seyedeh elahe adel rastkhiz; Ali Mobini Dehkordi; jahangir yadollahi farsi
Volume 23, Issue 1 , April 2019, , Pages 75-97
Abstract
Evaluating entrepreneurial opportunities exemplifies the decision-making under conditions of uncertainty. These evaluations mainly have been done in a complex and dynamic environment under true uncertainty. In contrast to risk and ambiguity, in true uncertainty not only all potential outcomes and their ...
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Evaluating entrepreneurial opportunities exemplifies the decision-making under conditions of uncertainty. These evaluations mainly have been done in a complex and dynamic environment under true uncertainty. In contrast to risk and ambiguity, in true uncertainty not only all potential outcomes and their assigned probabilities are unknown, but also it is not possible easily to estimate the probabilities and acquire knowledge about the results. In these situations, entrepreneurs evaluate opportunities based on minimal and inaccurate information, which is described by fuzzy variables, i.e. linguistic variables that do not have any clear boundaries. Hence, adopting a fuzzy approach, the purpose of this paper is to propose a model for evaluating entrepreneurial opportunities under conditions of uncertainty. This study is the first using fuzzy screening to formulate opportunity evaluation as a Multi-Expert Multi-Criteria Decision-Making (ME-MCDM) problem and it is innovative in this research area. In doing so, first, through a systematic literature review and focus group the authors identified entrepreneurs’ current solutions for evaluating opportunities under true uncertainty. Then, a ME-MCDM model has been suggested to evaluate opportunities and select between them. The model is based on fuzzy screening method and evaluates 12 opportunities by 15 experts in a medium entrepreneurial firm. R software has been used to perform calculations. With regard to experts’ aggregate evaluations, findings show that O6 and O11 have higher rating (better evaluation) among opportunities and considered as appropriate candidates for pursuing.
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Volume 14, Issue 4 , March 2011, , Pages 49-78
Abstract
Information systems decisions are of the main concerns of managers.
Existence of uncertainties and different objectives and attributes influence
the quality of decisions. Environmental uncertainties can challenge the
quality of IS investment decisions. Investment decisions, made without any
respect ...
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Information systems decisions are of the main concerns of managers.
Existence of uncertainties and different objectives and attributes influence
the quality of decisions. Environmental uncertainties can challenge the
quality of IS investment decisions. Investment decisions, made without any
respect to environmental changes, will loose their effectiveness as time
passes. IS investment decisions require attention to different attributes such
as return on investment, strategic competitiveness and user satisfaction.
Multi-attribute decision making (MADM) approaches can play an important
role to make investment decisions. This study aims to integrate scenario
planning (as a tool to meet environmental uncertainties), Axiomatic Design
(MADM approach) and Fuzzy Delphi method (experts opinions acquiring
and consensus tool) as a Hybrid Model to propose a new methodology to
make IS investment decisions about the outsourcing or insourcing of the
development of the information systems. A case study in IS investment has
been done. The case is about the selection of an ERP system in Iranian
National Oil Company (NOC).
Mansour Moemeni; Majid Esmaelian
Volume 10, Issue 4 , March 2007, , Pages 231-251
Abstract
The purpose of this study is to explain the ability of the simulation methodology to consider uncertainty of the multi criteria decisions making. The rank order of decision alternatives depends on two types of uncertainty:(1) uncertainty associated with the decision making judgment regarding each element ...
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The purpose of this study is to explain the ability of the simulation methodology to consider uncertainty of the multi criteria decisions making. The rank order of decision alternatives depends on two types of uncertainty:(1) uncertainty associated with the decision making judgment regarding each element of decision matrix described by distribution function, and (2) uncertainty regarding the future characteristics of the decision making environment described by a set of scenarios. Scenario is description of the decision making environment into some separate situations . Researchers concentrate on this type of uncertainty less than other types.
Both types of uncertainty are capable to opposite the rank of alternatives and decline the certainty of decision maker to the rank order of alternatives. In The present research, a simulation approach for handling both types of related uncertainty was described. The final conclusions showed that when uncertainty associated with the decision making judgment regarding each element of decision matrix increases, the probability of rank reversion and rank uncertainty increases too. Under these situations, the final ranking of the alternatives is probabilistic.
Payam Hanafizadeh; Seyyed Mohammad Arabi; Ali Hashemi
Volume 10, Issue 20 , June 2006, , Pages 137-170
Abstract
Time and uncertainty play a crucial role in the strategic planning process [1]. Many industries have collapsed or been knocked out of the competition due to unforeseen able changes in the environment and their forecast about the future failed. Organizations are faced with unpredictable changes in new ...
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Time and uncertainty play a crucial role in the strategic planning process [1]. Many industries have collapsed or been knocked out of the competition due to unforeseen able changes in the environment and their forecast about the future failed. Organizations are faced with unpredictable changes in new technologies, products and market places and their planned strategies are not able to respond to such a dynamic and changeable environment. These sorts of pressures are increasing in future because of the rapid developments of technology, economics and community.
Needless to say, the future is not predictable but it is noteworthy that organizations can prepare themselves to face such changes and this readiness results in competitive advantages. The more the uncertainties, the more considerable the competitive advantages of organizations devised robust and stable strategies against uncertainty will be.
This paper aims at introducing a method that enables organizations to draw up robust strategies in uncertain situations and leads to formulation of strategies to immunize them against environment changes.
The method put forth in this paper has combined 'scenario planning method' and 'fuzzy inference system' with traditional strategic planning by adopting a novel and creative approach. Using the values of uncertain factors in the external environment, this method designs some probable forthcoming scenarios of the organization and then based on fuzzy information defined by experts for fuzzy inference systems, defines a robust strategy to deal with the designed scenarios.
This method assists a manager and an organizational strategic planner in their evaluations of future environment and provides them with deep understanding of their
planned strategies to keep their competitive advantages in the unstable and unsettled future.
