Effect of different types of knowledge intensive business services on innovation and performance

IF 12.9 1区管理学 Q1 BUSINESS

Technological Forecasting and Social Change Pub Date : 2024-11-15 DOI:10.1016/j.techfore.2024.123886

Marlene Mendoza , Luis M. Molina , M. Teresa Ortega-Egea

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引用次数: 0

Abstract

In recent years, firms have increasingly used knowledge services provided by knowledge-intensive business services (KIBS), but evidence on their impact on customer outcomes is mixed. To explain these mixed findings, this research proposes two explanations: The mediating role of knowledge integration capability (KIC) and the differential impact of different types of KIBS. KIBS can be of different types: professional (P-KIBS), research and development (R&D-KIBS) and information and communication technology (ICT-KIBS). To test the hypotheses of the research model, data from 368 firms in a developing country (Ecuador) were collected using PLS-SEM software. The results show that the effect of KIBS use on customer performance is a more complex relationship than might be expected a priori, as it depends on several factors. First, the effect of P-KIBS on customer performance is mediated by the knowledge integration capability of the customer firm. Second, the effect of R&D-KIBS on innovation performance is direct but does not affect overall performance. Third, the results indicate that ICT-KIBS do not have a significant effect on customer performance. The analysis of these results indicates the need for further studies to understand the complexity underlying this relationship.

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不同类型的知识密集型商业服务对创新和绩效的影响

近年来，企业越来越多地使用知识密集型商业服务（KIBS）提供的知识服务，但有关这些服务对客户结果影响的证据却喜忧参半。为了解释这些参差不齐的研究结果，本研究提出了两种解释：知识整合能力（KIC）的中介作用和不同类型 KIBS 的不同影响。KIBS 可以分为不同类型：专业型（P-KIBS）、研发型（R&D-KIBS）以及信息和通信技术型（ICT-KIBS）。为了检验研究模型的假设，使用 PLS-SEM 软件收集了一个发展中国家（厄瓜多尔）368 家企业的数据。结果表明，使用 KIBS 对客户绩效的影响是一种比先验预期更为复杂的关系，因为它取决于多个因素。首先，P-KIBS 对客户绩效的影响是以客户企业的知识整合能力为中介的。其次，研发-知识创新支持系统对创新绩效的影响是直接的，但不影响总体绩效。第三，结果表明 ICT-KIBS 对客户绩效没有显著影响。对这些结果的分析表明，有必要开展进一步研究，以了解这种关系背后的复杂性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Technological Forecasting and Social Change Multiple-

CiteScore

21.30

自引率

10.80%

发文量

813

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