Adaptation set of factors for assessing the commercial potential of technologies in different technology manufacturing branches
Abstract
In the course of previous research, it has been revealed, that specifics of different technology manufacturing branches are important for assessing the commercial potential. Several technology manufacturing branches already had big input from past and now cover the most promising part of the national economy. For these reasons, it was decided to customize the model for assessing the commercial potential to biotechnology, mechatronics, laser technology, information technology, nanoelectronics. Development of a set of factors for assessing commercial potential for different technology manufacturing branches is the first stage of the model’s customization process and the main purpose of this article. The next steps will include an expert study aimed at clarifying a set of factors based on the literature analysis, identifying the significance and the meanings of factor values. The literature of technology management did not take into account the specifics of the different technology manufacturing branches, therefore sources analysing the problems of intellectual property law, problems of different engineering sciences was used. With the help of the aforementioned literature in order to adapt the set of factors to each technology manufacturing branch aims to identify the challenges and problems are faced by representatives of different technology manufacturing branches in the process commercialization.
Keyword : adaptation set of factors, specifics of different technology manufacturing branches, assessment of the commercial potential, multiple criteria decision making (MCDM), biotechnology, mechatronics, laser technology, information technology, nanoelectronics
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Cho, J., & Lee, J. (2013). Development of a new technology product evaluation model for assessing commercialization opportunities using Delphi method and fuzzy AHP approach. Expert Systems with Applications, 40, 5314-5330. https://doi.org/10.1016/j.eswa.2013.03.038
Dereli, T., & Altun, K. (2013). A novel approach for assessment of candidate technologies with respect to their innovation potentials: quick innovation intelligence process. Expert Systems with Applications, 40(3), 881-891. https://doi.org/10.1016/j.eswa.2012.05.044
EPO (European Patent Office). (2012). Retrieved from https://www.epo.org/searching-for-patents/business/ipscore.html#tab-1
Ferreira, A., & Franco, M. (2017). The mediating effect of intellectual capital in the relationship between strategic alliances and organizational performance in Portuguese technology-based SMEs. European Management Review, 14(3), 303-318. https://doi.org/10.1111/emre.12107
Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making methods and applications. Berlin: Springer-Verlag. https://doi.org/10.1007/978-3-642-48318-9
International Islamic University Malaysia. (2017). Evaluation criteria for commercial potential award. Retrieved from http://www.iium.edu.my/irie/13/index.php/evaluation-criteria/8-iriie/15-commercial-potentialaward
Khalique, M., Bontis, N., Shaari, A. N. B. J., & Isa, A. H. I. (2015). Intellectual capital in small and medium enterprises in Pakistan. Journal of Intellectual Capital, 16(1), 224-238. https://doi.org/10.1108/JIC-01-2014-0014
Kiškis, M., & Limba, T. (2016). Monografija: biotechnologijų MVĮ intelektinės nuosavybės strategijos. Mykolas Romeris University. Vilnius, Lithuania.
Lithuanian Laser Association. (2017). Laser technologies in Lithuania. Retrieved from http://www.ltoptics.org/uploads/documents/Laser%20Technologies%20in%20Lithuania.%202017.pdf
Mamzer, M. F., Sophie Duboisb, S., & Saoutc, Ch. (2018). How to strengthen the presence of patients in health technology assessments conducted by the health authorities, Therapie, 73, 95-105. https://doi.org/10.1016/j.therap.2017.11.004
NASA (The National Aeronautics and Space Administration). (2017). Method of selection and evaluation criteria. Retrieved from https://sbir.nasa.gov/solicit/58007/detail?l1=58014
Neumann, F. (2015). Chapter 2: mechatronic product development. Analyzing and modeling interdisciplinary product development (pp. 23-32). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-11092-5_2
Ozcan, S., & Islam, N. (2017). An empirical study of nanowire technological trends. The Journal of High Technology Management Research, 28(2), 246-260. https://doi.org/10.1016/j.hitech.2017.10.001
Park, J. H., Kim, Y. B., & Kim, M. K. (2017). Investigating factors influencing the market success or failure of IT services in Korea. International Journal of Information Management, 37, 1418-1427. https://doi.org/10.1016/j.ijinfomgt.2016.10.004
Price, C., Huston, R., & Meyers, A. D. (2008). A new approach to improve technology commercialisation in university medical schools. Journal of Commercial Biotechnology, 14(2), 96-102. https://doi.org/10.1057/palgrave.jcb.3050086
Schafer, W., & Wehrheim, H. (2007, 23-25 May). The challenges of building advanced mechatronic systems. Future of Software Engineering (FOSE ‘07). Minneapolis, MN, USA. IEEE. https://doi.org/10.1109/FOSE.2007.28
SearchDataCenter. (2018). Retrieved from https://searchdatacenter.techtarget.com/definition/IT
Soo, C., Tian, A. W., Teo, S. T., & Cordery, J. (2017). Intellectual capital-enhancing HR, absorptive capacity, and innovation. Human Resource Management, 56(3), 431-454. https://doi.org/10.1002/hrm.21783
Stetter, R., Pulm, U. (2009, 24-27 August). Problems and chances in industrial mechatronic product development. International Conference On Engineering Desing. Standford University, Standford, CA, USA.
Tsai, Ch. H., Wu, H. W., Chen, I. S., Chen, J. K., & Ye, R. W. (2017). Exploring benchmark corporations in the semiconductor industry based on efficiency. The Journal of High Technology Management Research, 28(2), 188-207. https://doi.org/10.1016/j.hitech.2017.10.007
Vasantha, G., Roy, R., & Corney, J. (2014). Challenges and opportunities in transforming laser system industry to deliver integrated product and service offers. In L. M. Camarintha-Matos, & H. Afsarmanesh (Eds.), Collaborative Systems for Smart Networked Environments. PRO-VE 2014. IFIP
Advances in Information and Communication Technology, 434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44745-1_12
VentureQuest Ltd. (2015). Online diagnostic tools, importance tree. Retrieved from http://www.venturequestltd.com/tools.html
Volpatti, L. R., & Yetisen, A. K. (2014). Commercialization of microfluidic devices. Trends in Biotechnology, 32(7), 347-350. https://doi.org/10.1016/j.tibtech.2014.04.010
Vu, Ch. H. T., Lee, H. G., Chan, Y. K., & Oh, H. M. (2018). Axenic cultures for microalgal biotechnology: establishment, assessment, maintenance, and applications. Biotechnology Advances, 36(2), 380-396. https://doi.org/10.1016/j.biotechadv.2017.12.01
WIPO (The World Intellectual Property Organization). (2005). Exchanging value: negotiating. Technology. Licensing agreements. Retrieved from http://www.wipo.int/edocs/pubdocs/en/licensing/906/wipo_pub_906.pdf
Zemlickienė, V. (2015). Assessment of the commercial potential of technologies (Doctoral Dissertation). Vilnius Gediminas Technical University.
Zemlickienė, V., Bublienė, R., & Jakubavičius, A. (2018). A model for assessing the commercial potential of high technologies. Oeconomia Copernicana, 9(1), 29-54. https://doi.org/10.24136/oc.2018.002
Zemlickienė, V., Mačiulis, A., & Tvaronavičienė, M. (2017). Factors impacting the commercial potential of technologies: expert approach. Technological and Economic Development of Economy, 23(2), 410-427. https://doi.org/10.3846/20294913.2016.1271061