Expert systems

Abstract Achieving the United Nations’ Sustainable Development Goals (SDGs) requires environmental, social, and governance (ESG) programs in the pharmaceutical industry. Using the Millennium Development Goals, the 2030 agenda aims to transform European Union companies toward sustainability. In pharmaceuticals, in particular, ESG programs come with complexities such as employee skills, corporate goals, and management expectations. Managing these programs effectively requires advanced technologies such as big data analytics (BDA) and dynamic capabilities (DC). In this study, DC theory is used to develop an architecture for managing ESG criteria, focusing on provenance, traceability, and availability. BDA’s role in ESG programs is explored, along with its use cases and benefits, and how DC drives success in ESG implementation. The study examined five pharmaceutical companies in Germany, Portugal, and Switzerland, all consulting the same firm for BDA systems, to identify the characteristics of effective BDA implementation. The research explores how BDA and DC jointly enhance ESG efforts, the essential skills needed, and how DC aids in real-time decision-making in BDA projects aligned with ESG standards. It highlights the BDA system’s accuracy and effectiveness in managing ESG programs, with DC as a pivotal facilitator. Findings reveal BDA’s value in operational efficiency and aligning business models with ESG goals, underscoring the need for diverse skills in BDA implementation and DC’s importance in integrating various managerial capacities into effective strategies. The study promotes a dynamic, data-driven approach in the pharmaceutical industry for managing complex ESG initiatives. It stresses continuous learning, adaptation, and integrating technological advances with ethical business practices. The research concludes by emphasizing BDA and DC’s vital roles in advocating ethical, socially responsible, and environmentally sustainable practices in the pharmaceutical sector, marrying technology with ethical business strategies.

Abstract This study seeks to answer the following research question: “What factors can explain the number of patent filing requests made by residents in Brazil at patent offices in Brazil, the United States, Europe, and triadic patent families?”. The methods used in this research are quantitative, using big data from private and public investments in Science and Technology, and about patent deposit numbers in Brazil from 2000 to 2017. A model of linear regression was performed and explains how these investments in Science and Technology influence patent deposit numbers. The results of this research study point towards the importance of universities, up and beyond the traditional training and education aspect of university activity. The importance of public and private innovation investments is also shown to be important. This study shows that the patent registrations in the different regions under analysis are affected by different factors. There is thus no single formula towards the creation of innovation output and governments would do well to continue to invest in higher education while also investing in public research and development activities. Additionally, and not least important, private entities should be continually encouraged to make innovation investments and favourable government policies need to thus exist for this to happen. Finally, the low numbers regarding patent filings in Brazil may be linked to institutional deficiencies in the country. Patent breaches may be difficult to punish, and the judicial system may be slow and untrustworthy, compared to the United States and to Europe—leading to diminished patent registrations in Brazil. A set of implications and recommendations for policy derived from this study and will be strategic for policymakers.