Comparative study of deep learning models for analyzing online restaurant reviews in the era of the COVID-19 pandemic

Online reviews remain important during the COVID-19 pandemic as they help customers make safe dining decisions. To help restaurants better understand customers’ needs and sustain their business under current circumstance, this study extracts restaurant features that are cared for by customers in current circumstance. This study also introduces deep learning methods to examine customers’ opinions about restaurant features and to detect reviews with mismatched ratings. By analyzing 112,412 restaurant reviews posted during January-June 2020 on Yelp.com, four frequently mentioned restaurant features (e.g., service, food, place, and experience) along with their associated sentiment scores were identified. Findings also show that deep learning algorithms (i.e., Bidirectional LSTM and Simple Embedding + Average Pooling) outperform traditional machine learning algorithms in sentiment classification and review rating prediction. This study strengthens the extant literature by empirically analyzing restaurant reviews posted during the COVID-19 pandemic and discovering suitable deep learning algorithms for different text mining tasks.     

Efficiency of travel agencies: A case study of Alicante,Spain

This study analyses the relative efficiency of 22 travel agencies of similar characteristics based in Alicante (Spain). This analysis is carried out using the Data Envelopment Analysis (DEA) technique and smoothed bootstrap. Following the analysis, possible lines of action that the agencies can take in order to improve their efficiency in the future are provided. Finally, using the Mann Whitney U Test, the relationship, or lack thereof, between the levels of efficiency of these agencies and their ownership type, location and level of experience is examined.     

蜜月游市场特征的相关与回归分析——针对北京常住居民蜜月游市场

在我国,蜜月游市场发展迅猛,潜力巨大,收益率颇高.特别值得注意的是,我们调研发现:高收入者与非高收入者共享蜜月游这一高端旅游产品.为此我们进行了相关的定量分析,以进一步研究其发展脉络,揭示其变动趋势,为政府主管部门及相关旅游企业提供决策依据.     

接受理论源流及其应用价值分析

人类接受活动广泛存在于信息传播、文学作品欣赏和知识教育与学习的过程中,所谓接受不仅仅是信息的给予和传递．还包括对象在接受信息过程中感知、判断和内化的过程,而接受过程的有效性在于使传导者、传导内容、传导渠道和受传者有较高的契合程度。将接受理论应用到德育教育中,对于德育教育方式方法的改进与创新,以及德育教育途径的拓展与优化亦具有重要的参照价值。     

盈余管理:动因分析与减少对策

盈余管理是公司管理层为实现自身效用或公司市场价值最大化等目的,进行会计政策的选择,从而调节公司盈余的手段。在我国特定的资本市场环境下,盈余管理的负面作用远远涵盖其正面作用,上市公司过多的盈余管理行为导致会计信息严重失真,有碍于资本市场资源配置功能。本文从我国上市公司盈余管理动因分析入手,提出了减少上市公司盈余管理行为的对策。     

“默示同意”：合理博弈与不完善制度——郑百文重组过程中表决规则的经济学分析

当主持者对表决方式有选择余地时,那么他会根据自己的偏好,直接或间接影响表决结果,这是无法避免的,是在现有制度下的一种合理博弈,是有效的。如果他本身就是博弈的一方,则更会充分利用这种影响。而主持人对议案内容的偏好是广泛存在的,不可能通过消除偏好来消除影响。但是如果加强民主和监督,使主持者的选择余地尽可能缩小,即他只能选择社会承认的最优的“公平”规则才符合他自己的成本－－收益平衡,那么这样就使个人的最优选择与社会的最优选择一致,提供了制度上的改进办法。而在未有更高程度的民主和更有效的监督制度之前,只能容忍在现有制度内的博弈行为。所以,只有通过进一步加强民主和健全法制,进行表决规则的制度建设,才有可能得到更优化和更真实的表决结果。     

Career patterns of top management team members in five countries: an optimal matching analysis

This paper introduces optimal matching analysis (OMA) to the field of top management research. With this method, we develop six career patterns of top management team (TMT) members from five countries based on their international experience, organizational tenure and professional experience. The results provide strong support for the significance of these patterns, since each country (Denmark, Germany, Japan, the United Kingdom and the United States) shows one to four predominant career patterns of their managers and the occurrence of these patterns also differs significantly between the fields of activity within the TMT (chairperson, head of a division, primary activities and support activities).     

火电厂锅炉微油点火技术的经济性分析

针对火电厂锅炉启动点火及低负荷助燃工况下耗油量大的问题,介绍了微油点火技术的特点及其在锅炉改造中的应用,对锅炉启动、低负荷运行的经济性进行计算和分析。通过分析可以看出,微油点火技术在火电厂锅炉上应用有很好的经济效益。     

Social Position and Behaviour: A Formalization

Modern society has witnessed anever-increasing development in the social sciences;partly due to changes in mentality, and partly due tothe growing requirements of the economic and political world – requirements which frequently takeon the guise of necessity, as for instance in thecases of market research and electoral opinion polls.Such development has produced an increasing paralleldemand for mathematical accuracy and exactitude inthese fields.The intention here is to rationalize the basic logicand methodology of the sociological procedure; anintention, it is hoped, which could be influential inimproving practical sociological work by rendering itmore comprehensible. This requires the employment offairly sophisticated mathematical and statisticalnotions.Section 1 outlines the definitions considered essential for the rationalization of the basiclogic framework previously described.Section 2 discusses the general concept of statisticalvariance. Section 3 introduces the notion of ``heterogeneity'and offers several propositions linked to this concept.Section 5 revolves around the notion of ``inaccuracy'.Section 6 presents a theorem relating to theimmersion of metric spaces in Banach spaces, andshows how the theorem can be used to constructtheoretically satisfactory immersion algorithms.Section 7 together with the material, which ispreviously introduced in Section 4, outlines thecluster analysis and the principal components methodologies.     

A Probabilistic Clustering Model for Variables of Mixed Type

This paper develops a probabilistic clustering model for mixeddata. The model allows analysis of variables of mixed type: thevariables may be nominal, ordinal and/or quantitative. The modelcontains the well-known models of latent class analysis as submodels.As in latent class analysis, local independence of the variables isassumed. The parameters of the model are estimated by the EMalgorithm. Test statistics and goodness-of-fit measures are proposedfor model selection. Two artificial data sets show the usefulness ofthese tests. An empirical example completes the presentation.