Generic Model Base Design for Decision Support Systems in Revenue Management: Applications to Hotel and Health Care Sectors - Efficient Decision Support Systems: Practice and Challenges from Current to Future - page 185

We can thus characterize DSS in RM problems as Model-Driven DSS following the
framework of Power (2002). This author presents different DSS classifications and proposes
a framework of DSS that includes five basic types of DSS characterized by their dominant
component, user groups, purpose and enabling technology: Data-Driven, Model-Driven,
Knowledge-Driven, Document-Driven and Communications-Driven. With respect to
Model-Driven DSS, Power (2002) outlines that “Model-Driven DSS emphasize access to and
manipulation of a model.” (Power 2002)
In the next section we present the proposed generic modeling approach consisting in a
hierarchy of levels of abstraction, which provides the conceptual key to design a flexible
model base component of a RM DSS. The remaining sections of the chapter first describe the
model associated with each of the levels of the abovementioned hierarchy and show the
potential of this approach with applications to specific cases taken from the quite different in
nature Hotel and Health Care sectors. One of the reasons for including the Health Sector in
this analysis is to show the applicability of the approach in intrinsically multiobjective/
multicriteria settings (Gupta & Denton 2008; Nordgren 2009).

2. Hierarchical modeling approach

As stated earlier, the key question to address in order to surmount the barrier to the
successful utilization of DSS in RM problems is the intrinsic linkage between the algorithms
and the specific design of the business process. Our approach to tackle this barrier stems
from a hierarchical generic modeling approach of the business processes. A business process
model defines the way a particular infrastructure element is assigned to one of its potential
uses. In the example of a hotel, that would be the design of the room reservation process,
considering aspects like alternative distribution channels through which rooms can be
reserved, pricing process (prices that can only increase as the execution/arrival date
approaches vs. prices that can go either up or down), etc.
In order to explain the proposed modeling hierarchy, we establish a parallelism with a
simple example of a mathematical model as can be seen in Fig.1. There are three hierarchical
modeling levels:
 The business process metamodel level corresponds to the highest abstraction layer.

The generic model of the business processes related to infrastructure assignment issues
is defined, providing the basic elements and their relationships, so that, through
instantiation, the set of possible models is derived. In the example of the mathematical
model, in this level we would find a metamodel describing the building blocks of a
mathematical equation, such as variables and operators, as well as the definition of the
possible ways to combine these elements to constitute the two members of a
mathematical equation.

 The business process model level encompasses the direct instances of the metamodel

defined in the former level. In the mathematical example, in this level we would find
generic equations such as that represented in the Figure: a - b = c 2 , a , b , and c being
natural numbers.

 The business process instance level emerges as the instantiation of the former level, in

the sense that each process instance will originate from a process model by means of
assigning specific values to a subset of its generic elements. The instances will become
feasibility or optimization problems, with a defined objective in the latter case. The