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THE ROLE OF EMOTIONS IN USER ACCEPTANCE
Innovation
From their first day, humanity is inventing, discovering and attempting to control and understand his environment. Innovation represents the best way found by human beings to deal efficiently with their constraints (Alter, 2010). Historically, the medieval era is the most impressive in terms of innovations, progress and technical advancements in various domains. In this large period of time, number of innovations (e.g. gunpowder, iron hammer) have been developed and are in some way perceived as the origin of ―the modern world‖ (Whitney, 2004).
As such, contemporary common words as innovation, invention, technical progress are all inherited from the Middle-Ages. First, the term ―invention‖ comes from the Latin ―inventio‖, meaning ―to find and to discover‖. Its utilization goes back to the end of the Middle Ages (XII century). Second, the word ―innovation‖, little more recent, comes from ―innovation‖, meaning ―renewal or change‖. In general, invention is defined as a creation whereas an innovation consists to give sense and efficacy to that creation. That is, innovation represents the social and economical process, bringing the invention to be finally used, or not (Alter, 2002).
In economy, Schumpeter (1934) was the first to introduce the term innovation. His concept of innovation covers five areas: (1) the introduction of a new good (product innovation); (2) the introduction of a new method of production (process innovation); (3) the introduction of a new organization (organizational innovation); (4) the exploitation of new markets; and (5) the introduction of new sources of supply of raw materials. In the framework of this thesis, we will exclusively consider innovations of products. Besides, according to the Organisation for Economic Co-operation and Development (OECD), innovation refers to new or improved goods or services, or methods and opinions which are also marketable. These are far different from organizational innovations that take place in a hierarchical context and lead to organizational structures changes. Products innovations, spread in a market, involve a good or service that is new or significantly improved (OECD definition). Note that numerous innovations do not necessary integrate any technological dimension (50, 98 % according to the OECD).
Generally, we distinguish two types of innovation according to their innovative nature.
First, incremental innovations are characterized by a product or current process amelioration.
They represent the most common innovation given that they pertain to 90% of all innovations. Second, rupture innovations are characterized by the creation of new products or new processes and are based on invention. Nevertheless, an invention or a discovery does not always come into an innovation. To illustrate that point, we can consider the case of the technique of the wheel. Indeed, if the Aztec knew this technique, they never had the idea to utilize it for transport and prefer it for activities relating to games (Alter, 2010). Inversely, an invention can lead to many innovations. It is for example the case of the nylon or the Teflon used in different textiles or materials. In contrast to incremental innovations, rupture innovation are rarer and revolutionize a sector or utilization. For example, in their early days, internet, mobile phones or digital cameras were considered as revolutionary innovations.
Nowadays, technical and social innovations unquestionably contribute to the economic growth. They are key factor allowing companies to avoid price competition by developing specific preferences through innovations offers (Morand & Manceau, 2009). They became very much part of our daily lives, in the private and professional sectors (education, communication, health, leisure, etc.). Indeed, in one century, many innovations have emerged such as the bicycle in 1867, computer in 1969 and the first mobile phone in 1983 in the United States to name few (Fournier, 2010). Unfortunately for innovation companies, not all new products have the same success than those cited above. Indeed, more innovations failed than succeed. According to a high failure rate (about 90% in France), companies have a strong interest in understanding why people accept product innovation. For this purpose, they generally use focus group or individual interviews to ask opinions of a group of people toward a new product in order to understand the conditions that make a product acceptable (or not) by an user before its real use. Next, we elaborate on the question of why would one use a certain innovation and others are reluctant to do so.
Presentation and critics of user acceptance theory
An overview of user acceptance models
Nowadays understanding whether and why users will adopt a new product is a critical issue for innovation companies. User acceptance is considered as a key factor to approach users‘ decision to use or not the innovation proposed. In general, intentions (see figure 3) are used as measures for acceptance and user behaviour (Jamieson & Bass, 1989; Whitlark, Geurts, & Swenson, 1993). Different cognitive-based model have been used to explain user innovation acceptance or use such as the innovation diffusion theory (Rogers, 2003), the technology acceptance model (Davis, 1989; Davis, Bagozzi, & Warshaw, 1992), the unified theory of acceptance and use of technology (Venkatesh, Morris, Davis, & Davis, 2003), the decomposed theory of planned behaviour (Taylor & Todd, 1995), and the social cognitive theory (Compeau, Higgins, & Huff, 1999).
In general, these models predict innovation use based on perceptions and beliefs about the instrumental nature of innovation such as effort and performance expectancy, perceived compatibility, ease of use, uncertainty, relative advantage and adopter characteristics. They have been used to study the acceptance of Information and Technology Systems, Human-Computer Interaction and other new products.
The Technology Acceptance Model (TAM) (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989) is the most widely applied user acceptance model acceptance. It has received support from numerous researches and is considered as a robust framework for predicting user acceptance (Adams, Nelson, & Todd, 1992; Chin & Todd, 1995; Davis, 1993; Taylor & Todd, 1995; Venkatesh & Morris, 2000; Yousafzai, Foxall, & Pallister, 2010). For this reason, we only describe this model in the framework of this thesis. Note that complete reviews cognitive-based model are available in Venkatesh et al. (2003) and Lheureux (2009).
The TAM was adapted from the Theory of Reasoned Action (TRA) (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975). It proposes that perceived ease of use and perceived usefulness are the two most important factors in explaining innovation use (see figure 4).
• Perceived ease of use – the extent to which a person believes using the innovation will enhance his or her performance ;
• Perceived usefulness – the degree to which a person believes using a particular innovation will be free of effort.
Limits of user acceptance model proposed in the literature
Whether the TAM has brought interesting insights to the study of user acceptance, many researchers have criticized user acceptance models such as the TAM. The most common criticism of user acceptance models is that they focus principally on a person‘s cognitions regarding an innovation and do not capture all of antecedents of behaviours such as emotional processes (Bagozzi, 2007). Indeed, emotions are widely recognized as a critical predictor of human behaviours and technology can trigger both positive and negative feelings (Mick & Fournier, 1998). As highlighted in Bagozzi (2007), consumers can, on the positive side, be pleasantly surprised, excited, and confident as they consider the adoption of technology, whereas on the negative side people can be annoyed, worried, or scared. Indeed, individuals are looking for ―fun, amusement, fantasy, arousal, sensory stimulation and enjoyment‖ (Hirschman & Holbrook, 1982, p. 4). It is nowadays commonly admitted that individuals decide to use or not an innovation not only to obtain useful benefits but also to enjoy the experience of using them.
Thus, emotion-based models are needed to complement rational-based approaches. In the next section, we review recent research addressing the influence of emotion on the decision to use innovation. We will see that emotion has been conceptualized in different ways within user acceptance research. Thus in the next section, we use for the sake of clarity the terms referring to emotion as they are originally used in the studies described.
Toward an emotional view of user innovation acceptance
Users do not only perform behaviour in order to achieve utilitarian goals (i.e. improve job performance) but also for hedonic reasons because it triggers positive emotions. That is, from now on, researchers are motivated to examine and incorporate emotional experiences in our understanding of user behaviour. By integrating emotion, researchers attempted to explain more variance in users‘ intention and behaviour (Davis, Bagozzi & Warshaw, 1992). Here, we describe how emotion is conceptualized in innovation research.
Intrinsic motivation: Perceived enjoyment and flow experience
The extension of user acceptance models to motivational models has probably been a first step towards taking into account the emotional factors. The motivational models introduce two constructs: extrinsic motivation and intrinsic motivation. The former refers to an individual‘s personal benefits associated with using an innovation. The latter relates to the desire to perform the behaviour because it is enjoyable (Vallerand, 1997). In this section, we describe two types of intrinsic motivation: perceived enjoyment and flow experience.
Nowadays, it is widely recognized that intrinsic motivation such as enjoyment/fun, playfulness and flow experience are key drivers of individual‘s intention to perform behaviour (Davis, Bagozzi & Warshaw, 1992; Igbaria, Parasuraman, & Baroudi, 1996).
First of all, the construct of enjoyment refers to the extent to which using an innovation is perceived to be enjoyable distinct from any performance results that might be obtained (Venkatesh & Speier, 1999). Empirical findings have shown that enjoyment is sometimes a determinant of behavioural intention (Davis et al., 1992; Ha, Yoon, & Choi, 2007) and other times a determinant of perceived ease of use (Sun & Zhang, 2008; Venkatesh, 2000) or both perceived usefulness and perceived ease of use (Yi & Hwang, 2003). For instance, Koufaris (2002) has shown that enjoyment is positively related to one‘s intention to return to an online shopping website. Therefore, researchers have extended the TAM by including ―perceived enjoyment‖ or ―fun‖ (Bruner & Kumar, 2005; Davis et al., 1989; Davis et al., 1992; Ha et al., 2007).
Secondly, the concept of enjoyment is considered by Moon and Kim (2001) as one of the dimensions of the concept of playfulness. So, the concepts of enjoyment and fun are directly associated to the concept of playfulness. Playfulness refers to three dimensions (i) concentration, (ii) curiosity and (iii) enjoyment (Moon & Kim, 2001). People experiencing playfulness are considered to be more absorbed and interested in their interaction.
At last, most of research on playfulness is based on the concept of flow experience (Csikszentmihalyi & Csikszentmihalyi, 1975) which refers to ―the holistic experience that people feel when they act with total involvement‖ (p. 36). In the literature, flow has been treated as multi-dimensional construct with several characteristics such as enjoyment and concernment (Ghani & Deshpande, 1994), control, attention, curiosity and intrinsic interest (Trevino & Webster, 1992). Agarwal and Karahanna (2000) considered cognitive absorption (CA) as a state of flow and they have described five of its dimensions in the context of software – temporal dissociation, focused immersion, enjoyment, control and curiosity. Moreover, some researchers have examined how ―flow experience‖ influence motivation adoption. For example, Hsu and Lu (2004) have revealed that the acceptance of on-line games can be predicted by extended TAM and that flow experience significantly and directly affected intentions to play on-line games.
In general, concepts of enjoyment, playfulness or flow experience seem to be good predictors of intention to use an innovative product or service. However, these concepts seem more appropriate to study the ―acceptation‖ of an innovation rather than the ―acceptability‖ since it involves the use or the manipulation of the innovation before deciding. Indeed, as mentioned by Terrade and collaborators, the intention to use an innovation can be studied before the user have had the opportunity to manipulate the innovation (i.e. acceptability) or when the user have had the possibility to manipulate at least once the innovation (i.e. acceptation) (Terrade, Pasquier, Reerinck-Boulanger, Guingouain, & Somat, 2009). We will see that a large part of research on intention to use an innovation focuses on ―acceptation‖ rather than on ―acceptability‖.
Pleasure and arousal
In the innovation literature, researchers have been interested in pleasure and arousal in order to capture the emotional reactions to stimulus. Mehrabian and Russell (1974) categorize the affective state along three dimensions: pleasure, arousal, and dominance (PAD). Pleasure refers to the degree to which a user feels good or happy with technology products in the use while arousal concerns the degree to which a user feels stimulated or excited from using an innovation (Kim et al., 2004; Lee, Ha & Widdows, 2011). Because dominance – defined in terms of control versus lack of control- has been shown to have a trivial effect on behaviour (Russell & Pratt, 1980), authors in general have been only interested in pleasure and arousal dimensions.
For instance, Kulviwat et al. (2007) have merged two models: the TAM and the PAD (the Pleasure, Arousal and Dominance paradigm of affect). They have called this unified theoretical framework, the Consumer Acceptance of Technology (CAT). Results showed a significant improvement in predicting adoption intention compared to TAM and that both pleasure and arousal (but no dominance) are significant predictors of attitude toward adoption. Thereby, being pleased and excited about a new technology positively influences the user‘s attitude toward adoption.
Moreover, Lee, Ha, and Widdows (2011) have investigated the influence of both cognitive and affective states on consumers‘ technology product evaluation and their subsequent behaviour. Based on Stimulus-Organism-Response (S-O-R; Mehrabian & Russell, 1974), the authors argue that an innovation through their attributes triggers users‘ cognitive and emotional states, leading to avoidance-approach behaviour. In their study, they focused on six aspects of technology product attributes: usefulness, ease of use, innovativeness of technology, visual appeal, prototypicality, and self-expression. Thus, respondents (high-technology product users) had to complete a survey based on their experiences with their own technology products. Results suggest that attitude and pleasure influence approach-avoidance behaviour directly, but arousal affects approach-avoidance behaviour indirectly via pleasure. That is, in addition to identifying key product attributes that play a role in consumer adoption of technology products, Lee and collaborators (2011) allow to identify the underlying process whereby product attributes influence consumer behaviour (approach–avoidance behaviour). Interestingly, they conclude that it is important to focus on the meaning of products (i.e. possibility to maintain social networks or express identity) in order to deliver a pleasing user experience.
The studies presented in this section show some differences regarding the status of emotion: sometimes a determinant of attitude, other times a co-determinant of intention to use innovation with attitude. Besides, it also seems that these studies address the emotion in terms of a cognitive approach, which we describe in more details in the second chapter. In other terms, emotions seem to directly arise from the evaluation of the characteristics of an innovation (prototypicality, usefulness, ease of use, and so on). In the next section we propose to present other dimensions that have been investigated in the literature.
Positive and negative emotions
Many recent studies have focused on positive or negative emotion. For instance, Arkkelin (2003) showed that positive affect towards a learning tool leads to gaining experience knowledge and self-efficacy regarding usage and negative affect causes students to avoid the learning tool. Besides, Cenfetelli (2004) has found that positive emotions such as fondness, happiness, joy and satisfaction were positively related to perceived ease of use and that negative emotions such as unhappiness, worry, anger, nervousness, regret, disgust, fear, anxiety and irritation were negatively related to perceived ease of use. Emotions also were significant predictors of technology usage. Emotions were measured via the scale proposed by Diener, Smith, and Fujita (1995).
Moreover, Beaudry and Pinsonneault (2010) have studied the influence of four classes of emotion in the use of a new banking system toward account managers. Drawing on appraisal theories of emotions (Smith & Ellsworth, 1985), they focused on anger (loss emotion), anxiety (deterrence emotion), happiness (achievement emotion) and excitement (challenge emotion). Appraisal theories of emotions are described in the chapter 2 of the manuscript. According to the authors, loss emotions are triggered by the perception of a threat and lack of control over the system‘s consequences. Deterrence emotions occur when the system is perceived as ―a threat and the individual feels that he/she has some control over its consequences‖ (p. 696). Challenge emotions are triggered by the perception of an opportunity and control. Achievement emotions ―result from the appraisal of an upcoming event that will generate positive outcomes‖ (pp. 697). In their study, account managers had to indicate how they felt each emotion at the announcement of the deployment of the new system and how often they used the new system to perform a list of specific tasks such as collecting information or negotiation. Results showed that excitement was not directly related to IT use but indirectly positively related to IT use through task adaptation which is seems consistent, according to the authors, with the evidence that ―excitement promotes creativity and flexibility in thinking, problem solving and performing specific tasks‖ (p. 704). Happiness was positively related to IT use. Anger and anxiety were not related to IT use directly.
Finally, Wood and Moreau (2006) have developed and validated the E3 (expectation → emotion→ evaluation) model. Interestingly, the E3 model allows describing how emotion arises in the early use of complex products. Indeed, the authors considered that users have expectations about the difficulty he/she will experience in using a new product, which would influence the quality of the usage experience. In turn, emotion would influence product evaluations. In their research, emotions were measured via a modified version of Izard’s (1977) differential emotion scale.
In the previous section, we saw that emotional experiences can be function of the product‘s characteristics and the gained benefits for the user. Interestingly, this section brings new suggestions for going further on our subject and to answer the question about how emotion arises. Indeed, Beaudry and Pinsonneault (2010) showed that specific emotions are associated with specific pattern of appraisal even if we don‘t totally agree with the category proposed. Nevertheless, the authors allow going beyond a valence-based approach. We will have the opportunity to discuss it at the end of this chapter. Moreover, Wood and Moreau (2006) suggested, through the E3 model, that emotions are determined by bottom-up process (products characteristics) but also by top-down processes (expectations). We now propose to address in more details the influence of expectation on product evaluation and more precisely on satisfaction.
Satisfaction
Multiple definitions of ―satisfaction‖ exist. In general, researchers considered satisfaction as a construct both cognitive and affective. For example, Legris, Ingham, and Collerette (2003) have defined satisfaction as ―the sum of one‘s feelings or attitudes toward a variety of factors‖ (p. 192). The construct of satisfaction has also been described, in ICT literature, as a positive attitude and perception toward an object (Bailey & Pearson, 1983; Melone, 1990). However, whether the boundaries between emotion and attitude, sometimes seem unclear, researchers have tried to distinguish them. Bhattacherjee (2001) for instance proposes that ―satisfaction is a transient experience-specific affect, while attitude is a relatively more enduring affect transcending all prior experiences‖ (p. 354).
Moreover, the construct of satisfaction has been mostly studied within the expectation-confirmation theory (Oliver 1977, 1980) which aims to explain why people accept or reject an innovation after using it. Indeed, business management has generally considered satisfying users to be a successful way of increasing user intention, user loyalty or repurchase intention. According to the expectation-confirmation theory, satisfaction is function of the level of confirmation or disconfirmation of expectations originally made by a user vis-à-vis an innovation. Whether, there are different standards of comparison, the most common is the expectations of performance (Tse & Wilton, 1988, Oliver et al., 1994, Ha, 2006; Battachjee & Premkumar, 2008). Broadly, confirmation or disconfirmation of expectations depends on the perceived performance of the innovation. Therefore, users compare innovation performance to their expectations when making satisfaction evaluations. Several studies have shown the effectiveness of this theory in predicting user acceptance and use of Information Technology (Bhattacherjee, 2001; Bhattacherjee & Premkumar, 2004; McKinney, Yoon, & Zahedi, 2002; Battacherjee & Premkumar, 2008; Roca et al., 2006, Thong et al., 2006).
Additionally, other studies have suggested that merely satisfying users is not enough to ensure the success of an innovation. That is, another stream of research has studied the construct of ―delight‖ (Chitturi, Raghunathan, & Mahajan, 2008; Kumar, Olshavsky, & King, 2001; Oliver, Rust, & Varki, 1997; Rust & Oliver, 2000). For example, Yang (2011) has focused on the development of a ―customer delight barometer‖. Besides, Spreng, MacKenzie, and Olshavsky (1996) have pointed out that satisfaction research has mainly focused on the disconfirmation of expectations, rather than on desires.
They considered that ―expectations are beliefs about the likelihood that a product is associated with certain attributes, benefits, or outcomes, whereas desires are evaluations of the extent to which those attributes, benefits, or outcomes lead to the attainment of a person’s values‖ (pp. 17). Though, they confirmed the importance of desires congruency as a determinant of satisfaction. Therefore, user satisfaction and user acceptance are considered to be the two dominants approaches within which perceptions of innovation success have been investigated (Wixom & Todd, 2005). The authors have successfully attempted to integrate the user satisfaction and technology acceptance literature. According to the authors satisfaction ―is a person‘s feelings or attitudes toward a variety of factors‖.
Finally, satisfaction has been studied in relation to usability. According to Brangier and Barcenilla (2003), satisfaction refers to an affective reaction related to the use of a device and eventually associated with the pleasure to use. In that case, satisfaction is linked to the usability of the system and its instrumental qualities.
To conclude this section, we first can note a conflicting conceptualization of the satisfaction construct. The boundaries between emotion and attitude also seem unclear. Secondly, interesting researches have introduced the constructs of ―delight‖ and ―desire‖. That is, the concept of satisfaction and usability has recently evolved to the concept of user experience.
User experience
Developed over the past fifteen years, the concept of user experience is an evaluative approach that gives a central place to affect ( see review by Hassenzahl & Tractinsky, 2006; Mahlke, 2008). Indeed, according to ISO: ISO 9241-210 (2010), user experience (UX) includes all the users’ emotions, beliefs, preferences, perceptions, physical and psychological responses, behaviours and accomplishments that occur before, during and after use.
Whether the UX concept seems accurate in the framework of this thesis centred emotions, it nevertheless poses many conceptual issues. Indeed, whether the concept of user experience has the advantage to go further a simple vision of instrumental value of the product (i.e., usefulness and ease of use), it is also perceived as an umbrella concept, associated with a wide range of meanings, such as beauty, hedonic aspect (Forlizzi & Battarbee, 2004). So it is not a surprise if the concept of UX has been massively discussed in the literature (Beauregard & Corriveau, 2007). Many definitions of user experience exist. For instance, according to Hassenzahl and Tractinsky (2006), user experience is ―a consequence of user‘s internal state (predispositions, expectations, needs, motivation mood, etc.), the characteristics of the designed system (e.g. complexity, purpose, usability, functionality, etc.) and the context (or the environment) within which the interaction occurs (e.g. organisational/social setting, meaningfulness of the activity, voluntariness of use, etc.) » (p. 95). Besides, presenting different design projects such as Gustbowl – a communication tool designed to connect children and parents, the authors discussed the influence of emotion in business. Interestingly, they show that emotions are not only important as antecedents of product use and evaluative judgements but emotions also are important as consequences of product use.
Finally, from a review of literature and empirical results, Thüring and Mahlke (2007) have proposed a model (CUE-Model), which incorporates various components of user experience found in different approaches. They identified three central components: the perception of instrumental qualities (usability, usefulness, ease of learning, etc.); the perception of non-instrumental qualities (aesthetic values, symbolic, etc.); and emotional reactions. That is, emotions are considered to be function of different aspects of the quality of the system (Figure 5).
Table of contents :
I. INDUSTRIAL CONTEXT
Description of the Ixiade Group
Activities of the Ixiade Group
II. REQUEST OF THE COMPANY
GENERAL INTRODUCTION
PART 1 – REVIEW OF THE LITERATURE
CHAPTER 1 – THE ROLE OF EMOTIONS IN USER ACCEPTANCE
I. INNOVATION
II. PRESENTATION AND CRITICS OF USER ACCEPTANCE THEORY
II.1 An overview of user acceptance models
II.2 Limits of user acceptance model proposed in the literature
III. TOWARD AN EMOTIONAL VIEW OF USER INNOVATION ACCEPTANCE
III.1 Intrinsic motivation: Perceived enjoyment and flow experience
III.2 Pleasure and arousal
III.3 Positive and negative emotions
III.4 Satisfaction
III.5 User experience
III.6 Anxiety
IV. CONCLUDING COMMENTS
CHAPTER 2 – AN OVERVIEW OF CONTEMPORARY APPROCHES TO EMOTIONS
I. WHAT IS AN EMOTION?
I.1 Conceptual Definitions and Distinctions
I.2 Appraisal Theory Approaches to Emotion.
II. THE INFLUENCE OF SPECIFIC EMOTIONS ON JUDGMENT AND DECISION MAKING.
II.1 Beyond Valence: The Appraisal-Tendency Framework
II.2 Emotion and Motivation
II.3 Empirical Contemporary Research to Emotion
a. Differentiating specific emotions to understand their behavioural implications
b. What about positive emotions?
CHAPTER 3 – PRESENTATION OF THE RESEARCH QUESTIONS
PART 2 – EMPIRICAL STUDIES
CHAPTER 1 – AFFECT EXPECTATIONS AND SPECIFIC EMOTIONS AS GUIDES TO BEHAVIORAL INTENTION WITH RESPECT TO INNOVATIONS
INTRODUCTION
I THEORETICAL BACKGROUND
I.1 Expectation disconfirmation theory versus Affective expectation theory
I.2 A model of expectations and post-use emotions: satisfaction or delight?
I.3 The present study and hypothesis
II METHOD
II.1 Participants and Design
II.2 Stimuli description
II.3 Procedure
II.4 Measures
II.5 Covariables
III RESULTS
DISCUSSION
CHAPTER 2 – WHY ARE WE PURCHASING PRODUCTS? TOWARDS A DYNAMIC VIEW OF THE IMPACT OF SPECIFIC EMOTIONS ON PRODUCT DESIRABILITY
INTRODUCTION
I THEORETICAL BACKGROUND
I.1 Dynamic affect regulation model versus static affective evaluation model
I.2 The present study and hypothesis
II METHOD
II.1 Participants and Design
II.2 Procedure
III RESULTS
DISCUSSION
CHAPTER 3 – LET’S PLAY OR SAVOR: THE INFLUENCE OF SPECIFIC EMOTIONS ON INNOVATIVE PRODUCT DESIRABILITY
INTRODUCTION
I RESEARCH IMPLICATIONS: THE MEDIATING ROLE OF EMOTIONSPECIFIC SHORT-TERM GOALS
I.1 Satisfaction
I.2 Amusement
I.3 Overview
II STUDY 3
II.1 Method
II.2 Results
II.3 Discussion
III STUDY 4
III.1 Method
III.2 Results
III.3 Discussion
GENERAL DISCUSSION
PART 3 – GENERAL DISCUSSION AND CONCLUSIONS
GENERAL DISCUSSION
CONCLUSIONS
RESUME FRANÇAIS
INTRODUCTION
ETUDE 1
ETUDE 2
ETUDES 3 & 4
