| Course | GB730 Applied Business Research Design and Methodology |
|---|---|
| Unit | Unit 3 |
| Paper type | Question alignment exercise |
| Length | About 800 words, 5 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | MBA |
| Updated | October 2026 |
Free sample paper for GB730 Unit 3
Four Draft Questions, One Intact: A Unit 3 Question Alignment Exercise for a Revenue Management Override Study
[Student Name]
Purdue University Global
GB730: Applied Business Research Design and Methodology
Unit 3 Question Alignment Exercise
[Instructor Name]
[Date]
The hotel company and the study are composite and illustrative; the methods sources cited are real.
The Purpose Being Tested Against
The Unit 2 purpose pairs a quantitative look at overrides and two outcomes, occupancy and average daily rate, with interviews meant to explain whatever the numbers show. The proposed design is explanatory sequential mixed methods using the company's revenue management and property management records for every hotel-night from 2023 through 2025, followed by interviews with about fifteen revenue managers.
How Each Question Is Tested
Each draft question is read two ways. Reading down, from purpose to data: does the question serve a purpose element, and could the proposed design produce data that answer it? Reading up, from question to purpose: does the purpose actually call for this question, or has the question introduced something new? A question passes only if both readings hold.
Draft Question 1
As drafted: Do revenue manager overrides cause higher revenue per available room?
Purpose element: the relationship between overrides and outcomes.
Data that would answer it: a comparison of outcomes on nights with and without overrides, under conditions where overrides were assigned independently of demand.
Can the design produce it? No. Overrides are chosen by managers on nights they judge unusual, and the design uses existing records without random assignment. The design can estimate associations adjusted for measured demand indicators but not causal effects (Shadish et al., 2002). The question also names revenue per available room, while the purpose separates occupancy and average daily rate.
Revision: To what extent are revenue manager overrides associated with hotel-night occupancy and average daily rate, after adjusting for bookings on hand, day of week, local events and competitors' rates?
Draft Question 2
As drafted: Do managers override more when they have information the system lacks?
Purpose element: the reasons for overriding.
Data that would answer it: a record of what each manager knew on each night that the system did not.
Can the design produce it? Not from the records. The company's systems do not record the information behind an override; reason codes exist in the software but are optional and were filled in for only about 6 percent of overrides. The variable the question depends on is missing from the data.
Revision: This question moves to the qualitative strand, where managers can describe the information they use. It is folded into Question 3.
Draft Question 3
As drafted: Why do revenue managers make costly overrides?
Purpose element: managers' described reasons.
Data that would answer it: interview accounts of override decisions.
Can the design produce it? The interviews can produce accounts, but the question assumes its answer. It presupposes that overrides are costly, which is precisely what the quantitative strand is meant to test, and it would lead interviewers to ask managers to defend decisions rather than describe them.
Revision: How do revenue managers describe the information and reasoning that lead them to override, or to accept, the system's recommended rates?
A question that calls overrides costly has answered the study's first question before asking its second.
Draft Question 4
As drafted: In what ways do revenue managers' accounts of their override decisions help explain the relationships found between overrides and occupancy and average daily rate?
Purpose element: using qualitative findings to explain quantitative results.
Data that would answer it: a comparison of quantitative patterns with interview themes, for example whether managers whose overrides associate with higher rates describe different reasoning from managers whose overrides associate with lower occupancy.
Can the design produce it? Yes. The explanatory sequential design is built to produce exactly this integration, with interviewees selected based on the quantitative results.
Revision: None. This question passes both readings unchanged.
The Revised Set
The study proceeds with three questions. A quantitative question on the association between overrides and occupancy and average daily rate after adjustment. A qualitative question on how managers describe their reasoning for overriding or accepting. And an integration question on how the accounts help explain the associations. Mixed methods texts recommend a question that addresses integration explicitly (Creswell & Plano Clark, 2018), and the fourth draft question already did. Onwuegbuzie and Leech (2006) add that each question in a mixed study should signal which strand answers it, which the revised set now does.
Hypotheses for the Quantitative Question
For occupancy, the null hypothesis is that overrides have no association with occupancy after adjustment; the alternative is that they do. The same pair applies to average daily rate. Hypotheses are two-sided, because the study has no basis for assuming overrides help rather than hurt.
References
Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE.
Onwuegbuzie, A. J., & Leech, N. L. (2006). Linking research questions to mixed methods data analysis procedures. The Qualitative Report, 11(3), 474-498.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin.
The Purdue Global GB730 Unit 3 instructions
Unit 3 of GB730 asks you to test your draft research questions against the purpose above them and the design below them. Restate the purpose and the proposed design briefly so the reader has both in view. Explain the test you will apply to each question; reading down from purpose to data and up from question to purpose is one method. Take each draft question in turn: state it as drafted, name the purpose element it serves, describe the data that would answer it and judge whether the design can produce those data. Revise any question that fails, and say why. Present the revised set and check it against at least one published standard for mixed methods questions. Add hypotheses for the quantitative question, stating whether they are one or two sided.
Inside the GB730 Unit 3 example
A short opening restates the Unit 2 purpose and the planned use of three years of hotel-night records and about fifteen interviews. The two-way test is defined next. Draft question one fails twice: its causal verb exceeds the design and it uses revenue per available room where the purpose separates occupancy from rate. Draft two needs a variable the systems barely record, so it moves to the interviews. Draft three presupposes costly overrides, and the highlighted sentence explains why that matters. Draft four, on how managers' accounts explain the associations, passes as written. The revised set of three questions is checked against Creswell and Plano Clark and Onwuegbuzie and Leech, and two-sided hypotheses follow for occupancy and average daily rate.
GB730 Unit 3 rubric: what earns full points
GB730 instructors give the alignment exercise its marks for diagnosis. Each draft question should be tested against both the purpose and the design, and the exercise loses points when a question is revised without saying what failed. Spotting a causal verb that a nonexperimental design cannot support is one of the checks most often rewarded. So is discovering a missing variable from the actual field list rather than from assumption. Questions that presuppose their answers are a separate category the rubric looks for. The revised set is judged on coverage: one question per strand plus integration in a mixed design. Hypotheses must match the quantitative question exactly. Citing the methods sources that define good questions shows the revisions meet a standard outside the student's own judgment.
GB730 Unit 3 help: mistakes that cost points
A frequent problem in GB730 alignment work is revising every question cosmetically without stating which test it failed, so the instructor cannot see the reasoning. Some students keep a causal verb because it sounds stronger, and the committee will strike it later. Others never check whether the records actually hold the variable a question needs, which is the cheapest moment to find out. Questions that use loaded words, such as costly or ineffective, often survive into the proposal unnoticed. Integration questions are frequently missing from mixed designs. Read each question both ways, name the failure, revise in words the design can support, confirm the data exist and add an integration question. Send your draft questions and we can run the same two-way test on them.
Get a GB730 Unit 3 example written to your instructions
Attach your current research questions, purpose statement and proposed design, plus whatever Unit 3 asks for and the rubric behind it. Returned in 24-48h: a custom alignment table testing each question upward and downward, failures explained, revisions shown in full and any removed question logged with its reason. A first order here is free. 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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GB730 Unit 3 questions, answered
How many research questions does GB730 expect?
Two to four is typical for an applied doctoral study, with one per strand in a mixed design plus an integration question. More questions multiply the analysis without necessarily sharpening the study. If a question cannot be tied to a distinct analysis in the Unit 9 plan, that is often a sign to merge or drop it.
Should quantitative questions include hypotheses?
Usually, yes, stated as null and alternative pairs tied to each quantitative question. Some sections place hypotheses in the alignment exercise; others hold them for the analysis plan. Qualitative questions do not take hypotheses. Check where your instructor wants them, and keep their wording consistent with the question each one tests. A directional hypothesis also commits the Unit 9 plan to a matching test.
What if the data needed for a question do not exist?
Then the question changes, or the study plans to collect the data through an instrument of its own. Discovering this in Unit 3 costs far less than discovering it at proposal. Check the actual field list or records schema with the organization early, rather than assuming a variable exists because a business seems likely to track it.
Where can I find a free GB730 Unit 3 sample paper?
This page holds a full GB730 Unit 3 question alignment exercise testing four draft questions for a hotel override study, with each failure named, three revised questions and hypotheses for occupancy and rate.
Why can a correlational design not answer a question with the word cause?
Without random assignment, other factors that differ between groups may produce the outcome. The design can estimate an association adjusted for measured factors, so the question should ask about association instead.