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Article
Publication date: 7 November 2016

Mohammadali Abedini, Farzaneh Ahmadzadeh and Rassoul Noorossana

A crucial decision in financial services is how to classify credit or loan applicants into good and bad applicants. The purpose of this paper is to propose a four-stage hybrid…

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Abstract

Purpose

A crucial decision in financial services is how to classify credit or loan applicants into good and bad applicants. The purpose of this paper is to propose a four-stage hybrid data mining approach to support the decision-making process.

Design/methodology/approach

The approach is inspired by the bagging ensemble learning method and proposes a new voting method, namely two-level majority voting in the last stage. First some training subsets are generated. Then some different base classifiers are tuned and afterward some ensemble methods are applied to strengthen tuned classifiers. Finally, two-level majority voting schemes help the approach to achieve more accuracy.

Findings

A comparison of results shows the proposed model outperforms powerful single classifiers such as multilayer perceptron (MLP), support vector machine, logistic regression (LR). In addition, it is more accurate than ensemble learning methods such as bagging-LR or rotation forest (RF)-MLP. The model outperforms single classifiers in terms of type I and II errors; it is close to some ensemble approaches such as bagging-LR and RF-MLP but fails to outperform them in terms of type I and II errors. Moreover, majority voting in the final stage provides more reliable results.

Practical implications

The study concludes the approach would be beneficial for banks, credit card companies and other credit provider organisations.

Originality/value

A novel four stages hybrid approach inspired by bagging ensemble method proposed. Moreover the two-level majority voting in two different schemes in the last stage provides more accuracy. An integrated evaluation criterion for classification errors provides an enhanced insight for error comparisons.

Details

Kybernetes, vol. 45 no. 10
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 13 August 2018

Mona Jami Pour, Zahra Kouchak Zadeh and Nima Ahmad Zadeh

Today, knowledge extraction and sharing in the organizations have been positioned as one of the most significant managers’ priorities. However, despite huge investments in…

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Abstract

Purpose

Today, knowledge extraction and sharing in the organizations have been positioned as one of the most significant managers’ priorities. However, despite huge investments in knowledge management (KM) area, the failure rates of these projects are high. One of the main reasons for these failures is the lack of a roadmap and a methodology for KM strategic planning which assist organizations to develop an integrated and aligned plan with business strategies which eventually reduces project’s failure rate. Yet, despite the extension of KM domain, little studies were conducted on strategic topics and especially KM strategic planning. Therefore, the purpose of this study is to offer an integrated methodology for KM strategic planning.

Design/methodology/approach

This study introduces a methodology for KM strategic planning by using the mixed methods. At the first stage, along with a comprehensive literature review, some semi-structured interviews with KM experts were conducted and the obtained data have been analyzed using the thematic analysis. After that, a survey is conducted to validate the extracted dimensions and activities of the proposed methodology via experts’ viewpoints.

Findings

The results of this study indicate that the main phases of the KM strategic planning methodology are as follows: strategic review, strategic orientation, implementation and evaluation. In the proposed methodology, main phases along with their related activities and their implementation order are presented as a roadmap for applying KM initiatives strategically.

Research implications/implications

In KM planning strategically, all phases of strategic management along with their related activities must be considered simultaneously. The proposed methodology can assist KM policy-makers to identify and guide KM initiatives as well as to perform appropriate actions for progress. This study tries to develop a coherent roadmap for knowledge initiatives by a strategic approach.

Originality/value

One of the major reasons for the failure of many KM projects is the absence of a strategic planning methodology. A review of the KM literature shows that there are few studies, which adequately integrate strategic KM planning process, yet most researchers view KM planning as the most difficult and complex part of KM implementation process. This study aims to introduce a novel methodology to KM strategic planning comprehensively. The main contribution of this study is to develop a new integrated methodology for strategic planning that considers the strategy formulation aspects along with strategy execution and control aspects, synchronously.

Details

VINE Journal of Information and Knowledge Management Systems, vol. 48 no. 3
Type: Research Article
ISSN: 2059-5891

Keywords

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