Return of the inoperability

There has been unrest in the research community investigating the inoperability of an economic system under disaster situations. The inoperability input–output model (IIM), which is very popular in the risk management field, has become a center of argument, particularly from the input–output researchers, that IIM is a straightforward application of the standard Leontief input–output model. This paper revisits the concept of inoperability, rather than IIM, and proposes its new role in disaster impact analysis using a conventional tool, i.e. the RAS method, for illustrating how the inoperability of an economic system in the aftermath of disaster can be evaluated. The proposed framework is employed to examine the inoperability of industries resulting from the 1995 Kobe earthquake. The findings of the analysis reveal the usefulness of inoperability concept that can even incorporate resilience (gained operability) using the proposed framework of this paper.     

Measuring industrial upgrading: applying factor analysis in a global value chain framework

ABSTRACT

A key question for promoting international competition is how to improve the position of countries and industries in global value chains (GVCs). The first step is to properly measure industrial upgrading in GVCs. This is not a trivial issue because upgrading has not been defined unambiguously. Several authors have used different (and sometimes related) measures, all of which indicate certain aspects of upgrading. Rather than trying to find the single, ultimate measure of upgrading, we propose a different approach. We examine the multidimensionality of industrial upgrading, using eight indicators in factor analysis. Four of the eight indicators adopt the GVC perspective and include, for example, the growth of the share in value-added exports. We provide three quantitative dimensions of industrial upgrading: process upgrading, product upgrading, and skill upgrading. With these dimensions, we compare and analyze the upgrading of different countries and industries using the World Input–Output Database.     

Synchronizing relational benefits with customer commitment profiles

ABSTRACT

The literature no longer considers commitment to be a distinct variable. Instead, commitment represents a combination of affective, calculative, and normative dimensions for individual customers, resulting in the adoption of a person-centric view for its measurement. However, customer satisfaction as a result of confidence benefit, social benefit, and special treatment benefit may vary among customers with different commitment profiles which encourages variable-centric view. Considering both variable- and person-centric views, this study uses survey data to examine the impact of relational benefits on the satisfaction of customers with different commitment profiles. It also examines the moderation role of relationship age. With cluster analysis identifying three commitment profiles, findings from structural equation modeling confirmed that highly-committed customers expected excessive special treatment benefit; low-commitment customers preferred confidence benefit to reduce cognitive dissonance; while affective-dominance customers expected all three types of benefit proportionately. The study’s theoretical and practical contributions conclude the paper.     

Predictive spatial network analysis for high-resolution transport modeling,applied to cyclist flows,mode choice,and targeting investment

Betweenness is a measure long used in spatial network analysis (SpNA) to predict flows of pedestrians and vehicles, and more recently in public health research. We improve on this approach with a methodology for combining multiple betweenness computations using cross-validated ridge regression to create wide-scale, high-resolution transport models. This enables computationally efficient calibration of distance decay, agglomeration effects, and multiple trip purposes. Together with minimization of the Geoffrey E. Havers (GEH) statistic commonly used to evaluate transport models, this bridges a gap between SpNA and mainstream transport modeling practice. The methodology is demonstrated using models of bicycle transport, where the higher resolution of the SpNA models compared to mainstream (four-step) models is of particular use. Additional models are developed incorporating heterogeneous user preferences (cyclist aversion to motor traffic). Based on network shape and flow data alone the best model gives reasonable correlation against cyclist flows on individual links, weighted to optimize GEH (r² = 0.78, GEH = 1.9). As SpNA models use a single step rather than four, and can be based on flow data alone rather than demographics and surveys, the cost of calibration is lower, ensuring suitability for small-scale infrastructure projects as well as large-scale studies.     

技术周期内的设备投资与经济高质量发展

包含关键技术的设备投资是打破技术壁垒,加快技术发展周期,实现制造业"弯道超车"的关键。本文从理论上剖析了技术生命周期内的设备投资对企业全要素生产率的影响程度和路径,并选取2009-2018年沪深两市A股上市公司数据实证检验该影响的异质性。结果表明:设备投资通常能够提升企业全要素生产率,且对低技术成熟度企业的促进作用大于高技术成熟度企业;设备投资对工艺创新有显著的促进作用,但对产品创新无显著正向影响,甚至存在抑制作用;低技术成熟度企业通过设备投资促进产品创新提升企业全要素生产率,而高技术成熟度企业倾向于投资工艺设备提升企业全要素生产率。因此,企业应重视技术发展阶段对企业投资决策的影响,根据自身技术发展情况,制定合理的投资策略和创新路径,并适度进行资本积累。     

民间借贷的组织化效率：山东省首家市级民间融资登记服务中心案例

本文通过对山东省首家市级民间融资登记服务中心的分析后认为,由政府主导的俱乐部性质的组织化管理安排,能够制定有效的外部规则,实现政府与市场的合理互动。其成功的运作,能够提高自发、无序发展的小额民间资本融资对接效率,促进民间融资市场规范化、阳光化发展。在当前民间融资风险频发背景下,具有较强的现实指导意义。     

跨国公司地区总部区位分布的特征与决定因素

文章以福布斯2008年排行榜全球2000家企业在中国设立的地区总部为研究对象,对其分布的特征及决定因素进行了研究。研究发现：在分布特征上,跨国公司地区总部在我国呈现出了地区集聚（96％集中于北京、上海两个城市）和国别集聚（73．9％集中于美日等6个国家）的特点;在决定因素上,最为显著的指标是城市大小与人口规模、第三产业占GDP比重和信息传递水平。研究还表明：跨国公司在我国选择非政治、商业、金融中心的城市时,表现得极为谨慎;同时,全球仅有34．3％的跨国公司在我国设立地区总部,说明世界各国在我国的投资强度目前仍较弱。     

OpenGL矿山虚拟设计及其应用

设计了系统的基本思路,在Visual Studio 2008数据库的基础上,利用OpenGL对矿山巷道,硐室设计等进行三维可视化虚拟,并通过数学模型,对矿井设计进行分析与纠错处理,用C#实现系统的功能。     

沈阳城市旅游的SWOT分析及发展对策

沈阳有丰富的城市旅游资源,但目前沈阳城市旅游优势与劣势并存,面临着重要机遇和严峻的挑战,搞好沈阳城市旅游开发建设将进一步促进沈阳经济的发展并加快城市建设的步伐。