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Single-shot multi-category clothing recognition and retrieval play a crucial role in online searching and offline settlement scenarios. Existing clothing recognition methods based on RGBD clothing images often suffer from high-dimensional feature representations, leading to compromised performance and efficiency.

To address this issue, this paper proposes a novel method called Manifold Embedded Discriminative Feature Selection (MEDFS) to select global and local features, thereby reducing the dimensionality of the feature representation and improving performance. Specifically, by combining three global features and three local features, a low-dimensional embedding is constructed to capture the correlations between features and categories. The MEDFS method designs an optimization framework utilizing manifold mapping and sparse regularization to achieve feature selection. The optimization objective is solved using an alternating iterative strategy, ensuring convergence.

Empirical studies conducted on a publicly available RGBD clothing image dataset demonstrate that the proposed MEDFS method achieves highly competitive clothing classification performance while maintaining efficiency in clothing recognition and retrieval.

This paper introduces a novel approach for multi-category clothing recognition and retrieval, incorporating the selection of global and local features. The proposed method holds potential for practical applications in real-world clothing scenarios.

Based on social influence theory, this paper aims to explore the influence of academic entrepreneurs on team innovation activities. The innovation behavior of academic team members is the key behavior in academic entrepreneurial activities. As a special entrepreneurial group, academic entrepreneurs' political skills play an important role in stimulating team innovative behaviors.

This paper adopts a multi-level study design and takes as samples the paired data of 91 academic entrepreneurial teams (n = 475). Based on team cognition, it constructs a model of the influence mechanism of academic entrepreneurs' political skills on team innovation behavior and explores the mechanism of transactive memory system in this influence effect. The authors use HLM and PROCESS macro to test our multilevel model.

The results show that academic entrepreneurs' political skills positively impact team innovation behavior, and a transactive memory system plays a mediating role between them. Team psychological safety significantly enhances the positive relationship of both academic entrepreneurs' political skills and a transactive memory system with team innovation behavior. Moreover, with enhanced perceptions of team psychological safety, academic entrepreneurs' political skills are more likely to improve team innovation behavior through the transactive memory system.

The study explores the influence of transactive memory system on the relationship between academic entrepreneurs' political skills and team innovation behavior, with the team cognitive perspective derived from social influence theory. This provides authors with new insights on the complex dynamics at place in the team innovation process and offers implications for how we can fruitfully manage this process.

This study aims to examine the risk-resistant role of environmental, social and governance (ESG) performance in the capital market, focusing on an organizational standpoint. Furthermore, it aims to offer management decision advice to companies seeking protection against stock market risks. Conclusions obtained through this research have the potential to enrich the economic consequences of ESG performance, provide practical implications for enhancing corporate ESG performance, improving corporate information quality and stabilizing capital market development.

Based on the data of Chinese A-share listed companies from 2009 to 2020, this study examines the risk-resistant function of ESG performance in the capital market. The impact of ESG performance on management behavior is analyzed from the perspective of organizational management and the three mechanisms of pre-event, during the event and post-event.

This paper demonstrates that companies that effectively implement ESG practices are capable of effectively mitigating risks associated with stock price crashes. Heterogeneity analysis reveals that the inhibitory effect of ESG performance on stock price crash risk is more pronounced in nonstate-owned enterprises and enterprises with higher levels of marketization. After controlling for issues such as endogeneity, the conclusions of this paper are still valid. The mechanism analysis indicates that ESG performance reduces the risk of stock price crash through three paths of organizational management: pre-event, during the event and post-event. That is, ESG performance plays the role of restraining managers’ opportunistic behavior, reducing information asymmetry and boosting investor sentiment.

This paper provides new insights into the relationship between ESG performance and stock price crash risk from an organizational management perspective. This study establishes three impact mechanisms (governance effect, information effect and insurance effect), offering a theoretical basis for strategic corporate decisions of risk management. Additionally, it comprehensively examines the contextual differences in the role of ESG performance, shedding light on the specific domains where ESG practices are influential. These findings offer valuable insights for promoting stable development in the capital market and fostering the healthy growth of the real economy.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

Surface acoustic wave (SAW) sensors have attracted great attention worldwide for a variety of applications in measuring physical, chemical and biological parameters. However, stability has been one of the key issues which have limited their effective commercial applications. To fully understand this challenge of operation stability, this paper aims to systematically review mechanisms, stability issues and future challenges of SAW sensors for various applications.

This review paper starts with different types of SAWs, advantages and disadvantages of different types of SAW sensors and then the stability issues of SAW sensors. Subsequently, recent efforts made by researchers for improving working stability of SAW sensors are reviewed. Finally, it discusses the existing challenges and future prospects of SAW sensors in the rapidly growing Internet of Things-enabled application market.

A large number of scientific articles related to SAW technologies were found, and a number of opportunities for future researchers were identified. Over the past 20 years, SAW-related research has gained a growing interest of researchers. SAW sensors have attracted more and more researchers worldwide over the years, but the research topics of SAW sensor stability only own an extremely poor percentage in the total researc topics of SAWs or SAW sensors.

Although SAW sensors have been attracting researchers worldwide for decades, researchers mainly focused on the new materials and design strategies for SAW sensors to achieve good sensitivity and selectivity, and little work can be found on the stability issues of SAW sensors, which are so important for SAW sensor industries and one of the key factors to be mature products. Therefore, this paper systematically reviewed the SAW sensors from their fundamental mechanisms to stability issues and indicated their future challenges for various applications.

The purpose of this study is to investigate when and why supervisor negative feedback is associated with employees' job performance via two different pathways (i.e. emotion-focused coping and problem-focused coping) and to introduce proactive personality as a moderator.

Time-lagged data were collected using a field survey research design. Participants included 389 dyads of employees and their direct supervisors from five companies in China.

Supervisor negative feedback can lead to employees' emotion-focused coping, which in turn impairs their job performance. Meanwhile, supervisor negative feedback can trigger employees’ problem-focused coping, which subsequently promotes their job performance. Furthermore, proactive personality moderates the indirect effect of supervisor negative feedback on employee performance through emotion-focused coping.

This study explored the double-edged effects of supervisor negative feedback on employee job performance from a coping strategy perspective and investigated how proactive personality influences the choice of coping strategies.

The study delves into the influence of wear cycles on these parameters. The purpose of this paper is to identify characteristic patterns of σ_RS and ε_PEEQ that discern varying wear situations, thereby contributing to the enrichment of wear theory. Furthermore, the findings serve as a foundational basis for nondestructive and in situ wear detection methodologies, such as nonlinear ultrasonic detection, known for its sensitivity to σ_RS and ε_PEEQ.

This paper elucidates the wear mechanism through the lens of residual stress (σ_RS) and plastic deformation within distinct fretting regimes, using a two-dimensional cylindrical/flat contact model. It specifically explores the impact of the displacement amplitude and cycles on the distribution of residual stress and equivalent plastic strain (ε_PEEQ) in both gross slip regime and partial slip regimes.

Therefore, when surface observation of wear is challenging, detecting the σ_RS trend at the center/edge, region width and ε_PEEQ distribution, as well as the maximum σ_RS distribution along the depth, proves effective in distinguishing wear situations (partial or gross slip regimes). However, discerning wear situations based on ε_PEEQ along the depth direction remains challenging. Moreover, in the gross slip regime, using σ_RS distribution or ε_PEEQ along the width direction rather than the depth direction can effectively provide feedback on cycles and wear range.

This work introduces a novel perspective for investigating wear theory through the distribution of residual stress (σ_RS) and equivalent plastic strain (ε_PEEQ). It presents a feasible detection theory for wear situations using nondestructive and in situ methods, such as nonlinear ultrasonic detection, which is sensitive to σ_RS and ε_PEEQ.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0005/

The purpose of this study is to investigate the technology-focused and technology-supported dilemmas that firms have encountered and their digital orientation from a nuanced perspective to answer the following research questions: What digital orientations do companies take in launching digital initiatives? How does the choice between a proactive digital orientation (Pro-DO) and a reactive digital orientation (Rea-DO) influence firm value?

The authors adopted machine learning and a quantitative research approach using observations from China’s listed companies from 2010 to 2020 and applied statistical techniques and regression analysis to examine the effect of digital orientation alternatives on firm value.

The findings of this study indicate that firms with a Pro-DO exhibit a positive effect on firm value. In contrast, firms with a Rea-DO do not demonstrate the same positive relationship with firm value. Additionally, this study reveals that firms with better corporate governance practices and lower financing constraints are more responsive to the positive effects of Pro-DO on firm value.

We elucidate two primary perspectives of digital orientation: Pro-DO and Rea-DO. Additionally, we empirically showcase their nuanced influences on firm value, thereby enriching knowledge in the fields of strategic orientation and digital transformation. Moreover, our findings underscore the importance of corporate governance and financing constraints as moderators.

One of the simplest ways to improve the profitability of a business is by saving energy. Responding to recent calls to investigate the mechanism leading to individuals’ energy-saving behaviors in the workplace, this study aims to investigate combining person-environment (PE) fit theory with normative factors to understand employees’ decisions to engage in energy-saving activities.

The results of an online survey reveal that person-organization fit, person-job fit and moral norm significantly affect employees’ energy-saving intention.

Furthermore, the findings show that moral norm is the strongest predictor of employees’ willingness to save energy. The results also demonstrate the interrelated relationships between PE fit and normative factors.

The results contribute overall to a greater understanding of energy-saving practices in the organizational context. Apart from the theoretical contributions, the findings of the current investigation offer valuable practical insights for organizations and policymakers to promote energy conservation practices.

The main purpose of our study is to investigate the impact of daily leader humor behaviors on healthcare workers’ daily psychological state and behavioral outcomes.

Based on the conservation of resources (COR) theory, this study proposes that daily leader humor behaviors are positively related to healthcare workers’ daily positive affect, which in turn affects their next-day helping behaviors towards patients. These predictions hinge on healthcare workers’ difficulty in maintaining display rules. We conducted a lagged experience sampling methodology (ESM) survey of 621 complete daily observations from 93 healthcare workers who work in direct contact with patients at a large public hospital in China across consecutive 10 working days.

Results of multilevel path analysis demonstrate that daily leader humor behaviors are positively related to healthcare workers’ same-day positive affect, and this positive affect enhances their next-day helping behaviors towards patients. Furthermore, healthcare workers’ higher difficulty in maintaining display rules attenuates the benefits of daily leader humor behaviors.

Building on the COR theory and adopting a diary research design, this study shows daily fluctuations in leader humor behaviors and proposes a mechanism through which daily leader humor behaviors indirectly affect healthcare workers’ next-day helping behaviors. Thus, our study disclosed possible means for healthcare organizations to improve service quality.