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In recent years, counterproductive knowledge behavior (CKB) and its types have received increasing interest in knowledge management as the degree of knowledge sharing and innovation in enterprises continues to increase. A rapidly growing number of studies have shed light on the important antecedents and consequences of employees’ CKB. However, the various labels, conceptualizations and operationalizations of CKB have fragmented this body of research. This study aims to systematically integrate the effects of the six types of organizational characteristics on CKB and further draws more general conclusions based on the results of previous studies.

Based on a survey of 103 effect values responsible for 52 CKB samples, the authors use the ABC theory to explore the effects of the six types of organizational characteristics on CKB. Moderator analysis were performed to resolve inconsistencies in empirical studies and understand the contexts under which CKB has the strongest or weakest effect.

The results showed that task interdependence and a positive organizational atmosphere, in general, negatively affect employees’ CKB in the moderation analysis. In contrast, workplace discomfort, negative organizational atmosphere, internal competition and time pressure positively and partly affect employees’ CKB. The direction and magnitude of these effects were affected by emotional factors, knowledge personnel types and sample sources. Discussing the theoretical, methodological and practical implications of these findings can offer a guiding framework for future research.

Better control of employees’ CKB is not achieved by adjusting organizational characteristics alone but by combining personal characteristics and mood changes with it to balance organizational characteristics and CKB. Furthermore, the large-sample joint study integrated the conceptual definition of CKB. The multivariate data study provided more reliable conclusions and a solid theoretical foundation for CKB research areas.

In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks.

This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient.

The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly.

The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community.

The purpose of this paper is to present a method for evaluating the structural dynamic characteristics of a flying probe tester.

The dynamic characteristics of a flying probe tester framework were analyzed based on a finite element analysis method. First, modal analysis was carried out to characterize the modal parameters of the structure. Second, the harmonic response was analyzed according to the modal analysis and the response curve of the structural system was studied. Finally, transient analysis was conducted to obtain the transient response of the structures at the beginning of the vibration.

The natural frequency and the response frequency of a natural granite structure was the highest and the transient vibration displacement amplitude was the smallest compared with cast iron and artificial stone structures.

A comprehensive understanding of the dynamic characteristics of the framework of a flying probe tester with three different materials has been achieved. The results of the analyses provide a reference for the framework design of a flying probe tester.

We study the correlates of immigrant location and migration choices to address the following questions: What location-specific, economic, and demographic factors are associated with these choices? Does the influence of these factors differ by immigrant characteristics? What are the factors associated with the observed increase in immigrant geographic dispersion during the 1990s? Our analysis suggests that: (1) There is significant heterogeneity in the correlates of immigrant location and migration choices; associations vary by immigrant birthplace, age, gender, education, and duration of residence in the United States. (2) Economic factors are, for the most part, weakly associated with immigrant location decisions. (3) Immigrants appear to be more attracted to states with large (growing) populations; less attracted to states with a high proportion of other foreign-born persons; more attracted to states with high unionization, and less attracted to states with high crime. (4) The association between location-specific characteristics and immigrant location choices changed between 1990 and 2000 for some immigrant groups and this explains most of the increase in geographic dispersion during the 1990s. In contrast, changes in location attributes and changes in immigrant composition explain relatively little of the increase in dispersion.

Under the background of open science, this paper integrates altmetrics data and combines multiple evaluation methods to analyze and evaluate the indicators' characteristics of discourse leading for academic journals, which is of great significance to enrich and improve the evaluation theory and indicator system of academic journals.

This paper obtained 795,631 citations and 10.3 million altmetrics indicators data for 126,424 published papers from 151 medicine, general and internal academic journals. In this paper, descriptive statistical analysis and distribution rules of evaluation indicators are first carried out at the macro level. The distribution characteristics of evaluation indicators under different international collaboration conditions are analyzed at the micro level. Second, according to the characteristics and connotation of the evaluation indicators, the evaluation indicator system is constructed. Third, correlation analysis, factor analysis, entropy weight method and TOPSIS method are adopted to evaluate and analyze the discourse leading in medicine, general and internal academic journals by integrating altmetrics. At the same time, this paper verifies the reliability of the evaluation results.

Six features of discourse leading integrated with altmetrics indicators are obtained. In the era of open science, online academic exchanges are becoming more and more popular. The evaluation activities based on altmetrics have fine-grained and procedural advantages. It is feasible and necessary to integrate altmetrics indicators and combine the advantages of multiple methods to evaluate the academic journals' discourse leading of which are in a diversified academic ecosystem.

This paper uses descriptive statistical analysis to analyze the distribution characteristics and distribution rules of discourse leading indicators of academic journals and to explore the availability of altmetrics indicators and the effectiveness of constructing an evaluation system. Then, combining the advantages of multiple evaluation methods, The author integrates altmetrics indicators to comprehensively evaluate the discourse leading of academic journals and verify the reliability of the evaluation results. This paper aims to provide references for enriching and improving the evaluation theory and indicator system of academic journals.

The study explores extant knowledge on the nature of the relationship between internal and external corporate governance mechanisms, particularly board characteristics and audit quality, respectively, while also investigating how the relationship varies across geographies.

The extant knowledge is synthesized using a meta-analysis, which is conducted using a sample of 56 empirical studies from publications of varying grades. The studies span over 25 years (1996–2021) and cover 147 empirical samples (343,787 firm-year observations) across more than 20 countries. The dependent variable is audit fees, and the independent variable captures 12 different measures of board characteristics.

Overall, the results reveal a positive association between board characteristics and audit fees, indicating complementarity between governance mechanisms. Effect size analysis shows board characteristics, like size and independence, are positively associated with audit fees. However, heterogeneity is noted for some characteristics, and further analysis by geography (developed vs emerging countries) explains the heterogeneity.

This study helps multiple stakeholders like firms, shareholders, boards, regulators and policymakers in designing and strengthening governance frameworks.

Both governance and auditing literature benefit from identifying specific board characteristics that drive audit quality consistently across different institutional settings and samples. Heterogeneity analysis helps improve the understanding of contradictions documented in prior literature.

This meta-analysis is the first to explore the interplay between internal and external corporate governance mechanisms, with a focus on board characteristics and audit quality. The study provides valuable insights on how different governance mechanisms influence each other while highlighting, for the first time, how the interaction between governance mechanisms varies by a country's level of development.

Educational institutes must embrace the principles of total quality management (TQM) if they seek to remain competitive, and survive and succeed in the long run. An educational institution must embrace the principles of quality management and incorporate them into all of their activities. Starting with a theoretical background, the paper outlines the results of a study conducted on both internal and external customers of the educational system, with select engineering and management institutes as foci of study. The study is an attempt toward developing an integrated customer-centric model of quality management in education, through the use of multiple methodologies so as to be able to evaluate service quality; prioritize improvement of service; and guide and develop educational services by incorporating the voice of the customer (VOC). The purpose of this paper is to establish the prioritization for improvement of service design of an educational system through incorporation of the VOC, be it internal or external customers, through the use of multiple methodologies, leading to generalization of results.

The study uses multiple methodologies with various techniques for analysis through the application of the SERVQUAL; quality function deployment (QFD); interpretive structural modeling (ISM); and path analysis. The SERVQUAL was applied to identify the gap and determine the level of service quality. Following this, QFD, ISM and path analysis were used to identify the set of minimum design characteristics/quality components that would meet the requirements the various internal and external customers of the educational system. The QFD was used to identify the set of minimum design characteristics/quality components that meet the requirements of the various internal and external customers of the educational system. The ISM and path analysis were used to identify and prioritize the design characteristics/quality components that would meet the requirements the various internal and external customers of the educational system.

The findings from the various techniques were amalgamated, and proposed as an integrated model of TQM in higher education. The study helped identify with a customer perspective, the quality components which would help design TQM for higher education institutions in India.

The paper could be useful to government bodies, funding agencies, policy makers and administrators in developing a system that could lead to satisfaction of both internal and external customers of the educational system.

The study includes within its scope the varied customers of the educational system, namely, internal and external customers of the educational system; the internal customers being the faculty and the administrative staff, and the external customers being the students and the industry (as the employer). This is yet to be seen in other research studies. Also, the integration of the multiple tools and their application to the field of higher education in India, has not yet been made available in the literature.

The purpose of this study is to review the levels of open government data (OGD) among various countries that are not consistent with the development levels of those countries. This study evaluates the associativity between OGD Index (OGD) and the characteristics of those countries as well as to compare the degree of OGD among countries. Accordingly, an advanced discussion to explore how a country’s characteristics affect how that country’s government opens data was presented.

The stakeholder relationships of OGD is analysed with the characteristics of a country. The usage data are compared with the data availability according to nine indicators. These data collected from the statistics and OGDI websites are grouped for comparative statistical analyses based on basic descriptive statistics, one-way analysis of variance and a regression model with variance inflation faction.

The results 1) revealed the reasons some countries have high-ranking indexes and 2) verified the high index values of countries in terms of their degrees of development. This study, thus, attempted to derive a balanced appraisal of national development and OGD.

The study sample is limited only to countries 1) which open the statistical data; and 2) are of uneven population density and development degree. The OGDI is limited to expert evaluation. The score might be vary to experts and users with diverse countries at different evaluation period. The limitations can be attributed to the differences between OGDI and real open levels. These differences might influence the reliability and validity.

Government departments with OGD policies provide raw data in various formats and with application interfaces for user access. This study, thus, attempts to derive a balanced appraisal of national development and OGD. The factors that evaluate which types of countries open the level of data are explored.

This study establishes stakeholder relationships of OGD and extends to analyse the characteristics of a country and OGD that affect the government data open level. The relationships are evaluated through the OGDI with design score scheme. The measurement results indicated that a country possesses high relation to open data with high DI and nature resource.

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

The purpose of this paper is to provide a comprehensive portrait of who earns the minimum wage, in terms of the characteristics of the individual that are most important in determining this outcome.

This study uses individual data from the Annual Income Supplements of the New Zealand (NZ) Household Labour Force Surveys between June 1997 and June 2004. This unit record data allows isolation of workers earning the minimum wage or close to it. A more sophisticated quantitative analysis is also carried out, where the probability of earning at or below the minimum wage is modelled to estimate what individual characteristics are most significant in determining minimum wage status.

One of the key findings was that individual characteristics (such as age) are much more important than household circumstance or industry affiliations, in terms of the probability of earning minimum wage.

NZ has substantially increased minimum wages for teenagers and adults since 2000. For example, since the youth minimum was introduced in March 1994, it had increased by 52 per cent in real terms by 2004. Consequently, recent NZ experience offers a rare opportunity to isolate who earns the minimum wage and which subgroups are more likely to be potentially impacted by a rising minimum.