The Role of Trust in the Intention to Use Feedback from Reputation Systems

Online reputation systems have evolved to increase our knowledge of sellers, products, services, and other individuals in the electronic setting of the Internet. Evidence from prior studies suggests that the feedback individuals provide through reputation systems in the form of numerical ratings, a given number of stars, and text commentary should alleviate an element of uncertainty when interacting in the online environment. However, the user of the feedback must believe that the feedback is trustworthy. To our knowledge, no studies exist which examine the role of trust with regard to the consumer’s intention to use feedback from reputation systems. As online interactions increase, mechanisms for reputation in this context continue to grow in importance. This study will endeavor to address a significant gap in current literature to examine how trust impacts the user’s intention to use feedback from online reputation systems

Factors That Influence Application Migration To Cloud Computing In Government Organizations: A Conjoint Approach

Cloud computing is becoming a viable option for Chief Information Officers (CIO’s) and business stakeholders to consider in today’s information technology (IT) environment, characterized by shrinking budgets and dynamic changes in the technology landscape. The objective of this study is to help Federal Government decision makers appropriately decide on the suitability of applications for migration to cloud computing. I draw from four theoretical perspectives: transaction cost theory, resource-based theory, agency theory and dynamic capabilities theory and use a conjoint analysis approach to understand stakeholder attitudes, opinions and behaviors in their decision to migrate applications to cloud computing. Based on a survey of 81 government cloud computing stakeholders, this research examined the relative importance of thirteen factors that organizations consider when migrating applications to cloud computing. Our results suggest that trust in the cloud computing vendor is the most significant factor, followed by the relative cost advantage, sensing capabilities and application complexity. A total of twelve follow-up interviews were conducted to provide explanation of our results. The contributions of the dissertation are twofold: 1) it provides novel insights into the relative importance of factors that influence government organizations’ decision to migrate applications to cloud computing, and 2) it assists senior government decision makers to appropriately weigh and prioritize the factors that are critical in application migration to cloud computing

Trusting Intentions Towards Robots in Healthcare: A Theoretical Framework

Within the next decade, robots (intelligent agents that are able to perform tasks normally requiring human intelligence) may become more popular when delivering healthcare services to patients. The use of robots in this way may be daunting for some members of the public, who may not understand this technology and deem it untrustworthy. Others may be excited to use and trust robots to support their healthcare needs. It is argued that (1) context plays an integral role in Information Systems (IS) research and (2) technology demonstrating anthropomorphic or system-like features impact the extent to which an individual trusts the technology. Yet, there is little research which integrates these two concepts within one study in healthcare. To address this gap, we develop a theoretical framework that considers trusting intentions towards robots based on the interaction of humans and robots within the contextual landscape of delivering healthcare services. This article presents a theory-based approach to developing effective trustworthy intelligent agents at the intersection of IS and Healthcare

Critical Impact of Social Networks Infodemic on Defeating Coronavirus COVID-19 Pandemic: Twitter-Based Study and Research Directions

News creation and consumption has been changing since the advent of social media. An estimated 2.95 billion people in 2019 used social media worldwide. The widespread of the Coronavirus COVID-19 resulted with a tsunami of social media. Most platforms were used to transmit relevant news, guidelines and precautions to people. According to WHO, uncontrolled conspiracy theories and propaganda are spreading faster than the COVID-19 pandemic itself, creating an infodemic and thus causing psychological panic, misleading medical advises, and economic disruption. Accordingly, discussions have been initiated with the objective of moderating all COVID-19 communications, except those initiated from trusted sources such as the WHO and authorized governmental entities. This paper presents a large-scale study based on data mined from Twitter. Extensive analysis has been performed on approximately one million COVID-19 related tweets collected over a period of two months. Furthermore, the profiles of 288,000 users were analyzed including unique users profiles, meta-data and tweets context. The study noted various interesting conclusions including the critical impact of the (1) exploitation of the COVID-19 crisis to redirect readers to irrelevant topics and (2) widespread of unauthentic medical precautions and information. Further data analysis revealed the importance of using social networks in a global pandemic crisis by relying on credible users with variety of occupations, content developers and influencers in specific fields. In this context, several insights and findings have been provided while elaborating computing and non-computing implications and research directions for potential solutions and social networks management strategies during crisis periods.Comment: 11 pages, 10 figures, Journal Articl

Opportunities for the digital transformation of the banana sector supply chain based on software with artificial intelligence

Artificial intelligence offers great opportunities for the supply chain, being this a competitive advantage for today’s changing market. This article aims to identify the impacts and opportunities that artificial intelligence software can offer to facilitate the operation and improve the performance of the supply chain in the banana sector in Colombia. The work methodology consists of six steps in which a total of 72 investigations were obtained. The sources of information were four databases. As a main conclusion, the supply chain of the banana sector has everything necessary for intelligent software based solutions to be implemented in order to achieve adaptation, flexibility and sensitivity to the context and domain of execution