As deans, each of us has the task of not only building and improving a research culture but also measuring it. Needless to say, it鈥檚 a challenge. Just how do you put a number on intellectual output and the creation of knowledge that makes a difference?
We all have our ways. In the spirit of exchanging best practices, here鈥檚 my take on an eight-year experiment we鈥檝e undertaken at the Carroll School of Management.
Interspersed with my comments will be pages from what we simply call 鈥淩esearch Reports.鈥� These are three-page summaries compiled every spring, capturing the quantity and quality of a 艾可直播member鈥檚 research. The reports give us a transparent way of evaluating the research, one that lends to comparison across positions and departments.
We鈥檝e found these annual summaries to be very useful. They don鈥檛 explain everything about a professor鈥檚 research, and they shouldn鈥檛, but they do offer a starting point for discussion.听They're one measure鈥攁 good first approximation of research productivity and impact.听Naturally the data points come into play when considering tenure and promotion, but in my mind the real value is that they begin a conversation.
In the pages displayed here, you鈥檒l see the standard references to 鈥淚mpact Factor鈥� and 鈥淎rticle Influence.鈥� As you know, both of these refer to the quality of journals in which our professors are published. 鈥淚mpact鈥� relates to how often the average article in these journals is cited; 鈥渋nfluence鈥� gives greater weight to citations in higher quality journals.
You鈥檒l see references to 鈥淔inancial Times,鈥� specifically the top 50 journals used by the听Financial Times听in compiling its rankings of business schools from the standpoint of research output. Our measures also take account of how often a given journal鈥檚 articles are cited in Web of Science, and how often articles written specifically by our 艾可直播are cited in Google Scholar.
In addition, metrics are influenced by whether a 艾可直播member鈥檚 article is coauthored, and if so, how many collaborators there are (more about how we don鈥檛 necessarily penalize coauthorship in a moment).
Here is the first page of the Research Report that every 艾可直播member receives. It shows how their statistics are calculated:
| 听 | Research Metrics | Description |
| 1 | Impact Factor x publications divided by co-author | Impact factor divided by the total number of authors, summed over all publications from 2009 onwards. Impact factor is 5-year impact factor from the Web of Science (WOS). |
2 | Article Influence Score x publications divided by co-author | Article Influence Score divided by the total number of authors, summed over all publications from 2009 onwards. |
3 | Financial Times听Ranked x publications divided by co-author | A publication in a听Financial Times听journal is assigned a score of 1, 0 otherwise. Aggregated score is divided by total number of authors, and summed over all publications from 2009 onwards. |
4 | Impact Factor x publications | Metric (1) with no division for number of authors. |
5 | Article Influence Score x publications | Metric (2) with no division for number of authors. |
6 | Financial Times听Ranked x publications | Metric (3) with no division for number of authors. |
7 | Web of Science citations divided by co-author | The number of Web of Science citations for each publication, divided by total number of authors, summed over all career publications. |
8 | Google Scholar citations divided by co-author | The number of Google Scholar citations for each publication, divided by total number of authors, summed over all career publications. 听 |
On the second page, the 艾可直播member sees his or her research statistics and how they compare with colleagues in the department and school. I have the honor here of using as a sample the May 2016 Research Report for Jeffrey Pontiff, the James F. Cleary Chair in Finance.
As you鈥檒l read in this edition of听Carroll Capital, Jeff recently won the听Journal of Finance鈥檚听2016 Amundi Smith Breeden First Prize for his paper, 鈥淒oes Academic Research Destroy Stock Return Predictability?鈥� He collaborated with our former doctoral student R. David McLean, now at Georgetown University鈥檚 McDonough School of Business.
Research Statistics for Jeffrey Pontiff (Finance)
听听听 听 |
|
|
|
|
|
|
1 | Impact Factor x publications divided by co-author | 16.42 | 90 | 66 | 66 | 69 |
2 | Article Influence Score x publications divided by co-author | 17.84 | 90 | 96 | 84 | 69 |
3 | Financial Times听Ranked | 2.58 | 84 | 78 | 62 | 66 |
4 | Impact Factor x publications | 37.90 | 99 | 74 | 70 | 79 |
5 | Article Influence Score | 41.16 | 99 | 96 | 81 | 79 |
6 | Financial Times听Ranked | 6.00 | 98 | 84 | 66 | 77 |
7 | Web of Science citations divided by co-author | 506.92 | 99 | 92 | 63 | 88 |
8 | Google Scholar citations divided by co-author | NA | NA | NA | NA | NA |
I alluded earlier to the issue of coauthorship. I say 鈥渋ssue鈥� because there鈥檚 more than one way to account for articles coauthored by our professors. On the one hand, we want to encourage collaboration; on the other, we want to see signs of independent authorship as well. The upshot: we include some measures that (in effect) subtract points for coauthorship and others that don鈥檛.
Finally, I return to the broader question of quantifying the value of knowledge. I strongly believe that everyone鈥檚 research is nuanced, and to understand it well, you have to get beneath the data. Still, the data can tell you a lot.
All of us have goals in this regard鈥攁t the Carroll School, we are focused heavily on producing high-quality, impactful research. We need a measuring system compatible with this goal, not necessarily the whole picture of scholarly output, but at least a snapshot. We keep tinkering every year with our measuring system to make sure we鈥檙e getting the clearest possible picture.
I would be thrilled to share more details about our approach with readers of听Carroll Capital, and hear about your efforts to measure research accomplishments. Please feel free to听send me an e-mail.
I leave you now with the third and final page of Jeff Pontiff鈥檚 Research Report. 鈥淲OS鈥� refers to Web of Science, and the 50 journals ranked by the听Financial Times听are assigned a value of 1 (all others carry a value of 0).
List of Publications for Jeffrey Pontiff (Finance)
| 听 Publication | 听 Year | 听 Source | Financial Times Journal |
| Times- | 5-year Impact Factor | Article Influence Score |
1 | Reversions of excess pension assets after takeovers | 1990听 | Rand Journal of Economics | 1 | 2 | 38 | 2.29 | 3.02 |
2 | Private benefits from block ownership and discounts on closed-end funds | 1993 | Journal of Financial Economics | 1 | 2 | 61 | 5.88 | 6.02 |
3 | Closed-end fund premia and returns 鈥� Implications for financial market equilibrium | 1995 | Journal of Financial Economics | 1 | 0 | 37 | 5.88 | 6.02 |
4 | Costly arbitrage: Evidence from closed-end funds | 1996 | Quarterly Journal of Economics | 1 | 0 | 157 | 9.79 | 16.06 |
5 | Excess volatility and closed-end funds | 1997 | American Economic Review | 1 | 0 | 40 | 4.95 | 7.04 |
6 | Book-to-market as a predictor of market returns | 1998 | Journal of Financial Economics | 1 | 1 | 101 | 5.88 | 6.02 |
7 | How are derivatives used? Evidence from the mutual fund industry | 1999 | Journal of Finance | 1 | 1 | 84 | 7.55 | 9.86 |
8 | Market valuation of tax-timing options: Evidence from capital gains distributions | 2006 | Journal of Finance | 1 | 2 | 9 | 7.55 | 9.86 |
9 | Costly arbitrage and the myth of idiosyncratic risk | 2006 | Journal of Accounting & Economics | 1 | 0 | 62 | 4.68 | 3 |
10 | Shares Issuance and Cross-Sectional Returns | 2008 | Journal of Finance | 1 | 1 | 82 | 7.55 | 9.86 |
11 | Share Issuance and Cross-Sectional Returns: International Evidence | 2009 | Journal of Financial Economics | 1 | 2 | 23 | 5.88 | 6.02 |
12 | Idiosyncratic return volatility, cash flows, and product market competition | 2009 | Review of Financial Studies | 1 | 1 | 63 | 6.19 | 6.94 |
13 | Investment Taxation and Portfolio Performance | 2012 | Journal of Public Economics | 0 | 1 | 3 | 2.81 | 2.71 |
14 | Hierarchies and the Survival of POWs during WWII | 2012 | Management Science | 1 | 1 | 0 | 3.4 | 2.67 |
15 | The Year-End Trading Activities of Institutional Investors: Evidence from Daily Trades | 2014 | Review of Financial Studies | 1 | 3 | 3 | 6.19 | 6.94 |
16 | Shareholder Nonparticipation in Valuable Rights Offerings: New Findings for an Old Puzzle | 2016 | Journal of Financial Economics | 1 | 1 | NA | 5.88 | 6.02 |
17 | Does Academic Research Destroy Stock Return Predictability? | 2016 | Journal of Finance | 1 | 1 | NA | 7.55 | 9.86 |