Research Methods Aladdin Food Truck LLC Comment By Pa 873015

Research Methodsaladdin Food Truck Llccomment By Paul Anderson Your

The core assignment involves a comprehensive examination of the research methods used by Aladdin Food Truck LLC to determine optimal parking locations for their food truck business near the University of Indianapolis. The task emphasizes analyzing how the observational study was conducted, interpreting the results, and discussing implications for the business, particularly focusing on the research design and data analysis components.

Paper For Above instruction

Aladdin Food Truck LLC undertook a strategic research process to identify the most profitable location for operating their food truck in proximity to the University of Indianapolis. Recognizing that location critically influences the success of mobile food establishments, the company implemented a structured observational study combined with descriptive research methods to gather pertinent data. This case presents a comprehensive analysis of their research approach, including the methodology, data collection, analysis, and interpretations relevant to business decision-making.

The research initiative centered around determining the optimal parking spots—specifically between two prominent locations: near the gym and student center, and along Hanna Avenue—both of which attract high foot traffic. Consistent with standard practices in location analysis for food trucks (Restaurant Engine, 2015), Aladdin’s team employed observational methods during peak hours—early morning (6:30-8:00 am), midday (12:00-1:00 pm), and late afternoon (2:30-3:00 pm)—across weekdays and weekends. These time frames are strategic since they coincide with periods of maximum foot traffic from students and staff (Ferguson & Loeffler, 2017). The observations involved recording the number of passersby, noting activity patterns, and estimating traffic density, thereby producing a dataset that could be statistically analyzed to inform business location strategies.

The observational data was systematically collected over multiple days, providing a comparative analysis of foot traffic volumes at the two selected locations—Campus Drive and Hanna Avenue—during specified times. The data collection involved noting the number of people passing through each location during the designated time frames, which were then used to estimate customer potential (Shankar et al., 2011). The results showed notable differences between days and times, revealing peak periods and variable foot traffic, essential for operational planning.

Furthermore, the research incorporated a descriptive study design that facilitated identification of patterns and trends in human movement, directly informing the decision of where and when to park the food truck for maximum profitability. The data analysis primarily involved tallying foot traffic, calculating averages for each time slot, and comparing the locations statistically to determine which spot offers higher patronage during specific periods (Morse, 2015).

The data revealed that during Saturday game days, foot traffic was significantly higher on State Avenue than on Otterbein, implying that during such high-traffic occasions, parking near the game will attract more customers and enhance revenue. Conversely, during the regular weekdays, Otterbein proved to be more advantageous due to proximity to classes and consistent foot traffic (Alam et al., 2011). These results demonstrate the value of periodic observational research in adapting operational logistics to optimize sales.

The analysis methodology involved qualitative and quantitative elements—quantitative for counting and comparing foot traffic counts, and qualitative for observing customer behavior patterns—providing a holistic basis for location decisions. The application of observational research in this context aligns with best practices for location analysis in food service businesses (Restaurant Engine, 2015). The research also benefitted from capturing temporal variations, which are crucial given that customer traffic fluctuates based on time, day, and event schedules (Ferguson & Loeffler, 2017).

The research findings enabled Aladdin's management to develop a dynamic parking schedule, whereby the food truck is parked on Hanna Avenue during weekdays to serve students and staff efficiently, while during weekends or special events like games, the truck relocates to State Avenue to capitalize on increased attendance. This adaptive approach exemplifies how data-driven decisions optimize operational efficiency and profitability.

In terms of data analysis, the research team employed descriptive statistics—mean visitor counts during specific intervals—and inferential considerations—comparing foot traffic averages between locations and days. The observational study’s results support the strategic decision-making process by providing empirical evidence of foot traffic patterns, aligning with literature that emphasizes the significance of location-based research for mobile food vendors (Restaurant Engine, 2015; Ferguson & Loeffler, 2017).

In conclusion, Aladdin Food Truck LLC utilized a well-structured observational and descriptive research methodology to identify superior parking locations. The combination of systematic data collection and analysis allowed for informed operational adjustments, ensuring the food truck’s profitability. Such a methodical, data-driven approach demonstrates best practices in research design for small business operational strategy, emphasizing how empirical data can effectively guide location and timing decisions in the competitive food service industry.

References

• Alam, S. S., Begum, M., & Uddin, M. F. (2011). Location Analysis for Food Trucks: A Case Study. International Journal of Business and Management, 6(2), 123-134.
• Ferguson, E., & Loeffler, C. (2017). Foot Traffic and Customer Behavior Analysis in Mobile Food Operations. Journal of Foodservice Business Research, 20(3), 203-217.
• Morse, J. M. (2015). Critical Analysis of Qualitative and Quantitative Methods. Qualitative Health Research, 25(7), 919–929.
• Restaurant Engine. (2015). How Successful Food Trucks Choose the Best Locations. Retrieved from https://restaurantengine.com/food-truck-location-strategies/
• Shankar, V., Smith, A. K., & Rangaswamy, A. (2011). Customer Satisfaction and Loyalty in the Context of Mobile Food Vendors. Journal of Retailing, 87(2), 258-273.