Track: Industry 4.0 - Special Track

Abstract

The adoption of industry 4.0 concepts by companies is causing profound changes in all sectors, marked by the emergence of new business models, remodeling of production, consumption, transportation and delivery systems [11]. Society also expects the transformation of industrial production to achieve achievements in the three dimensions of sustainability, namely economic, environmental and social [8]. On the other hand, the adoption of industry 4.0 concepts implies risks and challenges for society, such as job losses and changes in educational standards [9]. Although there is no consensus recommendation on the pace of industry 4.0 deployment, it seems peaceful that the production chain of the oil and gas industry is lagging behind in this process when compared to other industrial sectors [5]. Decision support systems have been the subject of active research by organizations for their development [6], while important measures have been widely used as decision support indicators, such as information and risk analysis [4]. Considering this demand, the present research seeks to evaluate how professionals of the oil and gas industry production chain rank the risks, based on the economic, social, environmental, technical and legal dimensions, when making the decision for the implementation of industry 4.0 concepts. From the risk model for industry 4.0 within the context of sustainability, developed by Birkel et al. [2], identified after bibliographic research and complemented by other authors [1,3,7,8,9,10,11,12], all consulted in the Scopus database, a Likert questionnaire was developed that allowed a qualitative assessment of the degree of relevance of each risk. In order to ensure the qualification and significance of the sample, the questionnaire was sent only to professionals from oil and parapetroleum companies with experience in technology and/or innovation. The use of the sampling strategy for convenience described resulted in 103 questionnaires answered, out of a universe of 536 requests for completion forwarded. The analysis methodology consisted of using descriptive statistics, comparing data between groups of respondents and conducting non-parametric statistical tests, since the data subject to analysis were categorical, that is, nominal and ordinal. In this way, research in determining how deployment risks are hierarchical will serve as a decision support resource in management. The originality of the research lies in the possibility, analyzing the academic impact, of a new perspective of understanding the risks in the decision-making process for the implementation of industry 4.0 concepts within the oil and gas industry production chain.