Defense of the Thesis of Gorka Mendizabal Arrieta

Back

Defense of the Thesis of Gorka Mendizabal Arrieta

Thesis

Defense of the Thesis of Gorka Mendizabal Arrieta

Thesis title: After-sales services based on industrial data: digitization, monetization and data lifecycle. Obtained the qualification SOBRESALIENTE.

2024·07·22

$titulo.getData()


On July 12, the doctoral student Gorka Mendizabal Arrieta made the reading of the Doctoral Thesis entitled: After-sales services based on industrial data: digitization, monetization and data lifecycle.

Director: Dr.  Eduardo Castellano Fernández. (MIK – Mondragon Unibertsitatea-Business Faculty)

Summary of the thesis:

Companies in the industrial sector are facing significant digitalisation and automation processes, where Industry 4.0 (I40), servitisation and Big Data offer the possibility of creating new organisational and business models. Thus, after-sales service models based on industrial data are gaining more prominence in the strategy of manufacturing companies. In this context, it is of great interest to understand the impact of I40 and digitalisation on such organisations, as well as to generate tools for companies to develop a data-driven management culture.

To respond to this challenge, this thesis proposes three related but independent research projects. The first one aims to deepen the impact of the Fourth Industrial Revolution on Small and Medium Enterprises (SMEs) and Large Enterprises. Specifically, 124 organisations in Germany and the Czech Republic were analysed. The results show that large enterprises are better able to cope with the challenges posed by I40 and digitalisation than SMEs.

The second one determines the most characteristic features of data lifecycle models in the industrial sector, based on the different models proposed by the scientific literature. In terms of the results obtained, it is concluded that there is no consensus among researchers on the terminology and conceptualisation of data lifecycle models.

Finally, the third study focuses on the development of an innovative conceptual framework and the proposal of a pricing model for industrial data. Specifically, the case of a manufacturing cooperative dedicated to the manufacture and sale of industrial machines that produce plastic packaging has been analysed. It is concluded that there are four components that affect price allocation, namely: quality, entropy, value and market actors. At the same time, variables such as supply price, data valuation, CRI, data entropy and data quality are relevant.