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PurposeThis study aims to present a study on the supply chain process of a Myanmar-based pharmaceutical company (named ABC Pvt. Ltd. in this study) that produces pharmaceutical products across Myanmar and aims of bringing quality medical products and best care for Myanmar people's health. The study aims to identify the key supply chain challenges and manage the opportunities executed by this pharmaceutical company to improve the supply chain process during the COVID-19 outbreak.Design/methodology/approachThis work used a case study and conducted semistructured interviews with the manager, senior managers and senior staff of the ABC Company to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the uncertainties, real-time information and agility in a digital supply chain using grey relational analysis (GRA) method.FindingsFrom the data analysis and results, "Impact of political factor,” "Delay in import process” and "Weak internet connection,” and "Weak knowledge of the use of digital platform,” "Poor information sharing in online by employees” and "Information flow from top management to operational level” have been identified as top and bottom three key challenges, respectively. "Inventory management,” "Selection of transport method” and "Operational cost”, and "Marketing and brand Innovation,” "Online delivery of products” and "E-commerce enablement (Launching applications, tracking system)” are identified as the top and bottom three managing the opportunities, respectively.Research limitations/implicationsThe findings of the study help to supply chain decision-makers of the company in their establishment of key challenges and opportunities during the COVID-19 era. As a leading company, it always tries to add value to its product through a supply chain system, effective management teams and working with skillful decision-making toward satisfying the demand on time and monitoring the supplier performance.Originality/valueThe novelty of this study is to identify the key supply chain challenges and opportunities by the GRA method to rank them, considering the case of Myanmar pharmaceutical manufacturing company as a case-based approach to measuring its performance during the COVID-19 outbreak era. This work will assist managers and practitioners help to the company to provide optimal services to its consumers on time in this critical situation.
ABSTRACT
The COVID-19 pandemic poses new challenges on pharmaceutical supply chain including the delays and shortages of resources which lead to product backorders. Backorder is a common supply chain problem for pharmaceutical companies which affects inventory management and customer demand. A product is on backorder when the received quantity from the suppliers is less than the quantity ordered. Knowing when a product will be on backorder can help companies effectively plan their inventories, propose alternative solutions, schedule deliveries, and build trust with their customers. In this paper, we investigate two problems. One is how to use machine learning classifiers to predict product backorders for a pharmaceutical distributor. The second problem we focused on is what are the particular challenges and solutions for such task under a pandemic setting. This backorder dataset is different from existing benchmark backorder datasets with very limited features. We discuss our challenges for this task including empirical data pre-processing, feature engineering and understanding the special definitions of backorder under the pandemic situation. We discuss experimental design for predicting algorithm and comparison metrics, and demonstrate through experiments that decision tree algorithm outperforms other algorithms for our particular task. We show through explainable machine learning approaches how to interpret the prediction results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Whereas most of technological trajectory research in evolutionary economics focuses on the sectoral level, our objective is to propose an analysis at the scale of the company. We are studying the leading pharmaceutical company Sanofi and focusing on the development of its vaccine technologies, a very topical issue in the Covid-19 context. What are the characteristics of Sanofi's vaccine technology trajectory and how can they explain the company's position in the Covid-19 crisis, i.e. its ability (or not) to innovate and respond to social demand for a vaccine? We contribute to technological trajectory literature by integrating a systemic dimension of the links between source and destination technology. Our ‘Knowledge Capital Approach' is based on patent citation data and network analysis. It has allowed us to identify the trajectory of Sanofi's vaccine technical system and to show its central position in its knowledge capital, where the technologies mastered by the company converge. These results can be viewed as paradoxical when considering Sanofi's lag in the Covid-19 race for a new vaccine. Our historical and qualitative approach adds to these findings by showing the role of strategic and institutional factors in explaining this situation. © 2023 Elsevier Ltd
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The pandemic of Covid-19 was a huge challenge for people, the economies of companies and nations. The supply chain, which is a link from suppliers to customers, is one of the many sectors hugely affected by the Covid-19 pandemic. Many suppliers were forced to shut down operations due to the pandemic and the transportation industry suffered immensely. World leaders, medical practitioners and pharmaceutical companies began to talk about vaccine development to help in the fight against the pandemic. A breakthrough in the Covid-19 vaccine development brought smiles again to the world as many countries were already struggling to deal with the effect of this pandemic. Since the supply chain industry has been gravely impacted by the pandemic, there rises another challenge in the distribution of the developed Covid-19 Vaccine. Using Statistical Analysis System (SAS) and a combination of different multivariate methods, this research explores the United States Covid-19 and Vaccine distribution dataset to uncover trends affecting the Covid-19 Vaccine Supply Chain (VSC). Furthermore, this research provides some suggestions on how to improve the Covid-19 VSC using supply chain drivers such as facilities, transportations, and information. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.
ABSTRACT
Purpose: This study aims to present a study on the supply chain process of a Myanmar-based pharmaceutical company (named ABC Pvt. Ltd. in this study) that produces pharmaceutical products across Myanmar and aims of bringing quality medical products and best care for Myanmar people’s health. The study aims to identify the key supply chain challenges and manage the opportunities executed by this pharmaceutical company to improve the supply chain process during the COVID-19 outbreak. Design/methodology/approach: This work used a case study and conducted semistructured interviews with the manager, senior managers and senior staff of the ABC Company to improve the supply chain process and develop a comprehensive structural relationship to rank them to streamline the uncertainties, real-time information and agility in a digital supply chain using grey relational analysis (GRA) method. Findings: From the data analysis and results, “Impact of political factor,” “Delay in import process” and “Weak internet connection,” and “Weak knowledge of the use of digital platform,” “Poor information sharing in online by employees” and “Information flow from top management to operational level” have been identified as top and bottom three key challenges, respectively. “Inventory management,” “Selection of transport method” and “Operational cost”, and “Marketing and brand Innovation,” “Online delivery of products” and “E-commerce enablement (Launching applications, tracking system)” are identified as the top and bottom three managing the opportunities, respectively. Research limitations/implications: The findings of the study help to supply chain decision-makers of the company in their establishment of key challenges and opportunities during the COVID-19 era. As a leading company, it always tries to add value to its product through a supply chain system, effective management teams and working with skillful decision-making toward satisfying the demand on time and monitoring the supplier performance. Originality/value: The novelty of this study is to identify the key supply chain challenges and opportunities by the GRA method to rank them, considering the case of Myanmar pharmaceutical manufacturing company as a case-based approach to measuring its performance during the COVID-19 outbreak era. This work will assist managers and practitioners help to the company to provide optimal services to its consumers on time in this critical situation. © 2022, Emerald Publishing Limited.
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The insurgence of the COVID pandemic calls for mass vaccination campaigns worldwide. Pharmaceutical companies struggle to ramp up their production to meet the demand for vaccines but cannot always guarantee a perfectly regular delivery schedule. On the other hand, governments must devise plans to have most of their population vaccinated in the shortest possible time and have the vaccine booster administered after a precise time interval. The combination of delivery uncertainties and those time requirements may make such planning difficult. In this paper, we propose several heuristic strategies to meet those requirements in the face of delivery uncertainties. The outcome of those strategies is a daily vaccination plan that suggests how many initial doses and boosters can be administered each day. We compare the results with the optimal plan obtained through linear programming, which however assumes that we know in advance the whole delivery schedule. As for performance metrics, we consider both the vaccination time (which has to be as low as possible) and the balance between vaccination capacities over time (which has to be as uniform as possible). The strategies achieving the best trade-off between those competing requirements turn out to be the q-days ahead strategies, which put aside doses to guarantee that we do not run out of stock on just the next q days. Increasing the look-ahead period, i.e. q, allows to achieve a lower number of out-of-stock days, though worsening the other performance indicators. © 2022, Springer Nature Switzerland AG.
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This paper analyses the variables influencing the capital structure of Ecuadorian pharmaceutical companies, which have experienced variations in their internal design in recent years, and evaluates the effect of the covid-19 pandemic on their debt levels. The leverage ratio is the proxy for capital structure with independent variables as growth, percentage of fixed assets (tangibility), profitability (ROA), firm size, and liquidity. Including a dichotomous variable to assess the effect of covid-19 in 2020. The panel data model helps to analyze the data varying across firms and years. The coefficients are estimated using the Pooled Ordinary Least Squares (POLS) method and the fixed-effects method. The results show that the profitability and liquidity variables are negatively correlated. While the growth, tangibility, and firm size variables are not statistically significant. During 2020 the covid-19 pandemic did not significantly influence the financial statements of the sector. In general, correct management of observed debt levels would allow the industry to face possible external shocks and not present payment problems in the short term. © 2021 ACM.
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Opioid Use Disorder (OUD) is one of the most severe health care problems in the USA. People addicted to opioids need various treatments, including Medication-Assisted Treatment (MAT), proper counseling, and behavioral therapies. However, during the peak time of the COVID-19 pandemic, the supply of emergency medications was disrupted seriously. Patients faced severe medical care scarcity since many pharmaceutical companies, drugstores, and local pharmacies were closed. Import-export was also canceled to consent to the government emergency law, i.e., lockdown, quarantine, and isolation. These circumstances and their negative effects on OUD patient's psychology could have led them to a drop out of MAT medications and persuaded to resume illicit opioid use. This project involves collecting and analyzing a large volume of Twitter data related to MAT medications for OUD patients. We discover the Active MAT Medicine Users (AMMUs) on twitter. For this, we build a seed dictionary of words related to OUD and MAT and apply association rules to expand it. Further, AMMUs' tweet posts are studied 'before the pandemic' (BP) and 'during the pandemic' (DP) to understand how the drug behaviors and habits have changed due to COVID-19. We also perform sentiment analysis on Tweets to determine the impact of the COVID-19 pandemic on the psychology of AMMUs. Our analysis shows that the use of MAT medications has decreased around 30.54%, where the use of illicit drugs and other prescription opioids increased 18.06% and 12.12%, respectively, based on AMMUs' tweets posted during the lockdown compared with before the lockdown statistics. The COVID-19 pandemic and lockdown may result in the resumption of illegal and prescription opioid abuse by OUD patients. Necessary steps and precautions should be taken by health care providers to ensure the emergency supply of medicines and also psychological support and thus prevent patients from illicit opioid use. © 2021 IEEE.
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Today more so than ever, a 'megabrand' is not something that is just discovered in the lab, but something that is taken from a 'promising molecule' to 'blockbuster product' through the coordinated and planned efforts of cross-functional teams, including R&D, medical and marketing and functions. Within global pharmaceutical industries portfolio, there is considerable potential for several products to be taken to megabrand status and make an important contribution to our business in the future. Marketing plays a critical and central role in the creation of a megabrand and, within that, effective communication support is vital in marketing mix innovation. This research thesis was through cases study to find out what are the keys to be responsible for creating and sustaining a megabrand? Why to be successful? And how to success? Maybe it can provide an overview of the key communication activities used to support a brand, from the perspective of launching a megabrand, through examples drawn from previous campaigns, many from within global pharmaceutical industry in Taiwan. In the same time, hope to offer the guidance and advice on the critical communication areas for megabrands: Issues preparedness, competitor strategies, opinion leader support, working with third-party organisations, working with the media, internal communications, working with agencies, and the use of digital/internet marketing. After COVID-19 situation impact, the new digital marketing platform will be more active to discuss and implement in the pharmaceutical companies and create new open innovation for science communication and business impact. Based on marketing-mix modelling 12 P's theories (product, price, place, promotion, power, public relations, probing, partitioning, prioritizing, positioning, people, and packaging), add on new “platform” of digital/internet marketing to analysis the business effect in the global pharmaceutical companies through product life cycle and marketing mix modelling. Finaly, the cases pharmaceutical companies (AstraZeneca/Pfizer/Johnson & Johnson) show different business impact in core therapy area products after new innovation platform of digital/internet marketing. Modern marketing relies on digital technology to analyze the comprehensive performance of a marketing campaign, and help guide future strategies and decision-making. The best way to define a digital marketing platform is to break it down into its two parts: digital marketing and digital business platforms. It also seems to provide us the new innovation marketing mix 13P's theories in global pharmaceutical industry. Copyright © 2021 by Naudé Scribante. Permission granted to IAMOT to publish and use.
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The healthcare industry is one of the top priorities for every country, as the government wants to improve the process and provide better services to the public in the health sector. In COVID19, there is a need to immediate response and secured way of storing data due to overwhelming patients admitting to the hospitals. Many stakeholders are involved in the health sector, such as patients, doctors, pharmaceutical companies, laboratories, and hospitals which makes the complete system complex. Security and privacy are the major concern of comprehensive patient-related information accessed by the involved participants. Blockchain technology is capable of ensuring data integrity and privacy with immutable features. The blockchain technology can be implemented in public and private means, but the medical data is sensitive information which cannot be shared to the public. In this paper, the permissioned blockchain is implemented for healthcare sector using Hyperledger Fabric. The Fabric is an open-source platform through which a Smart Contract is developed on the blockchain network. With the help of a smart contract, the secure transaction is performed on the ledger to store the confidential data related to a patient. The data stored in the form of an immutable block ensures the security of health records stored on distributed ledger through a smart contract. With this implementation, the efficient healthcare process is simplified and the transactions with multiple end-users are done securely, leading to transparency and traceability. © 2021 ACM.
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With the rise of the proportion of the elderly population and the improvement of the national economic level, people pay more and more attention to health. At the same time, the impact of COVID-19 on various industries has also made us realize that medicine is necessary. Pharmaceutical stocks have become one of the most prominent sectors in China's stock market in recent years. However, investors also have problems such as blind following and impulsive investment. In order to provide professional suggestions to investors, this paper makes an empirical analysis based on the stock data of pharmaceutical companies in the A-share market and the CSI 300 Index by using PE ratio, EPS ratio and CAPM model. Finally, according to the data analysis results and the nature of each pharmaceutical company, this paper suggests that investors with risk preference can invest in pharmaceutical manufacturing enterprises. In terms of those risk-averse investors, they can choose leading enterprises in the pharmaceutical retail industry. Moreover, the future market for vaccines will be a very large one with clear long-term value © 2021 ACM.