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Reputation measurement: a tool for ski station applied to Isère Mountain

Peer-reviewed article
Céline Desmoulins
Traduction de Université Bretagne Occidentale
Cet article est une traduction de :
La mesure de la réputation : un outil au service des territoires de ski appliqué aux stations iséroises [fr]
Autre(s) traduction(s) de cet article :
La medición de la reputación: una herramienta al servicio de los territorios de esquí, aplicada a las estaciones de Isère [es]


Endorsed as an asset by businesses, reputation as a resource appears to be overlooked by ski resorts. One of the main reasons is the lack of knowledge and measurement tool. Academic scholarship relating to the benefits of reputation for an organisation provides a sound justification for the development of a measurement tool tailored to ski resorts. This article explores the stages involved in designing a measurement scale, based on information collected from 803 respondents at five ski resorts in the Isère department. We carried out exploratory and then confirmatory factorial analysis on two separate samples in order to develop a measurement scale based on four factors: organisational values, territorial resources, fame, and inhabitants. This factorial approach to reputation provides ski resorts with new avenues to leverage their reputation rather than simply live with it.

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1The increasingly social nature of the world has brought the issue of good reputation into the spotlight. As a guarantee of decency and trustworthiness, this notion was developed in the corporate world in the 1990s, alongside, inter alia, the trend for resource-based theories focusing on using one’s own resources to boost performance in one’s market (Penrose, 1959). There is no clearer example of a resource specific to an organisation than its own reputation. Reputation as a resource has naturally prompted a great deal of research, both in terms of strategy and marketing (Bailey and Bonifield, 2010; Rindova, Williamson and Petkova, 2010). Its influence on the overall performance of a business has been clearly demonstrated (Boyd, Bergh and Ketchen, 2010). Such is its importance today, since the dawn of the Internet, that it is a source of concern for managers (Boistel, 2013).

2In ski resorts, however, which are a specific type of organisation, it seems to have been overlooked (Desmoulins, 2019). Ski resorts are obviously complex places to operate as they have to work within public management constraints (Puthod and Thévenard-Puthod, 2011), and contend with the pressures of an increasingly competitive market (due to advances in transport) (Vlès and Hatt, 2019), as well as highly seasonal tourism (Atout France, 2015). These pressures are being exacerbated by current climate phenomena which are drawing ski resorts down the route of built-in obsolescence (Cour des comptes, 2018), accentuated by changes in consumption patterns for skiing (Vanat, 2018). Faced with these issues, it appears that reputation could be both a lever for performance and a strategic positioning tool. Currently, a number of initiatives are leveraging it more or less consciously (branding, communications campaigns, roadshows, etc.) (Frochot and Kreziak, 2008), but no existing tool is appropriate for measuring it in a ski resort. Our approach therefore attempts not only to explain the importance of reputation (Rindova, Williamson and Petkova, 2010) within the context of a winter sports resort, but also to propose a measurement scale to mitigate an operational shortcoming.

I. From reputation benefits to reputation measurement

3Since the 1990s, the corporate benefits of reputation have been universally accepted; by contrast, this is not straightforward for ski resorts. Their issues and environment, and hence their problems, are different and we will unpack these in paragraph 1.A. We shall then explore how the benefits of corporate reputation can be transferred to ski resorts in 1.B. Finally, we will address the issue of how these resorts currently use their reputation in 1.C.

A. The issues of attractiveness for a ski resort

  • 1 For example, the Col du Lautaret resort in the commune of Villar d’Arène, with 330 inhabitants (INS (...)

4A ski resort is a unique area as even though “territory are portions of space which stand the test of time, come what may (Houllier-Guibert, 2019, p. 160) a ski resort can be abandoned if a neighbouring resort is more attractive. The administrative commune around which it is constructed survives, but the economic activity of skiing, and everything that underpins it disappears1 (Vlès, 2012). Just like businesses, ski resorts are bought out and go bankrupt (Vlès and Bouneau, 2016). Touristic attractiveness is more than just an objective for these resorts – their survival depends on it.

5Faced with this situation, ski resorts are uniquely robust and resilient (Bonnemains, 2015; Vlès, 2019), responding to climate change and shifts in customer expectations (François, 2007) with solutions to expand their offer (diversification of non-skiing activities) and/or address technical issues by improving infrastructure for accessing high-altitude areas, or to preserve snow (snow machines, run architecture, mountain pasture, etc.). Ski resorts are innovating, irrespective of size (Bonnemains, 2016; Mao, Hautbois and Langenbach, 2009), to fight against predicted closures due to climate change (Cour des comptes, 2018) and an ageing skier demographic (Steiger, 2012). In this context, ski resorts are attempting to increase (or at least not lose) their market share in the so-called mountain destination market (Tsiotsou, 2006). In 2018, this market comprised approximately two thousand resorts in sixty-seven countries (Vanat, 2018); the top three destinations are France, Austria and the United States (Domaines skiables, 2014 to 2018). However despite falling air travel costs and efforts by tour operators, the majority of skiers do not travel long-haul (Vanat, 2018). For French resorts, competition is mainly European, or even domestic, as there are three-hundred and twenty-five resorts in France spread across six mountain ranges. Tourists still have a wide choice. However, the northern Alps corner the French market with 72% of ski days in the last four years, according to Domaines skiables de France. This market share is split between three departments: Savoie 40%, Haute-Savoie 23%, and Isère-Drome 9%.2

6As part of a competitive approach, these resorts are developing segmentation strategies to try to differentiate themselves from their competitors based on their unique features rather than on the generic attractions of a snow-covered mountain (Frochot and Kreziak, 2008; Guallino and Salvador, 2015). According to Malakauskaite and Naviskas (2010), resorts are drawing on two types of resource – those which are available to areas from the outset (known as natural resources), and those built by stakeholders. Resorts must therefore use their resources to best advantage. Of the resources built by stakeholders, one in particular seems to be overlooked, even though it is considered to be one of the most strategic by businesses (Black and Boal, 1994), namely reputation (Desmoulins, 2019).

B. The importance of reputation for touristic attractiveness

7The role of corporate reputation has been extensively studied over the years in relation to the numerous benefits it offers, provided that it is good. By focusing on choice (Balmer and Greyser, 2003; Rhee and Haunschild, 2006) reputation allows companies to charge more, even when the products and/or services are identical (Karpik, 2013; Rao, 1994; Weiss, 1995). But it also protects an organisation, including in the event of a scandal, as stakeholders tend to give the benefit of the doubt to the organisation with the best reputation (Balmer and Greyser, 2003). There are also additional management benefits (Ashforth and Mael, 1989; Mercier, 1998; Whetten, 2002) as a good reputation attracts talent (Bromley, 1993; Gatewood, Gowan and Lautenschlager, 1993; Stigler, 1962) and ensures employee retention despite the increased threat of poaching from competitors (Bergami and Bagozzi, 2000). Lastly, the confidence generated by a good reputation allows businesses to attract finance (Guimaraes, 1985). Reputation therefore has an overall influence on the performance of a business (Balmer et al., 1997; Margulies, 1977).

8When applied to ski resorts, reputation can be defined as stakeholders’ perception based on past actions at the resort which contribute to an assessment of its ability to meet its commitments (Desmoulins, 2020b). In other words, when applied to the destinations market, it is the shared experiences which tourists have of a destination that inform assumptions about the quality of a future stay. To draw an analogy with the corporate world, good reputation favours the choice of a resort with the best reputation when the information available is similar and/or inadequate (Balmer and Greyser, 2003; Rhee and Haunschild, 2006). It also allows the resort with the best reputation to charge higher prices, thus improving its overall performance.

9In this case, it is in the interest of ski resorts (large and small) to leverage their reputation as it is an asset in territorial strategies to get all stakeholders to work together: institutional players, operators, inhabitants, seasonal visitors, tradespeople, tourists, etc. By capturing feedback from all stakeholders, reputation lends legitimacy to management decisions, thus facilitating their implementation, or contributes to a diagnostic process. This process could also, as part of a longitudinal approach, become an assessment tool for territorial policymaking by making it possible to “evaluate the daily impact of local policies on inhabitants and visitors” (Vlès, 2014, p. 55). However, it appears that the effects of a good reputation are more often used today to showcase a region in the manner suggested by segmentation or diversification strategies (Frochot and Kreziak, 2008).

C. What regions do with their reputation

10Although ski resorts are not aware of their reputation presented in terms of an assessment by stakeholders informing assumptions about future actions in the resort, it would be inaccurate to suggest that winter sports resorts do not leverage their reputation.

11Thus ski resorts, through their champions (or celebrities), enhance their reputation via a transfer effect, as one reputation is transferred to another (Cousin and Chauvin, 2012). Hosting sport and high-profile events demonstrates that the organising resort is a proficient place and thus boosts reputation by the same token (Garay and Pérez, 2017). In this context, a number of classifications and indicators are used to compare resorts to each other (Travelski, skipass, European Best Destinations, etc.). These scales range from basic indicators to more complex measurements which make it possible to extrapolate information about the ability of a region to appear attractive using metrics such as the number of runs, sunshine hours, the number and quality of infrastructures, etc. (Cugno, Grimmer and Viassone, 2012). Similarly, reputation can be measured on the basis of the resort’s profile in guides and other specialist publications (Ollivier et al., 2012), and even on social media (Twitter, Facebook, Instagram, etc.) (Alloing, 2016).

12Traditionally, when a resort attempts to measure its touristic attractiveness, the relevant Tourist Office looks at the figures: number of overnight stays/packages sold, average spend (Ravix, 2015). A segmentation strategy is then applied to establish visitor profiles from these figures (Guallino and Salvador, 2015). This a long and often painstaking data collection exercise which only measures the results of attractiveness, rather than its origins. It is therefore difficult to draw up a strategy for future development on this basis (Vlès, Egea and Kahn, 1994). Scales taking stakeholder opinions into consideration can certainly mitigate this shortcoming. One such measurement is the indice de richesse d’évocation [richness of evocation index] developed by Chamard and Liquet (2012), which consists of asking respondents to give five words that best describe a region, and also their valences and experience of it. This process makes it possible to capture overall opinion fairly easily, but it is often quite generic; in the case of ski resorts, it is characterised by mountains, skiing, pine trees, snow and chalets. It is therefore very difficult to use for development or differentiation purposes. More highly developed scales mix measurements such as the Global Competitiveness Indicator (GCI) or Nation Brand Indicator (NBI) using both statistical and opinion indicators. However, there are methodological issues associated with both of these indicators (the GCI has recently modified its calculation method) and/or they were developed for much larger areas than ski resorts (a country or nation), e.g. Country Reptrack®. This scale is actually a spinoff from a product with the same name designed for measuring corporate reputation.

13Furthermore, if reputation is the collective evaluation of a group of stakeholders as described by Fombrun (1996), then reputation depends on the groups of stakeholders concerned. In other words, there is not one reputation, but several reputations, depending on the groups involved. This is particularly true of a ski resort, where reputation will be different for inhabitants (a marginal group), tourists and active users (regular or occasional leisure), and resort managers/administrators.

14Although the effects of a good reputation are well known and well documented (from a corporate perspective), a literature survey reveals a lack of operational tools to measure the reputation of ski resorts. In fact, tourists and winter sports enthusiasts choose a resort on a whim (Frochot and Kreziak, 2008), for nostalgic reasons (Caton and Santos, 2007), for practical reasons (apartment available onsite or nearby) (Imesch, 2010), as a rational choice based on occasionally flawed information (Helme-Guizon, Mulholland and Lagrandeur, 2004), or even on the basis of a recommendation from friends or family (Desmoulins, 2020a). The latter two reasons are associated with reputation and we therefore believe that a requirement exists to develop a tailored measurement tool so that ski resort managers can make better-informed decisions.

II. Methodology

  • 3 We initially sent 50 emails (personal and professional network) and we recorded 269 answers; the on (...)

15In order to create a suitable scale for measuring the reputation of ski resorts, we used the methodology proposed by Churchill (1979), which consists of selecting items, testing them during an exploratory phase and then confirming them during another phase. Thus, the specifications of the construct were established based on a compilation of the literature measuring the reputation of a region and company, i.e. 250 articles. Contrary to Churchill’s (1979) recommendation to submit this compilation to expert judgement, we preferred to make use of a practice derived from crowdsourcing (Renault, 2013) the wisdom of the crowd. Our choice is justified by the fact that most of these items had already been established by experts without it having led to a consensus. According to Guittard and Schenk (2011), a crowd is defined as an anonymous and open group, of uncertain size. In order to be in line with these characteristics, we asked our network3 one single anonymous question about what the reputation of the territory means to them: “In your opinion, what accounts for the reputation of a territory? (Aterritory can be a city, a locality, a ski resort, a municipality, a department, etc.)”. We were able to select 36 items by submitting the answers to a lexical analysis, in combination with the literature (Desmoulins, 2020b); we then applied these items to a questionnaire, as per the recommendations of Groves et al. (2011).

  • 4 French ski school.

16As a result, the questionnaire created was comprised of 48 statements covering these 36 items. Some items had to be broken down in order to adjust to specific regional characteristics. For example, the item safety was broken down into safety at the ski resort and slope safety. This questionnaire was then distributed from February 2018 to March 2018, face-to-face, in five resorts in Isère with at least 100 ESF4 instructors. This threshold presupposes that the resort has a certain level of attractiveness to tourists as well as a sufficient reception capacity to attain the validity standards in terms of respondents. Consequently, it was decided to collect this information at the 2 Alpes, Alpe d’Huez, Villard-de-Lans Corrençon, 7 Laux and Chamrousse resorts. These five stations correspond to widely different target clientele (young people; senior executives; families), thereby increasing the nomological validity of our measurement scale. The interviewees had to answer the questions while considering the region in which they were located based on how much they agreed or disagreed with the statements (+4 on their future behaviour) according to a 7-point Likert scale. It should be noted that it is assumed that the overall reputation of the ski resort is good since it was chosen by the respondents. That said, we are trying to measure the reputation, not to make a comparison between several stations.

  • 5 At least 200 respondents for the factor analyses.

17We then followed the recommendations of Anderson and Gerbing (1988), which call for the joint use of an exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) so as to establish a measurement scale. Generally, these analyses are performed on two samples from two different data collections. However, given that our results were sufficient5 (+ 800), we divided our results into two, making sure to keep identical proportions for the variables sex, age and family status using the SPSS software. We therefore have 402 respondents for sample 1 and 401 respondents for sample 2. A descriptive and comparative analysis of these two samples is provided in the Appendix.

III. Analysis of the results

18We subjected Sample 1 to an exploratory maximum likelihood factor analysis and a Promax rotation using the SPSS software. Then we subjected sample 2 to a confirmatory analysis of the model as suggested by the maximum likelihood in the AMOS software.

A. Exploratory Factor Analysis (EFA)

19The initial KMO (0.907) and Bartlett’s test (Chi² 7782.681; df 990; p < 0.005) allow us to confirm that our data can be factorized. The internal consistency analysis gives a Cronbach’s alpha of 0.872.

20In the first purification step, we eliminate 21 items for reasons of insufficient extracted communities (< 0.4). Then, a second step eliminates three items for which the saturation coefficient is less than 0.4. Last, we eliminated the saturating items for more than one factor and which had a difference greater than 0.3. All of these steps give us a four-factor solution representing close to 66% of the cumulative variance (see Table 1).

Table 1: Matrix of the components after rotation


Perceived value of the institution

Territorial resource



Customer attentiveness





Inhabitant attentiveness




















Sustainable development










Social networks





Local products















Known internationally





Known in FranceNat. (.) renown





Pleasant inhabitants





Inhabitant welcome





Cumulative %




Bartlett’s sphericity test


Cronbach’s alpha


Extraction method: Maximum likelihood analysis

Rotation method: Promax

21The notion of social network refers both to the field of digital marketing (Boyd and Ellison, 2007), as well as to economic sociology (Granovetter, 1985). Today, social networks (Facebook, Twitter, Instagram) not only allow people to share their experiences with the people in their sphere, but also to connect with strangers sharing the same experience (Alloing, 2016; Boistel, 2013; Chamard, 2014), yet, one of the specific missions of the public service is to enable this sharing of experience, this creation of ties. In this respect, it is therefore logical that these items appear in the perceived value of the institution factor among other items related to management, ethics, sustainable development, the ability to communicate effectively and even innovation.

B. Confirmatory factor analysis (CFA)

22The CFA carried out with sample 1 suggests using a 4-factor model that we test using a CFA on sample 2 in the AMOS 23 software with a maximum likelihood analysis as the estimation procedure (Field, 2013). This allows us to judge the validity and reliability of our four dimensions, as well as their respective correlations.

  • 6 Significance of the indexes: GFI: Goodness of Fit Index/RMSEA: Root Mean Square Error of Approximat (...)
  • 7 0.438.

23Therefore, when we assess our model, we find that there are no outliers (correlation > 1 or not significant), the adjustment indices and the alpha of the items for the GFI–CFI and SRMR indicators6 are within normal ranges, but are slightly below the thresholds for AGFI, TLI and RMSEA (Frikha, 2019). As a result, AMOS suggests four improvements to our model: the disappearance of an item with an alpha < 0.57, and correlations between the measurement errors. As soon as the second improvement has been applied, all of the indices are satisfied, however we choose to continue with the improvements proposed by AMOS because we are not aware of any reasons justifying why they should not be applied (Jolibert and Jourdan, 2006).

24The reputation measurement model thus established is as follows:


Document 1: model for measuring the reputation of a ski resort (the list of questions is given in the appendix)

Document 1: model for measuring the reputation of a ski resort (the list of questions is given in the appendix)

Standardized Chi²
















< 3.000

> 0.95

> 0.95

> 0.95

> 0.95

< 0.06

< 0.08

C. Validity and reliability of the measurement scale

  • 8 Average variance extracted.

26The reliability of a measurement is the “quality of a measuring instrument that, applied several times to the same phenomenon, must give the same results” (Evrard et al., 2009, p. 586). As previously mentioned, we prefer to use Jöreskog’s Rho and Cronbach’s alpha (sensitive to the number of items), which is also per the recommendations of Peterson (1994). Validity refers to the ability of the measuring instrument to take the concept studied into account. It is measured by measuring the AVE8 and its relationship to the shared variance, which must be lower (Fornell and Larcker, 1981).

Table 2: Table of validity indicators


Jöreskog’s Rho



Perceived value of the institution




territorial resource












  • 9 It should be noted here that the value obtained is still quite similar.

27As per the recommendations of Roussel et al. (2002), factor 2 poses a problem given that its Jöreskog’s Rho value is less than 0.79. This factor corresponds to the fame measurement values (international and national renown), however, these two measurements overlap; if the resort is known internationally then it follows that it is certainly known on a national level as well. Consequently, we can put forth the hypothesis that a clearer distinction of the statement (Do you think the ski resort is known outside of France?) as well as the addition of an item (e.g.: The station is better known in Europe than in China) would resolve this problem of reliability with regards to the fame measurement.

  • 10 Variance inflation factor

28The AVE for the Perceived value of the institution factor also poses a problem. A value less than 0.5 suggests a multi-collinearity problem in our items, therefore we decided to calculate the VIF10 for the items under the Perceived value factor (Table 3) and to observe the scatterplot of regression standardized residuals as per the recommendations of Chatterjee, Hadi and Price (2000) (Document 2)

Table 3: VIF calculation of the Factor 1 items


Collinearity statistics




(Constant) Inst12


















Document 2: Normal standardized residual regression P-P plot - Dependent variable Inst 12 -via SPSS 23

Document 2: Normal standardized residual regression P-P plot - Dependent variable Inst 12 -via SPSS 23

29Since the VIF values are between 1 and 10 and the sum of their average is < 2 whereas the impact of multi-collinearity is negligible, all of the variables can be retained (still based on the recommendations of Chatterjee, Hadi and Price, 2000, p. 236).


  • 11 Reconciling mobility, economic development, energy, quality of life, as well as citizen participati (...)

30Using SEM equations with the LISREL method, we were able to establish a measurement of the reputation of ski resorts. This is based on elements of fame, the natural resources of the resort as well as certain appeals of the inhabitants (and assimilated) as well as, and particularly, on the capacity of the resort (as an organisation) to fulfil its commitments, both from a management point of view and in its smart values11 (Desponds and Nappi-Choulet, 2018).

31This research also sheds light on several key points that can affect the reputation of a station. First, the role of the inhabitants and associated persons (here, the seasonal workers) appears to be a major factor which, from a development point of view, seems to suggest that it is in the interest of resorts to ensure that their inhabitants (and associated persons) appear as welcoming and friendly.

32A second point corroborates this suggestion. In fact, mass media (press, TV, radio) is completely absent from our results. The territory ’s overall communication campaign, as well as social networks (creation of ties) are present, but integrated into the perceived values of the institution. Furthermore, we feel that it would be interesting to focus future research on the role of the inhabitants versus communication campaigns, in the perception and overall assessment of ski resorts while still focusing on the reputation.

33From this perspective, the experiences that can be had in the region, found in the literature on the destinations, is an important element with regards to forming an opinion, and consequently, making an assessment. For Walsh-Heron and Stevens (1990), tourist attractiveness is the characteristic of a place that strives to attract and manage visitors, by providing a fun experience. In the case of winter sports resorts, tourists choose a resort “based on the experiences that they want to have” (Guallino and Salvador, 2015, p. 89); i.e. an experience that is more than just having fun. In this context, marketing strategies developed around the concept of brand allow resorts to proactively highlight their (chosen) specific characteristics based on a specific customer segmentation (Rochette, 2015). Photography of the landscape, behaviours or even events, which are characteristic of the brand, is certainly a key element of the reputation (Brown et al., 2006), but it is not the only one. As a joint assessment made by a group of actors (Fombrun, 1996), it would be limiting to reduce the mobilization of the reputation to a comparative use based on the image. Because, if the brand alludes to a promise made by a resort (Rochette, 2015), the reputation itself is the guarantee that this promise will be kept through a contract of guarantee (Cornell and Shapiro, 1987) and the confidence it generates among the various actors (Artigas et al., 2017). Thus, marketing campaigns, although useful for product fame or segmentation, seem to play a limited role in the reputation and in guiding the choices because they are not included in the measurement scale. Conversely, it seems that the assessment of the organisation in terms of its capacities to be a smart territory is one way to develop the reputation and therefore the tendency for a ski resort to be chosen.

34Taking all of these results into account, we can estimate that our model captures the various dimensions of reputation quite well. Nevertheless, we believe that a number of improvements can be made. In the field, we came across respondents who did not want to answer this survey on the pretext that they had just arrived and therefore they did not have an opinion, despite our attempt to encourage them to answer based on their preconceptions. Without going so far as to say that it is necessary to have spent time in a region before it can have a reputation, we can assume that experimentation seems to be important for this assessment to be made. We believe that it would be very interesting to test this hypothesis in a future research project. Even if people did not have enough information to make an assessment, they had enough information to choose this destination. In addition, besides the so-called classic biases due to our data collection, we found that part of the population had not been included in our study: people under the age of 18 years. Given that children influence their parents in the choice of a tourist destination (Nickerson and Jurowski, 2001), it would therefore be interesting to address this lack of information since the way in which young people perceive a region guides the choices and they do not necessarily perceive or assess a region in the same way as their parents.

35Therefore our research, which establishes a measure of reputation, is a first step towards an extensive use of their reputation by ski resorts. Faced with the uncertainty of their future, and even more so against the background of the current health crisis (COVID-19), in our view, the reputation of ski resorts is a resource to be exploited. It is thus more than likely that, when in doubt, and just like for businesses, ski experience consumers will choose the resort with the best reputation. However, studies have shown that reputations are not founded on star ratings, given that these ratings are seen as part of the brand image that are more or less orchestrated by the destinations (Castellano and Dutot, 2017; Helme-Guizon, Mulholland and Lagrandeur, 2004).


Table 4: lists of items selected for the measurement scale



Perceived factor

The resort takes residents’ views into consideration

The resort is well run

The resort has a sustainable development policy

The resort is innovative

The resort uses cutting-edge technology

The resort communicates very effectively

The resort has a high profile on social media


The resort is known to French people as a ski resort

The resort is known internationally

Territorial resource

The resort’s heritage is important (Heritage is what has been handed down to the community

by previous generations)

Local products are of good quality


The resort’s inhabitants are welcoming

The resort’s inhabitants are unfriendly

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1 For example, the Col du Lautaret resort in the commune of Villar d’Arène, with 330 inhabitants (INSEE, 2016), which closed in 2014.

2 Source: domaines skiables de france, observatoire 2018.

3 We initially sent 50 emails (personal and professional network) and we recorded 269 answers; the only limitation in terms of having access to the question was having the internet link (open and indeterminate).

4 French ski school.

5 At least 200 respondents for the factor analyses.

6 Significance of the indexes: GFI: Goodness of Fit Index/RMSEA: Root Mean Square Error of Approximation; TLI: Tucker Lewis Index; CFI: Comparative Fit Index. SRMR: Standardized Root Mean Square Residual.

7 0.438.

8 Average variance extracted.

9 It should be noted here that the value obtained is still quite similar.

10 Variance inflation factor

11 Reconciling mobility, economic development, energy, quality of life, as well as citizen participation. (Desponds and Nappi-Choulet, 2018, p. 9).

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Table des illustrations

Titre Document 1: model for measuring the reputation of a ski resort (the list of questions is given in the appendix)
Fichier image/jpeg, 176k
Titre Document 2: Normal standardized residual regression P-P plot - Dependent variable Inst 12 -via SPSS 23
Fichier image/jpeg, 39k
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Céline Desmoulins, « Reputation measurement: a tool for ski station applied to Isère Mountain », Via [En ligne], 18 | 2020, mis en ligne le 27 décembre 2020, consulté le 14 juin 2021. URL : ; DOI :

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Céline Desmoulins

MCF SAF / Université Lyon 1

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Université Bretagne Occidentale

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