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Article
Publication date: 22 September 2020

Kalyanaram Gurumurthy and Avinandan Mukherjee

The novel coronavirus disease 2019 (COVID-19) pandemic has presented unique challenges in terms of understanding its unique characteristics of transmission and predicting…

Abstract

Purpose

The novel coronavirus disease 2019 (COVID-19) pandemic has presented unique challenges in terms of understanding its unique characteristics of transmission and predicting its spread. The purpose of this study is to present a simple, parsimonious and accurate model for forecasting mortality caused by COVID-19.

Design/methodology/approach

The presented Bass Model is compared it with several alternative existing models for forecasting the spread of COVID-19. This study calibrates the model for deaths for the period, March 21 to April 30 for the USA as a whole and as the US States of New York, California and West Virginia. The daily data from the COVID-19 Tracking Project has been used, which is a volunteer organization launched from The Atlantic. Every day, data is collected on testing and patient outcomes from all the 50 states, 5 territories and the District of Columbia. This data set is widely used by policymakers and scholars. The fit of the model (F-value and its significance, R-squared value) and the statistical significance of the variables (t-values) for each one of the four estimates are examined. This study also examines the forecast of deaths for a three-day period, May 1 to 3 for each one of the four estimates – US, and States of New York, California and West Virginia. Based on these metrics, the viability of the Bass Model is assessed. The dependent variable is the number of deaths, and the two independent variables are cumulative number of deaths and its squared value.

Findings

The findings of this paper show that compared to other forecasting methods, the Bass Model performs remarkably well. In fact, it may even be argued that the Bass Model does better with its forecast. The calibration of models for deaths in the USA, and States of New York, California and West Virginia are all found to be significant. The F values are large and the significance of the F values is low, that is, the probability that the model is wrong is very miniscule. The fit as measured by R-squared is also robust. Further, each of the two independent variables is highly significant in each of the four model calibrations. These forecasts also approximate the actual numbers reasonably well.

Research limitations/implications

This study illustrates the applicability of the Bass Model to estimate the diffusion of COVID-19 with some preliminary but important empirical analyses. This study argues that while the more sophisticated models may produce slightly better estimates, the Bass model produces robust and reasonably accurate estimates given the extreme parsimony of the model. Future research may investigate applications of the Bass Model for pandemic management using additional variables and other theoretical lenses.

Practical implications

The Bass Model offers effective forecasting of mortality resulting from COVID-19 to help understand how the curve can be flattened, how hospital capacity could be overwhelmed and how fatality rates might climb based on time and geography in the upcoming weeks and months.

Originality/value

This paper demonstrates the efficacy of the Bass Model as a parsimonious, accessible and theory-based approach that can predict the mortality rates of COVID-19 with minimal data requirements, simple calibration and accessible decision calculus. For all these reasons, this paper recommends further and continued examination of the Bass Model as an instrument for forecasting COVID-19 (and other epidemic/pandemic) mortality and health resource requirements. As this paper has demonstrated, there is much promise in this model.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 14 no. 3
Type: Research Article
ISSN: 1750-6123

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Article
Publication date: 4 September 2019

Gordhan K. Saini, Arvind Sahay and Gurumurthy Kalyanaram

This paper aims to examine three important questions: What would be the effects of pricing at the lower end of a wide vs narrow latitude of price acceptance (LPA) on…

Abstract

Purpose

This paper aims to examine three important questions: What would be the effects of pricing at the lower end of a wide vs narrow latitude of price acceptance (LPA) on consumer choice of the bundle? How would the nature of a bundle frame (i.e. discount on bundle vs discount on components) and discount frame (i.e. discount as absolute off vs discount as percentage off) influence the preference given to a price level that is at the wide or narrow end of the LPA? Would the effect be significantly different if the bundle components were complementary vs if they were non-complementary?

Design/methodology/approach

The authors carried out two studies using between-subject experimental design. In Study 1, the authors used 2 (LPA: wide/narrow) × 2 (complementarity: yes/no) × 2 (bundle frame: together/separate) design, and in Study 2, the authors replaced bundle frame with discount frame (i.e. absolute off/percentage off).

Findings

The authors find that the LPA effect is likely to outweigh the complementarity effect; however, a combined effect of complementarity and bundle frame is stronger than the LPA effect. Also, for a wide (narrow) LPA product bundle, absolute off (percentage off) discount frame is more attractive.

Practical implications

Managers should use bundling strategy with complementary products having wider LPA. In case of wide LPA and complementary products, both together and separate frame could be the best bundling strategy while in case of narrow LPA and complementary products, together frame could be the best bundling strategy.

Originality/value

The main contribution relates to the role LPA plays in consumer evaluation of a bundle offer and its interaction with complementarity and discount frame. The authors apply the range hypothesis principles (i.e. price-attractiveness judgments are based on a comparison of market prices to the endpoints of a range of evoked prices) in the bundling context and extend the earlier work in the area of complementarity and discount frame.

Details

Journal of Consumer Marketing, vol. 36 no. 7
Type: Research Article
ISSN: 0736-3761

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Article
Publication date: 4 April 2008

Gurumurthy Kalyanaram

This paper aims to study the effects of order of market entry on market share in prescription (Rx) and over‐the‐counter (OTC) pharmaceutical drugs market.

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1258

Abstract

Purpose

This paper aims to study the effects of order of market entry on market share in prescription (Rx) and over‐the‐counter (OTC) pharmaceutical drugs market.

Design/methodology/approach

Data on sales, price, direct‐to‐physicians (DTP) advertising, and direct‐to‐consumers (DTC) advertising for three Rx drugs categories and two OTC drugs categories were obtained for the period, January 1998 to December 1999. A log‐log statistical model was estimated using OLS methodology.

Findings

There is a significant order of entry effect on market share in both Rx and OTC drugs categories. This effect is higher in magnitude in the OTC category than in the Rx category. The effects of price, and DTP and DTC advertising are also significant. The differential effects of DTP and DTC advertising in the Rx and OTC categories are intuitive.

Originality/value

This study is unique in studying the differential effects of order‐of‐entry, and DTP and DTC advertising on market share in Rx and OTC drugs product categories.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 2 no. 1
Type: Research Article
ISSN: 1750-6123

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1710

Abstract

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 5 no. 4
Type: Research Article
ISSN: 1750-6123

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Abstract

Details

Review of Marketing Research
Type: Book
ISBN: 978-0-85724-728-5

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974

Abstract

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 5 no. 4
Type: Research Article
ISSN: 1750-6123

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Abstract

Details

Review of Marketing Research
Type: Book
ISBN: 978-0-85724-723-0

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Book part
Publication date: 1 January 2006

Donald R. Lehmann

Abstract

Details

Review of Marketing Research
Type: Book
ISBN: 978-0-7656-1305-9

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Article
Publication date: 4 April 2008

Avinandan Mukherjee

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332

Abstract

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 2 no. 1
Type: Research Article
ISSN: 1750-6123

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Book part
Publication date: 1 January 2005

Naresh K. Malhotra

Abstract

Details

Review of Marketing Research
Type: Book
ISBN: 978-0-85724-723-0

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