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A Revised Importance-Performance Analysis for Assessing Image: The Case of Cultural Tourism in Taiwan

Abstract

Destination image is critical to the success of any destination, particularly because of how it affects the level of satisfaction with the tourist experience. Importance-Performance Analysis (IPA) and its revision were selected for destination positioning analysis in this study. The first aim of this paper is to extend the traditional IPA approach and provides an option for destination positioning analysis. The measurement of image related to cultural tourism has received little attention in the tourism literature. Consequently, in this exploratory research, the first step is to conceptualize cultural tourism and determine the main attributes involved in its image measurement. Then, the scale developed was tested in an empirical manner. A questionnaire was used to examine the importance of 19 destination attributes for Taiwanese tourists who visited Taiwan’s cultural tourism attractions and to determine how they rated Taiwan’s performance with respect to these attributes post-visitation. This information was subsequently incorporated into the traditional and revised IPA grids. Then implications for destination positioning were provided by classifying the image attributes into factors so that the Taiwanese destination management organizations can make better decisions about how to improve the perceived image. The result confirms the importance of tangible and Taiwan-specific cultural assets, such as authentic sights, historic architecture, museums and galleries, literary and artistic sites, as well as Taiwanese customs and way of life. They can be pull factors for tourists looking to do something quintessentially Taiwanese. However, adequate resources have to be allocated to improve the welcome, gastronomy, as well as the expense of visiting Taiwan, not only because they are the major weaknesses but also because tourists regard them as prerequisites.

Moreover, attributes such as festivals/events and lively atmosphere can delight the tourists and strongly enhance overall satisfaction.

Keywords: destination image; destination positioning; cultural tourism; importance- performance analysis; three-factor theory

Introduction

Destination image is critical to the success of any destination, particularly because of how it affects the level of satisfaction with the tourist experience (O'Leary & Deegan, 2005). Tourism research into destination image (such as Baloglu & McCleary, 1999a; Beerli & Martín, 2004a, 2004b;

Chon, 1990) has also confirmed its importance for both marketing and the tourist decision making process. In fact, the influence of tourism image on the choice of holiday destination has been considered by various authors in consumer behaviour literature. Therefore, it is thought that destinations with stronger positive image will have a higher probability of being included and chosen in the process of decision making (Frías, Rodríguez, & Castañeda, 2008). A number of image studies have suggested effective destination positioning strategies to appeal to potential visitors, by either measuring existing images or the structure and formation dynamics of image (Choi, Lehto, &

Morrison, 2007). Several previous works have highlighted the importance-performance testing with respect to destinations or on the relationships between choice behaviours and loyalty to a destination (Joppe, Martín, & Waalen, 2001; Zhang & Chow, 2004; Chu & Choi, 2000). Importance- Performance Analysis (IPA) was therefore selected as a technique suitable for destination positioning analysis in this study. Although IPA is simple and intuitive, previous studies have demonstrated several shortcomings. The first objective of this paper is to extend the traditional IPA approach and provides an option for destination positioning analysis.

Furthermore, the study of cultural tourism image is an emerging field. Cultural tourism is now recognized as a mainstream tourism activity and a form of special interest tourism (McKercher, Ho, du Cros, & Chow, 2002). Knowledge of the cultural tourism market is still in its early stages, with much of the research still seeking to quantify the size of the market, or to describe how cultural tourists differ from other tourists (McKercher et al., 2002). According to Dolnicar (2002), among the 155 book and journal publications related to cultural tourism, 19% deal with cultural tourism or special kinds of cultural tourism (urban tourism, heritage tourism etc.) in a very general manner, 38%

are case studies describing and analyzing cultural tourism at one specific destination or attraction, 32% lay the main emphasis on contextual issues such as interaction with local culture and the social, economic and political effects of cultural tourism , 6% focus on managerial issues, both from the destination management and from the corporate perspective, and finally the remaining 5% centre around understanding and describing the group of cultural tourists. Not a single article could be found focusing on the measurement of the image of cultural tourism destination. This gap is filled by the study at hand in an empirical manner. The second objective is therefore to construct and measure the image of cultural tourism destination that has received relatively little attention in the tourism literature.

Since there is a lack of information about the characteristics of image related to cultural tourism, in this exploratory research, the first step is to conceptualize cultural tourism and determine the main attributes involved in the image of this type of destination. Then, the scale developed was tested in an empirical manner. A questionnaire was used to examine the importance of certain destination

attribute for Taiwanese tourists who visited Taiwan’s cultural tourism attractions and to determine how they rate Taiwan’s performance with respect to these attributes post-visitation. This information was subsequently incorporated into the traditional and revised IPA grids. Then some implications for destination positioning were provided by classifying the image attributes into factors so that the Taiwanese destination management organizations (DMOs) can make better decisions about how resources should be allocated to improve the perceived image. The paper is organized as follows:

First, it examines some recent literature and discusses the relevant theories, including the concept of cultural tourism and its features under the Taiwanese context, destination image and its measurement, as well as IPA and the three-factor theory of tourist satisfaction. Methodology, in terms of the data source and analytic approaches, is described in the third section. The results of the data analysis are presented in the fourth section, where a survey of Taiwanese tourists is presented focussing on the evaluation of selected image attributes of Taiwan. Finally, the paper concludes with the implications and future research suggestions.

Literature Review

Cultural tourism: definition and the Taiwanese context

The definitions suggested in literature to pin down the concept of cultural tourism are extremely diverse. Richards (1996) roughly groups all definitions in two broad categories: the ‘sites and monuments approach’ and the ‘conceptual approach’. The first point of view concentrates on the cultural attractions visited by tourists and thus makes measurement very easy. Sites include theatres, museums, historical sites, music and dance and similar points of attraction. The latter approach is more general and less directly measurable, with the main emphasis of the cultural tourist being to learn about the country they are visiting, especially the history, heritage and way of life. Cultural tourism is usually defined using an operational definition (i.e. the ‘sites and monuments approach’).

Based on the operational definition, cultural tourist can be defined as those who visit, or intend to visit, a cultural tourism attraction, art gallery, museum or historic site, attend a performance or festival, or participate in a wide range of other activities at any time during their trip, regardless of their main reason for travelling (McKercher, 2002; McKercher et al., 2002; McKercher & du Cros, 2003; Richards, 1996). This paper also adopts the operational definition in its methodology.

On the global stage, Taiwan has long enjoyed a dominant position in international tourism and the cultural industries (Mintel, 2008). More importantly, Taiwan tourism product is strongly associated with culture. For example, the heritage sector has been described as a major strength of the Taiwanese market for overseas visitors and is estimated to generate around 28% of all Taiwanese tourism expenditure annually (Mintel, 2008). Furthermore, Taiwan’s heritage and cultural offering is one of its key traits and selling points as well as a major potential growth area for tourism in Taiwan (Mintel, 2010). According to VisitTaiwan (the national tourist board in Taiwan), most tourist trips will touch a part of Taiwan’s culture or heritage and is the primary reason for taking a city trip. The country has a multifaceted range of cultural options, including museums and galleries as well as

historic buildings, especially those connected to royal heritage, which has strong associations with Taiwan (Mintel, 2008).

Destination image and its measurement

Destination image is important because of the role it plays in the potential tourist’s decision-making process. It is also significant because of how it affects the level of satisfaction with the tourist experience, which is critical in terms of encouraging positive word-of-mouth recommendations and return visits to the destination (Baloglu & McCleary, 1999; Beerli & Martín, 2004a, 2004b; O'Leary & Deegan, 2005; Royo-Vela, 2009). Analyzing destination image has become an important strand of tourism research. Therefore, several definitions of destination image have been reported. Although the definition of destination image is not so certain, it is widely accepted that destination image is an integral and influential part of the traveller’s decision process and consequently travel behaviours. It is also an internally accepted mental construct representing attributes and benefits sought of a product / destination (Choi et al., 2007; Pike & Ryan, 2004). One of the most comprehensive definitions is that put forward by Echtner and Ritchie (1991, 1993). They suggested that the destination image construct consists of three dimensions: attribute / holistic, functional / psychological, and common / unique. The most recent studies (such as Baloglu &

Brinberg, 1997; Baloglu & McCleary, 1999; Beerli & Martín, 2004a, 2004b; Gartner, 1993; MacKay

& Fesenmaier, 1997) tend to consider image as two closely interrelated concepts: perceptive / cognitive evaluations of their own knowledge and beliefs about the object and affective appraisals of their feelings towards the object.

Furthermore, the image of a destination is created through a combination of what is communicated by the destination and what is understood by the tourist. Therefore, destination image can be analyzed from two points of view. First, the projected image through the promotional activities of tourist destination bodies and tour operators as well as news and information about the destination derived from multiple sources; and second, the perceived image by the tourist, generated from the information received through word of mouth, and his/her experience at the destination (Andreu, Bigné, & Cooper, 2001). The projected image can be regarded as a ‘‘pull’’ factor in the destination decision process, which is transmitted by communication channels targeted at the potential tourists. In contrast to ‘‘pull’’ factors, ‘‘push’’ factors are considered as socio-psychological variables that predispose an individual to travel (Andreu et al., 2001; Baloglu & Uysal, 1996).

Various methodologies of measuring destination image have been developed over the past 30 years, most of which consist of either a structured, quantitative approach or, an unstructured, qualitative approach. Strong preference has been given to structured methods of image measurement when data were obtained as answers to closed-ended survey questions (Echtner & Ritchie, 1991, 1993; Pike, 2002). While structured methodologies have a number of advantages over qualitative methods, they focus on particular destination attributes and generally neglect the holistic, or overall, aspect of destination image. Qualitative studies, on the contrary, are advantageous to measuring the

holistic aspect, but do not facilitate statistical and comparative analyses of destination images (Jenkins, 1999). Therefore, several image literature claims using innovative and holistic approaches that combine both, quantitative and qualitative research. For instance, Echtner and Ritchie (1991, 1993) suggested that a combination of structured (such as Likert Scale or semantic differential associated with multivariate or bivariate statistical analysis) and unstructured (such as interview, focus group, open-ended survey questions, content analysis etc.) methodologies should be used to measure the complex nature of destination images. An operationalization of this concept is using a list of 35 attributes and three open-ended questions in order to capture the richness of the image.

Jenkins (1999) has also highlighted the importance of a preliminary phase of qualitative research to distil the constructs or attributes used by the study population in their cognition of destination image, followed by a quantitative phase of research to measure tourism destination image according to the relevant constructs. The combination of structured and unstructured are also becoming prevalent recently, such as the works of O'Leary and Deegan (2005) and Royo-Vela (2009).

IPA and its revision

Originally introduced by Martilla and James (1977), IPA is an easy-to-use method to identify which service attributes an organization should focus on. Based on IPA, survey data are utilized to construct a two-dimensional matrix. In this matrix, attribute importance is depicted along the x-axis and attribute performance is depicted along the y-axis. The average scores of performance and importance, commonly utilized in practice, and then divide the matrix into four quadrants. This analysis yields prescriptions for four strategies. Attributes in quadrant I, evaluated high in satisfaction and importance, represent opportunities for gaining or maintaining competitive advantages. In this area managers should ‘keep up the good work’. Attributes located in quadrant II are rated high in satisfaction but low in importance, implying that resources committed to these attributes would better be employed elsewhere (i.e. ‘possible overkills’). Quadrant III contains attributes both low in satisfaction and importance. Typically, it is not necessary to focus additional effort here (i.e. ‘low priority’). Finally, low satisfaction on highly important attributes demands immediate attention (quadrant IV: ‘concentrate here’).

Although IPA is simple and intuitive, previous studies have demonstrated several shortcomings.

For example, Matzler, Bailom, Hinterhuber, Renzl, & Pichler (2004a) noted the original IPA has two implicit assumptions: (1) attribute performance and attribute importance are independent variables;

and (2) the relationship between attribute performance and overall performance is linear and symmetrical. However, several studies have demonstrated that the relationship between attribute performance and attribute importance is causal (such as Matzler et al., 2004a; Oh, 2001), and the relationship between attribute-level performance and overall customer satisfaction is asymmetrical (such as Matzler & Sauerwein 2002; Matzler et al., 2004a). Since changes to attribute performance (satisfaction) are often associated with changes to attribute importance and the relationship between attribute-level satisfaction and overall satisfaction is nonlinear, some studies have emerged to

enhance the IPA.

One of the major IPA revisions is to argue that tourist satisfaction can be structured hierarchically (Deng, Kuo, & Chen, 2008; Deng, 2007; Johnston, 1995; Matzler & Sauerwein, 2002; Matzler, Sauerwein, & Heischmidt, 2003; Matzler et al., 2004a, Matzler, Fuchs, & Schubert, 2004b). Kano, Seraku, Takahashi, & Tsuji (1984) were the first to develop a theoretical explanation for the factor structure of customer satisfaction. In Kano’s model (also known as three-factor theory of customer satisfaction), service attributes are grouped into the following three categories with different impacts on overall satisfaction (see Figure 1 for illustration).

[Figure 1 around here]

- Basic factors (or dissatisfiers) are minimum requirements that cause dissatisfaction if not fulfilled but do not lead to satisfaction if fulfilled or exceeded; that is, negative performance on these attributes has a greater impact on overall satisfaction than positive performance. The fulfilment of basic requirements is necessary but not a sufficient condition for satisfaction.

- Excitement factors (or satisfiers) are the factors that increase satisfaction if delivered but do not cause dissatisfaction if they are not delivered; in other words, positive performance on these attributes has a greater impact on overall satisfaction than negative performance.

- Performance factors lead to satisfaction if performance is high and to dissatisfaction if performance is low. Namely, satisfaction increases linearly depending on performance.

This model implies that basic factors establish a market entry ‘‘threshold.’’ Performance factors typically are directly connected to tourists’ explicit needs and desires. Therefore, an organization should be competitive in this domain. Excitement factors are unexpected and surprise the tourists. As they generate ‘delight’, an organization should try to stand out from the rest as regards these attributes (Matzler & Sauerwein, 2002; Matzler et al., 2003, 2004a; 2004b; Fuchs & Weiermair, 2003).

To concretize the above concept, Vavra (1997) proposed an approach used to identify the abovementioned three factors of satisfaction, which combines explicit attribute importance (i.e.

tourists’ self-stated importance) and implicit attribute importance (i.e. based on an attribute’s correlation or regression analysis with overall tourist satisfaction) in a two-dimensional importance grid. The mean of the importance weights is normally used for the horizontal and vertical coordinates of the matrix. The following factors can then be identified:

- Basic factors: Attributes with low implicit and high explicit importance. Tourists rate these attributes as important but they do not affect overall satisfaction when expectations are met or exceeded.

- Excitement factors: Attributes with high implicit but low explicit importance. Tourists say they are not important, but if delivered they enhance overall satisfaction, but do not cause dissatisfaction if not delivered.

- Performance factors: Depending on their score level we can distinguish between high- and low-importance performance factors.

Methodology

The research process involved was composed of three phases. In the first phase, a list of image attributes for cultural tourism destination was developed - through a qualitative phase. Then, in the second phase, Taiwanese tourists who visited Taiwan’s cultural tourism destinations were surveyed, providing a quantitative dimension to this research. The tourists were asked to rate the importance of each of these attributes and Taiwan’s performance with respect to these attributes post-visitation.

Last, the ratings for performance, explicit importance and implicit importance (derived from partial correlation analysis) were used to construct the traditional and revised IPA grids as well as derive the three factors of tourists’ satisfaction.

Previous research has proposed a number of scales to determine the different attributes relevant to measuring perceived image. Research on the principal scales, Beerli and Martín (2004a, 2004b) revealed that the lack of agreement about the conceptualization of perceived destination image has given rise to great heterogeneity in its measurement. As argued by Echtner and Ritchie (1991), unless considerable effort is expended in the design stages, attribute lists may be incomplete by failing to incorporate all of the relevant characteristics of the destination image. Consequently, the image attributes were generated in a staged process to ensure content validity. The initial pool was composed of items used in other image studies reported in the literature and then fine-tuned to the study area – cultural tourism.

Then, suggested by O’Leary and Deegan (2005), content analysis of written information (such as websites, promotional materials) could provide a great deal of information about the images projected by a tourism destination. Consequently, the websites of three major travel agencies in Taiwan (i.e. ezTravel, Liontravel, Startravel) were selected for content analysis in order to reflect the cultural tourism offerings of Taiwan. Several scholars (such as Andreu et al., 2001; Baloglu &

Mangaloglu, 2001; Frías et al., 2008; Gartner, 1989; Gartner & Bachri, 1994) have demonstrated that the image that travellers hold about a destination (especially international destination) would be significantly influenced by travel intermediaries such as tour operators and travel agents. For instance, Baloglu and Mangaloglu (2001) proposed that tour operators and travel agents have multiple and critical functions in destination marketing efforts: (1) they provide information to potential travellers and (2) develop and promote destination packages. In either case, destination images held by tour operators and travel agents are more likely to influence these vital processes for a tourist destination. Secondly, the Internet as an information source exhibits considerable differences relative to other sources, such as accessibility, convenience in updating, real-time information service, interactive communications, etc. These features make the Internet a singular information source worthy of deep analysis (Frías et al., 2008). Finally, an expert panel comprising

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