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Mock Study Sampling and Data Collection Approaches - Assignment Example

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Existing literature indicates significance of leadership style and leadership potential to motivating employees in an organization (Graham, Ziegert, and Capitano, 2015; Liden, Wayne, Liao, and Meuser, 2014; Aragon-Correa, Garcia-Morales, and Cordon-Pozo, 2007). The proposed…
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Mock Study Sampling and Data Collection Approaches
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Mock study sampling and data collection approaches March 12, Mock study sampling and data collection approaches Existing literature indicates significance of leadership style and leadership potential to motivating employees in an organization (Graham, Ziegert, and Capitano, 2015; Liden, Wayne, Liao, and Meuser, 2014; Aragon-Correa, Garcia-Morales, and Cordon-Pozo, 2007). The proposed study aims at investigating effects of leadership style and leadership potential, of sales consultants at AT&T and the consultants’ supervisors, on the consultants’ level of sales.

This section discusses sampling and data collection approaches to be used in the study.Sampling approachStratified sampling approach is proposed for the study because of the wide geographical area that the target organization covers, suitability of the sampling design for such diversity, and statistical advantages of the design. Stratified random sampling is a restricted probability sampling approach (Sekaran and Bougie, 2010) in which a population is divided into subgroups and random sampling implemented in each sub-group.

Homogeneity within sub groups that distinguishes members of a subgroup from members of other subgroups informs the division (Votg, 2007). Differences in state laws and possible social and cultural values across state boundaries inform the boundaries as the basis for stratification. The sampling design will therefore ensure representation of all sales consultants of the organization towards internal reliability of the study’s results. In addition, eliminated bias through the randomized approach will ensure validity of developed data from sample besides external reliability.

Stratified random sampling, like simple random sampling, is easy to implement and this ensure validity due to sampling ccuracy. Sample size and its adequacyA sample size of 510 participants is proposed for the study. Seventeen states will be selected at random and a branch of the company selected from each of the states, at random. From each branch, five supervisors or managers will be selected at random and a further five sales consultants, operating under each of the supervisors or managers selected at random.

The stratified random approach will contribute to validity and reliability of the study (Christensen, Johnson, and Turner, 2011) and the sample size is adequate because it falls within used sample size ranges in similar studies. Explored literature from empirical studies identifies use of such sizes as 408, 71, and 74 (Graham, Ziegert, and Capitano, 2015; Liden, Wayne, Liao, and Meuser, 2014; Aragon-Correa, Garcia-Morales, and Cordon-Pozo, 2007). Economic feasibility, due to proposed use of internet-based data collection approaches also allows for use of the proposed sample size.

Statistical powerSample size determination did not rely on power analysis but guarantees significant statistical power. Even though power analysis offers a more accurate approach to sample size determination, its determined size may not be applicable due to possible constraints. In addition, reliance of applied sample sizes in previous studies in a field offers an insight to suitable sample sizes (Schmidt and Brown, 2014). Data collection techniquesOnline questionnaires and secondary data will be used in data collection.

Recorded data on sales consultants’ sales will be used to collect data on sales volumes for each of the sales consultants while Leadership Inventory Questionnaire and Multifactor Leadership Questionnaires will be used to collect data on leadership styles and leadership potentials. The questionnaires will be self-administered and will be sent online, leading to such benefits as cost effectiveness (Black, 1999), freedom from researcher bias, time convenience for participants, and ability to reach a larger number of research participants.

Use of secondary data also has such advantages as reliability, suitability, and adequacy of collected data besides time and economic convenience (Kothari, 2004). ReferencesAragon-Correa, J., Garcia-Morales, V., and Cordon-Pozo, E. (2007). Leadership and organizational learning’s role on innovation and performance: Lessons from Spain. Industrial Marketing Management 36(3), 349-359. Black, T. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics.

London, UK: Sage Publications.Christensen, L., Johnson, R., & Turner, L. (2011). Research methods, design, and analysis (11th ed.). Boston, MA: Allyn & BaconGraham, K., Ziegert, J., and Capitano, J. (2015). The effect of leadership style, framing, and promotion regulatory focus on unethical pro-organizational behavior. Journal of Business Ethics 126(3), 423-436. Kothari, C. (2004). Research methodology: Methods and techniques. New Delhi: New Age International. Liden, R., Wayne, S., Liao, C., and Meuser, J. (2014). Servant leadership and serving culture: Influence on individual and unit performance.

Academy of Management Journal 57(5), 1434-1452.Schmidt, N. and Brown, J. (2014). Evidence-based practice for nurses. Burlington, MA: Jones & Bartlett Publishers. Sekaran, U. and Bougie, R. (2010). Research methods for business: A skill building approach (5th Ed.). Hoboken, NJ: John Wiley & Sons. Vogt, W. (2007). Quantitative research methods for professionals. Boston, MA: Pearson.

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