Technology valuation of NTBFs in the field of cleaner production in terms of investors' exibility and uncertainty in public policy

Document Type : Article


Department of Progress Engineering at Iran University of Science and Technology (IUST), Narmak, Tehran, Iran


Technology valuation, especially in the early stages of new technology-based firms (NTBFs) growth is one of the most critical challenges, which most often hinders the investor and entrepreneur's deals during the venture capital (VC) financing process. It is clear that uncertainties arising from the likelihood of implementing public policies could significantly affect the volatility of NTBFs cash flows in the field of cleaner production. Commonly, these kinds of technologies require public supportive policies for achieving success. Consequently, their technology valuation is more challenging and traditional valuation methods are not suitable anymore because of the definitive assumption of cash flow and ignoring the investors’ flexibilities and uncertainties. Therefore, this paper proposes a method by introducing a framework based on the decision tree and the real options analysis which is tailored to meet the technology valuation of such firms during all stages of their growth. Furthermore, unlike previous papers that have utilized the compound options, option to choose has been used to apply investors’ flexibilities. Then, the proposed framework is supported by a case study, which has been conducted to verify and validate it. Finally, the conclusion section discusses the contributions and limitations of the study and provides directions for future research.


Main Subjects

  1. References:

    1. Stokes, D. and Wilson, N., Small Business Management and Entrepreneurship, Cengage., 6th Edn. (2010).
    2. Yague-Perales, R.M. and March-Chorda, I. Performance analysis of NTBFs in knowledge-intensive industries: Evidence from the human health sector", Journal of Business Research, 66(10), pp. 1983{1989 (2013).
    3. Jensen, A. and Clausen, T.H. Origins and emergence of exploration and exploitation capabilities in new technology-based _rms", Technological Forecasting & Social Change, 120, pp. 163{175 (2017).
    4. Camis_on-Haba, S., Clemente-Almendros, J.A., and Gonzalez-Cruz, T. How technology-based _rms become also highly innovative _rms? The role of knowledge, technological and managerial capabilities, and entrepreneurs' background", Journal of Innovation & Knowledge, 4(3), pp. 162{170 (2019). 5. Phan, P.H., Siegel, D.S., and Wright, M. Science parks and incubators: observations, synthesis and future research", Journal of Business Venturing, 20(2), pp. 165{182 (2005). 6. Stucki, T. Which _rms bene_t from investments in green energy technologies? -The e_ect of energy costs", Research Policy, 48(3), pp. 546{555 (2019). 7. Yabar, H., Uwasu, M., and Hara, K. Tracking environmental innovations and policy regulations in Japan: case studies on dioxin emissions and electric home appliances recycling", Journal of Cleaner Production, 44, pp. 152{158 (2013). 8. Guerzoni, M. and Raiteri, E. Demand-side vs. supplyside technology policies: Hidden treatment and new empirical evidence on the policy mix", Research Policy, 44(3), pp. 726{747 (2015). 9. Amankwah-Amoah, J. and Hinson, R.E. Contextual inuences on new technology ventures: A study of domestic _rms in Ghana", Technological Forecasting and Social Change, 143, pp. 289{296 (2019). 10. Quindlen, R. Confessions of a venture capitalist: Inside the high-stakes world of start-up _nancing", Business Plus, May 1st (2001). 11. Cumming, D. and Dai, N. Fund size, limited attention and valuation of venture capital backed _rms", Journal of Empirical Finance, 18(1), pp. 2{15 (2011). 12. Ari, G.B. and Vonortas, N.S. Risk _nancing for knowledge-based enterprises: mechanisms and policy options", Science and Public Policy, 34(7), pp. 475{ 488 (2007). 13. Engel, D. and Keilbach, M. Firm-level Implications of early stage venture capital investment: An empirical investigation", Journal of Empirical Finance, 14(2), pp. 150{167 (2007). 14. Hochberg, Y.V., Ljungqvist, A., and Lu, Y. Networking as a barrier to entry and the competitive supply of venture capital", Journal of Finance, 65(3), pp. 829{ 859 (2010). 15. Gompers, P., Kovner, A., Lerner, J., et al. Performance persistence in entrepreneurship", Journal of Financial Economics, 96(1), pp. 18{32 (2010). 16. McKaskill, T., Raising Angel & Venture Capital Finance, Melbourne: Breakthrough Publications (2009). 17. Meyer, T. Venture capital in Europa - Mehr Pep fur Europas Wirtschaft", Deutsche Bank Research, Frankfurt (2006). 18. Dixit, A.K., Dixit, R.K., Pindyck, R.S., et al., Investment Under Uncertainty, Princeton University Press (1994). 19. Kodukula, P. and Papudesu, C., Project Valuation Using Real Options: A Practitioner's Guide, Fort Lauderdale, Florida: J. Ross Publishing (2006). 20. Bagheri, R., Rezaeian, A., and Fazlaly, A. A mathematical model to evaluate knowledge in the knowledgebased organizations", Scientia Iranica, Transaction E, Industrial Engineering, 22(6), pp. 2716{2721 (2015). 21. Daum, J. How to better exploit intangible asset to create value", The New Economy Analyst Report, 6 (2001). 22. Kamiyama, S., Sheehan, J., and Martinez, C. Valuation and exploitation of intellectual property", OECD Directorate for Science, Technology and Industry, STI Working Paper 2006/5 (2006). K. Fattahi et al./Scientia Iranica, Transactions E: Industrial Engineering 27 (2020) 3322{3337 3335 23. Hanel, P. Intellectual property rights business management practices: A survey of the literature", Technovation, 26(8), pp. 895{931 (2006). 24. Smith, G.V. and Parr, R.L., Intellectual Property: Valuation, Exploitation, and Infringement Damages, Hoboken/N.J. Wiley (2005). 25. Hsieh, C.H. Patent value assessment and commercialization strategy", Technological Foracasting & Social Change, 80(2), pp. 307{319 (2013). 26. Loop, D. and Lipfert, S., Patentbasierte Unternehmens _nanzierung , Bankpraktiker 12/2006, pp. 594{599 (2006). 27. Reilly, R.F. and Schweihs, R.P., Valuing Intangible Assets, Boston, McGraw Hill Professional (1998). 28. Battersby, G.J. and Grimes, C.W., Licensing Royalty Rates, Licensing Royalty Rates, Aspen Publishers Online (2012). 29. Roman, V.B., LOPES, M., Marques, A., et al. Technologies valuation methods applicable to technology transfer in Brazilian universities: a review", In International Conference on Industrial Engineering and Operation Management, Valladolid, Spain (2013). 30. Shane, S.A., Academic Entrepreneurship: University Spin-O_s and Wealth Creation, Edward Elgar Pub, New York (2004). 31. Stewart, T.A., The Wealth of Knowledge: Intellectual Capital and the Twenty-First Century Organization, Crown Business (2007). 32. Hall, G. Lack of _nance as a constraint on the expansion of innovatory small _rms", In: Barber, J.L., Metcalfe, J.S., Porteous, M., Eds., Barriers to Growth in Small Firms, Routledge, London (1989). 33. Storey, D.J., Understanding the Small Business Sector, 1st. Ed., Cengage Learning EMEA (1994). 34. Blackburn, R.A. High-technology new _rms: variable barriers to growth", International Small Business Journal, 13(3), pp. 103{105 (1995). 35. Festel, G., Wuermseher, M., and Cattaneo, G. Valuation of early stage high-tech start-up companies", International Journal of Business, 18(3), p. 216 (2013). 36. Wang, Z. and Tang, X. Research of investment evaluation of agricultural venture capital project on real options approach", Agriculture and Agricultural Science Procedia, 1, pp. 449{455 (2010). 37. Razgaitis, R., Valuation and Dealmaking of Technology-Based Intellectual Property: Principles, Methods, and Tools, John Wiley & Sons, Hoboken (2009). 38. Hunt, F., Mitchell, R., Phaal, R., et al. Early valuation of technology: real options, hybrid models and beyond", Journal of The Society of Instrument and Control Engineers, 43(10), pp. 730{735 (2004). 39. Kjaerland, F. A real option analysis of investments in hydropower-The case of Norway", Energy Policy, 35(11), pp. 5901{5908 (2007). 40. Lee, S.C. and Shih, L.H. Renewable energy policy evaluation using real option model - The case of Taiwan", Energy Economics, 32, pp. 67{78 (2010). 41. Batista, F.R.S., de Melo, A.C.G., Teixeira, J.P., et al. The carbon market incremental payo_ in renewable electricity generation projects in Brazil: a real options approach", IEEE Transactions on Power Systems, 26(3), pp. 1241{1251 (2011). 42. Lee, S.C. Using real option analysis for highly uncertain technology investments: the case of wind energy technology", Renewable and Sustainable Energy Reviews, 15(9), pp. 4443{4450 (2011). 43. Boomsma, T.K., Meade, N., and Fleten, S.E. Renewable energy investments under di_erent support schemes: a real options approach", European Journal of Operational Research, 220(1), pp. 225{237 (2012). 44. Detert, N. and Kotani, K. Real options approach to renewable energy investments in Mongolia", Energy Policy, 56, pp. 136{150 (2013). 45. Martinez-Cesena, E.A., Azzopardi, B., and Mutale, J. Assessment of domestic photovoltaic systems based on real options theory", Progress in Photovoltaics: Research and Applications, 21(2), pp. 250{262 (2013). 46. Abadie, L. and Chamorro, J. Valuation of wind energy projects: a real options approach", Energies, 7(5), pp. 3218{3255 (2014). 47. Kim, K.T., Lee, D.J., and Park, S.J. Evaluation of R & D investments in wind power in Korea using real option", Renewable and Sustainable Energy Reviews, 40, pp. 335{347 (2014). 48. Kroniger, D. and Madlener, R. Hydrogen storage for wind parks: a real options evaluation for an optimal investment in more exibility", Applied Energy, 136, pp. 931{946 (2014). 49. Jeon, C., Lee, J., and Shin, J. Optimal subsidy estimation method using system dynamics and the real option model: photovoltaic technology case", Applied Energy, 142, pp. 33{43 (2015). 50. Weibel, S. and Madlener, R. Cost-e_ective design of ring wall storage hybrid power plants: a real options analysis", Energy Conversion and Management, 103, pp. 871{885 (2015). 51. Zhang, M.M., Zhou, P., and Zhou, D.Q. A real options model for renewable energy investment with application to solar photovoltaic power generation in China", Energy Econ, 59, pp. 213{226 (2016). 52. Mart__n-Barrera, G., Zamora-Ram__rez, C., and Gonz_alez-Gonz_alez, J.M. Application of real options valuation for analyzing the impact of public R&D _nancing on renewable energy projects: A company's perspective", Renewable and Sustainable Energy Reviews, 63, pp. 292{301 (2016). 53. Chen, S.H., Xu, S.H., Lee, C., Xiong, N.N., and He, W. The study on stage _nancing model of IT project investment", The Scienti_c World Journal, 2014, pp. 1{6 (2014). 3336 K. Fattahi et al./Scientia Iranica, Transactions E: Industrial Engineering 27 (2020) 3322{3337 54. Chu, H., Ran, L., and Zhang, R. Evaluating CCS investment of China by a novel real option-based model", Mathematical Problems in Engineering, 2016, pp. 1{15 (2016). 55. Wang, J., Wang, C.Y., and Wu, C.Y. A real options framework for R&D planning in technologybased _rms", Journal of Engineering and Technology Management, 35, pp. 93{114 (2015). 56. Stuart, R. and Abetti, P.A. Start-up ventures: towards the prediction of initial success", Journal of Business Venruring, 2(3), pp. 215{230 (1987). 57. Doutriaux, J. Emerging high tech _rms: how durable are their comparative sturt-up advantages?", Journal of Business Venturing, 7(4), pp. 303{322 (1992). 58. Cooper, R.G. and Kleinschmidt, E.J. Benchmarking the _rm's critical success factors in new product development", Journal of Product Innovation Management: An International Publication of the Product Development & Management Association , 12(5), pp. 374{391 (1995). 59. Kakati, M. Success criteria in high-tech new ventures", Technovation, 23(5), pp. 447{457 (2003). 60. Chorev, S. and Anderson, A.R. Success in Israeli hightech start-ups; Critical factors and process", Technovation, 26(2), pp. 162{174 (2006). 61. Sadeghi, A., Azar, A., and Rad, R.S. Developing a fuzzy group AHP model for prioritizing the factors a_ecting success of High-Tech SME's in Iran: A case study", Procedia - Social and Behavioral Sciences, 62, pp. 957{961 (2012). 62. Jain, D., Garg, R., Bansal, A., et al. Selection and ranking of E-learning websites using weighted distance-based approximation", Journal of Computers in Education, 3(2), pp. 193{207 (2016). 63. Garg, S.R. and Kumar, R. Computational MADM evaluation and ranking of cloud service providers using distance-based approach", International Journal of Information and Decision Sciences, 10(3), pp. 222{234 (2018). 64. Amit, G., Ramesh, K., and Tewari, P.C. Ranking of inventory policies using distance based approach Method", World Academy of Science, Engineering and Technology, International Science Index 86, International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering, 8(2), pp. 395{400 (2014). 65. Sandhya, S. and Garg, R. Implementation of multicriteria decision making approach for the team leader selection in IT sector", Journal of Project Management, 1(2), pp. 67{75 (2016). 66. Garg, R. and Jain, D. Prioritizing e-learning websites evaluation and selection criteria using fuzzy set theory", Management Science Letters, 7(4), pp. 177{184 (2017). 67. Garg, R. Optimal selection of e-learning websites using multiattribute decision-making approaches", Journal of Multi-Criteria Decision Analysis, 24(3{4), pp. 187{196 (2017). 68. Garg, R., Sharma, R., and Sharma, K. MCDM based evaluation and ranking of commercial o_-the-shelf using fuzzy based matrix method", Decision Science Letters, 6(2), pp. 117{136 (2017). 69. Garg, R. and Arora, S. Performance evaluation and selection of _nancial fraud detection models using MCDM approach", International Journal of Recent Research Aspects, 4(2), pp. 172{178 (2017). 70. Bansal, A., Kumar, B., and Garg, R. Multi-criteria decision making approach for the selection of software e_ort estimation model", Management Science Letters, 7(6), pp. 285{296 (2017). 71. Garg, R. Performance evaluation and selection of software e_ort estimation models based on multi-criteria decision making method", International Journal of Recent Research Aspects, 4(3), pp. 252{257 (2017). 72. Jain, D., Garg, R., and Bansal, A. A parameterized selection and evaluation of E-learning websites using TOPSIS method", International Journal of Research & Development in, 22(3), pp. 12{26 (2015). 73. Garg, R., Sharma, R., and Sharma, K. Ranking and selection of commercial o_-the-shelf using fuzzy distance based approach", Decision Science Letters, 5(2), pp. 201{210 (2016). 74. Garg, R.K., Sharma, K., Nagpal, C.K., et al. Ranking of software engineering metrics by fuzzy-based matrix methodology", Software Testing, Veri_cation and Reliability, 23(2), pp. 149{168 (2013). 75. Garg, R., Kumar, R., and Garg, S. MADM-based parametric selection and ranking of E-learning websites using fuzzy COPRAS", IEEE Transactions on Education, 99, pp. 1{8 (2018). 76. Garg, R. and Jain, D. Fuzzy multi-attribute decision making evaluation of e-learning websites using FAHP, COPRAS, VIKOR, WDBA", Decision Science Letters, 6(4), pp. 351{364 (2017). 77. Zavadskas, E.K., Antucheviciene, J., Turskis, Z., et al. Hybrid multiple-criteria decision-making methods: A review of applications in engineering", Scientia Iranica, Transaction A, Civil Engineering, 23(1), p. 1 (2016). 78. Jasemi, M. and Ahmadi, E. A new fuzzy ELECTRE based multiple criteria method for personnel selection", Scientia Iranica, 25(2), pp. 943{953 (2018). 79. Bruno, A.V. and Tyebjee, T.T. The entrepreneur's search for capital", Journal of Business Venturing, 1(1), pp. 61{74 (1985). 80. Gompers, P.A. and Lerner, J., The Venture Capital Cycle, MIT press (2004). 81. Lukas, E., Molls, S., and Welling, A. Venture capital, staged _nancing and optimal funding policies under uncertainty", European Journal of Operational Research, 250(1), pp. 305{313 (2016). 82. Antikarov, V. and Copeland, T., Real Options: A Practitioner's Guide, Texere, New York (2003). K. Fattahi et al./Scientia Iranica, Transactions E: Industrial Engineering 27 (2020) 3322{3337 3337 83. Herath, H.S. and Park, C.S. Multi-stage capital investment opportunities as compound real options", Eng Econ, 47(1), pp. 1{27 (2002). 84. Kim, K., Park, H., and Kim, H. Real options analysis for renewable energy investment decisions in developing countries", Renewable and Sustainable Energy Reviews, 75, pp. 918{926 (2017). 85. Property, WIPO World Intellectual, Valuation of Early Stage Technologies: How to Reach a Starting Price" for Negotiating a TT Agreement, Noordwijk, Holanda (2011).