Academic Seminar1. What is Your Phone Number?: Effects of Randomized Monetary Incentives for App Download Promotion (전치홍) 2. Reviewing Before Reading? An Empirical Investigation of Book Consumption Patterns and Their Effects on Reviews (이희승)
- 2018-10-30 ~ 2018-10-30
- SUPEX Buliding, 3rd floor, #301
- School of Management Engineering
We would like to invite you to participate in Management Engineering(ME) Seminar.
1. When: October 30th (Tuesday), 16:00~17:20
2. Where: SUPEX Building, 301 lecture room
3. Speaker: Chihong Jeon, Heeseung Lee (KAIST, PhD Candidate)
1) What is Your Phone Number?: Effects of Randomized Monetary Incentives for App
Download Promotion (Chihong Jeon)
2) Reviewing Before Reading? An Empirical Investigation of Book Consumption
Patterns and Their Effects on Reviews (Heeseung Lee)
5. Research field: IT Management
* Lecture will be delivered in English.
1.As the mobile app market becomes more competitive, firms try to attract more new customers via promotions such as price discount, targeted advertising, and incentivized app downloads. Also, it is hard to maintain the downloader’s engagement in the service. While some researchers asserted that a higher level of monetary incentives attracts more “cherry pickers” who are interested only in the compensation, not in the service, others showed that unconditional incentives could increase receivers’ engagement and performances. In this study, we examine a natural experiment with customers’ phone numbers to distribute monetary incentives randomly by a mobile app development company for personal finance management. Using a zero hurdle model, our results based on 184,809 mobile app users demonstrate that higher incentives tend to attract more downloads as expected, but do not significantly reduce the average engagement of customers. Instead, we find evidence that a large amount of monetary incentives make customers try and learn the service more actively in the initial period. Our research contributes to research streams on mobile app adoption, subsidies and customer acquisition, and cherry-picking behavior in online marketplaces by providing practical implications.
2.Over the past decades, research on online book reviews has inundated academic circles with numerous theoretical reflections and empirical manifestations aimed at explaining participation in such activities. Yet, these studies succumbed to the conventional pitfall of assuming that consumers write reviews only after they fully read the book that they purchased. A recent industry report revealed that numerous individuals initiate book reading but that only a few finish them—a tendency that holds even for bestsellers. Despite being unread or abandoned in early chapters, however, books may still receive positive reviews from consumers. With these considerations in mind, we investigated how consumers’ book consumption patterns (e.g., reading completion rates) affect their review behaviors and how reviews generated in prior to completion differ from reviews that are based on sufficiently complete consumption in terms of informative-ness and bias. Consumption patterns were traced and captured from records of reading activities on e-book devices and apps, and subsequent review behaviors were measured on the basis of review intention, valence, length, and extremity. Our results indicated that consumers who exhibit either extremely low or high completion rates are more likely to write online reviews than those with moderate completion rates. The findings also show that these consumers at the extreme ends of the completion continuum provide higher review ratings. Review length, however, exhibits an inverted U-shaped relationship with completion rate, suggesting that consumers with extremely low or high completion rates tend to write shorter reviews and exhibit higher variances in ratings than do consumers with moderate completion rates. We also find evidence to the relationship between incomplete consumption and biased online reviews due to inaccurate assessment of an information good. We provide novel insights for digital platforms and policy makers on how to correct biases embedded in reviews from consumers with incomplete consumption.