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 184

distribution channels through which rooms can be reserved, quota allocation and
reallocation to each channel, cancellation procedures and penalizations, pricing process
(prices that can only increase as the execution/ arrival date approaches vs. prices that
can go either up or down).
 The decision variable(s) to be optimized. In a hotel reservation process, the decision to
be taken might be when (how long before the actual stay date) to switch from a lower
price to a higher price, or alternatively consider this anticipation as a fixed parameter
and try to optimize which price to switch to.
 The business objective(s) to achieve. In the hotel sector it will typically be profit; given
its essentially fixed costs, this translates into managing/ maximizing revenue, hence the
“Revenue Management” term. In other service sectors the optimization objective is not
so clear, as it is the case of the Health Care sector. Nordgren (2009) discusses the
complexity of the multi-faceted concept of value in this sector and thus the number of
objectives that should be simultaneously taken into account when trying to find a match
between the service providers and the potential users.
Although potential benefits to be gained from the use of advanced RM techniques to guide
the allocation of infrastructures are substantial, in many cases merely applying the existing
algorithms adds limited value. In its thorough literature review on RM research, Chiang et
al . (2007) highlight the resulting complexity and difficulty of developing and implementing
RM projects, to the point of suggesting that these projects are viewed as strategic, as
opposed to tactical activities. There is a barrier to the adoption of RM algorithms, derived
from its dependency on the concrete design of the business process. Each service
organization uses a different business process design for infrastructure allocations (e.g., the
pricing and reservation process in a hotel). These organizations do not want to restrict
themselves to predetermined business process designs just to use a specific algorithm. Since
the appropriate algorithm is contingent on that design, organizations must tailor their
algorithms or redevelop them from scratch. Besides, given the currently prevailing non-
systematic approach to algorithm development, this adaptation requirement, both initially
and whenever the business process is redesigned, imposes a stiff hindrance, particularly to
the SME, and also limits its adaptability to changing market conditions.
The work presented here intends to overcome that barrier, by taking advantage of the
flexibility offered by a generic modeling approach to design the model base component of a
Revenue Management-based Decision Support System (DSS) aiming at the efficient
allocation of the abovementioned non-storable service infrastructures.
The Model Base can be identified as the key component in RM DSS according to the
definition provided by Sprague. In his classical DSS framework, Sprague distinguishes three
main components in a DSS (Sprague, 1980): database, model base and software system. The
software system in turn is composed of three components: the DBMS (Database
Management Software), which in conjunction with the database constitutes the data
subsystem; the MBMS (Model Base Management Software), which in conjunction with the
model base constitutes the model subsystem; and the dialog generation and management
software which forms the system user interface. The model subsystem is within the scope of
a DSS what is frequently referred to as a Model Management System (MMS), which
according to Muhanna & Pick (1994) can be defined with wide agreement as “a software
system that facilitates the development, storage, manipulation, control, and effective
utilization of models in an organization.”