Quantitative Tourism

As an adventurous traveler, I have always been intrigued by the question, “where do you recommend I go? It can be challenging to answer, given that different people have different interests. As I’m very interested in local history and architecture, the places at the top of my list probably do not feature on other people’s lists. To get around this mismatch, I need a model to make my recommendations more systematic. I want to create a simple model of how under or overrated a destination might be for different categories of tourists.

Who is the average tourist?

Why do people travel? Are we, as humans, driven by the desire to explore new places, experience new things, and meet new people? No, as it turns out. Most tourists care little about interacting with their destination in any meaningful way. Two-thirds of tourists are not interested in going somewhere new and travel only within their comfort zone, usually on a cruise ship or travel bus. Novel or authentic experiences are active detriments to this group, so they consume only familiar food and view the outside world through a filtered window (Verbeke & López 2005). 

Socializing is also a motivation for this group, and as before, the actual destination is unimportant (Laesser et. al. 2009.). Especially for families, which make up about a third of all travelers, the main objective is to keep everyone entertained. Only about 10% of tourists travel to see or experience something specific, and in general, “special-interest tourism ” represents a vanishing minority of the total (Mckercher 2005, McKercher 2014).

Of those who travel somewhere new, 40% get their ideas from watching popular media, such as television series or YouTube channels. Half of all travelers will book their vacation less than a week after deciding where to go. That being said, there is a huge demand for international tourism, with Americans alone spending more than 1 trillion USD in 2018. It’s clear that travel is a highly impulsive decision and not driven by deeper motivation for most people.

So enough with the random statistics collated from many sources, some trustworthy, most not. Herein lies the difficulty with studying tourism: measuring why and where people travel. Survey data is the only effective way to capture the complex reasons behind the decision to travel, and surveys are complicated (McKercher 2014). The associated cost locks them behind paywalls or corporate vaults, which only leak contextless statistics to popular media.

Even if essentially meaningless, the numbers point towards a broader narrative of social-media-driven travel. My tourism score, though, will have to rely on publically available macroeconomic and geographic data, so I must ensure my results are within the market consensus.

The code for all of the graphs can be seen in my GitHub repository. I tried to optimize them as much as possible for mobile view, but some will be better seen in desktop mode.

Authentic Tourism

Travel has always been the domain of the elite to signal their wealth and status. From the beginning of tourism in the cities of 19th-century Belle Epoch Europe to today, travel remains a form of conspicuous consumption. More reputable research in various contexts largely confirms this. Modern tourists continue to make travel decisions based on what a destination will signal to an audience. 

That global tourism is driven by such a shallow human desire, one that is also substituted easily with the purchase of an expensive handbag, is also an important policy question. Protection of heritage sites, and national parks and support for local artists is often justified because it will bring in tourist money. However, several studies have shown that UNESCO Heritage designation provides no benefit to tourism, and sightseeing or cultural immersion is typically at the bottom of any survey on travel motivation (Ribaudo & Figini 2017, Mariani & Guizzardi 2020).

What does seem to matter is this nebulous metaphysical concept of “authenticity.” The effectiveness of the signal sent by the consumption of expensive tourism depends on how real it is. Nobody will be impressed if an influencer posts a picture of them photoshopped in a private jet. Likewise, the destination must reflect authentic expenditure of time and money, but the target audience must also perceive it as worthy of the time and money spent. What interests me is how a travel destination becomes “authentic” enough for millions of tourists.

Justin Bunch | CityscapeTravel

All tourism is authentic, and other authors have pointed out that “destination authenticity” is a largely vacuous concept (McKercher 2014, Kock 2021). More relevant is what the literature calls “existential authenticity,” or the self-actualization that occurs in the individual during travel (Wang 1999). In most cases, this measures the dopamine rush one gets with hundreds of likes on Instagram. This authentic consumption of a tourist good will encourage others to follow suit.

Quantifying Tourism

If we can measure some sense of this authenticity, then it may be possible to determine which destinations receive more tourists than their authenticity score might suggest. Put another way, I want to build a “social return” score, or the average number of Instagram likes the average tourist can expect at a specific location. Or, at the very least, build a metric that allows special-interest travelers to avoid the crowds, and find the hidden gems out there.

To get there, there are several questions that I have to answer:

  • What are authenticity and social return?
  • Can we measure destination authenticity, and is it relevant?
  • Does tourist infrastructure impact tourist flows?
  • What is the relationship between tourist volume and social return? Do network effects propagate already-popular destinations?
  • Can I design a score for a city, region, and country?

I will examine the available literature and use publicly available data to try and answer these questions. Much of the literature uses unnecessarily complicated models on extremely thin survey-based data sets, which I find tend to provide misleading results. My data set comprises mainly small sample census and economic data, but I will avoid overcomplicating the analysis and focus on visualization.

Justin Bunch | CityscapeTravel Not authentic enough for most tourists

The first article will examine the relevance of historical architecture to the perceived authenticity of a location. Germany provides an interesting dataset, as most German city centers do not have many old buildings, but many remain global tourist magnets.

Articles in this Series

Ranking the Regions

Ranking the Regions

The website uses a simple ranking methodology to help categorize travel destinations into various categories. People travel for different reasons and have different expectations. Some travelers do so with a special interest in mind, maybe a castle or a local…

Counting the Hidden Gems

Counting the Hidden Gems

The final step in this model-building process is ranking the German counties and the aggregation into my geographic schema. The goal is to build a metric that might help me determine how “over-traveled” a region or destination might be. The…

If You Build It – Will They Come?

If You Build It – Will They Come?

“If you build it – they will come” is a quote often used satirically to deride investors in white elephant projects. However, supply is easier to measure than demand, which puts analysts in a predicament. Supply of a good typically…

Do Tourists like Nature?

Do Tourists like Nature?

Do tourists care about national parks? I think the answer is obviously yes, as the global success of the American National Park system suggests. The draw for travelers is obvious for the United States, with its incredible and uniquely well-preserved…

Counting Tourists

Counting Tourists

The holy grail of quantitative tourism would be a near-objective measure of “too many” tourists. Such information would allow airlines, tour providers, and municipalities to direct and redirect tourists to an optimal experience. However, there is no easy measure for…


Choi S., Lehto X. Y., Morrison A. M., Jang S. S. 2012. “Structure of Travel Planning Processes and Information Use Patterns.” Journal of Travel Research 51:26-40.

Laesser C., Beritelli P., Bieger T. 2009. “Solo Travel: Explorative Insights from a Mature Market (Switzerland).” Journal of Vacation Marketing 15 (3): 217-27.

Kock, F. (2021). What makes a city cool? Understanding destination coolness and its implications for tourism. Tourism Management86, 104317. https://doi.org/10.1016/j.tourman.2021.104317

Mariani, M. M., & Guizzardi, A. (2020). Does Designation as a UNESCO World Heritage Site Influence Tourist Evaluation of a Local Destination? Journal of Travel Research, 59(1), 22–36. https://doi.org/10.1177/0047287518821737

McCabe S., Li C., Chen Z. 2016. “Time for a Radical Reappraisal of Tourist Decision Making? Toward a New Conceptual Model.” Journal of Travel Research 55 (1): 3-15.

Mckercher, B., & Chan, A. (2005). How Special Is Special Interest Tourism? Journal of Travel Research, 44(1), 21–31. https://doi.org/10.1177/0047287505276588

McKercher, B., & Prideaux, B. (2014). Academic myths of tourism. Annals of Tourism Research, 46, 16–28. doi:10.1016/j.annals.2014.02.003

Ribaudo, G., & Figini, P. (2017). The Puzzle of Tourism Demand at Destinations Hosting UNESCO World Heritage Sites: An Analysis of Tourism Flows for Italy. Journal of Travel Research, 56(4), 521–542. https://doi.org/10.1177/0047287516643413

Verbeke W., López G. P. 2005. “Ethnic Food Attitudes and Behavior among Belgians and Hispanics Living in Belgium.” British Food Journal 107 (10/11): 823–40.

Wang N. 1999. “Rethinking Authenticity in Tourism Experience.” Annals of Tourism Research 26 (2): 349–70.

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