Global recessions as a cascade phenomenon with interacting agents

This paper examines global recessions as a cascade phenomenon. In other words, how recessions arising within one or more countries might percolate across a network of connected economies. An agent based model is set up in which the agents are Western economies. A country has a probability of entering recession in any given year and one of emerging from it the next. In addition, the agents have a threshold propensity, which varies across time, to import a recession from the agents most closely connected to them. The agents are connected on a network, and an agent’s neighbours at any time are either in (state 1) or out (state 0) of recession. If the weighted sum exceeds the threshold, the agent also goes into recession. Annual real GDP growth for 17 Western countries 1871–2006 is used as the data set. The model is able to replicate three key features of the statistical distribution of recessions: the distribution of the number of countries in recession in any given year, the duration of recessions within the individual countries, and the distribution of ‘wait time’ between recessions i.e. the number of years between them. The network structure is important for the interacting agents to replicate the stylised facts. The country-specific probabilities of entering and emerging from recession by themselves give results which are by no means as well matched to the actual data. We are grateful to an anonymous referee for some extremely helpful comments.     

我国旅行社从业人员总量需求趋势实证研究

随着旅游业在我国国民经济中地位的不断提高及旅游业的快速发展,旅游从业人员的数量也要不断增加,旅行社业作为旅游业的主要板块,其从业人员的数量及质量都将对其行业的发展产生重大影响。本文主要借助科学的方法,在占有大量资料的基础上,从实证的角度对我国旅行社未来几年的从业人员的总量进行了预测分析,以为相关部门及院校提供有益的参考。     

Trade Credit Management and the Decision to Use Factoring: An Empirical Study

This paper examines the firm's decision to use factoring amongst a cross-sectional sample of 655 manufacturing companies using a rich firm-level database. The paper develops and tests hypotheses that explain this particular choice of credit and financial management policy. We find strong evidence of a 'financing demand' explanation for the use of factoring, and also some support for theories which relate the decision to use a factor to the firm's product characteristics, to market characteristics and to the preferences of the factor (supply constraints). The motivation to use factoring, however, appears to be related more to a demand for asset-based finance from small companies than to firm-level choices about organisational structure.     

A Formal Study of Distributed Meeting Scheduling

Automating routine organizational tasks, such as meeting scheduling, requires a careful balance between the individual (respecting his or her privacy and personal preferences) and the organization (making efficient use of time and other resources). We argue that meeting scheduling is an inherently distributed process, and that negotiating over meetings can be viewed as a distributed search process. Keeping the process tractable requires introducing heuristics to guide distributed schedulers' decisions about what information to exchange and whether or not to propose the same tentative time for several meetings. While we have intuitions about how such heuristics could affect scheduling performance and efficiency, verifying these intuitions requires a more formal model of the meeting schedule problem and process. We present our preliminary work toward this goal, as well as experimental results that validate some of the predictions of our formal model. We also investigate scheduling in overconstrained situations, namely, scheduling of high priority meetings at short notice, which requires cancellation and rescheduling of previously scheduled meetings. Our model provides a springboard into deeper investigations of important issues in distributed artificial intelligence as well, and we outline our ongoing work in this direction.     

Modeling and supporting task-oriented group processes: Purposeful complex adaptive systems and Evolutionary Systems Design

Evolutionary Systems Design (ESD) is a universal general problem solving, formal modeling, design framework for purposeful complex adaptive systems (PCAS) and processes, i.e., task-oriented group processes. These processes constitute policy making, group decision, negotiation, and multiagent problem solving with human and/or artificial agents. ESD is also a framework for computer group support systems (GSS) that support these processes. The ESD general framework can be applied to define and solve specific problems. In this article the ESD framework is presented and illustrated by example. The article provides background for ESD computer implementations discussed in two other related articles (Lewis and Shakun 1996; Bui and Shakun 1996).     

徐霞客:中国古代的旅游圣人

本文从圣人的概念界定切入,参照徐霞客对中国旅游文学的独特贡献,提出他是中国古代的旅游圣人,是把毕生献给中国古代旅游事业的第一人。进而从徐霞客的旅途生活,论述了他最可贵的三种精神,即吃苦精神、探险精神和乐观精神。     

Using a Validation Process to Develop Market Segmentation Based on Travel Motivation for Major Metropolitan Areas

Studies on market segmentation based on travelers' push motivation have been conducted without implementing a statistically validated procedure for establishing the segmented markets. The purpose of this study is to identify validated traveler market segments by examining what travelers' push motivation dimensions are among the heterogeneity of travelers to a major metropolitan area. The six push motivation dimensions were extracted from the 20 motivation items by conducting factor analysis (i.e., Social/Interaction, Excitement/Fun, Relaxation, Sightseeing, Family/Friends, and Sports). Cluster analysis identified the three homogeneous groups of travelers. Subsequent discriminant analysis verified the existence of the three travelers' markets in the metropolitan area. Managerial implications are suggested for the three push motivation‐based segments.     

Travel deterrents to regional destinations

Travel motivation is prevalent in the tourism literature. Very few studies however have examined travel deterrents to visiting popular destinations. This study approaches from travel motivation understand why tourists do not visit regional destinations and from tourists’ background to identify who do not visit these destinations with a focus on well-known regional destinations in Australia. The results show that convenience to the destinations, timing, motivation and tourist attractions are the major deterrents, and the level of these deterrents is dependent upon some of the demographic background of tourists. The findings and implications conclude this paper.     

Application of graph theory to mining the similarity of travel trajectories

Travel mobility has attracted considerable attention from tourism scholars. Studies have extensively discussed discovering key (i.e., collective) movement patterns. Recently, the advancement of information technology has allowed tourism researchers to obtain detailed information regarding travel digital footprints. This study, which analyzes mobile sensor big data, proposes a data mining approach to measure the similarity of travel trajectories by performing a pair comparison of individual trajectory. This method considers the spatial and temporal dimensions of travel flow to help identify trajectory similarity across individual travelers. Considering graph theory, this research also applies graph-based spatiotemporal analytics to identify important insights from complex travel mobility networks. As a result, this study suggests an innovative approach to assess travel trajectory similarity, which can be regarded as a type of data-driven clustering method. This paper also demonstrates the applicability of network science in travel mobility.     

Afraid to travel after COVID-19? Self-protection,coping and resilience against pandemic ‘travel fear’

COVID-19 has generated an unprecedented level of public fear, likely impeding tourism industry recovery after the pandemic is over. This study explores what trigger the public's pandemic ‘travel fear’ and how people impose self-protection, coping and resilience related to travel. The study integrates theories including protection motivation theory, coping and resilience theories to address the research aim. Using a quota sampling, an online survey of 1208 respondents across mainland China was conducted. Results found that threat severity and susceptibility can cause ‘travel fear’, which leads to protection motivation and protective travel behaviors after the pandemic outbreak. Findings also revealed that ‘travel fear’ can evoke different coping strategies, which increases people's psychological resilience and adoption of cautious travel behaviors. Several strategies are provided on how to mitigate people's ‘travel fear’ and encourage travel in a post-COVID-19 world.