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RESEARCH PRODUCT
The Influence of Context-Based Complexity on Decision Processes
Jella Pfeiffersubject
Process (engineering)business.industryComputer scienceContext (language use)Machine learningcomputer.software_genreConjoint analysisEmpirical researchBusiness decision mappingEye trackingArtificial intelligenceMarketing researchbusinesscomputerTRACE (psycholinguistics)description
In this chapter, we present an empirical study which investigates the influence of context-based complexity on decision processes.1 To determine context-based complexity accurately, we measure each subject’s preferences individually with two advanced techniques from marketing research: choice-based conjoint analysis (CBC, Haaijer and Wedel 2007) and pairwise-comparison-based preference measurement (PCPM, Scholz et al. 2010), rather than relying on less precise estimates of preferences. Furthermore, we use eye tracking to trace the process of information acquisition precisely. Our results show that low context-based complexity leads to less information acquisition and more alternative-wise search. Moreover, people search information attribute-wise in the first stage of the decision process, then eliminate alternatives, and search alternative-wise in the last stage. We also found evidence that in situations of low context-based complexity, people switch earlier to alternative-wise processing. In essence, our findings suggest that people select decision strategies from an adaptive toolbox in situations of varying complexity, starting with lexicographic and elimination by aspect type rules and ending with strategies that imply an alternative-wise search.
year | journal | country | edition | language |
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2011-10-15 |