Prediction of choice in a technically complex, essentially intangible, highly experiential, and rapidly evolving consumer product

Nataraajan, Rajan

doi:10.1002/mar.4220100502

Cited by 14 publications

(5 citation statements)

References 19 publications

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“…This study adopts the stimulus-organism-response (S-O-R) model to examine the effects of choice variety cues on customers' emotional responses, and the influence of those responses on purchase intentions (Mehrabian and Russell, 1974;Sheng and Joginapelly, 2012;Zhang et al, 2014). We predict that if choice variety demands a more prolonged and extensive decision process, affect or emotion exerts a stronger influence on judgments, such that consumers' choices among complex products are more influenced by their emotional states (Forgas, 1995;Nataraajan, 1993). Despite the advances of design product variety in traditional contexts, some questions remain, especially in the process of determining how and when choice variety influences consumers' willingness to purchase through the personal emotion response.…”

Section: Introductionmentioning

confidence: 99%

Purchase decision: does too much choice leave us unhappy?

Tang

Hsieh²,

Chiu

2017

EJM

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Purpose The purpose of this study is to determine how and when choice variety influences consumers’ willingness to purchase, according to a personal emotion perspective. The choice paradox indicates that although having many choices can be beneficial, it can also cause customer decision paralysis and unhappiness. This article proposes that the desire and motivation to process information vary from person to person, and emotional factors are relevant. Design/methodology/approach With a 2 × 2 experimental design, this study examines the influence of the interaction of choice variety with need for cognition (NFC) on positive and negative emotions, and then tests the mediating effects on purchase intentions. The sample includes 214 college students, assigned randomly to self-assessment questionnaires. Findings Both high NFC respondents in the high variety condition and low NFC respondents in the low variety condition exhibit more positive emotions than low NFC respondents in the high variety condition but not more than high NFC respondents in the low variety condition. Positive (negative) emotions increase (decrease) consumers’ purchase intentions. Research limitations/implications The experiment was conducted in a virtual store, which may not match real-life store environments or reflect participants’ actual purchase behaviours, so additional research should consider the influence of involvement further. Practical implications The results offer suggestions for developing more effective communication with emotions, increasing involvement to maintain consumers’ positive emotions and relieve their confusion, and managing product variety. Originality/value This article meets the identified need to study how choice variety influences consumers’ willingness to purchase from a personal emotion perspective.

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Section: Introductionmentioning

confidence: 99%

Purchase decision: does too much choice leave us unhappy?

Tang

Hsieh²,

Chiu

2017

EJM

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“…Thus, this article will start with the TRA and compare it with two more recent derivatives by using structural equations modeling (SEM). The TRA -and both derivative models -have been used by other researchers to predict behavioral intentions toward new technologies (e.g., Nataraajan, 1993), but this may be the first research to directly compare all three models in a single study of consumers.…”

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confidence: 99%

A comparison of three models to explain shop‐bot use on the web

Gentry

Calantone

2002

Psychology and Marketing

190

123

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An ongoing requirement in the 21st century is that marketers must understand the impact of the network economy on buyer behavior. Although new models will certainly be developed, it seems reasonable that existing models of buyer behavior will still apply. This study uses structural-equations modeling to test if three popular models of behavioral intent -the theory of reasoned action, the theory of planned behavior, and the technology acceptance model -work in a network context. It recommends the technologyacceptance model as superior to the others in the current network context, and also shows how to check and account for the presence of common method bias in a single source instrument. ᭧

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“…Compared to traditional survey approaches that seek to determine the influence of separate product cues via selfexplicated customer importance ratings (e.g., Brucks et al, 2000;Olson and Jacoby, 1972), a conjoint approach offers several important benefits, including (1) the ability to directly assess consumer trade-offs on the cue level, (2) greater realism via scenario profiling, and (3) minimizing survey-based response errors such as acquiescence and common method variance bias (DeSarbo et al, 1994;Nataraajan, 1993;Ostrom and Iacobucci, 1995). Conjoint tasks are increasingly employed by marketing scholars as a means of capturing both consumer choice and managerial decision making (e.g.…”

Section: Conjoint Designmentioning

confidence: 99%