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This article investigates the application of generative artificial intelligence (GenAI) in experiential learning for authentic assessment in higher education. Recognized for its human-like content generation, GenAI has garnered widespread interest, raising concerns regarding its reliability, ethical considerations and overall impact. The purpose of this study is to explore the transformative capabilities and limitations of GenAI for experiential learning.

The study uses “thing ethnography” and “incremental prompting” to delve into the perspectives of ChatGPT 3.5, a prominent GenAI model. Through semi-structured interviews, the research prompts ChatGPT 3.5 on critical aspects such as conceptual clarity, integration of GenAI in educational settings and practical applications within the context of authentic assessment. The design examines GenAI’s potential contributions to reflective thinking, hands-on learning and genuine assessments, emphasizing the importance of responsible use.

The findings underscore GenAI’s potential to enhance experiential learning in higher education. Specifically, the research highlights GenAI’s capacity to contribute to reflective thinking, hands-on learning experiences and the facilitation of genuine assessments. Notably, the study emphasizes the significance of responsible use in harnessing the capabilities of GenAI for educational purposes.

This research showcases the application of GenAI in operations management education, specifically within lean health care. The study offers insights into its capabilities by exploring the practical implications of GenAI in a specific educational domain through thing ethnography and incremental prompting. Additionally, the article proposes future research directions, contributing to the originality of the work and opening avenues for further exploration in the integration of GenAI in education.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

The purpose of this study is to evaluate how Qatar Airways’ sponsorship of FC Barcelona affects Qatar’s sports diplomacy and brand awareness. It focuses on the sponsorship’s demand strategy and takes into account the opinions and attitudes of Spanish nationals toward Qatar and Qatar Airways.

To assess this, a survey of 434 Spanish nationals from 17 different regions from four zones (North, South, Center, and East) in Spain between November 3, 2022 and November 21, 2022 was conducted using a strata sampling method.

We argue that Qatar Airways’ sponsorship of FC Barcelona serves to improve Qatar’s recognition and national reputation in Spain. We also found that there is a need for consistent sponsorship and marketing efforts in sports diplomacy to better fulfill public diplomacy aims. Overall, this paper concludes that Qatar Airways’ sponsorship of FC Barcelona positively contributes to the country’s sports diplomacy despite significant challenges.

The major contribution of this study to the literature is the discussion of the role of sports sponsorships in the recognition of the sponsor, which was assessed through conducting a quantitative analysis of public opinion in the sponsored team’s host country.

Infrastructure forms a basis for the operations and sustainability of the modern society. This paper aims to recognize value creation from the infrastructure procurement ecosystem perspective to achieve those goals. The pursuit of enhancing value creation involves an examination of infrastructure procurement challenges, boundaries as well as boundary spanners that facilitate effective knowledge transfer and interaction.

The qualitative study is based on content analysis of 25 thematic interviews. Data was transcribed and coded via Atlas.ti software.

Infrastructure procurement value creation challenges appear complex and related to boundaries that hamper collaboration, coordination and knowledge sharing. Our results show that these boundaries locate within and between different levels of procurement ecosystem. Therefore, value creation in infrastructure procurement requires boundary spanners for leveraging knowledge sharing and interaction. Artifacts, discussion, processes and brokers as identified boundary spanners are strongly nested and interrelated in the industry. Special attention should be given to supporting individuals to act as brokers, since they play the key roles in trust building, culture steering and usage of other boundary spanners.

Promoting value creation in infrastructure procurement helps to achieve socio-economic development goals.

This study offers a unique perspective on value creation in the context of infrastructure by adopting an ecosystem lens and examining boundary crossing mechanisms. The results support future development of collaboration and knowledge sharing practices fostering procurement productivity.

We empirically assessed the antecedents of subjective well-being at work for French permanent employees.

The methodology includes qualitative and quantitative data analyses. In the first phase, interviews elicited the antecedents of subjective well-being at work among permanent French employees. In the second phase, a questionnaire survey was used to confirm the relevance of the antecedents uncovered in the first phase.

We found 14 distinct elements that influence French employees’ subjective well-being at work: corporate culture, job dissonance, relationships with colleagues, achievement, professional development, relationships with superiors, status, workload, perks, feedback, workspace, diversity and pay. Moreover, we identified discrete antecedents for the three components of subjective well-being at work: work achievement and relationships with superiors and colleagues for positive emotions at work, job dissonance and workload for negative emotions at work and organizational culture and professional development for satisfaction with one’s work.

The original contribution of this study is to have unpacked the black box of the antecedents of subjective well-being in the French workplace and to have uncovered discriminant predictors for each of the three components of subjective well-being at work. Furthermore, we specifically linked each of these three components with their most significant antecedents.

The impact of digital technology in the wider travel field has been substantial and significant, changing both the competitive landscape of businesses and the behavior of travelers. However, we are now on the cusp of new digital developments encompassing cloud computing, blockchain, internet of things (IoT) and above all, artificial intelligence (AI), which are predicted to disrupt the business and consumer sides of several industries – travel included. This study aims to frame this upcoming digital transformation in travel within a human-centered approach where the critical understanding of digital humanism principles will enrich social scientists’ research agenda in the coming years.

The viewpoint follows a structure based on (i) setting the scene for the rise of digital transformation, (ii) the historical perspective on digital transformation in travel, (iii) the pandemic’s impact and (iv) future development and research agenda.

It is only by fostering a human-centered digital transformation perspective that social science researchers in travel can realize the “high-tech for high-touch” promise of fostering a human-to-human encounter empowered and possibly hampered, by digital technologies. This work proposes to start from the concepts of digital technology control, participation, education and ethics to design a research agenda with a 2050 horizon.

This work has been designed to shift the attention of researchers toward a human-centered digital transformation approach to reflect on the human-machine relationship for a better society. Due to its inner characteristics the travel field can foster a reflection on this topic by reaffirming the centrality of human beings and their authorship in the travel product creation.

数字技术在更广泛的旅游领域产生了巨大而显著的影响, 改变了企业的竞争图景和游客行为。然而, 我们现在正处于新的数字发展的风口浪尖, 包括云计算、区块链、物联网以及最重要的人工智能, 预计这些技术将颠覆包括旅游业在内的多个行业的企业端和消费端。这项研究建议将即将到来的旅行数字化转型纳入以人为本的方法, 对数字人文主义原则的批判性理解将丰富社会科学家未来几年的研究议程。

该观点遵循基于以下方面的一种结构, (i)为数字化转型的兴起设定场景, （ii）旅行数字化转型的历史视角, (iii)疫情的影响和（iv）未来发展和研究议程。

只有培养以人为中心的数字化转型视角, 旅游领域的社会科学研究人员才能实现“高科技换高品质”的承诺, 培养一种被数字技术赋能但也可能受到阻碍的人与人之间的接触。这项工作建议从数字技术控制、参与、教育和伦理的概念出发, 设计一个2050年的研究议程。

这项工作旨在将研究人员的注意力转移到以人为中心的数字化转型方法上, 以反思更美好社会的人机关系。由于旅游领域的内在特征, 它可以通过重申人在旅游产品创造中的中心地位和作者身份来促进对这一主题的反思。

El impacto de la tecnología digital en el ámbito de los viajes en general ha sido sustancial y significativo, cambiando tanto el panorama competitivo de las empresas como el comportamiento de los viajeros. Sin embargo, en la actualidad estamos en la cúspide de nuevos desarrollos digitales que abarcan la nube informática, blockchain, IoT y, sobre todo, la inteligencia artificial, que se prevé que alteren los aspectos comerciales y de consumo de varias industrias, incluidos los viajes. Esta investigación propone enmarcar esta próxima transformación digital en los viajes dentro de un enfoque centrado en el ser humano, donde la comprensión crítica de los principios del humanismo digital enriquecerá la agenda de investigación de los científicos sociales en los próximos años.

El presente trabajo presenta una estructura basada en (i) el establecimiento del escenario para el auge de la transformación digital, (ii) la perspectiva histórica de la transformación digital en los viajes, (iii) el impacto de la pandemia y (iv) el desarrollo futuro y líneas de investigación.

Únicamente si se fomenta una perspectiva de transformación digital centrada en el ser humano podrán los investigadores de las ciencias sociales en el ámbito de los viajes hacer realidad la promesa de “alta tecnología para un alto contacto”, promoviendo un encuentro entre seres humanos potenciado, y posiblemente obstaculizado, por las tecnologías digitales. Este trabajo propone partir de los conceptos de control de la tecnología digital, participación, educación y ética para diseñar una agenda de investigación con horizonte 2050.

Este trabajo ha sido diseñado para desplazar la atención de los investigadores hacia un enfoque de transformación digital centrado en el ser humano para reflexionar sobre la relación ser humano-máquina para una sociedad mejor. Por sus características internas, el ámbito de los viajes puede propiciar una reflexión sobre este tema reafirmando la centralidad del ser humano y su autoría en la creación del producto turístico.