Developing TOPSIS method using statistical normalization for selecting knowledge management strategies

Amin Zadeh Sarraf · Ali Mohaghar · Hossein Bazargani

82 citations0/0 files storedJournal of Industrial Engineering and Management

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Multi-Criteria Decision Making Decision Support System Applications Strategic Planning and Analysis

Abstract

Purpose: Numerous companies are expecting their knowledge management (KM) to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. Design/methodology/approach: An extension of TOPSIS, a multi-attribute decision making (MADM) technique, to a group decision environment is investigated. TOPSIS is a practical and useful technique for ranking and selection of a number of externally determined alternatives through distance measures. The entropy method is often used for assessing weights in the TOPSIS method. Entropy in information theory is a criterion uses for measuring the amount of disorder represented by a discrete probability distribution. According to decrease resistance degree of employees opposite of implementing a new strategy, it seems necessary to spot all managers’ opinion. The normal distribution considered the most prominent probability distribution in statistics is used to normalize gathered data. Findings: The results of this study show that by considering 6 criteria for alternatives Evaluation, the most appropriate KM strategy to implement in our company was ‘‘Personalization’’. Research limitations/implications: In this research, there are some assumptions that might affect the accuracy of the approach such as normal distribution of sample and community. These assumptions can be changed in future work. Originality/value: This paper proposes an effective solution based on combined entropy and TOPSIS approach to help companies that need to evaluate and select KM strategies. In represented solution, opinions of all managers is gathered and normalized by using standard normal distribution and central limit theorem. Keywords: Knowledge management; strategy; TOPSIS; Normal distribution; entropy

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 82 citations exist upstream.

References

1981Multiple Attribute Decision Making 1981Multiple Attribute Decision Making: Methods and Applications 2003Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS 1999What's your strategy for managing knowledge?2011Multiple Attribute Decision Making: Methods and Applications 1979Multiple Objective Decision Making ― Methods and Applications: A State-of-the-Art Survey 2006An extension of TOPSIS for group decision making 1995Multiple attribute decision making : an introduction

Cited by

2018Pharmacological therapy selection of type 2 diabetes based on the SWARA and modified MULTIMOORA methods under a fuzzy environment 2023Fuzzy Method Based on the Removal Effects of Criteria (MEREC) for Determining Objective Weights in Multi-Criteria Decision-Making Problems 2021Multi-criteria decision approach to select carbon dioxide and hydrogen sources as potential raw materials for the production of chemicals 2018TOPSIS Method Application for Decision Support System in Internal Control for Selecting Best Employees

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.