Retweets of officials’ alarming vs reassuring messages during the COVID-19 pandemic: Implications for crisis management

Coronavirus related discussions have spiraled at an exponential rate since its initial outbreak. By the end of May, more than 6 million people were diagnosed with this infection. Twitter witnessed an outpouring of anxious tweets through messages associated with the spread of the virus. Government and health officials replied to the troubling tweets, reassuring the public with regular alerts on the virus's progress and information to defend against the virus. We observe that social media users are worried about Covid 19-related crisis and we identify three separate conversations on virus contagion, prevention, and the economy. We analyze the tone of officials’ tweet text as alarming and reassuring and capture the response of Twitter users to official communications. Such studies can provide insights to health officials and government agencies for crisis management, specifically regarding communicating emergency information to the public via social media for establishing reassurance.     

Will COVID-19 be the tipping point for the Intelligent Automation of work? A review of the debate and implications for research

As part of the urgent need to respond to the COVID-19 pandemic, governments, healthcare providers, and businesses have looked to applications of Artificial Intelligence (AI) to compensate for the unavailability of human workers. This interest has renewed the debate regarding the use of AI for the automation of work, which has been described as Intelligent Automation (IA). A new dimension to this debate is whether COVID-19 will be the catalyst for higher IA adoption levels. This article reviews arguments in favour of COVID-19 increasing the level of IA adoption and possible counter-arguments. Key arguments in favour of increased IA adoption include consumer preferences changing to favour IA, increasing familiarity of IA technologies, and increased business confidence in IA. Counter-arguments include big data availability and reliability limitations, many tasks still favouring human skills over IA, the narrow capabilities of IA technologies, and a high availability of human workers. The article also discusses the implications of this debate for information management research and practice.     

Who do you trust? The digital destruction of shared situational awareness and the COVID-19 infodemic

Developments in centrally managed communications (e.g. Twitter, Facebook) and service (e.g. Uber, airbnb) platforms, search engines and data aggregation (e.g. Google) as well as data analytics and artificial intelligence, have created an era of digital disruption during the last decade. Individual user profiles are produced by platform providers to make money from tracking, predicting, exploiting and influencing their users’ decision preferences and behavior, while product and service providers transform their business models by targeting potential customers with more accuracy. There have been many social and economic benefits to this digital disruption, but it has also largely contributed to the digital destruction of mental model alignment and shared situational awareness through the propagation of mis-information i.e. reinforcement of dissonant mental models by recommender algorithms, bots and trusted individual platform users (influencers). To mitigate this process of digital destruction, new methods and approaches to the centralized management of these platforms are needed to build on and encourage trust in the actors that use them (and by association trust in their mental models). The global ‘infodemic’ resulting from the COVID-19 pandemic of 2020, highlights the current problem confronting the information system discipline and the urgency of finding workable solutions.     

The adoption of M-government services from the user’s perspectives: Empirical evidence from the United Arab Emirates

The primary aim of this study is to examine the factors that predict end users’ intention to adopt mobile government (m-government) services in a developing country. The research is based upon a self-administered questionnaire survey of 120 current users’ in the United Arab Emirates (UAE), a leader in m-government development in the Arab world. The study employs advanced statistical techniques to test an extended the Technology Acceptance Model (TAM) by incorporating the determinants of trust, cost, social influence, variety of services, perceived usefulness in information technology and demographic profiles. The findings revealed that trust and social influence are positively associated with end users intention to adopt m-government services in the UAE. By identifying the predictors of users’ adoption of m-government, this study provides several theoretical and practical implications related to m-government service adoption.     

Online Versus Offline in the United States: Are the Media Shrinking?

We find that combined revenues for 10 major media in the United States have steadily declined as a proportion of overall economic activity or gross domestic product (GDP) from 1999 to at least 2009 (the latest year for which we have complete data). For individual media, we find a generally consistent pattern in which increasing revenues from Internet distribution are exceeded by declines in revenues from established distribution channels, with the exception of television and video games, whose revenues have so far kept pace with GDP. We also report a marked overall shift from advertiser to direct payment support for the media industries over this period. We consider four possible reasons for these revenue trends: shifts in consumer media usage, reduced appropriability due to more difficult copyright protection, inadequate advertising business models, and reduced costs due to more efficient Internet distribution. Our analysis suggests we may be entering an era of a declining size of media industries in terms of conventional measures, but not necessarily a falling supply of media products themselves.     

Emergence of Uncoventional Hydrocarbon Development in the United States： Global Implications on Oil ＆ Gas Markets

<正>The dynamic landscape for the quest for energy will continue as long as the human race exists and needs energy to grow and develop its economy.The demand for energy will continue to remain at the forefront of the U.S.economy even as China emerges as the world’s largest economy and consumer of energy.In 2008,the     

Investigating the business intelligence capabilities’ and network learning effect on the data mining for start-up's function

In recent years, Startups are new concepts in the tech world and are meant to be temporary organizations designed to find a repeatable, scalable business model, while offering a new solution to the problem. What matters most about the success of startups is the right and reasonable targeting. This is something that is usually overlooked by a large percentage of such businesses, causing them to fail within a short period of time. Production of new product or service delivery is not possible without planning. The purpose of this study is to look deeper into how startups should identify and prioritize issues and problems when launching a new product or service. First, startups and subject-related businesses reviewed and then novel and emerging issues, including the status of data mining on startups' performance, the topics of Business Intelligence (BI), innovation and networked learning, and also their role in startups business discussed. Results showed that BI can provide a competitive advantage to startups. With this in mind, these businesses may adapt to the diverse needs of customers in the market and continue to survive, as well as gain greater market share over their competitors. Further, employing technology tools helps companies make their data available seamlessly or securely and by analyzing it, giving managers a better way of making decisions. According to the hypotheses, it was found that BI as a powerful tool in the field of information technology, creates a competitive advantage and it is necessary for start-up managers to accept this tool.     

Nanotechnology for the management of COVID-19 during the pandemic and in the post-pandemic eraOA

Following the global COVID-19 pandemic,nanotechnology has been at the forefront of research efforts and enables the fast development of diagnostic tools,vaccines and antiviral treatment for this novel virus(SARS-CoV-2).In this review,we first summarize nanotechnology with regard to the detection of SARS-C oV-2,including nanoparticle-based techniques such as rapid antigen testing,and nanopore-based se quencing and sensing techniques.Then we investigate nanote chnology as it applies to the develop...     

The intermediating role of organizational culture and internal analytical knowledge between the capability of big data analytics and a firm’s performance

Firms are increasingly relying on business insights obtained by deploying data analytics. Analytics-driven business decisions have thus taken a strategic imperative role for the competitive advantage of a firm to endure. The extent and effectiveness through which business firms can actually derive benefits by deploying big data-based practices requires deep analysis and calls for extensive research. This study extends the big data analytics capability (BDAC) model by examining the mediatory effects of organizational culture (CL) between internal analytical knowledge (KN) and BDAC, as well as the mediating effects of BDAC between CL and firm performance. The findings bring into focus that CL plays the role of complementary mediation between BDAC and KN to positively impact firm performance (FP); BDAC also plays a similar mediatory role between CL and the performance of a firm.     

The anatomy of a troll? Patent licensing business models in the light of patent reassignment data

We examine patent licensing business models of non-practicing entities that generate revenue by selling, licensing, or litigating patents. They may also pursue R&D activities, invent new technologies, or provide services to inventors or product companies. We describe their business models and patent market behavior and then compare their litigation strategies against product companies using a matched sample of highly comparable patents. The main differences among patent licensing firms stem from their technological capabilities, patent portfolio sizes, and external relationships. We find that licensing firms with technological capabilities often pursue litigation until decision and engage in forum shopping. In contrast, litigation incidence, parties involved, and outcomes are primarily determined by patent characteristics, not entity types. Licensing business models drive the acquisition of certain types of patents that influence the outcomes of the patent system. We argue that patent policy should strengthen mechanisms to discover invention quality rather than focus on the amount of litigation or types of entities.