In recent decades, design creativity and design theory have made great progress in terms of understanding and supporting the logic of engineering design for breakthrough and disruptive innovation. Design for transition relies on these new methods, but it also requires the capacity to be creative to facilitate more effective preservation – whether in terms of natural resources, biodiversity, energy, ways of life or other factors. Design for transition calls for a type of engineering design that is not Schumpeterian, not a ‘creative destruction’, but rather a design that manages creative preservation, creativity for better preservation and preservation for improved creativity. In the first section, we clarify the notion of creative preservation for transition; in the second section, we show how creative preservation can be addressed by recent advances in design theory, namely, C-K/Topos. Finally, in the conclusion, we demonstrate the implications of C-K/Topos for the management of the unknowns of transitions and the underlying logic of creative preservation.

To address the social and environmental challenges (also called 'grand challenges') faced by our society, new forms of collaborative and innovative processes are needed to support profound transformations of socioeconomic ecosystems. In such contexts, actors are likely to be highly distant from each other, not only geographically but also cognitively (having heterogeneous knowledge and expertise), organisationally (being scattered across different organisations and possibly sectors) and institutionally (not sharing the same rules and norms). This paper defines these types of contexts as situations of 'grand distance' where collaborative innovation is hindered by too large a degree of cognitive, organisational and institutional distance. This paper thus aims to shed light on a specific class of co-design methods, called 'resilient-fit co-design methods', which help manage the distance between highly heterogeneous actors to foster collaborative innovation. An example of grand-distance situations can be seen in the field of Earth observation (EO), where data-based solution designers undertake dedicated co-design efforts to integrate data into multiple ecosystems with the specific aim of addressing contemporary socioenvironmental challenges. Based on an in-depth empirical investigation of two case studies in this field, this paper describes how resilient-fit co-design methods can be built in such contexts, revealing their similarities and specificities with respect to existing co-design methods. This paper also highlights several original forms of ecosystem dynamics, which are driven by external actors and oriented towards locally enhancing the resilience of ecosystems. As such, this research offers theoretical and practical contributions that enrich the pool of available co-design methods necessary for the transformation of socioeconomic ecosystems to address grand challenges.

Technology platforms spanning several scientific and technological fields hold great promise, both as future innovative tools for industry and as future experimental tools for academia. However, some of their characteristics are also still unknown and need to be designed. A classical approach to initiate their evolution dynamics is to seek funding for a subsequent design project. Using a single case study, we show that a much less costly approach is possible: adding training to the platform can play a central role in increasing the intensity of its use, with both scientific and industrial impacts. Yet, this approach requires that the training knowledge enables the exchange of ‘independent knowledge’ between platform designers and users: this demanding condition requires further research to characterise this promising training model which we propose to call “double impact training”.

Current transitions, such as digital and ecological ones, bring new challenges for organizations, characterized as unknowns. Addressing them requires new management paradigms for which design-based methods show promise. Yet their organizational implementation remains limited, what this paper investigates. Based on a two-year collaboration with a French healthcare company, the study involved developing, delivering and evaluating a four-day training program. Based on interviews and evaluations from 65 participants, results indicate high satisfaction, significant habit disruption and intent to adopt design-based tools. Due to the development of a common language in the organization and the emphasis on learnings’ co-creation, this training had a transformative power. Thus, highlighting its practical value and opening pathways for exploring its long-term impact on organizational practices.

This novel contributions reveal how environmental regulations drive engineering design costs, focusing on the emblematic case of packaging. Using a regulatory database and simulation-based modeling, we evaluate functional expansion as a key driver of cost escalation, identifying its volume effect (rising costs from added environmental functions) and scope effect (increased interdependencies among ecosystem actors). The findings offer a simulated cost envelope to support engineering design teams in their forecasts, but also underscore the hurdles of sustainably managing these regulatory-driven costs in the packaging product system, by benchmarking cost trajectories against sustainability metrics, such as carbon pricing.

Owing to their wide accessibility, data are currently at the root of many opportunities and challenges. Among the opportunities is the value that data can generate for innovation and new product development. The managerial implementation of this so-called value generation constitutes an associated challenge. This study addresses this issue with the goal of proposing a rationalisation of data management that allows organisations to leverage data for innovation. We draw upon knowledge management (KM) literature because data and knowledge have been closely linked for decades, as seen in the knowledge pyramid linking data to wisdom. Akin to KM practices, we begin by uncovering the four necessary dimensions that must be structured to leverage data (generation, relations, usage, and technologies). By recalling the singularities of data compared with knowledge, we hypothesise that anomalies play a potential role in operationalizing this framework for value generation. Evidence from several case studies support the proposed framework and lead us to introduce the notion of data heritage as a necessary condition for initiating a value generation process from data. Second, we highlight the importance of coupling between this data heritage and the knowledge heritage of organisations. Third, we emphasise that this coupling can be effectively realised through anomalies. Consequently, in response to recent calls in innovation management literature, this study provides insights into value generation from data by indicating several necessary conditions that need to be fulfilled. Moreover, it also benefits the KM literature by stressing the logic of a new KM pyramid.

Over the past few years, with the advent of ChatGPT, generative artificial intelligence (GenAI) has been at the centre of numerous discussions regarding generative and creative power, especially with the hope that it will enhance human creativity and, consequently, transformative power. Creativity, especially human creativity, has long been studied, particularly by psychologists and design scientists, who have revealed the difficulty of overcoming the fixation effect. This effect can hinder creativity and has not yet been explored in relation to GenAI, even though it is of major importance for understanding creative issues. In this work, we propose leveraging the rich body of literature on design creativity and creativity management to shed light on the fixation effect related to GenAI tools, which are considered partners in the design process, and possible defixation techniques. To study this issue, we propose a twofold methodology: a first, in-depth qualitative step with design theory experts, leading to the formulation of hypotheses, and a second, experimental step based on the well-documented egg task in creativity to test the hypotheses. Ultimately, we show that the use of GenAI tools in creative endeavours results in a greater number of generated ideas and that it does not prevent the fixation effect but can foster idea exploration and thus help with second-order defixation. These results consequently show the importance of considering a cocreativity regime involving both humans and GenAI, and they extend knowledge on the fixation effect in this context. They also indicate the capacity of GenAI in creative processes, thus suggesting some relevant use cases to leverage these tools.

This paper explores the generativity of generative design algorithms (GDAs). Generative design (GD) is a process in which designers assign some of their tasks to a computational tool to generate a set of design solutions. While GDAs have been heavily studied, few studies have focused on assessing their generativity; that is, their capacity to help designers create novel proposals that go beyond their initial knowledge. To address this gap, this research compares two GDAs, namely, NSGA-II and MAP-Elites, in terms of their capacity to generate Pareto fronts composed of highly varied design solutions (Pareto fronts with this property are called “splitting Pareto fronts” in this paper). Both algorithms are applied to the industrial design problem of constructing a battery layout for an electric vehicle. A statistical and empirical analysis of the design solutions generated is conducted. The results show that the Pareto fronts generated by MAP-Elites offer designers more degrees of freedom than those generated by NSGA-II do. Thus, the study highlights that the degrees of freedom afforded by GDAs depend on the working principles of the algorithms. From a practical point of view, the results of this study indicate that a GDA can artificially reduce the degrees of freedom of designers. This pressing issue is discussed to help designers make the best use of GDAs.

Some companies invest in fundamental research, but many struggle when developing novel in-house scientific knowledge and integrating it into their new inventions. While the literature advocates revised approaches to better understand this phenomenon, we investigate the processes that lead to Simultaneous Discovery-Invention (SDI). By adopting an abductive process, we propose a model that highlights the mechanisms of SDI. Notably, we reveal that teams must preserve independence in creative exploration during scientific knowledge creation and invention generation while maintaining intensive original knowledge exchange among them. We also demonstrate that anomaly detection and peer validation mechanisms are mandatory for SDI. We evaluate our model with a case study in the food industry: the discovery that CRISPR-Cas9 is an adaptative defense immune system of bacteria and the associated innovations in this industry. Finally, we discuss the insights provided by our model and the implications of our case study.

Co-design workshops seek solutions to complex, multi-stakeholder issues. These ephemeral encounters bring together designers and uninitiated individuals who embark in a facilitated process that mobilizes a range of simplified design tools and methods. Despite co-design's benefits in terms of representation and acceptability, these workshops also come with limitations and often fall short of their intended goals. Proceeding from stylized facts informed by both our experience and the literature, this study investigates why co-design struggles at maintaining engagement and fails to consistently deliver innovative output regardless of the number of participants involved. Namely, we employ a modelbuilding strategy to illuminate the main knowledge dynamics during workshops and to highlight a constrained 'reactive expansion' mechanism that explains known co-design's shortcomings. Implications for workshop facilitation and planning are offered in closing. (c) 2024 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Tackling grand challenges requires new forms of collaborative innovation to support intricate design processes involving heterogeneous actors. This article specifically investigates how co-design supports the anchoring of promising novelties into multiple socio-technical systems to accelerate their respective sustainability transitions. A co-design framework adapted to this multi-system context is derived from transition research and design and innovation management research. The framework is validated empirically based on 27 case studies where the novelty to be anchored corresponds to Earth observation data. Contributing to transition research, the article shows how this multi-system co-design framework provides novelty developers with a diagnostic tool to clarify their anchoring strategy, by framing the relevant actions to conduct at different time horizons. Several enrichments of the anchoring concept are also proposed, highlighting some complementarities between different forms of anchoring and the endless property of the process. Contributing to design and innovation management research, the article sheds light on co-design in an original perspective by considering a context crossing the usual boundaries of socio-technical systems and focusing on a diagnostic dimension preceding the organization of collective design sessions. The co-design framework also highlights a so-called “resource-based” form of collaborative innovation aiming to build novelty-based resources for heterogeneous actors facing grand challenges. This approach complements more common “challenge-based” approaches aiming to directly address a targeted challenge.

Recent theories of creative thinking propose that the generation of creative ideas by design novices and experts is restricted by the emergence of intuitive cognitive biases. To overcome these biases and explore expansive solutions, biased ideas must be discriminated from those with creative potential. Although studies in the field of reasoning have shown that biased participants tend to detect an incongruency between their provided solutions and the expected solution, the use of conflict detection in creativity has never been studied. Two experiments were conducted to determine the extent to which conflict detection occurs during creative idea generation and whether this mechanism is available for design novices (Experiment 1) and/or experts (Experiment 2). The results indicated that both groups of participants detected their fixation bias and managed to overcome it by switching from intuitive to deliberate thinking. In addition, we discussed implications for popular current (dual process) models.

AbstractMost manufacturing companies have tested and adopted sustainable design methods to navigate their product's environmental transition. While successful at first in enhancing their environmental performance, these companies later struggle to pursue their environmental transition. This entails mastering two critical competencies: identifying transition unknowns, and fostering adequate design efforts. This action research with an innovative design intermediary - which has completed four sustainable packaging missions - reveals the specific design barriers encountered for environmental transition.

Fixation is a cognitive bias hindering creativity through the activation of previous knowledge. This phenomenon is well-known in the literature, as demonstrated by the many studies on actions to help individuals overcome fixation effects. However, these studies have often focused on individuals as ideators overcoming their own fixations and not on the ability of leaders to help ideators overcome their fixations. This study tested different factors, such as fixation heterogeneity (difference in fixations between ideators and leaders), design (having leaders design on the creative problem), and reading ideas of ideators, to understand their effects on the ability of leaders to direct ideators toward creativity using directive feedback. We set up an experimental protocol simulating an interaction between a participant, in the leader role, and a (computer-simulated) ideator, where the participant had to help the ideator to be more creative by providing directive feedback. An analysis of the results highlighted a phenomenon of rejection of certain ideas that were inconceivable for the participants, which led to better creative results for leaders not having the same fixations as ideators. This rejection phenomenon was significantly less important when participants were allowed to design without a reading phase before giving feedback.