How to get Published

What makes a paper interesting to a reader?

  • Relevant (useful)

  • Challenges causal assumptions (Different)

  • Significant extension of current theory (likeable, useful)

  • Compare, Contrast, Categorize (useful)

  • Offers future orientation (imaginative)

  • Addresses a current problem (important)

  • Makes abstractions meaningful (imaginative)

  • Can you prescribe? (important)

  • Does the paper provide new insight that broadens understanding of what is happening in/to real-world organizations?

  • Can you influence people with this paper?

What does the reviewer look for?

  • Does this research make past concepts more precise?

  • Does its design limit the generalizability of the theory than past research?

  • Does the test privilege the theory?

  • What does the research tell me about the theory that I did not know before? How?

  • Can this be written better?

Why are manuscripts rejected?

  • No theory

  • Explain what variables mean and why they are related the way they are. The theory provides the story that gives data their meaning.

  • Concepts poorly operationalized

  • The concepts and the operationalization have to be in alignment – the macro-level concept can not be operationalized at the micro-level (e.g.) technology and structure; #of hospital beds as a measure of complexity. These do not give confidence in the findings as to the operationalization measures a different concept.

  • Insufficient definition – theory

  • Don’t do new labels for old measures if you don’t have theoretical backing. Justify variables in your study; don’t stick them in because another study did.

  • Insufficient rationale – design

  • In a study of Information processing, tell us what you mean by information and how it differs from data. Explain why the sample and procedure are appropriate to test the research question.

  • Poor organization, flow, style: macrostructure

  • Provide a clear road map, avoid frequent parenthetical statements and footnotes, asking the reader to see another paper to know what is meant here, referring ahead to future parts of the paper for an explanation. The paper has to be disciplined and not jump around.

  • Inadequate research design

  • Avoid contrived emphasis in the paper. Demonstrate that there are no gaps in your understanding of the literature. Build on previous research constructively and not by demolishing previous work.

  • Over-engineering, cutting up data

  • Don’t write up as if you have all the answers. The more you transform the data through methodological manipulations, the farther you get from the operational base of the data.

  • Conclusions not aligned to research

  • Describe your conclusions interpreting the findings and showing how the data add to or modify original theory, and state explicitly how the study adds to the developing knowledge base within the field.

  • Not relevant to the field

  • Don’t stray far beyond your empirical base. Use the conclusion to fully develop the theoretical contribution and point out the new understanding from the study.

How can I avoid rejection?

  • Tell a story

  • Discuss your procedures and thought processes

  • Concentrate on the macrostructure

  • Stick to the operational base of your research

  • Listen to your reviewers

  • Allow the manuscript to ripen naturally

  • Don’t exaggerate

If your operational measure is technology, don’t talk about ideology; if your operational measure is size, don’t talk about complexity. If your message does not get through the way you have written it, change it. With each revision, the paper matures; use your colleagues for feedback. Theory development and writing style come slowly with many iterations.

How can I get published?

  • Know who your audience is

  • Ask the questions: Who is this paper for? For what purpose? Who is going to cite my work and why?

  • Getting published requires persistence

  • Avoid data glut

  • Offer research and theory, not journalism

  • Scholarly publications count more as references

  • Read, and read well before you write

  • Think about what you have read

  • Write what you think and what you did, not about what someone failed to do

  • Non-significant results are publishable if the research is significant

  • Write theory to become famous; collect data first

  • Write up what you have been doing and thinking

  • Commit yourself to the data and ideas, not just getting published


Baba, V.V. (2002). Beyond measuring Canadian business school research output and impact: A commentary. Canadian Journal of Administrative Sciences, 19, 3, 207-209.
Barley, S.R. (2006). When I write my masterpiece: Thoughts on what makes a paper interesting. The Academy of Management Journal, 49, 16-20
Cummings, L.L., & Frost, P.J. (1995). Publishing in the Organizational Sciences (2nd Edition), Thousand Oaks, CA: Sage
Stablein, R.E., & Frost, P.J. (2004). Renewing research practice. Stanford, CA: Stanford University Press

Canadian Journal of Administrative Sciences Revue canadienne des sciences de l´administration