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The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding and analyzing the significant changes, patterns and trends in the subject as they are represented in academic papers is the goal of this research.

Using bibliometric methodologies, this study gathered and examined a large corpus of research papers, conference papers and related material from several academic databases.

Starting with Artificial Intelligence (AI), the Internet of Things (IoT), Big Data (BD), Augmentation Reality/Virtual Reality and Blockchain Technology (BT), the study discusses the advent of new technologies and their effects on libraries. Using bibliometric analysis, this study looks at the evolution of publications over time, the geographic distribution of research and the most active institutions and writers in the area. A thematic analysis is also carried out to pinpoint the critical areas of study and trends in emerging technologies and smart libraries. Some emerging themes are information retrieval, personalized recommendations, intelligent data analytics, connected library spaces, real-time information access, augmented reality/virtual reality applications in libraries and strategies, digital literacy and inclusivity.

This study offers a thorough overview of the research environment by combining bibliometric and thematic analysis, illustrating the development of theories and concepts during the last ten years. The results of this study helps in understanding the trends and future research directions in emerging technologies and smart libraries. This study is an excellent source of information for academics, practitioners and policymakers involved in developing and applying cutting-edge technology in library environments.

This paper aims to propose and test a moderated mediation model examining the relationships among ethical work climate, organizational identification, leader-member-exchange (LMX) and organizational citizenship behavior (OCB).

Numerous regression analyses were performed using PROCESS (version 2.13), a macro for SPSS developed by Hayes (2017) to test this moderated mediation model.

The analytical results showed that organizational identification mediates the positive relationship between an ethical work climate and OCB. The analytical results also showed that LMX moderates the direct effect of ethical work climate on organizational identification and that LMX also moderates the indirect effect of ethical work climate on OCB via organizational identification.

This study provides numerous valuable implications for hotels to develop effective strategies to promote employees’ OCB and improve their organizational identification.

This study was the first attempt to propose and test a moderated mediation model that explores the relationships among ethical work climate, organizational identification, leader-member-exchange (LMX) and OCB.

Nitrogen oxides (NO_x) have been considered as primarily responsible for many serious environmental problems. Removing NO is the key task to remove NO_x hazards. To clarify, NO removal process for pitch-based spherical-activated carbons (PSACs), an online prediction and optimization technique in real-time based on support vector machine algorithm in regression (support vector regression [SVR]) is discussed. The purpose of this paper is to develop a predictor and optimizer system on selective catalytic reduction of NO (SCRN) using experimental data and data-driven SVR intelligence methods.

Predictor and optimizer using developed SVR have been proposed. To modify the training efficiency of SVR, the authors especially customize batch normalization and k-fold cross-validation techniques according to the unique characteristics of PSACs model.

The results present that SVR provides a property regression model since it can linkage linear and non-linear process and property relationships in few experimental data sets. Also, the integrated normalization and k-fold cross-validation show a satisfying improvement and results for SVR optimization. The predicted results of predictor and optimizer in single and double factor systems are in excellent agreement with the experimental data.

SCRN-PO for predicting and optimization SCRN problems is developed by data-driven methods. The outperformed SCRN-PO system is used to predict multiple-factors property parameters and obtain optimum technological parameters in real-time. Also, experiment duration is greatly shortened.

The purpose of this paper is to examine the factors (including conservation payments) that influence household decisions to participate in off-farm work and estimate the impact of participation on household welfare under the auspices of the Grain for Green (GfG) program.

The authors used survey data from 225 farm households on the Loess Plateau and addressed the possible sample selection and endogeneity problems by employing a jointly estimated endogenous switching regression (ESR) model.

The findings of this paper are as follows: off-farm participation is positively related to households’ educational attainment and negatively related to their land resource endowment and the presence of children; participation in off-farm work exerts positive effects on household income and per capita household income, but negative effects on farm productivity; and conservation payments show no significant impact on off-farm participation, no significant impact on any of the three household welfare indicators for off-farm non-participant households, but a significantly negative impact for off-farm participant households.

This paper makes two contributions. First, the authors address the selection bias and endogeneity problem of GfG participating households by employing the ESR method and explicitly estimating the treatment effects of off-farm participation on their household welfare. Neglecting these problems leads to biased estimates and misleading policy implications. Second, this analysis stresses the important role of government in reducing market or institutional failure and other barriers that impede farmers’ efficient allocation choices instead of compensating households for conserving sloping land, shedding new light on the most effective policy options to achieve the program’s goals.

The purpose of this paper is to investigate how the 2007 global financial crisis (GFC) changed financial disclosure behavior using a sample of US equity real estate investment trusts (REITs) from 2000 to 2015.

The authors use panel data spanning from 2000 to 2015 to examine the impact of the GFC on REITs’ earnings management (EM) after controlling for other factors (including the market shock in 2007 and 2008). The measurements of EM are estimated by using the models developed from literature such as modified Jones models. The static panel data regression models are used to estimate the impact of GFC on the REITs’ EM.

The authors find that REITs are more likely to engage in income-increasing EM to embellish their financial reports during the GFC. However, the magnitude of the use of EM to manipulate disclosed financial information decreased following the GFC, indicating an improvement in the quality of financial disclosure as a consequence of the enhancement of the regulatory environment. REITs also changed the manner in which their EM behavior responded to the main factors in the market following the outbreak of GFC.

This study contributes to the finance and accounting literature by providing the first empirical test results concerning how the financial disclosure behavior and quality of listed portfolios and companies such as REITs have changed corresponding to the enhancement of the regulatory environment and adverse market conditions brought by GFC.

This study provides references for investors, auditors, and regulators to help them make adjustments for and improve the interpretation of the disclosed financial information.

This is one of the first empirical study testing the impact of the GFC on EM. It is also the first empirical study investigating the impact of GFC on the financial disclosure behavior of REITs.

The purpose of this paper is to study distance measuring and sorting method of general grey number.

First, the concept of generalised grey number based on grey system theory is given in this paper. Second, from the perspective of kernel and degree of greyness of general grey number, the method of measuring the distance of general grey number and its properties are given. At the same time, the concepts of the kernel expectation and the kernel variance of the general grey number are proposed.

Up to now, the method of measuring the distance and sorting of general grey number is established. Thus, the difficult problem for set up sorting of general grey number has been solved to a certain degree.

The method exposed in this paper can be used to integrate information form a different source. Distance measuring and sorting method of general grey number could be extended to the case of grey algebraic equation, grey differential equation and grey matrix which includes general grey numbers, etc.

The concepts of the kernel expectation and the kernel variance of the general grey number are proposed for the first time in this paper; the novel sorting rules of general grey numbers were also constructed.

Although an important facet of modernist architecture in which function plays a prominent role, building flexibility is not entirely a new concept. Its relevance transcends generations, allowing space and structure to evolve through time. This paper investigates the relationship among main building structures, infill elements, and space by studying examples in ancient Chinese architecture. It reveals the role of building owners, users, and craftsmen from a survey of historical documentation. In studying these examples, it is concluded that craftsmen in ancient China were involved not only during the construction phase but throughout the period of use as well. Thus, in select cases, the relationship between craftsmen and owners or users had been preserved for generations. Finally, this paper suggests potential strategies for the building industry and technology in the move towards sustainable development.

This paper aims to investigate how user expectations affect value-added service (VAS) investment and pricing decisions of two-sided platforms. It draws on the information asymmetry theory and offers suggestions on how platform operators can manage user expectations.

According to the game theory, this study considers three user expectations (responsive, passive and wary). By framing the Hotelling duopoly model and comparing the VAS investment, price and platform profits, the optimal platform decision is analyzed and discussed.

The conclusions demonstrate that the monopolistic two-sided platform obtains more profits from the informed users with responsive expectations than uninformed users with passive or wary expectations. The marginal investment cost and cross-network externalities are two key factors that determine the platform's VAS investment and pricing strategies of passive or wary users. Furthermore, considering the expectation preferences, i.e. the uniformed users hold wary expectations with more information and hold passive expectations with less or no information, the results suggest that the proportion of wary users to all uninformed users increases the platform's VAS investment, profits and the price of informed users, and increase (decrease) the price of uninformed users when the cross-network externalities of informed users are relatively small (larger).

These results can provide insightful enlightenment into how platform operators utilize bilateral users' expectations and information level to guide their VAS investment and pricing decisions.

This paper is one of the first to explore the impact of three user expectations and the heterogeneity of preferences in informing users' passive or wary expectations, based on different levels of information on the decision-making of two-sided platforms regarding VAS.