Review of Quantitative Article on Intellectual Protection
*Area of interest - Intellectual Property Rights (IPR) Laws in Pharmaceutical Industry Are in the Continuous State of Evolution in Emerging Markets.
Peer-reviewed, data-based article examples (You can find any other relevant source(s):
(1.) Gentile, E. (2020). Intellectual Property Rights and Foreign Technology Licensing in Developing Countries: An Empirical Investigation. Economic Development & Cultural Change, 68(2), 655–698. https://doi(dot)org/10.1086/701212
(2.) Motari, M., Nikiema, J. B., Kasilo, O. M., Kniazkov, S., Loua, A., Sougou, A., & Tumusiime, P. (2021). The role of intellectual property rights on access to medicines in the WHO African region: 25 years after the TRIPS agreement. BMC Public Health, 21(1), 1-19. https://bmcpublichealth(dot)biomedcentral(dot)com/articles/10.1186/s12889-021-10374-y
This is the final paper (previous paper is attached here).
ATTACHED ARE "Signature assignment instructions"; "week 5-8 discussions (Please use these in writing the paper)'; "paper writing guidelines by the professor"; and previous paper which was written based on week 1- 4 discussions.
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Find a peer-reviewed, data-based article in the TUW library associated with the topic you are considering for your *area of interest. Do NOT use the same article as used in your previous paper (written based on week 1- 4 discussions).
In 8-10 pages, provide the section headings as illustrated below and address the following:
A. SUMMARY: Summarize the article very briefly (no more than 1 page)
B. DESCRIPTIVE STATISTICS: Discuss the raw data presentation and discuss the descriptive statistics used to present the data – be sure to include both averages and distributions.
(1) Were these appropriate averaging techniques and examinations of the distribution?
(2) Could other types of averages or distributions have been used?
C. SCALES OF MEASUREMENT: Discuss the scales of measurement and the methodologies used.
(1) Were these appropriate scales and methodologies?
(2) Could other types of scaling have been used?
D. VISUAL PRESENTATION: For the visual presentations of raw data or averages, are there biases in the presentation.
(1) What conclusions do you draw simply by looking at the visual data presentation?
(2) How could the presentation be altered to adjust those conclusions?
E. INDIVIDUAL DATA: How were individual data reported (if at all)?
(1) What are the differences between individual results and the mean results?
(2) If not reported, do you have any concerns about what information might have been lost?
F. INFERENTIAL STATISTICS: What inferential statistical tests were used?
(1) Briefly summarize each.
(2) Why were those tests appropriate? Could other tests have been used?
G. Based on this article, what could you glean from it to use in your *Area of interest / research project?
Writing Guidelines: - • Running head and pagination. • The length of this paper should be between 8-10 pages (not including the cover or title page, table of contents, reference page and Appendices page). • APA style formatting (7th edition), double spaced, with 1-inch margins and 12 point Times New Roman font. • Add an EXECUTIVE SUMMARY (including THESIS statement) at the beginning of the document; and add INTRODUCTION and CONCLUSION paragraphs. • Please include TITLE PAGE, TABLE OF CONTENTS PAGE, REFERENCE PAGE, and any APPENDICES. • Please submit in a word document and NOT pdf version. • Please use HEADINGS AND SUBHEADINGS to organize your paper. • Use at least 10 academic, peer-reviewed, library trade publications, scholarly or professional practitioner sources, and minimum 40 in-text CITATIONS are required. • You must cite and reference all texts used, including page numbers as applicable to avoid plagiarism. • Please provide verifiable links/web address for each academic reference used. • Paper should be proofread for spelling and grammar mistakes. • Write your paper in an integrated fashion, weaving theory and application. In other words, do not merely respond to each bullet above as a checklist.
Professor’s Additional instructions – Please: - Use third person in writing. - Do not use quotes. - Use APA formatting (7TH Edition) of references and in text citations is required. - the following resources are NOT ACCEPTABLE as citations for this paper: • Wikipedia.com • Ehow.com • Dictionary.com • About.com • Smallbusiness.chron.com • Diffen.com • Yourbusiness.azcentral.com • Tjmarino.com • Investopedia.com • Boundless.com and Lumen • CourseHero.com • Chegg.com • Difference between • Answers.com • Any student essay website.
Review of Quantitative Article on Intellectual Protection
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Executive Summary
A review of data analysis and presentation approach in a quantitative study conducted in a field of interest can provide essential insight that one can use to inform decisions in a doctoral research project. In the current paper, the descriptive and inferential statistics used to analyze and present the dataset collected for the study in the article “Intellectual Property Rights and Foreign Technology Licensing in Developing Countries: An Empirical Study” are reviewed. In the article, Gentile (2019, pp. 1-32) explores whether expanded and enhanced protection of intellectual property has a positive impact on technology transfer in developing countries. While the researcher did not effectively present descriptive data to make it easy for the reader to understand the broad characteristics of the dataset, an ideal choice regarding the types of inferential tests used to answer the study question was made. The review will provide insights that will allow me to complete my doctoral research project effectively.
Table of Contents Executive Summary. 2 Introduction. 4 Article Summary. 4 Descriptive Statistics. 5 Scales of Measurement 6 Visual Presentation. 7 Individual Data. 8 Inferential Statistics. 8 Insight from Article. 10 Conclusion. 11 References. 12
Review of Quantitative Article on Intellectual Protection
Introduction
The extent to which a reader understands the empirical data presented in a research article depends on the researcher’s choice of descriptive and inferential statistics. To this end, a researcher has to use effective descriptive statistics to present the broad characteristics of a dataset collected to answer given research questions and choose the best inferential statistics to answer the research questions. In the empirical article “Intellectual Property Rights and Foreign Technology Licensing in Developing Countries: An Empirical Study,” the researcher uses both descriptive and inferential statistics to present the dataset collected for the study. The present paper reviews the researcher’s decision on the use of descriptive and inferential statistics to gain insights that can inform the decision in a doctoral research project. A review of data analysis and presentation approach in a quantitative study conducted in a field of interest can provide essential insight that one can use to inform decisions in a doctoral research project.
Article Summary
In the article “Intellectual Property Rights and Foreign Technology Licensing in Developing Countries: An Empirical Study,” Gentile (2017, pp. 1-37) examines whether the expanded and enhanced protection of intellectual property has a positive impact on technology transfer in developing countries. To this end, the researcher conducted a cross-analysis of firms from 42 countries using a dataset constructed from 33,372 interviews from the World Bank Enterprise Survey database (Gentile, 2017, p. 6). The 42 countries were spread over Europe and Central Asia, Sub-Saharan Africa, the Middle East and North Africa, and Latin America and the Caribbean.
The analysis of the data revealed two main conclusions. First, the researchers discovered a positive and statistically significant relationship between the protection of intellectual rights and foreign technology licensing for affiliated firms (Gentile, 2017, p. 22). The finding was in line with existing literature, which has shown that there is no positive relationship between IP protection and foreign technology licensing in unaffiliated firms. Second, the researchers found that the operating environment had a moderating effect on the relationship between IP protection and firm-level technology licensing, whereby Gentile (2017, pp. 22) found the operating environment to be a moderating variable of the relationship between IP protection and technology licensing at the firms that operate in upper-middle-income countries. The researcher found that firms operating in low-income and lower-middle-income countries did not report a correlation between IP protection and technology licensing (Gentile, 2019, p. 27). Overall, the data indicated that firm characteristics had a significant influence in determining its technology licensing status.
Notably, the study is limited by the binary nature of the dependent variables as the researchers could only capture how licensing activities responded to changes in IP policies (Gentile, 2019, p. 22). Nonetheless, the study provides a basis for future investigation on the potential indirect effects of tighter protection on technology adoption (Gentile, 2017, p. 22).
Descriptive Statistics
Descriptive statistics are an essential element in presenting the findings of an empirical study. To this end, researchers rely upon descriptive statistics to present broad aspects of the dataset after the combination of single values from an observational point of view (Clippinger et al., 2017, pp. 62-70). In the article, Gentile (2017, pp. 27-33) mainly uses descriptive data to present broad characteristics of the collected data. The author uses descriptive data to present the broad characteristics of the dataset. To this end, Gentile (2017, pp. 27) groups the dataset based on the country and the average proportion of firms with foreign technology licensees for each country. The researchers also used averages to present data on small and medium enterprises with domestic ownership and domestic sales.
Notably, the use of averages to present the broad characteristics of the dataset was ideal. However, the researcher could have used more forms of descriptive data to allow facilitate the understanding of the constructed dataset. Gentile (2017, pp. 27) largely groups the data based on year. A potential descriptive statistic that could have been used to facilitate the understanding of data was the use of distributions based on the common characteristic of the independent variables. For example, Son (2019, p.4) presented his descriptive data using the distributions with the geographical regions being the grouping variable. In the study, Gentile should have grouped the countries based on regions and presented descriptive data based on the regions (Goos & Meintrup, 2015, pp. 52-105).
In addition, the researcher should have used standard deviation to increase the reader’s understanding of the firm’s characteristics. Epstein (2020a, p.1) notes that standard deviation is a statistical measure of the dispersion of a dataset around the mean that gives a measure of how spread out the data is. To this end, Gentile (2019, p. 27) could have improved the presentation of the broad characteristics of the data by including standard deviations of the analyzed data.
Scales of Measurement
The scales of measurement used in a study are essential as they determine the types of statistical analyses that can be performed on the data. Different scales of measurement require different statistical techniques, and using the wrong statistical technique for a particular scale of measurement can lead to incorrect or misleading results (Hunter-Thomson, 2019, pp. 84-88). In the article, Gentile (2019, p. 27) uses a nominal scale of measurement to collect data such as the name of the country of study, the region in which the countries can be classified, and the years when the data was collected. Notably, a nominal scale is used to classify data that do not have a meaningful order or ranking (Clippinger, 2017, pp. 62-70). Consequently, the researcher mainly used distribution to describe the nominal data, as the various categories of nominal data cannot be compared to each other (Gentile, 2019, p. 27).
Further, the researcher uses the ratio scale to collect data about the proportion of licensees, the number of firms, and the index of patent rights (Gentile, 2019, p. 27). A ratio scale is used to measure data that has a meaningful order, equal differences between data points, and a true zero point (Clippinger, 2017, pp. 62-70). This means that the absence of the variable being measured represents a complete absence of the quantity. The ratio scale allowed the researchers to complete...