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Huffman Trucking Company Data Collection Coursework


Introduction

Huffman Trucking Company which is based in the United States of America is a transport and delivery company with its head offices in Cleveland. It has its branches spread all over the country for example in St Louis. The company has over 800 trailers and tractors. It employs 925 drivers and 425 support staff. Recent turnovers are 20% above the industry’s average.

Safety statistics are good though not good as those of its competitors. Several safety violations have been reported. This prompted the management of Huffman Trucking Company to recommend additional training for drivers. A new training meant to improve the drivers’ skills was implemented. The management also wanted to know the following before and after the training: 1.Did the training have a positive effect on the drivers?

What were the drivers’ attitudes on the training’s effectiveness, company policies, and job performance?

As a result, Huffman Trucking Company employed the services of a consultancy firm, Iwamoto • Crews • Coe. They were to design a data collection plan and perform data analysis so as to establish the effectiveness of the new training (Glaser & Strauss, 1967).

A data collection plan was drawn. It narrowed down the Huffman Trucking organization’s assessment study into three types of data namely demographic data, performance data, and assessment data.

Demographic data

The best way to collect the demographic data is through the personnel data in the human resource department. A structured data collection sheet should be formulated as the example below.

(Table 1)

Employed Driver’s Gender Region in which the driver is based 2010 Driver’s Salary

Since the targeted total population size is relatively large, about 925 cases and several sheets are required. The researcher should carefully go through all the personnel data and record the relevant data on the sheet (Shettleworth, 2010). A counter check of both the hardcopy and softcopy data is essential for verification purposes.

When the process of data collection is complete, identification of variables and their measurement scales is important for the purpose of analysis. The following table illustrates the variables identified and their measurements.

(Table 2)

Variable Name Type Measurement Labels
Employed Numeric
Continuous values
Scale – interval n/a
Gender String
Discrete values
Nominal 0 – Male
1 – Female
Region String
Discrete values
Nominal 0 – Cleveland
1 – Los Angeles
2 – St. Louis
3 – Bayonne
Salary Numeric Scale n/a

Performance Data

The primary role of the performance data is to examine the effectiveness of the new training program. The data already exists in the company’s various sources for example, in personnel data, assignment logs, and the training data but it may not be recorded (Hergenhahn, 2005). The best way to record this data for the purpose of analysis will be through the following sheet.

(Table 3)

Number of years of service in the company Driver’s skills level Number of hours of training a driver received Number of jobs assigned to a driver in the year 2010 Number of days the driver is on the road

With the sheet above, the following variables and measurement scales will be appropriate for the purpose of data analyzing.

(Table 4)

Variable Name Type Measurement Labels
Number of Years_10 Numeric
Discrete values
Scale – interval n/a
Skills _level String
Discrete values
Nominal 0 – Driver Trainee
1 – Light Truck Driver
2 – Route Driver
3 – Heavy Truck Driver
4 – Long Distance Driver
Training_10 Numeric
Discrete values
Scale
Ratio values
n/a
Number of Jobs 10 Numeric
Discrete values
Scale
Ratio value
n/a
Travel 10 Numeric
Discrete values
Scale
Ratio value
n/a

Assessment data

A survey was conducted. A questionnaire was used. The questionnaire had four questions. The questions are:

  1. Do I have the training necessary to do my job?
  2. I am satisfied with my job?
  3. Does the company place high importance on driver training?
  4. Does the company place high importance on safety? The respondents were supposed to rate their responses with a five-point Likert-type scale:
  • Strongly agree
  • Agree
  • Neither neither agree nor disagree
  • Disagree
  • Strongly disagree

The following table illustrates variable definitions and the measurement units in the assessment data.

(Table 5)

Variable Name Type Measurement Labels
Survey_1 Numeric Discrete values Ordinal
  1. Strongly agree
  2. Agree
  3. Neither agree nor disagree
  4. Disagree
  5. Strongly disagree
Survey_2 Numeric Discrete values Ordinal
  1. Strongly agree
  2. Agree
  3. Neither agree nor disagree
  4. Disagree
  5. Strongly disagree
Survey_3 Numeric Discrete values Ordinal
  1. Strongly agree
  2. Agree
  3. Neither agree nor disagree
  4. Disagree
  5. Strongly disagree
Survey_4 Numeric
Discrete values
Ordinal
  1. Strongly agree
  2. Agree
  3. Neither agree nor disagree
  4. Disagree
  5. Strongly disagree

Conclusion

Quantitative research enables the researcher to launch an objective assessment of a given case as statistical data of the variables is usually used (Given, 2008).This is important in getting accurate results. With the data collection executive summary, the Huffman Tucking Company will be able to properly analyze the data and hence examine it to realize if the objective the research was met.

References

Given, L. M. (2008). The Sage encyclopedia of qualitative research methods. Los Angeles, L.A, USA: Sage Publications.

Glaser, B. & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Chicago, Chgo: Aldine.

Hergenhahn, B.R. (2005). An introduction to the history of psychology. Belmont, CA, USA: Thomson Wadsworth.

Shettleworth, S. J. (2010). Cognition, Evolution and Behavior (2nd Ed). New York, NY: Oxford.

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IvyPanda. (2019, June 27). Huffman Trucking Company Data Collection. Retrieved from https://ivypanda.com/essays/huffman-trucking-company-data-collection/

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"Huffman Trucking Company Data Collection." IvyPanda, 27 June 2019, ivypanda.com/essays/huffman-trucking-company-data-collection/.

1. IvyPanda. "Huffman Trucking Company Data Collection." June 27, 2019. https://ivypanda.com/essays/huffman-trucking-company-data-collection/.


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IvyPanda. "Huffman Trucking Company Data Collection." June 27, 2019. https://ivypanda.com/essays/huffman-trucking-company-data-collection/.

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IvyPanda. 2019. "Huffman Trucking Company Data Collection." June 27, 2019. https://ivypanda.com/essays/huffman-trucking-company-data-collection/.

References

IvyPanda. (2019) 'Huffman Trucking Company Data Collection'. 27 June.

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