The Anesthesia Continuing Education Market and the Value Creation From a Sustainable Unified Platform

Practicing anesthesia professionals in the United States are all governed by various profession-specific regulatory bodies that mandate continuing education (CE) requirements. To date, no unified resource exists for anesthesia professionals (i.e., Anesthesiologists, Certified Registered Nurse Anesthetists, and Anesthesiologist Assistants) to explore the CE offerings available within the marketplace. This study endeavored to convey the potential value of a unified anesthesia CE resource. It investigated how to cultivate a sustainable platform to potentially improve how anesthesia professionals search available CE offerings and to potentially enhance how anesthesia CE providers reach anesthesia professionals. This qualitative study was conducted utilizing an integrative review of the literature. The key concepts identified and investigated were network effect, segmentation, first to market, best of breed, search costs, transaction costs, minimally viable product, evolutionary phases of platforms, platform theory, platform business model, platform economy, and types of platforms. Inductive content analysis was chosen as the organizational method for the resultant qualitative data. The goal of the analysis was to create a conceptual, practical, and strategically applicable platform paradigm for the anesthesia CE marketplace driven by the insights and amalgamations from the literature. The analyzed concepts, dimensions, and indicators of platform successes and their applications potentially facilitate anesthesia professionals’ CE explorations and CE providers’ marketing efforts, as well as contextualize the overarching impacts and implications onto the anesthesia CE industry and beyond. The conclusion portrays these impacts and implications

Technology in the 21st Century: New Challenges and Opportunities

Although big data, big data analytics (BDA) and business intelligence have attracted growing attention of both academics and practitioners, a lack of clarity persists about how BDA has been applied in business and management domains. In reflecting on Professor Ayre's contributions, we want to extend his ideas on technological change by incorporating the discourses around big data, BDA and business intelligence. With this in mind, we integrate the burgeoning but disjointed streams of research on big data, BDA and business intelligence to develop unified frameworks. Our review takes on both technical and managerial perspectives to explore the complex nature of big data, techniques in big data analytics and utilisation of big data in business and management community. The advanced analytics techniques appear pivotal in bridging big data and business intelligence. The study of advanced analytics techniques and their applications in big data analytics led to identification of promising avenues for future research

IT Artifacts and The State of IS Research

To understand the state of IS research is, to a large extent, to understand (1) what are considered IT artifacts by IS scholars, and (2) how do IS scholars approach IT artifacts in their studies. This study addresses these two questions by providing a conceptual model of five types of core IT artifacts and a five-facet framework of IS scholars’ approaches to studying IT artifacts. Using a critical literature review, the conceptualizations are tested with the collective wisdom by IS scholars in the most recent IS studies published in the 2009 and 2010 ICIS proceedings. The findings shed light on where the IS discipline is standing in terms of its focus on IT artifacts. Implications for research and practice are discussed. This study contributes to our continued understanding of the development and evolution of the IS discipline and the potential directions it may take

Skilling up for CRM: qualifications for CRM professionals in the Fourth Industrial Revolution

The 4th industrial revolution (4IR) describes a series of innovations in artificial intelligence, ubiquitous internet connectivity, and robotics, along with the subsequent disruption to the means of production. The impact of 4IR on industry reveals a construct called Industry 4.0. Higher education, too, is called to transform to respond to the disruption of 4IR, to meet the needs of industry, and to maximize human flourishing. Education 4.0 describes 4IR’s impact or predicted impact or intended impact on higher education, including prescriptions for HE’s transformation to realize these challenges. Industry 4.0 requires a highly skilled workforce, and a 4IR world raises questions about skills portability, durability, and lifespan. Every vertical within industry will be impacted by 4IR and such impact will manifest in needs for diverse employees possessing distinct competencies. Customer relationship management (CRM) describes the use of information systems to implement a customer-centric strategy and to practice relationship marketing (RM). Salesforce, a market leading CRM vendor, proposes its products alone will generate 9 million new jobs and $1.6 trillion in new revenues for Salesforce customers by 2024. Despite the strong market for CRM skills, a recent paper in a prominent IS journal claims higher education is not preparing students for CRM careers. In order to supply the CRM domain with skilled workers, it is imperative that higher education develop curricula oriented toward the CRM professional. Assessing skills needed for specific industry roles has long been an important task in IS pedagogy, but we did not find a paper in our literature review that explored the Salesforce administrator role. In this paper, we report the background, methodology, and results of a content analysis of Salesforce Administrator job postings retrieved from popular job sites. We further report the results of semi-structured interviews with industry experts, which served to validate, revise, and extend the content analysis framework. Our resulting skills framework serves as a foundation for CRM curriculum development and our resulting analysis incorporates elements of Education 4.0 to provide a roadmap for educating students to be successful with CRM in a 4IR world

INNOVATIVE DIGITAL START-UPS AND THEIR VENTURE CREATION PROCESS WITH ENABLING DIGITAL PLATFORMS

Start-ups have gained media attention since Google, Facebook and Amazon were launched in the 1990s. The book Lean Start-up, published in 2011, was another important milestone for digital start-up literature. As unicorn companies emerge around the world, topics highlighted in the news include the vast amount of capital that digital start-ups are raising, the ways in which these digital ventures are disrupting industries, and their global impact on digital economy. However, digital start-ups, digital venture ideas, and their venture creation process lack a unified venture creation model, as there is a gap in the re-search on entrepreneurial processes in a digital context. This research is an explorative study of the venture creation process of innovative digital start-ups that examines what is missing from entrepreneurial process models in a digital technology context and investi-gates how early stage digital start-ups conduct the venture creation process, starting with the pre-phase of antecedents and ending with the launch and scaling of the venture. The research proposes a novel process model of innovative digital start-up venture crea-tion and describes the nature and patterns of the process. A conceptual model was devel-oped based on the entrepreneurship, information systems, and digital innovation litera-ture and empirically assessed with a multi-method qualitative research design. The data collected from semi-structured interviews, internet sources, and observation field notes covered 34 innovative digital start-ups and their founders. Interviews were conducted in-ternationally in high-ranking start-up ecosystems, and the data were analysed with the-matic analysis and fact-checked by triangulating internet data sources. The contribution to entrepreneurship theory is a new illustrative model of the venture creation process of innovative digital start-ups, including the emergent outcome of the process having a digi-tal artefact at its core (e.g., mobile apps, web-based solutions, digital platforms, software solutions, and digital ecosystems). Digital platforms and their multiple roles in the process are presented, as well as the role of critical events as moderators of the process which trigger new development cycles. During the venture creation process, the recombining of digital technologies, modules, and components enabled by digital infrastructures, plat-forms, and ecosystem partners represent digital technology affordances. This recombina-tion provides opportunities for asset-free development of digital venture ideas

A Normative Classification of Consumer Big Data

The big data phenomenon has transformed every area of life and business. Businesses today rely on the volume, velocity, and variety (3Vs) of data available today in product design, advertisement, sales, and post-sale follow up activities. Communication between the firm and the consumer is personalized using data collected on the consumer to match the consumer’s location, time, and needs. Some marketers argue that this has birth a new era of marketing; transformative marketing, in which the firm’s ability to deliver value and to acquire and maintain long-run competitive advantage determined by the firm’s data resources. In other words, data are the currency of the transformative marketing era. This sentiment is pervasive and has led to massive investments in data in recent years. This dissertation puts forward a classification of consumer big data to aid the firm extract value out of big data despite the 3Vs. The classification also demonstrates how value in a transformative marketing era does not have to be created at the expense of the consumer, but with the consumer. Five conceptual dichotomies are put forward in essay two that are more comprehensive than any other classification of data available in the research. Finally, the third essay investigates how the big data phenomenon affects consumer freedom and emotions. Most people agree that freedom is a fundamental human right, and that business practices should respect consumer freedom. However, research on consumer freedom is scant. Two experiments investigate how the characteristics of data collected on consumers affects consumer perception of decision freedom and satisfaction with value propositions. With the big data phenomenon has come a push toward algorithmic decision making. Consumer’s anxiety toward algorithmic decision making is investigated along with the satisfaction derived from decisions made by third parties that collect data on consumers

Tools and techniques for security and privacy of big data: Healthcare system as a case study

As a case study, this Master thesis will also review the state-of-the-art of security and privacy issues in big data as applied to healthcare industry

Surveillance in ubiquitous network societies: Normative conflicts related to the consumer in-store supermarket experience in the context of the Internet of Things

Peer-reviewed journal articleThe Internet of Things (IoT) is an emerging global infrastructure that employs wireless sensors to collect, store, and exchange data. Increasingly, applications for marketing and advertising have been articulated as a means to enhance the consumer shopping experience, in addition to improving efficiency. However, privacy advocates have challenged the mass aggregation of personally identifiable information in databases and geotracking, the use of location-based services to identify one’s precise location over time. This paper employs the framework of contextual integrity related to privacy developed by Nissenbaum (Privacy in context: technology, policy, and the integrity of social life. Stanford University Press, Stanford, 2010) as a tool to understand citizen response to implementation IoT-related technology in the supermarket. The purpose of the study was to identify and understand specific changes in information practices brought about by the IoT that may be perceived as privacy violations. Citizens were interviewed, read a scenario of near-term IoT implementation, and were asked to reflect on changes in the key actors involved, information attributes, and principles of transmission. Areas where new practices may occur with the IoT were then highlighted as potential problems (privacy violations). Issues identified included the mining of medical data, invasive targeted advertising, and loss of autonomy through marketing profiles or personal affect monitoring. While there were numerous aspects deemed desirable by the participants, some developments appeared to tip the balance between consumer benefit and corporate gain. This surveillance power creates an imbalance between the consumer and the corporation that may also impact individual autonomy. The ethical dimensions of this problem are discussed

Big Data and Its Applications in Smart Real Estate and the Disaster Management Life Cycle: A Systematic Analysis

Big data is the concept of enormous amounts of data being generated daily in different fields due to the increased use of technology and internet sources. Despite the various advancements and the hopes of better understanding, big data management and analysis remain a challenge, calling for more rigorous and detailed research, as well as the identifications of methods and ways in which big data could be tackled and put to good use. The existing research lacks in discussing and evaluating the pertinent tools and technologies to analyze big data in an efficient manner which calls for a comprehensive and holistic analysis of the published articles to summarize the concept of big data and see field-specific applications. To address this gap and keep a recent focus, research articles published in last decade, belonging to top-tier and high-impact journals, were retrieved using the search engines of Google Scholar, Scopus, and Web of Science that were narrowed down to a set of 139 relevant research articles. Different analyses were conducted on the retrieved papers including bibliometric analysis, keywords analysis, big data search trends, and authors’ names, countries, and affiliated institutes contributing the most to the field of big data. The comparative analyses show that, conceptually, big data lies at the intersection of the storage, statistics, technology, and research fields and emerged as an amalgam of these four fields with interlinked aspects such as data hosting and computing, data management, data refining, data patterns, and machine learning. The results further show that major characteristics of big data can be summarized using the seven Vs, which include variety, volume, variability, value, visualization, veracity, and velocity. Furthermore, the existing methods for big data analysis, their shortcomings, and the possible directions were also explored that could be taken for harnessing technology to ensure data analysis tools could be upgraded to be fast and efficient. The major challenges in handling big data include efficient storage, retrieval, analysis, and visualization of the large heterogeneous data, which can be tackled through authentication such as Kerberos and encrypted files, logging of attacks, secure communication through Secure Sockets Layer (SSL) and Transport Layer Security (TLS), data imputation, building learning models, dividing computations into sub-tasks, checkpoint applications for recursive tasks, and using Solid State Drives (SDD) and Phase Change Material (PCM) for storage. In terms of frameworks for big data management, two frameworks exist including Hadoop and Apache Spark, which must be used simultaneously to capture the holistic essence of the data and make the analyses meaningful, swift, and speedy. Further field-specific applications of big data in two promising and integrated fields, i.e., smart real estate and disaster management, were investigated, and a framework for field-specific applications, as well as a merger of the two areas through big data, was highlighted. The proposed frameworks show that big data can tackle the ever-present issues of customer regrets related to poor quality of information or lack of information in smart real estate to increase the customer satisfaction using an intermediate organization that can process and keep a check on the data being provided to the customers by the sellers and real estate managers. Similarly, for disaster and its risk management, data from social media, drones, multimedia, and search engines can be used to tackle natural disasters such as floods, bushfires, and earthquakes, as well as plan emergency responses. In addition, a merger framework for smart real estate and disaster risk management show that big data generated from the smart real estate in the form of occupant data, facilities management, and building integration and maintenance can be shared with the disaster risk management and emergency response teams to help prevent, prepare, respond to, or recover from the disasters

Appropriating Play: Examining Twitch.tv as a Commercial Platform

This thesis critically analyzes Twitch.tv, a gaming-oriented, online live-streaming site. Viewing the site as a ‘lean platform’ (Srnicek, 2017), it analyzes many aspects of Twitch’s business operations, including ownership structure, video game industry affiliations, use of data, and the monetization of user activity. This analysis then identifies three major areas of concern arising from these operations: the tendency toward monopolization in the gaming industry and its peripheral activities; the intensification of audience commodification; and, the tendency to turn professional streamers into precarious creative labourers. All of these implications point to a growing need for concerted labour organization. The goal of this thesis is to address gaps in the existing literature about Twitch and to provide a foundation for future critical inquiries into the site