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The purpose of the paper is to highlight the role of Artificial Intelligence (AI) in the healthcare industry through the Ayushman Bharat health protection scheme by analyzing various technologies being integrated to improve the customer service and experiences in India. The key focus lies on the understanding of the influence of AI in the healthcare system services, the clinical treatment, and the facilities to progress with accurate and precise health screening in India.

A systematic study on the emerging technologies of AI and the applications in the healthcare sector is presented in the form of a viewpoint.

AI certainly enhances experiential services; however, it cannot surpass the human touch which is an essential determinant of experiential healthcare services. AI acts as an effective complementary dimension to the future of healthcare.

This viewpoint discusses the applications and role of AI with the help of relevant examples. It highlights the different technologies being applied and how they will be used in the future focusing upon the Ayushman Bharat health protection scheme in India.

This study aims to explore how the boundary between science and society can be addressed to support the transformation of higher education towards sustainable development (HESD) in the sense of the whole institution approach. It analyses students’ learning experiences in self-led sustainability projects conducted outside formal curricula to highlight their potential contribution to HESD. The students’ projects are conceived as learning spaces in “sustainability-oriented ecologies of learning” (Wals, 2020) in which five learning dimensions can be examined.

Using an iterative, grounded-theory-inspired qualitative approach and sensitising concepts, 13 in-depth semi-structured interviews were conducted exploring students’ learning experiences. Interviews were categorised in MAXQDA and analysed against a literature review.

Results revealed that students’ experiences of non-formal learning in self-led projects triggered deep learning and change agency. Trust, social cohesion, empowerment and self-efficacy were both results and conditions of learning. Students’ learnings are classified according to higher education institutions’ (HEIs) sustainability agendas, providing systematised insights for HEIs regarding their accommodative, reformative or transformative (Sterling, 2021) path to sustainable development.

The education for sustainable development (ESD) debate focuses mainly on ESD competences in formal settings. Few studies explore students’ learnings where formal and non-formal learning meet. This article investigates a space where students interact with different actors from society while remaining rooted in their HEIs. When acting as “change agents” in this hybrid context, students can also become “boundary agents” helping their HEIs move the sustainability agenda forward towards a whole institution approach. Learning from students’ learnings is thus proposed as a lever for transformation.

Drawing on an intersectional perspective on racial, migrant and entrepreneurial identities, this paper investigates the identity work of racial minority entrepreneurs with native-born and migrant backgrounds, confronted to experiences of othering in a White entrepreneurial ecosystem.

The study takes a qualitative-interpretivist approach and builds on six cases of racial minority entrepreneurs in nascent stages of venture development within the Dutch technology sector. The dataset comprises 24 in-depth interviews conducted over the course of one and a half year, extensive case descriptions and online sources. The data is thematically and inductively analysed.

Despite strongly self-identifying as entrepreneurs, the research participants feel marginalised and excluded from the entrepreneurial ecosystem, which results in ongoing threats to their existential authenticity as they build a legitimate entrepreneurial identity. Minority entrepreneurs navigate these threats by either downplaying or embracing their marginalised racial and/or migrant identities.

The study contributes to the literature on the identity work of minority entrepreneurs. The paper reveals that, rather than “strategising away” the discrimination and exclusion resulting from othering, racial minority entrepreneurs seek to preserve their sense of existential authenticity and self-worth, irrespective of entrepreneurial outcomes. In so doing, the study challenges the dominant perspective of entrepreneurial identity work among minority entrepreneurs as overly instrumental and market-driven. Moreover, the study also contributes to the literature on authenticity in entrepreneurship by highlighting how racial minority entrepreneurs navigate authenticity threats while building legitimacy in a White ecosystem.

The research aims to understand how smart speakers are perceived by their actual and potential users, their attitude towards smart speakers and consequently their intention to use them.

The authors apply a structural equation modelling (SEM) approach to test the research hypotheses through data coming from a structured questionnaire.

The results show that the higher the importance attributed to usefulness and ease of use, the higher the positive attitude that in turn positively affects the intention to use smart speakers. A significant relationship also emerged between task technology fit and attitude towards smart speakers, as well as between perceived enjoyment and attitude towards smart speakers. Perceived privacy risk, innovativeness and social attraction have been found to not significantly impact attitudes towards smart speakers.

Although several academic studies have focused on various aspects of smart technologies, only a few studies discuss the factors that push consumers to use smart speakers for activities related to commercial transactions. Therefore, looking at the rapid rise of smart speakers for daily tasks and the gradual acceptance of voice interaction with digital tools, the authors proposed a study about Italian users' intention to use smart speakers. Specifically, to fill the gap in the existing literature, the authors applied a SEM approach to identify utilitarian and hedonic benefits that motivate the use of these devices.

Digital voice assistants use wake word engines (WWEs) to monitor surrounding audio for detection of the voice assistant's name. There are two failed conditions for a WWE, false negative and false positive. Wake word false positives threaten a loss of personal privacy because, upon activation, the digital assistant records audio to the voice cloud service for processing.

This observational study attempted to identify which Amazon Alexa wake word and Amazon Echo smart speaker resulted in the fewest number of human voice false positives. During an eight-week period, false-positive data were collected from four different Amazon Echo smart speakers located in a small apartment with three female roommates.

Results from this study suggest the number of human voice false positives are related to wake word selection and Amazon Echo hardware. Results from this observational study determined that the wake word Alexa resulted in the fewest number of false positives.

This study suggests Amazon Alexa users can better protect their privacy by selecting Alexa as their wake word and selecting smart speakers with the highest number of microphones in the far-field array with 360-degree geometry.

A review of previous studies on the voices of employees and knowledge workers clarifies that paying attention to employees' voice is critical in human resource management. However, limited studies have been conducted on it, and much less emphasis has been placed compared to other human resource management activities such as human resource planning. Therefore, the voice of knowledge employees has been one of the critical issues that have attracted a great deal of attention recently. Nonetheless, there is no evidence of various comprehensive and integrated voice mechanisms. As a result, this study aims to design knowledge workers' voice patterns in knowledge-based companies specialising in information and communication technology (ICT) in Iran in May and June 2020.

This study is a qualitative grounded theory research. We collected the data from a target sample of 15 experts in knowledge-based ICT companies using in-depth semi-structured interviews. Since all the participants had practised the employee voice process, they were regarded as useful data sources. Data analysis was also performed using three-step coding (open, axial and selective) by Atlas T8, which eventually led to identifying 14 components and 38 selected codes. We placed identified components in a paradigm model, including Personality Characteristics, Job Factors, Economic Factors, Cultural Factors, Organisational Policies, Organisational Structure, Climate Of Voice in the Organisation, Management Factors, Emotional Events, Communications and Networking, Contrast and Conflict and, etc. Then, the voice pattern of the knowledge staff was drawn.

The results showed that constructive knowledge voice influences the recognition of environmental opportunities and, additionally, it helps the competitive advantages among the employees. By forming the concept of knowledge staff voice, it can be concluded that paying attention to knowledge staff voice leads to presenting creative solutions to do affairs in critical situations. The presentation of these solutions by knowledge workers results in the acceptance of environmental changes, recognition and exploitation of new chances and ideas, and sharing experiences in Iranian knowledge-based companies.

Strengthening and expanding the voice of employees in knowledge-oriented companies can pave the way to growth and development towards a higher future that prevents the waste of tangible and intangible assets.

Companies' ability to engage in knowledge workers is a vital factor in human resource management and strategic management. However, the employee voice has not been involved integrally in the context of corporate.

The purpose of the present article is to highlight the role of Artificial Intelligence (AI) and Robotics in the tourism industry. The various technologies being integrated to improve the service and customer experience in tourism. The expected changes and challenges in tourism in the future are focused in this paper.

A systematic study on the emerging technologies of AI and Robotics applied in the tourism sector is presented in the form of a viewpoint.

AI certainly enhances tourism experiential services however cannot surpass the human touch which is an essential determinant of experiential tourism. AI acts as an effective complementary dimension to the future of tourism. With the emergence of artificial travel intelligence, it is simpler to make travel arrangements. AI offers travel services that are automated, customized and insightful. AI allows travelers to learn about their behaviors, interests to inclinations and provide a personalized experience. Gone are the days to consult a travel agent, meet him physically and indulge in an endless chain of troubling phone calls to inquire about travel arrangements.

Tourism marketing to see a positive and improved change that will enhance the tourists’ overall experience due to the application of AI and Robotics. New emerging technologies like chatbots, virtual reality, language translators, etc. can be effectively applied in Travel, Tourism & Hospitality industry.

The present viewpoint discusses the application and role of AI and Robotics with the help of relevant industry examples and theory. The present paper highlights the different technologies being used and will be used in the future.

With the advent of increasingly sophisticated AI, the nature of work in the service frontline is changing. The next frontier is to go beyond replacing routine tasks and augmenting service employees with AI. The purpose of this paper is to investigate whether service employees augmented with AI-based emotion recognition software are more effective in interpersonal emotion regulation (IER) and whether and how IER impacts their own affective well-being.

For the underlying study, an AI-based emotion recognition software was developed in order to assist service employees in managing customer emotions. A field study based on 2,459 call center service interactions assessed the effectiveness of the AI in augmenting service employees for IER and the immediate downstream consequences for well-being relevant outcomes.

Augmenting service employees with AI significantly improved their IER activities. Employees in the AI (vs control) condition were significantly more effective in regulating customer emotions. IER goal attainment, in turn, mediated the effect on employee affective well-being. Perceived stress related to exposure to the AI augmentation acted as a competing mediator.

Service firms can benefit from state-of-the-art AI technology by focusing on its capacity to augment rather than merely replacing employees. Furthermore, signaling IER goal attainment with the help of technology may provide uplifting consequences for service employee affective well-being.

The present study is among the first to empirically test the introduction of an AI-fueled technology to augment service employees in handling customer emotions. This paper further complements the literature by investigating IER in a real-life setting and by uncovering goal attainment as a new mechanism underlying the effect of IER on the well-being of the sender.

The purpose of this paper is to facilitate the spread of accessible e-books, especially ones of STEM much more in developing countries, an efficient/systematic scheme to localize tools for producing/reading them should be established. Furthermore, even in many advanced countries, Print-disabled people still do not have a good tool to write a content including technical notations such as mathematical formulas in their own local language. This work is aimed at giving a practical solution for those problems.

Here, multilingual support in a tool to produce accessible STEM contents and its new localization scheme are discussed.

It is shown that the accessible STEM-document editor can be customized easily for print-disabled people so that they can read and author a material including complicated technical notations in their own local language. The localization for Vietnamese and other various languages actually has been worked on.

The Vietnamese version was completed, and some prototype versions for the other languages were also given. It is expected that the software can contribute to improve STEM accessibility much more in many countries.