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Top1. Introduction
Information and communication technologies (ICTs) are undoubtedly useful for businesses. However, testing new ICTs is not always cost effective. Business decision makers can be reluctant to incur the costs (not only financial) generated by the introduction of new ICTs, because even if a technology predicts a capital gain, it is not guaranteed that this will offset the integration and operation costs (Kleis, Chwelos, Ramirez, & Cockburn, 2012; Stratopoulos & Dehning, 2000; Xia, 2015).
On the one hand, this reluctance may deprive companies of useful technologies, whereas on the other hand, it may restrain research into these technologies. The objective of the model presented in this paper is to allow the simulation of the value generated by ICT in companies.
As technologies and business vary considerably, this work focuses on the technology of the Business Model Ontology (BMO) (Andersson et al., 2006) and the business function of Customer Relationship Management (CRM) (Reinartz, Krafft, & Hoyer, 2004).
These are not random choices, as the technology of ontologies is still relatively rare in business. The Business Model is an abstract concept that can particularly benefit from the representational capability of ontologies. According to (Osterwalder, 2004), the Business Model consists of four pillars:
The “customer interface” corresponds to CRM, and is a necessary component in creating, delivering, and capturing value in companies.
Simulating the impact of using a BMO for CRM requires the use of a model that is as generic as possible. This model must have a sufficient level of detail to achieve significant results when implemented as a simulator.
An extreme level of granularity is not always needed, but the model must be sufficiently detailed to perceive the positive or negative impact of the BMO in a company.
The authors’ hypothesis is that the positive or negative impact of this technology depends on the business type, its environment, and the relevant resources and policies.
The system must be able to represent the different alternatives. For example:
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Business type: a digital service company will have different communication channels to a car manufacturer.
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Environment: latency can be introduced and customers set according to the specific behavior of individuals from different countries.
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Resources: determined by the number of available employees.
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Policies: determined by the distribution of tasks to employees and the allocation of resources.
The following section discusses the prerequisites (background) for this study. Section 3 introduces the approach used to design the model. Sections 4 and 5 describe the model, agents, and system interactions. Section 6 presents application cases with and without BMO. Section 7 briefly discusses some related works, before Section 8 presents a summary and authors conclusions.
Top2. Background
2.1. CRM Definition
CRM is a popular area in the business and marketing literature. Researchers have described the basics of the field as well as its origins, evolution, and impact on business performance, and have studied problems such as the improvement and implementation of CRM strategies (Alhawari, Alryalat, & Hunaiti, 2016).
Zablah (Zablah, Bellenger, & Johnston, 2004) defined CRM as “…an ongoing process that involves the development and leveraging of market intelligence for the purpose of building and maintaining a profit-maximizing portfolio of customer relationships.” (p. 480)
There are three main forms of CRM: Strategic, Analytical, and Operational. A fourth Collaborative form is sometimes distinguished from the Operational (Geib, Reichold, Kolbe, & Brenner, 2005; Iriana & Buttle, 2007; Rababah, Mohd, & Ibrahim, 2011). This distinction is useful to subdivide the model into programmable units (in terms of computing) as autonomous software agents that can interact, communicate, and collaborate in the manner of human agents within a company.