Limited Information Disclosure Research Articles

Patient Perspective on Informed Consent In Surgery: A Qualitative Investigation

Background: Informed consent is a fundamental ethical principle in healthcare, representing mutual understanding and agreement between healthcare providers and patients, particularly crucial in surgical contexts. However, the patient's perspective on this process remains underexplored, especially in resource-constrained regions like Muzaffarpur and Bihar. Materials and Methods: This qualitative investigation employed a phenomenological research design to explore the experiences of 23 adult patients who underwent surgical procedures in Muzaffarpur. Semi-structured interviews, conducted in Hindi, were used to gather data, which were subsequently analyzed thematically. Results: The study revealed several key themes: (1) Limited Information Disclosure, (2) Short Timeframes for Decision-Making, (3) Varied Communication Styles, (4) Trust in Healthcare Providers, (5) Sociocultural Factors, and (6) Desire for More Information. These findings highlight the need for improved patient-centered communication, transparent information disclosure, trust-building, cultural sensitivity, and time allocation in the informed consent process. Conclusion: The patient's perspective on informed consent in surgical settings in Muzaffarpur, Bihar, underscores the importance of tailoring practices to local contexts. Enhancing communication, trust, and information accessibility can promote patient autonomy and improve the informed consent experience. These insights are vital for advancing ethical healthcare in resource-constrained regions.

The effect on stock performance of executives' emotions during IPO roadshows

This paper describes the correlation between executives' emotions expressed at IPO online roadshows and post-IPO stock performance in the Chinese stock market. The executives' emotion is quantified by face recognition models used for analyzing facial expressions during the IPO roadshows. Our results show that the more negative emotions are expressed by executives at the roadshow, the lower the short-term stock returns after IPO, and this finding is stronger for firms with limited information disclosure. These results are robust to the implementation of an instrumental variable strategy using Air Quality Index or Comfort Index of Human Body as the instrumental variable, various measures of management emotions, and the subsample analysis in which the financial firms and industries has the limited number of firms are excluded.

Agree to Disagree: Subjective Fairness in Privacy-Restricted Decentralised Conflict Resolution.

Fairness is commonly seen as a property of the global outcome of a system and assumes centralisation and complete knowledge. However, in real decentralised applications, agents only have partial observation capabilities. Under limited information, agents rely on communication to divulge some of their private (and unobservable) information to others. When an agent deliberates to resolve conflicts, limited knowledge may cause its perspective of a correct outcome to differ from the actual outcome of the conflict resolution. This is subjective unfairness. As human systems and societies are organised by rules and norms, hybrid human-agent and multi-agent environments of the future will require agents to resolve conflicts in a decentralised and rule-aware way. Prior work achieves such decentralised, rule-aware conflict resolution through cultures: explainable architectures that embed human regulations and norms via argumentation frameworks with verification mechanisms. However, this prior work requires agents to have full state knowledge of each other, whereas many distributed applications in practice admit partial observation capabilities, which may require agents to communicate and carefully opt to release information if privacy constraints apply. To enable decentralised, fairness-aware conflict resolution under privacy constraints, we have two contributions: 1) a novel interaction approach and 2) a formalism of the relationship between privacy and fairness. Our proposed interaction approach is an architecture for privacy-aware explainable conflict resolution where agents engage in a dialogue of hypotheses and facts. To measure the privacy-fairness relationship, we define subjective and objective fairness on both the local and global scope and formalise the impact of partial observability due to privacy in these different notions of fairness. We first study our proposed architecture and the privacy-fairness relationship in the abstract, testing different argumentation strategies on a large number of randomised cultures. We empirically demonstrate the trade-off between privacy, objective fairness, and subjective fairness and show that better strategies can mitigate the effects of privacy in distributed systems. In addition to this analysis across a broad set of randomised abstract cultures, we analyse a case study for a specific scenario: we instantiate our architecture in a multi-agent simulation of prioritised rule-aware collision avoidance with limited information disclosure.

Is “accredited crowdfunding” a lemons market? Evidence from 506(c) filings

ABSTRACT The United States Congress passed the JOBS Act of 2012, which allowed small private companies to advertise the sale of their securities to accredited investors. However, this new fundraising method is subject to criticism that it might lead to a lemons market in crowdfunding platforms due to limited information disclosure requirements. This article thus examines this concern, and the results do not support the development of a lemons market. Conversely, we identify a separating equilibrium in which quality companies choose to raise capital from the accredited investors. Firms’ operating characteristics and VC monitoring provide effective signals in the accredited crowdfunding markets.

A deep reinforcement learning-based algorithm for reliability-aware multi-domain service deployment in smart ecosystems

The transition towards full network virtualization will see services for smart ecosystems including smart metering, healthcare and transportation among others, being deployed as Service Function Chains (SFCs) comprised of an ordered set of virtual network functions. However, since such services are usually deployed in remote cloud networks, the SFCs may transcend multiple domains belonging to different Infrastructure Providers (InPs), possibly with differing policies regarding billing and Quality-of-service (QoS) guarantees. Therefore, efficiently allocating the exhaustible network resources to the different SFCs while meeting the stringent requirements of the services such as delay and QoS among others, remains a complex challenge, especially under limited information disclosure by the InPs. In this work, we formulate the SFC deployment problem across multiple domains focusing on delay constraints, and propose a framework for SFC orchestration which adheres to the privacy requirements of the InPs. Then, we propose a reinforcement learning (RL)-based algorithm for partitioning the SFC request across the different InPs while considering service reliability across the participating InPs. Such RL-based algorithms have the intelligence to infer undisclosed InP information from historical data obtained from past experiences. Simulation results, considering both online and offline scenarios, reveal that the proposed algorithm results in up to 10% improvement in terms of acceptance ratio and provisioning cost compared to the benchmark algorithms, with up to more than 90% saving in execution time for large networks. In addition, the paper proposes an enhancement to a state-of-the-art algorithm which results in up to 5% improvement in terms of provisioning cost.

A Privacy-Preserving Reinforcement Learning Algorithm for Multi-Domain Virtual Network Embedding

The problem of optimally deploying a virtual network onto a substrate physical network is referred to as Virtual Network Embedding (VNE). In general, this embedding is requested by a customer to an Internet Service Provider (ISP), which performs the VNE over its physical telecom network. In several situations, the physical substrate infrastructure is composed of multiple independent ISPs. In this scenario, ISPs are concerned about exposing to a third-party entity (e.g., the customer) sensitive infrastructural details that are needed to perform an effective embedding. Following a common privacy-preserving approach, known as Limited Information Disclosure (LID), the embedding may be performed by the customer based on a limited and abstracted view of the multi-domain infrastructure that ISPs accept to expose. With this approach, embedding is sub-optimal (e.g., embedding cost is not minimized) in comparison with the case where all information is available, i.e., Full Information Disclosure (FID). In this work, we propose a Reinforcement-Learning-based algorithm able to process data that the customer and ISPs cipher under the Shamir Secret Sharing (SSS) scheme. This approach guarantees total privacy to both the customer and the ISPs (e.g., details about a virtual function are only revealed to the ISP in charge of hosting it) and achieves comparable embedding cost of an existing FID heuristic, as observed from extensive simulations. The main drawback of our algorithm is the high overhead of data that ISPs and the customer need to exchange with each other to execute it. Hence, we also explore the trade-off between embedding cost and data overhead resulting from the reduction of operations done by the RL. In general, intermediate embedding costs between the FID and LID heuristics can be obtained at a significant reduction of data overhead, while not sacrificing any privacy guarantees.

Effective Risk Communication for Public Health Emergency: Reflection on the COVID-19 (2019-nCoV) Outbreak in Wuhan, China.

Risk communication is critical to emergency management. The objective of this paper is to illustrate the effective process and attention points of risk communication reflecting on the COVID-19 (2019-nCoV) outbreak in Wuhan, China. We provide the timeline of risk communication progress in Wuhan and use a message-centered approach to identify problems that it entailed. It was found that the delayed decision making of the local government officials and the limited information disclosure should be mainly responsible for the ineffective risk communication. The principles for effective risk communication concerning Wuhan’s outbreak management were also discussed. The whole communication process is suggested to integrate the accessibility and openness of risk information, the timing and frequency of communication, and the strategies dealing with uncertainties. Based on these principles and lessons from Wuhan’s case, this paper employed a simplified Government–Expert–Public risk communication model to illustrate a collaborative network for effective risk communication.

The impact of explanatory factors on a bidimensional model of transparency in Spanish local government

The aim of this paper is to analyse the transparency provided by local public managers and to determine whether this disclosure is limited to the minimum quantity permissible (in accordance with Agency Theory) or whether a maximum amount of information is supplied (following Legitimacy Theory). To do so, we present a Bidimensional Transparency Index (BTI), developed as an instrument for measuring the provision of information (i.e. e-disclosure), which contains two components, breadth and depth, to reflect the pattern of behaviour observed. The results obtained show that on average local managers disclose information corresponding to 60% of the indicators considered, but that only 52% of these indicators of transparency present a moderate or considerable depth of content. These findings reflect a pattern of limited information disclosure, with incomplete information. In addition, our study shows that explanatory factors have an asymmetric impact on the components of the BTI.

Identifying Collusion in English Auctions

We develop a fully nonparametric identification framework and a test of collusion in ascending bid auctions. Assuming efficient collusion, we show that the underlying distributions of values can be identified despite collusive behaviour when there is at least one bidder outside the cartel. We propose a nonparametric estimation procedure for the distributions of values and a bootstrap test of the null hypothesis of competitive behaviour against the alternative of collusion. Our framework allows for asymmetric bidders, and the test can be performed on individual bidders. The test is applied to the Guaranteed Investment Certificate auctions conducted by US municipalities over the Internet. Despite the fact that there have been allegations of collusion in this market, our test does not detect deviations from competition. A plausible explanation of this finding is that the Internet auction design involves very limited information disclosure.

Multi-Provider Virtual Network Embedding With Limited Information Disclosure

The ever-increasing need to diversify the Internet has recently revived the interest in network virtualization. Wide-area virtual network (VN) deployment raises the need for VN embedding (VNE) across multiple Infrastructure Providers (InPs), due to the InP's limited geographic footprint. Multi-provider VNE, in turn, requires a layer of indirection, interposed between the Service Providers and the InPs. Such brokers, usually known as VN Providers, are expected to have very limited knowledge of the physical infrastructure, since InPs will not be willing to disclose detailed information about their network topology and resource availability to third parties. Such information disclosure policies entail significant implications on resource discovery and allocation. In this paper, we study the challenging problem of multi-provider VNE with limited information disclosure (LID). In this context, we initially investigate the visibility of VN Providers on substrate network resources and question the suitability of topology-based requests for VNE. Subsequently, we present linear programming formulations for: (i) the partitioning of traffic matrix based VN requests into segments mappable to InPs, and (ii) the mapping of VN segments into substrate network topologies. VN request partitioning is carried out under LID, i.e., VN Providers access only information which is not deemed confidential by InPs. We further investigate the suboptimality of LID on VNE against a “best-case” scenario where the complete network topology and resource availability information is available to VN Providers.

Remuneration Committees in South African Listed Companies

This article examines the administration of executive compensation in listed South African companies in order to understand the background to the emotive expressions by the public concerning the amount of executive earnings. It conducts research in order to ascertain whether a Remuneration Committee (RC) is effective. It begins by looking at the history of limited information disclosure which existed before the 1990s and describes cases where companies suffered losses due to the Agency Theory (AT) when executives dominated boards. This was followed by the subsequent introduction and application of Corporate Governance and controls to a RC. The discussion is based on the available literature and the findings from interviews and an electronic survey that was dispatched to a large selection of listed companies. A variety of views indicate fresh thoughts on the topicality of the relatively new concepts surrounding RCs which enquiries and interviews have shown are not well understood. Thus the study fills the gap in knowledge on RCs.

Collaborative agglomerative document clustering with limited information disclosure

ABSTRACTDocument clustering is a practical and powerful data mining technique to analyze large amount of documents and large sets of text or hypertext documents. However, it also brings the problem of sensitive information leaking in disregard of privacy, especially when it is executed in distributed environment. In this paper, we propose a cryptography‐based framework to realize privacy‐preserving document clustering among the users under the distributed environment; there are two parties, each having his private document database, want to collaboratively execute agglomerative document clustering without disclosing their private contents. We provide two implementations of such a framework, one is with more precision and stronger security but requires more computational resources. The other is a simplified version with less computational complexity and achieves higher processing speed. Additionally, we provide the security proofs and experimental analysis of precision and scalability of our proposal. Copyright © 2013 John Wiley & Sons, Ltd.

Building virtual networks across multiple domains

This paper presents a platform for virtual network (VN) provisioning across multiple domains. The platform decomposes VN provisioning into multiple steps to address the implications of limited information disclosure on resource discovery and allocation. A new VN embedding algorithm with simultaneous node and link mapping allows to assign resources within each domain. For inter-domain virtual link setup, we design and realize a signaling protocol that also integrates resource reservations for providing virtual links with Quality-of-Service guarantees. Experimental results show that small VNs can be provisioned within a few seconds.

Introduction to the Special Issue on Economics and Strategy of Entrepreneurship

This special issue is the outgrowth of a 2007 conference, Entrepreneurship: Strategy and Structure, sponsored by the NBER Working Groups on Entrepreneurship and Innovation Policy and the Economy. The aim of the conference and special issue are to provide a forum for rigorous frontier research on the microeconomic and institutional foundations of entrepreneurship, and the strategic and market consequences of entrepreneurial activity. The papers included in the Special Issue include a subset of papers presented at the conference as well as papers submitted as the result of a solicitation for the Special Issue from the journal. As with all special issues in JEMS, all of the articles in this issue have gone through the standard editing and refereeing process that is applied to all submissions to JEMS. We would especially like to thank Dan Spulber, Josh Lerner, and Bob Strom for their help throughout the process, and the Kauffman Foundation for providing support for the original NBER conference. Although traditional research in economics has mostly ignored entrepreneurship, or otherwise equated it with a mechanism for finding market equilibrium, economists have made considerable progress more recently in understanding the economic foundations and consequences of entrepreneurial activity. Applying frontier theoretical and empirical

Sustainable tourism in Greek islands: the integration of activity‐based environmental management with a destination environmental scorecard based on the adaptive resource management paradigm

AbstractTourism is a major industry that can lead to economic gains as well as to degraded environment and social infrastructure. Tourism has the potential to destroy the available common environmental resources through overuse and poor management practices, as limited information disclosure and poor monitoring of actions encourage the perpetuation and extension of environmental problems. Based on the adaptive resource management paradigm for addressing problems related to the use of the commons, this paper suggests a methodology for the development of a management tool that can provide island hotels with a continuous flow of timely, relevant, accurate and objective information on the environmental impact of critical corporate activities. The tool, named the destination environmental scorecard (DES), draws on activity‐based management concepts and can help local hotel SMEs measure and compare their performance against certain standards and thus conduct operations in a responsible and measurable way to the benefit of both business financial performance and regional sustainability. The paper presents the DES operational characteristics and the potential benefits from its implementation. Copyright © 2008 John Wiley & Sons, Ltd and ERP Environment.