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Decision Sciences



Decision Sciences or decision-making is one of the branches of advanced management science, and it focus on making decisions and defining suitable policies for various companies and institutions. It also cares about developing the knowledge, machine learning, statistical decision theory, operations research, forecasting, behavioral decision theory and cognitive psychology, tools, and methodologies necessary for projects management, in a way that provides economic and moral addition to the companies or institutions. As well as solving complicated problems related to the globalized economy, whether it was financial or legal, or related to communication problems, according to the methods of quantitative and statistical analysis and data processing and modern methodologies.

So, this science provides us with a set of answers to the following important questions such as :

  • How should a reasonable person make decisions ?
  • How do people really make decisions ?
  • How can we help people, especially managers, improve their decision making ?

Utility Of Decision Sciences:

Organizations make many informed decisions, such as increasing production capacity, improving human capital, entering a new market, etc. This indicates that managers make one of two main types of decisions: programmed (structured) and non-programmed (unstructured) decisions. While programmed decisions concern perfectly stable situations, non-programmed decisions concern the real situation, surrounded by uncertainties, risks and ambiguities. For optimal value creation, this paper succinctly states that robust decision sciences and analysis serve as a precursor.

The decision-making environment is constantly changing and organizations must make decisions that change in proportion to these environmental changes if they are to survive. The decision maker uses probability values to convert uncertainties and risks into perfect knowledge poles for making informed decisions. Models are true decision-making tools and are deterministic and probabilistic (or stochastic) for scheduled and unscheduled decisions respectively.

So that, real-world value optimization focuses on decisions in situations of pure uncertainty and risk, generating model adjustments for optimal value creation. So, models for optimal value creation under uncertainty and risk are suggested and organizations are advised to use professional decision scientists and analysts if the need arises.

Decision Sciences And Manuscript Policies :

Decision Sciences give helpful and advancing audits to creators within 2 months of the original copy accommodation date. To realize this objective, the diary keeps up strict approaches for composition accommodation and survey process.

To guarantee that as numerous articles of intrigued show up in each issue as conceivable, original copies submitted to Decision Sciences must not exceed 40 double-spaced pages, counting references, reference sections, tables and figures. Supplementary documents, such as study cases, may be distributed online at the time of publication.

Authors submitting their original copy to Decision Sciences for distribution thought must certify that :

  1. None of the contents of their original copy has been copyrighted, distributed, or acknowledged for distribution by another diary, or is beneath survey by another diary.
  2. Authors whose manuscripts utilize information that are detailed in any other composition, distributed or not, are required to inform the editor at the time of submission in a cover letter  clarifying the duplication.
  3. The manuscript uses suitable citations for the propagation of somebody else's unique words or expression of thoughts.
  4. All working papers, earlier drafts, and/or last adaptation of submitted compositions that are posted on a Website will be taken down amid the survey handle.
  5. The manuscript has not been already submitted to Decision Sciences for survey.

Decision Making Problems:

Multiple Attribute Decision Analysis (MADA) problems in the situation of Belief Group Decision Making (BGDM) are a special class of decision problems, where the attribute evaluations of each decision maker (DM) are represented by belief functions. In order to solve these special problems, the TOPSIS model (technique for order preference by similarity to ideal solution) is extended by three approaches, whereby group preferences are aggregated in different ways. Based on these three approaches, three extended TOPSIS models, the pre-model, post-model and inter-model, are developed and their procedures are elaborated step by step. The aggregation of group preferences in the three extended models depends on some rules or its modifications, certain social choice functions and certain average approaches. Furthermore, a numerical example clearly illustrates the procedures of the three extended models for the BGDM. 

Conclusion:

Indeed, it can be said that overall, the decision science that is interested in making decisions could be a handle including choices. The process in general, comprises of a few steps: recognizing issues, producing options, assessing choices, choosing an elective, actualizing the decision, and assessing decision adequacy (Lunenburg, 2010). Every step in decision making prepare is imperative and directors ought to consider it. Typically since administration objectives or targets cannot be accomplished without legitimate choice making process.