A Fuzzy Set Approach in the Quantification of Technical Support Service Quality

J of Advced Transportation

Pietrucha³

2008

Driver satisfaction regarding travel information provided by variable message signs (VMS), which are part of the NamMountain Tunnel ATIS, was evaluated using fuzzy aggregation. Application of fuzzy aggregation to analyze driver satisfaction allows one to represent the variability and complexity of human perception with great fidelity. A fuzzy weighted average using two sets of fuzzy membership functions was applied to evaluate individual satisfactions of delay and travel time information provided. Then, those individual satisfactions were aggregated to estimate the driver group's overall satisfaction. The evaluated overall satisfaction was 0.65 for delay information and 0.63 for travel time information. Through these results, it was found that users of the travel information provided by the VMS in the NamMountain Tunnel ATIS were somewhat satisfied with the service quality. Those overall satisfactions were compared with a conventional weighted average and traffic operational effects to demonstrate the usefulness of the developed fuzzy method. IntroductionAdvanced traveler information systems (ATIS) are an intelligent transportation sub-area that has significant interactions between the system and users. In making the best use of these interactions, ATIS enable users to enhance their personal mobility, safety, and satisfaction D. Lee, C. Lee, M. T. Pietrucha 6with transportation services. These interactions include delivering data directly to travelers or allowing them to make better choices about alternate routes or modes of transportation. An important element in the transmission of information to travelers, as part of ATIS, is the variable message sign (VMS).Along with understanding these interactions, the evaluation of users' perceptions regarding the service quality of ATIS is also important. However, ATIS service quality is usually evaluated based on the investigation of traffic operational effects. For example, how does the installation of ATIS along the road affect average travel speed or average delay? This evaluation does not consider transportation user aspects, such as how the users perceive the service quality of these devices or how satisfied the users are with the service they are receiving. There are some evaluations of VMS that only assess the traffic operational impacts of traveler behavior based on the information the travelers received from VMS. Yim and Ygnace [1996] evaluated traveler responses to VMS in France using loop detector data. They analyzed how drivers responded in their route choice behavior to information about different lengths of delay. A study in the Netherlands evaluated network-wide effects of VMS in Amsterdam using several operational indicators including severity of congestion, traffic performance, and instantaneous travel time delay [Kraan et al., 1999].Another means to evaluate VMS is to investigate directly a transportation user's satisfaction with the provided transportation service. To investigate their satisfaction, a survey asking users their opinions regarding infor...

Section: Fuzzy Setsmentioning

confidence: 99%

Evaluation of driver satisfaction of travel information on variable message signs using fuzzy aggregation

J of Advced Transportation

Pietrucha³

2008

“…Since Zadeh developed the concept in 1965 (11), fuzzy sets have been applied in various areas other than transportation engineering to assess user perception: the evaluation of service quality (12), the study of operator safety in industrial engineering settings (13), and applications for multiple-attribute decision-making processes (14,15). Fuzzy sets are classes with "unsharp," vague boundaries in which a flexible sense of membership is possible.…”

Section: Fuzzy Aggregation and Cultural Consensus Analysis Fuzzy Setsmentioning

confidence: 99%

“…Participants were asked to form an overall perception regarding the service qualities of 12 signalized intersections and to simultaneously evaluate their satisfaction with six service-element criteria for those intersections. Rao and colleagues conducted a survey that included an overall rating and specific perceptions of seven criteria about technical support service quality (12). In that study, these two perceptions were not compared, but the possibility of validating fuzzy aggregation output using these two perceptions was demonstrated.…”

Section: Validationmentioning

confidence: 99%

Incorporation of Transportation User Perception into Evaluation of Service Quality of Signalized Intersections

Transportation Research Record: Journal of the Transportation R

Kim²,

Pietrucha

2007

Concepts of transportation service quality are related to efforts to evaluate driving conditions and the level of satisfaction that transportation users perceive. However, few data have been gathered from actual users about perceived service quality. A new method is developed for the evaluation of transportation service quality using a fuzzy aggregation and a cultural consensus analysis technique. After a literature review was conducted, six analysis criteria that showed promise as relevant indicators were selected to apply the developed method to assess the service quality of signalized intersections. With the use of a fuzzy weighted-average technique on six criteria, individual perceptions regarding the service quality of signalized intersections were evaluated. Then, the weight of an individual's perceptions, measured with consensus analysis, was applied to estimate a more realistic, aggregated overall service quality rating of a signalized intersection. Through the consensus analysis, the competence scores–which indicate how “correct” and relatively important each individual's response is–were estimated and used for each participant. Experimental results indicate that user perceptions of transportation service quality fall in a narrow measurable range of the scale constructed to perform this measurement. In other words, users' perceptions are not easily distinguished and vary greatly by individual. Therefore, user-perceived service quality ratings do not correspond to the level of service evaluated using the Highway Capacity Manual method. Ratings of user-perceived service quality of signalized intersections evaluated by using the new fuzzy aggregation method are in better agreement with the actual perceptions that people hold than those obtained by using a more conventional method.

“…Meanwhile, there are several studies of service quality conducted by using fuzzy techniques. Rao et al developed a method for the quantification of consumer perceptions of technical support service quality in their 1998 study (2). They indicated that consumers' perceptions of service quality are qualitative and subjective.…”

Section: Literature Reviewmentioning

confidence: 99%

Use of Fuzzy Sets to Evaluate Driver Perception of Variable Message Signs

Transportation Research Record: Journal of the Transportation R

Pietrucha

Sinha

2005

Current methods for evaluating the quality of service provided by a variable message sign (VMS) may not yield results that represent the satisfaction drivers experience because these techniques cannot represent the variability and complexity of human perception with great fidelity. To solve those problems, a new method that applies fuzzy set theory was developed. Results of a preexisting survey of VMS service quality were reanalyzed with this method. For this application, two membership functions were constructed with two different experimental methods: interval estimation and pairwise comparison. Specifically, construction of the second membership function used Saaty's eigenvector method. These two membership functions employ five linguistic statements to represent the degree of satisfaction and relative importance of six performance criteria. Quality of VMS service perceived by an individual driver was evaluated with the concept of the fuzzy weighted average. A set of 322 quality measures was computed, and they were aggregated and transformed into a single percentage value with the use of an arithmetic fuzzy mean. The defuzzified final value indicates the degree of satisfaction with VMS service perceived by a group of participating drivers, taking into consideration the variance of human perception and the degree of importance of the six criteria. By employing the proposed method, the quality of VMS service as subjectively perceived by humans and influenced by various exogenous factors can be evaluated while still considering the subjective and complicated manner of human thinking.