In the field of human–computer interaction, Josue and Bahm (2016) propose a method for measuring the emotional impact of pitch videos on sponsors, in line with the results uncovered in the field of marketing regarding the impact of videos on consumer attitudes (Graillot 1996).
The ECF investment framework presents several characteristics that probably make a marketing approach relevant: intrinsic and extrinsic motivations (Hemer 2011), a consumer rather than shareholder logic, linked to limited information and a lack of financial expertise (Bessière and Stéphany 2014), but, above all, a context of persuasion through storytelling, images and video pitches, which are the ingredients of the phenomenon of advertising persuasion studied in the field of consumer theory.
Moreover, beyond the management sciences, in the social sciences and humanities, more specifically, in the fields of the psychology of emotions and judgment and decision-making, the effects of emotional reactions on judgments and decisions are well-established (Zajonc 1980; Frijda 1986; Loewenstein et al. 2001; Slovic et al. 2002; Kahneman 2003). The neurosciences consolidate the theoretical edifice with the work of Bechara and Damasio (2005) on the somatic marker hypothesis, which constitutes, in a way, the linchpin.
This book falls within the field of behavioral finance, at the crossroads of finance and psychology, but is not confined to these disciplines, because knowledge cannot stop at the clear edge of a definition or disciplinary divides. Thus, an interdisciplinary theoretical framework is used, including concepts, models and theories that are reasonably transferable and capable of improving the understanding of our research object.
Purpose of the research
The purpose of this research is to understand, explain and predict the emotional dimension of project choices by ECF investors, without excluding the cognitive dimension. The particular role of a variable of congruence of the investor’s values with those put forward by the project is highlighted, which explains the title of this book. This variable, which is directly related to affective reactions (Schwartz 2006), emerged in the course of the research by means of abductive inference, and was then confirmed theoretically, but also empirically, because of a substantial body of qualitative data. Therefore, from our point of view, the rationality of the investor is complex, an axiological rationality is added to his instrumental rationality, as well as an “affective rationality” that we will define.
This work is exploratory in nature: its aim is to produce an original theory that brings a different and complementary perspective to signal theory. This theory is called the “affective matching” theory; part of its roots lie in the interactionist theory of “Fit-IO” for which individuals are attracted to organizations whose values and norms are congruent with their personal values and norms (Chatman 1989; Kristof 1996; Chapman et al. 2005). The theory of “affective matching” is also in line with the theories of “cognitive consistency” (Vaidis and Halimi-Falkowicz 2007), and it requires the investor to match the project with which they have a minimum “affective distance” or, equivalently, a maximum “affective matching”. The term “affective matching” replaces the term “utility” used in economic decision theory, because the model is not exclusively consequentialist, but nevertheless has similarities with the concept of utility taken from the original meaning of the precursors of decision theory, for which it was a measure of pleasure and punishment (Bentham 1789).
Methodology
Our epistemological approach is postpositivist and the chosen methodology is based on a recursive loop between abduction/deduction/induction types of inference using the body of qualitative data already mentioned (David 1999). An explanatory model is proposed; testing its hypotheses requires the organization of a controlled experiment. Its empirical validation is based on a structural equation model. Additonally, a second model that was developed as an extension of the explanatory model and qualified as an individual predictive model implements the theory of affective matching; testing its predictive quality requires developing an original similarity measure like the distance between vectors.
Expected contributions
The issue of this book is first of all theoretical: this research aims to contribute to the emerging movement of ECF research that advocates a project choice based on the affect and not exclusively on the cognitive. The proposed theory of affective matching and its implementation by an individualized model makes, on the one hand, the prediction of Mangot (2013) – for whom “behavioral finance should not, in the near future, be spared an approach aimed at personalizing behaviors” – a reality and responds, on the other hand, to the call of Pare and Rédis (2011) for the “integration of concepts, and even methods from other disciplinary fields” in order to go beyond the “hypotheses of traditional finance, which are, as has been shown, unsuitable for the new company”.
The theoretical questions to which this book will try to provide some answers are as follows:
– Do values and emotional reactions determine the choice of projects in ECF?
– What are the relative influences of these two variables?
– What is the link between values and affective reactions?
– What is the history of affective reactions?
– In the absence of social interactions, does the affective dimension dominate over the cognitive dimension of choice?
– Can an explanatory and predictive model of individual choice be established a priori based on knowledge of investor preferences?
– Is such a model meant to be normative?
– What is the investor’s rationale?
Beyond the expected theoretical output, this book aims to provide the practitioners of ECF – first and foremost, investors – with a better understanding of their choices and the judgmental biases or heuristics to which they may be unconsciously subjected. The Autorité des marchés financiers (AMF), the French organization whose mission is to protect retail investors, will be able to use these results to back up the warnings given to investors.
Fundraising entrepreneurs will be able to usefully draw conclusions about the factors that attract investors, as this shareholder community is sought after for reasons of cognitive input that go beyond financial input. Other applications of the affective matching model, of an industrial nature, are possible and will be discussed in the conclusion.
General structure
This work is organized into two volumes; the first sets out the choices and theoretical foundations on which the second volume (Goglin 2020), which presents our contribution, is based.
This research is organized as follows: the first part (Volume 1) first presents the context of crowdfunding and ECF and then progressively introduces and justifies the object of this research (Chapter 1). A state of the art that intersects several fields of social science research leads to a theoretical framework (Chapter 2). The second part (Volume 2) opens with the modeling and operationalization of the concepts (Chapter 1 of the second volume). The experimental test protocol is then presented (Chapter 2 of the second volume). The last chapter (Chapter 3 of the second volume) tests the hypotheses and initiates a discussion before the final conclusion.
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