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Facilitated by social media, employee activism is on the rise, often in response to organizations' own socially irresponsible behavior. Given that digital employee activism is a vital yet underexplored research arena, the purpose of this study is to propose and test a theoretical model for understanding this phenomenon.

A survey was launched on Dynata, a US-based consumer panel company. A total of 657 representative full-time employees working at different levels of positions participated the survey to indicate their perceptual and behavioral responses to organizational social irresponsibility.

Moral obligation was a significant factor in mediating the relationship between organizational social irresponsibility and digital employee activism. Ideological psychological contract adds supplemental weights moderating the mediation effect on digital employee activism.

This study, based on social regulation theory, explores the rise of employee activism in response to organizations’ socially irresponsible behavior. The study identifies moral obligation and ideological psychological contract as the driving forces behind digital employee activism. This study advances digital employee activism scholarship by incorporating the normative lens of moral obligation and ideological psychological contract.

This study aims to explore why Chinese consumers pay for digital content products by investigating the experiences of Chinese consumers living in first-tier and second-tier cities regarding paid digital knowledge products.

A total of 19 in-depth interviews were conducted to collect data, and the phenomenological reduction was adopted to analyze data.

This study reveals that Chinese consumers use paid digital knowledge products to alleviate stress and anxiety stemming from real-life competition and the fear of falling behind. While consumers acknowledge the limited assistance that paid knowledge products can offer, their acceptance and expectations of paid digital knowledge products remain positive.

Paid digital knowledge represents an innovative phenomenon, with few scholars outside China having studied it. This study contributes a conceptual framework to understand the motivations of Chinese consumers with high purchasing power residing in first-tier and second-tier cities to invest in digital content.

The purpose of this paper is to explore the changes of the scale of urban tourists in mainland China under the impact of COVID-19 and, specifically, the following questions: how did the scale of domestic tourists change nationwide and in the seven geographic regions? What are the differences in the changes among the seven geographic regions? What are the changes in the hot spot areas and spatial clustering of domestic tourists across the country?

Using the data of domestic tourist arrivals in 337 cities in mainland China from 2018 to 2021, this research analyzes the absolute differences and relative differences in the scale of domestic tourists nationwide and in seven geographic divisions with the help of indicators such as range analysis, standard deviation, coefficient of variation and Herfindahl–Hirschman Index and explores the changes in the hot spot areas and spatial concentration degree of the spatial scale of domestic tourists nationwide under the influence of the epidemic using kernel density analysis and spatial auto-correlation analysis.

The absolute differences in all seven geographical divisions continue to increase during 2018–2021. The domestic tourism in southwest China is extremely uneven. Absolute differences in the northwest and northeast regions are relatively small, and the development in attracting domestic tourists is more balanced. Relative differences in southwest China are comparatively large, with the trend of uneven development being obvious. The northeast, northwest and eastern regions of China are small, and the development is more balanced. The popularity of domestic tourism in the Beijing–Tianjin–Hebei region, as well as the Yangtze River Delta region, continues to decline and then pick up in 2021. The inland southwest region became a new domestic tourism hot spot in 2021. The size of domestic tourists from 2018 to 2021 in mainland China cities shows a significant positive spatial correlation, and there is a spatial agglomeration phenomenon, but some regional agglomeration types change from 2018 to 2021.

The impact of the epidemic on the number and spatial scale of domestic tourism in China has been clarified, which makes up for the comparison of domestic tourism changes before and after the epidemic. A clear understanding of the changes in the number and spatial scale of domestic tourists in different regions after the epidemic is conducive to the development of domestic tourism revitalization strategies in accordance with the actual situation of each province and promotes the internal circulation of Chinese tourism.

This paper tries to clarify the quantitative scale of domestic tourism in different regions after the epidemic, which is conducive to the development of domestic tourism revitalization strategies in cities in different regions according to regional characteristics and the actual situation of each province and to promote the healthy operation of the internal circulation of tourism in China. This paper also tries to show the changes of domestic tourism market hot spots, agglomeration conditions changes before and after the outbreak and the clarity of tourists’ preference space changes.

Scale of domestic tourists; Absolute difference; Relative difference; Spatial hot spot distribution; Spatial agglomeration change

本文旨在探寻疫情影响下中国大陆城市游客规模演化规律, 具体而言, 疫情影响下, 全国及七大地理分区的国内游客量规模变化如何？七大地理地区的变化有何差异？以及疫情影响下, 全国国内游客空间规模的热点区域和空间集聚程度有何变化？

利用2018-2021年中国大陆337各城市的国内游客量数据, 借助极差、标准差、变异系数、赫芬达尔指等指标分析全国及七大地理分区国内游客规模的绝对差异和相对差异; 借助核密度分析、空间自相关分析等ArcGIS分析工具, 探寻疫情影响下全国国内游客空间规模的热点区域和空间集聚程度的变化情况。

①绝对差异方面, 七大地理分区的绝对差异均持续增大。西南地区的游客量的绝对差异巨大, 国内游发展极不均衡。西北地区、东北地区绝对差异相对较小, 在吸引国内游客方面发展较为均衡。②相对差异方面, 西南地区的国内游发展相对差异较大, 发展不均衡趋势明显; 东北地区、西北地区、华东地区的国内游发展相对差异较小, 发展较为均衡。③热点区域变化方面, 京津冀地区、长三角地区的国内旅游热度持续下降, 在2021年有所回升; 内陆西南地区在2021年成为新的国内游热点区域。④2018年至2021年城市国内游客量规模均呈现出显著的空间正相关的关系, 存在着空间集聚现象, 但部分区域集聚类型在2018到2021年间发生变化。

①理论意义：明晰了疫情对中国国内旅游人次的数量规模和空间规模的影响, 弥补了当前疫情前后国内旅游业变化对比的研究; 阐明了疫情前后中国城市国内游客空间格局的变化, 拓展了研究情景, 丰富了中国旅游业时空变化的相关研究。②实践意义：明晰了疫后不同地区国内旅游人次的数量规模和空间规模变化情况, 以及国内旅游市场热点变化和游客空间偏好变化, 有利于各地区城市对症下药, 制定符合各省份实际情况的国内旅游业振兴策略, 促进中国旅游业内循环。

The purpose of this paper is to study the impact of different types of textures on the friction lubrication performance of cylindrical roller bearings.

In the present study, the composite texture hydrodynamic lubrication model that takes into account the effects of surface roughness is established, and the Reynolds equation for the oil film is numerically solved using the finite difference method. The study investigates the oil film carrying capacity and maximum pressure of bearings under two different arrangements of four composite textures and conducts a comparative analysis of the oil film characteristics under various texture parameters and surface roughness levels.

When the roughness of the inner texture surface and the contact surface are equal, the bearing capacity of the composite texture is intermediate between the two textures. The impact trend of surface roughness on fluid dynamic pressure effects varies with the type of composite texture; the internal roughness of the texture affects the micro-hydrodynamic pressure action. Composite textures with different depths exhibit improved bearing capacities; elliptical cylindrical parallel and elliptical hemispherical parallel textures perform better when their area densities are similar, while other types of composite textures show enhanced bearing performance as the ratio of their area densities increases.

This paper contributes to the theoretical investigations and analyses on designing the textured rolling bearings with high lubrication performance.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2024-0050

This article aims to develop and validate a theoretical model via survey data to identify the affordances and challenges influencing metaverse adoption. We specifically examine the impact of immersion on users' adoption decisions and identify which affordances predict this immersion. Additionally, this paper assesses the importance of perceived risks in users' decision-making processes regarding future metaverse engagement.

Using regression models applied to 198 survey responses, we tested our proposed model. To deepen our insights, we also conducted a qualitative analysis.

The findings confirm that users' perceptions of immersion and perceived risks are critical determinants in adoption decisions. Social presence, influenced by factors such as ubiquity and interoperability, emerges as a key component of immersion. From the qualitative data, we identified two potential strategies to enhance metaverse immersion: technical improvements and offline device-assisted strategies.

Our study contributes to the literature on information systems (IS) adoption and provides practical insights for practitioners on crucial considerations in metaverse design.

Market evaluation of products is the basis for product innovation, yet traditional expert-based evaluation methods are highly dependent on the specialization of experts. There exist a lot of weak expert-generated texts on the Internet of their own subjective evaluations of products. Analyzing these texts can indirectly extract the opinions of weak experts and transform them into decision-support information that assists product designers in understanding the market.

In social networks, a subset of users, termed “weak experts”, possess specialized knowledge and frequently share their product experiences online. This study introduces a comparative opinion mining framework that leverages the insights of “weak experts” to analyze user opinions.

An automotive product case study demonstrates that evaluations based on weak expert insights offer managerial insights with a 99.4% improvement in timeliness over traditional expert analyses. Furthermore, in the few-shot sentiment analysis module, with only 10% of the sample, the precision loss is just 1.59%. In addition, the quantitative module of specialization weighting balances low-specialization expert opinions and boosts the weight of high-specialization weak expert views. This new framework offers a valuable tool for companies in product innovation and market strategy development.

This study introduces a novel approach to opinion mining by focusing on the underutilized insights of weak experts. It combines few-shot sentiment analysis with specialization weighting and AHP, offering a comprehensive and efficient tool for product evaluation and market analysis.

This study aims to examine whether and how the effect of intimate relationships with micro-influencers on customer behaviour is interrupted by external cues such as sponsorship disclosures and negative electronic word-of-mouth (eWOM).

The study worked with Instagram micro-influences to conduct a vignette survey with four experimental scenarios.

The benefits of parasocial relationships (PSR) in enhancing customer engagement (CE), brand preference (BP) and purchase intention (PI) cannot be sustained in the presence of external interruptive cues. For micro-influencers, whilst sponsorship disclosures do not moderate the influence of PSR, customers are considerably sensitive to negative eWOM or when the two cues co-occur.

This study focusses on micro-influencers and investigates whether the follower–micro-influencer bond can be moderated by external cues including sponsorship disclosure and negative eWOM.

In the context of the severe global challenges posed by climate and environmental issues, this paper aims to explore the connection between female Chief Executive Officers (CEOs) and the level of sustainable development in companies. This study aims to investigate the impact of female CEOs on corporate ESG performance and provide a detailed analysis of the underlying mechanisms.

This study uses a sample of listed companies from 2010 to 2021, as reported by Bloomberg. This study uses logit regression models to test hypotheses and conduct robustness tests using the generalized method of moments, propensity score matching and heckman two statge tests.

The research findings indicate that female CEOs can enhance a company’s ESG performance, primarily by elevating the level of green innovation and engaging in more philanthropic activities. When environmental uncertainty is high, the risk-averse attitude of female CEOs may diminish the enhancement of ESG performance. However, granting a higher proportion of equity to female CEOs incentivizes risk-taking, thereby strengthening the improvement of ESG performance. Further analysis reveals that the impact of female CEOs on ESG performance is more significant in non-state-owned enterprises, high-pollution industries, and companies with low financing constraints.

The authors have shown that two key ways in which female CEOs enhance a company’s ESG performance are by increasing the level of green innovation and assuming more social responsibility. Nonetheless, this remains a shortcoming of this work, opening a door for future research to examine and enrich. There may be other possible mechanisms explaining the influence of female CEOs on corporate ESG performance. More research is warranted about the CEO’s additional traits, which were not considered in this study but may have an impact on a company’s ESG performance. Finally, while the analysis has delved into the moderating effects of external factors such as environmental uncertainty and CEO ownership on the influence of female CEOs on corporate ESG performance, there is room for exploring whether other factors also play a moderating role in future studies.

First, the findings of this study highlight the beneficial societal and economic effects of choosing female CEOs. The inclination to take on social responsibility and care for the environment are both higher among female CEOs. Furthermore, the authors have also discovered that female CEOs possess unique advantages in promoting corporate sustainability and enhancing ESG standards. This can contribute to breaking down stereotypes about gender roles in the workplace. Finally, this research shows that organizational heterogeneity and market risks have an impact on female CEOs’ capacity to improve company ESG performance.

A significant innovation of this paper lies in its unique focus on the connection between female CEOs and corporate ESG performance, along with the underlying mechanisms. Against the backdrop of sustainable development, the paper integrates social gender theory, upper echelon theory and agency theory into a comprehensive framework, shedding light on the influence of female CEOs on ESG performance and the associated mechanisms.

This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.