The Reification Bias in Marketing Communication: Antecedents and Consequences

几年前，苹果公司在其Mac电脑上推广了200美元的折扣券，称此折扣相当于iPod mini的价值。这样的优惠需要一个数字度量（节省200美元）和将该度量与一个对象（iPod mini）相关联的附加信息。因此，储蓄是具体化的。我们将具体化定义为一种机制，它通过将一个数值度量等同于一个非数值对象或问题，将其转化为某种具体的东西。具体化是向消费者传达折扣等数字信息的一种特殊方式。它不同于仅仅呈现一个简单数字的常规通信活动。我们的焦点问题是，物化是否会使消费者的反应产生偏差，比如对产品的态度。换句话说，消费者对具体化的信息比简单的数字信息更有好感吗？在总结以前的文献，研究是否以及如何具体化的偏见发生是缺乏的。我们的项目旨在通过调查物化对消费者反应的影响来填补这一空白。特别是，我们通过解决以前的研究没有研究过的四个主要研究问题，为营销文献做出了贡献：（1）是否存在物化偏见？在这里，我们第一次提出，并试图找到证据表明，消费者表现出物化的偏见在定价的情况下。我们将物化偏差定义为消费者对一家公司的产品的反应更积极，该公司将一个数字测量等同于一个对象或问题，而不是提供一个单独的抽象测量。(2)具体化偏误为什么会发生，又是如何发生的？为了回答这个问题，我们提供并测试心理意象作为物化偏见发生的理论解释。(3)物化是否总是对消费者的反应有积极的影响？在这里，我们确定了重要的边界条件下，具体化的优势可能会被放大，衰减，甚至逆转。(4)拟议效果的稳健性如何？当我们在一个定价环境中检验研究问题1-3时，作为向消费者呈现数字信息的原型环境，我们测试了具体化方法对其他营销传播环境的可推广性，即服务恢复，事业相关营销和技术产品提供。为了回答这四个研究问题，我们将进行九项实验研究（加上预测试），包括实验室和实地实验。这种方法使我们能够增加我们的结果的内部和外部有效性。此外，我们的研究对营销从业人员具有重要意义。具体化可以提高营销传播的有效性。重要的是，这种策略不仅可以应用于定价，还可以应用于多种营销环境，只要公司向利益相关者传达数字信息（即，广告）。

A few years ago, Apple promoted a 200 USD discount coupon on its Mac computers, stating that this discount corresponds to the value of an iPod mini. Such an offer entails a numerical measure (savings of 200 USD) and additional information that relates this measure to an object (an iPod mini). As such, the savings are reified. We define reification as a mechanism that converts a numerical measure into something concrete by equating it to a non-numerical object or issue. Reification is a particular way to communicate numerical information like discounts to consumers. It differs from regular communication activities that merely present a plain number. Our focal question is whether reification biases consumer responses, such as attitude toward the offer. In other words, do consumers respond more favorably to a reified than plain numerical information? In summarizing previous literature, research examining whether and how the reification bias occurs is lacking. Our project aims to fill this gap by investigating the effect of reification on consumer responses. In particular, we contribute to the marketing literature by addressing four major research questions that previous research has not examined: (1) Does a reification bias occur? Here, for the first time, we propose and attempt to find evidence that consumers exhibit a reification bias in a pricing context. We define reification bias as consumers responding more favorably to a firm's offering that equates a numerical measure with an object or issue than to an offering that presents the abstract measure alone. (2) Why and how does the reification bias occur? To answer this question, we offer and test mental imagery as a theoretical explanation for the occurrence of the reification bias. (3) Does reification always have a positive effect on consumer reactions? Here, we identify important boundary conditions under which the advantage of reification may be amplified, attenuated, or even reversed.(4) How robust is the proposed effect? While we examine research questions 1-3 in a pricing context serving as a prototypical context for presenting numerical information to consumers, we test the generalizability of the reification method to other marketing communication contexts, namely service recovery, cause-related marketing, and technological product offerings.In order to answer these four research questions, we will conduct nine experimental studies (plus pretests) including both laboratory and field experiments. This approach allows us to increase the internal and external validity of our results. Moreover, our research has important implications for marketing practitioners. Reification may increase the effectiveness of marketing communication. Importantly, this strategy can be applied not only to pricing, but also to multiple marketing contexts, whenever firms communicate numerical information to stakeholders (i.e., in advertising).