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In recent years, a still heterogeneous set of approaches originating essentially from sociology has renewed the call for caution for anyone intending to develop research on innovation. The collective study coordinated by Godin and Vinck (2017) offers a synthesis of this research: a statement of the various biases faced by researchers who primarily study innovation; a call for enhanced reflexivity; and a desire to identify innovation processes in a comprehensive manner. These critical analyses aim to avoid the reinforcement of a particularly prevalent “ready-made thinking”, whose concrete repercussions go beyond the academic sphere (Sveiby 2017). It is in fact a call for a less enthusiastic, more balanced and nuanced approach. We propose below a synthesis of these approaches, in the form of advice and calls for vigilance, which for the most part echo aspects developed earlier.

Several biases orient the study of innovation in a sometimes very marked direction. In some ways, they also shape managerial practices and political decisions in favor of innovation. The purpose of this section is to identify the factors that prevent us, in a certain way, from considering and analyzing innovation “as it is done”, in as realistic a manner as possible.

These biases are problematic insofar as they contribute to forming excessive confidence in the benefits of innovation, to exaggerating the control exercised over processes and to trivializing disruptive innovations, while strongly orienting towards techno-push proposals. All this is to the detriment of understanding complex, contingent and risky processes that require anticipation and preparation. Derived from or associated with a certain number of myths, they are at the origin of innovation models (Joly 2019). These interpretive frameworks generate shared representations and interpretations of how innovation is produced, then acting performatively, they guide our collective way of seeing innovation. Jasanoff and Kim (2015) speak of socio-technical imaginaries, imbued with values that impact both discourse and practice, more or less consciously.

Table 1.1. Summary of biases in innovation studies

Type of bias	Explanations and effects on the study of innovations
Pro-innovation bias	Taking for granted that innovation is positive, insisting on its virtues and neglecting the study of collateral effects and negative externalities. Understanding it less as a phenomenon to be studied than as a remedy to social and economic problems.
Pro-success bias	Drawing optimistic conclusions (feeding the pro-innovation bias) from the analysis of success (studying what worked). Leaving aside the analysis of unsuccessful projects and semi-failures, which are nevertheless in the majority and rich in lessons learned.
Pro-disruptive innovation bias	Associating innovation with disruption and exaggerating its “disruptive” character. Most often focusing on radical innovations while supporting and incremental innovations (recycling, maintenance are the majority).
Originality bias	Putting creativity and inventiveness on a pedestal. Associating innovation with the pioneering dimension of the precursor. Badmouthing imitation, considered the antithesis of innovation, although it is an integral part of the innovation process. Underestimating the rigidity and caution of most companies which are actually quicker to imitate and draw inspiration from others than to invent.
Short-term bias	Compressing the duration of innovation projects (being the first to market, introducing the novelty to the market and benefiting from a return on investment, keeping followers at bay). Accelerating innovation when real processes often take a long time. Overestimating the control that can be exerted on innovation processes.
Pro-technological innovation bias	Sanctifying technology as the main provider of solutions (“technological solutionism”), to the detriment of a detailed understanding of the problems to be solved. Approach sold as a technological fix to remedy the difficulties generated by the new solutions, thanks to other technological advances. Focusing on high-tech solutions (new technologies) and adding functionalities to the point of forgetting the low-tech possibilities (simplification, minimalism, removal, use or improvement of already proven technologies, continuity, etc.). Relegating service, organizational, process and social innovations to a secondary role.
Pro-business bias	Considering the enterprise, and in particular start-ups, as the natural cradle of innovations. Minimizing or even ignoring innovations coming from the third sector (associations, foundations), public actors or communities of practice (escaping at least temporarily from market-oriented rationale).