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The purpose of this paper is to investigate the implementation of digital transformation in small and medium-sized enterprises in Vietnam.

The research features in-depth personal interviews with SME executives and managers.

The findings of this study may be summarized into five main areas: (1) multi-tasking role and scarcity of resources; (2) risk; (3) data-driven decision-making processes; (4) efficient communications; and (5) strategic issues. These categories emerged from the content analysis process.

Qualitative research provides a good explanation for situations in actual firms but may not always be generalizable.

Means of overcoming problems with implementing digital transformation in Vietnamese SMEs are provided.

Most studies of Vietnamese companies focus on intensive manufacturing and membership in supply chains. Few studies consider the emergent service and technology sector.

This paper aims to assess the face validity to inform content validity of the Quality of Life – Aged Care Consumers (QOL-ACC), a new measure for quality assessment and economic evaluation in aged care.

Semi-structured interviews were conducted with older adults (66–100 years) receiving aged care services at home (n = 31) and in residential care (n = 28). Participants provided feedback on draft items to take forward to the next stage of psychometric assessment. Items were removed according to several decision criteria: ambiguity, sensitive wording, not easy to answer and/or least preferred by participants.

The initial candidate set was reduced from 34 items to 15 items to include in the next stage of the QOL-ACC development alongside the preferred response category. The reduced set reflected the views of older adults, increasing the measure’s acceptability, reliability and relevance.

Quality of life is a key person-centred quality indicator recommended by the recent Royal Commission into Aged Care Quality and Safety. Responding to this policy reform objective, this study documents a key stage in the development of the QOL-ACC measure, a new measure designed to assess aged care specific quality of life.

This study aimed to examine the similarities and differences between the ability to analyze the environment and exploit new knowledge (absorptive capacity) and the skills to generate value from innovation (appropriation). These fields have similar origins and are sometimes confused by practitioners and academics.

A review was conducted based on a full-text analysis of 681 and 431 papers on appropriation and absorptive capacity, respectively, from Scopus, Science Direct and Lens, using methodologies such as text mining, backward citation analysis, modularity clustering and latent Dirichlet allocation analysis.

In business disciplines, the fields are considered different; however, in other disciplines, it was found that some authors defined them quite similarly. The citation analysis results showed that appropriation was more relevant to absorptive capacity, or vice versa. From the dimension perspective, it was found that although appropriation was considered a relevant element for absorptive capacity, the last models did not include it. Finally, it was found that studies on both topics identified the importance of appropriation and absorptive capacity for innovation performance, knowledge management and technology transfer.

This is one of the first studies to examine in-depth the relationship between appropriation and absorptive capacity, bridging a gap in both fields.

This paper identifies the effects of different dimensions of the cuteness (i.e. baby schema cuteness and whimsical cuteness) of artificial intelligence (AI) agents on attachment to them. In addition, the current paper examines the consequences of the attachment to AI agents.

A pretest to validate the measurement scale for the attachment to AI agents and a survey study were conducted with AI agent users. The authors used structural equation modeling to analyze the data for hypothesis testing.

The baby schema and whimsical cuteness of AI agents drive consumers to develop stronger attachments to their AI agents. This is because consumers perceive cute AI agents as being more trustworthy. As a result, consumers who feel attached to their AI agents are more inclined to report higher satisfaction and commitment levels. They are also more likely to purchase products or services recommended by their AI agents and use them more frequently.

Despite the growing popularity of AI agents, there is a lack of understanding regarding which characteristics of AI agents affect consumer behavior. Therefore, this research examines how the attribute of cuteness influences consumers' attachment to AI agents and subsequently affects their satisfaction and purchase intention toward products recommended by AI agents. Our study demonstrates that the element of cuteness in AI agents plays a crucial role in shaping perceptions of benevolence trustworthiness, as well as fostering users' attachment to AI agents. Furthermore, we observe positive consumer behaviors as a result of their attachment to AI agents. The findings from this study provide valuable insights for practitioners on how to effectively utilize cuteness in AI agents.

This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned characteristics, that has generated a greater impact, offering clarity to tourism managers on the type of content they should publish to achieve greater visibility.

The methodology used in this work combines content analysis and data mining techniques. The classification tree using the chi-square automatic interaction detector (CHAID) algorithm was selected to determine predictors of like behaviour.

The results show that the predictor variables have been emotions, social marketing and topics. Also, the characteristics of the messages most likely to have a high impact are those related to emotions of joy or happiness, their purpose is behavioural, and they talk about rural, cultural issues, special dates, getaways, or highlights of a town or city for something specific.

This study is the first to analyze the content of the tweets shared by destination tourism managers from a social marketing, positive emotions, and sustainability perspective, determining the possible predictors of likes on Twitter. The authors contribute to the literature by deepening the understanding of how social marketing and the positive emotions promoted drive a more significant impact in tourism communication campaigns on social media. The authors provide destination managers with a way better to understand the variables relevant to users in tourism content.

Recent changes in university systems, debates on academic freedom, and changing roles of knowledge in society all point to questions regarding how higher education and research should be governed and the role of scientists and faculty in this. Rationalizations of systems of higher education and research have been accompanied by the questioning and erosion of faculty authority and challenges to academic collegiality. In light of these developments, we see a need for a more conceptually precise discussion about what academic collegiality is, how it is practiced, how collegial forms of governance may be supported or challenged by other forms of governance, and finally, why collegial governance of higher education and research is important.

We see collegiality as an institution of self-governance that includes formal rules and structures for decision-making, normative and cognitive underpinnings of identities and purposes, and specific practices. Studies of collegiality then, need to capture structures and rules as well as identities, norms, purposes and practices. Distinguishing between vertical and horizontal collegiality, we show how they balance and support each other.

Universities are subject to mixed modes of governance related to the many tasks and missions that higher education and research is expected to fulfill. Mixed modes of governance also stem from reforms based on widely held ideals of governance and organization. We examine university reforms and challenges to collegiality through the lenses of three ideal types of governance – collegiality, bureaucracy and enterprise – and combinations thereof.

Research on artificial intelligence (AI) and its potential effects on the workplace is increasing. How AI and the futures of work are framed in traditional media has been examined in prior studies, but current research has not gone far enough in examining how AI is framed on social media. This paper aims to fill this gap by examining how people frame the futures of work and intelligent machines when they post on social media.

We investigate public interpretations, assumptions and expectations, referring to framing expressed in social media conversations. We also coded the emotions and attitudes expressed in the text data. A corpus consisting of 998 unique Reddit post titles and their corresponding 16,611 comments was analyzed using computer-aided textual analysis comprising a BERTopic model and two BERT text classification models, one for emotion and the other for sentiment analysis, supported by human judgment.

Different interpretations, assumptions and expectations were found in the conversations. Three subframes were analyzed in detail under the overarching frame of the New World of Work: (1) general impacts of intelligent machines on society, (2) undertaking of tasks (augmentation and substitution) and (3) loss of jobs. The general attitude observed in conversations was slightly positive, and the most common emotion category was curiosity.

Findings from this research can uncover public needs and expectations regarding the future of work with intelligent machines. The findings may also help shape research directions about futures of work. Furthermore, firms, organizations or industries may employ framing methods to analyze customers’ or workers’ responses or even influence the responses. Another contribution of this work is the application of framing theory to interpreting how people conceptualize the future of work with intelligent machines.

This chapter explores how industrial PhD students are engaged in authentic leadership processes while coping with challenges through self-leadership. The authors illustrate how self-leadership can be a helpful approach to managing the leading-and-being-led dilemma. They argue that self-leadership is a process of goal achievement in collaboration with key stakeholders and, therefore, an important aspect of authentic leadership. The authors identify four aspects of self-leadership that influence authenticity: roles, resources, relations and results. Kringelum, Mortensen and Holmgren call for research into the emergence of self-leadership and authentic leadership, the leadership capabilities required and the double-sidedness and dilemmas inherent in such emergences across different contexts.