As described in Chapter, after making a purchase, customers compare the service they expected to get with what they actually receive. They decide how satisfied they are with service delivery and outcomes, and they also make judgments about quality.
Although service quality and customer satisfaction are related concepts, they are not exactly the same thing. Many researchers believe that customers' perceptions about quality are based on long-term, cognitive evaluations of a firm's service delivery, whereas customer satisfaction is a short-term emotional reaction to a specific service experience.
Following a service encounter, customers may evaluate their levels of satisfaction or dissatisfaction and may use this information to update their perceptions of service quality. They must, of course, experience a service before they can be satisfied or dissatisfied with the outcome. But beliefs about quality don't necessarily reflect personal experience.
People often make quality judgments about services they have never consumed, basing these evaluations on comments by acquaintances or on advertising messages. Figure shows the relationship between expectations, customer satisfaction, and service quality.
Managing a business to optimize customer satisfaction is a strategic imperative at many firms, since the cost of mediocre service quality may be as high as 40 percent of revenues in some service industries. Most companies realize that by improving per for manse on service attributes, customer satisfaction should increase. This should, in turn, lead to greater customer retention and improved profitability.
For example, the relative similarity of the products offered by different banks has led to an increased emphasis on service quality in the highly competitive retail banking sector. A large telephone survey of bank customers identified poor customer service quality as the most frequent reason for account closures. Analysis of the study results and bank branch profits indicated that customer service quality was a major determinant of how well individual branches performed.
The relationship between service quality and profitability is typically not easy to track for a variety of reasons. Service quality benefits accumulate over time rather than being experienced in the short term. This makes them difficult to measure using traditional market research techniques.
Another complicating factor is that many variables contribute to corporate profits (including pricing, distribution, advertising, and competition); it's hard to isolate the effects these individual factors have on the bottom line.
And finally, just spending money on service quality initiatives doesn't necessarily lead to increased profits. Service companies must identify the right quality initiatives and execute them effectively.
A strategic framework known as the satisfaction-profit chain can help managers identify the links between attribute performance, customer satisfaction, customer retention, and profits. However, the relationships between the different links in the chain are not necessarily linear.
Sophisticated analysis may be needed to pinpoint the priorities for improvements; for instance, investments designed to avoid negative outcomes on specific attributes may be as important as actions to increase positive performance on others.
Dimensions of Service Quality
Research has identified five broad dimensions of service quality:
Of these five dimensions, reliability has consistently proven to be the most important factor in customers’ judgments of service quality. Reliability improvements lie at the heart of service quality enhancement efforts because unreliable service implies broken promises on the attributes that customers care about.
If the core service is not performed reliably, customers may assume that the company is incompetent and may switch to another service provider. For a perspective on the dimensions of service quality in online environments, see the box "Service Quality Goes Online."
It isn't easy for many types of service businesses to maintain high levels of reliability day-in and day-out. When customers enter a service factory and are involved in service production, they experience mistakes directly often before a firm has an opportunity to correct them. In labor-intensive services, employees add a large degree of variability to the service production process.
It's difficult for service providers to control such variations, since each employee is somewhat different from the others in personality, skills, and attitudes. Moreover, the same employee can provide radically different service from one customer to the next or the same customer over time depending on situational factors like customer behavior, task complexity, and the employee's physical and mental state.
Service Quality Goes Online
Do customers use the same dimensions to evaluate service quality in electronic transactions as they do during more traditional service experiences? A recent study, based on data collected from focus group interviews, explored the criteria customers use to assess electronic service quality (e-SQ). The results indicate that some of the quality dimensions discussed earlier (reliability, responsiveness, and assurance) are important in both online and offline settings.
However, some other dimensions are unique to customers' evaluations of e-SQ, including ease of navigation, flexibility, efficiency, site aesthetics, and price knowledge. All of these are technology related except price knowledge, which reflects customers' desire for information about what their total online shopping charges are before they hit the "submit" button to complete their purchases.
Why is e-SQ so important? While many marketers believe that price is the biggest concern for Internet customers, survey results indicate that poor service quality is the reason that most people leave Web sites. Specific failings include the lack of an easy-to-use search engine to help with site navigation; memory-intensive graphics that take too long to download; slow and confusing online ordering processes (especially when advertising promises that it will be easy); and hidden charges.
A good way to understand user requirements in e-commerce is to establish continuous processes (like Web surveys or chat rooms) to monitor customers' responses to their sites, if research shows that customer preferences vary by target market and the type of products being sold, the supplier may want to offer alternative sites for different segments.
But in general, Web pages should be designed to load quickly while still conveying rich information. To close communication gaps, companies must plan realistically for adequate site functionality, promise only what their sites can deliver, and ensure that all aspects of fulfillment meet promised levels of performance.
Although mistakes occur in every organization, many companies strive to minimize errors to provide greater service reliability for their customers. Leonard Berry describes how the Hard Rock Cafe Orlando addresses service reliability:
Performing the service right the first time is a bedrock value at Hard Rock Cafe Orlando, the immensely successful restaurant chain and merchandise retailer. Hard Rock Café emphasizes "double checking" to minimize errors. The message of double checking is: Perform the service carefully to avoid mistakes. If a mistake does occur, correct it before it reaches the customer.
Hard Rock Cafe implements double checking through two "extra" people in the kitchen. One is stationed inside the kitchen and the other at the kitchen counter. The inside person reviews everything that is going on, looking for signs of undercooked or overcooked meals, wilting lettuce, or any below-standard product or performance. The counter person, or "expediter," checks each prepared plate against the order ticket before the food is delivered to the table.
Reliability is an outcome measure because customers judge it after the service experience: Either the service was delivered as promised or it wasn't. The other four dimensions of quality tangibles (physical evidence), responsiveness, assurance, and empathy are process dimensions because they can be evaluated by customers during service delivery.
These dimensions provide companies with the opportunity to delight customers by exceeding their expectations during interactions with employees and the service environment. As shown in Figure, exceeding customers' desired levels of expectations leads to positive perceptions of service quality.
A service performance that surprises and delights customers by falling above their desired service levels will be seen as superior in quality. If service delivery falls within their zone of tolerance, they will feel that it's adequate. But if perceived quality falls below the adequate service level expected by customers, a discrepancy or quality gap has occurred between the service provider's performance and customer expectations.
Why do quality failures occur? Gaps can occur at seven different points in the design, production, and delivery of services, as shown in Figure. The service gap is the most critical, because it involves the customer's overall assessment of the service, comparing what was expected against perceptions of what was received.
The ultimate goal in improving service quality is to narrow this gap as much as possible. To do so, service providers may have to reduce or close the six other gaps. The seven potential gaps in service quality are:
The presence of any one of these seven quality gaps can lead to a disappointing outcome that damages relationships with customers. Avoiding service gaps in every service encounter will help a firm improve its reputation for quality service. Although careful planning and monitoring will help reduce the likelihood that one of these gaps will occur, when customers indicate that service outcomes are disappointing, it's important to identify and eliminate the gap(s) that lead to this result.
A major problem in some firms is that service standards are defined by operations managers who have no knowledge of customer needs and expectations. Hence, it's vital that marketers be involved in the task of designing service standards and measuring performance against them.
Learning from Service Failures
Although every firm should have contingency plans for service recovery, there's no substitute for doing it right the first time. Recovery procedures shouldn't be seen as a substitute for improved service reliability. When a problem is caused by controllable, internal forces, there's no excuse for allowing it to happen again. Recurring service failures lower service quality and reduce productivity as time and money are wasted on correcting mistakes.
With prevention in mind, let's look briefly at some simple but powerful tools for monitoring quality and determining the root causes of service failures. Among the many tools available to quality improvement specialists, the following ones are particularly helpful for managers in identifying service failures and designing effective recovery strategies.
Flowcharts and Service Blueprints Flowchart and their more formalized derivative, service blueprints, are useful tools for thoroughly examining service delivery processes. Once managers understand these processes, it's easier for them to identify potential failure points, which are weak links in the chain. Knowing what can go wrong, and where, is an important first step in improving productivity and preventing service quality problems.
Control Charts It's frequently said that "you cannot manage what you do not measure." Control charts offer a simple method for graphing performance over time against specific quality criteria. Because the charts are visual, trends are easily identified. Figure shows an airline's performance on the important criterion of on-time departures. The results in this example suggest that management would do well to investigate the situation, because aircraft departure performance is erratic and unsatisfactory.
Cause-and-Effect Charts the Japanese/quality expert Kaoru Ishikawa created the fishbone diagramfor use in manufacturing firms. To produce a fishbone diagram (also known as a cause-and-effect chart), groups of managers and employees brainstorm factors that might be creating a specific problem.
In a traditional version of this diagram, the resulting factors are then categorized into one of five groupings equipment, people, materials, procedures, and other. It's important to recognize that failures are often sequential, with one problem leading to another in a different category. Figure displays no less than 27 possible reasons for late departures of a passenger aircraft!
Notice that the fishbone diagram shown in Figure includes eight groupings rather than just the five mentioned above. The extra categories are designed to provide additional information for service firms. For example, the People category has been changed to Front-Stage Personnel and Backstage Personnel. This highlights the fact that front-stage service problems are often experienced directly by customers, whereas backstage failures tend to show up more indirectly.
Information has been split from Procedures because many service problems result from information-related failures. For example, inadequate information about flight departures may lead passengers to arrive Late at the gate.
The expanded fishbone diagram also includes a new category Customers to acknowledge their increased involvement in service production and delivery, because customers can also be the cause of problems for a service business. As we've discussed before, customers of high-contact services are often heavily involved in front-stage operations.
If they don't play their roles correctly, they may reduce service productivity and cause quality problems for themselves and other customers. For instance, an aircraft that seats hundreds of passengers can be delayed if a single traveler tries to board at the last minute with an oversized bag, which then has to be loaded into the cargo hold.
Pareto Analysis The technique known as Pareto analysis (named after the Italian economist who first developed it) is useful in identifying the principal causes of observed outcomes. Application of this technique often highlights a phenomenon known as the "80/20 rule," showing that approximately 80 percent of the value of one variable (in this instance, the number of service failures) is accounted for by only 20 percent of the causal variables (i.e., the number of possible causes).
In the airline example above, 88 percent of the company's late-departing flights were caused by only four (15 percent) of all the possible causes late passengers, late push back tug, late fuel, and late weight and balance sheet. So, focus on these four factors rather than tackling all potential causes simultaneously especially when time and other resources are limited.
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