US Green Goods SMEs, 2008-2012

Published: 20 Aug 2019 | Version 1 | DOI: 10.17632/v8br9dgvsw.1
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Description of this data

Measuring dynamic capabilities in new ventures: Exploring strategic change in US green goods manufacturing using website data. Firm website and Dun and Bradstreet (DUNS) measures, US Green Goods SMEs, 2008-2012 (212 data variables; 298 total observations; 223 observations without missing variables). Anonymized. Stata dta format and Stata do file. The website data for the target firms is derived from archived website data from the Wayback Machine. We also use business data for these firms from Dun and Bradstreet. See associated paper for added details including definitions of "green goods" manufacturing and small and medium-sized enterprises (SMEs); enterprise sample selection; and methods applied to use website data combined with other available business data to gauge enterprise capabilities for market sensing and responding. In the analytic model, we use data variables for two time periods, 2008-09 and 2010-11, to explain sales growth for green goods enterprises in two later time periods, from 2010 to 2012.

Experiment data files

Steps to reproduce

The "firm_website_and_duns_measures.dta" file is a Stata .dta dataset comprising 212 data variables developed for the analysis reported and published in Arora et al (2019) "Measuring dynamic capabilities in new ventures: exploring strategic change in US green goods manufacturing using website data," Journal of Technology Transfer, DOI: 10.1007/s10961-019-09751-y. There are 298 firm observations in this data set. The "jtt-code.do" file is a Stata .do file that will reproduce key models and regression results reported in the paper for the 223 firm observations without missing variables. To undertake a new analysis with the same data set of firms, users may modify the Stata .do file. It is also possible to import the .dta data set into a file format useable by other statistical analysis programs. To undertake a new analysis with a different set of firms, it will be necessary to obtain the public website data for those firms, following the methods for web crawling, keyword variable extraction, and LDA topic modeling described in the paper, and to match with Dun and Bradstreet firm data. Additional references related to these methods are included in the paper.

Related links

Latest version

  • Version 1

    2019-08-20

    Published: 2019-08-20

    DOI: 10.17632/v8br9dgvsw.1

    Cite this dataset

    Arora, Sanjay K.; Li, Yin; Youtie, Jan; Shapira, Philip (2019), “US Green Goods SMEs, 2008-2012”, Mendeley Data, v1 http://dx.doi.org/10.17632/v8br9dgvsw.1

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Institutions

The University of Manchester

Categories

Entrepreneurship, Web Mining, Big Data, Dynamic Capability, Small to Medium Enterprise, Text Mining

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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