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Regional diffusion and adoption effects on HSR demand expansion

THSR monthly aggregated ridership from March 2007 is obtained when for the first time all
eight stations were in operation. The ridership in the first month was around 919 thousand and
gradually increased by 7.4% per month on average reaching 2.97 million in August 2007. In 2008,
passenger numbers almost doubled and the average daily ridership continued to grow to over
138,525 passengers per day in 2015. Figure 2 illustrates though that the growth rates differ
by city. The city with the highest growth rate is Hsinchu (1.63%), and the city with the lowest
growth rate is Zuoying which is the farthest station from the capital Taipei. This might imply
that the needs for HSR is higher in Hsinchu before the opening, though it could also mean that
Hsinchu has fast generated additional trips after the HSR opened. In the case of other cities,
the THSR ridership is increasing at a relatively higher rate after the opening and the growth
rate of cities located between Taipei and Taichung seems to be higher than for cities located in
south of Taichung. For more discussion on the general factors influencing Taiwan’s HSR demand
we refer to Li et al (2015).
In this study we are considering HSR as a new transportation system with which the population
might not be familiar with in the beginning. Familiarity here means a general lack of considering
HSR in one’s choice set which might be due to a wide range of reasons such as lack of information
but also issues such as trust in the system. In line with product adoption literature we consider
that factors related to information spread through social interaction are important to identify
how quickly people adopt to HSR.

Fig. 2 THSR monthly ridership and averaged growth rate by city

2. Literature Review

The effect of social interaction on decision making has been receiving significant attention.
Hartmann et al. (2008) implied that social interactions occur when individuals affect others’
choices directly. They suggested that word-of-mouth (WOM) could be considered a key element
in social interaction. This is arising through inter-related outcomes which are the factor to
represent WOM. Further they noted that WOM is endogenously chosen by individuals, and hence
viewed as an action, rather than a characteristic. Park and Chung (2006) also noted that general
phenomenon as to how consumer information is spreading through various networks can be
referred to as WOM. It has been confirmed through various previous studies that consumers’
satisfaction, evaluation, compliments, and complaints related to new product/technology
purchasing or using have an effect on other users’ choice behaviour and attitudes. Including the
effects of mass media and advertisements, Hong and Lee (2014) report that about 80% of buyers
are influenced by someone’s direct referrals when making decisions.

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