农地发展权流出、资本回流与区域经济增长*——基于重庆市的实证研究

[目的]以重庆市为研究区域,以农地发展权资本化的地票指标为研究对象,从理论和实证层面探讨农地发展权交易与资本要素的城乡互动关系及其对区域经济增长的影响,为进一步优化农地发展权交易政策、促进区域均衡发展提供相关建议。[方法]基于2008—2017年城乡统筹改革试验区重庆市地票指标交易的面板数据,运用要素禀赋理论和差分GMM模型从理论和实证层面分析农地发展权流出区土地与资本要素的互动关系及其对区域经济增长的影响。[结果]基于区域间资源禀赋的差异及要素相对价格的分化,在市场机制作用下,农地发展权指标将以配置效率优化为导向在不同区域间自由流动。[结论]短期内,由于资本约束,流出农地发展权的区域其经济增长会受到抑制;而当农地发展权指标资本化后,流出区获得了较为稀缺的货币资本,农地发展权流出将显著促进地方经济增长;同时,在研究时期内,由于农地发展权市场交易机制的构建,重庆市地方经济增长存在显著的收敛效应,区域间经济发展差距将会逐步缩小。     

Diagnosing a healthcare cybersecurity crisis: The impact of IoMT advancements and 5G

Internet of Medical Things (IoMT) technology remains in early stages of adoption, but advancements and breakthroughs are quickly moving this process forward. There is a critical need for cybersecurity to be a priority in the development of these new tools, alongside design and utility. Given the rapid pace and potential magnitude of the coming advancements in IoMT, if privacy and security risks are neglected, a significant crisis could emerge in the form of more frequent cybersecurity breaches. This article examines the market opportunities and risks associated with IoMT and outlines a plan for proactively mitigating concerns and providing a platform to foster growth, to modify attitudes and behaviors, and to continue to build consumer confidence in the overall health system without sacrificing security.     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

A Novel Compact Cat Swarm Optimization Based on Differential Method

ABSTRACT

A compact cat swarm optimization scheme (cCSO) is proposed in this paper, which is designed to solve application domains plagued with limited memory and less-computation power, as a member of cat swarm optimization algorithms (CSO), it composes of two sub-modes, i.e., tracing and seeking modes, so it keeps the same search logic of CSO. On the other hand, cCSO inherits the main feature of compact algorithms, a normal probabilistic model is used to represent the population of solutions instead of processing an actual population, which ensures the cCSO to have the modest memory requirement. The updating vector for the probabilistic model provides a clear moving direction for cats in next step. A cat without historical position and velocity is applied in the algorithm. When the cat is in seeking mode, it employs a differential operator to update the cat’s position, which makes it possible for the cat to have multiple searching directions. Experimental results show that cCSO has pretty performance compared with respect to some population-based testing benchmarks. And it also shows superior performance in convergence rate to some compact optimization algorithms. The case study of gray image segmentation proves that it suits for solving the optimization problem by limited hardware.     

Beyond concern: socio-demographic and attitudinal influences on privacy and disclosure choices

ABSTRACT

The co-option of consumers as unwilling agents in their own surveillance has enabled significant abuses of consumer privacy. Previous studies have largely used privacy concern as a proxy for overall privacy attitudes. In this study, we implement a choice experiment in combination with measures adapted from Communication Privacy Management theory to enable a broader exploration of the influences of privacy attitudes by contextualising privacy as a negotiation about accessibility over contextual boundaries. Key findings suggest individuals’ social media disclosure decisions are influenced at least in part by their privacy attitudes, particularly with respect to information categories which may cue other personal information. Findings are also presented on consumers’ willingness to pay for privacy, with implications for alternative revenue streams not built on consumer surveillance.     

基于不同城市化发展阶段的山西省城镇建设用地适度集约利用研究

研究目的:针对城市化进程中的土地低效利用以及过度集约问题,探讨不同城市化发展阶段的土地集约利用状况及适度集约利用状态。研究方法:采用匹配度模型、曲线估计模型和多目标规划模型,对山西省的土地集约利用进行分区优化。研究结果:(1)1999—2012年山西省土地集约利用与城市化水平之间的匹配趋势逐渐由失调、磨合向协调转变,但不同地区之间的匹配水平差距却在逐渐扩大;(2)2018年山西省城市化水平处于低于30%、30%～70%和高于70%时,以单位城镇建设用地固定资产投资额为表征的土地适度集约利用值分别为249.93万元/km~2、367.57万元/km~2和692.72万元/km~2,两项指标叠加全省可划分为平稳发展区、重点挖潜区和优化拓展区,并提出了不同地区差别化的建设用地管控政策。研究结论:不同城市化发展阶段的土地适度集约利用研究能为制定区域差别化政策提供参考,以促进该地区的土地集约利用水平达到适度状态。     

非线性延迟系统Runge-Kutta方法的稳定性探讨

针对时间依赖型的非线性多变延迟系统,采用变步长的Runge-Kutta方法求解,证明了匹配一定插值方法的代数稳定的Runge-Kutta方法是VR稳定的。     

A Typology of Communicative Strategies in Online Privacy Policies: Ethics, Power and Informed Consent

The opaque use of data collection methods on the WWW has given rise to privacy concerns among Internet users. Privacy policies on websites may ease these concerns, if they communicate clearly and unequivocally when, how and for what purpose data are collected, used or shared. This paper examines privacy policies from a linguistic angle to determine whether the language of these documents is adequate for communicating data-handling practices in a manner that enables informed consent on the part of the user. The findings highlight that corporate privacy policies obfuscate, enhance and mitigate unethical data handling practices and use persuasive appeals to increase companies’ trustworthiness. The communicative strategies identified provide starting points for redesigning existing privacy statements with a view to communicating data handling practices in a more transparent and responsible manner, laying the groundwork for informed consent.     

MULTIDIMENSIONAL DYNAMIC RISK MEASURE VIA CONDITIONAL g‐EXPECTATION

This paper deals with multidimensional dynamic risk measures induced by conditional g‐expectations. A notion of multidimensional g‐expectation is proposed to provide a multidimensional version of nonlinear expectations. By a technical result on explicit expressions for the comparison theorem, uniqueness theorem, and viability on a rectangle of solutions to multidimensional backward stochastic differential equations, some necessary and sufficient conditions are given for the constancy, monotonicity, positivity, and translatability properties of multidimensional conditional g‐expectations and multidimensional dynamic risk measures; we prove that a multidimensional dynamic g‐risk measure is nonincreasingly convex if and only if the generator g satisfies a quasi‐monotone increasingly convex condition. A general dual representation is given for the multidimensional dynamic convex g‐risk measure in which the penalty term is expressed more precisely. It is shown that model uncertainty leads to the convexity of risk measures. As to applications, we show how this multidimensional approach can be applied to measure the insolvency risk of a firm with interacting subsidiaries; optimal risk sharing for ‐tolerant g‐risk measures, and risk contribution for coherent g‐risk measures are investigated. Insurance g‐risk measure and other ways to induce g‐risk measures are also studied at the end of the paper.     

Assessing Gender Differences in Computer Professionals’ Self-Regulatory Efficacy Concerning Information Privacy Practices

Concerns with improper collection and usage of personal information by businesses or governments have been seen as critical to the success of the emerging electronic commerce. In this regard, computer professionals have the oversight responsibility for information privacy because they have the most extensive knowledge of their organization’s systems and programs, as well as an intimate understanding of the data. Thus, the competence of these professionals in ensuring sound practice of information privacy is of great importance to both researchers and practitioners. This research addresses the question of whether male computer professionals differ from their female counterparts in their self-regulatory efficacy to protect personal information privacy. A total of 103 male and 65 female subjects surveyed in Taiwan responded to a 10-item questionnaire that includes three measures: protection (protecting privacy information), non-distribution (not distributing privacy information to others), and non-acquisition (not acquiring privacy information). The findings show (1) significant gender differences exist in the subjects’ overall self-regulatory efficacy for information privacy, and, in particular, (2) that female subjects in this study exhibited a higher level of self-regulatory efficacy than males for the protection and non-acquisition of personal privacy information. The identification of the factorial structure of the self-regulatory efficacy concerning information privacy may contribute to future research directed to examining the links between privacy efficacy and psychological variables, such as ethical attitude, ethical intention, and self-esteem. Studies can also be extended to investigate how different cultural practices of morality and computer use in men and women may shape the different development patterns of privacy self-efficacy. Understanding the different cultural practices may then shed light on the social sources of privacy competence and the appropriate remedies that can be provided to improve the situation. Feng-Yang Kuo holds a B.S. degree in Management Science from Chiao-Tung University, Taiwan and a Ph.D.degree in Information Systems from University of Arizona. He was a faculty of Information Systems at University of Colorado at Denver from 1985 to 1997 and is currently an associate professor of Information Management in Sun Yat-Sen University, Taiwan. He has published articles in Communications of ACM, MIS Quarterly, Communications of AIS, Journal of Business Ethics, Information & Management, Journal of Systems and Software, Decision Support Systems, and Sun Yat-Sen Management Review. Among his current interests are information ethics, managerial cognition, and human-computer interfaces. Cathy S.Lin Professor Cathy S.Lin is an assistant professor of Information Management at National University of Kaohsiung, Taiwan. Her Ph.D.is in Management Information Systems from National Sun Yat-Sen University. She has published articles in the Information & Management, Journal of Information Management, and Sun Yat-Sen Management Review. Among her current interests are information ethics, ethical decision making, electronic commerce, and information management. Meng-Hsiang Hsu Professor Meng-Hsiang Hsu is a professor of information management at National Kaohsiung of First University of Science and Technology. His Ph.D. is in Management Information Systems from National Sun Yat-Sen University. He has published articles in the J. of Business Ethics, Behavior & information Technology, Decision Support System, and Industrial Management and Data Systems. Among his current interests are knowledge management, information ethics, strategic information systems, and electronic commerce.