Using different pair-wise comparison scales for developing industrial strategies

Tsyganok, Vitaliy; Kadenko, Sergii; Andriichuk, Oleh

doi:10.1504/ijmdm.2015.070760

Cited by 11 publications

(28 citation statements)

References 22 publications

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“…(In the latter case, the pair‐wise comparison matrix will be incomplete.) The experiment, described in Tsyganok et al (), clearly speaks in favour of a multiscale approach. If an expert finds it confusing to mix several scales while evaluating one and the same set of objects, he or she is free to provide all the estimates in the same scale.To derive priorities from pair‐wise comparison matrices, we suggest using the combinatorial approach, described in Tsyganok () and mentioned in Tsyganok et al ().…”

Section: Methodology Description: Phases and Steps Of Problem Solutionmentioning

confidence: 94%

“…The experiment, described in Tsyganok et al (), clearly speaks in favour of a multiscale approach. If an expert finds it confusing to mix several scales while evaluating one and the same set of objects, he or she is free to provide all the estimates in the same scale.To derive priorities from pair‐wise comparison matrices, we suggest using the combinatorial approach, described in Tsyganok () and mentioned in Tsyganok et al (). The reasons are as follows: combinatorial method utilizes the redundancy of expert information most thoroughly; it proves to be an effective aggregation tool (in comparison to other aggregation methods), when it comes to group decision making, as shown in (Tsyganok, ); it can be used for incomplete pair‐wise comparison matrices as well as for complete ones; it can be used for aggregation of expert estimates, provided in scales with different numbers of grades; it involves a single‐phase priority vector calculation (in contrast to two‐phase procedures of aggregation of judgements [AIJ] and aggregation of priorities [AIP], described, for instance, in Forman and Peniwati, ).…”

Section: Methodology Description: Phases and Steps Of Problem Solutionmentioning

confidence: 99%

“…At the lowest level of the hierarchy there are “elementary” or atomic subgoals that can be directly influenced by the decision maker (we call them projects P = { P i ; i = 1, … , n }—see problem statement above). After Stage 4, each of the edges in the hierarchy is assigned a weight, calculated by means of the AHP‐based combinatorial method using group pair‐wise comparisons (as described in Tsyganok et al, ): w = { w 1 , … , w N }, where N is the number of edges in the hierarchy graph.Function E ( S ) is calculated on the basis of these weight values (priorities) and project implementation levels { S i ; i = 1, … , n } at every given moment of time t . Priorities w = { w 1 , … , w N } are already calculated, and they remain constant.…”

Section: Methodology Description: Phases and Steps Of Problem Solutionmentioning

confidence: 99%

“…Its research has been applied as part of decision-making and strategic planning processes in various organizations, domains, and industries. Examples include project selection by a Ukrainian subsidiary of Soros Foundation ("Revival" foundation), project selection by the United Nations Development Programme office in Ukraine, assessment of higher educational establishments by the Ministry of Education and Science of Ukraine (Totsenko, Kadenko, & Sigal, 2008), evaluation of inspectors at high-risk technological objects (Tsyganok & Kadenko, 2010a), and efficiency evaluation of the National Space Programme of Ukraine (Tsyganok, Kadenko, & Andriichuk, 2015).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Usage of multicriteria decision‐making support arsenal for strategic planning in environmental protection sphere

Tsyganok

Kadenko

Andriychuk

et al. 2017

Multi Criteria Decision Anal

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This paper outlines an approach to strategic planning, based on decision‐making support methods. It provides a description of a step‐by‐step procedure, allowing the decision maker to build a strategy, targeted at solution of some weakly structured problem or at achievement of some complex goal, influenced by multiple tangible and intangible criteria. Criteria are formulated by experts and arranged into a hierarchy, as prescribed by the analytic hierarchy process. Relative weights of criteria are calculated on the basis of expert estimates, using the combinatorial approach, which is, in a way, an extension of analytic hierarchy process toolkit. In the context of this paper, a strategy is defined as the optimal way of currently available resource distribution among specific factors or projects, which influence the main goal of a strategic plan. Each project is characterized by certain funding volume constraints (minimum and maximum resource amounts) as well as time frames (launching and completion or termination dates). As an example of implementation of our approach, we consider a case of resource distribution among environmental projects.

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Section: Methodology Description: Phases and Steps Of Problem Solutionmentioning

confidence: 94%

Section: Methodology Description: Phases and Steps Of Problem Solutionmentioning

confidence: 99%

Section: Methodology Description: Phases and Steps Of Problem Solutionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Usage of multicriteria decision‐making support arsenal for strategic planning in environmental protection sphere

Tsyganok

Kadenko

Andriychuk

et al. 2017

Multi Criteria Decision Anal

View full text Add to dashboard Cite

show abstract

“…This matrix is used to solve a linear programming problem to find corresponding weights and scores. There are approaches which allow to combine different scales in pairwise comparisons as well (Tsyganok et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

ORCON - a tool for analysis of ordinal consistency in a pairwise comparison matrix

Moshkovich

Mechitov

2017

IJMDM

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Decision makers are often asked to make pairwise comparisons in the process of decision analysis with multiple criteria. Experiences show that decision makers make errors in expression of their judgements leading to ordinal and/or cardinal inconsistency in the comparison of objects. If results are highly inconsistent, the revision of a decision maker's comparisons should be carried out. The process may be quite complicated and usually is not part of the method. Ordinal consistency is often the first step to the success in many decision processes. We propose ORCON -an Excel-based tool that provides: 1) record of all cycles in the matrix of pairwise comparisons; 2) a list of all possible changes leading to consistency; 3) way to carry out those changes. The process is illustrated through ORCON application in a multi-criteria selection task.

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Significance of the order of pair‐wise comparisons in Analytic Hierarchy Process: an experimental study

Andriichuk,

Kadenko,

Tsyganok

2024

Multi Criteria Decision Anal

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The article describes an approach, ensuring higher credibility of expert estimation results, based on specific order of pair‐wise comparisons. The order of pair‐wise comparisons is, in its turn, based on the distance between estimated objects in the ranking. According to the suggested approach (and some human psychophysiological features), the most ordinally distant objects should be compared before ordinally closer ones. In order to empirically confirm this assumption, a special experiment involving real experts has been conducted. The results of the experiment indicate that if objects are presented to the expert for comparison in the suggested order, then in the majority of cases relative weights of objects, obtained using eigenvector method, most adequately reflect this expert's priorities. Moreover, pair‐wise comparison matrices constructed using the suggested comparison order tend to be slightly more consistent. The suggested approach to re‐ordering of pair‐wise comparisons can be applied as part of the AHP algorithm in weakly structured subject domains, influenced by multiple intangible criteria. It also provides conceptual basis for reduction of the number of pair‐wise comparisons, required to obtain credible results, in AHP without loss or distortion of expert data. It can also be used for modification of combinatorial pair‐wise comparison aggregation method, based on spanning tree enumeration. And, finally, it will improve the overall multi‐criteria decision‐making process in diverse subject domains, characterized by high uncertainty levels.

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Using different pair-wise comparison scales for developing industrial strategies

Cited by 11 publications

References 22 publications

Usage of multicriteria decision‐making support arsenal for strategic planning in environmental protection sphere

Usage of multicriteria decision‐making support arsenal for strategic planning in environmental protection sphere

ORCON - a tool for analysis of ordinal consistency in a pairwise comparison matrix

Significance of the order of pair‐wise comparisons in Analytic Hierarchy Process: an experimental study

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