How to create attractive and unique customer experiences

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How to create attractive and unique customer experiences An application of Kano’s theory of attractive quality to recreational tourism Claes Ho¨gstro¨m, Marina Rosner and Anders Gustafsson Service Research Center, Karlstad University, Karlstad, Sweden

Customer experiences

385 Received June 2009 Revised September 2009, October 2009 Accepted November 2009

Abstract Purpose – The aim of this paper is to understand the differences across various quality dimensions and how these contribute to experienced quality and satisfaction among users. Design/methodology/approach – The study applies the Kano model of attractive quality to a destination (in this case a snowpark). The fact that the Kano model was used means that a quantitative approach was applied. In total 270 respondents responded to the survey instrument, which in turn was based on qualitative interviews. Findings – The research shows the great importance of a destination that offers conditions that support specific goals or desired activities in order to achieve customer satisfaction. It also finds that the physical service environment has a major influence on customer satisfaction. Finally, the physical conditions seem to affect the destination’s image to a greater degree than the interactions. Practical implications – In order to create the most attractive offering, managers should focus primarily on the physical service environment. Originality/value – The Kano model is widely discussed and well known. There are, however, very few applications for which the Kano model has been used, especially with regard to hedonistic services, the motivation for this study. The theoretical contribution of this paper is an extension of Brady and Cronin’s model of what creates service quality. In this model, the location or place is added as an important construct for explaining the experience. Keywords Customer satisfaction, Tourism, Quality, Leisure activities, Norway Paper type Research paper

Introduction Increased demand for experiences has driven the development and growth of what is referred to as the experience economy (Richards, 2001). This has resulted in production and economy shifting its focus from manufacturing goods towards delivering services and offering experiences (Pine and Gilmore, 1998; Vargo and Lusch, 2004), which has probably always been the case for hedonistic services such as snowparks. Furthermore, there is a belief today that merely having satisfied customers is not enough; a higher degree of satisfaction is needed in order to create strong loyalty (Lilja and Wiklund, 2006). This gives relevance to a study of attractive quality from an experience perspective. One interesting question is the manner in which improvements or modifications of the conditions for creating experiences contribute to enhanced customer satisfaction. The aim of this study is to understand the differences across different quality dimensions and how these contribute to experienced quality and satisfaction among users. In other words, how do different dimensions of customer experience satisfy customers? This can help a firm to focus on the right dimensions of a hedonistic product in order to increase

Marketing Intelligence & Planning Vol. 28 No. 4, 2010 pp. 385-402 q Emerald Group Publishing Limited 0263-4503 DOI 10.1108/02634501011053531

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its competitiveness. This study uses Kano’s theory of attractive quality, the origins of which are similar to the two-factor theory of customer satisfaction (Oliver, 1997). The latter theory suggests that customer satisfaction is influenced by three attribute types: bivalent satisfiers, monovalent dissatisfiers, and monovalent satisfiers. The Kano model can be viewed as an operationalization of the two factor theory of customer satisfaction. Decision models are used to understand customer rational when making choices (Gigerenzer, 2000). The approach to understand customers in this research is to deconstruct customer satisfaction into components in order to understand “the whole” and how it is achieved (Meyer and Schwager, 2007). The Kano model enables the investigation of what parts of an offering affect customer satisfaction and the roles that they play in a customer’s perception of quality (Lo¨fgren and Witell, 2007). The theoretical contribution of this work is an extension of Brady and Cronin’s (2001) model of what creates service quality, in which the location or place is an important construct for explaining the experience. The managerial contribution of this study is that it creates a greater understanding of user preferences and how these can be used to guide the development of future destination products. From service to experience Like other players in the tourism industry, snowparks must respond to customer demand by offering services and physical characteristics that create experiences for their visitors. In other words, they must create conditions for the differentiation of service experiences, with each customer having the opportunity to create an experience that best fits their individual need. This is done by combining the results of the various processes that the producer has prepared (Fache´, 2000). The firm creates the platforms upon which the customers can co-create their own services. Both the quality of the experience and the experience itself are created through different dimensions or processes of the offering. Stamboulis and Skayannis (2003) offer a way of looking at how value is created in the experience-oriented hospitality industry, as opposed to traditional services. They argue that, when creating experiences, the roles of infrastructure, context and content change in comparison to services. In terms of experiences, infrastructure consists not only of technical and organizational solutions, but also of elements that contribute to and activate the experiences, such as food and logistics. In order to create actionable research for managers, this study only examines the parts of the infrastructure that can be explicitly influenced by the producers of the offering such as ski lifts (Flagestad and Hope, 2001) and will not include infrastructure or services that are not controlled by the producer of the core offering affect customers such as public transportation or local restaurants. The context consists of location-related factors and services that provide consumers access to possible experiences. In the service-oriented view, place acts as a setting only, while the service or experience itself creates both the content and value (Vargo and Lusch, 2004). In the experience-oriented industry, however, place and service both play an important role in creating the right conditions for experiences. They both become part of the context with which visitors interact in order to create content (in other words, the actual experience) with a destination-specific value. Experiential quality dimensions According to a model created by Brady and Cronin (2001), three main dimensions influence the quality of a service, as shown in Figure 1. These are: interaction,

Customer experiences

Experience (destination specific)

Place Attachment

Place identity/ image

Interaction quality

Attitude

Behavior

Expertise

387 Service quality

Place dependence

Physical environment quality

Ambient conditions

Design

Outcome quality

Social factors

Waiting time

Tangibles

Valence

the physical environment in which the service is produced, and how customer expectations are met by the service result. All three dimensions are, in turn, influenced by a series of underlying dimensions or attributes. The latter serve as indicators on the dimensions those are concrete and measurable. The suitability of this model and its design is supported by Edvardsson (1998), who argues that the service result is created through a process in which the customer’s participation as a co-producer influences the value and quality of the service along with the conditions provided by the service provider. This approach is similar to Stamboulis and Skayannis’ (2003) view of how experiences are created from interaction with the image that consumers have of the offer, and the conditions that the offer actually provides. Accordingly, the Brady and Cronin model is suitable as the basis for a study in the context of a snowpark because it takes both services and location into account, a factor that was also shown in an earlier study by Alexandris et al. (2006). The model has also proved useful as the starting point for a number of other tourism studies (Caro and Garcia, 2007; Ko and Pastore, 2005). The interaction dimension focuses on the ways in which services are delivered. Brady and Cronin (2001) argue that the quality of the interaction between the service provider and the customer is based on the attitude, behavior and skills that the customer encounters in their interactions with the service provider. According to Edvardsson (1998), important quality factors include the credibility and reliability of the service provider to deliver what is requested. Edvardsson also emphasizes the importance of staff showing empathy and a genuine interest in the customer. The physical environment in which services are delivered is perhaps the most crucial for the success of a resort or destination (Hudson, 2003). This part of the service is tangible for the customer and directly comparable to competing facilities (Flagestad and Hope, 2001), making it an important indicator of the company’s capacity to deliver

Figure 1. A hierarchical model of how destination specific experiences are created

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what they have promised (Edvardsson, 1998; Brady and Cronin, 2001). The physical environment influences the perception of quality in a resort’s offerings (Edvardsson, 1998; Ko and Pastore, 2005; Brady and Cronin, 2001). Brady and Cronin (2001) argue that the quality of the physical service environment is affected by ambient conditions, such as the atmosphere created, the design of facilities (functionalism, aesthetic value, etc.), and social factors (visibility of staff, other customers, group size, who the customers are and how they behave, etc.). The outcome dimension focuses on the actual outflow of the service process. Brady and Cronin (2001) link this dimension to valence, or the fulfillment of customer demand, waiting time, and tangible factors, all of which are regarded as important factors that affect the perception of quality. The importance of valence is supported by Edvardsson (1998), who says that when customers do not receive what they have demanded, they become more aware of what they have received. Edvardsson argues that the management of critical incidents and customer complaints is of great importance if a company wishes to create a strong relationship with its customers and enhance its customers’ perception of quality. Interaction and the physical service environment have been shown to have a high impact on the kind of attachment that customers have to a ski facility (Alexandris et al., 2006). According to Faullant et al. (2008), customer satisfaction is important but, in itself, not sufficient to create loyalty. The present study emphasizes the fact that the way in which the resort’s image is perceived by different groups of satisfied customers affects the level of loyalty. Brand and image is increasingly important for tourism producers, particularly in the case of services in which the potential for differentiation has already been exploited and in which the various players in the market have similar offers. In such cases, image might be the only factor that cannot be imitated (Faullant et al., 2008). Place attachment is a new element in Brady and Cronin’s (2001) model. According to Williams and Vaske (2003), place attachment is dependent on both place identity and place dependence and refers to the emotional and symbolic relationship that individuals form with recreational resources. Place dependence is a functional relation that reflects the importance of a location offering conditions that support specific goals or desired activities; it is mainly influenced by the physical service environment. Place identity, on the other hand, relates to the symbolic value of a location as a source for feelings and relationships, which may affect an individual’s sense of belonging and is mainly influenced by the interaction dimensions of the offering. The outcome quality dimension of the service mainly pertains to how customers regard the activity itself. This dimension has been shown to only have a minor impact on the attachment that a customer develops towards a certain place. The physical environment and interaction dimensions, meanwhile, contribute significantly to place attachment through both place identity and place dependence. The interaction dimension is the strongest predictor of place identity, while the physical environment dimension is the strongest predictor of place dependence, although both dimensions contribute significantly to both place identity and place dependence (Alexandris et al., 2006). In other words, the quality of the physical service environment and the interaction during the service production should have a direct impact on a snowpark’s brand and image as well as the customer’s willingness to revisit the destination, due to the emotional and symbolic relationship that customers form with the destination.

The model shown in Figure 1, which has been developed and used in this study, is based on the theories outlined above and has not been previously empirically tested. It shows how an experience is created through Brady and Cronin’s (2001) service dimensions and how that experience depends on conditions that support the desired activities in order to achieve satisfaction among customers. The model also shows how the service dimensions contribute to the creation of an attachment or relationship between the customer and the destination at which the services are performed (Williams and Vaske, 2003; Alexandris et al, 2006). Finally, the model also shows how place attachment, or the relationship that customers create with the resort, affects customer experiences, along with the quality of service, enabling customers to create unique experiences for the destination. The model captures both the context and content of the experience (Stamboulis and Skayannis, 2003) but also highlights the importance of both satisfaction and image (Faullant et al., 2008) in achieving quality. The theory of attractive quality Kano et al. (1984) developed a model that uses specific quality attributes and degrees of achievement to evaluate various patterns of quality based on customer satisfaction. A quality attribute is classified into different categories based on the relationship between the fulfillment of a particular quality attribute and the perceived satisfaction of that attribute. Kano’s theory of attractive quality has often been used in product and service development processes to investigate how various quality attributes affect the level of customer satisfaction and the roles that they play in a customer’s perception of quality (Lo¨fgren and Witell, 2007). Kano et al. (1984) used five categories – “attractive quality,” “one-dimensional quality,” “must-be quality,” “indifferent quality,” and “reverse quality” – in order to categorize the relationship between the degree of achievement and customer satisfaction of quality attributes (Figure 2). In each of these categories the absence of quality attributes categorized as “attractive” does not necessarily lead to dissatisfied customers, but their presence does create satisfaction. These attributes are not expected, so they create enthusiasm because they surpass customers’ expectations regarding the product or service. Customers are satisfied by the achievement of attributes that are classified as “one-dimensional,” but become dissatisfied if they are not achieved. The higher the degree of achievement, the more satisfied the customer will become. According to Shahin (2003) the attributes categorized as one-dimensional can be referred to as “more is better,” “faster is better,” or “easier is better,” depending on the situation. Meeting the attributes classified as “must-be” does not necessarily lead to satisfied customers, but customers do become dissatisfied if they are not met. According to Newcomb and Lee (1997), these attributes are demands that products or services must meet. “Indifferent” quality attributes do not contribute to satisfied or dissatisfied customers, regardless of whether they are achieved. “Reverse quality” attributes result in dissatisfaction among customers if they are achieved and in satisfaction if they are not. Methodology Context Over the last century, the winter sports industry has undergone remarkable growth and is one of the fastest growing tourism sectors in the world (Jafari, 2000).

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Customer satisfaction Very satisfied Attractive One-dimensional

390

Indifferent Not at all

Fully Must-be

Degree of achievement

Reverse

Figure 2. An overview of the theory of attractive quality

Very dissatisfied Source: Gustaffson (1996)

Furthermore, winter sports destinations, as an industry, have shown signs of maturing to the point where the combination of market stagnation and increased capacity creates a competitive challenge for all destinations within the industry (Flagestad and Hope, 2001). Winter sport destinations are what Weaver and Lawton (2002) refer to as “special recreational attractions” (SRAs), that is, attractions created specifically to meet a demand from the tourism and leisure market. Winter sport destinations distinguish themselves somewhat from this group because they require specific environments, something that SRAs usually do not. This combination of a maturing marketand resource-based industry with increased competition makes it an interesting context for the purposes of the present study. Snowparks were also chosen for the study because they are tailor-made facilities designed to create a more attractive environment, primarily for snowboarders and twin-tip skiers, within winter sport destinations (Hudson, 2000). As such, they can be regarded as a scaled down version of the attraction – the winter experience – as a whole. All the snowparks that were included in the study were based in Norway. Pre-study A total of 30 individual interviews were conducted in order to achieve a greater understanding of the expectations that customers have regarding snowparks and the needs that they wish to fulfill in their choice of snowpark, based on their perceptions and experiences. An interview guide was used to identify product attributes based on the four questions listed below, each of which have been tested and used in previous Kano studies (Matzler et al., 1996). The questions were re-worded as follows in order to make a direct connection to the offering being examined:

(1) What associations does the customer make when using product x? (2) What problems/defects/complaints does the customer associate with the use of product x? (3) What criteria does the customer take into consideration when buying product x? (4) What new features or services would better meet the expectations of the customer? What would the customer change about product x? The answers to the first question assisted in the gathering of information concerning attitudes towards the product, its purpose and field of application. This question is, therefore, very useful for identifying attributes belonging to the outcome dimension. The other questions are more closely related to attributes of the physical environment or interaction dimension. The second question is designed to identify desires and problems that have so far gone undetected, while answers to the third question indicate the qualities that customers explicitly demand. Finally, the fourth question is useful for identifying desires and expectations that customers are aware of but which have not yet been fulfilled by the current product range on the market. Informants helped to identify the attributes by giving examples of features they referred to in their answers. When analyzing the interviews it was noted that 79 percent of the attributes found were identified after five user interviews and 90 percent after 15 interviews. No new attributes were found after the 25th interview. The attributes were divided into different dimensions based on the results of earlier studies (Flagestad and Hope, 2001). Ski products were classified into snow production, preparation, and general handling of snow. This made it possible to divide all attributes related to snow or handling of snow, such as staff competence in maintenance and opening dates, into ambient conditions of the physical environment dimension. Other groups in the ski product category are slopes and lifts (Flagestad and Hope, 2001). Consequently, attributes related to these groups can be classified as design features of the physical environment dimension. Attributes were classified into the interaction dimension based on the assumption that they are services in which customers interact with the destination in some way, such as face-to-face or through a web site to gather information. Information access and interaction with staff fell clearly into this dimension, while evening opening hours was categorized as an interaction attribute since it is a service that includes lift ticket sales and lift operation, etc. However, these are all hybrids of the underlying groups. Two attributes – social factors and other guests following the rules – could be regarded as hybrids. Both are social factors according to the Brady and Cronin (2001) model and can belong to the outcome and/or the physical environment dimension. The social factors attribute was eventually classified as an outcome attribute because it related to the first interview question and was clearly something that respondents wanted to be a result of the activity itself; it was seen as a way to associate with friends, even though it falls into the group of social factors. Other guests following the rules was something that respondents experienced as part of the surroundings rather than a specific goal of the activity itself, so this was connected to the physical environment dimension. Because the purpose of the study was to investigate active snowboarders, the sample was based on geographical spread, capacity, age, and gender. In order to increase the validity of the survey, the people chosen were those who snowboard regularly at different locations.

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Questionnaire The survey was divided into three parts: an introduction with an explanation of the survey’s purpose, background questions, and a Kano survey. The background questions, which relate to gender, age, frequency of visiting any destinations that offer snowparks, skill level, and the most visited ski resorts, were used in cases where clear answers could not be obtained from the Kano questions. These questions can be used to determine how different segments respond and whether there are any differences in individual or combined segment answers. The Kano survey consists of paired questions regarding customer needs. One form of question is functional and one is dysfunctional, and respondents can choose one of five alternatives, in accordance with Berger et al. (1993) and Kano’s et al. (1984) survey constructions. The functional form can be described as, “How do you feel if the product has quality X ?” and the dysfunctional form as, “How do you feel if the product does not have quality X ?” (Berger et al., 1993). The alternatives were translated into Norwegian and were tested on a heterogeneous population of 30 Norwegian respondents. By combining the answers from the functional and dysfunctional questions, the product attributes can be classified through interpretation and evaluation into six different categories. These are: “attractive,” “must-be,” “one-dimensional,” “indifferent,” “reversible,” and “questionable.” If the outcome of the evaluation is “questionable”, there is a contradiction in the respondent’s answer (Berger et al., 1993), which indicates that the respondent has misunderstood the question, that is, the question was wrongly formulated. In addition to the background questions and the Kano questions, respondents also used a scale of 1 to 10 to rate the importance of the individual product attributes, as well as the degree to which the destination they visit most frequently and the destination they believe has the best offering offers each of the attributes. This helps to weight and prioritize the attributes that are experienced as being the most important within a quality category (Matzler et al., 1996; Berger et al., 1993). Population and sample The survey was sent electronically to all members of the Norwegian Snowboard Association who were connected online and registered in the association’s e-mail register. A total of 270 responses were received, which represents 17.2 percent of the total number of persons (1,570) that received the survey. The member register of the Norwegian Snowboard Association made it possible to control the groups that responded to the survey and show the respondents’ commitment to snowboarding Table I. Analysis The first step in the evaluation process was to classify the product attributes according to the theory of attractive quality, which involved combining the answers from the functional and dysfunctional questions based on the evaluation table used by Lo¨fgren and Witell (2005) (Table II). Berger et al. (1993) and Newcomb and Lee (1997) note that there are alternative evaluation tables. According to Newcomb and Lee (1997) an attribute cannot be classified as “must-be” or “like” in the functional form while simultaneously being “must-be” or “like” in the dysfunctional form. They argue that cells 1-2, 2-1 and 2-2 should give the classification of “questionable,” while Berger et al. (1993) prefer cells 2-2 and 4-4 to give the “questionable” classification. In this study, therefore, a sensitivity

% Gender Male Female Age 0-15 years 16-20 years 21-25 years 26-30 years 30 þ years Skill Beginner Intermediate Advanced Frequency (visits/season) 1 time 2-5 times 6-15 times 15 þ times

Quality attribute Functional 1. Like 2. Must-be 3. Neutral 4. Live with 5. Dislike

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85.56 14.44 11.48 46.67 21.85 11.48 8.52

393

9.26 58.15 32.22 1.48 3.33 13.70 81.48

1. Like

2. Must-be

Q R R R R

A I I I R

Dysfunctional 3. Neutral A I I I R

4. Live with

5. Dislike

A I I I R

O M M M Q

Notes: A – attractive; O – one-dimensional; M – must-be; I – indifferent; R – reverse; Q – questionable Source: Adopted from Lo¨fgren and Witell (2005) Reprinted with permission from Quality Management Journal q 2005 American Society for Quality. No further distribution allowed without permission

analysis was conducted by comparing the evaluation result from the two tables; this analysis did not show any changes in the results. Overall, the value of Q was either 0 percent or less than 1 percent, which means that respondents have understood the questions and the results have a high degree of reliability. In the second step, the results from the evaluation and the questions regarding weight and rate of accomplishment were listed in a table that shows the average distribution for each attribute. The results were analyzed in the third and final step based on the frequency of answers and with help from various coefficients. The coefficients total strength (TS), category strength (CS), and better and worse were estimated based on the answers in the result table. TS is the sum, expressed as a percentage, of the “must-be,” “one-dimensional,” and “attractive” answers (M þ O þ A ¼ TS) and this indicates whether the attribute contributed to the creation of satisfaction or subjective quality.

Table I. Distribution of respondents based on gender, age, skills, and frequency

Table II. Kano evaluation table

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CS stands for CS and signifies the strength of the classification compared to the next strongest category. The differences were expressed as a percentage between the strongest and the second-strongest category of M, O, A, I, and R for one single attribute (Newcomb and Lee, 1997). If an attribute could be classified significantly according to one of the categories, Matzler’s et al. (1996) evaluation rule M . O . A . I became useful (Lo¨fgren and Witell, 2005). According to Lo¨fgren and Witell (2005), when two categories are equal, or close to one another for a single attribute, this may be due to differently marked segments and it signifies that more information is required. One way to handle this problem is to classify the attribute as a “combination” (Newcomb and Lee, 1997). Another important factor, according to Kano (2001), is that successful service attributes are dynamic. For example, an attribute may change over time from being “indifferent” to “attractive” to “one-dimensional,” and then finally become a “must-be quality” attribute. According to Nilsson-Witell and Fundin (2005), there is limited empirical evidence that the life cycle for successful service attributes is dynamic in the way that Kano (2001) suggested. They argue that successful service attributes introduced on the market need not be received with indifference by customers. In other words, the presence of attributes with two equally strong categories might imply that the attribute is changing from one category to another. The coefficients “better” and “worse” indicate the degree to which an attribute contributes to satisfaction or dissatisfaction by including it in the product or service (Berger et al., 1993). These coefficients show whether the fulfillment of an attribute contributes to satisfaction or merely prevents the customer from being dissatisfied. The maximum value for better or worse is 1, where 1 indicates a high impact on customer satisfaction and 0 indicates a minor impact (Matzler et al., 1996). Finally, the importance of each attribute was estimated and a QI value was calculated. The QI value was used to estimate how respondents perceived the quality of various offerings compared to the offering that is considered to be the best. A positive QI value indicates that a product is of higher quality than that of the competitors, while a negative value indicates the opposite. The QI signifies the position of a certain offering on the market in relation to its competitors, which is of great importance in the design of strategies and can also serve as a measure of improvement (Griffin and Hauser, 1993). The QI values used in this study were based on the formula, QI ¼ importance(evaluation of own product 2 evaluation on competitors product). In order to achieve comparable data for the offerings studied, a rating was used that measured the degree to which the producer was voted as having the best offering in this case. Trysilfjellet was chosen by 40.74 percent of respondents, offered each attribute as the “competitor product.” This data were then related to the degree to which each attribute was offered by the most frequently visited the destination that 0 percent of respondents felt had the best offering. A statistical t-test was also conducted in order to increase the reliability of the result. The test was used to compare the two highest classified quality categories according to the survey results for each quality attribute. Findings/result The results of the Kano survey are presented in the table in the Appendix. 14 out of a total of 21 attributes, were statistically significant and could be classified; in other words, a certain quality category was given to each of the 14 attributes. Eight of these 14 attributes

were attractive attributes, three were one-dimensional attributes and three were must-be attributes. Six of the attributes that could not be classified belonged to the physical service environment dimension, while one belonged to the outcome dimension; these were classified as combinations. The reason for most of the combinations seemed to be that the attributes are dynamic, moving from indifferent to must-be through the attractive and one-dimensional categories. No attributes were found as being directly classified as one-dimensional. One explanation for this may be that the attributes of this dimension move quickly from attractive to must-be. The study also showed that this development was primarily driven by users with higher frequency and skill. Combinations can therefore also be explained, to varying degrees, by differences in gender, skill, frequency and age. More research is required in order to confirm whether the attributes are changing or if it only is a matter of differences between segments.

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Quality dimensions of a winter sport destination’s snowpark offering A “better-worse chart” was used in order to draw conclusions about how Brady and Cronin’s (2001) varying quality dimensions contribute to the performance of various resorts (Figure 3). In this chart the value of “worse” indicates the degree to which an attribute can contribute to dissatisfaction, while the value of “better” indicates the degree to which the same attribute contributes to satisfaction. How the outcome dimension affects customers’ choice of destination The attributes of the outcome dimension are all found in the one-dimensional section of Figure 3, except for one, which was classified as a combination. This combination could not be explained by differences between segments and it therefore seems as though it is moving from attractive to one-dimensional. This indicates that customers 1.0

Attractive

One-dimensional

Outcome

Interaction

0.5 Interaction Environmental Outcome

Physical environment

Indifferent 0

Must-be 0.5 Worse

1.0

Figure 3. Overview of the attributes and dimensions in a better-worse diagram

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choose sites at which they are given the best opportunities to get what they want from the activity in which they partake. Destinations are evaluated directly against each other and, in theory, respondents choose the facilities at which they believe the experiences can be created to the highest degree (Kano et al., 1984). In other words, customers seem to be loyal as long as no other facility is offering a product that they believe provides better conditions for the experience they seek. This is supported by the theory of place attachment (Alexandris et al., 2006). The results of the present study suggest that the choice of destination is made based on its physical appearance. The influence of physical environment and interaction dimensions on the choice of destination Attributes in the physical service environment are attractive, one-dimensional and must-be. In other words, it is difficult to say that there is a clear tendency for this dimension to contribute to satisfaction or dissatisfaction. However, it is only in this dimension that attributes classified as must-be are found. Of these attributes, two were design aspects (the presence of jumps and rails in the snowpark), while the third was a social element (that other visitors follow the rules). This is logical because these attributes were often highlighted in relation to product-related problems that users experienced in the pre-study. Attributes classified as attractive in this dimension were generally found among the answers to the pre-study questions related to the criteria that customers value in their choice of offering and what they lack, which also is logical in relation to their classification. There is a tendency within this dimension for no attribute to be categorized, with any statistical significance, as one-dimensional. These attributes are, instead, either combinations of one-dimensional and must-be or of one-dimensional and attractive. There are also some combinations of must-be and attractive. Within this dimension, however, the strongest degree of displeasure occurs if one or some of the attributes are not met. This is in line with the theory that place dependence reflects the conditions to specific targets or desired activities that a resorts offers, which in turn gives guests an idea of what the destination offers them and thus affects its image. Interaction attributes can, according to the better-worse diagram, be seen as creators of attractive quality, although one point (the “interaction with staff, possibilities to impinge the offering” attribute) falls within the one-dimensional area. Apart from this, the reason for the popularity of this quality dimension is that it contributes strongly to satisfaction – the higher the achievement of attractive attributes, the more satisfied the guests will be (Shahin, 2003) – but the absence of attractive attributes does not contribute to dissatisfaction to any significant degree. This means that resorts can use factors within this dimension to create unique competitive advantages. Importance and QI Attributes classified as attractive are the least important, while those classified as one-dimensional, must-be or a combination thereof are considered to be the most important. These results agree with Matzler’s et al. (1996) evaluation rule, M . O . A . I, only in that attributes classified as must-be and one-dimensional are more important than those classified as attractive. Significantly, the attribute identified as being the most important is “Feelings of relaxation and freedom”, which is categorized as one-dimensional and had quite a high CS value of 31.15 percent. Although this contradicts Matzler’s et al. (1996) evaluation rule, the pattern can

be explained by the fact that these attributes belong to the outcome quality dimension. As outcome quality attributes they are fundamental reasons to go snowboarding in a snowpark more than they are related to the actual choice of a certain resort. In other words, the more that snowboarding contributes to the feelings of relaxation, freedom, challenge and development, the more likely it is that the respondent will perform the activity again. If the attributes that belong to the outcome quality dimension are ignored, the importance ranking of attributes falls more in line with Matzler’s et al. (1996) evaluation rule. It is also logical to ignore these because they only have a weak connection to place attachment (Alexandris et al., 2006) and show what users want from the activity itself. The factors to which resort customers create a strong attachment are more dependent on the physical service environment and the interaction dimensions. When the three attributes of the outcome dimension are ignored, three of the five most important attributes are categorized as must-be and two as a combination of must-be and one-dimensional (Table III). This slight deviation from Matzler’s et al. (1996) evaluation rule can be explained by Kano’s (2001) theory that attributes are dynamic. In other words, attributes moving from one-dimensional to must-be might have the same weighting as statistically significant must-be attributes. If only the importance of statistically significant classified attributes is observed, their ranking will closely match the M . O . A . I evaluation rule. The exception to this is an attribute belonging to the interaction dimension, as long as the attributes belonging to the outcome quality dimension are ignored. In other words, the importance ranking seems to be logical in terms of how attributes (apart from the exception mentioned above) are categorized for the statistically significant attributes within the interaction and physical service environment dimensions. A comparison of the QI values in Table III helps explain why a certain destination was voted as having the best offering and why this destination was the most visited. The best destination’s offering profile outperforms the most visited of the worst destinations on all attributes except one. There is also a larger difference in QI values for attributes belonging to the physical environment dimension than the interaction dimension in general. The largest difference, however, is represented by the attribute named “challenge and development of skills,” which belongs to the outcome dimension. A logical explanation for this is that a better-suited physical environment offers the respondents better prerequisites for a particular desired outcome. Another observation is that, in general, there is less difference in QI values among attributes classified as attractive than in attributes with a higher classification. This indicates that offering profiles that fulfill attributes with significant must-be or one-dimensional classifications, or combinations that include one of those two classifications to a high degree, creates a stronger attachment. This supports the use of Kano’s theory of attractive quality and results in revisits and highly favorable reviews among customers, according to this study, since the same destination was voted as having the best offering and was, simultaneously, the destination that most customers visited on a regular basis. The influence of the dimensions on the destination-specific experience through place attachment and service quality As with Williams and Vaske (2003), the present study highlights the great importance of a destination offering conditions that support specific goals or desired activities in order to achieve satisfied customers. The present study found that the physical service

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Table III. A comparison of attribute importance

Note: aAttributes categorized as combinations

Outcome Challenge and development of skills Feelings of relaxation and freedom Social factors Interaction Access to information Open during evenings Activities Interaction with staff, possibility of impinging the offering Physical service environment Skilled staff that maintain the product during opening hours Guaranteed opening dates Own lift Offering divided by level of difficulty Diversity of elements in different sizes Flow of riding and overview of the layout Preparation, shape of elements, safety of elements Jumps Rails Transition elements Halfpipe Varying layout Other guests follow rules Offering of other slopes 8.05 8.26 7.59 6.59 6.93 5.05 6.74 7.27 7.56 6.88 6.31 7.88 7.41 7.97 8.01 7.03 5.65 5.99 5.35 7.74 6.44

Attractive Attractive Attractive One-dimensional Must-be/attractive One-dimensional/must-be Attractive Attractive Must-be/one-dimensional One-dimensional/attractive One-dimensional/must-be Must-be Must-be Attractive Attractive Attractive Must-be Must-be/attractive

Importance

One-dimensional/attractive One-dimensional One-dimensional

Classification

2 0.16 5.23 6.64 1.43 5.75 3.21 3.89 3.44 5.23 3.77 2 1.19 4.14 2.08 2.58

1.69 3.65 2.08 5.73

2 1.89 0.83 6.02

QI Best destination

2 14.81 2 10.91 2 8.81 2 14.58 2 17.78 2 20.46 2 22.14 2 14.88 2 14.64 2 14.11 2 13.79 2 8.06 2 1.91 2 5.71

2 9.24 8.83 2 9.24 2 8.33

2 28.59 2 16.29 2 0.041

QI Least best destination

398

Attribute

MIP 28,4

environment had a major influence on this, as did Alexandris et al. (2006). The physical conditions offered also seemed to affect the destination’s image to a greater degree than the interaction attributes. Similarly, the interaction dimension did not seem to have the same degree of influence on the choice of resort as the physical environment. This is because the majority of the interaction attributes were classified as attractive. This agrees with Faullant’s et al. (2008) research, which showed that high image combined with high satisfaction creates maximum loyalty, while high image combined with low satisfaction does not create the same degree of loyalty as high satisfaction combined with a low image. Although an interaction criteria scored the highest importance to image, the criteria itself was related to the physical environment dimension and was followed mainly by factors related to the physical part of the offering. This study’s conclusion is, therefore, to question whether interaction has a greater influence on place identity in the case of resource-based winter tourism. It seems more important for image and identity that the physical offering itself is innovative and adapted to users, that there are offerings for a diverse range of users, and that the destination knows how to create and maintain the physical product. This also demonstrates that the service offered by the destinations is just part of the context and not the actual content of the experience, as stated by Stamboulis and Skayannis (2003). It seems as though customers choose the destinations that offer the best possible conditions for the activity in which they intend to partake. Management implications This study shows that managers should focus primarily on the physical service environment dimension in order to create the most attractive offering. This, based on Kano et al. (1984), along with the attractive attributes of that dimension and of the interaction dimension, would serve to create a unique offering and place attachment among users. This was also confirmed by the fact that Trysilfjellet was voted as the destination with the best offering profile since it had the highest QI values on a majority of the must-be and must-be/one-dimensional attributes of the physical environment dimension. It also outperformed the other competitors in the interactive dimension. Although managers should focus on the interaction and physical environment of the design, their offerings and processes must be created with the outcome in mind. The outcome attributes are the most important and if the other dimensions processes do not support or strive to fulfill the requested outcome to some degree, it is very likely that the offering will become obsolete. The Kano classification of the attributes advises managers about the order in which attributes in these dimensions should be prioritized so as to create attractive offering profiles that, in turn, will result in higher customer satisfaction. It can also make managers aware that attributes are dynamic and have different lifecycles that increase in importance over time. The present study also shows that there might be differences between segments, and that Kano’s theory of attractive quality, in combination with segmenting questions, can help managers detect those differences, thereby helping them to tailor their offers for their intended customers. Future research This study was focused on general attributes connected to snowparks. As these attributes were highlighted by active users of the offering more research is need on how individuals combine and use attributes offered by different destinations to create

Customer experiences

399

MIP 28,4

400

their experiences. Also, how experiences are co-created from an individuals perspective through the interaction with the attributes offered by the suppliers and if and then to what extent those services are co-produced with the snowpark. Another future research issue is if there are differences in Kano classification between frequently used snowparks and not so frequently used ditto, in other words to explore if there are any differences in preferences between users depending on what they regularly consume. This study has used a model that was designed for experience-based products but there is still a need for further empirical testing of it. For instance, on the relations between the original dimensions in the model and the new dimensions that has been added. There is also a need to test the model in different contexts. Finally, since parts of infrastructure such as surrounding offerings, i.e. public transport and restaurants, and access to the offerings was left out of the study; there is a need for further exploration on how this affects the attraction of offerings and also to what extent these phenomena might be classified according to Kano’s theory of attractive quality.

References Alexandris, K., Kouthouris, C. and Meligdis, A. (2006), “Increasing customer’s loyalty in a skiing resort: the contribution of place attachment and service quality”, International Journal of Contemporary Hospitality Management, Vol. 18 No. 5, pp. 414-25. Berger, C., Blauth, R., Boger, D., Bolster, C., Burchill, G., DuMouchel, W., Pouliot, F., Richter, R., Rubinoff, A., Shen, D., Timko, M. and Walden, D. (1993), “Kano’s methods for understanding customer-defined quality”, The Center for Quality Management Journal, Vol. 2 No. 4, pp. 1-37. Brady, K. and Cronin, J. Jr (2001), “Some new thoughts on conceptualizing perceived service quality: a hierarchical approach”, Journal of Marketing, Vol. 65, pp. 34-49. Caro, L.M. and Garcia, J.A.M. (2007), “Developing a multidimensional and hierarchical service quality model for the travel agency industry”, Tourism Management, Vol. 29, pp. 706-20. Edvardsson, B. (1998), “Service quality improvement”, Managing Service Quality, Vol. 8 No. 2, pp. 142-9. Fache´, W. (2000), “Methodologies for innovation and improvement of services in tourism”, Managing Service Quality, Vol. 10 No. 6, pp. 356-66. Faullant, R., Matzler, K. and Fu¨ller, J. (2008), “The impact of satisfaction and image on loyalty: the case of Alpine ski resorts”, Managing Service Quality, Vol. 18 No. 2, pp. 163-78. Flagestad, A. and Hope, C.A. (2001), “Strategic success in winter sports destinations: a sustainable value creation perspective”, Tourism Management, Vol. 22, pp. 445-61. Gigerenzer, G. (2000), Adaptive Thinking: Rationality in the Real World, Oxford University Press, New York, NY. Griffin, A. and Hauser, J.R. (1993), “The voice of the customer”, Marketing Science, Vol. 12 No. 1, pp. 1-27. Gustaffson, A. (1996), “Customer focused product development by conjoint analysis and QFD”, Dissertation No. 418, Linko¨ping University, Sweden. Hudson, S. (2000), Snow Business, Cassell, London. Hudson, S. (2003), Sport and Adventure Tourism, The Hayworth Press, New York, NY. Jafari, J. (Ed.) (2000), Encyclopedia of Tourism, Routledge, London.

Kano, N. (2001), “Life cycle and creation of attractive quality”, paper presented at the 4th International QMOD Conference Quality Management and Organization of Development, Linko¨pings Universitet Sweden, Linko¨ping. Kano, N., Seraku, N., Takahashi, F. and Tsuji, S. (1984), “Attractive quality and must-be quality”, Hintshitsu, Vol. 14 No. 2, pp. 147-56. Ko, Y.J. and Pastore, D.L. (2005), “A hierarchical model of service quality for the recreational sport industry”, Sport Marketing Quarterly, Vol. 14 No. 2, pp. 84-97. Lilja, J. and Wiklund, H. (2006), “Obstacles to the creation of attractive quality”, The TQM Magazine, Vol. 18 No. 1, pp. 55-66. Lo¨fgren, M. and Witell, L. (2005), “Kano’s theory of attractive quality and packaging”, QMJ, Vol. 12 No. 3, pp. 7-20. Lo¨fgren, M. and Witell, L. (2007), “Classification of quality attributes”, Managing Service Quality, Vol. 17 No. 1, pp. 54-73. Matzler, K., Hinterhuber, H.H., Bailom, F. and Sauerwein, E. (1996), “How to delight your customer”, Journal of Product & Brand Management, Vol. 5 No. 2, pp. 6-18. Meyer, C. and Schwager, A. (2007), “Understanding customer experience”, Harvard Business Review, February. Newcomb, J. and Lee, M. (1997), “Applying the Kano methodology to meet customer requirements: NASA’s microgravity science program”, QMJ, Vol. 4 No. 3, pp. 95-110. Nilsson-Witell, L. and Fundin, A. (2005), “Dynamics of service attributes: a test of Kano’s theory of attractive quality”, International Journal of Service Industry Management, Vol. 16 No. 2, pp. 152-68. Oliver, R.L. (1997), Satisfaction: A Behavioral Perspective on the Consumer, McGraw-Hill, New York, NY. Pine, J.B. II and Gilmore, J.H. (1998), “Welcome to the experience economy”, Harvard Business Review, July-August, pp. 97-105. Richards, G. (2001), “The experience industry and the creation of attraction”, Cultural Attractions and European Tourism, Cabi Publishing, Oxon. Shahin, A. (2003), “Integration of FMEA and the Kano model – an exploratory examination”, International Journal of Quality & Reliability Management, Vol. 21 No. 7, pp. 731-46. Stamboulis, Y. and Skayannis, P. (2003), “Innovation strategies and technology for experience-based tourism”, Tourism Management, Vol. 24, pp. 35-43. Vargo, S. and Lusch, R.F. (2004), “Evolving to a new dominant logic for marketing”, Journal of Marketing, Vol. 68 No. 1, pp. 1-17. Weaver, D.B. and Lawton, L. (2002), Tourism Management, 2nd ed., Wiley, Milton. Williams, D. and Vaske, J. (2003), “The measurement of place attachment: validity and generalizability of a psychometric approach”, Forest Science, Vol. 49, pp. 831-40.

Corresponding author Claes Ho¨gstro¨m can be contacted at: [email protected]

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Customer experiences

401

Table AI. 38.15/31.85 54.23 44.14 45.78 50.42 50.67 41.25 31.56/31.15 36.44/30.08 50.63 39.3 37.87/33.62 41.70/35.32 46.38/40.43 55.56 43.72 40.27 41.92 48.92 61.14 27.39/24.35

Attractive Attractive Attractive One-dimensional Must-be/attractive One-dimensional/must-be Attractive Attractive Must-be/one-dimensional One-dimensional/attractive One-dimensional/must-be Must-be Must-be Attractive Attractive Attractive Must-be Must-be/attractive

Agreement (%)

One-dimensional/attractive One-dimensional One-dimensional

Note: Result of Kano Study divided by the service quality dimensions

Outcome Challenge and development of skills Feelings of relaxation and freedom Social factors Interaction Access to information Open during evenings Activities Interaction with staff, possibility of impinging the offering Physical service environment Skilled staff who maintain the product during opening hours Guaranteed opening dates Own lift Offering divided by level of difficulty Diversity of elements in different sizes Flow of riding and overview of the layout Preparation, shape of elements, safety of elements Jumps Rails Transition elements Halfpipe Varying layout Other guests follow rules Offering of other slopes

Classification

88.98 89.96 66.3 90.21 94.89 93.62 89.74 81.82 68.58 79.04 67.53 93.01 74.78

86.48

85.54 93.22 70.22 88.3

87.04 93.08 87.50

TS (%)

6.36 27.62 20.0 4.26 6.38 5.96 26.07 17.32 9.29 19.21 21.65 31.88 3.04

0.41

18.07 21.19 22.67 12.50

6.3 31.15 17.58

CS (%)

0.60 0.75 0.70 0.53 0.77 0.54 0.35 0.39 0.60 0.65 0.67 0.32 0.48

0.57

0.75 0.80 0.67 0.71

0.71 0.78 0.72

Better

0.68 0.40 0.32 0.72 0.60 0.88 0.86 0.71 0.28 0.37 0.20 0.92 0.52

0.57

0.40 0.43 0.20 0.60

0.56 0.70 0.62

Worse

1.27 1.26 0.74 0.74 0 0.43 0 0.43 0.00 0.44 0.43 0.87 0.43

2.46

1.61 0.42 0.44 0.83

0.74 0.38 1.17

Q (%)

402

Attribute

i.s i.s p , 0.01 p , 0.01 i.s i.s i.s p , 0.01 p , 0.01 p , 0.05 p , 0.01 p , 0.01 p , 0.01 i.s

p , 0.01

p , 0.01 p , 0.01 p , 0.01

i.s p , 0.01 p , 0.01

t-test

MIP 28,4 Appendix