Assessing the effects of policies on China’s outward foreign direct investment

This paper discusses the determinants of China’s outward foreign direct investment (OFDI) with a special focus on the role of government policy. In particular, we investigate the types of policies that are most influential in promoting OFDI. Our main contribution is to analyse, for the first time, China’s OFDI policies by means of quantitative indicators. We refine policies definitions and distinguish between Regulation Policies, Service Policies, Promotion Policies and Supervision Policies, and we develop a methodology for collecting, screening and coding policies; then we create new indices to capture different types of policies. We find that Regulation Policies, Service Policies and the general attitude of the government have significant effects on China’s OFDI at the national level.     

成都市国际化营商环境升级版战略研究--基于万博新经济研究院营商环境指数的分析

打造营商环境是促进经济的重要环节,提升营商环境是增强城市竞争力和吸引力的手段。论文通过引入万博新经济研究院发布的《后疫情时代中国城市营商环境指数评价报告(2020)》,多角度对比分析成都与国内先发城市,发现成都在营商环境方面的优势与短板,最后得出改进措施,旨在为成都打造国际化营商环境提供理论依据。     

基于VAR模型探究BDI和燃油价格的相互影响

燃油价格近期受疫情影响出现剧烈波动,国际干散货航运市场也受到巨大影响。基于Clarksons官方数据库1992年1月至2020年4月相关数据,进行实证研究发现,国际燃油价格的暴跌对波罗的海干散货运价指数的下降有着显著的正向影响;燃油价格虽然也在一定程度上受到BDI的影响,但存在一定的滞后性。这有利于干散货运输公司根据燃油价格波动预测运价指数的变化趋势,从而采取多样的方式应对冲击。也对保障干散货运输市场的稳定发展有重要意义。     

Dynamic management of aircraft stand allocation

This paper aimed to present an original approach for solving the aircraft stand allocation (SA) problem dynamically when due to operational disturbances, the planned allocation cannot be accomplished. The proposed Multiple-criteria Dynamic Stand Allocation (MDSA) method uses fuzzy logic to support decision-making under uncertainty. The MDSA method provides effective solutions in a short time, necessary for traffic management in case of delays, emergency, and untypical cases. It considers partially conflicting points of view of different airport users (airport managers, air traffic controllers, airlines, handling agents, and passengers) and may significantly support managers on the SA problem. The approach proposed can also be used for creating an initial SA plan for a considerable number of aircraft.     

关于企业成本管理的探讨

成本管理是预算管理和绩效管理的前提,企业需要正确地将成本进行分类、计量和归集。恰当的成本管理制度可以帮助企业提升运营效率和业务绩效,同时企业的流程改善、突破和优化与成本管理密不可分。另外,管理者需要令客户对产品和服务满意,并且有效控制各项成本。企业成本管理不是单纯地降低成本,而是通过利用成本分析工具,有效地管理和规划资源,进而提高总体运营效率,保证企业总体绩效的持续改善。论文通过成本计算制度的制定方法和业务流程改善分析技术两方面对成本管控进行探讨。     

Extinction accounting and accountability: Empirical evidence from the west European tissue industry

Recently, human activities are more and more invasive with respect to biodiversity. Several studies highlighted the key role played by accountants in contributing to the development of tools able to support company in assessing, reporting, and disseminating, as well as accomplishing, the preservation of natural species and ecosystems (King and Atkins, 2016). Corporate reporting of environmental information might increase the credibility of forest certifications, given that some scholars argued that certified forests are not often run, in a sustainable way. Moreover, certifications sometimes cover harmful forest practices (Elad, 2014) and do not ensure a good quality of environmental reporting and performance. The research question therefore intends to explore how extinction accounting and accountability (EAA) is able to reflect ex post the company's business strategy and, at the same time, influence ex ante its formulation by easing the prevention of deforestation risk and addressing the issue of credibility through specific actions. In more detail, the “Emancipatory Framework for Extinction Accounting and Accountability” (EFEAA) (Atkins and Maroun, 2018) was tested using content and interpretative analyses based on the reports inherent to top four companies working in West Europe in the tissue industry, where the preservation of forest heritage is a “compulsory route” for assuring the business sustainability, in terms of both raw material renewal and brand reputation. The findings highlighted the first attempt to carry out a qualitative research over the management of forest issues. In our study, companies tend to report advantages arising from the use of forest, but this kind of disclosure is too generic without providing evidence over the ecosystem services forests produce. Moreover, firm size affects the quantity and the quality of disclosure. At last, managerial implications and future research avenues are outlined and discussed.     

Excess capacity,production technology and technical inefficiency in hospitality sector

This article examines the effects of excess capacity on the production cost and technical inefficiency of hotels and restaurants in Norway. The dataset includes a daily unbalanced panel of 94 hotels and restaurants from 2003 to 2014. To accommodate inefficiency, we use an input distance function (IDF). Inefficiency in the IDF means that if inputs are overused by k% then production cost is also increased by k%. We also allow inefficiency to differ across locations and regions by using them as determinants. The results indicate that excess capacity considerably affects the cost and increases inefficiency. The marginal effect on cost increases with excess capacity, but the effect on inefficiency sets in when it exceeds 50 percent. Furthermore, we find less overuse of inputs by firms in small metro towns and the Northern region causing them to be more efficient [except for the Southern and Western regions] than their counterparts.     

Microfinance and social capital formation- a social network analysis approach

The microcredit program has emerged as an important poverty alleviation strategy over the last three decades, and several studies have examined its economic impacts on the community well-being. However, far too little attention has been paid to the effects of micro credits on community social connection and solidarity. This paper aims to examine the application of Social Network Analysis (SNA) to explore the impact of the rural microcredit fund on community social capitals. In doing so, the data on interactions of four rural development groups' members before and after the microcredit project implementation were collected using participatory workshops in Neyzar village of Qom province in Iran. The data were analyzed by Ucinet software, and the socio-graphs were produced by the NetDraw application. The results show that, more people have been involved in the social interactions after the project implementation and there was statistically significant increase in density and decrease in centralization of cooperation network. Furthermore, there were no important distinctions in centrality of people with various educational levels before and after the project implementation. Overall, it can be concluded that, the microfinance initiative considerably promotes the community social capital and participation in the rural development activities. Moreover, the SNA techniques are applicable as an impact assessment tool to investigate changes in community social capital.     

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.     

The mechanism of credit risk contagion among internet P2P lending platforms based on a SEIR model with time-lag

The credit risk contagion of Internet peer-to-peer (P2P) lending platforms is an important part of Internet financial risk management and supervision. This study analyzes the contagion path of credit risk in Internet P2P lending. Based on complex network theory and the theory of infectious disease dynamics, the characteristics of Internet P2P lending development are combined to construct a SEIR model of credit risk transmission among Internet P2P lending platforms with time lag, and the robustness of the model is analyzed and proven. The influence of platform correlations, the susceptible immune rate, the platform elimination rate, contagion latency, the saturation coefficient, and the susceptibility input rate on credit risk contagion behavior among Internet P2P lending platforms is analyzed, using the equilibrium point and threshold value. The impact of each variable is analyzed by simulation. Corresponding countermeasures and suggestions are proposed to prevent and control credit risk contagion among these platforms.