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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.

This study aims to shed light on the dilemma of “publish or perish” within the context of artificial intelligence (AI) and to suggest approaches that scholars and organizations can implement to enhance ethical behavior in research and publishing.

This investigation examined institutional guidelines, policies, processes, norms and prior research to pinpoint ethical patterns that could be leveraged to promote ethical behavior in research and publishing.

The research outlined various unethical behaviors that have a detrimental impact on research outcomes including falsification, fabrication, plagiarism, p-hacking, authorship conflicts of interest, salami publication, republishing and manipulation of visual data, as well as incorrect selection of statistical analysis techniques. Furthermore, the study recommends optimal strategies for researchers and institutions to improve the quality of research, such as embracing the Open Research Library, forming partnerships and consortia, adhering to established informed consent standards and safeguarding confidentiality and privacy, among other practices.

These findings can serve as a foundation for policies that enable institutions and scholars to heighten their comprehension of ethical research practices and establish mechanisms for supervising research outcomes.

Numerous research and educational institutions are contending with new obstacles brought about by using technologies such as AI. These findings can offer a reference point to stimulate the ongoing discourse regarding the utilization of generative AI in academic settings.

The purpose of this paper is to revisit the potential of the New Deal as a research context in management and organization studies and, in doing so, forward the role one of its chief architects, Harry Hopkins, played in managing the economic crisis. The exploration takes us to multiple layers that work together to form context around Hopkins including the Great Depression, the Roosevelt Administration, and ultimately, the New Deal. By raising Harry Hopkins as an exemplar of historical-narrative exclusion, the authors can advance the understanding of his role in the New Deal and how his actions produced early insights about management (e.g. modern crisis management).

The paper experiments with the methodological assemblage of ANTi-History and microhistorical analysis that the authors call “ANTi-Microhistory” to examine the life narrative of Harry Hopkins, his early association with President Franklin D. Roosevelt and later, the New Deal. To accomplish this, the authors undertake a programme of archival research (e.g. the digital repository of The Franklin D. Roosevelt Presidential Library and Museum) and assess various materials (e.g. speeches, biographies and memoirs) from across multiple spaces.

The findings suggest Harry Hopkins to be a much more powerful actor in mobilizing New Deal policies and their effect on early management thought than what was previously accepted. In the process, the authors found that because of durable associations with Roosevelt, key policy architects of the same ilk as Harry Hopkins (e.g. Frances Perkins, Henry Wallace, Lewis Douglas, and others) and their contributions have been marginalized. This finding illustrates the significant potential of little-known historical figures and how they might shed new insight on the development of the field and management practice.

The aim is to demonstrate the potential of engaging historical research in management with the individual – Harry Hopkins – as a unit of analysis. By engaging historical research on the individual – be it well-known or obscure figures of the past – the authors are considering how they contribute to the understanding of phenomena (e.g. New Deal, Progressivism or Keynesian economics). The authors build on research that brings to focus forgotten people, communities and ideas in management studies but go further in advocating for space in the research to consider the scholarly potential of the individual.

This article introduces the Responsible AI for Service Excellence (RAISE) framework. RAISE is a strategic framework for responsibly integrating AI into service industries. It emphasizes collaborative AI design and deployment that aligns with the evolving global standards and societal well-being while promoting business success and sustainable development.

This multidisciplinary conceptual article draws upon the United Nations' Sustainable Development Goals (SDGs) and AI ethics guidelines to lay out three principles for practicing RAISE: (1) Embrace AI to serve the greater good, (2) Design and deploy responsible AI and (3) Practice transformative collaboration with different service organizations to implement responsible AI.

By acknowledging the potential risks and challenges associated with AI usage, this article provides practical recommendations for service entities (i.e. service organizations, policymakers, AI developers, customers and researchers) to strengthen their commitment to responsible and sustainable service practices.

This is the first service research article to discuss and provide specific practices for leveraging responsible AI for service excellence.