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In order to solve the current imbalance of academic resources within the discipline, this article builds a three-dimensional talent evaluation model based on the topic–author–citation based on the z index and proposes the ZAS index to evaluate scholars on different research topics within the discipline.

Based on the sample data of the CSSCI journals in the discipline of physical education in the past five years, the keywords were classified into 13 categories of research topics including female sports. The ZAS index of scholars on topic of female sports and so on was calculated, and quantitative indexes such as h index p index and z index were calculated. Comparative analysis of the evaluation effect was performed.

It is found that compared with the h index and p index, the z index achieves a better balance between the quantity, quality and citation distribution of scholars' results and effectively recognizes that the citation quality is higher and the number of citations of each paper is more balanced. In addition, compared to the z index, this article is based on a ZAS index model with an improved three-dimensional topic–author–citation relationship in research fields such as female sports.

It can identify some outstanding scholars who are engaged in small-scale or emerging topic research such as female sports and are excellent in different research areas. Talents create an objective and fair evaluation environment. At the same time, the ranking ability of ZAS indicators in the evaluation of talents is the strongest, and it is expected to be used in practical evaluations.

Artificial Intelligence (AI) is an emerging technology and turned into a field of knowledge that has been consistently displacing technologies for a change in human life. It is applied in all spheres of life as reflected in the review of the literature section here. As applicable in the field of libraries too, this study scientifically mapped the papers on AAIL and analyze its growth, collaboration network, trending topics, or research hot spots to highlight the challenges and opportunities in adopting AI-based advancements in library systems and processes.

The study was developed with a bibliometric approach, considering a decade, 2012 to 2021 for data extraction from a premier database, Scopus. The steps followed are (1) identification, selection of keywords, and forming the search strategy with the approval of a panel of computer scientists and librarians and (2) design and development of a perfect algorithm to verify these selected keywords in title-abstract-keywords of Scopus (3) Performing data processing in some state-of-the-art bibliometric visualization tools, Biblioshiny R and VOSviewer (4) discussing the findings for practical implications of the study and limitations.

As evident from several papers, not much research has been conducted on AI applications in libraries in comparison to topics like AI applications in cancer, health, medicine, education, and agriculture. As per the Price law, the growth pattern is exponential. The total number of papers relevant to the subject is 1462 (single and multi-authored) contributed by 5400 authors with 0.271 documents per author and around 4 authors per document. Papers occurred mostly in open-access journals. The productive journal is the Journal of Chemical Information and Modelling (NP = 63) while the highly consistent and impactful is the Journal of Machine Learning Research (z-index=63.58 and CPP = 56.17). In the case of authors, J Chen (z-index=28.86 and CPP = 43.75) is the most consistent and impactful author. At the country level, the USA has recorded the highest number of papers positioned at the center of the co-authorship network but at the institutional level, China takes the 1st position. The trending topics of research are machine learning, large dataset, deep learning, high-level languages, etc. The present information system has a high potential to improve if integrated with AI technologies.

The number of scientific papers has increased over time. The evolution of themes like machine learning implicates AI as a broad field of knowledge that converges with other disciplines. The themes like large datasets imply that AI may be applied to analyze and interpret these data and support decision-making in public sector enterprises. Theme named high-level language emerged as a research hotspot which indicated that extensive research has been going on in this area to improve computer systems for facilitating the processing of data with high momentum. These implications are of high strategic worth for policymakers, library stakeholders, researchers and the government as a whole for decision-making.

The analysis of collaboration, prolific authors/journals using consistency factor and CPP, testing the relationship between consistency (z-index) and impact (h-index), using state-of-the-art network visualization and cluster analysis techniques make this study novel and differentiates it from the traditional bibliometric analysis. To the best of the author's knowledge, this work is the first attempt to comprehend the research streams and provide a holistic view of research on the application of AI in libraries. The insights obtained from this analysis are instrumental for both academics and practitioners.

Using capital asset pricing model (CAPM) and the Z-risk index based on weekly data, this study aims to estimate yearly unsystematic, total, three systematic and insolvency risks in the Gulf Cooperation Council (GCC) countries for the period 2010–2018. The findings of CAPM show positive systematic market risk exposure in all GCC countries for all years, which support the contribution of stock markets to bank prices and returns. The mixed signs of systematic interest rate and exchange rate risks in GCC countries provide hedging opportunities, diversification strategies and regional cooperation, which help risk managers to hedge and stabilize their portfolios against interest rate and exchange rate fluctuations. Therefore, it is necessary that managers and policymakers develop a monitoring system on factors affecting bank insolvency risks to avoid bankruptcies and insolvencies.

This study uses the three-factor CAPM and Z-risk index to measure six types of risks. The CAPM uses market information to estimate the sensitivity of banks to the fluctuations of equity markets, debt markets and foreign exchange markets. Sharpe (1964), Lintner (1965) and Treynor (1965) developed a single-factor CAPM and the coefficient of the model was called systematic market risk. The single-factor CAPM highlights stock markets as the only non-diversifiable source of systematic risks, whereas Stone (1974) and Jorion (1990) highlighted interest rate and exchange rate fluctuations as the other types of non-diversifiable systematic risks. The following functional form in equation (1) estimates five types of risks using CAPM.

The findings of CAPM show positive systematic market risk exposure in all GCC countries for all years, which support the contribution of stock markets to bank prices and returns based on CAPM theory. The mixed signs of systematic interest rate and exchange rate risks in GCC countries support hedging opportunities and diversification strategies which may help risk managers to hedge and stabilize their portfolios against the fluctuations of interest rate and exchange rate. Although, this policy may decrease the profits of banking sectors but at the same time it would stabilize the portfolios and prevent bankruptcies and big losses because of the fluctuations of interest rate. Moreover, a bank has a better chance to have more liquidity position during financial crises because of the diversifications into different regional markets.

Therefore, this study contributes to the existing literature by using risk measurement by a three-factor CAPM and the Z-risk index as discussed further in methodology.

It is necessary that managers and policymakers develop a monitoring system on factors affecting bank insolvency risks to avoid bankruptcies and insolvencies.

This paper aims to measure the stability extent of the banking sector in Saudi Arabia, including Islamic and conventional banks (CBs), using quarterly data.

The paper uses seemingly unrelated regressions to estimate the determinants of the z-score.

The panel data model shows that Islamic banks (IBs) reduce the financial stability index relatively; meanwhile, they contribute efficiently to enhance the financial stability through the diversification of their assets. The Saudi banking sector exhibits strong concentration affecting the financial stability negatively.

The paper’s topic can be extended to cover the recent period.

The limited presence of IBs in the Saudi banking sector jeopardizes any effort to improve the financial stability.

By attracting more clients, IBs would contribute more to the financial stability in the Saudi economy. Also, the monetary authority has to expand the share of IBs in the financial system at least 50-50 compared to CBs.

The z-score is mostly analyzed with yearly data; in this paper we use quarterly data to describe at infra-annual frequency the variability of the z-score index. Also, we consider in detail the statistical properties of the banks’ data.

The purpose of this paper is to investigate the risk-taking channel of monetary policy transmission in the Chinese banking industry. This study also investigates the role of various other factors in the risk-taking channel.

This study used panel data from 2000 to 2012, and a dynamic panel model (Difference GMM) was applied.

The empirical findings of this paper suggest that loose monetary policy rates increase bank risk-taking. Unlike previous studies, the results of this paper suggest that the bank-specific factors (size, liquidity and capitalization) do not significantly affect the risk-taking channel. However, the market structure does have a stabilizing effect on monetary policy transmission and the risk-taking channel. Higher market power weakens the risk-taking channel of monetary policy transmission.

Of significance to the policymakers' point of view is that loose monetary policy induces banks to take excessive risks. However, such effects can be mitigated by encouraging a proper level of market power in banking markets.

This study investigated the risk-taking channel of monetary policy transmission for the Chinese banking industry. Due to the unique features of the People's Bank of China (PBC, Central Bank of China) policy, this study also contributes to the literature by comparing price-based and quantity-based monetary policy tools and their effectiveness in financial stability and monetary policy transmission. Furthermore, the role of market structure is also investigated in the risk-taking channel.

Recognizing the differences between generations Y and Z, this exploratory study uses generational cohort theory as a framework to examine the brand perception of McDonald's, an international brand which has grown up with consumers for over 30 years in China. The paper aims to discuss this issue.

Measures of brand perception was built based on Aaker's brand personality model. A total 1,103 valid questionnaires were collected through an online survey platform. Factor analysis is the primary method to analysis the data.

The findings of this study reveal a favourable brand perception of McDonald's among young Chinese consumers which is consistent with Aaker's brand personality model and support the use of generational cohort theory as a market segmentation tool for brand perception. The differences between the two generational cohorts are not shown to be significant.

The most important contribution of this study is the evaluation of the personality of a major brand in China for Gen Z, a topic with very little existing research. Also, this research suggests future in-depth research into generational cohort theory in a Chinese context by recognizing homogeneity and heterogeneity exist simultaneously between generational cohorts.

We show that, even with flexible domestic wages, international outsourcing may worsen the welfare of the home country and reduce the profits of all firms. If wages are rigid, outsourcing is welfare-improving if and only if the sum of the “trade creation” effect and the “exploitation effect” exceeds the “trade diversion” effect. A wage subsidy may improve welfare. We also extend the model to a two-period framework. Delaying outsourcing can be gainful because the fixed cost of outsourcing may fall over time. A social planner would choose a different speed of outsourcing than that achieved under laissez-faire.

The purpose of this paper is to examine the financial aspects of high vs low-ranked firms in the Corporate Responsibility Index in Egypt, and to construct a Z-score model to discriminate between high- and low-ranked firms in the Corporate Responsibility Index.

This study empirically examines a comprehensive list of financial ratios for 24 firms listed in EGX30 for four fiscal years, 2007-2010. The authors calculate 90 financial ratios to provide better insights and evaluation of the firms’ financial performance. The ordinary least square regression method and discriminant analysis are utilized to explain differences between the low- and high-ranked firms regarding their corporate social governance index.

The results show that corporate governance and corporate social responsibility (CSR) are positively related to the firms’ financial performance in terms of sales turnover and customer loyalty. This suggests that in the long run, the market mechanism should be able to provide additional resources to those companies that are better at maximizing a widely defined bottom line of their social governance. The results also show that highly ranked firms are characterized financially by: strong bargaining power with suppliers; financing growth in fixed assets using debt mainly.

The study contributes to the literature in terms of providing practical insights on the financial strategies that help support effective CG and CSR in Egypt. In addition, this study offers a unique quantitative attempt to measure and examine the benefits of incorporation of socioeconomics into business practices.

This paper aims to analyze the relationship between bank institutional setting and risk-taking by exploring whether board education and turnover are drivers of the risk propensity of cooperative banks compared to joint-stock banks.

Based on a comprehensive data set of Italian banks over the 2011-2017 period, this paper examines whether these board characteristics affect the risk propensity of cooperative and joint-stock banks. Bank risk is measured by the Z-index, profit volatility and the ratio of non-performing loans to total gross loans.

The findings show that cooperatives take less risk than joint-stock banks and have lower board turnover and education. Furthermore, this study finds that while board education mediates the relationship between the cooperative model and bank risk-taking, there is no evidence for board turnover. Thus, the lower educational level of cooperative directors contributes to explaining the lower risk-taking of cooperative banks.

The findings have several implications. In terms of the more general policy debate, the results point to the need to strengthen the governance model for both joint-stock and cooperative banks while supporting the view that a more ad hoc perspective on the best models and practices for each type of institutional setting would be preferable. In particular, the study reveals how board education’s effects on bank risk-taking should be carefully monitored.

Through a mediation framework, this study provides empirical evidence on the relationship between bank institutional setting (by distinguishing between cooperative and joint-stock banks) and risk-taking behavior by exploring the underlying mechanisms at the board level, which is novel in the literature.

The purpose of this paper is to estimate the cost and profit efficiency (PE) of Chinese commercial banks in the last ten years and investigate how market power affects bank efficiency and stability.

The paper builds a stochastic frontier analysis model to evaluate the cost and PE of commercial banks. The paper then uses a Lerner index and Z-index to represent market power and stability, respectively. In addition, the paper empirically analyzes the relationship between market power and bank efficiency, stability in the last ten years.

The results show that the efficiency of banks on the Chinese mainland increased during the study period, but is still lower than that of banks in Hong Kong; moreover, the efficiency of four state-owned commercial banks is lower than that of medium and small banks. Market power has a negative relationship with efficiency while its relationship with stability varies among Chinese banks.

The results imply that the promotion of financial liberalization and banking reform to introduce an appropriate competition mechanism has had a positive effect on the efficiency and stability of Chinese commercial banks.

Thus, the paper will contribute to deepen reform and opening up the banking sector in China.

The healthy development of banking can enhance the ability of banks to withstand financial risks, to promote the harmonious development of society.

The paper estimates the cost and PE of Chinese commercial banks using SFA model and investigates how market power affects bank efficiency and stability. The study design has a certain novelty, where Lerner index and Z index are used, respectively, to measure market power and stability and management efficiency of commercial banks is investigated from two aspects – PE and cost efficiency – by the translog cost function, instead of Douglas production function. In addition, the paper tries to put some of Hong Kong banks included in the study sample, and has a certain reference value.