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In order to better optimize the internal management system of book publishing and to cope with the changes in the external market environment, the purpose of this paper is to carry out cross-border publishing with the help of a transmedia storytelling model to realize the transformation and upgrading of the industry. Focusing on the relationship between the book publishing transmedia storytelling model and business performance, the moderating effect of the innovation environment on different variables is assessed.

This paper proposes several feasible hypotheses based on existing research. The research data came from 365 managers of Chinese book publishing organizations, and the scale was validated by Cronbach’s a, composite reliability (CR) and average variance extracted (AVE). Reliability and validity were verified, and correlation and regression analyses were used to test the impact of the book publishing transmedia storytelling model on business performance and to analyze the moderating role of the innovation environment.

The results show that the book publishing transmedia storytelling model (content production, technology integration, organizational innovation, marketing integration) helps to improve business performance (market performance, financial performance), and the innovation environment has a positive moderating effect on the relationship between the book publishing transmedia storytelling model and business performance, which provides a guarantee for the transformation and upgrading of book publishing. The market information reflected in the innovation environment has a certain role in promoting the innovation and business performance of the book publishing transmedia storytelling model.

The empirical evidence provides a theoretical link between the book publishing transmedia storytelling model and business performance, but there are still some shortcomings, and more factors, such as equity structure, government subsidies and research and development investment, should be included in future research. In addition, the scope of the research should be broadened on this basis to make the results of the data analysis more objective.

This paper introduces the transmedia storytelling model and deeply analyzes the relationship between the book publishing transmedia storytelling model and business performance, which is of great practical significance for optimizing the application and service quality of book publishing, prolonging the industrial chain, enhancing the interaction and participation of users and perfecting the business management system of the book publishing industry.

The application and research of the book publishing transmedia storytelling model are imperfect. Therefore, this paper not only helps to promote the innovation of book publishing organizational structure and improve the management system of business performance, but also may help to improve the innovation environment of book publishing enterprises and promote the diversification of industrial structure.

As technology in tourism and hospitality (TTH) develops technical artifacts according to visitors’ demands, it must deal with both behavioral and design constructs in the context of structural equation modeling (SEM). While behavioral constructs are typically modeled as common factors, the study at hand introduces the composite into TTH to model artifacts. To deal with both kinds of constructs, this paper aims to exploit partial least squares path modeling (PLS-PM) as a confirmatory approach to estimate models containing common factors and composites.

The study at hand presents PLS-PM in its current form, i.e. as a full-fledged approach for confirmatory purposes. By introducing the composite to model artifacts, TTH scholars can use PLS-PM to answer research questions of the type “Is artifact xyz useful?”, contributing to a further understanding of TTH. To demonstrate the composite model, an empirical example is used.

PLS-PM is a promising approach when the model contains both common factors and composites. By applying the test for overall model fit, empirical evidence can be obtained for latent variables and artifacts. In doing so, researchers can statistically test whether a developed artifact is useful.

To the best of the authors’ knowledge, this is the first study to discuss the practical application of composite and common factor models in TTH research. Besides introducing the composite to model artifacts, the study at hand also guides scholars in the assessment of PLS-PM results.

因为旅游酒店科技（TTH）根据游客需求而定制科技产品, TTH必须在结构方程模型（SEM）下结合游客行为和设计等变量。一般行为变量在模型中是常见因子, 本研究将这些变量编入TTH结构成为模块。本研究采用PLS-PM方法来预估含有隐性变量和模块的模型。.

本研究设计PLS-PM模式, 即确定性全变量方法。TTH学者们通过引进结构形成模型模块, 使用PLS-PM研究方法, 以回答研究问题“模块xyz有用吗？”, 因此对TTH进一步理解。为了展示复合模型, 本论文采用实际验证。.

PLS-PM在面对模块内存在常见因子和复合模块的结构时是有力方法。实际验证结果通过整体最佳模型参数, 得到隐性变量和模块。为此, 研究者们能够在统计方法上测量是否开发的模型模块是否有用。.

据作者所知, 本论文是首个研究在TTH领域上应用模块和常见因子模型。本研究引进显性变量在模型模块中, 以指导学者评估PLS-PM结果报告。.

This study aims to build a framework of the influencing factors of construction workers' career promotion and identifies the critical determinants so as to propose suggestions for the government and enterprises to offer construction workers a path for career promotion.

In line with the theory of human resources, such as Herzberg's two-factor theory, this study constructs a theoretical framework that affects the career promotion of construction workers. Using evidence from Guangzhou city, valid data provided by 464 workers from 50 sites were collected by a questionnaire survey, and the significance test on the influencing factors of construction workers' career promotion was taken by binary logistic regression.

The overall career development of construction workers in Guangzhou is worrying. The binary logistic regression indicates that age, working years, type of work, career development awareness, legal awareness, professional mentality, vocational psychological training and career development path are critical factors that affect construction workers' career promotion.

This study for the first time explores the career promotion of frontline construction workers. Specifically, it identifies the critical factors that affect the career promotion of workers and thus lays a foundation for further research and the promotion and continuous and healthy development of the construction industry. Thus, this study is original and has theoretical and practical significance.

Marx’s monetary theory is an important part of Marxist economics and an irreplaceable milestone in the intellectual history of the monetary theory. The purpose of this paper is to summarize the main content of Marx’s monetary theory from three aspects: the source and nature of money, the function of money and the historical significance of money.

Moreover, this paper also gives an extended understanding of Marx’s monetary theory from four perspectives: the endogenous credit mechanism of money, the functions of money and demands for money, the financial function of money and the economic and social functions of money.

Lastly, the present paper discusses the practical significance of Marx’s monetary theory from three perspectives, namely, the inspection of “Bitcoin” from the nature and function of money, the definition of demands and the division of supplies at the monetary level, and the prevention of systemic financial risks and the focus of financial supervision.

Marx’s monetary theory is an important part of Marxist economics and an irreplaceable milestone in the intellectual history of the monetary theory. However, for a long time, the contribution of Marx has rarely been mentioned in the intellectual history of monetary theory. Even the book, Political Economy (On Capitalism), has been only summarily concerned with the source and function of money in Marx’s monetary theory, rather than revealing Marx’s outstanding contribution in the monetary theory and the financial connotation of Marx’s monetary theory, and expounding its practical significance.

This paper aims to provide readers with a comprehensive overview of the current state of the millennial literature, highlighting the significance and challenges of millennial professionals, their reported high turnover and the various recommendations designed to engage and retain them.

An integrated review approach was applied to synthesise contemporary peer-reviewed articles, supplemented by legacy and grey literature and relevant book chapters, to comprehensively explore and construct a cohesive overview of the current research on the millennial workforce.

Within the wealth of available information, examining the various studies on millennial turnover reveals diverse theories, evidence and opportunities for advancement, underscoring the necessity for more robust empirical studies. The investigation identified three overarching retention strategy themes: (1) intergenerational conflict management, (2) workplace adaptations and (3) solutions rooted in a protean career orientation. In alignment with protean career concepts, coaching shows promise as an underexplored option.

This article holds practical significance by offering researchers a comprehensive and cohesive overview of the millennial literature. Additionally, it gives organisations a novel perspective on the crucial role coaching can play in engaging and retaining millennial employees.

The increased focus on retaining millennial workers in recent decades has spurred a proliferation of articles and books on this subject. However, this body of research remains fragmented, lacking an overview that provides a clear picture of its current state. This review aims to bridge this gap.

Karl Marx's social capital reproduction theory is his significant contribution to economics. The purpose of this paper is to review the contributions of the exploration of Chinese economists (especially Professor Liu Guoguang) in the concretization of Marx’s social capital reproduction theory combined with socialist construction since 1949.

During this process, Professor Liu Guoguang, a famous Chinese Marxist economist, has made an outstanding contribution by creating a Marxist social capital reproduction model with Chinese characteristics and a distinctive Marxist economic growth model. Professor Liu's exploration is still of crucial practical significance to building a socialist market economy today.

The process and achievements in the sinicization exploration of Marx's social capital reproduction theory were reviewed. With the reform and opening up, fundamental changes have occurred in China's economic system – the centralized planned economic system has been transformed into a socialist market economic system.

The planned management of the national economy is replaced by a macro-regulation system characterized by gross control gradually, and the concepts of agriculture, light industry, and heavy industry, and their intercorrelation are no longer applied in theory and policy. However, the sinicization exploration of Marx's social capital reproduction theory in the older generation of Marxist economists represented by Liu is not only of historical significance but also of important practical significance.

Consumers' willingness to pay premium (WTPP) for two different types of agricultural brand labels (enterprise and regional), are evaluated through a non-hypothetical Random n-price auction experiment during the online purchase of fresh agricultural products. The purpose of this paper is to evaluate the two WTPP, compare their differences, and explore their sustainability.

Data were collected in July–August 2020 from a sample of 310 consumers in Liaoning Province, China. A nonhypothetical random n-price auction experiment was implemented in a simulated online shopping environment.

The results show that WTPP exists, and WTPP level of regional brand labels is higher than that of enterprise brand labels. Consumers' WTPP is sustainable. Consumers with low WTPP for enterprise brand labels and consumers with high WTPP for regional brand labels have stronger willingness to repurchase.

The results have direct practical implications for developing brand agriculture and encouraging “brand consumption”. The results can provide theoretical reference for policymakers, enlightenment for the development and effective dissemination of agricultural brand labels and important information to e-retailers on how to sale agricultural products with agricultural brand labels.

To the best of the authors' knowledge, no previous study has related WTPP and its sustainability for agricultural brand labels in China. We try to fill a gap in literature on consumers' WTPP for agricultural brand labels. And the authors explore the sustainability of WTPP by analyzing the impact of WTPP on repurchase intention and recommendation intention respectively.

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 article is to show the gains that can be made if researchers were to use gain-probability (G-P) diagrams.

The authors present relevant mathematical equations, invented examples and real data examples.

G-P diagrams provide a more nuanced understanding of the data than typical summary statistics, effect sizes or significance tests.

Gain-probability diagrams provided a much better basis for making decisions than typical summary statistics, effect sizes or significance tests.

G-P diagrams provide a completely new way to traverse the distance from data to decision-making implications.

This study aims to evaluate the short-term impact of brokerage analysts’ recommendations on abnormal returns using a sample selected from the S&P BSE 100 in the Indian context. The efficient market hypothesis, specifically, its semi-strong form, is tested for “Buy” stock recommendations published in the electronic version of Business Standard. The crucial issue is, are there any abnormal returns that can be earned following a recommendation? If so, how quickly do prices incorporate the information value of these recommendations? It tests the impact of analyst recommendations on average abnormal returns (AARs) and standardized abnormal returns (SRs) to determine their statistical significance.

Using a sample of stock recommendations published in the e-version of Business Standard, the event study methodology is used to determine whether AARs and SRs are significantly different from zero for the duration of the event window by using several significance tests.

The findings indicate a marginal opportunity for profit in the short term, restricted to the event day. However, the effect does not persist, i.e. the market is efficient in its semi-strong form implying that investors cannot consistently earn abnormal returns by following analysts’ recommendations. Post the event date, the market reaction to analyst recommendations becomes positive, however, insignificant until the ninth day after the recommendation providing support to the underreaction hypothesis given by Shliefer (2000) and post-recommendation price drift documented by Womack (1996). The study contributes by using different statistical tests to determine the significance of returns.

There are important implications for traders, investors and portfolio managers. The speed with which market prices incorporate publicly available information is useful in formulating trading strategies. However, stock characteristics such as market capitalization, volatility and level of analyst coverage need to be incorporated while making investment decisions.

The study contributes by using different statistical tests to determine the significance of returns.