A literature review of RFID-enabled healthcare applications and issues

Despite the rising implementation of RFID technology-based healthcare services, few empirical studies have been conducted to assess the potential of this technology within the healthcare sector. The purpose of this study is to help initiate and direct such empirical research by both conducting a review of the extant literature and using the findings to provide a discussion of current trends and future directions in this domain. In this paper, we develop a conceptual framework that can be used to classify publications on RFID applications and issues in the healthcare industry. We then use this framework to systematically summarize relevant articles. We conclude by highlighting future research directions where the deployment of RFID technology is likely to transform the healthcare sector.     

Healthcare big data processing mechanisms: The role of cloud computing

Recently, patient safety and healthcare have gained high attention in professional and health policy-makers. This rapid growth causes generating a high amount of data, which is known as big data. Therefore, handling and processing of this data are attracted great attention. Cloud computing is one of the main choices for handling and processing of this type of data. But, as far as we know, the detailed review and deep discussion in this filed are very rare. Therefore, this paper reviews and discusses the recently introduced mechanisms in this field as well as providing a deep analysis of their applied mechanisms. Moreover, the drawbacks and benefits of the reviewed mechanisms have been discussed and the main challenges of these mechanisms are highlighted for developing more efficient healthcare big data processing techniques over cloud computing in the future.     

User values and the development of a cybersecurity public policy for the IoT

Public administrators, entrusted to develop public policy to manage the growing complexities of the IoT, face significant challenges. The challenges exist because of three reasons; First, there is a lack of policy direction. Second, user values related to cybersecurity are not well understood. Third, there is a lack of clarity as to how IoT public policy should be developed. In this paper we argue that new IoT policy should be guided by key stakeholder values (i.e. what users think to be important). We utilize the Public Value Forum to elicit public values to inform decision-making surrounding IoT policy by public administrators, conceptually informed by Rational choice theory. We use a five-phase process to introduce the decision context (i.e. the policy problem), define fundamental objectives, rank these objectives, identify value-based trade-offs between them and construct a multi-attribute utility model. The findings indicate several key themes for IoT security from the citizens themselves and decision-making administrators in diverse public agencies developing IoT cybersecurity public policy.     

Context matters: A review of the determinant factors in the decision to adopt cloud computing in healthcare

Cloud computing is an IT service paradigm that can, if used meaningfully, enhance traditional health IT approaches and offer major benefits to the healthcare industry. However, its adoption by healthcare organizations has been accompanied by diverse challenges that could impede its meaningful use. Decisions about its adoption should be made after serious consideration of relevant industry-specific factors. Whereas the literature has focused on cloud computing adoption in general, the industrial specificities that influence the decision to adopt cloud computing in the healthcare context have yet to be systematically addressed. We reviewed empirical studies on both information systems and medical informatics to investigate the determinant factors of the cloud computing adoption decision in healthcare organizations and the industrial specificities of those factors. Based on the results of our review, we proposed a conceptual framework of cloud computing adoption studies in healthcare and made seven recommendations for related future research. Our research contributes to the theory by providing a comprehensive list of industry-specific factors that influence cloud computing adoption decisions in healthcare and explains their specificities for the healthcare industry. For practitioners, the identified factors serve as a checklist that informs healthcare organizations’ decision making regarding cloud computing adoption.     

学术创业：研究综述与展望

    以1980至2020年发表的相关文献为基础,对学术创业的研究内容进行梳理,内容如下：（1）总结了已有研究中常用的学术创业概念和分类;（2）围绕学术创业主体,重点阐述了个体层面学术创业活动的研究成果;（3）对学术创业领域常用的理论及其适用问题进行了诠释;（4）从社会经济和基础科学两个方面介绍了学术创业的影响;（5）提出学术创业的研究展望,即关注数智经济阶段学术创业类型的变化、拓展学术创业研究的理论视角、扩充学术创业的研究主题以及在进一步完善国内学术创业研究体系的同时,深化中国制度背景下学术创业问题的探索,如儒家文化环境中的学术创业动机,不同地区/省份的学术创业差异等。通过对已有研究的梳理,为中国学术创业的研究和发展提供了参考。     

高管团队认知能力、外部知识搜寻与效率型商业模式创新——大数据管理技能的调节作用

本研究以创新扩散理论为理论框架,通过两个阶段的问卷调查,以中国的323家企业为样本,考察了高管团队认知能力对EBMI的影响机制。层次回归结果表明：（1）高层团队认知能力对EBMI具有显著的正向影响;（2）外部知识搜寻在高管团队认知能力和EBMI之间起完全中介作用;（3）大数据管理技能调节高管团队认知能力和外部知识搜寻之间的关系,级大数据管理技能越高,高管团队认知能力和外部知识搜寻之间的正向关系越强;（4）大数据管理技能调节外部知识搜寻在高管团队认知能力和EBMI之间的中介效应,即大数据管理技能越高,外部知识搜寻在两者之间的间接关系越强。本研究结论验证了高层管理团队认知能力对EBMI的促进作用,拓展了EBMI前因变量的现有研究成果,对企业开展EBMI活动提供了理论指导。     

User resistance in IT: A literature review

User resistance is a complex phenomenon long viewed as a major constraint in successful information technology implementation. User resistance, which can vary between passive and active, could be a source of guidance towards reducing problems associated with organisational change. However, rather than embracing user resistance and seeing it as a learning opportunity and a tool for managing current and future difficulties around user resistance, organisations fear it. There exist a wide literature on user resistance spanning decades; focusing separately on user resistance, and various related factors. However, there is no comprehensive overview of the research work published. This study presents a comprehensive literature review to gain a better understanding of the contents of the current user resistance literature. Based on the findings from the literature review, areas of concern and the impact of user resistance on the development of new information technology are identified and how to overcome the resistance is suggested.     

Real-time big data processing for anomaly detection: A Survey

The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifically in the domain of anomaly detection in network, which is considered crucial for network security. However, preliminary investigations have revealed that the existing approaches to detect anomalies in network are not effective enough, particularly to detect them in real time. The reason for the inefficacy of current approaches is mainly due the amassment of massive volumes of data though the connected devices. Therefore, it is crucial to propose a framework that effectively handles real time big data processing and detect anomalies in networks. In this regard, this paper attempts to address the issue of detecting anomalies in real time. Respectively, this paper has surveyed the state-of-the-art real-time big data processing technologies related to anomaly detection and the vital characteristics of associated machine learning algorithms. This paper begins with the explanation of essential contexts and taxonomy of real-time big data processing, anomalous detection, and machine learning algorithms, followed by the review of big data processing technologies. Finally, the identified research challenges of real-time big data processing in anomaly detection are discussed.     

Making use of cloud computing for healthcare provision: Opportunities and challenges

Cloud or utility computing is an emerging new computing paradigm designed to deliver numerous computing services through networked media such as the Web. This approach offers several advantages to potential users such as “metered” use (i.e., pay-as-you-go) which offers scalability, online delivery of software and virtual hardware services (e.g., collaboration programmes, virtual servers, virtual storage devices) which would enable organizations to obviate the need to own, maintain and update their software and hardware infrastructures. The flexibility of this emerging computing service has opened many possibilities for organizations that did not exist before. Among those organizations are those engaged in healthcare provision. The aim of this article is to shed some light on this development and explore the potential (and future) of cloud computing in contributing to the advancement of healthcare provision. A small case study will also be presented and discussed.     

Social media and entrepreneurship research: A literature review

The rise of social media has led to changes in how entrepreneurs carry out their day-to-day activities. Studies on social media and entrepreneurship are relatively new and fragmented in their focus, however there is increasing interest from academia and practitioners for further research and investigation within this area. This study systematically reviews research carried out in the domain of social media and entrepreneurship. A total of 160 papers, published between 2002 and 2018 were synthesised to identify critical theories and research methods used in the domain. Based on the extent review, an integrative framework was developed to identify relationships amongst elucidated constructs. While most papers investigated the factors that drive social media adoption and use by entrepreneurs, it was found that the use of social media by entrepreneurs had transcended marketing and it is now used in business networking, information search and crowdfunding for their business. This has led to significant impact with improved firm performance and innovation enhancement being the essential outcomes. The literature review and framework further understanding of social media and entrepreneurship research, providing a useful basis for future studies and informs practice in this area.     

R&D人员绩效评价的研究述评 /FONT /P

21世纪是知识经济的时代,R&D人员是企业保持知识创新和持续竞争优势的最终源泉。当前学者大多集中于研究R&D部门、项目和团队的绩效,对R&D人员的绩效评价较少涉及。本文对国内外R&D人员绩效评价的主要方法进行了总结归纳,评述了当前R&D人员绩效评价研究的难点与问题,指出了R&D人员绩效评价的发展趋势,希望对R&D人员绩效评价的研究有所裨益。     

Remembering me: big data,individual identity,and the psychological necessity of forgetting

Each of us has a personal narrative: a story that defines us, and one that we tell about ourselves to our inner and outer worlds. A strong sense of identity is rooted in a personal narrative that has coherence and correspondence (Conway in J Mem Lang 53:594–628, 2005): coherence in the sense that the story we tell is consistent with and supportive of our current version of ‘self’; and correspondence in the sense that the story reflects the contents of autobiographical memory and the meaning of our experiences. These goals are achieved by a reciprocal interaction of autobiographical memory and the self, in which memories consistent with the self-image are reinforced, in turn strengthening the self-image they reflect. Thus, personal narratives depend crucially on the malleable nature of autobiographical memory: a strong sense of self requires that one remember what matters, and forget what does not. Today, anyone who is active online generates a highly detailed, ever—expanding, and permanent digital biographical ‘memory’—memory that identifies where we go, what we say, who we see, and what we do in increasing detail as our physical lives become more and more enmeshed with electronic devices capable of recording our communications, online activities, movements, and even bodily functions. This paper explores the consequences of this digital record for identity, arguing that it presents a challenge to our ability to construct our own personal narratives–narratives that are central to a sense of ‘self’. In the end, the ‘right to be forgotten’ may be, above all else, a psychological necessity that is core to identity—and therefore a value that we must ensure is protected.     

The dual effects of the Internet of Things (IoT): A systematic review of the benefits and risks of IoT adoption by organizations

The Internet of Things (IoT) might yield many benefits for organizations, but like other technology adoptions may also introduce unforeseen risks and requiring substantial organizational transformations. This paper analyzes IoT adoption by organizations, and identifies IoT benefits and risks. A Big, Open, Linked Data (BOLD) categorization of the expected benefits and risks of IoT is made by conducting a comprehensive literature study. In-depth case studies in the field of asset management were then executed to examine the actual experienced, real world benefits and risks. The duality of technology is used as our theoretical lens to understand the interactions between organization and technology. The results confirm the duality that gaining the benefits of IoT in asset management produces unexpected social changes that lead to structural transformation of the organization. IoT can provide organizations with many benefits, after having dealt with unexpected risks and making the necessary organizational changes. There is a need to introduce changes to the organization, processes and systems, to develop capabilities and ensure that IoT fits the organization’s purposes.     

Information,knowledge and collaboration management in the internationalisation of SMEs: A systematic literature review

Information and knowledge can be seen as key resources for improving the internationalisation processes of small and medium-sized enterprises (SMEs). Collaboration has also been considered as an important facilitator of these processes, particularly by nurturing information and knowledge sharing. However, the current literature is unclear about the way SMEs can access information and assimilate knowledge in a collaborative network context, to support decision-making. This paper systematically reviews the literature, examining the role of information, knowledge and collaboration in internationalisation decisions of SMEs. To this end, 38 relevant journal articles were analysed, with the identification of some important issues, as well as gaps in the existing empirical knowledge. This analysis provided valuable input for the development of research suggestions and directions for future work in this area.     

Big data management in healthcare: Adoption challenges and implications

The computerized healthcare information system has undergone tremendous advancements in the previous two decades. Medical institutions are paying further attention to the replacement of traditional approaches that can no longer handle the increasing amount of patient data. In recent years, the healthcare information system based on big data has been growing rapidly and is being adapted to medical information to derive important health trends and support timely preventive care. This research aims to evaluate organization-driven barriers in implementing a healthcare information system based on big data. It adopts the analytic network process approach to determine the aspect weight and applies VlseKriterijumska Optimizacija I Kzompromisno Resenje (VIKOR) to conclude a highly appropriate strategy for overcoming such barriers. The proposed model can provide hospital managers with forecasts and implications that facilitate the withdrawal of organizational barriers when adopting the healthcare information system based on big data into their healthcare service system. Results can provide benefits for increasing the effectiveness and quality of the healthcare information system based on big data in the healthcare industry. Therefore, by understanding the sequence of the importance of resistance factors, managers can formulate efficient strategies to solve problems with appropriate priorities.     

Real-time analytics,incident response process agility and enterprise cybersecurity performance: A contingent resource-based analysis

Emerging paradigms of attack challenge enterprise cybersecurity with sophisticated custom-built tools, unpredictable patterns of exploitation, and an increasing ability to adapt to cyber defenses. As a result, organizations continue to experience incidents and suffer losses. The responsibility to respond to cybersecurity incidents lies with the incident response (IR) function. We argue that (1) organizations must develop ‘agility’ in their IR process to respond swiftly and efficiently to sophisticated and potent cyber threats, and (2) Real-time analytics (RTA) gives organizations a unique opportunity to drive their IR process in an agile manner by detecting cybersecurity incidents quickly and responding to them proactively. To better understand how organizations can use RTA to enable IR agility, we analyzed in-depth data from twenty expert interviews using a contingent resource-based view. The results informed a framework explaining how organizations enable agile characteristics (swiftness, flexibility, and innovation) in the IR process using the key features of the RTA capability (complex event processing, decision automation, and on-demand and continuous data analysis) to detect and respond to cybersecurity incidents as-they-occur which, in turn, improves their overall enterprise cybersecurity performance.     

A survey towards an integration of big data analytics to big insights for value-creation

Big Data Analytics (BDA) is increasingly becoming a trending practice that generates an enormous amount of data and provides a new opportunity that is helpful in relevant decision-making. The developments in Big Data Analytics provide a new paradigm and solutions for big data sources, storage, and advanced analytics. The BDA provide a nuanced view of big data development, and insights on how it can truly create value for firm and customer. This article presents a comprehensive, well-informed examination, and realistic analysis of deploying big data analytics successfully in companies. It provides an overview of the architecture of BDA including six components, namely: (i) data generation, (ii) data acquisition, (iii) data storage, (iv) advanced data analytics, (v) data visualization, and (vi) decision-making for value-creation. In this paper, seven V's characteristics of BDA namely Volume, Velocity, Variety, Valence, Veracity, Variability, and Value are explored. The various big data analytics tools, techniques and technologies have been described. Furthermore, it presents a methodical analysis for the usage of Big Data Analytics in various applications such as agriculture, healthcare, cyber security, and smart city. This paper also highlights the previous research, challenges, current status, and future directions of big data analytics for various application platforms. This overview highlights three issues, namely (i) concepts, characteristics and processing paradigms of Big Data Analytics; (ii) the state-of-the-art framework for decision-making in BDA for companies to insight value-creation; and (iii) the current challenges of Big Data Analytics as well as possible future directions.