Case study: Staff retention and staying power: Nissan builds on loyalty at Sunderland plantSome of carmaker’s earliest recruits are now among its most senior executives.Since the first Bluebird rolled off….
You work for a company that develops and markets crew planning and optimization software and provides training and consulting in this area for the airline industry.
You work for a company that develops and markets crew planning and optimization software and provides training and consulting in this area for the airline industry. Currently, the firm is focused on regional airlines within the continental United States. Several inquiries have arisen during the last three years regarding opportunities to expand into the European Union (EU) and the United Kingdom (UK). The opportunity is clear, but what is less clear is the feasibility and cost associated with providing support to EU and/or UK clients, given that an additional overseas facility may be warranted upon such an expansion. Further, expansion will require significant investment. A wrong step could lead to disaster.
Your team is assigned to evaluate if expansion into the UK and/or EU markets is feasible. As a first step in this analysis and decision-making, you have been provided with anInternational Expansion spreadsheet
with data collected to aid in this decision. The first sheet in the workbook is data produced by a consultant that is a rating of four categories key to the expansion decision:
Criteria 1: Market similarity
Criteria 2: Strength of competitors
Criteria 3: Client application usage
Criteria 4: Management risk
Using the data in this worksheet, carry out the following analysis (refer to the readings and resources in this module to identify how to perform these tasks in Excel):
1. Conduct a t-test for the two UK locations for all categories. Determine if a significant difference exists between the two locations in any of the market location criteria ratings.
2. Conduct an ANOVA for all five locations for each rated category. Determine if a significant difference exists between the five locations in any of the categories.
3. Conduct a test to determine if there is a relationship between the number of support requests and the number of minutes required to support each request.
4. Calculate the p-value for each test and comment on what the value means for the significance of each test.
5. Identify one non-parametric test that could be substituted for any of the tests used in this assignment. Try the non-parametric test and identify and briefly describe any differences in results.