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The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

As coaching assumes an increasingly critical role in satisfying employees' demands for growth, the function of coaching has progressively shifted towards direct supervisors. This study seeks to investigate the distinct effects of managerial coaching behaviors on employee outcomes from an emotional perspective. Specifically, we aim to explore whether leaders' encourage-to-explore and guide-to-learn behaviors impact employees' creativity and performance through discrete emotional mechanisms upon appraisal theory of emotion.

We conducted two studies to test our proposition. In study 1, an experiment using coaching scenarios was performed with 128 students majoring in management. In study 2, data were collected from 311 supervisor-subordinate dyads.

The results indicate that encourage-to-explore behaviors are positively related to employee creativity by fostering feelings of inspiration, and guide-to-learn behaviors are positively related to employee performance by alleviating anxiety. These findings suggest that different leaders’ coaching behaviors influence employee outcomes through different emotional processes. The theoretical and practical implications of the findings are also discussed.

These findings suggest that different leaders’ coaching behaviors influence employee outcomes through different emotional processes. The theoretical and practical implications of the findings are also discussed.

To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.

Using a sample of listed firms from 2010 to 2020, this paper exploits text analysis of annual reports to construct a proxy for enterprise digital development.

Results show that enterprise digital development not only improves their own capacity utilization but also generates a positive spillover effect on the capacity utilization of peer firms and firms in the supply chain. Next, based on the incomplete information about market demand and potential competitors when making capacity-building decisions, the mechanism tests show that improving the accuracy of market forecasts and reducing investment surges are potential channels behind the baseline results. Cross-sectional tests show the baseline result is more pronounced when industries are highly homogeneous and when firms have access to less information.

This paper contributes to the research related to the economic consequences of digital development. With the development of the digital economy, the real effects of enterprise digital development have also triggered extensive interest and exploration. Existing studies mainly examine the impact on physical operations, such as specialization division of labor, innovation activities, business performance or total factor productivity (Huang, Yu, & Zhang, 2019; Yuan, Xiao, Geng, & Sheng, 2021; Wang, Kuang, & Shao, 2017; Li, Liu, & Shao, 2021; Zhao, Wang, & Li, 2021). These studies measure the economic benefits from the perspective of the supply (output) side but neglect the importance of the supply system to adapt to the actual market demand. In contrast, this paper focuses on capacity utilization, aimed at estimating the net economic effect of digital development by considering the supply-demand fit scenario. Thus, our findings enrich the relevant studies on the potential consequences of digital development.

This paper examines the direct and indirect effects of CEO intellectual capital on sustainable growth of small and medium-sized enterprises (SMEs) in China.

It adopts a quantitative approach based on 3,474 unbalanced panel data in 836 Chinese listed SMEs from 2008 to 2017.

The findings reveal a significant positive relationship between CEO intellectual capital and sustainable growth of SMEs. The findings also reveal that dual innovation (exploitative innovation and exploratory innovation) has a partial mediating effect on the relationship.

It further provides an original contribution to identifying and testing the mediating effect of dual innovation on the relationship between CEO intellectual capital and sustainable growth of SMEs.

In contrast to most of the extant literature, which considers intellectual capital as a whole at the organizational level or focuses on employee intellectual capital, this paper highlights the role of CEO intellectual capital for SMEs’ growth. It provides an original contribution to identifying and testing the mediating effect of dual innovation on the relationship between CEO intellectual capital and sustainable growth of SMEs.

This study explores the extent of undergraduate students' engagement in interdisciplinary learning experiences across their academic journey and its potential correlation with elevated levels of self-efficacy in learning. Furthermore, the research investigates how the clarity of career decisions and future goals contributes to the perception of relevance, value and alignment of interdisciplinary learning experiences among undergraduate students.

Data were collected using a self-report questionnaire in a longitudinal survey administered annually to undergraduate students at a university in northern Taiwan over four waves from 2018 to 2021. The sample analyzed for this study consisted of 123 undergraduate students who willingly and continuously participated in the research throughout the specified period.

The results showed that self-efficacy within interdisciplinary learning experiences could be classified into three clusters: high efficacy, moderate efficacy and fluctuating efficacy. The determinants influencing these clusters include career decisions and years spent in university. Undergraduate students who have determined their career decisions and are in their latter two years of undergraduate studies demonstrate higher self-efficacy in interdisciplinary learning. Conversely, students who have yet to determine their career decisions exhibit a fluctuating pattern of self-efficacy across the three interdisciplinary learning categories.

Two key limitations of this research include a small sample size and a confined university-specific context, potentially constraining the applicability of the results to a broader population.

This study contributes to the interdisciplinary learning experience in higher education by explaining the significance of undergraduates' self-efficacy and career-related factors. Whereas most research has focused on the effects of self-efficacy, this study investigated the factors that influence undergraduates' self-efficacy.

In the digital age, personalized services and accurate recommendations enhance the customer experience and streamline shopping. However, increasing concerns about personal privacy have led to resistance from consumers, necessitating a balance between providing high-quality online services and safeguarding personal data. The aim of this paper is to offer a comprehensive review of the fragmented literature on consumer privacy decision-making and to identify key issues worth exploring in future research.

Although previous studies have analyzed the antecedents and outcomes of privacy decisions, they have often been conducted in a fragmented manner. There remains a lack of a holistic understanding of the factors influencing privacy decisions, including their boundaries. Therefore, we build on the Theory of Planned Behavior to combine consumer privacy decision-making with a graphically conceptual framework used in a similar scoping methodology. We attempt to dissect the antecedent, moderator and outcome variables that influence consumer privacy decision-making, ultimately providing a comprehensive framework for understanding these dynamics.

Based on the Theory of Planned Behavior, we analyze the entire process of consumer privacy decision-making in terms of antecedent, moderating and outcome variables. The results indicate that consumer privacy decision-making is not an isolated behavior or a single choice but a complex, multi-level dynamic process. The factors influencing consumer privacy decisions primarily encompass five aspects: individual characteristics, information, organization, platform and interaction management, leading to various outcomes in both behavioral and perceptual dimensions. Furthermore, the process is constrained by multiple moderating variables, such as information sensitivity, platform knowledge and prior experience.

We build on the Theory of Planned Behavior to combine consumer privacy decision-making with a graphically conceptual framework used in a similar scoping methodology. We dissect the antecedent, moderator and outcome variables that influence consumer privacy decision-making, aiming to provide a comprehensive framework for understanding these processes.

The purpose of this paper is to study the importance of image data in hotel selection-recommendation using different types of cognitive features and to explore whether there are reinforcing effects among these cognitive features.

This study represents user-generated images “cognitive” in a knowledge graph through multidimensional (shallow, middle and deep) analysis. This approach highlights the clustering of hotel destination imagery.

This study develops a novel hotel selection-recommendation model based on image sentiment and attribute representation within the construction of a knowledge graph. Furthermore, the experimental results show an enhanced effect between different types of cognitive features and hotel selection-recommendation.

This study enhances hotel recommendation accuracy and user satisfaction by incorporating cognitive and emotional image attributes into knowledge graphs using advanced machine learning and computer vision techniques.

This study advances the understanding of user-generated images’ impact on hotel selection, helping users make better decisions and enabling marketers to understand users’ preferences and trends.

This research is one of the first to propose a new method for exploring the cognitive dimensions of hotel image data. Furthermore, multi-dimensional cognitive features can effectively enhance the selection-recommendation process, and the authors have proposed a novel hotel selection-recommendation model.

The inclusion of esports as an official event in the Hangzhou Asian Games is an important step towards the institutionalisation of esports. The significance of this event marks that Asia once again takes a lead in the global esportisation. This chapter investigates a series of history events in the inclusion process of esports into the comprehensive Games in Asia using process sociology and actor network theory (ANT). This study will analyse the type characteristics of esports events in Hangzhou Asian Games, whilst examining how key stakeholders' interact and balance in the network composed of international sports organisations, host of the event, emerging esports organisations and esports game companies. The chapter also examines the functions of global game industrial economic geography, local cultural politics, esports geopolitics and Olympic values in esports sportization, aiming to reveal the implications of esports inclusion in the Asian Games on the debate of whether esports meets the criteria to be classified as a ‘sport’ and its enlightenment of digital strategy to the inclusion esports in the Olympics.

Digitalization and supply chain collaboration are central to the successful servitization of manufacturing firms. However, how digitalization interacts with supply chain structure to affect servitization decisions in manufacturing firms has been understudied. In this study, we bridge resource dependence theory (RDT) and information processing theory (IPT) to examine how supply chain concentration interacts with digitalization to affect servitization decisions in manufacturing firms.

We tested the hypotheses using a panel dataset of 1,261 publicly listed machinery manufacturing firms in China. We addressed the endogeneity concerns using the control function approach and conducted multiple tests to ensure the robustness of the results.

We find that both supplier and customer concentration are negatively related to servitization, indicating that concentrated supplier and customer bases are hindrances to manufacturing servitization. Digitalization weakens the negative impact of customer concentration on servitization, but it strengthens the negative impact of supplier concentration on servitization.

The findings extend our understanding of supply chain structure and digitalization as determinants of servitization. This research also offers a nuanced view of how digitalization mitigates the negative impacts of supply chain concentration.

This study aims to explore scientific discourses on vaccination in YouTube comments using the Connectivism theory as a foundational guide in the inquiry of understanding knowledge seeking and sharing. The authors sought to understand how individuals share and seek information by using external sources through URL links to validate their arguments.

Using content analysis, the authors extracted and analysed 584 random comments with URL links from eight YouTube videos scientifically addressing the purpose of vaccines. The comments were coded by stance (pro, anti, and neutral) and the type of resource to observe how their links were used.

The results showed that URL links were composed of quotes, questions, and opinions. Many sources came from research papers, conspiracy websites, or other videos. Some of the comments did not accurately reflect the information from research papers and showed little scientific reasoning. This suggests the need for critical evaluation among individuals when finding information online.

The findings can be expanded to explore different types of information literacy practices in the comment section of social media for both informal and formal environments.

YouTube is useful in fostering scientific discourse and information-seeking/sharing practices among individuals. However, considering the inaccuracy of content deliverance, educators and individuals will need to consider how to teach/conduct information literacy skills when implementing social media for educational purposes.

Only a few studies have conducted research on comments using URL links, the originality of sources and how the sources were used in argumentation.