Prior literature indicates conflicting effects of online product information, which may complicate or simplify consumer purchase decisions. Therefore, the purpose of this paper is to investigate how different online product information (i.e. the choice set size and the popularity information and its presentation) affect consumers’ decision making and the related market outcomes.
This research relies on information-processing theories and social learning theory. By stepwise conducting two 2×2 within-subject factorial design experiments, this research examines the effects of the choice set size, product popularity information and product presentation on consumers’ decision making and the aggregated market outcomes.
The results show that product popularity information led consumers to either simplify or complicate their decision strategy, depending on the size of the choice sets. Additionally, presenting products by their popularity in descending order resulted in consumers making decisions with a larger decision bias. The results also show that the presence of product popularity was more likely to forge a “superstar” structure in a large market.
The research suggests that e-retailers and e-marketplace operators should carefully utilize product popularity information. Multiple mechanisms that shape different shopping environments with different orders are necessary to create a long-tailed market structure.
This study found the mixed effects of product popularity information when it is presented in different environments (i.e. the large/small choice set and the sorted/randomized product presentation). The overuse of popularity information may induce consumers’ decision bias.
The work described in this paper was partially supported by grants from the National Natural Science Foundation of China under Grant Nos: 71571184, 71471011, 91846204, 71531001, 71331007.
Yu, Y., Liu, B., Hao, J. and Wang, C. (2019), "Complicating or simplifying? Investigating the mixed impacts of online product information on consumers’ purchase decisions", Internet Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/INTR-05-2018-0247Download as .RIS
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