军民融合协同创新驱动产业园区高质量发展研究

军民融合产业园区高质量发展对于推进军民深度融合、在全国形成可复制可推广经验具有重要意义。军民融合协同创新通过促进新知识涌现、推进新产业集聚发展，最终汇聚经济发展新动能，驱动园区高质量发展。在提出军民融合协同创新驱动园区高质量发展的机理与组织框架基础上，将发展模式归纳为以分享经济为背景的资源共享模式、以新型研发机构为核心的第三方模式、以产业联盟为核心的产业链拓展模式和以交易平台为核心的“PPP”模式，最后提出相关对策建议。     

Interorganisational project dynamics: A longitudinal study of perceptual distance and client-contractor collaborative relationships

Despite the importance of good collaborative relationships in interorganisational projects, clients and contractors often develop adversarial relationships due to perceptual distance about key project issues. In this case study research, we investigated how perceptual distance emerges and changes over time, and how the collaborative relationship between client and contractor develops alongside these dynamics. In this exploration, we built upon agency theory and stewardship theory as complementary perspectives for understanding client-contractor collaborative relationships. We gathered quantitative and qualitative data in two projects, conducting three assessments in about one year. We found that perceptual distance increased and decreased over time, and that a reduction was typically associated with the collaborative relationship being characterized by stewardship rather than agency. These findings suggest that a regular assessment and evaluation of partners’ perceptions of critical project issues is warranted to timely detect and counteract perceptual distance. Moreover, partners would best adopt a stewardship orientation to reduce perceptual distance, although this may take considerable effort given the distributive nature of many pre-project negotiations.     

复杂山区铁路客运站自动选址研究

无备选站址条件下的客运站自动选址是线站协同优化的前提和基础,而不局限于车站选址的代价最小化,同时考虑连接车站间区间线路的代价具有重要意义。构建复杂山区铁路客运站自动选址模型,首先,建立综合地理信息模型,基于线站一体化的设计理念,实现单个车站选址,确定站心位置及站坪方向;其次,以公路线形优化模型的改进算法完成站—站间自动选线设计;最后,将车站选址代价与区间线路代价紧密结合起来,计算综合代价,实现站址方案的优选。以山区铁路为例对该方法进行验证,结果表明,该方法能高效生成山区铁路车站方案集,并辅助设计人员进行方案优化。     

What is happening in Paris? Airbnb,hotels, and the Parisian market: A case study

Airbnb has been the subject of heated discussions among tourism and hospitality scholars. In order to understand the true impact of P2Psharing on the tourism and hospitality landscape, it is important to understand that market in detail first. Therefore, in this paper, we explore the development of the Airbnb market over the last seven years in Paris, the most popular destination for Airbnb guests with more than 40,000 accommodation rentals. This research note is a summary of our findings on the Paris market. Our study shows different growth and seasonality patterns for Airbnb and hotels and dissimilarities in the geographical location of the offers. The findings indicate that the two products are not in direct competition and that their relationship might be more complex than previously thought. We trust that exploring the nature of the competitive relationship would be a valuable avenue for further investigation.     

Sharing versus collaborative economy: how to align ICT developments and the SDGs in tourism?

Great hopes have been placed in the sharing economy to provide a new business model based on peer-to-peer (P2P) exchanges of underutilized assets. As a model, the sharing economy has been expected to make significant contributions to sustainability, providing new opportunities for entrepreneurship, more sustainable use of resources, and consumer co-operation in tight economic networks. However, in recent years, digital platforms have turned into the most important actors in the global sharing economy, turning global corporations, such as AirBnB, Booking, or TripAdvisor into intermediaries controlling and profiting from most transactions. Focused on accommodation, this paper conceptualizes the sharing economy in comparison to the wider collaborative economy, and discusses its social, economic, environmental, and political impacts in comparison to the sustainable development goals. It concludes that the sharing economy has great potential to make very significant contributions to sustainability, though the model is increasingly being replaced by the collaborative economy, which performs as an extension and acceleration of neoliberal economic practices.     

Correspondence to what? Coherence to what? What is good scenario-based decision making?

This paper provides a framework for the evaluation of scenario planning and other strategic decision making methods or techniques. If scenario planning is useful, we should be teaching it in schools and we as individuals should be using it to cope with the uncertainty inherent in modern life. A prerequisite to this is the need to identify why, where and how (in what way) scenario planning and other methods or techniques are useful. Here, I review evaluations of scenario planning. Taking a Brunswikian perspective, I highlight the issues that have failed to be addressed in this evaluation. I demonstrate that there are many ways in which scenario planning could be useful other than those that have appeared in previous discussions. These multiple routes are dependent upon the interaction between the individual organisation, the environment in which they are operating and the method being followed.     

Testing Rival Theories of Budgetary Decision–making in the US States

This article tests three common budgetary decision–making theories in the US states. Pooled time series cross–section analysis is used from 1960 to 1996 to test the garbage can theory and incrementalism, and from 1989 to 1996 to test various theories of rational budgeting. The results demonstrate that there was some support for all three theories in terms of their impact on reducing state budget outputs. Rational budgeting reduces expenditures in aggregate, incrementalism has relatively low explanatory power below the aggregates, and garbage can budgeting is more prevalent in functional areas than for government as a whole. These findings imply that the future research agenda on budgetary decision–making theories should focus more on a system–wide approach, which takes into account many of the characteristics of all three rival models of decision–making, rather than exclusively focusing on each one singly.     

基于粗糙集理论的决策树方法在贷款客户信用评估中的应用

决策树是数据挖掘中常用的分类技术，其生成的规则便于决策者理解和应用。然而面对较多的属性且含有冗余和噪声属性的记录集生成的决策树时，无法删除冗余属性，造成运算过程复杂。本文旨在通过应用粗糙集理论，将其与决策树方法进行结合，对属性进行约简，降低运算复杂度，并生成相对简化的规则形式，并将其应用到银行个人贷款客户信用评估之中。