A Regression-Based "Patent Data Analysis" Approach: A Case Study for "Weapon Technology" Evaluation Process

被引:4
作者
Altuntas, Serkan [1 ]
Dereli, Turkay [2 ]
机构
[1] Yildiz Tech Univ, Dept Ind Engn, TR-34349 Istanbul, Turkey
[2] Hasan Kalyoncu Univ, Off President, TR-27010 Gaziantep, Turkey
关键词
Patents; Weapons; Defense industry; Data analysis; Linear regression; Companies; Market research; Linear regression model; patent analysis; technology evaluation; weapon technology; SOCIAL NETWORK ANALYSIS; DEFENSE INDUSTRY; KNOWLEDGE; FUTURE; FIRMS; PERFORMANCE; INNOVATION; DOCUMENTS; COMPANIES; GROWTH;
D O I
10.1109/TEM.2021.3088804
中图分类号
F [经济];
学科分类号
02 ;
摘要
Technology evaluation is one of the most essential tasks for today's companies to make correct decisions that will increase their competitiveness. To date, numeroushave been made to address technology evaluation in the literature. Nevertheless, none of them have built a technology map or classified technologies based on their effects on the competitive power of a company in practice. To overcome the limitations of previous studies, a regression-based patent data analysis is proposed here for technology evaluation in this article. To this end, the proposed approach builds a technology map and classifies the technologies into four classes with respect to the technology effect ratio, namely 1) very high effect class, 2) high effect class, 3) medium effect class, and 4) low effect class. The technology evaluation of weapon technology in the defense industry has been conducted to show how the proposed approach works in real life. A good technology management strategy can be selected among available alternatives by decision makers and managers using the proposed approach. The results show that the proposed technology evaluation process can be used effectively in practice.
引用
收藏
页码:3874 / 3886
页数:13
相关论文
共 75 条
[61]   Technology Forecasting Based on Semantic and Citation Analysis of Patents: A Case of Robotics Domain [J].
Qiu, Zhipeng ;
Wang, Zheng .
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2022, 69 (04) :1216-1236
[62]  
Ranaei S, 2014, PORTL INT CONF MANAG, P2924
[63]   Country survey X: Defence spending in Turkey [J].
Sezgin, S .
DEFENCE AND PEACE ECONOMICS, 1997, 8 (04) :381-409
[64]   Pakistan's defense industry: An effort towards self-reliance? [J].
Siddiqa-Agha, A .
DEFENCE AND PEACE ECONOMICS, 1999, 10 (04) :347-359
[65]   Visualizing patent statistics by means of social network analysis tools [J].
Sternitzke, Christian ;
Bartkowski, Adam ;
Schramm, Reinhard .
WORLD PATENT INFORMATION, 2008, 30 (02) :115-131
[66]   The future of the defence firm in small and medium countries [J].
Struys, W .
DEFENCE AND PEACE ECONOMICS, 2004, 15 (06) :551-564
[67]   Patent Value Analysis Using Deep Learning Models-The Case of IoT Technology Mining for the Manufacturing Industry [J].
Trappey, Amy J. C. ;
Trappey, Charles, V ;
Govindarajan, Usharani Hareesh ;
Sun, John J. H. .
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2021, 68 (05) :1334-1346
[68]   Using patent data for technology forecasting: China RFID patent analysis [J].
Trappey, Charles V. ;
Wu, Hsin-Ying ;
Taghaboni-Dutta, Fataneh ;
Trappey, Amy J. C. .
ADVANCED ENGINEERING INFORMATICS, 2011, 25 (01) :53-64
[69]   Combining neural network model with seasonal time series ARIMA model [J].
Tseng, FM ;
Yu, HC ;
Tzeng, GH .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2002, 69 (01) :71-87
[70]   Defense conversion, technology policy and R & D networks in the innovation system of Israel [J].
Vekstein, D .
TECHNOVATION, 1999, 19 (10) :615-629