Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Business analytics meets artificial intelligence: Assessing the demand
  effects of discounts on Swiss train tickets   We assess the demand effects of discounts on train tickets issued by the
Swiss Federal Railways, the so-called `supersaver tickets', based on machine
learning, a subfield of artificial intelligence. Considering a survey-based
sample of buyers of supersaver tickets, we investigate which customer- or
trip-related characteristics (including the discount rate) predict buying
behavior, namely: booking a trip otherwise not realized by train, buying a
first- rather than second-class ticket, or rescheduling a trip (e.g.\ away from
rush hours) when being offered a supersaver ticket. Predictive machine learning
suggests that customer's age, demand-related information for a specific
connection (like departure time and utilization), and the discount level permit
forecasting buying behavior to a certain extent. Furthermore, we use causal
machine learning to assess the impact of the discount rate on rescheduling a
trip, which seems relevant in the light of capacity constraints at rush hours.
Assuming that (i) the discount rate is quasi-random conditional on our rich set
of characteristics and (ii) the buying decision increases weakly monotonically
in the discount rate, we identify the discount rate's effect among `always
buyers', who would have traveled even without a discount, based on our survey
that asks about customer behavior in the absence of discounts. We find that on
average, increasing the discount rate by one percentage point increases the
share of rescheduled trips by 0.16 percentage points among always buyers.
Investigating effect heterogeneity across observables suggests that the effects
are higher for leisure travelers and during peak hours when controlling several
other characteristics.

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The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
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The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
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The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
19
The categories of this paper are: eess
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The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
1
The categories of this paper are: cs
3
The categories of this paper are: physics