Identification of the clusters of employee brand using FIMIX-PLS and FCM
by N. Thamaraiselvan; P. Sridevi; B. Senthil Arasu; Thushara Srinivasan
International Journal of Business Forecasting and Marketing Intelligence (IJBFMI), Vol. 3, No. 2, 2017

Abstract: Ensuring sustenance of service brand using functional difference is arduous in this competitive era. Such brand difference is significantly based on service employees' interaction with customers. A favourable employee brand presented by employees to customers affords service organisations with competitive advantage. This study attempts to identify the optimum number and types of clusters in employee brand of Air India using two modern data mining techniques, viz., finite mixture partial least squares (FIMIX-PLS) and fuzzy c-means (FCM) clustering for decision making. Employees of Air India, Chennai Division were surveyed and four optimum numbers of clusters of employee brand were identified by both FIMIX-PLS and FCM. It was identified that the employees' knowledge of the desired brand (KDB) their satisfaction in terms of psychological contract (PC) varied across clusters. Quality training, developmental programs, internal communication and feedback systems must be focused and enhanced to increase the employees' KDB and PC.

Online publication date: Mon, 08-May-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Forecasting and Marketing Intelligence (IJBFMI):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email