Tourism accounts for around 10% of the world’s gross domestic product (GDP) and approximately 10% of total global employment, making it an important source of economic activity. Understanding tourism demand is vital if tourism-related businesses are to succeed. Anticipating this demand requires a knowledge of the factors driving tourist activity. Arrivals and expenditure are often used as measures of tourism demand. Moreover, income has been deemed a crucial determinant, with a higher income in the tourists’ country of origin leading to a higher demand for travel and tourism.
Dr. Jorge Ridderstaat from Rosen College of Hospitality Management has carried out an extensive review of the use of income as an indicator for tourist demand. His investigation has revealed that the relationship between income and consumption does not always hold and can be distorted by fluctuations in consumers’ wealth, while applied proxies are not always useful. In response to these shortcomings, Dr. Ridderstaat investigates the effect of cycles of US households’ net financial position on US tourism demand and proposes net financial wealth as a key determinant of tourism demand.
TOURISM DEMAND CYCLES
During periods of economic uncertainty, households may save more of their income and reduce expenditure on non-essential goods and services. Likewise, tourists will tend to sacrifice leisure travel and holiday closer to home. Alternatively, they may forgo secondary holidays so that they can have their main vacation.
These dynamics in tourism demand are short-run changes, with contraction periods when tourism demand underperforms its long-term trend and expansion periods when it overperforms. Contraction periods can bring about stalled tourist arrivals, macroeconomic imbalances, declining room capacity, and the offer of incentives to invest in new tourism development. Monitoring these tourist demand cycles is critical to planning and developing appropriate management strategies and avoiding these risks.
INCOME AS INDICATOR
Income has traditionally been considered a key determinant of tourism demand, with researchers preferring to use approximations of national income (in terms of per capita income and the real GDP) rather than personal income proxies. Temporary fluctuations in the economy’s performance, producing deviations from the long-term growth trend—known as business cycles—have also been used as indicators of tourism demand.
Approximating national income, however, has its limitations. Firstly, national accounting methodology is used to assess the economic development of nations. The latter is not always based on observed values and can include estimates. Secondly, consumers’ income sources such as job creation and wage developments may not align with the GDP. This disconnect with the GDP can distort results determined from the relationship between business cycles and tourism demand. Thirdly, the annual and quarterly publishing of the GDP makes it difficult to assess more frequent (e.g., monthly) short-term effects of business cycles.
Dr. Ridderstaat explains how using income as an indicator of tourism demand can be deceiving, as the relationship between income and consumption does not always work because of their connection with a third factor: wealth. Tourism literature rarely recognizes the effect of wealth on tourism demand. Those who do only consider gross wealth and ignore the effects of consumers’ liabilities on tourism demand. They also assume that tourists are homogenous, in that one size fits all and ignore the possibility of consumers making different decisions.
NET FINANCIAL WEALTH
Net wealth is the difference between a household’s assets, such as a house or savings account, and liabilities, such as mortgages or credit card loans. It is used to describe a household’s financial position.
Financial wealth is one reason why income and consumption are not necessarily connected. Increased consumption can result from running down on assets or increasing debt. Similarly, consumption can be reduced by saving more and adding to assets.
During uncertain economic periods, households tend to increase their saving rate as there is a greater risk of job loss. They will often curtail and defer expenditure on non-essential goods and services until the economy improves. These variations in consumers’ wealth can distort the connection between income and tourism demand. The latter suggests that households’ net financial wealth developments may be a better indicator of tourism demand than income.
METHODOLOGY
Based on their income, three types of households are considered in this study: the bottom-third income earners, referred to as the Commoners; the middle-third income earners, the Intermediates; and the top-third income earners, the Capstoners.
Compared to their situation a year earlier, the households perceive that either they are now better off, denoted as ‘Waxed’; their financial state is the same and denoted as ‘Allied’; or they are now worse off, denoted as ‘Waned’.
These income classifications and perceptions of financial wealth produce nine different types of households: Waxed Capstoners, Allied Capstoners, Waned Capstoners, Waxed Intermediates, Allied Intermediates, Waned Intermediates, Waxed Commoners, Allied Commoners and Waned Commoners.
To examine the effect of cycles of US households’ net financial position on the flows of US tourism demand, this study determines the likelihood and time horizon of these nine households to travel to Aruba, Barbados, and Jamaica.
DESTINATIONS
Dr. Ridderstaat selected the destinations using the Structured Focused Comparison case-study approach. The three islands are similar because they are all Small Island Developing States with specific social, economic, and environmental vulnerabilities. They are also tourism-dependent destinations located in the Caribbean.
Their differences include the islands’ travel distance from the United States, with Jamaica geographically closest (560 miles), followed by Aruba (1,130 miles) and Barbados (1,596 miles). The islands also differ in terms of their exchange rate systems. Both Aruba and Barbados have a fixed exchange rate system, while Jamaica’s is flexible. Aruba and Jamaica cater mainly to the US market, while Barbados has three large markets: the UK, US, and Canada.
DATA COLLECTION
Monthly observations were collected for the 23 years from January 1996–December 2018. Data for the nine households were collected using the Surveys of Consumers conducted by the University of Michigan. The survey sample represented all American households, excluding Alaska and Hawaii.
Tourism demand data for the three islands came from the socioeconomic data collected by their central banks.
ANALYSIS
Dr. Ridderstaat used the unobserved components model (UCM) to decompose the time series into trend, seasonal, cyclical, and irregular components. He standardized the resulting cycles and completed a statistical method called a unit root test to avoid spurious or regression results.
Then he tested for co-integration to establish any correlation between the time series and determine if there was a long-run cycle equilibrium relationship between tourism demand and those of the nine different households.
He used combinatorial regression to measure the relationship between variables and determine whether the households’ financial position cycles affect tourism demand cycles. Finally, he applied a logistic regression approach—a form of regression with a binary dependent variable—to the tourism demand cycles with the expansion phases coded as one and the contraction phases coded as zero.
Using this logistic regression approach, he determined the influence of the household financial positions on tourism demand and estimated the probability of each of the nine household groups affecting tourism demand cycles.
FINDINGS
Dr. Ridderstaat found that the results differed between periods of expansion and contraction in tourism demand cycles. Furthermore, only particular households influenced the US tourism demand cycle for the destinations.
Five of the nine households could become tourists in the expansion stage, while six of the nine households could become tourists in the contraction stage. Interestingly, neither Allied nor Waned Capstoners affected the expansion stage of the US tourism demand cycle for any of the destinations. They may prefer other destinations, or wealth effects may not alter their tourism consumption.
The results are also country-specific, which may well reflect the unique characteristics of the islands.
Dr. Ridderstaat notes that these contextual conditions echo the heterogeneity in consumers’ decisions, indicating that a one-size-fits-all approach to understanding the effect of wealth position perceptions on US tourism demand cycles may not be possible for these destinations. A circumstantial approach may be required instead.
IMPLICATIONS
Dr. Ridderstaat’s research reveals that the influence of net financial wealth on tourism demand is context-based and specific to households, cycles, and countries, across both time and probability dimensions.
Context matters for policymaking. The goal should be to prolong expansion periods of tourism demand, thus shortening the contraction periods.
He recommends that policymakers steer US tourism demand for their destination by targeting households based on their probabilities and reaction periods. Destinations should, therefore, follow a diagnostic approach based on what works for them rather than automatically pursuing best practice approaches such as targeting high-income tourists.
