How to Appropriate Value from General-Purpose Technology by Applying Open Innovation

2021 ◽  
pp. 000812562110417
Author(s):  
Jialei Yang ◽  
Henry Chesbrough ◽  
Pia Hurmelinna-Laukkanen
Keyword(s):  
Artificial Intelligence ◽  
Open Innovation ◽  
General Purpose ◽  
General Purpose Technology ◽  
Application Field ◽  
Closed Approach ◽  
Ibm Watson

Artificial intelligence increasingly attracts attention and investments. However, appropriating value from this general-purpose technology (GPT) can be difficult. To understand these challenges, this article analyzes why IBM failed to generate significant profits from IBM Watson Health despite its promising starting points. The findings suggest that, considering the characteristics of GPT, an overly closed approach for taking it to market contributed to the failure. Furthermore, conditions such as the immaturity and the complexity of the application field intensified the challenges. This study suggests that using a strong appropriability regime in open innovation can enhance the appropriation of value from a GPT.

The multifaceted dimensions of potent nanostructures: a comprehensive review

2021 ◽  
Author(s):  
Deepika Jamwal ◽  
Aashima Sharma ◽  
Rohini Kanwar ◽  
Surinder Kumar Mehta
Keyword(s):  
General Purpose ◽  
General Purpose Technology ◽  
Comprehensive Review

Nanoscience as a powerful general-purpose technology for commercialization.

scholarly journals Lessons from the COVID-19 Pandemic on the Use of Artificial Intelligence in Digital Radiology: The Submission of a Survey to Investigate the Opinion of Insiders

Healthcare ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 331
Author(s):  
Daniele Giansanti ◽  
Ivano Rossi ◽  
Lisa Monoscalco
Keyword(s):  
Artificial Intelligence ◽  
General Purpose ◽  
Point Of View ◽  
General Point ◽  
Thoracic Radiography ◽  
Digital Radiology ◽  
Electronic Survey ◽  
Radiology Technicians ◽  
Medical Radiology ◽  
Great Development

The development of artificial intelligence (AI) during the COVID-19 pandemic is there for all to see, and has undoubtedly mainly concerned the activities of digital radiology. Nevertheless, the strong perception in the research and clinical application environment is that AI in radiology is like a hammer in search of a nail. Notable developments and opportunities do not seem to be combined, now, in the time of the COVID-19 pandemic, with a stable, effective, and concrete use in clinical routine; the use of AI often seems limited to use in research applications. This study considers the future perceived integration of AI with digital radiology after the COVID-19 pandemic and proposes a methodology that, by means of a wide interaction of the involved actors, allows a positioning exercise for acceptance evaluation using a general purpose electronic survey. The methodology was tested on a first category of professionals, the medical radiology technicians (MRT), and allowed to (i) collect their impressions on the issue in a structured way, and (ii) collect their suggestions and their comments in order to create a specific tool for this professional figure to be used in scientific societies. This study is useful for the stakeholders in the field, and yielded several noteworthy observations, among them (iii) the perception of great development in thoracic radiography and CT, but a loss of opportunity in integration with non-radiological technologies; (iv) the belief that it is appropriate to invest in training and infrastructure dedicated to AI; and (v) the widespread idea that AI can become a strong complementary tool to human activity. From a general point of view, the study is a clear invitation to face the last yard of AI in digital radiology, a last yard that depends a lot on the opinion and the ability to accept these technologies by the operators of digital radiology.

An IBM PC Based Computer Program for the Analysis of Infrared Spectra

1991 ◽  
Vol 45 (10) ◽  
pp. 1739-1745
Author(s):  
Min J. Yang ◽  
Paul W. Yang
Keyword(s):  
Artificial Intelligence ◽  
Operating System ◽  
Computer Program ◽  
Infrared Spectra ◽  
Personal Computer ◽  
Research Laboratory ◽  
General Purpose ◽  
Disk Operating System ◽  
Interpretation System ◽  
Ibm Pc

A computerized infrared interpreter has been developed on an IBM personal computer (PC) running under the Microsoft disk operating system (DOS). Based on the original Merck Sharp & Dhome Research Laboratory Program for the Analysis of InfRared Spectra (PAIRS), this infrared interpreter, PC PAIRS+, is capable of analyzing infrared spectra measured from a wide variety of spectrophotometers. Modifications to PAIRS now allow the application of both artificial intelligence and library searching techniques in the program. A new algorithm has been devised to combine the results from the library searching and the PAIRS program to enhance the dependability of interpretational data. The increased capability of this infrared interpreter along with its applicability on a personal computer results in a powerful, general-purpose, and easy-to-use infrared interpretation system. Applications of PC PAIRS+ on petrochemical samples are described.

Investigating Determinants of Industry–University Collaboration in an Open Innovation Context: Comparative Evidence from an Exploratory Study

2021 ◽  
pp. 097172182110204
Author(s):  
Calin Florin Baban ◽  
Marius Baban ◽  
Adalberto Rangone
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Open Innovation ◽  
Exploratory Study ◽  
Correlation Matrices ◽  
Related Literature ◽  
Industrial Areas ◽  
The Impact ◽  
Intelligence Approach ◽  
Artificial Intelligence Approach

In an open innovation (OI) paradigm, universities are considered as important sources of external scientific knowledge for industry, and comparative study of such collaboration can result in more effective and efficient employment of OI. Within this framework, this study explores how the determinants of collaboration between industry and universities in an open context of innovation are addressed by firms within industrial areas. For this purpose, a conceptual framework of industry–university determinants in an open context of innovation is developed from the related literature. Taking into consideration the determinants integrated into the framework, this study compares motives, barriers, channels of knowledge transfer, benefits and drawbacks of such collaboration in two Italian and Romanian industrial areas. Comparative differences in each OI determinant between the firms from the two Italian and Romanian industrial areas are analysed. The associations among the study determinants are also investigated based on correlation matrices among the five determinants in both Italian and Romanian firms. An artificial intelligence approach based on fuzzy logic was developed to predict the impact of the study determinants on the perception of universities as a source for OI activities of firms.

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