Destination Marketing of Australia

Abstract

The efficient targeting of destination marketing depends not only on identifying markets that are currently or potentially “high yielding” but also on the cost effectiveness of marketing expenditure in different markets. At least three different types of yield measures that are relevant to “return” on marketing investment have not been clearly distinguished in the literature. One relates to the expenditure associated with the additional tourism flows generated as a result of the marketing effort—this is a well-used measure. Another relates to the economic contribution associated with different inbound market segments. A third measure relates to the (economy-wide) impact of the visitor spending. The article uses each measure, combined with marketing elasticities, to estimate the return on investment associated with promoting Australia in nine key markets. While Australia provides a context for study, the approach taken and the results have relevance to destination marketing organizations worldwide.

Keywords

destination marketing inbound tourism Australia marketing return on investment

Introduction

Tourism is Australia’s largest services export industry, generating around AU$24 billion in exports (in early 2012 AU$1.00 was approximately equal to US$1.00). Depending on industry definitions, it can also be regarded as Australia’s second largest export market. In 2009–2010, there were a total of 5.7 million international visitor arrivals to Australia, contributing AU$9.5 billion to Australia’s GDP. However, over the past decade, tourism has diminished in importance in the Australian economy and also in the global tourism market. Australia’s share of global tourism has been in decline for more than a decade. The average rate of growth in arrivals, 0.7% a year over the period 2000–2009, is significantly slower than average annual growth rates of 9.4% and 9.1%, respectively, recorded in the 1980s and 1990s (Tourism Australia 2010). Meanwhile the historically high value of the Australian dollar over recent years continues to make Australia a relatively more expensive destination than its major competitors.

Tourism Australia, with its predecessor the Australian Tourist Commission, has been vigorously marketing Australia internationally as a tourist destination since 1967. An important part of its mission is to increase demand for Australia as a destination by building Australia’s profile and reputation as an exciting and desirable leisure and business events destination, driving demand and visitation. The Brand Australia logo features the nation’s most recognized icon, the kangaroo, which helps to ensure instant recognition for Australia around the world. The kangaroo is symbolic of the warmth, boundless energy, and optimism that are integral parts of the brand. The brand identity is featured in all tourism promotion, providing a unifying link across markets and campaigns. The continued existence of Tourism Australia, in its present form and with its present programs, is dependent on government policy and on continuing funding by parliament for Tourism Australia’s administration and programs. Not surprisingly, Tourism Australia has changed its strategies over the years, selling Australia to the world through a combination of brand, consumer, and tactical marketing initiatives, in contexts of changing consumer values, world economic circumstances, and competitor initiatives (Tourism Australia 2010).

The problem faced by Tourism Australia, which it shares with other major destination management organizations (DMOs) globally, is that its inbound tourism market is diverse and the market segments vary in their contribution to the economy. The concept of marketing activity is broader than mere “advertising” or “promotion” activity. In 2010–2011, Tourism Australia’s investment in advertising, promotion, and publicity, films, publications, and distribution totaled AU$86.16 million, slightly down from AU$86.9 million in 2010 (Tourism Australia 2011). Of this amount, AU$81.9 million was allocated to advertising, promotion, and publicity. To allocate its marketing budget most efficiently, any DMO must know the potential growth rates of key origin markets, the marketing elasticities associated with those markets as well as the amount of expenditure associated with the “average tourist” from each market.

Funds spent on marketing activity to generate greater tourism expenditure have an opportunity cost. If marketing budgets are to be allocated efficiently, it is important to estimate the potential “return” on such investment. Given that those market segments that comprise large numbers of visitors and high durations of stay will be associated with the greater return, it is more meaningful to estimate the return on investment per visitor (or visitor night) for key markets rather than for the market segment taken as a whole. Several steps are involved in estimating the return or “yield” on marketing expenditure. For each source market, projecting the return on marketing investment involves

allocating a change in marketing expenditure to each market;

estimating the marketing elasticity of demand by each market for tourism in the host country; and then

estimating the return associated with the tourism flows associated with the increased marketing expenditure allocated to each source market.

Regarding assessment of the return on marketing investment, at least three different, but related, types of measures may be employed.

One measure relates to the expenditure associated with the additional tourism flows generated as a result of the marketing effort. Most empirical assessments of yield use this type of approach.

A second yield measure relates to the direct economic contribution associated with different inbound market segments (contribution to such variables as tourism gross value added, tourism gross operating surplus, and tourism employment). These estimates require the use of a tourism satellite account (TSA) or equivalent model.

A third measure relates to the (economy-wide) impact of the visitor spending, including the impact on gross value added, gross operating surplus and employment. Estimation of the economy-wide economic impacts requires the use of a computable general equilibrium (CGE) model to simulate the outcomes.

These different measures of “marketing return” are seldom distinguished in either the research or industry literature despite the fact that markets targeted and tourism promotion budget allocation and performance may well depend on which measure is adopted. Certainly, it should not be assumed that any key origin market will rank in a consistent way across each of three measures.

This paper has three main aims. The first is to distinguish the different measures of tourism yield that are relevant to estimating the “return on investment” in tourism marketing. The second aim is to estimate the return on investment from a country’s marketing effort to key inbound market segments, using each of the three measures. The country selected is Australia, where there exists sufficient data and model development to estimate key performance indicators. The present focus is on the return on investment associated with promoting Australia in nine key markets. These comprise five origin markets: New Zealand, China, Korea, United Kingdom, United States; three types of travel motivations: holiday, visiting friends and relatives (VFR), and business; and one niche market: backpackers. The final aim of the paper is to explore the implications of the different measures for destination management.

While Australia provides a context for study, the approach taken and the results have relevance to DMOs worldwide. This article is different from conventional studies of the yield from marketing in two significant respects. First, it develops and analyzes new measures of the yield from destination marketing in ways that capture different aspects of the economic outcomes to a tourism destination. Second, it links the analysis of marketing tourism to the measurement of yield, in a way that the impacts of marketing on economic and financial variables can be assessed.

Concepts of Tourism Yield

Until recently, tourism industry focus has been on visitor numbers rather than yield. However, there is now widespread recognition of the fact that tourism visitor numbers have little meaning unless the expenditure injected into the destination is taken into account. The concept of tourism yield is now receiving increasing attention in the research literature. Operational measures of yield have been developed at the level of the firm and regional, state, and national destination management levels (Salma and Heaney 2004; Becken et al 2007; Dwyer et al. 2007; Becken and Simmons 2008; Dwyer and Thomas 2012). A focus on “yield” is recognized to be an important aspect of business strategies to maintain and enhance destination competitiveness (Dwyer et al. 2007). These strategies include new product development and types of destination marketing. As indicated in the following section, an increasing number of DMOs explicitly identify increased expenditure yield as the main objective of their domestic and international marketing activity

In this article, we outline and measure three different concepts of tourism yield. There are many possible measures of yield, depending on what impacts and variables are of interest. Thus, for example, the concept of environmental yield has been used. We set out three related concepts of economic yield. The first of these is very commonly used, while the second and third are new. Both are ways of measuring different impacts of tourism expenditure, on the tourism industry and on the economy as a whole. While new, these measures are solidly based on techniques that are widely used in tourism analysis—the TSA and CGE models. As noted below, the limitations of yield as expenditure have led to the development of these further concepts.

The three yield concepts are as follows:

Yield as Expenditure Injection, the commonly used measure

Yield as Economic Contribution, which measures the impact on the tourism industry itself.

Yield as Economy Wide Impact, which measures the impact on the entire economy

We discuss these in turn.

Yield as Expenditure Injection

Expenditure is the most commonly used concept of yield. It corresponds to the well-known concept of “marketing yield” that is found in the mission statements of many DMOs. The expenditure yield of different markets informs the marketing effort of many destinations worldwide at both national and regional levels. In Australia, for example, the key theme of the Federal Government’s Tourism White Paper is that “Effective niche marketing targeted at high-yield markets will seek to ensure the industry gains optimal returns on tourism investment. By understanding the yield potential of different source markets and segments, the industry will know why and how to target them” (Australian Government 2004, p. 29). The mission statement of Tourism Australia, the agency responsible for marketing the country internationally includes the statement “We are responsible for identifying and understanding the needs and drives for consumer segments that give the greatest return on investment” (http://www.tourism.australia.com/en-au/research/default_research.aspx). At the state level in Australia, the issue of increasing tourism yield has been identified by a number of government tourism bodies as a priority (see, e.g., Tourism Victoria’s Strategic Plan 2002–2006). The stated mission of Tourism Western Australia is to increase visitor daily expenditure and duration of stay and attract more higher-spending tourists. The tourism strategic plan states that “effective marketing targeted at high yield markets should ensure the industry gains optimal returns on tourism investment” (www.tourism.wa.gov.au/…/Strategic%20Plan_2008.pdf). The mission of the Kenya Tourism Board is to offer value-added activities and experiential holidays in order to sustainably increase tourism yield and profits (http://www.wtmlondon.com/page.cfm/Action=Exhib/ExhibID=6743). The New Zealand Tourism Strategy 2010 advocates “a focus on increasing the yield from tourism, over increasing the numbers of tourists that visit” (TIANZ 2003). The Hong Kong Tourism Board has emphasized the importance of attracting high-yield visitors in order to increase the contribution made by tourism to the overall economy (eTurbo News February 5, 2007). Meanwhile, both the British Tourism Partnership and the Northern Ireland Tourism Board have identified business tourism as a key priority on the grounds that “it is at the high quality, high yield end of the tourism spectrum” (British Tourism Partnership 2005, p. 2). More recently, the Ministry of Tourism Malaysia has developed the Malaysia Contemporary Art Tourism 2011 (MCAT 2011) expecting “to attract high-yield tourists, which is anticipated to increase the tourism industry’s contribution towards the economy” (Eturbonews.com, http://www.worldtourismdirectory.com/news/July 06, 2011). All of these “yield” measures appear to be related to the injected expenditures associated with different inbound markets.

While expenditure appears to be the standard measure of tourism yield used by researchers and practitioners, it has several limitations (Dwyer and Forsyth 2008). First, gross expenditure data does not in itself provide information on what goods and services tourists purchase and so gives no indication of the sectors of tourism or the wider economy that receive the sales revenues. Second, tourist expenditure is not an indicator of profitability to firms. Profit comprises only a small proportion of visitor expenditure and is not uniform across industries. Third, gross tourist expenditure is only a partial indicator of the contribution to the economy from the injected tourism expenditure because it includes the import content of the goods and services purchased by tourists. Fourth, in emphasizing expenditure injections, the approach ignores the economic impacts of tourist expenditure. These impacts include contribution to gross domestic (or regional) product, gross value added, and employment. The size of the economic impacts depends on several considerations such as the amount of expenditure incurred, the types of goods and services purchased, and the type of economic model used for the estimates. Fifth, since the focus is on sales revenues, the approach neglects the aggregate costs of providing the services to each segment and may thus provide a misleading basis for marketing strategies at both the firm and destination level. Sixth, the approach does not provide information on each segment’s relative spread of impacts and economic and social benefit to the wider destination. For destinations where enhancing regional economies is an explicit goal of government tourism yield may need to encompass distributional issues at least at the destination management level. Finally, expenditure injections per se tell us nothing about the social or environmental costs and benefits associated with different visitor market segments. There is widespread recognition of the need to develop the notion of sustainable yield to a destination in acknowledgement of the fact that visitors who spend similar amounts of money in a destination may leave very different social and environmental (ecological) “footprints” (Dwyer et al. 2007). Recently, standard expenditure measures have been extended to develop measures of “local expenditure impact” and “pro-poor impact” per visitor by origin market (Dwyer and Thomas 2012). Expenditure measures can also form the basis for estimating tourism’s carbon footprint (Dwyer et al. 2010). Despite these extensions, operationalizing the notion of an “ideal” tourist from a sustainability perspective remains elusive.

The limitations of expenditure measures of tourism yield appear to be relatively un-appreciated in the tourism research literature and in the strategic plans of DMOs. An exception is Tourism Research Australia (TRA). Recognizing that visitor expenditure does not fully account for all expenditure associated with visitation to a destination, TRA converts the expenditure data into measures of “total inbound economic value” (TIEV). TIEV, a proxy measure for tourism exports, is calculated from total trip expenditure by inbound tourists to Australia (derived from the Internal Visitor Surveys and benchmarked to the “International Consumption” series in the Australian Bureau of Statistics (ABS) Tourism Satellite Account (ABS catalogue no.5249.0) and ABS Overseas Arrivals and Departure data (ABS catalogue no. 3401.0). Key assumptions underlying the estimates relate to the treatment of a number of expenditure items derived from the International Visitor Surveys. The following adjustments are made to International Visitor Survey total trip expenditure data:

Deductions

50% of international airfares. This takes account of ticket revenue associated with airlines that does not flow through to the Australian economy.

20% of the value of the non-airfare component of packages and other prepaid items. This allows for commissions at the retail and wholesale levels that accrue to foreign markets.

33% of the average international airfare component by package visitors. It is assumed that package travelers receive a discount due to bulk purchasing by the wholesaler from the airline(s) and the average class of travel for package travelers is usually lower than that of nonpackage travelers (a lower share of business travelers).

Additions

airfare revenue that is spent by airlines on services in Australia (e.g., departure tax, airport taxes, ground handling charges, fuel costs etc.);

TIEV also includes an estimate of the value of goods and services consumed by international visitors in domestic homes (Tourism Research Australia 2006, pp. 14-17).

While not addressing all of the problems relating to expenditure measures of tourism yield, the adjustment of expenditure to TIEV provides more accurate data concerning the economic value of different inbound markets. The type of adjustments required for each type of origin market implies, of course, that the relationship between tourism expenditure and TIEV is different for each of the selected inbound markets. Since TIEV measures are more accurate estimates of the expenditure associated with tourist visitation to Australia than are simple (unadjusted) expenditure estimates, we use these in the analysis below.

Yield as Economic Contribution

A second measure of the return on investment from marketing activity involves estimation of the economic contribution associated with different inbound market segments. For this purpose, a TSA must be used. TSA enables the relationships between tourism and other economic activity to be explored within the national accounts framework, extracting all the tourism-related economic activity that is included in the national accounts but not identified as tourism (Spurr 2006). TSA provide macroeconomic aggregates that describe the size and the economic contribution of tourism consistent with similar aggregates for the total economy, and for other productive economic activities. The TIEV associated with different inbound markets can provide the input to a TSA to estimate the economic contribution of tourists from each market in total, per trip, and per visitor night. Depending on the composition of consumption of the visitors within a market segment, the economic contribution of different market segments will vary, despite their aggregate expenditure amount (or TIEV) being the same.

Use of a TSA enables the analysis to be extended beyond the simple expenditure measure, and beyond the TIEV measure, to estimate the economic contribution of key inbound markets to Australia such as tourism direct gross value added, tourism gross operating surplus, and tourism employment. Drawing on the structure and definitions used in the Australian Tourism Satellite Account (ABS 2010), TSA data were developed for the nine markets examined in the study. This data related to (1) the total tourism expenditure by each tourist, (2) the pattern of tourism consumption of each tourist, and (3) the input–output (I-O) structure of the Australian states and territories. Data for (1) and (2) were from TRA (2010), and for (3) was from the Monash Multi-Regional Forecasting (MMRF) database (Adams 2008).

While a TSA represents an important information base for the estimation of the economic contribution of changes in tourism demand, it is not in itself a modeling tool for economic impact assessment. A TSA measures the economic contribution of tourism, that is, the size and overall significance of the industry within an economy. In contrast, economic impact refers to the changes in the economic contribution resulting from specific events or activities that comprise “shocks” to the tourism system. This should not be confused with the contribution itself.

Yield as Economy Wide Impact

Economic impact implies that the overall change in the economic contribution must take account of any interactive effects that occur across the economy, thus requiring a model to provide the simulations (Dwyer, Forsyth, and Spurr 2004). CGE models recognize that an expanding tourism industry tends to “crowd out” other sectors of economic activity. The extent of these crowding-out effects depends on factor constraints, changes in the exchange rate, the workings of labor markets, and the macroeconomic policy context (Dwyer et al. 2000). Proponents of CGE modeling point out that those economy-wide, interactive, effects should be taken into account in determining the impacts of increased tourism expenditure on a destination. Resource supplies are constrained, and greater resource requirements in one part of the economy will lead to lower use, and output, in other parts of the economy. Prices for goods and services that are used as inputs will be bid up, discouraging production elsewhere in the economy. In countries with a floating exchange rate, when there is an increase in spending in the economy from visitors from abroad, the exchange rate will be bid up, discouraging exports and economic activity in other parts of the economy (Dwyer, Forsyth, and Spurr 2004).

A specific CGE model was developed for this project, based on the widely used MMRF model (Adams 2008). MMRF provides results for economic variables on a year-on-year basis. It employs dynamic properties that have been styled on a national CGE model, Monash (Dixon and Rimmer 2002). It is a recursive-dynamic multiregional CGE model, linking a sequence of single-period equilibria via stock-flow relationships. The model captures the behavior of economic agents in each of Australia’s eight states and territories. In each region, there are twenty-six industries, a representative household, importers and exporters, and a regional government. The model also has a federal government that interacts with economic agents in each region. Production by industries, consumption by householders, and investment are modeled in accordance with conventional economic theory. The eight regions are linked via interstate movements of commodities and factors of production (particularly labor). The model treats producers as operating in a competitive market. Producers choose their inputs so as to minimize the costs of producing a particular quantity of output, subject to a given production technology. Substitution is allowed between commodity inputs from different geographical sources, and between labor, capital, and land. If there is no change in relative prices, producers will vary their inputs in direct proportion to their output. However, if a particular input becomes relatively expensive compared with substitutable inputs, producers will substitute toward the cheaper inputs. Consumers in MMRF are also assumed to be optimizing agents. They choose goods according to their preference pattern and relative prices but are constrained by their amount of disposable income. Details of the model structure and assumptions underlying the simulations are provided in Dwyer et al. (2011).

Within the CGE framework, interactions among industries are simultaneous and dynamic; an increase in one industry could be at the expense of the others. Therefore, the contributions of additional tourism expenditure to tourism industry value added, tourism gross operating surplus (GOS) and tourism employment will typically be very different from the overall impact on the economy, because impacts on other industries are now also factored in. Thus, the economy-wide measures are better measured in the CGE framework, since it explicitly recognizes that resources are limited. Competition for resources is necessary and losers and winners coexist when marketing expenditure attracts more tourists to the domestic economy. Behavioral relationships state how economic agents (consumers, suppliers, investors, and so on) acting in their own best interests can lead to changes in price and income levels. The foundation of CGE models incorporates a detailed industry structure (they can be made as disaggregated as data will permit) and price mechanism, with explicit links among industries as well final demands of an economy. Such a foundation enables estimates of overall impacts on economic activity to be made in the presence of crowding out effects explicitly (Dwyer et al. 2000; Dwyer, Forsyth, and Spurr 2004; Blake, Sinclair, and Gillham 2006).

To obtain yield measures by tourist market segment, the expenditure patterns of visitors were incorporated into the MMRF database explicitly in order to capture the economic impacts of changes in TIEV. These yield measures show the economy-wide impact of tourists from different markets after all industry interactive effects have been accounted for. They thus represent “the bottom line” of the economic impacts of a visitor market to any destination.

Measuring the Return on Marketing Expenditure

Destination marketing and promotion by any destination may be expected to increase inbound tourist numbers and the associated expenditure. The extent to which tourism numbers increase in response to a given change in marketing expenditure depends on the marketing elasticity of demand. In broad terms, elasticity describes the sensitivity of one variable to changes in another variable. Marketing elasticity refers to the responsiveness of sales to changes in marketing/promotion expenditures. In particular, it measures the percentage changes in the targeted variable (e.g., visitor, visitor nights, or tourism expenditure revenue) in response to 1% change in the controlled variable (marketing expenditure). Alternatively, it is the responsiveness of demand to a dollar change in marketing expenditure. The higher the marketing elasticity value, the more responsive injected tourism expenditure is to a given change in marketing expenditure.

Several difficulties challenge researchers in their effort to estimate such marketing elasticity:

It is difficult to measure the extent to which marketing and promotion expenditure influence tourism demand. Establishing cause and effect is not easy. Ideally, any assessment of effectiveness of marketing expenditure should be able to demonstrate that such activity caused an improvement in inbound tourism. Provided that all other variables are identified and held constant, repeated experiments, where the only condition is changing marketing expenditure, would allow us to build up a set of observations about how inbound tourism performance varies as marketing expenditure varies. However, controlled experiments are not possible since we cannot hold all variables except for marketing expenditure constant.

Typically, researchers have used the marketing budget of national tourism offices as a proxy for marketing expenditure. A limitation of using this data base is that the estimated return on investment is tied to the marketing expenditure funded only by the peak international marketing body, in the case of Australia by Tourism Australia (formerly the Australian Tourist Commission), sometimes with the addition of state and territory international marketing expenditures. While this marketing effort is supported by funding from private operators, data limitations have compelled researchers to exclude private sector marketing activity undertaken outside the umbrella of Tourism Australia.

The amount spent on a marketing campaign may not be a good indicator of its effectiveness as the approach to marketing could vary across campaigns and marketing agencies, thus the effectiveness of the marketing approaches are not the same. Marketing campaigns that capture the imagination of consumers and generate sales are not necessarily those that cost the most. A marketing campaign that is less costly than others may still be able to generate more visitation than all the others if the campaign is more effective.

There are great difficulties in modeling the impact of marketing and of separating its effect from the other major influences on tourism demand. Even if marketing expenditure can be estimated accurately across different origin countries, which is often difficult to do because of data limitations, marketing expenditure per se does not indicate that the promotion is effective in attracting tourist visits. The effectiveness of marketing campaigns depends on their ability to engage the potential consumer rather than the expenditure undertaken. Different nationalities and cultures are likely to respond differently to marketing and different destinations vary in their ability to use marketing effectively to attract tourists. Few studies have attempted to model these differences in tourism and little is known about the likely directions of the differences (Crouch 1995).

Potentially, there is a delay effect in the increased in demand, which could spread over several periods, which may be different in different markets and for different target groups, which makes the estimation of elasticity more difficult.

Given the inability of researchers to quantify the subjective elements of a marketing campaign (its appeal, humor, novelty, etc.), it is little wonder that marketing expenditure has been the independent variable most studied for its impact on tourism flows. Those few studies that have been undertaken indicate that marketing expenditure has a positive, but relatively small, effect on international tourism demand. In his meta-analysis of tourism demand, Crouch (1995) estimated that the mean value of marketing elasticities was 0.31 for all destinations and 0.23 for Oceania. Crouch’s analysis indicates that marketing elasticities are lower than the other demand elasticities studied. The results for studies that specifically concern Australia support this view. They are summarized in Table 1.

Table 1.

Comparison of Estimates of Marketing Elasticities of Australian Key Source Markets.

		Kulendran and Divisekera 2007
Market	Crouch, Schultz, and Valerio 1992	Cointegration Analysis	Dynamic Modeling	Kulendran and Dwyer 2009	Access Economics 2002
United States	0.11	0.03	0.04	0.15
Japan	0.20	0.02	0.08	0.16
United Kingdom	0.14	0.05	0.05	0.05
New Zealand	0.25	0.08	0.07	0.11
Asia				0.37
Germany	0.23
Total					0.09–0.12

The most recent and most sophisticated of the Australian empirical studies, that of Kulendran and Dwyer (2009), estimates marketing elasticities of between +0.05 and +0.16 for some of the key markets examined in the present study. Of course, a range of elasticity values could be employed, but for the purposes of this study we use +0.10. This assumed elasticity of +0.10 also falls within the range +0.09 to +0.12 estimated in the Access Economics study (1997, 2002). An elasticity value of +0.10 implies that an extra $1 million of promotion expenditure generates $10.0 million of tourism expenditure.

The selected markets for the present study are as follows:

Five origin markets: New Zealand, China, Korea, United Kingdom, United States

Three types of travel motivations: holiday, VFR, business

One niche market: Backpackers.

These markets were selected following discussions with managers in Tourism Research Australia (TRA). The country origins represent Australia’s most important inbound markets, representing more than half (50.3%) of total inbound flows. The three types of travel motivation account for 85.9% of inbound tourism (excluding employment and other). Backpackers was selected as a particularly important market for Australia at present and into the future, representing 11.0% of inbound tourism in 2010.

Measuring the Return on Destination Marketing

Tourism Expenditure Measures

Table 2 displays some data for the selected origin markets for year ended June 30, 2010 (TRA 2010). Column 1 shows the total TIEV associated with each visitor market prior to the extra marketing expenditure. Column 5 shows the projected increase in TIEV that results from a $1-million increase in marketing expenditure directed toward each market (taken independently). Given a marketing elasticity of +0.10, an additional $1 million of marketing expenditure generates an additional $10 million of expenditure into Australia. Column 5 shows the estimated TIEV per night resulting from each additional visitor from the identified market.

Table 2.

TIEV Measures for Australia, for Selected Markets, before and after Additional Marketing Expenditure of $1 Million (Year Ended 30 June 2010).

	Before Additional Marketing					After Additional Marketing
Market Segment	TIEV, in million $	Number of Visitors, ×1000	Number of Visitor Nights, ×1000	Average Duration of Stay (Nights)	Additional Marketing-Induced TIEV, in million $	TIEV per Night, $
New Zealand	1,900.20	1,020.74	13,104.49	12.84	13.272	145.00
Korea	1,052.01	182.65	12,195.70	66.77	11.274	86.26
China	2,838.60	376.62	22,458.98	59.63	12.108	126.39
United States	1,803.37	459.33	10,124.51	22.04	14.802	178.12
United Kingdom	2,898.82	614.62	22,445.18	36.52	15.764	129.15
Holiday	8,548.27	2,408.64	63,218.76	26.25	16.392	135.22
VFR	3,337.08	1,309.50	33,286.00	25.42	15.132	100.25
Business	2,137.95	816.38	10,969.68	13.44	15.311	194.90
Backpackers	4,384.97	583.06	43,026.90	73.79	12.097	101.91
Australia total	23,061.17	5,279.74	182,677.33	34.60	14.017	126.24

Source: Authors’ estimates of TIEV based on data in TRA (2010).

Note: Total Australia does not double-count visitor markets. TIEV = total inbound economic value.

Total TIEV for Australia in 2009–2010 was $23.061 billion. Of the countries of origin, the greatest TIEV is associated with the UK market ($2.899 billion), followed by China ($2.839bn), New Zealand (1.90 billion), United States ($1.803 billion), and Korea ($1.052 billion). Of the travel purpose markets, holiday visitors TIEV is $8.548 billion, compared to VFR ($3.337 billion) and business visitors ($2.138 billion). The backpacker market TIEV is $4.385 billion.

The additional TIEV associated with additional visitation generated by the $1-million marketing expenditure is shown in the fifth column of results in Table 2. The greatest increase is associated with holiday visitors ($16.369 million) followed by visitors from the United Kingdom ($15.764 million) and business visitors ($15.311 million). The smallest additions to total TIEV were associated with visitors from Korea ($11.274 million) and backpackers ($12.097 million). For all visitation to Australia, the additional marketing induced TIEV is $14.017 million.

The average TIEV per night for all inbound tourism to Australia is $126.24, with average duration of stay at 34.60 nights. Of the selected markets, visitors from the United States have the highest TIEV yield, injecting, on average, $178 per night into the Australian economy. The second highest TIEV per night by origin is associated with visitors from New Zealand ($145), and then United Kingdom ($129) and China ($126). Each of these country source markets injected more per night than Korea ($86). For travel purpose, holiday visitors injected $135 per visitor night, with VFR $100 and business travel $195 per night. Backpackers are associated with an average of $102 TIEV per night.

Origin markets associated with higher than average TIEV per night and longer duration of stay are China and the United Kingdom (Figure 1). As might be expected, the VFR market is associated with lower than average TIEV per night and lower than average length of stay.

Figure 1.

Total inbound economic value per night and length of stay, selected niche markets, Australia, 2009–2010.

The matrix indicates that the only markets in the top right quadrant associated with higher than average TIEV per night (above $126.34) and longer duration of stay (above 34.60 nights) are China and the United Kingdom. Greater than average TIEV per night is associated with visitors from New Zealand and the United States as well as holiday makers and business travelers, all of whom stay below the average duration of visitors. This presents a challenge to explore ways of getting additional duration of stay from these markets. While Koreans and backpackers have high durations of stay, they are associated with lower than average TIEV per night. As might be expected, the VFR market is associated with lower than average TIEV per night (and lower than average length of stay).

Economic Contribution Measures

Australia’s TSA can be used to calculate, for each origin market, the increase in economic contribution (tourism gross value added, tourism gross operating surplus, and tourism employment) associated with the marketing-induced increase in TIEV. Assuming a $1-million increase in marketing expenditure allocated to each market (taken independently), Table 3 shows the contribution of the additional TIEV to these key economic variables.

Table 3.

Economic Contribution of Additional Tourism Induced by $1 Million Increase in Marketing to Selected Origins, Australia.

Market Segment	Additional TIEV, million $	Contribution to Tourism GVA, million $	Contribution per Visitor to Tourism GVA, $	Contribution per Visitor Night to Tourism GVA, $	Contribution to Tourism GOS ($m), by Target Market	Contribution per Visitor to Tourism GOS, $	Contribution per Visitor Night to Tourism GOS, $	Yield Rate, %	Contribution to Tourism Employment, No. of Persons	Contribution per $1 million TIEV to Tourism Employment, No. of Persons
New Zealand	13.272	4.109	515.16	40.12	1.236	154.96	12.07	9.32	70.36	5.31
Korea	11.274	4.299	1448.62	21.70	0.931	313.67	4.70	8.25	73.78	6.54
China	12.108	4.995	1857.21	31.15	0.906	336.84	5.65	7.47	83.65	6.90
United States	14.802	5.024	829.09	37.62	1.287	212.41	9.64	8.69	84.23	5.69
United Kingdom	15.764	4.760	779.74	21.35	1.477	241.98	6.63	9.37	79.38	5.03
Holiday	16.392	5.233	646.48	24.63	1.543	190.60	7.26	9.40	90.37	5.51
VFR	15.132	4.696	606.91	23.88	1.309	169.19	6.66	8.66	76.77	5.08
Business	15.311	4.689	631.03	46.95	1.458	196.15	14.59	9.52	77.70	5.08
Backpackers	12.097	4.297	978.26	13.26	1.090	248.03	3.36	9.01	69.22	5.72
Australia average	14.017	4.927	933.25	26.97	1.289	266.79	7.71	9.21	75.94	5.42

Source: Author estimates based on TRA data (2010) and MMRF database (Adams, 2008).

Note: TIEV = total inbound economic value; GVA = gross value added; GOS = gross operating surplus.

Column 1 shows the additional TIEV associated with an increase of $1 million marketing expenditure allocated to each inbound market (considered independently not simultaneously). The TIEV values are the same as those in Table 2.

Column 2 shows the contribution to tourism gross value added (TGVA) that results from the additional TIEV in each inbound market. TGVA is measured as the value of the output of tourism products by industries less the value of the inputs used in producing these tourism products. Value added is the “value” businesses add to the goods and services they purchase (intermediate inputs) and use in the process of producing their own outputs. Alternatively, TGVA is the value of wages/salaries and profits in businesses from the direct supply of goods and services to visitors. The greatest contribution to tourism GVA in Australia following an increase of $1 million in marketing expenditure targeted to each market is associated with the spending of visitors from United States ($5.024 million), followed by visitors from China ($4.995 million), United Kingdom ($4.760 million), Korea ($4.299 million), and New Zealand (4.109 million). Of the three travel purpose markets, TGVA from holiday visitors is estimated to be $5.233 million, followed by VFR ($4.696 million) and business travel ($4.689 million). Backpackers are estimated to generate $4.297 million in TGVA.

As shown in column 3, the average tourist is estimated to contribute $933 to TGVA during their visit to Australia. Of the selected markets, the greatest contribution per visitor to TGVA in Australia is associated with the spending of visitors from China ($1,857), followed by visitors from Korea ($1,449), United States ($829), United Kingdom ($780), and New Zealand ($515). Of the three travel purpose markets, the contribution per trip from holiday makers, VFR, and business visitors are $646, $607, and $631, respectively. For backpackers, it is a relatively high $978, reflecting their greater than average length of stay.

Column 4 shows that contribution to TGVA per visitor night is $26.97 on average. It varies substantially, however, between the selected inbound markets. For country origins, the greatest contribution to TGVA per visitor night, following $1 million additional marketing expenditure, is associated with visitors from New Zealand ($40.12), and then United States ($37.62), China ($31.15), Korea ($21.70), and United Kingdom ($21.35). Of the three travel purpose markets, the highest GVA per visitor night is associated with business visitors ($46.95), followed by holiday ($24.63) and VFR ($23.88). For backpackers, it is a relatively low $13.26.

The matrix indicates that the only market in the top right quadrant associated with higher than average TGVA per night and longer duration of stay is China (Figure 2). Greater than average TGVA per night, but less than average duration of stay, is associated with visitors from New Zealand and the United States as well as business travelers. This presents a challenge to explore ways of getting additional duration of stay from these markets. While Koreans and backpackers have high durations of stay, they are associated with lower than average TGVA per night. Markets associated with lower than average TGVA per night and lower than average length of stay include holiday travelers and VFR.

Figure 2.

Tourism gross value added per night and length of stay, selected niche markets, Australia, 2009–2010.

Column 5 of Table 3 shows the contribution of the marketing-induced TIEV associated with each market on tourism gross operating surplus (TGOS), or return to capital. The largest contribution to TGOS in Australia following an increase of $1 million in marketing expenditure targeted to each market is associated with the spending of visitors from the United Kingdom ($1.477 million), followed by visitors from United States ($1.287 million), New Zealand ($1.236 million), Korea ($0.931 million), and China ($0.906 million). Of the three travel purpose markets, the highest contribution to TGOS per visitor is associated with holiday ($1.543 million), business ($1.458 million), and VFR ($1.309 million). Backpackers are projected to generate $1.090 million TGOS. Averaged over Australia, the contribution to TGOS is $1.289 million.

As shown in column 6, the highest estimated contribution to TGOS per visitor is associated with the China market ($337), followed by Korea ($314), United Kingdom ($242), United States ($212), and New Zealand ($155). Of the three travel purpose markets, the highest contribution to GOS per visitor is associated with business ($196), holiday makers ($191), and VFR ($169). Each backpacker contributed $248 to GOS on average. On a per-night basis (column 7), business travelers contribute the greatest to TGOS ($14.59), followed by visitors from New Zealand ($12.07). The least contribution to TGOS per night is associated with visitors from Korea ($4.70) and backpackers ($3.36). Averaged over Australia, the contribution to TGOS per night is $7.71. The yield rate in column 8 shows the percentage of contribution to TGOS divided by the additional TIEV associated with the increased marketing expenditure. The highest yield (9.52%) is associated with business travelers followed by holiday makers (9.41%) and visitors from the United Kingdom (9.37%). The lowest yields are associated with China (7.48%) and Korea (8.26%). Average yield for Australia is 9.21%.The yield measures are of particular importance to tourism operators, as they are most relevant to business profitability.

The matrix indicates that there is no market in the top right quadrant associated with higher than average TGOS per night and longer duration of stay (Figure 3). Greater than average TGOS per night, but less than average duration of stay, is associated with visitors from New Zealand and the United States as well as business travelers. This presents a challenge to explore ways of getting additional duration of stay from these markets. While Koreans and backpackers have high durations of stay, they are associated with lower than average TGOS per night. Markets associated with lower than average TGOS per night and lower than average length of stay include holiday travelers and VFR.

Figure 3.

Tourism gross operating surplus per night and length of stay, selected niche markets, Australia, 2009–2010.

As shown in column 9, the greatest contribution to tourism employment in Australia following the additional marketing effort is associated with visitation of holidaymakers (90.37 jobs), followed by United States (84.23) and China (83.65). The least job creation is associated with backpackers (69.22 jobs). Average for Australia is 75.94 jobs created as a result of the additional $1 million destination marketing expenditure. Column 10 shows that the average visitor creates or maintains 5.42 tourism jobs for every $1 million TIEV. Of the selected markets, the highest tourism employment–generating market is China (6.90 jobs generated per $1 million), followed by Korea (6.54). UK visitors generated the least number of jobs per $1 million of TIEV (5.03) (Figure 4).

Figure 4.

Tourism employment generated by $1 million marketing expenditure.

The results shown in Table 3 demonstrate the additional TIEV associated with marketing-induced tourism on Australia’s tourism GVA, tourism GOS, and tourism employment using the relationships from the Australian TSA. However, TSAs are essentially descriptive in nature and do not include any measurement of the indirect and induced effects of visitor consumption on the economic system as a whole. The additional value added generated by the industries supporting the initial “round” of tourism spending is excluded. That is, direct value added does not measure the full impact of tourism on the host economy because it is limited to those businesses that have a direct relationship with tourists. Inclusion of the indirect effects of tourist expenditure acknowledges that tourism’s total economic significance is greater than just the direct contribution estimated in the TSA. Measuring indirect tourism value added involves tracing the flow-on effects of businesses’ intermediate purchases that are used directly in producing tourism products and measuring the cumulative value added that these purchases generate. These indirect effects should be understood as a method of redistributing to the tourism sector value added, gross operating surplus, and employment that occurs outside the tourism sector but as a result of tourism activity. They reflect the value of production and employment that occur on an economy-wide basis as a result of the demand of tourists for goods and services. To estimate the indirect effects, we need an I-O model to trace these “secondary” effects. This has not been attempted in the present paper because of the weakness of the I-O multiplier technique, which lacks a capacity to deal with price effects and resource constraints.

Unfortunately, it is not always understood by researchers and policy makers that the wider economic impacts of a change in tourism demand cannot be estimated by using averages from a TSA. These wider changes occur at the margin and involve interindustry and other economy-wide effects. Tourism demand shocks reallocate resources in the economy to accommodate changes in sectoral outputs through interactive effects (Dwyer, Forsyth, and Spurr 2003). This is clearly beyond the contribution of the tourism sector itself. Estimation of the economy-wide economic impacts of the marketing-induced TIEV requires the use of a CGE model to simulate the outcomes (Dwyer et al. 2000; Dwyer, Forsyth, and Spurr 2004).

CGE Measures

Table 4 shows the economic impacts on the Australian economy as a whole of $1 million in additional marketing expenditure directed toward each of the nine inbound markets, taken individually.

Table 4.

Economic Impacts on Australia of $1 Million Additional Marketing Expenditure Directed toward Each Inbound Market.

Market Segment	Marketing-Generated TIEV, Million $	Real GVA, Million $	Contribution per Visitor Night to Real GVA, $	Real GOS, Million $	Contribution per Visitor Night to Real GOS, $	Number of Jobs	Contribution per $1 Million TIEV to Employment, No. of Persons
New Zealand	13.272	8.568	124.23	3.641	52.80	128.30	10.34
Korea	11.274	7.961	68.67	2.871	24.76	123.21	9.15
China	12.108	9.086	114.84	3.229	40.81	136.47	8.87
United States	14.802	9.949	177.21	3.977	70.83	148.33	9.98
United Kingdom	15.764	9.906	127.94	4.253	54.93	147.15	10.71
Holiday	16.392	11.100	150.09	4.757	64.33	167.87	9.76
VFR	15.132	9.618	96.42	4.071	40.82	138.92	10.89
Business	15.311	9.493	185.02	4.059	79.12	140.33	10.91
Backpackers	12.097	8.071	76.12	3.188	30.07	121.09	9.99
Average	14.017	9.306	124.50	3.783	45.65	139.07	10.08

Source: Author’s estimates based on TRA data (2010) and MMRF database (Adams, 2008).

Column 1 shows the TIEV generated by each market following the assumed $1 million increase in marketing expenditure allocated to that market (this information replicates that in column 1 of Tables 2 and 3).

Column 2 shows the real GVA for the Australian economy as a whole that is generated by each market following the assumed $1 million increase in marketing expenditure. The greatest real GVA is generated by the holiday market ($11.100 million), followed by United States ($9.949 million) and United Kingdom ($9.906 million). The smallest contribution to real GVA is associated with New Zealand ($8.568 million) and Korea ($7.961 million).

Column 3 shows real GVA per night generated by each market following the assumed $1 million increase in marketing expenditure. Average real GVA generated per night is $124.50. The greatest contribution comes from business travelers ($185.02), followed by visitors from the United States ($177.21) and holiday makers ($150.09).

The matrix indicates that the United Kingdom is the only market in the top right quadrant associated with higher than average economy-wide GVA per night and longer duration of stay (Figure 5). Greater than average economy-wide GVA per night, but less than average duration of stay, is associated with visitors from the United States and holiday and business travelers. This presents a challenge to explore ways of getting additional duration of stay from these markets. Chinese, Koreans, and backpackers have high durations of stay but are associated with lower than average economy-wide GVA per night. The VFR market is associated with lower than average economy-wide GVA per night and lower than average length of stay.

Figure 5.

Economy-wide gross value added per night and length of stay, selected niche markets, Australia, 2009–2010.

Column 4 shows the real GOS generated by each market following the assumed $1 million increase in marketing expenditure. The greatest real GOS is generated by the holiday market ($4.757 million), followed by United Kingdom ($4.253 million), and then VFR ($4.071 million) and business travel ($4.059 million). The smallest contribution to real GOS is associated with Korea ($2.871 million) and backpackers ($3.188 million).

Column 5 shows the real GOS per night generated by each market following the assumed $1 million increase in marketing expenditure. Average GOS generated per night is $45.60. The greatest contribution comes from business travelers ($79.12), followed by visitors from the United States ($70.83) and holiday makers ($64.33).

The GOS matrix indicates that the United Kingdom is the only market in the top right quadrant associated with higher than average economy-wide GOS per night and longer duration of stay (Figure 6). Greater than average economy-wide GOS per night, but less than average duration of stay, is associated with visitors from New Zealand, the United States, and United Kingdom and holiday and business travelers. Chinese, Koreans, and backpackers have high durations of stay but are associated with lower than average economy-wide GOS per night. The VFR market is associated with lower than average economy-wide GVA per night and lower than average length of stay.

Figure 6.

Economy-wide gross operating surplus per night and length of stay, selected niche markets, Australia, 2009–2010.

Column 6 shows the number of jobs generated by each market across the Australian economy as a whole following the assumed $1 million increase in marketing expenditure. The greatest number of jobs is generated by the holiday market (167.874), followed by United States (148.333) and United Kingdom (147.150). The smallest contribution to employment is associated with backpackers (121.09) and Korea (123.21).

Column 7 shows jobs generated per $1 million contribution to TIEV. Average number of jobs created was 10.08 for all tourists to Australia. The greatest contribution was from business visitors (10.91 jobs), followed by VFR (10.89) and United Kingdom (10.71). The relatively high economy-wide effects of VFR expenditure on employment is interesting and consistent with recent arguments to the effect that VFR tourism makes a greater economic contribution to destinations than is commonly believed (Backer 2007) (Figure 7).

Figure 7.

Estimated economy-wide employment (all industries) generated by $1 million marketing, Australia.

Implications for Policy

The results indicate that, for any given value of marketing elasticity, a destination’s return on investment from marketing activity depends on the measure adopted. The different measures give different signals to policy makers. The standard expenditure measure of yield has several problems associated with it, of which destination managers seem to be largely unaware. For the reasons given, we have preferred to use TIEV rather than simple (unadjusted) expenditure measures. Tourism Research Australia appears to be one of the few major tourism DMOs that have appreciated the sophistication of this measure and its advantages over simple expenditure measures.

Assuming a marketing elasticity of +0.10, we estimated TIEV measures of the return on investment from increased tourism marketing. Our results indicate that two markets are associated with higher than average TIEV per night and longer duration of stay: China and the United Kingdom. While the UK market is a mature one for Australia, China is regarded as having enormous growth potential. China is the fastest-growing outbound market in the world (UNWTO 2011), with an annual growth of 13.5% between 2006 and 2010 and a stronger increase of 20.0% in 2010. In the longer term, average annual growth of 7.2% is forecast between 2010 and 2020. By 2020, this would boost Chinese visitor arrivals to Australia to 908,000 while real TIEV would reach $6.0 billion. This will make China by far the largest of Australia’s inbound markets in terms of economic value (Tourism Research Australia 2011). Greater than average TIEV per night is associated with visitors from New Zealand the United States, holiday makers, and business travelers. Although the duration of stay of these visitors is below that of the representative tourist, it may be possible to increase this through attempts to better understand visitors, their expectations, needs, requirements, satisfactions, and dissatisfactions and to improve the types of tourism experiences on offer. Not only can such information form the basis for strategies to make Australia more interesting, with the ability to offer a more varied set of tourism experiences, but it is also likely to generate an increase in average length of stay as well as greater repeat visitation (Australian Government 2009). As the discussion makes clear, we see the importance of expenditure-based estimates of yield (including TIEV) as in providing the basis for more informative TSA-based economic contribution and CGE based economy-wide impact measures.

The use of a TSA allows the estimation of the economic contribution of tourism to key variables such as GVA, GOS, and employment. By this means, destination managers can determine, for a given increase in marketing expenditure, the relative economic contribution made by different origin markets to the tourism industry. The TSA-based return-on-investment measure enables us to measure the economic contribution to the tourism industry of any increased marketing effort. The results show that the only market associated with higher than average TGVA per night and longer duration of stay is China. Greater than average TGVA per night is also associated with visitors from New Zealand and the United States as well as business travelers. These results are of direct relevance to tourism industry stakeholders, ignoring as they do the effects on other (nontourism) industry sectors. The results regarding contribution to TGOS shows that while no market is associated with both above-average TGOS per night and above-average duration of stay, visitors from New Zealand and the United States as well as business travelers contribute above-average TGOS per night, thereby most positively affecting the financial position of tourism stakeholders. The contributions to tourism employment per $1 million spending were seen to be greatest for visitors from China and then Korea. This measure is particularly useful for industry or sectoral policies formulated to develop the tourism industry relative to others in an economy. Long-term tourism development strategies could particularly benefit from incorporating information on the contribution of different visitor market segments to tourism GVA, tourism GOS, and tourism employment.

We also estimated the economic impacts of a $1-million increase in marketing expenditure targeted at each selected inbound market, using a CGE model. This provided economy-wide yield estimates for the Australian economy. Greater than average economy-wide GVA per night is associated with visitors from the United States, and United Kingdom and holiday and business travelers. Greater than average economy-wide GOS per night is associated with visitors from New Zealand, the United States, and United Kingdom and holiday and business travelers. The only market associated with higher than average economy-wide GVA and GOS per night and longer duration of stay is the United Kingdom. Interestingly, the greatest economy-wide impact on jobs (10.91 jobs created per $1 million) is associated with business visitation, a market sector in Australia with strong projected growth.

From a public policy perspective, the overall impact on the economy is a critical dimension of the yield from increased tourism marketing. The destination manager will wish to know what impact additional tourists of a particular type will have on real GVA, GOS and employment across the entire economy. Public policy makers and treasury officials at the national and state or provincial levels, who are concerned with wider policy and development planning issues, or with funding and resource allocation decisions affecting tourism, will be particularly interested in how the economy as a whole will be affected by growth in tourism numbers and expenditure, not just the tourism industry. For this purpose, economy-wide measures of visitor yield provide information unavailable on the other approaches.

Conclusions

Destination marketing and promotion by Australia may be expected to increase inbound tourist numbers and the associated expenditure. The extent to which tourism numbers increase in response to a given change in marketing expenditure depends on the marketing elasticity of demand. Measures of the return on marketing can inform organizations in both the private and public sectors about effective allocation of marketing resources and the types of tourism development that best meet operator and destination manager objectives.

Different stakeholders with different objectives or ends in view will emphasize different target markets. In respect of the above economic yield measures, operators are likely to emphasize the importance of high injected expenditure (TIEV) from inbound tourism markets or real GOS per visitor night, while destination managers are likely to emphasize the economic contribution to the tourism industry. Government policy makers and treasury officials are likely to be more interested in the economy-wide impacts of such expenditure. The different measures of yield do not provide generally consistent rankings across each of these sets of results for the origin markets examined. No single origin has above-average yield performance on all of the measures.

Given the data limitations confronted in this study, the results should be regarded as indicative only. To date, only a small number of studies have attempted to estimate marketing elasticities internationally and for Australia specifically. Several difficulties challenge researchers in their effort to estimate marketing elasticities as discussed above. The assumed marketing elasticities were based on the findings of empirical studies previously undertaken for Australia. The results indicate that an additional dollar of marketing expenditure generates approximately $10 of additional expenditure into Australia from inbound markets, which was then converted to TIEV. Since the results are close to linear for small changes in marketing expenditure, sensitivity analysis can be readily undertaken using different marketing elasticity values.

Measures of tourism yield can provide guidance to destination stakeholders both as to the origin markets that should be emphasized in marketing/promotion activity and to the types of products and services that should be developed to attract “high yield” visitors. Further research needs to be undertaken, however, on the most appropriate yield measures to employ in different circumstances and the consistency of the rankings from different measures.

The method employed here can, data permitting, be applied to destinations worldwide. The changing dynamics of the tourism marketplace, as well as increasing constraints on DMOs to allocate scarce marketing funds efficiently, demand that the prospective return on investment in destination marketing be estimated as accurately as possible. This study has emphasized that, estimation problems aside, different measures of yield can be employed. The rewards from further research in developing and operationalizing yield measures to determine the returns to marketing activity is more informed policy making by operators, destination managers, and for wider public policy purposes in respect of destination marketing and funding and for new product development. This should result in improving the economic benefits from inbound tourism.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author Biographies

Larry Dwyer is Research Professor in the School of Marketing University of New South Wales. Larry is President of the International Academy for the Study of Tourism. His research interests are in tourism economics and management.

Tien Pham is manager, economic modelling, Tourism Research Australia, and a Research Fellow at School of Tourism, Queensland University. He has extensive experience in computable general equilibrium. His research interests lie in the area of economic tourism policy.

Peter Forsyth is a professor of economics at Monash University, Australia. His primary research interest is in aviation and tourism economics.

Ray Spurr is a research fellow at University of New South Wales with interest in tourism policy issues.

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