| Course | GM586 Transformational Leadership |
|---|---|
| Unit | Unit 5 |
| Paper type | Empirical article critique |
| Length | About 1,130 words, 7 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | MS in Management |
| Updated | October 2026 |
Free sample paper for GM586 Unit 5
One Survey, One Sitting: A Unit 5 Critique of a Field Study on Transformational Team Leaders
[Student Name]
Purdue University Global
GM586: Transformational Leadership
Unit 5 Empirical Article Critique
[Instructor Name]
[Date]
The study critiqued, its authors' claims and every figure are composite and illustrative, built to resemble common designs in the field; the methodological research cited is real.
Summary of the Study
The study surveyed installation and repair technicians at one regional broadband provider. Of about 345 technicians invited, 214 responded, a response rate of 62 percent. They worked in 31 field teams, each led by a team leader. Technicians rated their team leader on the transformational scales of a full range leadership questionnaire, and in the same survey they rated their own extra effort and satisfaction using the outcome scales of that questionnaire.
The authors report that the transformational scales correlated with extra effort at 0.61 and with satisfaction at 0.68, both significant. In a regression, transformational leadership explained a large share of the variance in both outcomes. The discussion states that transformational leadership "leads to" greater technician effort and recommends transformational leadership training for team leaders.
The study has strengths. The sample is reasonably large, the response rate is respectable for a field survey, and the setting, technicians working alone at customers' homes with limited supervision, is one where leadership might plausibly matter for effort. The questions below concern what the design can and cannot show.
Question One: Who Supplied Each Variable?
Every variable came from the same technicians, answering one questionnaire on one occasion. Leadership, effort and satisfaction were all reported by one person in one sitting. Philip Podsakoff and colleagues describe this as a classic source of common method bias: when predictor and outcome come from the same rater at the same time, correlations can be inflated by the rater's general mood, desire to be consistent or overall impression of the job (Podsakoff et al., 2003). A technician who likes their job is likely to rate their leader well, their effort as high and their satisfaction as high, whether or not the leader caused any of it.
The problem is sharper because the outcome scales come from the same questionnaire as the leadership scales. Daan van Knippenberg and Sim Sitkin argue that transformational leadership research has often measured leadership partly by its supposed effects, so that a follower's report of being inspired is treated as both a leadership behavior and an outcome (van Knippenberg & Sitkin, 2013).
When the same technician rates the leader, their own effort and their satisfaction in one sitting, a strong correlation may reflect how that technician feels about work rather than what the leader did.
Question Two: How Were Technicians Who Share a Leader Handled?
The 214 technicians share 31 leaders, about seven per team. Technicians in the same team rate the same person, and their ratings are not independent. The study analyzed individual responses as though each were a separate observation of a separate leader. John Antonakis and colleagues note that ignoring this kind of nesting can understate standard errors and make effects look more certain than they are (Antonakis et al., 2010). With only 31 leaders, the effective sample for any claim about leaders is 31, not 214. A multilevel analysis, or at least an analysis at the team level, would have given a fairer test.
Question Three: Was Contingent Reward Controlled?
The study did not include contingent reward in its regression. Timothy Judge and Ronald Piccolo's meta-analysis found that contingent reward correlated very strongly with transformational leadership, and that it predicted several outcomes about as well (Judge & Piccolo, 2004). If a team leader who recognizes good work also scores high on transformational scales, the study cannot tell which of the two drives effort. The recommendation to train leaders in transformational behavior may be premature if clear, fair recognition explains much of the effect.
Question Four: What Did the Company Already Record?
The company's dispatch system records every service visit, including repeat truck rolls, which occur when a technician must return to the same address within 30 days for the same problem. This is a widely used quality measure in the industry, and it is recorded by a system, not reported by the technician. Each team's repeat rate could have been matched to its leader's mean transformational score.
That outcome would answer the first question directly. If teams with more transformational leaders had fewer repeat visits, the finding would not depend on technicians' self-reports. The dispatch system also records time on site and jobs completed per day, which bear on effort. None of these were used.
A Further Concern: Who Did Not Respond
About 130 invited technicians did not answer. The study does not compare respondents with nonrespondents on tenure, team or any company measure, though the company could easily have supplied these. Technicians who are unhappy with their team leader may be less willing to complete a survey about that leader, especially if they doubt it is anonymous within a seven-person team. If so, the respondents would overrepresent satisfied technicians, which narrows the range of leadership ratings and can distort correlations in either direction. A simple comparison of response rates by team would show whether some teams are missing more members than others.
Alternative Explanations
Three other explanations fit the data as well as the authors' account. First, teams in newer, easier service areas may have both happier technicians and leaders who look better, because their work goes more smoothly. Second, satisfied technicians may describe their leaders more generously, so that satisfaction drives the leadership ratings rather than the reverse. Third, a leader's skill at assigning routes and backing up technicians with customers, which the transformational scales do not measure directly, could explain both effort and satisfaction. The study's design cannot rule out any of these, because it has no measure taken at a different time or from a different source.
What the Study Can Claim
The study shows that, at one company, technicians who see their team leader as transformational also report more effort and satisfaction. It cannot show that the leader's behavior caused the effort, because the data are cross-sectional and from one source. It cannot separate transformational behavior from contingent reward. And its precision is overstated because nesting was ignored.
A stronger design would gather leadership ratings from technicians and outcomes from company records, analyze at the team level or with multilevel models, include contingent reward as a control, and ideally measure outcomes some months after leadership. Antonakis and colleagues recommend exactly this kind of separation of sources and timing before causal language is used (Antonakis et al., 2010). The authors' phrase "leads to" should be replaced with "is associated with" until such evidence exists.
References
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A review and recommendations. The Leadership Quarterly, 21(6), 1086-1120. https://doi.org/10.1016/j.leaqua.2010.10.010
Judge, T. A., & Piccolo, R. F. (2004). Transformational and transactional leadership: A meta-analytic test of their relative validity. Journal of Applied Psychology, 89(5), 755-768. https://doi.org/10.1037/0021-9010.89.5.755
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879-903. https://doi.org/10.1037/0021-9010.88.5.879
van Knippenberg, D., & Sitkin, S. B. (2013). A critical assessment of charismatic-transformational leadership research: Back to the drawing board? Academy of Management Annals, 7(1), 1-60. https://doi.org/10.5465/19416520.2013.759433
Reading the GM 586 Unit 5 instructions
GM586 Unit 5 asks you to critique an empirical study of leadership in the article's own order. Summarize the design and findings first: sample, response rate, measures, analysis and the authors' claims, including any causal language. Credit the study's strengths before turning to questions. Then work through specific design questions: who supplied each variable and when, whether people who share a leader were treated as independent, whether closely related behaviors such as contingent reward were controlled, who did not respond and why that might matter. Propose alternative explanations the design cannot rule out. Identify data that could have tested the claim independently, such as organizational records. Close by stating what the study can claim and how a stronger design would look. Expect about five pages, citing methodological research in APA 7.
Inside the GM586 Unit 5 example
The summary describes the survey of technicians at one regional broadband provider, the full range scales and outcome scales on the same questionnaire, the correlations and the authors' recommendation for training. Strengths are credited. Question one applies Podsakoff and colleagues on common method bias and van Knippenberg and Sitkin on measuring leadership by its effects, with the highlighted sentence stating the core problem. Question two applies Antonakis and colleagues to seven technicians per leader and an effective sample of 31. Question three cites Judge and Piccolo on contingent reward. Question four names repeat truck rolls, time on site and jobs per day from the dispatch system. Further sections address roughly 130 nonrespondents and three alternative explanations. The close states what the study supports and proposes separated sources, team-level analysis, controls and delayed outcomes.
GM586 Unit 5 rubric: what earns full points
GM586 instructors look for a critique that is precise about design and fair about what the study shows. A clear summary of sample, measures and claims earns early credit. Each methodological question should be tied to the study's actual choices, such as one survey supplying every variable. Recognizing nesting under shared leaders and its effect on sample size shows statistical understanding. Raising the contingent reward control connects the critique to course content. Naming specific organizational records that could test the claim carries significant weight. Alternative explanations show critical thinking. Ending with the claim the study can bear, and a better design, persuades more than rejecting it. Podsakoff and colleagues, Antonakis and colleagues, Judge and Piccolo and van Knippenberg and Sitkin provide the reference list in APA 7.
Common GM586 Unit 5 mistakes, and how to avoid them
Many GM586 Unit 5 critiques list generic limitations, such as a small sample or one company, without connecting them to the study's design. Others reject the study outright. A frequent gap is the source of the data: when leadership and outcomes come from the same people at the same time, the correlation can be inflated, and this is usually the most important point. Some writers overlook nesting or related leadership behaviors. Summarize the study fairly, ask who supplied each variable, check how shared leaders were handled, look for missing controls and nonresponse, name records that could test the claim and say precisely what the study can and cannot show.
Get a GM586 Unit 5 example written to your instructions
Upload the assigned article, or one you chose where the prompt allows, along with the Unit 5 critique prompt and its rubric; a note on any appraisal checklist the course names is useful too. Within 24-48h a free first critique follows the article's own order, keeping summary and evaluation apart and citing the method literature your reading lists. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
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GM586 Unit 5 questions, answered
What is common-source bias in plain terms?
When the same people supply both the predictor and the outcome, on the same occasion, anything that colors their answers colors both, and the correlation between them rises for reasons unrelated to the leader. Mood, a wish to appear consistent and general liking are typical causes. Critiques in this area check which variables share a source before judging any result.
Should the critique conclude the study is worthless?
Rarely. Most studies in this literature are informative within limits, and a critique that states those limits precisely is more persuasive than one that rejects the work. Say what the design can support, such as an association within one company at one time, and what it cannot. Proposing the data that would settle the question shows the critical reading graders look for.
Can I critique a meta-analysis instead of a single study?
Some sections permit it, though a single empirical study usually gives more to work with, since its design choices are visible. If a meta-analysis is assigned, the questions shift toward which studies were included, how they were coded and whether same-source designs were separated from others. Check the prompt's wording, since 'empirical article' sometimes excludes reviews.
Where can I find a free GM586 Unit 5 sample paper?
This page carries a full GM586 Unit 5 critique of a field study on transformational team leaders and technicians, covering common method bias, nesting, controls and company records, with APA 7 references.
Why does nesting matter in this study?
The 214 technicians share 31 leaders, about seven per team, so their ratings of the same leader are not independent. Analyzing them as separate observations overstates the certainty of the results; for claims about leaders, the effective sample is closer to 31.