Hybrid Genetic Algorithms for Scheduling Advertisements on a Web Page

Many web sites provide free services to users. The revenue for these sites is dependent on the advertisements they place on their web pages. For these firms, therefore, the optimal placing of advertisements on their web pages becomes a critical issue. In a given planning horizon, we assume that the number of advertisements available for placement on a web site is greater than the available space. The site, therefore, needs to determine the optimal allocation of advertisement space. We develop a hybrid genetic algorithm (GA) that uses problem specific knowledge during the evolution of solutions to solve this problem. Our initial computational results show that the hybrid GA performs exceptionally well in the sense that it provides optimal or near optimal solutions for a variety of problems

Solving the Social Dilemma with Equilibrium Data Harvesting Strategies: A Game-Theoretic Approach

Social media platforms generate huge profits from targeted advertising by collecting massive amounts of data from their users, usually referred to as data harvesting. However, practitioners from the social media industry suggest that data harvesting hurts users by promoting social media addiction and the spread of misinformation. Therefore, policymakers have recently been considering regulating social media platforms. This paper investigates how imposing the regulation on data harvesting impacts social media platforms and users by developing a game-theoretic model. Our main finding shows that while the objective of the regulation on data harvesting is to discourage platforms from collecting a massive amount of data from the users, imposing the regulation may sometimes increase the data harvesting levels and profits of social media platforms. We contribute to the Information Systems literature by broadening the knowledge of the impact of the government\u27s regulation on social media platforms and users

The Economics of Online Subsidiary Healthcare Systems

During the era of COVID-19, many hospitals start to build their own online healthcare systems (hereafter referred to as online subsidiary healthcare systems). The presence of online subsidiary healthcare systems brings hospitals an additional traffic source; however, in the meanwhile, it cannibalizes hospitals’ traditional offline traffic. Using a game-theoretic model, we obtain the optimal design of such an online healthcare system and investigate its impact on the traditional offline healthcare system. Surprisingly, we find that instead of reducing the offline traffic, such an online subsidiary healthcare system actually incentivizes more patients to visit the hospital offline, failing to fulfill the purpose of adopting online healthcare during COVID-19. Moreover, we find that online healthcare systems do not necessarily improve the profitability of the hospital and the surplus of patients. Our findings provide important implications regarding the management and regulation of such online subsidiary healthcare systems

Does Platform Competition Drive Ratings Inflation? The Impact of Vertical Spillover Effects

The familiar 5-star ratings system is an important information source for consumers deciding where to eat or what products to buy. Ideally, a retail platform owner should safeguard ratings against various biases, yet platform owners sometimes let average ratings become inflated. We study a situation in which a platform faces competition from another platform that offer the same items and, consequently, consumers may see different ratings for items across the platforms. Using a series of experiments in an online food ordering setting, we show that consumers are more likely to buy the item from a platform where it is rated higher. Therefore, a platform that offers lower but perhaps more accurate ratings risks hurting itself by not letting its ratings become inflated. We explain this by a vertical spillover effect by which diverging ratings across platforms influence platform choice and discuss implications to platform owners, regulators, and consumers

Provider Selection Framework for Bundled Payments in Healthcare Services

Identification of competitive healthcare providers is an important issue for the successful operation of a bundled payment reimbursement program. We develop a healthcare provider selection framework via data envelopment analysis (DEA) and combinatorial auction (CA). Our goal is to cover target regions with adequate numbers of healthcare providers to optimally deploy a bundled payment program across these regions. Our methodology balances bid prices and performance of applicants to cover the entire regions in an equitable manner, allows for provider preferences in selecting the bundle of services, and determines winners considering service quality, efficiency and the price of the bundles. Our work provides a practical and systematic selection procedure for payers compared to the extant subjective selection methods

Can Platform Competition Drive Ratings Inflation? The Impact of Vertical Spillover Effects

The familiar 5-star ratings system is an important information source for consumers deciding where to eat or what products to buy. Ideally, a retail platform owner should safeguard ratings against various biases, yet platform owners sometimes let average ratings become inflated. We study a situation in which a platform faces competition from another platform that offers the same items and, consequently, consumers may see different ratings for items across the platforms. Using a series of experiments in an online food ordering setting, we show that consumers are more likely to buy the item from a platform where it is rated higher. Therefore, a platform that offers lower but perhaps more accurate ratings risks hurting itself by not letting its ratings become inflated. We explain this by a vertical spillover effect by which diverging average ratings across platforms influence platform choice and discuss implications to platform owners, regulators, and consumers

The Business Value of Virtual Showrooms

A significant acceleration of research-online and purchase offline behavior makes online channels crucial for brick-and-mortars. Realizing this trend, many retail stores have been using a novel strategy, called virtual appointments, whereby consumers can access rich information online before visiting the stores. This study investigates the multifaceted business value of virtual appointments by using a rich dataset related to the car dealers’ business across the U.S. We empirically show that virtual appointments increase dealers’ sales. However, the effect depends on the competition level. The presence of within-brand competitors decreases the benefits of virtual appointment services, while the existence of between-brand competitors increases the benefit of the service

Progressive recovery of macrobenthic fauna in Chilika Lagoon after its restoration, with a focus on Stenothyra blanfordiana (Gastropoda: Stenothyridae)

The macrobenthic fauna of Chilika Lagoon was investigated from July 2012 to June 2016 to comprehend the status post its restoration and to discern signs of biological recovery. The study revealed the existence of 42 macrobenthic faunal taxa belonging to 28 families, apart from polychaetes, oligochaetes and fishes. Gastropods dominated the macrobenthic population of the lagoon, especially in its Central sector during pre-monsoon and monsoon seasons. Stenothyra blanfordiana an endemic species with an abundance as high as 3067 no./m2 , contributed to 80% of the total abundance of the macrobenthic fauna. Despite its importance concerning global biodiversity, information on its ecology, habitat, feeding behaviour, etc. is seldom available worldwide. This study elucidated the distribution, habitat preference and behaviour of S. blanfordiana in Chilka Lagoon. This endemic species showed a preference for comparatively less sandy substratum with higher C:N values and exhibited a dietary preference for dead and decaying plankton, particularly prevalent in macrophytedominated regions. The study has also demonstrated the gradual recovery of the macrobenthic community within the ecosystem, particularly notable in the case of S. blanfordiana, from previously degraded conditions

Traditional vs Cloud-Based Services: A Game Theoretical Analysis

The cloud gaming service (e.g., Google Stadia) is an emerging business that delivers game screen as streamed video to customers through the internet. Customers are endowed with the option of gaming on the cloud or staying with traditional consoles (e.g., Sony PlayStation). Hence, it becomes important for both the cloud gaming and console services to analyze the decision-making process of customers while optimizing their prices. Even though it is becoming an important problem for these service providers, it has not been analyzed rigorously in the literature. In this paper, we attempt to fill this important gap by analyzing the competition between the cloud gaming and console services in a game-theoretical setting. Our results show that revenues of console service providers are not necessarily hurt if customers’ valuation of the strengths of cloud services is higher. Besides, cloud gaming services do not always benefit from a higher percentage of core customers

Economics of Advertising Misattribution on E-commerce Platforms

Recently, some e-commerce platforms have started to provide advertising attribution tools for sellers, claiming to help them measure the effectiveness of multichannel advertising and optimize their budget allocation. It is unclear, however, what impact the attribution tools will have on key stakeholders involved in attribution, due to potential credibility concerns (e.g., the platform may underestimate the effectiveness of other publishers\u27 ads). Through the lens of a game-theoretic model, we analyze whether the platform, sellers, and other publishers can benefit from the adoption of attribution tools. Our results show that adopting the attribution tools can sometimes be detrimental to sellers. Another interesting finding is that sellers’ adoption of attribution tools can benefit regular publishers even when the platform understates the effectiveness of their ads. Moreover, we find that introducing the attribution tools can sometimes hurt the platform. Our findings provide important implications for the key stakeholders involved in the attribution