Social Media in Business Decisions of MSMEs: Practices and Challenges

Social Media in Business Decisions of MSMEs: Practices and Challenges

Vikas Kumar, Pooja Nanda, Samira Tawangar
Copyright: © 2022 |Pages: 12
DOI: 10.4018/IJDSST.286686
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Abstract

Social media has progressively grown in the last century and is now seen as a potential opportunity for various purposes, including the decision-making. The present work explores how social media platforms such as Facebook, Twitter, and Instagram can be used to support the decision making process of MSMEs. The work is exploratory in nature, and relevant literature has been reviewed to identify the decision making approaches at different managerial levels and how they have been integrated with the social media applications. Specific examples of social media platforms have been discussed, considering the MSMEs' business environment. Along with the practices, the most important challenges to social media integration have also been presented.
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2. Changing Paradigms Of Organizational Decision Making

There are many ways in which decisions can be made in the professional world. Earlier, organizations used to make business decisions on the basis of surveys, interviews, group discussions and finally the wisdom of managers. However, this was a time consuming process and the decisions were not very optimal. Organizations began to computerize many of the operational aspects of their business in the early 1960s. Information systems were developed to incorporate applications such as: order processing, accounting, inventory control, payroll and payable accounts. Management Information Systems (MIS) originally had the goal of making the information accessible for decision-making purposes in transaction processing systems. However, these systems were very large and inflexible and the reports produced were usually big, thus limiting the effectiveness of these systems (Ackoff, 1967). Eventually, this led to the development of Decision Support Systems in 1980s. Decision Support Systems (DSS) can help managers perform tasks such as resource allocation, budget comparison with actual results, data base testing to assess operating results, revenue forecasting and scenario assessment (Power and Heavin, 2017).

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