Missing information and discounting: Exploration and extension

Missing information (MI), if detected, often leads to alternative discounting. However, inferences reduce uncertainty of MI and thus reduce discounting. This paper suggests that discounting results not only from uncertainty of MI, but from consumer’s overall “confidence in evaluating" (CE). Confidently held inferences help resolve MI uncertainty, improve CE and attenuate discounting. This mediating role of CE suggests discounting/evaluation effects could also be observed in ‘non-MI’ contexts involving other types of uncertainty detection and resolution. An experiment demonstrates the role of CE, and a model proposes interactive effects of sources of uncertainty, and uncertainty detection and resolution on overall CE and discounting. The model extends the long observed discounting effect of MI to broader situations and highlights roles of ambiguity detection/resolution in evaluation effects. Introduction and Conceptual Development A choice situation involves MI when values for one or more of the attributes considered relevant for the decision task are not immediately available for one or more alternatives in the choice set (Burke 1996). Most studies agree that uncertainty associated with MI results in evaluation differentials between full and partially described alternatives (Edenbach and Moore 2000, Huber and McCann 1982; Jaccard and Wood 1988, Johnson and Levin 1985, Kardes, Posavac and Cronley 2004; Levin, Chapman and Johnson 1988). Discounting or the “penalty effect” refers to the common finding that alternatives with a missing value are evaluated less favourably than alternatives with at least an average value for the attribute. While a number of different processes may cause discounting of MI alternatives (Kardes, Posavac and Cronley 2004), it is generally agreed to be driven by a penalty for uncertainty associated with the MI coupled with risk aversion (Kahneman and Tversky 1979). Some studies, however, have shown that MI can lead to equally or even more favourable evaluations than fully described alternatives in certain conditions (Jaccard and Wood 1988; Levin, Johnson and Faroane 1984; Levin, Chapman and Johnson 1988). These conflicting findings have been reconciled by considering the effects of MI detection and the use of inferences to fill in MI. Studies show that consumers may 1) reduce the uncertainty and discounting associated with MI by filling in the MI (Dick, Chakravarti and Biehal 1990; Ford and Smith 1987; Huber and McCann 1982; Levin, Chapman and Johnson 1988), or 2) fail to detect the MI at all resulting in no effect of the MI uncertainty. Sanbonmatsu, Kardes and Herr (1992) found that subjects did not always recognize the absence of information and that ilure to do so lead to failure to moderate judgments and confidence in those judgments. fa Finally, studies have also considered the impact of the level of confidence in inferences about MI on evaluations. Levin, Chapman and Johnson (1988) found that rather than having lower levels of confidence in MI tasks, confidence was in fact higher when subjects were asked to infer missing values. The overconfidence may be the result of accepting one’s own inferences as information without considering possible error. Lim and Kim (1992) found that discounting was attenuated when inferences were used to fill-in missing attributes as well. However, they also found that the effect was moderated by consumers' confidence in the