Goals constrain choices: the role of goals in choice set formation

摘要: Past research has supported the existence of choice set formation (CSF) processes as a means to ease cognitive burden arising from individual decision making (Hauser, 2014; Roberts & Lattin, 1997; Swait, 1984). The motivations for makers use screening/CSF are varied and restrictions that motivate filtering criteria diverse (Botti et al., 2008). More generally, constraints range characteristics individuals, contextual factors attributes alternatives, among others (e.g., In this paper we propose goals can exert an influential, even primary, role in addition their final deliberation itself (Li, 2013). Our statement play significant CSF is not merely speculation, but based on past demonstrating products perceived attainment desired end-states van Osselaer Janiszewski, 2012). sense, subjective value product derived its compatibility with active lead these (Markman Brendl, 2000). Consider following situations which highlight importance understanding goal-based CSF. A traveller interested history religion may refrain considering visiting Jerusalem so “to avoid feeling unsafe”; or yet other individuals prefer travel by bus rather than airplane fear flying”. Participants auction do gain social status”, acquire rare goods” “experience thrill pursuing difficult objective”. consumer choose decadently delicious ice cream because he wants indulge himself through eating”, fruit pieces when his goal stick healthy diet”, compromise some gelato frozen yoghurt attempt reconcile both goals. Strawberry gelatine, contributing towards either goal, might be considered situation. To test whether act screeners, conducted two studies each categories (tourism destinations dessert selection). main objective first study category was identification relevant consumption used second study. Additionally, also intended explore influence multiple simultaneous category, investigate relative occurrence cited goals, identify association outcomes (see: Carver, 1996; 2012), well insight into popular tourism options sample. questions collected open-ended responses real time text mining algorithm. This approach allowed instrument more closely align qualitative laddering techniques, conventionally understand “why’s” underlying decision-making, probing respondents own answers. designed basis alternatives observed one. task consisted discrete experiments manipulated conditions. For tasks, dependent variable referred indicating they presented worthy consideration given condition. between-subjects design randomly allocated one three experimental conditions category. We selected (A) avoidance (B) (Carver, 1996) list previously elicited, account any potential differential effects (Florack, Scarabis, Gosejohann, 2005), third combined-goals (both B) Balanced Incomplete Block Design, 13 being groups four, different scenarios. total 367 valid were across categories. results strongly support differences evaluation function activated conditions: i.e., quality according given. These findings suggest attainability goal(s). Managerially, suggests changes bundling impacts usefulness members bundle. Understanding how phenomenon incorporated existing models particular cut-offs implemented decision-makers, promising outcome currently undertaken develop extended goal-sensitive behaviour. References Botti, S., Broniarczyk, Haubl, G., Hill, R., Huang, Y., Kahn, B., . Wansink, B. (2008). Choice under restrictions. Marketing Letters, 19(3-4), 183-199.  C. S. (1996). Some ways differ implications those differences. P. M. Gollwitzer J. A. Bargh (Eds.), Pyschology action: linking cognition motivation New York: Guilford Press. Florack, A., M., (2005). Regulatory focus information processing. F. R. Kardes, Herr Nantel Applying consumer-focused strategy (pp. 235-263). Hauser, (2014). Consideration-set heuristics. Journal Business Research, 67(8), 1688-1699.  Li, L. (2013). antecedent volition evaluative behavior. (Doctor Philosophy Dissertation), University Alberta, Edmonton, Canada. Markman, (2000). choice. Psychology Learning Motivation, 39, 97-128.  Roberts, H., (1997). Consideration: Review prospects future insights. 406-410.  (1984). Probabilistic generation transportation demand models. (PhD), Massachusetts Institute Technology, Massachusetts. Osselaer, J., (2012). Goal-Based Model Product Evaluation Choice. Consumer 39(2), 260-292.