| Course | DBAX 9102 Business Research Project Stage 2 |
|---|---|
| Week | Week 9 |
| Paper type | Evidence plan |
| Length | About 760 words, 5 pages |
| Format | APA 7 student paper |
| School | Walden University |
| Program | Doctor of Business Administration (DBA) |
| Updated | October 2026 |
Free sample paper for DBAX 9102 Week 9
An Address and a Standard for Every Construct: The Evidence Plan for a Multilevel Study of Coaching and Quota Attainment, Naming Where Each Measure Comes From, How It Is Scored and What Would Make It Unusable
Student Name
Walden University
DBAX 9102: Business Research Project Stage 2
Instructor Name
Month Day, Year
An Address and a Standard for Every Construct: The Evidence Plan for a Multilevel Study of Coaching and Quota Attainment, Naming Where Each Measure Comes From, How It Is Scored and What Would Make It Unusable
The Principle
Every construct in a design needs an address, meaning the exact place its data will come from, and a standard, meaning the condition under which those data are good enough to use. A design that names a construct without an address is a wish; one that names an address without a standard cannot tell good data from bad. This evidence plan gives both for each construct in my study, which links managers' coaching to recorded quota results at an industrial supply distributor.
The Plan
Table 1
Constructs, Sources and Standards
| Construct | Address | How scored | Standard for use | |
|---|---|---|---|
| Coaching frequency | Coaching sessions logged by managers in the customer relationship system | Count per salesperson per quarter | Sessions must have a date, a salesperson and a note of at least one sentence; entries without notes are flagged | |
| Coaching skill | Survey of salespeople, using items adapted from the managerial coaching measure developed by Heslin et al. (2006) | Mean of items on guidance, facilitation and inspiration, each on a seven-point scale | Internal consistency of at least .80 in this sample; at least five salespeople rating each manager | |
| Quota attainment | Quarterly sales reports from the company's enterprise system | Sales divided by quota, as a percentage | Quotas set before the quarter began; mid-quarter quota changes excluded or flagged | |
| Territory potential | Company's annual estimate of sales opportunity by territory | Dollars of estimated opportunity | Estimate made by sales operations, not by the manager | |
| Tenure | Human resources records | Months in role | None beyond accuracy check against a sample of files | |
Item wording will be adapted for sales settings and pilot-tested with four salespeople before use.
Why These Sources
The review found that ratings-based outcomes inflate the apparent link between coaching and performance. Quota attainment therefore comes from records, and coaching frequency from logs, so neither shares a source with the other. Only coaching skill comes from the salespeople themselves, and it will be collected at the start of the year, before the outcome quarters. Podsakoff et al. (2003) recommend separating sources and timing in exactly this way.
Heslin et al. (2006) developed a measure of managerial coaching with three dimensions: guidance, facilitation and inspiration. Using an established measure, rather than writing new items, allows comparison with other studies, and its dimensions match what the goal-setting literature says matters: clear direction and feedback (Locke & Latham, 2002).
What Would Make Each Measure Unusable
Rules for discarding each measure are fixed before any data arrive. If more than a quarter of logged sessions have no notes, the frequency measure will be treated as unreliable and analyzed only as a secondary variable. If fewer than five salespeople rate a manager, that manager's skill score will not be used, since a mean of three or four ratings is too easily swayed by one unhappy salesperson. If quotas were changed during a quarter for more than a tenth of salespeople, that quarter will be dropped. Writing these rules now prevents adjusting them after seeing the results.
Measures Considered and Rejected
Two alternatives were considered. Managers could rate their own coaching skill, which would be easier to collect, but self-ratings of skill tend to be generous and would not reflect what salespeople experience. Gross profit could replace quota attainment as the outcome, since it captures pricing discipline as well as volume. I kept quota attainment because quotas already adjust for differences between territories and because the coaching policy was introduced to raise attainment specifically. Gross profit will be recorded as a secondary outcome, so that a finding on attainment can be checked against a measure that managers cannot easily influence by discounting.
Data Handling
All data will be anonymized by the sales operations team before I receive them, with a code linking each salesperson's records and survey responses. Managers will not see individual survey responses. The survey will state that participation is voluntary and has no effect on evaluation.
Pilot
Before the main collection, I will run the plan on one branch's previous quarter to check that the addresses work: that logs, sales reports and personnel records can be linked by the code, and that the standards can be applied as written. Any problems will be fixed before the study begins, and the changes will be recorded in a short methods log that travels with the proposal to the committee.
References
Heslin, P. A., Vandewalle, D., & Latham, G. P. (2006). Keen to help? Managers' implicit person theories and their subsequent employee coaching. Personnel Psychology, 59(4), 871-902. https://doi.org/10.1111/j.1744-6570.2006.00057.x
Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57(9), 705-717. https://doi.org/10.1037/0003-066X.57.9.705
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
Reading the DBAX 9102 Week 9 instructions
Week 9 asks you to write an evidence plan for every construct in your design. For each construct, give its address, meaning the exact source of the data, how it will be scored and the standard the data must meet to be used. Present this in a table. Explain why each source was chosen, especially where it avoids a weakness identified in your review. Justify any established measure you adapt. State in advance what would make each measure unusable and what you would do then. Explain alternatives you rejected. Describe data handling and confidentiality. Close with a pilot that tests whether your sources can be linked and your standards applied as written.
How this DBAX 9102 Week 9 example is built
The plan opens by defining address and standard. A table covers five constructs with source, scoring and standard. A section explains why records and logs avoid ratings-based inflation, citing Podsakoff and colleagues. A section justifies adapting the measure from Heslin and colleagues and links its dimensions to Locke and Latham. A section sets rules for unusable data: logs without notes, managers with too few raters and changed quotas. A section explains rejecting manager self-ratings and keeping quota attainment over gross profit, which becomes secondary. A section describes anonymized handling. A closing section plans a pilot on one branch. Each standard is written as a rule a research assistant could apply without asking the author.
Reading the DBAX 9102 Week 9 rubric
The core expectation is that every construct has a source and a standard, and the table that provides both carries the most weight. Choosing sources that avoid known weaknesses shows the review shaped the plan. Justifying adapted measures with citations demonstrates rigor. Rules for unusable data written in advance show integrity, since they prevent adjusting after results are seen. Explaining rejected alternatives shows deliberation. Confidentiality procedures show ethical awareness. A pilot shows practical foresight. Plans that name constructs without sources, set no quality standards or adapt measures without justification fall short. Writing the rules for unusable data before collection is the single most persuasive sign of integrity in an evidence plan. A pilot that tests linking across sources shows the plan has been tried, not only written.
Common DBAX 9102 Week 9 mistakes, and how to avoid them
Make a row for every construct in your design. For each, ask where exactly the data live, who controls them and what would make them unreliable. Write the quality standard as a rule you could apply mechanically. Then decide now what you will do if the standard is not met, before you see any results. If you adapt a published measure, cite it and explain your changes. Many students name a construct and assume the data will appear in usable form. Others fix data problems after seeing results, which invites bias. Run your plan on a small slice of data first. Our writers can help you set standards that are strict but workable.
Get a DBAX 9102 Week 9 example written to your instructions
Name the design committed in Week 8 and its variables, then add the Week 9 prompt and rubric. The construct table, validity checks and advance judging rules come back inside 24-48h, free the first time. Measures are specified in general form, which means no system extracts or records are asked for.
More DBAX 9102 papers and DBA samples
- DBAX 9102 Week 1: Burden of Proof Discussion
- DBAX 9102 Week 2: Literature Search Protocol
- DBAX 9102 Week 3: Literature Claim Sort
- DBAX 9102 Week 4: Literature Disagreement Analysis
- DBAX 9102 Week 5: Settled Findings Statement
- DBAX 9102 Week 6: Open Remainder Statement
- DBAX 9102 Week 7: Research Design Options
- DBAX 9102 Week 8: Research Design Commitment
- DBAX 9102 Week 10: Design Peer Challenge
- DBAX 9102 Week 11: Stage 2 Assembly Document
- DBAX 9101C Week 9: Consultant Independence Note
- DBAX 9101 Week 9: Study Feasibility Sketch
- DBAX 8151 Week 9: Practice Implications Paper
- DBAX 8101 Week 9: Plain-Language Study Summary
DBAX 9102 Week 9 questions, answered
Where can I find a free DBAX 9102 Week 9 sample paper?
The evidence plan, construct table included, is posted below free of charge.
Where does coaching frequency come from in the DBAX 9102 Week 9 plan?
Sessions logged by managers in the customer relationship system.
Which measure is adapted for coaching skill?
The managerial coaching measure developed by Heslin and colleagues.
When is a manager's skill score unusable?
When fewer than five salespeople rate that manager.
What secondary outcome is added?
Gross profit, to detect attainment gained through discounting.