Analyzing technological competencies in the patent-based supplier portfolio: introducing an approach for supplier evaluation using semantic anchor points and similarity measurements

INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT(2022)

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摘要
Purpose The purpose of this paper is the development of a patent-based supplier portfolio that can be used to evaluate and select suppliers on account of their technological competencies. Design/methodology/approach In addition to traditional approaches, the authors develop a supplier portfolio that characterizes suppliers according to the similarity between supplier's and OEM's technological competencies as well as their technological broadness. These variables are measured on the basis of patents, which constitute a valuable source of information in technology-driven industries. Contrary to existing binary measurement approaches, the authors' portfolio uses semantic analyses to make use of the specific information provided in the patents' texts. The authors test this method in the field of gearings, which is a key driver for the automotive industry. Findings The authors identify six generic positions, characterizing specific risks for an OEM to become either technologically dependent or dependent on suppliers' production capacities. For each position the authors develop specific management strategies in face of the aforementioned risks. The approach helps OEMs navigate in the competitive landscape based on the most recent and publicly available information medium. Originality/value This work explicitly applies the construct of technological competencies to supplier evaluation and selection on the basis of portfolio approaches. Furthermore, the authors improve the use of patents for supplier evaluation in two respects: First, the authors analyze OEMs and upstream suppliers on an organizational level. Second, the authors utilize advanced semantic analysis to generate variables for the measurement of the criteria mentioned above.
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关键词
Supplier selection, Supplier relationship management, Supplier portfolio, IP Management, Text mining, Automotive industry
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