University of Wollongong
Browse

Profiling the One- and Two-star Hotel Guest for Targeted Segmentation Action: a Descriptive Investigation of Risk Perceptions, Expectations, Disappointments and Information Processing Tendencies

Download (255.53 kB)
chapter
posted on 2024-11-13, 12:07 authored by Sara Dolnicar
Identifying the target segment is the basis of developing efficient market segmentation strategies and efficient market segmentation is vital in an industry that is becoming increasingly competitive, as in the case of international tourism. In Austria, hotels in higher star grading categories have addressed this need through systematic market research designed to identify the needs of their consumers. Not so the hotels in the one- and two-star category: these typically do not segment the market and tend to assume that increasing their star grading will lead to increased market demand instead of investigating the specific needs of tourists who very consciously choose low star graded hotels. This paper aims to examine this a priori segment with regard to issues that are known to influence choice behaviour, namely expectations, disappointments with past experiences and perceived risk, while taking into account information need and processing habits. The ultimate purpose of the study is to stimulate development of a segment-oriented marketing strategy for one and two-star hotels should this guest segment differ significantly from that comprising tourists staying in higher-graded hotels.

History

Citation

This chapter was originally published as: Dolnicar, S, Profiling the One- and Two-star Hotel Guest for Targeted Segmentation Action: a Descriptive Investigation of Risk Perceptions, Expectations, Disappointments and Information Processing Tendencies, in G.I. Crouch et al. (eds.), Consumer Psychology of Tourism, Hospitality, and Leisure, CAB International, New York, 3, 11-20.

Pagination

11-19

Language

English

RIS ID

10180

Usage metrics

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC