Do environmental regulations hamper small enterprises' market entry? Evidence from China

Due to the serious increase of environmental pollution in China, environmental regulations have become significantly stringent. Such regulations are playing an increasingly important role in the development of small enterprises (SEs) in China, especially in SEs' market entry. However, existing studies pay little attention to this issue. This paper investigates for the first time the effect of environmental regulations on SEs' market entry and the mechanism of environmental regulation effects in China. We consider two sets of panel data for the periods 2003–2010 and 2012–2015 in China. We also use the fixed effect model and the instrumental variable method to explore the role of environmental regulations in SEs' market entry. The results show that, overall, environmental regulations play a significantly positive and robust role in SEs' market entry. However, the mechanisms associated with the effect of environmental regulations on different innovative types of SEs differ. Environmental regulations promote the market entry of SEs with product innovation, but this impact is not significant for SEs with research and development (R&D) activities and R&D institutions. Our findings indicate that China's SEs prefer product innovation, which is a lower level innovative type, over R&D innovation, as a means to avoid the negative impact of stringent environmental regulations.     

A systematic review of AI technology-based service encounters: Implications for hospitality and tourism operations

The hospitality and tourism industry faces serious challenges during public health emergencies such as COVID-19. Managers are concerned not only about how to maintain business and provide humanized services but also about social distancing. This study presented artificial intelligence (AI) technology-based service encounters as a possible solution and examined the antecedents and consequences of the encounter triad including customers, employees, and AI. Based on a systematic literature review, the study identified 4 modes of AI technology-based service encounters: AI-supplemented, AI-generated, AI-mediated, and AI-facilitated encounters. In addition, the study developed an integrated model to specify the factors that influence AI technology-infused service encounters in general and the customer service outcomes that result from the encounters. The findings contribute to service management and AI application theoretically and practically.     

秦迁陵县粮仓设置体系探讨--以出粮机构粮食来源问题为中心

除仓官外,秦迁陵县内的出粮机构还包括田官、离乡及司空等。它们并非都建有独立粮仓,所出粮食的来源也不尽一致。田官不设粮仓,它的出粮地是公共粮仓中的一间专属仓房。离乡建有供应该乡粮食开支的独立粮仓,且粮仓数量与该乡人口规模有关。小乡可能仅有一座粮仓,故有时会产生因储备不足而需要仓官额外输粮的问题。司空、发弩及■舍三者既未建有独立粮仓,也不如田官那般在公共粮仓内占有一间仓房,它们向外供应的粮食全都是由仓官转输。总之,秦迁陵县内设置的粮仓包括县级公共粮仓和离乡粮仓两类。田官、司空、发弩及舍虽承担了部分出粮职能,但并未给县内粮仓体系带来影响。     

A new assessment of economic integration in East Asia: Application of an industry-specific G-PPP model

It is well known that intra-industry trade and cross-border production networks have promoted economic growth and regional integration in East Asia. However, regional supply and production chains may have been formed differently across industries, reflecting different degrees and a different scope of regional economic linkages at an industry level. This paper makes a threefold contribution. First, to assess industry-level differences, this study adopts the generalized purchasing power parity (G-PPP) model using industry-specific producer prices. Second, the momentum threshold autoregressive (M-TAR) model is employed to allow for possible nonlinearity arising from the dynamic nature of regional economic growth and development. Third, the Granger causality test is also conducted to assess whether regional economies have autonomously integrated. The empirical results reveal that economic integration has progressed more autonomously in the electrical industry, as well as in the transportation equipment industry, as China and the ASEAN countries have become the final destination markets for finished products in these two industries.     

Perceived hygiene attributes in the hotel industry: customer retention amid the COVID-19 crisis

The COVID-19 pandemic has caused a crisis in the hotel industry worldwide, but few studies have suggested methods to retain customers. This study proposes hygiene management as a means to minimize the indirect damage from COVID-19 to the hotel industry. It identifies perceived hygiene attributes and explores their influence on hotel image, word of mouth, and revisit intentions. This study identifies and validates three types of perceived hygiene attributes through qualitative and quantitative methods. It uses structural equation modeling to validate hypotheses and concludes that there are significant relationships of influence between the proposed variables. This study provides important and meaningful insights into hotel image and customer behavior through perceived hygiene attributes.     

Ratio-based design hour determination for airport passenger terminal facilities

To avoid both over-design and under-sizing of airport passenger terminal facilities such as security checkpoints, the infrastructure is designed for a specifically determined design load. As such, the design load is considered for a short period of time, usually an hour of operation, during which peak, though not necessarily maximum, demand occurs. For strategic planning applications, future design loads can be determined by either fictitious flight schedules or ratio-based models which forecast the relationship between design load and annual demand. This study presents two ratio-based methods which allow the direct determination of design hour loads (DHL) for passenger terminal facilities. The unsaturated DHL model considers the relationship between observed passenger flows in the terminal and aggregated annual demand data. The saturated DHL model includes several operational constraints which limit the actual DHL, such as limitations in the runway system or the fleet mix operating at an airport. Both models are applied to two real-world airports, for which the DHL of the security checkpoint facilities is estimated from large datasets covering multiple years. Results are significant at the 5 % level and suggest that the proposed ratio-based methods are appropriate for airport strategic planning applications.     

海南城乡居民消费水平差异性分析和预测

从1985-2018年海南城乡居民收入、消费数据出发，分别建立消费关于收入、消费差距关于收入差距的自回归模型，结果表明农村居民当期消费更易受近期收入和消费水平的影响，具有不稳定性。再利用GM(1,1)模型预测城乡居民收入差距，结合自回归模型，完成未来10年海南城乡消费差距的预测：收入差距和消费差距将呈直线递增趋势，收入差距的增幅高于消费差距增幅。缩小海南城乡居民消费差距的根本途径在于缩小收入差距，应因地制宜，切实提高农民收入水平。     

决策可靠性分析及在SAR图像目标识别中的应用

决策融合是提高合成孔径雷达（Synthetic Aperture Radar,SAR）目标识别性能的重要手段，然而，可靠性较弱的决策往往会导致最终决策融合的效果变差。将可靠性分析引入基于决策融合的SAR目标识别方法中，分别计算各个决策的可靠性系数并选取可靠性的决策参与最终的决策融合。为了验证方法的有效性，分别将提出的可靠性分析应用于多特征决策融合以及多分类器决策融合并基于MSTAR（Moving and Stationary Target Acquisition and Recognition）数据集进行了目标识别实验。在基于主成分分析、线性鉴别分析和非负矩阵分解三种特征进行多特征决策融合的条件下，所提方法和直接进行决策融合的方法的识别率分别为97.47%和96.50%。在基于K近邻、支持向量机和稀疏表示分类器的多分类器决策融合中，所提方法和直接进行决策融合的方法的识别率分别为97.10%和96.28%。实验结果充分证明了所提方法的有效性。     

Combining wavelet decomposition with machine learning to forecast gold returns

This paper combines the discrete wavelet transform with support vector regression for forecasting gold-price dynamics. The advantages of this approach are investigated using a relatively small set of economic and financial predictors. I measure model performance by differentiating between a statistically-motivated out-of-sample forecasting exercise and an economically-motivated trading strategy. Disentangling the predictors with respect to their time and frequency domains leads to improved forecasting performance. The results are robust compared to alternative forecasting approaches. My findings on the relative importances of such wavelet decompositions suggest that the influences of short-term and long-term trends are not stable over the full evaluation period.     

A spatial autoregressive stochastic frontier model for panel data incorporating a model of technical inefficiency

By integrating Battese and Coelli’s (1995) model and the spatial autoregressive model (SAR), a spatial autoregressive stochastic frontier model for panel data is developed. The main feature of this frontier model is a spatial lag term of explained variables and the joint structure of a production possibility frontier with a model of technical inefficiency. The model addresses both spatial dependence and heteroskedastic technical inefficiency. This study applies maximum likelihood methods considering the endogenous spatial lag term. The proposed model nests several existing models. Further, an empirical analysis using data on the Japanese manufacturing industry is conducted and the existing models are tested against the proposed model, which is found to be statistically supported. The findings suggest that estimates in the existing spatial and non-spatial models may exhibit bias because of lack of determinants of technical inefficiency, as well as a spatial lag. This bias also affects the technical efficiency score and its ranking.