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This study aims to use psychological contract theory to explore the substantial impact of illegitimate tasks on the well-being of hospitality employees. It also examines the mediating role of psychological contract breach and the moderating role of employee emotional intelligence within the proposed moderated mediation model.

Data were collected from 338 hospitality employees in Guangdong, China, and the hypotheses were examined through hierarchical regression analysis.

The results revealed that illegitimate tasks could negatively impact employee well-being through psychological contract breach. Furthermore, employee emotional intelligence was confirmed as a critical moderator that buffers the negative impact of illegitimate tasks on psychological contract breach.

This research offers novel insights into the dynamics affecting hospitality employee well-being by framing illegitimate tasks within psychological contract theory. It identifies the critical conditions under which employees’ well-being is impacted, thus broadening the understanding of employee–organization interactions.

Entrepreneurial passion has important implications for entrepreneurial success and psychological well-being. But their connections are complicated by the fact that three entrepreneurial passions (passion for inventing, passion for founding and passion for developing) can be combined differently according to their level and shape difference. A variable-centered approach cannot explain their relationship very well, by only focusing on the level difference and ignoring the different combination of entrepreneurial passion in subpopulations. The purpose of this study is to explore the function of entrepreneurial passion on entrepreneurial success and psychological well-being from a person-cantered approach.

In this study, the authors conducted latent profile analyses to identify different configurations of different entrepreneurial passions (passion for inventing, passion for founding, passion for developing) on two samples of Chinese students and entrepreneurs. Then in the sample of Chinese entrepreneurs, the authors utilized the DCON command in Mplus to provide comparisons among the profiles on entrepreneurial success and psychological well-being.

Based on identity theory, the authors found four entrepreneurial passion profiles across two samples—fully passionate, action-driven, interest-driven and dispassionate. Furthermore, the authors found that fully passionate entrepreneurs showed the highest level of entrepreneurial success, followed by action-driven, and then by interest-driven and dispassionate showed the lowest level. Action-driven entrepreneurs experienced the highest level of psychological well-being, followed by fully passionate entrepreneurs, then by interest-driven and dispassionate.

The results provide new insights into the nature and influence of entrepreneurial passion on entrepreneurial success and psychological well-being from a person-centered perspective.

The purpose of this study is to examine the impact of political relations on trade in strategic emerging industries (SEIs) in the Belt and Road initiative (BRI) associated countries. This investigation encompasses not only from the perspective of bilateral political relations but also the political intervention of third parties.

The study employs the temporal exponential random graphmodel to analyze the dynamic structure and influencing factor of SEIs trade network among 150 BRI-associated countries from 2015 to 2020.

The results indicate that the trade of SEIs in the BRI-associated countries exhibits a pattern of concentrated exporters and decentralized importers. Amicable bilateral political relations foster trade cooperations in SEIs, while political pressure from the United States has the opposite effect. Furthermore, compared with the influence of third parties, the BRI has created a more robust trade environment characterized by political mutual trust.

BRI-associated countries should strengthen their political communication, and endeavor to transform political consensus and shared vision into concrete collaborative projects, while mitigating geopolitical uncertainties through a sound risk evaluation system. Moreover, they should establish a more transparent and consistent consultation mechanism and leverage the BRI trade network to foster balanced and mutually beneficial partnerships that minimize rivalry and dependence on a single market.

This study goes beyond observed trade cost and incorporates the political factor into the determinants of the BRI trade, thereby expanding the theoretical boundaries of existing BRI research. Also, this study employs bilateral trade data to construct SEIs trade networks (SEITNs) along the BRI route. It provides a comprehensive understanding of the dynamic determinates of the SEITNs will provide valuable practical guidance for enhancing and expanding trade and cooperation among BRI-associated countries.

Short-form video advertisements have recently gained popularity and are widely used. However, creating attractive short video advertisements remains a challenge for sellers. Based on the visual-audio perspective and signaling theory, this study investigated the impacts of three visual features (number of shots, pixel-level image complexity and vertical versus horizontal formats) and two audio features (speech rate and average spectral centroid) on user engagement behavior.

We conducted a field study on TikTok. To test our various hypotheses, we used regression analysis on 2,511 videos containing product promotion information posted by 60 sellers between January 1, 2020 and November 20, 2021.

For visual variables, the number of shots and pixel-level image complexity were found to have nonlinear (inverted U-shaped) relationships with user engagement behavior. The vertical video form was found to have a positive effect on comments and shares. In the case of audio variables, speech rate was found to have a significant positive effect on shares but not on likes and comments. The average spectral centroid was found to have significant negative influences on likes and comments.

This study provides specific suggestions for sellers who create short-form videos to improve user engagement behavior.

This study contributes to the literature on short-form video advertising by extending the potential drivers of user engagement behavior. Additionally, from a methodological perspective, it contributes to the literature by using computer vision and speech-processing techniques to analyze user behavior in a video-related context, effectively overcoming the limitations of the widely adopted survey method.

This paper aims to address the limitations of current deep learning algorithms for sound source localization (SSL), which focus on a single feature and frequency scale, neglecting the integration of multi-scale information. The method developed in this study enhances localization accuracy by effectively using the spatial information and spectral diversity provided by microphone arrays.

The method is based on a multi-scale cross-short-time Fourier transform (STFT) complex-valued convolutional neural network (CCNN). It uses cross-STFT spectra at different scales to capture detailed acoustic information across various frequencies. The effectiveness of the algorithm was validated through both simulations and experimental studies.

Experimental results demonstrate that the proposed multi-scale cross-STFT CCNN not only outperforms the single-scale cross-STFT model but also delivers superior localization performance compared to other advanced methods, achieving consistently higher accuracy. The method shows excellent robustness across various signal-to-noise ratio (SNR) conditions and performs well even on imbalanced datasets, confirming its strong generalization capabilities.

This paper introduces a novel approach to SSL that integrates multi-scale information, addressing a key limitation of existing methods. The findings offer significant value to researchers and practitioners in the field of acoustic signal processing, particularly those focused on deep learning-based localization techniques.

From the perspective of local government tax administration, the impact of geographic dispersion on the corporate tax burden is investigated in this paper.

Using unbalanced panel data with a sample of listed companies from 2003 to 2020 in China, this paper focuses on the effect of geographic dispersion on corporate tax burden and the mechanisms.

It is found that corporate tax burden is positively related to geographic dispersion. It is also found that geographic dispersion affects the corporate tax burden by increasing the effort of local government tax administration. In addition, the relation between geographic dispersion and corporate tax burden is more pronounced for local SOEs prior to the implementation of Golden Tax Project III and in cases where local governments face stronger financial pressure to obtain revenue.

This study has important implications for the promotion of the coordinated development of the regional economy, as well as the legalization, modernization and informatization of tax administration.

This study explores the role of industrial co-agglomeration and digital economy in influencing the green high-quality development of the Yellow River National Cultural Park to provide countermeasures and suggestions for promoting the whole-area high-quality development.

This study is based on panel data from 56 cities from 2010 to 2022. First, a Super-SBM model is built to evaluate green high-quality development. Secondly, location entropy is used to measure industrial co-agglomeration and the entropy weight method is used to measure the digital economy. Finally, the panel Tobit model is used to analyze the impact of industrial co-agglomeration and digital economy on the green high-quality development of Yellow River National Cultural Park.

This study found that (1) industrial co-agglomeration has a negative implication in green high-quality development, while the digital economy boosts green high-quality development; (2) industrial co-agglomeration is a less critical dependency on the level of development of the digital economy in influencing green high-quality development, while the facilitating effect of the digital economy is more dependent on industrial co-agglomeration and (3) the trend of slow growth in industrial co-agglomeration and digital economy development, with significant regional differences in green high-quality development.

Undeniably, our study has several limitations. Firstly, as the study area only includes some cities in individual provinces, such as Qinghai, this paper only analyzes at the city level, which does not better reflect the differences between provinces; secondly, this study only adopts one method to determine the digital economy. In the future, other methods can be explored to measure digital economy; finally, in addition to the main role of digital economy and industrial co-agglomeration, other factors may also affect the green high-quality development of YRNCP. Future research should introduce other variables to improve the theoretical framework.

First, it provides countermeasures and suggestions for promoting the green high-quality development of YRNCP. Second, it helps to implement the new development concept, cultivate the new quality productivity of culture and the tourism industry and promote the green high-quality development of YRNCP. Third, it provides references to improve the management measures and related policies of the YRNCP more accurately and efficiently. Fourth, it helps to build a new development pattern and has important practical significance in promoting the high-quality development of the whole basin, protecting and inheriting the Yellow River Culture and helping the Chinese-style modernization and development, which are of great practical significance.

The research is carried out from the new perspective of industrial co-agglomeration and digital economy, which provides the theoretical basis and reference for solving the problem of green high-quality development of YRNCP. Second, it broadens the research idea of green high-quality development. Third, it quantitatively analyzes the impact of industrial co-agglomeration and digital economy on the high-quality development of YRNCP, deepening the research on the green high-quality development of YRNCP. Fourth, it helps to enrich and improve the theoretical research related to the national cultural park development and has positive significance in promoting the management and innovation of the cultural industry and the construction of related disciplines.

The paper’s findings illustrate the functional relationship of the digital economy and industrial co-agglomeration with green high-quality development and propose countermeasures to facilitate the high-quality development of the Yellow River National Cultural Park.

The purpose of this study is to design a long-term vibration monitoring system for track beams of suspended maglev trains to ensure safe and smooth operation of the trains.

The paper begins by focusing on the selection of hardware for the wireless monitoring and acquisition terminal and the circuit design. It connects to a wireless Access Point (AP) via Wi-Fi and utilizes the Transport Control Protocol (TCP) to upload the sensor data collected by the monitoring terminal to the upper computer. Additionally, the design includes software for the upper computer to parse the uploaded data packets and create a visualization interface, which is crucial for monitoring the vibrations of the track beams.

The vibration monitoring system developed in this study can display the data collected by the monitoring terminal in real time on the upper computer, while also allowing remote commands to query the status of the monitoring terminal. Due to the low-power design of the monitoring and acquisition terminal, it is capable of meeting the long-term vibration monitoring requirements for the track beams. Through precision testing of the monitoring terminal, we can ensure that the sensors meet experimental requirements, providing reliable data support for scientific research.

The vibration monitoring system presented in this paper integrates modern wireless communication technology and data visualization technology.

This study addresses the gap in understanding text analytics within the service domain, focusing on new service development to provide insights into key research themes and trends in text analytics approaches to service development. It explores the benefits and challenges of implementing these approaches and identifies potential research opportunities for future service development. Importantly, this study offers insights to assist service providers to make data-driven decisions for developing new services and optimising existing ones.

This research introduces the hybrid thematic analysis with a systematic literature review (SLR-TA). It delves into the various aspects of text analytics in service development by analysing 124 research papers published from 2012 to 2023. This approach not only identifies key practical applications but also evaluates the benefits and difficulties of applying text analytics in this domain, thereby ensuring the reliability and validity of the findings.

The study highlights an increasing focus on text analytics within the service industry over the examined period. Using the SLR-TA approach, it identifies eight themes in previous studies and finds that “Service Quality” had the most research interest, comprising 42% of studies, while there was less emphasis on designing new services. The study categorises research into four types: Case, Concept, Tools and Implementation, with case studies comprising 68% of the total.

This study is groundbreaking in conducting a thorough and systematic analysis of a broad collection of articles. It provides a comprehensive view of text analytics approaches in the service sector, particularly in developing new services and service innovation. This study lays out distinct guidelines for future research and offers valuable insights to foster research recommendations.

This paper aims to investigate the gear performance during meshing. The effects of line load, velocity and rough surfaces (kurtosis and skewness) on the lubrication characteristics and fatigue life of gears were analyzed.

In the mixed thermoelastohydrodynamic lubrication (TEHL) model, the distributions of pressure and film thickness are predicted using the Reynolds equation. The elastic–plastic rough contact model is used to calculate the contact force and area. To predict the fatigue life of the gears, the Dang–Van fatigue model is used to obtain the fatigue parameters under different line loads, velocities and rough surfaces.

The skewness of rough surfaces has a more significant effect on gear performance. In addition, according to fatigue parameters, it is found that when the load is too large, it leads to an increase in the probability of gear failure.

In this paper, a mixed TEHL model considering the effects of kurtosis and skewness is developed for the line contact to predict the mixed lubrication problem during gear meshing.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0356/