Achieving Business Performance Via Implementation of Knowledge Management: A Comparative Study of MAKE and non-MAKE Companies

Achieving Business Performance Via Implementation of Knowledge Management: A Comparative Study of MAKE and non-MAKE Companies

Trevor Tin Shing LUI (University of Hong Kong, Hong Kong), Zhicheng LI (The University of Hong Kong, Hong Kong) and Samuel K.W. Chu (The University of Hong Kong, Hong Kong)
Copyright: © 2019 |Pages: 15
DOI: 10.4018/IJKM.2019100101

Abstract

This article explores whether organisations that have received the Most Admired Knowledge Enterprises (MAKE) award boast better business performance relative to those that have not received or participated in the award. This quantitative study is based on 59 MAKE award winners in 2009, along with 59 counterparts. Financial data were collected from publicly available annual reports for the period 2009-2016. Applying the Value Added Intellectual Coefficient (VAIC) methodology, regression models were developed to examine the associations and connections between MAKE and non-MAKE companies' Intellectual Capitals and their financial performance indicators. Based on correlation and linear multiple regression analysis, the VAIC components (HCE, SCE and CEE) have no statistical predictive trend for market value (MB). However, HCE, SCE and CEE were significant predictors of three corporate financial performance indicators (ROA, ATO and ROE). The group of non-MAKE companies demonstrates a higher VAIC value. There is no statistical significance between the two groups' business performance.
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1. Introduction

In today’s competitive world of globalisation, many companies and organisations believe that knowledge management awards are helpful not only in promoting their brands but also in improving their business performance (Porter & Kramer, 2002). This may or may not be the case; however, as business performance depends on a host of factors beyond a given award’s objectives and panel expertise (Akins, et al., 2005). Such factors include market competition, products’ or services’ perceived value to customers and operational efficiency and effectiveness (Grant, 2016). Traditional methods do not adequately measure Intellectual Capital (IC), as it is incredibly difficult to quantify (Zéghal & Maaloul, 2010). Another problem is that simple, commonly accepted measurements have yet to be developed (Valentine St Leon, 2002). Among the many IC-measuring models that have been developed, Pulic’s (2000) Value Added Intellectual Coefficient (VAIC™) model is widely accepted by companies because of its objectiveness and simplicity of calculation (Yu, et al., 2010; Firer & William, 2003).

To recognise companies that surpass peers in IC and wealth creation growth values, Teleos and the KNOW Network established the global Most Admired Knowledge Enterprises (MAKE) research program in 1998 (Chase, 2015). This research program quickly became an effective award system, recognising leading companies in regional, national and global categories. The MAKE award recognises organisations that excel in various areas and that commit to implementing KM theories (MAKE, 2016). Primarily, the award committee evaluates an organisation’s ability to increase shareholders’ wealth by translating tacit and explicit enterprise knowledge and IC into better products, services and solutions. It is the international benchmark for KM best practices. The winners of the global MAKE award are selected by an expert panel comprising business executives from Fortune 500 companies, leading KM practitioners and IC experts. Underlying the award is the expectation that effective use of IC and KM can enhance the performance of an organisation.

No solid proof exists that achieving an award increases productivity, employee and customer satisfaction or profits. The purpose of the present study is to explore whether companies that have received the MAKE award have higher business performance (higher revenue, higher profit, lower cost, lower employee turnover, etc.) relative to those that have not received or participated in the award (hereafter referred to as non-MAKE companies). Through a quantitative comparison of MAKE award winners’ financial data and non-MAKE companies’ data, this research aims to find out whether discrepancies exist in the business performances of MAKE award winners and non-MAKE companies.

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