DBAX 9104 Week 6 Limitations Section Example

Course	DBAX 9104 Business Research Project Stage 4
Week	Week 6
Paper type	Limitations section
Length	About 830 words, 6 pages
Format	APA 7 student paper
School	Walden University
Program	Doctor of Business Administration (DBA)
Updated	October 2026

Free sample paper for DBAX 9104 Week 6

The Limitations That Actually Arrived: Replacing a Proposal's Forecast With the Constraints Met in a Survey of Small Retailers' Intentions to Adopt Mobile Payment Systems, Starting With a Mid-Collection Change of Recruitment Source

Student Name

Walden University

DBAX 9104: Business Research Project Stage 4

Instructor Name

Month Day, Year

What this page is doingThe title contrasts forecast and encountered limitations and names the largest one, so the section's priorities are visible before it begins.

Forecast and Arrival

Chapter one of my proposal listed four limitations: a cross-sectional design, self-reported data, a sample limited to one state's retailers and possible low response. Two of these arrived much as forecast. One never materialized: the single-state limit fell away when recruitment expanded, though that expansion brought a larger problem. Two limitations were not forecast at all. This section replaces the proposal's list with the constraints the study actually met, in order of their effect on the conclusions.

What this page is doingThe section opens by comparing what the proposal forecast with what happened, which shows the reader that the list was rebuilt rather than copied.

The Study in Brief

The study surveyed owners of small independent retailers about their intention to adopt mobile payment systems, using constructs from the technology acceptance model, which Davis (1989) built around how useful and how effortless a system seems to its prospective users. The analysis tested whether perceived usefulness and perceived ease of use were related to adoption intention. Of 208 usable responses, the first 97 came from a state retail association's mailing list and the remaining 111 from an online business panel.

Unforeseen Limitation 1: A Change of Recruitment Source

After eight weeks, the retail association list had produced 97 usable responses against a target of 200, and two reminder rounds had stopped adding many more. With my chair's approval, recruitment moved to a commercial online panel of small business owners for the remaining six weeks. The switch is recorded in the deviation log with its date.

The two groups differ. Panel respondents were more likely to sell online, more likely to already accept some mobile payments and younger as businesses. Walter et al. (2019) compared results from online panels with conventional samples and found that relationships among variables often converge while levels of variables can differ. That pattern fits what happened here. The most likely direction of bias is toward higher adoption intention: retailers already selling online are closer to adopting mobile payments. The conclusion this weakens is the descriptive one, that most small retailers intend to adopt within two years. That conclusion rests heavily on panel respondents and is now stated separately for each source. The relationships between perceived usefulness, ease of use and intention were estimated in both groups separately and were similar in direction and size, so the main conclusion about those relationships is weakened less.

Table 1

Respondents by Recruitment Source

Characteristic	Association list (n = 97)	Online panel (n = 111) \|
Sell online as well as in store	38 percent	71 percent \|
Already accept card payments by phone or tablet	22 percent	49 percent \|
Years in business, median	14	7 \|
Located outside the original state	0 percent	64 percent \|
Mean adoption intention, 1 to 7 scale	4.1	5.3 \|

Characteristics from the survey's background items.

What this page is doingThe section states the likely direction of bias and the conclusion it weakens, rather than only that a bias may exist.

Unforeseen Limitation 2: One Respondent, One Questionnaire

Perceived usefulness, perceived ease of use and intention were all measured in one questionnaire answered by one person per firm, at one time. Podsakoff et al. (2003) describe this as a classic condition for common method bias, in which shared measurement inflates the relationships among constructs. The proposal mentioned self-report but did not anticipate how much of the analysis would rest on relationships among self-reported constructs. A single-factor test showed that no one factor accounted for most of the variance, but Podsakoff et al. (2003) caution that this test is weak. The relationships reported may therefore be somewhat larger than they would be with separate sources. The conclusion affected is the strength of the association, not its existence.

Forecast Limitations That Arrived

The cross-sectional design limits the study to association, as forecast; no conclusion uses causal language. Low response arrived as forecast, at a response rate of about 9 percent from the association list. Groves and Peytcheva (2008) found that response rates alone predict nonresponse bias poorly, so the low rate is reported as a reason for caution, not as proof of bias.

The Forecast Limitation That Did Not Arrive

The single-state limit did not hold, because 64 percent of panel respondents were outside the original state. That broadened the sample geographically but in an uncontrolled way, which is why it is discussed under the recruitment switch rather than counted as a gain.

Limitations and the Conclusions They Bound

The closing chapter now attaches each limitation to the conclusion it bounds. The descriptive estimate of adoption intention carries the recruitment limitation and is reported by source. The relationships among model constructs carry the common method limitation. No conclusion is left without the limitation that applies to it, and none is weakened by a limitation that does not.

A Note on Candor

Reporting a mid-study change of recruitment source can feel like admitting a flaw. It is a flaw, but an unreported one would be worse, because anyone setting the method chapter beside the sample description would spot the change anyway.

References

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

Groves, R. M., & Peytcheva, E. (2008). The impact of nonresponse rates on nonresponse bias: A meta-analysis. Public Opinion Quarterly, 72(2), 167-189. https://doi.org/10.1093/poq/nfn011

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

Walter, S. L., Seibert, S. E., Goering, D., & O'Boyle, E. H. (2019). A tale of two sample sources: Do results from online panel data and conventional data converge? Journal of Business and Psychology, 34(4), 425-452. https://doi.org/10.1007/s10869-018-9552-y

DBAX 9104 Week 6 instructions, in plain terms

In this week you write the limitations section of your closing chapter from what happened, not from what the proposal anticipated. Begin by comparing the limitations forecast in chapter one with those that arrived, noting any that never materialized. Give the most space to the limitation that most affects your conclusions. For each one, describe what happened and when, show how it may have shaped the data, state the likely direction of any bias and name the specific conclusion it bounds. Distinguish limitations that weaken descriptive results from those that weaken relationships. Avoid boilerplate that could apply to any study. Support each with a methods source. Two to three pages is typical, and a small table comparing groups can carry the evidence for a recruitment problem.

How this DBAX 9104 Week 6 example is built

The section compares the four forecast limitations with what arrived: two held, one vanished and two were new. A brief study description precedes the largest new limitation, the mid-collection move to an online panel, approved by the chair and dated in the deviation log. A five-row table compares the 97 association respondents with the 111 panel respondents on online selling, existing mobile payments, years in business, location and mean intention. The section judges bias toward higher intention, weakening the descriptive claim about adoption, while relationships estimated separately by source looked similar, as Walter and colleagues' comparison of sample sources would predict. Common method bias from one respondent and one questionnaire follows. Forecast limitations, the one that never arrived and a mapping of limitations to conclusions close the section.

Reading the DBAX 9104 Week 6 rubric

Instructors can tell recited limitations from encountered ones within a paragraph. A section listing self-report, cross-sectional design and generalizability with nothing tied to this study reads as boilerplate and loses marks. The recruitment change carries most of the analytic weight: dating it, comparing the two groups and stating the direction of bias show the author understands what happened to the evidence. Credit also depends on connection, since a limitation that names no conclusion leaves the reader to guess its effect. Separating effects on levels from effects on relationships is a mark of doctoral judgment. Common method bias earns credit when it is described as a condition present in the design, with its likely consequence, not as a generic caution. Sources should support each judgment.

DBAX 9104 Week 6 help from the desk

The quickest way to a weak limitations section is to copy chapter one's list and add a sentence to each. Start instead with your deviation log, field notes and response records, and list everything that went differently from the plan. For each item, ask what it did to your data and which way it would push your results. Then match each to the conclusion it affects, and say whether it threatens a level, a relationship or both. Do not hide a mid-study change; a reader comparing your method and sample sections will find it. Keep the tone factual rather than apologetic. If you are unsure of the direction of a bias, say what evidence would tell you. Our consultants can set out a two-group comparison from your response records with you.

Get a DBAX 9104 Week 6 example written to your instructions

Send the Week 6 prompt and rubric along with the limitations your chapter one anticipated and anything that went differently during data collection. A limitations section tying each constraint to the conclusions it affects returns within 24-48h; the first costs nothing. The example study is a stand-in, so the limits described are illustrative rather than yours.

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DBAX 9104 Week 6 questions, answered

Where can I find a free DBAX 9104 Week 6 sample paper?

The full Week 6 limitations section, with its respondent comparison table, is available on this page without any charge.

What was the largest unforeseen limitation in the DBAX 9104 Week 6 sample?

A switch from a retail association mailing list to an online business panel after eight weeks of low response.

Which way would the recruitment change bias the results?

Toward higher adoption intention, because panel retailers more often sold online and already used some mobile payments.

Which conclusion does that limitation weaken?

The descriptive estimate of adoption intention, which is now reported separately for each recruitment source.

How is common method bias handled?

As a design condition, since all constructs came from one respondent per firm in one questionnaire, possibly inflating relationships.