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Social-Technology Fit: A Conceptual Model

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The 8th International Conference on Knowledge Management in Organizations

Part of the book series: Springer Proceedings in Complexity ((SPCOM))

Abstract

Literature has paid limited attention to the explanation model of social networking performance. It is argued that a healthy social networking should have a fitting structure among the technology characteristics (e.g., communication and cooperation), social characteristics (e.g., demands of privacy and trust), and individual characteristics (e.g., the tendency of self-realization) to develop its social values in a stable manner. In consequence, this study proposes a conceptual explanation model for social networking performance, which is called Social-Technology Fit Model (STFM). The STFM is based on the theories of technology-performance model and technology-task fit model. The STFM with theoretical arguments and instrument for variables is presented in this paper.

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References

  1. Allen B (1990) Information as an economic commodity. Am Econ Rev 80(2):268–273

    Google Scholar 

  2. Bandura A (1986) Social foundations of thought and action: a social cognitive theory. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  3. Bertot JC, Jaeger PT, Hansen D (2012) The impact of polices on government social media usage: issues, challenges, and recommendations. Gov Inf Q 29(1):30–40

    Article  Google Scholar 

  4. Carpenter JM, Green MC, LaFlam J (2011) People or profiles: individual differences in online social networking use. Pers Individ Differ 50(5):538–541

    Article  Google Scholar 

  5. Castelfranchi C (2001) Theory of social functions: challenges for computational social science and multi-agent learning. Cogn Syst Res 2(1):5–38

    Article  Google Scholar 

  6. Chen JV, Ross WH, Huang SF (2008) Privacy, trust, and justice considerations for location-based mobile telecommunication services. Info 10(4):30–45

    Article  Google Scholar 

  7. Csikszentmihalyi M, Csikszentmihalyi IS (1988) Optimal experience: psychological studies of flow in consciousness. Cambridge University Press, Cambridge

    Book  Google Scholar 

  8. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q 13(3):319–340

    Article  Google Scholar 

  9. Delone WH, McLean ER (1992) Informaiton system success: the quest for the dependent variable. Inf Sys Res 3(1):60–95

    Article  Google Scholar 

  10. Dennis AR, Wixom BH, Vandenberg RJ (2001) Understanding fit and appropriation effects in group support systems via meta-analysis. MIS Q 25(2):167–193

    Article  Google Scholar 

  11. Edwards JR (1991) Person-job fit: a conceptual integration, literature review, and methodological critique. In: Cooper CL, Robertson IT (eds) International review of industrial/organizational psychology. Wiley, New York, pp 283–357

    Google Scholar 

  12. Enders A, Hungenberg H, Denker H-P, Mauch S (2008) The long tail of social networking: revenue models of social networking sites. Eur Manage J 26(3):199–211

    Article  Google Scholar 

  13. Fournier S, Lee L (2009) Getting brand communities right. Harvard Bus Rev 87(4):105–111

    Google Scholar 

  14. Fuller J, Faullant R, Matzler K (2010) Triggers for virtual customer integration in the development of medical equipment—From a manufacturer and a user’s perspective. Ind Mark Manage 39(8):1376–1383

    Article  Google Scholar 

  15. Goodhue DL, Thompson RL (1995) Task-technology fit and individual performance. MIS Q 19(2):213–236

    Article  Google Scholar 

  16. Haefliger S, Monteiro E, Foray D, von Krogh G (2011) Social software and strategy. Long Range Plan 44(5–6):297–316

    Article  Google Scholar 

  17. Hahnel R (2005) Economic justice and democracy: from competition to cooperation. Routledge, New York

    Google Scholar 

  18. Hartmann RW, Manchanda P, Nair H, Bothner M, Dodds P, Godes D, Hosanagar K, Tucker C (2008) Modeling social interactions: identification, empirical methods and policy implications. Mark Lett 19(3–4):287–304

    Article  Google Scholar 

  19. Hoegl M, Schulze A (2005) How to support knowledge creation in new product development: an investigation of knowledge management methods. Eur Manage J 23(13):263–273

    Article  Google Scholar 

  20. Hoffman DL, Novak TP (1996) Marketing in hypermedia computer-mediated environments: conceptual foundations. J Mark 60:50–68

    Article  Google Scholar 

  21. Hogel M, Beisheim O (2005) How to support knowledge creation in new product development: an investigation of knowledge management methods. Eur Manage J 23:263–273

    Article  Google Scholar 

  22. Hsu HY, Tsou HT (2011) Understanding customer experiences in online blog environments. Int J Inf Manage 31:510–523

    Article  Google Scholar 

  23. Jan UA, Contreras V (2011) Technology acceptance model for the use of information technology in universities. Comput Hum Behav 27:845–851

    Article  Google Scholar 

  24. Junglas I, Abraham C, Watson RT (2008) Task-technology fit for mobile locatable information systems. Decis Support Syst 45:1046–1057

    Article  Google Scholar 

  25. Junglas IA, Watson RT (2008) Location-based services. Commun ACM 51(3):65–69

    Article  Google Scholar 

  26. Keng CJ, Ting HY (2009) The acceptance of blogs: using a customer experiential value perspective. Internet Res 19(5):479–495

    Article  Google Scholar 

  27. Kim SK, Trimi S (2007) IT for KM in the management consulting industry. J Knowl Manage 11(3):145–155

    Article  Google Scholar 

  28. Koufaris M (2002) Applying the technology acceptance model and flow theory to online consumer behavior. Inf Syst Res 13(2):205–223

    Article  Google Scholar 

  29. Kristof AL (1996) Person-organization fit: an integrative review of its conceptualizations, measurement, and implications. Pers Psychol 49:1–49

    Article  Google Scholar 

  30. Kwon O, Choi K, Kim M (2007) User acceptance of context-aware services: self-efficacy, user innovativeness and perceived sensitivity on contextual pressure. Behav Inf Technol 26(6):483–498

    Article  Google Scholar 

  31. Mainela T (2007) Types and functions of social relationships in the organizing of an international joint venture. Ind Mark Manage 36(1):87–98

    Article  Google Scholar 

  32. McAfee A (2006) Mastering the three worlds of information technology. Harvard Bus Rev 84:132–144

    Google Scholar 

  33. Paul JA, Baker HM, Cochran JD (2012) Effect of online social networking on student academic performance. Comput Hum Behav 28(6):2117–2127

    Article  Google Scholar 

  34. Shin YY (2004) A Person-environment fit model for virtual organizations. J Manage 30(5):725–743

    Google Scholar 

  35. Smith CD, Mentzer JT (2010) Forecasting task-technology fit: the influence of individuals, systems and procedures on forecast performance. Int J Forecast 26:144–161

    Article  Google Scholar 

  36. Tsoukas, H. (2003), Do we really understand tacit knowledge?. In: Easterby-Smith, Lyles (eds), The blackwell handbook of organizational learning and knowledge management, Blackwell Publishing, Cambridge, pp. 411–427

    Google Scholar 

  37. Vezzetti E, Moos S, Kretli S (2011) A product lifecycle management methodology for supporting knowledge reuse in the consumer packaged goods domain. Comput Aided Des 43:1902–1911

    Article  Google Scholar 

  38. Wasko MM, Faraj S (2005) Why should i share? examining social capital and knowledge contribution in electronic networks of practices. MIS Q 29(1):35–57

    Google Scholar 

  39. Webster J, Ahuja JS (2006) Enhancing the design of web navigation systems: the influence of user disorientation on engagement and performance”. MIS Q 30:661–678

    Google Scholar 

  40. Werbel JD, Gilliland SW (1999) Person-environment fit in the selection process. Res Pers Hum Resour Manag 17:209–243

    Google Scholar 

  41. Wu CH, Kao SC, Shih LH (2010) Assessing the suitability of process and information technology in supporting tacit knowledge transfer. Behav Inf Technol 29(5):513–525

    Article  Google Scholar 

  42. Wu CH, Lee TZ, Kao SC, Lee MM (2010) Examining participation willingness of virtual community using structure equation model. J Stat Manag Syst 13(5):899–920

    Article  Google Scholar 

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Correspondence to Chien-Hsing Wu .

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Liao, HY., Wu, CH., Sundiman, D., Peng, F. (2014). Social-Technology Fit: A Conceptual Model. In: Uden, L., Wang, L., Corchado Rodríguez, J., Yang, HC., Ting, IH. (eds) The 8th International Conference on Knowledge Management in Organizations. Springer Proceedings in Complexity. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7287-8_30

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  • DOI: https://doi.org/10.1007/978-94-007-7287-8_30

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-7286-1

  • Online ISBN: 978-94-007-7287-8

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