Information representations such as ratings and reviews play an important role in assisting users in making decisions in online environments. Prior information systems (IS) research has mostly focused on the role of extreme valence, i.e., the positivity/negativity of information, portrayed by such representations. Yet this bipolar approach discounts how the coexistence of positivity and negativity (i.e., ambivalence) or their absence (i.e., indifference) is formed and leads to distinct attentional processes and outcomes such as purchase decisions. We theorize how and why the valence of information projected through such representations may elicit mixed feelings and influence decision-making in online environments. We conducted four randomized controlled experiments, including an electroencephalography (EEG) study, to disentangle the influence of ambivalence and indifference on decision-making in an online shopping context. We found that ambivalence and indifference to online information distinctly influenced attention and purchase decisions relative to positivity and negativity. Our findings further suggest the inability of incumbent bipolar representations, such as the widely implemented star rating system, to capture the mixed feelings expressed in online content. We propose a bivariate intervention that overcomes the limitations of bipolar representations by not only discerning ambivalence from indifference but also amplifying purchase decisions for products with ambivalent information by at least 50%, compared to incumbent bipolar representations. Our findings advance ongoing research on the role of information valence in online environments and offer implications for practice.

中文翻译：

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矛盾心理比冷漠好：在线环境中矛盾心理的行为和神经生理学评估

评级和评论等信息表示在帮助用户在在线环境中做出决策方面发挥着重要作用。先前的信息系统 (IS) 研究主要集中在极端效价的作用上，即信息的正/负性，由此类表示法描绘。然而，这种两极方法忽视了积极和消极共存（即矛盾心理）或它们的缺失（即冷漠）是如何形成的，并导致不同的注意力过程和结果，如购买决定。我们从理论上分析了通过此类表示形式投射的信息效价如何以及为何会引发复杂的感受并影响在线环境中的决策制定。我们进行了四项随机对照实验，包括一项脑电图 (EEG) 研究，理清在线购物环境中矛盾心理和冷漠对决策的影响。我们发现，相对于积极性和消极性，对在线信息的矛盾心理和漠不关心会明显影响注意力和购买决策。我们的研究结果进一步表明，现有的两极代表无法捕捉在线内容中表达的复杂感受，例如广泛实施的星级评级系统。我们提出了一种双变量干预，与现有的双极表征相比，它不仅可以从冷漠中辨别矛盾情绪，而且可以将具有矛盾信息的产品的购买决策放大至少 50%，从而克服双极表征的局限性。