1. Introduction
The daily activities of people who live in the Bangkok Metropolitan Region, especially those who do not own personal vehicles, are supported by public transportation as an intermediary to link almost all such activities. As a result, public transit is unavoidably important and connected to their everyday lives. In particular, the bus operated by the Bangkok Mass Transit Authority (BMTA) helps link all public transportation networks and has more than 200 million users each year, which is more than all forms of mass transportation systems provided in the Bangkok Metropolitan Region
[1]. However, a survey showed that the number of bus users has continued to decline: the number of bus passengers per day in 2013 was 690,000, but in 2021 it was found that there were only 491,673 people per day
[2]. This means that the number of bus passengers dropped an average of 22,036 people per day per year from 2013 to 2021. Furthermore, there are still problems with traffic congestion, traveling time, and travel routes that are not yet covered in all areas, so these issues are considered the main problems that should be urgently addressed.
Traffic problems in Bangkok are likely to worsen as the number of private cars increases. This is a problem that must be thoroughly studied, analyzed, and solved properly and systematically. Both domestic and international organizations have conducted extensive research on the problems associated with mass transit systems. Khemapech and Kidbunjong
[3] identified the issues and challenges confronting Bangkok’s mass transit system development, and they showed that the quality of the mass transit system in Bangkok lags behind other major cities in the region. The rail project was developed as a stand-alone project with no connection to the bus system. The network connection between the public transportation system, the activity source, and the community is inefficient. Moreover, Bangkok residents spend a lot of time and travel expenses without being able to predict the time it takes to travel. The traffic area is mainly occupied by private cars.
Bangkok is known for its severe traffic congestion and has a congestion level of 44%. This means that a 30 min trip in Bangkok will take 44% more time than it would under normal, uncongested conditions. Furthermore, a study reported that Bangkok commuters spend an additional 35 min per trip, resulting in an opportunity cost of THB 11 billion annually or THB 66 million daily
[4]. This issue also led to a THB 6 billion increase in Thailand’s fuel spending per year and forced many Bangkok commuters to reallocate their spending
[5]. The government is making efforts to encourage residents to use public transportation instead of personal cars in order to reduce road congestion and address PM2.5 issues, which are primarily caused by cars. However, the coordination in addressing these issues is not as unified as it should be, and there are still flaws in the discipline of road users. All of these things are important factors causing more traffic problems. However, the service attributes are numerous and wide-ranging. Commuters are not only concerned about safety, speed, punctuality, and convenience, but also value the driver’s service attitude, information provision, a friendly ride environment, etc.
[6].
From a business operation perspective, in a fiercely competitive market, improving service quality to attract customers and make them loyal customers has become an important issue for many companies. However, when faced with limited resources, knowing how to formulate improvement strategies is an important issue. In traditional thinking and research, service quality is often evaluated as either good or bad based on sophisticated indicators for each attribute, and improving bad service quality is believed to increase customer satisfaction and repurchase rates
[7]. However, in a complex reality, if you blindly invest in the improvement of unreasonable service attributes, you cannot know the impact on customer satisfaction, which often prompts companies to face the dilemma of increasing sunk costs with no improvement in operating performance
[8].
Mass transportation is very important for national development both economically and socially, especially in reducing residents’ living costs. In addition, having a good public transportation system, a variety of modes of transportation, and convenient and reasonable prices also helps tourists decide to travel to Thailand as well, resulting in the growth of the Thailand tourist industry. Based on the survey results of the Office of the Permanent Secretary of the Prime Minister’s Office on the number of complaints, it was found that the BMTA was the state enterprise with the highest number of complaints on average. The most complaints about the BMTA’s bus service regarded the quality of drivers, fare collectors, bus conditions, increasing numbers, expanding routes, services, and travel convenience
[9]. People in Bangkok spend a lot of time and expenses traveling without being able to predict the time spent traveling
[3]. While Bangkok already has the BTS SkyTrain and MRT subway, these do not cover all the routes available in Bangkok. The bus services in Bangkok are deployed to cater to locales beyond the purview of the BTS SkyTrain and MRT subway. The commuters still need to use the public bus for transport. Despite the interconnectivity of bus and subway stations, the schedules of the two modes of transportation do not always align perfectly. In addition, residents also rely on buses for transferring to other modes of transportation such as water transport and trains. Therefore, bus service still plays a crucial role as a mode of transportation for the residents. However, in some areas of Bangkok, passengers have raised significant concerns about the physical amenities and dependability of the bus services
[10,11][10][11]. Enhancing the service quality of Bangkok’s bus service is a crucial matter.
The quality of bus service is a significant research topic in the field of public transportation. This means if passengers are satisfied with the bus’s service quality, they will continue to use it and it can reduce the traffic problem, which tends to become more severe due to the increasing number of private cars. Susilawati and Nilakusmawati
[12] investigated the factors that affect the public bus transportation services quality in Bali Province, Indonesia. They identified six factors that influence the satisfaction of public transportation users in Bali: comfort, responsiveness, capacity, tangibility, safety, and reliability. Furthermore, Farrar et al.
[13] conducted a study on customer satisfaction with bus service users in Cape Town, South Africa. The study found that the most important service quality items for customers were the helpfulness of staff, affordability of fares, and reliability of buses not breaking down. The study revealed that there are certain areas in need of improvement, specifically the travel time after boarding the bus and the availability of routes. Therefore, service quality is a critical issue that the public sector should consider to provide commuters with an attractive alternative to private cars.
Service failure refers to any breakdown, flaw, or issue that occurs during the delivery of a service that leads to an unsuccessful service outcome or customer dissatisfaction. This affects the quality and reliability of the service; businesses are unable to deliver services that meet customer expectations, and issues are still not being resolved effectively until it may have a negative impact on the relationship with the customer. Services failure can be remedied through effective restoration, helping to keep customers loyal to the service. The service-restoration process can lead to positive word of mouth or help reduce negative rejection of erroneous services. Few studies have examined the quality risk concerning bus service. Wijaya
[14] explored service failure of public bus transportation in Jakarta, Indonesia. Commuters expect public bus services to be efficient, high quality, convenient, and affordable, but unfortunately, these expectations are often not met due to the buses being unreliable, uncomfortable, and even dangerous. Therefore, despite being a key solution to reducing the number of cars on the road, commuters often avoid using public buses due to their unreliability, lack of comfort, and safety issues. Hu and Hsiao
[15] developed a model of service quality risk assessment that combined Kano’s model, an importance–performance analysis (IPA), and a failure mode and effects analysis (FMEA). The service quality was assessed through a quantitative evaluation of quality risks, which allowed for the identification of improvement priorities for various attributes to enhance the overall quality of service. A useful tool for prioritizing improvements to bus service quality attributes is the quality risk evaluation developed by Hu and Hsiao
[15].
2. Combining Kano’s Model, IPA, and FMEA to Evaluate Service Quality Risk for Bus Service
2.1. Bus Service Quality
In the context of education, according to researchers, service quality is defined as the gap between a customer’s initial expectations and their actual experience with a particular service provider,
[16]. For the evaluation of service quality, the SERVQUAL model is one of the most commonly used models
[17]. The widely used SERVQUAL model, developed by Parasuraman et al.
[18], is an effective tool for evaluating service quality that analyzes the gap between customer expectations and perceptions of an organization’s service quality performance. Service quality is determined by two factors: perceived quality and expected quality. Perceived quality is the customer’s evaluation of the overall status and excellence of the service provided, while expected quality refers to the customer’s anticipated level of service
[19]. The SERVQUAL scale, also known as gap analysis, measures the extent to which the service quality meets customer expectations
[20]. According to Parasuraman et al.
[18], service quality can be defined as the sum of positive and negative service features that occur during the interaction process between the service provider and the customer. To assess service quality, Parasuraman et al.
[18] proposed a SERVQUAL scale that includes five crucial aspects of quality (tangibility, reliability, responsiveness, assurance, and empathy) to assess service quality. These five aspects serve as the evaluation criteria and provide a practical measure for assessing service quality.
The satisfaction and perception of the quality of the public transport system are crucial to its success. Grujičić et al.
[21] demonstrated that improving the cleanliness and ventilation of vehicles can have a dual effect on increasing user satisfaction and improving the overall impression of public transport quality. This in turn may attract more private car users to switch to public transportation. Therefore, an improvement in these elements should be a starting point in the process of enhancing the quality of public transport services with a focus on meeting the needs of both users and non-users.
Mahmoud and Hine
[22] conducted a study to examine the impact of perceived service quality on the perception of both current and potential users of bus services in Belfast City, UK. Their research revealed 11 key factors that influence passengers’ perceptions of the service. These factors include the frequency and reliability of the service, waiting and transfer times, security at stops/stations, bus comfort, availability of discounted tickets, information at stops/stations, bus fares, needs for transfers, bus stop locations, and availability of park and ride services. Chaikittiphorn and Pavakanun
[23] conducted a study on the bus service of the Bangkok Mass Transit Authority (BMTA) and identified areas where improvements were needed. The most pressing issue was the timeliness of the buses followed by the frequency or continuity of the buses, the poor condition of the buses, the coverage/thoroughness of the bus routes, the safety of the service, and the quality of the buses. By improving and developing the quality of the bus services, the majority of users were likely to switch to using more BMTA bus services. In a separate study, Pokwanvit
[6] investigated the factors that influence Bangkok commuters to switch from driving cars to using buses. The results showed that the top three factors were bus punctuality, sense of safety, and routing information, while payment methods and bus fare were the least important factors. The researcher recommended several improvements to the Bangkok Mass Transit Authority (BMTA) based on the study results. These included increasing the number of buses to reduce waiting times, providing clear and accurate information about bus routes and arrival times at each bus stop, and enhancing the mobile application to estimate the correct arrival time of the bus for which commuters are waiting.
Deb and Ali Ahmed
[24] conducted a study to investigate the service quality of the city bus service by examining users’ perceptions and expectations. The study findings indicated that passenger perceptions and expectations are both crucial factors in assessing service quality. Through the analysis, four underlying factors were identified: safety, comfort, accessibility, and timely performance. These factors were extracted based on the perceived and expected values of the passengers. Sonita et al.
[25] conducted an evaluation of the city bus service quality in Cambodia and identified five main factors that contribute to public transit service quality: the quality of the bus services, the condition of the vehicles, the attitude of the drivers, the facilities at the bus stops, and the bus capacity. Moslem
[26] utilized the AHP-BWM method to assess public transport quality based on four criteria: service quality, transport quality, tractability, and fare.
2.2. Kano’s Model
Kano’s model is one of the techniques used to study consumer demand and is based on the principle that consumer satisfaction with the product is strongly related to the ability to meet consumers’ needs. The consumer must achieve the highest satisfaction with the defect that causes the consumer’s least dissatisfaction. Customer satisfaction has often been seen as one-dimensional, which means that when the quality elements are sufficient, people feel satisfied (and vice versa); however, in reality, not all quality factors are the same
[27,28][27][28].
Kano et al.
[29] proposed a two-dimensional quality model that pointed out that the customer’s “satisfaction” and “quality attributes” are not completely linearly related. When the quality factors are sufficient, it may not make people feel satisfied, and sometimes it will cause dissatisfaction or unsatisfactory results; or when a certain aspect of the service does not meet the customers’ expectations, it can result in dissatisfaction. However, after improving these quality factors, there is no significant improvement in the satisfaction of consumers. It can be inferred that the quality attributes that affect consumer satisfaction or dissatisfaction are different. Chen and Lee
[30] also pointed out that quality factors may cause customers to be dissatisfied or indifferent.
Kano’s model classifies quality into five attributes
[29[29][31],
31], which are attractive quality attributes (A), one-dimensional quality attributes (O), must-be quality attributes (M), indifferent quality attributes (I), and reverse quality attributes (R). A Kano questionnaire allows for determining individual features/requirements of customers and referring to the significance of quality-perception features
[32]. Kano’s questionnaire is designed to ask questions about customer needs, and each question on customer needs is answered in a functional and dysfunctional format
[29,33][29][33]. The classification of attributes can be obtained by cross-checking the results of the positive and negative responses of the interviewees. Participants can choose from five response options when answering each item: “I like it that way”, “I expect it to be that way”, “I am neutral”, “I can accept it that way”, and “I dislike it that way”.
Table 1 provides a questionnaire matrix that categorizes a quality attribute as either functional or dysfunctional. Matzler et al.
[34] found that the customer’s most important quality element was must-be quality followed by one-dimensional quality. Therefore, when some quality attributes cannot be classified into a certain category, the classification rule is M > O > A > I
[35].
Table 1.
Kano Category Table.
In addition, Berger et al.
[33] developed two customer satisfaction indices based on Kano’s model to analyze the impact of meeting certain attributes on customer satisfaction. The satisfaction increment index (SII) is used to measure the increase in customer satisfaction after a certain attribute is met, while the dissatisfaction decrement index (DDI) is used to measure the decrease in customer dissatisfaction after meeting their demand
[33,34][33][34]. SII and DDI are calculated using the percentage numbers of the A, O, M, and I from Kano’s model. The formulas used to calculate customer satisfaction coefficients are shown below
[33].
Kano’s model has been applied in many other industries. Materla et al.
[37] conducted a systematic search of databases to explore the application of Kano’s model in service quality improvement, business growth, and sustainability in the healthcare industry. Moreover, Chiang et al.
[38] employed the Kano methodology in the hotel industry and obtained valuable insights that can guide hotel operators who intend to incorporate technology in their establishments. Currently, many industries face higher competition to fulfill customers’ demands and product design requirements. Backar
[39] utilized Kano’s model to enhance the development of a light bulb changer and to ensure customer satisfaction and requirement tracking in future product development. In addition, Pai et al.
[40] utilized Kano’s model to categorize restaurant service quality attributes and examine how each attribute may affect customer satisfaction differently. Kano’s model was also used in the airline industry. Wong and Ho
[41] applied Kano’s model to low-cost carrier airlines to identify the service area that needed to improve and pay attention to increasing customer satisfaction in the future.
2.3. Importance–Performance Analysis (IPA)
Martilla and James
[42] introduced the importance performance analysis (IPA). An IPA is typically presented as an importance–performance matrix, which shows the relationship between the level of importance that customers place on various aspects of an institution’s services and their level of satisfaction with those aspects. In other words, this concept is used to measure or assess consumers’ acceptance of a product for a variety of characteristics. It is an easy-to-use analytical method for evaluating or measuring the performance and importance of a product that can lead to a breakthrough in effective marketing. By analyzing customer perceptions of importance, the most dominant variable can be identified and associated with the reality of the customer experience. For instance, if price is deemed a crucial factor by customers but they perceive the price to be high, then reducing the price could improve the company’s performance. This can be represented in an importance–performance matrix that combines customer satisfaction levels with an institution’s services
[43].
An IPA has been widely used in many other industries. Disastra et al.
[44] applied an IPA in the tourist industry to investigate the tourists’ satisfaction levels with tourism destination attributes in Ciamis Regency, Indonesia. By using IPA, they knew which attributes needed to be a priority to improve and which attributes should be maintained to ensure tourist satisfaction. Moreover, Simpson and Parker
[45] utilized an IPA to evaluate the importance and satisfaction levels of public green infrastructure and urban nature spaces in Perth, Western Australia. By applying the IPA technique, the researchers were able to collect valuable data that could be used to inform evidence-based approaches for managing and allocating resources to PGI and UN spaces. Das and Basu
[46] utilized an IPA to evaluate the satisfaction of local communities with ecosystem services in Chatra Wetland, India. An IPA has also been used by colleges for measuring student satisfaction levels to increase competitive advantages. Zulfahri et al.
[7] implemented an IPA to evaluate services provided to students so the college could improve the quality of service based on students’ perspectives to increase student satisfaction in the future.
An IPA has the advantage of assessing consumer acceptance in marketing programs. It is a low-cost assessment, has easy-to-understand assessment techniques, and provides important in-depth information in terms of the marketing mix. It is very important in defining the marketing mix of an organization because it allows management to analyze what factors are important to improve and develop and to effectively manage the company’s resources or budgets.
2.4. Failure Mode and Effect Analysis
A failure mode and effects analysis (FMEA) focuses on identifying the nature of the damage or the cause that could lead to the failure (potential failure mode) due to the design, manufacture, or service. After that, the impact of the expected damage (effects analysis) will be analyzed, and finally, a way is found to prevent the expected damage (problems prevention)
[47]. Using FMEA principles to analyze and solve the root of real problems in the process (design, manufacture, or service) will give manufacturers a more comprehensive perspective on problem solving, which will reduce repetitive problems and thus result in reduced variations in the manufacturing process
[48]. Therefore, every product is of consistent quality and meets the required standards. During an FMEA, risks are prioritized based on predefined criteria, and actions are then taken to address the higher-priority failure modes first
[49].
The FMEA technique was developed for aerospace, vehicle, and military applications in the 1950s and was initially known as the failure mode effects and criticality analysis (FMECA); later in the 1960s it was applied to reliability engineering
[50]. The FMEA technique is a widely used method for engineering risk analysis aimed at identifying possible defects and predicting their consequences. It was developed and applied to assess the risk of defect characteristics in design, process, and quality management, and it is a popular tool in these areas
[51]. A risk analysis using the FMEA technique prioritizes the risk of the critical failure characteristics (potential failure mode) under the risk priority number (RPN) obtained from the three criteria assessments: severity: S, occurrence: O, and detectability: D; this is calculated as PRN = S × O × D
[52]. To evaluate the severity, occurrence, and detectability of each failure mode, a 10-point scale is used. Failure modes with higher RPN values are considered more critical and given higher priority than those with lower RPN values
[52,53][52][53]. While FMEA techniques are widely used across various industries to assess the risks of failure modes, multiple expert opinions can result in vague and imprecise risk evaluations, leading to conflicting evidence that can be challenging to manage. As business situations become more complex with uncertainties and service process characteristics, FMEA applications are continuously evolving and becoming more advanced
[54].
FMEA has been applied in many other industries and is widely used by many companies worldwide to develop new designs and technologies and analyze and plan the quality of production processes and products. An FMEA has been used in previous studies to assess service quality and enhance the quality of services provided in the airline industry
[15,55,56][15][55][56]. Anjalee et al.
[57] applied an FMEA in the healthcare industry to improve medication safety in the medication use process. The authors used an FMEA to analyze both existing systems and new policies to identify potential errors in the system. Borkovskaya and Passmore
[58] applied an FMEA in the construction industry in the Russian Federation and demonstrated its potential application to ecological issues. Applying the FMEA methodology in ecology enables developers to evaluate the risks and potential damages resulting from inconsistencies in design and technological processes at the early stages of product development. Tang et al.
[59] proposed a method for enhancing the service quality of logistics centers by integrating an FMEA with Kano’s model. The approach allows for the identification of potential failures and their consequences as well as the evaluation of customers’ satisfaction and dissatisfaction with logistics center services.