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This study aims to increase the novelty of clothing design and fabric texture. The element library that can be used for design is systematically summarized. The element database can also be continuously filled according to the existing logic to realize the diversity of design. Improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. And verify the feasibility of the simulation software to assist pleated clothing design.

Firstly, according to the logical framework of origami theory, different innovative designs and combined designs are made for the basic units of hyperbolic paraboloid, and the element library that can be used for design is systematically summarized. This database can also be continuously filled according to the existing logic to realize the diversity of design. Secondly, it summarizes three methods of pleated element filling clothing – uniform filling method, the irregular filling method and geometric addition method – that improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. Finally, the virtual software is used to simulate the effect of pleated clothing, and the three-dimensional simulation software 3dclo is used to make an empirical study on the application of hyperbolic paraboloid origami in clothing pleated design to verify the feasibility of the simulation software to assist pleated clothing design.

The theoretical results of hyperbolic paraboloid origami are collected and arranged to establish the element library of hyperbolic paraboloid origami. The results expand the designer's design ideas and auxiliary design technology and improve the design efficiency using a sample of hyperbolic paraboloid fabric to verify its practicability and three-dimensional clothing simulation software for exploring the design. The design rules of hyperbolic paraboloid clothing and the realization method of fabric are summarized, including the expansion and combing of elements, the application of size and shape and the method of combination.

Owing to the hyperbolic paraboloid origami’s length shrinkage, the loose computation of clothing requires targeted computation. This paper solely applies a paper model for estimating the shrinkage, and then we tend to subsequently explore the way to precisely compute the porosity, to determine the existing differences in the two-dimensional shrinkage of hyperbolic paraboloid creases of varying materials and to know if the clothing after large-scale production is capable of reaching the anticipated value.

The exploration of this experiment brings a new 3D experiment process to the design process.

This experiment brings new possibilities for the development of virtual fitting and virtual display in the industry.

This study combines hyperbolic paraboloid origami and clothing and combs and expands the unit with logical thinking to expand the designer's design ideas.

This research aims at understanding the routes public e-marketplaces take, in the motor carrier spot market, to generate trust among participants.

This work borrows cue signaling theory and an e-marketplace content analysis instrument from information systems literature. Our primary data captures differences in usage of a broad spectrum of cues between motor carrier spot e-marketplaces and a control sample.

Transportation e-marketplaces use graphical cues more frequently than the control sample, display these cues on their “operational path” (where users click to conduct transactions) and try to generate beliefs in participants' integrity and competence.

The motor carrier online spot market constitutes a relevant test bed for trust-related theories. Several levels of trust-building conceptualizations are tested; the cue level shows the most potential. This paper extends cue signaling theory in the transportation e-marketplace context and calls for further work on operational path cues to enrich swift trust theories.

This study helps e-marketplace designers by identifying essential and facultative cues for the motor carrier spot market.

Research on public spot e-marketplaces in the motor carrier context is scant. The context is described in detail to show its specificities in structures and behaviors. This helps to contribute to both practice and research. By evolving an existing research instrument from information systems literature, this study ensures replicability (problematic in academic research) .

This study aims to present a holistic synopsis of the current scientific structure of inbound tourism research and suggest further research directions.

A 30-year bibliometric analysis was conducted using the Web of Science Core Collection database through CiteSpace, covering 568 Social Sciences Citation Index articles.

This study systematically identifies the evolution of scientific structures and emerging research trends in the inbound tourism field. The findings show that: co-authorship patterns reveal a trend of international cooperation; the evolution of research themes is consistent with the development of the macro-environment and inbound tourism industry, the most recent focus being on sustainable development of destinations; varied multivariate data analysis methods dominate current empirical analysis; there exist three major research dimensions in the inbound tourism field; and unilateral political factors in destinations and bilateral linkage factors affecting inbound tourism demand have aroused research interest increasingly.

This study helps scholars and practitioners understand the current issues and needs of the inbound tourism industry and develops a future research agenda to promote the industry’s continuous development.

This study is the first attempt to provide insights into the theoretical development of inbound tourism over the past three decades from the perspective of a knowledge-based platform and further facilitate sustainable development of the industry.

本篇论文旨在全面地梳理入境旅游研究的整体知识架构, 进而提出未来研究方向。

本篇论文基于文献计量法, 运用CiteSpace对从Web of Science Core Collection数据库中检索得到的30年间568篇社会科学引文索引文献进行分析。

本篇论文系统地梳理了入境旅游领域知识架构的演化和新兴研究趋势, 填补了现有研究空白。结果揭示：（1）作者协作模式展现出国际化合作趋势; （2）入境旅游领域研究主题的演化趋势与宏观环境和国际旅游的发展阶段相吻合, 并且目的地可持续发展的研究成为热点; （3）目前实证分析主要采用各种多元数据分析方法; （4）入境旅游领域的研究可以归纳为三个主要研究方向; （5）单边政治因素和国家双边联系因素对入境旅游需求的影响逐渐成为近年研究热点。

本篇论文提出了未来研究方向, 有助于学界和业界人士掌握入境旅游产业的现状和需要, 从而推动该产业的可持续发展。

本篇论文首次从知识平台视角出发, 揭示了过去三十年间入境旅游的理论发展情况。

关键词 入境旅游, 文献计量法, 知识架构, 知识平台, 未来研究方向, CiteSpace

文章类型 ：研究型论文

El objetivo de este estudio es presentar una sinopsis holística de la actual estructura científica de la investigación turística entrante y sugerir nuevas direcciones de investigación.

Se condujo un análisis bibliométrico de 30 años utilizando la base de datos de recopilación de datos de la red de ciencias básicas a través de CiteSpace, que abarcó 568 artículos del Índice de Citación de Ciencias Sociales.

Este estudio identifica sistemáticamente la evolución de estructuras científicas y las tendencias de investigación emergentes en el campo del turismo entrante. Las conclusiones muestran que: i) las pautas de coautoría han revelado una tendencia a la cooperación internacional; ii) la evolución de los temas de investigación es coherente con el desarrollo del macro-entorno y de la industria del turismo entrante, centrándose más recientemente en el desarrollo sostenible de los destinos; iii) los diversos métodos de análisis de datos multivariados predominan en el análisis empírico actual; iv) existen tres grandes dimensiones de investigación en el ámbito del turismo entrante; y v) los factores políticos unilaterales en los destinos y los factores de vinculación bilateral que afectan a la demanda turística entrante han despertado un interés cada vez mayor a la investigación.

Este estudio ayuda a los académicos y los profesionales a entender problemas y necesidades actuales de la industria turística entrante y desarrollar una futura guía de investigación para fomentar el desarrollo continuo de la industria.

Este estudio es el primer intento de proporcionar información sobre el desarrollo teórico del turismo entrante en las últimas tres décadas, desde la perspectiva de la plataforma basada en un conocimiento y facilitar aún más el desarrollo sostenible de la industria.

Turismo entrante, Bibliométrica, Estructura científica, Plataforma basada en el conocimiento, Agenda de investigación futura, CiteSpace

Revisión bibliográfica

Socio-economic, health and environmental turbulences experienced during the past decades have caused major value chain disruptions, triggering multinational enterprises (MNEs) to rethink the footprints of their global operations and redesign for resilience. These developments have fueled a rapidly expanding scholarly literature on resilience. Yet, its conceptual understanding and practical utility remain highly fragmented, cross-disciplinarily disconnected and ambiguous. This study explores the intellectual structure of resilience research in business and management, relying on a systematic literature review approach based on bibliometric techniques and content analysis. A unique database consisting of 545 peer-reviewed articles published in 65 leading Academic Journal Guide (AJG) journals are analyzed. Based on the findings, three leading research communities dominate the resilience discussion in business and management. Moreover, the intellectual structure of the field through the most productive authors and top cited journal articles is discussed. Based on the results, five potential research avenues are suggested.

This study examines the relative effects of human capital (HC), social capital (SC) and psychological capital (PC) on hotel employees’ job performance.

A sample of 417 employees from seven five-star hotels in China was recruited for the study. Both exploratory and confirmatory factor analyses were used to confirm the quality of measurement structures. Stepwise regression was used to examine the relative effects of the three capitals on hotel employees’ job performance.

PC was found to be the strongest predictor of self-reported job performance (SJP) among the three capitals under investigation. Education and work experience in the HC domain affected SJP, whereas SC dimensions did not. However, only education and work experience in the HC domain were found to affect supervisor-rated job performance (RJP).

Given the impact of PC on hotel employee’s SJP, human resource managers should attend to this capital in staff recruitment, retention and training and development.

This study provides a holistic comparative lens to examine the relative contribution of the three capitals on hotel employees’ job performance. This will help to further clarify the roles played by each of the capitals in hotel service work, thus advancing the development of the theories underlying each of the three capitals.

The paper aims to explore how perceived prosumer content quality (PPCQ) and perceived interaction quality (PIQ) improve users' co-creation experiences and subsequently influence their co-creation intentions in the future. In addition, the paper examines users' prosumer ability into consideration.

The research model based on stimulus-organism-response (S-O-R) paradigm is developed to observe users' participation in value co-creation activities. In total, 318 valid responses were collected from a survey. Structural equation modeling was used to examine the model and Statistical Package for the Social Sciences (SPSS) PROCESS macro (Model 58) by Hayes was applied to investigate the moderating effect of prosumer ability in mediation paths.

It is observed that co-creation intention is determined by user-learning value, social-integrative value and hedonic value, which are influenced by PPCQ and PIQ. Besides, uses' prosumer ability moderates the indirect effects of PPCQ and PIQ on co-creation intentions through co-creation experiences.

The paper provides a prosumption perspective to explain users' co-creation intentions in social commerce and proposes the importance of user-learning, social-integrative and hedonic values in determining co-creation intentions.

Social commerce platforms can encourage prosumption activities and cultivate multi-level prosumers to achieve a win–win situation.

Little prior research has explicitly examined how and why users participate in value co-creation activities in social commerce from prosumption perspective. The current paper seeks to fill this gap and open new avenues for other value co-creation researchers.

To predict the passenger volume reasonably and accurately, this paper fills the gap in the research of quarterly data forecast of railway passenger volume. The research results can also provide references for railway departments to plan railway operation lines reasonably and efficiently.

This paper intends to establish a seasonal cycle first order univariate grey model (GM(1,1) model) combing with a seasonal index. GM (1,1) is termed as the trend equation to fit the railway passenger volume in China from 2014 to 2018. The railway passenger volume in 2019 is used as the experimental data to verify the forecasting effect of the proposed model. The forecasting results of the seasonal cycle GM (1,1) model are compared with the traditional GM (1,1) model, seasonal grey model (SGM(1,1)), Seasonal Autoregressive Integrated Moving Average (SARIMA) model, moving average method and exponential smoothing method. Finally, the authors forecast the railway passenger volume from 2020 to 2022.

The quarterly data of national railway passenger volume have a clear tendency of cyclical fluctuations and show an annual growth trend. According to the comparison of the modeling results, the authors know that the seasonal cycle GM (1,1) model has the best prediction effect with the mean absolute percentage error of 1.32%. It is much better than the other models, reflecting the feasibility of the proposed model.

As the previous grey prediction model could not solve the series prediction problem with seasonal fluctuation, and there are few research studies on quarterly railway passenger volume forecasting, GM (1,1) model is taken as the trend equation and combined with the seasonal index to construct a combination forecasting model for accurate forecasting results in this study. Besides, considering the impact of the epidemic on passenger volume, the authors introduce a disturbance factor to deal with the forecasting results in 2020, making the modeling results more scientific, practical and referential.

Forecasting outpatient volume during a significant security crisis can provide reasonable decision-making references for hospital managers to prevent sudden outbreaks and dispatch medical resources on time. Based on the background of standard hospital operation and Coronavirus disease (COVID-19) periods, this paper constructs a hybrid grey model to forecast the outpatient volume to provide foresight decision support for hospital decision-makers.

This paper proposes an improved hybrid grey model for two stages. In the non-COVID-19 stage, the Aquila Optimizer (AO) is selected to optimize the modeling parameters. Fourier correction is applied to revise the stochastic disturbance. In the COVID-19 stage, this model adds the COVID-19 impact factor to improve the grey model forecasting results based on the dummy variables. The cycle of the dummy variables modifies the COVID-19 factor.

This paper tests the hybrid grey model on a large Chinese hospital in Jiangsu. The fitting MAPE is 2.48%, and the RMSE is 16463.69 in the training group. The test MAPE is 1.91%, and the RMSE is 9354.93 in the test group. The results of both groups are better than those of the comparative models.

The two-stage hybrid grey model can solve traditional hospitals' seasonal outpatient volume forecasting and provide future policy formulation references for sudden large-scale epidemics.

This paper aims to explore the relationship between environmental regulation, technological innovation and manufacturing quality competitiveness to provide some references for emission reduction activities and improvements in manufacturing quality competitiveness to achieve environmental protection targets and economic development as part of a win–win situation.

Based on the structure-behavior-performance paradigm and Grabowski’s research, a new empirical model was provided. The software, EViews 6.0, was used for econometric analysis. Regression analysis was adopted to explore the three indicators’ relationships.

First, environmental regulation can promote technological innovation effectively. Second, compared with wasted gas and wasted solids, investment in wasted water control promotes Chinese technological innovation most. Third, the impact of research and development investment, induced by environmental regulation, on manufacturing quality competitiveness is greater than that induced by non-environmental regulation. Fourth, the impact of lagged two-phase environmental regulation on manufacturing quality competitiveness is similar to that of lagged one-phase regulation.

The issue that Chinese manufacturing is facing is how to manage the trade-off between pollution control investment and improved quality competitiveness. This study enables managers to understand how to better implement environmental regulation initiatives while achieving environmental protection and quality competitiveness as part of a win–win situation.

This paper analyzes the relationships between environmental regulation, technological innovation and manufacturing quality competitiveness for the first time and provides the basic argument for integrating Chinese environmental regulation with quality competitiveness to reveal the uniqueness of the circumstances determining China’s economic development.

This study examines the relationship between streamers' product descriptions, customer comments and online sales and focuses on the moderating effect of streamer–viewer relationship strength.

Between June 2021 and April 2022, the structured data of 965 livestreaming and unstructured text data of 42,956,147 characters from two major live-streaming platforms were collected for the study. Text analysis and regression analysis methods were employed for data analysis.

First, the authors' analysis reveals an inverted U-shaped relationship between comment length and product sales. Notably, comment volume and comment emotion positively influence product sales. Furthermore, the semantic richness, emotion and readability of streamers' product descriptions also positively influence product sales. Secondly, the authors find that the strength of streamer–viewer relationship weakens the positive effects of comment volume and comment emotion without moderating the inverted U-shaped effect of comment length. Lastly, the strength of streamer–viewer relationship also diminishes the positive effects of emotion, semantics and readability of streamers' product descriptions on product sales.

This study is the first to concurrently examine the direct and interactive effects of user-generated content (UGC) and marketer-generated content (MGC) on consumer purchase behaviors in livestreaming e-commerce, offering a novel perspective on individual decision-making and cue utilization in the social retail context.