Journal of Tourism & Hospitality

Journal of Tourism & Hospitality
Open Access

ISSN: 2167-0269

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Research Article - (2020) Volume 9, Issue 3

Impact of Marital Status on Customer-centric Measures in Ski Resorts Using the Importance-performance (IPMA) Framework

Matti Haverila1*, Kai Haverila2 and Jenny Twyford3
 
*Correspondence: Matti Haverila, School of Business and Economics, Thompson Rivers University, Canada, Tel: + 4388202641, Email:

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Abstract

Impact of marital status towards customer-centric measures in a Canadian ski resort is assessed. The perceptions of three marital groups were assessed using the importance-performance framework. The customer-centric measures included customer satisfaction overall repurchase intent, value for money, relationship quality and skiing service quality. Results indicate that for four of the five customer-centric measures, there were significant differences between the marital status groups. Overall, singles appeared to have the lowest perceptions of the customer-centric measures, whereas respondents living in partnership with children had the highest. The 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 between the respondents living in partnership with children and others.

Keywords

Customer satisfaction; Repurchase intent; Value for money; Service quality; Ski resort; Importanceperformance (IPMA) analysis

Introduction

Satisfying customers is one of the key factors for any business. This is not an exception for ski resorts in Canada and elsewhere. In 2017, tourism alone contributed $9 billion dollars to British Columbia’s GDP, with more than 10% of this coming from ski resorts [1]. 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 [2]. In this research, the focus is on understanding the importance of marital status on the customercentric measures in the context of a ski resort.

Previous research has discovered that demographic variables can have an impact on the assessment of customer-centric measures [3]. 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 [4]. 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 accordingly requires research and consideration when assessing the customer experience at a ski resort. These measures were customer satisfaction repurchase intent, relationship quality, value for money and service quality of skiing. By studying these constructs, this research paper 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 importance-performance evaluations of the ski resort visitors.

Literature Review

Regarding the profile of a ski resort customer, it is critical to understand the expectations that customers consider before traveling (destination attributes), since these expectations will directly affect the degree of satisfaction after the visiting experience [5]. 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 has also been mentioned [5]. 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 [5]. So, it appears that the assessment of the ski resorts is a multidimensional 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 seem worthwhile.

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 [6]. The significance of loyalty is to retain customers by giving the customer a competitive service [7]. Satisfaction can promptly be extended to customer longevity, which may over time bring positive financial results. In the context of ski resorts, 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 their importance varies from segment to segment indicating that the causes for satisfaction by the type of ski resort visitors may differ [8,9].

Repurchase intention

Repurchase intent 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 ascertained 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 [10,11].

When trying to find a link between customer satisfaction and repurchase intent, 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 [11]. While retaining customers tends 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 set and for that reason their brand preference may be higher [12]. 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.

Value for money

Consumer’s value for money perceptions on the basis of their visit experiences is a predictor of service choice, which again may have a positive impact on the repurchase intentions and behaviour of customers [13,14]. Consumers’ value judgments are based on the perceived benefits in relation to the perceived costs [15]. 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 increases [16]. As value perceptions of consumers are among the most important drivers of customer satisfaction, it can be concluded that perceived value and service quality dimensions should be incorporated into the customercentric measurement assessment profile [17]. The consumer value judgments 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 [16]. 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 [17].

Willingness to recommend

Willingness to recommend is defined as the likelihood of a customer recommending a product to a friend, relative or colleague [18]. It can reflect customers’ behavioural intentions and may even be a better predictor of repeat purchase behaviour than the assessment of customer satisfaction [19,20]. Along with customer intentions to repurchase a product or service, their willingness to recommend the product or service is a strong indicator of customer loyalty. This information in turn helps the company to understand the stability of its customer base and provides them with a better idea for future customer acquisition costs [21]. The repurchase intentions and willingness to recommend can both help to maintain and expand the customer base.

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 [22]. 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 [23]. 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 and an indicator to establish the quality of relationship [24,25].

Service quality-skiing

Skiing is obviously the most important service component in the ski resort and therefore likely has an impact on customer-centric measures. Prior research has examined variables affecting customer satisfaction, and has proved that indeed this is the case [8]. In this research paper, it was necessary to concentrate on variables directly related to the ski experience as part of the service experience. It is clear that the whole ski resort experience is affected by many other constructs and variables, but as indicated the goal here is to concentrate on the skiing experience only. 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, and 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 [26-29]. Therefore, these variables will used as service quality skiing indicator variables in this study.

To verify the dimensionality of the service quality-skiing construct, the researchers performed an Exploratory Factor Analysis (EFA) on the service quality skiing variables, and the results indicated the existence of two factors instead of one. The first factor included the aforementioned skiing related 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.

Impact of demographic variables on customer centric measures

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 [30]. In the context of segmentation for example, when trying to make 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 and categorizing the product or service market as the demographic variables may cause differences in purchasing behaviour in industries like travel, sports, tourism and ski resorts [31-35].

Marital status has received relatively little attention in previous research in the context of ski resorts as marital status has been mainly used as a background or control variable, but not so much as a focal variable in prior in academic research. Not surprisingly, Google Scholar revealed numerous research papers where marital status had been used a control variable in ski-resort research. In prior research demographic variables were used as a potential basis for segmentation to predict satisfaction with tourism services, and it was discovered that marital status (even when including the existence of children in the relationship) were not able to classify customers into highly satisfied and less satisfied customers [36]. It is known, however, that individuals who are married have a higher average level of happiness [37]. 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.

Hypotheses development

On the basis of the literature review above, it can be concluded that marital status may have an impact on customer-centric measures, and therefore the following hypotheses are set: There are significant differences between the three marital status states (singles, partnership without children and partnership with children) regarding:

H1. Customer satisfaction

H2. Value for money

H3. Repurchase intent

H4. Quality of relationship

H5. Service quality skiing.

Methodology

The sample

The surveys were conducted by students as part of their graduate marketing course among ski resort visitors in British Columbia, Canada in two consecutive weekends. In sampling, a multi-stage approach was used [38]. First, for the purposes of cluster sampling, the modified classification of legal marital status of Statistics Canada was used so that the population was divided into separate clusters according to marital status [39]. In addition, it was felt to be important to make a distiction between partnership with or without children, as the presence of the children in the visit to the ski resort may make the experience a better one as they provide emotional satisfaction [40]. Therefore, the initial marital status classes in this study were singles, partnership without children, partnership with children, divorced, and single parents. After this, within each marital status cluster, simple random sampling was applied with an aim to catch all five types of ski resort visitors. However, as the number of responses to the categories “divorced” and “single parent” was really low, these responses were excluded from the further analysis and therefore only singles, partnership without children, and partnership with children respondents were included in the statistical analysis.

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

When considering the adequacy of the sample size, Cochran’s formula for continuous data was used [41]. Using the selected alpha level of 0.025 in each tail of 1.96, estimated standard deviation in a 5-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 needed. As there were 192 responses in the sample, the requirement for the overall level of the sample size was met.

With regard to the partial least squares modelling, previous research has determined that if the maximum number of arrows pointing to a construct is two, the required significance level is at 5%, and minimum R2 is 0.50, then only 14 responses are needed meaning the minimum sample size criteria is met [42].

Measurement and questionnaire development

For the customer-centric measures, standard global measures were used. These measures included satisfaction (as measured with customer satisfaction, and meeting expectations in terms of overall performance), repurchase intent (as measured with willingness to recommend, and repurchase intentions), value for money, and quality of relationship. These measures have been frequently used in customer satisfaction studies and there are numerous examples of the use of these customer-centric measures in the extant literature also in the context of ski resorts [43-46]. In addition to the standard customer-centric measures, the service quality with regard to skiing was also assessed.

The questionnaire included 12 questions. There was one background question regarding the marital status, six questions related to customer-centric measures and five questions for the service quality of skiing. The following Table 1 provides a summary of the measurement variables and the sources for measurement. A five-point Likert response scale was used. Questions employed the scale “Very satisfied-Satisfied-Neither satisfied/dissatisfied- Dissatisfied-Very dissatisfied” or equivalent to measure the ski resort visitors’ perceptions of the ski resort’s performance. A “Don’t Know” option was also available for all questions. There has been some discussion in previous research about the use of 5-, 7-, or even 10-point Likert scales in terms of the validity of the instruments in parametric research. Dawes cites on Malhotra and Peterson indicating that the 5- or 7-point formats are the most common and concluded that either 5-, 7- or 10-point scales are all comparable for analytical tools (e.g. Partial Least Squares Modelling, PLS) [47,48].

Method

To conduct the statistical analysis, first, the means and standard deviations were calculated to give an overview of the nature 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 conducted. Third, to conduct the importance-performance analysis, a Partial Least Squares Structural Equation Modelling (PLS-SEM) analysis tool was used.

Model specification, measurement and testing

The importance-performance assessment part of the research was done with Partial Least Squares Structural Equation Modelling (PLSSEM). In order to use the importance-performance tool embedded in Smart-PLS, a model needed to be developed. The starting point for the model development in this study is the original customer satisfaction research done with regard to the European Customer Satisfaction Index [49]. 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, which is an important driver of loyalty [50-52]. Service quality is usually an antecedent of customer satisfaction. Consequently, the model for this research is illustrated in Figure 1.

tourism-hospitality-research

Figure 1: The structural model of the research.

In the model, the value for money construct was a single item construct satisfaction was measured with two items (satisfaction and overall performance) repurchase intentions was measured with two items (willingness to recommend and repurchase intent) relationship quality was a single item construct and skiing service quality was a five-item construct as specified in Table 1 [53-57].

Table 1: Measurement scales of study variables.

Construct Indicator variables Relevant measure
Overall satisfaction 1. Satisfaction
2. Overall performance in terms of meeting expectations
•(Ferrand and Vecchiatini, 2002)
•(Kyle, Theodorakis, Karageorgiou, and Lafazani, 2010)
•(Matzler, Füller, and Faullant, 2007)
•(Matzler, Füller, Renzl, Herting, and Späth, 2008)
Value for money 1. Value for money •(Ferrand and Vecchiatini, 2002)
•(Matzler, Füller, and Faullant, 2007)
Repurchase intent 1. Willingness to recommend
2. Repurchase intent
•(Faullant, Matzler, and Füller, 2008)
•(Ferrand and Vecchiatini, 2002)
Quality of relationship 1.Quality of relationship •(Rajati and Nikseresht, 2016)
Service quality skiing 1.Capacity of ski lifts
2.Length of ski slopes
3.Number of slopes
4.Speed of lifts
5.Variety, length and quality of ski slopes
•(Alexandris et al. 2006)
•(Bédiová and Ryglová, 2015)
•(Kyle, Theodorakis, Karageorgiou, and Lafazani, 2010)
•(Matzler, Füller, Renzl, Herting, and Späth, 2008)

A two-stage approach was used to test the model results, so that the first stage included the assessment of the measurement model and the second stage included the assessment of the structural model [58]. As the indicator variables were reflective in the measurement model, indicator reliability, internal consistency reliability, convergent validity and discriminate validity were assessed. In terms of indicator reliability, the loadings should exceed 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 (Table 2). Previous research has noted, however, that the relative contribution is not the only required information; in addition, the significance of the outer weights needs to be assessed. Table 2 includes the bias-corrected and accelerated bootstrapping (with no sign changes) confidence intervals, and the results indicate all indicator variables, in fact, contribute significantly to the corresponding constructs [59].

Table 2: Outer weights and loadings of the indicator variables and their significance to the corresponding constructs.

Construct Indicator variable Outer weights Outer loadings (5% bias corrected confidence interval Significance (p<0.05)
2.5% 97.5%
Service quality skiing Capacity of the ski lifts 0.198 0.596 0.489 0.699 Yes
Length of ski slopes 0.292 0.820 0.761 0.866 Yes
Number of slopes 0.310 0.860 0.809 0.893 Yes
Speed of ski lifts 0.199 0.572 0.432 0.685 Yes
Variety, length and quality of ski slopes 0.323 0.813 0.754 0.860 Yes
Overall repurchase intent Repurchase intent 0.483 0.837 0.761 0.890 Yes
Willingness to recommend 0.652 0.914 0.885 0.932 Yes
Relationship quality Relationship quality 1.000 1.000 1.000 1.000 Yes
Overall satisfaction Satisfaction 0.558 0.853 0.790 0.897 Yes
Meeting expectations 0.599 0.874 0.833 0.907 Yes
Value for money Value for money 1.000 1.000 1.000 1.000 Yes

The results in Table 2 further indicate that the variety, length and quality of ski slopes contribute the most to the service quality skiing construct; willingness to recommend contributes most to the repurchase intent construct; and meeting expectations in terms of performance contributes most to the satisfaction construct.

With regard to internal consistency reliability, the Cronbach 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 for which the Cronbach alpha value was just below 0.70. Previous research has indicated that the Cronbach alpha value is the most conservative criteria and composite reliability value the most liberal one [58]. The convergent validity, which is usually measured with Average Variance Extracted (AVE), should exceed the value of 0.50, which was the case here (Table 3).

Table 3: Construct reliability and validity.

Construct Cronbach's Alpha Composite Reliability Average Variance Extracted (AVE)
Overall satisfaction 0.661 0.855 0.746
Repurchase intent 0.704 0.869 0.768
Service quality skiing _ 0.790 0.857 0.551

Recent 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, which was the case (Table 4).

Table 4: Discriminant validity with the Heterotrait-Monotrait criterion.

Construct Overall Satisfaction Repurchase intent Relationship quality Service quality skiing
Repurchase intent 0.827      
Relationship quality 0.706 0.679    
Service quality skiing 0.845 0.673 0.613  
Value for money 0.646 0.648 0.617 0.523

In terms of the assessment of the structural model, collinearity, predictive relevance, significance of the path coefficients and assessment of heterogeneous data structures should be done [58]. The strict Variance Inflation Factor (VIF) guideline for the existence of collinearity is 3.33, and as all the VIF values were below 2, there was no collinearity issues in the structural model. The R2 values indicated weak to moderate predictive relevance [60,61]. The Stone-Geisser Q2 values [62,63] with the blindfolding procedure indicate predictive relevance as well as all Q2 values were higher than 0 (Table 5). 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.

Table 5: R2, R2 adjusted and Q2 Stone-Geisser values for predictive relevance

Construct R Square R Square Adjusted Q2
Overall satisfaction 0.456 0.450 0.333
Repurchase intent 0.424 0.418 0.311
Relationship quality 0.330 0.326 0.325

Findings of the partial least squares modelling analysis suggest that all paths’ standardized coefficients predicting the endogenous constructs of satisfaction and repurchase intent are significant (p<0.01) (Figure 2).

tourism-hospitality-analysis

Figure 2: Results of the Partial Least Squares Modelling (PLS) analysis.

Results and Discussion

Background data

Table 6 includes the mean values and standard deviations for all customer-centric constructs and their indicator variables. Table 7 includes the mean values and standard deviations for the respondents with the three marital status categories as well as significant differences between the categories.

Table 6: Mean values and standard deviations of collapsed constructs and their indicator variables in the sample population*).

Construct Variable Mean value Standard deviation Mean value for the collapsed construct Standard deviation
Overall satisfaction Satisfaction 4.38 0.95 4.01 0.61
Met expectations 3.65 0.84
Overall repurchase intent Repurchase intent 4.20 0.95 4.30 0.71
Willingness to recommend 4.41 0.65
Value for money Value for money 3.66 1.00 3.66 1.00
Relationship quality Relationship quality 3.84 0.91 3.84 0.91
Service quality - skiing Capacity of ski lifts 4.23 0.61 4.31 0.48
Length of ski slopes 4.35 0.59
No. of slopes 4.35 0.65
Speed of ski lifts 4.29 0.71
Variety, length and quality of slopes 4.32 0.66

Table 7: Significant differences in mean values and standard deviations of the customer centric measures on the basis of the marital status.

Construct Singles Partnership with no children Partnership couples with children  Significance
Customer satisfaction 3.87 (0.69) 3.93 (0.56) 4.14 (0.59) *
Repurchase intent 4.07 (0.81) 4.15 (0.71) 4.52 (0.57) ***
Value for money 3.42 (0.95) 3.43 (0.96) 3.92 (0.99) **
Relationship quality 3.72 (1.02) 3.67 (0.89) 4.02 (0.84) *
Service quality - skiing 4.31 (0.47) 4.20 (0.49) 4.38 (0.46) n.s.

The results in Table 6 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 mean values. The lowest ratings were received by the overall performance (met expectations) and value for money variables.

Impact of marital status groups on the customer centric measures

Regarding the differences between the three marital status groups, it is apparent that the ski resort visitors living in a partnership with children had the highest ratings in all customer-centric measures. These differences were significant except for service quality skiing. Therefore, hypotheses one through four are supported and hypothesis five is rejected. Further analysis revealed that there were no significant differences in any of the customer-centric measures between singles and respondents living in a partnership without children.

The findings may be caused by the importance of the emotional satisfaction for families living with children where memories, content, and rejoice play an important role as families prioritize their health, family and the natural environment [64]. 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 and thus psychological factors play an important role in the assessment of satisfaction [64]. With regard to the high repurchase intentions, customers visiting the same resort again are a great asset for a ski resort, which is especially true in the case of visitors living in a partnership with children [12].

These results are interesting as there appears to be a divergence with the findings of the Mittal & Kamakura (2001) study, which stated that marital status revealed no significant differences with regard to customer satisfaction and repurchase intent [11]. 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) [65]. The findings by Mittal and Kamakura may be explained by the different context of the study (automotive) as automobiles are a significant purchase regardless of marital status. Skiing as a service may be perceived quite differently by different kinds of customers. 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 interesting as skiing is a comparatively high-priced leisure activity especially if the whole family is involved. This may be due to the fact that people living in partnership with children may be financially better off than others, and for that reason, the value for money considerations are not considered to be as important [37]. 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 better value for money.

The willingness to recommend responses were also significantly higher for the respondents living in partnership with children. This shows the higher emotional elevation and feelings of the respondents for their children [66]. 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 [64]. 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/or exceeds their expectations, then they will definitely recommend the service due to the inherent difficulty in finding places that are “kid-friendly” and “appropriate”.

With regard to 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 and have different expectations [64]. 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 ratings in their responses in terms of the relationship quality as the ski resort operators tend to cater to their needs with better service quality as they require more attention, which requires more interaction with the ski resort operator.

Finally, in terms of the skiing service quality, there were no significant differences between the three marital status categories. 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 for children and adults alike. In conclusion, the results in terms of the differences for the customer-centric measures indicate that demographics play an important role in detecting behavioural and attitudinal differences in the ski resort marketplace and thus may have implications for the service quality offerings as well as for the segmenting of the ski resort market.

Results and discussion on the importance-performance analysis

To complement the analysis and discussion above, an importanceperformance analysis was conducted with the Partial Least Squares Structural Equation Modelling (PLS-SEM). The target construct in the analysis was repurchase intentions. The importanceperformance analysis was 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 8 and Figure 3.

Table 8: Results of the importance-performance analysis at the construct level for the different marital status classes.

Marital status Item Importance Performance Action
All respondents Satisfaction (SAT) 0.577 72.617 Keep up
Relationship quality (RQ) 0.368 62.189 Do better
Service quality skiing 0.278 80.817 Education
Value for money (VM) 0.171 66.418 No change
Singles (REL 1) Satisfaction (SAT) 0.533 71.726 Keep up
Relationship quality (RQ) 0.430 57.447 Do better
Service quality skiing 0.294 80.875 Education
Value for money (VM) 0.087 60.638 No change
Partnership without children (REL 2) Satisfaction (SAT) 0.480 68.234 Do better
Relationship quality (RQ) 0.312 55.556 No change
Service quality skiing 0.212 77.351 Education
Value for money (VM) 0.164 60.965 No change
Partnership with children (REL 3) Satisfaction (SAT) 0.599 75.855 Keep up
Relationship quality (RQ) 0.332 67.424 No change
Service quality skiing 0.309 82.372 Education
Value for money (VM) 0.138 73.011 No change
Average 0.349 70.510  
tourism-hospitality-partnership

Figure 3: Importance-performance map (IPMA) at the construct level for the various marital status classes. Note: (REL1=Singles. REL2=Respondents living in partnership without children and REL3=Respondents living in partnership with children).

Importance performance analysis at the construct level

The importance-performance maps (Figures 3 and 4) for the constructs and indicators contain four managerial recommendation sections of “Keep up”, “Do better” ,“Education”, and “No change”on the basis of the mean values of the constructs for importance and performance in the study [67-69]. The shortcuts in Figure 3 are “ALL” for all respondents, REL 1 for singles, REL 2 for respondents living in partnership without children and REL 3 for respondents living in partnership with children.

tourism-hospitality-children

Figure 4: Importance-performance map (IPMA) at the service quality skiing indicator level. Note: (REL1=Singles. REL2=Respondents living in partnership without children and REL3=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. It is evident that all marital status groups appear to be in the same general region in 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 0-100. 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 6. 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 6) about the high responses for the value for money construct by the respondents living in partnership with children appears to hold in the importance-performance map as well. Again, this may due to the fact that they are able to purchase family packages or the prices for children and youth are lower than for adults, which tend to offer better perceived value for money for that group.

It is clear that the three marital status groups do not share the same views in terms of the importance of the customer-centric constructs. For example, the perceptions of the respondents living in a partnership with children appear to see the importance of satisfaction to be far higher than the other marital status groups. Also, the importance of the relationship quality construct for the singles appears to be 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, which may 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 also feeling like the best possible value for money is not being offered.

Importance-performance analysis at the indicator level

The results in Table 8 and Figure 3 are interesting for the constructs as they reveal and confirm that there are differences between the marital status groups at the latent construct level. Smart-PLS software, however, also enables the assessment of the importance and performance of the ski resort at the indicator variable level, which creates more managerially relevant and actionable results. In this paper, the indicator level assessment will be done for the five reflective indicators of the service quality skiing construct including 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 9 and Figure 4.

Table 9: The results of the importance-performance analysis at the indicator level in the whole data set and for the three marital status classes.

Marital status Item Importance Performance Action
All respondents Capacity of ski lifts 0.055 74.793 No change
Length of ski slopes 0.081 78.441 Do better
No. of slopes 0.086 83.831 Keep up
Speed of ski lifts 0.055 82.463 Education
Variety, length and quality of slopes 0.090 83.333 Keep up
Singles (REL 1) Capacity of ski lifts 0.061 75.887 No change
Length of ski slopes 0.094 79.433 Do better
No. of slopes 0.102 82.979 Keep up
Speed of ski lifts 0.050 81.915 Education
Variety, length and quality of slopes 0.110 82.447 Keep up
Partnership without children (REL 2) Capacity of ski lifts 0.053 71.930 No change
Length of ski slopes 0.056 75.439 No change
No. of slopes 0.056 80.263 No change
Speed of ski lifts 0.051 78.509 No change
Variety, length and quality of slopes 0.060 81.140 Education
Partnership with children (REL 3) Capacity of ski lifts 0.057 75.000 No change
Length of ski slopes 0.086 79.924 Do better
No. of slopes 0.095 86.364 Keep up
Speed of ski lifts 0.058 84.943 Education
Variety, length and quality of slopes 0.096 84.375 Keep up
Average (All respondents) 0.078 82.121  

When looking at the overall performance scores at the indicator level, it is clear that there is room for improvement as the performance scale is from 0-100. The result in Table 9 and Figure 4 are rather interesting as they indicate pretty large differences between the marital status groups in terms of the perceived importance and performance of the skiing service 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 respondents 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 lower 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, appears to be quite similar for the marital status groups.

Implications

This research discusses the impact of the demographic variable, marital status, on the customer-centric measures in a ski resort. These customer-centric measures are customer satisfaction, repurchase intent, value for money, willingness to recommend, overall performance in terms of meeting expectations, relationship quality, and service quality skiing. As significant differences emerged between the respondents living in partnership with children and others, the importance of tailoring products and services for different demographics at a ski resort appears to be warranted.

In order to improve the ratings for the customer-centric measures, a 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 the ski resort in many ways. Customercentric measures are of prime concern for any company, but it is clear that the various types of visitors to a ski resort appreciate these measures in different ways. On the basis of the findings in this research, 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.

Limitations

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 have an impact as well. Also, the study was conducted in British Columbia. Canada and therefore adding other geographical regions to the study might be interesting as far the generalizability of the findings is concerned.

Conclusions

This study examined the impact of the demographic variable, marital status, on the customer-centric measures in the context of a ski resort. Also, the importance and performance of the customercentric measures were investigated at the latent construct level as well as at the more specific and actionable indicator level. The results indicate that marital status indeed has an impact on the assessment of the customer-centric measures as four out of the five customer-centric 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 the 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, this means that they should offer a skiing experience more tailored to the marital status of the ski resort visitors.

References

Author Info

Matti Haverila1*, Kai Haverila2 and Jenny Twyford3
 
1School of Business and Economics, Thompson Rivers University, Canada
2John Molson School of Business, Concordia University, Canada
3School of Business, University of Manchester, UK
 

Citation: Haverila T, Haverila K, Twyford J (2020) Impact of marital status on customer-centric measures in ski resorts using the importance-performance (IPMA) framework. J Tourism Hospit 9:430. doi: 10.35248/2167-0269.20.9.430

Received Date: Mar 18, 2020 / Accepted Date: May 04, 2020 / Published Date: May 11, 2020

Copyright: © Haverila T, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

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