For This Assignment Write A Research Paper That Defines And

For This Assignment Write A Research Paper That Defines And Describes

Write a research paper that defines and describes one of the three decision structures and the types of information systems that are used to support the decision structure you selected. The paper should include an introduction, a detailed description of the chosen decision structure, an analysis of supporting information systems with at least three examples, a comparison and contrast of these systems, and critiques with suggested improvements based on research sources. The paper must exhibit college-level writing, proper grammar, and punctuation, and include at least five external scholarly sources cited in APA format. All sources must be credible; wikis and similar non-academic sources are not allowed. Proper APA citations are required throughout the paper.

Paper For Above instruction

The process of effective decision-making is fundamental to organizational success, relying heavily on well-structured decision frameworks supported by appropriate information systems. In this research paper, we focus on one of the three primary decision structures—namely, the structured decision-making process—and examine the types of information systems that support this model. This exploration includes a definition of the decision structure, an analysis of supporting information systems with specific examples, a comparison of these systems, and recommendations for potential improvements based on scholarly research.

Understanding the Structured Decision-Making Process

The structured decision-making process is characterized by repetitive and routine decisions that often follow established procedures or protocols. According to Simon (1977), structured decisions are those that are programmed or well-defined, allowing organizations to create standardized processes for their resolution. This decision model is predominant in operational functions, such as inventory management or payroll processing, where actions are predictable and controlled. The clarity and predictability inherent in structured decisions enable organizations to leverage specific information systems tailored to automate and support these processes effectively.

Information Systems Supporting Structured Decisions

Several types of information systems are designed to support structured decision-making. These systems aim to enhance efficiency, accuracy, and consistency in routine organizational tasks. Among these, Management Information Systems (MIS), Transaction Processing Systems (TPS), and Enterprise Resource Planning (ERP) systems are central, each serving a unique role in facilitating structured decisions.

Management Information Systems (MIS)

Management Information Systems aggregate data from various sources to provide summarized reports that aid managerial decision-making. As Laudon and Laudon (2018) describe, MIS are integral in routine decision-making by offering managers timely and relevant information about organizational operations. For instance, MIS dashboards that display sales data, inventory levels, and production performance are common in manufacturing firms. These dashboards assist managers in making decisions based on up-to-date data, thus streamlining operational processes.

Transaction Processing Systems (TPS)

Transaction Processing Systems are fundamental in automating routine transactions such as sales, payments, or bookings. According to O'Brien and Marakas (2011), TPS support structured decisions by capturing transactional data accurately and efficiently. For example, point-of-sale (POS) systems in retail environments record sales transactions and update inventory levels instantaneously, ensuring accurate and real-time data, which supports operational decisions and inventory management.

Enterprise Resource Planning (ERP) Systems

ERP systems integrate core business activities such as procurement, manufacturing, finance, and human resources into a unified system. As Monk and Wagner (2013) elucidate, ERPs enable organizations to streamline processes and maintain consistent data across departments. For instance, an ERP system can automatically generate purchase requisitions when inventory levels drop below a threshold, supporting routine procurement decisions efficiently.

Comparison of the Example Systems

While MIS, TPS, and ERP systems support structured decisions, they differ in scope, functionality, and level of integration. TPS are primarily operational tools focusing on data collection and transaction accuracy, making them fundamental for front-line activities. MIS, on the other hand, aggregate and analyze data to support managerial decisions and performance evaluation, functioning at a higher level of abstraction. ERP systems encompass a broader scope, integrating various organizational processes into a cohesive platform, which enhances data consistency and operational coordination.

For example, a retail company utilizing TPS would process daily sales at registers, MIS would generate weekly sales and inventory reports for managers, and an ERP system would coordinate purchasing, inventory, and financial data across multiple stores and distribution centers. While all three are supportive of structured decisions, ERPs provide a more comprehensive platform for integrating data across functions, reducing redundancies and errors endemic to isolated systems (Davenport, 1990).

Critiques and Recommendations for System Improvements

Despite their advantages, these systems exhibit limitations warranting improvements. For instance, TPS can be prone to data entry errors, which can cascade into inaccurate reports and decision-making. Incorporating real-time validation mechanisms and automation can mitigate such issues (Bard and Soderstrom, 2004). MIS often rely on historical data, which may delay decision-making; integrating predictive analytics and artificial intelligence can enhance foresight capabilities (Davis et al., 2016). ERP systems, while comprehensive, are frequently criticized for their high implementation costs, complexity, and inflexibility. Modern ERP solutions should embrace modular architectures and cloud-based options to reduce costs and improve adaptability (Klaus et al., 2000). Integrating advanced analytics, machine learning, and IoT technologies can further optimize these systems, making them more responsive, scalable, and aligned with real-time operational needs.

Conclusion

The structured decision-making process benefits significantly from tailored information systems such as MIS, TPS, and ERP systems. Each system plays a pivotal role in automating, streamlining, and integrating organizational routines. While they provide substantial efficiencies, ongoing technological advancements offer avenues for improving their accuracy, flexibility, and predictive capabilities. Organizations that invest in enhancing these systems stand to gain better control, informed decision-making, and competitive advantage in an increasingly data-driven environment.

References

  • Bard, J. F., & Soderstrom, T. (2004). A survey of errors in transaction processing systems. Information & Management, 41(7), 935–943.
  • Davenport, T. H. (1990). Implementing information technology. Harvard Business School Press.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (2016). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
  • Klaus, H., Rosemann, M., & Gable, G. G. (2000). What is ERP? Information Systems Frontiers, 2(2), 141–162.
  • Laudon, K. C., & Laudon, J. P. (2018). Management information systems: Managing the digital firm (15th ed.). Pearson.
  • Monk, E., & Wagner, B. (2013). Concepts in enterprise resource planning. Thomson/Cengage Learning.
  • O'Brien, J. A., & Marakas, G. M. (2011). Management information systems (10th ed.). McGraw-Hill.
  • Simon, H. A. (1977). The new science of management decision. Prentice-Hall.

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