Sustaining Web 2.0 services: A survival analysis of a live crowd-casting service

Securing continuous inflows of user created content and promoting them to the potential consumers are basic yet critical tasks for many Internet businesses to succeed in Web 2.0 environments. Managers of Web 2.0 services need to quickly identify value-adding content and encourage the content contributors to keep supplying valuable content. This study surveys the previous literature to explain the lifespan of user created content and proposes a theoretical framework that considers three major stakeholders in the Web 2.0 business environments - content contributors, content consumers, and service platform providers. Based on the theoretical understanding, a model that explains the survivability of a user created content is developed and empirically tested using three months of log data collected by an Internet personal broadcasting service provider. The proposed theoretical framework provides researchers with insights into the interworking of the three major players in the novel business environments. The results of the empirical analysis suggest that content providers' commitments and positive rewards to intrinsic motivations, content consumers' acceptances and perceived popularity of available content, and the service platform provider's support for social network capabilities and popularity signaling mechanisms are important factors that Web 2.0 service providers must carefully manage in order to improve the longevity of value-adding user created content.

[1]  Efraim Turban,et al.  Groups Formation and Operations in the Web 2.0 Environment and Social Networks , 2008 .

[2]  Keith Brown,et al.  How many viewers does a cable network need? A survival analysis of cable networks , 2006 .

[3]  Brent A. Scott,et al.  The popularity contest at work: who wins, why, and what do they receive? , 2009, The Journal of applied psychology.

[4]  Paul E. Spector,et al.  Causes of employee turnover: A test of the Mobley, Griffeth, Hand, and Meglino model. , 1982 .

[5]  Rahul Telang,et al.  The Effect of Digital Sharing Technologies on Music Markets: A Survival Analysis of Albums on Ranking Charts , 2007, Manag. Sci..

[6]  Joseph F. Hair,et al.  Multivariate data analysis -6/E , 2006 .

[7]  Gregory S. Berns,et al.  Neural mechanisms of the influence of popularity on adolescent ratings of music , 2010, NeuroImage.

[8]  Allen C. Bluedorn A Unified Model of Turnover from Organizations , 1982 .

[9]  Edward L. Deci,et al.  Intrinsic Motivation and Self-Determination in Human Behavior , 1975, Perspectives in Social Psychology.

[10]  Kenneth H. Rubin,et al.  Peer Interactions, Relationships, and Groups , 2007 .

[11]  Thomas W. Lee,et al.  Voluntarily Leaving an Organization: An Empirical Investigation of Steers and Mowday's Model of Turnover , 1987 .

[12]  Izak Benbasat,et al.  E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact , 2007, MIS Q..

[13]  D.,et al.  Regression Models and Life-Tables , 2022 .

[14]  Dan Cosley,et al.  Think different: increasing online community participation using uniqueness and group dissimilarity , 2004, CHI.

[15]  Karim R. Lakhani,et al.  Why Hackers Do What They Do: Understanding Motivation and Effort in Free/Open Source Software Projects , 2003 .

[16]  M. Hoffman Is altruism part of human nature , 1981 .

[17]  E. A. Locke,et al.  Building a practically useful theory of goal setting and task motivation. A 35-year odyssey. , 2002, The American psychologist.

[18]  A. Newcomb,et al.  Children's friendship relations: A meta-analytic review. , 1995 .

[19]  Sumiko Asai,et al.  Factors Affecting Hits in Japanese Popular Music , 2008 .

[20]  H. J. Arnold,et al.  A multivariate analysis of the determinants of job turnover. , 1982 .

[21]  Roger Clarke,et al.  Web 2.0 as Syndication , 2008, J. Theor. Appl. Electron. Commer. Res..

[22]  J. Concato,et al.  Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. , 1995, Journal of clinical epidemiology.

[23]  A. Maslow A Theory of Human Motivation , 1943 .

[24]  W. Bukowski,et al.  Popularity and friendship: Issues in theory, measurement, and outcome. , 1989 .

[25]  Todd Dane Bozeman Job satisfaction. , 2007, Nursing management.

[26]  Paul E. Spector,et al.  "Causes of employee turnover: A test of the Mobley, Griffeth, Hand, and Meglino Model": Correction to Michaels and Spector. , 1983 .

[27]  Chris W. Clegg,et al.  Psychology of employee lateness, absence, and turnover: A methodological critique and an empirical study. , 1983 .

[28]  R. Cardy,et al.  Affect and appraisal accuracy: Liking as an integral dimension in evaluating performance. , 1986 .

[29]  Larry J. Williams,et al.  Antecedents and consequences of satisfaction and commitment in turnover models: A reanalysis using latent variable structural equation methods. , 1986 .

[30]  Ben Y. Zhao,et al.  Understanding user behavior in large-scale video-on-demand systems , 2006, EuroSys.

[31]  Ramesh Sharda,et al.  Movie forecast Guru: A Web-based DSS for Hollywood managers , 2007, Decis. Support Syst..

[32]  Charles A. O'Reilly,et al.  The commitment and job tenure of new employees: Some evidence of postdecisional justification. , 1981 .

[33]  Richard M. Steers,et al.  Organizational commitment, job satisfaction, and turnover among psychiatric technicians. , 1974 .

[34]  Sandra Slaughter,et al.  Understanding the Motivations, Participation, and Performance of Open Source Software Developers: A Longitudinal Study of the Apache Projects , 2006, Manag. Sci..

[35]  John R. Hollenbeck,et al.  Turnover functionality versus turnover frequency: A note on work attitudes and organizational effectiveness , 1986 .

[36]  A. Tversky,et al.  Advances in prospect theory: Cumulative representation of uncertainty , 1992 .

[37]  Allen C. Bluedorn,et al.  Precursors of employee turnover: A multiple‐sample causal analysis , 1985 .

[38]  John P. Meyer,et al.  Job satisfaction, organizational commitment, turnover intention, and turnover: Path analyses based on meta-analytic findings. , 2006 .

[39]  Tim O'Reilly,et al.  What is Web 2.0: Design Patterns and Business Models for the Next Generation of Software , 2007 .

[40]  K. Dodge,et al.  Dimensions and types of social status: A cross-age perspective. , 1982 .

[41]  Y Shoda,et al.  Reconciling processing dynamics and personality dispositions. , 1998, Annual review of psychology.

[42]  Belle M. Nixon Altruism , 1938, Encyclopedia of Social Insects.

[43]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[44]  Guido Hertel,et al.  Motivation of software developers in Open Source projects: an Internet-based survey of contributors to the Linux kernel , 2003 .

[45]  Georg von Krogh,et al.  The Promise of Research on Open Source Software , 2006, Manag. Sci..

[46]  D. Giles Survival of the hippest: life at the top of the hot 100 , 2007 .

[47]  G. Zaltman,et al.  Relationships between Providers and Users of Market Research: The Dynamics of Trust within and between Organizations , 1992 .

[48]  Jessi L. Smith,et al.  Interest and self-regulation: The relation between having to and wanting to , 2000 .

[49]  Xin Li,et al.  Using Social Psychology to Motivate Contributions to Online Communities , 2005, J. Comput. Mediat. Commun..

[50]  Alexander Hars,et al.  Working for Free? Motivations for Participating in Open-Source Projects , 2002, Int. J. Electron. Commer..

[51]  Ephraim R. McLean,et al.  Measuring information systems success: models, dimensions, measures, and interrelationships , 2008, Eur. J. Inf. Syst..

[52]  P. Allison Survival analysis using the SAS system : a practical guide , 1995 .

[53]  John P. Meyer,et al.  A three-component conceptualization of organizational commitment , 1991 .

[54]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .