Model for the Incorporation of Big Data in Knowledge Management Oriented to Industry 4.0

Author(s):  
Lizeth Juliana Arenas Cárdenas ◽  
Whitney Fernanda Tenjo Ramírez ◽  
José Ignacio Rodríguez Molano
2021 ◽  
Vol 319 ◽  
pp. 01021
Author(s):  
Ettaibi Mohamed ◽  
Mokhtari Bouchaib

The objective of our paper is to transpose the Industrial Acceleration Plan 2.0 on the aeronautical industry in Morocco (IAM) by proposing a transition strategy to the aeronautical industry 4.0 (STIA 4.0). The latter will be based on the establishment of a transverse ecosystem (TSE) of knowledge management (KM) that will feed the innovation by strategic knowledge. The objective is to innovate through the exploitation of Big Data to implement the transverse ecosystem digital and renewable energy. This is justified by the fact that the digitization and decarbonization of industries have become the main vectors of competitiveness of companies in the aerospace industry 4.0. The choice of the latter, to conduct our study, is justified by the fact that it is a sector that requires digital resources to cope with its sophistication. Despite its complexity, it can be developed by own resources in the Moroccan context. That is why we have proposed this integrative strategy that integrates, in addition to digitalization, other resources (Barney, 1991) based on dynamic capabilities (Teece and all, 1997) and that takes into account the context and contextualization (Doha S. and Louitri A., 2020).


2017 ◽  
Vol 21 (3) ◽  
pp. 623-639 ◽  
Author(s):  
Tingting Zhang ◽  
William Yu Chung Wang ◽  
David J. Pauleen

Purpose This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are either knowledge intensive or not. Design/methodology/approach This study is based on an event study using data from two stock markets in China. Findings The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along. Research limitations/implications This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets. Originality/value Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.


Author(s):  
Renan Bonnard ◽  
Márcio Da Silva Arantes ◽  
Rodolfo Lorbieski ◽  
Kléber Magno Maciel Vieira ◽  
Marcelo Canzian Nunes

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