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The practice of sharing online user information with external third parties has become the focal point of privacy concerns for consumer advocacy groups and policy makers. We explore the decisions by websites regarding the obfuscation that they use to make it difficult for users to discover the extent of information sharing. Using a Bayesian model, we shed light on the websites’ incentive to obfuscate user information sharing. We find that as content sensitivity increases, a website reduces its level of obfuscation. Furthermore, more popular websites engage in higher levels of obfuscation than less popular ones. We provide an empirical analysis of obfuscation and user information sharing in News (low content sensitivity) and Health (high content sensitivity) websites and confirm key results from our analytical model. Our analysis illustrates that obfuscation of information sharing is a viable strategy that websites use to improve their profits. History: Ram Ramesh, area editor for Data Science & Machine Learning. Funding: Financial support from the Social Sciences and Humanities Research Council of Canada is gratefully acknowledged. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.1266 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2021.0070 ) at http://dx.doi.org/10.5281/zenodo.7336098 .

Efforts to promote Health Information Exchanges (HIEs) on a nationwide scale are beset with major challenges, and one of them is its meaningful use for both physicians and patients. Referrals potentially provide a context for the meaningful use of HIE, and we are yet to understand how HIEs affect referrals. This research studies the impact of HIE on referral patterns. We establish that participation in an HIE network increases the referrals sent to and received from other HIE participants. We investigate this relationship using both econometric and network-analytic methods. Whereas the econometric analysis focuses on the underlying associations between HIE adoption and referral patterns, the network analysis addresses the transformation process by which HIE adoption and referrals coevolve over time. This study has significant implications for healthcare policy making, development of innovative HIE business models, and management of healthcare organizations. This paper was accepted by Anindya Ghose, information systems. Supplemental Material: Data and the online supplement is available at https://doi.org/10.1287/mnsc.2022.4435 .

Black-Scholes (BS) equation is a popular mathematical model for determining the value of option in financial derivatives. To predict the option value during the contract of the option is a big problem. Several studies have been shown that the option price value can be determined by applying different methods. In this paper, we have discussed three finite difference methods: Explicit, Implicit and Crank-Nicolson for solving Black-Scholes equation for European call option and compared the obtained results with the exact value. It is found that the Crank-Nicolson method is more accurate and cost effective in comparison with explicit and implicit methods.

Advances in machine learning and the development of very large knowledge graphs have accompanied a proliferation of ontologies of many types and for many purposes. These ontologies are commonly developed independently, and as a result, it can be difficult to communicate about and between them. To address this difficulty of communication, ontologies and the communities they serve must agree on how their respective terminologies and formalizations relate to each other. The process of coming into accord and agreement is called “harmonization.” The Ontology Summit 2021 examined the overall landscape of ontologies, the many kinds of ontology generation and harmonization, as well as the sustainability of ontologies. The Communiqué synthesizes and summarizes the findings of the summit as well as earlier summits on related issues. One of the major impediments to harmonization is the relatively poor quality of natural language definitions in many ontologies. The summit surveyed the state of the art in natural language definition development, based on lexicographic principles, as well as examples of ongoing projects that are explicitly dealing with harmonization and sustainability.

Widespread abuse of internet users' privacy online has prompted user advocacy groups to implore governments to intervene and protect consumer rights. To study such interventions' effects, we examine data-protection policies that policy makers and governments can enforce on websites, including consent-based user information sharing and subsidizing competing websites. Interestingly, we find that even though a consent-based policy may improve user surplus, it has the unintended consequence of increasing the number of third-parties and, thus, sharing of user information. We also determine that both consent-based and website subsidization policies may reduce competition by driving websites out of the market—to the detriment of user surplus and social welfare. Moreover, consent-based policies are not beneficial to websites, but are beneficial for third-parties. Policy makers should consider the different policy mechanisms at their disposal. Website subsidization is similar to a scalpel, enabling them to sculpt around and impact specific target markets. Consent-based policies are more comparable to a sledgehammer that uniformly affects all market segments. For circumstances where it is difficult for the government to enact a law for the entire market, website subsidization policies may be appealing alternatives, as they may yield higher user surplus than consent-based policies.

The research on, ‘Studies on rainwater harvesting and reutilization for protective irrigation with farm pond’ was conducted during the year 2016-17 at demonstration farm of the Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani. The daily depth of water impounded in the farm pond was recorded for developing stage-storage relationship of the farm pond. For estimation of the loss of water through evaporation from farm pond, daily pan evaporation data was multiplied by pan co-efficient (0.70). The harvested water in the farm pond was utilized for applying protective irrigation to the pigeon pea crop. The experiment consisted six replications and two treatments. One protective irrigation for pigeon pea at pod development stage (T1) was applied on 30.11.2016. The treatment T2 consisted without protective irrigation to pigeon pea. The grain yield of pigeon pea was recorded plot wise.The grain yield data was analyzed using MAUSTAT software and results obtained were compared treatment wise. For economic analysis of the treatments, cost of cultivation, cost of cultural operations, fixed and operational costs of pump and accessories were calculated. These total cost was be used to determine the gross monetary returns (GMR), net monetary returns (NMR) and benefit cost ratio (B:C ratio). The area of top section and bottom section of the farm pond was 279.75 m2 and 516.82 m2 respectively. The average elevation of embankment at top was 413.130m. The average elevation of bottom of pond was 410.210m. The elevation at the bottom of outlet was 412.437m. The maximum depth of water impounded and maximum storage volume in the farm pond was 2.165m and 933.99m3 respectively. The total water evaporated through farm pond for the month of July, August, September, October, November and December 2016 was found to be 19.14 m3, 32.60m3, 25.40 m3, 35.9882m3, 29.8620m3 and 1.1965 m3 respectively. The maximum water evaporated through the farm pond was recorded in the month of October-2016. Total evaporation loss through the farm pond recorded was144.17 m3.The seepage loss through the pond for the month of July August, September, October, November and December 2016 was found to 634.88, 358.05 m3, 651.80 m3, 611.64 m3, 147.33 m3, and 37.89 m3 respectively. The maximum water seepage through the farm pond was recorded in the month of September -2016.The total seepage loss recorded through the farm pond was 2441.59 m3. The harvested water in the farm pond was utilized for irrigating the pigeon pea crop at its pod development stage. One of protective irrigation (T1) recorded significantly higher pigeon pea grain yield than treatment of without protective irrigation (T2). Due to the one protective irrigation, 27.30 per cent grain yield increased over or control was observed. The study revealed that the treatment T1 i. e. one protective irrigations at pod development stage recorded highest GMR (111302.00Rs/ha) and NMR (76302.00) as compared to control (T2) i. e. without protective irrigation. The benefit- cost ratio (2.18) is found to be higher under the treatment T1i. e. one protective irrigation pod development stage. The lowest B:C ratio (1.69) is estimated under the treatment T2 (without protective irrigation).