Financial Decision-Making


Annotated Bibliography: Financial Decision-Making

  • Doumpos, M., & Zopounidis, C. (2014). Introduction to financial decision-making. Multicriteria Analysis in Finance, Springer Briefs in Operations Research, 1-10.

The study provides a thorough discussion of the financial decision-making process as a whole. In particular, the scope of this article ranges from distinguishing features of financial decision problems to a brief overview of the most influential frameworks for dealing with the issue. However, the greatest emphasis is put on the importance of the salient financial decisions with respect to risk management strategies, financial modeling, and financial engineering. Apart from detailing several risk management initiatives, the authors have paid substantial attention to outlining multicriteria aspects of financial decisions, which have to be taken into account by the company in the decision-making process. The above-mentioned facts would be of great significance to Starbucks in order to ensure proper organization of its financial stability while minimizing the risks. Nonetheless, it should be noted that this research simply reviews existing models but does not evaluate which of them can be preferably used in the current market conditions. In this regard, the study may seem too general, and as a result, theorizing an array of techniques not focused but briefly. Hence, even though this article is of general knowledge, its findings are applicable and relevant for Starbucks to be able to reconsider and possibly reshape its approaches to decision-making in terms of finances.

  • Merigo, J. M., & Casanovas, M. (2011). Induced aggregation operators in the Euclidean distance and its application in financial decision-making. Expert Systems with Applications, 38(6), 7603-7608.

The research deals with Euclidian distance as the primary component of induced aggregation operators applicable in financial decision-making. To be more precise, the scholars have introduced, explained in detail and tested the induced Eucledian ordered weighted averaging distance (IEOWAD) as “a parameterizing family of aggregation operators” (Merigo & Casanovas, 2011, p. 7603) on the example of selection of the investments. The framework is grounded on the values of arguments and, as asserted by researchers, may be used with respect to several theories and disciplines, such as decision and fuzzy theory, statistics, engineering, economics, soft computing, to list a few. Since the hypothesis is a new or rather redeveloped model, it is not amply tested to be found absolutely appropriate to be used in the intended field. However, owing to the fact that the authors have justified its applicability regarding selection investment area of finances, Starbucks may be able to follow this strategy in this sphere.

  • Singh, A. K., & Parida, P. (2013). Soft computing in financial decision-making. Global Journal of Management and Business Studies, 3(2), 103-110.

The article underlines a vital role of proper financial decision-making concerning managing organizational resources and offers soft computing technique as an alternative to conventional statistical models. The centerpieces of the proposed method are Fuzzy Logic and Euclidean Distance concepts, providing “greater scope for evaluation of situations which are closer to the real world” (Singh & Parida, 2013, p. 104). Besides theorizing this technique, the authors have provided a detailed explanation of that how this framework works in practice. Specifically, this part involved model description, representation in formulas gradually, and a comprehensive discussion of the process of using this algorithm. As argued by the researchers, the model is appropriate for financial decision-making in any industry, with slight modifications in the algorithm and specific data necessary for the analysis. Therefore, it would be useful for implementing on Starbucks’ basis due to its comparable simplicity of application and high probability degree results. Nevertheless, this strategy has just been proposed, thus, holistic testing of its usage would be recommended to make sure that it really works as has been theorized and predicted. In any case, information from the article would be notable for Starbucks within financial dimension as, for instance, it is able to determine the gap between its ideal and actual performance or assess the competitors’ performance among other issues. The managers could have tested it and improved the model in accordance with specificities of their operational area and organizational performance.

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