Review the culture index power point slides in the additional power point slides folder. Answer the following 4 questions.
1) Describe the major components of the Lewis Model?
2) How could you utilize this model in your sourcing activities and engagement with other professionals?
3) How does the global mindset differ from the domestic mindset?
4) To bridge a cultural gap how would you address the 7 cultural dimensions at play?
1) Lewis model of Economic development emphasizes on the fact of rural agricultural productivity, urban industrial productivity, migration of rural population to urban areas and level of unemployment.
It states that as more population is involved in agriculture in rural areas, the marginal productivity of individual labor reduces. A stage comes when the marginal product is lower compared to additional labor. The labor should be then shifted from rural areas to urban areas and engage in industrial production. As more labors are involved in industrial production the output would increase and unemployment level would come down. This would thus lead to economic development.
2) Firms should source the materials from countries where more people are engaged in agricultural activities. The sector is called as capitalist sector where people carry out plantation, and manufacture raw materials.Engagement with other professionals is in subsistence sector where people are involved in industrial production and absorbs the surplus labor.
3) Domestic mindset is more involvement in capitalist sector and manufacture the things with excessive of labor. Global mindset is shifting surplus labor to the subsistence sector and involve in manufacturing in industrial sector where people would earn higher returns.
4) To bridge 7 cultural dimensions at play
Dimension | Strategies |
Universalism |
Time should be given to people to make decisions. Promises should be kept Give clear instructions and process. |
Particularism |
Let people make own decisions Respect others feelings while making decisions Flexibility should be there to make decisions. |
Individualism |
Praise people individually Flexibility should be given to make their own decisions |
Communitarianism |
Praise group performance Dont praise the individual publicly |
Specific |
Be to the point Keep the personal and professional lives separate |
Diffuse |
Good relationship should be built first and then the focus should be on business Social gatherings should be more where business matters are discussed and personal matters should be discussed at workplace. |
Neutral |
Emotions should be managed effectively Body language should not convey any negative emotions |
Emotional |
Emotions should be sued to communicate objectives Open up with people to build rapport |
Achievement |
People should be rewarded for their contribution Titles should be used appropriately |
Ascription |
Authority should not dominate your role Respect should be given to people in authority |
Sequential Time |
Maintain deadlines Punctuality should be emphasized |
Synchronous Time |
Be flexible Allow people to be flexible in projects |
Internal Directions |
People should be allowed to develop their skills Clear objectives should be set |
Outer Directions |
Regular feedback should be given Conflict should be managed quietly |
Review the culture index power point slides in the additional power point slides folder. Answer the following 4 questio...
22 Use data_Americas. Plot year vs gdpPercap. Scale gdpPercap by log10. Color the data by country. 23 Use data_Americas. Plot year vs gdpPercap. Scale gdpPercap by log10. Color the data by country and size by pop. Looking for the answers in R command codes. 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 142 142 142 142 142 142 142 142 142 142 142 142 > table(gapminder$country) Afghanistan Albania Algeria 12 12 12 Angola Argentina Australia 12...
12 Use data_2002. Use ggplot. Plot gdpPercap vs lifeExp. 13 Use data_2002. Use ggplot. Plot gdpPercap vs lifeExp by continent (color) 14 Use data_2002. Use ggplot. Plot gdpPercap vs lifeExp by continent and pop (color and size) 15 Get data for Europe in 2002. Call it data_Europe Looking for these problems in R command code answers. 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 2002 2007 142 142 142 142 142 142 142 142 142 142 142 142...
DATA: # happy2.py import csv def main(): happy_dict = make_happy_dict() print_sorted_dictionary(happy_dict) def make_happy_dict(): filename = "happiness.csv" happy_dict={} with open(filename, 'r') as infile: csv_happy = csv.reader(infile) infile.readline() for line in csv_happy: happy_dict[line[0]] = line[2] return happy_dict def lookup_happiness_by_country(happy_dict): return def print_sorted_dictionary(D): if type(D) != type({}): print("Dictionary not found") return print("Contents of dictionary sorted by key.") print("Key","Value") for key in sorted(D.keys()): print(key, D[key]) main() "happines.csv" Country,Year of Estimate,Happiness Index Afghanistan,2018,2.694303274 Albania,2018,5.004402637 Algeria,2018,5.043086052 Angola,2014,3.794837952 Argentina,2018,5.792796612 Armenia,2018,5.062448502 Australia,2018,7.17699337 Austria,2018,7.396001816 Azerbaijan,2018,5.167995453 Bahrain,2017,6.227320671 Bangladesh,2018,4.499217033...
11.38 Building a multiple linear regression model. Let’s now build a model to predict the life-satisfaction score, LSI. (a) Consider a simple linear regression using GINI as the explanatory variable. Run the regression and summarize the results. Be sure to check assumptions. (b) Now consider a model using GINI and LIFE. Run the multiple regression and summarize the results. Again be sure to check assumptions. (c) Now consider a model using GINI, LIFE, and DEMOCRACY. Run the multiple regression and...
8 AutoSave D The Home Data Review View Help Power Pivot Formulas Insert Draw Page Layout ES - per capita GDP 1 Country Name 2 Central African Republic 3 Myanmar 4 Congo, Dem. Rep. 5 South Sudan 6 Madagascar 7 Burundi 8 Ethiopia 9 Guinea 10 Malawi 11 Niger 12 Gambia, The 13 Bangladesh 14 Guinea-Bissau 15 Lao PDR 16 Benin 17 Pakistan 18 Chad 19 Nepal 20 Mozambique 21 uberia 22 Kenya 23 Senegal 24 Burkina Faso 25 Mauritania...
Will reward thumbs up 100% if works. thank you Pickling with Python code and Pandas code Do both pickling assignment in one Jupyter Notebook file. Python Pickle steps: Download the CSV file. Load into a Pandas DataFrame. Make the column ‘country’ the index. Print the header. Using Python code, pickle the DataFrame and name the file: PythonPickle. Load back the PythonPickle data into the DataFrame. Print the header. (Note both printed headers should match.) Pandas Pickle steps: Download the CSV...