The influence of marital status on customer-centric measures in the context of a ski resort using the importance-performance map analysis (IPMA) framework

Matti Haverila (Department of Marketing, Thompson Rivers University, Kamloops, Canada)
Kai Christian Haverila (Department of Marketing, Concordia University, Montreal, Canada)
Jenny Carita Twyford (The University of Manchester, Manchester, UK)

European Journal of Management Studies

ISSN: 2183-4172

Article publication date: 1 February 2023

Issue publication date: 10 May 2023




This study assesses the impact of marital status towards customer-centric measures in a Canadian ski resort using the importance-performance map analysis (IPMA) as the analytical framework. For the purpose of this paper, the three groups that were assessed included singles, partnership without children and partnership with children as marital status indicators. From the theoretical and especially managerial point of view, knowing the importance and the performance of the relevant ski resort-related customer-centric perceptions is of key importance.


A survey was completed to assess customer-centric measures including customer satisfaction, repurchase intent, value for money, willingness to recommend, overall performance in terms of meeting expectations, relationship quality and skiing service quality. An IPMA was conducted with partial least square-structural equation modelling (PLS-SEM) to assess the importance-performance perceptions of the three marital status groups.


The results indicated that for five of the seven customer-centric measures, there were significant differences between the marital status groups. Overall, singles appeared to have the lowest values in customer-centric measures, whereas respondents living in partnership with children had the highest. This was also the case with the value for money perceptions, although the cost for the ski resort visit was likely to be the highest for the respondents living in partnership with children. There were also differences between the marital status groups in terms of the importance-performance evaluations.


Results of this research have implications for ski resort management as the three marital status groups appear to perceive the customer-centric measures quite differently in the IPMA framework.



Haverila, M., Haverila, K.C. and Twyford, J.C. (2023), "The influence of marital status on customer-centric measures in the context of a ski resort using the importance-performance map analysis (IPMA) framework", European Journal of Management Studies , Vol. 28 No. 1, pp. 49-68.



Emerald Publishing Limited

Copyright © 2022, Matti Haverila, Kai Christian Haverila and Jenny Carita Twyford


Published in European Journal of Management Studies. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at


Satisfying customers is one of the key factors for any business. This is not an exception for ski resorts in Canada and elsewhere. In 2020, tourism alone contributed $7.1 billion dollars to British Columbia's gross domestic product (GDP) (CTV News, 2019), with more than 10% of this coming from ski resorts. Because of this significant economic contribution, it is essential that the ski industry continuously strives to maintain and improve customer-centric measures, as even the smallest details can have an impact on them (Hyde, 2008). In this research, we focus on understanding the impact of marital status on the customer-centric measures in the context of a ski resort using importance-performance map analysis (IPMA) as the analytical and theoretical framework.

Previous research has discovered that demographic variables have an impact on the assessment of customer-centric measures (Taks and Ragoen, 2016). For example, a recession can have an effect on average family income, which has a direct impact on the overall demand in the skiing industry (Hudson, 1998; Taks and Ragoen, 2016). This study examines how demographic variables, and more precisely marital status, can play an important role in influencing customer-centric measures. Addressing the impact of marital status and adjusting the marketing strategy requires research and consideration when assessing the customer experience at a ski resort. In this research, seven customer-centric measures will be used as the key constructs in a structural model by identifying the causal relationships between them. These seven measures were customer satisfaction, repurchase intent, value for money, willingness to recommend, overall performance in terms of meeting expectations, relationship quality and service quality of skiing. This research is important as it aims to demonstrate that marital status does indeed have an impact on customer-centric measures in the context of a ski resort, and also that the marital status has an impact on the IPMA evaluations of the ski resort visitors. All this will be done on the basis of a structural model grounded on theoretically sound relationships, which identifies the causality between the constructs.

Literature review

Regarding the profile of a ski resort customer, it is critical to understand the expectations that customers consider before travelling (destination attributes), since these expectations will directly affect the degree of satisfaction after the visiting experience (Miragaia et al., 2016). The degree of satisfaction after experiencing the services is crucial because it may have an influence on revisit intentions to skiing destinations. Studies have shown that the practices of winter sports destinations have been developed to meet the most crucial attributes in consumer choice, and that for example the snow and slope conditions are important attributes for ski resort visitors. In addition, services associated with skiing and safety have also been mentioned (Miragaia et al., 2016). Major aspects such as accessibility, proximity to residence and price have been mentioned in the extant research as they may play a significant role in meeting consumer expectations (Miragaia et al., 2016). So, it appears that the assessment of the ski resorts is a multi-dimensional construct, and thus assessing it with a single item is not feasible. As skiing is a relatively high-priced activity, it is important that ski resorts provide relevant services that make a customer's money spent worthwhile. In the following sections, the impact of demographic variables and customer-centric measures will be discussed in more detail.

Impact of demographic variables on customer-centric measures

On the basis of market segmentation theory (see, e.g. Jones et al., 2005), and in terms of making segmentation schemes actionable and for them to be useful for targeting consumers, it is sometimes necessary to segment the market on the basis of demographic variables. Demographic variables such as family size, gender, income and age can be major determinants for segmentation as the demographic variables may cause differences in purchasing behaviour (Cleveland et al., 2011) in industries like travel (Abenoza et al., 2017), sports (Janssen et al., 2017), tourism (Trane, 2016) and ski resorts (Hall et al., 2017). Some of the demographic variables that may have an impact on the customer-centric measures are marital status, age, gender, income and ethnicity. With regard, for example, to age, people of different ages may prefer skiing with different levels of intensity (Muller et al., 2015).

Marital status has received relatively little attention in previous research in the context of ski resorts. Marital status has been used often as a control variable, but not so much as a focal variable in prior marketing research. In prior research when demographic variables were used as a potential basis for segmentation to predict satisfaction with tourism services, it was discovered that marital status (even including the existence of children in the relationship) could not be used to predict satisfaction (Tsiotsou and Vasioti, 2006). It is known, however, that individuals who are married have a higher average level of happiness (Diener et al., 2000). From this it can be inferred that marital status may have an impact on customer-centric measures also in the context of ski resorts as there possibly may be a distinct psychological difference between the three marital status groups. Therefore, marital status is the focal demographic variable in this study. Next, the importance of the customer-centric measures will be discussed.

Customer satisfaction

Satisfaction can be considered by a customer's sentiments of glee, content and delight towards an organization for the services provided and can influence a customer's commitment to rebuy or patronize a preferred product or service consistently in the future (Oliver, 1999). The significance of loyalty is to retain customers by giving the customer a competitive service (Thaichon and Quach, 2015). Satisfaction can promptly be extended to customer longevity, which may over time bring positive financial results. In the context of ski resorts, it has been discovered that the determinants of ski resort choice criteria may include items like downhill skiing services, cross-country skiing services, restaurants, social life and spa services, and that their importance varied from segment to segment indicating that the causes for satisfaction varied by the type of ski resort visitors (Haverila and Haverila, 2018; Konu et al., 2011). In the extant research, customer satisfaction has been frequently linked to willingness to recommend and repurchase intentions, which will be discussed next. Based on the previous discussion, the following hypothesis is set:


There are significant differences between the three marital status states (singles, partnership without children and partnership with children) regarding customer satisfaction.

Willingness to recommend

Willingness to recommend is defined as the likelihood of a customer recommending a product to a friend, relative or colleague (Korneta, 2014). It can reflect customers' behavioural intentions and may even be a better predictor of repeat purchase behaviour than the assessment of customer satisfaction (Marquis et al., 1983; Yi and La, 2004). Along with customer intentions to repurchase a product or service, their willingness to recommend the product or service to other people is a strong indicator of customer loyalty. This information in turn helps a company to understand the stability of its customer base and provides them with a better idea for future customer acquisition costs (Srivastava et al., 1999). The repurchase intentions and willingness to recommend can both help to maintain and expand the customer base.

Repurchase intention

Repurchase intention is the idea of the customers revisiting the same provider for the next purchase of either products or services. It paves the way for customer loyalty and thereby plays an important role in the success of any business. Previous research has been able to ascertain a connection between the well-established constructs of customer satisfaction and repurchase intentions and behaviours, and also discovered that the relationship is usually not linear so that the rate of change in the repurchase intent and behaviour with higher customer satisfaction ratings might be proportionally higher or lower depending upon the intensity of competition (Jones and Sasser, 1995; Mittal and Kamakura, 2001).

When trying to find a link between customer satisfaction and repurchase intention, it has been realized that apart from reducing the cost of acquiring a new customer, there is also a great deal of maintenance cost reduction as retained customers are easier to keep than new customers, which obviously has an impact on profitability (Mittal and Kamakura, 2001). While retaining customers tend to have a positive impact on profitability, it also poses a purchase decision advantage as higher levels of satisfaction tends to increase the probability of customers keeping the brand in question in their consideration sets and for that reason their brand preference may be higher (Hellier et al., 2003). This is particularly important as the ski season is relatively short, and the geographical proximity of ski resorts in many cases may not be close. Getting the competitive advantage over other ski resorts and ensuring returning customers may make all the difference. In the context of customer-centric measures, value for money has been frequently discussed and will be discussed next. Based on the previous discussion, the following hypothesis is set:


There are significant differences between the three marital status states (singles, partnership without children and partnership with children) regarding repurchase intentions.

Value for money

Consumer's value for money perceptions on the basis of their visit experiences is a predictor of service choice (Duman, 2002; Lai et al., 2009), which again may have a positive impact on the repurchase intentions and behaviour of customers. Consumers’ value judgements are based on the perceived benefits in relation to the perceived costs (Ravald and Gronroos, 1996). Therefore, providing value for customers is integral when aiming to improve customer satisfaction and ultimately customer repurchase behaviour. Additionally, with price being a component in a consumer's judgement of value, customers may also have less resistance for price increase (Dick and Basu, 1994). As value perceptions of consumers is among the most important drivers of customer satisfaction, it can be concluded that perceived value and service quality dimensions should be incorporated into the customer-centric measurement assessment profile (Mcdougall and Levesque, 2000). The consumer value judgements are not only based on individual customer perceptions; they also depend heavily on the service provider. Consumers who perceive repetitive encounters of poor value provision by the service organization will likely develop negative attitudes toward the value of the service offering, which will, in turn, have a negative influence on the consumer's repeat purchase behaviour and loyalty (Dick and Basu, 1994). Similarly, by consistently providing perceived high value for the customers, a service provider will likely realize a positive influence on consumers' attitudinal loyalty towards the company (Mcdougall and Levesque, 2000). In the context of consumer marketing, and especially so in the tourism, the quality of relationship, due to the frequency of customer interactions, is matter of importance for the repurchase intentions of the customers and will be discussed next. Based on the previous discussion, the following hypothesis is set:


There are significant differences between the three marital status states (singles, partnership without children and partnership with children) regarding value for money.

Quality of relationship

The quality of a relationship can be characterized as the quality of the situation existing between those having relations or dealings with each other. It can be between individuals, groups of people or an organization (Merriam-Webster, 2019). The leisure, recreation and tourism industry are no different in this regard as purchasers have plenty of different options to allocate their recreational energies and discretionary cash flows (Clark and Maher, 2007). Providing benefits to customers is a basis for relationship promotion to increase consumer satisfaction and loyalty. The interaction between employees and customers one or several times is the key issue (Hennig-Thurau et al., 2002) and an indicator to establish the quality of relationship (Gremler and Gwinner, 2000).

Previous research has examined the interaction between relationship quality and customer satisfaction. The causality between them appears not to be clear. Some researchers claim that the relationship quality is an antecedent of customer satisfaction (e.g. Williams et al., 2015). Similarly, customer orientation has been regarded as an antecedent of relationship quality (Barry and Doney, 2011), while in other cases, relationship quality has been measured with trust in the service provider and satisfaction with the service provider (Chen et al., 2008). In other cases, relationship quality has been treated as an outcome of customer satisfaction leading to customer retention (Hennig-Thurau and Klee, 1997). The point of view in this last study is that satisfaction with the product or service must be considered an absolute essential condition of high relationship quality. This research will adopt this point of view as the satisfaction with the products and services of the ski resort is again a necessary condition for the excellent relationship quality. In services marketing, service quality is of paramount importance and will be discussed next. Based on the previous discussion, the following hypothesis is set:


There are significant differences between the three marital status states (singles, partnership without children and partnership with children) regarding the quality of the relationship.

Service quality skiing

Skiing is obviously the most important service component in the ski resort and therefore has an impact on customer-centric measures. Prior research has examined variables affecting customer satisfaction and has proved that indeed this is the case (Haverila and Haverila, 2018). In this research paper, we wanted to concentrate on variables directly related to the ski experience as part of the service experience. It is clear that the whole experience is affected by many other constructs and variables, but as indicated, the goal here is to only concentrate on the skiing experience. For that reason, variables like moguls, safety, entertainment and skiing lessons were not included. It is obvious that these variables may also be important for some visitors of a ski resort, but likely they are not that important for all visitors and not directly related to the actual skiing experience for the entire ski resort's visitor base. At the same time, as the actual ski experience is a multi-dimensional experience, it is affected by issues like the variety, length and quality of ski slopes, capacity of the ski lifts, length of ski runs, speed of access to the ski lifts and number of slopes (Alexandris et al., 2006; Bédiová and Ryglová, 2015; Kyle et al., 2010; Matzler et al., 2007). Therefore, these variables will be used as service quality skiing indicator variables in this study. To verify this, the researchers performed an exploratory factor analysis (EFA) on the service quality skiing variables, and the results indicated the existence of two factors. The first factor included the aforementioned variables and the other consisted of a variety of other variables like snow conditions, ski lessons, entertainment and moguls. Thus, only the service quality variables directly related to the actual skiing experience were included in this study. Based on the previous discussion, the following hypothesis is set:


There are significant differences between the three marital status states (singles, partnership without children and partnership with children) regarding service quality of skiing.


The sample

The survey responses were collected by graduate business students at a Canadian university. In sampling, a multi-stage approach was used (Dudovsky, 2014). First, stratified sampling was used so that the population was divided into distinct groups according to marital status (i.e. singles, partnership without children, partnership with children, divorced and single parents). After this, within each marital status group, non-probability sampling was employed with a goal to capture all five types of ski resort visitors. As the number of responses to the groups “divorced” and “single parent” was very low, these responses were omitted from the subsequent analysis and therefore just singles, partnership without children and partnership with children respondents entered into the statistical analysis.

In total, there were 198 respondents in the survey, and after eliminating the divorced and single parent response categories, there were valid 192 responses in the sample. Before handing out the survey, the purpose of the research was clarified, and a background question regarding the marital status of the ski resort visitor question was asked. Subsequently, 47 of the respondents were singles, 57 in a partnership without children and 88 in a partnership with children.

When contemplating the adequacy of the sample size, Cochran's formula for continuous data was used (Cochran, 1977). Using the selected alpha level of 0.025 in each tail of 1.96, estimated standard deviation in a five-point scale of 0.8 and acceptable margin of error of 0.15 (number of points on primary scale * margin of error = 5*0.03), an overall sample size of 137 was desired. As there were 192 responses in the sample, the condition for the overall level of the sample size was met.

With regard to the use of partial least squares modelling-structural equation modelling (PLS-SEM), literature has established that if the required minimum path coefficient is 0.21, and the desired significance level of 5%, the sample size should be at least 69 (Hair et al., 2022), meaning the minimum sample size criteria is met.

Measurement and questionnaire development

For the customer-centric measures, established measures were used. These measures included customer satisfaction, value for money, willingness to recommend, repurchase intentions, overall performance and quality of relationship. There are several examples of the use of these customer-centric measures in the existing literature (Gruca and Rego, 2005; Hayes, 1997) also in the context of ski resorts (Faullant et al., 2008; Ferrand and Vecchiatini, 2002). In addition to the customary customer-centric measures, the service quality of skiing was also evaluated. The questionnaire was used during two successive weekends.

The questionnaire comprised of 12 questions. There was one background question for marital status, six questions related to customer-centric measures and five questions for the service quality of skiing (Table 1).

A five-point Likert response scale was employed. Questions used the scale “Very satisfied–Satisfied – Neither satisfied/dissatisfied – Dissatisfied – Very dissatisfied” or comparable to assess the ski resort visitors' perceptions of the ski resort's performance. A “Don't Know” option was also present for the questions. Previous research has discussed the use of 5-, 7- or even 10-point Likert scales in terms of the validity of the instruments in parametric research. Dawes (2008) cites on Malhotra and Peterson and specifies that the 5- or 7-point setups are the most usual and determined that the 5-, 7- or 10-point scales are all comparable for analytical tools (e.g. PLS-SEM) (Malhotra and Peterson, 2006).


To carry out the statistical analysis, first, the means and standard deviations were computed to get an impression of the character of the data for the reader. Second, to test the significance of differences between the three marital status groups, one-way ANOVA for the customer-centric measures and the service quality skiing was done. Third, to perform the IPMA analysis, a PLS-SEM analysis was applied. PLS-SEM method was chosen as it enables the conduct of the IPMA analysis in the context of structural equation modelling. Further, the use of PLS-SEM leads to high efficiency of parameter estimation meaning greater statistical power in comparison to the covariance based structural equation method (CB-SEM) (Hair et al., 2022). Fourth, the existence of common method bias was tested individually for dependent and independent constructs (Hair et al., 2010) using the Harman's single factor test, and the analysis revealed no existence of a single factor as the variance both in the case of the dependent and independent constructs was less than 50%.

Model specification, measurement and testing

The IPMA assessment was done with PLS-SEM. The starting point for the model development is the original customer satisfaction research done with regard to the European Customer Satisfaction Index (Kristensen and Eskildsen, 2010). In this model, perceived value is an antecedent of customer satisfaction, which on the other hand is an antecedent of loyalty. With regard to relationship quality, previous research has established that customer satisfaction is one of the central predictors of relationship quality (Van Tonder and Petzer, 2018; Vesel and Zabkar, 2010), which on the other hand is an important driver of loyalty (Ng et al., 2017). Service quality is usually an antecedent of customer satisfaction. Consequently, the model for this research is illustrated in Figure 1.

In the model, the value for money construct was a single-item construct (Ferrand and Vecchiatini, 2002; Matzler et al., 2007; Rodríguez-Díaz and Espino-Rodríguez, 2018), satisfaction was measured with two items (satisfaction and overall performance) (Williams et al., 2015), repurchase intentions was measured with two items (willingness to recommend and repurchase intent) (Khan et al., 2012), relationship quality was a single item construct (Chen et al., 2015; Rajati and Nikseresht, 2016) and skiing service quality was a five-item construct (Table 1).

A two-stage approach was used to test the model results (Ringle et al., 2018), so that the first stage comprised of the appraisal of the measurement model, and the second stage involved the assessment of the structural model. As the indicator variables were reflective in the measurement model, indicator reliability, internal consistency reliability, convergent validity and discriminant validity were evaluated. In terms of indicator reliability, the loadings should surpass to value of 0.70, which was the case in most cases except for the two variables (capacity of ski lifts and speed of the ski lifts) as their loadings were slightly below this threshold value. Current literature recommends that if the loading exceeds 0.70, the variable should be kept in the model. In case the loading is in between 0.40 and 0.70, construct's internal consistency reliability and convergent validity should be assessed (Hair et al., 2022). This will be done next.

With regard to internal consistency reliability, the Cronbach’s alpha values should exceed the value 0.70, and composite reliability value should be between 0.70 and 0.95. This was the case in the analysis except for the customer satisfaction construct where the Cronbach’s alpha value was just below 0.70. Previous research has indicated that the Cronbach’s alpha value is a conservative criterion, and composite reliability value a liberal one (Ringle et al., 2018). Thus, the true internal consistency reliability is in between of the Cronbach’s alpha and composite reliability values. On this basis, the internal consistency reliability has been achieved.

The convergent validity, which is usually measured with average variance extracted (AVE), should exceed the value of 0.50, which was the case here. As both the internal consistency reliability and convergent validity were achieved for the dataset, all indicator variables were kept for further analysis (Hair et al., 2022).

Current research recommends the use of the Heterotrait-Monotrait (HTMT) criteria for the assessment of discriminant validity and has stated that the value of 0.95 should not be exceeded (Ringle et al., 2018), which was the case in the assessment. Consequently, the assessment for the measurement model has been concluded.

For the evaluation of the structural model, collinearity, predictive relevance, significance of the path coefficients and appraisal of heterogeneous data structures should be done. The strict variance inflation factor (VIF) guideline for the existence of collinearity is 3.33 (Diamantopoulos and Siguaw, 2006), and this value was not exceeded in the analysis. With regard to the significance of the indicator weights, all indicator variables were significant as verified with the bootstrapping analysis tool available in Smart-PLS and using the significance of the weights as well as the confidence intervals as the basis for assessment. The R2 values indicated weak to moderate predictive relevance (Hair et al., 2011), and similar conclusions can be drawn from the Q2 values with the blindfolding procedure, as all Q2 values were higher than 0. The analysis of the observed heterogeneity was deemed to be unnecessary as the inherent assumption in this research is the existence of the observed heterogeneity with the three marital status groups.

PLS-SEM analysis suggests that all paths' standardized coefficients predicting the endogenous constructs of satisfaction and repurchase intent are significant (p < 0.01) (Figure 2). It is also to be noted that a power analysis was conducted as a post-hoc analysis and discovered that there was satisfactory power (>0.8) in the complete data set model with two predictors, observed R2 of 0.42 in the endogenous construct of repurchase intent, probability level of 0.05 and sample size of 192 (Faul et al., 2009). Therefore, the claim can be made that there is enough statistical power to deduce the significance of the relationships in the structural model. This was also the case for each of the marital status groups.

Results and discussion on the significant differences between the marital status groups

Table 2 includes the mean values and standard deviations for all customer-centric measures. Table 3 includes the mean values and standard deviations for the respondents with the three categories of marital status as well as significant differences between the categories.

The results in Table 2 reveal that the respondents had the highest perceptions for the willingness to recommend question, which was followed by the satisfaction, service quality skiing and repurchase intentions responses. The lowest ratings were received by the overall performance (met expectations) and value for money questions.

Regarding the differences between the three marital status groups, it is clear that the ski resort visitors living in a partnership with children had the highest ratings in all customer-centric measures (Table 3). These differences were significant with regard to all customer-centric measures except overall performance in terms of meeting expectations and service quality skiing. Therefore, hypotheses one through four and six are supported, and hypotheses five and seven are rejected. Further analysis divulged that there were no significant differences in any of the customer-centric measures between singles and respondents living in a partnership without children meaning that the significant differences between the three groups (if any) stem from the significantly higher ratings by the “Partnership couples with children” marital status group.

The findings may be caused by the importance of emotional satisfaction for families living with children where memories, content and rejoice play an important role seeing as families prioritize their health, family and the natural environment (Fuller and Matzler, 2008). The presence of the children in the visit to the ski resort may also have the capacity to make the experience a better one as they provide emotional satisfaction (Yu and Dean, 2001). Thus psychological factors play an important role in assessing satisfaction (Fuller and Matzler, 2008). Concerning the high repurchase intentions, customers visiting the same resort again are a great asset for a ski resort, which is especially true for visitors living in a partnership with children (Hellier et al., 2003).

These results are interesting as there appears to be a conflict with the findings of Mittal and Kamakura’s (2001) study, which stated that marital status revealed no significant differences with regard to customer satisfaction and repurchase intent (Mittal and Kamakura, 2001). The lack of significant differences in these ratings between the marital status groups is interesting as the sample size in the Mittal and Kamakura study was very large (N = 100,040), which should cause even quite small differences to be significantly different (but lacking practical significance) (Hair et al., 2010). The findings by Mittal and Kamakura may be explained by the different context of the study (automotive) because automobiles are a significant purchase regardless of marital status; it is not a service like skiing that can vary quite widely in terms of its offerings from customer to customer. It may also be explained by the fact that the marital status categories in the Mittal and Kamakura study only included “married”, “singles” and “other” categories, and thus no further refinement in terms of the existence of children was made.

As for the value for money ratings, the respondents living in partnership with children somewhat surprisingly indicated significantly higher responses than singles and respondents living in partnership without children. This is particularly surprising as skiing is comparatively a high-priced leisure activity, especially if the whole family is involved. This may be because people living in partnership with children may be financially better off than others (Diener et al., 2000), and for that reason, the value for money considerations are not considered to be as important. It may also be explained by the fact that many ski resorts offer family packages (that may include skiing passes, accommodation, food, etc.), which typically offer relatively good value for money.

The willingness to recommend responses were also significantly higher for the respondents living in partnership with children. This again shows the respondents’ higher emotional elevation and feelings for their children (Dalsgaard et al., 2006). The lower responses to the willingness to recommend question by the singles and respondents living without children may indicate a degree of redundancy in sharing their experiences with their social circle. This can perhaps be attributed to the different effects caused by an individual's life stage (Fuller and Matzler, 2008). For instance, for individuals without children, most service offerings will always be available to them, whereas, for individuals with children, some service offerings will be out of the question due to a plethora of potential issues. Therefore, when there is a service offering that meets and exceeds all of their expectations, then they will definitely recommend the service due to the inherent difficulty in finding places that are “kid-friendly” and “appropriate.”

The overall performance in meeting expectations was a variable that did not show any significant differences between the three marital status groups. This could be explained to a degree by the fact that married individuals may demonstrate a disparity between what they expect and how they perceive a service (Bishop Gagliano and Hathcote, 1994).

Concerning the relationship quality with the service provider, every business should aim to have good quality relationships with its customers. Good relationship quality may, however, be difficult to achieve as different segments of people show different attitudes (Fuller and Matzler, 2008). Again, the respondents living in partnership with children had significantly higher ratings than other respondents consistently with the responses to the other customer-centric measures. It may be that respondents living in partnership with children demonstrate higher responses in terms of relationship quality as the ski resort operators tend to cater to their needs with better service as they require more attention, which necessitates more interaction with the ski resort operator.

Finally, there were no significant differences between the three marital status categories in terms of the skiing service quality. In addition, the skiing service quality ratings were all quite high with relatively low standard deviations, indicating uniformity of the responses. This makes sense, as most skiing services offer a wide variety of ski slopes for individuals with varying degrees of skill, which means they are equally appealing to children and adults alike. In conclusion, the results regarding the differences for the customer-centric measures indicate that demographic segmentation is appropriate to detect behavioural and attitudinal differences in the market.

Results and discussion on the importance-performance map analysis

The main purpose of the hypotheses testing in this paper was to safeguard the suitability of the structural model for the conduct of the IPMA analysis. The IPMA analysis was conducted with the PLS-SEM to complement the data analysis and discussion above. The target construct in the analysis was repurchase intentions. The IPMA analysis will be done at two levels, construct and indicator, starting with the construct level analysis. The results at the construct level for all respondents and the three marital status groups can be seen in Table 4 and Figure 3.

Importance performance analysis at the construct level

The IPMA maps (Figures 3 and 4) for the constructs and indicators contain four managerial recommendation sections of “Keep up”, “Do better”, “Education” and “No change” (Hsu, 2008) on the basis of the mean values of the constructs for importance and performance in the study (Martilla and James, 1977). The shortcuts in Figure 3 are “ALL” for all respondents, REL1 for singles, REL2 for respondents living in partnership without children and REL3 for respondents living in partnership with children.

The circled areas in Figure 3 describe the areas for the constructs in the study, i.e. satisfaction, relationship quality, service quality skiing and value for money. All marital status groups appear to be in the same general region on the map. It is also clear, however, that the marital status groups do not share similar views for the customer-centric measures present in the study.

When looking at the overall performance scores, it is noticeable that there is room for improvement as the performance scale is from 0 to 100. It is also evident that the respondent group living in a “partnership with children” has the highest scores in terms of assessing the construct performance of the ski resort consistently with the findings described in Table 3. The performance differences between the groups in terms of the satisfaction, value for money and relationship quality constructs appear to be quite large and quite small in terms of the service quality skiing construct. The somewhat surprising notion mentioned earlier (Table 3) about the high ratings for the value for money construct by the respondents living in partnership with children appears to hold in the IPMA map as well. Again, this may be due to the fact that they can purchase family packages, which tend to offer better value for money for that group.

The three marital status groups clearly do not share the same views regarding the importance of the customer-centric constructs. For example, the respondents living in a partnership with children appear to rate the importance of satisfaction higher than the other marital status groups. Also, the importance of the relationship quality construct for singles is much higher than for the other marital status groups. Also, the importance of the value for money construct appears to be quite low for all marital status groups in relation to other customer-centric measures; this may be due to the fact that going to a ski resort is a relatively high-priced experience and there are not too many alternative ski resorts nearby, which means that value for money is not as important in a relative sense. One can have a satisfactory experience and a good relationship with a ski resort while feeling like the best possible value for money is not being offered.

Previous research has used the IPMA approach combined with segmentation and found it as an effective approach. In one case, the visiting frequency was used as a segmentation variable when the visitors were divided into residents, seasonal residents and tourists. It was evident IPMA evaluations differed among these segments (Bruyere et al., 2002). Further, consistently with this research paper, segmentation was found to be a necessary component of IPMA to identify differences between distinct user groups that allow more accurate planning and managerial decision-making. Additionally, the research studied how the adjustment of IPMA crosshairs can potentially augment IPMA beyond traditional methods. While the adjustment of the crosshairs makes sense, it is perhaps even more important to adjust the centre lines in the IPMA graphs to take the managerial point of view more into account. In another study, the IPMA analysis was also used in the context of a ski resort by using the indicator variables only as the point of view (Uysal et al., 1991). The distinct point in this research was that a rather comprehensive approach was used, as indicated by the use of 117 ski resort attributes in the IPMA analysis. Since the causal relationships between the various constructs were not examined, and potential lack of significance in these relationships and also a large number of ski resort attributes present in this research, the results appear to be quite fuzzy, as evidenced by Figure 1 in the Uysal et al. (1991) study. This approach could be enhanced by concentrating on the various individual products available in a ski resort to gain more meaningful results.

Importance-performance map analysis at the indicator level

The results in Table 4 and Figure 3 are interesting for the constructs as they reveal and confirm differences between the marital status groups at the latent construct level. Smart-PLS software, however, enables the assessment of the importance and performance of the ski resort at the indicator variable level, which also creates more actionable results. In this paper, the indicator level assessment will be done for the five reflective indicators of the service quality skiing construct, including the capacity of ski lifts, length of ski slopes, number of slopes, speed of lifts, and variety, length and quality of ski slopes. The results are portrayed in Table 5 and Figure 4.

When looking at the overall performance scores at the indicator level, there is clear room for improvement as the performance scale is from 0 to 100. The results in Table 5 and Figure 4 are rather interesting as they indicate pretty large differences between marital status groups in terms of importance and perceived performance of skiing quality indicators. For example, it is apparent that singles perceive the importance of the indicators “length of the ski slopes”, “variety, length and quality of ski slopes” and “number of ski slopes” to be quite a bit higher than the other marital status groups responses especially in comparison to the respondent group living in partnership without children. This may be due to the fact that singles are most likely interested in the ski slopes, and all other supplementary services that would be more important for individuals with children such as queue times, skiing schools, accommodation, day care facilities and so on are not as important to them. Simply put, families require more from a ski resort in terms of performance, and thus it is not enough to have a high quantity and quality of ski slopes, whereas for singles, having those may be more than enough for them to perceive that the ski resort is performing well. Also, the differences with regard to the “speed of ski lifts” and “capacity of ski lifts” appear to be quite as bit smaller in terms of their importance.

There are also differences between the three marital status groups in terms of the perceived performance of the skiing service quality indicators. For example, the performance perceptions of the marital status group “partnership with children” for the speed of ski lifts and number of slopes appear to be more positive in comparison to the other marital status groups. The performance perceptions for the “variety, length and quality of ski slopes” indicator, on the other hand, appear to be quite similar for the marital status groups.


This research discusses the impact of the demographic variable, marital status, on the customer-centric measures in a ski resort. The customer-centric measures used in this research are customer satisfaction, repurchase intent, value for money, willingness to recommend, overall performance in meeting expectations, relationship quality and service quality skiing. The research findings indicated significance in all hypothesized relationships so that higher value in the perceived value for money and service quality skiing lead to higher customer satisfaction ratings, which contribute to higher relationship quality evaluations. Also, as significant differences emerged between the respondents living in partnership with children and other marital status groups, the importance of tailoring products and services for different demographics at a ski resort appears to be warranted.

To improve the ratings for the customer-centric measures, the management of the ski resort must first understand the different variables that impact the assessment of these measures. The data gathered from this study can be useful for ski resorts in many ways. Customer-centric measures are of prime concern for any company. Still, the visitors to a ski resort appreciate these measures in different ways based on the IPMA analysis.

Based on the findings, marital status appears to be a major concern in this regard. Although satisfaction arises from external factors like cosiness of the facilities, marital status appears to have an impact as well. Therefore, the management of the ski resort should utilize these findings and try to tailor their marketing strategies accordingly. A key management implication is that the IPMA method enables the management to reallocate (and likely re-educate) the ski resort resources and assign them more appropriately, as suggested by the IPMA framework. In this research, there appear to be some differences between the marital status groups at the construct level, but expectedly so more at the indicator variable level. For example, the results reveal for the ”Length of the ski slopes” variable an overall assessment (including all response groups) a “Do better” assessment. However, this is not the case for the marital status group “Living in partnership without children,” which gained a “No change” assessment. Therefore, the management of the ski resort should ensure that there are longer (and more challenging) ski slopes available for the singles. Also, it is apparent that the ski lift capacity is adequate (in relationship to the other customer-centric measures). There the capacity of ski lifts got a “No change” recommendation. It is to be noted here that the ski resort business is seasonal also during the weeks and months of the season. Thus the capacity issue might be more critical during weekends and holidays (Note: The survey for this research was conducted during the weekends).

In addition to knowing the actual IPMA results, it is also important to acknowledge the importance of existence of a good-quality structural model as the basis of the IPMA analysis. This includes the existence of significant relationships in the model, which enables the marketing manager to understand what impacts what in the context of the ski resort.

Previous research for the context of this research is scarce. In a notable exception in the study by Fuller and Matzler (2008), lifestyle was used as a segmentation variable. Marital status was discovered to significantly differentiate the lifestyle-based segments as the marital status composition of the segments was quite different, which is consistent with the findings of this research. Again, the emphasis was more in the comprehensive ski resort experience rather than skiing only.


Although this research highlights the significance of marital status in regard to customer satisfaction, there are limitations to the study as well. When evaluating the customer-centric measures in the context of a ski resort, other demographic variables may also have an impact. Also, the study was conducted in British Columbia, Canada, so adding other geographical regions to the study might be interesting as far as the generalizability of the findings is concerned. It is important to note, however, that each IPMA analysis is unique, and thus comparison to the existing research is not that interesting or important.


This study examined the impact of the demographic variable, marital status, on customer-centric measures in the context of a ski resort. Also, the importance and performance of the customer-centric measures were investigated at the latent construct level and at the more specific and actionable indicator level. The results indicate that marital status indeed impacts the assessment of the customer-centric measures, as five out of the seven measures had significant differences with regards to marital status. It was evident that these significant differences were mainly between the respondents living in a partnership with children and the other two marital status groups (singles and respondents living in a partnership without children). This information is crucial for ski resort management as it highlights the significance of the impact of consumer demographics, not only on the assessment of the customer-centric measures but also on the importance and performance evaluations. For the management of the ski resort, they should offer a skiing experience more tailored to their marital status.


The structural model

Figure 1

The structural model

Results of the partial least squares modelling (PLS) analysis

Figure 2

Results of the partial least squares modelling (PLS) analysis

Importance-performance map (IPMA) at the construct level

Figure 3

Importance-performance map (IPMA) at the construct level

Importance-performance map (IPMA) at the service quality skiing indicator level

Figure 4

Importance-performance map (IPMA) at the service quality skiing indicator level

Measurement scales for the indicator variables

ConstructIndicator variableRelevant measure used by
Customer satisfactionSatisfaction
Overall performance
Repurchase intentRepurchase intent
Willingness to recommend
Value for moneyValue for money
RelationshipQuality of relationship
Service quality (skiing)
  • Capacity of ski lifts

  • Length of ski slopes

  • Number of slopes

  • Speed of lifts

  • Variety, length, and quality of ski slopes

Mean values and standard deviations of the indicator variables in the sample population

Customer satisfactionMet expectationsRepurchase intentWillingness to recommendValue for moneyRelationship qualityService quality–skiing
4.38 (0.60)3.65 (0.84)4.20 (0.95)4.41 (0.65)3.66 (1.00)3.84 (0.91)4.31 (0.48)

Differences in mean values and standard deviations of the customer-centric measures between the marital status groups

ConstructSingles (REL1)Partnership with no children (REL2)Partnership couples with children (REL3)Significance between the groups
Customer satisfaction4.23 (0.63)4.25 (0.66)4.53 (0.50)**
Met expectations3.51 (0.88)3.61 (0.73)3.75 (0.87)n.s.
Willingness to recommend4.26 (0.67)4.26 (0.70)4.58 (0.56)**
Repurchase intent3.89 (1.18)4.04 (0.96)4.47 (0.71)***
Value for money3.43 (0.95)3.44 (0.96)3.92 (0.99)**
Relationship quality3.72 (1.02)3.67 (0.89)4.02 (0.84)*
Service quality–skiing4.31 (0.47)4.20 (0.49)4.38 (0.46)n.s.

Note(s): *** significance at <0.001, ** significance at <0.01, * significance at <0.05, n.s. = not significant

The results of the importance-performance map analysis at the construct level

Marital statusItemImportancePerformanceAction
All respondentsSatisfaction (SAT)0.57772.617Keep up
Value for money (VM)0.17166.418No change
Relationship quality (RQ)0.36862.189Do better
Service quality-skiing0.27880.817Education
Singles (REL1)Satisfaction (SAT)0.53371.726Keep up
Value for money (VM)0.08760.638No change
Relationship quality (RQ)0.43057.447Do better
Partnership without children (REL2)Satisfaction (SAT)0.48068.234Do better
Value for money (VM)0.16460.965No change
Relationship quality (RQ)0.31255.556No change
Partnership with children (REL3)Satisfaction (SAT)0.59975.855Keep up
Value for money (VM)0.13873.011No change
Relationship quality (RQ)0.33267.424No change

The results of the importance-performance map analysis at the indicator level

Marital statusItemImportancePerformanceAction
All respondentsCapacity of ski lifts0.05574.793No change
Length of ski slopes0.08178.441Do better
No. of slopes0.08683.831Keep up
Speed of ski lifts0.05582.463Education
Variety, length and quality of slopes0.09083.333Keep up
SinglesCapacity of ski lifts0.06175.887No change
Length of ski slopes0.09479.433Do better
No. of slopes0.10282.979Keep up
Speed of ski lifts0.05081.915Education
Variety, length and quality of slopes0.11082.447Keep up
Partnership without childrenCapacity of ski lifts0.05371.930No change
Length of ski slopes0.05675.439No change
No. of slopes0.05680.263No change
Speed of ski lifts0.05178.509No change
Variety, length and quality of slopes0.06081.140Education
Partnership with childrenCapacity of ski lifts0.05775.000No change
Length of ski slopes0.08679.924Do better
No. of slopes0.09586.364Keep up
Speed of ski lifts0.05884.943Education
Variety, length and quality of slopes0.09684.375Keep up
Average (All respondents)0.07882.121


Abenoza, R.F., Cats, O. and Susilo, Y.O. (2017), “Travel satisfaction with public transport: determinants, user classes, regional disparities and their evolution”, Transportation Research Part A: Policy and Practice, Vol. 95, pp. 64-84.

Alexandris, K., Kouthouris, C. and Meligdis, A. (2006), “Increasing customers' loyalty in a skiing resort: the contribution of place attachment and service quality”, International Journal of Contemporary Hospitality Management, Vol. 18 No. 5, pp. 414-425.

Barry, J.M. and Doney, P.M. (2011), “Cross-cultural examination of relationship quality”, Journal of Global Marketing, Vol. 24 No. 4, pp. 304-323.

Bédiová, M. and Ryglová, K. (2015), “The main factors influencing the destination choice, satisfaction and the loyalty of ski resorts customers in the context of different research approaches”, Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Vol. 63 No. 2, pp. 499-505.

Bishop Gagliano, K. and Hathcote, J. (1994), “Customer expectations and perceptions of service quality in retail apparel specialty stores”, Journal of Services Marketing, Vol. 8 No. 1, pp. 60-69.

Bruyere, B.L., Rodriguez, D.A. and Vaske, J.J. (2002), “Enhancing importance-performance analysis through segmentation”, Journal of Travel and Tourism Marketing, Vol. 12 No. 1, pp. 81-95.

Chen, Z.X., Shi, Y. and Dong, D.-H. (2008), “An empirical study of relationship quality in a service setting: a Chinese case”, Marketing Intelligence and Planning, Vol. 26 No. 1, pp. 11-25.

Chen, N., Zhao, Q. and Ardley, B. (2015), “The impact of personal connection on customer behaviours (word-of-mouth intention and retention) in service encounters”, 3rd International Conference on Contemporary Marketing Issues, Kingston, Kingston University.

Clark, J.S. and Maher, J.K. (2007), “If you have their minds, will their bodies follow? Factors affecting customer loyalty in a ski resort setting”, Journal of Vacation Marketing, Vol. 13 No. 1, pp. 59-71.

Cleveland, M., Papadopoulos, N. and Laroche, M. (2011), “Identity, demographics, and consumer behaviors: international market segmentation across product categories”, International Marketing Review, Vol. 28 No. 3, pp. 244-266.

Cochran, W.G. (1977), Sampling Techniques, John Wiley & Sons, New York.

CTV News (2019), “CTV News. Retrieved from Tourism contributing $9B to B.C. economy, government says”, available at:

Dalsgaard, T., Skov, M.B., Stougaard, M. and Thomassen, B. (2006), “Mediated intimacy in families: understanding the relation between children and parents”, Proceedings of the 2006 conference on Interaction design and children, Tampere, ACM New York, pp. 145-152.

Dawes, J.G. (2008), “Do data characteristics change according to the number of scale points used? An experiment using 5 point, 7 point and 10 point scales”, International Journal of Market Research, Vol. 51 No. 1, pp. 61-77.

Diamantopoulos, A. and Siguaw, J.A. (2006), “Formative versus reflective indicators in organisational measure development: a comparison and empirical illustration”, British Journal of Management, Vol. 17 No. 4, pp. 263-282.

Dick, A.S. and Basu, K. (1994), “Customer loyalty: toward an integrated conceptual framework”, Journal of the Academy of Marketing Science, Vol. 22 No. 2, pp. 99-113.

Diener, E., Gohm, C.L., Suh, E. and Oishi, S. (2000), “Similarity of the relations between marital status and subjective well-being across cultures”, Journal in Cross-Cultural Psychology, Vol. 31 No. 4, pp. 419-436.

Dudovsky, J. (2014), The Ultimate Guide to Writing a Dissertation in Business Studies, BV, NewYork.

Duman, T. (2002), “A model of perceived value for leisure travel products”, Electronic Theses and Dissertations for Graduate School, available at:

Faul, F., Erdfelder, E., Buchner, A. Lang, A.G. (2009), “Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses”, Behavior Research Methods, Vol. 41, pp. 1149-1160, doi: 10.3758/BRM.41.4.1149.

Faullant, R., Matzler, K. and Füller, J. (2008), “The impact of satisfaction and image on loyalty: the case of Alpine ski resorts”, Managing Service Quality: An International Journal, Vol. 18 No. 2, pp. 163-178.

Ferrand, A. and Vecchiatini, D. (2002), “The effect of service performance and ski resort image on skiers' satisfaction”, European Journal of Sport Science, Vol. 2 No. 2, pp. 1-17.

Fuller, J. and Matzler, K. (2008), “Customer delight and market segmentation: an application of the three-factor theory of customer satisfaction on life style groups”, Tourism Management, Vol. 29 No. 1, pp. 116-126.

Gremler, D.D. and Gwinner, K.P. (2000), “Customer-employee rapport in service relationships”, Journal of Service Research, Vol. 3 No. 1, pp. 82-104.

Gruca, T.S. and Rego, L.L. (2005), “Customer satisfaction, cash flow, and shareholder value”, Journal of Marketing, Vol. 69 No. 3, pp. 115-130.

Hair, J., Black, B., Babin, B., Anderson, R. and Tatham, R. (2010), Multivariate Data Analysis, Pearson, New York.

Hair, J., Ringle, C. and Sarstedt, M. (2011), “PLS-SEM: indeed a silver bullet”, Journal of Marketing Theory and Practice, Vol. 19 No. 2, pp. 139-151.

Hair, J., Hult, T., Ringle, C. and Sarstedt, M. (2022), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage, Thousand Oaks.

Hall, J., O'Mahony, B. and Gayler, J. (2017), “Modelling the relationship between attribute satisfaction, overall satisfaction, and behavioural intentions in Australian ski resorts”, Journal of Travel and Tourism Marketing, Vol. 34 No. 6, pp. 764-778.

Haverila, M. and Haverila, K. (2018), “Applying the customer satisfaction model in the context of major Canadian Ski Resort: the impact of the type of the customer”, Asia Pacific Journal of Marketing and Logistics, Vol. 30 No. 2, pp. 438-459.

Hayes, B. (1997), Measuring Customer Satisfaction: Survey Design, Use, and Statistical Analysis Methods, ASQ Quality Press, Milwaukee, WI.

Hellier, P.K., Geursen, G.M., Carr, R.A. and Rickard, J.A. (2003), “Customer repurchase intention: a general structural equation model”, European Journal of Marketing, Vol. 37 Nos 11/12, pp. 1762-1800.

Hennig-Thurau, T. and Klee, A. (1997), “The impact of customer satisfaction and relationship quality on customer retention: a critical reassessment and model development”, Psychology and Marketing, Vol. 14 No. 8, pp. 737-764.

Hennig-Thurau, T., Gwinner, K.P. and Gremler, D.D. (2002), “Understanding relationship marketing outcomes: an integration of relational benefits and relationship quality”, Journal of Service Research, Vol. 4 No. 3, pp. 230-247.

Hsu, S.-H. (2008), “Developing an index for online customer satisfaction: adaptation of American customer satisfaction index”, Expert Systems with Applications, Vol. 34 No. 4, pp. 3033-3042.

Hudson, S. (1998), “There's no business like snow business! Marketing skiing into the 21 st century”, Journal of Vacation Marketing, Vol. 4 No. 4, pp. 393-407.

Hyde, K.F. (2008), “Information processing and touring planning theory”, Annals of Tourism Research, Vol. 35 No. 3, pp. 712-731.

Janssen, M., Scheerder, J., Thibaut, E., Brombacher, A. and Vos, S. (2017), “Who uses running apps and sports watches? Determinants and consumer profiles of event runners' usage of running-related smartphone applications and sports watches”, PLoS One, Vol. 7.

Jones, T.O. and Sasser, W.E. (1995), “Why satisfied customers defect”, Harvard Business Review, Vol. 73 No. 6, pp. 88-99.

Jones, S.C., Rees, L., Hall, D. and Tang, A. (2005), “Using market segmentation theory to select target markets for sun protection campaigns”, University of Wollomgong, available at:

Khan, S., Naumann, E. and Williams, P. (2012), “Identifying the key drivers of customer satisfaction and repurchase intentions: an empirical investigation of Japanese B2B services”, Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, Vol. 25, pp. 159-178.

Konu, H., Laukkanen, T. and Komppula, R. (2011), “Using ski destination choice criteria to segment Finnish ski resort customers”, Tourism Management, Vol. 32 No. 5, pp. 1096-1105.

Korneta, P. (2014), “What makes customers willing to recommend a retailer-the study on roots of positive Net Promoter Score index”, Central European Review of Economics and Finance, Vol. 5 No. 2, pp. 61-74.

Kristensen, K. and Eskildsen, J. (2010), “Design of PLS-based satisfaction studies”, in Vinzi, V.E., Chin, W.W., Henseler, J. and Wang, H. (Eds), Handbook of Partial Least Squares: Concepts, Methods and Applications, Springer, Hamburg.

Kyle, G.T., Theodorakis, N.D., Karageorgiou, A. and Lafazani, M. (2010), “The effect of service quality on customer loyalty within the context of ski resorts”, Journal of Park and Recreation Administration, Vol. 28 No. 1, pp. 1-15.

Lai, F., Griffin, M. and Babin, B.J. (2009), “How quality, value, image, and satisfaction create loyalty at a Chinese telecom”, Journal of Business Research, Vol. 62 No. 10, pp. 980-986.

Malhotra, N. and Peterson, M. (2006), Basic Marketing Research: A Decision-Making Approach, Prentice-Hall, New Jersey.

Marquis, M.S., Davies, A.R. and Ware, J.E. (1983), “Patient satisfaction and change in medical care provider: a longitudinal study”, Medical Care, Vol. 21 No. 8, pp. 821-829.

Martilla, J.A. and James, J.C. (1977), “Importance-performance analysis”, Journal of Marketing, Vol. 41 No. 1, pp. 77-79.

Matzler, K., Füller, J. and Faullant, R. (2007), “Customer satisfaction and loyalty to Alpine ski resorts, the moderating effect of lifestyle, spending and customers' skiing skills”, International Journal of Tourism Research, Vol. 9 No. 6, pp. 409-421.

Matzler, K., Füller, J., Renzl, B., Herting, S. and Späth, S. (2008), “Customer satisfaction with Alpine Ski areas: the moderating effects of personal, situational, and product factors”, Journal of Travel Research, Vol. 46 No. 4, pp. 403-413.

Mcdougall, G.H. and Levesque, T. (2000), “Customer satisfaction with services: putting perceived value into the equation”, Journal of Services Marketing, Vol. 14 No. 5, pp. 392-410.

Merriam-Webster (2019), “Merriam-webster”, Merriam-Webster Dictionary, available at:

Miragaia, D., Conde, D. and Soares, J. (2016), “Measuring service quality of ski resorts: an approach to identify the consumer profile”, The Open Sports Sciences Journal, Vol. 9 No. 1, pp. 53-61.

Mittal, V. and Kamakura, W.A. (2001), “Satisfaction, repurchase intent, and repurchase behaviour: investigating the moderating effect of customer characteristics”, Journal of Marketing Research, Vol. 38 No. 1, pp. 131-142.

Muller, L., Hildebrandt, C. and Raschner, C. (2015), “The relative age effect and the influence on performance in youth alpine ski racing”, Journal of Sports Science and Medicine, Vol. 14 No. 1, pp. 16-22.

Ng, S., David, M.T. and Dagger, T.S. (2017), “Examining customer perceptions of relationship quality over time”, in Campbell, C. (Ed.), The Customer Is NOT Always Right? Marketing Orientationsin a Dynamic Business World, Springer, Cham, p. 304.

Oliver, R.L. (1999), “Whence consumer loyalty?”, Journal of Marketing, Vol. 4 No. 1, pp. 33-44.

Rajati, S. and Nikseresht, F. (2016), “Explanation of the role of customer participation in production on customer's compatibility and satisfaction”, International Journal of Humanities and Cultural Studies (Special), pp. 2664-2674.

Ravald, A. and Gronroos, C. (1996), “The value concept and relationship marketing”, European Journal of Marketing, Vol. 30 No. 2, pp. 19-30.

Ringle, C., Sarstedt, M., Mitchell, R. and Gudergan, S. (2018), “Partial least squares structural equation modeling in HRM research”, International Journal of Human Resource Management, Vol. 19 No. 2, pp. 1617-1643.

Rodríguez-Díaz, M. and Espino-Rodríguez, T.F. (2018), “A methodology for a comparative analysis of the lodging offer of tourism destinations based on online customer reviews”, Journal of Destination Marketing and Management, Vol. 8, pp. 147-160.

Srivastava, R.K., Shervani, T.A. and Fahey, L. (1999), “Marketing, business processes, and shareholder value: an organizationally embedded view of marketing activities and the discipline of marketing”, Journal of Marketing, Vol. 4 No. 1, pp. 168-179.

Taks, M. and Ragoen, J. (2016), “Coping with recession in the ski-industry: a suppliers' and consumers' perspective”, University of Windsor, available at: (accessed October 2019).

Thaichon, P. and Quach, T.N. (2015), “From marketing communications to brand management: factors influencing relationship quality and customer retention”, Journal of Relationship Marketing, Vol. 14 No. 3, pp. 197-219.

Trane, C. (2016), “The determinants of Norwegians' summer tourism expenditure: foreign and domestic trips”, Tourism Economics, Vol. 22 No. 1, pp. 31-46.

Tsiotsou, R. and Vasioti, E. (2006), “Using demographics and leisure activities to predict satisfaction with tourism services in Greece”, Journal of Hospitality and Leisure Marketing, Vol. 14 No. 2, pp. 69-82.

Uysal, M., Howard, G. and Jamrozy, U. (1991), “An application of importance-performance analysis to a ski resort: a case study in North Carolina”, Visions in Leisure and Business, Vol. 10 No. 1.

Van Tonder, E. and Petzer, D.J. (2018), “The interrelationships between relationship marketing constructs and customer engagement dimensions”, The Service Industries Journal, Vol. 38 Nos 13/14, pp. 1-26.

Vesel, P. and Zabkar, V. (2010), “Relationship quality evaluation in retailers' relationships with consumers”, European Journal of Marketing, Vol. 44 Nos 9-10, pp. 1334-1365.

Williams, P., Ashill, N.J., Naumann, E. and Jackson, E. (2015), “Relationship quality and satisfaction: customer-perceived success factors for on-time projects”, International Journal of Project Management, Vol. 33 No. 8, pp. 1836-1850.

Yi, Y. and La, S. (2004), “What influences the relationship between customer satisfaction and repurchase intention? Investigating the effects of adjusted expectations and customer loyalty”, Psychology and Marketing, Vol. 21 No. 5, pp. 351-373.

Yu, Y.-T. and Dean, A. (2001), “The contribution of emotional satisfaction to consumer loyalty”, International Journal of Service Industry Management, Vol. 12 No. 3, pp. 234-250.

Further reading

Pollak, R.A. and Wales, T.J. (1981), “Demographic variables in demand analysis”, Econometrica, Vol. 49 No. 6, pp. 1533-1551.

Corresponding author

Matti Haverila can be contacted at:

Related articles