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2.8 Analysis of Non-Systemic Approaches of Evaluation 87
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Responsiveness, accessibility, courtesy, comfort, aesthetics of environment, competence, dependability, accuracy, completeness, credibility and effective communication of learners.
From the review of the literature it is evident that Parasuraman et al. (1985) and Goetsch and Davies (2006) concur regarding quality dimensions such as reliability, responsiveness, competence, accessibility, courtesy, communication, credibility, security and tangibles. However, there is disparity on knowing the customer and customization as part of service quality.
The above literature indicates that although quality assurance has been on the agenda of higher education both nationally and internationally for some time, the implementation of quality assurance systems is a complex process. Having reviewed some of the challenges faced by institutions of higher learning regarding implementation of service quality assurance, the focus now shifts to analysis of existing non-systemic approaches.
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According to Van Dyke, Prybutok and Kappelman (1999:878) the disconfirmation concept is a poor choice by which to measure psychological paradigms because there is little evidence of customers’ actual assessments of service quality. Cronin and Taylor (1992) question the validity of the P – E introduced in the disconfirmation paradigm, suggesting that this concept is a potentially misleading gauge of service quality perceptions.
Another conceptual critique highlighted by Buttle (1998:8) is that Service Quality [(SQ) = Performance (P) – Expectations (E)] is based upon disconfirmation, rather than the attitudes of the customers. The premise of disconfirmation is that service quality depends not on the absolute level of performance experienced, but on performance compared to expected performance. There has been considerable debate that the performance-minus-expectation construct is possibly a flawed and incoherent measurement of the assessment of service quality (Cronin and Taylor, 1992:58). In addition to the conceptual criticisms pertaining to the disconfirmation paradigm, which is the foundation of SERVQUAL, another issue has also been raised by some researchers on its dimensionality. Teas (1994:133) highlighted a problem as to whether SERVQUAL domains are vectors or ideal points. Certain elements like empathy become difficult to conceptualise on a linear scale. It is equally difficult to see how this instrument can be of any use in quality assurance, unless its domains are easy for the average customer to understand.
Ladhari (2008:66) suggests that SERVQUAL has several theoretical and empirical criticisms and limitations. Van Dyke et al. (1999:880) argue that the gap score is a poor choice as a measure of psychological construct while Ekinci and Riley (1998:352) mention that the SERVQUAL model has no equivalent in theories of psychological function. The concept of expectation is loosely defined and leads to multiple interpretations (Teas, 1993, 1994) and the resulted operationalisation of the SERVQUAL model is open to multiple interpretations (Ladhari, 2008:67). The Factor-loading pattern on the items and dimension of the SERVQUAL model indicates a weakness in convergent validity. Literature analysis confirms that a
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number of researchers cannot agree on the different dimensions which are appropriate for expectations, perceptions and gap scores. SERVQUAL only focuses on the process of service delivery rather than outcomes of service encounters (Gronroos, 1995; Richard and Allaway, 1993, Brady and Cronin, 2001). According to Dabholakar, Thorpe and Rentz (1996); Brady and Cronin (2001) and Wilkins, Merrilees and Herington (2007) the SERVQUAL model is fundamentally flawed as researchers contended that service quality is an aggregation of various quality sub- dimensions and service quality is a multilevel construct as well as a multidimensional construct.
Service quality frameworks and customer satisfaction models have generally come under criticism for the composition and number of domains they include. All these frameworks consist of pre-defined domain attributes that are generic to all service organisations. Babakus and Boller (1992:254) suggest that service quality may be complex in some industries, and unidimensional in others. As a consequence, the predefined domains and attributes are not universal and are likely to require contextualization with respect to the measurements of attributes and the industry being investigated (Buttle, 1998; Schneider and White 2004). A detailed analysis of these models reveals an underrepresentation of the construct of customer satisfaction in relation to service quality. This implies that the models do not possess a framework required for the holistic understanding of customer satisfaction relative to service quality in a given environment. Some of these models are static and generic in nature and have not been specially developed for a particular environment, for example a UOT in South Africa.
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Following is a table expounding on the benefits and limitations of the evaluation models investigated in the study.
Table 2.2: Evaluation Models applied to Higher Education
EUROPEAN FOUNDATION FOR QUALITY MANAGEMENT (EFQM) Benefits:
Integrated map of the management issues valued and useful for securing confidence of stakeholders.
Useful as a basis of self-assessment.
Tests relationship between enablers/results
Limitations:
More relevant to service functions.
Dilemma of applying business language to public sector.
It may be 3 to 5 years before benefits are evident.
Challenges regarding managerial skills and top-level commitment to higher education.
Lack of integration between EFQM and national Higher Education quality control mechanisms.
BALDRIGE NATIONAL QUALITY PROGRAMME (BNQP) Benefits:
Evident in operational elements;
strategic and budget planning, careers, outreach and information services.
May be immediate and long standing.
Limitations:
It is primarily aimed at institutions based in the USA.
DATA ENVELOPMENT ANALYSIS (DEA) Benefits:
Can be applied to a multiple input multiple output production context.
Used to obtained measures of technical and allocative efficiencies for
Limitations:
There are no significant tests for comparing models or for comparing the efficiency scores of individuals or groups of decision making units.
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individual departments. There is a lack of a unifying index of performance in many public decision- making units, such as profit in a private sector, which substantially increases the complexity of the problem.
SERVQUAL Benefits:
Enables assessment of internal and external customer views which is important in a competitive environment
Limitations:
Student culture impacts on perceived importance of different elements of higher education and thus on perceptions of quality.
Performance indicators related to management processes but do not address education quality.
SERVPERF Benefits:
Overcomes the problems raised regarding SERVQUAL, namely, raising expectations, administration of the two parts of the questionnaire and the statistical properties of difference scores.
Limitations:
Does not take into account customer expectations and only utilizes the perceptions of service performance.
IMPORTANCE-PERFORMANCE ANALYSIS (IPA) Benefits:
Identifies which service attributes should be maintained at present levels
Limitations:
A number of issues need to be addressed prior to the application of
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Useful management tool in deploying scarce resources to areas where performance improvement is likely to have the most effect on overall customer satisfaction.
the technique, i.e. Differentiate between determinants and important attributes for consumers and the issue of bias and the separation of the performance and importance scales.
Confusion between concepts of importance and expectation.
BALANCED SCORECARD APPROACH (BSC) Benefits:
Is a simple, systematic, easy-to- understand approach for performance measurement, review and evaluation.
Emphasizes the role of the customer;
internal processes; and innovation and learning.
System can increase educational quality.
Staff understand performance targets.
Focus is on performance management and evaluation.
Limitations:
Education sector has not embraced the BSC framework.
Is not sufficiently rich to reflect the dual operational and strategic issues of faculty.
Performance indicators require careful identification specific to situations and can be dysfunctional unless grounded in strategy.
HIGHER EDUCATION QUALITY COMMITTEE (HEQC) Benefits:
Places specific emphasis on higher education in South Africa.
Conformance to national legislation.
Limitations:
A new system that is evolving as a quality management system for institutions of higher learning with specific reference to universities of technology in South Africa.
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SOUTH AFRICAN EXCELLENCE MODEL (SAEM) Benefits:
The use of this model demonstrates commitment to excellence in South African organisations
Limitations:
Not ideal for organisations operating globally as the framework is only supported in South Africa.
Source: Adapted from Brookes and Becket, 2006 and Weideman, 2008