Chebli Youness* Université de Grenoble, cerag

Transcription

1 L'E-REPUTATION DU POINT DE VUE CLIENT : PROPOSITION D'UN MODELE EXPLICATIF Chebli Youness* Université de Grenoble, cerag youness.chebli@gmail.com Pierre Valette-Florence Université de Grenoble, cerag pierre.valette-florence@iae-grenoble.fr * 150 rue de la chimie, Saint Martin d Hères, Résumé : Bien que la réputation en ligne ait attiré une attention particulière parmi les praticiens en marketing, la recherche dans ce domaine est encore limitée. Dans ce papier, les auteurs examinent les antécédents et les conséquences de l e-réputation du point de vue client. Une approche selon un modèle d équations structurelles est utilisée pour tester le modèle basé sur les données d une enquête auprès de 1100 acheteurs en ligne français. Les résultats montrent l impact de la confiance et l héritage sur l e-réputation, ainsi que la façon dont l eréputation affecte l engagement du client et le bouche à oreille. Plusieurs implications managériales et théoriques sont ensuite discutées. Mots clef : e-réputation ; model intégrateur ; PLS SEM ; e-commerce E-REPUTATION FROM A CUSTOMER PERSPECTIVE: PROPOSITION OF AN EXPLICATIVE MODEL Abstract: Although online reputation has attracted significant attention among marketing practitioners, research in this area is still limited. In this paper, the authors examine the antecedents and consequences of online reputation from the customer s perspective. A structural equation modeling approach is used to test the model based on data from a survey of 1100 French online buyers. The results show the impact of trust and heritage on online reputation, as well as how online reputation affects customer commitment and word of mouth. Several implications either in terms of conceptual or managerial insights are then discussed. Keywords: online reputation; integrated model; PLS SEM; e-commerce

2 E-REPUTATION FROM A CUSTOMER PERSPECTIVE: PROPOSITION OF AN EXPLICATIVE MODEL Introduction Firms are progressively becoming more conscious that intangible assets add more competitive advantage than functional attributes. Various studies describe corporate reputation as one of the most important intangible assets. Corporate reputation is an intangible asset that provides companies with sustainable competitive advantage in the marketplace (Boyd et al., 2010). In order to manage their reputations, firms need to measure it and the dimensions that influence it. All existing measures deal with the stakeholders of the firm; however, a particular emphasis should be given to the customer, who remains the most important stakeholder for marketers. To the best of our knowledge, the customer-based corporate reputation scale (Walsh & Beatty, 2007) is the only known measurement scale that takes the customer aspect into consideration. Although it was developed in an offline context, it has been successfully tested online. With the development of e-commerce, firms have now a greater interest than before in investing in intangible assets especially their online reputation. The online reputation hence becomes a crucial challenge in a highly interactive communication environment where customers share their opinions online. The literature review shows that studies in the field of online reputation are still limited. Furthermore, existing studies (e.g. Walsh & Beatty, 2009) tend to focus on antecedents and consequences of corporate reputation that are associated with the offline context, but do not analyze variables related to online consumer behavior. The objectives of this paper are hence twofold: (1) examining the dimensions of the customer-based online reputation; (2) introducing a causal model that associates online reputation with some key antecedents and consequences. In order to address these two main research questions, the paper is structured as follows: in the following section, the relevant literature review on corporate reputation is presented; section 2 explains the methodology, and section 3 discusses the results. Theoretical Background and Hypotheses The importance of intangible assets in general and of corporate reputation more precisely has grown quickly. The reputation consists of the emotions and knowledge held by people (Hall, 1992). From the client perspective, a definition was proposed by Walsh and Beatty (2007) and was characterized as the overall evaluation done by the clients of a company based on their reactions to its offerings and communications activities. A company s favorable reputation signals its trustworthiness to clients, which should motivate them to deal with this company (Bartikowski & Walsh, 2011). With the development of e-commerce, managing e-reputation is becoming essential. Literature review shows that there is no study that measures the e-reputation from the customer perspective. Paquerot et al. (2011) define the online reputation as the general perception that stakeholders have of a firm based on the information available online. In this research, we define more precisely the customer-based online reputation as the assessment done by the online buyers of a company based on their reactions to its products, communication activities, and interactions with its website. The main focus of this study being on the antecedents and the consequences of online reputation, we will first start by presenting the antecedents and then the consequences of the conceptualized e-reputation. 1

3 Trust: Anderson and Weitz (1989) define trust as one party s belief that its needs will be fulfilled in the future by actions undertaken by the other party. Walsh and Beatty (2009) demonstrated that trust is an antecedent of corporate reputation. The study was done in an offline context, on a German energy supply company more precisely. It is likely that online customers who trust the company will positively evaluate its online reputation. Thus, our first hypothesis is: H1: Trust has a positive effect on customer-based online reputation. Heritage: It represents sustainability as an engagement to the stakeholders that the core values of the company are genuine (Urde, 2003). Consumers prefer company with a heritage that indicates their credibility, reliability and authenticity (Leigh et al., 2006). Heritage brands have built a meaningful past, and having a heritage helps to make a brand relevant to the present and prospectively to the future. Therefore, we suggest that heritage has a positive influence on customer based online reputation. H2: Heritage has a positive effect on customer-based online reputation. Commitment: We conclude from our literature review that there are three general themes of commitment which are: affective commitment, calculative commitment, and normative commitment. Bennette and Gabriel (2011) demonstrated that a good reputation provides buyers with repeated positive reinforcement, which created commitment. Bartikowski and Walsh (2011) proved that customer based corporate reputation positively influences customer commitment. Thus, our third hypothesis is: H3: Customer-based online reputation has a positive effect on customer commitment. Word of mouth: Word-of-mouth (WOM) is the means of exchanging opinions on goods and services offered by markets. With the development of web 2.0, the influence of WOM has grown exponentially and given consumers the option to gather the other consumers comments. The relationship between reputation and WOM has been emphasized in marketing. Hong and Yang (2009) proved that when buyers perceive a company s reputation to be favorable, they are more likely to engage in favorable WOM. We therefore hypothesize that H4: Customer-based online reputation has a positive effect on customers positive WOM. Methodology Scales and samples. Before testing our hypotheses, we chose to build up a scale designed to uncover the dimensions of the customer-based e-reputation. The process went through two main phases. First, we designed 3 qualitative studies in order to delineate the main dimensions surrounding e-reputation and to generate corresponding items. The first study employed semi-structured interviews of experts in the field. The second and third studies relied on projective techniques with customers (collages and pictures metaphoric collection). A total of 42 items emerged from all these approaches. Second, we collected preliminary data on 452 customers among a set of 8 websites. Exploratory as well as confirmatory factor analyses allowed us to create a new e-reputation scale structured around 8 dimensions with sound psychometric properties as for reliability, convergent and discriminant validity indices (detailed results are available upon request). In order to test the hypothesized relationships, a new survey was conducted. A questionnaire was sent by mail to randomly chosen samples in France. The respondent had to be a client and to choose the one he was the most familiar among the top 8 websites in France, based on the fédération e-commerce et vente à distance and Mediametrie, which are: Amazon, Cdiscount, Fnac, Ebay, Carrefour, PriceMinister, Vente-Privée et La Redoute. The data collection process lasted 6 weeks. This process resulted in a usable sample of 1100 respondents. Most respondents fell into the age group. 49% of the respondents navigate at least once per month on the chosen website. 2

4 Trust (Hess, 1995) is assessed according to a three-dimensional structure, representing the reliability, honesty, and altruism dimensions. Coefficient alpha was.86,.81,.83 respectively. Heritage is assessed by a seven-item scale adapted from Merchant and Rose (2012). Coefficient alpha is Affective (α=0.83) and calculative (α=0.70) commitments are each assessed by a three-item scale (Bansal et al., 2004; Fullerton, 2005). Normative commitment (α=0.94) is assessed by a five-item scale (Bansal et al., 2004). WOM is assessed by a six-item scale adapted from Goyette et al. (2010) with a coefficient alpha of Data analyses and results. A PLS approach has been selected because its suitability to handle higher order latent constructs and violation of multivariate normality. First, the reliability and validity of each concept have to be first estimated. As shown in Table 1, indicators of convergent validity and reliability are satisfied: the reliability is greater than 0.7 and the convergent validity is equal to or greater than 0.5. In order to assess discriminant validity, we relied on the discriminant validity check (available upon request) put forward by Fornell and Larcker (1981) and that shows that all the latent variables encompassed within this research are different. Before we look into more details the path coefficients, we would like to stress the good structure of the new e-reputations scale which achieves high convergent and reliability indices. This second survey does confirm the structure of the new online reputation scale which comprises six main dimensions one of which (quality) has three specific sub-facets. Table 1: Convergent Validity and Reliability Indices (Bootstrapped Estimates) Latent variable Convergent validity (AVE: Average Variance Extracted) Reliability (Jorsekög s Rho) Heritage 0,576 0,856 TRUST (second order) 0,750 0,900 Altruism 0,626 0,869 Honesty 0,753 0,902 Reliability 0,690 0,870 E-REPUTATION (higher order) 0,566 0,920 Customer orientation 0,747 0,899 Good Employer 0,911 0,968 Financially Strong 0,741 0,896 Social Responsibility 0,756 0,903 Price 0,710 0,880 Quality 0,527 0,869 Reliable Delivery 0,542 0,780 Innovativity & Singularity 0,695 0,872 High Savings Offerings 0,644 0,845 COMMITMENT (second order) 0,774 0,911 Affective Commitment 0,837 0,939 Cognitive Commitment 0,717 0,884 Normative Commitment 0,654 0,881 Word of Mouth 0,578 0,890 Figure 1 presents the path coefficients. The predictive power of the model is fairly high and all the path coefficients are statistically significant. Trust seems to be a better antecedent of e-reputation than heritage. One possible explanation lies in the fact that pure e-commerce brands are fairly new and hence not able to establish themselves with a high heritage level as 3

5 for instance high-end luxury brands. More importantly, e-reputation is equally balanced as a good predictor of either commitment or word of mouth. Moreover, a finer analysis (bootstrapped analysis with 500 replications) of the indirect paths form respectively heritage and trust on both commitment and WOM shows that they are all statistically significant, hence putting the stress in our research on the core mediating role played by e-reputation. Figure 1: Causal Model of Antecedents & Consequences of E-Reputation Discussion and Conclusion Despite rising practitioners interest in e-reputation, research in this area is still limited. Prior research focuses on studying the reputation and its relationships with other variables in the offline context. To test our causal model, our survey includes a large sample of customers from the top eight e-commerce websites in France. In this paper, we specify a model of direct effects that links the e-reputation to two antecedents (heritage and trust) and to two consequences (commitment and WOM). All the four hypothesized model relationships are supported. Our results show that a high level of trust positively impacts the online reputation. The same is true for heritage, but with less impact, maybe because the online commerce is relatively new, and e-commerce websites do not have a heritage yet compared to wellestablished brick and mortar companies. In terms of consequences, a favorable reputation increases the customer commitment toward the website, meaning that online customers will have a higher desire to maintain this valued relationship. In addition, the positive influence on WOM is very important especially in our digital era where brand choices and personal influences are increasingly taking place online. As for the measure of e-reputation, our results confirm that it can be assessed through 8 specific factors: Customer orientation, Reliable Delivery, Innovativity and Singularity, High Standard Offerings, Price, Social and Environmental Responsibility, Good employer, and Financially Strong Company. From an operational point of view, this new scale could be used repeatedly as a barometer enabling to periodically asses the e-reputation of diverse online companies. Our results also point out other managerial implications as far as improving customer-based online reputation is concerned. From the perspective of antecedents, increasing trust should be the choice in order to improve the online reputation. With regards to the consequences, online reputation is a significant indicator of customer commitment to the website and spreading a positive WOM. 4

6 In order to have a positive WOM, managers should focus on enhancing their e-reputation. In terms of limitations and future perspectives, one can first notice than two of our chosen websites are bricks and clicks. Hence, further testing should be conducted to understand the relationship between the online and the offline reputation. Second, our study is also limited as for the number of antecedents and consequences encompassed. Future researches should test other related concepts such as web quality or perceived risk. Ultimately, the applicability of this model could be evaluated in other cultural setting than the French one. References Anderson E et Weitz B (1989) Determinants of continuity in conventional industrial channel dyads. Marketing Science 8(4): Bansal HS, Irving PG, et Taylor SF (2004) A three-component model of customer commitment to service providers. Journal of the Academy of Marketing Science 32(3): Bartikowski B et Walsh G (2011) Investigating mediators between corporate reputation and customer citizenship behaviors. Journal of Business Research 64(1): Bennett R et Gabriel H (2001) Reputation, trust and supplier commitment: the case of shipping company/seaport relations. Journal of Business & Industrial Marketing 16(6): Boyd BK, Bergh DD et Ketchen Jr DJ (2010) Reconsidering the reputation-performance relationship: A resource-based view. Journal of Managemen, 36(3): Fornell C et Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18(1): Fullerton G (2005) How commitment both enables and undermines marketing relationships. European Journal of Marketing 39(11/12): Goyette I, Ricard L, Bergeron J et Marticotte F (2010) e-wom Scale: Word-of-Mouth Measurement Scale for e-services Context. Canadian Journal of Administrative Sciences 27(1): Hall R (1992) The Strategic Analysis of Intangible Resources. Strategic Management Journal 13(2): Hess JS (1995) Construction and Assessment of a Scale to Measure Consumer Trust. In Barbara B. Stern and George M. Zinkhan (Eds.). American Marketing Educator s Proceedings 6: Hong S et Yang S (2009) Effects of Reputation, Relational Satisfaction, and Customer- Company Identification on Positive Word-of-Mouth Intentions. Journal of Public Relations Research 21(4): Merchant A et Rose MG (2012) Effects of advertising-evoked vicarious nostalgia on brand heritage. Journal of Business Research 66(12): Paquerot, M., Queffelec, A., Sueur, I.& Biot-Paquerot, G. (2011). L e-réputation ou le renforcement de la gouvernance par le marché de l hôtellerie?. Revue Management et Avenir, 45(5), Urde M (2003) Core value-based corporate brand building. European Journal of Marketing 37(7-8):

7 Walsh G et Beatty ES (2007) Measuring customer-based corporate reputation: scale development, validation, and application. Journal of the Academy of Marketing Science, 35(1):