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Article
Publication date: 1 December 2003

Henning Gebert, Malte Geib, Lutz Kolbe and Walter Brenner

The concepts of customer relationship management (CRM) and knowledge management (KM) both focus on allocating resources to supportive business activities in order to gain…

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Abstract

The concepts of customer relationship management (CRM) and knowledge management (KM) both focus on allocating resources to supportive business activities in order to gain competitive advantages. CRM focuses on managing the relationship between a company and its current and prospective customer base as a key to success, while KM recognizes the knowledge available to a company as a major success factor. From a business process manager’s perspective both the CRM and KM approaches promise a positive impact on cost structures and revenue streams in return for the allocation of resources. However, investments in CRM and KM projects are not without risk, as demonstrated by many failed projects. In this paper we show that the benefit of using CRM and KM can be enhanced and the risk of failure reduced by integrating both approaches into a customer knowledge management (CKM) model. In this regard, managing relationships requires managing customer knowledge – knowledge about as well as from and for customers. In CKM, KM plays the role of a service provider, managing the four knowledge aspects: content, competence, collaboration and composition. Our findings are based on a literature analysis and six years of action research, supplemented by case studies and surveys.

Details

Journal of Knowledge Management, vol. 7 no. 5
Type: Research Article
ISSN: 1367-3270

Keywords

Content available
Book part
Publication date: 18 April 2018

Andreas Herrmann, Walter Brenner and Rupert Stadler

Abstract

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Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

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Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

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Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

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Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

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Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

Abstract

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Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

Abstract

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Autonomous Driving
Type: Book
ISBN: 978-1-78714-834-5

Book part
Publication date: 13 December 2023

Lan Phuong Ho Dang

This chapter delves into the impact of digital initiatives on firms and sheds light on how they can be explained through market reactions and the resource/capabilities mechanism…

Abstract

This chapter delves into the impact of digital initiatives on firms and sheds light on how they can be explained through market reactions and the resource/capabilities mechanism. By providing a novel conceptual framework that reflects the potential impact of digital initiatives on the sensing, seizing and transforming capabilities of dynamic capabilities, this chapter reveals the tremendous potential of digital initiatives to help firms become more adaptive to their environment and create sustainable competitive advantages that elicit positive market responses. This conceptual framework represents an original contribution to the literature. It enhances the understanding of the resource-based view and efficient market hypothesis, providing a fresh perspective on the influence of digital initiatives on firm performance and the dynamic capabilities mechanism that has hitherto been overlooked. As a result, this chapter enables researchers to develop testable hypotheses that examine the causal relationships between digital initiatives, dynamic capabilities and market performance using robust quantitative research methods. Furthermore, this chapter offers valuable insights for managers seeking to develop a more focused approach to digital transformation and enhance their competitive advantage. By exploring the impact of digital initiatives on sensing, seizing and transforming capabilities, managers can gain a deeper understanding of how they can leverage digital initiatives to improve their organisational performance and respond more effectively to the demands of an ever-changing landscape.

Article
Publication date: 1 November 2006

Malte Geib, Lutz M. Kolbe and Walter Brenner

The aim of this paper is to identify key issues and successful patterns of collaborative customer relationship management (CRM) in financial services networks.

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Abstract

Purpose

The aim of this paper is to identify key issues and successful patterns of collaborative customer relationship management (CRM) in financial services networks.

Design/methodology/approach

The study takes the form of a multi‐case analysis.

Findings

The paper finds that key issues of CRM in financial services networks are redundant competencies of partnering companies, privacy constraints, CRM process integration, customer information exchange, and CRM systems integration. To address these issues, partnering companies have to agree on clear responsibilities in collaborative processes. Data privacy protection laws require that customer data transfer between partnering companies has the explicit approval of customers. For process integration, companies have to agree on process standards and a joint integration architecture. Web services and internet‐based standards can be used for inter‐organizational systems integration. Data integration requires the development of a joint data model. Either a unique customer identification number or a matching algorithm must be used to consolidate customer data records of partnering companies.

Research limitations/implications

Because of the limited number of case studies, generalizability is limited. The findings can serve as a starting point for researchers seeking to further explore the topic with quantitative methods.

Practical implications

The findings can be used by financial services networks to improve their collaborative CRM approaches.

Originality/value

The importance of collaborative CRM in business networks is likely to increase due to the continuing deconstruction of value chains not only in the financial services industry, but in other industries as well. Nevertheless, the topic has not received much attention in research.

Details

Journal of Enterprise Information Management, vol. 19 no. 6
Type: Research Article
ISSN: 1741-0398

Keywords

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