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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.

Financial services industry is increasingly showing interest in automated financial advisors, or robo-advisors, with the aim of democratizing access to financial advice and stimulating investment behavior among populations that were previously less active and less served. However, the extent to which consumers trust this technology influences the adoption of rob-advisors. The resemblance to a human, or anthropomorphism, can provide a sense of social presence and increase trust.

In this paper, we conduct an experiment (N = 223) to test the effect of anthropomorphism (low vs medium vs high) and gender (male vs female) of the robo-advisor on social presence. This perception, in turn, enables consumers to evaluate personality characteristics of the robo-advisor, such as competence, warmth, and persuasiveness, all of which are related to trust in the robo-advisor. We separately conduct an experimental study (N = 206) testing the effect of gender neutrality on consumer responses to robo-advisory anthropomorphism.

Our results show that consumers prefer human-alike robo-advisors over machinelike or humanoid robo-advisors. This preference is only observed for male robo-advisors and is explained by perceived competence and perceived persuasiveness. Furthermore, highlighting gender neutrality undermines the positive effect of robo-advisor anthropomorphism on trust.

We contribute to the body of knowledge on robo-advisor design by showing the effect of robot’s anthropomorphism and gender on consumer perceptions and trust. Consequently, we offer insightful recommendations to promote the adoption of robo-advisory services in the financial sector.

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 purpose of this article is to theoretically outline and empirically test two contribution-based indicators: (1) the scholars' annual contribution-based measurement and (2) the annual contribution modified h-index, computing six criteria: total number of papers, computed SCImago Journal Rank values, total number of authors, total number of citations of a scholar’s work, number of years since paper publication and number of annual paper citations.

Despite widespread scholarly agreement about the relevance of research production in evaluation and recruitment processes, the proposed mechanisms for gauging publication output are still rather elementary, consequently obscuring each individual scholar’s contributions. This study utilised the Technique for Order of Preference by Similarity to Ideal Solution method, and the authors built two indicators to value author's contribution.

To test both indicators, this study focussed on the most productive scholars in communication during a specific time period (2017–2020), ranking their annual research contribution and testing it against standard productivity measures (i.e. number of papers and h-index).

This article contributes to current scientometric studies by addressing some of the limitations of aggregate-level measurements of research production, providing a much-needed understanding of scholarly productivity based on scholars' actual contribution to research.

The purpose of this study was to gather insights from sport marketing professionals and identify key opportunities, challenges and knowledge that sport marketing educators and researchers could utilize in developing curriculum and research agendas.

A qualitative approach was used, and data were collected through in-depth interviews with 15 sport marketing professionals. Participants were asked questions related to the knowledge, skills and experiences that they believe are important for students to have to be successful in the industry, as well as the types of research that would be most useful in their day-to-day work.

Industry professionals noted collaboration, transformation in digital marketing, data and analytics and experiential marketing as key trends facing the industry today. The findings suggest that sport marketing curriculum should focus on soft skill development such as communication, relationship building and empathy alongside hard skill development such as data analysis and storytelling. As well, findings show research areas where scholars can aid practitioners with a focus on consumer insights, technology, measuring ROI and experiential marketing.

With these findings, educators and scholars can better prepare students for successful careers in industry and contribute to the ongoing advancement of the scholarly field. This study serves as a starting point for further research in this area, and it is hoped that it will spark continued collaboration between academia and industry.

The purpose of this research is to develop empirically grounded propositions for further research into UK manufacturing productivity.

Interviews were conducted with managers from strategic, tactical and operational levels from four manufacturing sectors to produce case studies. A modified strategic alignment theory framework was used to code, compare and contrast narratives on perceived productivity antecedents, definitions, compatibility with the definition from the UK Office for National Statistics, and vertical alignment issues within and across cases.

It was found that different key antecedents can facilitate and/or prevent strategic vertical alignment. Discussion reveals complex nuances in perceptions of manufacturing productivity and using the modified strategic alignment theory/productivity antecedent framework.

In revealing the alignment or otherwise of productivity definitions at different levels within the firm, the paper reveals nine propositions for future research including definitions, skills, metrics, performance measurement systems, people and system-centric perspectives, the value-added perspective of productivity and the role of innovation.

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.