Essay on Strategic Global Expansion: Unveiling Optimal Cities for a New York-Based Marketing Firm

The New York City-based marketing organization has proven to be a versatile and successful firm. Over the last decade, the company has provided its customers in America with the best of marketing services, the company has made through some of the spotty economic periods in the united states and come out successful. At this time, the company has contracted Mercer Human resources management organisation which decipher the information and uses it to meet the needs and requirements outcomes towards creating a healthier future as published in Cost of Living 2020 Ranking (2020). The focus of the company is a New York-based marketing client who is seeking expansion. The VP and the company chief executive officer have contracted our organisation seeking advice regarding which market is ideal for opening a branch. Our approach is to identify economic predictors in the selected cities and target the country through its predicted cost of living.

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The marketing organisation, which is based in New York, has successfully provided its services at an affordable price in the united states. Therefore, the company is ready to venture into foreign markets. We have therefore made a compilation of 17 cites internationally that can be economically sound environment to open a new office. “The data includes general cost of living, rent for a three-bedroom apartment a month, transportation cost per month, the cost of a mid-range bottle of wine, the cost of a gallon on milk, the cost of a loaf of bread as well as the cost of 12oz of coffee” as published in Cost of Living 2020 Ranking (2020). These are the necessary factors considered to be essential when deciding on company expansion to a new country and city.

Therefore, we ran a multiple linear regression test by employing a standard significance level 0.05, and the focus, in this case, is the p-value of each necessary factor, and this will help in determining if the variable is significant to base a decision. However, if the p-value of an item is above the alpha value of 0.05, then that value can not be used in the decision-making process, and this is because it is not significant. From the analysis done then, we can confidently conclude that the cost of transportation, as well as the cost of a loaf of bread, are the predictors that are significant while the rest are not. It makes sense that food, rent and transportation costs take up a significant percentage of a person’s monthly income. The p-value of transportation was recorded at 0.00299, which is less than the alpha value while the cost of bread was recorded at 0.033, also less than the alpha value. The R- square was also a good fit for the model, and it was determined to be 0.875767, and this means that the model explains for 87.5% of the variance in data values.

Additionally, a descriptive statistic was helpful in decision making as it shed some right on the criteria for making the decision. The transportation cost had a mean medium and minimum of 78.01,74.28 and 7.66 dollars respectively, and the quantile costs one and three were recorded at 41.20 and 105.93 dollars respectively. On the other hand, the cost of a loaf of bread had a mean, medium and a minimum cost of 1.47,1.37 and 0.41 dollars respectively I addition to the quartile one and three recorded at 1.04 and 1.77 dollars respectively. It is therefore important to note that in this case, New York City is set as the baseline. In the contract, it is listed to have the highest cost amid all the cities with the transportation cost recorded at 141 dollars which is higher than the price of quartile three. While the cost of a loaf in the New York city is recorded at 2.93 dollars other cities that are a good fit for relocation would have a lower cost mean, Q3 and the medium for the same. Through the descriptive statistics helped narrow down to Athens, Mumbai, Warsaw, Rome and Prague. The cities names above all fall under the baseline mean, medium and the quartile costs.

Based on the multiple linear regression analysis and the descriptive data provided them with the Mercer consulting organisation would, therefore, recommend that the firm should expand to Mumbai as well as Warsaw in that order. The projected cost of living in Mumbai was approximately 34.33 dollars, and hence making it a perfect fit for relocating. Among the selected cities, Mumbai recorded the lowest cost of living index. Having the second-lowest projections, Warsaw is the next suggestion for relocation recording a 49.41dollars on the cost of living index. These two cities have the leading predictor cost for significant, cost of living as well as in terms of descriptive data analysis.

Work Cited

Cost of Living 2020 Ranking. (2020). Mercer. https://www.mercer.com/newsroom/2020-cost-of-living.html