SERVQUAL is a multi-dimensional research instrument designed to capture consumer expectations and perceptions of a service along five dimensions (originally ten) which are said to represent service quality. SERVQUAL is built on the expectancy–disconfirmation paradigm, which, in simple terms, means that service quality is understood as the extent to which consumers' pre-consumption expectations of quality are confirmed or disconfirmed by their actual perceptions of the service experience. The SERVQUAL questionnaire was first published in 1985 by a team of academic researchers in the United States, A. Parasuraman, Valarie Zeithaml and Leonard L. Berry, to measure quality in the service sector.[1]
On its introduction, the survey represented a breakthrough in the measurement methods used for service quality research. The diagnostic value of the instrument is supported by the model of service quality which forms the conceptual framework for the development of the scale (i.e. instrument or questionnaire). The instrument has been widely applied in a variety of contexts and cultural settings and found to be relatively robust. It has become the dominant measurement scale in the area of service quality. In spite of the long-standing interest in SERVQUAL and its myriad of context-specific applications, it has attracted some criticism from researchers.
SERVQUAL is a multidimensional research instrument designed to measure service quality by capturing respondents’ expectations and perceptions along five dimensions of service quality.[2] The questionnaire consists of matched pairs of items - 22 expectation items and 22 perceptions items - organised into five dimensions which are believed to align with the consumer's mental map of service quality dimensions. Both the expectations component and the perceptions component of the questionnaire consist a total of 22 items, comprising 4 items to capture tangibles, 5 items to capture reliability, 4 items for responsiveness, 4 items for assurance and 5 items to capture empathy.[3] The questionnaire may be administered as a paper survey, web survey or in a face-to-face interview. Known studies have published high scores for validity and reliability from small to large size sample sizes. In practice, it is customary to add additional items such as the respondent's demographics, prior experience with the brand or category and behavioural intentions (intention to revisit/ repurchase, loyalty intentions and propensity to give word-of-mouth referrals). Thus, the final questionnaire may consist of 60+ items though the 22 questions are the same. The face to face interview version may take one hour per respondent to administer, but not the print or web survey forms.
| Dimension | No. of Items in Questionnaire | Definition | |
|---|---|---|---|
| Reliability | 5 | The ability to perform the promised service dependably and accurately | |
| Assurance | 4 | The knowledge and courtesy of employees and their ability to convey trust and confidence | |
| Tangibles | 4 | The appearance of physical facilities, equipment, personnel and communication materials | |
| Empathy | 5 | The provision of caring, individualized attention to customer | |
| Responsiveness | 4 | The willingness to help customers and to provide prompt service |
The instrument which was developed over a five-year period; was tested, pre-tested and refined before appearing in its final form. The instrument's developers, Parasuraman, Zeithaml and Berry, claim that it is a highly reliable and valid instrument.[5] Certainly, it has been widely used and adapted in service quality research for numerous industries and various geographical regions. In application, many researchers are forced to make minor modifications to the instrument as necessary for context-specific applications. Some researchers label their revised instruments with innovative titles such as LibQUAL+ (libraries), EDUQUAL (educational context),[6] HEALTHQUAL (hospital context) [7] and ARTSQUAL (art museum).[8]
Businesses use the SERVQUAL instrument (i.e. questionnaire) to measure potential service quality problems and the model of service quality to help diagnose possible causes of the problem. The model of service quality is built on the expectancy–confirmation paradigm which suggests that consumers perceive quality in terms of their perceptions of how well a given service delivery meets their expectations of that delivery.[10] Thus, service quality can be conceptualized as a simple equation:
SQ = P − E
where;
SQ is service quality
P is the individual's perceptions of given service delivery
E is the individual's expectations of a given service delivery
When customer expectations are greater than their perceptions of received delivery, service quality is deemed low. When perceptions exceed expectations then service quality is high. The model of service quality identifies five gaps that may cause customers to experience poor service quality. In this model, gap 5 is the service quality gap and is the only gap that can be directly measured. In other words, the SERVQUAL instrument was specifically designed to capture gap 5. In contrast, Gaps 1-4 cannot be measured, but have diagnostic value.
| Gap | Brief description | Probable Causes | |
|---|---|---|---|
| Gap 1The Knowledge Gap | Difference between the target market's expected service and management's perceptions of the target market's expected service |
| |
| Gap 2The standards Gap | Difference between management's perceptions of customer expectations and the translation into service procedures and specifications |
| |
| Gap 3 The Delivery Gap | Difference between service quality specifications and the service actually delivered |
| |
| Gap 4 The Communications Gap | Difference between service delivery intentions and what is communicated to the customer |
|
The development of the model of service quality involved a systematic research undertaking which began in 1983, and after various refinements, resulted in the publication of the SERVQUAL instrument in 1988.[12] The model's developers began with an exhaustive literature search in order to identify items that were believed to impact on perceived service quality. This initial search identified some 100 items which were used in the first rounds of consumer testing. Preliminary data analysis, using a data reduction technique known as factor analysis (also known as principal components analysis) revealed that these items loaded onto ten dimensions (or components) of service quality. The initial ten dimensions that were believed to represent service quality were:
Further testing suggested that some of the ten preliminary dimensions of service quality were closely related or autocorrelated. Thus the ten initial dimensions were reduced and the labels amended to accurately reflect the revised dimensions. By the early 1990s, the authors had refined the model to five factors which in testing, appear to be relatively stable and robust.
These are the five dimensions of service quality that form the basis of the individual items in the SERVQUAL research instrument (questionnaire). The acronym RATER, is often used to help students of marketing remember the five dimensions of quality explicitly mentioned in the research instrument. It is these five dimensions that are believed to represent the consumer's mental checklist of service quality.
Nyeck, Morales, Ladhari, and Pons (2002) stated that the SERVQUAL measuring tool “appears to remain the most complete attempt to conceptualize and measure service quality” (p. 101). The SERVQUAL measuring tool has been used by many researchers across a wide range of service industries and contexts, such as healthcare, banking, financial services, and education (Nyeck, Morales, Ladhari, & Pons, 2002).
Although the SERVQUAL instrument has been widely applied in a variety of industry and cross-cultural contexts, there are many criticisms of the approach. Francis Buttle published one of the most comprehensive criticisms of the model of service quality and the associated SERVQUAL instrument in 1996 in which both operational and theoretical concerns were identified.[13] Some of the more important criticisms include:
Face validity: The model of service quality has its roots in the expectancy-disconfimation paradigm that informs customer satisfaction.[14] A number of researchers have argued that the research instrument actually captures satisfaction rather than service quality.[15] Other researchers have questioned the validity of conceptualising service quality as a gap.[16]
Construct validity: The model's developers tested and retested the SERVQUAL scale for reliability and validity. However, at the same time, the model's developers recommended that applied use of the instrument should modify or adapt them for specific contexts. Any attempt to adapt or modify the scale will have implications for the validity of items with implications for the validity of the dimensions of reliability, assurance, tangibles, empathy and responsiveness.[17]
Ambiguity of expectations construct: SERVQUAL is designed to be administered after respondents have experienced a service. They are therefore asked to recall their pre-experience expectations. However, recall is not always accurate, raising concerns about whether the research design accurately captures true pre-consumption expectations. In addition, studies show that expectations actually change over time. Consumers are continually modifying their expectations as they gain experience with a product category or brand.[18] In light of these insights, concerns have been raised about whether the act of experiencing the service might colour respondents' expectations.
Operational definition of the expectations construct: The way that expectations has been operationalised also represents a concern for theorists investigating the validity of the gaps model. The literature identifies different types of expectations.[19] Of these, there is an argument that only forecast expectations are true expectations. Yet, the SERVQUAL instrument appears to elicit ideal expectations.[20] Note the wording in the questionnaire in the preceding figure which grounds respondents in their expectations of what excellent companies will do. Subtle use of words can elicit different types of expectations. Capturing true expectations is important because it has implications for service quality scores. When researchers elicit ideal expectations, overall service quality scores are likely to be lower, making it much more difficult for marketers to deliver on those expectations.[21]
Questionnaire length: The matched pairs design of the questionnaire (total of 22 expectation items plus 22 perception items= 44 total items) makes for a very long questionnaire. If researchers add demographic and other behavioural items such as prior experience with product or category and the standard battery of demographics including: age, gender, occupation, educational attainment etc. then the average questionnaire will have around 60 items. In practical terms, this means that the questionnaire would take more than one hour per respondent to administer in a face-to-face interview. Lengthy questionnaires are known to induce respondent fatigue which may have potential implications for data reliability. In addition, lengthy questionnaires add to the time and cost involved in data collection and data analysis. Coding, collation and interpretation of data is very time consuming and in the case of lengthy questionnaires administered across large samples, the findings cannot be used to address urgent quality-related problems. In some cases, it may be necessary to carry out 'quick and dirty' research while waiting for the findings of studies with superior research design.
Administration of the questionnaire: Some analysts have pointed out that the SERVPERF instrument, developed by Cronin and Taylor,[22] [23] and which reduced the number of questionnaire items by half (22 perceptions items only), achieves results that correlate well with SERVQUAL, with no reduction in diagnostic power, improved data accuracy through reductions in respondent boredom and fatigue and savings in the form of reduced administration costs.
Dimensional instability: A number of studies have reported that the five dimensions of service quality implicit in the model (reliability, assurance, tangibles, empathy and responsiveness) do not hold up when the research is replicated in different countries, different industries, in different market segments or even at different time periods.[24] [25] Some studies report that the SERVQUAL items do not always load onto the same factors. In some empirical research, the items load onto fewer dimensions, while other studies report that the items load onto more than five dimensions of quality. In statistical terms, the robustness of the factor loadings is known as a model's dimensional stability. Across a wide range of empirical studies, the factors implicit in the SERVQUAL instrument have been shown to be unstable.[26] Problems associated with the stability of the factor loadings may be attributed, at least in part, to the requirement that each new SERVQUAL investigation needed to make context-sensitive modifications to the instrument in order to accommodate the unique aspects of the focal service setting or problem. However, it has also been hypothesised that the dimensions of service quality represented by the SERVQUAL research instrument fail to capture the true dimensionality of the service quality construct and that there may not be a universal set of service quality dimensions that are relevant across all service industries.[27]
In spite of these criticisms, the SERVQUAL instrument, or any one of its variants (i.e. modified forms), dominates current research into service quality.[28] In a review of more than 40 articles that made use of SERVQUAL, a team of researchers found that “few researchers concern themselves with the validation of the measuring tool”.[29] SERVQUAL is not only the subject of academic papers, but it is also widely used by industry practitioners.[30]