How do policy levers shape the quality of a national health system?

Poor quality of care may have a detrimental effect on access and take-up and can become a serious barrier to the universality of health services. This consideration is of particular interest in view of the fact that health systems in many countries must address a growing public-sector deficit and respond to increasing pressures due to COVID-19 and aging population, among other factors. In line with a rapidly emerging literature, we focus on patient satisfaction as a proxy for quality of health care. Drawing on rich longitudinal and cross-sectional data for Spain and multilevel estimation techniques, we show that in addition to individual level differences, policy levers (such as public health spending and the patient-doctor ratio, in particular) exert a considerable influence on the quality of a health care system. Our results suggest that policymakers seeking to enhance the quality of care should be cautious when compromising the level of health resources, and in particular, health personnel, as a response to economic downturns in a sector that traditionally had insufficient human resources in many countries, which have become even more evident in the light of the current health crisis. Additionally, we provide evidence that the increasing reliance on the private health sector may be indicative of inefficiencies in the public system and/or the existence of features of private insurance which are deemed important by patients.     

科技保险的困境—一个制度供求非均衡分析

现阶段，我国步入了创新驱动引领升级的关键时期，科技创新受到了整个社会的空前重视。科技保险作为分散和转移科技风险的重要手段，可以为科技创新提供有力的风险保障。目前，我国科技保险工作已经进入全面推广阶段，虽然取得了一定的成效，但整体运行并不理想，科技企业参保率低，科技保险缺失严重。究其原因，主要在于制度供给不能适应科技企业对科技保险的需求，科技保险制度供求非均衡，在现行的科技保险制度下积聚着大量的潜在利润，而这些潜在利润既是科技保险制度非均衡的原因，又是科技保险制度创新的动力。     

客户集中度、市场环境与存货管理效率

客户处在供应链的下游,对企业存货的采购、生产和销售都会产生重要影响,而多变的市场环境也在无形当中影响着客户与企业之间的关系。从企业所处行业、地区产品市场和客户三个角度所带来的市场环境变化入手,采用2011—2017年我国沪深两市A股制造业上市公司的数据,实证分析客户集中度与企业存货管理效率之间的关系。研究发现:(1)客户集中度越高,企业存货管理效率越高；(2)产品市场竞争力度越强,客户集中度对企业存货管理效率的影响越大；(3)产品市场发育越好,客户集中度对企业存货管理效率的影响越大。进一步研究发现,当企业因客户生产经营原因导致需求发生较大变化时,客户集中度对企业存货管理效率的正向影响更加显著。研究结论表明,政府应当注重市场竞争力的提升和良好经营环境的建设,使得企业在维护客户关系的同时充分发挥客户集中度对企业存货管理效率的积极作用。     

融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法研究

挖掘特定产品的需求模式无法从整体掌握该类产品的市场特征；短生命周期体验品因缺乏历史销售数据，并且销售总量波动性极大，尤其需要从整体掌握销售总量与产品属性间关系的需求特征规律，但又难以挖掘，亟待提出适用于该类产品的需求特征模式挖掘方法。基于按销售总量分区后各区的需求特征的规律性，提出了一种按销售总量分区、以已有产品介绍集和销售总量为源信息、适用于新产品开发前使用、融合内容分析和关联分析的短生命周期体验品需求特征模式挖掘方法。该方法包括基于内容分析法的产品属性挖掘方法和基于关联分析的产品属性关系模式挖掘方法。前者可以得到较全面的产品属性；后者能够构建不同销售总量区间内产品集的属性关系模式，得到各区间的产品属性关系网，获得高销售总量区间具备，但中、低区间不具备的属性关系模式，从而获得需求特征模式。通过不断更新产品介绍集和销售总量并迭代挖掘，该方法能够动态挖掘需求特征模式。最后利用2013至2016年国产犯罪和爱情类电影数据验证了该方法的可行性，并得到了这两类电影的产品属性及近年的需求特征模式，可用于指导这两类电影的创作。     

京津冀文化消费的影响因素与结构特征

在京津冀协同发展战略中,文化创意产业在取得初步发展成果的同时,还依旧面临着不少亟待解决的问题。采用问卷调查法实地走访采集区域居民文化消费数据,并进一步通过决策树算法进行数据挖掘,发现京津冀文化消费的影响因素及结构特征,据此提出打造区域共同文化品牌、保障居民收入持续平稳增长、针对青少年文化消费市场创新营销模式、培养其正确的文化价值观及文化创新能力等改进措施,从而优化推动京津冀文化消费市场协同发展的路径,打造互联互通、开放统一的区域文化消费市场,使区域居民文化消费需求成为促进文化产品供给的市场新动力。     

全球价值链背景下加工贸易企业升级路径分析

金融危机以来国际贸易保护主义色彩浓郁，中国内部粗放型经济增长方式存在一定的不可持续性和人口红利开始逐渐消失，中国加工贸易嵌入发达国家主导的全球价值链低附加值和低生产率问题引起了学者的注意。随着外部贸易环境、国内新常态要素禀赋结构的变化和深化供给侧结构性改革的需要，推动加工贸易企业升级已经成为中国经济结构调整的一个重要部分。通过分析中国加工贸易的起源、发展和现状，描述全球价值链背景下加工贸易的若干特征和“低端锁定”问题，引出了融资约束对企业经营决策、出口行为以及企业全球价值链上地位的影响，并围绕以生产过程、产品升级和功能升级为主的产业内升级和以劳动密集型向技术密集型转变为特征的产业间升级两个角度，提出了中国加工贸易企业在全球价值链上攀升的路径。研究认为，着重强调人力资本积累、本土企业技术外溢的吸收能力以及自主研发能力的培养，同时结合国际产能合作和“一带一路”倡议等现实背景，实现东西双向开放，塑造以我为主的包容性的区域价值链和国内价值链等，是中国加工贸易企业升级的路径和新机遇。     

Expanding our sociolinguistic horizons? Geographical thinking and the articulatory potential of commodity chain analysis

Conceptual linearity and analytic parochialism (aka focus) can make it more difficult for sociolinguists or discourse analysts to apprehend the far‐reaching, exploitative ways inequality is nowadays produced. A suitably material‐cum‐materialist class critique certainly entails empirical and phenomenological worlds flagged by, for example, multi‐sited ethnographies but otherwise side‐lined as merely “extra‐situational” in much talk/text‐directed scholarship. I propose we think more geographically by properly engaging spatiality à la Harvey (1990) and especially the radical politics of simultaneity (Massey, 2005)—the literal, “right‐now” connectedness of places and people. To this end, and allied with deepening interest in political economy, I combine the principles of articulation theory with the procedures of commodity chain analysis for picking apart an epitomic, contemporary manifestation of extreme privilege: the business‐class meal. The proposed discourse‐centred commodity chain analysis offers an ecumenical but systematic framework for tracking how commodity fetishism is actually and discursively accomplished (or not) across dispersed voices, stories, and social meanings.     

航线网络中需求无约束估计的非参数选择模型

传统的航空客运需求无约束估计方法仅针对平行直达航班中的顾客需求“溢出”和“再 现”问题，未能考虑航空网络中直达和中转联程航班之间的网络替代效应． 基于顾客偏好排序列表定义了航空网络顾客类型集合，建立了考虑顾客策略行为的网络型非参数离散选择模型．考虑到网络环境下历史预售数据的不完备性，站在线上和线下交易平台的角度，分别建立了非截尾和截尾需求情况下的完备数据对数似然函数． 采用 EM 算法对顾客到达率和概率质量函数进行联合估计，并提出了网络环境下的顾客“初始需求”、“再现需求”和“溢出需求”无约束估计计算方法．通过数值模拟验证了所提方法的可行性和有效性，相较于现有方法能准确反映产品间网络替代效应对顾客选择行为影响，从而更加有效地避免对历史顾客“初始需求”的高估问题．     

Averting the rise of the dark side of social media: The role of sensitization and regulation

Social media have fundamentally influenced the way we live. Thus far, research has mainly focused on the ‘bright side’ of social media and the many advantages these platforms bring. More and more, however, research is also beginning to address the ‘dark side’ of social media. Dark side phenomena include cyberbullying, manipulation of elections, fear of missing out, social media addiction and the distribution of fake news. In this editorial for the management focus section of the European Management Journal, we propose two strategies (sensitizing and regulating) to manage this dark side of social media. Additionally, this editorial introduces the four articles included in this management focus section. We hope that the featured articles will help to encourage further research in this area.     

A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand

The U.S. electric power system is increasingly vulnerable to the adverse impacts of extreme climate events. Supply inadequacy risk can result from climate‐induced shifts in electricity demand and/or damaged physical assets due to hydro‐meteorological hazards and climate change. In this article, we focus on the risks associated with the unanticipated climate‐induced demand shifts and propose a data‐driven approach to identify risk factors that render the electricity sector vulnerable in the face of future climate variability and change. More specifically, we have leveraged advanced supervised learning theory to identify the key predictors of climate‐sensitive demand in the residential, commercial, and industrial sectors. Our analysis indicates that variations in mean dew point temperature is the common major risk factor across all the three sectors. We have also conducted a statistical sensitivity analysis to assess the variability in the projected demand as a function of the key climate risk factor. We then propose the use of scenario‐based heat maps as a tool to communicate the inadequacy risks to stakeholders and decisionmakers. While we use the state of Ohio as a case study, our proposed approach is equally applicable to all other states.