Benchmarking hotel service quality using two-dimensional importance-performance benchmark vectors (IPBV)

Purpose: Importance-performance analysis (IPA) is an effective tool for firms to prioritise service quality attributes, but has limitations in evaluating and enhancing service quality within a competitive environment. The purpose of this paper is to present an evolved model of IPA – importance-performance benchmark vectors (IPBV) – as a benchmarking tool and investigate its applicability in the context of hotel service quality. Design/methodology/approach: Empirical studies based on self-completion survey data from 150 customers of two full-service hotels in Taiwan were conducted in to examine the practical utility of IPBV. Findings: Eight key benchmark typologies were identified and expressed as vectors in the IPBV model which are as follows: “sustainable advantage”, “potential strength”, “false advantage or outstanding advantage”, “cease-fire competition”, “false disadvantage or on-hand disadvantage”, “potential weakness”, “dangerous warning” and “head-on competition”. Research limitations/implications: The paper extends the methodology to more cases, and other service industries to test further the discriminatory power of the model and to explore the descriptors in the IPBV vector model. Alternative seven-point or nine-point Likert scales could be explored to test the discriminant validity using means. The alternative IPA diagonal approach focussing on GAP analysis may reveal alternative interpretations for the IPBV vector model. Other extended models of IPA, which include competitor analysis, should be compared in practice using a data set where both quantitative and qualitative data could be generated. Practical implications: The paper proposes the two-dimensional IPBV model which retains the advantages of IPA, but also includes competitor or benchmark comparisons which enable organisations to analyse their relative competitive position. The two-part model provides both quantitative information and qualitative interpretation of relativities. The graphical matrix models provide simple quantitative analysis of attributes, whilst the IPBV vector model provides qualitative interpretations of the eight competitive market positions. Vector analysis enables the development of competitive strategies relative to benchmarks, or within a competitive set. Importance is retained and means that organisations can benchmark against a range of competitors prioritising specific attributes for resource allocation. Social implications: The interpretive utility of the model should be explored with practitioners and decision makers in the service industries. The model has been designed for practical use in industry to inform operational and strategic decision making, its usefulness in practice should be explored and the attitudes of practitioners to the model should be tested. Originality/value: Traditional approaches to benchmarking have adopted a one-dimensional approach that does not include a measure of the relative importance of the service quality dimensions in specific markets. This research develops a two-dimensional advanced model of IPA, called IPBV, which is based on vector relationships between key attributes of service quality. These vectors are explored and described in competitive terms and the model is discussed with regard to its implications for industry, practitioners and researchers.