The fallacy of imitating the physical sciences: parallels between Economics and Transport Planning

-by Dr. Asha Pandey & Satyendra Pandey

This note was inspired after reading of the speech by economist Friedrich August von Hayek who accepted the Nobel Prize in 1974. Borrowing from his speech, this note parallels draws parallels between Economics and the art of transport planning. The crux of his argument (and this note) is that quantitative models are limited in their ability to help reach decisions – and thus must be supplemented with other qualitative and “subjective” inputs.

The heart of developing tourism lies in the ability to develop a transportation network. The role of transport planning involves determining:

  • What cities to connect
  • Modes of transport (road, rail, air)
  • Schedules and frequencies for the routes
  • Intermodal connectivity (between road, rail and air)
  • The shape of the network (minimizing disruption patterns)

All too often, transport planning aims to follow a strictly quantitative method and to replicate the procedure of physical sciences. This then has impacts on the overall organization.

 Hayek states: “It seems to me that this failure of the economists to guide policy more successfully is closely connected with their propensity to imitate as closely as possible the procedures of the brilliantly successful physical sciences”

Transport planning too aims to replicate the procedure of physical sciences. City pairs are looked at, demographics examined and price elasticity of demand arrived at with mathematical models. What this process fails to incorporate is the behavioural patterns and the complex interdependence between connectivity, consumer behaviour and choice. For instance, take the following scenario:

  • Some new airports are almost 2 hours away from the city centre (land constraints)
  • Buses offer a great road alternative
  • Trains offer a product that is most preferred at the right price points
  • While some modes offer speed others offer convenience
  • With improvements in infrastructure there is shift between modes of travel

Take for example the below availability chart and comparison of train fares versus rail:avalibility

Note: Data pertains to travel during May 2017

 

While the quantitative answer as the chart suggests would be a shift to air as a “compelling proposition” the reality is that: it still depends.

For bus travel as well, a quantitative model, while it can point to trends, cannot fully capture consumer behaviour as there are various other factors at play. Perhaps best captured by this tweet below:

 Tweet bus.

“The theory which has been guiding monetary and financial policy during the last thirty years, and which I contend is largely the product of such a mistaken conception of the proper scientific procedure, consists in the assertion that there exists a simple positive correlation between total employment and the size of the aggregate demand for goods and services; it leads to the belief that we can permanently assure full employment by maintaining total money expenditure at an appropriate level.”

Hayek speaks about economics assuming that a positive correlation exists between supply and demand. The same holds true for transport planning. This in turn leads to the belief that where demand exists supply will be absorbed (at the right price levels). A widely used metric is the seat to population ratio which simply put looks at the number of airplane/train/bus seats per person. What this fails to account is for wealth distribution, competing modes of transport, price points at which the consumer simply chooses to switch modes of transport or not travel at all.

 

 “…in economics and other disciplines that deal with essentially complex phenomena, the aspects of the events to be accounted for about which we can get quantitative data are necessarily limited”

This holds very true for transport planning. There are some aspects for which quantitative data is simply not available, or shows wide variation if taken with a sample. For instance:

  • At what price point does the consumer switch between modes of transport
  • At what times (schedules) does the consumer switch
  • How does connectivity to the airport impact choice of flight
  • How does familiarity versus service add to the mix
  • How does past experience with a mode of transport/or a country add up
  • How does perception play into demand for a particular mode

“We know: of course, with regard to the market and similar social structures, a great many facts which we cannot measure and on which indeed we have only some very imprecise and general information. And because the effects of these facts in any particular instance cannot be confirmed by quantitative evidence, they are simply disregarded …”

Transport planning by its very nature is imprecise. For instance take the issue of income levels and luxury class travel. One may tend to assume that income levels beyond a certain bracket would gravitate towards the business class offerings on buses/ rail/ air. However, this is not the case. Perhaps summed up best in this tweet posted by a gentleman travelling on a low cost carrier:

Tweet rail

Note: Raymond’s is a well known mens suit maker in India very famous with the business community

 “… But when we are asked for quantitative evidence for the particular structure of prices and wages that would be required in order to assure a smooth continuous sale of the products and services offered, we must admit that we have no such information.”

Pricing is a core element of the network. Yet it is usually looked at as a separate discipline. A close look at pricing across modes of transport reveals that a mix of models is followed and the basic assumption that pricing is rational may not hold true:

# Strategy Description Objective
1 Cost plus §  Unit cost + margin §  Recover cost and build profit
2 Simplified §  Set number of price points – usually 3 or 5 §  Simplicity
3 Unbundling §  Pricing individual items separately and offering as a choice §  Ensuring core product is lowest cost
4 Bundling §  Combining items and pricing together as a bundle §  Maximizing value
5 Competitor driven §  Matching competition pricing §  To compete (often in price driven markets)
6 Loss leadership §  Pricing below cost to entice customer and then offer range of products §  Where the lifetime customer value (LTV) > loss incurred on first sale
7 Premium pricing §  Pricing higher than competition – capturing on brand value and other attributes §  Positioning
8 Geographic (POS) §  Different pricing depending on geography and point of sale §  Leveraging different demand characteristics
9 Uniform §  Offering the same price regardless of market, competition, margin §  Building a brand via single price point

 

 “…the social sciences, like much of biology but unlike most fields of the physical sciences, have to deal with structures of essential complexity, i.e. with structures whose characteristic properties can be exhibited only by models made up of relatively large numbers of variables.”

This is perhaps the most critical aspect of a transportation network. Earlier we highlighted the proximity of the airport to the city centre. The fact is that to different folks this weighs in different forms. Were it not the case, one would not fathom the success of European low cost airlines flying to airports that are more than a fair distance away from the city centre.

Similarly, there is a market in India that is famous for diamond trading. Here the train is preferred because it is just lesser hassle and procedures (imagine airline security each time a bag of uncut diamonds goes through the scanner!)

Schedules too have to deal with complexity. Some of this complexity is revealed in booking patterns (famously referred to as yield curves) which shows how the traveller books across price points and from a time window 120 days out to the day of departure. The patterns are very different as illustrated below:

Study of 3 modes of transport in a market

3 modes.

These patterns then influence how the network is to be structured (and sold) and can very well mean the difference between success and failure. These behavioural patterns then have to be incorporated in the following ways:

  • Schedules have to be aligned to office timings – for business travellers
  • Schedules aligned to hotel check in and check out for leisure travellers
  • Where hotel capacity is not an issue schedules aligned to after work travel
  • Where there is festival travel – schedules have to be aligned to same day returns
  • Where schedules are not aligned creation of amenities such as rest areas, stops, hotel capacity can help bridge the gap

 

“phenomena of unorganized complexity,” in contrast to those “phenomena of organized complexity” with which we have to deal in the social sciences.2 Organized complexity here means that the character of the structures showing it depends not only on the properties of the individual elements of which they are composed, and the relative frequency with which they occur, but also on the manner in which the individual elements are connected with each other.

The above is best summed up by the fact that transportation is influenced by a variety of market and non-market actors.

If we are to safeguard the reputation of science, and to prevent the arrogation of knowledge based on a superficial similarity of procedure with that of the physical sciences, much effort will have to be directed toward debunking such arrogations…

Prevailing management theory has led to a disproportionate focus on all things quantitative. The mantra of “what cannot be measured, cannot be improved” is one that is repeated time and again. The role of intuition and qualitative and subjective inputs in the management process is absent. Suggesting this to some quarters may elicit a reaction of shock and dismay but as one airline CEO put it during an interaction: no quantitative model showed us that the route would work. But gut feel told me so. And it just worked!

Similarly transport planning must incorporate the entire picture including the benefit of intuition and the inclusion of more non-quantitative inputs. As Hayek states, “…I prefer true but imperfect knowledge, even if it leaves much indetermined and unpredictable, to a pretence of exact knowledge that is likely to be false.”

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