Background Artificial intelligence (AI) can transform health care processes with its increasing ability to translate complex structured and unstructured data into actionable clinical decisions. Although it has been established that AI is much more efficient than a clinician, the adoption rate has been slower in health care. Prior studies have pointed out that the lack of trust in AI, privacy concerns, degrees of customer innovativeness, and perceived novelty value influence AI adoption. With the promotion of AI products to patients, the role of rhetoric in influencing these factors has received scant attention. Objective The main objective of this study was to examine whether communication strategies (ethos, pathos, and logos) are more successful in overcoming factors that hinder AI product adoption among patients. Methods We conducted experiments in which we manipulated the communication strategy (ethos, pathos, and logos) in promotional ads for an AI product. We collected responses from 150 participants using Amazon Mechanical Turk. Participants were randomly exposed to a specific rhetoric-based advertisement during the experiments. Results Our results indicate that using communication strategies to promote an AI product affects users’ trust, customer innovativeness, and perceived novelty value, leading to improved product adoption. Pathos-laden promotions improve AI product adoption by nudging users’ trust (n=52; β=.532; P<.001) and perceived novelty value of the product (n=52; β=.517; P=.001). Similarly, ethos-laden promotions improve AI product adoption by nudging customer innovativeness (n=50; β=.465; P<.001). In addition, logos-laden promotions improve AI product adoption by alleviating trust issues (n=48; β=.657; P<.001). Conclusions Promoting AI products to patients using rhetoric-based advertisements can help overcome factors that hinder AI adoption by assuaging user concerns about using a new AI agent in their care process.
BackgroundThe potential of blockchain technology to achieve strategic goals, such as value-based care, is increasingly being recognized by both researchers and practitioners. However, current research and practices lack comprehensive approaches for evaluating the benefits of blockchain applications.ObjectiveThe goal of this study was to develop a framework for holistically assessing the performance of blockchain initiatives in providing value-based care by extending the existing balanced scorecard (BSC) evaluation framework.MethodsBased on a review of the literature on value-based health care, blockchain technology, and methods for evaluating initiatives in disruptive technologies, we propose an extended BSC method for holistically evaluating blockchain applications in the provision of value-based health care. The proposed method extends the BSC framework, which has been extensively used to measure both financial and nonfinancial performance of organizations. The usefulness of our proposed framework is further demonstrated via a case study.ResultsWe describe the extended BSC framework, which includes five perspectives (both financial and nonfinancial) from which to assess the appropriateness and performance of blockchain initiatives in the health care domain.ConclusionsThe proposed framework moves us toward a holistic evaluation of both the financial and nonfinancial benefits of blockchain initiatives in the context of value-based care and its provision.
As activities are increasingly being digitalized in business and society, organizations have sought ways to effectively and competitively, use data. Business intelligence and analytics (BI&A) systems which support managerial decision-making continue to be developed and used. Given the importance of these systems, it would be useful to have a comprehensive and mature guide to support their development and improvement. This research proposes a BI&A Competitive Advantage Maturity Model to identify the main technical and non-technical dimensions of a system to support business intelligence and analysis. The model is based on work systems theory and related research. It maps descriptive characteristics of its main dimensions across analytic adoption stages of aspirational, experienced, and transformed. The development of the model employed a modified Delphi study technique, design science research, and citation analysis.
The challenge of securing critical data increases year after year. Evolving technology developments, involving the growth in cloud and the Internet of Things adoption make businesses' confidential data more vulnerable to sophisticated attackers. Protect the Whole Organization by using the Industry’s First Extended Detection and Response (XDR) Platform Security teams have been inundated with inaccurate, inadequate alerts. As a result of today's siloed security tools, specialists should pivot from the console to the console to piece together investigative clues, which will result in horribly slow investigations. Although they’ve implemented countless tools, teams still lack enterprise-wide visibility as well as the deep analytics necessary to locate threats. Confronted with a lack of security professionals, teams need to streamline operations. Extended Detection and Response is the world's very first extended detection and response platform which integrates endpoint, network, as well as cloud data to halt advanced attacks. It combines prevention, investigation, detection, and response in a single platform for unparalleled security and operational effectiveness. In combination with a Managed Threat Hunting assistance, XDR offers continuous protection and industry-leading coverage. A new and more comprehensive approach to detection and response is clearly needed, one which not just includes traditional endpoints but then also includes the enhanced attack surface like the network and cloud. Luckily, these are only a few of the difficulties XDR was intended to solve. XDR unites and extends detection and response capacity through multiple security layers, offering security teams along with centralized end-to-end enterprise visibility, strong analytics, automatic response across the entire technology stack. XDR, clients can get integrated and proactive security measures designed to protect the whole technology stack, which makes it easier for security analysts to detect and stop attacks in progress prior to the impact to the business. Companies of all sizes and types, irrespective of their levels of cybersecurity expertise, is necessary to be considered sophisticated detection, improved visibility, and immediate response to sophisticated threats. The goal here is to explain what XDR is and how it empowers Information Technology, security teams, to stop threats and put them on the defensive. And also show how it provides superior extensibility and analytics which will fit the needs of the future. In the present article, we’ll describe the fundamentals of XDR, and demonstrate how it help out for organizations as well as how it facilitates new security challenges. Moreover, this research paper will be useful for organizations to understand XDR in-depth, as well as how XDR can assist organizations in preventing cyberattacks as well as simplifying and improving security processes. In addition, this paper explains XDR, the capability of current and emerging technologies to offer greater visibility, collect and correlate threat information, andutilize analytics and automation to detect today and future attacks.
BACKGROUND The potential of blockchain technology to achieve strategic goals, such as value-based care, is increasingly being recognized by both researchers and practitioners. However, current research and practices lack comprehensive approaches for evaluating the benefits of blockchain applications. OBJECTIVE The goal of this study was to develop a framework for holistically assessing the performance of blockchain initiatives in providing value-based care by extending the existing balanced scorecard (BSC) evaluation framework. METHODS Based on a review of the literature on value-based health care, blockchain technology, and methods for evaluating initiatives in disruptive technologies, we propose an extended BSC method for holistically evaluating blockchain applications in the provision of value-based health care. The proposed method extends the BSC framework, which has been extensively used to measure both financial and nonfinancial performance of organizations. The usefulness of our proposed framework is further demonstrated via a case study. RESULTS We describe the extended BSC framework, which includes five perspectives (both financial and nonfinancial) from which to assess the appropriateness and performance of blockchain initiatives in the health care domain. CONCLUSIONS The proposed framework moves us toward a holistic evaluation of both the financial and nonfinancial benefits of blockchain initiatives in the context of value-based care and its provision.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.