Search results

The goal of this article is to provide an overview of healthcare entrepreneurship, both in terms of its current trends and future directions.

The article engages in a systematic review of extant research on healthcare entrepreneurship using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) as the review protocol and bibliometrics or scientometrics analysis as the review method.

Healthcare entrepreneurship research has fared reasonably well in terms of publication productivity and impact, with diverse contributions coming from authors, institutions and countries, as well as a range of monetary and non-monetary support from funders and journals. The (eight) major themes of healthcare entrepreneurship research revolve around innovation and leadership, disruption and technology, entrepreneurship models, education and empowerment, systems and services, orientations and opportunities, choices and freedom and policy and impact.

The article establishes healthcare entrepreneurship as a promising field of academic research and professional practice that leverages the power of entrepreneurship to advance the state of healthcare.

The article offers a seminal state of the art of healthcare entrepreneurship research.

The aim of this paper is to identify some of the challenges that need to be addressed to accelerate the deployment and adoption of smart health technologies for ubiquitous healthcare access. The paper also explores how internet of things (IoT) and big data technologies can be combined with smart health to provide better healthcare solutions.

The authors reviewed the literature to identify the challenges which have slowed down the deployment and adoption of smart health.

The authors discussed how IoT and big data technologies can be integrated with smart health to address some of the challenges to improve health-care availability, access and costs.

The results of this paper will help health-care designers, professionals and researchers design better health-care information systems.

The concept of a sustainable warehouse management system (WMS) is a relevant yet under-researched area within warehousing logistics. The purpose of this research is twofold: first, to review the literature on the topic of socially and environmentally sustainable practices; second, to lay the theoretical base for identifying social and environmental sustainability practices in warehousing operations that can serve as focus areas for WMS operational functions.

This research built knowledge on a systematic literature review and bibliometric analysis in Scopus Elsevier and Web of Science Core Collection databases. After comprehensively filtering English literature from 2016 to 2024, only 43 out of the initial 601 studies comprised relevant warehousing practices that can be incorporated into the scope of WMS activities.

As a result, retrieved practices were allocated to a specifically designed warehouse model within the main processes, equipment and resources. This model could serve as a baseline for incorporating 48 sustainable WMS practices. The prevailing share of practices focuses on environmental rather than social warehouse sustainability. WMS should adopt sustainable warehousing practices to reduce warehouses' carbon footprint, energy and resource consumption and improve working conditions in a warehouse.

There have not been any existing reviews on warehouses' social and environmental sustainability to synthesize knowledge and serve as a base for WMS sustainability. This research will contribute to developing more sustainable and environmentally responsible warehousing operations, ultimately benefiting society and the environment. By incorporating such practices into WMS, warehouse owners can ensure efforts toward social and environmental sustainability while still maintaining efficient operations.

The study aims to investigate the effect of autonomy on employee job performance and the mediation effect of engagement. It also explores whether an employee’s age moderates the model.

Data were collected through a face-to-face survey administered to various types of workers in their workplaces. The selection of companies was based on a database available at the university. Response rate was 35%, yielding 210 instruments with complete responses. Structural Equation Modeling was the chosen method for data analysis.

Results demonstrate a positive and significant relationship between autonomy and engagement as well as between engagement and job performance. Moreover, engagement plays a full mediating role in the relationship between autonomy and job performance. Additionally, while age does not moderate the relationship, it does have a differential impact on the mediation process.

The creation of management strategies focused on resources such as autonomy must be adapted according to seniority, with the purpose of enhancing employee engagement and performance in today’s organizations.

This paper closes a gap between autonomy and Job Demands-Resources theory by providing evidence on the effects of autonomy, engagement and age on job performance.

The purpose of this paper is to develop a theoretical model and investigate the relationship between talent management (TM) processes and knowledge creation (KC) in Australian public and private universities. This is because of the pragmatic advantages for organisations that focus on talents and knowledge.

This research adopted the mixed-methods design. The sample comprised 23 individuals for the qualitative study and 286 individuals for the quantitative survey questionnaire, all conducted in nine public and private universities in Australia.

The qualitative outcomes were utilised to develop the quantitative survey statement. These outcomes are based on a three-stage method of thematic analysis. The core conclusion of the quantitative study is that there is a significantly positive influence on TM processes (TMPs) on KC.

The principle limitation of this study was the scope. It only targeted one country (Australia), one state (Queensland) and a part of the higher education sector (the university).

This research designed a quantitative instrument of TMPs and KC for the Australian educational institutions. The instrument is severely designed and comprehensively conceptualised utilising social, excellent, performance, strategic, behavioural and developmental concepts within TMPs with innovative, informational and technological concepts underlining KC within the Australian public and private universities in Queensland.

The study adds value to both TM and knowledge management literature through designing a conceptual model that links both of these variables in one tool regarding the university sector.

This study investigated the effects of an intercultural communication (IC) course on Emirati university students' intercultural sensitivity (IS).

The participants were 89 Emirati students. The course required student involvement in a variety of tasks and activities, both inside and outside the classroom. The development of the students' IS was tracked using two instruments: the Intercultural Sensitivity Scale (ISS) and a reflective writing task.

The difference between the students' overall pre-test and post-test scores was at a statistically significant level. The data from the reflective writing papers showed that the course developed the students' IS with a particular effect on their awareness of other cultures, barriers to effective communication and self-confidence.

In an increasingly globalized world, the findings of this study highlight the importance of a course designed to enhance university students' IS and therefore intercultural competence. They also indicate the need for more experiential learning to bridge in-class and out-of-class experiences which facilitate the development of students' intercultural competence.

The practice of frontline employees articulating their brand voice and posting work-related content on social media has emerged; however, employee brand equity (EBE) research has yet to be linked to employees’ social media activity. This paper aims to take a methods-based approach to better understand employees’ roles as influencers. As such, its objective is to operationalize and apply the three EBE dimensions – brand consistent behavior, brand endorsement and brand allegiance – using Instagram data.

This qualitative research uses a case study of employee influencers at SoulCycle, a leading North American fitness company and examines 100 Instagram images and 100 captions from these influential employees to assess the three EBE dimensions.

Brand consistent behavior (what employees do) was the most important EBE dimension indicating that employees’ social media activities align with their employer’s values. Brand allegiance (what employees intend to do in the future) whereby employees self-identify with their employer on social media, followed. Brand endorsement (what employees say) was the least influential of the three EBE dimensions, which may indicate a higher level of perceived authenticity from a consumer perspective.

This research makes three contributions. First, it presents a novel measure of EBE using public Instagram data. Second, it represents a unique expansion and an evolution of King et al.’s (2012) model. Third, it considers employees’ work-related content on social media to understand employees’ role as influencers and their co-creation of EBE, which is currently an under-represented perspective in the internal branding literature.

Our study was designed to investigate the longitudinal trajectories of student leader development capacities in a sample of students enrolled in multiple leadership-focused courses across several semesters. Our goal was to assess the degree to which course enrollment was associated with growth over the time that students engage as undergraduates in academic leadership programs, and if so, to assess the shape and speed of capacity change.

We utilized a multilevel intra-individual modeling approach assessing students’ motivation to lead, leader self-efficacy, and leadership skills across multiple data collection points for students in a campus major or minor focused on leadership studies. We compared an unconditional model, a fixed effect model, a random intercept model, a random slope model, and a random slope and intercept model to determine the shape of score trajectories. Our approach was not to collect traditional pre-test and post-test data – choosing to collect data only at the beginning of each semester – to reduce time cues typically inherent within pre-test and post-test collections.

Our results strongly suggested that individual students differ greatly in the degree to which they report the capacity to lead when initially enrolling in their first class. Surprisingly, the various models were unable to predict a pattern of longitudinal leader development through repeated course enrollment in our sample.

Our investigation employed statistical methods that are not often utilized in leadership education quantitative research, and also included a data collection effort designed to avoid a linear pre-test/post-test score comparison.

In this paper, the authors study the production and pricing decisions of a remanufacturing supply chain composed of a supplier, an assembler and a remanufacturer, in which the remanufacturing of components requires patent licensing from the supplier.

The authors consider three different models with government subsidy for remanufacturing: (1) no government subsidies; (2) the government subsidizes the remanufacturing behavior of the supplier and (3) the government subsidizes the remanufacturing behavior of the remanufacturer and use the Stackelberg game model to solve and analyze the equilibrium wholesale prices of components and the equilibrium outputs of new and remanufactured products under three subsidy modes.

The results show that the equilibrium wholesale prices of two kinds of components decrease with the unit patent licensing fee and the unit government subsidy, and the equilibrium quantity of the remanufactured products under the three modes is obviously higher than that of the new products.

Finally through numerical simulation, it is found that the equilibrium profits of the supplier, the manufacturer and the supply chain increase monotonously in relation to the unit government subsidy, while the optimal profit of the assembler in relation to the unit government subsidy tends to decrease first and then increase.

The purpose of this article is to explore how participants with different motivations (educational or leisure), familiarity with the medium (newbies and active Twitter users), and participating instructions respond to a highly structured digital social reading (DSR) activity in terms of intensity of engagement and social interaction.

A case study involving students and teachers of 211 Italian high school classes and 242 other Twitter users, who generated a total of 18,962 tweets commenting on a literary text, was conducted. The authors performed both a quantitative analysis focusing on the number of tweets/retweets generated by participants and a network analysis exploiting the study of interactions between them. The authors also classified the tweets with respect to their originality, by using both automated text reuse detection approaches and manual categorization, to identify quotations, paraphrases and other forms of reader response.

The decoupling (both in space and time) of text read (in class) and comments (on Twitter) likely led users to mainly share text excerpts rather than original personal reactions to the story. There was almost no interaction outside the classroom, neither with other students nor with generic Twitter users, characterizing this project as a shared experience of “audiencing” a media event. The intensity of social interactions is more related to the breadth of the audience reached by the user-generated content and to a strong retweeting activity. In general, better familiarity with digital (social) media is related to an increase in the level of social interaction.

The authors analyzed one of the largest educational social reading projects ever realized, contributing to the still scarce empirical research about DSR. The authors employed state-of-the-art automated text reuse detection to classify reader response.