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Brad Zehner and Gary Pletcher

Technologies - Getting from Mind to Market. Boston, Massachusetts: Harvard Business School Press, p. 19 8. Maltby, A., Zehner, W., & Difford, R. (2006). Quick Mark Market Assessment and Business Opportunity Validation Methodology - a major boon for innovative SMEs? An evaluation ofthe effectiveness of quick cut market assessment tool for small businesses. Academy of Marketing Conference, London, England, June 4 to June 2006. 9. Moriarty, R. & Kosnik, T. (October 14, 1987). High Tech vs. Low Tech Marketing: Where's the Beef? Harvard Business

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Ryszard Depta

References 1. Bielecki, W.T. (2001). Informatyzacja zarządzania. Warszawa: PWE. 2. Chudzian, C., Granat, J., Klimasara, E., Sobieszek, J., Wierzbicki, A.P. (2011). Wykrywanie wiedzy w dużych zbiorach danych i przykład personalizacji inżynierii ontologicznej. Telekomunikacja i techniki informacyjne, No. 1-2. 3. Corcho, O., Fernandez-Lopez, M., Gomez-Perez, A. (2003). Methodologies tools and languages for building ontologies Where is their meeting point? Data and Knowledge Engineering, 46, p. 43. 4

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Marzena Feldy


Both the size of appropriation as well as their distribution have had a profound impact on the shape and activities of the science sector. The creation of a fair system of distribution of public resources to research that will also facilitate the effective implementation of the pursued scientific policy goals represents a major challenge. The issue of the determination of the right proportions of individual distribution channels remains critical. Despite this task being the responsibility of the State, establishing cooperation in this respect with the scientific community is desirable. The implementation of solutions that raise the concerns of scientists leads to system instability and reduced effectiveness which is manifest among others in a lower level of indicators of scientific excellence and innovation in the country.

These observations are pertinent to Poland where the manner in which scientific institutes operate were changed under the 2009-2011 reform. A neoliberal operating model based on competitiveness and rewarding of top rated scientific establishments and scientists was implemented. In light of these facts, the initiation of research that will provide information on how the implemented changes are perceived by the scientific community seems to be appropriate. The aim of this article is in particlar presenting how the project model of financing laid down under the reform is perceived and what kind of image has been shaped among Polish scientists. In order to gain a comprehensive picture of the situation, both the rational and emotional image was subject to analysis.

The conclusions regarding the perception of the project model were drawn on the basis of empirical materials collected in a qualitative study the specifics of which will be presented in the chapter on methodology. Prior to that, the author discusses the basic models for the distribution of state support for science and characterises the most salient features of the system in place in Poland. To conclude, the possible implications of the shaped image of the project model on the national science system will be presented.

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Jerzy Koszałka


More and more premises suggest that maintaining positive trends in Polish economy won’t be possible without changing the philosophy of activity which many companies follow. Taking into consideration the growing demands of clients and the market, globalization, which is strengthening competition, as well as the growing complexity of tools and production-service methods, it is not enough to continue building market position based on limitation of costs and lower product prices. Rising to the growing challenges, in particular, the challenges ahead of production-service units, will require a broad application of the achievements of science and technology to the processes of development. Even the biggest companies more and more often take advantage of the help of various partners, who support them in the process of introducing new solutions raising the efficiency of activities.

The partners and allies of business practice in the processes of modernization of the economy are scientificresearch institutions, such as scientific institutes, research-development units and universities. A market on which companies can look for the solutions they need and scientific-research institutions can look for inspiration, partners and capital is being formed. The market provides conditions for operation, development and implementation of developed solutions. Taking into consideration the complexity of market, technical, legal, financial, or intellectual property protection issues, research-development units are more and more frequently unable to function efficiently without a clear and unequivocal definition of goals, methods and conditions of activity. Their market offer has to take into consideration not just scientificresearch, or methodological aspects. Taking into consideration continuously growing demands of the clients and pressure of the competition, scientific-research institutions have to pay attention also to market, information, personnel, or financial aspects typical of strictly commercial ventures. What may support a comprehensive preparation and implementation of scientific-research activities under market conditions are tools successfully used in trade and economy, such as business models. These issues are the basis of deliberations contained in this work.

In order to make it easier for scientific-research institutions to work out models of conduct arranging activity and facilitating efficient functioning on the market, below attention is paid to the consideration of such issues as:

• the notion of business model in the economy and its components,

• characteristic features of research-development activity (R&D),

• the concept of components of business models in research-development activity,

• the essence of business model in research-development activity,

• benefits and conditions of using business models in research-development activity.

The paper ends with a summary - formulation of final conclusions.

Open access

Juan García-Machado

). Advanced PLS-SEM Topics: PLS Multigroup Analysis . Working paper, University of Seville, November. 41. Ringle, C.M., Wende, S., & Becker, J.M. (2015). SmartPLS 3 . Boenningstedt: SmartPLS GmbH:, 42. Roldán, J.L. & Sánchez-Franco, M.J. (2012). Variance-based Structural Equation Modeling: Guidelines for using Partial Least Square. In: Mora M., Gelman, O., Steenkamp, A., & Raisinghani, M.S. (2012). R esearch Methodologies, Innovations and Philosophies in Software System Engineering and Information Systems . USA: IGI Global. 43

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Małgorzata Grzegorczyk

university technologies. Journal of Engineering and Technology Management, 21, 115-142. 47. Smith, J.B. (1998). Buyer-Seller relationships: Similarity, relationship management, and Quality. Psychology and Marketing, 15, 3-21. 48. Sung, T.K., Gibson, D. (2005), Knowledge and technology transfer grid: empirical assessment. International Hournal of technology Management, 29, 216-230 49. Tranfield, D., Denyer, D. and Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of