Skip to main content
SpringerLink
Log in

The Impact Rules of Recommendation Sources for Adoption Intention of Micro-blog Based on DRSA with Flow Network Graph

  • Chapter
Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 43))

  • 983 Accesses

Abstract

A micro-blog is a social media tool that allows users to write short text messages for public and private networks. This research focuses specifically on the micro-blog on Facebook. The main purposes of this study are to explore and compare what recommendation sources influence the intention to use micro-blogs and to combine the personal characteristics/attributes of gender, daily internet hour usage and past use experience to infer the usage of micro-blogs decision rules using a dominance-based rough-set approach (DRSA) with flow network graph. Data for this study were collected from 382 users and potential users. The analysis is grounded in the taxonomy of induction-related activities using a DRSA with flow network graph to infer the usage of micro-blogs decision rules. Finally, the study of the nature of micro-blog reflects essential practical and academic value in real world.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ajzen, I.: Attitudes, Personality, and Behavior. Dorsey Press, Chicago (1988)

    Google Scholar 

  2. Ajzen, I., Fishbein, M.: Understanding Attitudes and Predicting Social Behavior. Prentice Hall, Englewood Cliffs (1980)

    Google Scholar 

  3. Akhter, S.H.: Digital divide and purchase intention: Why demographic psychology matters. Journal of Economic Psychology 24(3), 321–327 (2003)

    Article  Google Scholar 

  4. Andreasen, A.R.: Attitudes and customer behavior: A decision model. In: Kassarjian, H.H., Robertson, T.S. (eds.) Perspectives in Consumer Behavior, pp. 498–510. Scott, Foresman and Company, Glenview (1968)

    Google Scholar 

  5. Awareness: Enterprise Social Media: Trends and Best Practices in Adopting Web 2.0 (2008), http://www.awarenessnetworks.com/resources/resources-whitepapers.asp

  6. Bagozzi, R.P., Baumgartner, H., Yi, Y.: State versus action orientation and the theory of reasoned action: An application to coupon usage. Journal of Consumer Research 18(4), 505–518 (1992)

    Article  Google Scholar 

  7. Błaszczyński, J., Greco, S., Słowiński, R.: Multi-criteria classification - A new scheme for application of dominance-based decision rules. European Journal of Operational Research 181(3), 1030–1044 (2007)

    Article  MATH  Google Scholar 

  8. Carchiolo, V., Malgeri, M., Mangioni, G., Nicosia, V.: Emerging structures of P2P networks induced by social relationships. Computer Communications 31(3), 620–628 (2008)

    Article  Google Scholar 

  9. Chan, C.-C., Tzeng, G.-H.: Dominance-Based Rough Sets Using Indexed Blocks as Granules. In: Wang, G., Li, T., Grzymala-Busse, J.W., Miao, D., Skowron, A., Yao, Y. (eds.) RSKT 2008. LNCS (LNAI), vol. 5009, pp. 244–251. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  10. Chau, P.Y.K., Hu, P.J.H.: Investigating healthcare professionals’ decisions to accept telemedicine technology: An empirical test of competing theories. Information & Management 39(4), 297–311 (2002)

    Article  Google Scholar 

  11. Cheong, M., Lee, V.: Integrating Web-based intelligence retrieval and decision-making from the Twitter trends knowledge base. In: Proceeding of the 2nd ACM Workshop on Social Web Search and Mining, pp. 1–8 (2009)

    Google Scholar 

  12. Cox, D.F.: Risk taking and information handling in consumer behavior. In: Cox, D.F. (ed.) Risk Taking and Information Handling in Consumer Behavior, pp. 604–639. Boston University Pres, Boston (1967)

    Google Scholar 

  13. Crisci, R., Kassinove, H.: Effects of perceived expertise, strength of advice, and environmental setting on parental compliance. The Journal of Social Psychology 89(2), 245–250 (1973)

    Article  Google Scholar 

  14. Crow, S.M., Fok, L.Y., Hartman, S.J., Payne, D.M.: Gender and values: What is the impact on decision making? Sex Roles 25(3-4), 255–268 (1991)

    Article  Google Scholar 

  15. Davis, F.D.: Perceived usefulness, Perceived ease of use, and user acceptance of information technology. MIS Quarterly 13(3), 319–340 (1989)

    Article  Google Scholar 

  16. Fang, S.K., Shyng, J.Y., Lee, W.S., Tzeng, G.H.: Combined data mining techniques for exploring the preference of customers between financial companies and agents based on TCA. Knowledge-Based Systems 27(1), 137–151 (2012)

    Article  Google Scholar 

  17. Ford, L.R., Fulkerson, D.R.: Flows in Networks. Princeton University Press, Princeton (1962)

    MATH  Google Scholar 

  18. Gefen, D., Straub, D.W.: Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS Quarterly 21(4), 389–400 (1997)

    Article  Google Scholar 

  19. Gilly, C.M., Graham, J.L., Wolfinbarger, M.R., Yale, L.J.: A dyadic study of interpersonal information search. Journal of the Academy of Marketing Science 2(2), 83–100 (1998)

    Article  Google Scholar 

  20. Greco, S., Matarazzo, B., Słowiński, R.: A new rough set approach to evaluation of bankruptcy risk. In: Zopounidis, C. (ed.) Operational Tools in the Management of Financial Risk, pp. 121–136. Kluwer Academic Publishers, Boston (1998)

    Chapter  Google Scholar 

  21. Greco, S., Matarazzo, B., Słowiński, R.: Rough set theory for multicriteria decision analysis. European Journal of Operation Research 129(1), 1–47 (2001)

    Article  MATH  Google Scholar 

  22. Greco, S., Matarazzo, B., Słowiński, R.: Dominance-Based Rough Set Approach as a Proper Way of Handling Graduality in Rough Set Theory. In: Peters, J.F., Skowron, A., Marek, V.W., Orłowska, E., Słowiński, R., Ziarko, W.P. (eds.) Transactions on Rough Sets VII. LNCS, vol. 4400, pp. 36–52. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  23. Günther, O., Krasnova, H., Riehle, D., Schöndienst, V.: Modeling microblogging adoption in the enterprise. In: Proceedings of the 15th Americas Conference on Information Systems, San Francisco, CA, USA (2009)

    Google Scholar 

  24. Häubl, G., Trifts, V.: Consumer decision making in online shopping environments: the effects of interactive decision aids. Marketing Science 19(1), 4–21 (2000)

    Article  Google Scholar 

  25. Hoadley, C.M., Xu, H., Lee, J.J., Rosson, M.B.: Privacy as information access and illusory control: The case of the Facebook news feed privacy outcry. Electronic Commerce Research and Applications 9(1), 50–60 (2010)

    Article  Google Scholar 

  26. Janda, S.: Does gender moderate the effect of online concerns on purchase likelihood? Journal of Internet Commerce 7(3), 339–358 (2008)

    Article  Google Scholar 

  27. Java, A., Song, X., Finin, T., Tseng, B.: Why We Twitter: An Analysis of a Microblogging Community. In: Zhang, H., Spiliopoulou, M., Mobasher, B., Giles, C.L., McCallum, A., Nasraoui, O., Srivastava, J., Yen, J. (eds.) WebKDD 2007. LNCS, vol. 5439, pp. 118–138. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  28. Kim, S.S., Malhotra, N.K., Narasimhan, S.: Two competing perspectives on automatics use: A theoretical and empirical comparison. Information Systems Research 16(4), 418–432 (2005)

    Article  Google Scholar 

  29. Lin, C.S., Tzeng, G.H., Yang-Chieh Chin, Y.H.: Combined rough set theory and flow graph to predict customer churn in credit card accounts. Expert Systems with Applications 38(1), 8–15 (2011)

    Article  Google Scholar 

  30. Liou, J.H., Tzeng, G.H.: A dominance-based rough set approach to customer behavior in the airline market. Information Sciences 180(11), 2230–2238 (2010)

    Article  Google Scholar 

  31. Liou, J.H., Yen, L., Tzeng, G.H.: Using decision-rules to achieve mass customization of airline service. European Journal of Operation Research 205(3), 680–686 (2010)

    Article  MATH  Google Scholar 

  32. Mark, B., Munakata, T.: Rule extraction from expert heuristics: A comparative study of rough sets with neural networks and ID3. European Journal Operational Research 136(1), 212–229 (2002)

    Article  Google Scholar 

  33. Murray, K.B.: A test of services marketing theory: Consumer information acquisition activities. Journal of Marketing 55(1), 10–25 (1991)

    Article  Google Scholar 

  34. Ou Yang, Y.P., Shieh, H.M., Tzeng, G.H., Yen, L., Chan, C.C.: Combined rough sets with flow graph and formal concept analysis for business aviation decision-making. Journal of Intelligent Information Systems 36(3), 347–366 (2011)

    Article  Google Scholar 

  35. Park, D.H., Lee, J., Han, I.: The effect of on-line consumer reviews on consumer purchasing intention: The moderating role of involvement. International Journal of Electronic Commerce 11(4), 125–148 (2007)

    Article  Google Scholar 

  36. Pawlak, Z.: Rough sets. International Journal of Computer and Information Sciences 11(1), 341–356 (1982)

    Article  MathSciNet  MATH  Google Scholar 

  37. Pawlak, Z.: Rough sets, decision algorithms and Bayes’ theory. European Journal of Operational Research 136(1), 181–189 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  38. Pawlak, Z.: Decision rules and flow networks. European Journal of Operation research 154(1), 184–190 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  39. Pawlak, Z.: Flow graphs and intelligent data analysis. Fundamenta Informaticae 64(1), 369–377 (2005)

    MathSciNet  MATH  Google Scholar 

  40. Richins, M.L., Root-Shaffer, T.: The Role of Involvement and Opinion Leadership in Consumer Word-of-Mouth: An Implicit Model Made Explicit. Advances in Consumer Research 15(1), 32–36 (1988)

    Google Scholar 

  41. Rogers, E.M.: The ’Critical Mass’ in the diffusion of interactive technologies in organizations. In: Kraemer, K.L. (ed.) Information Systems Research Challenge.: Survey Research Methods. Harvard Business School Research Colloquium, vol. 3, pp. 245–264. Harvard Business School, Boston (1991)

    Google Scholar 

  42. Rogers, E.M.: Diffusion of Innovations, 5th edn. Free Press, New York (1995)

    Google Scholar 

  43. Sankey, D.: Networking sites used for background checks, http://www2.canada.com/components/print.aspx?id=ba0dcc0d-f47d-49c9-add4-95d90fd969ab

  44. Shyng, J.Y., Shieh, H.M., Tzeng, G.H.: Compactness rate as a rule selection index based on rough set theory to improve data analysis for personal investment portfolios. Applied Soft Computing 11(4), 3671–3679 (2011)

    Article  Google Scholar 

  45. Sledgianowski, D., Kulviwat, S.: Social network sites: antecedents of user adoption and usage. In: Proceedings of the Fourteenth Americas Conference on Information Systems (AMCIS), Toronto, ON, Canada, pp. 1–10 (2008)

    Google Scholar 

  46. Słowiński, R.: New Applications and Theoretical Foundations of the Dominance-based Rough Set Approach. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS (LNAI), vol. 6086, pp. 2–3. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  47. Słowiński, R.: The international summer school om MCDM 2006. Class note. Kainan University, Taiwan (2006), Software available on line, http://idss.cs.put.poznan.pl/site/software.html

  48. Słowiński, R., Greco, S., Matarazzo, B.: Rough sets in decision making. In: Meyers, R.A. (ed.) Encyclopedia of Complexity and Systems Science, pp. 7753–7786. Springer, New York (2009)

    Google Scholar 

  49. Smith, D., Menon, S., Sivakumar, K.: Online peer and editorial recommendation, trust, and choice in virtual markets. Journal of Interactive Marketing 19(3), 15–37 (2005)

    Article  Google Scholar 

  50. Sung, S.K., Malhotra, N.K., Narasimhan, S.: Two competing perspectives on automatics use: a theorectical and empirical comparison. Information Systems Research 17(2), 418–432 (2005)

    Google Scholar 

  51. Wang, C.H., Chin, Y.C., Tzeng, G.H.: Mining the R&D innovation performance processes for high-tech firms based on rough set theory. Technovation 30(7-8), 447–458 (2010)

    Article  Google Scholar 

  52. Yi, Y., Wu, Z., Tung, L.L.: How individual differences influence technology usage behavior? Toward an integrated framework. Journal of Computer Information Systems 46(2), 52–63 (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Management Science, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, 300, Taiwan

    Yang-Chieh Chin & Chiun-Sin Lin

  2. Department of International Business, National Dong Hwa University, No.1, Sec.2, Da Hsueh Rd., Shoufeng, Hualien, 97401, Taiwan

    Chiao-Chen Chang

  3. Department of Business Administration, Kainan University, No. 1 Kainan Road, Luchu, Taoyuan, 338, Taiwan

    Gwo-Hshiung Tzeng

  4. Institute of Management of Technology, National Chiao Tung University, 1001 Ta-Hsueh Road, Hsinchu, 300, Taiwan

    Gwo-Hshiung Tzeng

Authors
  1. Yang-Chieh Chin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chiao-Chen Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chiun-Sin Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gwo-Hshiung Tzeng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yang-Chieh Chin .

Editor information

Editors and Affiliations

  1. Institute of Mathematics, Warsaw University, Banacha 2, Warsaw, 02097, Poland

    Andrzej Skowron

  2. Institute of Computer Science, University of Rzeszów, ul. Dekerta 2, Rzeszów, 35-030, Poland

    Zbigniew Suraj

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Chin, YC., Chang, CC., Lin, CS., Tzeng, GH. (2013). The Impact Rules of Recommendation Sources for Adoption Intention of Micro-blog Based on DRSA with Flow Network Graph. In: Skowron, A., Suraj, Z. (eds) Rough Sets and Intelligent Systems - Professor Zdzisław Pawlak in Memoriam. Intelligent Systems Reference Library, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30341-8_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-30341-8_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30340-1

  • Online ISBN: 978-3-642-30341-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation