“Data localization”: The internet in the balance

There is a steady global trend towards “Data Localization,” laws by which data is required to be maintained and processed within the geographic boundaries of its state of origin. This development has raised concerns about its possible adverse impacts on emerging data-intensive technologies such as Cloud services/E-commerce, Big Data, Artificial Intelligence and the Internet of Things (collectively, the Embedded Infosphere). The inability to reach an international agreement on rules for cross-border data flows may have significant adverse consequences for all future users of the Internet.The basis of Data Localization is grounded in two distinct but inter-related policy models: Data Sovereignty and Trans-Border Data Flows. These two concepts have different origins. “Data Sovereignty” is derived from the historic power of a state of absolute and exclusive control within its geographic borders. Policies behind TBDFs arose in Europe following World War II, primarily motivated by Nazi use of early proto-computers to help round up Jews and others. As they have evolved, TBDF policies have been directed primarily at protecting personal data and privacy.This article first examines the issues of: 1) “Information Sovereignty” and 2) TBDFs. It then describes the arguments for and against “Data Localization,” offers some examples of strong localization policies (Russia, China), and summarizes contesting policy proposals. It then contextualizes TBDF with issues of human rights (free flow of information) and privacy.While the utility of an international agreement on TBDFs is clear, the differences in approaches are tenacious. For the free-market developed world (e.g, EU, OECD), the path forward seems to lead through policy convergence to compatible rules, with differentiated levels of data protection and accountability. It is far from clear whether these rules will address, in a mandatory way, issues of the “free flow” of information in the human rights sense. At the same time, there are countries (e.g., BRICS), representing a majority of the world's population, in which political and cultural resistance will produce stringent Cyber Sovereignty and Data Localization policies with few if any human rights components.The article concludes that the more the Internet is “localized”, the more attenuated its benefits will become. The negative consequences of Data Localization will become increasingly obvious as new, data-intensive technologies become ubiquitous, creating a condition of “Data Dependence”. It is projected that in the future the nations with the least amount of Data Localization and the most open flow of information will be the most successful in benefiting from new data-intensive embedded, networked technologies. This will most likely be characterized by values adopted as policies and practices in the EU.     

Stochastic leader–follower DEA models for two-stage systems

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). In recent years, it has been widely used to evaluate two-stage systems under different organization mechanisms. This study modifies the conventional leader–follower DEA models for two-stage systems by considering the uncertainty of data. The dual deterministic linear models are first constructed from the stochastic CCR models under the assumption that all components of inputs, outputs, and intermediate products are related only with some basic stochastic factors, which follow continuous and symmetric distributions with nonnegative compact supports. The stochastic leader–follower DEA models are then developed for measuring the efficiencies of the two stages. The stochastic efficiency of the whole system can be uniquely decomposed into the product of the efficiencies of the two stages. Relationships between stochastic efficiencies from stochastic CCR and stochastic leader–follower DEA models are also discussed. An example of the commercial banks in China is considered using the proposed models under different risk levels.     

Mobile payment and online to offline retail business models

Mobile payments are services that use mobile devices to make payments. When digitalization moves across channel boundaries, online to offline channel retail will expand. Online to offline retailing will become the future retail owner stream and retail operators will move from cross-channel or multi-channel to omni-channel. This study investigates a market survey in Taiwan developing a data mining analytics including clustering analysis and association rules based on a snowflake schema database design. The role of mobile payment is determined in terms of new retail payment mechanism that promotes a better consumer purchase experience in an online to offline business environment.     

Coloring the destination: The role of color psychology on Instagram

Color psychology plays important roles in product packaging, the retail environment, and online marketing. This study analyzed current practices related to color composition in tourism-related photographs on Instagram. Data mining and pictorial content analysis were adopted to investigate how lightness, chroma, and hue may influence Instagram posts' popularity. Generally, individuals appeared more likely to respond to brighter and more saturated destination pictures. Orange, yellow, blue, and violet contributed significantly to post popularity based on different photographic typologies. Overall, color is a complex construct that functions within diverse dimensions and can enrich tourists’ destination-related perceptions. Based on brand post popularity and color theories, the study findings provide valuable implications for effective and efficient destination promotion via Instagram. Relevant limitations and future directions are also discussed.     

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.     

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.     

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.     

Efficiency in the provision of social care for older people. A three-stage Data Envelopment Analysis using self-reported quality of life

Using a three-stage data envelopment analysis approach, this paper explores efficiency in the provision of social care for older people in 148 English Councils in 2009/10. Departing from D'Amico and Fernández (2012) [31] our measure of efficiency is inscribed within the production of welfare framework and based on self-reported quality of life of recipients of the services. Our results indicate a high level of efficiency, but once we control for the effects of a number of environmental variables, we found that more stringent eligibility criteria and higher assessment costs are negatively associated with the efficiency in the provision of social services.     

我国居民杠杆率现状及影响因素研究

近年来,我国居民部门杠杆率的快速上升引起社会各界关注。本文使用货币信贷和城镇储户调查数据,对我国居民部门杠杆率和偿债能力现状进行了分析,并运用各省住户贷款数据计算各省的居民杠杆率,使用面板数据模型对居民杠杆率上升的原因进行了实证分析。结果表明,房价的快速上涨和住房销售的增长都对居民部门杠杆率的上升有显著正向影响,其中房价上涨的影响程度更大。此外,金融发展水平和老年人抚养比对居民杠杆率有正向影响,少年人抚养比对居民杠杆率有负向影响。     

数据的要素化过程及其与传统产业数字化的融合机制研究

从生产过程和价值创造来看,数据具备了传统生产要素所具备的功能,但又具有区别于传统生产要素的新特征。数据作为一种新型生产要素,对于数字产业化的高速发展和传统产业数字化进程的深入推进,具有关键作用。数据要素的形成和发展一方面需要与数字产业化、产业数字化融合发展进程相适应;另一方面,数据要素的形成过程本身又是与传统产业数字化进程的一个深度技术融合过程。因而,多样化和异质性的数据要素,其实质乃是数字技术与传统产业专用性技术融合的结果,其间的融合机制表现为深化、促进和多元性。