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Description‫المملكة العربية السعودية‬ ‫وزارة التعليم‬ ‫الجامعة السعودية اإللكترونية‬ Kingdom of Saudi Arabia Ministry of Education Saudi

Description

‫المملكة العربية السعودية‬
‫وزارة التعليم‬
‫الجامعة السعودية اإللكترونية‬
Kingdom of Saudi Arabia
Ministry of Education
Saudi Electronic University
College of Administrative and Financial Sciences
Assignment-3
MGT425-Spreadsheet Decision Modeling
Due Date: 04/05/2024 @ 23:59
Course Name: Spreadsheet Decision
Modeling
Course Code: MGT425
Student’s Name:
Semester: Second
CRN:
Student’s ID Number:
Academic Year: 2023-2024 (1445 H)
For Instructor’s Use only
Instructor’s Name:
Students’ Grade: Marks Obtained / Out of 10 Level of Marks: High/Middle/Low
General Instructions – PLEASE READ THEM CAREFULLY








The Assignment must be submitted on Blackboard (WORD format only) via
allocated folder.
Assignments submitted through email will not be accepted.
Students are advised to make their work clear and well presented; marks may be
reduced for poor presentation. This includes filling your information on the cover
page.
Students must mention question number clearly in their answer.
Late submission will NOT be accepted.
Avoid plagiarism, the work should be in your own words, copying from students
or other resources without proper referencing will result in ZERO marks. No
exceptions.
All answered must be typed using Times New Roman (size 12, double-spaced)
font. No pictures containing text will be accepted and will be considered
plagiarism).
Submissions without this cover page will NOT be accepted.
Course Learning Outcomes-Covered
Aligned (PLOs)
MGT.K.1
(1.1)
MGT.K.3
(1.2)
MGT.S.1
(2.1)
MGT.V.1
(3.1)
Course Learning Outcomes (CLOs)
Question
Find some structured ways of dealing with complex managerial
decision problems.
Explain simple decision models and management science ideas
that provide powerful and (often surprising) qualitative insight
about large spectrum of managerial problems.
Demonstrate the tools for deciding when and which decision
models to use for specific problems.
Build an understanding of the kind of problems that is tackled
using Spreadsheet Modeling and decision analysis.
Question-1
Question-4
Question-2
Question-3
Assignment Instructions:
• Log in to Saudi Digital Library (SDL) via University’s website
• On first page of SDL, choose “English Databases”
• From the list find and click on EBSCO database.
• In the Search Bar of EBSCO find the following article:
Title: “Modeling Autonomous Decision-Making on Energy and Environmental
Management Using Petri-Net: Case Study”.
Author: Niken Prilandita, Benjamin McLellan, Tetsuo Tezuka.
Assignment Questions: (Marks 10)
Read the above case study and answer the following Questions:
Question 1: Explain the autonomous decision-making process, its advantages and
disadvantages (250-300 words) (2.5-Marks).
Question 2: Discuss the Centralized and De-centralized Decision-Making Approaches with
suitable examples (250-300 words). (2.5-Marks).
Question 3: Explain the various stages of Decision-Making Cycle based on this case study
(250-300 words) (2.5-Marks).
Question 4: Why are the most decisions made on energy and environmental management
known as the decisions of community interest. (250-300 words) (2.5-Marks).
Answers:
1.
The autonomous decision-making process refers to the ability of a system or
mechanism to make decisions and take actions without direct human intervention. In the
context of energy and environmental management, this process involves the use of
sophisticated algorithms and models to analyze various data inputs, such as energy
consumption patterns, weather conditions, and resource availability, and make informed
decisions about resource allocation, load balancing, and other operational aspects.
One of the primary advantages of autonomous decision-making in energy and
environmental management is its ability to respond rapidly to changing conditions and
optimize resource utilization in real-time. Efficiency, waste reduction and sustainability
can all be enhanced through this technology (Cao et al. 2020). What is more, such
systems can also run continuously without the need for constant human supervision so
human mistakes will be avoided and usually the reliability of the system is improved as
well.
On the one hand, such systems can have numerous obvious benefits. Yet, they
also have some shortcomings. They are highly dependent on the “data” inputs accuracy
and the robustness of the algorithms and models underneath. It can affect the decisions
made by the AI systems in an unfavourable or even disastrous way if there are any
inaccuracies or biases in the data or models (Castellanos Contreras & Rodríguez Urrego,
2023). Moreover, the level of complication of these systems may be insurmountable to
understanding and translating their decision-making logic, which calls for openness and
accountability.
Another possible drawback is the risk of system failure due to the cyber-attack,
and this can be seen as a disaster in the management of energy and environmental
systems. Autonomy systems should have a sound security promotion and a backup plan
to tackle possible risks.
In the long run, delegating the decision making to automation provides significant
advantages in terms of efficiency and response rate. Nevertheless, it is important to
deliberate on the downsides and difficulties that the systems could face and implement
appropriate measures to guarantee safety and effectiveness.
2.
The two decision-making styles, namely one centralized and the other
decentralized, are used in many fields, for example, energy and environmental
management. The centralized one implies that a single, broader governing structure should
be in charge of the whole organization. On the contrary, decentralized approach is
characterized by giving the autonomy of decision making across different units of a system
or its subsystems (Castellanos Contreras & Rodríguez Urrego, 2023).
A supervisory authority of a centralized decision-making mechanism is in charge
of gathering and processing all the details from the whole system in order to make wellinformed decisions. Such approach usually serves these cases, which global perspective
and cooperation matters the most like a large-scale energy network or environmental
monitoring systems. For example, a centralized energy management system can be set up
to control power distribution across an area by considering real-time demand, the capacity
of the generation plants, and the constraints of the transmission network (Cao, et al., 2020).
By this side, the migration of decision making to the individual entities or
subsystems allow them to use local information and restrictions to make autonomous
choices. It works wholly in situations that are complicated, dynamic and where the
centralized approach is not economical or practical. Let us take, for example, a smart micro
grid. In it, individual homes or buildings can independently manage their consumption or
generation of energy, based on their different needs and power resources while still
preserving the whole system’s stability
Both of these approaches has their strong points and weak points. A centralized
decision-making system may achieve a global optimum solution so as to guarantee systemwide coordination, whereas it may become less flexible and less resilient to failures in the
system as abrupt changes occur. Decentralized decision making provides flexibility,
adaptability and scalability but conflicts may emerge among different entities if it was not
properly coordinated (Cao et al., 2020).
In use, most conventional systems would utilize a congruence of centralized and
decentralized approaches for decision-making, which is called a hierarchical (or hybrid)
architecture. The hybrid approach combines top-down governing and the coordination of
the system with a bottom-up decision-making process at the local level, by individuals or
subcomponents. It is a type of approach that strives to maintain a balance between global
optimization and local flexibility by implementing the best features of centralized and
decentralized systems (Cosellanos Contreras & Rodríguez Urrego, 2023).
3.
The Petri-Net modelling-based energy and environmental management procedure
in the case study by Prilandita et al. (nd) is multistage that uses a Petri-Net model. The
primary phase is the one that includes definition of the problem, which is a call for the most
efficient energy management and reducing the environmental impact in the energy systems
with many interdependence ties. Next data collection and analysis takes place, information
is gathered from various sources, including energy consumption patterns, renewable
energy resources and environmental indicators. Through this, current state of the system is
understood.
The next stage will use Petri-Nets simulation and modelling which is one of the
most famous mathematical and graphical tools used for representing complex systems with
concurrent and asynchronous behaviour (Castellanos Contreras & Rodríguez Urrego,
2023). First, the authors utilize a timed stochastic hybrid Petri-Net style presented by Cao
et al. (2020) which represents the decision making process. The results of simulations give
the fifth stage which is decision-making and optimization; consider different scenarios and
choose the best solutions that will allow you to optimize energy consumption, reduce the
cost and environmental impact by using optimization techniques and algorithms.
On the next step, implementation and monitoring set up the identified strategies and
continuously assess their performance through feedback cycles by pulling out the weak
spots and taking the necessary steps to modify those (Prilandita et al., n.d.). On the other
hand, the last but not the least stage of evaluation and adaptation carefully evaluates the
consequences of the used strategies, providing an opportunity to correct any mistake, and
finally bring about sustainable energy and environmental management strategies
(Prilandita et al., n.d.). It is at this stage that the authors refine and customize the decisionmaking process using the gathered data and evidence, this way that the approach remains
relevant and effective to achieve the set purpose.
4.
Environmental and energy-related problems are not local but overall societal issues
that influence not only the local individual interests but the whole community or society as
a whole. Decision-making on energy management, for instance, the choice of energy
sources, distribution networks, and mode of consumption, has a direct impact not only on
the availability, affordability and sustainability of energy for households, businesses, and
public services but also on the lives of the people within the community. Additionally, the
environmental management decision which includes the air, water and waste pollution and
resource conservation will have a profound consequences for the health of the community,
its quality of life and sustainability of the natural environment that is essential for
communities. Environmental destruction can cause various demerits on the human health,
the biodiversity and the ecosystem services which communities depend on.
As a result, the energy and environmental management decisions have significant
impacts on the community’s quality of life, socio-economic perspectives, and the
environment. As an example, the movement toward clean and renewable energy sources
gives rise to new employment prospects, clearer air, and the mitigations of the effects of
climate change, because the whole community will gain from this (Cao et al., 2020). Like
this, the efficient management of waste and environmental safeguards can serve the
interests of both present and future generations by providing fresh water and green spaces.
On the other hand, energy and environmental problems usually imply complicated
arguments and inter-relationships which therefore call for considering different opinions
and interests of the stakeholders within a community. In the sphere of urban planning,
choices must come up with inclusive and interactive processes that take into consideration
the social and environmental considerations of all people, including residents, businesses,
policy makers and environmental advocates (Castellanos Contreras & Rodríguez Urrego,
2023). Due to the wide-ranging and cross-cutting impacts of energy and environmental
management decisions, they are rightfully seen as community interest decisions that
require a careful, deliberate, inclusive, and a weigh-in process of the economic, social, and
environmental dimensions so as to promote communities’ well-being.
References
Castellanos Contreras, J. U., & Rodríguez Urrego, L. (2023). Technological Developments
in Control Models Using Petri Nets for Smart Grids: A Review. Energies, 16(8),
3541.
Cao, R., Hao, L., Gao, Q., Deng, J., & Chen, J. (2020). Modelling and decision-making
methods for a class of cyber–physical systems based on modified hybrid stochastic
timed Petri net. IEEE Systems Journal, 14(4), 4684-4693.

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