R S A Study on Complexity and Uncertainty Perception and Solution Strategies
Brown (2012) argue in favor of business
games by stating that real-life experience
imposes limitations because it doesn’t
offer opportunities to experience the
full range of possibilities and skill development. Business games have been
applied to simulate business and operations management in the electronics
industry (Haapasalo & Hyvönen, 2001),
to teach business ethics (Schumann
et al., 1997), to develop entrepreneurial
skills (Stumpf, Dunbar, & Mullen, 1991),
and to enhance systems thinking and
business process redesign (Van Ackere,
Larsen, & Morecroft, 1993).
Complexity and uncertainty. The
articles listed in Table 1 focus on what
Pollack (2007) describes as the hard par-
adigm, which is commonly associated
with quantitative techniques and deduc-
tive reasoning. However, the author
identifies research streams that suggest
an increasing acceptance of the soft
paradigm, which focuses on qualitative
elaborate on these contributions from a
literature point of view.
Business games. Business games
have a long history within an educational context. Early research focused
on the internal validity through assessing the advantages and disadvantages
of simulations versus other pedagogies
(Schumann, Anderson, & Scott 1997) and
later on, the validity of top management
games was confirmed by Wolfe (1997).
The most-cited advantages of the use
of business games are their high degree
of realism; a broader learning environment; competition between players; as
well as soft skills such as communication skills, group behavior, and organizational skills (Saunders, 1997; Faria,
2001). On top of this, business games
craft personal experiences by chal-
lenging participants on intellectual
and behavioral levels and hence fall
within the nominator experiential learn-
ing (Kolb, 1984). Parente, Stephan, and
characteristics to the (D)TCTP. A brief
overview of the key publications associ-
ated with each avenue along with their
contributions, are provided in Table 1.
The contribution of this article to the
existing body of literature is threefold.
First, the two solution strategies of students participating in a project management business game, called the Project
Scheduling Game (PSG), are distilled.
These solution strategies are a combination of five building blocks: focus,
activity criticality, ranking, intensity, and
action. Second, we take two contextual
factors—complexity and uncertainty—
into account. While the first contribution
makes use of real-life data, experiments
are constrained by the fact that classroom sessions need to be held in order
to gather additional data. The final contribution overcomes this problem by
testing the derived solution strategies on
computer-generated project networks.
In the remainder of this section, we will
Research Stream Paper Contribution
Problem extensions Vanhoucke (2005)
Vanhoucke and Debels (2007)
Sonmez and Bettemir (2012)
Tareghian and Taheri (2006)
Tareghian and Taheri (2007)
Pour et al. (2010)
DTCTP with time-switch constraints. Outperforms Vanhoucke
et al. (2002).
Metaheuristic for time/switch constraints, work continuity, and
net present value maximization.
Hybrid genetic algorithm for the DTCTP.
Three integer programming models for the time/cost/quality
Scatter search with electromagnetic properties for the time/
cost/quality trade-off problem.
Genetic algorithm: hill-climbing and decreasing mutation rate
for the time/cost/quality trade-off problem.
Stochastic characteristics Azaron et al. (2005)
Azaron and Tavakkoli-Moghaddam (2007)
Cohen et al. (2007)
Ke et al. (2009)
Hazir et al. (2010)
Klerides and Hadjiconstantinou (2010)
Hazir et al. (2011)
Mokhtari et al. (2011)
Chen and Tsai (2011)
Ke et al. (2012)
Ghoddousi et al. (2013)
Genetic algorithm for multi-objective TCTP with activity
PERT network as queuing system, spawning of new project and
activity durations Exponential.
Robust optimization for the stochastic TCTP.
Genetic algorithm-based algorithm for the stochastic TCTP.
Robust scheduling and robustness measures based on slack.
Two-stage stochastic integer programming approach.
Schedule robustness with unknown interval-based cost
Ant system approach for the stochastic TCTP.
TCTP using fuzzy numners.
Formulation of three stochastic TCTP models using chance-constrained and dependent-chance programming.
Non-domination based genetic algorithm for multi-objective TCTP.
Table 1: Overview of current literature on the discrete time/cost trade-off problem.