC complexity on performance, the interplay among factors that promote, or hinder, the development of an SC complexity capability continues to be poorly understood. By mapping the complexity capability development process, this study explicates a more nuanced approach to managing SC complexity that can yield a competitive edge.

SC complexity prevails because the dynamic, iterative complexity capability development process is overlooked. Managers can use the complexity capability roadmap to assess the cost/benefits of pursuing a distinctive complexity management capability more accurately.

This study demystifies the development of a complexity management capability, showing how some companies develop the capability to distinguish between value-added and value-dissipating complexity and thus become empowered to leverage SC complexity for competitive advantage.