Search

This research studies the impact of articles appearing in the top four journals for consumer research— JCR , JMR , JM , and JCP— by examining factors that influence scholarly, public, and practical impact. This conceptually distinguishes between "incongruent novelty" (novelty arising from incongruity between an article and other existing articles) and "recombinant novelty" (novelty based on drawing from more disparate references). Incongruent novelty is decomposed into two components: (1) topic incongruity—incongruity between an article's topic and other existing topics at the time and (2) article incongruity—incongruity between an article and other existing articles on the same primary topic. By integrating topic modeling and word embedding to measure these constructs, we demonstrate varying impacts of types of novelty on three types of impact. Overall, our findings illustrate that topic and article incongruity have effects above and beyond recombinant novelty. For both scholarly and public impact, our results suggest that moderately high topic incongruity has the largest influence, suggesting that researchers should address novel topics. Additionally, scholarly citations are positively affected by lower and higher (vs. moderate) levels of article incongruity, suggesting that researchers either engage in programmatic research or add a new approach to the existing research on a topic. [ABSTRACT FROM AUTHOR]

Persuasion success is often related to hard-to-measure characteristics, such as the way the persuader speaks. To examine how vocal tones impact persuasion in an online appeal, this research measures persuaders' vocal tones in Kickstarter video pitches using novel audio mining technology. Connecting vocal tone dimensions with real-world funding outcomes offers insight into the impact of vocal tones on receivers' actions. The core hypothesis of this paper is that a successful persuasion attempt is associated with vocal tones denoting (1) focus, (2) low stress, and (3) stable emotions. These three vocal tone dimensions—which are in line with the stereotype content model—matter because they allow receivers to make inferences about a persuader's competence. The hypotheses are tested with a large-scale empirical study using Kickstarter data, which is then replicated in a different category. In addition, two controlled experiments provide evidence that perceptions of competence mediate the impact of the three vocal tones on persuasion attempt success. The results identify key indicators of persuasion attempt success and suggest a greater role for audio mining in academic consumer research. [ABSTRACT FROM AUTHOR]

This research investigates reviewing experts on online review platforms. The main hypothesis is that greater expertise in generating reviews leads to greater restraint from extreme summary evaluations. The authors argue that greater experience generating reviews facilitates processing and elaboration and enhances the number of attributes implicitly considered in evaluations, which reduces the likelihood of assigning extreme summary ratings. This restraint-of-expertise hypothesis is tested across different review platforms (TripAdvisor, Qunar, and Yelp), shown for both assigned ratings and review text sentiment, and demonstrated both between (experts vs. novices) and within reviewers (expert vs. pre-expert). Two experiments replicate the main effect and provide support for the attribute-based explanation. Field studies demonstrate two major consequences of the restraint-of-expertise effect. (i) Reviewing experts (vs. novices), as a whole, have less impact on the aggregate valence metric, which is known to affect page-rank and consumer consideration. (ii) Experts systematically benefit and harm service providers with their ratings. For service providers that generally provide mediocre (excellent) experiences, reviewing experts assign significantly higher (lower) ratings than novices. This research provides important caveats to the existing marketing practice of service providers incentivizing reviewing experts and provides strategic implications for how platforms should adopt rating scales and aggregate ratings. [ABSTRACT FROM AUTHOR]

The authors propose a creative advertising system (CAS) for the generation and testing of advertising creative ideas, founded on artificial intelligence (AI) principles. The proposed system emerges from a conceptual framework where advertising creativity is more broadly defined as a search process, the outcomes of which should be evaluated based on a set of rules. This broader definition provides a generative perspective and extends current approaches to advertising creativity that are mainly based on outcome measures such as perceived novelty and appropriateness (value). The framework is flexible enough to accommodate existing advertising concepts such as advertising templates and explain why executional advertising elements are not consistently effective across different ads. The proposed system can be used both as a reflection and a generation tool for advertising creators and offers promising opportunities for interdisciplinary research. Fundamentally, it can help aspiring and established creators understand that creativity is not an elite privilege but rather a systematic process which can be aided by data and computation. [ABSTRACT FROM AUTHOR]

Our Tablet Computer data set, collected from various websites, contains market dynamics related to 2,163 products, characteristics of 794 products, more than 40,000 consumer-generated product reviews, and information about 39,278 [...]