Integracja modeli dojrzałości i akceptacji technologii informacyjnych: przypadek RDS
Marek Nahotko
https://orcid.org/0000-0002-4823-8080
Afiliacja: Faculty of Management and Social CommunicationJagiellonian University, Polska
Abstrakt
Cel/Teza: W artykule przedstawiono trzy metody ewaluacji innowacji technologicznych, ze szczególnym uwzględnieniem innowacji technologii informacyjnych, takich jak systemy i serwisy informacyjne. Metody te obejmują ocenę dojrzałości, dyfuzję innowacyjnych technologii informacyjnych oraz ich akceptację przez użytkowników. Celem jest wskazanie na komplementarność tych metod, co czyni właściwym ich zintegrowane stosowanie.
Koncepcja/Metody badań: Wykorzystano dwa rodzaje teorii uwzględniających punkt widzenia zarówno twórców technologii informacyjnych (modele dojrzałości technologii), jak i użytkowników (modele akceptacji technologii). Podjęto próbę wskazania podobieństw pomiędzy tymi modelami umożliwiających ich łączne stosowanie. Zaprezentowano łączne stosowanie tych modeli na przykładzie modeli dojrzałości serwisów danych badawczych (RDS). Przeanalizowano sześć modeli dojrzałości RDS dostępnych w literaturze przedmiotu, badając ich kompletność przy użyciu modelu akceptacji technologii (TAM).
Wyniki i wnioski: Wykazano możliwość integracji modeli stosowanych do oceny SI. Przedstawione podejście badawcze pozwoliło na ocenę badanych modeli dojrzałości z punktu widzenia potrzeb użytkowników RDS, wpływających na poziom ich akceptacji. Wyniki wskazują, że istniejące modele dojrzałości RDS niewystarczająco uwzględniają potrzeby i punkt widzenia użytkowników tych serwisów, utrudniając ich akceptację.
Oryginalność/Wartość poznawcza: W artykule zaprezentowano nowy punkt widzenia na ocenę systemu informacyjnego służący integracji dwóch, stosowanych dotąd metod oceny SI: modeli dojrzałości i modeli akceptacji innowacyjnych technologii informacyjnych. Zaproponowano połączenie obu metod dla uzyskania bardziej spójnego i uniwersalnego narzędzia badawczego.
Bibliografia
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ISO/IEC 15504. Information technology – Process assessment.
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Lee, Y., Kozar, K., Larsen, K. (2003). The Technology Acceptance Model: past, present and future. Communications of AIS, 12(1), 752–780.
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Anderson, E., Jessen, S. (2003). Project maturity in organizations. International Journal of Project Management, 21(6), 457–461.
Babalhavaeji, F. i in. (2010). Quality assessment of academic libraries’ performance with a special reference to information technology-based services. Suggesting an evaluation checklist. The Electronic Library, 28(4), 592–621.
Baishya, K., Samalia, H., Joshi, R. (2017). Factors influencing e-district description: an empirical assessment in Indian context. International Review of Management and Marketing, 7(1), 514–520.
Becker, J., Knackstedt, R., Pöppelbuß, J. (2009). Developing maturity models for IT management – a procedure model and its application. Business & Information Systems Engineering, 1(3), 213–222.
Biberoglu, E., Haddad, H. (2002). A survey of industrial experiences with CMM and the teaching of CMM practices. Journal of Computing Sciences in Colleges, 18(2), 142–152.
Bucciarelli, L. (2015). A review of innovation and change management: stage model and power influences. Universal Journal of Management, 3(1), 36–42.
Buttle, F. (1996). SERVQUAL: review, critique, research agenda. European Journal of Marketing, 30(1), 8–32.
Chen, S., Li, S., Li, Ch. (2011). Recent related research in technology acceptance model: a literature review. Australian Journal of Business and Management Research, 1(9), 124–127.
Christensen, C. (1997). The innovator’s dilemma. Boston: Harvard Business School Press.
Cox, A. i in. (2017). Developments in research data management in academic libraries. Towards an understanding of research data service maturity. Journal of the Association for Information Science and Technology, 68(9), 2182–2200.
Cox, A. i in. (2019). Maturing research data services and the transformation of academic libraries. Journal of Documentation, 75(6), 1432–1462.
Crawford, J. (2006). The project management maturity model. Information Systems Management, 23(4), 50–58.
Curdt, C., Hoffmeister, D. (2015). Research data management services for a multidisciplinary, collaborative research project: design and implementation of the TR32DB project database. Program, 49(4), 494–512.
Davis, F. (1985). A technology acceptance model for empirically testing. New end-user information systems: theory and results. Cambridge, MA: MIT Press.
Davis, F., Bagozzi, R., Warshaw, P. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003.
Dempsey, L. (2017). Library collections in the life of the user: two directions. Liber Quarterly, 26(4), 338–359.
Derfert-Wolf, L., Górski, M., Marcinek, M. (2005). Quality of academic libraries – funding bodies, librarians and users’ perspective: a common project of Polish research libraries on comparable measures. In Proceedings of the 71st IFLA General Conference and Council, Libraries – A Voyage of Discovery. Oslo, 14–18 August 2005.
Dillon, A., Morris, M. (1998). From “can they?” to “will they?”: extending usability evaluation to address acceptance. In Hoadley, E., Benbasat, I. (Eds.), Proceedings Americas Conference on Information Systems (AMCIS), Baltimore, Univ. of Baltimore.
Drljevic, N., Aranda, D., Stantchev, V. (2022). An integrated adoption model to manage blockchain-driven business innovation in a sustainable way. Sustainability, 14(5), art. 2873.
Fishbein, M., Ajzen, I. (1975). Belief, attitude, intention and behavior: an introduction to theory and research. Reading: Addison-Wesley.
Fishbein, M., Ajzen, I. (2010). Predicting and changing behavior: the reasoned action approach. New York: Psychology Press.
Fitterer, R., Rohner, P. (2010). Towards assessing the networkability of health care provides: a maturity model approach. Information Systems and E-Business Management, 8(3), 309–333.
Fry, J. i in. (2021). RDM maturity assessment model in Canada (MAMIC). Toronto: Digital Research Alliance of Canada.
Głowacka, E. (2009). Ocena wpływu usług biblioteczno-informacyjnych na środowisko społeczne w badaniach jakości bibliotek. In J. Kamińska, B. Żołędowska-Król (Eds), Jakość usług bibliotecznych w społeczeństwie informacyjnym. Warszawa: Wydaw. SBP, 13–22.
Gomes, J., Romao, M. (2018). Information system maturity models in healthcare. Journal of Medical Systems, 42(11), art. 235.
Hart, S., Amos, H. (2018). The library assessment capability maturity model: a means of optimizing how libraries measure effectiveness. Evidence Based Library and Information Practice, 13(4), 31–49.
Harvey, L., Green, D. (1993). Defining quality. Assessment & Evaluation in Higher Education, 18(1), 9–35.
Heath, F. (2011). Library assessment: the way we have grown. Library Quarterly, 81(1), 7–25.
Hiller, S. (2001). Assessing user needs, satisfaction, and library performance at University of Washington libraries. Library Trends, 49(4), 605–626.
Hufford, J. (2013). A review of the literature on assessment in academic and research libraries, 2005 to August 2011. Portal: Libraries and Academy, 13(1), 5–35.
ISO/IEC 15504. Information technology – Process assessment.
Jankowska, M. (2006). Wymagania informacyjne użytkowników w bibliotekach akademickich XXI wieku: LibQUAL+TM jako narzędzie pomiaru jakości usług bibliotecznych. In II Konferencja Biblioteki Politechniki Łódzkiej Biblioteki XXI wieku. Czy przetrwamy?. Łódź, 19–21 czerwca 2006. Łódź: Polit. Łódzka, 197–208.
Jayasundra, Ch. (2021). Adoption of electronic books in a higher education setting: an exploratory case study on diffusion of innovation and Gartner’s hype cycle paradigms. Annals of Library and Information Studies, 68(3), 258–267.
Jia, G. i in. (2011). Program management organization maturity integrated model for mega construction programs in China. International Journal of Project Management, 29(7), 834–845.
Kamath, G. I in. (2022). LibQUAL+® based importance-performance matrix analysis for assessing library services quality: a case study. Annals of Library and Information Studies, 69(4), 269–276.
Keshavarz, H., Norouzi, Y. (2022). A maturity model for digital information management in university libraries: a design science study. International Information & Library Review, 54(4), 299–314.
Kim, J. (2021). Determining research data services maturity: the role of library leadership and stakeholder involvement. Library and Information Science Research, 43(2), art. 101092.
Kiran, k., Diljit, S. (2012). Modeling web-based library service quality. Library & Information Science Research, 34(3), 184–196.
Kohlegger, M., Maier, R., Thalmann, S. (2009). Understanding maturity models. Results of a structured content analysis. In K. Tochtermann, H. Mauer (Eds.) Proceedings of the 5th International Conference on Semantic Systems I-KNOW’09 and I-SEMANTICS’09, 51–61, 2–4 September 2009, Graz, Austria, 51–61. Graz: Verlag der Technische Universität Graz
Korbel, A., Benedict, R. (2007). Application of the project management maturity model to drive organizational improvement in a state owned corporation. In Proceedings of the AIPM Conference, Hobart, Tasmania, 7–10 Oct. 2007, 7–10.
Korpelainen, E. (2011). Theories of ICT system implementation and adoption – z critical review. Helsinki: Aalto Univ.
Kouper, I. i in. (2017). Research data services maturity in academic libraries. In L. Johnston (Ed.). Curating research data. Vol. 1: Practical strategies for your digital repository. Chicago: ACRL, 153–170.
Lajoie, E., Bridges, L. (2014). Innovation decisions: using the Gartner hype cycle. Library Leadership & Management, 28(4).
Lee, Y., Kozar, K., Larsen, K. (2003). The Technology Acceptance Model: past, present and future. Communications of AIS, 12(1), 752–780.
Lin, H. (2007). Effects of extrinsic and intrinsic motivation on employee knowledge sharing intentions. Journal of Information Science, 33(2), 135–149.
Looy, A., De Backer, M., Poels, G. (2011). Defining business process maturity. A journey towards excellence. Total Quality Management & Business Excellence, 22(11), 1119–1137.
Mauri, A., Minazzi, R., Muccio, S. (2013). A review of literature on the gaps model on service quality: a 3-decades period: 1985–2013. International Business Review, 6(12), 134–144.
Merriam-Webster (n.d.). Quality. In Merriam-Webster.com Dictionary. Retrieved 17.02.2023, from https://www.merriam-webster.com/dictionary/quality.
Mettler, T. (2011). Maturity assessment models: a design science research approach. International Journal of Society Systems Science, 3(1/2), 81–98.
Mettler, T. (2009). A design science research perspective on maturity models in information systems. Report no. BE IWI/HNE/03. St. Gallen: University of St. Gallen.
Mettler, T., Rohner, P., Winter, R. (2010). Towards a classification of maturity models in information systems. In A. D’Atri et al. (Eds.), Management of the interconnected world. Berlin, Heidelberg: Springer-Verlag, 333–340.
Moore, G. (1991). Crossing the chasm: marketing and selling high-tech products to mainstream customers. New York, Harper Business.
Murray-Rust, P. (2008). Chemistry for everyone. Nature, 451, 648–651.
Nahotko, M. (2022). Modele dojrzałości systemów informacyjnych na przykładzie bibliotek cyfrowych i serwisów danych badawczych. Zagadnienia Informacji Naukowej, 60(1), 7–25.
Nahotko, M. (2014). Zastosowanie modeli akceptacji technologii w badaniu użyteczności bibliotek cyfrowych. Bibliotheca Nostra, 1(35), 49–61.
Nitecki, D. (1996). Changing the concept and measure of service quality in academic libraries. Journal of Academic Librarianship, 22(3), 181–190.
Oslo Manual (2005). Guidelines for collecting and interpreting innovation data. 3rd ed. Paris: OECD.
Paulk, M. i in. (1993). Capability maturity model, version 1.1. IEEE Software, 10(4), 18–27.
Peng, G. i in. (2015). A unified framework for measuring stewardship practices applied to digital environmental datasets. Data Science Journal, 13, 231–253.
Pöppelbuß, J., Röglinger, M. (2011). What makes a useful maturity model? A framework for general design principles for maturity models and its demonstration in business process management. In Proceedings of the 19th European Conference on Information Systems (ECIS 2011). Helsinki, paper 28. https://aisel.aisnet.org/ecis2011/28.
Qin, J., Crowston, K., Kirkland, A. (2014). A capability maturity model for research data management. Syracuse, NY: School of Information Studies, Syracuse University.
Reykowski, J. (1982). Emocje i motywacja. In Tomaszewski, T. (red.), Psychologia. Warszawa: PWN.
Rogers, E. (2003). Diffusion of innovations, 5th ed. New York: Free Press.
Schumpeter, J. (1934). The theory of economic development: an inquiry into profits, capital, credit, interest, and the business cycle. Cambridge, MA: Harvard Univ. Press..
Sen, A., Ramammurthy, K., Sinha, A. (2012). A model of data warehousing process maturity. IEEE Transactions of Software Engineering, 38(2), 336–353.
Shareef, M. i in. (2011). E-Government adoption model (GAM): differing service maturity levels. Government Information Quarterly, 28(1), 17–35.
Sheikhshoaei, F. i in. (2021). Development and validation of a measuring instrument for digital library maturity. Library and Information Science Research, 43(3), art. 101101.
Staniszewska, M. (2015). Everett Roger’s diffusion of innovation and the possibility of its application in the dissemination of renewable energy sources. Acta Innovations, 15, 45–50.
Thorpe, C., Howlett, A. (2020). Understanding EBLIP at an organizational level: an initial maturity model. Evidence Based Library and Information Practice, 15(1), 90–105.
Utterback, J. (1971). The process of technological innovation within the firm. Academy of Management Journal, 14(1), 75–88.
Uttreback, J., Abernathy, W. (1975). A dynamic model of process and product innovation. Omega, 3(6), 639–656.
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Marek Nahotko
marek.nahotko@uj.edu.pl
https://orcid.org/0000-0002-4823-8080
Afiliacja: Faculty of Management and Social CommunicationJagiellonian University, Polska
Biogram:
https://orcid.org/0000-0002-4823-8080
Afiliacja: Faculty of Management and Social CommunicationJagiellonian University, Polska
Biogram:
MAREK NAHOTKO, dr hab. prof. uczelni, zatr. w Instytucie Studiów Informacyjnych Uniwersytetu Jagiellońskiego. Jest kierownikiem Zakładu Metodologii Badań Informacyjnych. Doktorat uzyskał na Uniwersytecie Wrocławskim (2002), habilitację na Uniwersytecie Warszawskim (2012). Specjalizuje się w zagadnieniach organizacji informacji i wiedzy, metadanych dokumentów elektronicznych oraz w stosowaniu internetu, dokumentów elektronicznych i danych badawczych w komunikacji naukowej i procesach informacyjnych. Najważniejsze publikacje obejmują książki: Teoria gatunków w organizacji informacji i wiedzy (Kraków, 2018), Komunikacja naukowa w środowisku cyfrowym (Warszawa, 2010), Naukowe czasopisma elektroniczne (Warszawa, 2007), Opis dokumentów elektronicznych. Teoretyczny model i możliwości jego aplikacji (Kraków 2006), Metadane. Sposób na uporządkowanie Internetu (Kraków, 2004). Opublikował także wiele artykułów w naukowych czasopismach informatologicznych, takich jak Journal of Academic Librarianship, Cataloging & Classification Quarterly, Annals of Library and Information Studies, Information Research, ZIN, Przegląd Biblioteczny, Zagadnienia Naukoznawstwa.
Kontakt do Autora:
e-mail: marek.nahotko@uj.edu.pl
Wydział Zarządzania i Komunikacji Społecznej
Uniwersytet Jagielloński
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