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The statistical method plays an extremely important role in quantitative research studies in library and information science (LIS). The purpose of this paper is to investigate the status of statistical methods used in the field, their application areas and the temporal change patterns during a recent 15-year period.

The research papers in six major scholarly journals from 1999 to 2013 in LIS were examined. Factors including statistical methods, application areas and time period were analyzed using quantitative research methods including content analysis and temporal analysis methods.

The research studies using statistical methods in LIS have increased steadily. Statistical methods were more frequently used to solve problems in the information retrieval area than in other areas, and inferential statistical methods were used more often than predictive statistical methods and other statistical methods. Anomaly analysis on statistical method uses was conducted and four types of anomaly were specified.

The findings of this study can help educators, graduates and researchers in the field of LIS better understand the patterns and trends of the applications of statistical methods in this field, depict an overall picture of quantitative research studies in LIS from the perspective of statistical methods and discover the change patterns of statistical method applications in LIS between 1999 and 2013.

The purpose of this study is to examine the impact of Confucianism on auditor changes by highlighting the role of the cultural embeddedness mechanism in audit contracts from the perspective of credit governance.

Using a unique sample of Chinese A-share listed firms from 2008 to 2018, this study uses logit regression as the baseline methodology while controlling for macro-level factors and firm-level characteristics, as well as industry and year fixed effects. This study also conducts different mediation/channel analyses, endogeneity tests (using two-stage least squares and difference-in-differences techniques) and robustness checks.

The findings show that the embeddedness of Confucianism in a corporation reduces auditor changes. Furthermore, the channel analyses (using moral self-discipline, social trust, professional ethics and the quality of accounting information as four potential channels) reveal that Confucianism can improve moral credit and consolidate the cultural foundation of credit governance. Specifically, the stronger the embeddedness of Confucianism, the more stable the auditing contract. Finally, Confucianism in formal and informal systems can be mutually substituted.

There is limited research on how culture affects auditing contracts. This study offers new contributions and extends the literature on the connection between cultural embeddedness and contract stability. Confucianism has the potential to strengthen the efficiency of credit governance and maintain the stability of contracts. This study offers a thoughtful orientation toward duly using Confucianism vis-à-vis credit governance.

Data mining has been a popular research area in the past decades. Many researchers study data-mining theories, methods, applications and trends; however, there are very few studies on data-mining-related topics in social media. This paper aims to explore the topics related to data mining based on the data collected from Wikipedia.

In total, 402 data-mining-related articles were obtained from Wikipedia. These articles were manually classified into several categories by the coding method. Each category formed an article-term matrix. These matrices were analysed and visualized by the self-organizing map approach. Several clusters were observed in each category. Finally, the topics of these clusters were extracted by content analysis.

The articles obtained were classified into six categories: applications, foundation and concepts, methodologies, organizations, related fields and topics and technology support. Business, biology and security were the three prominent topics of the applications category. The technologies supporting data mining were software, systems, databases, programming languages and so forth. The general public was more interested in data-mining organizations than the researchers. They also focused on the applications of data mining in business more than in other fields.

This study will help researchers gain insight into the general public’s perceptions of data mining and discover the gap between the general public and themselves. It will assist researchers in finding new techniques and methods which will potentially provide them with new data-mining methods and research topics.

In large-scale group decision-making (LSGDM) situations, existing TODIM group decision-making methods often fail to account for the influence of social network relationships and the bounded rationality of decision-makers (DMs). To address this issue, a new TODIM-based group decision-making method is proposed that considers the current trust relationships among DMs in a large-scale trust relationship network.

This method consists of two main stages. In the first stage, the large-scale group is partitioned into several sub-clusters based on trust relationships among DMs. The dominance degree matrix of each sub-cluster is then aggregated into the large-scale group dominance degree. In the second stage, after aggregating the large-scale group dominance degree, the consensus index is calculated to identify any inconsistent sub-clusters. Feedback adjustments are made based on trust relationships until a consensus is reached. The TODIM method is then applied to calculate the corresponding ranking results. Finally, an illustrative example is applied to show the feasibility of the proposed model.

The proposed method is practical and effective which is verified by the real case study. By taking into account the trust relationships among DMs in the core process of LSGDM, it indeed has an impact on the decision outcomes. We also specifically address this issue in Chapter Five. The proposed method fully incorporates the bounded rationality of DMs, namely their tendency to accept the opinions of trusted experts, which aligns more with their psychology. The two-stage consensus model proposed in this paper effectively addresses the limitations of traditional assessment-based methods.

This study establishes a two-stage consensus model based on trust relationships among DMs, which can assist DMs in better understanding trust issues in complex decision-making, enhancing the accuracy and efficiency of decisions, and providing more scientific decision support for organizations such as businesses and governments.

This study aims to investigate the impact of corporate social responsibility (CSR) on green innovation by considering the three dimensions of green innovation cognition, behavior and outcomes and to explore the role of situational and measurement factors in this relationship.

This study adopts a meta-analysis method to integrate 208,997 observations from 48 independent empirical studies on CSR and green innovation.

CSR positively affects green innovation cognition, behavior and outcomes. Additionally, the relationship between CSR and green innovation is stronger in Western cultural background than in Eastern ones. The impact of CSR on green innovation is also more significant in small and medium-sized enterprises (SMEs). Moreover, this study shows that the correlation between CSR and green innovation is stronger when the source of data is primary data and when green innovation is measured by non-patent methodologies.

This study elucidates the impact of CSR on green innovation and further clarifies the potential reasons for the divergent findings in existing related studies. The article enriches the theoretical results related to CSR and green innovation and provides valuable insights and references for corporate decision-makers.

In order to verify the feasibility of different techniques, this chapter further studies the adaptability of two massive straw biomass applications in rural areas in China.

The methods of assessing biomass power generation project with Life Cycle Assessment (LCA), survey and field test of one biogas station, and game-theoretic analysis are adopted.

The following conclusions can be drawn: The air pollution costs account for more than 60% of the total environmental cost, followed by depreciation expense and maintenance fee of 18%, compared to that of biomass power generation at 0.01711 CNY/kWh. The adopted greenhouse sunlight technology of Solar Biogas Plant in Xuzhou, China, raises the inside average temperature by 11.0 °C higher than outside and keeps the pool temperature above 16 °C in winter, ensuring a gas productivity of biogas project in winter up to 0.5–0.7 m³/m³ by volume. This chapter also analyzes the information cost incurred by asymmetric information in biomass power generation via game theory method and illustrates the information structure with game results. It provides not only a foundation for the policy research in promoting straw power generation but also theoretical framework to solve the problem of straw collection.

These studies will propose solutions to relevant problems arisen in the running process.

These studies are all based on real cases, field research, and appropriate theoretical analyses, so, they can reduce the relevant costs and promote the application of relevant technologies.

Quantitative methods, especially statistical methods, play an increasingly important role in research of library and information science (LIS). For different journals, the uses of statistical methods vary substantially due to different journal scopes and aims. The purpose of this paper is to explore the characteristics of statistical methodology uses in six major scholarly journals in LIS.

Research papers that used statistical methods from the six major journals were selected and investigated. Content analysis method, descriptive statistical analysis method, and temporal analysis method were used to compare and analyze statistical method uses in research papers of the investigated journals.

The findings of this study show that there was a clear growth trend of statistical method uses in five of the investigated journals; statistical methods were used most in The Journal of the Association for Information Science and Technology and Information Processing & Management; and the top three most frequently used statistical methods were t-test, ANOVA test, and χ2-test.

The findings can be used to better understand the application areas, patterns, and trends of statistical methods among the investigated journals and their statistical methodology orientations in research studies of LIS.

This paper aims to examine the role of corporate governance (CG) in the earnings management (EM) of affiliated companies in family business groups (FBGs) listed on the Pakistan Stock Exchange (PSX), using principal–principal agency theory.

The sample of 327 nonfinancial firms of the PSX, consisting of 187 group-affiliated firms and 140 nonaffiliated firms has been used in this study for the period of 2010 to 2019. The study uses different regression models for analysis, with robustness tests of various alternative measures of EM and FBG affiliation. In addition, endogeneity is controlled with the propensity score matching method.

The findings show that EM is less prevalent in affiliated firms compared to nonaffiliated companies. The results show a negative and significant relationship between FBGs affiliated firms and EM. Moreover, the results also show a positive relationship between EM and the interaction term of the CG index and group affiliation. It refers to the fact that effective governance cannot reduce EM in affiliated companies of FBGs as well as in the nonfinancial companies of the PSX. In addition, the quality of CG is higher in affiliated companies compared to its counterpart in nonaffiliated firms. The findings support the principal–principal agency theory that CG cannot mitigate the expropriating behavior of controlling shareholders against minority shareholders by reducing EM in emerging markets due to the ownership concentration phenomenon.

This research study has implications for small investors, government agencies and regulators. The findings of the study show that CG code should make it mandatory for companies to reveal information about their complex ownership structure and ownership information about affiliated companies and directors. Furthermore, it is suggested to revisit the code of CG in the Pakistani context of principal–principal conflict instead of the agent–principal explanation of agency theory based on Anglo–Saxon countries.

This research study has contributed to the CG and FBG literature in relation to EM in idiosyncratic settings of Pakistan. One of the prime contributions of the paper is the development of a comprehensive CG index. This research study used detailed, manually collected novel data on affiliated firms of FBGs in Pakistan.

The regulatory landscape surrounding international construction projects presents significant challenges, and contractors are still struggling to pay a painful price for their performance in the project. While existing research has identified various causes of contractor compliance, the intricate interplay of these factors and their impact on compliance remain largely elusive. The motivation-opportunity-ability (MOA) framework may hold the key to determining what factors can foster induced contractor compliance in international projects.

This study collected 124 valid data samples from practitioners involved in large-scale international contracting projects through expert interviews and questionnaire surveys. Fuzzy-set qualitative comparative analysis (fsQCA) was employed to analyze the diverse combinations of contractor compliance factors.

The study identifies seven key factors that contribute to compliance behavior among international construction contractors: economic motivation, social motivation, normative motivation, legal completeness, deterrent sanctions, organizational learning and compliance management ability. The interplay of these factors promotes compliance in the following ways: When international construction contractors are influenced by both social and normative motivations, they exhibit a higher level of compliance. In situations where regulatory systems are relatively weak, the ability to manage compliance becomes the primary driver of compliance behavior for businesses. A comprehensive legal framework creates a conducive environment for contractors to improve their compliance through organizational learning.

The findings offer guidance for international construction contractors in enhancing compliance by considering factors such as motivations, legal frameworks, organizational learning and compliance management. This can lead to improved risk management and performance in international projects.

This research enhances fair and ethical practices in international construction by identifying compliance drivers, fostering positive social impact, mitigating negative consequences and empowering local communities. It informs legal and regulatory reform, encourages improved business practices and contributes to knowledge advancement in the field. Overall, the findings have the potential to positively impact the social fabric of international construction projects.

This study has made an important contribution to the field of compliance theory by integrating theories from multiple disciplinary domains and constructing a new theoretical framework from the perspectives of motivation, opportunity and capability. By elucidating how these factors interact and influence compliance behavior among international construction contractors, this research aids in understanding the complex dynamics of contractor compliance behavior and provides theoretical reference for compliance governance within the construction industry.