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This study aims to develop a polymer cement-based waterproof coating with self-healing capability to efficiently and intelligently solve the building leakage caused by cracking of waterproof materials, along with excellent durability to prolong its service life.

Ion chelators are introduced into the composite system based on ethylene vinyl acetate copolymer emulsion and ordinary Portland cement to prepare self-healing polymer cement-based waterproof coating. Hydration, microstructure, wettability, mechanical properties, durability, self-healing performance and self-healing products of polymer cement-based waterproof coating with ion chelator are investigated systematically. Meanwhile, the chemical composition of self-healing products in the crack was examined.

The results showed that ion chelators could motivate the hydration of C₂S and C₃S, as well as the formation of hydration products (C-S-H gel) of the waterproof coating to improve its compactness. Compared with the control group, the waterproof coating with ion chelator had more excellent water resistance, alkali resistance, thermal and UV aging resistance. When the dosage of ion chelator was 2%, after 28 days of curing, cracks with a width of 0.29 mm in waterproof coating could fully heal and cracks with a width of 0.50 mm could achieve a self-healing efficiency of 72%. Furthermore, the results reveal that the self-healing product in the crack was calcite crystalline CaCO₃.

A novel ion chelator was introduced into the composite coating system to endow it with excellent self-healing ability to prolong its service life. It has huge application potential in the field of building waterproofing.

Tourism is a labor-intensive sector with extensive links to other industries and plays a vital role in creating employment. This study aims to propose a new framework to analyze the intrinsic structure of the employment effects of tourism-related sectors and their drivers.

This study uses input–output and structural decomposition analysis (IO-SDA) to quantify the employment effects of tourism-related sectors and their driving mechanisms based on China’s I-O tables of 2002, 2007, 2012 and 2017.

The results show a declining trend in the intensity of direct or indirect employment effects in tourism-related sectors, indicating a decreasing number of jobs directly or indirectly required to create a unit of tourism output. Among tourism-related sectors, catering has the highest intensity of indirect employment effects over the study period. Catering stimulates the indirect employment of agriculture, forestry, animal husbandry, fishery and food and tobacco manufacturing. The decomposition analysis reveals that final demand is the largest contributor to the increase in tourism employment, while technological progress shifts from an employment-creation effect in 2002–2012 to an employment-destruction effect in 2012–2017.

This study proposes a new analytical framework to investigate the structural proportional relationship between the direct and indirect employment effects of various tourism-related sectors and their dynamic changes. Doing so, it provides valuable references for policymakers to promote tourism employment.

旅游相关部门就业效应的驱动因素：以中国为例

摘要

旅游业是一个劳动密集型部门, 与其他国民经济部门有着广泛的联系, 这在创造就业方面发挥着重要作用。本研究旨在建立一个框架, 分析旅游相关部门就业效应的内在结构及其驱动因素。

本研究基于中国2002年、2007年、2012年和2017年的投入产出表, 引入投入产出和结构分解分析（IO-SDA）法量化了旅游相关行业的就业效应及其变化的驱动机制。

旅游相关部门的直接或间接就业强度呈下降趋势, 可见创造一个单位的旅游产出所需的直接或间接工作数量在减少。在旅游相关部门中, 餐饮部门在研究期内的间接就业效应强度最高, 主要带动了农、林、牧、渔业和食品及烟草制造业的间接就业。旅游就业效应变动的驱动因素中, 最终需求是旅游就业效应增加的最大贡献者, 技术效应从2002-2012年期间的就业创造效应转变为2012-2017年期间的就业破坏效应。

本研究建立了一个全新的分析框架, 可以揭示各个旅游相关部门的直接和间接就业效应之间的结构比例关系及其动态变化。对旅游就业效应的驱动因素分析可以为政策制定者提供针对性的建议, 以促进旅游就业。

Factores que impulsan los efectos del empleo en los sectores relacionados con el turismo: El caso de China continental

Resumen

El turismo es un sector intensivo en mano de obra con amplios vínculos con otras industrias y desempeña un papel vital en la creación de empleo. Este estudio propone un nuevo marco para analizar la estructura intrínseca de los efectos en el empleo de los sectores relacionados con el turismo y sus impulsores.

Este estudio utiliza el análisis de entrada-salida (input-output) y de descomposición estructural (structural decomposition) (IO-SDA) para cuantificar los efectos sobre el empleo en los sectores relacionados con el turismo y sus mecanismos impulsores, basándose en las tablas input-output de China de 2002, 2007, 2012 y 2017.

Los resultados muestran una tendencia a la baja en la intensidad de los efectos directos o indirectos del empleo en los sectores relacionados con el turismo, lo que indica un número cada vez menor de puestos de trabajo directos o indirectos necesarios para crear una unidad de producción turística. Entre los sectores relacionados con el turismo, la restauración tiene la mayor intensidad de efectos indirectos sobre el empleo durante el periodo de estudio. La restauración estimula el empleo indirecto de la agricultura, la silvicultura, la ganadería, la pesca y la fabricación de alimentos y tabaco. El análisis de descomposición revela que la demanda final es la que más contribuye al aumento del empleo turístico, mientras que el progreso tecnológico pasa de ser un efecto de creación de empleo en 2002-2012 a un efecto de destrucción de empleo en 2012-2017.

Este estudio propone un nuevo marco analítico para investigar la relación estructural proporcional entre los efectos directos e indirectos del empleo de varios sectores relacionados con el turismo y sus cambios dinámicos. De este modo, proporciona valiosas referencias para que los responsables políticos promuevan el empleo en el sector turístico.

The purpose of this paper is to provide reference for researchers by reviewing the research advances and trend of agricultural product price forecasting methods in recent years.

This paper reviews the main research methods and their application of forecasting of agricultural product prices, summarizes the application examples of common forecasting methods, and prospects the future research directions.

1) It is the trend to use hybrid models to predict agricultural products prices in the future research; 2) the application of the prediction model based on price influencing factors should be further expanded in the future research; 3) the performance of the model should be evaluated based on DS rather than just error-based metrics in the future research; 4) seasonal adjustment models can be applied to the difficult seasonal forecasting tasks in the agriculture product prices in the future research; 5) hybrid optimization algorithm can be used to improve the prediction performance of the model in the future research.

The methods from this paper can provide reference for researchers, and the research trends proposed at the end of this paper can provide solutions or new research directions for relevant researchers.

The selection of purchasing channels by wine consumers indirectly affects buying experience and satisfaction, therefore, it is of great practical significance to study consumers' preference on channel selection. The purpose of this study is to investigate the current state of consumer selection for purchasing channel and the corresponding influencing factors.

A total of 2,976 valid questionnaires were collected by convenience sampling from 34 provinces, municipalities and autonomous regions of China in 2020 via the Internet, yielding a response rate of 82.2%. A categorical statistical approach was used to understand consumer's selection for each channel. Besides, binary logistic regression model was used to analyze the factors affecting consumers' channel selection.

The results show that Chinese wine consumers' main purchasing channels are as follows: supermarket/mall, wine specialty stores, comprehensive e-business flagship stores, comprehensive e-business individual stores, restaurants and short video and live streaming platforms. Estimation results showed that among the 12 influencing factors in 4 categories, consumers' education and some other factors significantly influenced consumers' decision on wine purchasing channels.

Limited by time and experimental conditions, this study did not analyze the trend of wine consumers' purchasing channel selection. Future work would concentrate on multi-year data and conduct longitudinal comparative analysis.

This study innovatively subdivides the currently popular wine sales channels in Chinese market and conducts research related to consumer channel selection. The results of the study can provide reference for wine producers and distributors to update their strategic layout and also help various channels to understand the characteristics of their customer groups for targeted marketing.

This paper aims to investigate the fast attitude coordinated control problem for rigid satellite swarms with communication delays.

Based on behavior‐based control approach, the attitude control system is designed to guarantee that the attitude of the satellite swarm converge to a dynamic reference state in finite time. A fast sliding mode is developed to improve the convergence rate and robustness of the control system. All the effects of communication delays, parameter uncertainties and external disturbances are taken into account simultaneously, and the communication topology of the satellite swarm can be arbitrary types. Numerical simulations are provided to demonstrate the analytic results.

Despite the existence of communication delays, parameter uncertainties and external disturbances, the stability of the closed‐loop system can be successfully guaranteed and the proposed control strategies are effective to overcome these unexpected phenomena subject to arbitrary communication topology.

This paper introduces a fast terminal sliding mode control method which can guarantee the fast convergence of the attitude state of the satellite swarm in the presence of communication delays, switched communication topology, parameter uncertainties and external disturbances.

The purpose of this paper is to propose an optimized hybrid model based on artificial intelligence methods, use the method of time series forecasting, to deal with the price prediction issue of China’s table grape.

The approaches follows the framework of “decomposition and ensemble,” using ensemble empirical mode decomposition (EEMD) to optimize the conventional price forecasting methods, and, integrating the multiple linear regression and support vector machine to build a hybrid model which could be applied in solving price series predicting problems.

The proposed EEMD-ADD optimized hybrid model is validated to be considered satisfactory in a case of China’ grape price forecasting in terms of its statistical measures and prediction performance.

This study would resolve the difficulties in grape price forecasting and provides an adaptive strategy for other agricultural economic predicting problems as well.

The paper fills the vacancy of concerning researches, proposes an optimized hybrid model integrating both classical econometric and artificial intelligence models to forecast price using time series method.

Ready-to-drink (RTD) tea beverages are widely consumed worldwide and play a prominent role in people’s daily lives, yet few studies have investigated the motivation of RTD tea beverage consumers as well as their underlying attitudes and desires. The purpose of this paper is to explore why these attributes are motivational factors by focussing on the attributes of RTD tea beverage products that motivate consumers to purchase RTD tea.

The attribute-consequence-value model of the means-end chain approach was employed to investigate consumer motivations for purchasing RTD tea beverages. Data were collected through a qualitative face-to-face survey of 153 RTD tea beverage consumers in Taiwan.

The results indicate that consumers purchase RTD tea beverages because the taste, flavor, packaging, and ingredients (attributes) satisfy their desire to drink RTD tea and fulfill the benefits of being delicious to drink, possessing thirst-quenching properties, and possessing health-promoting properties (perceived consequences), thereby fulfilling their ideal goal of experiencing enjoyment (perceived product value).

The findings may serve as a reference for producers of RTD tea beverages regarding product development and marketing.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

The purpose of this paper is to examine the effect of hotel safety leadership on employee safety behavior during the COVID-19 pandemic, and the mediation role of belief restoration and the moderation role of perceived risk between safety leadership and behavior were also investigated.

The COVID-19 outbreak served as the background for a questionnaire survey of 23 hotels in China with 1,594 valid responses being received. The statistical analysis techniques used were exploratory and confirmatory factor analysis, correlation analysis, structural equation modeling and hierarchical regression.

The results showed that: hotel safety leadership positively affected employee safety behavior (compliance, participation and adaptation); belief restoration partially mediated the influence of safety leadership on safety behavior; and perceived risk negatively moderated the direct effect and the mediation effect of “safety leadership – belief restoration – safety behavior.”

The main limitation was that the questionnaires were collected with the same measurement system within a certain period of time (cross-sectional design). Then, future research should test and expand this conceptual model in different crises, business fields, theoretical orientation and cultural backgrounds.

Hotels should develop management strategies based on safety leadership and motivate and promote employee safety behavior from the four aspects of safety coaching, care, motivation and control.

This investigation expanded the research on the effectiveness of safety leadership and especially with respect to safety in the hospitality industry during a major global crisis. Also, the research conceptual model and variables contained therein are original contributions to the hospitality research literature.

The farm size-productivity relationship has long been the subject of debate among development economists. Few studies address this issue for China, and those that do only with outdated data sets poorly representing the current situation after the past decade of rapid change, which includes the rapid development of land rental markets, village labor out-migration and use of farm machines. Meanwhile, many studies have researched this relationship for Indian, which is undergoing similar changes except for the development of active land rental markets. The purpose of this paper is to measure the farm size-productivity relationship under the situations of rapid transformation in China and India.

Based on the data of 325 Jiangxi and 400 Allahabad rice farmers in 2011, the survey covered multiple plots of each household in one/multiple growing season(s). The authors use the production function approach and the yield approach, and control for farmland quality, imperfect factor markets, and farm size measurement error, to identify the farm size-productivity relationship.

The regressions show that land yields increase with plot size both by season and over the year in China. This may be one of the reasons that farm sizes are growing in some areas. In India, however, the inverse farm size-productivity relationship is observed by the study, despite recent changes. Moreover, land yields increase with farm machine use in both China and India. This result contributes to the debate over whether mechanization improves yields or just expands the land frontier.

The paper empirically estimates the farm size-productivity relationship under rapid agrarian transformation in both China and India based on a unique data set collected by the authors in a detailed primary survey. The paper considers measurement error in the analysis, which adds values to this type of analysis.