IS

Ma, Xiao

Topic Weight Topic Terms
0.408 online users active paper using increasingly informational user data internet overall little various understanding empirical
0.347 reviews product online review products wom consumers consumer ratings sales word-of-mouth impact reviewers word using
0.262 behavior behaviors behavioral study individuals affect model outcomes psychological individual responses negative influence explain hypotheses
0.159 characteristics experience systems study prior effective complexity deal reveals influenced companies type analyze having basis
0.154 model research data results study using theoretical influence findings theory support implications test collected tested
0.146 research study influence effects literature theoretical use understanding theory using impact behavior insights examine influences
0.134 participation activities different roles projects examined outcomes level benefits conditions key importance isd suggest situations
0.116 community communities online members participants wikipedia social member knowledge content discussion collaboration attachment communication law
0.112 structural pls measurement modeling equation research formative squares partial using indicators constructs construct statistical models
0.101 use support information effective behaviors work usage examine extent users expertise uses longitudinal focus routine

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Kim, Sung S. 3 Khansa, Lara 2 Deng, Yun 1 Kim, Seung Hyun 1
Liginlal, Divakaran 1
active participation 1 consumer review 1 decision making under uncertainty 1 dynamic panel data analysis 1
elaboration likelihood model 1 goal-oriented action 1 hierarchical modeling 1 hierarchical analysis 1
habit incentives 1 MCMC simulation 1 multilevel analysis 1 online user behavior 1
online gambling 1 online community 1 online question-and-answer community 1 panel data 1
reputation systems 1 repeated behavior 1 simultaneous equations model 1 system-generated data 1

Articles (3)

Understanding Members Active Participation in Online Question-and-Answer Communities: A Theory and Empirical Analysis (Journal of Management Information Systems, 2015)
Authors: Abstract:
    Community-based question-and-answer (Q&A) websites have become increasingly popular in recent years as an alternative to general-purpose Web search engines for open-ended complex questions. Despite their unique contextual characteristics, only a handful of Q&A websites have been successful in sustaining members' active participation that, unlike lurking, consists of not only posting questions but also answering others' inquiries. Because the specific design of the information technology artifacts on Q&A websites can influence their level of success, studying leading Q&A communities such as Yahoo! Answers (YA) provides insights into more effective design mechanisms. We tested a goal-oriented action framework using data from 2,920 YA users, and found that active online participation is largely driven by artifacts (e.g., incentives), membership (e.g., levels of membership and tenure), and habit (e.g., past behavior). This study contributes to the information systems literature by showing that active participation can be understood as the setting, pursuit, and automatic activation of goals. > >
Online Gambling Behavior: The Impacts of Cumulative Outcomes, Recent Outcomes, and Prior Use (Information Systems Research, 2014)
Authors: Abstract:
    The objective of this work is to examine various psychological forces underlying the behavior of people’s online gambling, an increasingly popular form of entertainment in the gaming industry. Drawing on extant theories, we first developed a model of how cumulative outcomes, recent outcomes, and prior use affect online gambling behavior differently. We empirically tested the model using longitudinal panel data collected over eight months from 22,304 actual users of a gambling website. The results of a multilevel panel data analysis strongly supported our hypotheses. First, consistent with gambling theory, individuals' online gambling was found to increase with any increase in a cumulative net gain or cumulative net loss. Second, as the availability heuristic prescribes, a recent loss reduced online gambling, whereas a recent gain increased it. Third, consistent with the literature on repeated behavior, regular use and extended use moderated the relationship between current and subsequent gambling. Taken together, the present study clarifies how people react differently to immediate and cumulative outcomes and also how regular use and extended use facilitate routine behavior in the context of online gambling. In general, our findings suggest that the three perspectives, i.e., gambling theory, the availability heuristic, and repeated behavior, should be taken into account to understand online gambling, which is in essence a series of risk-taking attempts with the potential of eventually becoming routine behavior. This study is expected to offer valuable insights into other types of online games that could engage people in risking real or cyber money and, at the same time, could be easily enmeshed with everyday life (e.g., fantasy sports, online virtual worlds).
Impact of Prior Reviews on the Subsequent Review Process in Reputation Systems. (Journal of Management Information Systems, 2013)
Authors: Abstract:
    Reputation systems have been recognized as successful online review communities and word-of-mouth channels. Our study draws upon the elaboration likelihood model to analyze the extent that the characteristics of reviewers and their early reviews reduce or worsen the bias of subsequent online reviews. Investigating the sources of this bias and ways to mitigate it is of considerable importance given the previously established significant impact of online reviews on consumers' purchasing decisions and on businesses' profitability. Based on a panel data set of 744 individual consumers collected from Yelp, we used the Markov chain Monte Carlo simulation method to develop and empirically test a system of simultaneous models of consumer review behavior. Our results reveal that male reviewers or those who lack experience, geographic mobility, or social connectedness are more prone to being influenced by prior reviews. We also found that longer and more frequent reviews can reduce online reviews' biases. This paper is among the first to examine the moderating effects of reviewer and review characteristics on the relationship between prior reviews and subsequent reviews. Practically, this study offers businesses effective customer relationship management strategies to improve their reputations and expand their clientele.