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Methods of Data Collection Essay

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Updated: May 23rd, 2021

Introduction

The purpose of the paper is the evaluation of data collection methods and the creation of efficient instruments for the accumulation of information about BI System usage and its effects on organizational performance. It is observed that BI software creates benefits in the data organization and operation (Agiu, Mateescu, & Muntean, 2014; Carlsson, Skog, & Tona, 2010). And the purpose of the study is the identification and assessment of BI’s favorable impacts.

The study will employ both qualitative and quantitative data collection methods. While qualitative methods provide information that may help to identify the patterns between the variables’ interrelations, quantitative data is associated with a high level of precision, accuracy, and objectivity (Creswell, 2003). Qualitative data is interpretable; it is subjective yet can be effectively correlated with the theoretical frameworks (Morgan & Smircich, 1980). Quantitative data is numerical and statistical, and it is characterized by a minimal possibility of result biasing (Brown & Hedges, 2009). The survey, questionnaire, and interviews (comprised of expanded versions of survey and questionnaire questions) complement each other and will help to evaluate the accumulated data from multiple perspectives.

The data collection tools will be designed considering the major ethical principles of research conduct. It is important to provide complete information about the purpose of the experiment to the participants to get their consent. In this way, the researchers act according to the principle of voluntary participation (Trochim, 2006). The conduction of experiments without the consent of the individuals may be regarded as a violation of the ethical code. It is also important to use the personal information confidentially and avoid its disclosure without permission (Beskow, Dame, & Costello, 2008).

Assignment Task

Instruments of Data Collection

This survey is a part of an academic assignment. The information provided by you will be kept confidential and will be used for academic/research purpose only.

Questionnaire

  1. What is your age? ___
  2. What is your gender?
  • Male
  • Female
  1. Do you apply BI software at work?
  • Yes
  • No
  1. How often do you use BI System?
  • At least one time a day
  • More than one time a day
  1. For how long do you use BI System a day?
  • Less than 15 minutes
  • More than 15 minutes
  1. How would you assess System quality?
  • High
  • Low
  1. How would you assess information quality?
  • High
  • Low
  1. Does System application positively impact your working productivity?
  • Yes
  • No
  1. Does it have a favorable influence on organizational performance?
  • Yes
  • No
  1. How would you assess your overall satisfaction with the BI System application?
  • Positive
  • Negative
  • Survey
Question Extremely Negative
1
Neutral
2
Satisfactory
3
Good
4
Extremely Positive
5
Evaluate the effectiveness of BI System application in the following aspects of performance:
  1. Data collection
  1. Data analysis
  1. Planning
  1. Allocation of resources
  1. Data organization
  1. Data querying
  1. Sharing information between the working site units
  1. Assessment of working performance
  1. Data visualization (i.e. infographics)
  1. Reporting
  1. Archiving and storage of information
Evaluate the overall impact of the BI System on organizational performance:
  1. Units collaboration
  1. Personnel management
  1. Knowledge management
  1. Decision-making efficiency
  1. Financial management
  1. Evaluation of external and internal environment
  1. Productivity level increase
  1. Operational efficiency increase
  1. Job satisfaction
  • Questionnaire: Table of Findings
  • Sample: N=102
  • The average age of study participants: 29
Gender Female: 23
Male: 79
BI Application Frequency Never: 11
One time a day: 77
More than one time a day: 14
Time of Application Less than 15 minutes: 24
More than 15 minutes: 78
BI System Quality High: 88
Low: 14
Information Quality High: 97
Low: 5
Positive Effect on Work Productivity Yes: 56
No: 46
Positive Effect on Organizational Performance Yes: 88
No: 14
User Satisfaction Positive: 88
Negative: 14
  • Survey: Table of Findings
  • Sample: N=91 (Excluding 11 participants who never use BI System at work)
Evaluation of BI System effectiveness:
Data collection Negative: 1
Neutral: 22
Satisfactory: 23
Good: 26
Positive: 19
Data analysis Negative: 0
Neutral: 8
Satisfactory: 29
Good: 29
Positive: 25
Planning Negative: 0
Neutral: 1
Satisfactory: 10
Good: 79
Positive: 1
Allocation of resources Negative: 1
Neutral: 27
Satisfactory: 45
Good: 3
Positive: 15
Data organization Negative: 0
Neutral: 0
Satisfactory: 0
Good: 15
Positive: 76
Data querying Negative: 2
Neutral: 16
Satisfactory: 19
Good: 30
Positive: 28
Sharing information between the working site units Negative: 0
Neutral: 0
Satisfactory: 0
Good: 56
Positive: 35
Assessment of working performance Negative: 1
Neutral: 32
Satisfactory: 25
Good: 16
Positive: 17
Data visualization Negative: 3
Neutral: 25
Satisfactory: 40
Good: 15
Positive: 8
Reporting Negative: 0
Neutral: 3
Satisfactory: 2
Good: 56
Positive: 30
Archiving and storage of information Negative: 0
Neutral: 1
Satisfactory: 25
Good: 50
Positive: 15
Evaluation of the overall BI System impact on the organizational performance:
Units collaboration Negative: 2
Neutral: 17
Satisfactory: 49
Good: 12
Positive: 11
Personnel management Negative: 0
Neutral: 0
Satisfactory: 58
Good: 31
Positive: 2
Knowledge management Negative: 0
Neutral: 0
Satisfactory: 12
Good: 23
Positive: 56
Decision-making efficiency Negative: 1
Neutral: 22
Satisfactory: 19
Good: 26
Positive: 23
Financial management Negative: 2
Neutral: 16
Satisfactory: 0
Good: 26
Positive: 47
Evaluation of environment Negative: 0
Neutral: 71
Satisfactory: 8
Good: 11
Positive: 1
Productivity increase Negative: 0
Neutral: 44
Satisfactory: 19
Good: 15
Positive: 13
Operational efficiency increase Negative: 0
Neutral: 15
Satisfactory: 49
Good: 12
Positive: 15
Job satisfaction Negative: 0
Neutral: 45
Satisfactory: 30
Good: 15
Positive: 1

Conclusion

The data collection tools were designed and implemented to evaluate the effectiveness and efficiency of the BI System application in the randomly selected UAE police office. The items included and assessed in surveys may be regarded as the representative indicators of BI impacts (Moskovitz, & Even, 2014). Their analysis will allow the identification of dynamics in interrelations between the study variables.

The data collection tools were designed considering the principles of voluntary participation, informed consent, and confidentiality. According to other ethical principles the researchers need to reduce the possibility of harm and negative influencing on the participants not merely in terms of physical well-being but terms of psychological state and social identity as well (Trochim, 2006). However, this principle is irrelevant to the current study methods because the assessed information addresses impersonal characteristics and cannot damage participants.

References

Agiu, D., Mateescu, V., & Muntean, I. (2014). Business Intelligence overview. Database Systems Journal, 5(3), 23-36.

Beskow, L. M., Dame, L., & Costello, E. J. (2008). Science, 322(5904), 1054–1055. Web.

Brown, B., & Hedges, D. (2009). Use and misuse of quantitative methods: Data collection, calculation, and presentation. In D. Mertens, & P. Ginsberg (Eds.), The handbook of social research ethics. (pp. 373-387). Thousand Oaks, CA: SAGE Publications, Inc.

Carlsson, S., Skog, L., & Tona, O. (2010). The success of a business intelligence system in a police organization: An evaluation study. Web.

Creswell, J. (2003). Research design: Qualitative, quantitative, and mixed methods approach. London, UK: Sage Publications.

Morgan, G., & Smircich, L. (1980). The case for qualitative research. Academy of Management. The Academy of Management Review, 5(4), 491. Web.

Moskovitz, E., & Even, A. (2014). The Impact of a BI-Supported Performance Measurement System on a Public Police Force. International Journal of Business Intelligence Research (IJBIR), 1(5), 13-30. Web.

Trochim, W. M. K. (2006). Research Methods Knowledge Base. Web.

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IvyPanda. 2021. "Methods of Data Collection." May 23, 2021. https://ivypanda.com/essays/methods-of-data-collection/.

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