Unveiling the dynamic complexity of rebound effects in sustainability transitions:Towards a system's perspective

Rebound effects (RE) are systemic responses to sustainability-oriented actions that have relentlessly offset the anticipated effects, hindering sustainability transitions. Limitations to account for feedback, delays, and non-linearities hinder a deep understanding of RE, leading to divergent magnitude estimates and management recommendations. Therefore, a better understanding of the dynamic complexity surrounding RE occurrence is needed. Dynamic complexity manifests from the feedback relationships between system elements and how they change over time. This work aims to enhance the understanding of RE's causal and dynamic traits, following system dynamics (SD) as the investigation frame. Based on a literature review, 24 RE-specific dynamic complexities were identified and further categorised following the Iceberg model, which deepens into the causes of RE occurrence, providing additional leverage to prevent or mitigate them. The RE-specific dynamic complexities are then explored in case studies investigating RE through SD, which sustains three propositions for moving forward in RE investigations. This work sets the foundation for enabling less deterministic examinations of RE, capable of reaching recommendations that consider the true nature of the phenomenon

Towards a systemic view on rebound effects:Modelling the feedback loops of rebound mechanisms

Rebound Effects (RE) are systemic responses that are relentlessly hindering the achievement of sustainability actions’ intended effects. Despite the wide recognition of RE, the limited understanding of the underlying causal structures sustaining their occurrence hampers the ability to anticipate, prevent, and tackle them. To explore how feedback thinking can explain the occurrence of RE, this paper describes the structure of 26 rebound mechanisms based on qualitative system dynamics (SD) modelling using causal loop diagrams (CLD). Apart from a comprehensive catalogue of mechanisms, the elicitation of two generic rebound mechanisms reveals that RE are either the result of (1) reinforcing loops acting against quick fixes to control local resource consumption or (2) balancing reactions in the opposite direction of attempts to control local resource consumption leading to escalation behaviour. Four contributions highlight how this research supports a systemic view on RE, the natural evolutionary step required to understand and manage its occurrence

Replicating Lean Six Sigma Green Belt Education

Purpose – This paper describes the intricates and possibilities of replicating a Lean Six Sigma Green Belt (LSSGB) education model from a pilot program to other universities—employing ‘replication as strategy’—based on a validated ‘business model.’ Study design/methodology/approach – This work is grounded in a case study on the ESTIEM LSSGB educational method and draws on the replication literature. Specifically: (1) replication as strategy (Winter and Szulanski, 2001) to replicate stimulating learning environments, and (2) replicating sets of teaching practices (Baden-Fuller and Winter, 2007). These theories are practiced using data obtained from various sources: Participant-observer data, interview data, and secondary case data. Findings – To replicate this educational program, a thorough understanding of the ‘business model’ of the LSSGB course is required. This includes a clear understanding of what is valued in each local environment, what configurations of practices create such value, and what environments contain the inputs that stimulate such value creation. Moreover, the replicating speed is substantially affected by the replicators’ knowledge on recognizing course locations for replication and successfully implementing a new course with a suitable configuration. In conclusion, replication of teaching practices between courses is mediated by predefined high-quality course content. Originality/value – The LSSGB course in ESTIEM shows how blended learning opportunities can be configured to deliver impact on a European scale. Decomposing a course to teaching practices and analyzing their inputs identifies the environmental requirements for a course. Keywords Lean Six Sigma, blended learning, replication, replication as strategy, ESTIEM Paper type Research pape

A dynamic perspective on collaborative innovation for smart city development:The role of uncertainty, governance, and institutional logics

Collaborative innovation is at the heart of smart city development, yet also notoriously challenging due to fundamental differences between public and private sector actors that need to collaborate, while dealing with high levels of uncertainty. Whereas existing practice-based work on collaborative innovation describes various relevant antecedents, barriers and success factors, this prior work potentially underestimates the true complexity of collaborative innovation initiatives. Therefore, scholars have increasingly called for a more dynamic, theoretical understanding of collaborative innovation. In response to these calls, our study draws on institutional theory to build a dynamic understanding of collaborative innovation for smart city development. Specifically, we conduct a longitudinal in-depth case study to develop a causal loop model, grounded in rich qualitative data, to capture and theorize the key behavioural patterns of a collaborative innovation initiative for smart city development. The model describes how the dynamic interplay between uncertainty, adherence to own institutional logics and governance complexity can both enable and undermine collaborative initiatives. We contribute by developing a dynamic theoretical perspective on collaborative innovation, one that promotes cross-fertilization at the intersection of the smart city theory, organization theory and collaborative innovation literature. Moreover, our findings highlight the important role of organization theory, specifically institutional logics, in explaining the collaborative dynamics of smart city development.<br/

Determining intervention thresholds that change output behavior patterns

This paper details a semi-automated method that can calculate intervention thresholds—that is, the minimum required intervention sizes, over a given time frame, that result in a desired change in a system’s output behavior pattern. The method exploits key differences in atomic behavior profiles that exist between classifiable pre- and post-intervention behavior patterns. An automated process of systematic adjustment of the intervention variable, while monitoring the key difference, identifies the intervention thresholds. The results in turn can be studied and presented in intervention thresholds graphs in combination with final runtime graphs. Overall, this method allows modelers to move beyond ad hoc experimentation and develop a better understanding of intervention dynamics. This article presents an application of the method to the well-known World 3 model, which helps demonstrate both the procedure and its benefits

Overcoming transformational failures through policy mixes in the dynamics of technological innovation systems

The need for challenge-led innovation policies to address grand societal challenges is increasingly recognised at various policy levels. This raises questions how to overcome a variety of ‘failures’ prohibiting innovations to flourish. A key-line of thought in theory and policy emerged since the late 1990s on the role of system failures, next to more conventional market-failure thinking. More recently, scholarly work introduced the notion of ‘transformational failures’, which implies an even broader perspective on innovation failures as resting in challenges related to transforming entire systems of production and consumption. This paper combines the literature on Technological Innovation Systems (TIS) with literature on multi-level approaches to sustainability transitions to make a contribution to this debate. In particular, this paper argues that the current literature, so far, has failed to explore how different kinds of policies, or policy mixes, can overcome transformational failures. The paper uses a simulation model (i.e. a system dynamics model) and illustrative examples on electric vehicles to explore relations between transformational failures and (mixes of) policy interventions. A key conclusion is that, in particular in the case where an emerging TIS is in a competitive relation with an incumbent system, overcoming transformational failures can be realised either by directly addressing the incumbent system, for instance by taking away its resources (which may be political challenging). Alternatively, the model results show that a clever mix of policy interventions elsewhere in the system may lead to sufficient performance improvements of the emerging TIS so that it can challenge the incumbent system on its own – albeit with a need for substantial additional resources

Game of skill or game of luck? Distant search in response to performance feedback

Despite its strategic benefits, there is persistent heterogeneity across firms to what extent they engage in distant search activities. According to the default prediction of behavioral theory of the firm (BTF), poor past performance will increase a firm's propensity for distant search, whereas good performance will lead to a decrease. However, a contrasting view is taken within the emerging capability cue perspective, which predicts the opposite. To understand these conflicting views, we emphasize the key role of context that is formed by a firm's sectoral innovation pattern and shapes the dominant cognition of firms' managers. Building on this sectoral innovation perspective and Pavitt's seminal work (1984; 1995) we distinguish between a science-based innovation pattern (here, we focus on the semiconductor industry) and a specialized-supplier innovation pattern (we focus on the machinery industry). The key claim we make is that different sectoral innovation patterns shape other dominant managerial cognitions, leading to a different interpretation of past performance that influences the decision to increase or decrease distant search. Our paper contributes to an understanding of how the competing ideas on different ways in which firms respond to feedback, in view of distant search, can be reconciled. We also contribute to the literature on technological innovation by considering the role of managerial cognition and how differences therein can be associated with different firm choices on their distant search activities

Combining system dynamics modeling with other methods: A systematic review

Although&nbsp; a significant number of system dynamics (SD) studies draw on multi-method approaches, there is not much knowledge on when and how SD is combined with other methods. Yet, combining SD with other methods allows both researchers and practitioners to enhance the contribution of their modeling work. For a comprehensive review of current SD multi-method practices, this paper draws on an assessment of 45 studies that used SD modeling along with at least one other method. We adopt an evidence-based systematic approach in reviewing these studies and find that additional methods can be embedded in two main phases in the SD modeling process: conceptualization and simulation. Our review contributes to the multi-methodology research practice by consolidating one of the main areas where substantial experience in combining methods has been obtained. In addition, this paper provides insights and a reference point for system dynamicists who wish to go beyond stand-alone SD modeling in addressing complex problems. The paper concludes with suggestions for future research in this area

Overcoming transformational failures through policy mixes in the dynamics of technological innovation systems

\u3cp\u3eThe need for challenge-led innovation policies to address grand societal challenges is increasingly recognised at various policy levels. This raises questions how to overcome a variety of ‘failures’ prohibiting innovations to flourish. A key-line of thought in theory and policy emerged since the late 1990s on the role of system failures, next to more conventional market-failure thinking. More recently, scholarly work introduced the notion of ‘transformational failures’, which implies an even broader perspective on innovation failures as resting in challenges related to transforming entire systems of production and consumption. This paper combines the literature on Technological Innovation Systems (TIS) with literature on multi-level approaches to sustainability transitions to make a contribution to this debate. In particular, this paper argues that the current literature, so far, has failed to explore how different kinds of policies, or policy mixes, can overcome transformational failures. The paper uses a simulation model (i.e. a system dynamics model) and illustrative examples on electric vehicles to explore relations between transformational failures and (mixes of) policy interventions. A key conclusion is that, in particular in the case where an emerging TIS is in a competitive relation with an incumbent system, overcoming transformational failures can be realised either by directly addressing the incumbent system, for instance by taking away its resources (which may be political challenging). Alternatively, the model results show that a clever mix of policy interventions elsewhere in the system may lead to sufficient performance improvements of the emerging TIS so that it can challenge the incumbent system on its own – albeit with a need for substantial additional resources.\u3c/p\u3