Ke-Hong Chen’s research while affiliated with National Chi Nan University and other places

Although the coronavirus disease (COVID-19) has been under control in Taiwan, the accumulated number of confirmed patients has reached up to 14,853, where 661 cases were fatal with a fatality rate of 4.45% (since the virus outbreak until July 1, 2021). Globally, the toll of confirmed cases has reached 182,641,391 people, where 3,955,679 cases were fatal with a fatality rate of 2.17% (from the virus outbreak until July 1, 2021). Considering the disease has not been under control yet and IT still significantly influences people’s daily travel behavior worldwide, it is urgent to investigate as to what extent it changes people’s travel habits. Therefore, we conducted a survey from April 24 to May 2, 2020, to obtain data on Taiwanese people’s travel behavior before and after the outbreak of COVID-19. Two models, logistic regression and ordered logit models, were used. As for the models’ performance, the estimated thresholds of the ordered logit model are significantly positive, and its coefficient is smaller than that of the logistic model, indicating that the estimated coefficients would be overestimated if the dependent variable is dichotomous. Hence, this study suggests that the influence of COVID-19 on travel behaviors in Taiwan can be explained by the ordered logit models. Several important conclusions are described as follows. First, people might significantly reduce travel activities related to social entertainment during the pandemic outbreak. Second, the total travel activities by private vehicles are significantly reduced, while there is no significant decrease in the use of transit. Finally, the important explanatory variables included the importance of the time to promote government policies (such as implementing the real-name registration system for mask purchases, publishing confirmed cases, and establishing the transit disinfection system), types and number of weekly activities, and storage of various types of consumer goods. The results of our study can serve as an important reference for accommodating similar scales of pandemics occurring in the future.

In the present study, we used the stated preference approach to design different situations, including appearance, different services, and different times to further explore passengers’ acceptance of and expected price to be paid for taxi service levels. In addition to using general ordered models, the results of this study were also compared with the multinomial logit model and the partial proportional odds (PPO) model. The results of comparison between the models ultimately revealed that the PPO model statistically had a better explanatory power. In the model estimation results, the key explanatory variables included the ability to recognize the appearance, seating space, honorable service, the development of user payment concepts, and demographic grouping, all of which could increase acceptance. The results obtained in this study could provide a key reference for the classification of taxis in the Taiwan region and serve as a basis for the development of strategies by operators in the future.

Much research has verified that the active development of the High Speed Rail (HSR) can create business activities and promote tourism growth. However, based on the related research review, there is currently a lack of profound discussion on the development of the overall transportation system and tourism growth in Taiwan, thus, this study intends to discuss this issue and hopes to provide an important reference for future regional development. This study conducts an in-depth investigation of the relationship between HSR and tourism volume. The Difference in Difference (DID) model is used to verify the impact of HSR services on the tourism volume in Taiwan. In addition, the aggregate data of socio-economic variables and the constituent factors of the transportation mode are incorporated. Finally, the possible consequences are described through elastic analysis. The results of this study can be an important reference for the future development of counties and cities.

Although there is research focused on real-time traffic information, in terms of types of information, timing of provision and drivers’ acceptance, not much is related to quantifying real-time traffic information and its perceived value, i.e., amount of information and willingness to pay (WTP) for that information. In this study, freeway drivers’ preferred types of real-time traffic information and their willingness to pay for them are investigated. Due to traffic information having the property of non-market goods, a contingent valuation method is applied. A computer-aided survey was conducted in rest areas along freeways to obtain the samples needed. A Spike model is used to overcome the serious biases that would otherwise be caused by numerous zero WTPs in samples when logit and probit models are used. Finally, freeway drivers’ WTP for different types of real-time traffic information can be obtained from the estimation results. The results may be of importance in pricing different types of traffic information more realistically in the future.

This study investigates the effects of various factors on highway drivers' speeding behaviour and estimates the amount of money that a highway driver is willing to pay for speeding violations in Taiwan. The contingent valuation method is applied to measure drivers' preference and to derive the value function of the amount of money. Logit and probit models are estimated to analyse the significant variables influencing speeding behaviour and to calculate the willingness to pay for speeding violations. The research results show that increasing speeding fines is an effective way to reduce illegal driving behaviour on highways. Significant variables affecting highway drivers' speeding behaviour include gender, engine capacity, past offenders in the previous year, and the risk‐seeking characteristics of drivers. Finally, the logit and probit models show that the amounts of money that highway drivers are willing to pay for speeding violations are $US119 and$US116, respectively. Copyright © 2012 John Wiley & Sons, Ltd.

Taiwanese drivers, like most drivers, often exceed the legal speed limit and expose themselves to the risk of fine. Although the propensity to exceed the legal speed limit is common in many counties, it is of interest to understand the amount that drivers are willing to pay for driving faster than the law permits. This may provide useful guidance on the extent to which current fines are adequate as a deterrent to speeding. In this paper, the contingent valuation method (CVM) is used to measure drivers' preferences and to estimate econometric models to determine Taiwanese drivers' willingness to pay (WTP) for driving faster than the law allows. Given the high incidence on a zero WTP, a spike model is used to capture this phenomenon. The study identifies some key influences on WTP such as the personal income, the presence/absence of past violations, the risk tolerance of the driver, and the proportion of time spent on the roads where the driver exceeded the speeding limit last year. On average, the freeway drivers in various locations in Taiwan were willing to pay between $43 and$51 for driving faster than the law allows.

A computer-aided survey was designed and conducted face-to-face with freeway drivers in Taiwan to gauge the demand for and reasonable pricing of customized real-time traffic information in the event of three different traffic conditions. Bivariate ordered probit models were estimated to investigate factors that significantly influence the demand for traffic information both for main freeways and secondary alternative routes. The results indicated that the demand for traffic information for non-recurring conditions was the strongest of the factors investigated. Basic information was the main type of information requested for normal and recurring conditions, whereas dynamic travel time prediction was the main type of information requested for non-recurring conditions. The estimation results from bivariate ordered probit models showed that by providing node-to-node information and encouraging a greater willingness to pay for information the demand for traffic information about main freeways and secondary alternative routes will increase. Finally, the significant and positive correlations of models imply that the greater the demand for traffic information about main freeways, the greater the demand for information about secondary alternative routes.

A distinguishing feature of this study is that drivers’ attitudes and preference towards risk were considered and their perceptions of gains and losses were modelled using cumulative prospect theory (CPT). The parameters of the value function and the weighting function were estimated to reflect the risk attitudes of freeway drivers in Taiwan. The resulting estimates showed that the behaviour of most Taiwanese freeway drivers can be captured by the features of CPT if real-time traffic information is used.

In an attempt to reduce CO2 emissions from motorized transport, the Taiwanese government introduced an idling stop policy for vehicles in early 2007. This paper seeks to quantify the environmental benefits of the policy based on a stated preference analysis. Motorcyclists were surveyed at urban intersections in Taiwan, to identify the amount of time they would be willing to turn off their engines while waiting at traffic lights (the WTO). A contingent valuation framework based on stated preference questions was designed to determine the WTO. Results obtained from the Spike model showed that the average motorcyclist’s WTO is 82s. In another analysis, in which other variables were taken into consideration, such as the possibility that the policy will be enacted as legislation, the expected WTO increased to 101s. In both cases, an idling stop policy would have positive environmental effects, reducing gasoline usage by 1021L per hour and reducing CO2 emissions by 0.56 metric tons per hour at the intersection studied during peak periods. KeywordsIdling stop policy–Contingent valuation–Spike model–Environmental effect