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The purpose of this study is to primarily focus upon the acknowledged benefits of tourist-to-tourist (t2t) encounters through productive interactions among tourists, rather than focusing on interactions between tourists and service providers.

This study delves into various value dimensions among Indian tourists that arise during different co-creation stages. A rigorous mixed-methods approach, coupled with a three-wave analysis, was used to develop a comprehensive six-dimensional scale for measuring t2t value co-creation.

The research findings shed light on the dimensions constituting t2t value co-creation, thereby providing a nuanced understanding of their interactions. The developed six-dimensional scale offers a structured framework to quantify positive interactions among tourists, previously unexplored in the literature.

This study significantly contributes to the field of tourism experience by enriching the literature on t2t interaction and value co-creation. Moreover, it provides valuable conceptual, practical and instructive insights for service design and administration within the tourism industry. These insights potentially enhance the overall tourist experience and facilitate more meaningful interactions among tourists, thereby contributing positively to the tourism sector.

The research breaks new ground by shifting the focus from tourist-service provider interactions to productive relationships among tourists. It introduces a pioneering six-dimensional scale, quantifying positive t2t value co-creation. Concentrating on Indian tourists, this study offers unique cultural insights. Methodologically rigorous and practically impactful, it clarifies conceptual ambiguities laying the foundation for nuanced research in understanding tourist interactions and value co-creation.

COVID-19 has caused unprecedented disruption to health systems. There is much to be gained by capturing what was learned from changes and adaptations made by health services and systems. The Ministry of Health in New South Wales (NSW), Australia, sought to prioritise health services research (HSR) to address critical issues arising from the COVID-19 pandemic. We tested a priority setting methodology to create priorities for a specific funding opportunity and to extract generalisable lessons.

A virtual roundtable meeting of key stakeholders was held in June 2020. We used a modified Nominal Group Technique (NGT) for priority setting, with potential items (n = 35) grouped under headings. Data was analysed through a reflective deliberative process.

We engaged 89 senior policy makers, health service executives, clinicians and researchers in the roundtable. The NGT proved an efficient method with participants reaching consensus on eight priorities. Findings included strong support for learning from the rapid response to COVID-19 and addressing needs of vulnerable populations and the health workforce. Opinions differed about strategic areas investment and where learnings should be via internal evaluation rather than funded research. Three of the eight recommended priorities were included in the funding opportunity.

Coronavirus disease 2019 (COVID-19) required unprecedented change and adaptations within health systems, and rapid, applied health services research can help to create, understand and (where relevant) sustain change beyond the immediate impact of the pandemic. While final decisions may be dependent on a wider range of considerations by government, stakeholder enthusiasm for engagement in priority setting exercises may be dampened if they do not perceive their application in decision-making.

A modified nominal group technique can be used to set research priorities in constrained conditions by engaging large numbers of stakeholders in rankings and then using an online delivery of a roundtable and to reach consensus on priorities in real time. Recommended priorities for health services research can be readily generated through rapid engagement but does not guarantee their application.

Australia’s swift response to COVID-19 pandemic in 2020 was perceived as a relative success due to the rapid public health and policy response and a relatively low number of cases. This response was underpinned by systematic knowledge mobilisation including support for targeted and prioritised health services research to fill knowledge gaps.

Setting priority processes can provide rich, engaged input to support government funding decisions about HSR. A wide range of dynamic and iterative processes influence decision-making in a rapidly evolving situation in the health system response to COVID-19. It is crucial to consider how major investment decisions will support a value-based healthcare system.

The objectives of this study are twofold: (1) to investigate whether the increase in FLFP enriches women's inclusive rights (economic, social, and political), (2) whether the effect of FLFP on inclusive rights is different across different economics (developed vs developing).

The study utilizes panel data encompassing 188 countries spanning the years 1981–2011. Discrete choice models, namely ordered probit and ordered logit, are employed, while also controlling for observable heterogeneity across countries, including factors such as inflation, income inequality, education, and human rights.

We find a positive association between FLFP and all aspects of women's rights (economic, social, and political). The results related to developed and underdeveloped countries are robust for women's political rights; however, the effect of FLFP on women's social and economic rights is insignificant for developing countries.

The need for continuous policy commitment to gender equality may be needed to bring about equality of inclusive rights (economic, social, and political rights) and to fulfill the sustainable development goals (SDGs). Therefore, the current study particularly adds value in existing research by investigating (empirically) the link between FLFP and different dimensions of women's inclusive rights.

This study aims to examine the acceptance of adaptive learning (AL) amongst construction professionals in Singapore. It seeks to compare their perceptions and attitudes with those of professionals from other industries to assess the rate of AL adoption in the construction sector. Furthermore, the study aims to identify the factors influencing construction professionals’ intention to adopt AL technologies.

A questionnaire survey was conducted with 188 construction professionals and 153 non-construction professionals. By employing the extended unified theory of acceptance and use of technology (UTAUT2) and the general extended technology acceptance model for e-learning (GETAMEL), this study also explored factors influencing construction professionals’ behavioural intention (BI) towards AL adoption. An SEM-machine learning approach facilitated the evaluation of the factors’ influence on BI.

A comparative analysis of the data found that construction professionals’ intention to use AL surpassed 75%, which had no significant difference with professionals from other industries. The findings revealed that learning value (LV) and self-efficacy (SE) were statistically significant predictors of construction professionals’ intentions to use AL. Furthermore, a supervised machine learning analysis identified performance expectancy (PE) as a crucial factor in predicting these intentions.

The study’s focus on self-reported intentions and a specific demographic limits its generalisability; further research should examine actual usage across diverse cultures.

The results offered insights into construction professionals’ perceptions and attitudes towards AL adoption, guiding the integration of AL into construction professional development.

This paper addresses a recognised gap by examining construction professionals’ perceptions and attitudes towards adopting AL.

The COVID-19 pandemic was a shock to the food supply chain without modern precedent. Challenges in production, manufacturing, distribution and retailing led to the highest rates of food price inflation in the US since the 1970s. The major goal of this paper is to describe statistically the impact of the pandemic of food price inflation and volatility in the US and to discuss implications for industry and for policymakers.

We use Bureau of Labor Statistics data to investigate food prices in the US, 2020–2021. We apply 16 statistical approaches to measure price changes and volatility and three regression approaches to measure counterfactuals of food prices, had the pandemic not occurred.

Food price inflation and volatility increased substantially during the early months of the pandemic, with a great deal of heterogeneity across food products and geographic regions. Food price inflation was most pronounced for meats, and contrary to expectations, highest in the western US Forecasting approaches demonstrate that grocery prices were about 7% higher than they would have been without the pandemic as of the end of 2021.

The research on COVID-19 and the food system remains in its nascent stage. As findings on food loss and waste, employment and wages, food insecurity and more proliferate, it is vital to understand how food prices were connected to these phenomena and affected. We also motivate several ideas for future work.

This study aims to explore the role of sustainable fashion knowledge in shaping individual sustainable responsibility within the dynamic landscape of the fashion industry from a novel perspective, by exploring the intricate interplay between sustainable fashion knowledge, emotional and spiritual sustainable capacities.

A quantitative study was used, and a causal model with partial least squares structural equation modeling was developed. A total of 211 valid responses were obtained, and data were analysed to confirm the proposed hypotheses.

The findings confirm the positive impact of sustainable fashion knowledge on individual sustainable responsibility, mediated by both spiritual and emotional sustainable capacities. This study underscores the significance of individuals in influencing societal norms, prompting fashion companies to adopt sustainable practices.

The proposed conceptual framework integrates insights from the emotional and spiritual knowledge dynamics. This study uncovers the pathways through which individuals contribute to a more sustainable society.

The study not only advances the understanding of sustainable fashion practices but also provides actionable insights for policymakers, businesses and individuals seeking to foster a culture of sustainability in the fashion ecosystem.

This study analyses the organizational consequences of work–family conflict (WFC) among female nurses in health care sector. Moreover, this study focuses on the moderating effect of intrinsic motivation on the association between WFC dimensions with different organizational outcomes.

Data are collected from 347 female nurses working in health care sector at Islamabad, Rawalpindi, Lahore, Multan and Bahawalpur regions of Pakistan, using random sampling technique. Regression analysis is used to test the hypotheses of this study.

The findings demonstrate that WFC conflict lowers job satisfaction, affective commitment and organizational citizenship behaviour. Contrary, WFC reduces job satisfaction, affective commitment and organizational citizenship behaviour and increases turnover intentions among female nurses. Moreover, intrinsic motivation moderates the association between WFC and certain organizational outcomes.

The study offers valuable insights for female nurses at health care sector about WFC and finally leads to theoretical contributions and practical implications for the healthcare sector of Pakistan.

Capable service employees are increasingly scarce and costly. Many organizations opt to partially replace, support or augment human employees with AI systems. This study builds a framework to help managers map and understand the challenges of crafting a service climate that fosters synergies between AI and human employees, where customers require value-added, personalized and excellent service.

This conceptual article identifies barriers and facilitators of building a service climate for organizations using both human and AI-based employees through an eclectic review of relevant literature.

A conceptual framework is built, and a future research agenda is brought forth.

By identifying barriers and facilitators for AI–human synergies in service settings, this article clarifies how AI can be made to complement human employees, especially in delivering personalized, value-added services, while also highlighting knowledge gaps.

This study provides a practical framework for integrating AI into the workforce. It offers insights into addressing challenges in creating a service climate that combines human and AI capabilities to maintain service excellence. Identifying key barriers and facilitators, the framework guides managers to improve efficiency and customer satisfaction in a rapidly changing service landscape.

This research offers insights on incorporating AI to address labor shortages while maintaining high-quality, personalized service. It provides a pathway to improving service experiences, especially in sectors facing staffing challenges from an aging population.

This research builds on Bowen and Schneider’s (2014) seminal service climate framework to account for a mix of human and AI-based employees.

This study aims to examine the influence of digital financial literacy (DFL) on the financial well-being (FWB) of students in Andhra Pradesh, specifically exploring the factors of impulsivity and self-control. Both DFL and FWB are treated as multi-dimensional constructs in the study. The research delves into the impact of DFL dimensions, viz. digital financial knowledge, digital financial experience and digital financial skills, on both impulsivity and self-control. Subsequently, the study assesses the effects of impulsivity and self-control on financial well-being.

To gather data, a questionnaire-based survey method was employed, reaching 475 university students through purposive sampling. The study utilizes confirmatory factor analysis for scale validation and structural equation modeling for hypothesis testing.

The results reveal a significantly negative influence of digital financial knowledge (DFK), digital financial experience (DFE) and digital financial skills (DFS) on impulsivity, while demonstrating a significantly positive impact on self-control. Additionally, the study finds that impulsivity negatively affects financial well-being, whereas self-control has a positive impact. Focusing on higher education institutions in Andhra Pradesh, the research highlights students’ limited concern for long-term financial planning.

This study underscores the relevance of understanding the crucial role of digital financial literacy in enhancing their financial well-being. The implications of these research findings are substantial and can be utilized to shape educational programs for students in higher education institutions. Such programs can guide institutions in imparting knowledge and skills related to personal finance management, particularly in the context of the increasing digitalization of financial transactions.

The purpose of this study is to propose an analytical framework for generating main path analysis (MPA) and demonstrate the process involved in identifying, analyzing the MPA on a citation network and empirically testing in the research field chromosome anomalies (CA).

The proposed methodological structure involves five phases of the process. Search path method is used to measure the weights of each citation link from a source vertex to a sink vertex. The key route local main path and global main path are generated to identify the knowledge diffusion trajectories and validated by cross-referencing with existing literature, co-citation analysis and centrality measures of social network analysis.

The empirical validation of this framework within CA research demonstrates its potential for tracing knowledge diffusion and technological development trajectories over three decades. This approach elucidates two major intellectual knowledge flows. The first key-route main path identified the primary diagnostic protocols. The second key-route main path revealed that cancer or carcinogenesis is identified as one of the mainstream of CA.

The limitations of the data and coverage period restrict the scope of this study. MPA was applied exclusively to the most influential sub network and disregarded other sub networks. MPA identified the seminal papers that provided a historical development in diagnostic protocol and their interconnectedness of disorders and diseases. This helps the researchers to develop targeted therapies and interventions, especially in cancer treatment.

Exploiting MPA on CA research provides valuable insights to stakeholders in developing evidence-based public health policies. This is crucial for preventing the birth of children with birth defects or genetic diseases, promoting public health and reducing the socioeconomic burden on a country through enhanced surveillance and prevention efforts.

The study suggests that in addition to traditional scientometrics measures, MPA can be used to trace the evolution of knowledge and technological advancements. It also highlights the role of social network analysis measures in extracting main paths.