The university technology transfer revolution in Saudi Arabia

2010 ◽  
Vol 35 (6) ◽  
pp. 585-596 ◽  
Author(s):  
Ahmed Alshumaimri ◽  
Taylor Aldridge ◽  
David B. Audretsch
Keyword(s):  
Saudi Arabia ◽  
Technology Transfer ◽  
University Technology Transfer ◽  
University Technology ◽  
The University

Priority Challenges of University Technology Transfer with Interpretative Structural Modeling and MICMAC Analysis

2020 ◽  
Vol 17 (05) ◽  
pp. 2050038
Author(s):  
Renissa S. Quiñones ◽  
June Anne A. Caladcad ◽  
Hubert G. Quiñones ◽  
Charena J. Castro ◽  
Shirley Ann A. Caballes ◽  
...  
Keyword(s):  
Technology Transfer ◽  
Geographic Distance ◽  
Structural Modeling ◽  
The Philippines ◽  
Complex Nature ◽  
University Technology Transfer ◽  
Joint Research ◽  
Micmac Analysis ◽  
University Technology ◽  
The University

Translating university technology via the university–industry route faces an array of challenges. Subsequently, understanding the interrelationships of these challenges hopes to provide a better outlook on the complex nature of the university technology transfer (UTT) process. Such an agenda remains a gap in the domain literature. To advance this oversight, this study intends to identify the UTT challenges and determine their complex contextual relationships. The interpretative structural modeling, together with the MICMAC analysis, was sequentially adopted to derive the overarching structure of the challenges of UTT. A case study in a public university in the Philippines was conducted to carry out these objectives. Findings show that time constraints, knowledge being too theoretical, high costs of managing joint research projects, complex organizational structure, institutional bureaucracy, geographic distance, and lack of national benchmark are driving challenges that influence other challenges in impeding UTT in the representative Philippine university. These findings provide policy insights to key decision-makers and stakeholders on the success of technology transfers.

scholarly journals Open Innovation with Fuzzy Cognitive Mapping for Modeling the Barriers of University Technology Transfer: A Philippine Scenario

2019 ◽  
Vol 5 (4) ◽  
pp. 94 ◽  
Author(s):  
Renissa Quiñones ◽  
June Anne Caladcad ◽  
Hubert Quiñones ◽  
Shirley Ann Caballes ◽  
Dharyll Prince Abellana ◽  
...  
Keyword(s):  
Technology Transfer ◽  
Cognitive Mapping ◽  
The Philippines ◽  
Complex Nature ◽  
University Technology Transfer ◽  
State University ◽  
Joint Research ◽  
Fuzzy Cognitive Mapping ◽  
University Technology ◽  
The University

The University technology transfer (UTT) process is hindered by various barriers to achieving a successful translation of innovative technologies from universities to industries and other partners. Identifying these various barriers and understanding their interrelationships would provide a better understanding of the complex nature of the UTT process, which may be considered as inputs to crucial decision-making initiatives. This paper addresses this gap by holistically determining UTT barriers and their intertwined relationships. Using the Delphi method and fuzzy cognitive mapping, a case study in a state university in the Philippines was conducted to carry out this objective. The Delphi process extracts 24 relevant barriers of UTT, out of 46 barriers obtained from a comprehensive review of the extant literature. The results show that misalignment between research and commercialization objectives is the barrier that was influenced most by the other barriers. In contrast, high costs of managing joint research projects in terms of time and money and institutional bureaucracy have the highest out-degree measures or are the barriers that influence other barriers the most. These findings provide guidelines to various stakeholders and decision-makers in understanding the existence of barriers in the formulation of strategies and initiatives for a successful UTT process.

Dynamic capabilities, subnational environment, and university technology transfer

2016 ◽  
Vol 16 (1) ◽  
pp. 35-60 ◽  
Author(s):  
Changhong Yuan ◽  
Yang Li ◽  
Cristina O. Vlas ◽  
Mike W. Peng
Keyword(s):  
Technology Transfer ◽  
Value Creation ◽  
Dynamic Capabilities ◽  
Institutional Environment ◽  
Future Research ◽  
University Technology Transfer ◽  
Value Capture ◽  
University Technology ◽  
The University ◽  
Dynamic Capabilities Perspective

University technology transfer allows universities to extract benefits from their research. We examine how universities can create and capture value from their technology creation and technology commercialization efforts by embracing a dynamic capabilities perspective. Our longitudinal analysis involves 829 universities and 3908 university-year observations in 30 subnational regions (provinces) in China during a 6-year period. Our findings reveal (1) that universities create more ideas and capture more licensing value through dynamic management and active orchestration of assets, (2) that a developed factor market accelerates value creation and commercialization, and (3) that a developed institutional environment at the subnational level stimulates value creation but inhibits value capture. These interesting findings justify a dynamic capabilities perspective of the university technology transfer process while opening avenues for future research.

ASSESSING UNIVERSITY TECHNOLOGY TRANSFER: A MEASURE OF EFFICIENCY PATTERNS

2008 ◽  
Vol 05 (04) ◽  
pp. 495-526 ◽  
Author(s):  
JISUN KIM ◽  
TIMOTHY ANDERSON ◽  
TUGRUL DAIM
Keyword(s):  
Data Envelopment Analysis ◽  
Technology Transfer ◽  
Transfer Efficiency ◽  
University Technology Transfer ◽  
Data Envelopment ◽  
New Approach ◽  
University Technology ◽  
Changing Patterns ◽  
Input Variables ◽  
The University

There have been very active and significant studies done in the area of university technologies transfer (UTT). One interested topic among them is to measure performance of the UTT. Data Envelopment Analysis (DEA) has been regarded as a proper approach to measure the university technology transfer efficiency (UTTE). However, current studies stay in identifying efficient and inefficient universities and related output or input variables which could contribute to improve their efficiencies. This study is intended to understand further how the universities recognized efficient are different and the changes of their performance over years. For this purpose, this study proposes a new approach, the efficiency pattern diagram, to identify changing patterns of the technology transfer of 17 efficient universities out of 51 US universities from 2001 to 2004. Five efficiency patterns are identified by this study: "newly emerging", "strengthening", "strong", "weakening", and "declining". The properties of each pattern and limitations of the approach are discussed with verification of the pattern by extending them to 2005.

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