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Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application: Evidence from Econometric Models and Machine-Learning Instruments

2022 | Management Information Systems Quarterly | Citations: 0
Authors: Adamopoulos, Panagiotis; Ghose, Anindya; Tuzhilin, Alexander

Abstract: In this paper, we examine the effectiveness of various recommendation strategies ... Expand

Abstract: In this paper, we examine the effectiveness of various recommendation strategies in the mobile channel and their impact on consumers’ utility and demand levels for individual products. We find significant differences in effectiveness among various recommendation strategies. Interestingly, recommendation strategies that directly embed social proofs for the recommended alternatives outperform other recommendations. In addition, recommendation strategies combining social proofs with higher levels of induced awareness due to the prescribed temporal diversity have an even stronger effect on the mobile channel. We also examine the heterogeneity of the demand effect across items, users, and contextual settings, further verifying empirically the aforementioned information and persuasion mechanisms and generating rich insights. We also facilitate the estimation of causal effects in the presence of endogeneity using machine-learning methods. Specifically, we develop novel econometric instruments that capture product differentiation (isolation) based on deeplearning models of user-generated reviews. Our empirical findings extend the current knowledge regarding the heterogeneous impact of recommender systems, reconcile contradictory prior results in the related literature, and have significant business implications. Collapse

Semantic filters: consumer search theory

Topics: mobile system broadband cellular network mobile channel online review mobile application

Methods: econometric modeling instrumental variables estimation machine learning robustness check computational algorithm

Theories: symbolic interaction theory social network theory cognitive theory consumer search theory trust theory
The Effects of Web Personalization on User Attitude and Behavior: An Integration of the Elaboration Likelihood Model and Consumer Search Theory

2014 | Management Information Systems Quarterly | Citations: 0
Authors: Shuk Ying Ho; Bodoff, David

Abstract: Web personalization can achieve two business goals: increased advertising revenu ... Expand

Abstract: Web personalization can achieve two business goals: increased advertising revenue and increased sales revenue. The realization of the two goals is related to two kinds of user behavior: item sampling and item selection. Prior research does not provide a model of attitude formation toward a personalization agent nor of how attitudes relate to these two behaviors. This limits our understanding of how web personalization can be managed to increase advertising revenues and/or sales revenues. To fill this gap, the current research develops and tests a theoretical model of user attitudes and behaviors toward a personalization agent. The model is based on an integration of two theories: the elaboration likelihood model (ELM) and consumer search theory (CST). In the integrated model, a user's attitude toward a personalization agent is influenced by both the number of items he/she has sampled so far (from CST) and the degree to which he/she cognitively processes each one (from ELM). In turn, attitude is modeled to influence both behaviors-that is, item selection and any further item sampling. We conducted a lab study and a field study to test six hypotheses. This research extends the theory on web personalization by providing a more complete picture of how sampling and processing of personalized recommendations influence a user's attitude and behavior toward the personalization agent. For online merchants, this research highlights the trade-off between item sampling and item selection and provides practical guidance on how to steer users toward the attitudes and behaviors that will realize their business goals. Collapse

Semantic filters: consumer search theory

Topics: usability personalization website perceived usefulness Near Field Communication

Methods: laboratory experiment field study survey path analysis chi squared test

Theories: technology acceptance model consumer search theory information systems theory elaboration likelihood model
THE EFFECTS OF TIME AND NUMBER OF PERSONALIZED ITEMS ON USERS´ AMOUNT OF SAMPLING

2014 | European Conference On Information Systems | Citations: 0
Authors: Bodoff, David; Ho, Shuk Ying

Abstract: With advances in personalization technologies, websites are increasingly able t ... Expand

Abstract: With advances in personalization technologies, websites are increasingly able to personalize web content and provide users with a unique experience. This research examines the effects of personalization on the amount of sampling of (1) personalized and (2) stock items. Two theories, Elaboration Likelihood Model (ELM) and Consumer Search Theory (CST), provide the basis for four hypotheses about these extended indicators. The two theories differ in theoretical level of abstraction. ELM models a user's response to an appealing item, whereas CST models a user's overall search strategy. They complement each other, but sometimes lead to competing hypotheses. This research conducts an online field experiment to examine these predictions and provide empirical evidence to validate the proposed hypotheses. Theoretically, our research extends personalization literature by providing a more complete picture of the effects of personalization on users' sampling behavior. Practically, our research reveals how effective personalization influences various users' sampling in return visits. This provides insights for online merchants who plan to invest in personalization technologies. Collapse

Semantic filters: consumer search theory

Topics: usability personalization website internet technology user behavior

Methods: longitudinal research data modeling parametric test survey experiment

Theories: consumer search theory elaboration likelihood model psychological theory
THE IMPACT OF SMARTPHONES, BARCODE SCANNING, AND LOCATION-BASED SERVICES ON CONSUMERS’ SEARCH BEHAVIOR

2013 | International Conference on Information Systems | Citations: 0
Authors: Daurer, Stephan; Molitor, Dominik; Spann, Martin; Manchanda, Puneet

Abstract: With their barcode scanning capabilities, positioning technologies and internet ... Expand

Abstract: With their barcode scanning capabilities, positioning technologies and internet access smartphones converge online and offline world in consumers’ search. Combining context-specific information with consumer search data allows us to measure how consumers search on the mobile Internet. Our research objective is to investigate the drivers of consumer search on the mobile Internet. We use a novel and unique behavioral data set from a mobile location-based smartphone product information (i.e., barcode scanning) application. Our data comprises more than 200 million observations at the individual consumer level. Our preliminary results provide insights in consumer search behavior using smartphones. We show that information needs differ by the type of products that are scanned. We expect that our findings will give marketers a better understanding of consumers’ search behavior and thus help companies to proactively target them with marketing programs in order to acquire “search prone consumers” and to better retain existing consumers. Collapse

Semantic filters: consumer search theory

Topics: mobile application smartphone mobile system social media consumer behavior

Methods: descriptive statistic digital trace data conjoint analysis instrumental variables estimation chi squared test

Theories: economic search theory consumer search theory
Competing "Creatively" in Sponsored Search Markets: The Effect of Rank, Differentiation Strategy, and Competition on Performance
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2011 | Information Systems Research | Citations: 0
Authors: Animesh, Animesh; Viswanathan, Siva; Agarwal, Ritu

Abstract: Although efficiency-enhancing features of online markets have been well studied, ... Expand

Abstract: Although efficiency-enhancing features of online markets have been well studied, much less is known about firms' differentiation strategies in these competitive markets or the outcomes of such differentiation. This study examines competition among firms in online sponsored search markets—one of the fastest growing and most competitive of online markets. We develop and test a model that predicts the clickthrough rate (CTR) of a seller's listing in a sponsored search setting. Drawing on consumer search theory and competitive positioning strategies, we theorize that CTR is jointly driven by a seller's positioning strategy as reflected by the unique selling proposition (USP) in its "ad creative," by its rank in a sponsored search listing, and by the nature of competition around the focal firm's listing. We use data from a field experiment conducted by a leading firm in the mortgage industry where the firm varied its rank and USP dynamically. Results suggest that sponsored search listings can act as effective customer segmentation mechanisms, consistent with a model of consumer search in directional markets. We further find that the effect on CTR of a firm's positioning strategy and its rank in a listing is strongly moderated by its ability to differentiate itself from adjacent rivals. We discuss the implications of our findings for sellers' strategies in sponsored search markets and for extending the understanding of consumer search behavior in directional markets. Collapse

Semantic filters: consumer search theory

Topics: search engine search engine marketing electronic commerce electronic market consumer behavior

Methods: regression analysis method field experiment statistical hypothesis test theory development descriptive statistic

Theories: consumer search theory
Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior
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2011 | Information Systems Research | Citations: 86
Authors: Shuk Ying Ho; Bodoff, David; Kar Yan Tam

Abstract: Web personalization allows online merchants to customize Web content to serve th ... Expand

Abstract: Web personalization allows online merchants to customize Web content to serve the needs of individual customers. Using data mining and clickstream analysis techniques, merchants can now adapt website content in real time to capture the current preferences of online customers. Though the ability to offer adaptive content in real time opens up new business opportunities for online merchants, it also raises questions of timing. One question is when to present personalized content to consumers. Consumers prefer early presentation that eases their selection process, whereas adaptive systems can make better personalized content if they are allowed to collect more consumers' clicks over time. A review of personalization research confirms that little work has been done on these timing issues in the context of personalized services. The current study aims to fill that gap. Drawing on consumer search theory, we develop hypotheses about consumer responses to differences in presentation timing and recommendation type and the interaction between the two. The findings establish that quality improves over the course of an online session but the probability of considering and accepting a given recommendation diminishes over the course of the session. These effects are also shown to interact with consumer expertise, providing insights on the interplay between the different design elements of a personalization strategy. Collapse

Semantic filters: consumer search theory

Topics: usability personalization electronic commerce user satisfaction music download

Methods: laboratory experiment field experiment experiment survey field study

Theories: consumer search theory

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Found 6 articles

Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application: Evidence from Econometric Models and Machine-Learning Instruments

The Effects of Web Personalization on User Attitude and Behavior: An Integration of the Elaboration Likelihood Model and Consumer Search Theory

THE EFFECTS OF TIME AND NUMBER OF PERSONALIZED ITEMS ON USERS´ AMOUNT OF SAMPLING

THE IMPACT OF SMARTPHONES, BARCODE SCANNING, AND LOCATION-BASED SERVICES ON CONSUMERS’ SEARCH BEHAVIOR

Competing "Creatively" in Sponsored Search Markets: The Effect of Rank, Differentiation Strategy, and Competition on Performance

Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior