Managerial support and individual performance – All assignments are individual assignments

You are tasked to provide a scientific (empirically anchored) report which discusses the effects of different levels of managerial support on individual performance. Let assume the CEO of a large beer brewery has tasked your to do this as a consultant. To complete this task you will have to collect, without the assistance of the UNISA librarian, five peer reviewed journal articles linking managerial support to performance in the workplace. (Question: Why should you not have access to the librarian? Answer: The search task, finding the appropriate articles, is core to your assignment.) Note: In practice, collecting only five articles may be insufficient to provide an empirically anchored report, but for the sake of this report let’s assume this is sufficient.  

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-State the titles of the five articles you have chosen for the analysis (25 marks). It may be a very time consuming process to find these articles, as you will quickly realize that not all the article you find meet the requirements set out below. As you are interested in writing a report on the possible link between two variables, article which focus on the variables and not proxies to the variables will be more accurate and accrue more marks. (E.g. An article on “managerial support and individual performance” would accrue more marks than an article on “LMX and group performance”.) 

-Report and comment on the way the variables were measured in each article (E.g. Managerial support was measured with X instrument and individual performance was measured with Y instrument. Maximum marks: 1 marks per article = 5). 

-Also, as you are to report on the link between the variables in a very specific environment (a large beer brewery), reporting on studies in that environment or close proxies to that environment will heal the most valid results, and as such receive high marks. Report and comment on from where the data were gathered (E.g. Data collected in the wine industry would accrue more marks than data collected in tertiary education sector. Maximum marks: 1 mark per article = 5). 

- If data is collected from larger samples, it normally heals more reliable results, thus better results. Report and comment on the sample size of the studies (E.g. Samples with more than a 100 respondents would accrue more marks than data collected from 25 respondents. Maximum marks: 1 mark per article = 5). 

-The most important part of the report relates to the link between the variables. This link may be reported as part of longitudinal studies, experiments, or quasi experiments, where the effects of an intervention is tested, or be the results of a cross-sectional design, where the overlap between the variables is presented. Causality can only be assessed in longitudinal studies, experiments, or quasi experiments while a cross-sectional data only provide information on covariance. As such, reporting on longitudinal studies, experiments or quasi experiments will bare more valid results and as such accrue better marks than reporting on cross-sectional designs. (Note: If you only report on longitudinal or experimental or quasi experimental design you will receive 10 “bonus” marks. Maximum marks: 10). 

-Next you need to report on the empirical results of the studies reported on in the articles. This may take on the form of reporting differences (for the longitudinal, experimental or quasi experimental designs) or correlations (in the case of the cross-sectional designs). Report these differences and / or correlations per article. Differences are often calculated using t-tests or analysis of variance (Anova) – so look out for this in the articles. Correlations are often calculated using the equation suggested by Pearson, so look out for that or a correlation matrix in the results section of the articles studies (Note: It is important that you gather data which can be integrated – say calculate the average t-values or the average correlation coefficients (r- values). Thus, if your articles do not provide information that is of the same sort / nature, you will not be able to integrate the results, disqualifying you from providing a scientific (empirically anchored) report. Essential then is to find data which can be integrated. Maximum marks: 25).

-Also, report on the practical significance of these results if you can find such a statistic in the article, or calculate it yourself once you have collected the data. The following phrases will

 

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assist you in the search for finding answers to the questions and equations regarding practical significance: “Cohen d-value for mean differences” and “Practical significance of correlations” (Note: With this you can accrue bonus marks:  Maximum marks: 10).

-You now need to write a 200 word recommendation to the CEO of the brewery explaining why they should / should not adopt measures to improve managerial support based on the way managerial support relates to the improvement of individual performance. Here you should demonstrate your understanding of the empirical information on the link between managerial support and individual performance (Maximum marks: 30).

The maximum marks you can score are 120. This is very unlikely to achieve such a score. You will receive a score out of 100.

Please note that you should only report on what you found in published scientific articles. The way you should reference the articles is as follows:  

Overstreet, R. E., Hanna, J. B., Byrd, T. A., Cegielski, C. G., & Hazen, B. T. (2013). Leadership style and organizational innovativeness drive motor carriers toward sustained performance. The International Journal of Logistics Management, 24(2), 247-270. 

If it is impossible to report in this format, the sources you have located are most likely not academic articles, and you need to find alternative sources. Please use this exact format. The reference list should be provided at the end of the assignment. (Inaccurate reporting in the reference list may negatively affect the marks allocated.). 

Completing this assignment will empower you to have a scientific argument for or against the fostering supervisor support.