Fashioning tourism future for visiting large cities

Abstract

Purpose

Large cities are and will continue to become important tourism destinations in foreseeable future. Tourists' motives of the present is the prognosis for their future tourists' behavior. In respond to the longstanding critics in city tourism study, the present research aims to examine the underlying motives of tourists visiting large cities and offer insights into fashioning tourism future for visiting large cities. The identified motives inform three distinct implications fashioning tourism future of large cities.

Design/methodology/approach

A quantitative investigation was performed by surveying city tourists. Measurements on the survey form were derived from both scholarly and grey literature in relation to tourists' motivations. 326 valid questionnaires were netted to attain the study aim. Three-quarters of respondents were from Europe, Australia and Pacific. Descriptive analysis and exploratory factor analysis were conducted to achieve the research aims.

Findings

Five underlying motives of tourists visiting large cities were revealed: shopping indulgence, urban commons, city icons, cultural and lifestyle and personal advancement. Mapping the findings with a conceptual scheme depicting tourism product in destination, the author revealed a new dimension, urbanity and offered critical reflection on three implications for the tourism future of large cities.

Originality/value

Literature examining city tourists' motives neglect the context-specific measurements while administering the investigation. The research design embraces the urban-specific measurements in the data collection tool, contributing to deeper understanding on how tourism functions in cities. A new dimension, urbanity, which illustrates tourists' motives exclusive in large cities, was identified. Furthermore, three implications fashioning tourism future of large cities are revealed with the support of empirical evidence.

Citation

Lee, L.Y.S. (2023), "Fashioning tourism future for visiting large cities", Journal of Tourism Futures, Vol. 9 No. 3, pp. 381-392. https://doi.org/10.1108/JTF-07-2021-0186

Introduction

The city has come into the spotlight for both academia and the real world. The city environment has emerged as an area of interest for many researchers although not within the tourism discipline (Pacione, 2003). The economic, social and cultural importance of cities is growing. In 1950, one-third of the world's population lived in cities whereas in 2012 half of the global population lived in cities (United Nations Human Settlements Programme, 2013). The level of urbanization will grow to six billion people, or two-third of the entire world's population, by 2050. High levels of urbanization offer opportunities for many forms of economic activities, making the city an important arena in foreseeable future.

Cities began to emerge as formidable tourism destination from the early 20th century due to the variety of activities provided to tourists (World Tourism Organization, 2012). Tourists' spending in cities has increased more than as twice as fast as global GDP (Wong, 2013). Despite the economic ebbs and flows over the past decade, both international tourist arrivals and expenditures have recorded a steady growth since 2009 (Mastercard, 2019). The importance of cities in the real world fosters the establishment of International Journal of Tourism Cities in 2015, an exclusive academic journal dedicated to city tourism studies. Looking into the future, city tourism is apparently a barometer of the tourism industry around the globe.

Studies on city tourism become all the more important as tourism activities are stepped up in the city. Researcher in urban studies (Gospodini, 2001) reported that two aspects of the urban tourism phenomenon, namely urban planning and management issues, have already been well-documented. These aspects however center on spatial issues rather than activities of human. With unbridled growth of tourism, the future of city tourism should move beyond the spatial aspect.

Professor John Ashworth (2012), an eminent city tourism scholar, comments that there is no absence of articles, books and official reports produced in the past several decades in wide ranges of aspects of tourism in cities. Notably, he highlights the insufficient understanding on the critical asymmetry in the relationship between tourism and city. Ashworth (2012, p. 1) denotes “prefixing the adjective urban to the noun tourism gives the activity a spatial context but does not itself define or explain that activity”. Understanding why tourists are motivated in visiting cities is the fundamental question needed to be addressed so as to precisely elucidate the possible interactions between tourism and city as a multifaceted and ever-changing entity.

Large cities are and will continue to become important tourism destinations in the foreseeable future. Tourists' motives of the present is the prognosis for their future tourists' behavior. As a response to the call of Ashworth and the increasingly practical significance of large cities, this study serves as a start in calling for more meaningful research effort in city tourism. The aims of the paper are to examine the underlying motives of tourists visiting large cities, and offer insights into fashioning tourism future for visiting large cities. The greater knowledge cities obtain in understanding tourists motives the greater the capacity of destinations to fashion a strategic tourism future.

Literature review

Understanding large cities

Although cities are important spatial entities, no mutual consensus on the definition of city has been reached. The United Nations defines the city as “an urban agglomeration as the built-up or densely populated area including the suburbs and continuously settled commuter areas, which may be smaller or larger than a metropolitan area” (United Nations Human Settlements Programme, 2008, p. 7). The United Nations also defined cities based on the size of population perspective. Small cities have less than 500,000 inhabitants while intermediate cities have between one to five million inhabitants. Large cities refer to inhabitants numbering more than five million.

The present study focuses on large cities for the following reasons. First, large cities exhibit stronger agglomeration effects in comparison to cities with fewer inhabitants (Combes et al., 2012). Proximity brings merits in numerous ways. Human contacts are essential for sensitive yet valuable information exchange in which the diversity in large cities assembles dizzying combinations of talents. Sizeable population naturally creates centrality where number of consumers could ensure profitability (Timur and Getz, 2009). Thus, the sustained value of human interaction and innovation can be realized, enabling large cities as appealing tourism destinations.

Second, an emerging trend of metropolitan expansion is prevalent (United Nations Human Settlements Programme, 2008). Urban commuters are relocating to suburban locations or satellite towns connected to the main cities. The phenomenon is prevalent in the two economic giant nations, China and India. City regions have been formed around New Delhi, India and along the eastern coastal belt of China. The growth of large cities is major contributor to metropolitan expansion, justifying that city tourism is the future catalyst for tourism research. Thus, the practical significance of large cities foster the present investigation.

Conceptual scheme: the tourism product

To create a desirable city tourism future, the study purports to understand why tourists are motivated to visit large cities. There is no shortage of literature researching tourists' motivations (Pincus, 2004). Motivations tell the reason why an individual or group behave or intend to behave in certain action. Kay (2003) conducts an extensive review on motivation studies. Four main approaches in the examination of motivation were identified, namely needs-based, values-based, benefits sought and expectancy theory. The needs-based approach is the most recognized in realizing tourists' motivations among the four said approaches (Albayrak and Caber, 2018). Murray's (1938) classification of needs theory, Maslow's (1943) hierarchy of needs theory, McClelland's (1955) theory of learned needs and Pearce and Lee’s (2005) travel career patterns model are a handful of examples. Needs that drive individuals to go after what they lack are essential to the existence and well-being of individuals (Taormina and Gao, 2013). Hence, understanding needs could be reckoned as crystalizing the universal necessities of humans. Based on this justifications, the present study considers a needs-based conceptual scheme to guide the investigation.

Understanding tourists' motivations could not be separated from the spatial context (Ashworth, 2012). Prior understanding of what is happening in cities is vital. Globalization has led to a creative turn of cities that the production of service and knowledge dominates (Postma et al., 2017). Plausible reasons include the little investment for major infrastructure change and reshaping urban spaces. Looking into the future city tourism will continue to grow and encounter constant change. The inquiry of how tourists make use of the urban features is the basis of explaining the current state and the future trajectories of urban tourism. Pearce (2010) alerts that tourism research should consider a sound theoretical basis. In response to the call, the present study is underpinned by the tourism product conceptual scheme proposed by Kastarlak and Barber (2014).

According to Kastarlak and Barber (2014), tourists are primarily motivated to travel because of satisfying their recreational and utilitarian needs. Once tourists fulfilled their recreational and utilitarian motives, they would consider their tourism experiences satisfactory. From the destinations' perspective, tourism product consisting of attractions and facilities should be offered to satisfy the two tourists' motives (see Figure 1). Attractions, as the primary magnets inducing tourism demand, should be the focus of the tourism policy agenda. Facilities, offering supporting function rather than inducing growth, depend on attractions. As a result, attractions are designed to satisfy the recreational motives and facilitates are for satisfying the utilitarian motives of tourists. The tourism product theory delineates that both attractions and facilitates are intended to serve tourists visiting the destinations. Notably, it presumes that the competitive power of a tourism destination is highest where the quality and diversity of tourism product are greatest. The conceptual scheme underlines the recreational-utilitarian dichotomy as guiding principle for tourism policy planning.

The author would like to offer constructive critiques on the conceptual scheme. First, the theory does not specify the context. Since cities are characterized by density and diversity, diverse city users including residents, local visitors, holiday makers, business delegates, consumers cities with varying motives (Ashworth and Page, 2011). Individuals visit cities for wide range of reasons that the conceptual scheme may not be applicable to all city users. Second, in the modern era, tourists are increasingly authenticity-seeking and are moving away from conventional attractions tailored for tourists. The phenomenal expansion of AirBnB is a good example (Paulauskaite et al., 2017). While immersion in localness is well-regarded as a vital element in contemporary travel, the purposefully-built attractions may no longer be the drawcard of generating tourism demand. These constructive critiques reveal the limited explanatory power in the large city context for tourism policy planning. It further informs the research design in collecting insights on tourists' motivations with a stronger context-specific focus in order to enhance the explanatory power of the conceptual scheme.

Research method

Quantitative inquiry was adopted for the following reasons. Tourist motivation is a longstanding research interest for tourism scholars as it legitimates tourists' behaviors and proclivities (Novelli, 2005). Motive is an internal factor arousing, directing and integrating a person's behavior (Iso-Ahola, 1980). Although many other variables explain behavior, motives are the starting point that triggers the decision process. Substantial literature investigates tourists' motivation in generic tourism contexts. Ashworth and Page (2011) highlights the fact that motivations of city users should reflect the key elements of the urban. In this sense, the present investigation adopts both items measuring context-specific and non-context specific travel motivations. Since prior understanding on tourists' motivations is notable, quantitative approach was considered as appropriate to further reveal the underlying pattern in the city context.

To achieve the research aim, a self-administrated survey was conducted. The survey consists of three sections. The first section contains one screening question that potential respondents were asked whether they considered themselves as city tourists. Eligible respondents who self-perceived themselves as city tourists were invited to proceed. The second section enquires the motivations of visiting large cities. Items measuring tourists' motivation from both generic destinations and city destinations were consolidated from a range of relevant scholarly literature (e.g. Law, 1996; Spirou, 2011; Page and Hall, 2003) and grey literature (e.g. Glaeser, 2011; Brook, 2013). Given a shorter publishing time comparing with scholarly literature, grey literature is also an important source of information as it captures the actualities in a timely manner (Prideaux and Whyte, 2013). Eventually, a list of 22 motivations travelling to large cities was adopted and respondents were requested to rate their level of agreement on a 5-point Likert type scale where 1 = not at all important and 5 = very important. Demographic information was also collected in the last section.

The survey was undertaken in 2015 at the Cairns International Airport on six weekdays appointed by the airport authority. A research assistant used convenience sampling to approach potential interviewees at the departure hall. If the selected respondent was not willing to be interviewed, the next immediate convenient sampling respondent would be invited and interviewed. In total, 343 people completed the survey. After discarding incomplete data and duplicate entries, 326 valid questionnaires were netted for further analysis.

The collected data would be analyzed in a series of steps, and the entire data analysis process was performed using the IBM Statistical Package for the Social Sciences Version 26 program. Data initially would be screened out missing value or invalid data for further analysis. To begin, the basic descriptive analysis was conducted to obtain a general overview of the respondents' demographic information. An exploratory factor analysis (EFA) using the principal component method with varimax rotation was then run on the 22 motivations traveling to large cities to identify the underlying factors.

Findings and discussions

Demographic profile

Table 1 shows the demographic characteristics and travel party of respondents. In a sample of 326 respondents, more females (58.2%) partook in this study. Europe (40%) and Australia and Pacific (34.6%) were the two largest regions of respondents' place of origin. Respondents were relatively young with around three-fifths of them aged from 20 to 49. Two-fifths of them were bachelor degree holders while a quarter of them had secondary school attainment. AU$31,000 or below (34.5%) and AU$32,000 to $69,000 (27.5%) were the two common annual income ranges. As for the current trip, almost half of the respondents travelled with their couples while a quarter travelled with friends.

Motivations to visit large cities

An EFA using the principal component method with varimax rotation was employed. The detailed EFA results on city destination selection criteria were tabulated in Table 2. Measuring items that exhibited low factor loadings (≤ 0.40), high cross-loading (≥ 0.40) or low communalities (< 0.50) were deleted (Hair et al., 2010). After performing the removal of offending items in a stepwise manner, five factors with 19 measuring items were extracted. The factors explained 60.372% of total variance and all the eigenvalues were greater than 1.0. Cronbach's Alpha, a common index of reliability, was computed to examine the internal consistency of individual factors. The closer the results are to 1.0, the higher the estimate of reliability (Hair et al., 2010). The resultant alpha coefficient ranged from 0.671 to 0.774, indicating adequate internal consistency for all five factors. The Kaiser–Meyer–Olkin (KMO) was 0.822, exceeding the threshold of 0.6 (Hair et al., 2010). The Barlett's test of sphericity was 1,589.219 with a significance of 0.000.

Kaiser–Meyer–Olkin (KMO): 0.822; Barlett's test of sphericity: 1,589.219 at df = 171 with a significance of 0.000. The principal component method with Varimax Rotation; 5-point Likert type scale was used where 1 = Not at all important and 5 = Very important.

The first factor, shopping indulgence, accounted for the largest proportion of the total explained variance (28.044%) with an eigenvalue of 5.328. It contained five shopping-related measurements, such as variety of shopping, trendy fashions and arcades, bazaars and malls. On one hand, most large cities resided along the coastlines or at the strategic locations with high connectivity via sea, land and air (Timmerman and White, 1997; European Environment Agency, 2006). This beneficial condition aided large cities becoming significant trading and distributing places for decades. With the historical factor and gigantic demand, cities always attracted the establishment of variety of brands and flagship shops. Another plausible explanation would be the dominance of younger sample in the present study. Stein (2013) explained that shopping indulgence may come down to personal level. Younger generation does care about personal image building and inflate their egos by flaunting their brand-name possession. This phenomenon was particularly common among the younger generation who were born in peace time. As reported in Table 1, about half of the samples were aged from 20 to 39 years old. The result is therefore not surprising and may explain that shopping is important in both their everyday lives and during travels.

Urban commons was the second extracted factor, explaining 11.645% of the total variance with an eigenvalue of 2.213 and four measuring items. Urban commons are defined as “the perceived public spaces that are found interwoven into the tapestry of the urban environment” (Boydell and Searle, 2014, p. 323). Appealing streetscapes, street art and free activities were inclusive in this factor. The findings echoed with existing literature pointing to the rise of authenticity-seeking tourists. Tourists are conscious about unique and authentic local experience beyond merely consuming quality goods and services. Local markets, public street arts, streetscapes and free activities in cities are arenas of showcasing the contemporary culture and the authentic way of living of the locals. Thus, the happenings in the public space offers interesting landscapes from all walks of life, giving tourists a taste of authenticity. The finding echoes with recent work by Carvache-Franco et al. (2021) that knowing locals' lifestyle is one of the motivating factors for city tourists.

City icons, explaining 8.361% of the total variance with an eigenvalue of 1.589, was the third factor. Four measurements about visiting iconic buildings and attractions, as well as the unique skyline, were included. The city icons, which are widely used from destination marketing collaterals, all kinds of advertisements to tourist guidebooks, are the symbols of a city. For majority of tourists, they would visit the landmarks of the destinations as a must-do item on their trip checklists (Human, 1999). Fuelled with the photo-sharing and check-in functions of social media sites, manifest evidence points to the importance of city icons in the travel business. Travel, as the second most talked-about life event on Facebook, tourists inclined to check-in the places visited during their trip (D'Onofrio, 2013). In 2013, Siam Paragon shopping mall, a massive yet major shopping complex in Bangkok, Thailand, and Time Square in New York, US edged out to become the top two locations on Instagram (2014). These two places coincidentally were the landmarks of the two cities. These evidence in the real world provides strong justification of city icons as motive of visiting large cities.

The fourth factor was culture and lifestyle with four measurements. Explaining 6.999% of the total variance with an eigenvalue of 1.330, the factor was about enjoying the vibrant lifestyle, diversity of cultures and artistic cultural displays in cities. Culture, in an organic nature, is evolving over time (Prideaux and Timothy, 2008). Large cities accommodate individuals with varying cultures and ethnics for living, studying, doing business and traveling. The diversification of cultures is demonstrated in the heterogeneous way of livings and cultural displays. Furthermore, large cities are well-known for 24/7 business hours. The vibrancy of lives in both days and nights is an appealing experience to tourists, especially for those from small towns or rural areas.

Personal advancement, explaining 5.323% of the total variance with an eigenvalue of 1.011 and two measurements, was the fifth factor. It was about seeking for potential education and working opportunities in large cities. As a place with massive flow of economy activity, the city offers a battery of career opportunities across various industries and sectors. In order to support a healthy growth of industry development and succession of talents, a large quantum of education institutions, vocational training schools and universities are established in cities. Besides, the increasing level of globalization, perceiving travel as a necessity and affordability of travels trigger people's craving for international exposure as well as cross-cultural understanding and appreciation (Hjalager, 2007; World Tourism Organization, 2011). The finding was not surprising since over two-fifths of the respondents were aged 29 or below.

Fashioning tourism future of large cities

Understanding the future is based upon empirical evidence (Yeoman and Beeton, 2014). The findings offer empirical evidence that responds to the call of Ashworth and Page (2011), as well as Ashworth (2012) in researching urban tourism with context-specific research design. Mapping the EFA results with the conceptual scheme by Kastarlark and Barber (2014), the author presents a tourism product framework applicable for the future of large cities (see Figure 2). A new dimension, urbanity, is present in addition to the attractions and facilities components based on the empirical evidence (see Figure 2). Looking into the future informs public and private sectors what might happen next. The following section draws together some key implications for the tourism future for large cities based on the current findings and critical reflection by the author.

As informed by the EFA results, urbanity elucidates the urban nature of tourism and the inherent difference from other geographically demarcated tourism destinations. The notion embraced the density and diversity nature of cities with multi-users. The everyday happenings, the presence of multi-users and the city-exclusive landscapes are important constituents of city tourism. The first, second and forth factors, shopping indulgence, urban commons as well as cultural and lifestyle, identified from the EFA are explicit manifestations of urbanity. Shopping facilities and urban commons are originally built to serve local residents for utilitarian purpose that facilitate their everyday lives. The facilities and public space form unique structures that accidently become appealing to tourists. Along the same vein, the population structure in large cities is not purposefully arranged to draw tourists. Cities are filled with people with various cultural and ethnical backgrounds which contribute to the diversity and vibrancy. In short, the urbanity serves both locals and tourists in attaining both recreational and utilitarian motives.

The third factor, city icons, identified in the EFA fits in the attractions component. City icons are unique physical structures intentionally built and arranged to attract tourists. Despite that it is arguable that some iconic landmarks were originally built for non-tourism purpose, they are now used to differentiate cities from one another to a large extent. In addition, the fifth factor, personal advancement, from the EFA is categorized as the facilities component. Availability and aggregation of diverse education institutes, public and private organizations in large cities are for tourists realizing their self-actualization needs. Therefore, it is considered as satisfying tourists' utilization motive.

The past is past. Only the future can be changed and crated. To plan for a better future for tourism cities, a question “how best we can make cities a better place for future major users?” should be addressed. Against this findings, the author posits three critical reflection fashioning tourism future of large cities. First, large cities tourists are primarily motivated by authenticity-seeking while tourist-oriented infrastructure remains necessary. Authenticity moves beyond the tangible and intangible cultural heritage inherited from the past. Contemporary living culture is found to be notable and appealing in the perspective of large city tourists. It is suggested that the placement of tourism facilitates should be decentralized beyond conventional touristy areas. In the future of large cities, facilities should be both attraction and urbanity-oriented so as to serve tourists.

Second, residents are place-makers and drawcard of future large cities. Place-making is how locals “recognize, define and create the places they often call home” (Lew, 2017, p. 450). All place-making practices, including locals' daily mundane, spontaneous interactions, lifestyles, places of running errands and street corners in the neighborhood, are fundamental to tourists attractiveness of places. In the future, residents will continue to play an active role in making their home at the backstage of cities and emerge as an alternative form of tourism practitioners. Tourism literature on place-making, such as community challenges, needs and solutions, has still been little. Future policy agenda should shift away from reproducing attractions but center on engaging residents on place-making. Public and private sectors are recommended to encourage place-making activities and assigned public space as place-making realm.

Third, the socio-material assemblages of diverse ethnic inhabitants in large cities gives meaning to geographic space. People dwelling permanently or temporality in large cities have diverse ethnic and cultural backgrounds. These cultural groups imprint varying values, memories and traditions in tourism destinations. Overtime, the diverse ethnic make-up would transform into interesting and distinct places (Lew, 2017). The places allow locals and tourists to congregate and reveal deeper interconnectedness, reflecting quality public social lives in cities (Sommer and Kip, 2019). Diverse racial mixtures of cities fuel the development of cultural and creative industry. Studies on the value chain of the cultural and creative industry, for instance how tourism map to content creation, production and distribution of cultural and creative goods and services, should be explored.

Concluding thoughts

City tourism is of practical significance given the phenomenal tourism growth in city destinations worldwide. In response to the longstanding critics in city tourism study, the present research aims to identify the underlying motives of tourists visiting large cities. A conceptual scheme depicting tourism product in destination was employed to underpin the research design. A total of 326 valid questionnaires were consolidated to attain the study’s aim. Descriptive analysis and EFA were conducted to achieve the objectives. Majority of them were young adults from Europe and Australia. Upon the completion of EFA, five underlying motives of tourists visiting large cities were revealed: shopping indulgence, urban commons, city icons, cultural and lifestyle and personal advancement. The empirical findings introduced a new dimension, urbanity, to the conceptual scheme.

The study demonstrates contributions to the real world. Policy planning is forward-looking as all the development are prepared for the future. City tourism in the foreseeable future will contribute to grow which requires policy planning in integrating tourism with other sectors or functions in cities. Tourists' motives of the present is the prognosis for their future tourists' behavior because their motives correspond to values provided at city tourism destinations. Public and private sectors in large cities should bear in mind recognizing the bundle of motives of large cities tourists when planning for the future. Three implications for the future large cities should be taken into serious consideration in the tourism policy agenda.

The findings also proffer significant theoretical contributions to tourism literature. Existing tourism literature examines tourist's motives in a narrow focus, such as shopping motivation (Chang et al., 2006) and dining motivation (e.g. Quan and Wang, 2004), or investigated travel motivation of specific segments, for instance, senior travelers (e.g. Lee et al., 2012), ethnic travelers (e.g. King and Gamage, 1994), female travelers (e.g. Li et al., 2011). The literature neglects the context-specific measurements while administering the investigation, which may limit the explanatory power. Whilst tourism occurs in cities as well as other environments, such as rural, seaside, mountain areas, the research designs on city tourism have to reflect the urban characteristics highlighting the distinctive interactions between tourism and cities. To address the longstanding pitfall in research design of city tourism studies mentioned by Ashworth and Page (2011), and Ashworth (2012), the current research design embraces the urban-specific measurements in the data-collection tool. Furthermore, prior knowledge on city tourism relatively centers on generic urban destinations but seldom focusing on large cities. The EFA results offered empirical evidence to reveal the underlying motives of large city tourists. It is conducive in deeper theoretical understanding on how tourism functions and fashions future changes in large cities with increasing importance in the real world.

Furthermore, the complexity of multifaceted cities hinder theoretical progress in this research domain (Lucarelli, 2012). The present study approaches the research domain by adopting a conceptual scheme that explains how tourism destinations offer tourism product to satisfy the motives of tourists. The conceptual scheme has two components constructing tourism product, attractions and facilities. The empirical findings from the present study introduce one new dimension, urbanity, which illustrates tourists' motives exclusive in large cities. It adds value to understand how tourism functions on the city nature and explains the explanatory power of the conceptual scheme. Empirical evidence was presented to justify the significance of urbanity and prompts further investigation on urban commons and place-making practices.

Several limitations are noted. In the present study, most respondents were from the Western countries and established economics. According to IPK International (2016), Asia–Pacific ranks the highest in terms of market share of city holidays, followed by Europe, North America and Latin-America. Thus, the views from Asian city tourists may not be congruent with their Western counterparts. Future studies may center on the perspective of Asian travelers. Besides, the current study did not specify the types of cities in the survey. Cities themselves could be different in nature and offer varying functions, namely historic city, cultural city, business city, sport city, nightlight city, leisure shopping city and the tourist city (Ashworth and Page, 2011). Further investigation may explore insights on tourists' motives into varying contextual situations.

Figures

Figure 1

Tourism product

Figure 2

Tourism product in future large cities

Table 1

Demographic characteristics of respondents (N = 326)

	Percentage (%)		Percentage (%)
Gender		Education attainment
Male	41.8	Secondary	25.8
Female	58.2	Vocational training	9.1
		Diploma	14.8
Place of origin		Bachelor degree	39.9
Europe	40	Others	10.4
Australia and pacific	34.6
Americas	22.4	Annual income
Asia	2.4	AU$31,000 and under	34.5
Africa	0.9	AUS$32,000-$69,000	27.5
		AU$70,000-$99,000	18.7
Age group		AU$100,000 plus	19
Under 20 years old	8
20–29 years old	36.1	Travel party
30–39 years old	13	Couple	45.5
40–49 years old	9.6	Friends	24.5
50–59 years old	13.6	Family with children	10.2
60–65 years old	9.6	Alone	9.9
Over 65 years old	10.2	Tour group	5.6
		Relatives	4
		Club	0.3

Table 2

Exploratory factor analysis on city destination selection motives (N = 326)

Factors	Mean	Factor loading	Communality	Eigen- value	Variance explained	Cronbach's alpha
Factor 1: shopping indulgence				5.328	28.044	0.751
Variety of shopping	3.01	0.760	0.657
Trendy fashions	2.48	0.754	0.680
Experiencing the glamour	2.59	0.678	0.612
Arcades, bazaars and malls	2.99	0.619	0.536
Just relaxing	3.86	0.490	0.435
Factor 2: urban commons				2.213	11.645	0.774
Local markets	3.69	0.793	0.698
Public street art	3.25	0.756	0.679
Free activities	3.90	0.696	0.609
Interesting streetscapes	3.52	0.554	0.679
Factor 3: city icons				1.589	8.361	0.671
Variety of attractions	4.01	0.726	0.622
Enjoying the skyline	3.46	0.635	0.522
Iconic buildings and attractions	3.61	0.628	0.492
Wide range of entertainment	3.66	0.572	0.427
Factor 4: culture and lifestyle				1.330	6.999	0.721
Diversity of cultures	3.41	0.847	0.746
Vibrant lifestyle	3.67	0.720	0.662
Learning about the destination's history	3.69	0.679	0.569
Artistic and cultural displays	3.45	0.469	0.476
Factor 5: personal advancement				1.011	5.323	0.762
Potential education opportunity	2.24	0.859	0.772
Potential working opportunity	2.17	0.839	0.776