The themes of technological innovation, entrepreneurship, and organizing

Self Regulation on Innovative Products Choice

Paulo Henrique Muller Prado

Federal University of Parana, Brazil

Danielle Mantovani Lucena da Silva

Federal University of Parana, Brazil

Jose Carlos Korelo

Federal University of Parana, Brazil

ABSTRACT

This chapter explores how choice goals influence consumers ’ innovativeness in a product category domain. The intentions to adopt new products are guided by promotion and prevention self-regulation systems. Thus, two of the choice goals were classified as promotion goals—justifiability and choice confidence—and two were classified as prevention goals - anticipated regret and evaluation costs. Two groups emergedfrom the analysis: one named “most innovative” and another called “less innovative.” When comparing the groups, the results show that the “most innovative” cluster demonstrated higher choice confidence, higher justifiability and was more capable of avoiding a possible choice regret. The differences found in the group analysis highlight the need of understanding in further detail how consumers behave during the choice process of innovative products. Therefore, the Regulatory Focus Theory has been shown to be very important for understanding the choice process, especially for the innovation adoption.

INTRODUCTION

Consider two individuals. One is Peter, who is worried about avoiding negative consequences. Thus, when he uses his cell phone he is probably more concerned about losing any information,

DOI: 10.4018/978-1-61350-165-8.ch027 such as his contacts, calls, e-mails and any other thing that may be important to him. On the other hand, John always approaches positive results in his daily life, and he uses his cell phone to try to achieve these positive results, such as be in con­tact with his friends, be able to check his e-mail wherever he is and register some good moments by using his cell phone to take pictures. Peter and

John use their cell phones with the same goals (e. g. make calls, surf the internet, check e-mails, send messages to their contacts). However, they are very different in the way they try to achive a goal. Peter is more concerned about avoiding negative consequences whereas John probably seeks to achieve positive ones.

One day, Peter and John decide to upgrade their equipments to a better one, with new attributes and services. In this situation, these consumers will be faced with a lot of options and alterna­tives that will make their choice more difficult. Their choice process will probably be very dif­ferent as well. Peter will prefer attributes that fit his prevention-focused orientation and John will prefer attributes that fit his promotion-focused orientation. Peter and John might end up buying different cell phones or maybe one of them may abdicate upgrading, just because he could not find any option that fits his self-regulation orientation.

When people pursue a goal, they begin with some motivational orientation, some concerns or interests that direct the goal pursuit, and the self­regulation orientation is one of these concerns (Freitas & Higgins, 2002). The two scenarios above illustrate two distinct goals highlighted in regulatory focus theory (Higgins, 1997), which builds on the general hedonic notion that people approach pleasure and avoid pain. The theory distinguishes between two major categories of desired goals: those that relate to attaining posi­tive outcomes such as advancement, achievement, and aspirations (termed promotion goals), and those that relate to avoiding negative outcomes, such as responsabilities, obligations and security (termed prevention goals). According to the regu­latory focus theory, individuals with a promotion focus will regulate their behavior toward positive outcomes, and those with a prevention focus will regulate their behavior away from negative outcomes (Liberman et al., 2001).

There are some studies that have explored the choice process topic of research (Coupey, 1994; Dhar; Nowlis; Sherman, 1999; Chernev, 2006; Thompson; Hamilton; Rust, 2005) and specifically, some studies (Herzenstein; Posavac; Brakus, 2007; Alexander; Lynch Jr; Wang, 2008) emphasize that it is important to understand con­sumer’s behavior that are more interested in trying new products and services. Bettman (Bettman, 1979; Bettman, Luce, & Payne, 1998) proposed that consumers usually have a set of goals which are pursued during most of the choice situations. Furthermore, studies of the choice process must consider the choice goals in order to understand the heuristict strategies that consumers use to decide which product to buy (e. g. Bettman; Johnson; Payne, 1991; 2000; Heitmann; Lehmann; Her­rmann, 2007).

These goals may influence consumers in a different way, depending on the individual dif­ferences or on the characteristics of the choice context (Kahn, Luce, & Nowlis, 2006). Thus, the impact of the choice goals on the innovativeness process has not been studied yet. Therefore, it has become relevant to understand how choice goals influence consumers’ innovativeness, and how this relationship applies to the organizational strategy. In order to achieve this goal, an extension of part of the model proposed by Heitmann, Lehmann and Hermann (2007) is suggested in this study, relating the innovativeness in a product category domain to the choice goals. The choice goals are analyzed from the self-regulation perspective (Higgins, 1997). The self-regulation approach to studying the innovation and decision processes highlights the possibility of exploring how these two variables relate to each other in the consumer behavior context.

The importance of Heitmann, Lehmann and Herrmann (2007)’s study to understand the choice goals is that they have classified these goals ac­cording to the regulatory focus theory, which was proposed by Higgins (1997). Thus, there are goals that are pursued in order to avoid negative consequences of the choice, and goals that are pursued so as to achieve positive results of the choice process.

The use ofthe regulatory focus theory to study the innovation adoption process highlights the possibility to explore how the two regulatory foci (promotion and prevention) are related to consum­ers’ behavior. For instance, Herzenstein, Posavac and Brakus (2007) found that when risks associated with a new product are not specified to consum­ers, promotion-focused consumers state higher purchase intentions than prevention-focused consumers. Nevertheless, when the judgmental context makes the risks salient, prevention and promotion-focused participants are equally un­likely to purchase the product. Therefore, Peter, who is more prevention-focused and John, who is more promotion-focused, will have different decisions regarding an innovation. However, we do not know yet how Peter and John achieve their goals in order to become more innovative. That is what we are going to understand in this chapter.

THEORETICAL DEVELOPMENT Innovativeness

Rogers (2003) explains that an innovation is an idea, practice or object that is perceived as new by the individual. Thus, a product will be considered an innovation only if it adds new attributes and/ or benefits, and consumers are more likely to adopt an innovation if it is perceived as useful and important to the individual. In a series of studies, Okada (2006) demonstrates that consumers with existing products are more likely to upgrade when the enhanced product is generally dissimilar to the existing product. For instance, a new cell phone will be considered an innovation and thus more likely to be adopted if it is perceived as dissimilar to the existing version of the product.

However, when we analyse individuals’ innovation adoption, we need to consider the innovativeness behavior. Rogers (2003, p.22) defined innovativeness as the “degree to which an individual is relatively earlier in adopting an innovation than other members of this system.” In an earlier study, Hirschman (1980) had stated that this author conceptualized innovativeness as a variable that all individuals have, in a greater or lower degree. Thus, it is a construct that can be generalized to all product categories. Roehrich (2004) explains that the novelty seeking is mea­sured in a series of activities, which leads to three different types of innovativeness behavior: (1) in­novativeness information, that is the information acquisition of a new product; (2) innovativeness adoption, that is the adoption of the new product; and (3) the innovativeness use, that expresses the product use in a different way or all the ways of using the product. This categorization increases the interest consumers will have toward new products.

Another important innovation characteristic is that it has two dimensions: symbolic and tech­nological (Hirschman, 1980). The symbolic in­novation communicates a different social meaning than it previously did. Its physical form remains predominantly unchanged but the meaning as­signed to that form is novel. The technological innovation possesses some tangible features never previously found in that product category and can be adopted because of the features’ performance and new functionalities (Hirschman, 1980).

As individuals do not adopt an innovation all at the same time, they can be classified in an adoption categorization (see Figure 1). These categories are: (1) innovators; (2) early adopters; (3) early majority; (4) late majority; (5) laggards. Rogers

(2002) proposed this categorization to facilitate group comparisons.

Rogers (2003) explains that the innovators are adventurous. The innovators can deal with the uncertainty about an innovation and are experts in the innovation adopted. They represent only 2.5% ofthe population. The early adopters, which represent 13.5% of the population, are more in­tegrated to the social system than the innovators because they act locally. This group is closer to other members of the social system and work as an example to the other groups. The early major-

Figure 1. Innovativeness categorization (Source: Adapted from Rogers [2003, p. 251])

early / early

ity (34% of the population) adopt a new idea before the average of the members of the social system. They interact with the early adopters and among their group, but they are not opinion lead­ers. The late majority adopt new ideas after the majority ofthe members ofthe social system. The adoption, for this group, is a result of an eco­nomic need or due to a pressure of their group. They are not used to adopting an innovation, until the majority of their group has adopted it. The laggards are the last group in a social system to adopt an innovation and do not have any lead­ership opinion. They are very isolated inside the social system and their reference point is the past. They usually interact with people with tradi­tional values and their decision process to adopt an innovation is slower than the other groups. In addition, their resources are limited and they need to be certain that the new idea is going to work to be adopted (Rogers, 2003).

During the 90’s, some researchers began to consider the innovativeness in a product category as different construct ofthe innate innovativeness, which is an individual characteristic (Goldsmith; Hofacker, 1991; Goldsmith; Freiden; Eastman, 1995). Goldsmith and Hofacker (1991) state that the innovativeness construct is very specific, and a consumer that is innovative in a product category, may not be innovative in another. The authors proposed the Domain Specific Innovativeness (DSI) scale, with six items that measure the in­novativeness in a product category. In our study, we follow the perspective of the innovativeness in a product category because we are analysing techonological product, which is a specific product category.

Self-Regulation

The value given to pursue a certain goal varies due to its importance to the individual (Higgins et al., 2003). As a result, people pursue goals that fit their values. This prediction is based on the Regulatory Focus Theory (RFT) (e. g., Higgins, 1997; Freitas; Higgins, 2002). Higgins (1997) proposed this theory, which introduces the concept of regulatory focus, a principle that underlies the hedonic principle that people seek pleasure and avoid pain. The RFT demonstrates that there are different ways of approaching pleasure and avoiding pain. The differences in performance, emotions and in decision making may occur as a result of the individual’s self-regulation.

This theory has two foci: promotion and pre­vention, which are different in their strategies to achieve a final end state. The promotion-focused

individuals favour approach strategies, so they frame goal pursuit in terms of gains and non­gains; prevention-focused individuals do so with respect to losses and nonlosses because of their preference for avoidance strategic means. Under a promotion focus, the individual’s strategic in­clination is to approach matches to end states he or she would like to achieve (Freitas & Higgins,

2002) . Such individuals are more eager to avoid errors of omission (i. e., missing an emerging opportunity to accomplish something), resulting in an initial inclination to act (Liberman et al,

2001) . In contrast, a prevention focus fosters a tendency to avoid mismatches to end states he or she would like to attain, with an orientation toward maintaining the status quo and shielding oneself from losses. Such individuals therefore prefer cognitive or behavioral courses that avoid errors of commission (i. e., making mistakes).

Self-Regulation and the Role of the Choice Goals in Innovativeness

Bettman (1979) proposed that consumers have a hierarchy of goals, which they seek to achieve during the choice process. Bettman, Luce and Payne (1998) argue that these goals are the most important motivational aspects to the decision making process. The authors explain that these goals are inherent to most of the choice contexts and determine the main aspects of the choice process analysis. In order to understand how con­sumers assess their choices, Heitmann, Lehmann and Herrmann (2007) related the choice goals pro­posed by Bettman (e. g., Bettman, 1979; Bettman, Luce, & Payne, 1998) to the Regulatory Focus Theory (RFT). Two of the goals were classified as promotion goals—justifiability and choice confidence—and two were classified as prevention goals—anticipated regret and evaluation costs.

Consumers will value a goal if it is important for them (Higgins et al., 2003). Therefore, people pursue goals and get more engaged in the choice process that fit their values (Freitas; Higgins, 2002; Lee; Keller; Sternthal, 2010). This predic­tion comes from the RFT, which suggests that the regulatory fit that people experience when the manner of their engagement in an activity sus­tains their goal orientation or interests regarding that activity, their motivation to pursue that goal increases. This prediction is also based on the self­regulation. More promotion-focused individuals will be more engaged to achieve promotion goals whereas prevention-focused individuals will be more engaged to achieve prevention goals.

When we analyse the promotion goals (choice confidence andjustifiability), we find that they are related to each other and also impact the preven­tion goals (evaluation costs and anticipated regret) (Heitmann; Lehmann; Hermann, 2007). Bettman, Luce and Payne (1998) state that the confidence during the choice process is a consequence of the use of more compensatory choice strategies. Thus, the justifiability also increases the choice confidence.

H1: Consumers’choice confidence is a positive function of the higher justifiability during the choice process.

When analyzing the impact of the choice confidence on the other choice goals, we must bear in mind that the negative emotions that result from a bad choice is a consequence of the lack of confidence in the decision process (Bet - tman; Johnson; Payne, 1991; Landman, 1993; Tsiros; Mittal, 2000). After the decision is made, individuals that are not confident about the right choice, often ask themselves if they should have looked for a better option.

In addition, the application of the anticipated regret goal in the innovation context, Bettman, Luce and Payne (1998) and Heitmann, Lehmann and Herrmann (2007) state that decision makers feel that they are being evaluated by others (e. g., family and friends) and by themselves about their decisions. As a consequence, consumers try to anticipate regret and do this by searching for more information, in order to maximize the accuracy of their decision. Some studies (e. g., Stone, 1994; Chernev, 2006; Heitmann; Lehmann; Herrmann, 2007) also demonstrate that uncertainty about the choice leads to a lack of confidence, which increases the probability of regretting the choice.

Studies (e. g., Stone, 1994; Chernev, 2006; Heitmann; Lehmann; Herrmann, 2007) also dem­onstrate that consumers that are more uncertain about a choice are also less confident, which increases the probability of regretting the choice after the decision is made. Hence, we propose our second hypothesis.

H2: The higher the choice confidence, the higher the anticipated regret.

The evaluation cost of the choice process can be defined as the cost associated with the information search and analysis of a decision process of a product or service (Burnham; Frels; Mahajan, 2003). This cost is not just about the economic aspects, but also about the time spent searching information, analysing the alternatives and learning how to use the new product. Thus, time and effort are associated with collecting the information needed to evaluate potential al­ternative providers. Mental effort is required to restructure and analyse available information in order to arrive at an informed decision (Burnham; Frels; Mahajan, 2003).

Consumers are also likely to perceive higher evaluation costs when products are complex, be­cause the difficulty in understanding the product leads to uncertainty, and increases the percep­tion that a negative outcome may occur (Holak; Lehmann, 1990; Luce; Bettman; Payne, 1997). Similarly, the large number of attributes associated with complex products makes both information collection and direct comparison attributes more costly (Shugan, 1980)

Herzenstein, Posavac and Brakus (2007) state that those consumers guided by the promotion - focused self-regulation are more innovative, once they are more confident in the choice process. When the promotion goals are achieved, it is easier to achieve the prevention goals (Higgins,

2003) . Therefore, for consumers that have higher decision difficulty, the choice confidence becomes more important and will have a stronger impact on the evaluation costs.

H3: The lower the choice confidence, the higher the perception ofthe evaluation costs during the choice process.

Individuals that feel more insecure about the choice often have more difficulty in anticipating regret. Even after the decision is made, these individuals are not sure about the best alternative or option for that moment. As a consequence, they question themselves about the possibility of searching more information and invest more time to get a better option (Heitmann; Lehmann; Herrmann, 2007).

These consumers are also less confident and believe that a longer decision process might be better (Bettman; Luce; Payne, 1998). Consumers that are more worried about avoiding regret are more motivated to get engaged in order to reduce the possibility of a negative consequence of a decision (Zeelenberg, 1999).

H4: The perception of the evaluation costs is a negative function of the anticipated regret during the choice

Choice Goals Influence on the Innovativeness

The literature demonstrates that the adoption intentions for new products are guided by pro­motion and prevention self-regulation systems (e. g., Herzenstein, Posavac, & Brakus, 2007). Concerning the promotion goals, the confidence during the choice process is a consequence of the use of more complete and compensatory choice strategies (Bettman; Luce; Payne, 1998).

Promotion-focused consumers are more likely to purchase new products than prevention-focused consumers because they demonstrate higher choice confidence (Chernev, 2006; Herzenstein, Posavac, & Brakus, 2007).

The choice confidence is related to the thought that positive results may arise from the choice pro­cess. Therefore, the choice process is constructive (Bettman; Johnson; Payne, 1991; Bettman; Luce; Payne, 1998), and when consumers are faced with the possibility of upgrading to a better product, they will probably remember the rules that were applied to choose the last product. Cowley (2001) states that individuals use only one piece of this information. However, this recovered informa­tion is more reliable and influences the current choice process.

Concerning this process, there are situations where the assortment of options and features is high, such as in the case of technological prod­ucts, which decreases consumer’s confidence in the decision process. In spite of this situation, those consumers with a promotion-focused self­regulation are more confident, because they expect positive results (Chernev, 2006). As a result, they become more innovative. We summarize this discussion with the following hypothesis:

H5: The innovativeness in a product category is a positive function of the choice confidence.

It is possible that the justifications that con­sumers use during the choice process are above certain aspects, such as the trade-off between cost and benefits. In some situations, the lack of justifiability may lead the consumer to stop the choice process and abdicate the idea of buying the product (Hsee et al., 2003; Okada, 2005; Amir; Ariely, 2007).

Chernev (2001) also proposed that consum­ers evaluate common features in a manner that confirms their already established preferences. When the consumer is in a choice situation, he is more likely to justify his decision, for instance, by the preference that he already has for a particular brand. This decision behavior demonstrates that individuals try to find reasons that are consistent and acceptable both for themselves and for others. Thus, choice confidence is a positive function of the justifiability (see H1).

Murray and Haubl (2007) analysed this be­havior and demonstrated that consumers tend to keep a product or a brand to try to avoid switch and search costs for a possible better alternative. In addition, as consumers already know the cur­rent product they have been using, it is easier to justify their decision when they keep this product. The upgrade decision may be more difficult to justify if the consumer is not innovative in this product category.

In addition, the comparison within the options is more difficult to be evaluated if there are a lot of different alternatives or if the differences among the options are not easy to be distinguished by the consumer (Thompson; Hamilton; Rust, 2005). In the case of technological products, it is possible that consumers will have more difficulty to compare the options, because the new features may be difficult to use. Thus, if the consumer is able to justify the decision and explain why he is buying these new features, he will probably be more innovative. This prediction is summarized in the following hypothesis:

H6: The innovativeness in a product category is a positive function of the justifiability.

Concerning the prevention-focused goals, Her - zenstein, Posavac and Brakus (2007) demonstrated that prevention-focused consumers are less likely to adopt a new product. This effect is due to the way these consumers deal with the prevention goals (evaluation costs and anticipated regret). These consumers are more worried about possible negative outcomes and try to protect themselves. The result is that they abdicate adopting a prod­
uct or decide to adopt it later in a social system. Therefore, if the consumer is not able to achieve the prevention goals, he will be less likely to adopt an innovation.

The prevention goal related to anticipate re­gret predicts that consumers feel they are being evaluated by others all the time (Bettman; Luce; Payne, 1998; Heitmann; Lehmann; Herrmann, 2007). If we analyse this goal in an innovation adoption decision, this prediction may be even more evident. Innovative consumers are opinion leaders (Gatignon, Robertson, 1991; Foxall, 1994; Rogers, 2003) and they feel required to show they are able to make good choices based on cognitive aspects.

When the decison context, as an innovation for instance, requires a previous knowledge about the product category, the anticipated regret will be more difficult to be executed or it will take a longer time if the consumer does not know too much about the product category. In this situation, it will be more difficult to achieve this goal and it will explain, partly at least, why consumers may not adopt an innovation. This behavior leads to a lower innovativeness in a product category. Thus, our seventh hypothesis is:

H7: The innovativeness in a product category is a positive function of the anticipated regret.

An extensive choice process probably will have higher evaluation costs (Burnham; Frels; Mahajan, 2003). For innovative consumers, the evaluation about the product category in which they are innovators is not done at the moment they are going to make a new purchase. The evaluation of new alternatives, information search and other activities related with the choice process is con­stantly made by this group (Gatignon, Robertson, 1991; Christia, 2000; Rogers, 2003); it is part of its behavior. As a consequence, the evaluation costs are not perceived as high by the group of innovators, but for the laggards it may be.

Hirschman (1980) characterized the novelty seeking individuals as those that are always search­ing information, and they are really interested in searching this information. Although the innova­tors spend more time on this activity, they do not perceive the evaluation cost to be high. On the other hand, for non-innovators these costs will seem much higher.

The influence of the evaluation costs in a deci­sion to upgrade and adopt a new product may take into consideration some specific characteristics. The innovativeness in a product category may be evaluated by the consumers’ interest to adopt the enhancements proposed in the new version of the product. However, the consumer already has a product and is used to it. The switch to an enhanced product increases the evaluation costs to find the best new alternative (Okada, 2006). In this situation, if the consumer’s perception of the evaluation costs is not high, the probability of innovating will be higher.

The literature (e. g., Midgley; Dowling, 1978; 1993; Goldsmith; Hofacker, 1991; Roehrich, 2004; Alexander; Lynch Jr; Wang, 2008) shows that the innovativeness is a consequence of a series of activities performed during the decision making process. Hence, the lower the perception about the evaluation costs, the higher the innovativeness.

H8: The innovativeness in a product category is a negative function of the evaluation cost perception.

We represent the specific hypotheses described above in Figure 2.

EMPIRICAL ANALYSIS Method and Scale Measurement

The participants in this study were 366 undergradu­ate students from a Federal University in the south of Brazil (59% female), who had purchased an
electronic device in the last three months. The most frequently reported purchases were cell phones and digital cameras, but others were also reported, such as MP3 players. Data were collected using a self-administered paper survey.

The scale purification and measurement fol­lowed the work of Churchill (1979) andAnderson and Gerbing (1988). Existing measures were adapted for the model constructs. The innova­tiveness in the product category was measured based on the Goldmith and Hofacker (1991) and Goldsmith and Flynn (1992) scales. We also applied Midgley and Dowling’s (1978) innova­tiveness measurement, asking respondents how many and which were the electronic equipments they already had. This question was used later to classify the respondents according to the in­novativeness profile.

The choice goals were measured in accordance with the work of Bettman, Luce and Payne (1998), which argues that this construct is essential to the choice process. As in other studies on choice goals, we also followed other authors to measure choice goals. Thus, the choice confidence was measured with the scale proposed in the study of Urbany et al (1997). The justifiability followed the work of Simonson (1989) and Heitmann, Lehmann, and Herrmann (2007). The measurement of the anticipated regret followed the work of Schwartz et al (2002) and Tsiros and Mittal (2000). The measurement of the evaluation costs followed the work of Burnham, Frels and Mahajan (2003).

As in other surveys on purchase decisions and search behavior, we rely on the recall of prior experiences (e. g., Srinivasan; Ratchford, 1991; Ratchford, Lee, and Talukdar, 2003; Heitmann; Lehmann; Herrmann, 2007). Following the work of Srinivasan and Ratchford (1991), we tested whether “forgetting” had a significant impact on the data by splitting the sample into three groups: those who reported purchasing a product within the month, between one and two months before this participation, and between two and three months before this participation. None ofthe comparisons showed significant differences.

Furthermore, the cluster based on the innova­tiveness profile was run using the Multiple Com­ponents Analysis, following the work of Bagozzi (1995). This analysis generated two groups: one named “Most Innovative” and another called “Less Innovative.”

The internal consistency analysis presented good results, following the recommendation of Hair et al (2005): Justifiability (a = 0.72), Choice Confidence (a = 0.76), Anticipated Regret (a = 0.79), Evaluation Costs (a=0.75) and Innovative­ness (a = 0.73). Most of the data were analyzed using Structural Equation Modeling (Hair et al, 2005), with the Amos 6.0 (SPSS, 1993). Before the model verification, we run the Confirmatory FactorialAnalysis (CFA), which presented accept­able reliability values: Choice Confidence (0.72); Justifiability (0.75); Evaluation Costs (0.81); An­ticipated Regret (0.89) and Innovativeness (0.89). The Average Variance Stracted (AVE) was also accepted: Choice Confidence (0.52); Justifiabil­ity (0.52); Evaluation Costs (0.58); Anticipated Regret (0.63); Innovativeness (0.63).

The analysis demonstrated that there was no significant correlation between the constructs. The results denote a CFA model that includes the multi-item measures selected after scale pu­rification: %2= 264.069; d. f = 137; p<.001; f/d. f = 1.928; NFI =.921; RFI=.901; CFI =.960 and RMSEA =045.

Innovative Profile Evaluation

In order to evaluate the differences concerning the innovative behavior, an innovative score was created, based on the number of equipments the respondents owned (e. g., cell phones, digital cameras, players; etc) and the features that each product had (basic, intermediary and advanced fea­tures). The results showed two different groups. As mentioned before, those respondents with higher scores were named “Most innovative” (G1 - 186 respondents) and those with lower scores were the “Less Innovative” (G2 - 180 respondents).

An independent-sample t-test was conducted to compare the variables for the two groups. The results are presented in Table 1.

There were significant different scores for most and less innovative groups. The most innovative respondents reported higher scores of Innovative­ness, Choice Confidence, Justifiability and An­ticipated Regret. This group also reported a lower score ofEvaluation Costs. For instance, the most innovative group seems to be more promo­tion-focused and the less innovative one is more prevention-focused. These results show that the Most Innovative group has equipments with more innovative features. They are also more confident about their choice, which increases their justifi­ability. In addition, they perceive that the evalu­ation costs are not as high as the Less Innovative group thinks.

Model Evaluation

The structural model presented in Figure 2 was tested for the two groups, using the Amos 6.0. The results and the tested hypotheses are presented in Table 2.

The first hypothesis predicts that there is a positive relationship between justifiability and choice confidence. This relationship was empiri­cally demonstrated in the work of Heitmann, Lehmann and Herrmann (2007), and had been proposed by Bettman (e. g., Bettman, Luce, Payne, 1998). In our study, this hypothesis was statisti­cally significant for both groups (B=.621, p<.001 for the Most Innovative and B=.549, p<.001 for the Less Innovative). The Most Innovative group reported a higher standardized score (B), which demonstrate that this group is better able to jus­tify its choices as a consequence of the choice confidence.

The second hypothesis proposes that the higher the choice confidence, the higher the anticipated regret is. This prediction was confirmed for the Most Innovative (B =.176; p<.05) and was more significant for the Less Innovative (B =.326;

G1 (group 1) = most innovative; G2 (group 2) = less innovative

*p <.01

G1 (most innovative): f = 106.559, d. f = 92; f/ d. f = 1.158; NFI =.862; CFI =.978; RMSEA =.036 G2 (less innovative): f = 118.339 d. f = 92; f/ d. f = 1.286; NFI =.904; CFI =.976; RMSEA =.036

* p<.01

**p<.05

n. s. = not significant.

p>.01). The Less Innovative group is more con­cerned about having choice confidence in order to avoid regretting the decision. As the Most Innovative group is more confident in the choice process (see Table 1), they are not so worried about anticipating regret. In fact, this group seems to be more interested in the positive outcomes of the choice process.

The third hypothesis suggests that the lower the choice confidence, the higher the perception of the evaluation costs is during the choice process.

The results reported a significant relationship only for the Most Innovative group (B = -.217; p<.05). This relationship did not reach statistical significance for the Less Innovative group (B = -.103; p=n. s). These results highlight the effect ofthe promotion goals over the prevention goals. Promotion-focused consumers tend to be more innovative, because they are more confident during the choice process (Herzenstein, Posavac, Brakus, 2007). In addition, when the promotion goals are achieved, the consumer can also achieve

the prevention goals easily (Higgins et al., 2003), which explains why the H3 was not significant for the Less Innovative.

The fourth hypothesis is about the relationship within the prevention goals. Thus, it predicts that the perception of the evaluation costs is a nega­tive function of the anticipated regret during the choice. This hypothesis was also found in the work of Heitmann, Lehmann and Herrmann (2007). It was confirmed for both groups (B= -.216, p<.01 for the Most Innovative and B=-.277, p<.01 for the Less Innovative). Although this hypothesis was confirmed in both groups, we may note that the Less Innovative group reported a higher standardized score (B). The literature have shown the relationship among the prevention goals (e. g., Bettman; Luce; Payne, 1998; Zeelenberg, 1999), because consumers try to protect themselves against negative outcomes. Therefore, they get more engaged in information search, especially for products with new features, large assortment size and that are always being upgraded. This behavior seems to be consistent for both groups.

The fifth hypothesis predicts that the inno­vativeness in a product category is a positive function ofthe choice confidence. This prediction was supported only by the Most Innovative group (B=.218, p<.01). The Less Innovative did not show statistical significance concerning this relation­ship (B=.162,p= n. s). These results demonstrate that the Most Innovative respondents are more confident in the choice process because they are more promotion-focused (Herzenstein; Posavac; Brakus, 2007).

The sixth hypothesis is about the justifiability and its impact on the innovativeness behavior. Only the Most Innovative group showed signifi­cant results for this relationship (B=.214, p<.01). The Less Innovative did not show statistical significance (B=-.080, p=n. s). For innovative products, consumers that can justify their choice are more likely to innovate. The seventh hypoth­esis, which predicts that the innovativeness is a positive function of the anticipated regret, was confirmed only in the Most Innovative respon­dents (G1: B=.214, p<.01G2: B=.125,p=n. s). As predicted, consumers that are less worried about the possible negative outcomes are more likely to be innovative. These consumers are more con­cerned about achieving positive results, instead of avoiding negative ones.

The eighth hypothesis, which suggests that the innovativeness in a product category is a negative function of the evaluation cost perception was statistically significant for both groups (G1: B= -.286, p<.01; G2: B= -.291, p<.05). For extensive choice processes, such as in the case ofinnovative products, the evaluation costs are higher. In this situation, consumers need to get more engaged in the choice process in order to compare the dif­ferences between the products (Burnham; Frels; Mahajan, 2003). The results described above confirm that the choice goals are antecedents of the innovativeness in a product category.

As the groups presented statistically different means in all variables (see Table 1), an analysis of which variables could contrast the groups in the framework was run. Thus, each path of the proposed model was analysed separately, fol­lowing the recommendations of Byrne (2001). The results are presented in the right column (A X2 [d. f.]), Table 2.

The relationship between the choice confidence and the anticipated regret indicates that there is a significant difference between the groups. The difference between the value ofthe free model and the restricted model suggests a A%2 = 4.54 (Ad. f. = 1; p <.05). In addition, the impact of the goal to anticipate regret on the evaluation costs was also significant between the groups (A%2 = 6.17 (Ad. f. = 1;p <.01). These results suggest that the less innovative group needs to feel confident in the choice process to not regret the choice. The prevention goals (anticipate regret and evaluation costs) seem to be more important for the less inno­vative group in relation to the most innovative one.

Any of the other paths were statistically sig­nificant, which means that expect for the two significant paths described above, the groups are not very much different for the paths presented in the framework. Particularly, the impact of the choice goals on the innovativeness did not dif­ferentiate the groups. However, the Independent Samples T-test performed to verify the mean dif­ferences between the groups suggests that there is a difference for all the variables and that the innovativeness is a construct that distinguishes the groups. Besides that, the behavior pattern of the paths was not different.

DISCUSSION

Although recent studies (e. g. Herzenstein, Posavac and Brakus, 2007) have shown that promotion - focused consumers are more innovative than prevention-focused consumers, we have not found yet any study that has identified which goals are more relevant in this process. Studies that work with the RFT (Higgins, 1997; Freitas; Higgins, 2002; Higgins et al, 2003) assume the prediction that individuals seek pleasure and satisfaction, and avoid losses and pain. In fact, this prediction is also applied to the innovativeness behavior in the product category, because the less innova­tive consumers are more interested in avoiding negative outcomes whereas the most innovative consumers seek positive outcomes.

The results indicate that the respondents show a similar pattern ofbehavior regarding the proposed model. If we analyse the hypotheses that relate the choice goals (H1-H4), we note that the less innovative group has lower standardized score (B) for most of the hypothesis. On the other hand, the most innovative group showed higher standardized score (B) for most of the paths. An exception is the predicted relationship between the anticipated regret and the evaluation costs (H4), which had a higher loading for the Less Innovative group. This result reinforces the idea that for this group, the relationship between prevention goals still need to be better established. Another example is the fact that H3, which relates confidence to evalua­tion cost, was not statistically significant for the Less Innovative group. This finding indicates that these consumers still need to achieve their prevention goals and then have any impact on choice confidence.

The H5 and H6, which demonstrated the impact ofthe promotion goals on the innovativeness, were confirmed only for the Most Innovative group. This result relies on the constructive choice process (Bettman, Luce, Payne, 1998; Payne; Bettman, 2007). The confidence during the choice process is a consequence of the use of compensatory decision strategies. Thus, confident consumers are also more innovative in the product category.

Concerning the impact of the prevention goals on the innovativeness (H7 and H8), the fact that only the goal of evaluation costs had a significant impact on the innovativeness for the Less Innova­tive group is probably due to the choice context. For technological based product, consumers need to be more engaged in the evaluation of the alternatives in order to make comparisons among the options. According to the constructive choice process theory, the negative emotions that may arise from a regreted choice are a consequence of the lack of confidence about the choice. In this situation, the Most Innovative group seemed to be better able to anticipate regret. This ability is probably because they have more expertise about the product category, which makes them more confident. This may be the reason why anticipated regret was not significant for the Less Innovative group.

CONCLUSION AND FUTURE RESEARCH DIRECTIONS

The results demonstrate that the choice goals’ achievement is a positive function of Innova­tiveness in a product category. Therefore, the RFT has proved to be very important for better understanding the choice process and specifically the innovation adoption.

The differences found in the groups highlight that the marketing managers need to consider the consumer behavior during the choice process of electronic devices that are constantly being up­graded. The results reported here suggest that the self-regulation could be used as a marketing and segmentation variable. As the self-regulation can be a context variable, a marketing communication can be elaborated with a promotion-focused idea to target promotion-focused consumers. On the other hand, a prevention-focused communication could be elaborated in order to fit with the pre­vention-focused individuals. It seems reasonable that those with a chronic extreme prevention (vs. promotion) tendency will likely be less suscep­tible to a promotion (vs. prevention) advertising manipulation. This could influence consumers’ orientation toward positive results about the in­novation adoption. In fact, Herzenstein, Posavac and Brakus (2007) have proved that consumers are susceptible for such a manipulation. Thus it might have a have a managerial utility. The fit between the consumers’ regulatory focus and the marketing communication to new products may be particularly interesting to managers.

In our study, prevention-focused consumers will be more concerned regarding the possibility of regretting the choice. As a result, a promotion - focused communication will not fit their interest, but a prevention-focused communication may work. As our results show that one of the reasons for the consumer to not adopt a new produt is because they have not achieved the prevention goals, the Less Innovative consumers need first to avoid negative outcomes, and then they try to achieve positive results.

Future studies should analyse consumers’ evaluations during the choice process and the subsequent innovation adoption that may arise from these emotional reactions. The innovative­ness is a consequence ofthe results that consumers expect from a new product. The use of heuristic choice was showed in a study conducted by Pham (1998). The author demonstrates the significant role of emotions in the decision making process. When consumers try to predict possible emotions, they may overstimate the negative emotions of a choice. Further analysis concerning how consum­ers predict and deal with these emotions requires future studies.

Another suggestion is to constrast the frame­work proposed including samples not only from students. In this situation, a field study would be interesting to demonstrate that the results are consistent with the predictions made in this study.