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Prior knowledge, industry 4.0 and digital servitization. An inductive framework

机译:事先知识,行业4.0和数字伺服。 一个归纳框架

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Over the last few years digital servitization has become a very popular topic in the industrial marketing and technology management literature. The present article contributes to the extant literature on business models for digital servitization by investigating the roles and effects of prior technological knowledge. To date, this rich and growing body of literature has underestimated a crucial corporate asset for value creation, and that is firms' past experience and knowledge. Such a corporate heritage may have relevant implications for a firm's approach and decisions regarding digital servitization, however, especially if it is related to one (or more) of the I4.0 technologies. The research question posed in the present article is thus: how does a company's prior knowledge affect its digital servitization strategies? To answer this question, we conducted a multiple case study, collecting and analyzing primary and secondary data about Italian medium- to large-sized enterprises that had recently implemented digital servitization. The findings illustrate the different effects of the technological solutions adopted on the companies' business models, and delineate an inductive matrix with four different ideal-typical business models: expert industrializer; explorative solutioner; explorative industrializer; and expert solutioner.
机译:在过去的几年中,数字驾驶已经成为工业营销和技术管理文献中的一个非常受欢迎的话题。本文通过调查现有技术知识的作用和影响,为数字驾驶的商业模式有助于扩大文献。迄今为止,这种丰富的富裕和越来越多的文献已经低估了价值创造的至关重要的公司资产,这是公司过去的经验和知识。这种企业遗产可能对公司的方法和关于数字驾驶的决定有相关的影响,特别是如果它与I4.0技术的一个(或更多)相关。因此,本文提出的研究问题是:公司的先验知识如何影响其数字伺服化策略?为了回答这个问题,我们进行了多种案例研究,收集和分析了关于最近实施数字驾驶的意大利媒体至大型企业的主要和次要数据。调查结果说明了公司业务模式采用的技术解决方案的不同效果,并用四种不同的理想典型商业模式描绘了一种归纳矩阵:专家工业化器;探索方案;探索工程化;和专家解决方案。

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