Published November 28, 2010 | Version 12123

A Framework to Support the Design of Mobile Applications

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This paper introduces a framework that aims to support the design and development of mobile services. The traditional innovation process and its supporting instruments in form of creativity tools, acceptance research and user-generated content analysis are screened for potentials for improvement. The result is a reshaped innovation process where acceptance research and usergenerated content analysis are fully integrated within a creativity tool. Advantages of this method are the enhancement of design relevant information for developers and designers and the possibility to forecast market success.

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References

  • M. Amberg, M. Hirschmeier, J. Wehrmann, "The compass acceptance model for the analysis and evaluation of mobile services", International Journal of Mobile Communications 2(3), pp. 248-259, 2004.
  • V. Bilgram, A. Brem, K.-I. Voigt, "User-Centric Innovations in New Product Development; Systematic Identification of Lead User Harnessing Interactive and Collaborative Online-Tools", International Journal of Innovation Management, 12 (3), pp. 419-458, 2008.
  • H. Cunningham, D. Maynard, K. Bontcheva, V. Tablan, "GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications", Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics (ACL'02), Philadelphia, July 2002.
  • M. Csikszentmihalyi, Das Flow-Erlebnis: Jenseits von Angst und Langeweile im Tun aufgehen. (The Flow-Experience: Being carried away with action beyond fear and boredom.), Stuttgart, Klett-Cotta, 1987.
  • F. Davis, A Technology Acceptance Model for Empirically Testing New End-User Information systems, Massachusetts Institute of Technology, Sloan School of Management Thesis, 1985.
  • G. Druck, C. Pal, X. Zhu, A. McCallum, "Semi-Supervised Classification with Hybrid Generative/Discriminative Methods", Proceedings of the Conference on Knowledge Discovery and Data Mining, August 12-15 2007, San Jose, USA, 2007.
  • G. Druck, B. Settles, A. McCallum, "Active Learning by Labeling Features", Proceedings of the Empirical Methods in Natural Language Processing, August 6-7 2009, Singapore, 2009.
  • M. Fishbein, I. Ajzen, Belief, Attitude, Intention and Behavior: An introduction to Theory and Research, Reading, Addison-Wesely, 1975.
  • U. Frank, "Interview mit Rudi Studer zum Thema "Semantische Technologien" (Interview with Rudi Studer concerning the topic of "semantic technologies")", Wirtschaftsinformatik 52(1), pp. 49-52, 2010. [10] O. Gassmann, M. Zeschky, "Radikale Innovation ist nicht planbar wie ein Produktionsprozess (Radical innovation is not as planable as a production process)", Innovation Management 3, pp. 8-10, 2007. [11] D. L. Goodhue, R. L. Thompson, "Task-Technology fit and individual performance", MIS Quarterly 19, pp. 213-236, 1995. [12] A. R. Hevner, S. T. March, J. Park, "Design Science in Information Systems Research", MIS Quarterly 28, pp. 75-105, 2004. [13] E. v. Hippel, "Lead Users. A Source of novel product concepts", Management Science 32, pp. 791-805, 1986. [14] D. L. Hoffman, T. P. Novak, "Marketing in hypermedia computermediated environments: conceptual foundations", Journal of Marketing 60(3), pp. 50-68, 1996. [15] T. Kollmann, Akzeptanz individueller Nutzungsg├╝ter und -systeme. Konsequenzen f├╝r die Einf├╝hrung von Telekommunikations- und Multimediasystemen (Acceptance of individual goods and systems. Consequences for the introduction of telecommunication and multimedia systems), Wiesbaden, Gabler, 1998. [16] J. Kranz, C. Janello, A. Picot, "Die Rolle von Web 2.0-Prinzipien im Innovationsprozess (The role of web 2.0 principles within the innovation process)", Information Management und Consulting 24, pp. 39-47, 2009. [17] M. C. Lacity, M. A. Janson, "Understanding Qualitative Data: A Framework of Text Analysis Methods", Journal of Management Information Systems 11(2), pp. 137-155, 1994. [18] A. McCallum, D. Jensen, "A Note on the Unification of Information Extraction and Data Mining using Conditional-Probability, Relational Models", IJCAI-03 Workshop on Learning Statistical Models from Relational Data, August 9-15, Acapulco, Mexico, 2003. [19] A. McCullam, "Information Extraction: Distilling Structured Data from Unstructured Text", ACM Queue 3 (9), 2005. [20] K. Nigam, A. McCallum, T. M. Mitchell, "Semi-Supervised Text Classification Using EM", in: O. Chapelle, A. Zien, B. Schalkopf, Eds., Semi-Supervised Learning, Boston: MIT Press, 2006. [21] O. Petrovic, C. Kittl, E. Maxl, Werbefinanzierung und Mobile TV - Internationales Benchmarking von Mobile TV-Werbeformen (Advertisment-based finance and mobile TV - International benchmarking of mobile TV advertising forms), Schriftenreihe der Rundfunk und Telekom Regulierungs-GmbH, 2009. [22] E. Platzer, "A critical review of user acceptance research in the area of mobile services", Libri: international journal of libraries and information services 59 (4), pp. 213-227, 2009. [23] L. R. Rabiner, "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition", Proceedings of the IEEE 77 (2), pp. 257-286, 1989. [24] S. Reiss, "Multifaceted Nature of Intrinsic Motivation: The Theory of 16 Basic Desires," Review of General Psychology 8(3), pp. 179-193, 2004. [25] E. M. Rogers, Diffusion of innovations, 5. ed., New York, Free Press, 2003. [26] M. Schmid, ÔÇ×Mobile TV 2012. Marktpotenziale f├╝r rundfunkbasiertes Mobile TV in Deutschland (Mobile TV 2010. Market potentials of broadcasting-based mobile TV in Germany)", Goldmedia, 2007. [27] C. Sutton, A. McCallum, "An Introduction to Conditional Random Fields for Relational Learning", in: L. Getoor, B. Taskar, Eds., Introduction to Statistical Relational Learning, Boston, MIT Press, 2006. [28] V. Venkatesh, "User Acceptance of Information Technology: Toward a Unified View", MIS Quarterly 27, pp. 425-478, 2003. [29] Y. Yang, "An Evaluation of Statistical Approaches to Text Categorization", Journal of Information Retrieval 1 (1/2), pp. 67-88, 1999.