Article 35

How Disconfirmation, Perception and Actual Waiting Times Impact Customer Satisfaction

Mark M. Davis & Janelle Heineke

Presented by: Darleen Olarig

Objective• To analyze and compare the results of both the

disconfirmation approach and perception approach in measuring satisfaction with waiting for service.

• If perception model more appropriate for relating to customer satisfaction, then to understand satisfaction only perception data is required.

• If disconfirmation approach is superior, then both expectation and perception data are required.

Objective

• In addition, this study investigates customer satisfaction with actual waiting time (or actual performance of the service delivery) and compares these results with those obtained with the disconfirmation and perception models.

Previous Work

• Previous research on customer satisfaction with respect to waiting in service operations can be divided into three areas:

1. Developing a method to define customer satisfaction.

2. Measuring customer satisfaction

3. Identifying factors that affect the level of customer satisfaction.

Previous Work• Chebat et al (1994)

– Study of bank customers support the notion of “halo effect” meaning customer’s evaluation of service quality was affected not only by the end service received but also by service delivery process itself, including waiting time.

• Beardon & Teale (1983), Day & Landon (1977)– Customer satisfaction can be conceived as one

element of an overall model of customer behavior that evolves over time.

• Reichheld & Sasser (1990)– Customer loyalty, in the form of repeat business, is a

key determinant of the success many service companies

Previous Work Defining Customer Satisfaction

• Defining Customer Satisfaction has been approached in two ways:

1. Satisfaction as a function of disconfirmation

2. Satisfaction as a function of perception

Previous Work

• Anderson (1973), Parasuraman (1994), Swan (1981)

– Attempted to define satisfaction in terms of disconfirmation. Satisfaction= f (Perception-Expectation)

• Customer expectations are set in two ways:

1. Through advertising and word of mouth2. After previous encounter with the firm, from

personal experience.

Previous Work

• Anderson (1973) & Swan (1981)

– Proposed two dimensions to the expectation construct: the level of service desired by the customer and the level of service predicted by the customer.

– High CS: the service performance ≥ the customer’s desired service level.

– CS: desired level > performance ≥ predicted level.

– Dissatisfaction: performance level is less than both the desired level and the predicted levels of service.

Previous Work

• Zeithaml (1993) argued that desired service is the level of service a customer believes can and should be delivered. Adequate service is the level customer considers acceptable.

• Spreng & Olshavsky (1993) showed there was a significant relationship between the extent to which performance is congruent with desires, but did not find the disconfirmation of expectations to be significant.

Previous Work

• Goode & Moutino (1995) state “the disconfirmation of expectations model has been increasingly criticized in recent years. As a result, standards other than expectations have been suggested.”

• Teas (1994) argues that multiple definitions of expectations and difficulties with measurement undermine the value of models incorporating expectations.

Previous Work• Cronin & Taylor (1994), Teas (1993)

– Satisfaction depends on customer’s perception of service performance, not disconfirmation between performance and expectations.

Satisfaction= f (Perception)

• Parasuraman (1994) argues while perception alone may be a better predictor of satisfaction, it offers less understanding of the underlying phenomena than the disconfirmation model.

Previous WorkMeasuring Customer Satisfaction

• Hawes & Arndt (1982) suggest the use of a single global indicator of a customer’s reaction to service experience to be the most common measure of CS.

• However, the single indicator is suspect when the construct is complex in regards to validity and reliability.

• A Customer Survey using multi-item/specific approach is more valid and reliable.

Previous WorkFactors Affecting Customer Satisfaction

• Maister (1985) developed a conceptual framework that identified the factors affecting CS with waiting; widely accepted.

• The framework identified situations in which waits were perceived positively or negatively as a result of the circumstance of the wait.

• Maister Model: the perception of the wait determines satisfaction rather than actual waiting.

Previous Work

• Davis & Vollmann (1990) supported Maister’s notion.

• Conducted study of customer waiting times and level of satisfaction in a fast food restaurant.

• There were significant differences in levels of satisfaction depending on time of day and how busy the stores were when customer visited.

– Tolerant of waiting in line if store because there was a identifiable reason for the wait.

– Impatient if on a lunch break and had limited time.

Previous Work• Davis & Maggard (1990) also supported

Maister’s notion that customers tend to be more dissatisfied with a given wait before making their first contact with a service provider than they are with subsequent waits within a single service encounter.

• Katz (1991) examined how a bank might improve customer satisfaction with waiting time by installing a clock and an electronic news board, but failed to distract customers.

• Smidts & Pruyn (1994) study of health care customers in outpatient clinics had similar results.

Previous Work

• Distractions Fail because:

1. It does not actually affect perception of waiting time and satisfaction with waiting.

2. It was not the appropriate distraction given the context of wait. For example, TV would be irritating to a sick patient who is sick.

Previous Work

• Davis & Heineke (1994) categorized factors that can affect a customer’s satisfaction with waiting in line based on the degree to which service managers could control the factors.

1. Factors that can be controlled by the firm: would be fairness in serving customers on first come, first serve basis.

2. Factors that can be partially controlled: such as customer expectations

3. Factors that are outside of the firm’s control: whether customer arrives alone or in a group.

Methodology• Used the same database in studies conducted

by Davis & Vollmann (1990) and Davis & Maggard (1990).

• Selected a fast food chain for administering the survey.

• Waiting time for customers were recorded with a stop watch without their knowledge.

• After being served, customers were asked to complete a survey. Satisfaction was measured on a 1-5 Likert Scale.

• Customers were asked how long they expected to wait prior to entering the store and how long they perceived they had waited.

Methodology

• 90% of customers agreed to participate. Total of 723 waiting times and corresponding surveys collected.

• Responses to two questions relating to customer’s satisfaction with the waiting time before service were averaged to develop a measure for satisfaction with initial wait. (WaitSat)

1. How satisfied are you with how long you had to wait in line from the time you walked in to when you placed your order?

2. What is your opinion of the overall speed of service you received from when you first entered to when you began placing your order?

Methodology

• The WaitSat values were then related to three different independent variables using simple linear regression.

Actual customer waiting times Perceived waiting times Expected waiting times

Analysis and Results• There is a correlation between actual wait time

and perceived wait time, although it is not as high, r = 0.596 = 59.6%

• Correlation between perceived wait and expected wait is very small, r = 0.280= 28 %

Table I.

Independent variable correlation matrix.

Analysis and Result• Confirms that customer satisfaction with waiting

time is inversely related to perceived waiting time and actual waiting time.

• Findings indicate the effect of actual wait on satisfaction is greater than the effect of either perceived wait or disconfirmation.

Table II.The relationship between CS and disconfirmation, perception, expected wait, and actual wait.

Analysis and Result

• When time is important, the perception of waiting time is a much better predictor of satisfaction than the actual wait time.

• When time is not critical, the differences between the predictive value of actual wait, perceived wait, and disconfirmation are small.

Table III.The relationship between CS and disconfirmation, perception, expected wait, and actual wait with time constraint.

• Actual waiting time exerts a stronger influence over satisfaction.

Conclusion• These findings support the argument that

perception of waiting time is a better predictor of customer satisfaction than either actual waiting or disconfirmation.

• In the analysis of customers for whom time was an important variable, perception appeared to be a much better predictor of customer satisfaction.

• In all analyses, the coefficient for actual wait was larger than for either perceived wait or for disconfirmation. This indicates that actual waiting time exerts a stronger influence over customer satisfaction with waiting.

Conclusion & Implications

• What customers expect their waits to be is a poor predictor of satisfaction and the expectation regarding waiting is not highly correlated with the perception of wait.

• The difference between perceived wait and expected wait, Disconfirmation, does not predict satisfaction any better than the perception of the wait alone.

Implications

• It is always critical to improve actual process performance to reduce waiting time.

• Service managers must continue to look for new approaches not only to reduce waiting times, but also to explore new ways of improving customer satisfaction with a given waiting time.

• Managers must also continue to develop new measures for relating customer satisfaction to waiting time.

Implications

The real goal is to determine how waiting times affect customer loyalty as measured by their repeat business in the future.