Technology management degree programs: Meeting the needs of employers

Becker, Pamela

doi:10.1109/picmet.2009.5261906

Cited by 2 publications

(2 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…MOT is a multidisciplinary approach based on engineering, science, and business. Although there are diverse approaches to MOT, this study addresses MOT in more general terms and proposes a classified technology matrix map of MOT based on previous MOT research (Becker, 2009;Chatratana, 2009;Cyert and Kumar, 1994;McDermott et al, 2001;Phaal et al, 2000). That is, we construct a matrix map of MOT by the MOT classification results.…”

Section: Technology Classification By Matrix Mapmentioning

confidence: 99%

Technology forecasting using matrix map and patent clustering

Jun

Park

Jang

2012

Industr Mngmnt & Data Systems

View full text Add to dashboard Cite

Purpose -The purpose of this paper is to propose an objective method for technology forecasting (TF). For the construction of the proposed model, the paper aims to consider new approaches to patent mapping and clustering. In addition, the paper aims to introduce a matrix map and K-medoids clustering based on support vector clustering (KM-SVC) for vacant TF. Design/methodology/approach -TF is an important research and development (R&D) policy issue for both companies and government. Vacant TF is one of the key technological planning methods for improving the competitive power of firms and governments. In general, a forecasting process is facilitated subjectively based on the researcher's knowledge, resulting in unstable TF performance. In this paper, the authors forecast the vacant technology areas in a given technology field by analyzing patent documents and employing the proposed matrix map and KM-SVC to forecast vacant technology areas in the management of technology (MOT). Findings -The paper examines the vacant technology areas for MOT patent documents from the USA, Europe, and China by comparing these countries in terms of technology trends in MOT and identifying the vacant technology areas by country. The matrix map provides broad vacant technology areas, whereas KM-SVC provides more specific vacant technology areas. Thus, the paper identifies the vacant technology areas of a given technology field by using the results for both the matrix map and KM-SVC. Practical implications -The authors use patent documents as objective data to develop a model for vacant TF. The paper attempts to objectively forecast the vacant technology areas in a given technology field. To verify the performance of the matrix map and KM-SVC, the authors conduct an experiment using patent documents related to MOT (the given technology field in this paper). The results suggest that the proposed forecasting model can be applied to diverse technology fields, including R&D management, technology marketing, and intellectual property management. Originality/value -Most TF models are based on qualitative and subjective methods such as Delphi. That is, there are few objective models. In this regard, this paper proposes a quantitative and objective TF model that employs patent documents as objective data and a matrix map and KM-SVC as quantitative methods.

show abstract

Section: Technology Classification By Matrix Mapmentioning

confidence: 99%

Technology forecasting using matrix map and patent clustering

Jun

Park

Jang

2012

Industr Mngmnt & Data Systems

View full text Add to dashboard Cite

show abstract

“…The significant amount of time respondents spent on project management activities and the increase in that time over the course of their careers indicate that this warrants more attention. The importance of project management skills have been highlighted elsewhere [2][3][4][5] , but these data further show the need for emphasis in project management. Creating a foundation for program graduates to be lifelong learners in project management would seem justified.…”

Section: Discussionmentioning

confidence: 96%

Tool Use and Activities of Practicing Engineers over Time: Survey Results

Johnson

Natarajarathinam

2011 ASEE Annual Conference &Amp; Exposition Proceedings

View full text Add to dashboard Cite

show abstract

Technology management degree programs: Meeting the needs of employers

Cited by 2 publications

References 19 publications

Technology forecasting using matrix map and patent clustering

Technology forecasting using matrix map and patent clustering

Tool Use and Activities of Practicing Engineers over Time: Survey Results

Contact Info

Product

Resources

About