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Report on the Best Location for a New Happy Buns Restaurant
The success of any organization is determined by its ability to make sound and strategic decisions for its activities. In fact, the management process mainly entails making various critical decisions, which determine the short term and long term success of the organization. A multi-Attribute Decision Making (MADM) process is an effective system used by organizations to determine the most optimizing decision (Tzeng & Huang, 2011). Simply, MADM is the process of making decisions in discrete decision spaces with an aim of selecting the pre-determined alternatives (Kalbande & Thampi, 2009). In this report, we aimed at determining the best investment location for the business given the prevailing conditions in each area. The alternative locations were Little Rock, Stuttgart, Daisy, Pine Bluff, and Newport.
The MADM analysis aimed at identifying the most suitable location for the establishment of the business among Little Rock, Stuttgart, Daisy, Pine Bluff, and Newport towns. In this analysis, six main attributes for each location were considered: traffic count, building lease and taxes, building size, parking space, insurance costs, and ease of access. Traffic count referred to the average number of people in thousands-per-day who passed near the premises. Building lease and taxes showed the costs in thousands-per-year charged for operating the business. Parking space indicated the available slots available for customers to keep their vehicles. Insurance costs indicated a number of charges in thousands-per-year that was paid to cover risks involved in operating the business. Finally, ease of access showed the degree of accessibility of the business.
The process of developing a MADM analysis schedule entailed first identifying the attributes that were being analyzed and listing them in rows. Secondly, there was the inputting of the values that each location had its respective attributes. Notably, the building lease and taxes attributes and also the insurance cost attribute were written with a negative sign since an increase in the cost for these attributes made the respective location less desirable. On the contrary, the other attributes were written in positive since an increase in these attributes made the location more desirable. The final column, which was denoted as “basis,” was used in the determination of the utilities for each location. The assumption used in this column were the highest traffic count possible is 25,000 people per day, the highest building lease and tax costs were $5,000 annually, and the largest building size is 5000square feet. It was also assumed the largest parking space can accommodate 100 cars, the highest insurance cost is $10,000, and the ease of access has the best rating of 4. In general, these assumptions used figures that were slightly higher than the optimal value for each location since all regions have some level of limitations that make it impossible for them to attain maximum performance.
In table two, the utilities for each location were calculated by dividing the values for each location-column with the respective value in the “basis” column. In table three, the weight for each attribute was determined by dividing 100% by 6, since each attribute was assumed to have an equal weight. In table 4, the value of the attribute for each location was the product of the utilities and their respective weight. The final row, which was labeled “TOTAL,” indicated the desirability of each location. It was calculated as the total sum of the values of each attribute in their respective column. The location that had the highest value in the “TOTAL” row was the most desirable. Since Little Rock region had the highest value, it was the most desirable location.
            The business should be established in Little Rock region. This location has the highest value in the MADM sensitivity analysis, which indicates it is the most desirable. In terms of traffic count, it has the highest value of 0.1333. It has the third highest building and lease value of 0.087. Its building size was the third largest, which is shown by a value of 0.107. In terms of parking space, it has the fourth largest space. Its insurance cost is also the fourth highest at 0.087. Finally, it has the second highest rating in ease of access at 0.125. Therefore, although Little Rock did not have the best value in all the available attributes, it has the best combination, which makes it the best location for establishing the business.
Kalbande, D., & Thamli, G. (2009). Multi-attribute and Multi-criteria Decision Making
Model for technology selection using fuzzy logic. International Journal of Computing Science and Communication Technologies, 2(1), 377-384.
Tzeng, G., & Huang, J. (2011). Multiple attribute decision making: Methods and applications (1st Ed.). Chapman and Hall, New York: NY.