Yi-Shih Chung

Factor complexity of crash occurrence: An empirical demonstration using boosted regression trees

Factor complexity is a characteristic of traffic crashes. This paper proposes a novel method, namely boosted regression trees (BRT), to investigate the complex and nonlinear relationships in high-variance traffic crash data. The Taiwanese 2004-2005 single-vehicle motorcycle crash data are used to demonstrate the utility of BRT. Traditional logistic regression and classification and regression tree (CART) models are also used to compare their estimation results and external validities. Both the in-sample cross-validation and out-of-sample validation results show that an increase in tree complexity provides improved, although declining, classification performance, indicating a limited factor complexity of single-vehicle motorcycle crashes. The effects of crucial variables including geographical, time, and sociodemographic factors explain some fatal crashes. Relatively unique fatal crashes are better approximated by interactive terms, especially combinations of behavioral factors. BRT models generally provide improved transferability than conventional logistic regression and CART models. This study also discusses the implications of the results for devising safety policies.

Analyzing heterogeneous accident data from the perspective of accident occurrence

Clustering and classification approaches have been commonly applied in reducing the heterogeneity in accident data. As part of an effort to understand the features of the heterogeneity, this study assessed accident data from the perspective of accident occurrences. Using the rule-based classification method, rough set theory, rules were derived which consisted of indispensable factors to certain accident outcomes and reflected the process of accident occurrences. The occurring frequency of each derived rule was then adopted as the basis for grouping accidents for further analyses. Empirical results showed that rules with high occurring frequencies were largely related to drivers with high-risk characteristics. On the other hand, road facilities played a key role in rules with low-occurring frequencies. The distinctive features indicated the essential differences between the frequently repeated and the sparsely unique processes of accident occurrences. This suggests that the heterogeneity of accident data is not limited to one single factor, such as age, gender or area. Thus, the proposed approach, which takes the process of accident occurrences into consideration, can be a potential alternative to more comprehensively analyze the heterogeneity in accident data.

Developing effective professional bus driver health programs: An investigation of self-rated health

The health of professional bus drivers is a critical factor in their driving performance; any impairment may lead to undesired consequences. In an attempt to develop and prioritize health and wellness programs, this study investigates the factors significantly affecting the health conditions of professional bus drivers, as well as the strength of these factors. This study uses self-rated health as the examination measurement. This simple assessment is an inclusive measure of health status for judging health trajectory, and is highly associated with changes in functional ability, including perceived control over driving. This study evaluates driver responses of self-rated health with ordered response models that consider factors such as the driver reported health problems, physical and psychological conditions, demographic factors, driving experience, and working environment. Analysis of a sample of 785 drivers shows that age, body mass index, depression, daily working hours, perceived company safety culture, and health problems are the factors significantly affecting self-rated health. Depression has the greatest effect among all factors except health problems. Unlike the linear relationships for the other factors, the relationships between depression levels and perceived health are S-shaped. The results of ordered response models suggest that these influential factors have distinct effects on the self-rated health of individual drivers and on the different levels of self-rated health.

Seemingly irrational driving behavior model: The effect of habit strength and anticipated affective reactions

An increasing amount of evidence suggests that aberrant driving behaviors are not entirely rational. On the basis of the dual-process theory, this study postulates that drivers may learn to perform irrational aberrant driving behaviors, and these behaviors could be derived either from a deliberate or an intuitive decision-making approach. Accordingly, a seemingly irrational driving behavior model is proposed; in this model, the theory of planned behavior (TPB) was adopted to represent the deliberate decision-making mechanism, and habit strength was incorporated to reflect the intuitive decision process. A multiple trivariate mediation structure was designed to reflect the process through which driving behaviors are learned. Anticipated affective reactions (AARs) were further included to examine the effect of affect on aberrant driving behaviors. Considering the example of speeding behaviors, this study developed scales and conducted a two-wave survey of students in two departments at a university in Northern Taiwan. The analysis results show that habit strength consists of multiple aspects, and frequency of past behavior cannot be a complete repository for accumulating habit strength. Habit strength appeared to be a crucial mediator between intention antecedents (e.g., attitude) and the intention itself. Including habit strength in the TPB model enhanced the explained variance of speeding intention by 26.7%. In addition, AARs were different from attitudes; particularly, young drivers tended to perform speeding behaviors to reduce negative feelings such as regret. The proposed model provides an effective alternative approach for investigating aberrant driving behaviors; corresponding countermeasures are discussed.

Transportation research trends in environmental issues: a literature review of methodology and key subjects

Environmental issues have been a popular topic in various academic research areas including transportation. The aim of this paper is to identify major environmental research topics and research methods in the transportation field and thereby explore possible global research agenda. This paper selected a total of 1,291 papers from 51 journals based on keywords including both transport and environment. The literature survey shows that the number of environmental issue papers published in transportation journals has been growing significantly since 2007. Greenhouse gas emission is among the hottest topic in our literature survey. Little environmental research was conducted regarding maritime transport, as compared to passenger, land and aviation sectors. In terms of popular methodologies adopted to tackle environmental issues in the transportation journals, the top three methods are emission analysis, survey and simulation. There is plenty of room in conducting future transportation research in environmental topics, particularly in the maritime field.

Burnout in seafarers: its antecedents and effects on incidents at sea

ABSTRACT Seafarer health and well-being has long been a concern in the shipping industry because of the unique characteristics of working at sea. This paper aims to identify the role of burnout in seafarer health and well-being and its effect on safety. In particular, we differentiated seafarer burnout into personal and work-related burnout to reflect the ambiguous distinction between rest and work in seafarers’ job environment. We also investigate the effectiveness of emotion regulation for seafarers to reduce burnout. This study proposes a conceptual framework to identify the causal relationship between occupational stress, sleepiness, emotion regulation, burnout, and incidents at sea. To verify the proposed framework, scales were adapted from established scales in the literature; a cross-sectional survey was also conducted to collect empirical data for analysis with path and simultaneous equation models. The analysis results revealed that personal and work-related burnout in seafarers are mutually affected; however, only work-related burnout exerts a direct effect on incidents. Reappraisal is an effective emotion regulation strategy in seafarers to reduce personal burnout, but not work-related burnout. Occupational stress and sleepiness exert positive effects on both personal and work-related burnout; yet, their effect on incidents is mediated by work-related burnout.

Comparison analysis for subjective and objective weights of financial positions of container shipping companies

This paper explores the positions of financial ratios identified utilizing both subjective and objective weighting methods—the consistent fuzzy preference relation (CFPR) and entropy—based on questionnaires collected from experts and the financial statements of major shipping companies in Taiwan and Korea. The comparison of perceptions of financial ratios by country and by expert group illuminates some financial aspects that experts may have ignored or not paid close attention to during the business operating process, especially in today’s turbulent world shipping market. The major results of this paper show that experts in the two countries have different perceptions of the debt-to-equity ratio and that by combining the results of objective and subjective weights, categorization of financial ratios by quadrant can help decision-makers find business options and strategies to improve the financial performance of their companies. This research approach may be applied to other business entities, improving on the direct rating method used in previous studies.

Effect of Burnout on Accident Involvement in Occupational Drivers

Managing the health and wellness of occupational drivers requires the recognition of burnout as an occupational hazard. However, the literature is dominated by studies of stress rather than burnout. The manner in which burnout may affect accident involvement is investigated in occupational drivers. The proposed causal structure is based on the stressor–strain model, in which burnout mediates between occupational stress and accident involvement. The study recruited 915 public transport drivers. The Copenhagen Burnout Inventory and an effort–reward imbalance scale were adopted to measure burnout and occupational stress, respectively. Results of the analysis indicated that burnout exerted a direct effect on accident involvement beyond the effect of occupational stress. Enhancing the perception of a safety culture does not significantly reduce the effect of occupational stress on burnout; however, it does significantly reduce the effect of burnout on accident involvement and thus indirectly alleviates the effect of occupational stress on accident involvement. In summary, as a comprehensive measure of the adverse effect of various types of chronic stressors, burnout provides a strong indicator for the identification of drivers who pose a risk to the organization and to road safety. Burnout management should be incorporated into overall stress management. Occupational drivers normally experience a low level of empowerment and long work hours; thus, a safety culture is crucial to this occupational category to reduce burnout and ensure workplace safety.

Exploring the Impact of Introducing Scheduled Flights on Aviation Markets: Experience from Opening of China–Taiwan Nonstop Flights

The commencement of regular nonstop flights between mainland China and Taiwan in December 2008 was expected to increase the flow of traffic across the Taiwan Strait. Travelers would no longer have to stop to change aircraft; the flight between mainland China and Taiwan would be quicker, cheaper, and more convenient. Hong Kong and Macau, formerly the gateways connecting Taiwan to China, would now compete with point-to-point nonstop flights available to cross-strait travelers. The aim of this study was to examine the evolving supply and demand associated with the aviation market between China and Taiwan and to focus on the changes resulting from the introduction of scheduled nonstop flights. Data covering a 15-month period were collected and analyzed by using multilevel models. The results show that despite rapid growth in the nonstop cross-strait air travel market, growth rates are still restricted by limitations set by the Chinese and Taiwanese governments, particularly those routes connecting Taiwan with first-tier Chinese cities. For this reason, some travelers are forced to make a detour through Hong Kong or Macau on their way to China. However, city pairs connecting Taiwan with second- or third-tier Chinese cities have not performed as well as expected, and some markets have even demonstrated a negative trend over time, indicating a shrinking market. The market for cross-strait air travel exhibits clear heterogeneous characteristics in city pairs, which should be considered as governments take the next steps in opening up the market.

Method of Selection of Poisson-Based Wavelet Shrinkage Sites:

When effective programs to improve roadway safety are being developed, one of the primary tasks is to select sites for data collection. Selecting sites by ranking them simply by crash counts or crash rates is a common practice of transportation agencies because only crash data are required. Although the empirical Bayes (EB) method is a better option for site selection than this simple ranking method, the EB method requires additional data that might not be readily available or up to date, such as on annual average daily traffic and roadway characteristics, and this requirement could subsequently hinder the implementation of any EB method. This research, sponsored by the Georgia Department of Transportation, is motivated by the need to develop a more effective site selection method. The contributions of this paper include (a) proposing a Poisson distribution–based wavelet shrinkage site selection (WASSS) method that can incorporate various wavelet shrinkage methods; (b) obtaining a superior wavelet shrinkage method, the Bayesian Multiscale method (BMSM), for WASSS by evaluating various wavelet shrinkage methods; and (c) comparing the EB method and this proposed WASSS method. It is found that the proposed BMSM-based WASSS method, as compared with the EB method, produces slightly better (or at least the same) level of performance (i.e., in terms of rates of false negatives and false positives); in addition this proposed method does not require additional data (as does the EB method). This study demonstrates that the proposed WASSS method is a promising site selection alternative that requires only crash data and that performs acceptably.