突发公共卫生事件应对中政府管控与大数据治理研究——基于对新冠肺炎疫情的治理能力思考

随着数据在社会治理创新中的普及与发展,数据治理开始进入公众视野。在网络信息时代,数据治理是应对重大公共利益挑战的一场数据革命,如何实现在疫情时期的数据共享,重构政府管控与数据治理的关系,实现在大数据时代的数据高效治理,是摆在当前社会治理体系构建过程中的重大现实考验。本文从突发公共卫生事件对数据治理的机制诉求与挑战、强化政府舆论引导与数据治理在突发公共卫生事件中的双向发力、数据治理新机制的科学创建以及数据治理对预防突发公共卫生事件的实践效能等四个方面来探析突发公共卫生事件应对中的舆情引导与大数据治理,以此推动大数据治理体系建设的固定化、制度化、法治化。     

Impact of data trade restrictions on IT services export: A cross-country analysis

Trade in digital goods and services have witnessed increasing growth in recent years, accompanied by a corresponding increase in data flows across national boundaries. At the same time, governments around the world have enacted data policies that restrict such cross border data flows in their effort to claim sovereignty over data generated from within their countries. However, scholars have long proclaimed that any restrictions to the Internet and associated digital trade will have serious economic consequences. Given this context, we analyze the impact of data policies that impose restrictions on digital trade, specifically on cross border data flows. We construct Market Data Restrictions Index (MDRI), that measures the data restrictions faced by an exporting country from their trade partners. We use a variation of random effect model on a panel data set consisting of 60 countries that contribute to more than 50 percent of IT services export during the period 2006–2017. The results indicate that apart from variables such as Foreign Direct Investment, and Service Value Added, the MDRI of partner countries has a moderate negative effect on IT services export. If countries move from liberal policies to stringent data restrictions, the economies of the country that exports its ICT services to these partner countries is affected substantially. Hence government regulators shall be cautious in imposing stringent data restrictions as it affects global digital trade.     

Shifts in consumer behavior towards organic products: Theory-driven data analytics

Consumer behavior is key in shifts towards organic products. A diversity of factors influences consumer preferences, driving planned, impulsive, and unplanned purchasing decisions. We study choices among organic and conventional wine using an extensive survey among Australian consumers (N = 1003). We integrate five behavioral theories in the survey design, and use supervised and unsupervised machine learning algorithms for analysis. We quantify a gap between intention and behavior, and emphasize the importance of cognitive factors. Findings go beyond correlation to the causation of behavior when combining predictive prowess with explanatory power. Results reveal that affective factors and normative cues may prompt unplanned and spontaneous purchasing behavior, causing consumers to act against their beliefs.     

A $10 million question and other cybersecurity-related ethical dilemmas amid the COVID-19 pandemic

Cybercrime and cybersecurity are like two sides of the same coin: They are opposites but cannot exist without each other. Their mutual relation generates a myriad of ethical issues, ranging from minor to vital. The rapid development of technology will surely involve even more ethical concerns, like the infamous example of a fitness tracking company allegedly paying $10 million worth of ransom. Every cybersecurity solution, tool, or practice has to be ethical by design if it is to protect people and their rights. To identify the ethical issues that cybersecurity/cybercrime might bring about in the future, we conducted the first broad and comprehensive horizon-scanning study since the COVID-19 pandemic arose. As we began this project, nobody had the slightest idea that the coming months would bring the COVID-19 pandemic, and that the reality we had known was about to change dramatically. As it soon became apparent, the deadly coronavirus brought completely new cybersecurity/cybercrime ethical dilemmas to light, and some of the ones known before were transformed or shifted. This article presents the results of our horizon-scanning study concerning the ethical dilemmas that emerged amid the COVID-19 pandemic.     

A comparative efficiency analysis of Spanish and Turkish airports

AENA in Spain and DHMI in Turkey operate a large majority of the airports in their respective countries. These two airport operators share some similar characteristics, but also present many differences with respect to their management strategies. For instance, the Turkish DHMI introduced a Build-Operate-Transfer (BOT) model and concession agreements, which enables active private participation in airport management. In contrast, management and operation responsibilities at all airports in Spain –with a few exceptions-have remained with AENA. This paper utilizes a data envelopment analysis (DEA) to compare the relative efficiency of airports within AENA and DHMI for the years between 2009 and 2011. Based on the efficiency scores, it further identifies the sources of inefficiencies resulting from various management strategies and other external factors. The results indicate higher average efficiency levels at Spanish airports, but private involvement enhances efficiency at Turkish airports. The majority of the airports in Spain and Turkey operate under increasing returns to scale. Certain policy options, including a higher private involvement and improvement of the airport network by closing some inefficient airports, should be considered in order to increase the airport efficiency in both countries.     

Productivity efficiency analysis of the airlines in China after deregulation

Using data envelopment analysis and the Malmquist productivity index, this paper studies productivity efficiency of various airlines in China after the Chinese government deregulated the aviation industry in 2005. The results show that the productivity efficiency of non-state-owned airlines improves rapidly and eventually exceeds state-owned airlines after the deregulation policy. Among the state-owned airlines, the productivity of the local airlines and their technical changes are better than those of the central airlines.     

Comparing efficiency of holding business model and individual management model of airports

This research compares the efficiency of holding business model to individual management model of airports, employing some robust non-parametric partial frontier-based methods to compare the statistical distributions of efficiency, under different scenarios, to find out which group of airports yields better global performance. The comparison between groups will follow a Malmquist index decomposition, which seems to be the most appropriate tool for within- and inter-group performance comparison. For this purpose, a sample of 145 airports from three continents is utilized. The results provide evidence that European airports are the most productive ones, and within this cluster, the individual management model presented a significant frontier shift with respect the holding cluster frontier, meaning that the former is much more productive than the latter.     

On the discrepancy in the social efficiency measures between parametric and non-parametric production technology identification

In conventional social productive efficiency measurements that consider the production of undesirable outputs such as CO2, a DEA-based non-parametric method of production possibility frontier (PPF) identification coupled with the directional distance-function approach a-la Luenberger (1992) is typically employed. This paper shows that the discrepancy between parametric and non-parametric methods of PPF identification in social inefficiency measures can be non-negligibly large when the number of observations is small or the data are not well-scattered. By using the same data as Ha et al. (2011), who used non-parametric PPF identification to measure the social efficiency of Japan's inter-city transport services with lifecycle CO2 as the undesirable output, this paper demonstrates that adopting parametric PPF identification instead can result in considerably higher inefficiency measures for decision making units (DMUs) with relatively large undesirable outputs.     

Technical efficiency of mainstream airlines and low-cost carriers: New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.     

An estimation of returns to scale of airport airsides under multiple optimal solutions in DEA

The returns to scale (RTS) nature of 37 Chinese airport airsides are investigated in this paper. Multiple optimal solutions in DEA (Data Envelopment Analysis) models may lead to error RTS estimation. To address this problem, we use the (Zhu and Shen, 1995) RTS method. The empirical study shows that all those airsides with two runways operate under decreasing RTS and those airsides with only one runway either operate in the area of increasing RTS or in the area of constant RTS.