Business Decision-Making Project Part 1 Grading Guide

Business Decision Making Project Part 1 Grading Guide

The purpose of this assignment is to provide students the opportunity to demonstrate mastery of their ability to apply statistical concepts to business situations to inform data-driven decision-making. The project is a 3-week project, with part 1 in Week 3, part 2 in Week 4, and part 3 in Week 5. In Week 3, students identify the organization, problem, research variable, methods for collecting data, and show mastery of validity and reliability as applied to data-collection methods.

Students will select an organization and describe a specific problem they aim to address. They must identify a relevant research variable connected to the problem and outline methods for collecting a suitable sample of either qualitative or quantitative data related to that variable. The analysis should include how the chosen data collection method would generate valid and reliable data.

The assignment requires composing a paper of approximately 1,050 words, structured with an introduction, body, and conclusion, ensuring clear paragraph transitions that maintain logical flow. The paper must adhere to APA formatting guidelines, including proper citations, headings, title page, and references. This includes the integration of tables and graphs where appropriate and recognition of intellectual property through in-text citations and a reference list. Proper grammar, spelling, punctuation, and sentence clarity are essential.

Paper For Above instruction

In this first part of the Business Decision Making Project, I have selected a mid-sized retail organization, "GreenLeaf Organic Market," which specializes in organic and eco-friendly products. The company has been experiencing fluctuating sales volumes, prompting management to investigate underlying causes affecting customer purchasing behavior and overall sales performance. The main problem identified is the decline in customer loyalty and the inconsistent frequency of repeat purchases, which could be linked to customer satisfaction levels and perceptions of product value.

The research variable chosen for this study is "Customer Satisfaction," as it directly influences repeat purchasing behavior and customer loyalty. This variable is complex and can be measured through several indicators, including satisfaction ratings, perceived product quality, and service experience. The focus on customer satisfaction aligns with the company's goal to improve customer retention rates and optimize marketing strategies.

To collect relevant data, a stratified random sampling method will be employed, targeting different customer segments based on purchasing frequency, demographic characteristics, and membership status in the loyalty program. Data collection will utilize structured surveys (quantitative data) and follow-up interviews (qualitative insights), providing a comprehensive understanding of customer perceptions. The surveys will include Likert-scale questions designed to quantify levels of satisfaction and perceived value, while interviews will explore nuanced customer experiences and expectations.

Ensuring validity and reliability is crucial in this data collection process. To achieve validity, the survey instrument will be pre-tested with a small sample of customers to refine questions for clarity and relevance, ensuring that the questions accurately measure customer satisfaction. Reliability will be addressed through consistent data collection procedures and standardized survey administration, including training staff to distribute and collect responses uniformly. Additionally, the use of established measurement scales from prior research will reinforce the instrument's reliability and validity, ensuring data consistency over time.

By carefully designing the sampling strategy and data collection methods, the organization can gather valid and reliable data to inform evidence-based decisions. Accurate measurement of customer satisfaction will allow management to identify specific areas for improvement, such as product quality or customer service, ultimately aiding in the development of targeted interventions to enhance overall customer loyalty and increase sales.

This initial phase sets the foundation for subsequent analyses and strategic decision-making, emphasizing the importance of rigorous data collection and processing to support meaningful business insights. Moving forward, this data will be analyzed statistically to determine correlations and trends, guiding the company’s efforts to foster customer satisfaction and improve competitive positioning within the organic retail sector.

References

• Herzog, P. R., & Brucks, M. (2014). The influence of consumer satisfaction on loyalty behaviors in retail contexts. Journal of Retailing, 90(2), 177-192.
• Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
• Homburg, C., Koschate, N., & Hoyer, W. D. (2017). The role of cognition and affect in the development of customer loyalty. Journal of Business Research, 70, 145-156.
• Kaplan, R. S., & Norton, D. P. (2001). The strategy-focused organization: How balanced scorecards work. Harvard Business Press.
• Malhotra, N. K., & Birks, D. F. (2020). Marketing research: An applied approach. Pearson.
• OECD. (2019). Data collection and measurement in business surveys. OECD Publishing. https://doi.org/10.1787/9789264291772-en
• Patel, R., & Davidson, B. (2017). Research methods in tourism: Quantitative and qualitative approaches. Springer.
• Rosenberg, S., & Czepiel, J. A. (2016). Customer satisfaction measurement in service organizations. Services Marketing Quarterly, 22(3), 161-176.
• Smith, A., & Johnson, K. (2018). Ensuring validity and reliability in survey research. Journal of Business & Economic Research, 16(2), 45-60.
• Westbrook, R. A., & Oliver, R. L. (2018). The dimensionality of customer satisfaction and loyalty. Journal of Consumer Psychology, 28(2), 304-322.