Social media enable fast and widespread dissemination of information, both honest and dishonest. Misinformation is generally spread unintentionally. Disinformation, on the other hand, is intentionally dishonest and is designed to harm individuals and organizations, which usually benefts the sender fnancially. Health-related disinformation can be especially dangerous if people act on its claims. How do people determine if health content on social media is honest or if it contains disinformation? This review considers four papers about inductive research studies, where participants were exposed to actual social media posts about 10 health topics, ranging from weight loss to COVID-19 vaccines. Some of the posts were honest and some were dishonest. Participants in all four studies were asked to evaluate the veracity of the posts that they saw and to provide the reasons for their evaluations. Two studies were online surveys. The other studies were conducted in the lab, where the eye movements of participants were recorded with an eye tracker. The key fndings from the review were: (1) People were relatively good at detecting health-related disinformation, with detection success rates ranging from 66% to 90%; (2) People most frequently cited the quality of the source of a post as the reason they decided it was honest; (3) Variables key to successful detection were need for cognition and gender (and to a lesser extent, political aÿliation, education, and age); (4) In the eye tracking studies, the most common determinants of fxations on particular parts of a post were need for cognition, gender, and the veracity of the post; (5) The most important measure of fxation that infuenced detection success was number of fxations; and (6) Overall, need for cognition was the key factor in successful disinformation detection.
This paper provides a comprehensive analysis of the challenges and controversies associated with blockchain technology. It identifies technical challenges such as scalability, security, privacy, and interoperability, as well as business and adoption challenges, and the social, economic, ethical, and environmental controversies present in current blockchain systems. We argue that responsible blockchain development is key to overcoming these challenges and achieving mass adoption. This paper defines Responsible Blockchain and introduces the STEADI principles (sustainable, transparent, ethical, adaptive, decentralized, and inclusive) for responsible blockchain development. Additionally, it presents the Actor-Network Theory-based Responsible Development Methodology (ANT-RDM) for blockchains, which includes the steps of problematization, interessement, enrollment, and mobilization.
We encounter trust every day in our lives but it becomes increasingly important in technology-based transactions as traditional interpersonal trust factors cannot be applied as usual. As technology becomes more and more ubiquitous in our lives, we need to understand how trust in technology contexts is created, maintained, destroyed, and possibly rebuilt. This knowledge is important for the developers of technology, to create successful use, and for the users of technology, to be aware of the vulnerabilities and potential risks of technology use. This monograph examines the rich history of trust research outside of a technology context to assess existing trust studies in technology contexts and to inform the design and execution of future trust research in technology contexts. Because trust is a very complex construct, the authors first review the term. The rest of the review is organized in the context of personal, professional, and organizational relationships, looking at initial trust and the long-term evolution of trust. An overview of existing technology-based trust studies published in MIS Quarterly, Information Systems Research, and other Information Systems research outlets is provided. Finally, the authors identify where research and practical gaps and opportunities exist for future technology-based trust studies by balancing acquired and practical relevance.
With most technical fields, there exists a delay between fundamental academic research and practical industrial uptake. Whilst some sciences have robust and well-established processes for commercialisation, such as the pharmaceutical practice of regimented drug trials, other fields face transitory periods in which fundamental academic advancements diffuse gradually into the space of commerce and industry. For the still relatively young field of Automated/Autonomous Machine Learning (AutoML/AutonoML), that transitory period is under way, spurred on by a burgeoning interest from broader society. Yet, to date, little research has been undertaken to assess the current state of this dissemination and its uptake. Thus, this review makes two primary contributions to knowledge around this topic. Firstly, it provides the most up-to-date and comprehensive survey of existing AutoML tools, both open-source and commercial. Secondly, it motivates and outlines a framework for assessing whether an AutoML solution designed for real-world application is 'performant'; this framework extends beyond the limitations of typical academic criteria, considering a variety of stakeholder needs and the human-computer interactions required to service them. Thus, additionally supported by an extensive assessment and comparison of academic and commercial case-studies, this review evaluates mainstream engagement with AutoML in the early 2020s, identifying obstacles and opportunities for accelerating future uptake.
Information technology (IT) use has become essential to how individuals interact with the world. From ordering meals to taking classes or consulting a physician, so many aspects of daily life are bound up with IT that effective participation in the world demands IT use. The ubiquity of IT in work and personal lives has created a shift from IT as a tool to IT as a basis of identity formation and verification, making it fundamental to how we see ourselves and act in the world. The essential role of IT use in all aspects of daily life and social interactions has drawn information systems (IS) researchers' focus to identity issues. In this stream, IS scholars have examined IT implementation and usage as a determinant of identity, a medium for communicating and protecting identities, and how identities influence IT use. In recent years, IT use as identity has garnered interest. The IS literature on identity is rich and varied. There is substantial research interest in understanding the complex and constantly changing relationship between people and IT. To facilitate new theorizing, this monograph provides a review of diverse perspectives on IT use and identity. This work reviews 90 conceptual and empirical IS studies and identifies major themes, examines their theoretical foundations, and suggests an agenda for future research on IT use and identity.
Computer self-efficacy (CSE) has captured the interest of researchers from widely diverse knowledge domains for over four decades. During that time, the realm of computer adoption and use has evolved and flourished. Along with this evolution, our understanding of CSE, its utility in behavior modeling and training development, and its relationship to a diverse array of antecedents and precedents has continued to evolve. This monograph provides a comprehensive history of the CSE construct as it has been developed and applied within the field of information systems (IS), and within the broader academic communities that benefit from reference to IS research contributions. The authors present the breadth and depth of the CSE construct and offer a framework of extant knowledge and implications for future research within this knowledge domain. The principal contribution of this work is the assemblage of the bulk of the authors’ understanding and knowledge regarding the CSE construct and its associated streams of research into a single compendium. It is intended to facilitate future researchers to access the current thinking regarding the CSE construct and direct their efforts to the continued advancement of our understanding of computer self-efficacy.
Researchers travel on paths of knowledge throughout life and the outcomes of rigorous scientific investigation result in contributions of new knowledge to the world. The Information Systems (IS) discipline is particularly suited for contributing to digital innovations and the corresponding knowledge growth. IS research develops not only knowledge in the form of understanding and designing digital technologies but also the implementation and use of actual socio-technical systems. In this review, the authors integrate the current thinking in the design science research (DSR) literature around the conceptual and methodological foundations of these high-level topics into a conceptual knowledge path framework. The authors position DSR at the intersection of science and technology where the interplay of descriptive and prescriptive knowledge is most active. They delineate the various forms of prescriptive design knowledge and examine the knowledge paths that utilize and produce the varied forms of knowledge in a DSR project. They define, analyze, and expand the ideas of knowledge gaps and journeys and argue that more attention to design postulates in DSR along the outlined knowledge paths can contribute to an increase in actionable and sustainable digital innovations within the IS discipline. By doing so, the authors aim to guide and inspire design-oriented IS researchers to actively and deliberately consider and incorporate a greater variety of existing knowledge into their designs, reflect even more thoroughly and systematically on their knowledge usage and contributions, and explicate and document these reflections in their publications.
This monograph presents a unique and powerful bottom-up methodology for promoting and securing Sustainable Development Goals (SDGs) through innovative and creative decision-making and enactment in a wide variety of entrepreneurial innovation contexts. The authors identify four sustainable development enabling factors – (1) the presence of a trustworthy trading system for private and public goods; (2) the need for communication facilities for provenance exploration, authentication and demonstration; (3) the ability to build and support entrepreneurial innovation clusters bottom-up; and (4) the ability to establish caravanserai – and argue that these four factors can enable a strong bottom-up contribution to sustainability in all its forms. The authors investigate the changing contexts for decision support now emerging from the responses to pandemic-driven lockdowns, explore how in ancient history a set of sustainable development enabling factors was responsible for the enduring success of safe local and trans-national trading relationships, and reveal the role of these factors in recent history. They also provide a case study example of a coffee grower in Peru that successfully promotes the full set of sustainability-enabling factors through their own bottom-up innovative and creative activities. They discuss the opportunities arising from building a Sustainability-Enabling Decision Support (SEDS) platform and conclude by examining how success stories, mediated by a SEDS at the micro level can promote into new territories at the meso sand macro level guided by these sustainable development enabling factors.
Failure to learn from past mistakes and successes has consistently been a major obstacle to improving IT project management. IT Project Management: Lessons Learned from Project Retrospectives 1999-2020 addresses this shortcoming by integrating, updating, and extending the research findings from four previous studies on IT project retrospectives. The result is a “meta-retrospective” of 264 IT projects analyzed as part of a program of action research conducted between 1999 and 2020. When viewed individually, each retrospective tells a unique story and provides a rich understanding of the project management practices taken within a specific context during a particular timeframe. When viewed as a whole, these 264 projects provide an incredible opportunity to understand project management practices at a more macro level and to generate findings that can be generalized across a wide spectrum of applications and organizations.
The purpose of Process Theory: Background, Opportunity, and Challenges is to promote the use of process theory as an essential part of the body of knowledge relative to information systems (IS) which should be nurtured and expanded. To do this, this monograph addresses why process theory is important, how it can potentially enhance the discipline, and what needs to be tackled to make the development and application of process theory routine and useful. Process Theory: Background, Opportunity, and Challenges elaborates on the nature of theory, process, and their application to IS knowledge. While there is not an easy infrastructure for investing in this type of research and this monograph provides an initial piece around which the many pieces of infrastructure which are needed can be created. This monograph is aimed primarily at doctoral students, early career academics, and any other scholars who have not had a chance to focus on process as a component of their conceptual tool kit. It is intended to be helpful for those who intend to use process theory in their own research but also for those wishing to confidently review, promote, or just understand work in this area. It is hoped that this monograph will serve as a basis for invention of new process theory and new tools for creating, testing, and evaluating such theory.
Business-IT alignment and information technology-enabled innovation are essential for firm performance and competitive advantage. Over the last 30 years, alignment and innovation literature streams have grown and become important areas of inquiry in the Information Systems field. However, both literature streams have remained separate, and it is unclear where and how the two streams overlap. None of the existing reviews have systematically examined this overlap or how each literature stream informs the other. This monograph bridges this gap and presents findings from a review of the alignment and innovation literature streams published between 1990 and 2020. The authors summarize approaches, challenges, and opportunities seen in the alignment and innovation literature streams. The analysis reveals that alignment scholars tend to overlook the complexities inherent in the process of innovating and view innovation as a black box. Meanwhile, innovation scholars assume different organizational components during the innovation process seamlessly work together to support alignment. The authors conclude that scholars in both camps should consider undertaking studies that examine aligning and innovating as interdependent processes: aligning involves coordination and cooperation among business units, and, in many cases, innovations are needed to achieve alignment. Similarly, innovating with information technology jolts the organization out of its previous alignment and requires aligning in parallel to innovating to restore alignment. Information Technology Alignment and Innovation: 30 Years of Intersecting Research provides guidance to both scholars and practitioners interested in alignment and IT-enabled innovation.
Speech analytics utilizes speech recognition, predictive analytics, and authentication of the data streams while assessing customers' complaints in real-time. Assessment occurs through the collection and analysis of current data mixed with historical facts to determine patterns and to predict trends. In the current research, the authors have chosen to focus primarily on speech analytics, serving as an umbrella term encompassing speech analytics, audio-mining technologies. The use of speech analytics typically refers to a broader range of speech products, such as analyzing voice identification, emotion detection, and phonetics/speech analysis. Speech Analytics for Actionable Insights proceeds with the discussion of an overview of enterprise needs for speech analytics, a brief history of the speech recognition, the infrastructure of phonetic versus transcription approaches and real-time versus post-call solutions, major speech analytics vendors and their features, applications found within case studies, and recommendations and guidance. The primary goal of this monograph is to help business decision-makers educate themselves on the burgeoning field of speech analytics as well as to understand how it impacts the broader enterprise landscape.
Structured Conflict Approaches Used in Strategic Decision Making focuses on strategic planning processes which use structured conflict to aid in elicitating and exposing management’s underlying assumptions and how to stimulate management to adopt a broader view of the planning problem. The objective is to examine the whether structured conflict procedures are superior to expert or consensus-oriented procedures in face-to-face and virtual teams working on strategic decision-making tasks. The author begins with a brief background in section 2, then section 3 discusses structured conflict, followed by philosophical and empirical debate in section 4. Section 5 examines structured conflict: devil’s advocacy and dialectical inquiry studies in both case and field, and experimental studies. Section 6 presents an integrative analysis of the structured conflict studies. Section 7 focuses on leadership. Section 8 addresses structured conflict and leadership in virtual teams. Section 9 is the conclusion and addresses the issues of this paper and discusses potential future studies.
