Periodic Reporting for period 4 - IllegalPharma (Competitive Dynamics in the Informal Economy: The case of Illegal Pharmaceutical Drugs)
Okres sprawozdawczy: 2021-11-01 do 2023-01-31
According to the European Commission (2012), the informal economy accounts for about 19% and 50% of annual GDP for developed and emerging economies respectively. Despite this, the informal economy has received little attention in management research. Due to this lack of research on the informal economy, we have a very limited understanding about how firms compete in illegal markets. This study attempts to fill this gap by developing and testing a theoretical model about the competitive dynamics in the illegal economy. Particularly, this project focuses on the trading of illegal pharmaceutical drugs. According to the World Health Organization (WHO), the sale of illegal pharmaceuticals amounts to about 400€ billion annually (WHO, 2018). Furthermore, the WHO also estimates that up to 1 million people (250,000 being children) die globally because of counterfeit drugs.
The main objective of this project is to develop and test a conceptual model that explains the competitive dynamics in illegal markets. This project will focus on three specific competitive outcomes: (1) market entry decisions (i.e. entry by an illegal pharmacy into a particular drug-market) (2) price decisions (i.e. the price gap between drugs sold in illegal and legal pharmacies), and (3) illegal drug sales (i.e. the volume of illegal sales versus legal sales for each medicine).
To explain variance along these three competitive dimensions, we will develop our theoretical model around the concept of legitimacy. According to Suchman (1995), legitimacy is the perception that “actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions” (Suchman, 1995: 574). Our main conceptual proposition relies on the claim that the illegal trading of medical drugs will be perceived as more legitimate in those cases where individuals perceive that the existing laws and regulations are “unfair”. Specifically, we expect that illegal pharmacies are (1) more likely to enter new niches, (2) increase drug price and (3) achieve greater sales, when there is a greater perception among agents that illegal trade of such drugs is a legitimate activity and is justified from a moral standpoint.
To capture perceptions of legitimacy, we look at whether a certain law or regulation is perceived as unfair and unreasonably strict. Specifically, we will look at three laws: (1) prescription law, (2) manufacturing law and (3) intellectual property law. In each of these 3 laws there is a conflict between a value that is left in the legal side of the spectrum and another value that remains in the legal side: tension between patient safety versus patient privacy (prescription law), tension between patient safety and timely access for a drug (manufacturing law), and tension between rewarding innovators and drug affordability (intellectual property law). Accordingly, for each pharmaceutical drug, we argue that the more salient the value left in the illegal side is compared to the value remaining in the legal side, the more strict and unfair a regulation will be perceived, meaning that the more illegal trade will be perceived as a legitimate and morally justified activity.
In sum, the main objective is to show how perceptions of legitimacy explain illegal pharmacies’ decisions with respect to (1) new market entry, (2) prices and (3) sales.
The main objective of this project is to develop and test a conceptual model that explains the competitive dynamics in illegal markets. This project will focus on three specific competitive outcomes: (1) market entry decisions (i.e. entry by an illegal pharmacy into a particular drug-market) (2) price decisions (i.e. the price gap between drugs sold in illegal and legal pharmacies), and (3) illegal drug sales (i.e. the volume of illegal sales versus legal sales for each medicine).
To explain variance along these three competitive dimensions, we will develop our theoretical model around the concept of legitimacy. According to Suchman (1995), legitimacy is the perception that “actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions” (Suchman, 1995: 574). Our main conceptual proposition relies on the claim that the illegal trading of medical drugs will be perceived as more legitimate in those cases where individuals perceive that the existing laws and regulations are “unfair”. Specifically, we expect that illegal pharmacies are (1) more likely to enter new niches, (2) increase drug price and (3) achieve greater sales, when there is a greater perception among agents that illegal trade of such drugs is a legitimate activity and is justified from a moral standpoint.
To capture perceptions of legitimacy, we look at whether a certain law or regulation is perceived as unfair and unreasonably strict. Specifically, we will look at three laws: (1) prescription law, (2) manufacturing law and (3) intellectual property law. In each of these 3 laws there is a conflict between a value that is left in the legal side of the spectrum and another value that remains in the legal side: tension between patient safety versus patient privacy (prescription law), tension between patient safety and timely access for a drug (manufacturing law), and tension between rewarding innovators and drug affordability (intellectual property law). Accordingly, for each pharmaceutical drug, we argue that the more salient the value left in the illegal side is compared to the value remaining in the legal side, the more strict and unfair a regulation will be perceived, meaning that the more illegal trade will be perceived as a legitimate and morally justified activity.
In sum, the main objective is to show how perceptions of legitimacy explain illegal pharmacies’ decisions with respect to (1) new market entry, (2) prices and (3) sales.
Conceptual model: The model described above has already been developed and a theoretical draft is under preparation. The objective is to combine this conceptual model with the empirical tests described below, in the form of a series of academic papers, which will be submitted to conferences and peer-review journal publication.
Empirical analysis: So far, the main progress in this front has been in the collection, cleaning and preparation of the final database that will be used to test the predictions derived from the conceptual model:
1. Data collection: data has been collected to create all three outcome variables and to develop the construct of perceived legitimacy in each of the three examined regulations/laws. In addition, additional data has been collected to create control variables in order to avoid omitted variable bias in our estimations.
2. Data cleaning and preparation of the final dataset: All the datasets collected so far have been cleaned using a machine learning algorithm. The cleaning process has been homogenized for all these datasets to ensure that the same unique drug identifier is extracted for each data point, so that it can be later used to merge these datasets together.
3. Data merging: Data from legal and illegal sources has been matched. This has led to the creation of a final dataset with information about presence of illegal drugs in particular online pharmacies and their price.
4. Empirical tests: Tests are being implemented for the first two outcomes (and will be implemented with the third as soon as this measure is constructed). After empirical results are obtained, the preparation of a final paper(s) will take place.
Empirical analysis: So far, the main progress in this front has been in the collection, cleaning and preparation of the final database that will be used to test the predictions derived from the conceptual model:
1. Data collection: data has been collected to create all three outcome variables and to develop the construct of perceived legitimacy in each of the three examined regulations/laws. In addition, additional data has been collected to create control variables in order to avoid omitted variable bias in our estimations.
2. Data cleaning and preparation of the final dataset: All the datasets collected so far have been cleaned using a machine learning algorithm. The cleaning process has been homogenized for all these datasets to ensure that the same unique drug identifier is extracted for each data point, so that it can be later used to merge these datasets together.
3. Data merging: Data from legal and illegal sources has been matched. This has led to the creation of a final dataset with information about presence of illegal drugs in particular online pharmacies and their price.
4. Empirical tests: Tests are being implemented for the first two outcomes (and will be implemented with the third as soon as this measure is constructed). After empirical results are obtained, the preparation of a final paper(s) will take place.
The main progress achieved so far, and the expected results until the end of the project, can be grouped into two different fronts: theoretical contribution and the creation of a novel dataset.
1. Theoretical contribution: The multidisciplinary perspective of the conceptual model developed so far is expected to provide important academic contributions to different fields:
a. Business literature: This project will have a strong impact on the management field in two dimensions. On the one hand, most of the management literature examines the drivers of firms’ competitiveness focusing on the legal economy. Thus, this research will fill this gap by developing a new theory of the competitive dynamics in the informal economy. On the other hand, management research has not yet deeply explored the role of legitimacy in the illegal sector. In this sense, this research will contribute to prior literature in this field by examining the role of legitimacy in the illegal pharmaceutical sector.
b. Social Sciences literature: This research could also contribute to research in economics, psychology and sociology. As a matter of fact, the data and methodology proposed in this research could foster further empirical and conceptual research in all these areas.
c. Medical literature: Medical research examining the illegal pharmaceutical sector, and the risks that it entails for public health, could also benefit from this project.
2. Novel data and methodology: In this project we collected a large amount of data using a very unique methodology. Accordingly, we expect that the construction of this database will provide the following advantages once completed.
a. Unique data on pharmaceutical drugs. This project develops a unique data using a range of very novel and rich sources. This will turn into a very unique resource that could be very useful to develop empirical research on both illegal and legal sectors.
b. Unique methodology. We also believe that the methodology used to capture perceptions of legitimacy is in itself an important useful resource that comes out of this project.
1. Theoretical contribution: The multidisciplinary perspective of the conceptual model developed so far is expected to provide important academic contributions to different fields:
a. Business literature: This project will have a strong impact on the management field in two dimensions. On the one hand, most of the management literature examines the drivers of firms’ competitiveness focusing on the legal economy. Thus, this research will fill this gap by developing a new theory of the competitive dynamics in the informal economy. On the other hand, management research has not yet deeply explored the role of legitimacy in the illegal sector. In this sense, this research will contribute to prior literature in this field by examining the role of legitimacy in the illegal pharmaceutical sector.
b. Social Sciences literature: This research could also contribute to research in economics, psychology and sociology. As a matter of fact, the data and methodology proposed in this research could foster further empirical and conceptual research in all these areas.
c. Medical literature: Medical research examining the illegal pharmaceutical sector, and the risks that it entails for public health, could also benefit from this project.
2. Novel data and methodology: In this project we collected a large amount of data using a very unique methodology. Accordingly, we expect that the construction of this database will provide the following advantages once completed.
a. Unique data on pharmaceutical drugs. This project develops a unique data using a range of very novel and rich sources. This will turn into a very unique resource that could be very useful to develop empirical research on both illegal and legal sectors.
b. Unique methodology. We also believe that the methodology used to capture perceptions of legitimacy is in itself an important useful resource that comes out of this project.