Study on Chinese Tourism Web Sites' Distribution and Online Marketing Effects.

As a platform and carrier of tourism information, tourism websites (TWs) and online tourism marketing have deeply affected the tourism industry. The authors adopt a geographical perspective to analyze the distribution of Chinese tourism websites (CTWs), and statistical analysis with SPSS16.0 was conducted to explore the online marketing effects of CTWs, and some meaningful results has been produced: 1) The number of CTWs generally decreases from eastern China to central and western China, and are especially dominant in tourism developed provinces. 2) The number of tourists has strong statistical correlation with the number of CTWs. 3) The strongest correlation for inbound tourists is with hotel websites, and the highest correlation coefficient is 0.807 between the number of domestic tourist and resort websites. Both inbound and domestic tourists have a low correlation coefficient with travel agency websites (TA). 4) There exist some statistical models between tourist numbers and different kinds of CTWs. The results clearly unveil the marketing effects and correlation of CTWs and is helpful for further online marketing strategies

Is it time to withdraw from china?

This research cross-employs the Social Cognitive Theory (SCT) and three major labor theories comprised of Maslow’s theory, Alderfer’s theory and Herzberg’s theory with Multiple Criteria Decision Making (MCDM) consisting of Factor Analysis (FA), Analytical Network Process (“ANP”), Fuzzy Analytical Network Process (FANP) and Grey Relation Analysis (GRA) to evaluate the four types of innovative investment strategies in China after the Domino Effect of the China’s Labor Revolution. The most contributed conclusion is that the “change of original business at the raising compensation policy” (CBRCP) is the best choice for Taiwanese manufacturers operating in China because it is the highest scores of three assessed measurements in the CBRCP. This conclusion further indicates that manufacturing enterprises have little leverage, in the interim, but to increase employment compensation and benefits to satisfy the demands from the ongoing Chinese labor revolution even though it brings about an incremental expenditure in their manufacturing costs. Therefore, the next step beyond this research is to collect additional empirical macroeconomic data to develop a more comprehensive evaluation model that takes into consideration a more in-depth vertical measurement and horizontal assessment methodologies for developing added comprehensive and effective managerial strategies for surviving in this momentous, dynamically-changing and lower-profit Chinese manufacturing market.China labor revolution; Maslow theory; Alderfer theory and Herzberg theory; Multiple criteria decision making

Predicting software project effort: A grey relational analysis based method

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.The inherent uncertainty of the software development process presents particular challenges for software effort prediction. We need to systematically address missing data values, outlier detection, feature subset selection and the continuous evolution of predictions as the project unfolds, and all of this in the context of data-starvation and noisy data. However, in this paper, we particularly focus on outlier detection, feature subset selection, and effort prediction at an early stage of a project. We propose a novel approach of using grey relational analysis (GRA) from grey system theory (GST), which is a recently developed system engineering theory based on the uncertainty of small samples. In this work we address some of the theoretical challenges in applying GRA to outlier detection, feature subset selection, and effort prediction, and then evaluate our approach on five publicly available industrial data sets using both stepwise regression and Analogy as benchmarks. The results are very encouraging in the sense of being comparable or better than other machine learning techniques and thus indicate that the method has considerable potential.National Natural Science Foundation of Chin

Indoor thermal environments in Chinese residential buildings responding to the diversity of climates

China has a diversity of climates and a unique historic national heating policy which greatly affects indoor thermal environment and the occupants’ thermal response. This paper quantitatively analyzes the data from a large-scale field study across the country conducted from 2008 to 2011 in residential buildings. The study covers nine typical cities located in the five climate zones including Severe Cold (SC), Cold (C), Hot Summer and Cold Winter (HSCW), Hot Summer and Warm Winter (HSWW) and Mild (M) zones. It is revealed that there exists a large regional discrepancy in indoor thermal environ- ment, the worst performing region being the HSCW zone. Human’s long-term climate adaptation leads to wider range of acceptable thermal comfort temperature. Different graphic comfort zones with accept- able range of temperature and humidity for the five climate zones are obtained using the adaptive Predictive Mean Vote (aPMV) model. The results show that occupants living in the poorer thermal environments in the HSCW and HSWW zones are more adaptive and tolerant to poor indoor conditions than those living in the north part of China where central heating systems are in use. It is therefore recommended to develop regional evaluation standards of thermal environments responding to climate characteristics as well as local occupants’ acclimatization and adaptation in order to meeting dual targets of energy conservation and indoor thermal environment improvement

Rural Labor Absorption Efficiency in Urban Areas under Different Urbanization Patterns and Industrial Structures: The Case of China

In this paper, we use Data Envelopment Analysis (DEA) to estimate how well China’s urban areas absorb migrant workers under the interaction of urbanization and industrialization. We applied an output-oriented BCC model to evaluate provincial and regional rural labor absorption efficiency in mainland China. It appears that 4 out of 31 provinces and municipals are efficient, and 2 out of 8 economic regions are efficient in absorbing migrant workers. In the southern and eastern parts of China, urban labor absorption efficiency is higher compared with the western and northern parts of China. Different urbanization patterns and industrial development strategies should be adopted in different economic areas to enhance labor absorption ability in these areas. Urban areas in many parts of China still have potential to accommodate rural migrant workers. The inter-regional flow of production factors would affect urban labor absorption efficiency.rural labor absorption in urban areas, urbanization, industry structure, DEA

ImageNet Large Scale Visual Recognition Challenge

The ImageNet Large Scale Visual Recognition Challenge is a benchmark in object category classification and detection on hundreds of object categories and millions of images. The challenge has been run annually from 2010 to present, attracting participation from more than fifty institutions. This paper describes the creation of this benchmark dataset and the advances in object recognition that have been possible as a result. We discuss the challenges of collecting large-scale ground truth annotation, highlight key breakthroughs in categorical object recognition, provide a detailed analysis of the current state of the field of large-scale image classification and object detection, and compare the state-of-the-art computer vision accuracy with human accuracy. We conclude with lessons learned in the five years of the challenge, and propose future directions and improvements.Comment: 43 pages, 16 figures. v3 includes additional comparisons with PASCAL VOC (per-category comparisons in Table 3, distribution of localization difficulty in Fig 16), a list of queries used for obtaining object detection images (Appendix C), and some additional reference

Meta-Analysis of General and Partial Equilibrium Simulations of Doha Round Outcomes

Quantification of welfare changes due to trade liberalisation play a crucial role for political decision making. However, meaningful comparisons of simulation results from different sources are difficult. Often significant differences in simulated gains from liberalisation do not serve to increase confidence in quantitative assessments based on trade models. We employ a metaanalysis of applied trade simulations under the WTO Doha Round to identify model characteristics that influence the magnitude of simulation results, and to estimate the magnitude of this influence. Findings from our simple econometric model are plausible and show that each simulation experiment represents a complex interaction of experimental settings that may not easily be understood by and communicated to non-experts. Meta-analysis proves to be a useful tool for empirically assessing this complexity.Meta-analysis, CGE, Partial Equilibrium, Trade Liberalization, C00, C23, C68, F10, International Relations/Trade,