Deterministic construction of compressed sensing matrices based on semilattices

A central problem in compressed sensing is the construction of sensing matrices. In this paper, we show how to construct sensing matrices by using semilattices, and give many examples of sensing matrices constructed from specific semilattices. Moreover, we show that the new construction for some examples with small parameters gives better sensing matrices compared with previously known constructions.     

Developing virtual team performance: an integrated perspective of social exchange and social cognitive theories

Review of Managerial Science - The emerging trend toward physically distributed work teams has necessitated a critical inquiry into the nature and roles of psychological contract and leadership in...     

Online MapReduce processing on two identical parallel machines

In this work we investigate the online over-list MapReduce processing problem on two identical parallel machines, aiming at minimizing the makespan. Jobs are revealed one by one, and each job consists of one map task and one reduce task. The map task can be arbitrarily split and processed on both machines simultaneously, while the reduce task has to be processed on a single machine and it cannot be started unless the map task has been completed. We first show that the general case of the problem reduces to the classical two machine online scheduling model with an optimal competitive ratio of 3/2. For a special case where the map task is at least as long as the reduce task, we prove that no online algorithm can be less than 4/3-competitive. An optimal Greedy algorithm with a matching competitive ratio is proposed as well.     

运营滞后与信用担保互换下的项目投资决策模型

在项目投资面临运营滞后以及债务融资约束的情形下，基于实物期权框架构建了企业家签订信用担保互换契约的两阶段投资决策模型。运用动态规划以及均衡定价方法，给出了企业家股权及期权价值的显示表达，得到了两个阶段担保成本满足的代数方程，并进一步分析了运营滞后和信用担保下企业家的最优投资决策问题。数值结果表明：外部运营时滞会提高杠杆率，导致企业家提前投资，同时会提高企业家第一阶段债务融资的担保成本，但会降低第二阶段债务融资的担保成本；随第一阶段投资额度逐渐增大，企业家的最优投资水平呈U型变化，第一阶段债务融资时的担保成本单调递减，而第二段债务融资时的担保成本呈现倒U型；企业家两个阶段的融资缺口对项目最优投资水平、最优破产水平以及担保成本有显著影响。     

Genetic distance,international experience and the performance of cross-border R&D for EMNEs

Cross-border R&D can contribute to the enhancement of independent innovation capabilities of emerging markets multinational enterprises (EMNEs) by benefiting from knowledge management. However, scant research exists examining the location impact of cross-border R&D for EMNEs on performance implications. This paper fills this important theoretical gap by building upon the literature of genetic distance in connection with knowledge management. We use a panel data of Chinese high-tech listed companies to empirically examine the impact of genetic distance on the performance of cross-border R&D and the role played by international experience. Our results reveal a positive relationship between genetic distance and the performance of cross-border R&D. Importantly, we highlight the motivation for cross-border R&D of EMNEs to acquire technical knowledge magnifies the positive effects of genetic distance and performance. Furthermore, our analysis indicates that international experience significantly enhanced the positive effect of genetic distance on cross-border R&D performance. We conclude this paper by discussing theoretical contributions to genetic distance, international management and knowledge management, as well as practical implications for cross-border R&D of EMNEs.     

Cultural values and innovation: The mediating role of entrepreneurial learning capacity

Although both cultural values and innovation are widely acknowledged as collective embodiments of individual values and assets, little is known about the mechanisms through which cultural values influence the likelihood of innovation by some entrepreneurs rather than others. We argue that institutional pressures arising from cultural values affect entrepreneurial learning capacity which in turn impacts innovation activities. Our multi-level analysis of entrepreneurs from 19 countries between 2006 and 2011 suggests that entrepreneurial learning capacity serves as a mediator through which entrepreneurs maximize the innovation-related benefits of cultural values to their businesses.     

Human Factors Analysis for Maritime Accidents Based on a Dynamic Fuzzy Bayesian Network

Human factors are widely regarded to be highly contributing factors to maritime accident prevention system failures. The conventional methods for human factor assessment, especially quantitative techniques, such as fault trees and bow-ties, are static and cannot deal with models with uncertainty, which limits their application to human factors risk analysis. To alleviate these drawbacks, in the present study, a new human factor analysis framework called multidimensional analysis model of accident causes (MAMAC) is introduced. MAMAC combines the human factors analysis and classification system and business process management. In addition, intuitionistic fuzzy set theory and Bayesian Network are integrated into MAMAC to form a comprehensive dynamic human factors analysis model characterized by flexibility and uncertainty handling. The proposed model is tested on maritime accident scenarios from a sand carrier accident database in China to investigate the human factors involved, and the top 10 most highly contributing primary events associated with the human factors leading to sand carrier accidents are identified. According to the results of this study, direct human factors, classified as unsafe acts, are not a focus for maritime investigators and scholars. Meanwhile, unsafe preconditions and unsafe supervision are listed as the top two considerations for human factors analysis, especially for supervision failures of shipping companies and ship owners. Moreover, potential safety countermeasures for the most highly contributing human factors are proposed in this article. Finally, an application of the proposed model verifies its advantages in calculating the failure probability of accidents induced by human factors.     

From design to operations: a process management life-cycle performance measurement system for Public-Private Partnerships

Public–Private Partnerships (PPPs) have become a critical vehicle for delivering infrastructure worldwide. Yet, the use of such a procurement strategy has received considerable criticism, as they have been prone to experiencing time/cost overruns and during their operation poorly managed. A key issue contributing to the poor performance of PPPs is the paucity of an effective and comprehensive performance measurement system. There has been a tendency for the performance of PPPs to be measured based on their ex-post criteria of time, cost and quality. Such criteria do not accommodate the complexities and lifecycle of an asset. In addressing this problem, the methodology of sequential triangulation is used to develop and examine the effectiveness of a ‘Process Management Life Cycle Performance Measurement System’. The research provides public authorities and private-sector entities embarking on PPPs with a robust mechanism to effectively measure, control and manage their projects’ life cycle performances, ensuring the assets are ‘future proofed’.     

社交网络个体活跃行为的大数据分析：从网络外部性的视角

用户是社交网络平台的基石，用户的活跃行为为平台创造内容、带来价值，因而用户活跃度一直是社交网络平台的关注重点。已有研究仅关注用户是否存在持续使用意向或行为，将持续使用行为定义为二元变量，未对持续使用行为细分，忽略了对用户活跃行为的研究。此外，社交网络中用户活跃行为之间有着不可忽视的相互影响，而受制于用户的关系网络数据难以获取，少有研究从该角度对社交网络中的用户行为进行研究。 将持续使用行为进一步细分为个体活跃和沉默行为，从网络外部性视角探讨同伴活跃行为对焦点个体活跃行为的影响以及个体网络规模与活跃行为的关系，并进一步探讨个体间关系强度和个体特征的调节作用。以超过百万用户的真实关系网络、个体特征信息和使用行为数据进行实证分析，通过Tobit模型验证上述关系。 研究结果表明，同伴活跃度和个体网络规模对个体活跃度有显著的正向作用，同时关系强度具有正向调节作用；个体特征在同伴活跃度与个体活跃度之间起调节作用，具体来说，女性用户和年轻用户受同伴活跃行为的影响更强。 从网络外部性的角度探讨用户活跃行为的影响因素，拓展了关于在线社交网络用户持续使用行为的研究和网络外部性测量方式，关注不同节点对于网络外部性贡献的差异性，对今后网络外部性的研究有一定的借鉴意义。基于中国数百万真实用户的数据集，结果更具普适性，同时反映出中国在线社交网络中用户的行为特征，可为今后的研究者提供参考。研究结果可以帮助社交网络平台的管理者更加了解用户活跃度的影响机理以及用户行为之间的内在联系，从而能以更科学合理的方式激发用户活跃度，保持社交网络平台的持续运营。     

Optimal RSUs deployment with delay bound along highways in VANET

In order to broadcast an alert message from the accident site to the control center as soon as possible, the roadside units (RSUs) act as the critical component in vehicular ad hoc networks (VANETs). It is not possible to make a pervasive RSU deployment due to the huge cost and market requirement. Hence, how to deploy a minimum number of RSUs in a given region becomes a challenge problem. In this paper, we present an analysis for the total delay of broadcasting alert messages in VANETs along highways. Based on the analysis, the relationship between optimal number of RSUs with the highway distance is given. Moreover, the experiment results verifies the delay analysis and the optimization of RSUs deployment.