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Статті в журналах з теми "Predicting Innovation"
Schwabsky, Nitza, Ufuk Erdogan, and Megan Tschannen-Moran. "Predicting school innovation." Journal of Educational Administration 58, no. 2 (December 23, 2019): 246–62. http://dx.doi.org/10.1108/jea-02-2019-0029.
Повний текст джерелаBlagojevic, Marija, Zivadin Micic, and Momcilo Vujicic. "Cluster analysis of knowledge sources in standardized electrical engineering subfields." Serbian Journal of Electrical Engineering 13, no. 3 (2016): 405–22. http://dx.doi.org/10.2298/sjee1603405b.
Повний текст джерелаHang Do, Thuy, Tim Mazzarol, Thierry Volery, and Sophie Reboud. "Predicting anticipated rent from innovation commercialisation in SMEs." European Journal of Innovation Management 17, no. 2 (May 6, 2014): 183–208. http://dx.doi.org/10.1108/ejim-12-2012-0113.
Повний текст джерелаRojas-Córdova, Carolina, Boris Heredia-Rojas, and Patricio Ramírez-Correa. "Predicting Business Innovation Intention Based on Perceived Barriers: A Machine Learning Approach." Symmetry 12, no. 9 (August 19, 2020): 1381. http://dx.doi.org/10.3390/sym12091381.
Повний текст джерелаPark, Kyungbo, Jeonghwa Cha, and Jongyi Hong. "Developing a Framework for Evaluating and Predicting Management Innovation in Public Research Institutions." Sustainability 15, no. 9 (April 27, 2023): 7261. http://dx.doi.org/10.3390/su15097261.
Повний текст джерелаRamiz Abdinov, Vidadi Akhundov, Ramiz Abdinov, Vidadi Akhundov. "METHODOLOGY FOR ASSESSING THE IMPACT OF INNOVATIONS ON THE PRODUCTION OF THE REGION'S FINAL PRODUCTS." PIRETC-Proceeding of The International Research Education & Training Centre 21, no. 04 (November 9, 2022): 33–38. http://dx.doi.org/10.36962/piretc21042022-33.
Повний текст джерелаSwart, Rachelle R., Maria JG Jacobs, Cheryl Roumen, Ruud MA Houben, Folkert Koetsveld, and Liesbeth J. Boersma. "Factors predicting timely implementation of radiotherapy innovations: the first model." British Journal of Radiology 94, no. 1117 (January 1, 2021): 20200613. http://dx.doi.org/10.1259/bjr.20200613.
Повний текст джерелаGashema, Bruce. "Predicting innovative work behaviors through transformational leadership." International Journal of Research in Business and Social Science (2147- 4478) 10, no. 1 (February 11, 2021): 69–84. http://dx.doi.org/10.20525/ijrbs.v10i1.999.
Повний текст джерелаRani, Ruchi, Sumit Kumar, Rutuja Rajendra Kadam, and Sanjeev Kumar Pippal. "A machine learning model for predicting innovation effort of firms." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 4 (August 1, 2023): 4633. http://dx.doi.org/10.11591/ijece.v13i4.pp4633-4639.
Повний текст джерелаPan, Han, Wu Xin, and Yuping Li. "A review on the concept of consumer innovativeness." E3S Web of Conferences 251 (2021): 01080. http://dx.doi.org/10.1051/e3sconf/202125101080.
Повний текст джерелаДисертації з теми "Predicting Innovation"
Reagan, James L. "Predicting disruptive innovation| Which factors determine success?" Thesis, Shenandoah University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3680894.
Повний текст джерелаDisruptive Innovation theory explains how industry entrants can defeat established firms and quickly gain a significant share of their key markets, in spite of the fact that incumbents tend to be significantly more experienced and better resourced. The theory has been criticized for being underspecified: whilst the general mechanics of the phenomenon of disruptive innovation are clear, it has not been established which individual variables are essential to the process and which ones are merely ancillary. As a consequence, to date it has not been possible to build a predictive model on the basis of the theory managers can use to assess the disruptive potential of their own and their competitors' innovation projects. In this research project the predictive power of each of the main variables that are mentioned in the literature has been assessed on the basis of a qualitative analysis of five real world case studies. Only variables for which information can be collected using publicly available data before disruption happens have been retained. By clarifying the detail of disruptive innovation theory, this study has been able to address a key issue in the debate, namely, whether products that are more expensive and more complex than the market standard can ever be classified as 'disruptive innovations' or whether they should always be regarded as 'high-end anomalies'. In this study two distinct disruptive innovation strategies have been identified based on the current phase of the product life cycle, the current focus of mainstream demand and the market segments first targeted when coming to market. The first strategy entails growing an existing market by moving the focus of demand on to a secondary market driver as soon as customers begin to lose their willingness to pay a premium for upgrades in the performance areas they historically used to value. Early on in the product life cycle, disruptors can conquer the mainstream market 'from above' with products that are different and more reliable or more convenient but not simpler or cheaper. The second strategy creates a new separate market by offering a radically new type of additional functionality. Over time the new market replaces the old market. These products are likely to be expensive because of their small production run and difficult to use because they are the first models of their kind. High-end customers constitute a natural foothold market for these products as they are wealthy and highly skilled.
Heesen, Bernd. "Diffusion of innovations : factors predicting the use of e-learning at institutions of higher education in Germany." Berlin dissertation.de, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2833665&prov=M&dokv̲ar=1&doke̲xt=htm.
Повний текст джерелаHeesen, Bernd. "Diffusion of innovations factors predicting the use of e-learning at institutions of higher education in Germany." Berlin dissertation.de, 2004. http://deposit.d-nb.de/cgi-bin/dokserv?id=2833665&prov=M&dok_var=1&dok_ext=htm.
Повний текст джерелаChan, Tan Fung Ivan. "Predicting the Probability for Adopting an Audience Response System in Higher Education." ScholarWorks, 2015. https://scholarworks.waldenu.edu/dissertations/1529.
Повний текст джерелаBohling, Timothy R. "Predicting Purchase Timing, Brand Choice and Purchase Amount of Firm Adoption of Radically Innovative Information Technology: A Business to Business Empirical Analysis." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/bus_admin_diss/3.
Повний текст джерелаOcal, Kubilay. "Predicting Employee Performance In Non-profit Sport Organizations: The Role Of Managerial And Financial Performance And The Mediating Role Of Support For Innovation And Individual Creativity." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613403/index.pdf.
Повний текст джерелаSpears-Dean, Dorothy. "Predicting the Diffusion of Next Generation 9-1-1 in the Commonwealth of Virginia: An Application Using the Deployment of Wireless E9-1-1 Technologies." VCU Scholars Compass, 2011. http://scholarscompass.vcu.edu/etd/183.
Повний текст джерелаMcSharry, Patrick E. "Innovations in consistent nonlinear deterministic prediction." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.342590.
Повний текст джерелаEustace, Paul Alan. "Structural mass of innovative concept aircraft." Thesis, Loughborough University, 2001. https://dspace.lboro.ac.uk/2134/7361.
Повний текст джерелаLe, An Hai. "Innovative neural network approaches for petrophysical parameter prediction." Thesis, Heriot-Watt University, 2004. http://hdl.handle.net/10399/326.
Повний текст джерелаКниги з теми "Predicting Innovation"
Christopher, Layne, Arquilla John, Rand Corporation, and Arroyo Center, eds. Predicting military innovation. Santa Monica, CA: RAND, 1999.
Знайти повний текст джерелаBarbara, Collier, and U.S. Army Research Laboratory, eds. ARL, predictive technology. Adelphi, Md: Army Research Laboratory, 1993.
Знайти повний текст джерелаKiruluta, Andrew M. Predictive head movement tracking using innovations generated by Kalman filters. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1993.
Знайти повний текст джерелаBrueck, Terrance M. Forecasting the future: Progress, change, and predictions for the water sector. Denver, Colo: Water Research Foundation, 2012.
Знайти повний текст джерелаLee, Jinsuk. Lifetime prediction for degradation of solar mirrors using step-stress accelerated testing. Golden, Colo.]: National Renewable Energy Laboratory, 2011.
Знайти повний текст джерелаLittleton, Eliza Beth. Predicting rapid decision-making processes required by the dismounted objective force warrior. Alexandria, VA: United States Army Research Institute for the Behavioral and Social Sciences, 2003.
Знайти повний текст джерелаYŏng-sŏn, Kwŏn. Homo k'ŏnbŏjŏnsŭ: Che 4-ch'a sanŏp hyŏngmyŏng kwa mirae sahoe = Homo convergence. Kyŏnggi-do P'aju-si: Asia, 2016.
Знайти повний текст джерела(Firm), Knovel, ed. Case studies in novel food processing technologies: Innovations in processing, packaging and predictive modelling. Oxford: Woodhead Publishing, 2010.
Знайти повний текст джерелаTransizione, dall'era industriale a quella post-industriale: Verso la Terza Guerra Mondiale o alla conquista del futuro? Milano: Nuovi autori, 1986.
Знайти повний текст джерелаMaxence, Layet, Bultez Adams Philippe, and Kaplan Frédéric, eds. Futur 2.0: Comprendre les 20 prochaines années. Limoges: Fyp éditions, 2007.
Знайти повний текст джерелаЧастини книг з теми "Predicting Innovation"
Gatignon, Hubert, David Gotteland, and Christophe Haon. "Predicting New Product Acceptance." In Making Innovation Last: Volume 2, 211–71. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1007/978-1-137-57264-6_5.
Повний текст джерелаNg, Shien Wee, Hoa Khanh Dam, Morakot Choetkiertikul, and Aditya Ghose. "Predicting Issues for Resolving in the Next Release." In Service Research and Innovation, 164–77. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76587-7_11.
Повний текст джерелаHiltunen, Elina. "Some Thoughts about Predicting the Future, Its Ease and Difficulty." In Foresight and Innovation, 17–25. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137337702_2.
Повний текст джерелаChadha, Akalbir Singh, Yashowardhan Shinde, Neha Sharma, and Prithwis Kumar De. "Predicting CO2 Emissions by Vehicles Using Machine Learning." In Data Management, Analytics and Innovation, 197–207. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2600-6_14.
Повний текст джерелаBhosale, Hrushikesh, Aamod Sane, Vigneshwar Ramakrishnan, and Valadi K. Jayaraman. "Distributed Reduced Alphabet Representation for Predicting Proinflammatory Peptides." In Data Management, Analytics and Innovation, 161–73. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1414-2_14.
Повний текст джерелаMaiti, Reetun, and Balagopal G. Menon. "Predicting Injury Severity in Construction Using Logistic Regression." In Data Management, Analytics and Innovation, 175–85. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1414-2_15.
Повний текст джерелаMohanty, Samuka, and Rajashree Dash. "Predicting the Price of Gold: A CSPNN-DE Model." In Smart Innovation, Systems and Technologies, 289–97. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6202-0_29.
Повний текст джерелаWilliams, Louis, Salman Waqar, Tom Sherman, and Giovanni Masala. "Comparative Study of Pattern Recognition Methods for Predicting Glaucoma Diagnosis." In Innovation in Medicine and Healthcare, 93–103. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5852-8_9.
Повний текст джерелаPoovammal, E., Mayank Kumar Nagda, and K. Annapoorani. "Predicting Property Prices: A Universal Model." In EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing, 259–68. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19562-5_26.
Повний текст джерелаRadhakrishnan, Hari Kumar, C. P. Ramanarayanan, and R. Bharath. "Machine Learning Based Automated Process for Predicting the Anomaly in AIS Data." In Data Management, Analytics and Innovation, 303–14. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2600-6_21.
Повний текст джерелаТези доповідей конференцій з теми "Predicting Innovation"
Ahmad Rafi, Mohamed Eshaq, and Scott Chase. "Transforming Grammars for Goal Driven Style Innovation." In eCAADe 2007: Predicting the Future. eCAADe, 2007. http://dx.doi.org/10.52842/conf.ecaade.2007.879.
Повний текст джерелаThomson, A., M. Haggith, and Ravi Prabhu. "Innovation diffusion: predicting success of system development." In Proceedings. 15th International Workshop on Database and Expert Systems Applications, 2004. IEEE, 2004. http://dx.doi.org/10.1109/dexa.2004.1333545.
Повний текст джерелаYu, Chen-Hsiang, Jungpin Wu, and Aa-Chi Liu. "PREDICTING LEARNING OUTCOMES WITH MOOCS CLICKSTREAMS." In 2nd Eurasian Conference on Educational Innovation 2019. International Institute of Knowledge Innovation and Invention Private Limited, 2019. http://dx.doi.org/10.35745/ecei2019v2.079.
Повний текст джерелаKorableva, Olga, Viktoriya Mityakova, and Olga Kalimullina. "Designing a Decision Support System for Predicting Innovation Activity." In 22nd International Conference on Enterprise Information Systems. SCITEPRESS - Science and Technology Publications, 2020. http://dx.doi.org/10.5220/0009565706190625.
Повний текст джерелаSrivatsa, Hosur Srinivasan, Arun R, Sandeep N, and Vijaya Kumar S. "Predicting Green Innovation Levels Among Automobile and Earthmoving Sectors." In 2nd Indian International Conference on Industrial Engineering and Operations Management. Michigan, USA: IEOM Society International, 2022. http://dx.doi.org/10.46254/in02.20220283.
Повний текст джерелаVesic, Ana, Vuk Ignjatovic, Sava Lakicevic, Luka Lakicevic, Bojan Gutic, Hristo Skacev, Dusan Dotlic, Andrej Micovic, Marina Marjanovic Jakovljevic, and Miodrag Zivkovic. "Predicting Plant Water and Soil Nutrient Requirements." In 2020 Zooming Innovation in Consumer Technologies Conference (ZINC). IEEE, 2020. http://dx.doi.org/10.1109/zinc50678.2020.9161433.
Повний текст джерелаHajek, Petr, and Jan Stejskal. "Predicting the innovation activity of chemical firms using an ensemble of decision trees." In 2015 11th International Conference on Innovations in Information Technology (IIT). IEEE, 2015. http://dx.doi.org/10.1109/innovations.2015.7381511.
Повний текст джерелаKekulanadara, K. M. O. V. K., B. T. G. S. Kumara, and Banujan Kuhaneswaran. "Comparative Analysis of Machine Learning Algorithms for Predicting Air Quality Index." In 2021 From Innovation To Impact (FITI). IEEE, 2021. http://dx.doi.org/10.1109/fiti54902.2021.9833033.
Повний текст джерелаKlavans, Richard, Kevin Boyack, and Caleb Smith. "Field Effects in Predicting Exceptional Growth in Research Communities." In 27th International Conference on Science, Technology and Innovation Indicators (STI 2023). International Conference on Science, Technology and Innovation Indicators, 2023. http://dx.doi.org/10.55835/643f1aa90f649f6042841876.
Повний текст джерелаKhalaf, Fatema, and Subhashini S. Baskaran. "Predicting Acute Respiratory Failure Using Fuzzy Classifier." In 2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD). IEEE, 2023. http://dx.doi.org/10.1109/itikd56332.2023.10099746.
Повний текст джерелаЗвіти організацій з теми "Predicting Innovation"
Coughlan, Peter, William Gates, and Jeremy Arkes. Innovations in Defense Acquisition: Asymmetric Information, Mechanism Design and Prediction Markets. Fort Belvoir, VA: Defense Technical Information Center, February 2011. http://dx.doi.org/10.21236/ada563409.
Повний текст джерелаJoseph, Earl C., and Steve Conway. Create full-scale predictive economic models on ROI and innovation with performance computing. Office of Scientific and Technical Information (OSTI), October 2017. http://dx.doi.org/10.2172/1405141.
Повний текст джерелаBitz, Cecilia M. An Innovative Network to Improve Sea Ice Prediction in a Changing Arctic. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada617899.
Повний текст джерелаGoldsmith, Stephen, Susan Crawford, and Benjamin Weinryb Grohsgal. Innovations in Public Service Delivery: Issue No. 4: Predictive Analytics: Driving Improvements Using Data. Inter-American Development Bank, July 2016. http://dx.doi.org/10.18235/0000421.
Повний текст джерелаSánchez- Sesma, Francisco José, Hiroshi Kawase, and Joseline Mena Negrete. Working Paper PUEAA No. 5. The collaboration between Mexico and Japan in earthquake engineering and seismology. Universidad Nacional Autónoma de México, Programa Universitario de Estudios sobre Asia y África, 2022. http://dx.doi.org/10.22201/pueaa.003r.2022.
Повний текст джерелаMattsson, Ann Elisabet, Scott A. Mitchell, and Stephen W. Thomas. LDRD 102610 final report new processes for innovative microsystems engineering with predictive simulation. Office of Scientific and Technical Information (OSTI), August 2007. http://dx.doi.org/10.2172/913217.
Повний текст джерелаХолошин, Ігор Віталійович, Наталя Борисівна Пантелєєва, Олександр Миколайович Трунін, Людмила Володимирівна Бурман, and Ольга Олександрівна Калініченко. Infrared Spectroscopy as the Method for Evaluating Technological Properties of Minerals and Their Behavior in Technological Processes. E3S Web of Conferences, 2020. http://dx.doi.org/10.31812/123456789/3929.
Повний текст джерелаSandford, Robert, Vladimir Smakhtin, Colin Mayfield, Hamid Mehmood, John Pomeroy, Chris Debeer, Phani Adapa, et al. Canada in the Global Water World: Analysis of Capabilities. United Nations University Institute for Water, Environment and Health, November 2018. http://dx.doi.org/10.53328/vsgg2030.
Повний текст джерелаSaville, Alan, and Caroline Wickham-Jones, eds. Palaeolithic and Mesolithic Scotland : Scottish Archaeological Research Framework Panel Report. Society for Antiquaries of Scotland, June 2012. http://dx.doi.org/10.9750/scarf.06.2012.163.
Повний текст джерелаLandau, Sergei Yan, John W. Walker, Avi Perevolotsky, Eugene D. Ungar, Butch Taylor, and Daniel Waldron. Goats for maximal efficacy of brush control. United States Department of Agriculture, March 2008. http://dx.doi.org/10.32747/2008.7587731.bard.
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