Automated topic modeling of tourist reviews: Does the Anna Karenina principle apply?

Automated content analysis of online travel reviews allows identification of topics of travelers' satisfaction, yet its domain is not well researched. We suggest that the Anna Karenina principle positing a greater variability of the factors leading to business failure as opposed to those leading to success can be applied to the domain of visitors’ reviews of historic and cultural attractions. The larger variability of issues in reviews of dissatisfied visitors is likely to result in limitations for automated topic modeling. We confirm our proposition using TripAdvisor reviews of the Terracotta Army museum in China, and validate the outcome with two additional sites. The study strongly suggests that application of unsupervised topic mining algorithms to negative reviews may be problematic and the results should be treated with caution. The main themes of dissatisfaction of visitors to all three sites are reported and practical implications for management of the attractions are discussed.     

A novel model to manage air cargo disruptions caused by global catastrophes such as Covid-19

The outbreak of the COVID-19 pandemic has drastically disrupted the air cargo industry. This disruption has taken many directions, one of which is the demand imbalance which occurs due to the sudden change in the cargo capacity, as well as demand. Therefore, the random change leads to excessive demand in some routes (hot-selling routes), while some other routes suffer from a big shortage of demand (underutilized routes). Routes are substitutable when there are several adjacent airports in the Origin & Destination (O&D) market. In this market, demand imbalance between substitutable routes occurs because of the above reasons. To tackle the demand imbalance problem, a novel model is introduced to estimate the quantity combinations which maintains the balance between underutilized and hot-selling routes. This model is a variant of the classic Cournot model which captures different quantity scenarios in the form of the best response for each route compared to the other. We then cultivate the model by integrating the Puppet Cournot game with the quantity discount policy. The quantity discount policy is an incentive which motivates the freight forwarders to increase their orders in the underutilized routes. After conducting numerical experiments, the results reveal that the profit can increase up to 25% by using the quantity discount. However, the quantity discount model is only applicable when the profit increase in the hot-selling route is greater than the profit decrease in the underutilized route.     

土地市场扭曲如何影响制造业出口产品质量升级*——基于土地市场交易数据和制造业企业数据的实证分析

地方政府“以地谋发展”的策略在促进各地区制造业大规模集聚和出口贸易快速增长的同时，也势必会给企业出口产品质量带来深刻影响。本文综合利用中国土地市场网城市土地交易数据、中国工业企业数据、中国海关进出口产品数据和中国城市面板数据，实证检验了土地市场扭曲对企业出口产品质量升级的影响，并对其内在机制进行了探讨。研究发现：中国城市建设用地配置存在明显的工业偏向性，进而导致工业用地价格被低估，产生工业用地应得收益大于实际价格的反向扭曲问题。这种反向扭曲可通过抑制技术进步、阻碍产业结构高级化、弱化集聚经济效应等机制显著降低制造业企业出口产品质量。土地市场扭曲对企业出口产品质量升级的影响具有明显的异质性特征。具体而言，土地市场扭曲不利于一般贸易企业与混合贸易企业出口产品质量提升，但对加工贸易企业出口产品质量提升具有促进作用。土地市场扭曲对企业出口产品质量升级的抑制作用由东到西依次递增。土地市场扭曲不利于外资企业和国有企业出口产品质量提升，对集体企业及民营企业的影响不显著。     

When do sell-side analysts switch industries they follow?

Between 1984 and 2014 over 3400 sell-side analysts changed the primary industry they followed. This article documents that analysts are more likely to change their industries when their absolute and relative forecasting accuracy in that industry is low and when the accuracy in the new industry is high. Analysts are more likely to switch industries at the beginning of their careers, after a recent change of an employing brokerage house, and if they have a history of switching industries before. Analysts are less likely to make a switch when their forecasting activity in the industry is high, when the industry is followed by many analysts and when they are employed by a top brokerage house.     

Does Targeted Monetary Policy Matter? A Perspective from China

Several major central banks have experimented with targeted monetary policy to improve credit resource allocation. This policy only applies to ‘eligible’ banks. For example, The People's Bank of China conducted seven targeted reductions of reserve requirements during 2014–15. This article documents the phenomenon of targeted monetary policy and evaluates its effects. The results show that, in the case of China, this policy has generated an extra significant, positive return on the stocks of eligible banks, amounting to 1.2–1.3 per cent in a four‐day treatment period. This substantial return gives commercial banks an extra incentive to align with the policy goals of central banks.     

The airfare pricing and seat allocation problem in full-service carriers and subsidiary low-cost carriers

This study investigates the competitive market situation in the air transport industry considering full-service carriers (FSC), subsidiary low-cost carriers (LCC) and rival LCCs on the flight-leg level while subsidiary LCCs are established by FSCs against rival LCCs to keep the market share and to make more profit. It is assumed that the demand of economy class for each airline follows a known distribution, and the mean value of that distribution is a function of its airfare and the airfare differences with other airlines. In addition, no-shows and cancellations are introduced to reflect a real situation. Based on this situation, a mathematical model is developed to derive efficient airfare pricing and seat allocation for each airline for maximizing the profit sum of both FSCs and subsidiary LCCs using a repeated game. A repeated game model integrated with a Tabu search algorithm and an EMSR based heuristic is suggested to deal with the proposed repeated game. A numerical example is provided to validate the model and solution procedure with hypothetical system parameter values under two kinds of market situations that show before and after the emergence of subsidiary LCCs.     

重庆市农业科技创新资源配置效率及影响因素研究

[目的]通过分析重庆市农业科技资源配置效率及影响因素,以期对重庆市的农业科技资源的合理配置提出参考建议。[方法]构建评价指标体系,以农业科技创新资源配置环境、农业科技资源经费投入、农业科技人才储备和农业科技创新成果4个方面构成综合层,向下分16个具体指标,运用层次分析法和模糊评判综合评价重庆市农业科技资源配置效率及影响因素。[结果]重庆市农业科技创新资源的配置效率综合得分为81.08,为2级水平,其中农业科技人员流失比例较大,投入产出效率较低成为主要制约因素。[结论]重庆市农业科技创新资源的配置效率处于中等水平,合理配置农业科技人员和经费投入以及提高资源配置环境是提高重庆市农业科技协同创新资源的配置效率的关键;农业科技资金投入浪费严重和农业科技活动成果的转化率较低、农业科技人才结构和农业科技创新资源配置方式的不合理以及农业科技市场机制尚不完善是影响农业科技资源配置效率的主要因素。     

Transport infrastructure equities in mixed-asset portfolios: estimating risk with a Garch-Copula CVaR model

Transport infrastructure is an important subsector within infrastructure, but knowledge of its equities in terms of risk-return characteristics and contribution to portfolio performance is still limited. This study assesses the subsector individually and in a multi-asset, index-based portfolio. In doing so, we apply a t-Copula-based Conditional Value-at-Risk model to simulate risk and returns. Our findings reveal that the subsector has a relatively low dependency on other equities, performs like other alternative asset classes such as general real estate, and does not grant significant risk diversification benefits for mainstream institutional investors such as pension funds. Investors aiming for higher target returns may however assign substantial weights to transport infrastructure, supporting our conjecture that it does not share the same asset class characteristics as general infrastructure. By contrasting Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) scores for both the mean-variance framework and the t-Copula simulation, we further document the limitations of traditional VaR approaches. Hence, this study’s results support the use of risk assessment tools that incorporate non-normal distributions to represent multivariate dependence structures.     

Linear programing models for portfolio optimization using a benchmark

We consider the problem of constructing a perturbed portfolio by utilizing a benchmark portfolio. We propose two computationally efficient portfolio optimization models, the mean-absolute deviation risk and the Dantzig-type, which can be solved using linear programing. These portfolio models push the existing benchmark toward the efficient frontier through sparse and stable asset selection. We implement these models on two benchmarks, a market index and the equally-weighted portfolio. We carry out an extensive out-of-sample analysis with 11 empirical datasets and simulated data. The proposed portfolios outperform the benchmark portfolio in various performance measures, including the mean return and Sharpe ratio.