مقاله انگلیسی رایگان در مورد مدیریت دانش در محصولات پیشرفته و رضایت مشتری – الزویر 2023

 

مشخصات مقاله
ترجمه عنوان مقاله مدیریت دانش در محصولات پیشرفته و رضایت مشتری
عنوان انگلیسی مقاله Knowledge management in high-tech products and customer satisfaction: The smartphone industry
نشریه الزویر
انتشار مقاله سال 2023
تعداد صفحات مقاله انگلیسی 13 صفحه
هزینه دانلود مقاله انگلیسی رایگان میباشد.
نوع نگارش مقاله
مقاله پژوهشی (Research Article)
مقاله بیس این مقاله بیس میباشد
نمایه (index) Scopus – DOAJ
نوع مقاله ISI
فرمت مقاله انگلیسی  PDF
ایمپکت فاکتور(IF)
5.910 در سال 2022
شاخص H_index 38 در سال 2023
شاخص SJR 0.736 در سال 2022
شناسه ISSN 2199-8531
شاخص Quartile (چارک) Q1 در سال 2022
فرضیه ندارد
مدل مفهومی دارد، تصویر 1 صفحه 4
پرسشنامه ندارد
متغیر دارد
رفرنس دارد
رشته های مرتبط مدیریت
گرایش های مرتبط بازاریابی – مدیریت دانش – مدیریت فناوری اطلاعات
نوع ارائه مقاله
ژورنال
مجله  مجله نوآوری باز: فناوری، بازار و پیچیدگی – Journal of Open Innovation: Technology, Market, and Complexity
دانشگاه University of Salerno, Fisciano, Italy
کلمات کلیدی مدیریت دانش، ثبت اختراع، واحد دانش، دانش محصول، رضای مشتری
کلمات کلیدی انگلیسی Knowledge management, Patent, Module knowledge, Product knowledge, Customer satisfaction
شناسه دیجیتال – doi
https://doi.org/10.1016/j.joitmc.2023.100012
لینک سایت مرجع https://www.sciencedirect.com/science/article/pii/S2199853123001142
کد محصول e17396
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فهرست مطالب مقاله:
Abstract
Introduction
Literature review
Methodology
Results
Discussions
Conclusions
References

بخشی از متن مقاله:

Abstract

     Knowledge management for high-tech products, based on innovative product architectures and components, is a critical issue for market satisfaction. Scientific research has widely investigated the competitive advantage that product knowledge owned by Original Equipment Manufacturers (OEMs) has on product innovation. Nonetheless, the linkage between OEMs’ accumulated knowledge on single modules and customer satisfaction is less explored. The article aims at identifying what level of knowledge OEMs should have on both the single modules and the whole product architecture to achieve better customer satisfaction. The research method uses text mining techniques on patent documents to detect associations of modules and product knowledge with patented technologies. Regression analyses are thereafter performed to test the linkage of such a knowledge with customer satisfaction using SPSS. The explorative analysis of the smartphone industry demonstrates that an effect on the final market is found for specific modules, such as application processor, camera and touchscreen controller.

Introduction

     In an era of globalization, featured by new digital technologies and extremely variable markets, products are becoming increasingly complex and customized (Cammarano et al., 2021, Cappa et al., 2021, Olsen and Tomlin, 2020). Effectively managing the complexity of high-tech products featured by modular architecture may require a specific level of knowledge. Knowledge management is an essential and strategic element for a company’s competitive advantage (Gloet and Terziovski, 2004, Pereira et al., 2021, Yang, 2010). In particular, companies performance is highly dependent on the exploitation of internal knowledge resources to create greater value for the end product (Alavi and Leidner, 2001). From managerial literature, several theoretical developments, such as the ‘Knowledge Based-View’, affirm that the innovative abilities of companies strictly depend on intellectual capital and knowledge (Lam et al., 2021, Subramaniam and Youndt, 2005, Xie et al., 2018b). Moreover, it is well-known that, in order to gain cost and production flexibility, many high-tech companies employ modular product architectures as a competitive strategy to manage product complexity (Garud and Kumaraswamy, 1995, Grant, 2005). Specifically, a modular product architecture simplifies the complexity of product development by defining the design of the single modules which will be integrated into the end product through standard interfaces (Baldwin and Clark, 2002).

Conclusions

     The study investigates the relationship between knowledge management, modular products and customer satisfaction in the smartphone industry. Patent data provides an indication of the technological knowledge possessed by the company, while customer satisfaction was measured through a total score based on online reviews and opinions. The use of text mining techniques supported the decomposition of a complex product into several modules. Specifically, the patent content analysis defined different levels of knowledge on the product and smartphone modules. Using this approach, it was possible to analyse the association between knowledge on single modules and customer satisfaction. The results provide a range of insights, indicating on which modules knowledge needs to be preserved for the OEM in order to increase customer satisfaction.

     The use of patent data to identify the stock of knowledge a corporation possesses is one of this study’s drawbacks. In fact, not all inventions are filed for patents and, aspects of tacit knowledge are not considered. Future research will aim to analyse other sectors with modular products such as automotive. A further direction of future research might involve analysis on a bigger and more recent sample of smartphones, also considering other modules besides the ten studied in this article.

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