Academic journal article Asian Social Science

Choice Experiment Attributes Selection: Problems and Approaches in a Modal Shift Study in Klang Valley, Malaysia

Academic journal article Asian Social Science

Choice Experiment Attributes Selection: Problems and Approaches in a Modal Shift Study in Klang Valley, Malaysia

Article excerpt

1. Introduction

Choice experiment (CE) is a stated preference method that could be employed to derive individual utilities based on attributes of goods and services in question (Boxall, 1996). The underlying basis of a choice modeling relies on random utility theory, and is based on Lancaster's characteristics theory of value. This allows that any specific goods to be valued based on their attributes; "any good can be described in terms of its attributes, or characteristics, and the levels that these take" (Bateman et al., 2002, p. 249). Therefore, in any CE studies potential policies or products are described by their assigned characteristics which is called attributes and a range of defined dimensions assigned to each attribute that is referred as attribute level (Abiiro et al., 2014). The experimental design in choice experiment forms finite number of alternatives from different combination of attributes and levels. The presented alternatives are policy scenarios or intervention programs. The respondents are then asked to choose their most preferred options or alternatives from set of presented ones. As it is obvious, designing the questionnaire, selecting attributes, levels, and experimental design is fundamental part in conducting every CE study (Hensher et al., 2005).

Experts of economic valuation of non-market goods have underscored the undesirable impact of bad instruments on valuation outcomes (Portney, 1994; Bateman et al., 2002). In the specific case of choice experiment, the proficiency of researchers to specify the appropriate sub-set of all potential choice-influencing attributes determines the validity of outcomes (Mangham et al., 2009; Adam et al., 2013). This is because, since any CE study is an attribute based research, the accuracy of study is greatly depend on appropriate selection of attributes and levels (Abiiro et al., 2014). Accordingly, if attributes are not specified accurately, there would be a chance of producing inaccurate results which can mislead policy implementation (Abiiro et al., 2014). Since the number of attributes which are affecting decision making could be extensive, reducing the number of attributes to be included in the study has various benefits (Louviere, Hensher, & Swait, 2000). First, as the number of attributes increase, the task of choice becomes more complicated to a respondent. It also can result in respondents' confusion and fatigue and less accurate trade-off. Second, as the attributes and attribute level increases, the size and complexity of the choice task increases which needs more effort (in term of time and cost) to conduct. Hence, as choice metric team suggest, it is better to limit the number of attributes and levels to a more manageable size. To avoid complexity and confusing respondents, researchers need realistic attributes which make them policy implementable. Blamey et al. (2002) suggested that selected attributes have to be "demand relevant, policy relevant and measurable". In the process of selecting or reducing attributes if the specified attributes are not those about which respondents have the highest possible preference, attribute non-attendance problem, that biases estimated welfare measure could be induced (Alemu et al., 2013; Hess et al., 2012; Hensher et al., 2012). It means some of respondents might intentionally ignore those attributes that are least preferred by them in making choices (Lagarde, 2013). Thus, a great deal of caution is required in attribute selection which constitutes the first stage of analysis in CE (Coast & Horrocks, 2007; Kløjgaard et al., 2012). This is because, products, services or environmental goods possess long list of attributes beyond those usually modeled in CE studies (De Bekker-Grob et al., 2012). Choice-attribute selection is usually determined via the exploration of the views of target population in interviews as well as compilation of attributes from literature review (Hanley et al., 1998; Coast & Horrocks, 2007; Mangham et al. …

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