航班计划优化研究概述

从航班计划优化的不同时间阶段分析,可以将航班计划优化分为航班计划静态编排优化、基于航班延误预测的航班计划动态反馈优化和基于机场协同决策(A-CDM)的航班计划动态调整角度三类;进而从航班时刻、机型指派、航班频率等编制环节分析了航班计划静态编排优化;随后利用延误波及预测与数据挖掘预测的优化方法分析了基于航班延误预测的航班计划动态反馈优化的相关研究。最后,根据航班计划优化复杂性分析,给出了航班计划优化的发展趋势和未来研究方向。     

基于模糊多属性群决策的维护方式选择研究

维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。     

Learning from R&D outsourcing vs. learning by R&D outsourcing

We analyze how research and development (R&D) outsourcing influences product innovation. We propose a separation between learning from R&D outsourcing, whereby the firm improves its ability to innovate by using outsourced R&D directly in new products, from learning by R&D outsourcing, whereby the firm indirectly uses outsourced R&D by integrating it with internal R&D to create new products. Building on the knowledge-based view, we argue that learning from R&D outsourcing is likely to have an inverse U-shaped relationship with product innovation, because the initial benefits of using outsourced component R&D knowledge to innovate products is eventually outweighed by the hollowing out of the firm's ability to innovate. In contrast, we propose that learning by R&D outsourcing is likely to have a U-shaped relationship with product innovation, because the initial challenges of integrating internal and external R&D are eventually overcome, resulting in more innovations. Finally, we distinguish between domestic and foreign R&D outsourcing and propose a liability of foreignness in R&D outsourcing as it has a lower impact on new products than domestic R&D outsourcing. The empirical analysis shows that outsourced R&D has an inverted U-shaped relationship with the number of new products, while the interaction between outsourced R&D and internal R&D has a U-shaped relationship with the number of new products. It also shows that domestic outsourced R&D has a higher positive impact on the number of new products than foreign outsourced R&D.     

Investment decision-making under economic policy uncertainty

It is widely established that economic policy uncertainty (EPU) affects investment decisions and performance, yet research in this area has overlooked the direct property investment market. This article seeks to rectify this and proposes a multistage multilevel analytical framework to offer new insights and a richness of findings. Using a news-based measure of EPU in the United Kingdom, and controlling for economic conditions, a national-level analysis reveals some evidence of Granger-Causality between EPU and total returns, indicating that pricing is responsive to uncertainty. These findings suggest that EPU is an important risk factor for direct property investments, with pricing implications. Differences in data and performance measure are important, however, with income returns unresponsive. A micro-level investigation begins to reveal some of the asset-pricing decisions underpinning the national results, indicating investors’ concerns for income streams are consistently high, regardless of varying EPU. Pricing can also cause changes in EPU, such as in the retail and industrial markets (increasingly linked through logistics) reflecting sector-specific stakeholder groups and newsworthy issues. This evidence highlights how important it is for policy-makers to understand the complex and bi-directional relationship, that indecision can undermine investment confidence and cause investment market volatility, in turn raising EPU.     

Obstacles and solutions on the ladder of citizen participation: a systematic review

This article presents a systematic review of the English-language empirical literature about citizen participation to identify the obstacles to its implementation and the most successful ways to address them. Three sets of variables seem to impact effectiveness: contextual factors, including information asymmetries and public officials’ attitude; organizational arrangements, including community representation criteria and process design; and process management patterns, including group dynamics and collaboration quality. Two recommendations stem from our analysis: internalize decisions in organizational procedures, and establish ongoing interactions between government bodies and their stakeholders. We conclude that half-hearted engagement is unlikely to lead to successful citizen participation.     

金融素养、家庭财富与家庭创业决策

本文利用2015年中国家庭金融调查(CHFS)数据,分析了金融素养、家庭财富与家庭创业决策三者之间的关系。整体上,金融素养的提高显著增加了家庭参与创业的可能性,但家庭参与创业面临着"财富约束效应";而金融素养对家庭财富具有替代作用,提高金融素养有效缓解了家庭的"财富约束效应",促进家庭参与创业。同时,研究发现家庭财富对家庭创业决策的影响并不存在明显的城乡差异,但金融素养更能缓解农村家庭创业所面临的"财富约束效应"。另外,提高金融素养能有效缓解家庭的信贷约束,增加其风险偏好,间接地促进创业。     

承接金融服务外包对中国就业的影响

研究以金融行业外包服务数据为样本,沿直接与间接两种影响渠道,分析承接金融服务外包对我国就业数量与就业结构的影响,对就业数量变动的流向与趋势进行测算,深入到了劳动力就业质量层面。实证结果表明,承接金融服务外包可以扩大第三产业的相对就业比重,改善知识结构,有利于就业结构与产业结构之间的平衡。但不熟练工人的金融外包业准入将受到限制,加深了他们的就业困境。如何借此机遇将大量低技术劳工培训成合格人才将成为一个严峻的挑战。研究还提出了针对这一新产业形态未来发展的总结与展望。     

Exploring heritage tourism performance improvement for making sustainable development strategies using the hybrid-modified MADM model

Industrial heritage tourism has become increasingly popular in recent years. However, strategies for improving the industrial heritage tourism development-related performances are still an underdeveloped research topic academically. Therefore, this study’s purpose is to explore the feasibility performance-improving strategies using a hybrid-modified multiple attribute decision-making (MADM) based on the DEMATEL technique in constructing the influential network relation map (INRM) and in determining the influential weights of DANP. Then, the modified VIKOR method is combined with the influential weights of DANP, performance gaps were identified, and then the most effective strategies for improving tourism development-related performance at industrial heritage sites can be generated using INRM. Finally, an empirical real case study of a rehabilitated gold-mining site of Taiwan is used to demonstrate the effectiveness of the hybrid-modified MADM model. According to the results, the decision-makers should highly prioritize improving high-priority criteria such as ‘social usefulness’, ‘resource integration’, ‘destination policy and development’, ‘economic development’, ‘cultural links’, ‘cultural learning’, and ‘natural landscape resources’ in advance to successfully achieving the aspired performance levels. Additionally, this study suggests meaningful industrial heritage tourism performance improvement strategies that have been rehabilitated throughout the world.     

A decision support model for buying battery electric vehicles considering consumer learning and psychological behavior

Developments in battery electric vehicles (BEVs) have received more and more attentions in the last decades due to alleviating carbon emissions and energy crisis. Consequently, how to rank alternative BEVs to assist consumers make better purchasing decisions is a worthy research study. However, there are still some defects in the existing studies for ranking of BEVs: 1) the evaluation index system of BEVs is not comprehensive; 2) the determination of criteria weights cannot be well applied to the actual purchase scenarios; and 3) the psychological behavior of consumers is ignored. To address those shortcomings, this paper proposes a decision support model to assist with consumers to buy BEVs. First, a systematic evaluation criteria system of BEVs including quantitative and qualitative indicators from parameter configurations and online reviews is constructed. Then, a weight algorithm considering consumer learning is proposed to determine the criteria weights. Furthermore, a decision support process considering consumers' regret avoidance behavior is proposed. Finally, an actual BEV purchase case is given to illustrate the practicability of the decision support model. This can be seen in case studies the proposed support model can be well applied to consumers with different regret avoidance behaviours.     

时空大数据支持的土地储备智能决策体系与应用研究

研究目的:设计土地储备智能决策体系,将土地储备决策环节进行科学化、定量化和模型化,为政府合理开展土地储备提供决策依据。研究方法:遵循科学性、实用性、先进性、开放性原则,以数据为驱动,人工智能为核心,通过基于Hadoop/Spark的大数据处理技术、多源异构数据融合技术、智能决策模型集对多源时空大数据挖掘分析。研究结果:提出了土地储备智能决策体系,研究了一套面向土地储备的决策方法集,实现对现状条件的精准刻画,对土地储备规模、结构、时序等内容的科学决策;在此基础上,研发了智能决策支持平台,将数据资源共享、现状条件评估、智能决策专题等功能集成,构建土地储备智能决策"一张图",并实现平台的自我学习和更新。研究结论:应用于宁波市实例验证,该体系有效地促进了土地储备科学智慧决策,对优化土地资源配置具有参考意义。