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Drawing on the social cognitive model of career self-management (CSM model) and deep learning theory, the authors' study aims to investigate the effect of knowledge sharing on career adaptability and explore how and when this effect occurs. The authors proposed a moderated sequential-mediation model linking knowledge sharing, knowledge depth, self-efficacy and career adaptability, moderated by reflective thinking.

The authors used a field survey involving 611 employees working in different enterprises in China to test the authors' predictions. For supplementary validation, the authors conducted a scenario-based experiment with a distinct sample of 148 employees from Chinese enterprises. The authors used hierarchical regression analysis, ANOVA analysis and moderated sequential-mediation analysis to test the hypotheses.

The results indicated a positive effect of knowledge sharing on career adaptability, sequentially mediated through knowledge depth and self-efficacy. Additionally, reflective thinking strengthened the positive effect of knowledge sharing on knowledge depth and further moderated the sequential mediating effect.

Previous research has predominantly focused on the perspective that individuals act as “recipients” from the environment in developing career adaptability. Instead, the authors adopt a “giving” perspective by investigating the influence of knowledge sharing on career adaptability, which advances the existing knowledge on the predictors of career adaptability.

The purpose of this paper is to examine the roles of one’s original family and current family in influencing his or her entering entrepreneurial endeavors. Specifically, individuals’ original family is also crucial for entrepreneurship, which has been neglected by prior studies to a large extent. Moreover, the authors argue that a good marital relationship between two parents within the original family could facilitate an entrepreneurial spirit by providing better family support, whereas a good relationship with one’s life partner or spouse within their current family could also increase the likelihood of entrepreneurial activities through reducing work stress.

The authors use two archival data sets: National Longitudinal Survey of Youth 1997 and 2013 Global Entrepreneurship Monitor Adult Population Survey to test whether a harmonious relationship between two parents or with life partner/spouse could encourage individuals to become an entrepreneur and whether family support and work conflict mediate such a relationship.

This study found that parents’ relationship in one’s adolescence provides individuals with more support, which leads to more entrepreneurial endeavors, whereas the conflicts between two parents will reduce their likelihood of initiating entrepreneurial activities. Besides, a good relationship with one’s life partner/spouse can release his/her work stress, which is also important for entrepreneurship development.

Different from the extant related research that focuses more on on-site predictors of entrepreneurship, the current study proposes factors from other life domains, including those in one’s adolescence, that can also influence and change individuals’ choice of entrepreneurial activities throughout their entire life. Harmonious family relationships (i.e. fewer family conflicts) are important for one to start a business, and family conflicts can reduce the likelihood of choosing entrepreneurship as the main occupation.

An anomaly of entrepreneurship literature was that, despite serious efforts required to manage a business, few studies had investigated entrepreneurs' health conditions at the end of their careers. This study investigated whether one's entrepreneurship in a lifetime enhanced their health after a career plateau.

The authors tested the main effect and mediating effects of entrepreneurs' life habits and self-esteem, respectively, using two longitudinal representative examples with 8,984 and 12,686 participants.

Results indicated that entrepreneurship significantly improved individuals' general lifetime health condition. Moreover, life habits (e.g. vigorous activities or sports, light activities, drinking habits and diet habits) and self-esteem significantly mediated the relationship between entrepreneurship and lifetime health. Entrepreneurs tended to have better health due to healthier life habits and higher self-esteem than salaried employees. In this paper, the authors also discussed theoretical and practical implications.

The authors proposed and found that, to counter the harsh requirements of entrepreneurial actions, entrepreneurs need to seek personal physical and psychological resources, and these resources can benefit their health even after decades.

This paper aims to propose that the extent to which activating self-identity increases resource-saving behavior varies across these three levels of self-identities. In particular, the authors hypothesize that activating relational or collective self-identity increases saving behavior more than activating individual self-identity does. Moreover, activating relational self-identity has a stronger impact on workplace saving behavior than activating collective self-identity does. In addition, the authors suggest that prosocial motive mediates the relationship between the three levels of self-identity and saving behavior.

Workplace saving behavior such as office supply savings could help save organizational resources and build more environmentally conscious organizations. Drawing from self-identity theory, the authors examine the influences of three types of self-identities (i.e. individual, relational and collective self-identities) on workplace resource-saving behaviors.

The results obtained from a field experiment conducted in a Chinese company and an online vignette study generally support the proposed hypotheses. The authors also discuss the theoretical and practical implications of the findings.

The authors contribute to the literature on saving behavior in organizations by studying an individual-level predictor from the perspective of self-identity and the research on self-identity and saving behavior by testing the mediating role played by prosocial motive. Based on the findings, the authors also propose some human resource policies to increase workplace saving behavior.

This paper aims to answer the following four research questions: Where do tourists gaze at the destination? What do tourists gaze at the destination? How do tourists gaze differently? Why do tourists gaze differently referring to relevant theory?

With a computer vision approach, this study illustrated a series of maps that reflect where and what do tourists gaze at and compared the differences in the visual perceptions among Asian, European and North American tourists in Hong Kong.

The findings confirm that the “tourist gaze” is influenced by geographical and cultural conditions. The conclusions provided three types of implementations for destination management strategies and advocated a high engagement with computer vision technology.

In theory, this study proves that the “tourist gaze” is influenced by geographical and cultural conditions. The study’s methodological contribution lies in applying advanced technology of visual content analysis for big data relevant to the issue of the tourist gaze. Practically, the finding that has not been achieved via previous questionnaire surveys will serve as a reference for tourism recommendations and precision marketing. In addition, its practical contribution is that it offers a means by which to explore tourists’ perceptions of destinations and understand the attractiveness of destinations to tourists.

研究一方面使用计算机视觉深入学习模型对游客照片内容进行识别, 比较了亚洲、欧洲和北美游客在香港不同空间场景的视觉感知差异。另一方面, 研究借助ArcGIS软件对游客凝视地点和内容差异进行了具体可视化分析。

这项研究有四个研究子问题：

• （1） 游客在哪里凝视？

• （2） 游客凝视了什么？

• （3） 游客凝视内容有什么不同？

  （4） 为什么游客凝视不同？

（1） 游客在哪里凝视？

（2） 游客凝视了什么？

（3） 游客凝视内容有什么不同？

（4） 为什么游客凝视不同？

不同游客在旅游目的地的“凝视”存在差异, 差异表征具体体现在地点选择和内容偏好等维度。同时, 研究结果显示计算机视觉技术在旅游研究领域呈现较好的应用潜力。

理论上, 本研究佐证了”游客凝视”受地理和文化条件影响的理论。技术上, 本研究探索了视觉分析技术在游客凝视议题上应用, 为旅游目的地感知评估提供了新的视角。应用层面, 研究结论为旅游目的地精准营销提供了参考。

Resumen

Con un enfoque de visión artificial, este estudio ilustra una serie de mapas que reflejan dónde y qué miran los turistas, y compara las diferencias en las percepciones visuales entre los turistas asiáticos, europeos y norteamericanos en Hong Kong.

El estudio tiene cuatro preguntas de investigación:

• (1) ¿Dónde miran los turistas en el destino?

• (2) ¿Qué miran los turistas en el destino?

• (3) ¿Cómo miran los turistas de forma diferente?

• (4) ¿Por qué los turistas miran de forma diferente en referencia a la teoría pertinente?

(1) ¿Dónde miran los turistas en el destino?

(2) ¿Qué miran los turistas en el destino?

(3) ¿Cómo miran los turistas de forma diferente?

(4) ¿Por qué los turistas miran de forma diferente en referencia a la teoría pertinente?

Las conclusiones confirman que la “mirada del turista” está influida por las condiciones geográficas y culturales. Las conclusiones aportan tres tipos de aplicaciones para las estrategias de gestión de destinos y abogan por un alto compromiso con la tecnología de visión artificial.

En teoría, este estudio demuestra que la “mirada del turista” está influenciada por las condiciones geográficas y culturales. La contribución metodológica del estudio radica en la aplicación de tecnología avanzada de análisis de contenido visual para big data relevante para el tema de la mirada del turista. En la práctica, los hallazgos que no se han logrado a través de encuestas anteriores servirán de referencia para las recomendaciones turísticas y el marketing de precisión. Además, su contribución práctica es que ofrece un medio para explorar las percepciones de los turistas sobre los destinos, y comprender el atractivo de los mismos para los turistas.

This study aims to build a research model from the perspectives of knowledge hiding and idea implementation to examine what factors influence idea implementation and the cross-level moderating role of team territory climate.

Data were collected from universities, 52 (R&D) teams in China via a two-wave survey. The final sample contained 209 team members and their immediate supervisors. Hierarchical linear modeling was used to test hypotheses.

The results indicated that individuals’ knowledge-hiding behavior had a significantly negative impact on idea implementation and creative process engagement, which played a mediating role. Team territorial climate played a cross-level moderating role between knowledge hiding and idea implementation. If team territorial climate was at a high level, then the negative connection between knowledge hiding and idea implementation would be weaker.

Under the perspective of territorial behavior in Chinese cultural, it can help to distinguish territorial behavior and be preventive at individual and team levels. This study not only enables managers to clearly understand the precipitating factors of idea implementation but also provides constructive strategies for alleviating the negative effects of knowledge territoriality on creative process engagement and idea implementation.

This study constructs a cross-level model to explore the relationship among knowledge hiding, creative process engagement and idea implementation at individual and team levels in the context of Chinese R&D enterprises. Additionally, the study analyzes the influence of territoriality on idea implementation under boundary conditions.

This study aims to conduct an empirical investigation of differing perceptions of nine types of urban space and nine visual elements among tourists in destination using a computer vision (CV) approach.

The data for this study was extracted from YFCC 100 M dataset. Nine types of urban space in Beijing were initially identified using a scene recognition model. Subsequently, a semantic segmentation model was applied, which yielded substantial evidence relating to nine visual elements that were used to elicit differing perceptions among tourists from different continents.

Tourists from three continents had different perceptions about corridors, old buildings, overlooks and traffic spaces, reflecting their cultural convention. Asians, Europeans and North Americans diversely gazed at the landscape element of buildings, foliage, sky and people in urban space. All those provided evidence to contribute to the tourist gaze theory's construction.

This study firstly depicted how tourists perceive the tourism symbol of urban space. The novel approach of employing two CV models offer methodological insights to tourism research relevant to visual perception.

游客对城市空间的感知:计算机视觉途径

本研究采用计算机视觉方法, 探究游客对旅游目的地九种城市空间类型及九种视觉元素的感知差异。

本研究数据提取自YFCC 100M图片数据集。首先, 利用场景识别模型识别了游客图片中的九种城市空间类型。其次, 应用语义分割模型识别了游客图片的九个视觉元素。这些分析结果被用于探究不同大洲游客的视觉感知差异。

来自不同大洲的游客对城市空间有不同的感知偏好。亚洲人更喜欢拍摄自己与著名的城市建筑, 欧洲人和北美人更喜欢自然元素, 如水、树叶和天空。不同大洲游客对视觉元素的偏好佐证了旅游凝视理论。

本研究选取了独特的城市空间为研究对象, 来验证游客凝视理论。此外, 两种计算机视觉模型为旅游研究提供了新的方法论视角。

La percepción de los turistas del espacio urbano: Un enfoque de vision artificial

Resumen

Los datos para este estudio se extrajeron del conjunto de datos YFCC 100 M. Inicialmente se identificaron nueve tipos de espacio urbano en Pekín mediante un modelo de reconocimiento de escenas. Posteriormente, se aplicó un modelo de segmentación semántica, que aportó pruebas sustanciales en relación con nueve elementos visuales que se utilizaron para suscitar percepciones diferentes entre turistas de distintos continentes.

El objetivo de este estudio es llevar a cabo una investigación empírica sobre las diferentes percepciones de nueve tipos de espacio urbano y nueve elementos visuales entre los turistas en destino, utilizando un enfoque de visión artificial (CV).

Los turistas de tres continentes tenían percepciones diferentes sobre los pasillos, los edificios antiguos, los miradores y los espacios de tráfico, lo que refleja su convención cultural. Los asiáticos, los europeos y los norteamericanos observaron de forma diversa el elemento paisajístico de los edificios, el follaje, el cielo y las personas en el espacio urbano. Todos ellos aportaron pruebas para contribuir a la construcción de la teoría de la mirada turística.

Este estudio describe por primera vez cómo los turistas perciben el símbolo turístico del espacio urbano. El novedoso enfoque de emplear dos modelos de vision artificial ofrece conocimientos metodológicos para la investigación del turismo relacionados con la percepción visual.

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

In many instances, the data exhibits periodic and trend characteristics. However, indices like the Digital Economy Development Index (DEDI), which pertains to science, technology, policy and economy, may occasionally display erratic behaviors due to external influences. Thus, to address the unique attributes of the digital economy, this study integrates the principle of information prioritization with nonlinear processing techniques to accurately forecast rapid and anomalous data.

The proposed method utilizes the new information priority GM(1,1) model alongside an optimized BP neural network model achieved through the gradient descent technique (GD-BP). Initially, the provincial Digital Economic Development Index (DEDI) is derived using the entropy weight approach. Subsequently, the original GM(1,1) time response equation undergoes alteration of the initial value, and the time parameter is fine-tuned using Particle Swarm Optimization (PSO). Next, the GD-BP model addresses the residual error. Ultimately, the prediction outcome of the grey combination forecasting model (GCFM) is derived by merging the findings from both the NIPGM(1,1) model and the GD-BP approach.

Using the DEDI of Jiangsu Province as a case study, researchers demonstrate the effectiveness of the grey combination forecasting model. This model achieves a mean absolute percentage error of 0.33%, outperforming other forecasting methods.

First of all, due to the limited data access, it is impossible to obtain a more comprehensive dataset related to the DEDI of Jiangsu Province. Secondly, according to the test results of the GCFM from 2011 to 2020 and the forecasting results from 2021 to 2023, it can be seen that the results of the GCFM are consistent with the actual development situation, but it cannot guarantee the correctness of the long-term forecasting, so the combination forecasting model is only suitable for short-term forecasting.

This article proposes a grey combination prediction model based on the principles of new information priority and nonlinear processing.