Estimating Life Cycle Sales of Technology Products with Frequent Repeat Purchases: A Fractional Calculus-Based Approach

2023 | Information Systems Research | Citations: 0

Authors: Lotfi, Aslan; Jiang, Zhengrui; Lotfi, Ali; Jain, Dipak C.

Abstract: Accurately predicting the sales trajectory of a product in its life cycle is cri ... Expand

Abstract: Accurately predicting the sales trajectory of a product in its life cycle is critically important for firms’ medium- and long-term planning. Because classic product-diffusion models such as the Bass model consider only initial product purchases, they are ill-fitted for sales prediction for today’s technology products with a shorter life cycle and frequent repeat purchases or subscription renewals. Despite the long tradition of product diffusion research, there exists no viable model option when repeat purchases constitute a large proportion of product sales. The present study introduces a new sales growth model, termed the generalized diffusion model with repeat purchases (GDMR), to fill this void. The GDMR formulates the growth rate of sales using a noninteger-order integral equation rather than the integer-order differential equation typically adopted in existing diffusion models. The GDMR is parsimonious and easy to implement. Empirical results show that the GDMR fits sales data with varying proportions of repeat purchases quite well, making it suitable for predicting sales of a wide variety of products. In addition, the GDMR can be extended to incorporate marketing mix variables, thus enhancing its applicability in business decision making. Furthermore, using both real and simulated data, we show that the GDMR can reliably recover a product’s adoption trend using only sales data, thus cementing its theoretical validity and empirical effectiveness. Finally, we show that the GDMR is superior to generic time series and machine learning models in predicting future product sales. History: Ram Gopal, Senior Editor; Wenjing Duan, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1131. Collapse

Topics: marketing management DVD innovation management diffusion of innovation tablet

Methods: longitudinal research time series analysis machine learning simulation autoregressive integrated moving average

Text Performance on the Vine Stage? The Effect of Incentive on Product Review Text Quality

2023 | Information Systems Research | Citations: 0

Authors: Qiao, Dandan; Rui, Huaxia

Abstract: Incentivized reviews have become increasingly prevalent on product review sites ... Expand

Abstract: Incentivized reviews have become increasingly prevalent on product review sites such as Amazon. Whereas outright fake reviews are clearly unacceptable and should be removed from review platforms, reviews by incentivized consumers with otherwise authentic product experiences fall into a gray area. On the one hand, many critics and researchers have warned of their harm by pointing out their biased ratings. On the other hand, these reviews might complement organic reviews with review text of higher quality. The current paper studies whether incentivized reviews on Amazon are more coherent and offer richer detail. We use Amazon’s platform-incentivized reviews, known as Vine reviews, for our primary sample and use seller-incentivized reviews for checking robustness. Estimations from a two-way fixed-effect model consistently show that incentivized reviews do compensate for their reduced impartiality through better text quality, measured by discourse coherence and level of relevant detail. This finding is further supported by a randomized experiment using Amazon Mechanical Turk. Hence, current literature findings on the poor quality of text of incentivized reviews, based on review length and lexical complexity, portray only an incomplete picture of incentivized reviews. Given that numerical ratings for products via incentivized reviews are likely biased whereas their text content is of high quality, a natural way to embrace incentivized reviews is to keep their text content, suppress their numerical ratings, and always highlight the label of “incentivized reviews.”History: Juan Feng, Senior Editor; Jianqing Chen, Associate Editor.Funding: This work was supported by Singapore Ministry of Education Tier 1 Research Grant [Grant A-0008174-00-00].Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1146. Collapse

Topics: Vine experience good online review DVD video game

Methods: experiment qualitativ observational study product review experimental group robustness check

Return of the Movie Night? Analyzing the Impact of Netflix Subscriptions on Offline Movie Spending

2022 | International Conference on Information Systems | Citations: 0

Authors: Fang, Sihan; Gopal, Anand; Kwon, Hyeokkoo Eric; Park, Yongjin

Abstract: The subscription-based business model is disruptive in the copyright industries ... Expand

Abstract: The subscription-based business model is disruptive in the copyright industries. More than a digitalized distribution channel, it fundamentally transforms both supply and demand sides regarding content provision and consumption. However, there is scant evidence about how and why it affects the local traditional industry. This study investigates the impact of the subscription-based business model on offline activity consumption in the motion picture industry. Leveraging a unique dataset with individuals' every transaction record and a difference-in-differences approach, we conclude that Netflix subscription increases offline movie consumption. We support that individuals have unmet hedonic and social demands with the imperfect disruptive technology. They, therefore, attend more hedonic and social activities, including movies, dining, entertainment, to satisfy their unmet needs. In addition, the identified effect is more pronounced for individuals with higher hedonic (i.e., younger people) and social (i.e., lower-income and residents of smaller towns) needs. Theoretical and practical implications are discussed. Collapse

Topics: digital service Netflix streaming service video streaming service mobile application

Methods: experimental group robustness check longitudinal research difference in differences quasi experiment

The causal effect of subscription video streaming on DVD sales: Evidence from a natural experiment

2022 | Decision Support Systems | Citations: 0

Authors: Yu, Yinan; Chen, Hailiang; Peng, Chih-Hung; Chau, Patrick Y.K.

Abstract: Subscription-based video streaming has recently become the main revenue driver i ... Expand

Abstract: Subscription-based video streaming has recently become the main revenue driver in the home entertainment industry. Whether and how it affects the sales of physical media, which was previously the industry’s largest revenue source for decades, is still not well understood. We answer this question using a natural experiment that occurred on October 1, 2015, when the content owner Epix switched its streaming partner from Netflix to Hulu. This event created an exogenous shock that significantly reduced the streaming availability of Epix’s content because of the difference in the market shares of the two streaming service providers at the time. This occurrence allows us to investigate the causal effect of subscription streaming on physical DVD sales. Our difference-indifferences analysis shows that the decline in the streaming availability of Epix’s content caused an increase of 36.07% in its monthly DVD sales during the 15 months after the event. We also find that the cannibalization between these two channels is much stronger for movies with higher level of content stickiness (e.g., more recent titles, and titles with a general audience (G) or parental guidance (PG) rating or belonging to the children/family genre). Our findings provide important implications for content owners on how to balance physical sales with revenues from streaming licenses. Collapse

Topics: DVD digital service Netflix Hulu streaming service

Methods: experimental group natural experiment Internet Movie Database review longitudinal research robustness check

Incorporating the Time–Order Effect of Feedback in Online Auction Markets through a Bayesian Updating Model

2021 | Management Information Systems Quarterly | Citations: 0

Authors: Chau, Michael; Li, Wenwen; Yang, Boye; Lee, Alice; Bao, Zhuolan

Abstract: Online auction markets host a large number of transactions every day. The trans ... Expand

Abstract: Online auction markets host a large number of transactions every day. The transaction data in auction markets are useful for understanding the buyers and sellers in the market. Previous research has shown that sellers with different levels of reputation, as shown by the ratings and comments left in feedback systems, enjoy different levels of price premiums for their transactions. Feedback scores and feedback texts have been shown to correlate with buyers' level of trust in a seller and the price premium that buyers are willing to pay (Ba and Pavlou 2002;Pavlou and Dimoka 2006). However, existing models do not consider the time-order effect, which means that feedback posted more recently may be considered more important than feedback posted less recently. This paper addresses this shortcoming by (1) testing the existence of the time-order effect, and (2) proposing a Bayesian updating model to represent buyers' perceived reputation considering the time-order effect and assessing how well it can explain the variation in buyers' trust and price premiums. In order to validate the time-order effect and evaluate the proposed model, we conducted a user experiment and collected real-life transaction data from the eBay online auction market. Our results confirm the existence of the time-order effect and the proposed model explains the variation in price premiums better than the benchmark models. The contribution of this research is threefold. First, we verify the timeorder effect in the feedback mechanism on price premiums in online markets. Second, we propose a model that provides better explanatory power for price premiums in online auction markets than existing models by incorporating the time-order effect. Third, we provide further evidence for trust building via textual feedback in online auction markets. The study advances the understanding of the feedback mechanism in online auction markets. Collapse

Topics: online auction electronic market smart watch mobile system decision making

Methods: regression analysis method experiment robustness check parametric test descriptive statistic

Theories: lemon market theory signaling theory game theory economic theory

Measuring Product Type and Purchase Uncertainty with Online Product Ratings: A Theoretical Model and Empirical Application

2021 | Information Systems Research | Citations: 7

Authors: Chen, Peiyu; Hitt, Lorin M.; Hong, Yili; Wu, Shinyi

Abstract: Building on the distinction between search and experience goods, as well as vert ... Expand

Abstract: Building on the distinction between search and experience goods, as well as vertical and horizontal differentiation, we propose a set of theory-grounded, data-driven measures that allow us to measure not only product type (search vs. experience, horizontal vs. vertical differentiation) but also sources of uncertainty and to what extent consumer reviews help resolve uncertainty. The proposed measures have two advantages over prior methods: (1) unlike prior categorization schemes that classified goods as either search or experience goods, our measure is continuous, allowing us to rank-order the degree of search versus experience and horizontal versus vertical differentiation among products or categories. (2) Our approach is easier to implement than prior methods, because it relies solely on consumer ratings information (as opposed to expert judgment) and can be employed at multiple levels (attributes, products, or product categories). We illustrate empirical applications of our proposed measures using product rating data from Amazon.com. Our data-driven measures reveal the relative importance of fit in driving product utility and the importance of search for determining fit for each product category at Amazon. Our results also show that, while ratings based on verified purchasers are informative of objective product values, the current Amazon review system appears to have limited ability to resolve fit uncertainty. Our method and findings could facilitate further research on product review systems and enable quantitative measurement of product positioning to support marketing strategy for retailers and manufacturers, covering an expanded group of products. Collapse

Topics: experience good horizontal differentiation product differentiation online review marketing management

Methods: longitudinal research Amazon review descriptive statistic product review time series analysis

An Enhanced Approach to Map Domain-Specific Words in Cross-Domain Sentiment Analysis

2021 | Information Systems Frontiers | Citations: 0

Authors: Geethapriya, A.; Valli, S.

Abstract: Domain adaptation in sentiment analysis is one of the areas where a classifier t ... Expand

Abstract: Domain adaptation in sentiment analysis is one of the areas where a classifier trained in one domain often classifies sentiments poorly when applied to another domain due to domain-specific words. Extracting features and their relevant opinion words from different domain sources and mapping them to the target domains are herculean tasks as far as domain adaptation is concerned. In this paper, the feature extraction technique is refined by which the mapping task is enhanced. The feature extraction technique uses both the syntactic and semantic properties of the features for extracting similar words. The features are further refined by merging synonyms and by replacing negative polarity terms with the appropriate antonyms. This refinement in the feature selection improves the mapping functionality of the domain adaptation and also exploits the relationship between domain-specific words and domain-independent words from different domains. Collapse

Topics: DVD enterprise architecture knowledge representation online review website

Methods: computational algorithm sentiment analysis experiment literature study product review

The Impact of Animated Banner Ads on Online Consumers: A Feature-Level Analysis Using Eye Tracking

2021 | Journal of the Association for Information Systems | Citations: 0

Authors: Hong, Weiyin; Cheung, Muller; Thong, James

Abstract: Despite the popular use of animated banner ads on websites, extant research on t ... Expand

Abstract: Despite the popular use of animated banner ads on websites, extant research on the effects of web animation has generated mixed results. We argue that it is critical to identify feature-level animation characteristics and examine their individual and combined effects on capturing online consumers’ attention across different task conditions. We identify three key animation features (i.e., motion, lagging, and looming) based on three attention theories and investigate their effects on online consumers’ attention and recall across browsing and searching tasks in three laboratory experiments using an eye tracking machine. Experiment 1 found that both motion and looming (animation features) are effective in attracting online consumers’ attention to animated ads when they are performing a browsing task. However, combining a salient feature (e.g., motion) with another salient feature (e.g., looming) does not improve the original attention attraction effect, suggesting a “banner saturation” effect. Further, we found that online consumers’ attention positively affects their recall performance. In Experiment 2, none of the animation features or their interactions had a significant effect when the subjects were performing a searching task, indicating that task is an important boundary condition when applying attention theories. Experiment 3 replicated Experiment 1 in a more realistic context and produced similar results. We conclude the paper by discussing theoretical and practical implications as well as avenues for future research. Collapse

Topics: website DVD web page online advertising robotic

Methods: experiment oculometry longitudinal research within subject experiment multivariate analysis of variance

Theories: cognitive attention theory cognitive theory

Manufacturer’s “1-Up” from Used Games: Insights from the Secondhand Market for Video Games

2021 | Information Systems Research | Citations: 0

Authors: Kim, Antino; Saha, Rajib L.; Khern-am-nuai, Warut

Abstract: In contrast to industries of other types of information goods, the video game in ... Expand

Abstract: In contrast to industries of other types of information goods, the video game industry still has a sizable secondhand market for games. This is particularly notable because some of the major gaming-console companies (e.g., Sony and Microsoft) actually possess the ability to annihilate the secondhand market altogether; it appears that those companies have given tacit approval to buying and selling used games. Naturally, the question is, what is the special ingredient in the gaming industry that gives a manufacturer incentive to keep a healthy secondhand market even when it has the technological means to shut it down? In this study, leveraging a game-theoretic model, we investigate the effect of gaming console on a manufacturer’s strategy in the presence of a secondhand market for games. We find that when the manufacturer offers a valuable console that provides utilities in addition to playing games, the secondhand market increases the manufacturer’s profit, and that is not at the cost of consumers; the consumers—as well as the society as a whole—also benefit from the secondhand market. This is in stark contrast with settings where there are no consoles involved or the consoles do not offer any intrinsic value; in such settings, the manufacturer would opt to shut down the secondhand market. In the case with a valuable console, however, the increasing appeal of the secondhand market to consumers may improve the manufacturer’s profit, consumer surplus, and social welfare, all at the same time. We discuss our findings along with managerial and welfare implications. Collapse

Topics: IS economics network effect price management video game consumer surplus

Methods: survey

Theories: game theory

Seller Labs: Democratizing E-merchants Competitiveness

2021 | Communications of the Association for Information Systems | Citations: 0

Authors: Rodriguez, Joaquin; Watson, Richard; Piccoli, Gabriele

Abstract: Seller Labs began as an effort to improve Amazon's third-party sellers' competi ... Expand

Abstract: Seller Labs began as an effort to improve Amazon's third-party sellers' competitiveness. The company's core offerings had evolved from a messaging service that facilitated communication between customers and sellers to an advanced suite of marketing, advertisement, and financial software tools. Since its inception, Seller Labs continually increased its customer base and reached more than 9,000 customers by 2019. As among the first and most successful software tool providers that addressed specific business problems that Amazon sellers face, Seller Labs was part of Amazon's Marketplace developer council and at the frontline of innovation. However, Seller Labs' main competitors continued to grow in size and strength both nationally and internationally, which threatened its competitive position. In order to expand its offerings outside the Amazon's Marketplace, Seller Labs acquired X-Cart, an ecommerce platform. However, many challenges lay ahead after the acquisition. How should Seller Labs continue to grow? Should the firm continue to focus on developing solutions targeted to Amazon's third-party sellers? Or should it pivot outside the Amazon Marketplace and develop an integrated e-commerce platform? Collapse

Topics: DVD advertising management