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Tourism in Switzerland: how perceptions of place attributes for short and long holiday can influence destination choice.

1. Introduction

The importance of tourism to destinations is well documented in the literature (Colman, 1989; Cooper, Fletcher, Gilbert, Schepherd, & Wanhill, 1998; France, Towner, Evans, & Sowden, 1994; Goodall & Ashworth, 1988; Laws, 1995; Proenca & Soukiazis, 2008; Rita, 2000), but there has been little research into the impact this has on short and long visits (Herington, Merrilees, & Wilkins, 2013). Yet, tourism continues to be one of the fastest-growing industries in both developed and developing countries (Tasci & Knuston, 2004), and tourism competitiveness is considered to be an important economic indicator. Hence, these tourist destinations must develop strategic plans to attract increasingly demanding customers and meet a range of requirements for short and long term visits if they are to make full use of the available attractions and amenities of that place.

Similar to product marketing, the most important element in destination marketing is to understand customer' needs and wants to be able to match those with the products and services at the destination. So it is important for marketers and planners first: to fully understand the destination and what it has to offer, and second: to gain knowledge about visitors and how attributes of the destination may influence their selection of a destination for leisure or business activities. This understanding of different consumer or "visitor" requirements helps tourism managers to make better decisions as they communicate and differentiate a destination (Day, 2010), since it allows them to match visitor perceptions to the specific market segments on offer at each destination (Wheeler, Frost, & Weiler, 2011). In other words, marketers need to consider individual visitors' needs and tailor the destinations to meet those needs. For example Herington et al. (2013) argues that the attractiveness of destinations should reflect the needs of target market to ensure visitors arrive on a regular basis. It is therefore relevant to address not only visitor needs but also how they can match destination attributes that become part of the destination brand.

In another context, the destination attractiveness attributes may be different depending on visitor length of stay. Although prior research (e.g., Formica & Muzaffer, 2006; Hanqin & Lam, 1999; Hu & Ritchie, 1993; Jang & Cai, 2002; Plog, 2001; Prayag & Rayan, 2011) has investigated travel motivations and destination features Herington et al. (2013) observe that few have studied the factors that influence visitors choice of long and short breaks. They argue that existing models are too broad and general ignoring the possibility of differing requirements of tourists at different times in different contexts or for different holiday purposes. Additionally, understanding destination attractiveness attributes in the tourism sector is often limited to research in a US context (Herington et al., 2013). Yet, the findings of these studies are unlikely to be appropriate for generalization into other cultures, systems and service sectors (Hofstede, 1980; Jogaratnam and Ching-Yick Tse, 2006, Tajeddini, 2014; Tajeddini & Trueman, 2014). More specifically, it is important to investigate length of stay in relation to destination branding attractiveness in different locations, countries and cultures to gain a better understanding of push factors (market demand forces) as well as pull factors (supply-side factors) that may create a more competitive environment.

Switzerland enjoys an excellent reputation in the field of tourism and the country has been one of the first to develop tourism as a major industry (Tajeddini, 2010). However there is considerable scope for tourism development, as this country continues to offer natural resources such as snow-capped mountains, high alpine meadows, sunny plateau, tranquil valleys, impressive waterfalls and picture-perfect villages. In fact the World Economic Forum (2013) observed that the number of domestic tourism trips was effectively static and arrivals declined by 4% in 2012. Therefore, the objective of this research is to examine how the needs and perceptions of tourists can be influenced by place brand attributes as they make their choice of destinations to visit, and how these decisions relate to a long or short-term break in countries such as Switzerland. More specifically, this study has three main objectives: (i) To explore destination attributes and destination brands that influence tourists in selecting short and long holidays in general; (ii) To explore destination attributes and destination brands that influence tourists in selecting short and long holidays in Switzerland; (iii) To analyze how the relationships between destination attributes and destination brands may influence tourists in their selection of short vs. long holiday breaks.

2. Background and literature review

The literature identifies several studies on destination choice and destination decision process (Chon, 1990; Ewing & Haider, 1999; Gunn, 1989; Hanlan, Fuller, & Wilde, 2005; Moutinho, 1986; Muller, 1991; Um & Crompton, 1999; Woodside & Lysonski, 1989). Destination attractiveness for tourists is associated with the ability of the destination in delivering its perceived attributes. Mayo and Jarvis (1981, p. 201) view destination attractiveness as 'the relative importance of individual benefits and the perceived ability of the destination to deliver these individual benefits'. Equally, Hu and Ritchie (1993) focus on individuals' feelings, beliefs, and opinions of the destination in satisfying vacation needs. They link the level of destination attractiveness with destination selection. Ragavan, Subramonian, and Sharif (2014, p. 404) commented that 'performance of a destination can be measured through the perception of destination travel attributes to tourists'. They concluded that there is evidently a relationship between destination attributes and selecting the holiday destination.

Aspects of destination attributes have drawn attention to some researchers. For example using a mix qualitative approach entailing some focus group discussions and interviews, Battour, Ismail, and Bator (2010) examined the impact of destination attributes on Muslim tourist's choice. An attempt made to identify tangible and intangible aspects that influence the Muslim tourists in choosing their holiday destination. They found that some aspects such as access to worship places, availability of Halal food were priority attributes, which means that destination marketers would need to address Islamic culture in their marketing strategies.

At the same time, another empirical analysis on factors affecting the selection of tourist destination was conducted in the case of Bangladesh. The study considered the various preferences of tourists and examined the tour intention in selecting different tour destination. Employing a multiple regression model, Ahmed (2010) considered nine factors related to a number of different aspects of tourism. He reported that service quality, natural beauty, security and shopping facility were statistically significant in selecting a tour destination in Bangladesh. A similar result was found in the study conducted by Hsu, Tsai, and Wu (2009) who identified 22 attributes that influence the tourists' choice of destination indicating that visiting friends/relatives and personal safety to be the most important factors for inbound tourists to Taiwan.

Using a preference analysis model for selecting tourist destinations in the case of Keda in Malaysia, Mohamad and Jamil (2012) evaluated critical factors influencing local tourists' destination choice. They focused on internal factors that motivate tourists in selecting their destination where they found that visiting friends and relatives was the most important factor while novelty being the least motivating factor.

Further, Herington et al. (2013) carried out a thorough review of previous literature and synthesized six main components of destination attractiveness features; '(1) actual attractions, which include the nature features of scenery and climate as well as manmade attractions such as historical/architectural attractions, theme parks or cultural/sporting events; (2) service, a component that includes accommodation & food; (3) facilities, including infrastructure, accessibility, transport, shopping; (4) reputation, that encompasses the overall image of the destination, including attitudes to tourists and tourism, that is, how easy it is to be a tourist at the destination; (5) social component, that includes how the destination is 'looked after' by locals; and (6) economic, related to the economic attractiveness of the destination in relation to the value for money and or cost of the holiday' (p. 151).

Moreover, in the World Economic Forum report on Travel and Tourism Competitiveness, competitiveness is based on three main categories or sub-indexes: regulatory; business environment and infrastructure; human, cultural, and natural resources. Those sub-indexes contain fourteen pillars of travel and tourism; Policy rules and regulations; Environmental sustainability; Safety and security; Health and hygiene; Prioritization of Travel & Tourism; Air transport infrastructure; Ground transport infrastructure; Tourism infrastructure; Information & Communication Technologies (ICT) infrastructure; Price competitiveness; Human resources; Affinity; Natural resources; Cultural resources (World Economic Forum, 2013, p. xv).

It can be therefore argued that there is a relationship between the attributes of the destination and travelers' decision in selecting their destination. Yet, most studies, evaluated the attributes without much of a distinction between long and short holidays, a point that was raised by Herington et al., (2013). In the following section the concept of short and long term holiday is reviewed.

3. Short vs. long holiday

Travelers have various reasons for taking a holiday such as relaxation, exploration, taking a break from work, attending family or friends' events. The length of the holiday could be short or long and may be determined by the type of activities chosen. Literature on short and long holidays did not provide clear definitions or an agreed opinion on the length of stay of each type. For example, Herington et al. (2013, p. 152) defined 'short break as being one to three nights away from home and a long break as being four or more nights away'. For the purpose of this research a short holiday is defined as being up to one week while a long holiday being one to three weeks break. This distinction of the two types of holiday is mounting in the tourism industry. Scholarly work differentiating between short and traditional holidays began in the nineties (see for example, Beioley, 1991; Davies, 1990; Edgar, Littlejohn, & Allardyce, 1994; Schmidhauser, 1992; Smith, 1996). It can be argued that short break travelers do not necessarily engage in similar activities as long break travelers. Also, short breaks are available more frequently during the year as opposed to long breaks that are mainly seasonal. As motivations and reasons are different for both types, it is assumed that the importance of destination attributes is evaluated differently by travelers. This was evident in the study of Herington et al. (2013) who suggest that the destination attractiveness attributes may be different depending on the length of stay. The latter conducted an exploratory research in Australia evaluating the assessment of participants of the destination attributes as a short vs. long holiday break. They claim that most research focused on broad travel motivations and destination features and that 'the notion of differing set of destination attractiveness features or long versus short breaks is yet to be fully explored' (p.149). Using cluster analysis, the authors report findings on tourists' preferences for short vs. long holidays assuming that the same customer could have different preferences when selecting short or long breaks. Additionally, the study concluded with practical implications for destinations to develop appropriate strategies in promoting the destination as a short, long or a mix of short and long holiday destination bearing in mind the type of market segment(s) and understanding their needs.

Some gaps were identified from the previous research which indicated that distinguishing short and long breaks are pioneering without precedence in the literature. An important finding was that 'both short-break and long-break destinations should be able to meet the needs of the mainstream segment. In particular, short-break-oriented destinations cannot assume that the dominant segment would be satisfied simply, say, with a short, sharp and dynamic shopping spree or attending a major event. The major (mainstream) segment wants a balanced vacation, combining excitement and relaxation and so on, even if it is just a short break' (Herington et al., 2013, p. 160). Given that the former study was exploratory and pioneering in nature it is important to replicate in other countries. As a result, the authors of this research decided to follow up on the research and evaluate to what extent preferences for destination attributes differ in selecting short and long breaks in the case of Switzerland.

4. Tourism in Switzerland

In its recent report, the World Economic Forum report outlined that Switzerland continues to lead the top rank of travel and tourism competitive where the main attributes that are highly rated for Switzerland are its infrastructure, mainly transportation and hotels; its natural resources and environmental sustainability; and Safety and Security (World Economic Forum, 2013). It is worth noting that for some time, Switzerland has been considered a matured market (Bieger & Laesser, 2002; Tajeddini, in press) and is believed to be at the stagnation stage of the Product Life Cycle (PLC) for the past four decades (Mayor, 2013). According to the Federal Office of Statistics, despite its top ranking, the number of tourists in Switzerland between 2008 and 2012 fell in its main markets (Germany 27%, Italy 16% and France 8%) (Mayor, 2013, p. 1). In 2012 Switzerland was facing some challenges due to the remaining strength of the Swiss currency, lower arrivals among European tourists and weak domestic tourism growth, reduced profits for Swiss travel retailers, rising unemployment in the industry and price hikes for food and beverages' (Research Monitor, 2013). Although, the exchange rate of the Swiss franc was fixed at the value of 1.20 CHF/EUR and was predicted to remain stable between 2015 and 2017 (SECO, 2014) this is no longer the case after the National Bank of Switzerland scraped the exchange rate ceiling in January 2015. As a result, this would more likely influence the occupancy rate in hotels in Switzerland where tourists could select other destinations that they consider less expensive. Further, that may well challenge the forecasts for the number of hotel nights that were expected to increase; BAKBASEL believed that domestic demand would grow by 1.6% and international demand was estimated at 2.4% (SECO, 2014). Yet, at this stage, it might be too early to speculate the impact of the new currency exchange on tourism in Switzerland and this aspect is not the main focus of this research. Nonetheless and despite the various challenges that Switzerland has faced, the Travel and Tourism Competitive Index (TTCI) reported that Switzerland has the most competitive travel and tourism industry in the world; it 'continues to lead the rankings, performing well on almost all aspects of the Index' (World Economic Forum, 2013).

With this in mind, it would be interesting to measure the main attributes that sustained tourism visitations to Switzerland as a leisure destination. Some literature was found on the Swiss Traveler such as in the study on market segment by motivations on Swiss travelers (Bieger & Laesser, 2002; Tajeddini, 2015) where they concluded that the travel profile and the attraction of a destination are the elements that determine the Swiss travel behavior. Additionally, the research conducted by Simma, Schlich, and Axhausen (2002) analyzed destination choice of Swiss within Switzerland. Yet, none of the literature examined the differences of preference or destination attributes for short and long holiday breaks in Switzerland by foreign travelers. The current research would contribute to the insight of strategic marketing issues for Destination Marketing Organizations (DMOs) in promoting their destination and customizing their products and services to the relevant market segments.

5. Method

5.1. Data gathering and scale development

The objective of this study is to explore destination attributes influencing travelers in selecting short and long holidays in Switzerland. Measuring the attributes of short vs. long holidays is more problematic, as less empirical research and theoretical effort have been expended in this area. Until firmer foundation has been laid, a more narrowly focused strategy seems desirable. One approach would consist of adopting a sequential mixed-method approach using focus groups of travelers with varied levels of experience in a given destination domain followed up with some in-depth interviews to explore opinions and their travel experiences in more depth. This method enables to uncover and explore the most likely destination attractiveness criteria to access a large group of typical tourist consumers to determine the existence and characteristics of cluster segments (Herington et al., 2013). It is anticipated that this approach will dictate the operationalization of short and long attributes of destination attraction. In doing so, two stages for data collection were used. In the first stage the authors tried to identify the relevant attributes and in the second stage administered the survey using the identified attributes.

5.2. Stage I

In order to explore and identify the relevant attributes of long and short holidays in Switzerland the authors used two groups composed of 21 international students (ten in one group and eleven in the other group) representing various cultures and nationalities gathered in a class meeting room to explore destination attributes in their travel behavior. Two focus groups using convenience sampling method were conducted in June 2013. Each focus group lasted approximately 45 min in duration. Saturation was reached after the second focus groups, with no further data and insights being received at that point. The focus groups were digitally recorded for information accuracy and later transcribed and entered into NVivo software for content analysis.

As a result of the analysis, a general list of characteristics was compiled, which could evaluate attractiveness of short and long holidays. These results largely agreed with previous research, with the most consistently mentioned destination attractiveness features being efficiency, safety, security and lifestyle. Table 1 provides the list of the 25 key destination attractiveness attributes that were extracted from the focus groups and also those extracted from the literature.

5.3. Stage II

After some preliminary content analyses, the authors identified four subset attributes for each dimension. The discussion was set around four key dimensions derived from reviewing prior research as: (1) Destination brand/reputation; (2) Tourism attractions; (3) Tourism infrastructure; and (4) Tourism services.

These attributes were discussed in the second focus group discussion, and the participants agreed on the subsets of dimensions. In the second step, a survey questionnaire was designed to collect relevant data from international visitors about these attributes.

The questionnaire was pre-tested using two academics in order to insure that the survey content and measurement scales were clear, valid and appropriate. Following modifications, a second pretest was carried out with 30 international visitors, to make sure that all the questions were relevant for respondents. This practice follows previous research to ensure the scales for all the dimensions were clearly marked and each item was critically evaluated and verified. Finally, a few open-ended questions were added to give "color" to the data and lead the respondents to think analytically and critically.

After the process of refining, the authors followed the procedure done by Ekinci and Hosany (2006) to collect the main data. Using two different samples, the study was conducted at four different locations: three Swiss cities (Sample 1), and two International airports (Sample 2). For the first sample, the retrieval hypothesis (Solomon, Bamossy, & Askegaard, 1999) was used to capture destination evaluation for visitors of Switzerland. Respondents were instructed to recall the last tourism destination they had visited inside of Switzerland in the previous 3 months. This method resulted in a number of destinations being evaluated. To participate in the survey, respondents were approached randomly on the high street, and around shopping complexes and train stations in Geneva and Zurich. These two cities were chosen due to their multicultural flair and the variety of leisure activities on offer attracts guests from all over the world. In general, participants were responsive and willing to participate, and refusal rates were predominantly low (around 10%). For the second sample, two trained MBA and MA researcher were hired. Data were collected in the departure lounge of two major International airports. Foreign tourists, waiting for their flights to return home after visiting Switzerland, were approached randomly to complete a questionnaire. Unlike the first sample, these respondents had to evaluate the same destination only a few hours after the holiday experience. In both cases, whenever a respondent refused to participate, the researcher moved to the next random available one. After the process of refining, a total of 158 questionnaires were collected, making a response rate of 56.4% that were valid and useful for analysis purposes across both samples (Sample 1: n = 83; Sample 2: n = 75). Care was taken that Swiss travelers were not included.

6. Results

The analysis started with a summary profile of the respondents of the 158 surveys. The percentage of Gender respondents was very close with (48.1%) male and (51.9%) female. The age of the respondents surveyed was skewed towards young aged people, with the majority (92.4%) falling between 18 and 33 years old. Table 2 provides the remaining details of the respondents' demographic characteristics.

The identified destination attributes exhibited in Table 1 were used in the survey questionnaire. Participants were first asked to rate the importance of destination attributes for short holidays then for long holidays. The survey continued using the same questions to evaluate participants' perception on the importance of attributes in selecting Switzerland for short and long holidays.

6.1. Data analysis

To determine whether general destination attributes of long and short holidays differed depending on travel behavior (i.e., past travel behavior, future intention to travel), different analytical techniques were implemented. Cluster analysis was used to determine potential target segments as well as ANOVA and cross-tabulation were computed to verify the characteristics of target segments and the preferred activities for target segments. Following the recommendation of Herington et al. (2013, p. 155), a two-step cluster analysis was chosen to determine the likely existence of distinguishable target segments according to what the group members were attracted to for short and long holidays, as well as any distinguishing features of each cluster on demographic characteristics. Cluster analysis is considered an exploratory multivariate statistical technique for organizing observed data (e.g. people, things, events, brands, companies) into clusters based on homogeneous characteristics that they possess (Field, 2009; Hair, Anderson, Tatham, & Black, 1998). Similar to factor analysis, cluster analysis makes no distinction between dependent and independent variables and the entire set of interdependent relationships are examined. Whereas factor analysis reduces the number of variables by grouping them into a smaller set of factors, cluster analysis reduces the number of observations or cases by grouping them into a smaller set of clusters (Field, 2009). Cluster analysis specifically attempts to maximize between-group variance (Hair et al., 1998) which the results provide an opportunity for marketers of destinations to target particular market segments for similar destination types (Herington et al., 2013).

6.2. Findings

Table 3 provides the list of the destination attractiveness attributes that were extracted from the focus groups and also those extracted from the literature, with a summary of the ratings of importance for each of these attractiveness attributes for both short and long holidays. The most noticeable feature is the similarity in importance placed by respondents when considering either type of holiday. In order of importance, the most important attributes for short stay holiday type were found to be 'Price', 'Safety and Security of the Destination', 'Quality of Food', 'Value for Money' and 'Culture'. Similarly, in order of importance, the most important attributes for long holiday type were found to be 'Price', 'Quality of Food', 'Relaxation', 'Location' and 'Quality & Variety of Accommodation'. Apart from 'Price', 'Quality of Food', which were rated more highly for long and short stays, all other destination attributes were rated similarly and were in similar positions on the importance ranking. Further, for short holidays in general Table 3 shows 'Sports Facilities', 'Adventure', 'Education' and 'Shopping' being least important and for long holidays 'Shopping' and 'Sports Facilities' being least important. This could mean that Switzerland is not a destination for shopping or for sports for this market segment. Therefore when dealing with this type of market, Swiss DMOs could use the most important attributes as valued by this market segment.

Table 4 provides the list of destination attractiveness with a summary of the ratings of importance for each of these attractiveness attributes for both short and long holidays in Switzerland. In this list, it is noticeable that rating of importance of attributes when selecting Switzerland for short vs. long holiday differs. It could imply that the destination itself influences the level of importance of attributes. In order of importance, the most important attributes for short stay holiday in Switzerland were found to be 'Efficiency of Transportation', 'Location, Natural Resources', 'Relaxation & Health', and 'Reputation of Destination'. Both 'Location' and 'Natural Resources' have equal importance to respondents. Similarly, in the order of importance, the most important attributes for long holiday in Switzerland type were found to be 'Location', 'Quality of Food', 'Reputation of Destination', 'Perceived Service Quality', 'Access to the destination', 'Efficiency of Transportation', 'Quality & Variety of Accommodation', 'Recommendations of Friends', 'Natural Resources', 'Availability of tourist information', 'Lifestyle', 'Entertainment', and 'Events & Festivals'. Various attributes are noted to have similar level of importance such as 'Perceived Service Quality', 'Access to the destination', 'Efficiency of Transportation', 'Quality & Variety of Accommodation' and 'Natural Resources', 'Availability of tourist information'. Furthermore, Table 4 identifies 'Sports Facilities & shopping' being least important and again 'Sports facilities' being least important for long holidays.

The Cronbach alpha coefficient (Cronbach, 1951) was used to evaluate the extent of reliability (Table 5) for short and long holidays in Switzerland. This test resulted in the calculation of coefficients which ranged from 0.837 (for Tourism services in long holidays) to 0.667 (for Destination brand/reputation in short holiday). The high coefficient scores led to the conclusions that the scales were acceptably reliable.

In order to examine if there is a difference of importance of attributes for short and long holiday, a univariate t-test was performed as shown in Table 6. As can be noted the p-value is below 0.5 which is not statistically significant, yet it also means that there is a difference of opinion with regards the importance of attributes for short and long holidays. Moreover, the t-value indicates the differences of the four attribute groups where Tourism infrastructure and Tourism attractions differs significantly (10.5 & 8.8) when selecting short and long holidays in Switzerland.

To further investigate short and long holiday travelers' perceptions in a multivariate setting, logit analysis was performed (Tajeddini & Mueller, 2009). The dependent variable is short holiday in Switzerland and the independent variables are the four short term attributes. Logit analysis results are summarized in Table 7. As shown, the logit model has a p value of 0.000, indicating a good fit. The results of logit analysis are consistent with those of the t tests in that, at a 0.05 level of significance, destination brand/reputation, Tourism attractions, Tourism infrastructure, and Tourism services are statistically significant. The negative coefficients indicate that short travelers' attributes have a great importance of destination brand/reputation, Tourism attractions, Tourism infrastructure, and Tourism services.

7. Discussion and conclusion

The aim of the research was to explore destination attributes influencing travelers in selecting short and long holidays and assess the level of importance of these attributes in their selection. More specifically, the authors made an attempt to explore if there is a difference in the level of importance when selecting Switzerland for short vs. long holidays. The results of the research show that the level of importance of destination attributes differ in selecting short and long holidays. It is also noted that the level of importance varies when selecting short and long holidays in General vs. Switzerland. This could be interpreted that the destination may influence customers' evaluation of destination attributes.

The main findings from this research are in line with the literature (e.g. Herington et al., 2013) on meeting the needs of the market segments more specifically in this context when marketing the destination for short and long holidays. Participants evaluated destination attributes differently when choosing their short and long holidays as demonstrated in Tables 4 and 5. This entails the need for practical strategies to be taken when promoting Switzerland for short vs. long holidays. Destination marketers are advised to focus on the most important attributes when preparing their destination marketing strategies.

The findings show that 'Efficiency of Transportation' in selecting Switzerland for a short holiday was considered to be the most important. This is not surprising considering the positive reputation of the Swiss infrastructure well documented in the literature (World Economic Forum, 2013). While for long holiday, 'Location' came on top of the list. This confirms Herington et al. (2013) suggestion about destination attributes being different depending on length of stay. However, what was surprising to see was that participants considered 'Sports Facilities' and 'Shopping' as least important both for short and long holiday in Switzerland. Considering that Switzerland is perceived as an expensive destination, the results imply that Switzerland may not be promoted as a shopping destination for example.

The results presented in Tables 6 and 7 indicate the important variance in considering attributes in selecting short and long holidays. With this in mind, destinations could develop the relevant approach in marketing its destination for each type. For example, in the context of Switzerland, there are various promotions for city breaks which may be considered as short holidays. For such activities, considering the relevant attributes in their promotions would be beneficial as they would better target and meet the needs of the travelers. It would attract the attention of the relevant segment a very important first step in getting the customer interested in the product offer.

Furthermore, the profile of participants from the demographic characteristics resulted from the research could be of an interest to the destination marketer who would be able to better understand what is considered important for this segment (i.e., young travelers) when they select their short or long holiday destination. In this context Swiss DMOs could make better decisions to differentiate the destination from its competitors by matching their values to the relevant market segment.

As destinations compete to attract tourists, they need to differentiate themselves from their competitors. Taking into considerations that many destinations have similar offer, marketers need to come up with innovative ideas and better understand customers' needs. Differentiating between short and long holidays could further assist marketers in understanding their need and better tailor the destination offer according to segment and length of stay. In this sense, marketers may work on better delivering Switzerland's perceived attributes to its customers. Further, the research has demonstrated such differences and confirms some findings found in previous research by Herington et al. (2013). To the latter, it adds new findings in the context of a new destination Switzerland using a different market segment.

Previous research demonstrated in the literature review section shows the factors considered most important in selecting the tourist destinations which are not the same findings in this research. The authors believe that the destination itself influences the level of importance of destination attractiveness attributes. What could be important in selecting Taiwan or Australia for a holiday is not necessarily the same for Switzerland, a finding that could be appreciated by Swiss DMOs when considering strategic marketing planning.

To conclude, as customers may not engage in similar activities when selecting short and long holidays, it is evident from the research that the destination attractiveness attributes are evaluated differently. This is demonstrated clearly in the research both in general context and in Switzerland. Alluding to such differences could better assist marketers in meeting customers' expectations where the results from the research showed that same customers evaluate attributes differently for short and long holidays indicating that same customers have different preferences when selecting short and long holidays.

8. Limitations and future research

It should be noted that the overall results of research on these characteristics remains inconclusive. As with any research project of this nature, there are limitations. First, the study is limited to Swiss short and long holiday travelers. Generalizing the results to other countries may not be appropriate. Second, the main data were collected in a cross sectional manner, so all what the authors can conclude is that the role variables and their posited consequences are related at one point in time. Three major priorities are proposed for future research. First, it would be useful to replicate this study and repeat this model-testing approach using a completely different sample. Interesting comparisons could then be undertaken by using an identical model for a developing country and a different industry and then comparing the estimated structural parameters. Second, more antecedent variables could be incorporated into the model. Finally, using a longitudinal study may help to identify the direction of causality between variables.


Article history:

Received 23 March 2015

Received in revised form

18 September 2015

Accepted 19 September 2015

Available online 27 November 2015


The authors are grateful to Dr. Myfanwy Trueman, Bradford University, UK, for her thoughtful suggestions, invaluable help and insightful comments on an earlier version of this paper.


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Gretel Qumsieh Mussalam (a), Kayhan Tajeddini (b,c) *

(a) Les Roches School of Hospitality Management, Bluche, Switzerland

(b) Department of Business Administration, School of Economics and Management, Alpha Building, Room: 3090, P.O. Box 7080, Lund University, SE-220 07, Lund, Sweden

(c) Cesar Ritz Colleges Switzerland, Englisch-Gruss-Strasse 43, CH-3902 Brig, Switzerland

* Corresponding author. Department of Business Administration, School of Economics and Management, Alpha Building, Room: 3090, P.O. Box 7080, Lund University, SE-220 07 Lund, Sweden

E-mail addresses:, gretel.qumsieh@ (G.Q. Mussalam),, (K. Tajeddini).
Table 1
Key destination attractiveness attributes on short and long holiday
extracted from focus groups & the literature.

Recommendations of Friends      Natural Resources   Past experience
Efficiency of Transportation    Reputation of       Perceived Service
                                  Destination         Quality
Access to the destination       Value for money     Price
Safety & Security of the        Image               Education
Architecture                    Sports Facilities   Lifestyle
Quality & Variety of            Location            Adventure
Entertainment, Events &         Culture             Food & Wine
Relaxation & Health             Shopping
Availability of tourist         Quality of Food

Table 2
Descriptive statistics of samples and variables.

                     Frequency   Percent

Resident (Country)
China                74          46.8
Germany              18          11.4
Indonesia            2           1.3
Island               2           1.3
Korea                1           .6
Malaysia             10          6.3
Mongolia             1           .6
Russia               13          8.2
Sweden               4           2.5
Switzerland          2           1.3
Syria                1           .6
Taiwan               17          10.8
USA                  3           1.9
Vietnam              10          6.3
Mode                 China

Male                 76          48.1
Female               82          51.9

18-25                119         75.3
26-33                27          17.1
34-41                12          7.6
Median               18-25

Table 3
Mean scores and standard deviations of the 25 attributes in general.

Attributes                           Short holiday      Long holidays
                                     (up to one week)   (1-3 weeks)

                                     Mean (Standard     Mean (Standard
                                     deviation)         deviation)

Destination brand/reputation
Safety & Security of the             4.11 (1.009)       3.89 (1.071)
Image                                3.25 (1.210)       3.83 (1.110)
Past experience                      3.06 (1.232)       3.32 (1.125)
Perceived Service Quality            3.99 (.814)        3.95 (.931)
Price                                4.20 (.936)        4.18 (1.001)
Recommendations of Friends           3.36 (.939)        3.58 (.995)
Reputation of Destination            3.71 (1.268)       3.79 (1.069)
Value for money                      4.09 (.870)        3.90 (.945)
Quality of Food                      4.11 (.910)        4.12 (1.069)
Education                            2.59 (1.262)       3.05 (1.182)
Lifestyle                            3.41 (.896)        3.75 (.843)

Tourism attractions
Adventure                            2.54 (.842)        3.31 (.818)
Architecture                         3.24 (1.269)       3.46 (.903)
Location                             4.06 (.716)        4.09 (.946)
Natural Resources                    3.34 (1.013)       3.34 (1.047)
Relaxation & Health                  3.66 (.842)        4.12 (.838)
Culture                              4.08 (.810)        3.89 (.990)
Entertainment, Events & Festivals    3.73 (.907)        3.86 (1.329)

Tourism infrastructure
Access to the destination            3.70 (.961)        3.31 (.818)
Shopping                             2.86 (1.541)       2.92 (1.316)
Sports Facilities                    2.49 (1.172)       2.26 (1.011)
Efficiency of Transportation         3.95 (1.027)       4.01 (.867)

Tourism services
Quality & Variety of Accommodation   3.94 (1.121)       4.05 (1.312)
Food & Wine                          3.75 (1.069)       3.85 (.773)
Availability of tourist              3.50 (1.039)       3.74 (1.127)

Note: Individuals were asked to indicate the level of importance on a
5-point Likert scale ranging from 1 = least important to 5 = most

Table 4
Mean scores and standard deviations of the 25 Attributes in

Attributes                     Short holiday      Long holidays
                               (up to one week)   (1-3 weeks) per year

                               Mean (Standard     Mean (Standard
                               deviation)         deviation)

Destination brand/reputation
Safety & Security of the       3.60 (1.557)       3.83 (1.155)
Image                          3.89 (.804)        4.31 (.468)
Past experience                3.10 (1.225)       4.29 (.459)
Perceived Service Quality      3.19 (1.269)       4.48 (.505)
Price                          3.73 (1.241)       4.04 (1.071)
Recommendations of Friends     3.62 (1.275)       4.23 (1.057)
Reputation of Destination      4.04 (1.177)       4.56 (.501)
Value for money                3.82 (1.489)       3.71 (1.071)
Quality of Food                3.66 (1.076)       4.69 (.512)
Education                      3.47 (.955)        4.02 (1.211)
Lifestyle                      3.69 (.684)        4.15 (.652)

Tourism attractions
Adventure                      3.10 (1.012)       3.58 (.679)
Architecture                   3.70 (1.070)       3.73 (.844)
Location                       4.52 (.503)        4.79 (.410)
Natural Resources              4.52 (.785)        4.19 (.891)
Relaxation & Health            4.20 (1.130)       3.67 (.859)
Culture                        3.98 (1.022)       4.00 (.769)
Entertainment, Events &        3.79 (1.133)       4.10 (.722)

Tourism infrastructure
Access to the destination      4.29 (.829)        4.48 (.545)
Shopping                       2.47 (1.207)       3.25 (.887)
Sports Facilities              2.38 (1.257)       2.69 (1.240)
Efficiency of Transportation   4.72 (.543)        4.48 (.505)

Tourism services
Quality & Variety of           3.52 (1.149)       4.48 (.545)
Food & Wine                    3.88 (1.085)       3.79 (.898)
Availability of tourist        3.90 (.966)        4.19 (.491)

Note: Individuals were asked to indicate the level of importance on a
5-point Likert scale ranging from 1 = least important to 5 = most

Table 5
Reliability short holidays and long holidays in Switzerland.

Attributes                       Short holiday      Long holidays
                                 (up to one week)   (1-3 weeks)

                                 Cronbach's alpha   Cronbach's alpha
                                 if Item deleted)   if Item deleted)

Destination brand/reputation     (Cronbach's        (Cronbach's
                                   alpha = .667)      alpha = .739)
Safety & Security of the         .623               .735
Image                            .570               .733
Past experience                  .661               .737
Perceived Service Quality        .694               .680
Price                            .695               .668
Recommendations of Friends       .617               .697
Reputation of Destination        .599               .758
Value for money                  .650               .714
Quality of Food                  .694               .708
Education                        .669               .727
Lifestyle                        .586               .742

Tourism attractions              (Cronbach's        (Cronbach's
                                   alpha = .720)      alpha = .663)
Adventure                        .700               .619
Architecture                     .654               .616
Location                         .677               .604
Natural Resources                .668               .675
Relaxation & Health              .729               .611
Culture                          .716               .593
Entertainment, Events &          .671               .673

Tourism infrastructure           (Cronbach's        (Cronbach's
                                   alpha = .689)      alpha = .733)
Access to the destination        .551               .742
Shopping                         .724               .595
Sports Facilities                .525               .547
Efficiency of Transportation     .690               .788

Tourism services                 (Cronbach's        (Cronbach's
                                   alpha = .690)      alpha = .837)
Quality & Variety of             .607               .883
Food & Wine                      .733               .747
Availability of tourist          .481               .526

Table 6
Results of univariate tests-T-tests of significant differences

Attributes                 Means scores

                           Short holiday (up to   Long holidays (1-3
                           one week) per year     weeks) per year

Destination brand/         4.0741 (.37829)        3.4760 (.37829)
Tourism attractions        3.8128 (.38593)        3.5264 (.72061)
Tourism infrastructure     4.2604 (.49454)        3.6582 (.03238)
Tourism services           4.1667 (.50059)        4.2903 (.69717)

Attributes                 t-Value   p-Value

Destination brand/          5.868    .000
Tourism attractions         8.827    .000
Tourism infrastructure     10.556    .000
Tourism services            4.016    .000

Table 7
Results of multivariate analysis--logit analysis results (Short
holiday in Switzerland).

Attributes               df   Coefficient   Chi-square   p value

Intercept                1    41.695         4.745       .000
Destination              1    -2.398         2.583       .000
Tourism attractions      1    -3.745         2.089       .000
Tourism infrastructure   1    -2.8436        2.795       .000
Tourism services         1    -2.746         2.543       .000
Model (-2Log L)          1    -2.981        32.481       .000
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Author:Mussalam, Gretel Qumsieh; Tajeddini, Kayhan
Publication:Journal of Hospitality and Tourism Management
Article Type:Statistical data
Geographic Code:8AUST
Date:Mar 1, 2016
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