The contribution of economic, social and environmental factors to life and tourist satisfaction

Jarvis, Diane (2016) The contribution of economic, social and environmental factors to life and tourist satisfaction. PhD thesis, James Cook University.

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The world faces many different challenges such as climate change, refugee flows, terrorism, and the ongoing consequences of the global financial crisis. In response, many governments aim to foster economic growth, regarding GDP as an indicator for overall progress and a proxy for overall well-being.

However, research has shown that increasing GDP does not necessarily increase the levels of well-being or life satisfaction (LS) experienced by individuals, particularly within the developed world. Many different factors influence an individual's wellbeing; these factors are interrelated together forming a highly complex, dynamic system of which economic activity is just one part. A focus on GDP means that other factors that may contribute equally, or even more, to overall well-being than GDP may be ignored.

Economics is traditionally the science of choice and provides many tools and methods to consider trade-offs and choices; these methods work particularly well when considering trade-offs between priced goods or services, but it is more difficult to assess trade-offs between non-priced items. Difficult, but not impossible. Economics focuses on utility (historically assumed only measureable in ordinal terms), and revealed and stated preference valuation methods (such as contingent valuation and choice modelling) were developed to monetise the values of non-market goods.

That said, these traditional valuation methods restrict the researcher to investigating just a small part of the picture (perhaps looking at choice between option 1 rather than option 2) rather than taking a more holistic approach (whereby many different options are considered within the analysis). More recently it has emerged that LS can be used as a (cardinal) proxy for 'utility' which negates the need to rely on valuation methods that assume utility is only measurably ordinally and which allows researchers to take a more holistic view of 'value'. LS researchers seek to understand more about factors affecting people's overall LS – often regressing LS against a wide range of explanatory variables to determine which factors contribute most/least to LS.

The LS literature focuses on explaining variations in satisfaction with life to inform social policy, but the insights gained from this research approach need not be restricted to social policy. The LS approach is likely to be a useful tool for industry to evaluate customer satisfaction in commercial enterprises. Analogously, marketing studies sometimes rely, like non-market valuation studies, on techniques such as choice modelling, to identify key factors contributing to customer satisfaction. Despite similarities (in both the underlying concepts and the methodologies adopted) between the study of what makes individuals satisfied with their lives (and thus what trade-offs they must face), and what makes customer satisfied with their purchases/choices in the commercial world (and thus what trade-offs they must face), as far as I am aware, no-one has investigated both using a conceptually parallel approach to see what lessons can be learnt from the comparison.

The overall aim of my thesis is thus to improve our understanding of the trade-offs that arise within complex interlinked social-economic-environmental systems. I focus on both trade-offs for social policy and trade-offs for industry. The region of Queensland, Australia, including urban and rural areas, adjacent to the Great Barrier Reef (GBR) is used as a study area primarily because of its natural beauty and abundance of resources which presents numerous trade-offs for assessment. The local economy, for example, is focused around three industries, mining, agriculture and tourism, all of which are based on using the environment, in sometimes competitive ways.

The thesis addresses four specific research objectives to fill a number of identified research gaps. Objectives one and two focus on the commercial sector, using tourism as the case study industry, investigating tourist trip satisfaction. Objectives three and four focus on the public sector, investigating residents LS.

Objective one is addressed in Chapter 3. First, I investigate the determinants of tourist trip satisfaction (TS). The insights I concentrate on here are those relating to the potential impact of climate change on tourism. Using (secondary) survey data collected from tourists visiting the GBR catchment region, I find that economic, social and environmental factors all influence TS, along with factors specific to the visit. I found that the relationship between maximum temperatures and TS is non-linear; it has an inverted U shape, with the average maximum daily temperature that optimises TS found to be just above 29 degrees centigrade. This finding could have significant implications for the tourism industry, across the world. Global warming could result in a redistribution of tourists between regions, with hotter regions suffering due to the negative relationship between temperatures and trip satisfaction above 29 degrees, whilst currently cooler regions benefit from the positive relationship between maximum temperatures and tourist satisfaction at lower temperatures.

Objective two is addressed within Chapter 4, using the same dataset as Chapter 3. To determine how changes to factors impacting TS may subsequently affect the likelihood of tourists returning, a two stage ordinal regression with instrumental variables is applied to estimate the TS model. Ordinal regression is then used to estimate the model explaining variations in the likelihood of the tourist returning with TS as one of the explanatory variables. A significant positive relationship is found between TS and the likelihood of repeat visits, whilst TS is found to be influenced by environmental, social and economic factors, in addition to income, whether the tourist visited the Reef and whether they had just arrived in the region. These relationships were then used to estimate a financial value for the impact (in terms of lost revenues from reduced numbers of returning visitors) that could result from deterioration in any factors that influence TS. A deterioration of 10% in perceptions of crime, or intensity of construction work, or water turbidity (with all other factors held constant) is estimated to reduce the tourism income generated in the regional economy by between $300,000 and $400,000 per annum.

Objective three is addressed in Chapter 5, using (secondary) survey data collected from residents of the Wet Tropics World Heritage Area. Principal component analysis is used to group different factors that may explain variations in LS into separable discrete categories, based on subjective data regarding the importance of, and the satisfaction with, these factors. Geographically weighted regression (GWR) is used to estimate a LS model including the composite variables calculated from the groupings, finding that significant composite variables represent the social, environmental and economic domains, and finding significant spatial variations in the factors contributing to resident LS. Social factors have the strongest impact on LS across the region; but the second strongest influencer is the environment in the northern and central sections of the region, and income for the south of the region. These variations in preferences were found to correspond to the electoral boundaries that existed prior to the fairly recent local government amalgamations. It was apparent that those successful amalgamations comprised combinations of regions with fairly homogenous preferences whilst the unsuccessful amalgamations (that were subsequently reversed) tried to combine residents with very different preferences. Thus improved understanding of spatial variations in preferences gained from the LS approach could provide clear benefits if used to inform discussions regarding the redrawing of electoral boundaries or amalgamating existing electorates.Objective four is addressed in Chapter 6, using (secondary) survey data collected from residents of the GBR catchment region. Variations in the LS of residents are explained using GWR to specifically identify and evaluate the spatial heterogeneity of values within the region, including a composite variable derived from exploiting principal component analysis to represent the satisfaction of residents with the cultural ecosystem services provided by the GBR. Cultural ecosystem services comprise a wide range of values including existence and bequest constructs that arise from people's beliefs or understandings. Significant spatial variation is found in the residents' values, with those of the north appearing to gain relatively more satisfaction from the cultural ecosystem services (and less satisfaction from income) than residents of the south. The coefficients from this LS model are used to estimate the compensation required to maintain current level of resident LS should there be a decline in their satisfaction with these cultural ecosystem services, finding that the cultural ecosystem services provided by the GBR contribute to resident LS, with an estimated value of around $8.7 billion per annum. This study indicates that the LS valuation approach offers promise as an alternate method for estimating the hard to monetise non-market non-use values.

Overall, the key findings are that factors from all domains of life – social, environmental and economic – are important to trip and life satisfaction. Of these, economic factors are frequently the least important in explaining LS, although significant spatial variations exist in the significance and magnitude of impact that the different explanatory factors have. Distinct spatial variations are found – income is more important to residents in the south of the study region whilst for those in the north, social and/or environmental factors are more important.

The LS approach has been demonstrated as a highly versatile tool, enabling us to better understand what truly makes people satisfied with their lives or purchases; my findings reveal that different things contribute differently to the satisfaction of different people in different places. Thus a national or international focus on increasing GDP is unlikely to meet the preferences of most people; local solutions focused on the local preferences and choices of people in particular areas are much more likely to improve the welfare of the people. Similarly, commercial organisations are likely to find that a better understanding of the preferences of their customers, and the spatial variations within these, will enable them to differentiate their service offering and thus best satisfy the preferences of those people who comprise their potential customer base.

Item ID: 45681
Item Type: Thesis (PhD)
Keywords: life satisfaction, tourist satisfaction, economic social and environmental domains
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Additional Information:

Publications arising from this thesis are available from the Related URLs field. The publications are:

Chapter 3: Jarvis, Diane (2015) Could climate change redistribute global tourism activity by impacting trip satisfaction? In: Proceedings of the 24th Annual Council for Australasian University Tourism and Hospitality Education Conference, pp. 178-190. From: CAUTHE 2015: 25th Annual Council for Australasian University Tourism and Hospitality Education Conference: rising tides and sea changes, 2-5 February 2015, Gold Coast, QLD, Australia.

Chapter 4: Jarvis, Diane, Stoeckl, Natalie, and Liu, Hong-Bo (2016) The impact of economic, social and environmental factors on trip satisfaction and the likelihood of visitors returning. Tourism Management, 52. pp. 1-18.

Date Deposited: 04 Oct 2016 22:43
FoR Codes: 14 ECONOMICS > 1402 Applied Economics > 140205 Environment and Resource Economics @ 40%
14 ECONOMICS > 1402 Applied Economics > 140216 Tourism Economics @ 30%
14 ECONOMICS > 1499 Other Economics > 149902 Ecological Economics @ 30%
SEO Codes: 90 COMMERCIAL SERVICES AND TOURISM > 9003 Tourism > 900301 Economic Issues in Tourism @ 35%
96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960507 Ecosystem Assessment and Management of Marine Environments @ 35%
96 ENVIRONMENT > 9606 Environmental and Natural Resource Evaluation > 960699 Environmental and Natural Resource Evaluation not elsewhere classified @ 30%
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