Applications of Management Science: Volume 21

In this chapter, we applied Data Envelopment Analysis (DEA) to a group of property and casualty insurance companies' data from 2018 to 2020. The calculated relative efficiencies were compared with selected traditionally used financial measures. We conclude that DEA and its relative efficiency calculation provide a consistent measure with selected IRIS ratios. The result and method can be used for situations when multiple ratios and change-based financial metrics provide inconsistent conclusions.

Mutual fund ratings are extremely popular among mutual fund investors, with over 8,000 mutual funds currently available to them and a huge increase in privately managed retirement accounts. Morningstar introduced the star-rating system to mutual funds, grading them on a range of one to five stars, with one star being the lowest and five stars being the highest. Because of its simplicity and resemblance to the ratings of so many other products we buy, the star-rating system has become an intrinsic element of mutual fund jargon. Morningstar experts award 5-star funds a gold, silver, or bronze medal ranking based on their instinctual analysis. This research investigates whether all gold-medal winning five-star mutual funds are equally efficient in terms of risk-adjusted performance. When total return, adjusted expense ratio, standard deviation, tax cost ratio, Sharpe ratio, and fund alpha are all considered, we discovered that not all “gold medal” mutual funds are equally efficient. Investors should take care even among “gold medal” funds since some are more efficient than others.

Skincare, hair care, make-up, perfumes, toiletries and deodorants, and oral cosmetics are the main product categories of the cosmetic market. Since the early twentieth century, the production of cosmetics and beauty products has been controlled by a handful of multi-national corporations. COVID-19 impacted the cosmetics industry in several different and sometimes conflicting ways. This study benchmarks the performance of 20 largest cosmetics companies against their competition as well as against their previous years to analyze the impact of COVID-19. We find that only one company has consistently performed than its peers over the period of 2015–2020. We also find that average efficiency score of cosmetics companies declines in 2020 relative to 2019.

This chapter develops a productivity analysis of the New Jersey PPO Health Insurance Industry for 2018. The chapter concerns five New Jersey PPO insurance companies. The two output variables are claims paid and loss ratio. The two input variables include premiums collected and assets.

This chapter develops a productivity analysis of the US pharmaceutical industry via Data Envelopment Analysis (DEA). This study concerns itself with 16 US pharmaceutical companies. The output variables are profit margin, operating margin, return on assets, and return on equity. The input variables are corporate workers and market capital. Since negative data appear in DEA, a directional distance approach was applied.

This chapter presents mathematical model for geothermal energy allocation. The objective is to a find the minimal length of connections between sources and demand points. The problem is formulated as a transportation problem. The model presented in this case study finds optimal assignment of energy sources to urban areas, with full demand for energy satisfied in all districts using one type of energy.

A mathematical model for sustainable optimization is presented. The sustainability parameters are linked to end-of-life considerations in product design and development. The sustainability considerations such as total embodied energy, eco-materials selection, CO₂ emission, cost savings due to recycling and reuse including the water savings are presented for helical compression springs used in mattresses.

The purpose of this chapter was to develop a framework for comprehensive business diagnostics, which can be integrated into the management of small and medium-sized businesses.

The chapter proposes a multiloop model of comprehensive business diagnostics, which provides the company with timely and objective information about the dynamics of its key performance indicators. The model allows enterprises of the real sector to optimize the information acquiring process with the help of the express diagnostics indicators and ensure the high quality and efficiency of the obtained information. Testing of the multiloop model at the Pavlovo Posad Shawl Manufactory JSC involved three stages: express diagnostics (ED), general diagnostics (GD), and comprehensive diagnostics (CD).

The results determined the need to move to the comprehensive diagnostics (CD) loop of the model. The approbation of the suggested model at the shawl manufacture, particularly the CD loop, allowed the authors to identify the key factors influencing the company's main economic and financial indicators.

The proposed multiloop model can be used at enterprises with different forms of ownership, including small and medium-sized businesses, both in Russia and abroad.

A multiloop model of comprehensive business diagnostics provides managerial staff with qualitative real-time information that helps them make informed and effective management decisions.

The proposed multiloop model allows businesses to acquire data about the dynamics of key indicators, determine the factors' impacts on key financial and economic indicators, and ensure high efficiency of management decisions with minimal cost.

For two-sided platforms, the utility of users on one side of the platform depends in part on the number of users on the other side of the platform, a phenomenon called indirect network externalities. With the rapid development of two-sided platform and the popularity of platform membership, more and more two-sided platforms have launched joint membership through horizontal cooperation in order to take advantage of indirect network externalities to increase platform profits.

Our study explores the optimal bundling strategy for platform memberships under horizontal cooperation considering indirect network externalities. The main purpose of our study is to obtain the optimal pricing under different strategies (pure component, pure bundling, and mixed bundling) and contrast different strategies under different indirect network externalities.

Results suggest that the platform's optimal pricing for consumers and sellers depends on the indirect network externalities. Interestingly, the higher the indirect network externalities from consumers, the higher the price of the platform charges to sellers, and the platform might even subsidize sellers. Besides, when there are equal proportions of different types of consumers in the market, indirect network externalities that are too high, too low, or heavily lopsided may discourage the platforms from bundling their memberships. When the composition of consumers changes, the optimal strategy will also change. Our results can be employed in practical applications of bundling, which can help the platform increase profits.

Manufacturers and remanufacturers strive to maximize supply chain effectiveness by eliminating wastes in all their forms. This line of research extends the effectiveness during the products' working lives. Fraud in the warranty service chain (WSC) is one such source of waste that leads to revenue losses in the short term but when left unchecked leads to far worse results in the long term. Warranty frauds in the new product industry have received significant attention in recent literature. Addressing fraud issues in the remanufacturing industry have not been a high priority. Previous studies considered the primary parties in the WSC as possible sources of fraud. However, several unique opportunities exist for the secondary parties when it comes to fraud. This chapter considers fraud originating from one of the secondary parties of the WSC, namely the warranty administrator. The chapter models this fraud scenario using discrete event simulation and explores a possible fraud mitigation scenario.

The number of business analytics classes and programs has been rapidly increasing over the past 20 years. However, while we are educating students with the knowledge of advanced analytical techniques and tools, we are not providing them with sound problem-solving skills. In an effort to improve student problem-solving skills by increasing their understanding and increasing their engagement, in this chapter we will describe, discuss the implementation of, and discuss the results of employing an experiential learning (EL) exercise in an analytics course.