DDBA 8300 Week 11 Design Defense Paper Example

Answering the Questions a Numbers-Minded Reviewer Will Ask: A Written Design Defense for an Interview Study of Why Mid-Sized Home Builders Adopt, Abandon or Decline Off-Site Construction, and What It Will Never Know

Student Name

Walden University

DDBA 8300: Qualitative and Quantitative Methodology for Applied Business Research

Instructor Name

Month Day, Year

Answering the Questions a Numbers-Minded Reviewer Will Ask: A Written Design Defense for an Interview Study of Why Mid-Sized Home Builders Adopt, Abandon or Decline Off-Site Construction, and What It Will Never Know

The Study Being Defended

My study asks: "How do owners and senior managers of mid-sized home builders decide whether to adopt, continue or abandon off-site construction methods such as wall panels, floor trusses and modular units?" Mid-sized builders, those completing roughly 100 to 1,000 homes a year, face labor shortages that off-site methods promise to ease, yet adoption remains uneven, and some builders who tried panelized framing have returned to building on site. I will interview about 18 owners and senior managers from builders in four Southeastern and Midwestern states, chosen to include builders who adopted and continued, adopted and abandoned and considered and declined. A committee member who favors quantitative research is likely to raise five challenges. This defense answers them in writing before the meeting.

Challenge 1: "Eighteen builders cannot tell us anything general."

That is correct, and the study does not claim to. Its findings will not estimate how many builders adopt or what predicts adoption across the industry. The study aims to describe how the decision is made, including reasons and sequences that are not yet in the literature. Edmondson and McManus (2007) argued that research on phenomena in an early state of understanding should aim at building constructs rather than testing them, and builders' decisions about off-site methods are at that stage. The findings will be transferable in the sense that readers can judge whether they fit similar builders, which depends on describing each builder's context fully, as the method chapter commits to doing.

Challenge 2: "Why not survey builders and test what predicts adoption?"

A survey would answer a different question, and it would need to know in advance what to ask. My preliminary conversations with four builders surfaced reasons I had not expected, among them insurance and lender requirements for modular homes, inspectors unfamiliar with panelized walls and framing crews who resisted. A survey written before those conversations would have missed them. Once this study identifies the main reasons, a survey testing how widespread they are would be a valuable next study.

Challenge 3: "How will you know you are not just finding what you expect?"

Three steps address this. Before interviewing, I recorded my expectations in a dated memo. A second coder, a classmate with no construction background, will code four transcripts independently, and we will compare codes and discuss differences. And participants will receive a summary of findings and be asked whether it fits their experience. Tracy (2010) lists such practices under credibility, one of several markers of quality in qualitative work.

Challenge 4: "Self-reported reasons may not be the real reasons."

This is the strongest challenge, and it is partly right. Builders may present a decision to abandon panels as a careful business choice when it followed a single bad project. Interviews alone cannot fully separate the reasons people give from the reasons that operated. The design reduces the problem by asking each participant to walk through specific projects and decisions in sequence rather than to state general reasons, and by asking for documents, such as cost comparisons prepared at the time, where builders are willing to share them. But the study will report what builders say and did, not what caused their decisions in a causal sense.

Challenge 5: "How did you decide on eighteen?"

Malterud et al. (2016) proposed that the number of participants depends on the study's information power: a focused aim, participants who lived the decision and good dialogue each lower the number required. My aim is focused on one decision, and every participant made or shaped it. Interviewing will end once two interviews in a row bring no new reasons or decision sequences, and I will report the point at which that happened.

What the Study Will Never Know

The study will not know how common each pattern is among mid-sized builders. It will not know whether builders who adopted off-site methods became more profitable, since it does not examine financial outcomes. It will not know what builders in other regions, with different labor markets and codes, would say. And it will not know with certainty whether the reasons participants give are the reasons that drove their decisions. Yin (2018) notes that every design trades some kinds of knowledge for others; this one trades breadth and causal inference for an account of how the decision is actually made. The proposal states each of these limits beside the finding it bounds.

Why the Design Still Holds

The business problem is that builders are making expensive, hard-to-reverse decisions about construction methods with little shared understanding of how peers have decided. A study that describes those decisions in depth, honestly bounded, answers that problem directly.

References

Edmondson, A. C., & McManus, S. E. (2007). Methodological fit in management field research. Academy of Management Review, 32(4), 1246-1264. https://doi.org/10.5465/amr.2007.26586086

Malterud, K., Siersma, V. D., & Guassora, A. D. (2016). Sample size in qualitative interview studies: Guided by information power. Qualitative Health Research, 26(13), 1753-1760. https://doi.org/10.1177/1049732315617444

Tracy, S. J. (2010). Qualitative quality: Eight "big-tent" criteria for excellent qualitative research. Qualitative Inquiry, 16(10), 837-851. https://doi.org/10.1177/1077800410383121

Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications.