Search results

Most process FMEA systems in the market simply fill out the worksheet/form, and can not effectively express, organize, and utilize process failure knowledge of production process during process planning. This paper proposes a knowledge‐enriched representation model for enhancing process FMEA in process planning. This model can effectively represent the process FMEA knowledge other than specific process failure instances or data. Furthermore, in order to effectively utilize the previous process FMEA knowledge, an algorithm is proposed to calculate the similarity among process failure problems based on “concept distance”. A knowledge‐enriched process FMEA tool has been developed by adopting Web technique so as to provide cooperative process FMEA services for process planner on the Internet or Intranet.

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.

Although the prior literature has identified the relevance of dealer participation for multinational enterprises (MNEs), it is unclear whether such participation could also be an important means for local dealers to learn from MNEs. By adopting local firms’ viewpoint, our study draws on organizational learning theory to examine how local dealers benefit from their participation with foreign suppliers in Africa.

The empirical setting is a combinative dataset of secondary data and primary survey of 164 small- and medium-sized local dealers with nine subsidiaries of a Chinese motorcycle company in six countries of Sub-Saharan Africa.

This research shows that dealer participation is positively associated with dealer performance, and this positive effect is stronger when local dealers operate in regions with low government corruption and high government support. However, the positive relationship is weaker when local dealers use the local tongue extensively but becomes stronger when their foreign suppliers have a high dealer coverage.

By taking a local-participant perspective, our study extends the participation literature to show how firms from a resource-constrained region may benefit from their proactive participation with foreign counterparts. Additionally, we identify the boundary conditions of institutional factors and strategic choices of local dealers and foreign suppliers, providing a nuanced understanding of firm behaviors in complex and uncertain markets.

In this paper, an attempt is made to obtain buckling loads, ultimate bearing capacity and other required structural characteristics of grid structure panels. The numerical method for post-buckling behavior analysis of panels involving multiple invisible damages is also presented.

In this paper, two bidirectional stiffened composite panels are manufactured and tested. Multiple discrete invisible damages are introduced in different positions of the stringers, and the experimental and simulation investigation of buckling and post-buckling were carried out on the damaged stiffened panels.

The simulation load–displacement curves are compared with the experimental results, and it is found that the simulation model can well predict the occurrence of buckling and failure loads. The strain curve shows that the rate of strain change at the damaged site is greater than that at the undamaged site, which reflects that the debond is more likely occurred at the damaged site. The simulation verifies that the panel is usually crushed due to matrix compression and fiber–matrix shear.

In this paper, post-buckling tests and numerical simulations of bidirectional stiffened composite panels with impact damage were carried out. Two panels with four longitudinal stringers and two transverse stringers were manufactured and tested. The buckling and post-buckling characteristics of the grid structure are obtained, and the failure mechanism of the structure is explained. This is helpful for the design of wall panel structure.

This study aims to contribute novel insights into understanding and mitigating the harmful consequences of abusive supervision (AS) by examining the association between AS experiences, revenge, forgiveness, and the moderating role of emotional intelligence (EI). The key argument is that employees' EI can influence the AS experience through affective processes, countering supervisors' abusive behaviors.

A between-person scenario-based experiment was conducted with 366 participants divided into AS and control groups. The study explored the association between AS experience and revenge/forgiveness, mediated by core affect (valence and activation). EI abilities were measured as a moderator. Data analysis examined the relationships and interactions among AS, revenge/forgiveness, EI, and affective experiences.

The study reveals significant findings indicating that AS experiences were positively associated with revenge and negatively associated with forgiveness. The mediation analysis confirmed the role of core affect in these relationships. EI emerged as a moderator, shaping the association between AS experiences and revenge/forgiveness. Importantly, participants with higher EI exhibited lower revenge intentions, demonstrating the potential of EI to mitigate the adverse effects of AS. Unexpectedly, individuals with high EI also expressed fewer forgiveness intentions.

This study provides a comprehensive understanding of how employees can effectively counterbalance the impact of AS through higher levels of strategic EI. Examining core affect as a mediator offers novel insights into coping mechanisms in response to AS experiences and their consequences.

The study acknowledges several limitations, as the scenarios may only partially capture the complexities of real-life AS situations. The focus on a specific context and the sample characteristics limit the generalizability of the findings. Future research should explore diverse organizational contexts and employ longitudinal designs.

The findings have practical implications for organizations as enhancing employees' EI skills through training programs interventions and integrating EI into organizational culture and leadership conduct.

Line–cell conversion and rotation of operators between cells are common in lean production systems. Thus, the purpose of this study is to provide an integrated look at these two practices through integrating job rotation scheduling and line-cell conversion problems, as well as investigating the effect of rotation frequency on flow time of a Seru system.

First, a nonlinear integer programming model of job rotation scheduling problem and line–cell conversion problem (Seru-JRSP) was presented. Then, because Seru-JRSP is NP-hard, an efficient and effective invasive weed optimization (IWO) algorithm was developed. Exploration process of IWO was enhanced by enforcing two shake mechanisms.

Computations of various sample problems showed shorter flow time and less number of assigned operators in a Seru system scheduled through job rotation. Also, nonlinear behavior of flow time versus number of rotation periods was shown. It was demonstrated that, setting number of rotation frequency to one in line with the literature leads to inferior flow time. In addition, ability of developed algorithm to generate clusters of equivalent solutions in terms of flow time was shown.

In this research, integration of job rotation scheduling and line–cell conversion problems was introduced, considering lack of an integrated look at these two practices in the literature. In addition, a new improved IWO equipped with shake enforcement was introduced.

This study investigates the impact of customer stability on the cost of debt and the moderating effect of environmental uncertainty on the above relationship.

An empirical analysis based on the ordinary least squares (OLS) regression model is conducted using China’s A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2007 to 2021.

The results indicate that customer stability significantly inhibits the cost of debt, and the higher the environmental uncertainty, the more significant the inhibitory effect of customer stability on the cost of debt. The results of heterogeneity analyses indicate that the more intense the industry competition, the higher the customer concentration or the older the average customer age, the more significant the inhibiting effect of customer stability on the cost of debt.

This study highlights the importance of customer relationship management and supply chain risk management, which have both theoretical and managerial implications. Despite its contributions, this study has limitations, such as China’s institutional context limits, which the generalisability of our results, and the sample size for this study is small because of limitations in measuring customer stability.

Existing literature has not yet reached a consistent conclusion on how customer relationships affect the cost of debt, and such studies are mainly centered around perspectives such as customer concentration and the contagion effect of supply chains. This study constructs an indicator of customer stability using detailed information on the top five customers of China’s A-share listed companies and dynamically examines the impact of customer stability on the cost of debt, which expands the research on the influencing factors of the cost of debt, the economic consequences of customer stability and the theory of customer relationship management.

The purpose of this paper is to explore suzhi requirements and expectations to double-shouldered academics as middle-level cadres (双肩挑处级干部) in a Chinese higher education institute (HEI) as an initial step to examine the interplays between suzhi requirement and expectations and organizational operational mechanism in the Chinese context.

The study adopted an exploratory single-case approach for the study. In this study, 22 participants composed of middle-level cadres, other stakeholders at the university, college/department and business unit levels were interviewed.

Suzhi requirements for the cadres followed the Communist Party of China’s (CPC) guideline, the required de, neng, qin, ji and lian (德, 能, 勤, 绩, 廉) was abstract and vague. With the parallel systems, the CPC and administrative lines, there were discrepancies between the CPC required suzhi and those expected by the stakeholders. A social phenomenon, “official rank-oriented standard” (ORS, guan ben wei, 官本位), was found significantly intertwining with the self suzhi expectation of the cadres, unveiling a more complex dynamics than most research reported for the Chinese public sector organizations (PSOs).

With the initial qualitative findings unveiling suzhi as an organizational construct, this study informs future empirical research in the indigenous suzhi phenomenon in organizational setting. The conceptualized results of our study offer new insight for future indigenous Chinese management research in all PSOs including state-owned enterprises (SOEs).

As an initial step, this study endeavored to explore suzhi as an organizational construct in a Chinese HEI. The paper contributes to the literature by unveiling the complexity of PSOs in the interplays of dual management systems and ORS coupled with dual-role suzhi requirements for the cadres.

Due to the worldwide internet usage and online presence of businesses, digital marketing is an integrated part of the overall marketing strategy. One of the main investments in this field is the investment on more creative content that engages more potential customers. Online brand communities (OBCs) are used by businesses as a tool to have higher rates of engagement. Many researchers have developed customer engagement (CE) models to better understand it, but the transition economies like the countries of the Balkan are somehow left aside. Due to this identified gap in the literature, this paper aims to provide a model explaining the drivers and outcomes of CE, specifically on OBCs.

The research is based on primary data collected with an online questionnaire. Sample consisted of 764 respondents from four Balkan countries (Kosovo, North Macedonia, Albania and Montenegro). Data were analyzed using SPSS Statistics and IBM AMOS 26. To test the research model and hypotheses, confirmatory factor analysis and structural equation modeling were used.

First, the study found a positive impact of entertainment and customer satisfaction, and celebrities’ endorsement in CE. Furthermore, the results revealed a positive impact of CE on customer purchase intention and customer loyalty.

The research findings aim to help businesses of Balkan countries to better understand the importance and operation of CE in OBC.

This paper enriches the existing digital marketing literature of transition economies with a model of online CE.

This chapter elaborates on the role of clusters and innovational networks in Russia and interprets that the future growth of Russia’s economy depends on the development of clusters and innovational networks. We substantiated that clusters and innovational networks possess considerable potential in the sphere of provision of sustainable growth of Russia’s economy. Today, this potential is not used due to unequal distribution of clusters and innovational networks on Russia’s vast territory and due to their being at the initial stage of development – despite their prolonged period of existence. However, even in the current conditions, clusters and innovational networks make a significant contribution to Russia’s GDP (15.58% in 2018). By 2024, by implementing our described optimal scenario of clusters and innovational networks development, it would be possible to expand Russia’s GDP by 15 times, which will allow increasing the country’s GDP by 2.5 times. This positive effect will be achieved due to the provision of balance and stability of economic growth, which will make it more sustainable. Clusters and innovational networks should become a basis for sustainable growth of Russia’s economy. We recommend a scenario of sustainable growth based on a more equal distribution of clusters and innovational networks across Russia and a quicker development of clusters and innovational networks via more extensive involvement of private businesses.

This study explores how controlling leadership behaviors, such as authoritarian leadership and abusive supervision, affect police officers’ proactive behavior. Specifically, it examines how perceived powerlessness mediates the relationship between these leadership styles and officers’ proactive behavior.

We employed structural equation modeling with partial least squares analysis to test our hypotheses, utilizing a sample of police officers employed within a regional police institution in Indonesia.

The findings of this study indicate that both authoritarian leadership and abusive supervision have the potential to diminish or impede the proactive behavior of police officers by shaping their perception of powerlessness.

This study contributes to the broader understanding of how leader-controlling behaviors, such as authoritarian leadership and abusive supervision, impact the proactive behavior of police officers within the specific context of Indonesia.

In 2001, the US moved to regulate internal control reporting by management and auditors. While some jurisdictions have followed the lead of the US, many others have not. An important question, therefore, is the relevance of internal control to stakeholders. The more specific issue of the benefits of US-style regulation of internal control reporting is also topical. We review studies on the determinants of internal control quality and its economic consequences for stakeholders including investors, creditors, managers, auditors and financial analysts. We extend previous reviews by focusing on US studies published since 2013 as well as all non-US studies investigating IC quality including countries regulating IC disclosure as well as unregulated settings and both developed and developing economies. In doing so, we identify research questions where evidence remains mixed and new directions in which there are research opportunities.

Three main insights arise from our analysis. First, evidence on the economic consequences of internal control quality suggests that the quality of internal control can have a significant effect on decision making by users of financial information. Second, the results of research on the empirical association between ownership structure, certain board characteristics and internal control quality is generally mixed. Empirical evidence concerning the association between audit committee characteristics and internal control quality generally supports a positive and significant association. Finally, while studies in non-US jurisdictions are increasing, opportunities remain to explore the determinants and consequences of internal control in other jurisdictions. Our review provides evidence for policy makers of whether there are benefits from requiring management and auditors to report on internal control over financial reporting.

This study aims to investigate technology-based health and safety (H&S) management to control the spread of disease on construction sites using a partial least squares structural equation modelling (PLS-SEM) approach.

An extensive literature review is conducted to develop a conceptual framework. The variables identified from the literature review are included in a cross-sectional survey which gathered a total of 203 valid feedback. The variables for challenges are grouped under their relevant construct using exploratory factor analysis. Then, a hypothesized model is developed for PLS-SEM analysis using Smart PLS software. Later, the outcome of the model is further validated by nine construction experts using a semi-structured questionnaire survey.

The results rationalized the relationships between the COVID-19 H&S measures, challenges in implementing COVID-19 H&S measures on construction sites and the innovative technologies in transforming construction H&S management during the COVID-19 pandemic. The possible challenges that obstruct the implementation of H&S measures are highlighted. The potential technologies which can significantly transform H&S management by reducing the impact of challenges are presented.

The findings benefited the industry practitioners who are suffering disruption in construction operations due to the pneumonic plague.

By developing a conceptual model, this study reveals the contribution of technology-based H&S management for construction projects during the COVID-19 pandemic, which remains under-studied, especially in the context of the developing world.

Research into older adults' use of social media remains limited. Driven by increasing digitalisation in China, the authors focus on Chinese older adults (aged 60–75)’ use of WeChat.

This study used a qualitative interpretive approach and interviewed Chinese older adults to uncover their social practices of WeChat use in everyday life.

By using social practice theory (SPT), the paper unfolds Chinese older adults' social practices of WeChat use in everyday life and reveals how they adopt and resist the drastic changes in Chinese society.

The study contributes to new understandings of SPT from technology use by emphasising the dynamic characteristics of its three elements. The authors synthesise both adoptions and resistance in SPT and highlight the importance of understanding three elements interdependently within specific contexts, which are conditioned by structure and agency.

The current popular image processing technologies based on convolutional neural network have the characteristics of large computation, high storage cost and low accuracy for tiny defect detection, which is contrary to the high real-time and accuracy, limited computing resources and storage required by industrial applications. Therefore, an improved YOLOv4 named as YOLOv4-Defect is proposed aim to solve the above problems.

On the one hand, this study performs multi-dimensional compression processing on the feature extraction network of YOLOv4 to simplify the model and improve the feature extraction ability of the model through knowledge distillation. On the other hand, a prediction scale with more detailed receptive field is added to optimize the model structure, which can improve the detection performance for tiny defects.

The effectiveness of the method is verified by public data sets NEU-CLS and DAGM 2007, and the steel ingot data set collected in the actual industrial field. The experimental results demonstrated that the proposed YOLOv4-Defect method can greatly improve the recognition efficiency and accuracy and reduce the size and computation consumption of the model.

This paper proposed an improved YOLOv4 named as YOLOv4-Defect for the detection of surface defect, which is conducive to application in various industrial scenarios with limited storage and computing resources, and meets the requirements of high real-time and precision.

Consumer adoption of online shopping continues to increase each year. At the same time, online retailers face intense competition and few are profitable. This suggests that businesses and researchers still have much to learn regarding key antecedents of online shopping adoption and success. Based on extensive past research that has focused on the importance of various online shopping antecedents, this work seeks to provide an integrative, comprehensive nomological network.

The authors employ a mixed-methods approach to develop a comprehensive model of consumers online shopping behavior. To that end, in addition to a literature review, qualitative data are collected to identify a broad array of possible antecedents. Then, using a longitudinal survey, the model of consumer shopping intentions and behaviors is validated among 9,992 consumers.

The authors identified antecedents to online shopping related to culture, demographics, economics, technology and personal psychology. Our quantitative analysis showed that the main drivers of online shopping were congruence, impulse buying behavior, value consciousness, risk, local shopping, shopping enjoyment, and browsing enjoyment.

The validated model provides a rich explanation of the phenomenon of online shopping that integrates and extends prior work by incorporating new antecedents.

The assessment of risk to existing tunnels within the context of pit construction is influenced by a multitude of factors. The conventional fuzzy analytic hierarchy process (FAHP) method may lack precision due to its inability to incorporate the inherent randomness associated with numerous risk factors. To enhance the precision of risk evaluation for existing tunnels, this research introduces an improved FAHP approach grounded in cloud modeling theory.

We developed a risk assessment index system for existing tunnels, categorizing risk sources into three areas: hydrogeological conditions, foundation pit construction and tunnel structural bearing capacity. The system includes 11 evaluation indicators linked to these sources, with defined risk level thresholds for each. Using the cloud model, we calculated the membership degree of these indicators to risk levels, replacing traditional membership function formulas. The cloud model’s three digital characteristics (Ex, En and He) account for the randomness and ambiguity between qualitative descriptions and quantitative values, enhancing assessment accuracy. We applied hierarchical analysis to determine the weights of each risk factor and combined these with the membership degrees to evaluate overall risk levels. Engineering applications and model comparisons confirmed the method’s reliability, while sensitivity analysis identified key risk indicators affecting evaluation outcomes, allowing for targeted risk control measures to safeguard existing tunnels during foundation pit construction.

The evaluation results of engineering applications show the same results with the traditional FAHP method, which proves the reliability of the improved method. Furthermore, when comparing the evaluation result vectors between the two methods, it is observed that the outcomes of the improved method are more concentrated on a specific risk level compared to the traditional FAHP. This concentration mitigates the potential for bias in the evaluation results, thereby enhancing their accuracy. Through sensitivity analysis, four indicators were identified to have a significant influence on the evaluation result. After implementing targeted risk control measures, a downgrade in risk level to III was revealed. This aligns with the actual construction circumstances, as no safety incidents occurred in the Line 1 metro tunnel throughout the duration of the pit construction. This confirms the efficacy of the measures taken based on the evaluation results.

The novelty of this study is demonstrated through two key advancements. First, in response to the lack of a mature evaluation index system for risk assessment of existing tunnels during pit construction, the authors have meticulously curated a comprehensive risk evaluation index system. This system provides a valuable reference for the selection of appropriate risk evaluation indices in similar projects. Second, building upon the established index system, the study introduces a cloud model FAHP risk evaluation method. This method automates the generation of the membership degree between indicators and risk levels. The improved method has good reliability for the risk evaluation of existing tunnels, and it can provide decision-making reference for related studies when they carry out risk evaluations of similar projects.

In the field of steel defect detection, the existing detection algorithms struggle to achieve a satisfactory balance between detection accuracy, computational cost and inference speed due to the interference from complex background information, the variety of defect types and significant variations in defect morphology. To solve this problem, this paper aims to propose an efficient detector based on multi-scale information extraction (MSI-YOLO), which uses YOLOv8s as the baseline model.

First, the authors introduce an efficient multi-scale convolution with different-sized convolution kernels, which enables the feature extraction network to accommodate significant variations in defect morphology. Furthermore, the authors introduce the channel prior convolutional attention mechanism, which allows the network to focus on defect areas and ignore complex background interference. Considering the lightweight design and accuracy improvement, the authors introduce a more lightweight feature fusion network (Slim-neck) to improve the fusion effect of feature maps.

MSI-YOLO achieves 79.9% mean average precision on the public data set Northeastern University (NEU)-DET, with a model size of only 19.0 MB and an frames per second of 62.5. Compared with other state-of-the-art detectors, MSI-YOLO greatly improves the recognition accuracy and has significant advantages in computational cost and inference speed. Additionally, the strong generalization ability of MSI-YOLO is verified on the collected industrial site steel data set.

This paper proposes an efficient steel defect detector with high accuracy, low computational cost, excellent detection speed and strong generalization ability, which is more valuable for practical applications in resource-limited industrial production.

This study explores the deep integration of digital technology and cultural heritage to promote the preservation and inheritance of cultural heritage. Focusing on Digital Cultural Heritage (DCH), this research investigates its key role in activating theoretical research and practical applications in cultural heritage.

This study conducted an extensive bibliometric analysis utilizing VOSviewer and Bibliometrix visualization software to meticulously examine DCH research. Insights were gleaned from a dataset comprising 2,997 DCH-related publications harvested from the Web of Science database.

The bibliometric analysis reveals several notable findings: driven by active contributions from Italy, China, Spain, and the USA, the number of DCH publications shows a linear upward trend. Consiglio Nazionale delle Ricerche in Italy emerges as a prominent institution, while the Journal of Cultural Heritage stands out as the most influential journal in the DCH field. Scholars such as Remondino, Guidi, Barazzetti, and Carrozzino have significantly impacted DCH research. Furthermore, an in-depth analysis of keyword co-occurrence networks elucidates six major research trajectories in the DCH field, covering various aspects from cultural heritage digitization to digital humanities.

The study emphasizes the value of global knowledge exchange, interdisciplinary collaboration, innovative technology applications, and digital content provision practices in advancing DCH research.

By delving into the multifaceted landscape of DCH research, this study brings forth original insights into the escalating trends, pivotal contributors, and burgeoning research directions.

The purpose of this paper is to provide a critical historical analysis of the business (mis)behaviors and influencing factors that discourage enduring cooperation between principals and agents, to introduce strategies that embrace the social values, economic motivation and institutional designs historically adopted to curtail dishonest acts in international business and to inform an improved principal–agent theory that reflects principal–agent reciprocity as shaped by social, political, cultural, economic, strategic and ideological forces

The critical historical research method is used to analyze Chinese compradors and the foreign companies they served in pre-1949 China.

Business practitioners can extend orthodox principal–agent theory by scrutinizing the complex interactions between local agents and foreign companies. Instead of agents pursuing their economic interests exclusively, as posited by principal–agent theory, they also may pursue principal-shared interests (as suggested by stewardship theory) because of social norms and cultural values that can affect business-related choices and the social bonds built between principals and agents.

The behaviors of compradors and foreign companies in pre-1949 China suggest international business practices for shaping social bonds between principals and agents and foreign principals’ creative efforts to enhance shared interests with local agents.

Understanding principal–agent theory’s limitations can help international management scholars and practitioners mitigate transaction partners’ dishonest acts.

A critical historical analysis of intermediary businesspeople’s (mis)behavior in pre-1949 (1840–1949) China can inform the generalizability of principal–agent theory and contemporary business strategies for minimizing agents’ dishonest acts.

The purpose of this study is to examine the impact of customers' environmental concern on corporate green innovation and its underlying mechanisms.

This study empirically examines the impact of customer environmental concern on corporate green innovation using 967 company-customer-year observations of Chinese A-share listed companies over the period 2012–2022.

The empirical results show that customer environmental concern significantly enhances corporate green innovation. Furthermore, executive environmental awareness and research and development (R&D) investment play a partial mediating role in this relationship. The heterogeneity analysis reveals that state-owned customers, customers located in the same province with the corporate and the intellectual property model cities contribute to strengthening this relationship. Moreover, corporate performance analysis shows that customer environmental concern can significantly increase corporate financial performance and sustainable performance.

This study innovatively proposes a measure of customer environmental concern and examines its impact on corporate green innovation and its underlying mechanisms. In addition, this study also proposes some insights for policymakers.

Sports bras can effectively reduce breast displacement, alleviate breast pain and protect the breast. Different bra components have different effects on breast support. This study aims to explore the quantitative relationship between bra components and vibration reduction function.

To understand the effects of different bra component parameters on breast support, 30 sports bras were fabricated with precise component parameters. The dynamic vertical breast displacement when wearing each sports bra was monitored using motion capture technology. The breast displacement data from five breast positions was used to analyze the overall vertical displacement of the breast. To address variability due to differences in human anatomy, the experiments were conducted on a custom-made manikin prepared using three-dimensional printing.

Compared with bare breasts, breasts supported by bras made with high-elastic-modulus cup materials, high-elastic-modulus shoulder strap materials and polyester underbands exhibited reduced vertical displacement during physical activity. Structurally, bras with higher cup heights, shorter strap lengths and smaller underband circumferences were associated with reduced overall breast displacement during physical activity.

By systematically studying the effects of different bra components on breast support, this study provides valuable insight and recommendations for the design and materials selection of sports bras.

This paper is one of the first studies to examine specificities, including limits of mindfulness at work in an African organisational context, whilst dealing with the ongoing COVID-19 pandemic. It specifically addresses the role of organisational and managerial support systems in restoring employee wellbeing, social connectedness and attachment to their organisations, in order to overcome the exclusion caused by the ongoing pandemic.

The study uses a qualitative research methodology that includes interviews as the main data source. The sample comprises of 20 entrepreneurs (organisational leaders) from Ghana and Nigeria.

The authors found that COVID-19-induced worries restricted the practice of mindfulness, and this was prevalent at the peak of the pandemic, particularly due to very tough economic conditions caused by reduction in salaries, and intensified by pre-existing general economic and social insecurities, and institutional voids in Africa. This aspect further resulted in lack of engagement and lack of commitment, which affected overall team performance and restricted employees’ mindfulness at work. Hence, quietness by employees even though can be linked to mindfulness was linked to larger psychological stress that they were facing. The authors also found leaders/manager’s emotional intelligence, social skills and organisational support systems to be helpful in such circumstances. However, their effectiveness varied among the cases.

This paper is one of the first studies to establish a link between the COVID-19 pandemic and mindfulness limitations. Moreover, it is a pioneering study specifically highlighting the damaging impact of COVID-19-induced concerns on leader–member exchange (LMX) and team–member exchange (TMX) relationships, particularly in the African context. It further brings in a unique discussion on the mitigating mechanisms of such COVID-19-induced concerns in organisations and highlights the roles of manager’s/leader’s emotional intelligence, social skills and supportive intervention patterns. Finally, the authors offer an in-depth assessment of the effectiveness of organisational interventions and supportive relational systems in restoring social connectedness following a social exclusion caused by COVID-19-induced worries.

Friendships, an important form of people’s everyday relationships with others, have been studied by many scholars from different disciplines. However, there is limited research on friendship in the context of childhood, particularly that of Chinese rural children. This chapter presents findings from an in-depth study on Chinese children’s understandings and experiences of friendships with peers in the context of a rural primary boarding school. Data for this research were collected through an intensive five-month study, using an ethnographic approach, in a rural primary boarding school (given the pseudonym ‘Central Primary School’) in the western area of China in 2016. This chapter discusses parents’ influences on children’s selection of friends, particularly their ‘good’ friends, and their understandings of the functions of making friends in the context of rural China. It unpacks parents’ interventions on children’s friendships by discussing the moralised hierarchical relationship between children and their parents – children are expected to show obedience to parents. Then, it argues that the Confucian-collectivist values construct a relationship between a child’s individual achievement and their family’s collective good, which makes friendship not only an individual issue but also a collective one too.

The purpose of this study is to discuss the principles and factors that influence the site selection of emergency medical facilities for public health emergencies. This paper discusses the selection of the best facilities from the available facilities, proposes the capacity of new facilities, presents a logistic regression model and establishes a site selection model for emergency medical facilities for public health emergencies in megacities.

Using Guangzhou City as the research object, seven alternative facility points and the points' capacities were preset. Nine demand points were determined, and two facility locations were selected using genetic algorithms (GAs) in MATLAB for programing simulation and operational analysis.

Comparing the results of the improved GA, the results show that the improved model has fewer evolutionary generations and a faster operation speed, and that the model outperforms the traditional P-center model. The GA provides a theoretical foundation for determining the construction location of emergency medical facilities in megacities in the event of a public health emergency.

First, in this case study, there is no scientific assessment of the establishment of the capacity of the facility point, but that is a subjective method based on the assumption of the capacity of the surrounding existing hospitals. Second, because this is a theoretical analysis, the model developed in this study does not consider the actual driving speed and driving distance, but the speed of the unified average driving distance and the driving distance to take the average of multiple distances.

The results show that the method increases the selection space of decision-makers, provides them with stable technical support, helps them quickly determine the location of emergency medical facilities to respond to disaster relief work and provides better action plans for decision makers.

The results show that the algorithm performs well, which verifies the applicability of this model. When the solution results of the improved GA are compared, the results show that the improved model has fewer evolutionary generations, faster operation speed and better model than the intermediate model GA. This model can more successfully find the optimal location decision scheme, making that more suitable for the location problem of megacities in the case of public health emergencies.

The research findings provide a theoretical and decision-making basis for the location of government emergency medical facilities, as well as guidance for enterprises constructing emergency medical facilities.

Vicarious abusive supervision (VAS) has recently garnered the attention of hospitality researchers. VAS is prevalent in hospitality work settings characterized by long production chains and open operating environments. Based on the conservation of resources (CORs) theory, this study aims to examine how VAS influences hospitality employees’ work behaviours (i.e. supervisor-directed deviance, silence and helping behaviour) via affective rumination, with the moderating role of industry tenure as an individual contingency on the relationship between VAS and affective rumination.

The data were gathered from 233 restaurant frontline employees and their supervisors in Turkey. The authors tested the proposed model using partial least squares method through SmartPLS 3.

The results reveal that VAS triggers affective rumination, which, in turn, is positively related to supervisor-directed deviance and silence, and negatively related to helping behaviour. Moreover, industry tenure, as a buffer resource, significantly moderates the relationship between VAS and affective rumination.

To reduce the occurrence of VAS and mitigate its negative effects, managers should establish a work environment that embraces understanding and respect, pay attention to how they communicate with employees, implement appropriate interventions when VAS occurs and conduct stress management training and improve employees’ emotion regulation skills in ways that correspond to the employees’ industry experience.

This study advances research on VAS by offering insight into how VAS impacts employees’ work behaviours via the underlying mechanism of affective rumination through a COR lens. The findings also shed light on the salient buffering effect of industry tenure as an individual contingency.

Drought is the primary disaster that negatively impacts agricultural and animal husbandry production. It can lead to crop reduction and even pose a threat to human survival in environmentally sensitive areas of China (ESAC). However, the phases and periodicity of drought changes in the ESAC remain largely unknown. Thus, this paper aims to identify the periodic characteristics of meteorological drought changes.

The potential evapotranspiration was calculated using the Penman–Monteith formula recommended by the Food and Agriculture Organization of the United Nations, whereas the standardized precipitation evaporation index (SPEI) of drought was simulated by coupling precipitation data. Subsequently, the Bernaola-Galvan segmentation algorithm was proposed to divide the periods of drought change and the newly developed extreme-point symmetric mode decomposition to analyze the periodic drought patterns.

The findings reveal a significant increase in SPEI in the ESAC, with the rate of decline in drought events higher in the ESAC than in China, indicating a more pronounced wetting trend in the study area. Spatially, the northeast region showed an evident drying trend, whereas the southwest region showed a wetting trend. Two abrupt changes in the drought pattern were observed during the study period, namely, in 1965 and 1983. The spatial instability of moderate or severe drought frequency and intensity on a seasonal scale was more consistent during 1966–1983 and 1984–2018, compared to 1961–1965. Drought variation was predominantly influenced by interannual oscillations, with the periods of the components of intrinsic mode functions 1 (IMF1) and 2 (IMF2) being 3.1 and 7.3 years, respectively. Their cumulative variance contribution rate reached 70.22%.

The trend decomposition and periods of droughts in the study area were analyzed, which may provide an important scientific reference for water resource management and agricultural production activities in the ESAC. However, several problems remain unaddressed. First, the SPEI considers only precipitation and evapotranspiration, making it extremely sensitive to temperature increases. It also ignores the nonstationary nature of the hydrometeorological water process; therefore, it is prone to bias in drought detection and may overestimate the intensity and duration of droughts. Therefore, further studies on the application and comparison of various drought indices should be conducted to develop a more effective meteorological drought index. Second, the local water budget is mainly affected by surface evapotranspiration and precipitation. Evapotranspiration is calculated by various methods that provide different results. Therefore, future studies need to explore both the advantages and disadvantages of various evapotranspiration calculation methods (e.g. Hargreaves, Thornthwaite and Penman–Monteith) and their application scenarios. Third, this study focused on the temporal and spatial evolution and periodic characteristics of droughts, without considering the driving mechanisms behind them and their impact on the ecosystem. In future, it will be necessary to focus on a sensitivity analysis of drought indices with regard to climate change. Finally, although this study calculated the SPEI using meteorological data provided by China’s high-density observatory network, deviations and uncertainties were inevitable in the point-to-grid spatialization process. This shortcoming may be avoided by using satellite remote sensing data with high spatiotemporal resolution in the future, which can allow pixel-scale monitoring and simulation of meteorological drought evolution.

Under the background of continuous global warming, the climate in arid and semiarid areas of China has shown a trend of warming and wetting. It means that the plant environment in this region is getting better. In the future, the project of afforestation and returning farmland to forest and grassland in this region can increase the planting proportion of water-loving tree species to obtain better ecological benefits. Meanwhile, this study found that in the relatively water-scarce regions of China, drought duration was dominated by interannual oscillations (3.1a and 7.3a). This suggests that governments and nongovernmental organizations in the region should pay attention to the short drought period in the ESAC when they carry out ecological restoration and protection projects such as the construction of forest reserves and high-quality farmland.

The findings enhance the understanding of the phasic and periodic characteristics of drought changes in the ESAC. Future studies on the stress effects of drought on crop yield may consider these effects to better reflect the agricultural response to meteorological drought and thus effectively improve the tolerance of agricultural activities to drought events.

Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

The aging population, a higher proportion of older adults (aged 65+), is considered a global and severe problem, while the information systems (IS) literature on detecting the relationship between the aging population and the development of electronic commerce (e-commerce) is limited and insufficient. Hence, the main objective of this paper is to examine whether an aging population can moderate the effect of infrastructure constructions on e-commerce sales and whether an aging population can affect e-commerce sales.

To investigate the relationship between the aging population and e-commerce sales, this study proposes two potential influential mechanisms: moderating the effects of infrastructure development on e-commerce sales and direct influence. Subsequently, a sample of 31 Chinese provinces from 2013 to 2019 is utilized to conduct regression analyses in order to examine these hypotheses.

The findings suggest that the development of urban transportation infrastructure and network constructions can significantly contribute to the enhancement of e-commerce sales, and the influence cannot be affected by aging population. Furthermore, it is noteworthy that an aging population can have a positive effect on e-commerce sales.

The findings can inform future infrastructure constructions by assessing the potential of infrastructure projects to boost e-commerce sales and examining whether this effect varies in an aging population context.

The findings substantiate the pivotal role of older adults in the e-commerce industry. Moreover, the obtained results establish a positive relationship between an aging population and e-commerce sales, thereby offering diverse perspectives on existing theories.

Based on the theory of performance feedback, this study aims to explore the theoretical relationship between performance shortfalls and the financialization of non-financial enterprises. It further analyzes the moderating effect of economic policy uncertainty (EPU) and organizational redundant resources.

Multiple regression analysis is used on 16,555 initial samples of 2,658 Chinese A-share issuing enterprises from 2007 to 2019 to empirically test the relationship between performance shortfalls and the financialization of non-financial enterprises, and an instrumental variables-generalized moments estimation model is also used to verify the robustness of the results.

The results reveal that the greater the performance gap below the aspiration level, the higher the degree of enterprise financialization. Moreover, EPU strengthens the relationship between performance shortfalls and financialization, whereas organizational redundant resources weaken the relationship between performance shortfalls and financialization.

Decision-makers should determine the aspirated performance level of enterprises to make investment decisions that are most conducive to the long-term development of enterprises. Each enterprise should establish scientific management evaluation and supervision systems to avoid financial investment behaviors that place too much emphasis on short-term performance.

This study finds that financialization is one of the reactions when performance of enterprises is lower than the aspiration level, thus expanding the functional dimensions of performance feedback and supplementing the research on the influencing factors of enterprise financialization. The results also reveal information about situational factors, helping identify the boundary conditions through which performance below aspirations affects enterprise financialization.

This paper seeks to discuss the genealogical sources for Chinese immigrants as well as the settlement of Chinese in the USA and the historical evolution of Chinese names, their origins, arrangement and development. It aims to cover the origins of various classes of Chinese surnames, followed by the content description of a traditional genealogical book for jiapu.

The paper researches the various ways that a Chinese person can find out about their ancestry.

The paper reveals the roles of libraries, including serving the needs of patrons interested in genealogical research, preserving and interpreting information through oral and family history projects and collaborating with other libraries through interlibrary loan, document delivery, library consortia, collection management and international resource‐sharing.

The study provides information on where and how to locate the genealogical resources for researching the genealogy of a Chinese family.

The paper analyzes the value of genealogical research as a documentary source for population history, life expectancy in a clan, marriages and family connections, as well as lineage organizations and inter‐lineage relations.

The paper aims to present a systematic literature review to analyze interrelated enablers of Industry 4.0 for implementation. Industry 4.0 is an integrated manufacturing strategy embedded with disruptive technologies. Adapting these technologies with the present industrial scenario is dependent on understanding the dynamics of various critical enablers in the existing literature. In this paper, an effort has been taken to validate and reinforce these enablers by experts in the field of Industry 4.0 for implementation.

A mixed-methodology is designed in this paper. A text mining approach with an expert’s linguistic assessment method is planned to discover the enablers from literature 2010 to 2019. The most critical enablers and their dependencies on other enablers are studied by using correlation analysis.

The research explores the power driving enablers in three groups: technology, features and requirements for implementing Industry 4.0 in the existing factory. In each group, a high degree of associated and dependent enablers is fragmented in detail.

This paper will benefit the research communities and practitioners to understand the significance of an integrated ecosystem of Industry 4.0 technologies, features and requirements for implementation.

The text mining approach integrated with expert’s linguistic assessment to explore the pairwise relationship among the enablers using word correlation is a novel approach in this paper. Moreover, to best of the authors’ knowledge, this is the first-ever attempt to conduct a structured literature review combined with text analysis and linguistic assessment to identify the enablers of Industry 4.0 for implementation.

This paper aims to regulate the oil retention rate and tribological properties of pored polytetrafluoroethylene (PPTFE) using polyvinyl alcohol (PVA)-based oil gel.

PPTFE was first prepared by using citric acid (CA) as an efficient pore-making agent. Subsequently, PVA and chitosan solution was introduced into the pores and experienced a freezing-thawing process, forming PVA-based gels inside the pores. Then, the PPTFE/PVA composite was impregnated with polyethylene glycol 200 (PEG200), yielding an oil-impregnated PPTFE/PVA/PEG200 composite.

It was found that the oil-impregnated PPTFE/PVA/PEG200 composite exhibited advanced tribological properties than neat PTFE with reductions of 53% and 70% in coefficient of friction and wear rate, respectively.

This study shows an efficient strategy to regulate the tribological property of PTFE using a PVA-based oil-containing gel.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2024-0432/

This study aimed to investigate positive associations between three main motivations (social interaction, information and entertainment) for the use of social network sites (SNSs) and users' well-being, as well as the multiple mediating effects of perceived social support, positive and honest self-presentation.

A sample of 759 active users of SNSs (WeChat Moments, Qzone and Weibo) aged 14–43 years was measured with online questionnaires. Correlation analysis and structural equation modeling were implemented to examine the corresponding hypotheses.

The results showed the overall intensity of motivations was positively associated with users' well-being; perceived social support and positive self-presentation played intermediary roles and honest self-presentation and perceived social support had a chain mediation effect. However, the motivations of social interaction, information and entertainment indirectly affected users' well-being through three different mediation paths.

Although some studies have investigated the effects of motivations (including social interaction, information and entertainment) for SNS use on users' well-being, there has not been a consistent conclusion. The findings may shed light on the motivations for SNS use and how they may affect people's well-being in the digital era, thereby promoting their healthy use of SNSs as well as improved interface design and user management of SNSs.

The purpose of this paper is to analyze long-term institutional causes and consequences of preference falsification by studying the evolution of China’s patriarchal clan system.

The historic study shows that although the clan system was abolished in the Qin dynasty, it re-emerged among high-standing families in the Han dynasty and spread to common people after the Tang dynasty.

The author submits that the clan system was an institutional response to the preference falsification problem that arose due to the dictatorial political institutions first established in the Qin dynasty. It helped people to take collective action by themselves and also opened a back door to influence government decisions. A piece of clear evidence is the co-evolution of the clan system and government personnel system.

In this sense, the clan system probably also helped to prolong the political institutions for 2,000 years.

This is the first institutional study on the clan system in China.

Compared to other areas in China, Chaoshan region in Guangdong province has a more developed clan system set within a rural landscape. This paper aims to explore the relationship between the social structure (family–clan) and spatial form (housing settlement) of clan-organized rural China to understand the spatial form represented by “family and clan.”

By examining Dongli village and Huayao village, this paper outlines the typical path of spatial representation: dwelling of individual’s core family → mansion of the big family → settlement of a single clan → co-settlement of several clans. Moreover, it identifies three critical elements of the spatial representation: prototype (the spatial representation of the etiquette system); order (a hierarchical space set by the patriarchal system); and boundary (constructed on both physical and mental facts).

All elements indicate that descendants of migrants from the North maintain their self-identity and discipline clan members by planning the ideal space.

The findings contribute to the ongoing discussions regarding how local cultural and historical experiences can influence renewed designs of traditional settlement areas (Aksulu and Eryildiz, 2003) and how digital means can facilitate updating designs of traditional buildings (Han et al., 2017). Such planning and design should involve greater public participation, considering the impact on residents’ daily lives (Pandya, 2005).

This paper contributes to the understanding of the relationship between cultural values and the spatial form of residential settlements in Chinese history.

Advancement and disruptions in technologies have attracted cyberentrepreneurs globally, but what factors influence their intentions is an area that requires in-depth investigation. In order to dig down the phenomenon of cyberentrepreneurial intentions (CEIs), this study entails investigation of both direct and indirect effects (through cyberentrepreneurial self-efficacy; CESE) of the dark personality traits (e.g. Machiavellianism, narcissism and psychopathy). It also aims to investigate the moderating role of positive thinking (PT) on the association between CESE and CEIs.

Data are collected, using personally administrated questionnaires, from students enrolled in business and information technology (IT) programs in large public sector universities in three waves to tackle common method bias. A total of 641 useful responses were considered for analysis purposes.

The results reveal that not all dark triad dimensions influence CEIs and CESE. Narcissism is the only positive predictor of both the outcome variables (CESE and CEIs). Specifically, psychopathy positively influences CEIs, while its effects on CESE are negative; whereas Machiavellianism does not predict CESE, however, it negatively influences CEIs. In addition, CESE mediates the association between narcissism and CEIs; however, PT strengthens the relationship between CESE and CEIs.

The study collected data from a country with low entrepreneurs; therefore, results may vary for countries with a large number of entrepreneurs. The findings of the study offer both theoretical and practical implications, while it highlights the role of dark personality traits and their link with the CESE and CEIs.

There is a dearth of literature on CEIs, which this study extends through the dark personality traits (Machiavellianism, narcissism and psychopathy). This study also explored the mediating mechanism of CESE and the conditional role of PT between dark personality traits and CEIs.

Customer resource allocation efficiency (RAE) refers to the ability of customers to use, allocate and manage their available resource inputs to produce valuable outputs. This study draws on organizational entrainment theory (OET) to examine how the implementation of supplier digitalization affects customer RAE through supply chain entrainment.

Based on supplier and customer data disclosed by Chinese A-share listed firms from 2009 to 2022, this study uses fixed effects panel data models to empirically examine the impact of supplier digitalization on customer RAE and the mechanistic role of supply chain entrainment.

The results show that supplier digitalization significantly increases customer RAE. It improves RAE by influencing the three dimensions of supply chain entrainment (the bullwhip effect, inventory management coordination and risk management coordination).

This study provides important insights into how managers can adapt the external digital environments and maintain synchronous operations with their supply partners. Our findings demonstrate how managers can fully leverage the advantages of digitalization of their suppliers to improve their own RAE through supply chain entrainment strategies.

This study introduces the concept of supply chain entrainment to reveal how firms optimize their own resource allocation strategies and achieve efficient operations. Our research enriches the understanding of supply chain governance in the digital age and contributes to the literature on supply chain digitalization.

The purpose of this paper is to answer the question whether it is possible to recognise the gender of a web browser user on the basis of keystroke dynamics and mouse movements.

An experiment was organised in order to track mouse and keyboard usage using a special web browser plug-in. After collecting the data, a number of parameters describing the users’ keystrokes, mouse movements and clicks were calculated for each data sample. Then several machine learning methods were used to verify the stated research question.

The experiment showed that it is possible to recognise males and females on the basis of behavioural characteristics with an accuracy exceeding 70 per cent. The best results were obtained while using Bayesian networks.

The first limitation of the study was the restricted contextual information, i.e. neither the type of web page browsed nor the user activity was taken into account. Another is the narrow scope of the respondent group. Future work should focus on gathering data from more users covering a wider age range and should consider the context.

Automatic gender recognition could be used in profiling a user to create personalised websites or as an additional feature in automatic identification for security reasons. It might be also considered as a confirmation of declared gender in web-based surveys.

As not all users perceive personalised ads and websites as beneficial, this application requires the analysis of a user perspective to provide value to the consumer without privacy violation.

Behavioural characteristics, such as mouse movements and keystroke dynamics, have already been used for user authentication and emotion recognition, but applying these data to gender recognition is an original idea.

The purpose of this paper is to propose an new online path planning method for porcine belly cutting. With the proliferation in demand for the automatic systems of pork production, the development of efficient and robust meat cutting algorithms are hot issues. The uncertain and dynamic nature of the online porcine belly cutting imposes a challenge for the robot to identify and cut efficiently and accurately. Based on the above challenges, an online porcine belly cutting method using 3D laser point cloud is proposed.

The robotic cutting system is composed of an industrial robotic manipulator, customized tools, a laser sensor and a PC.

Analysis of experimental results shows that by comparing with machine vision, laser sensor-based robot cutting has more advantages, and it can handle different carcass sizes.

An image pyramid method is used for dimensionality reduction of the 3D laser point cloud. From a detailed analysis of the outward and inward cutting errors, the outward cutting error is the limiting condition for reducing the segments by segmentation algorithm.

This paper seeks to address the following two research questions. RQ1: What are the influential user archetypes in the social question-answering (SQA) community? RQ2: To what extent does user feedback affect influential users in changing from one archetype to another?

Based on a sample of 13,840 influential users drawn from the Covid-19 community on Zhihu, the archetypes of influential users were derived from their ongoing participation behavior in the community using the Gaussian mixture model. Additionally, user feedback characteristics such as relevance and volume from 222,965 commenters who contributed 546,344 comments were analyzed using the multinomial logistic regression model to investigate the archetype change of influential users.

Findings suggest that influential users could be clustered into three distinctive archetypes: touch-and-go influential users, proactive influential users and super influential users. Moreover, feedback variables have various impacts on the influential user archetype change, including a shift toward creating higher-quality content and fostering increased interaction, a shift toward generating lower-quality content and decreased interaction but improved speed and having mixed effects due to differences in information processing among these archetypes.

This study expands the existing knowledge of influential users and proposes practical approaches to cultivate them further.

The purpose of this study is to solve the problems of poor stability and high energy consumption of the dynamic window algorithm (DWA) for the mobile robots, a novel enhanced dynamic window algorithm is proposed in this paper.

The novel algorithm takes the distance function as the weight of the target-oriented coefficient, and a new evaluation function is presented to optimize the azimuth angle.

The jitter of the mobile robot caused by the drastic change of angular velocity is reduced when the robot is closer to the target point. The simulation results show that the proposed algorithm effectively optimizes the stability of the mobile robot during operation with lower angular velocity dispersion and less energy consumption, but with a slightly higher running time than DWA.

A novel enhanced dynamic window algorithm is proposed and verified. According to the experimental result, the proposed algorithm can reduce the energy consumption of the robot and improves the efficiency of the robot.

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.

Damage of engineering structures is a nonlinear evolutionary process that spans across both material and structural levels, from mesoscale to macroscale. This paper aims to provide a comprehensive review of damage analysis methods at both the material and structural levels.

This study provides an overview of multiscale damage analysis of engineering structures, including its definition and significance. Current status of damage analysis at both material and structural levels is investigated, by reviewing damage models and prediction methods from single-scale to multiscale perspectives. The discussion of prediction methods includes both model-based simulation approaches and data-driven techniques, emphasizing their roles and applications. Finally, summarize the main findings and discuss potential future research directions in this field.

In the material level, damage research primarily focuses on the degradation of material properties at the macroscale using continuum damage mechanics (CDM). In contrast, at the mesoscale, damage research involves analyzing material behavior in the meso-structural domain, focusing on defects like microcracks and void growth. In structural-level damage analysis, the macroscale is typically divided into component and structural scales. The component scale examines damage progression in individual structural elements, such as beams and columns, often using detailed finite element or mesoscale models. The structural scale evaluates the global behavior of the entire structure, typically using simplified models like beam or shell elements.

To achieve realistic simulations, it is essential to include as many mesoscale details as possible. However, this results in significant computational demands. To balance accuracy and efficiency, multiscale methods are employed. These methods are categorized into hierarchical approaches, where different scales are processed sequentially, and concurrent approaches, where multiple scales are solved simultaneously to capture complex interactions across scales.

Nature and occurrence of food-borne pathogens in raw and processed food products evolved greatly in the past few years due to new modes of transmission and resistance build-up against sundry micro-/macro-environmental conditions. Assurance of food health and safety thus gained immense importance, for which bio-sensing technology proved very promising in the detection and quantification of food-borne pathogens. Considering the importance, different studies have been performed, and different biosensors have been developed. This study aims to summarize the different biosensors used for the deduction of food-borne pathogens.

The present review highlights different biosensors developed apropos to food matrices, factors governing their selection, their potential and applicability. The paper discusses some related key challenges and constraints and also focuses on the needs and future research prospects in this field.

The shift in consumers’ and industries’ perceptions directed the further approach to achieve portable, user and environmental friendly biosensing techniques. Despite of these developments, it was still observed that the comparison among the different biosensors and their categories proved tedious on a single platform; since the food matrices tested, pathogen detected or diagnosed, time of detection, etc., varied greatly and very few products have been commercially launched. Conclusively, a challenge lies in front of food scientists and researchers to maintain pace and develop techniques for efficiently catering to the needs of the food industry.

Biosensors deduction limit varied with the food matrix, type of organism, material of biosensors’ surface, etc. The food matrix itself consists of complex substances, and various types of food are available in nature. Considering the diversity of food there is a need to develop a universal biosensor that can be used for all the food matrices for a pathogen. Further research is needed to develop a pathogen-specific biosensor that can be used for all the food products that may have accuracy to eliminate the traditional method of deduction.

The present paper summarized and categorized the different types of biosensors developed for food-borne pathogens.

This paper aims to find proper technological parameters of low-temperature joining technique by silver sintering to eventually use this technique for reliable electronic packaging.

Based on the literature and author’s own experience, the factors influencing the nanosized Ag particle sintering results were identified, and their significance was assessed.

It has been shown that some important technological parameters clearly influence the quality of the joints, and their choice is unambiguous, but the meaning of some parameters is dependent on other factors (interactions), and they should be selected experimentally.

The value of this research is that the importance of all technological factors was analyzed, which makes it easy to choose the technological procedures in the electronic packaging.

It is found that previous studies only focus on how digital transformation contributes to individual firms’ green innovation performance while ignoring the important role that it plays in the spillover and diffusion of green innovations among peer firms. Therefore, this study aims to investigate the influence of focal firms’ digital transformation on the spillover of green innovation among peer firms in heavily polluting industries mediated by environmental, social and governance (ESG) performance and agency conflict. Further, this study is also expected to explore the effects of digital transformation’s green innovation spillover.

This study chooses 6,438 A-share heavily polluting listed firms in the stock exchanges based in Shanghai and Shenzhen in China during 2010–2020 as samples and tests the hypothesis with ordinary least squares (OLS) regression. Results prove to be robust to a battery of robustness analyses the authors performed to take care of endogeneity.

The results show that the focal firm’s digital transformation may trigger their peer firms’ green innovation spillover and prompt them to engage in green innovation activities actively. The mechanism test shows that peer firms’ ESG performance and agency conflict mediate the influence path between digital transformation and peer firms’ green innovation spillover. Finally, among heavily polluting firms with high industry competition and large scale, digital transformation’s green innovation spillover effects are more significant in conventional energy-based source control, end-of-pipe treatment and substantive green innovation.

This study is possible to provide a potential driving mechanism of green innovation spillovers. The findings lay a sound foundation for future research, providing important theoretical support and practical insights for digital transformation to empower heavily polluting industries to achieve green transformation and low-carbon development.