رویکرد ترکیبی با استفاده از SOM دو سطحی و رتبه بندی تحلیل سلسله مراتبی ترکیب شده و روش AHP / DEA-AR برای انتخاب بهینه تکنولوژی در حال ظهور امیدبخش

Emerging technologies are playing an important role in establishing competitive advantage for technology based companies. Selecting an efficient and important emerging technology to invest in is significant to the companies also. In this study, we propose a method for selecting optimal emerging technology which is efficient, important and the most suitable to a company’s actual levels of input resource among various emerging technology alternatives. In order to select optimal emerging technology, the proposed method uses two-level-SOM to cluster the emerging technology alternatives based on alternatives’ required levels of input resource. For selecting efficient and important promising emerging technology, the proposed method calculates emerging technology alternatives’ efficiency score by using AHP/DEA-AR and their importance score by using AHP rating method in each technology cluster generated by two-level-SOM. Finally, the proposed method selects optimal promising emerging technology according to a company’s actual levels of input resource and each emerging technology alternative’s combined scores which is calculated by adding its efficiency score and importance score. A Korean company’s case of selecting optimal promising nanotechnology is employed to illustrate the proposed method. The result shows that the proposed method can provide an effective and reasonable selection of optimal promising emerging technology.

Emerging technologies are technologies which have not yet demonstrated potential for changing the basis of competition (Hung & Chu, 2006). Emerging technologies have significant implications and profound consequences for firms, markets, government policy, and society (Hu, Hung, & Gao, 2011). Emerging technologies are also characterized by rapid development in terms of significance and development rate of new ideas and technologies (Van der Valk, Moors, & Meeus, 2009). Nowadays, many technology based companies try to use various emerging technologies in their products and services to contribute on value added streams and establish competitive advantages. Among so many emerging technologies, it is not easy to select an optimal promising emerging technology. To select an optimal emerging technology is difficult because many different emerging technologies need different requirements on the levels of input resource such as R&D capability, cost, etc. and the companies also have different levels of input resource capability. For selecting optimal emerging technology which is suitable to a company, consideration of the company’s actual levels of input resource is necessary. If a company selects a technology ignoring the difference between its own actual levels of input resource and the selected technology’s required levels of input resource, the selected technology cannot be carried out in reality. In this case, it is not an optimal technology to the company. Selecting a promising emerging technology is also difficult because of the increasing number and complexity of emerging technology alternatives, and the considerations of multi-criteria in technology selection. In order to select a promising emerging technology, emerging technology alternatives especially should be evaluated at many aspects such as efficiency or importance and so on. In technology selection, the information of technology alternatives should be collected under the predefined selection criteria, then evaluate the technology alternatives against each other based on the identified criteria (Lamb & Gregory, 1997). But many companies, especially many small and medium-sized enterprises (SMEs), they don’t have enough resources and capabilities to evaluate various emerging technologies and invest in several emerging technologies simultaneously. In this case, among so many emerging technology alternatives, companies should select an optimal promising emerging technology. In this study, we present a new method to select an optimal promising emerging technology which is efficient and important, and suitable to a company’s actual levels of input resource. In order to select an optimal emerging technology, the proposed method first uses two-level self-organizing map (two-level SOM) to cluster emerging technology alternatives with similar levels of input resource. Two-level SOM is a clustering method which is composed of self-organizing map (SOM) and K-means (Vesanto & Alhoniemi, 2000). In order to select promising emerging technologies, the proposed method combinedly uses AHP/DEA-AR and AHP rating method. Analytic hierarchy process (AHP)/Data Envelopment Analysis-Assurance Region (DEA-AR) is used to measure the efficiency of emerging technology alternatives by hybrid using AHP and DEA. The efficiency of emerging technology alternatives can be evaluated by comparing emerging technology’s input resource and output result. In AHP/DEA-AR, AHP is used first to set assurance region (AR) to restrict the weights’ distributions for using DEA-AR, then, DEA-AR uses the AR set by AHP to calculate the efficiency of emerging technology alternatives. The efficiency value is defined as DEA score in this study. AHP rating method is used to evaluate the importance of emerging technology alternatives, which is different from the traditional AHP. The importance of emerging technology alternatives can be evaluated by degree of society’s need and government’s support to an emerging technology. When there are a large number of alternatives and pair-wise comparison is impracticable, AHP rating method is particularly useful (Sueyoshi, Shang, & Chiang, 2009). In this study, we use AHP rating method instead of pair-wise comparison to evaluate importance of emerging technology alternatives because of the large number of emerging technology alternatives which are independent with each other. The importance value is defined as AHP score in this study. At last, the proposed method calculates each emerging technology alternative’s combined score by adding the alternative’s DEA score and AHP score. The promising emerging technology is selected according to combined scores of emerging technology alternatives. This study organizes the remaining structure as follows. In the literature review, technology selection, introduction of two-level SOM, DEA-AR and AHP rating method are introduced. The third section introduces the procedures of the proposed method. Then, the proposed method is applied to a case of the Korean company A’s optimal promising nanotechnology selection and the process of optimal promising nanotechnology selection is explained. The final section discusses the conclusion.

Selecting an optimal promising emerging technology to invest in is not easy during so many emerging technology alternatives, because different emerging technology alternatives have different requirement at the levels of input resource, and the increasing number and complexity of emerging technology alternatives. For a company, selecting an optimal promising emerging technology considering its own actual levels of input resource is very important, because an emerging technology which is suitable to the company’s actual levels of input resource and can be practicable is the optimal promising emerging technology to the company. Emerging technologies should also be evaluated comprehensively, such as efficiency and importance and so on. Especially, many small and medium-sized enterprises (SMEs) don’t have enough resources and capabilities to evaluate various emerging technologies and invest in several emerging technologies simultaneously. In this situation, a comprehensive evaluation to emerging technology alternatives is necessary to help the companies to select optimal promising emerging technology. In this study, under the consideration of a company’s actual levels of input resource and emerging technology’s efficiency and importance, we propose a combined method to help it select optimal promising emerging technologies. The proposed method clusters emerging technology alternatives based on ratings to emerging technology alternative’s required levels of input resource by two-level SOM, then in each cluster, applies AHP/DEA-AR to evaluate the efficiency of emerging technology alternatives and AHP rating method to evaluate importance of emerging technology alternatives. Then, an emerging technology alternative’s combined score is calculated. In each cluster, the emerging technology alternative with the highest combined score is selected as the cluster’s promising emerging technology. Finally, we make a guidance table to help a company to select optimal promising emerging technology. A company should decide a proper technology cluster whose required levels of input resource are most similar with the company’s actual levels of input resource by calculating the Euclidean distance. Under the consideration of own actual levels of input resource, then, select the proper cluster’s promising emerging technology as the optimal promising emerging technology to finish the process of emerging technology selection. We applied the proposed method to a Korean company A to help it to select optimal promising nanotechnology and the application result showed that the Korean company selected a nanotechnology which was not only efficient and important, but also suitable to the company’s actual levels of input resource. In the proposed method, the first salient point is that the emerging technology selected by the proposed method is more suitable to a company’s actual levels of input resource. This is very important for selecting emerging technology to invest in. The second one is the proposed method provides a comprehensive evaluation to emerging technology alternatives on both efficiency and importance. Therefore, we can conclude that the proposed method is a reasonable and effective technology selection method. With the proposed method, companies, especially the SMEs can select an optimal promising emerging technology.