research

Weekly Reads – Jun 17

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It has been quite a while since I’ve updated my blog. I was busy with finishing my PhD and securing my postdoc position. I’m still pursuing academia for now and thus, would still have to continue reading the literature for the latest advances in the management sciences. These are my interesting reads of the week.

Disruption Versus Discontinuity: Definition and Research Perspective From Behavioral Economics – I have to admit that I use the terms disruption and discontinuity interchangeably. This articles explains the difference between the two. Discontinuity refers to when a new technology competes directly with an established one based on having better performance on some technological dimension (typically 10x better). On the other hand, disruptions attach dominant technologies by satisfying customer needs even though they may not be performing as well on this primary dimension.

Technological impact of biomedical research: The role of basicness and novelty – another study looking at patents and publications to assess the impact of research.

The European research landscape under the Horizon 2020 Lenses: the interaction between science centers, public institutions, and industry – contains nice network visualizations of interacting partners at various levels (country, affiliations and organizations)

Anchor entrepreneurship and industry catalysis: The rise of the Italian Biomedical Valley – fascinating account on the role of entrepreneurship in transforming a depressed rural area into an internationally known medical-device cluster. I especially like how much they take into account the role of luck in the story of this entrepreneur Mario Veronesi: “many of Veronesi’s successes came accidentally, a result of serendipity, being present at the dawn of an emerging medical field that married knowledge about renal and cardiac treatment to improved plastics.”

From creative destruction to creative appropriation: A comprehensive framework – study exploring Didi, usually called China’s Uber. I appreciated the typology in the paper talking about the other forms of creative destruction. Destruction is when a firm outright does not cooperate with the incumbents. Creative cooperation is when incumbents work together with the disruptors. In the middle of these two is creative appropriation, where a firm disrupts a market by leveraging the complementary resources of an incumbent without directly cooperating with them.

Bibliometrics as a Tool for Literature Review

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Literature review can be a tedious process. With so many articles to read, new researchers in a field can find themselves stuck, trying to stay on top of all the readings required. In an effort to streamline the process, bibliometrics can be a powerful tool to make the article selection more efficient, adding a visual component to it.

Last November 10-11, I gave a talk on bibliometric methods at the 8th joint PhD workshop of VU Amsterdam and FH Munster. I got really great response from my talk, with people asking me to make a manual on the topic. Though I only started using bibliometrics three months ago, I found that learning the basics to be a very useful investment. In this post, I will try to create a simple manual on the basics of the method.

Benefits of Bibliometrics

Especially for researchers, here are some things you would be able to do after reading this post:

  • Get an overview of the important publications in your field of study
  • Generate a database of important researchers and institutes in your field
  • Visualize how your field is connected

Workflow

Though there are many ways to do this, I found using the Web of Science as database and the bibliometric software VosViewer and CitiNetExplorer to have the easiest learning curve. The process generally is composed of the following steps:

  1. Formulating keywords
  2. Downloading the articles from the database
  3. Generating the maps using the software

Formulating the Keywords

The first part is just the regular literature search on the Web of Science. Most scientists would be knowledgeable already on this area, having done literature search in the past. Though the basic search would usually suffice, it would be more efficient to learn how to use the advanced search with the Boolean operators.

For example, if you are researching on entrepreneurship in the Netherlands. You want to search the terms entrepreneurship and Netherlands together. At the same time, you might want to include related words like business or industry and even the words Holland and Dutch. With these in mind, your keyword search could be:

TS = ((entrepreneurship OR business OR industry) AND (Netherlands OR Holland OR Dutch))

This yielded 3,381 results as of Nov 2016. A preliminary look at the results can then be done. At this point, you can decide to reformulate the keywords or stick with the results.  The good thing is that you can easily change your keywords if the list of articles fail to reflect your intended outcome.

Downloading the articles

This part is the easiest yet most tedious. The problem with the Web of Science is that you can only download 500 article data at a time. Thus, if you have 3,000 articles, then you have to repeat the saving process 6 times.

At the results page, what you want to do is click the down arrow beside ‘Save to EndNote online’ and click ‘Save to Other File Formats’

Afterwards, save the first 500 records by typing at the records space 1 to 500. Also, for the record content should be with the cited references. And finally, click send.

You will then have a text file containing information about the first 500 records.

To save the next 500, click again the down arrow and save records 501-1000, 1001-1500 and so on.

Using the Software

With the articles downloaded, it is now possible to analyze them with the software. Download  CitNetExplorer. It’s just a matter of loading the text files into the program. It automatically generates a map of the most cited papers in your set of papers. This software is smart such that even if an article does not have the keywords you used, it can still be included if it is cited a lot by the papers in your database.

More importantly, it also shows the connection among these papers. Through this, one can infer how the field developed and how ideas have evolved over time. By being able to visualize how these papers are related to one another, doing literature review then becomes a little bit easier.