Skip to main content

Affecting Factors of Knowledge-Based Companies Using Fuzzy AHP Model, Case Study Tehran University Enterprise Park

Abstract

Knowledge-based economy is a new economy in which the production, distribution, and use of knowledge is the main source of growth and wealth creation, which the knowledge-based economy companies are the engine of this system. These companies are usually private organization or cooperative companies, which their synergy is science and wealth, knowledge-based economic development, scientific and economic goals, and commercialization of research results. This study was conducted to investigate factors affecting these companies’ development. To this end, the target groups, including corporate executives and experts from the Ministry of Health was surveyed. Also, the fuzzy AHP technique is used to rate the judgments. For this purpose, eight factors, including technological factors, social and market conditions, political, administrative, economic, legal, and environmental factors are investigated. Finally, the views of these two groups have been compared and the differences in both approaches are discussed regarding the development of knowledge-based companies.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  • Al-Harbi, K. M. A. S. (2001). Application of the AHP in project management. International Journal of Project Management, 19(1), 19–27. https://doi.org/10.1016/S0263-7863(99)00038-1.

    Article  Google Scholar 

  • Amidon, D. M. (2001). Origin of the knowledge-based firms. Management Systems Research, 7, 212–223.

    Google Scholar 

  • Amiri, M. P. (2010). Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods. Expert Systems with Applications, 37(9), 6218–6224. https://doi.org/10.1016/j.eswa.2010.02.103.

    Article  Google Scholar 

  • Asllanaj, F., Milandri, A., Jeandel, G., & Roche, J. R. (2002). A finite difference solution of non-linear systems of radiative–conductive heat transfer equations. International Journal for Numerical Methods in Engineering, 54(11), 1649–1668. https://doi.org/10.1002/nme.490.

    Article  Google Scholar 

  • Beccali, M., Cellura, M., & Mistretta, M. (2003). Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy technology. Renewable Energy, 28(13), 2063–2087. https://doi.org/10.1016/S0960-1481(03)00102-2.

    Article  Google Scholar 

  • Bellman, R. E., & Zadeh, L. A. (1977). Local and fuzzy logics. In J. M. Dunn & G. Epstein (Eds.), Modern uses of multiple-valued logic. Boston: Kluwer.

    Google Scholar 

  • Caetano, M., & Amaral, D. C. (2011). Roadmapping for technology push and partnership: a contribution for open innovation environments. Technovation, 31(7), 320–335. https://doi.org/10.1016/j.technovation.2011.01.005.

    Article  Google Scholar 

  • Chan, E. H., Suen, H. C., & Chan, C. K. (2006). MAUT-based dispute resolution selection model prototype for international construction projects. Journal of Construction Engineering and Management, 132(5).

  • Chang, D. Y. (1996). Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research, 95(3), 649–655. https://doi.org/10.1016/0377-2217(95)00300-2.

    Article  Google Scholar 

  • de FSM Russo, R., & Camanho, R. (2015). Criteria in AHP: a systematic review of literature. Procedia Computer Science, 55, 1123–1132.

    Article  Google Scholar 

  • Deng, H. (1999). Multicriteria analysis with fuzzy pairwise comparison. International Journal of Approximate Reasoning, 21(3), 215–231. https://doi.org/10.1016/S0888-613X(99)00025-0.

    Article  Google Scholar 

  • Dunk, A. S. (2011). Product innovation, budgetary control, and the financial performance of firms. The British Accounting Review, 43(2), 102–111. https://doi.org/10.1016/j.bar.2011.02.004.

    Article  Google Scholar 

  • Ertuğrul, İ., & Karakaşoğlu, N. (2008). Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. [journal article]. The International Journal of Advanced Manufacturing Technology, 39(7), 783–795. https://doi.org/10.1007/s00170-007-1249-8.

    Article  Google Scholar 

  • Falahati, A., Navid, B. J., Barimizadeh, E., & Koolivand, E. (2013). Identifying and prioritizing capabilities and skills necessary for marketing knowledge-based companies of science and Technology Park in Kermanshah. European Online Journal of Natural and Social Sciences, 2(3).

  • Fattahi, R., Vahidi, H., Hosseinpour, M., Jalaeifar, F., & Masoomi, M. (2014). Solid waste management modeling in small islands by using the improved CHANG’S FAHP method: case study, LAVAN island, PERSIAN gulf. Advances in Civil and Environmental Engineering, 2(2), 20–36.

    Google Scholar 

  • Ghorbani, Z. (2015). Iran and knowledge-based economy: challenges and solutions. Journal of Applied Environmental and Biological Sciences, 5(2090–4274), 475–481.

    Google Scholar 

  • Gumus, A. T. (2009). Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology. Expert Systems with Applications, 36(2, Part 2), 4067–4074. https://doi.org/10.1016/j.eswa.2008.03.013.

    Article  Google Scholar 

  • Jia-quan, W. (2005). Delphi-AHP method for allocation of waste loads in a region. Journal of Harbin Institute of Technology, 37(1), 84–88.

    Google Scholar 

  • Kaasa, A. (2009). Effects of different dimensions of social capital on innovative activity: evidence from Europe at the regional level. Technovation, 29(3), 218–233. https://doi.org/10.1016/j.technovation.2008.01.003.

    Article  Google Scholar 

  • Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi-criteria supplier selection using fuzzy AHP. Logistics Information Management, 16(6), 382–394. https://doi.org/10.1108/09576050310503367.

    Article  Google Scholar 

  • Karamouz, M., Zahraie, B., Kerachian, R., Jaafarzadeh, N., & Mahjouri, N. (2007). Developing a master plan for hospital solid waste management: a case study. Waste Management, 27(5), 626–638. https://doi.org/10.1016/j.wasman.2006.03.018.

    Article  Google Scholar 

  • Kiker, G. A., Bridges, T. S., Varghese, A., Seager, T. P., & Igor Linkov, I. (2005). Application of multicriteria decision analysis in environmental decision making. Integrated Environmental Assessment and Management, 1(2), 95–108.

    Article  Google Scholar 

  • Klir, G. J., & Yuan, B. (1995). Fuzzy sets, fuzzy logic, and fuzzy systems (Vol. 6). World scientific publishing co Pte ltd.

  • Landry, R., Amara, N., & Ouimet, M. (2007). Determinants of knowledge transfer: evidence from Canadian university researchers in natural sciences and engineering. [journal article]. The Journal of Technology Transfer, 32(6), 561–592. https://doi.org/10.1007/s10961-006-0017-5.

    Article  Google Scholar 

  • Levitas, E. F., McFadyen, M. A., & Loree, D. (2006). Survival and the introduction of new technology: a patent analysis in the integrated circuit industry. Journal of Engineering and Technology Management, 23(3), 182–201. https://doi.org/10.1016/j.jengtecman.2006.06.008.

    Article  Google Scholar 

  • LotfiNejad, F., RashidZadeh, H., Fattahi, R., & Vahidi, H. (2013). Assessment and strategic planning for in-door and out-door sports with the application of SWOT analysis and AHP in fuzzy environment. International Journal of Sport Studies, 3(11), 1281–1291.

    Google Scholar 

  • Magnus, W., Karrass, A., & Solitar, D. (2004). Combinatorial group theory: Presentations of groups in terms of generators and relations. Courier Corporation.

  • Mcmullan, E. W., & Kentworthy, T. P. (2014). Creativity and entrepreneurial performance: A General Scientific Theory Exploring Diversity in Entrepreneurship. Springer.

  • Mehrabi, J., Soltani, I., Nilipour, A., & Pegah Kiarasi, P. (2013). Studying knowledge commercialization. International Journal of Academic Research in Business and Social Sciences, 3(7), 267–278.

    Article  Google Scholar 

  • Mikhailov, L., & Tsvetinov, P. (2004). Evaluation of services using a fuzzy analytic hierarchy process. Applied Soft Computing, 5(1), 23–33. https://doi.org/10.1016/j.asoc.2004.04.001.

    Article  Google Scholar 

  • Musango, J. K., & Brent, A. C. (2011). A conceptual framework for energy technology sustainability assessment. Energy for Sustainable Development, 15(1), 84–91. https://doi.org/10.1016/j.esd.2010.10.005.

    Article  Google Scholar 

  • Naseri, R., & Davoodi, R. (2011). Commercialization of nanotechnology in developing countries. Paper presented at the 2011 3rd International Conference on Information and Financial Engineering Singapore,

  • Önüt, S., & Soner, S. (2008). Transshipment site selection using the AHP and TOPSIS approaches under fuzzy environment. Waste Management, 28(9), 1552–1559. https://doi.org/10.1016/j.wasman.2007.05.019.

    Article  Google Scholar 

  • Pires, A., Chang, N.-B., & Martinho, G. (2011). An AHP-based fuzzy interval TOPSIS assessment for sustainable expansion of the solid waste management system in Setúbal peninsula, Portugal. Resources, Conservation and Recycling, 56(1), 7–21. https://doi.org/10.1016/j.resconrec.2011.08.004.

    Article  Google Scholar 

  • Ramanathan, R. (2001). A note on the use of the analytic hierarchy process for environmental impact assessment. Journal of Environmental Management, 63(1), 27–35.

    Article  Google Scholar 

  • Reeves, G. R. (1990). Decision making: descriptive, normative and prescriptive interactions: D.E. Bell, H. Raiffa and A. Tversky (eds.) Cambridge University press, Cambridge, 1988, x + 623 pages, £20.00. European Journal of Operational Research, 48(1), 166–167. https://doi.org/10.1016/0377-2217(90)90077-O.

    Article  Google Scholar 

  • Saaty, T. L. (1994). Highlights and critical points in the theory and application of the analytic hierarchy process. European Journal of Operational Research, 74(3), 426–447. https://doi.org/10.1016/0377-2217(94)90222-4.

    Article  Google Scholar 

  • Şener, B., Süzen, M. L., & Doyuran, V. (2006). Landfill site selection by using geographic information systems. [journal article]. Environmental Geology, 49(3), 376–388. https://doi.org/10.1007/s00254-005-0075-2.

    Article  Google Scholar 

  • Shagholi, R., & Hussin, S. (2009). Participatory management: an opportunity for human resources in education. Procedia - Social and Behavioral Sciences, 1(1), 1939–1943. https://doi.org/10.1016/j.sbspro.2009.01.341.

    Article  Google Scholar 

  • Subramaniam, M. Y., & Mark, A. (2005). The influence of intellectual capital on the types of innovative capabilities. Academy of Management Journal, 48(3), 450.

    Article  Google Scholar 

  • Vahidi, H., Ghazban, F., Abdoli, M., Kazemi, V., & Banaei, S. (2014). Fuzzy analytical hierarchy process disposal method selection for an industrial state; Case Study Charmshahr. Arabian Journal for Science & Engineering (Springer Science & Business Media BV), 39(2).

  • van Laarhoven, P. J. M., & Pedrycz, W. (1983). A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems, 11(1–3), 229–241. https://doi.org/10.1016/S0165-0114(83)80082-7.

    Article  Google Scholar 

  • Van Looy, B., Ranga, M., Callaert, J., Debackere, K., & Zimmermann, E. (2004). Combining entrepreneurial and scientific performance in academia: towards a compounded and reciprocal Matthew-effect? Research Policy, 33(3), 425–441. https://doi.org/10.1016/j.respol.2003.09.004.

    Article  Google Scholar 

  • Vetschera, R., & de Almeida, A. T. (2012). A PROMETHEE-based approach to portfolio selection problems. Computers & Operations Research, 39(5), 1010–1020. https://doi.org/10.1016/j.cor.2011.06.019.

    Article  Google Scholar 

  • Wang, T.-C., & Chen, Y.-H. (2007). Applying consistent fuzzy preference relations to partnership selection. Omega, 35(4), 384–388. https://doi.org/10.1016/j.omega.2005.07.007.

    Article  Google Scholar 

  • Wang, Y.-M., Luo, Y., & Hua, Z. (2008). On the extent analysis method for fuzzy AHP and its applications. European Journal of Operational Research, 186(2), 735–747. https://doi.org/10.1016/j.ejor.2007.01.050.

    Article  Google Scholar 

  • Wang, G.-Q., Luo, Y.-M., Li, G.-X., Xu, D.-G., & Zhang, H.-Y. (2008–2009). Optimizing the collection and transportation of municipal solid wastes based on AHP. China Environmental Science, 28(9), 838–842.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hamid Safarpour.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Amini, E., Baniasadi, M., Vahidi, H. et al. Affecting Factors of Knowledge-Based Companies Using Fuzzy AHP Model, Case Study Tehran University Enterprise Park. J Knowl Econ 11, 574–592 (2020). https://doi.org/10.1007/s13132-018-0554-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13132-018-0554-9

Keywords

  • Knowledge-based companies
  • Fuzzy AHP model
  • Tehran University Enterprise Park
  • Development factors