Today I’m discussing another paper that uses Total Q. I won’t spend too long on that. I have said plenty elsewhere about how bad Total Q is as a measure of firm performance. In this post, I want to somewhat sympathize with the authors of a paper that uses Total Q. I will tell a story that I have no idea whether it is true. I might be completely wrong in my guess about what happened as I don’t know the authors. Still, my tale feels plausible from my knowledge of peer review and reading of the paper. It is a tale of how reviewers might scupper a paper. My main message is that not all papers must feature firm performance. Please don’t add things that don’t make sense just to say you have got to firm performance.
A Business Case For A Moral Argument
Patel and Feng were interested in whether LGBT Workplace Equality Policies make business sense.
While advocacy for LGBT rights should be a moral and ethical imperative for all firms, from a marketing perspective the “business case” for this policy is not necessarily clear.
Patel and Feng, 2021, page 7
This is an interesting question. It requires a bit of careful writing. Such policies are just morally good so some will ask, ‘why even test whether they are good for business?’ After all, we should just do them anyhow. Still, I have a lot of time for Patel and Feng, and those taking a similar approach. While arguing something is moral is great there is no harm in having a secondary argument of — “it is good business”. You can always unveil the secondary argument if the moral case isn’t winning everyone over. As long as you get to the right outcome it doesn’t matter too much how you got there.
Anti-workplace discrimination policies can stop discrimination, a worthy goal, even if the motives behind them weren’t pure. I’m a big fan of trying to win a little lazy, somewhat self-centered, and a tad greedy people over with whatever arguments you make. This is especially important because pretty much all human beings are, at least somewhat, lazy, self-centered, and greedy. Let’s make arguments that help us make progress in the world we have rather than assume we are in a place where everyone is going to be saintly and just do the right thing.
LGBT Workplace Equality Policy And Customer Satisfaction
The authors look at the link between LGBT-friendly policies and customer satisfaction. It is an empirical piece, i.e., they crunch data to say that LGBT-friendly policies help. One can imagine that who your customers are would make a big difference to the relationship between LGBT-friendly policies and customer satisfaction. That said, my main focus isn’t really on their findings. It is what seemed to happen next.
Did The Reviewers Break The Paper?
The authors didn’t really seem to be that interested in going to firm performance in the main body of the paper. I think this is sensible. A good lesson in published papers is don’t try things unless you can do them well. That said, they suddenly spring a “supplementary analysis and results” section on the reader. It is not at all good.
They add this small section using Total Q as their measure of firm performance. They tell us that:
Total q is measured as the ratio between market value and the sum of the physical assets and the estimated replacement costs of intangible capital.
Patel and Febg, 2021, page 20
But Total Q isn’t that. It capitalizes a, somewhat arbitrary proportion of expenses, to generate a proxy for intangible capital. At no point does anyone, in the Peters and Taylor method the authors cite, properly estimate the replacement cost of intangible capital. If we had a good estimate of intangible capital that would be great but we don’t.
Still, I’m not going on about Total Q and its use as a measure of firm performance. The point is that they randomly shoehorn a really disappointing section onto the end of their paper.
This is where my story comes in. I’m guessing the reviewers are the guilty party. The reviewers probably broke the paper.
Not All Papers Must Feature Firm Performance
Why can’t the authors just look at the link between LGBT-friendly policies and customer satisfaction? Why did they have to add non-credible claims about the impact on long-term firm performance based upon simply incorrect statements about Total Q? I’m guessing a reviewer said: “But we need to get to firm performance to show what you are doing is important”. (Important to whom is a valuable question, surely LGBT-friendly policies are important in themselves, but let’s get beyond that).
The authors probably didn’t have any idea what to do because that wasn’t what they were studying. They likely searched around, e.g., looked at Google Scholar, for a way to do it. Maybe the reviewer even “helpfully” suggested Total Q. The authors then tacked on a supplementary analysis using Total Q. Do I believe it? No, of course I don’t. Do they? I very much doubt it. But the reviewer suggested it had to happen, and so it happened I’m guessing.
A key lesson is that not all papers must feature firm performance. If adding in firm performance, given the data you have, doesn’t make sense then please don’t do it. Better to report something you believe in despite it being limited in scope than something you don’t believe in that has all the bells and whistles. [The good thing about being tenured is I can issue such smug advice.]
Here is my Total Q flowchart giving advice on when to use it.
For more on Total Q see here, here, and here.
Read: Pankaj Patel, Cong Feng (2021) LGBT Workplace Equality Policy and Customer Satisfaction: The Roles of Marketing Capability and Demand Instability, Journal of Public Policy and Marketing, 40(1), 7-28
