A quick bite and instant gratification: A simulated Yelp experiment on consumer review information foraging behavior

Abstract In the post-industrial information-based economy, classical information economics models are often used to explain consumer choices and decision-making behaviors. However, many heuristic consumer behaviors are better explained by behavioral ecology models, such as information foraging. In this study, we examined how consumers explore task-oriented review information in an online environment where they may or may not have prior visiting experience. Our findings indicate that consumers overestimate their expected search effort before using a review site. Compared with consumers who had used Yelp before, those who had never used the site expect their browsing duration and review counts to be 42% and 93% higher, respectively. In addition, before making a decision, most consumers spend only five minutes or less, read five or fewer reviews, and browse seven to eight pages. This finding indicates the review information consumers choose to use within those limited-time ranges may significantly influence the restaurant choices of those foraging consumers.

[1]  Ravi Kumar,et al.  A characterization of online browsing behavior , 2010, WWW '10.

[2]  Davide Balzarotti,et al.  Extension Breakdown: Security Analysis of Browsers Extension Resources Control Policies , 2017, USENIX Security Symposium.

[3]  Chulmo Koo,et al.  An empirical examination of online restaurant reviews on Yelp.com , 2017 .

[4]  Paul A. Pavlou,et al.  The Spillover Effects of User-Generated Online Product Reviews on Purchases: Evidence from Clickstream Data , 2016, ICIS.

[5]  Makoto Nakayama,et al.  Is culture of origin associated with more expressions? An analysis of Yelp reviews on Japanese restaurants , 2018, Tourism Management.

[6]  Makoto Nakayama,et al.  Cross-Cultural Examination on Content Bias and Helpfulness of Online Reviews: Sentiment Balance at the Aspect Level for a Subjective Good , 2019, HICSS.

[7]  Amanda Spink,et al.  Determining the informational, navigational, and transactional intent of Web queries , 2008, Inf. Process. Manag..

[8]  Gregoris Mentzas,et al.  Leveraging exploratory search with personality traits and interactional context , 2018, Inf. Process. Manag..

[9]  G. Menon,et al.  Health Risk Perceptions and Consumer Psychology , 2006 .

[10]  Benjamin Livshits,et al.  Verified Security for Browser Extensions , 2011, 2011 IEEE Symposium on Security and Privacy.

[11]  Ramesh K. Sitaraman,et al.  Video Stream Quality Impacts Viewer Behavior: Inferring Causality Using Quasi-Experimental Designs , 2013, IEEE/ACM Transactions on Networking.

[12]  Peter Pirolli,et al.  An elementary social information foraging model , 2009, CHI.

[13]  D. Funder,et al.  Delay of gratification: Some longitudinal personality correlates. , 1983 .

[14]  John Dimmick,et al.  Revisiting Interpersonal Media Competition , 2008, Commun. Res..

[15]  Peter H. Bloch,et al.  Shopping Without Purchase: an Investigation of Consumer Browsing Behavior , 1983 .

[16]  Catarina Sismeiro,et al.  A Model of Web Site Browsing Behavior Estimated on Clickstream Data , 2003 .

[17]  Kurt A. Carlson,et al.  Unrealistically Optimistic Consumers: A Selective Hypothesis Testing Account for Optimism in Predictions of Future Behavior , 2009 .

[18]  Thomas S. Tullis,et al.  Online Viewing and Aesthetic Preferences of Generation Y and the Baby Boom Generation: Testing User Web Site Experience Through Eye Tracking , 2011, Int. J. Electron. Commer..

[19]  Stuart K. Card,et al.  Information foraging in information access environments , 1995, CHI '95.

[20]  Metin Ersoy,et al.  Usability and functionality factors of the social network site application users from the perspective of uses and gratification theory , 2015, Quality & Quantity.

[21]  Ryen W. White,et al.  WWW 2007 / Track: Browsers and User Interfaces Session: Personalization Investigating Behavioral Variability in Web Search , 2022 .

[22]  Choon-Ling Sia,et al.  Is This Review Believable? A Study of Factors Affecting the Credibility of Online Consumer Reviews from an ELM Perspective , 2012, J. Assoc. Inf. Syst..

[23]  J. Najman,et al.  The Generalizability of Deferment of Gratification , 1986 .

[24]  Ronaldo Menezes,et al.  Returners and Explorers Dichotomy in Web Browsing Behavior - A Human Mobility Approach , 2016, CompleNet.

[25]  Sandeep R. Chandukala,et al.  Exploring the Effects of “What” (Product) and “Where” (Website) Characteristics on Online Shopping Behavior , 2016 .

[26]  Peter Pirolli,et al.  Information Foraging , 2009, Encyclopedia of Database Systems.

[27]  Ying Zhang,et al.  Time series analysis of a Web search engine transaction log , 2009, Inf. Process. Manag..

[28]  Christopher J. Holden,et al.  Assessing the reliability of the M5-120 on Amazon's mechanical Turk , 2013, Comput. Hum. Behav..

[29]  Miriam J. Metzger,et al.  Credibility and trust of information in online environments: The use of cognitive heuristics , 2013 .

[30]  Chirag Shah,et al.  Evaluating user search trails in exploratory search tasks , 2017, Inf. Process. Manag..

[31]  Eda Gurel-Atay,et al.  Comparing Data Collection Alternatives: Amazon Mturk, College Students, And Secondary Data Analysis , 2013 .

[32]  Echo Huang,et al.  Use and gratification in e-consumers , 2008, Internet Res..

[33]  Jordi Grau-Moya,et al.  Bounded Rationality, Abstraction, and Hierarchical Decision-Making: An Information-Theoretic Optimality Principle , 2015, Front. Robot. AI.

[34]  Olivier Toubia,et al.  A Bounded Rationality Model of Information Search and Choice in Preference Measurement , 2014 .

[35]  C. Zhong,et al.  You Are How You Eat , 2010, Psychological science.

[36]  D. Ridder,et al.  Unresolved questions in nudging research: Putting the psychology back in nudging , 2017 .

[37]  David Mendonça,et al.  Temporal modeling of group information foraging: An application to emergency response , 2013, Inf. Process. Manag..

[38]  Makoto Nakayama,et al.  Exploratory Study on Anchoring: Fake Vote Counts in Consumer Reviews Affect Judgments of Information Quality , 2017, J. Theor. Appl. Electron. Commer. Res..

[39]  I-Chin Wu,et al.  Sequential analysis and clustering to investigate users' online shopping behaviors based on need-states , 2020, Inf. Process. Manag..

[40]  Atish P. Sinha,et al.  Role of navigational ability in website visit duration , 2019, European Journal of Marketing.

[41]  Gerd Gigerenzer,et al.  Heuristic decision making. , 2011, Annual review of psychology.

[42]  Amit Bhatnagar,et al.  An Analysis of Frequency and Duration of Search on the Internet , 2004 .

[43]  Kylie Jarrett,et al.  Google and the Culture of Search , 2012 .

[44]  Meredith Ringel Morris,et al.  What do you see when you're surfing?: using eye tracking to predict salient regions of web pages , 2009, CHI.

[45]  Chulmo Koo,et al.  Why People Share Information in Social Network Sites? Integrating with Uses and Gratification and Social Identity Theories , 2012, ACIIDS.

[46]  Djoerd Hiemstra,et al.  Analysis of Search and Browsing Behavior of Young Users on the Web , 2014, TWEB.

[47]  JungKun Park,et al.  Consumers’ travel website transferring behaviour: analysis using clickstream data-time, frequency, and spending , 2009 .

[48]  John Raacke,et al.  MySpace and Facebook: Applying the Uses and Gratifications Theory to Exploring Friend-Networking Sites , 2008, Cyberpsychology Behav. Soc. Netw..

[49]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[50]  Dong-Hee Shin,et al.  Understanding e-book users: Uses and gratification expectancy model , 2011, New Media Soc..

[51]  Peter Pirolli,et al.  Rational Analyses of Information Foraging on the Web , 2005, Cogn. Sci..

[52]  Makoto Nakayama,et al.  Exploratory Study on the Stability of Consumer Rationality in Judging Online Reviews , 2017, J. Electron. Commer. Organ..

[53]  P. Pirolli Information Foraging Theory: Adaptive Interaction with Information , 2007 .

[54]  Sha Yang,et al.  Unrealistic optimism in consumer credit card adoption , 2007 .

[55]  Mary C. Dyson,et al.  The influence of reading speed and line length on the effectiveness of reading from screen , 2001, Int. J. Hum. Comput. Stud..

[56]  Wendy W. Moe,et al.  Capturing evolving visit behavior in clickstream data , 2004 .

[57]  Jinglu Tan,et al.  Identifying Worldwide Interests in Organic Foods by Google Search Engine Data , 2019, IEEE Access.

[58]  D. Valentin,et al.  Craft vs. industrial: Habits, attitudes and motivations towards beer consumption in Mexico , 2016, Appetite.

[59]  Anabel Quan-Haase,et al.  Uses and Gratifications of Social Media: A Comparison of Facebook and Instant Messaging , 2010 .

[60]  P. Pinson,et al.  Accommodating Bounded Rationality in Pricing Demand Response , 2019, 2019 IEEE Milan PowerTech.

[61]  D. Gursoy A critical review of determinants of information search behavior and utilization of online reviews in decision making process (invited paper for ‘luminaries’ special issue of International Journal of Hospitality Management) , 2019, International Journal of Hospitality Management.

[62]  Jeffrey C. Fuhrer,et al.  Does Consumer Sentiment Forecast Household Spending? If So, Why? , 1994 .

[63]  Yun Wan,et al.  The Matthew Effect in social commerce , 2015, Electron. Mark..

[64]  Cornelius Puschmann,et al.  Explaining Online News Engagement Based on Browsing Behavior: Creatures of Habit? , 2019, Social Science Computer Review.

[65]  Miriam J. Metzger,et al.  Social and Heuristic Approaches to Credibility Evaluation Online , 2010 .

[66]  E. Katz,et al.  Uses and Gratifications Research , 2019, The International Encyclopedia of Journalism Studies.

[67]  Ying-Yao Cheng,et al.  Escaping the impulse to immediate gratification: the prospect concept promotes a future-oriented mindset, prompting an inclination towards delayed gratification. , 2012, British journal of psychology.

[68]  Jan Kemper,et al.  Generating Consumer Insights from Big Data Clickstream Information and the Link with Transaction-Related Shopping Behavior , 2017, ECIS.

[69]  Chang Liu,et al.  The effects of perceived chronic pressure and time constraint on information search behaviors and experience , 2019, Inf. Process. Manag..

[70]  Gokul Bhandari,et al.  How Loud is the Scream of a Clickstream? Insights from Big Data Analysis , 2018, AMCIS.

[71]  I. Tanta,et al.  Uses and Gratification Theory – Why Adolescents Use Facebook? , 2014 .

[72]  Daniel L. Sherrell,et al.  Extending the concept of shopping: An investigation of browsing activity , 1989 .

[73]  Chuan-Hoo Tan,et al.  Sequentiality of Product Review Information Provision: An Information Foraging Perspective , 2017, MIS Q..

[74]  Tayfun Keskin,et al.  Exploring the trade-off between immediate gratification and delayed network externalities in the consumption of information goods , 2008, Eur. J. Oper. Res..