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Fuzzy model of hesitant decision making in evaluating business plans under uncertainty (an approach to developing new products) | ||
Journal of Optimization in Industrial Engineering | ||
مقاله 1، دوره 16، شماره 2 - شماره پیاپی 35، آذر 2024، صفحه 1-13 اصل مقاله (935.96 K) | ||
نوع مقاله: Original Manuscript | ||
شناسه دیجیتال (DOI): 10.22094/joie.2023.1975398.2024 | ||
نویسندگان | ||
Amir Bahramipour؛ Sadegh Abedi* ؛ Alireza Irajpour | ||
Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran | ||
چکیده | ||
The current research was conducted with the aim of designing a Intuitionistic fuzzy model of hesitant decision making in the evaluation of business plans under conditions of uncertainty as an approach for the development of new products while various researches have been conducted on the development of new products based on innovation. According to the previous researches, decision-making in the uncertain environment for choosing exogenous variables of the business development model based on the development of new products was not observed. Also in the evaluation of economic plans, the parameters are usually considered as certain whereas the investigation of uncertainty is considerably important. In this research, the main goal is to investigate and find factors affecting the feasibility of new product development plans and finally to obtain a method for evaluating new product development plans. For this purpose, 12 people were selected from the elite community and experts of the chemical industry using the theoretical purposeful sampling method. The results of Intuitionistic fuzzy analysis have shown that 6 exogenous variables were chosen as key variables in the selection and development of a new product in the organization. In this research, Intuitionistic fuzzy analytic hierarchy method has been used to determine the importance of exogenous variables that experts have applied in determining their importance. The significant importance of exogenous variables are the rate of certainty of investment in product development (0.239), new product acceptance share in the market (0.275), new product development strategy (0.209), attracting funds for applied research factor (0.077), passing standards and requirements (0.136), and funding for product development research (0.061). The dynamic product development model, which is based on the cause and effect relationship needs to be designed and tested in future studies to simulate the current and future decision-making performance.. | ||
تازه های تحقیق | ||
The current research was conducted with the aim of designing a fuzzy model of hesitant decision making in the evaluation of business plans under conditions of uncertainty as an approach for the development of new products. The method of the current research was of a fuzzy type, for this purpose, 12 people were selected from the elite community and experts of the chemical industry using the theoretical purposeful sampling method. The results of fuzzy analysis have shown that 6 exogenous variables were chosen as key variables in the selection and development of a new product in the organization. In this research, to determine the importance of exogenous variables that experts have in determining their importance, fuzzy analytic hierarchy method has been used. The weighted importance of exogenous variables is the share of new product acceptance in the market (0.275), investment confidence in new product development (0.239), new product development strategy (0.209), the level of passing standards and requirements (0.136), attracting development research funds. Product (0.077) and absorption of applied research funds (0.061). The dynamic product development model, which is based on the cause and effect relationship, needs to be designed and tested in future studies to simulate the current and future decision-making performance | ||
کلیدواژهها | ||
Fuzzy model؛ decision making؛ dynamic model؛ product development | ||
مراجع | ||
Aljumah, A. I., Nuseir, M. T., & Alam, M. M. (2021). Traditional marketing analytics, big data analytics and big data system quality and the success of new product development. Business Process Management Journal, 27(4), 1108-1125.
Bailey, D.E., Leonardi, P.M., Chong, J. (2020). Minding the gaps: understanding technology interdependence and coordination in knowledge work. Organ.Sci. 21, 713–730.
Bibaud-Alves, J., El-Haouzi, H. B., Thomas, P., & Boucinha, V. (2019). Toward a sustainable new product development approach based on industry 4.0 assets. In Service Orientation in Holonic and Multi-Agent Manufacturing: Proceedings of SOHOMA 2018 (pp. 156-167). Springer International Publishing.
Barrane, F. Z., Ndubisi, N. O., Kamble, S., Karuranga, G. E., & Poulin, D. (2021). Building trust in multi-stakeholder collaborations for new product development in the digital transformation era. Benchmarking: An International Journal, 28(1), 205-228.
Chiu, Y. J., Hu, Y. C., Yao, C. Y., & Yeh, C. H. (2022). Identifying Key Risk Factors in Product Development Projects. Mathematics, 10(8), 1295.
Chan, T. H., Lee, Y. G., & Jung, H. (2021). Anchored differentiation: The role of temporal distance in the comparison and evaluation of new product designs. Organization Science, 32(6), 1523-1541.
Cooper, R. G. (2019). The drivers of success in new-product development. Industrial Marketing Management, 76, 36-47.
Dehghani, M., Abubakar, A. M., & Pashna, M. (2022). Market-driven management of start-ups: The case of wearable technology. Applied Computing and Informatics, 18(1/2), 45-60.
Ferreras-Méndez, J. L., Llopis, O., & Alegre, J. (2022). Speeding up new product development through entrepreneurial orientation in SMEs: The moderating role of ambidexterity. Industrial Marketing Management, 102, 240-251.
Globocnik, D., Faullant, R., & Parastuty, Z. (2020). Bridging strategic planning and business model management–A formal control framework to manage business model portfolios and dynamics. European Management Journal, 38(2), 231-243.
Gann, D.M., Salter, A.J. (2020). Innovation in project-based, service-enhanced firms: the construction of complex products and systems. Res. Policy 29, 955–972.
Graesch, J. P., Hensel-Börner, S., & Henseler, J. (2021). Information technology and marketing: an important partnership for decades. Industrial Management & Data Systems, 121(1), 123-157.
Huang, S., Zhang, J., Yang, C., Gu, Q., Li, M., & Wang, W. (2022). The interval grey QFD method for new product development: Integrate with LDA topic model to analyze online reviews. Engineering Applications of Artificial Intelligence, 114, 105213.
Ji, X., Gao, Q., & Wang, H. (2022). A bilevel-optimization approach to determine product specifications during the early phases of product development: Increase customer value and reduce design risks. Expert Systems with Applications, 188, 116012.
Knudsen, M. P., Von Zedtwitz, M., Griffin, A., & Barczak, G. (2023). Best practices in new product development and innovation: Results from PDMA's 2021 global survey. Journal of Product Innovation Management.
Koulinas, G. K., Marhavilas, P. K., Demesouka, O. E., Vavatsikos, A. P., & Koulouriotis, D. E. (2019). Risk analysis and assessment in the worksites using the fuzzy-analytical hierarchy process and a quantitative technique–A case study for the Greek construction sector. Safety science, 112, 96-104
Li, S. M., Chan, F. T., Tsang, Y. P., & Lam, H. Y. (2021). New product idea selection in the fuzzy front end of innovation: A fuzzy best-worst method and group decision-making process. Mathematics, 9(4), 337.
Laine, T., Korhonen, T., Martinsuo, M. (2020). Managing program impacts in new product development: an exploratory case study on overcoming uncertainties. Int. J. Proj. Manag. 34, 717–733.
Minderhoud, S., & Fraser, P. (2005). Shifting paradigms of product development in fast and dynamic markets. Reliability Engineering & System Safety, 88(2), 127-135.
Montero, J., Weber, S., Bleckmann, M., Atzberger, A., Wirths, L.,and Paetzold, K. (2019).Spare part production in remote locations throughAdditive Manufacturing enhanced by agile development principles,in2019 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), 1–8.
Mero, J., & Haapio, H. (2022). An effectual approach to executing dynamic capabilities under unexpected uncertainty. Industrial Marketing Management, 107, 82-91.
Neumann, W. P., Winkelhaus, S., Grosse, E. H., & Glock, C. H. (2021). Industry 4.0 and the human factor–A systems framework and analysis methodology for successful development. International journal of production economics, 233, 107992.
Qi, Y., Mao, Z., Zhang, M., & Guo, H. (2020). Manufacturing practices and servitization: The role of mass customization and product innovation capabilities. International Journal of Production Economics, 228, 107747.
Quigley, J. M., & Gulve, A. (2023). Modernizing Product Development Processes: Guide for Engineers. SAE International.
Qureshi, S.M., Kang, C. (2020). Analysing the organizational factors of project complexity using structural equation modelling. Int. J. Proj. Manag. 33, 165–176.
Rouf, S., Malik, A., Singh, N., Raina, A., Naveed, N., Siddiqui, M. I. H., & Haq, M. I. U. (2022). Additive manufacturing technologies: industrial and medical applications. Sustainable Operations and Computers, 3, 258-274.
Shaker, F., Shahin, A., & Jahanyan, S. (2022). Investigating the causal relationships among failure modes, effects and causes: a system dynamics approach. International Journal of Quality & Reliability Management, 39(8), 1977-1995.
Yan, T., Dooley, K. (2020). Buyer-supplier collaboration quality in new product development projects. J. Supply Chain Manag. 50, 59–83.
Zhang, Y., Khan, U., Lee, S., & Salik, M. (2019). The influence of management innovation and technological innovation on organization performance. A mediating role of sustainability. Sustainability, 11(2), 495. | ||
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