Analysis of the Role of Global Information Management in Advanced Decision Support Systems (DSS) for Sustainable Development

Analysis of the Role of Global Information Management in Advanced Decision Support Systems (DSS) for Sustainable Development

Brij B. Gupta, Prabin Kumar Panigrahi
Copyright: © 2023 |Pages: 13
DOI: 10.4018/JGIM.320185
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Timely intelligent decision support systems (DSS) are increasingly important for the sustainable development of entrepreneurship. Global information management plays an important role in accurate DSS. Judgments can be made more quickly, accurately, and objectively thanks to the availability of large data and sophisticated artificial intelligence in the realm of quantitative smart decisions. In this context, this research analyzes the contribution of global information management for sustainable business development through DSS. This paper used the Scopus database to collect relevant research papers related to the research topic. This research helps researchers analyze the recent trend and development in the field of DSS in the context of global information management.
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People must make choices on a regular basis and sometimes in the split second that separates two options. Some judgments are crucial while others are not, and it is seldom possible to make a choice in isolation from the actions of others. Access to information and how that information is processed may also affect the quality of decisions. When more specific data are collected, a more comprehensive understanding can be built and better choices can be made. Due to this, there is a need for an intelligent decision support system that can help people make better decisions when they have limited access to relevant data and expertise (Zhou et al., 2015; Sarkissian & Tekli, 2021; Ren et al., 2021; Gaurav et al., 2022). To aid in the process of making decisions, organizations often use what is known as a “decision support system” (DSS), which is an information system. DSSs are used primarily to help the user at the strategic, tactical, and operational levels (Sriyanto et al., 2019; Almomani et al., 2022; Ginzarly, 2021; Wu et al., 2018).As everyone, from people to governments to NGOs to enterprises, relies on making sound and well-considered decisions. The ability to make good choices at the right moment is becoming more and more crucial in today’s world. Smarter, more timely judgments may be made with the help of cutting-edge technology like artificial intelligence (AI) (Hajjar & Tekli, 2022; Dhaini & Mansour, 2021; Xu et al., 2021; Deveci et al., 2022), machine learning (ML) (Tay & Mourad, 2020; Abbas et al., 2021; Gegres et al., 2022; Maroun et al., 2022), and big data (Slim et al., 2021; Wu et al., 2016; Kaur et al., 2021).

Researchers understand the importance of DSS at an early stage; therefore, they try to integrate the concept of DSS in most domains. Due to this, there are many definitions of DSS with respect to its application in the domain.

A number of distinct descriptions and taxonomies of decision support systems have also been pro- posed. Different writers classify them in different ways, some based to the general activities they support and others according to the technical component or driver that is the most important factor in their development. The methodologies, tools, and ideas for decision support, together with the data and players engaged at various organizational levels, are the primary subject of this in-depth examination of the incorporation of strategic sustainability in decision systems (Hallstedt et al., 2010; Prathiba et al., 2021). According to the definition of DSS, its characteristics keep on changing. However, decision- makers should evaluate performance as part of reviewing the sustainability process. This procedure is essential to ensure the sustainability process and to assist decision-makers in improving their operations on an operational, tactical, and strategic level. Some scholars have created a number of instruments us- ing a wide range of models to evaluate the corporate or strategic level of sustainability performance, but they have yet to find a suitable model for assessing operational-level sustainability (Sriyanto et al., 2019; Hadiguna, 2013).

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