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This study aims to empirically analyze the significance of various knowledge management (KM) elements to the environment in a military organization and establish the efficacy of performance indicators of civil organizations for a military organization.

The research methodology includes the development of a research model based on a comprehensive literature review. A sample of 454 Indian Air Force Veterans was obtained and structural equation modeling (SEM) analysis using statistical package for the social sciences (SPSS) analysis of moment structures (AMOS) was conducted to test the hypotheses. The study first employed exploratory factor analysis (EFA) for redefining the theoretical constructs and then confirmatory factor analysis (CFA) to test the hypotheses.

The study empirically establishes the significance of various KM elements on the knowledge environment that creates, stores, transfers and applies knowledge to achieve military objectives. Findings indicate the complexity of KM in a military setup while applying the performance measures used in the civil organization.

The study expects to expand the scope of the KM literature to the militaries of developing countries and provide a methodology to the leaders and practitioners in the military organizations, and to study the available KM practices, models and tools in the civil world.

To the best of the authors’ knowledge, the present research is one of the first to generate empirical insights into a knowledge environment in military organizations and test its relation with parameters used in civil organizations. The paper would significantly contribute to the underexplored area of KM in military organizations and infuse a theoretical rigor into the KM literature.

This study aims to review the progress of research on artificial intelligence (AI) relating to the hospitality and tourism industry, focusing on the content, focal points, key terms and trends of AI research.

A total of 491 referred papers are selected from the Web of Science core collection database. These papers, published in the past 30 years (1991–2021), are analyzed by using Gephi and VOSviewer software.

AI research shows a growing trend since 1991, and the number of publications and citations increased significantly since 2018, indicating that AI became a focus for researchers. AI studies are grouped into four clusters, namely, AI technology, technology acceptance, customers’ perception and future trends. The research focus changed from AI technology in the early stage to customers’ attitudes toward and willingness to accept AI.

The findings contribute to advance knowledge development, identify research gaps and shed light on future research. The results offer practical enlightenment for governments, tourism destinations and hospitality organization.

The results offer practical enlightenment for governments, tourism destinations and hospitality organization.

This study is the initial attempt to provide a systematic review of AI research relating to the tourism and hospitality fields.

The purpose of this study is to explore knowledge management (KM) initiatives for achieving sustainable development goal (SDG) 4.7 and to investigate enablers and barriers to insert KM to prepare higher education institutions (HEIs) ready to contribute to SDGs’ performance. At the end, this paper provides a practical perspective of KM initiatives for higher education for sustainable development (HESD).

This is an exploratory study. It applies a descriptive-interpretative-qualitative approach. The analysis is based on the opinions collected from 170 HEIs’ stakeholders. Discussions among participants have been organized through zoom meetings, telephone interviews and focus group discussions in three phases. In the first phase, a total of 113 informants took part in the discussion on various dates. In the second phase, 10 interviews were conducted with university officials using three open-ended questions; and in the third phase, three focus group discussions were organized to interact about the effectiveness of the Masters in Business Administration in Global Leadership and Management programme and curriculum with teachers, students and the programme initiators.

From the analysis of stakeholders’ views, it appears that Nepalese HEIs have yet to move forward with integrating KM activities into their aims, structure and functions to address the government’s policy guidelines applicable to maximizing SDG’ performance. A KM cultural framework that values intellectual capital is urgently needed to fill the knowledge-doing gap for the benefit of society. HEIs appear to require multidisciplinary teaching, learning and research methods to play a civic role in society. They have to improve their rules and regulation, develop a boundary-spanning structure from a conventional structure and apply KM initiatives to support achieving SDGs’ performance. Understanding and inculcating these initiatives in the academic programmes could provide a value-adding higher education in the country.

This paper is entirely based on the perspectives of stakeholders in higher education. So, understanding their points of view and perspectives may have resulted in vague explanations. Furthermore, because the setting of Nepal’s HEIs differs from that of developed countries, the results should only be interpreted in Nepalese contexts.

This paper acknowledges the gaps and complexities in Nepalese HEIs from the standpoints of HEIs’ leaders, teachers and students for the application of KM initiatives to reform HEIs, with HESD in consideration, and enhance SDGs’ performance.

To the best of the authors’ knowledge, the paper is the first of its kind in the context of Nepal, exploring KM initiatives for SDGs. It provides a new perspective on KM and comprehends KM initiatives in the case of Nepalese HEIs transformation into HESD for achieving SDG 4.7.

We use design thinking in the context of accounting pedagogy to exploit recent advances in cybernetics in the form of generative artificial intelligence technology. Relying on the intuition that supplementing or augmenting human argumentation (natural intelligence or NI) with parallel AI output can produce better student written assignments, we posit the “augmentation premise,” that is, ((NI + AI) > AI > NI). To test the augmentation premise, we compare student written submissions in an Accounting Information Systems (AIS) course with and without the benefit of parallel generative AI output. We then evaluate how the generative AI output enhances student-crafted revisions to their initial submissions. Using a summative quality improvement index (QII) consisting of quantitative and qualitative assessments, we present preliminary evidence supporting the augmentation premise. The augmentation premise likely extends to other accounting subdisciplines and merits generalization for enriching accounting pedagogy.

While social media data are used increasingly in studies of social movements, social media evolves far more rapidly than academic research and publication. This chapter argues that researchers should adopt historical and archival approaches to social media data. Treating social media data as an “instant archive” – one that is self-curated, is co-constituted, and changes rapidly – we caution researchers to pay attention to the features of this archive and their implications for working with the data therein. Applying insights from recent discussions of archival methods for social science research to the specific features of social media data, we explore how platform features, repressive effects, and user innovations affect the content of the instant archive. We then offer strategies for researchers' methodological approaches, including how best to select units of analysis and platforms, how to collect and interpret archival materials, and how to identify silences in the data.

This paper discusses data-collection strategies that use digitized historical newspaper archives to study social conflicts and social movements from a global and historical perspective focusing on nationalist movements. I present an analysis of State-Seeking Nationalist Movements (SSNMs) dataset I, which includes news articles reporting on state-seeking activities throughout the world from 1804 to 2013 using the New York Times and the Guardian/Observer. In discussing this new source of data and its relative value, I explain the various benefits and challenges involved with using digitized historical newspaper archives for world-historical analysis of social movements. I also introduce strategies that can be used to detect and minimize some potential sources of bias. I demonstrate the utility of the strategies introduced in this paper by assessing the reliability of the SSNM dataset I and by comparing it to alternative datasets. The analysis presented in the paper also compares the labor-intensive manual data-coding strategies to automated approaches. In doing so, it explains why labor-intensive manual coding strategies will continue to be an invaluable tool for world-historical sociologists in a world of big data.

This chapter analyzes the campaign against race norming in the 2013 National Football League (NFL) concussion settlement that caregivers of retired players designed, and it considers how their collective action throws new light on activism in sport. While there is a substantial literature on how individual athletes engage in protest, less work has focused on how families – partners, children, siblings, and parents – of athletes organize as a group to answer back to anti-Black racism in professional sport. I argue that a group of spouses used their position as caregivers to shame the NFL, the presiding judge of the settlement, Class Counsel, and even the Department of Justice into acknowledging not only individual suffering from traumatic brain injury but also of the distribution of that suffering across households. Specifically, the wives group expanded definitions of risk and damage to include not only individual illness but also family and group suffering and demanded inclusion of gendered and racialized aspects of social care. Through their campaign, the group recast what is considered protest in the world of sport and who has the ability to access an activist subjectivity.

We are long overdue for a conversation about ethical treatment of student researchers. Ethical treatment of research participants has been carefully defined through decades of public conversation, and ethical practices have been institutionalized through mechanisms like mandatory ethics trainings and Institutional Review Boards. Student researchers deserve the same level of consideration. While there are many types of ethical violations of student labor in research projects, there are two that are of particular concern to social movements researchers: use of volunteer labor without clear academic or professional benefits, and failure to ensure the safety of student researchers. The first of these ethical violations is especially common in social movements research because of the emergent nature of protests: new rounds of protests begin and researchers seek to rapidly collect data on a tight timeframe, making grant funding to pay student researchers challenging. The second situation emerges when faculty researchers do not consider the ways students' race, gender identity, or other characteristics, or the nature of the protests themselves might create potential risks for students.

In this paper, I propose using the Belmont Report principles to create guidelines for ethical treatment of student researchers. While these principles were developed for the purposes of protecting research participants, the principles of respect for persons, beneficence, and justice help us to clarify the risks and benefits for student researchers, to find ways to maximize the benefits of student research participation, and to understand and address the inequalities that plague graduate student training.