Segmenting International Tourists in Thai Resort Hotels: Motivations and Characteristics, Exams of Tourism

Download Segmenting International Tourists in Thai Resort Hotels: Motivations and Characteristics and more Exams Tourism in PDF only on Docsity! i UNDERSTANDING RESORT HOTEL CLIENTELE THROUGH SEGMENTATION: A STUDY OF THAILAND Jiraporn Chomsuan Thesis submitted in fulfilment of the requirements for the degree of Professional Doctorate in Business Administration University of Canberra 2016 i Understanding resort hotel clientele through segmentation A Study of Thailand Jiraporn Chomsuan Abstract Tourist resort hotels have been considered a fundamental leisure tourism product in recent decades. Resort style hotels are becoming popular accommodation options in the tourism industry all around the world, as a result of the special services and functions they offer. Resort hoteliers need to understand their customers well so that they can provide better service than their competitors, thereby attracting and retaining customers. One way for resort hoteliers to gain a better understanding of their customers is via segmentation: subdividing a large resort tourist market into clearly identifiable segments for the purpose of responding to the expectations of resort guests in the targeted segment. This thesis presents research into segmentation of resort tourists visiting Thailand. The distinct segments are identified based on their push factors (tourists’ underlying reason to travel), and they are profiled with respect to demographics and travel behaviour. Additionally, each segment is considered in relation to the importance of pull factors (resort hotel attributes, products and services provided, and activities) and the tourists’ opinions of the resorts they chose to stay in. Tourists who were visiting beach resorts located in the popular destinations of Phuket, Krabi, Samui, Ranong and Chonburi from May to August 2012 were asked to complete a survey divided into five sections: (1) the main reason they travelled (push factors), (2) the resort’s attractions that influenced them to choose it (pull factors), (3) the activities they were interested in participating in while they stayed at the resort, (4) their opinions regarding the resort they chose, and vi 3.4.1 Customer satisfaction ................................................................................................ 72 3.4.2 Customer loyalty ...................................................................................................... 74 3.5 Conceptual framework .................................................................................................... 77 Chapter 4. Methodology........................................................................................................ 83 4.1 Research strategies (deductive and inductive approach) ................................................... 84 4.1.1 Deductive approach .................................................................................................. 84 4.1.2 Inductive approach.................................................................................................... 85 4.1.3 Research strategy for this study ................................................................................. 86 4.2 Types of research design ................................................................................................. 88 4.2.1 Experimental design ................................................................................................. 88 4.2.2 Cross-sectional design .............................................................................................. 89 4.2.3 Longitudinal design .................................................................................................. 90 4.2.4 Case study ................................................................................................................ 90 4.2.5 Comparative design .................................................................................................. 91 4.2.6 Research design for this study ................................................................................... 91 4.3 Sources of data: primary or secondary data sources.......................................................... 93 4.3.1 Primary data sources ................................................................................................. 93 4.3.2 Secondary data sources ............................................................................................. 94 4.3.3 Sources of data for this study .................................................................................... 94 4.4 Sampling design .............................................................................................................. 95 4.4.1 Population frame: resort hotels sampling ................................................................... 95 4.4.2 Sample size............................................................................................................... 98 4.4.3 Distributing and collecting questionnaires ............................................................... 102 4.4.4 Questionnaire design and construct ......................................................................... 104 4.5 Construct reliability and validity .................................................................................... 112 4.5.1 Reliability ............................................................................................................... 112 4.5.2 Validity .................................................................................................................. 114 4.6 Data analysis ................................................................................................................. 118 4.7 Limitations and weaknesses of overall approach ............................................................ 120 4.8 Summary ....................................................................................................................... 122 Chapter 5. Data Analysis and Results .................................................................................. 125 5.1 Sample profile (from part 5 of questionnaire)................................................................. 125 5.1.1 Descriptive analyses concerning tourists’ profiles ................................................... 127 5.2 Result of factor analysis on push factors (from part 1 of questionnaire) .......................... 129 5.3 Results of cluster analysis .............................................................................................. 134 vii 5.3.1 Cluster interpretation through mean component values (regression factor scores) .... 136 5.4 Results of Chi-square analysis (from part 5 of questionnaire) ......................................... 138 5.4.1 Demographics description ....................................................................................... 145 5.5 Result of ANOVA analysis (from parts 2, 3 and 4 of questionnaire) ............................... 149 5.5.1 Clusters explained by pull factors............................................................................ 154 5.5.2 Clusters explained by pull factors (activities) .......................................................... 162 5.5.3 Clusters explained by various aspects ...................................................................... 168 Chapter 6. Discussions, Recommendations and Conclusions ............................................... 175 6.1 Discussion ..................................................................................................................... 175 6.1.1 Discussion of travel motivation (push and pull factors) ........................................... 175 6.1.2 Discussion of resort tourists’ segmentation.............................................................. 177 6.1.3 Discussion of tourists’ reflections on experiences (satisfaction and loyalty) ............. 186 6.2 Recommendations for Thai resort businesses ................................................................. 188 6.2.1 Macro-level recommendations ................................................................................ 188 6.2.2 Micro-level recommendations (applied for operational marketing strategies) ........... 190 6.3 Recommendations for future researchers ....................................................................... 197 6.4 Conclusion .................................................................................................................... 199 References ................................................................................................................................ 203 Appendix A Information Sheet for Hotels and Participants ....................................................... 227 Appendix B Questionnaire ....................................................................................................... 233 Appendix C SPSS Results ........................................................................................................ 239 Appendix C.1 ........................................................................................................................ 239 Appendix C.2 ........................................................................................................................ 240 Appendix C.3 ........................................................................................................................ 241 Appendix C.4 ........................................................................................................................ 244 Appendix C.5 ........................................................................................................................ 245 Appendix C.7 ........................................................................................................................ 247 Appendix C.8 ........................................................................................................................ 248 Appendix C.9 ........................................................................................................................ 249 ix List of Tables Table 2.1: Number of persons engaged, number of rooms, and average persons engaged per room, by region .......................................................................................................................... 29 Table 2.2: Thai hotel occupancy, 2015 ......................................................................................... 33 Table 3.1: Tourist segmentation: previous literature ................................................................... 70 Table 4.1: Number of resorts, by region and location .................................................................. 97 Table 4.2: Summarised number of cases of tourism segmentation studies ................................ 101 Table 4.3: Reliability of measurement scales of Cronbach’s alpha ............................................. 114 Table 4.4: Data analysis process ................................................................................................ 119 Table 5.1: Frequency analysis of respondents’ demographic and trip-related behavior ............. 126 Table 5.2: Factor analysis of determinant factors (1) Challenge/explore journey ....................... 132 Table 5.3: Factor analysis of determinant factors (2) Escape trip ............................................... 133 Four attributes falls into this factor (Get away, Release pressure, Escape routine, and Seek peaceful life) Itrepresents 16.473% of total varience explained with an Eigenvalue of 2.800 and an Alpha at 0.894. An overall mean value of 3.13 was found. This factor was labled as ‘Escape trip’. ................................................................................................................................................. 133 Table 5.4: Factor analysis of determinant factors (3) Simply relax vacation ............................... 133 Table 5.5: Final cluster centres .................................................................................................. 135 Table 5.6: ANOVA output for means analysis with four segments.............................................. 137 Table 5.7: Euclidean distances between final cluster centres ..................................................... 138 Table 5.8: Number of cases in each cluster ................................................................................ 138 Table 5.9: Clusters explained by demographics attributes ......................................................... 140 Table 5.10: Segment cluster differences for pull factors ............................................................ 151 Table 5.11: Segment cluster differences for pull factors (activities) ........................................... 159 Table 5.12: Segment cluster differences for their visiting experiences ....................................... 166 Table 5.13: Segment cluster differences for their views............................................................. 167 Table 5.14: Summary of characteristics of tourist segments ...................................................... 170 Table 5.15: Summary of findings: whether the hypotheses are supported or rejected ............... 172 Table 6.1: Summary of marketing strategies focused for each segment..................................... 197 1 Chapter 1. Introduction 1.1 Rationale of the study Tourism has become a global phenomenon since international travel emerged as a major revenue-generating industry for many countries (UNWTO 2013). The tourism industry is considered to be the largest and fastest growing industry in the world (ESCAP 2007). Like many countries, in Thailand tourism is one of the key pillars of economic development (BOI 2013). In the past the Thai economy largely depended on the agricultural sector. This has been changing to reflect Thailand becoming an economically progressive state, with exports dominated by manufactured goods and services (Bunbongkran 1996; Phongpaichit & Baker 1997). Currently, the Thai economy is dominated by the services sector (44.3%), which includes the financial sector, education and tourism, followed by the industry sector (43.6%), and the agricultural sector (12.1%) (see Figure 1.1). Figure 1.1: Thailand GDP: composition by sector Source: Adapted from National Economics and Social Development Board, 2012. Agriculture 12.1% Services 44.3% Industry 43.6% GDP by sector % 2 The tourism industry has become an effective driver of economic growth as the country shifts from an agricultural based economy to a more industrialised and service based economy (Ratanakomut 1995; Bunbongkarn 1996). According to World Travel and Tourism Council (WTTC 2015), the tourism sector continues to play a crucial role in Thailand’s socioeconomic development, accounting for about 8.6% of gross domestic product (GDP) (NESDB 2014). Thailand has valuable resources for the tourism industry, as it offers visitors great scenic beauty, an exotic culture and compelling indigenous architecture, and so it has become one of the world’s most popular tourist destinations (WTTC 2015). Thailand attracts many international tourists, and numbers of arrivals have considerably increased each year (see Figure 1.2). Figure 1.2 Yearly tourist arrivals to Thailand (1998–2015) Source: Tourism Authority of Thailand, and National Statistical Office, Thailand; compiled by the researcher Thailand is among the top ranked countries for tourist arrivals in Southeast Asia. It is second only to Malaysia, as can be seen in Figure 1.3. 7.76 8.58 9.51 10.06 10 11.85 13.82 14.15 15.9 19.23 22.3 27.4 24.7 29.88 0 5 10 15 20 25 30 35 1 9 9 8 1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3 2 0 0 4 2 0 0 5 2 0 0 6 2 0 0 7 2 0 0 8 2 0 0 9 2 0 1 0 2 0 11 2 0 1 2 2 0 1 3 2 0 1 4 2 0 1 5 Number of Tourists Number of Tourists 3 Figure 1.3: Number of tourist arrivals in different Southeast Asian countries, 2012 Malaysia 25 million Thailand 22 million Singapore 14 million Indonesia 8 million Vietnam 6 million Philippines 4 million Laos, Cambodia 3 million Source: Association of Southeast Asian Nations, 2012 Thailand was the first country in the region to develop tourism at a national level and has enjoyed exceptional growth in international tourism for many years, as noted by Song et al. 2013. Thailand as a tourist destination welcomes a wide variety of international tourists who differ not only in their physical appearances but also in their thoughts and feelings. Recent research has shown that the inbound market segment of the Andaman Cluster in Thailand is made up of groups that differ in sociodemographics, trip-related characteristics and the benefit they seek from travelling (O’Mahony et al. 2013). Therefore, it is reasonable to state that the guests of international hotels and resorts must also differ, and that it is possible to divide them into distinct groups of tourists with differing and specific needs and desires. Customer demands and expectations are changing in today’s fast-paced, technologically oriented world. Customers, in general, have higher expectations. They expect products and services of better quality: a wider range and a specific and unique style of products and 6 of Russia, Europe and the Middle East (TAT 2013). This reflects an awareness of tourists’ dissimilarities; tourists who visit Thailand can be grouped into quite different segments. Another example addressing the importance of market segmentation presented here regards tourism accommodation types. People travel for many reasons, for example, to visit friends and relatives, for business, or to attend conventions and take holidays. Moreover, they do not travel under the same restrictive conditions—in particular, personal factors can vary among individuals, such as time, monetary issues and personal preferences. Tourism accommodation types must differ from one to another in order to accommodate tourists’ different purposes and travel conditions. For example, these could be budget hotels or guesthouses for backpackers who have limited travel funds, urban hotels which cater to business travellers, or resorts or boutique hotels for other specific type of tourists. Tourism marketers are aware of the heterogeneous nature of customers (i.e., tourists’ dissimilarities) and consequently classify tourist accommodation into various categories. Failure to apply segmentation could lead to unfocused and ineffective marketing. Resort style hotels are one type of tourism accommodation, and they have the kind of accommodation favoured by one particular type of tourist. That is, they attract guests who like to stay in a self-titled hotel, often for a longer period of time and with numerous activities (Mill 2008). However, this type of tourist still has its own requirements in terms of accommodation. It would be reasonable, thus, to apply the concept of market segmentation to their businesses. Doing so would not only lead them to focus on the right target market but also allow them to properly position themselves in the market. There are several factors to consider when setting out to engage in market segmentation. A very wide selection of variables can be used to divide and describe segment characteristics. 7 Kotler and Keller (2009) provided a useful guideline of segmentation bases which have emerged as the most popular in market segmentation studies: (1) demographics based segmentation, including studies based on age, sex, socioeconomic group, family size, life cycle, income, occupation, and education (2) geographic based segmentation, in which markets are divided into geographic units which include region, country, city size, population density and climate (3) behaviour based segmentation, including brand loyalty, usage rate, benefit sought and use occasions (4) psychographics based segmentation, including lifestyle, activities, interests, opinions, needs, values and motivations as market delineators. Segmentation based on demographics has been the most researched because of its practicality: the segments are easy to identify and measure. There is much more data available to help with the segmentation process. The segments are easily recognised (Tynan & Dryton 1987; Kotler 1991; Gunter & Furnham 1992; Inbakaran et al. 2012). Similarly, the geographic approach is simple and clear, and can be easily understood, so geographic segmentation is popular as well (Dolnicar 2004). Each basis for segmentation has its own advantages and disadvantages. The disadvantage of geographical segmentation lies in the danger of mixing very heterogeneous people from the same country of origin and artificially treating them as one segment. It is very likely that the entire segment consists of more than one subgroup. In the same way, although customers are allocated to subgroups when they are segmented demographically, they may have differences in their psychographic traits, such as their lifestyles and motives, which could influence their buying behaviour. For example, customers who are in the same segment because they share characteristics in terms of 8 demographics, like age range or occupation, may have different motives and may respond to marketing campaigns in different ways. Moreover, demographic characteristics could sometimes portray the differences which are the determinants of a customers’ behaviour; demographics merely describe but do not provide an understanding of why a market segment responds to a product in a certain way, unlike psychographics (Kotler & Keller 2009). Behavioural segmentation, despite being a relatively effective approach, does not really consider why consumers buy the product, their needs or their lifestyles, and so the level of market understanding may not be high. Businesses too reliant on behavioural or benefit segmentation may fall behind in innovation, as they could end up focusing on existing needs, behaviours or benefits rather than looking at other opportunities and other ways of meeting customer needs (Kotler & Keller 2009). Dissatisfaction with geographic, demographic and behavioural characteristics as segmentation bases has led to the use of psychological variables as a basis for predicting consumer behaviour (Tynan & Dyton 1987). Psychographics researchers have moved beyond geographic, demographic and behavioural segmentation to consider segments based on activities, interests, opinions, needs, values, attitudes, personal traits and motives. Although there is an increasing amount of research on psychographics segmentation, there is a need to understand more about the various aspects of psychographic segmentation, especially in the service sector, such as the hotel industry. Moutinho (2000) points out that psychographic segmentation allows a substantially deeper grasp of the tourist’s psychological make-up. Psychographic segmentation is considered to have made a great contribution to both describing and understanding tourists. 11 1.2 Major research aim This research aims to understand international tourists visiting resort hotels in Thailand by grouping them on the basis of psychographic segmentation, including their travel motivations (push factors), and to investigate their characteristics in terms of their demographics, trip-related behaviours and opinions about the resorts they stayed at. 1.3 Research objectives The major research aim can be broken down into several objectives: (1) to identify underlying dimensions of travel motivations (push factors) of international resort hotel tourists in Thailand (2) to identify segments of international resort hotel tourists in Thailand according to their motives (3) to investigate the characteristics of the identified segments (4) to provide recommendations about designing strategies for marketers of resort hotels in Thailand. 1.4 Definition of a resort hotel Resort style hotels are the area of interest in this study, thus the term ‘resort hotel’ needs to be defined. Definitional issues remain around the appropriate use of the term ‘resort’ where no regulations exist around tourist accommodation businesses using the word ‘resort’ to describe their properties (Sharma 2008). This is the case for Thailand. The Hotel Act B.E 2547 does not contain a section relating to the use of the word ‘resort’. As previously mentioned, tourists’ expectations, specifically at a time when global travel is increasing and tourists want something different, are based on a differentiated market (Adner 2011). In order to satisfy that expectation, the style of many traditional commercial 12 hotels is moving more closely to that of a resort style hotel. Resort hotels have become the world’s most common form of tourism accommodation (Sharma 2008). There are numerous resort hotels in the tourist destinations of the Asia-Pacific region (including Thailand) and the number has been increasing (Smith & Henderson 2008). Resort locations in Thailand, such as Phuket, Krabi and Pattaya, receive many international tourists every year (NSO 2012). It is obvious that the number of resort hotels is growing, and even traditional hotels frequently advertise themselves as being a resort to take advantage of tourist perceptions (Sharma 2008). Consequently, there are mixed applications of the terms ‘hotel’ and ‘resort hotel’ among hotel businesses. There are differences between the present operation of resort hotels and of conventional hotels of the past. Such differences are in visitor markets, seasonality, visitors’ purpose of stay, space allocation, facilities design, recreational provisions and other amenities, service expectations, and human resource issues (Gee 2010). Scholars’ definitions of the term ‘resort’ vary. Weigh and Gibbings (1991), while reviewing the performance of the accommodation sector, focused on hotels, motels and caravan parks yet alluded to the future role of resorts, which they identified as destinations and genuine contenders for product development. Gunn (1988, p.108) states that resorts are ‘complexes providing a variety of recreations and social settings at one location’. Leiper (2004, p.7) refers to resorts as ‘a destination, normally not far away, for recreational purposes—for rest, relaxation and/or entertainment’ which people visit temporarily. Another definition by Burkart and Medlik (1985, p.14) is still very general but does refer to tourism: ‘gradually the term resort has come to acquire its literal meaning to denote any visitor centre to which people resort in large numbers’. 13 The Australian Bureau of Statistics (1989, p.6) defines resorts as ‘establishments which are integrated complexes containing accommodation and a variety of eating and drinking places’. These establishments provide facilities and services additional to those commonly provided by hotels or motels. They may encompass some natural physical amenities, and a special location, attraction or activity. They provide accommodation like rooms, suites, cabins or units. These establishments provide sufficient night life and daytime activities to encourage an extended, self-contained, on-site holiday. King and Whitelaw (2003) claim that in most of the general tourism textbooks the term ‘resort’ is used widely but never defined; academic definitions of resorts have tended to be general and pragmatic. Based upon input from resort executives and professionals, research undertaken by the University of Memphis developed a clear definition for the term ‘resort’ (as related to lodging) to be: A resort is a full-service lodging facility that provides access to or offers a range of amenities and recreation facilities to emphasise a leisure experience. Resorts serve as the primary provider of the guests’ experience, often provide services for business or meetings, and are characteristically located in vacation-oriented settings (University of Memphis 2009, p.2). According to Mills (2008), based on location classification criteria, the resort style has three subdivisions of its own: • proximity to primary market • setting and primary amenities • mix of residential and lodging properties. 16 It can be argued that travellers who choose to stay in resort hotels may have specific requirements which traditional hotels do not provide for—because resort hotels have distinct styles for their vacations. Therefore, resort hotels should be considered and treated as one particular tourist segment. However, there must be various aspects of dissimilarity between particular resort hotels. It is necessary to investigate and to understand resort hotel tourists as a subsegment within a segment. 1.5 Scope of the study This research was narrowly focused on resort hotels rather than any other types, such as urban or business hotels, because the aim of the research was to understand tourists who travel for recreational reasons (e.g., to be around people, to reduce stress, to relax and/or to enjoy nature) over any other reason, such as for business or to visit friends and relatives. The National Statistical Office has revealed that the number of tourists visiting Thailand for holiday purposes has been increasing significantly year after year, while the numbers of tourists travelling for business purposes have not seen an increase as considerable (NSO 2012). As a result, the tourism market in Thailand is oriented more towards the holiday market, including resort hotels, than business tourism. Therefore, this research centred on tourists who were accommodated in resort hotels rather than on business travellers who normally lodge in other types of accommodation, such as hotels situated in the heart of the city or business area. Nevertheless, there were no set selection criteria in terms of ownership structure and branding for those resort hotels (i.e., this study did not investigate whether the resort hotels belonged to an international chain or were stand-alone properties). Likewise, whether the resort hotels were international brands or local brands was not a concern. Although there was a deliberate attempt to capture only resorts at and above the 3-star level, it was not the primary objective of the research to study resorts on the basis of their star category. One 17 selection criterion was that selected resorts have the presence of international tourists, regardless of their location. The main intention of this was to focus on international tourists, that is, to survey as many different nationalities of resort visitors as possible. Regarding scope, another important criterion was that resorts which agreed to take part in this research were all located at or near beach areas. Therefore, the scope of the research is limited to only one form of resort type instead of many (e.g., lakes, waterfalls, mountains) with regard to geographic location. 1.6 Contributions of the study This study makes up for current research deficiencies in resort tourist segmentation in Thailand. Its significance lies in both academic and practical aspects. On the academic level, the outcome of the study contributes to the current body of knowledge in the following areas. Firstly, as will be discussed in Chapter 3, Review of the related literature, although an extensive body of research exists into the motivations of tourists using push and pull factors, there is limited research that uses push factors as a segmentation base for tourists, particularly in the context of Thailand. This can be partially explained by the obvious lack of suitable theoretical frameworks in the study area. The theoretical framework developed for this study covers the key dimensions and variables which will enable marketing management theorists to further examine market segmentation practices in tourism industries other than the hotel industry of Thailand. Secondly, the introduction of push and pull factors in segmentation will provide a more comprehensive understanding of the travel motivation of resort hotel tourists. The study provides new knowledge of relationships between push and pull factors. For example, 18 resort attributes (pull factors) which are sought by resort visitors could be predicted from their travel motives (push factors). Thirdly, it provides the opportunity for confirmation or replication in future studies in other geographical settings. At the end of 2015, Thailand has joined the Association of Southeast Asian Nations Economic Community (AEC), which comprises 10 countries in Southeast Asia: Thailand, Myanmar, Laos, Vietnam, Malaysia, Singapore, Indonesia, Philippines, Cambodia and Brunei. A goal of establishing the AEC is to transform the region into a single market, allowing the free flow of goods, services, investment, capital and skilled labour. This event will provide opportunities for increased tourism to the region, and the research may have implications for practice beyond Thailand. In practical aspects, the study will contribute to resort hoteliers’ marketing practices in two main areas: (1) choosing the right target market and positioning a brand that suits the specific target market (segment) (2) implementing suitable marketing strategies. On point (1), this study will help resort hotel operators in Thailand to know exactly which types of resort hotel visitors choose their business, and this information is valuable in determining where and how resorts should position themselves in the marketplace. For example, if they realise their visitors are family oriented, positioning the business as a family resort may be appropriate. On the other hand, if the resort is found to be crowded with young visitors looking for a challenge, a position as an adventurous resort could be developed. Bloom (2005) suggests that tourists should be categorised according to their similarities so that they can be targeted. Thus destinations (i.e., resort hotels) can target markets profitably rather than wasting scarce resources trying to attract all customers 21 Chapter 5, Data analysis and results describes the findings of the study. A frequency analysis table is presented to describe respondents’ characteristics. Factor analysis was used to identify the underlying structure of the push motives, then factors are displayed with significant figures such as factor loadings, Eigenvalues and percentage of total variance in table form—which make it easier to understand. Apart from factor analysis, K-means cluster analysis was utilised to determine the number of tourist groups. The substance of the findings of the technical details behind the numbers extracted from the analysis are mostly presented in words, but tables are also provided. Cluster group differences are compared using Chi-square analysis for nominal data, while interval data is one-way analysis of variance (ANOVA), which are presented in tables and in text. Chapter 6, Discussions, recommendations and conclusions concludes the study and presents the summary of findings in relation to segmentation of resort tourists visiting Thailand. The clusters that arose out of the analysis are also discussed. The study has determined that there are interesting and distinguishable clusters—this is a good sign, as these clusters can be individually approached for marketing purposes. The practical implications of the study are discussed, and recommendations for providers of Thai resort hotels and suggestions for future research are made. 23 Chapter 2. Hotel and Resort Industry in Thailand 2.1 An overview of the hotel industry of Thailand 2.1.1 Revolution of the hotel business in Thailand In 2005, Angkasuvana presented a clear overview of the revolution of the Thai hotel industry, as outlined in Note 1 below. Note 1: The revolution of the Thai hotel industry In ancient times, when travelling, Thai people stayed with their relatives or in temples. Businesses providing accommodation were extremely rare. In recent history, overnight stay behaviour has changed because of the influence of the international tourism phenomenon. The foundation for international tourism in Thailand can be traced back to the reigns of Thai kings Rama IV and Rama V, who encouraged international trading, which brought in not only a flow of capital but also a flow of investors, traders and a few tourists (Li & Zhang 1997). As a result, new forms of demand for accommodation from travelling visitors emerged. The first three hotels, namely, the Union Hotel, Fisher’s Hotel and the Oriental Hotel, were established in 1863 to provide rooms and services for foreigners in Bangkok. After that, as the railway system improved, the number of resort hotels in the seaside provinces, such as Cholburi and Prachuabkirikhun, increased along the railway route (Somsap 1985). The hotel business grew steadily without regulation for decades, until the government first announced the Hotel Act of 1935 to regulate the standards of rooms and services. The Hotel Act defined a hotel as ‘an establishment offering food and drink and temporary sleeping accommodation if so required for any traveller who appears able and willing to pay for services and facilities provided’ (Kijphanpanich 2001). 24 Following liberalisation in tourism, advancement in information technology and the perception of tourism as an avenue for the development and enhancement of life experience, people worldwide have been motivated to travel more. After World War II, the tourism industry in Thailand rapidly expanded because of the development of air transportation. Many airlines directed flights to Bangkok, and the number of foreign tourists increased. Consequently, the government launched Investment Promotion ACT of 1977 to encourage investment in hotel businesses. This was a vital first step towards Thai hotel businesses having the opportunity to develop to meet the universal standard, and its development remains ongoing (Phatrapipat 2001). Source: Angkasuvana (2005, pp.17-18) 2.1.2 Types of hotels in Thailand Several types of travel markets exist based on travelling purpose, such as travel for government business, for corporate business, to visit friends and relatives, or for pleasure (Crompton 1979). Each travel market has a unique expectation of the hotels they choose. Travellers refer to hotel classifications as an important factor in choosing a hotel; therefore, it is important to classify hotels into distinct types. Hotels can be classified on the basis of size, location, star system and ownership (Knowles 1998; Kijphanpanich 2001; Phatrapipat 2001). In general, there are official standards for categories of hotels in Thailand, but these are limited in terms of their application to the law (the Building Control Act B.E. 2522, which is in connection with the Hotel Act B.E. 2547). The following classifications could be applied to businesses in the Thailand hotel industry: 27 In 2012, according to Jones Lang LaSalle (2013), which is a professional services and investment management company specialising in real estate, there were four major transactions of over 1 billion Thai baht each for hotel investments in Phuket, the hotspot for hotel investment in Thailand, all of which were foreign investments. Moreover, in 2015 Thailand has become a member nation of the AEC, and the number of tourists visiting Thailand is expected to increase (Economic Intelligence Center of Siam Commercial Bank 2011). Consequently, demand for hotel rooms is expected to increase. The hotel business is a key element of the tourism industry that is becoming a more attractive investment sector for both domestic and foreign investors. As a result, investment in the country will also grow. 2.1.3.3 Employment creation Jobs are the main source of income for any country and a key driver of poverty reduction (World Bank 2013). Thailand has faced changing economic conditions over recent decades. For example, people in several of the provinces in the southern part of the country were dependent on agriculture for their living, as well as other industry sectors, such as tin mining and rubber farming, and export items, such as farmed shrimp (Kontogeorgupoulos 1998). The tourism industry stepped in when the tin mining industry collapsed after 1980, the value of rubber declined, and shrimp farming began to put great stress on the natural environment. The Thai government, therefore, has utilised the natural attractions of those regions to implement a national tourism strategy, which has affected the expansion of the tourism business and in turn the hotel business (Angkasuvana 2005). The expansion of hotel business investment has resulted in an increase in the size of the labour forces in the industry, thereby improving Thai labour employment opportunities: 28 TripAdvisor, the world’s largest travel site (Turban et al. 2015) announced the results of the latest TripAdvisor Industry IndexTM, the world’s largest hotel survey. With more than 25,000 responses from hoteliers around the globe, and more than 500 from Thailand alone, the survey revealed some interesting findings about top hospitality industry trends. Among the key findings is that Thailand ranks third in the world for best places to find a hotel job, with 31% of hoteliers expecting to increase their staff in the six months from August 2012 (Prnews 2012). The World Travel and Tourism Council in its annual report (2013) predicted that the travel and tourism industry in Thailand would create 6,838,500 jobs, including both direct and indirect jobs. This was expected to rise by 10% to approximately 7,528,000 jobs in 2013, and by 4% to approximately 10,539,200 jobs in the next 10 years from the release of report (2013). As part of the tourism industry, the hotel industry is vital to the Thai economy and to creating employment for local communities. This can be seen from Table 2.1, which shows how hotel and resort businesses have an impact on local job creation in a local community. 29 Table 2.1: Number of persons engaged, number of rooms, and average persons engaged per room, by region Region Number of hotels and guesthouses Number of persons engaged Number of rooms Average persons engaged per room Whole kingdom 10,018 244,318 457,029 0.5 Bangkok 704 54,593 87,626 0.6 Central 2,532 56,285 112,757 0.5 Northern 1,854 27,788 61,483 0.5 North-eastern 1,215 15,265 39,422 0.4 Southern 1,753 90,387 155,741 0.6 Source: The National Statistical Office, Thailand, 2014 Table 2.1 shows that, for the whole kingdom of Thailand, 244,318 people were employed in the hotel business. The region with the most people engaged in hotel jobs is the southern part of the country, where around 90,387 people are engaged in hotel jobs, while the north- eastern region has the least, with around 15,265 hotel business employees. 2.1.3.4 Increasing standards of living According to a World Bank report published in 2012, employment leads to higher standards of living. People in rural communities of Thailand have lower standards of living than those in urban areas. Several factors contribute to this. One is the lack of job opportunities in rural areas (rural people need to migrate to big cities to find work). Employment in rural communities could help resolve the problem of people needing to migrate to big cities. A person looking for work would have no need to move to Bangkok 32 source (NSO 2014) show that (as seen in Figure 2.4) there are 457,029 hotel rooms in the whole country. The southern region has the highest number of hotel rooms available (155,741), accounting for 34.08% of the total, followed by the central region with 112,757 rooms (24.67%). The north-eastern region holds the lowest number of hotel rooms. Figure 2.4: Number and percentage of rooms, by region Source: Adapted from National Statistical Office of Thailand, 2014 A hotel occupancy survey by the Bank of Thailand reveals that Thailand’s hotel businesses in 2014 gained valuable points in occupancies and room rates. Occupancy in 2015 improved 6.14%, to 61.72%, compared with 55.58% in 2014 across the country. Hotels in Bangkok, including the central region, had the highest occupancy rate at 65.38%, followed by the southern region (Samui to the Andaman coast) at 62%, while hotel bookings along the eastern coast increased 0.80 % (see Table 2.2: Thai hotel occupancy, 2015). 19.18% 24.67% 13.45 11.3% 19.7% % of rooms by region Bangkok Central Northern Northeastern Southern 33 Table 2.2: Thai hotel occupancy, 2015 Year round occupancy 2015 (%) 2014 (%) Percentage growth (%) Bangkok, including Central 65.38 59.29 +6.09 North-east 42.66 46.49 -3.83 North 57.68 53.87 +3.81 South 62.00 59.46 +2.54 East 60.00 59.20 +0.80 West 52.12 48.00 +4.12 Source: Hotel occupancy survey: Bank of Thailand, 2015 To conclude, the Thai economy depends heavily on the performance of its tourism industry; millions of jobs and a wide range of other industries are directly or indirectly dependent on the tourism industry and its management. The hotel business is one key part of the tourism industry and always makes an important contribution to the country. A large number of international tourists come to Thailand, and this sector has seen growth every year. Importantly, those tourists have different needs and different expectations, and the tourism and hotel and resort industry has had to adapt to new and more specialised accommodation products to appeal to those travellers. However, it is difficult to meet the needs and expectations of travellers if the hotel and resort businesses do not know what the travellers’ different needs and expectations are. One way to help business managers to gain a better understanding of their guests is by applying segmentation practices. Development of the hotels and resort hotels industry will play an important role in helping Thailand to remain a popular tourist destination. 35 Chapter 3. Review of the Related Literature The purpose of this study is to understand the guests of resort hotels in Thailand. The study focuses on their travel motivations (push and pull factors), and many other aspects, such as guests’ opinions about the particular resort they chose as their accommodation, their overall satisfaction and their intention to revisit. One effective way of acquiring such understanding is to identify and recognise tourists as distinct segments. Therefore, literature and empirical studies mainly related to the theme of tourist segmentation are reviewed in this chapter. Travel motivations theory, particularly push and pull factors, as a psychological factor in forming tourist segments for this study is also reviewed. Another theme is tourists’ reflections on experiences. ‘Experiences’ here refers to the resort hotel vacation experience. In order to capture an overview of the study of global resort hotels, the literature regarding resort hotels is also examined. As can be seen in Figure 3.1, tourist segmentation is a central theme of the literature, while the other three themes—resort hotels, travel motivation and tourists’ reflection on experiences—are also essential components. 38 resort hotels. Callan and Bowman (2002) completed comprehensive research on 38 hotel selection attributes to verify their influence on older guests’ choices of accommodation. Thomas (2002) used action research inside a resort community to study the inefficiency of a customer service training program and its subsequent impact on new and repeat visitors to that resort. Juwaheer and Ross (2003) used a modified version of the ServQual model to measure the service quality in the hotel industry in Mauritius. More recently, Konu (2010) studied segmentation of Finnish ski resort visitors according to ski destination choice attributes using data driven segmentation. Juan and Lin (2011) studied resort hotel location factor selection, while Smerecnik and Anderson (2011) examined sustainable tourism for the hotel industry. Among the wide range of studies in the resort hotel sector, the chief methods of investigation can be very broadly divided in two ways: the approach from the supply side and the approach from the demand side. On the one hand, researchers placed emphasis on the supply side, such as physical features of the hotel or resort hotel (e.g., construction and landscape), the products and services the hotel or resort hotel was offering (e.g., accommodation, atmosphere, facilities and amenities), or the management of the hotel or resort hotel (e.g., the resort’s personnel management). On the other hand, many researchers paid much attention to the study of resort hotels from the demand side, that is, the resort hotels’ clients. As the focus of this study is resort hotel guests, it represents a consideration of the demand side. One way to create good and specific understandings of tourists is to understand their travel motivations (Uysal & Hagen 1993). This subject should not be ignored. Knowledge of why tourists travel is essential because it is associated with tourist destination selection, and such knowledge plays an important role in predicting future travel patterns (Uysal & 39 Hagen 1993). This point of view is in line with Rix (2011), who points out that all behaviours start with motivation. Therefore, it is reasonable to state that there is a need to understand the travel motivations of hotel guests. 3.2 Travel motivation People’s motivation to behave in a particular way is an interesting issue to explore, especially leisure motivation. This section first describes the theory of travel motivation and then discusses contemporary studies on motivation in the tourism context. Fridgen (1996) defines motivation as an inner force pushing an individual to do something to fulfil their desires, which could be either biological or psychological. Travel motivation relates to why people travel (Hsu & Huang 2008). This is similar to the view of Crompton (1979) and Iso-Ahola (1982), who point out that travel motivation is the fundamental reason people wish to travel. In order to gain more understanding of the subject of travel motivation, various theories proposed by several theorists are considered below. 3.2.1 Travel motivation theory Over the years, a number of academic theories have been developed to explain tourist motivations for travelling. Four major theories developed: (1) Plog’s psychocentric–allocentric model (2) Dann’s theory of anomie and ego-enhancement (3) Crompton’s push–pull model (4) Iso-Ahola’s theory. In addition, Gray’s wanderlust and sunlust, and Pearce’s career ladder theory are examined in this study. 40 Additionally, one very common motivation theory regularly used in the study of travel motivations is scrutinised: Maslow’s hierarchy of human needs (see for example Pearce & Caltabiano 1983). According to Maslow (see Tikkanen 2007 for an example explanation) humans seek to satisfy levels of needs which can be separately divided into five stages, from least important to most important. Maslow explained that these needs act in sequence: once needs at the lower levels are met, humans will seek to fulfil needs at the next highest level in the hierarchy. Basic physiological needs, which are the first needs that humans try to satisfy, arise mainly from internal stimuli such as hunger, thirst and fatigue, although some arise from external sources which threaten the individual with pain, injury or death. Generally, satisfaction of these needs is foremost and takes priority over all others. Safety needs come next in importance, and these are ranked in a rough hierarchy: physical security, stability and a routine pattern of living, that is, avoiding taking risks and gaining protection against unknown or uncertain situations. Next are social needs: humans seek love, affection and a sense of belonging to a particular group, which could be family, work or a social circle. The two latter needs originate from fear feelings, so humans seek both physical and mental security. The fourth stage of the hierarchy is the need for esteem, including recognition, status, prestige and reputation. The ultimate need is self- actualisation, which is the highest level of need and refers to an individual’s ability to do ‘one’s own thing’. Cooper et al. (2005) criticise Maslow’s theory, stating that the reason Maslow selected the five basic needs is ambiguous. They also question the arrangement of the needs. In the same way, Pride et al. (2006, p. 115) are critical and state: ‘Maslow’s hierarchy of motives constitutes a general statement of behaviour at the macro level’. To understand the behaviour of the individual, a more comprehensive classificatory scheme is needed. Despite criticisms of Maslow’s theory, many researchers agree that the tourism industry 43 personal and interpersonal components, and all these factors work as push factors for a tourist to engage in leisure and other recreational activities (Biswas 2008). Apart from the five main theories mentioned above, others are also relevant. Gray (1970), for example, tried to explain the reasons for travelling by characterising travellers’ motives, and he mentions wanderlust and sunlust. In Gray’s motivation theory, wanderlust is described as the desire to exchange the known for the unknown. Curiosity motivates people to travel. Sunlust characterises vacations which are motivated by the desire to experience different or better amenities than those that are available in the environment in which one normally lives, for a specific purpose. One other theory, introduced by Pearce (1993), is referred to as the travel career ladder which comprises relaxation, stimulation, relationship, self-esteem and development, and fulfilment. Pearce claims that all of these are dynamic elements, and people are likely to change their motivation from one stage to another over time. Page and Connell (2006) agree with Pearce that tourist motivations are ever-changing. As people progress through the various phases of the life cycle, they move up the ladder; travel motivation will change along with life cycle stages. Furthermore, in Pearce’s model, the motivation lists can be categorised into two broad groups. The needs may be formulated as self-centred or directed at others. Hence, for instance, relaxation may be a solo exercise if the tourist tries to find a peaceful time alone for the purpose of body and mind retreat, or it can take the form of relaxation in the company of others and originate from the need for external excitement and desire for novelty. Stimulation can be self-centred, originating from self- concern, but at the same time others-centred, if it springs from a concern for the interests of others. Relationships can be self-directed, where they start from giving love and affection to others for maintaining relationships; conversely, they can be directed towards 44 others, where the desire to receive affection from others or to be with a group is the goal. Self-esteem and development may be self-driven, such as through the development of skills, special interests or competence and mastery, or directed at others, such as for the prestige or glamour of travelling. Fulfilment is a completely self-directed dimension attributable to the fact that it accomplishes individual dreams and touches one’s inner peace and harmony. With regard to the present study, in all of those theories identified by several scholars, only two travel motivation theories consider the characteristics of the place the traveller visits: Crompton’s push–pull model and Plog’s psychocentric and allocentric model. Both present underlying reasons for travel motivations from both sides, whereas the other theories do not. The others emphasise only the tourist side (why) but leave out the destination factors (where). In other words, the push–pull model and Plog’s psychocentric and allocentric model disclose why tourists travel and where they travel to. Why and where factors connect tourists with destinations, so they are related. However, place or destination characteristics in Plog’s model are not suitable for this research, because they refer to the familiarity of the travellers with their destination. Characteristics of place in the push–pull model have a broader meaning. Therefore, this study utilises the theory of the push–pull model to provide a major theoretical framework. 3.2.2 The push–pull model Dann (1977) and Crompton (1979) introduced the concept of push and pull factors. The idea behind the concept is that people are driven by internal forces, which are called push factors, but at the same time drawn by external forces (e.g., the attraction of a destination’s attributes), called pull factors. The theory of push and pull motivations is a common and useful way to examine tourist motivations (e.g., Dann 1977; Crompton 1979; Epperson 45 1983; Pearce & Caltabiano 1983; Pyo, Mihalik & Uysal, 1989; Brayley 1990; Yuan & McDonald, 1990; Uysal & Hagan 1993; Fodness 1994). Stated differently, push and pull factors have become a central concept to explain tourist motivations, and they provide the critical framework for this study. As suggested by Dann (1977), push motivational factors can be classified as anomie and ego-enhancement. Anomie refers to the desire to feel free from everyday life, while ego- enhancement is derived from the need for acknowledgement and is achieved through the status conferred by travel. These two terms refer to intrinsic motivators. Crompton (1979) further identified push factors in relation to seven sociopsychological motives: escape, self-exploratory, relaxation, prestige, regression, kinship-enhancement and social interaction. According to Crompton, push factors have been thought useful for explaining why travellers wish to go and be somewhere else, without specifying where that may be. On the other hand, pull factors have been described as those factors influencing when, where and how people travel (Mill & Morrison 1985). Uysal and Jurowski (1994) and You et al. (2000) explain that pull factors can be recognised as destination attributes that respond to and reinforce inherent push motivations. They emerge from two main reasons: firstly, for travellers with the capacity to travel, the attractiveness of a destination, such as beaches, recreation facilities, natural and cultural attractions; secondly, a traveller’s perceptions, such as from marketing images, and expectations, such as for novelty and benefits. Since the initial empirical effort by those two pioneers, many followers have attempted to further identify this motivational theory in different settings, such as nationalities and destinations (Jang & Wu 2006). Examples include Yuan and McDonald’s (1990) work on motivations for overseas travel from four countries (Japan, France, West Germany and the 48 The facilities and amenities of tourist products are normally a vital motivation factor for tourist flows. An absence of facilities and amenities may cause a reduction in the number of tourists visiting to enjoy the attractions of an area (Brey et al. 2008). For example, the inability to hire sailing boats in an area noted for sailing possibilities would be a deterrent to that type of tourism. Similarly, an absence of luxury accommodation facilities would deter affluent tourism groups, who are likely to seek extra pampering. Although facilities may form part of the attractions of a destination, they are rarely the sole reason for tourism to it. In the same way, different tourists may have different reasons for choosing Thailand as their destination—but, if they arrive at the resort they have chosen to stay at and find they are not offered the style of services expected from Thai resorts (such as Thai spa massage and Thai food), they may not be satisfied and may not come back to that resort. Those facilities and amenities may not perform as effective resort pull factors. Accessibility is also a crucial component of tourist products. It is related to transport to the destination chosen by the tourist, and it is best interpreted in terms of the amount of time and cost it will take a traveller to reach the destination (Brey et al. 2008). These days, travellers use communication technology, such as the internet and the World Wide Web, to find savings in time and costs. Easy access to hotel websites has become an important consideration for travellers. Ease of access is not restricted to hotel websites but includes other channels (e.g., agent websites) facilitating contact with hotels. In addition to the three factors described above, Middleton and Clark (2001) added two more components. One of these, destination, is discussed in detail below. They divided the total tourist product into five main components: (1) destination attraction (2) facilities 49 (3) accessibility to the destination (4) images people have in mind (5) price—the sum of what it costs to travel, make use of accommodation and participate in different activities. Any destination has particular products or services to offer. ‘Destination’ means the place travellers go; it could be a country, a town, a natural site or a very specific area, such as a resort establishment. Resort hotels are currently the dominant accommodation form within the tourism industry (Inbakaran, 2011) and offer as pull factors features like an attractive location, an appealing climate, decoration, staff courtesy and a wide variety of services for customers that make them feel like ‘guests’. As described by Jones and Lockwood (2002), the hotel product is made up of elements which are related to the physical characteristics of the provision and the interpersonal contact occurring during the stay. This is in accordance with Echtner and Ritchie (1993), who state that the hotel product covers two types of elements: tangible and intangible elements. 3.2.3 Contemporary studies utilising travel motivation Many studies have examined the concept of travel motivation. The purpose of these studies can be summarised into three main areas: (1) to examine travel motivation in terms of the reasons underlying travelling, to see which motivations were more important in someone’s decision to travel and their effect on destination selection (2) to examine travel motivation in terms of push factors affecting tourist behaviour, such as tourists’ satisfaction and tourists’ intention (3) to examine travel motivation regarding its relationship with other aspects, such as tourists’ demographics. 50 With regard to point (1), travel motivation in terms of reasons underlying travelling, Prebensen (2005) examined Norwegian tourists’ perceptions of a place visited and compared them to their motivations and experiences. In the analysis, Prebensen identified eight factors: culture, avoid stress, fitness, accomplishment, sun/bathing, friends, children/family and hedonic. Culture (adventure and knowledge) was found to be a very strong motive for Norwegian travellers. Vandermerwe and Saayam (2008) determined the reasons (the travel motives) tourists visited the park, and identified six factors: nature, activities, attractions, nostalgia, novelty and escape from routine. Vuuren and Slabbert (2011) studied the travel motivations of tourists visiting resorts in South Africa, and found that the main travel motivations were resting and relaxation, enriching and learning experiences, participation in recreational activities, personal values and social experiences. With regard to point (2), travel motivation in terms of push factors such as tourists’ satisfaction and tourists’ intention affecting tourist behaviour, Konu and Laukkanen (2009) identified various motivation factors of potential tourists, and assessed the roles of motivation factors in predicting tourists’ intentions to take wellbeing holidays. Correia et al. (2013) explored the concept of push and pull satisfaction and related it to a uni-dimensional measure of satisfaction. Results suggested that overall satisfaction reflects tourists’ assessments of push and pull dimensions of satisfaction. Lee (2009) examined a behavioural model of wetlands tourism, using variables of destination image, attitude, motivation, satisfaction and future behaviour for tourists at Cigu, Sihcao and Haomeiliao in south-western Taiwan. Empirical results indicate that tourist satisfaction has a significant influence on future behaviour, and satisfaction proved a significant mediating variable within this behavioural model. Huang and Hsu (2009) developed the study by examining the effects of mainland Chinese visitors’ travel motivations, past experiences, perceived constraints, and attitudes on their intention of revisiting. Findings indicate that 53 The most widely recognised definition in the marketing field was introduced by Phillip Kotler (1991), who wrote that market segmentation is ‘dividing a market into distinct groups of buyers on the basis of needs, characteristics or behaviour who might require separate marketing mixes’ (in Kotler and Armstrong 2008, p.167). Although there are numerous definitions, they share the same ideas; as noted by Howard and Sheth (1969), segmentation depends on the idea that ‘the company should segment or divide the market in such a way as to achieve sets of buyers’ (in Tynan and Drayton 1987, p.302). Howard and Sheth (in Tynan and Drayton 1987) go on to provide the concept of dividing an entire market into different customer groups on pre-defined parameters. Importantly, those numerous definitions also lead to one ultimate goal: to scrutinise each segment in-depth as a single entity in order to create tailor-made products and services for them. Individual human beings differ, and, in terms of consumers or buyers, Baker et al. (1998) claim that the reasons people consume differently are based on factors that may influence customer behaviours, such as culture, social class, reference groups, role and family. Similarly, Kotler et al. (2004, p.345), confirmed that a ‘market consists of buyers, and buyers differ in one or more ways’. Because buyers differ in several characteristics, such as the demographic and geographic aspects—like age, gender, education and country of residence—their attitudes and behaviours towards products also differ. Marketers have to consider these different factors in order to understand the real needs of those different customers. They differ in their needs and wants, and thus they also differ in the way they buy and consume products. As claimed by Tsiotsou and Vasioti (2006), each identified segment group (buyer group) has a unique requirement in consuming products and services. Therefore, it is unlikely that a business working among a variety of customers will survive if its marketing strategy is dependent upon targeting an entire mass market. It 54 is impossible for a business to deliver a feature or set of features which would satisfy every customer. The importance of segmentation is that it is a tool to help businesses precisely reach a customer with specific needs and wants; consequently, businesses are able to make better decisions about marketing strategies and to use their marketing budgets more effectively (Stanton et al. 1995). If the market is well defined and easily understood then it will no longer be a problem to match marketing strategies based on product, price, promotion and place with the unique requirements of customers, in order to achieve their satisfaction. To the contrary, poorly defined market segments will lead to problems later, because marketers will have lost their knowledge about their customers’ needs and will have also lost an opportunity to exercise efficient marketing strategies. Thus, it is sensible to find the variables that split the market into actionable segments. 3.3.2 The major segmentation variables When a marketer arrives at a decision about market segmenting stages, on which bases should segments be classified? Which variables can be used? The consideration of segmentation bases is important because an unsuitable segmentation strategy resulting from poorly defined segmentation variables may lead to misunderstanding of the business’s market. This in turn can result in lost sales and missed profit opportunities. Market segmentation variables are data that reflect unique and specific aspects of a business’s existing and/or potential market and are used to answer specific questions and provide more detailed information regarding existing and potential clients. Considering variable selection for segmentation is a vital task before proceeding to market 55 segmentation. While those categories of variables are adopted as segmentation bases, they are simultaneously used for segment profiling to explain consumers and their behaviours. In other words, they have the advantage of being bases for both segmentation and profiling. Such variables are gathered using information acquisition techniques, which is followed by analysis designed to answer and address a business’s key objectives and concerns. Once the information is derived from the analysis and presented, the business may then have an increased probability of making more sound financial and operational marketing decisions, including in its communication strategy. The consumer literature mentions a wide selection of variables as possible bases for both segmentation (dependent variables) and descriptors (independent variables) of a segment (Tynan & Drayton 1987). One or several variables can be used to segment a market. These segmentation bases are rarely used alone; a combination of two or more is usual. As asserted by Frank et al. (1972), these variables may be grouped into two broad categories, namely, general and situation-specific variables. General variables comprise broad consumer characteristics, such as demographics, personality traits or lifestyle. Situation-specific variables are associated with consumption patterns, such as frequency of usage, brand loyalty, product benefits or perceptual maps. Kotler (1991) went further by giving a more nuanced categorisation of variables, namely, demographics, geographics, psychographics and behaviour. He explained that demographics describe consumers’ personal information, such as gender, age and marital status, while geographics can be explained in terms of climate, population density and whether the area is urban or rural, which all influence customer product needs. Psychographics reflect customer insight in three main ways: personality, motives and lifestyle. Finally, businesses can divide a market according to some features of consumer behaviour towards a product. For example, a 58 just one. For example, research by AMR: Quantum Monitor Service noted that ‘the attitudes and behaviours of 25-year-olds have significant differences between those who are full-time students and those who are unemployed and not studying full-time’ (cited in Baker et al. 1998, p.166). Thus, it is worth noting that while there is support for age being effective as a strong indicator for customer profiling, it is necessary to apply a certain amount of caution before marketing solely on this basis. Tynan and Drayton (1987) noted that there were authors who claimed that in some cases the life cycle concept had proven more useful for segmentation and profiling than the age variable. Life cycle stages can also be a useful measure. These reflect the stages through which most people progress in life, from childhood through to adulthood. As suggested by Tynan and Drayton (1987), life cycle is a composite variable, made up of numerous factors such as age, number of years married, age of children and working status. Hence, life cycle stages have to be considered together with other demographic factors. Gunter and Furnham give the following example: … single people who have a tendency of purchasing new fashionable items due to the fact that they have no other economic obligations. This is opposed to married people, who have a large economic obligation and thereby they prioritize their economy different (Gunter and Furnham 1992, p.11). Furthermore, Middleton and Clark (2001) state that life cycles are associated with behavioural characteristics and buying patterns. They give the following example: 59 … travel behaviour of many people aged eighteen to thirty-five may not vary much according to whether they are single or married, but it is likely to vary enormously according to whether or not they have children (Middleton & Clark 2001, p.116). It may be concluded that family life cycle is important to marketers because it gives them clues about consumer behaviours and buying patterns. Income level is also used to segment markets (Rix 2011). Many companies seek to target high-income customers. Others seek to target customers with lower incomes, in order to gain consumer loyalty and lower competitive pressures (Kotler & Keller 2009). However, some companies try to cover both segments for the purpose of market defence. For holiday flights, Rix exemplified, an airline might target the upper income market with its first-class seats and lower income travellers with its economy class. Although income segmentation is another useful scheme, several authors (e.g., Slocum & Mathews 1970; Myers, Stanton & Haug 1971; Allt 1975) commented strongly that the income variable is the best of the demographic variables for segmenting markets. Some scholars (e.g., Kotler & Keller 2009; Rix 2011) point out that, before considering the income variable in studies or applying it to businesses, one must consider the fact that income does not always predict the most suitable customers for a given product, due to the fact that customers may have other preferences and prioritise their money differently. Therefore, income should usually be combined with other variables in market segmentation, for example, lifestyle and occupation, in order to more completely explain the segment. Apart from the variables already mentioned, many other demographic variables are frequently used in segmentation studies, including education, ethnicity and cultural background. Although demographic variables are the most popular for use in segmentation tasks, there are some controversial issues around its use. Tynan and Drayton (1987) reveal 60 that numerous studies report that demographic variables such as age, sex, income and occupation are not good predictors of behaviour and are of limited value in the formulation of market segmentation studies. This is in accordance with Haley (1968, p.31), who noted that they are ‘not efficient predictors of future buying behaviour, and it is future buying behaviour that is of central interest to marketers’. This is similar to Rix’s (2011, p.127) argument that ‘even though demographics often correlate with behaviour, they themselves are not [the] cause of behaviour and do not explain it’. Demographics rely on descriptive rather than causal factors. This may imply that demographics variables are more appropriate for the purpose of profiling than as a basis of segmentation. Moreover, demographics profiling is normally combined with other types of segmentation variables, for greater plausibility. 3.3.2.2 Geographic variables Geographic segmentation subdivides the whole market based on location (Rix 2011). Rix indicated that particular locations do reflect differences in climate, population density and urban rural area characteristics. These have an impact on customer product needs. It is reasonable to segment according to geographics, due to the fact that the purchasing behaviour of customers is influenced by where they live and work. Pride et al. (2006, p.118) declared that regions could reasonably be classified as market segments because ‘one or more geographic variables can cause customers to differ from one region to another’. For example, people who live in urban areas may tend to prefer small economical cars to multipurpose vehicle models which have higher fuel consumption, as a result of traffic conditions. Therefore, automobile companies could efficiently target markets by defining the right market segment in the first place. Living in one particular region is basically linked to differences in cultural background; customers’ 63 Typically, all segment variables, on the basis of function, are utilised either as (1) segment bases or (2) segment profiling. Behavioural and psychological variables should, rather, be used to segment customers into groups in relation to their similar behaviour or psychological features. Demographics and geographics are more appropriate for use as supplements for gaining a richer segment profile. 3.3.3 Benefit segmentation versus psychographic segmentation Segmentation is a widely accepted and effective method for examining tourist behaviour. Behavioural segmentation, as mentioned earlier, allows markets to be divided based on the way they respond to, use or know of a product. Therefore, behavioural segmentation can group customers based on occasion, usage, loyalty and benefit sought. Benefit sought is an important way of grouping behaviours for segmentation. Haley (1968) proposed benefit segmentation to be more effective as a determinant of behaviour than other techniques, such as demographic, geographic and psychological segmentation. Likewise, Kotler and Turner (1993) agreed that benefit segmentation is acknowledged as a powerful method of grouping customers. Benefit segmentation was first introduced by Russell Haley in the late 1960s. Based on his definition, benefit segmentation is a technique for identifying market segments for a particular product in terms of those who want the benefits the product offers. The belief underlying this segmentation strategy is that ‘the benefits which people are seeking in consuming a given product are the basic reasons for the existence of true market segments’ (Haley 1968, cited in Moriarty & Reibstein 1986, p.465). That is the reason benefit sought is arguably the most logical method of segmentation. The aim of benefit segmentation, as Hsu et al. (2008, p.99) assert, is ‘to determine what benefits customers are seeking from particular products and services’. They define benefits 64 as ‘what the product’s features (any fact about the product or service that can be offered or demonstrated) will do for or give to the prospect’. Frochot and Morrison (2000) indicate that normal benefit statements derived from tourism contexts include: • to get away from everyday life routine • to be with friends • to develop knowledge and abilities • to release tensions/stress • to experience tranquility and solitude • for social recognition • to meet new people • to do nothing • to experience new cultures and places • to experience something authentic • to satisfy curiosity. Since Haley’s proposal, a body of research has been developed which employs benefit segmentation with the aim of understanding visitors’ behaviour, motivations and specific needs. It is logical to segment a market on the basis of the different benefits that customers want from a product or service. A number of studies on benefit segmentation in the field of tourism have been undertaken. Froucot (2005), Molera and Albaladejo (2007) and Park and Yoon (2009) identified benefit segments of tourists in the context of rural areas, while Hu and Yu (2007) studied benefit segmentation for craft selection criteria and shopping. Furthermore, Huang and Sarigöllü (2007) profiled tourists to the Caribbean and suggested four segments based on benefits sought. There have recently been studies on specific tourism products such as national parks and resorts (e.g., Galloway 2002; Inbakaran & 65 Mervyn 2005; Beh & Bruyere 2007). Yoon and Uysal (2005), Saayman et al. (2009), Van der Merwe et al. (2011) and Rudež et al. (2013) completed benefit segmentation research in coastal destinations. Frochot and Morrison (2000) claim that benefit segmentation research can be classified in three main ways, depending on what type of benefit statements are used. They are: (1) research that uses motivations (2) research that uses destination attributes (3) research that maintains mixed benefits, both attributes based and motivations based (cited in Pesonen et al. 2012, p.71). As can be seen, the difference between psychographic segmentation and benefit segmentation is sometimes not clear; in fact, the methods overlap. According to Kotler and Keller (2009), psychographic segmentation buyers are divided into different groups on the three mains bases of personal traits, lifestyle and values. In tourism segmentation this has meant using motivations (e.g., Bieger & Lasser 2002; Li, Xu & Weaver 2009), benefits (e.g., Moleara & Albaladejo 2007) or attitudes, interests and opinions (the AIO model) (e.g., Gonzalez & Bello 2002). Evidently, there have been some mixed interpretations of motivations and benefits sought. For this study, motivational segmentation is regarded as segmentation based on push factors, whereas benefit sought is one of the pull factors. This research should be considered to be based on psychographic segmentation rather than benefit segmentation. 68 attraction. Likewise, Mehmetoglu (2007) investigated the relationship between four groups of trip activities and the daily expenditures of a sample of visitors at two nature based attractions in northern Norway. Two segments, which accorded to two different locations, were grouped in advance using prior knowledge that some differences existed between those two places. Chhabra (2010), who was interested in generation Y as an a priori segment, investigated generation Y members’ perceptions of authenticity that influenced their decisions to become heritage tourists. The starting point was an existing subgroup, generation Y, of the population of tourists, and predicted differences between a heritage tourist and a non-heritage tourist derived from response based research afterward. Another way researchers can investigate tourist segmentation is by using the posteriori approach. In contrast with the a priori approach, the posterior approach does not allow the researcher to use prior knowledge for tourist segmentation. Rather, information to partition the segment is derived from data collected in a survey. Researchers that have used this approach include Dallen (2007), who chose a form of posteriori market segmentation to understand the attitudes of tourists and local communities towards using the Looe Valley Branch Railway Line in the United Kingdom, revealing five segments. Kim, Lee and Chon (2010), who emphasised only the group of Hallyu (the Chinese term for the Korean cultural wave) tourists, grouped these tourists into data driven segments according to their preferences for Korean wave products. Furthermore, short-term visitors of mountainous destinations in Greece were the centre of interest for Tsiotsou and Vasioti (2006), who examined the potential differences in loyalty formation processes across different demographic groups of ski resort customers. Konu (2010) concentrated his investigation on Finnish wellbeing tourism segments, based on factors connected to tourists’ lifestyles, which were gathered from a survey. Focusing on resort hotel tourists, Inbakaran et al. (2011) grouped visitors based on their selection reasons and preference for resort 69 destination, identifying four clusters. Again, such information had been derived after data analysis. Apart from types of segmentation approaches, which are broadly identified as a priori and posteriori, as explained above, categorical variables can be used for the clustering base. All those variables can be classified into one of four major categories: demographics, geographics, behaviour and psychographics. Table 3.1 provides a summary of tourist segmentation research over the last decade—studies which are different in their use of segment method and variable bases. 70 Table 3.1: Tourist segmentation: previous literature Researcher Approach Bases of segmentation Klemn (2002) A priori Demographics & geographic: ethnic minorities Israeli (2002) A priori Demographics: disabled and non-disabled Jaffe & Pasternak (2004) A priori Geographics: destination (inbound and outbound tourists) Jensen (2006) A priori Demographics: nationality Mehmetoglu(2007) A priori Geographic: region Chhbra (2010) A priori Demographics: generation Tsiotsou & Vasioti (2006) Post hoc Behaviour: loyalty Dallen (2007) Post hoc Psychographics: attitude Mimi, Zhuowei & Cai (2009) Post hoc Psychographics: motivation Kim, Lee & Chon (2010) Post hoc Psychographics: preference Konu (2010) Post hoc Behaviour: lifestyle Inbakaran et al. (2011) Post hoc Psychographics: preference, motives Pesonen, Laukkanen & Komppula (2011) Post hoc Psychographics: benefit sought Kim et al. (2011) Post hoc Psychographics: benefit sought Typically, previous research using priori segmentation uses geographic and demographic variables as their market bases. The posteriori approach, on the other hand, has been extensively found to exploit psychographic and behavioural bases. Previous research on tourist segmentation can be considered to have been classified in various ways, such as whether an a priori or post hoc model has been used or variables the segments are based on—demographics, geographics, behaviours or psychographics. This research used post hoc and psychographic segmentation. 73 tourist satisfaction can be defined as post-consumption evaluation concerning a specific product or service (Westbrook & Oliver 1991). Thus, if the actual consumption is better than the consumer had expected, this allows positive disconfirmation; in the tourism sector, this would mean that the tourist is satisfied with the tourism products they chose. Extensive studies have established the dependence of satisfaction on tourists’ demographic and behavioural characteristics. For example, Huh (2002) observed the relationship between overall tourist satisfaction and their demographic characteristics and found that there were no significant differences in age, state of origin, educational level and household income, but there was a difference in gender. In terms of behavioural characteristics, Huh (2002) found significant dependence between overall tourists’ satisfaction and their past experience. No significant difference was found in length of stay, membership of group or distance to destination. Conversely, Martin, Bridges and Grunwell (2006) found that age, income and gender distribution in the sample was significantly different, meaning that these factors affected satisfaction. On behavioural characteristics, there was significant dependence in terms of accommodation type and spending. Valle et al. (2006) found no significant dependence between cluster members of tourist groups and demographic variables, including gender, occupation, marital status and type of lodging, but they found that educational level, nationality and age were significantly dependent. Valle et al. also reported significant variation in the cluster membership on the bases of length of stay in destination and mode of transportation. Apart from studies of the relationship between a tourist’s overall satisfaction and their demographic and behavioural characteristics, other studies regarding tourists’ satisfaction have been conducted in a different manner. For example, Esu and Arrey (2009) did not 74 investigate how tourists’ demographic and behavioural characteristics impacted on their satisfaction; instead, they explored the relationship between a tourist’s overall satisfaction and the attributes of their destination, in that case, cultural festival attributes. Dominici and Guzzo (2010) evaluated both the overall customer satisfaction level for the hotel and the customer satisfaction level for each service supplied. Customer satisfaction practices can assist hotel providers to identify the crucial elements affecting customers’ purchasing experiences as an indicator to measure hotel performance. Moreover, customer satisfaction is the starting point to build customer loyalty. Research regarding guest satisfaction, which translates into the consideration of post-purchase behaviour, such as repeat purchase (i.e., whether or not customers will return to a hotel), is pivotal to the success of a hotel business. Neglecting to pay attention to guest satisfaction leads to negative evaluation of the hotel and restricts the chance of repeat patronage. 3.4.2 Customer loyalty Similar to customer satisfaction, the marketing literature recognises the concept of customer loyalty as one of the most important indicators of business success. In terms of destination potential and competitiveness, striving for loyalty has been deemed to be highly important within a tourism context (Neuts et al. 2012). ‘Customer loyalty’ is defined as: a deeply held commitment to re-buy or re-patronize a preferred product or service consistently in the future, which causes repetitive same-brand or same-brand set purchasing, despite any situational influences and marketing efforts that might cause switching behaviour (Oliver 1999, p.34). Dick and Basu (1994) identified four loyalty categories: 75 (1) real loyalty (positive attitude and high repeat patronage) (2) latent loyalty (positive attitude but low repeat patronage) (3) spurious loyalty (high repeat patronage but low attitude) (4) no loyalty (low on both dimensions). Undoubtedly, the first kind of category is preferable because the tourist is likely not only to continue their patronage of the resort by revisiting it but also to share news of their positive attitude, via word of mouth. Especially in the tourism sector, having customers with real loyalty delivers a great competitive advantage to the international market. In the last two decades, tourism and leisure researchers have incorporated the concept of consumer loyalty into tourism products such as destinations or recreational activities (Selin et al. 1988; Blackman & Crompton 1991; Pritchard & Howard 1997; Iwasaki & Havitz 1998, 2004; Mazanec 2000; Baloglu 2001). Generally, tourist loyalty is assessed in one of the following three ways: (1) intention to continue buying the same product at the same rate (2) intention to buy the same product at a greater frequency (3) willingness to recommend the product to others (Hepworth & Mateus 1994). Different tourism products (e.g., airlines and destinations) can apply the same loyalty measurements scheme. Chen and Gursoy (2001), for example, measured airline tourist loyalty, while Chi and Qu (2008) assessed destination loyalty. These researchers focused their works on different tourism product types, but they used the same indicators to measure tourists’ loyalty—that is, the intention to repurchase and the willingness to recommend to others. Similarly, this present research takes one of those three indicators (intention to revisit) as the measurement of resort hotel tourists’ loyalty. 78 Figure 3.2: Conceptual framework Where they choose to go Experience of visit and response to it By Baloglu & Shoemaker 2001, Yoon & Uysal 2005 Why they go ByCrompton19By Kotler 1 Resort hotel attributes  Attractions (both in terms of tangible and intangible)  Facilities/ame nities  Accessibility Geographic Behaviour  Nationality/region Demographic  Gender  Age group  Level of education  Household characteristic  Occupation  Income Evaluation/satisfaction on destination choice (resort hotel attribute) Intention to revisit *Push factors Inner forces  Escape  Self-exploration  Relaxation  Prestige  Regression  Kinship relation  Social interaction  History of resort visiting  Usual length of stay  Source of information Tourist segments **Pull factors Note: * Red highlighting refers to the factors which are used for cluster segmenting. ** Yellow highlighting refers to the factors which are used for cluster profiling. 7 8 79 Each component of the framework was selected on the basis of the literature review for the purpose of understanding tourist segments in the resort hotel industry in Thailand. The framework has been broken down into three separate sections: (1) travel motivation (push and pull factors) (2) tourist segmentation (3) tourists’ experiences and their responses. First, travel motivation theory was utilised in the first phase of this research. In order to gain a proper understanding of tourists in various dimensions, particularly relating to their needs and wants in terms of what the resort hotel is offering, their tourist travel motivations should first be highlighted. As stated by Cai (2002), Klenosky (2002) and Jang and Wu (2006), understanding what motivates tourist travel behaviour and destination selection is crucial to predicting their travel decisions and future travel patterns. Therefore, hoteliers need to determine why tourists decide to travel, and where they choose to go (e.g., what those destinations look like). For this study, destinations were narrowed down specifically to resort style hotels where tourists chose to stay while on holiday in Thailand. Of the theories proposed by scholars, Dann and Crompton’s push–pull model is the most appropriate to apply to this research, because other theories do not introduce an external factor to the model but emphasise only internal factors of tourists. External factors, where they are associated with the destination choice of tourist, are also important as they explain what the features of destinations where tourists choose to go should look like. Information with respect to external forces is required, especially pull factors of resorts that draw tourists to them. Such information will benefit resort businesses, because if they know which kinds of hospitality products and services customers value, they can create and provide those products and services in their resorts to attract and retain guests. For this 80 reason, this research uses the model providing external factors (pull factors), that is, the push–pull model. The push–pull model, which posits that people are pushed by their own internal forces to travel while at the same time being pulled by the external force of destination attributes, has been widely used because of its approach to exploring the underlying behaviour for motivations (Baloglu & Uysal 1996). Crompton expanded Dann’s basic ideas by classifying push factors into seven main motives: escape, relaxation, self-exploration, regression, prestige, kinship relationships and social interaction. These motives form the bases of tourist segments in the following phase of the study. Second, turning to tourist segmentation, previous studies, as suggested by Kotler (1991), reveal that tourists can be efficiently segmented based on several criteria: demographics, geographics, behaviour, and psychographic or psychological dimensions. This section looked at how tourist segments are profiled. For this study, based on Kotler’s segmentation categories, demographic variables include gender, age, education, household type, occupation and income. Behaviour variables are covered by frequency of visitation, length of stay and the resorts’ information sources. The last variable in this study is associated with geographics and refers to tourists’ nationality. Apart from using these variables to define each segment and explain its characteristics, pull factor variables were used to demonstrate differences among those segments. Many studies have used destination attributes (pull factors) to classify tourists into groups, but, despite the popularity of pull factors, there is no set of destination attributes that is universally accepted. Therefore, for this study pull factors were used only to describe which resort attributes tourists preferred, not to segment tourists into groups. However, according to Jeffries (1971) pull factors can be considered in three main ways: 83 Chapter 4. Methodology In reality it has not always been easy to undertake research according to a fixed number of steps; however, it is helpful to have a structured idea of the way to work through the main elements of designing and implementing a plan for research. This study, therefore, made use of guideline steps offered by Neuman (1997, p.13). Figure 4.1: Steps in the research process Source: Neuman (1997, p.13) Figure 4.1 shows three elements that refer to the research methodology: step 3, design study; step 4, collect data; and step 5, analyse data. This chapter explains those three major elements of the design process, which take the form of decisions to be made about the following issues: 3. Design study 6. Interpret data 2. Focus question 1. Select topic 4. Collect data 5. Analyse data 7. Inform others THEORY 84 • Which research strategies will be used (i.e., what is the form of the logical underpinnings to the research)? • Which types and forms of design will be used and what is the time dimension in the research process? • Which sources of data will be used? • Which main methods of data collection will be used? • Which methods of data analyses will be used? The above questions are clearly answered within this chapter. 4.1 Research strategies (deductive and inductive approach) A research strategy is a methodology that helps the researcher to investigate the research issue. According to Saunders et al. (2003), the research strategy is a general plan that helps the researcher to answer the research questions in a systematic way. Researchers have two broad methods of reasoning when doing their research: deductive and inductive approaches. 4.1.1 Deductive approach Deduction is the process of drawing conclusions from rational and logical principles; induction is essentially the opposite of deduction (Lee & Lings 2008). Deduction always refers to working from the more general to the more specific. As Figure 4.2 below illustrates, a researcher might begin by identifying a theory about a topic of interest and then narrow that down into more specific hypotheses that can be tested. Collecting observations to address the hypotheses leads to even further narrowing 85 down by testing the hypotheses with specific data to determine whether or not a confirmation of the original theory is possible. Figure 4.2: Way of thinking in the deductive approach     Source: Adapted from Babbie (2010, p. 22–23) 4.1.2 Inductive approach Inductive reasoning works another way: by moving from specific observation to broader generalisation then theorisation. Inductive reasoning begins with specific observations and measures. Patterns and regularities are detected, and then the researcher formulates some tentative hypotheses that can be explored, and finally ends up developing some general conclusions or theories, as shown in Figure 4.3. Theory Hypothesis Observation Confirmation 88 of 320 respondents. The hypotheses were deduced from existing theory, and these then guided the process of data collection, so this study can be classified as taking the deductive approach. 4.2 Types of research design Which research design is best suited for the research question is one of a researcher’s most discussed issues before they commit to undertaking a project. There are normally five different types of design to consider: experimental design, cross-sectional or survey design, longitudinal design, case study and comparative design (Bryman 2008). Each type of research design was considered in order to determine the most appropriate for use in this study. A brief explanation of each type follows. 4.2.1 Experimental design Experimental research is conducted mostly in laboratories. The principal advantage of experimental design is that it provides the opportunity to identify cause-and-effect relationships (Montgomery 2012). Experiments are typically structured in terms of independent, organism and dependent variables. The independent variable is a manipulated environmental stimulus, the organism variable contains more or less stable characteristics of the organism (e.g., sex, race), and the dependent variable is behavioural and reflects the influence of the independent and organism variables. The general objective in experimental research is to define the relationship between the antecedent (independent and organism) variables and the consequent (dependent) variables. Experimental designs are quite common in sociology and are usually considered strong because they allow the researcher to control variation in the independent variables and then observe variation in the dependent variables. The change in those dependent variables can be observed in two ways: (1) between the control and experimental group and (2) between the pre- and post- treatment time period (Montgomery 2012). 89 4.2.2 Cross-sectional design One of the most common and well-known research designs is the cross-sectional study. Bryman (2008, p.44) emphasises a number of elements of this type of research design. Cross-sectional design involves: • more than one case. Cross-sectional research is interested in variation, which can exist in many forms: people, families and organisations, for example. Variation can be established only when more than one case is being examined. Therefore, cross-sectional research must observe variation in the relevant variables by studying multiple cases. • a single point in time. Data on the variables of interest in cross-sectional design research are collected simultaneously. A respondent completes a questionnaire with many variables, and so all answers are provided at one time. • quantifiable data. It is essential to have a systematic method for gauging variation in order to establish variation between cases. One of the advantages of quantification is that the research will contain a good, consistent benchmark. • patterns of association. It is difficult to draw causal inferences from research based on a cross-sectional design, as cross-sectional research examines only relationships between variables. 90 4.2.3 Longitudinal design With a longitudinal design, the sample is surveyed at least once more after the initial survey. Longitudinal research involves studying the same group of individuals over an extended period of time. Data is collected at the outset of the study, and data may then be gathered repeatedly throughout the length of the study (Menard 2007). In some cases, longitudinal studies can last several decades. It is usually an extension of cross-sectional research, and it may allow causal inferences. 4.2.4 Case study A case study is an in-depth study of a particular situation, rather than a sweeping statistical survey. It is a method used to narrow down a very broad field of research into one easily researchable topic. There are multiple definitions and understandings of the case study method. According to Bromley (1990, p.302), it is a ‘systematic inquiry into an event or a set of related events which aims to describe and explain the phenomenon of interest’. The unit of analysis can vary, from an individual to a corporation. While there is utility in applying this method retrospectively, it is most often used prospectively (Bromley 1990). Data come largely from documentation, archival records, interviews, direct observations, participant observation and physical artefacts (Yin 2003). Case study research is not confined to a study of a single case; multiple-case designs have become increasingly common in business and management research (Yin 2003). The results generated from case study design are often difficult to generalise to larger populations (Yin 2003). Lee, Collier and Cullen (2007) suggest that particularisation, rather than generalisation, constitutes the main concern of case studies. According to Yin (2003), a case study design should be considered when (a) the focus of the study is to answer ‘how’ and ‘why’ questions, (b) you cannot manipulate the behaviour of those