Statistical approaches in accounting for optimal choice and business location decisions

Background: Choosing an optimal business location is a critical decision that can significantly impact an organization's success. Many businesses fail because their initiators were not properly guided with informed counsel prior to the commencement.

Methods: This study employed stratified random sampling to collect data from a sample of 1200 business units across the southern and middle belt regions of Nigeria. Using statistical tools such as factor analysis, empirical literature review, and ordinal logistic regression, the study explores accounting perspectives from type and locational factors necessary in making impactful business decisions. These include analyzing the turnover potential of various business types and locations.

Results: The study found that business success and sustainability are sensitive to factors such as culture, government regulation, religion, and population density. The findings also indicate that the choice of business type—such as consumer goods, industrial goods, foodstuff, supermarkets—and their locations in rural or urban areas all have significant implications for business survival.

Conclusion: By integrating accounting and statistical perspectives, businesses can make more informed and strategic location decisions. These decisions can leverage the analytical advantages of understanding business types and locations, ultimately improving operational efficiency and profitability.

Methods
Data was collected through the use of structured questionnaire, collated and aggregated using the formula: value = (score/n) * 10

Where,

         n = number of business or sales outlets under the control of the respondent

         score = respondent's score of the occurrence of the turnover range under each of the predictors (consgood, indgoods, foodstuff, supmkts, rural, and urban). The scores ranged between 1 (least likely) and 10 (most likely).

         value = figure entered in the Excel sheet cell