Human Factors and Ergonomics in Manufacturing, Vol. 18 (4) 454–463 (2008) C 2008 Wiley Periodicals, Inc. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/hfm.20102
Human Factors and Usability in Service Quality Measurement Lesley Strawderman Department of Industrial and Systems Engineering, Mississippi State University, Mississippi State, Mississippi 39762, USA Rick Koubek Harold and Inge Marcus Department of Industrial and Manufacturing Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA
ABSTRACT The purpose of this study was to develop a modified measurement instrument for service quality that includes human factor considerations. Tangibles, reliability, responsiveness, assurance, and empathy were dimensions commonly used to measure service quality through a survey instrument termed SERVQUAL. A sixth dimension, usability, was added in a modified survey instrument termed SERVUSE. To examine the predictive power of both instruments, 200 patients at an on-campus health clinic were surveyed. The survey measured subject expectations and perceptions regarding the service system. Gap scores were calculated as the difference between these two measures. Positive gap scores reflected the exceeding of customer expectations. Negative gap scores reflected a failure to meet these expectations. The three response variables were perceived quality, satisfaction, and behavioral intention. Usability was found to be a significant predictor of all response variables. It also adds C 2008 significant predictive value to the regression models when measuring behavioral intention. Wiley Periodicals, Inc.
1. INTRODUCTION According to the Bureau of Labor Statistics, nearly 79 million Americans are employed in the service sector. This includes jobs that are derived from the performance of services, rather than the production of a product. In the United States, services represent nearly 74% of the gross domestic product (Albrecht & Zemke, 2002). These statistics demonstrate the prevalence of service industries in our society and the need to apply scientific knowledge to aid in the success of service. Human factors has traditionally focused on product and process improvement in manufacturing, product design, and human–computer interaction. A logical extension of human factors would be into the service sector. There is a large human component in most service systems, including both the customer and company ends of the spectrum. Because of this large human involvement, the use of human factors in these systems appears justified. By utilizing human factors theories, tools, and techniques, service systems can be improved to be more productive, effective, safe, and comfortable for employees and customers. The Correspondence to: Lesley Strawderman, Department of Industrial and Systems Engineering, Mississippi State University, P.O. Box 9542, 39762, Mississippi State, MS. E-mail:
[email protected]
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overall goal of this project is to develop a modified measurement instrument for service quality that includes human factor considerations. 2. SERVICE QUALITY 2.1. Defining Services Services consist of two components: a technical outcome and a functional outcome. The technical outcome is often referred to as the what of service. It is that which is delivered to the customer. The functional outcome is often referred to as the how of service. It consists of the service delivery process (Brown, Gummesson, Edvardsson, & Gustavsson, 1991; Schneider & White, 2004). Consider a service system in a restaurant. The technical outcome is the meal that is eaten by the customer. The functional outcome consists of being seated and placing an order. All service systems can be defined by these two components. Services can be characterized by three defining features: intangibility, inseparability, and heterogeneity. These features are what separate services from goods. Services cannot be seen, touched, or held. They are intangible in the sense that they have no physical manifestation (Schneider & White, 2004). Service industries supply the needs of the customer without producing tangible goods (Stebbing, 1990). Similarly, services are perishable. They cannot be stored, resold, or returned. Consumption occurs immediately following production (Zeithaml & Bitner, 2003). The production and consumption of a service cannot be separated. Therefore, services are inseparable (Schneider & White, 2004). There is no way to make a service, inspect it, fix any problems, and then deliver it to a customer. The customer is present while the service is being produced. Therefore, the customer views and often takes part in the production process (Zeithaml & Bitner, 2003). Customer activities at the time of service delivery are often essential to the completion of the service transaction (Wetzels & de Ruyter, 2001). Based on the notion that production and consumption of a service occur simultaneously, companies strive to ensure that a maximum number of customers are available to consume the service as it is being produced (Schneider & White, 2004). Examples of this can be seen in entertainment venues, airline flights, and education systems. Services are heterogeneous. The human element in the production and delivery of services results in no two service instances being identical (Schneider & White, 2004). Customers have different demands from one another. Additionally, different service personnel will deliver the same service in different manners. This high degree of person-to-person interaction lends to the heterogeneity of services. Services can also be different each time an individual experiences the service (Schwantz, 1996). Services are highly people and behavior dependent. Each individual has unique needs and expectations that he or she is seeking to satisfy (Sarkar, 1998). 2.2. Human Factors in Services Human factors has been utilized in a number of areas. In product design, human factors can make the product user friendly and satisfying for the customer. In manufacturing, processes are designed to increase safety as well as productivity and quality (Karwowski & Salvendy, 1998). Human factors has also been used in many service industries, including hospitals and health care, package delivery, and air traffic control. These service applications have looked primarily at the employee’s workplace environment. The internal operations of a service industry are often studied. However, human factors has not been used to improve Human Factors and Ergonomics in Manufacturing
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the service delivery process. The customer relation and involvement in the service process could benefit from the use of human factors. The potential use of human factors in service industries can be described using this definition of human factors: Human factors discovers and applies information about human behavior, abilities, limitations, and other characteristics to the design of tools, machines, systems, tasks, jobs, and environments for productive, safe, comfortable, and effective human use. (Sanders & McCormick, 1993, p. 5)
By decomposing this definition into goals, systems, and attributes, we are able to see how the field of human factors is well matched with service industries. The goal of human factors, as described in the definition, is to create systems that are productive, safe, comfortable, and effective. A productive service is one that provides the service requested by the customer. There is a high output of services provided when compared to the amount of input required. The customer accomplishes his or her goal with a productive service. A safe service is one that keeps customers and their assets protected. A comfortable service is one that is easy for the customers to access and use. It also makes the customers feel at home and put trust into the service organization. An effective service meets a customer’s requirements and needs. It accomplishes its goals for service delivery. The systems addressed by human factors include tools and machines, tasks and jobs, and environments. Tools and machines are items that are utilized in the service process. This may include computers, interfaces, or office equipment. Tasks and jobs are completed throughout the service process. These may be completed by the customer or the company. Environments are the surroundings of both the customer and the company. They may include an office setting, home, restaurant, or even a Web site. Attributes of human factors include human behavior, limitations, and abilities. In a service system, it is important to understand the prevalence of human action in the system. Humans dominate the system, both on the customer as well as the company end of the transaction. Human behavior in a service system includes actions taken by the customer or company representative that affects the service transaction. Limitations include impairments in knowledge, communication, or resources that may restrict the success of the service. Abilities define the attributes the customer and company representative have that allow them to complete the service transaction. Common limitations and abilities could include computer and communication skills. 2.3. Service Quality Measurement Quality is one’s ability to achieve innate excellence (Schneider & White, 2004). In manufacturing, this is measured technically through product specifications, conformance measures, and objective standards. In services, however, quality is much more subjective. Service quality is the ability of an organization to meet the needs, wants, and expectations of the customer (Albrecht & Zemke, 2002; Edvardsson, Thomasson, & Øvretveit, 1994; Martin, 2003). The quality of a service is dependent on the individual perceptions of the customer. These perceptions are formed over time, with customers basing their opinion on past experience, the service process, and service delivery (Albrecht & Zemke, 2002; Zeithaml, Parasuraman, & Berry, 1990). The customer is the only person that can judge service quality (Zeithaml et al., 1990). Quality indicators are often quantified to measure service excellence. For example, if a Human Factors and Ergonomics in Manufacturing
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phone is answered within three rings at a call center, then quality is achieved. Using these measures, however, may limit quality of service in areas that cannot be objectively measured, such as customer satisfaction. An objective measure may be best for measuring the technical component of service, whereas user-based judgments are best for measuring the quality of service delivery. Services should be aimed at meeting customer requirements while preventing nonquality characteristics (e.g., wasted time, delays, unsafe conditions, unnecessary service; Rosander, 1991). Although they may seem identical at first inspection, there are differences between service quality and customer satisfaction. Whereas service quality is a consumer’s judgment about the service itself, customer satisfaction is a consumer’s evaluation of specific experiences. Consumers can make quality judgments about a service system even if they have never used the system (Schneider & White, 2004). To measure the quality of a service system, users compare their perceptions to preconceived expectations. To measure satisfaction, however, users simply evaluate a single service encounter. The exact relationship between the two measurements has not yet been determined (Asubonteng, McCleary, & Swan, 1996). As previously noted, the quality of a service is in the eye of the user. Users consider personal preferences, expectations, and experiences to judge the quality of a service. Users often base their evaluations on multiple aspects, or even multiple occurrences, of a particular service experience. Many researchers have proposed characteristics of service that are essential in assessing the quality of service. These critical quality characteristics are the fundamental issues that impact service quality. Zeithaml, Parasuraman, and Berry (1990) identified 10 service quality dimensions: tangibles, reliability, responsiveness, competence, courtesy, credibility, security, access, communication, and understanding the customer. These dimensions were identified through focus groups with service systems executives (Zeithaml et al., 1990). They proceeded to create a 200-item survey that scored these dimensions for any given service experience. Through factor analysis, they narrowed the list to five dimensions (see Table 1). Finally, a 22-item survey, SERVQUAL, was created to measure these five dimensions (Parasuraman, Berry, & Zeithaml, 1991). The SERVQUAL tool has been used in many service industries. Some researchers have adapted the survey to fit an industry-specific need, such as DINESERV for restaurants and LODGSERV for lodging properties (Schneider & White, 2004).
TABLE 1. SERVQUAL Dimensions Dimension
Definition
Reliability Tangibles Responsiveness Assurance (Combination of Competence, Courtesy, Credibility, Security) Empathy (Combination of Access, Communication, Understanding the Customer)
Delivering the promised performance dependably and accurately Appearance of the organization’s facilities, employees, equipment, and communication materials Willingness of the organization to provide prompt service and help customers Ability of an organization’s employees to inspire trust and confidence in the organization through their knowledge and courtesy Personalized attention given to a customer
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The assessment of service quality is traditionally done by speaking with customers. This can be done through focus groups, interviews, or surveys. Three system outcomes are traditionally focused on: perceived service quality, satisfaction, and behavioral intention (Baker & Taylor, 1997; Cronin & Taylor, 1992; Zeithaml, Berry, & Parasuraman, 1996). These dimensions are measured by asking customers questions relating to these outcomes. To determine perceived service quality, customers are generally asked if they felt the level of service was high quality or poor quality. Additionally, customers are asked if they are satisfied or dissatisfied with the service system. To examine behavioral intention, customers are often asked if they would return to the same system for service. They are also asked if they would refer a friend to the same service system. Measurement tools often question a customer’s perceptions of specific system characteristics, as well as how they relate to the three outcome dimensions. While the three outcomes are related to one another, the exact relationship has not been clarified. They each measure desirable features in a service system from a different perspective. Therefore, all three should be included when measuring service quality (Baker & Taylor, 1997). When customers enter into a service experience, they bring expectations of that service with them. There are four types of expectations that a customer may consider: predictive, normative, excellence, and adequate (Schneider & White, 2004). A predictive expectation describes what customers believe will actually happen during the service experience. A normative expectation is what people believe should happen, regardless of whether they believe it actually will. An excellence expectation is a customer’s belief of how an excellent service experience should perform. The entity a customer uses as the excellent experience does not have to be the current process. Oftentimes, it does not exist. Rather, customers may have an ideal experience in mind that they measure a service experience to. Adequate expectations describe the minimum level of performance a customer would be willing to accept. Customers use a variety of inputs to form expectations about a service system. Past experience, current needs and requirements, and communications with the system all factor into the development of customer expectations (Morgan, 1992). Customers’ perceptions are another key factor in their judgment of service quality. Customers compare their perceptions of the current service process to expectations they created prior to the service experience. The basis for evaluating service from the customer’s perspective is the comparison between expected and perceived service (Edvardsson & Gustavsson, 1991). The gap between perceptions and expectations is used by customers to judge service quality. Gap models are a tool that is commonly used to describe service quality. People base their service quality judgments on the gap that existed between their perceptions of what happened during the service transaction and their expectations for how the service transaction should have occurred. When these gaps exist, quality is compromised (Murphy, 1993). Therefore, a quality control strategy in services is to narrow and eventually close these gaps. 3. MODEL DEVELOPMENT The convergence of human factors and service quality is displayed graphically in Figure 1. All human factors goals are matched with at least one service quality dimension. This shows that the two areas are compatible, often striving to accomplish the same goals. To further examine the use of human factors in services, usability was considered. Assessing a system’s usability presents many benefits for the user. Increased productivity, decreased task time and cost, decreased errors, and increased accuracy are all benefits of Human Factors and Ergonomics in Manufacturing
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Reliability Productive Responsiveness Safe
Human Factors
Assurance
Service Quality
Comfortable Empathy Effective Tangibles
Figure 1
Graphical combination of human factors and service quality.
improved usability. A company that creates usable products can benefit from greater profits, increased business, decreased support costs, and an increase in customer satisfaction (Mayhew, 1999). The comparison of usability and service quality is shown in Figure 2. Three usability factors are matched with three service quality dimensions. However, two usability factors (learnability and memorability) and two service quality dimensions (assurance and empathy) do not pair with other factors. This demonstrates the possibility of combining these two areas to improve service systems. The improvement of a system’s service quality leads to increased customer satisfaction and return behavior. This eventually translates into increased profits for a service company. The proposed model of service quality is shown in Figure 3. The five SERVQUAL dimensions (reliability, responsiveness, assurance, empathy, and tangibles) and usability are shown to be factors that impact service quality. It is theorized that customers consider all six of these factors when judging a service system’s quality. To test this model, two surveys will be compared. The original SERVQUAL with be compared with a modified survey, SERVUSE. The modified survey includes the original SERVQUAL dimensions in addition to the usability dimension. If the usability dimension is found to be significantly different, evidence is shown for including usability in a service quality assessment. This would suggest that the additional usability factor adds significant predictive value to the survey.
Usability
Figure 2
Efficiency
Responsiveness
Errors
Reliability
Satisfaction
Tangibles
Learnability
Assurance
Memorability
Empathy
Service Quality
Graphical combination of usability and service quality. Human Factors and Ergonomics in Manufacturing
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Responsiveness
Assurance
Service Quality
Reliability
Usability
Learnability
Figure 3
Empathy
Tangibles
Memorability
Proposed service quality model.
4. METHODOLOGY To test the proposed model that includes all six dimensions, three dependent variables were examined. These variables were service quality, satisfaction, and behavioral intention. The original SERVQUAL measurement tool was modified to include the usability dimension. The modified instrument was termed SERVQUAL. Wording of the survey items was adjusted to fit the health care domain (Zeithaml et al., 1990). The selection of items was based on expert opinion and past studies that utilized SERVQUAL in the health care field (Babakus & Mangold, 1992; Dean, 1999; McAlexander, Kaldenberg, & Koenig, 1994; Pakdil & Harwood, 2005). The questions in SERVQUAL measured the subjects’ expectations of a health care system, as well as their perceptions of a specific provider. The survey also assessed the importance they placed on the six dimensions and their overall opinion of the provider. The survey was completed by 200 patients of University Health Services (UHS) on the Pennsylvania State University campus. Any patient that was treated at UHS during the study was eligible to participate. 5. RESULTS To test whether SERVUSE has an increase in predictive ability as compared to SERVQUAL, regression models from two measurement tools were compared. The adjusted R-squared values for each analysis were tested for differences. The full model, SERVUSE, was compared to the restricted model, SERVQUAL, for the analysis. The addition of the usability dimension could then be examined. The difference in the adjusted R-squared values for the full and restricted models was calculated and tested for significance. Table 2 displays the results of the difference significance testing. The R-squared increment is the increase or decrease in adjusted R-squared values when the usability dimension was added to the model. After calculating an incremental F statistic, the p value for each comparison was calculated. The test was not completed for two of the model comparisons due to the fact that the R-squared adjusted value decreased with the addition of the usability dimension. As shown in Table 2, only two models had significant differences at the 99% confidence level. These significant differences were found when the dependent variable was Human Factors and Ergonomics in Manufacturing
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TABLE 2. Regression Model Comparison
Dependent Variable
Source Data
Restricted Model R-Squared Adjusted
Perceived quality Satisfaction Behavioral intention Perceived quality Satisfaction Behavioral intention Perceived quality Satisfaction Behavioral intention
Gap Gap Gap Perception Perception Perception Expectation Expectation Expectation
.384 .387 .157 .578 .611 .292 .061 .092 .066
∗∗∗ Test
Full Model R-Squared Adjusted
R-Squared Increment
F Incremental
p Value
.391 .392 .191 .582 .613 .318 .059 .090 .071
0.007 0.005 0.034 0.004 0.002 0.026 −0.002 −0.002 0.005
2.218 1.587 8.111 1.847 0.997 7.358
0.1380 0.2093 0.0049 0.1757 0.3193 0.0073
∗∗∗
∗∗∗
∗∗∗
∗∗∗
1.039
0.3093
not conducted due to negative R-squared increment.
behavioral intention, using source data from gap and perception scores. This indicates that the usability dimension adds significant value to the models when behavioral intention is the response of interest. Therefore, the final hypothesis is supported. Additionally, a stepwise regression model was created for each dependent variable. The three models show the dimensions that create a model with the largest adjusted R-squared value for each dependent variable. An overview of each model, including the final regression equations, is shown in Table 3. The comparison of SERVQUAL results to SERVUSE was done by examining the adjusted R-squared values for each regression model. The results in Table 2 show that although the adjusted R-squared values increased with the addition of the usability dimension for a majority of the models, only two improvements were significant. The significant differences were found when the dependent variable was behavioral intention and the source data was gap scores or perception scores. The fact that only behavioral intention produced significant improvements in the model implies a number of important results. First and foremost, the improvement suggests that adding the usability dimension produces a more accurate predictor of behavioral intention. Therefore, the usability of a system is an important factor in predicting a customer’s return behavior. If a system is easy to use, the customer will be more likely to return in the future. TABLE 3. Regression Model Results Dependent Variable
R-Squared Adjusted
Regression Model p Value
Perceived Quality
.3901
0.109
Satisfaction
.3918
0.071
Behavioral Intention
.1981
