421
Views
5
CrossRef citations to date
0
Altmetric
Relationship Quality in Services

Adapted customer relationship management implementation framework: facilitating value creation in nursing homes

, &
Pages 991-1003 | Published online: 29 Apr 2013
 

Abstract

This paper proposes a framework to support customer relationship management (CRM) implementation in nursing homes. This work critically considers existing studies, which conducted in-depth questionnaires to identify critical CRM features (termed value-characteristics) that were identified as potentially adding the most value to nursing homes if implemented. Although the existing research proposed an implementation framework, summary of, and inconsistent inclusion of value-characteristics, limits the practical use of this contribution during implementation. In this paper we adapt the originally proposed framework to correct perceived deficiencies. We link the value characteristics to operational, analytical, strategic and/or collaborative CRM solution types, to allow consideration in context of practical implementation solutions. The outcome of this paper shows that, practically, a ‘one solution meets all characteristic’ approach to CRM implementation within nursing homes is inappropriate. Our framework, however, supports implementers in identifying how value can be gained when implementing a specific CRM solution within nursing homes; which subsequently supports project management and expectation management.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 404.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.