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Universities play a critical role in improving the economic prosperity and social well-being of a country. Many countries have invested heavily in higher education and funding university education for their citizens. Does more investment enhance universities' performances? What other factors contribute to universities' productivity? This research used the data envelopment analysis methodology to study the total factor productivity (TFP) of 60 Chinese universities from 2006 to 2016. The study found the values of TFP fluctuated between 0.950 and 1.050 and were relatively stable. Contrary to common belief about productivity improvements, universities with more investment from the Chinese government did not show better performances. Nevertheless, the study found evidence that human resources (e.g., postgraduate-teacher ratio), physical resources (e.g., campus areas), and policy factors (e.g., tenure of the presidents, mergers) have a positive impact on universities' productivity.

PurposePhishing attacks are the most common cyber threats targeted at users. Digital nudging in the form of framing and priming may reduce user susceptibility to phishing. This research focuses on two types of digital nudging, framing and priming, and examines the impact of framing and priming on users' behavior (i.e. action) in a cybersecurity setting. It draws on prospect theory, instance-based learning theory and dual-process theory to generate the research hypotheses.Design/methodology/approachA 3 × 2 experimental study was carried out to test the hypotheses. The experiment consisted of three levels for framing (i.e. no framing, negative framing and positive framing) and two levels for priming (i.e. with and without priming).FindingsThe findings suggest that priming users to information security risks reduces their risk-taking behavior, whereas positive and negative framing of information security messages regarding potential consequences of the available choices do not change users' behavior. The results also indicate that risk-averse cybersecurity behavior is associated with greater confidence with the action, greater perceived severity of cybersecurity risks, lower perceived susceptibility to cybersecurity risks resulting from the action and lower trust in the download link.Originality/valueThis research shows that digital nudging in the form of priming is an effective way to reduce users' exposure to cybersecurity risks.

IS/IT plays an important role in our everyday life, especially in today's Internet era This article discusses the roles of IS/IT in providing services and support on information gathering, analysis, and management during major public emergencies and pandemic crises such as the battle against the new coronavirus The five selected papers in this special issue introduce advanced methods on data collection and social media user analysis to deal with the challenges brought by the COVID-19 pandemic This paper also presents future research directions on the use of IS/IT in emergency and pandemic management such as IS control and governance, intelligent health care, enhancing people's lives and mental health, and knowledge management Copyright © 2021, IGI Global Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited

The exponential advancement in artificial intelligence (AI), machine learning, robotics, and automation are rapidly transforming industries and societies across the world. The way we work, the way we live, and the way we interact with others are expected to be transformed at a speed and scale beyond anything we have observed in human history. This new industrial revolution is expected, on one hand, to enhance and improve our lives and societies. On the other hand, it has the potential to cause major upheavals in our way of life and our societal norms. The window of opportunity to understand the impact of these technologies and to preempt their negative effects is closing rapidly. Humanity needs to be proactive, rather than reactive, in managing this new industrial revolution. This article looks at the promises, challenges, and future research directions of these transformative technologies. Not only are the technological aspects investigated, but behavioral, societal, policy, and governance issues are reviewed as well. This research contributes to the ongoing discussions and debates about AI, automation, machine learning, and robotics. It is hoped that this article will heighten awareness of the importance of understanding these disruptive technologies as a basis for formulating policies and regulations that can maximize the benefits of these advancements for humanity and, at the same time, curtail potential dangers and negative impacts.

This is an empirical research investigating the impact of business analytics (BA) and business intelligence (BI) use, IT infrastructure flexibility, and their interactions on organizational agility. Synthesizing the systems theory and awareness-motivation-capability framework, the authors propose that BA-Use, IT infrastructure flexibility, and their interactions significantly influence organizational agility. The results show the significant association of BA use and IT infrastructure flexibility with organizational agility. The results also suggest that BA use may demand corporations to build a more flexible IT infrastructure. However, the data does not reveal the proposed interaction between the two drivers of organizational agility.

Artificial intelligence (AI)-based technology has achieved many great things, such as facial recognition, medical diagnosis, and self-driving cars. AI promises enormous benefits for economic growth, social development, as well as human well-being and safety improvement. However, the low-level of explainability, data biases, data security, data privacy, and ethical problems of AI-based technology pose significant risks for users, developers, humanity, and societies. As AI advances, one critical issue is how to address the ethical and moral challenges associated with AI. Even though the concept of “machine ethics” was proposed around 2006, AI ethics is still in the infancy stage. AI ethics is the field related to the study of ethical issues in AI. To address AI ethics, one needs to consider the ethics of AI and how to build ethical AI. Ethics of AI studies the ethical principles, rules, guidelines, policies, and regulations that are related to AI. Ethical AI is an AI that performs and behaves ethically. One must recognize and understand the potential ethical and moral issues that may be caused by AI to formulate the necessary ethical principles, rules, guidelines, policies, and regulations for AI (i.e., Ethics of AI). With the appropriate ethics of AI, one can then build AI that exhibits ethical behavior (i.e., Ethical AI). This paper will discuss AI ethics by looking at the ethics of AI and ethical AI. What are the perceived ethical and moral issues with AI? What are the general and common ethical principles, rules, guidelines, policies, and regulations that can resolve or at least attenuate these ethical and moral issues with AI? What are some of the necessary features and characteristics of an ethical AI? How to adhere to the ethics of AI to build ethical AI?

The implementation of artificial intelligence (AI), machine learning, and autonomous technologies in the mining industry started about a decade ago with autonomous trucks. Artificial intelligence, machine learning, and autonomous technologies provide many economic benefits for the mining industry through cost reduction, efficiency, and improving productivity, reducing exposure of workers to hazardous conditions, continuous production, and improved safety. However, the implementation of these technologies has faced economic, financial, technological, workforce, and social challenges. This article discusses the current status of AI, machine learning, and autonomous technologies implementation in the mining industry and highlights potential areas of future application. The article presents the results of interviews with some of the stakeholders in the industry and what their perceptions are about the threats, challenges, benefits, and potential impacts of these advanced technologies. The article also presents their views on the future of these technologies and what are some of the steps needed for successful implementation of these technologies in this sector.