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This research finds out to what extent companies’ names are influenced by the place’s attributes versus the official branding policies of a place and, consequently, whether and how local companies “buy into” the place’s strategies put forth by official bodies.

This paper is both conceptual and empirical, as a mixed quantitative and interpretive approach is used. The companies’ names of a tourist industry (the tour and guiding companies) in three destinations are compared and pitched against the branding of these cities. The companies' names are classified into categories to ascertain whether they reflect (or diverge from) the official strategies. Finally, a conceptual model is developed to explain the findings: the strategic naming model (SNM).

Our main finding is that the overall business features of a place being stronger determinants to the naming strategies than tourist destination branding initiatives. The intrinsic features of a place seem thus to be “above” destination branding policies. The researched features account for different naming strategies, such as highly original names, flat names or non-strategic names.

As the work is based on a convenience sample, it cannot claim strong representativity. The fact that each of the three data sets was processed by a different researcher might bring up personal biases.

This work is a call for a more intensive use of naming strategies to the companies’ advantages, as naming is found out to be strategy used to a very low degree. Thanks to this research, companies will understand the different naming possibilities and be able to apply them to their strategies by choosing names which express “uniqueness” or “belonging”. Practitioners will also be aware of whether they are communicating towards the industry or towards the market.

No works were found that empirically pursue our research goals. Therefore, this research might be considered as a novelty. The proposed SNM model explains and relates the most usual company naming techniques, which were unrelated up to date.

This paper is a bibliometric analysis of articles published on the influence of Covid-19 on consumer behaviour.

Biblioshiny and VOSviewer applications are employed for the bibliometric analysis and visualisation, respectively.

The most influential documents, authors, affiliations, countries and journals are presented. Citation, Co-citation and keyword co-occurrence analysis is conducted and presented in the form of a clustered network diagram.

This paper found three main themes of the research in consumer behaviour amid Covid-19 a) Food purchasing decisions and food wastage, b) Adoption of technology and c) Intrinsic and extrinsic influence on consumer behaviour.

The Covid-19 pandemic has shaken the world’s economy and left behind its adverse effect on almost every walk of life. Consumer behaviour is no exception, studies have reported paradigm shifts in the way consumers are reacting to marketing stimuli, making purchase and consumption decisions. For the marketers to sustain profitability, they need to understand the changing behaviour and tailor their offerings accordingly.

The article offers the emerging theme and sub-themes in the consumer behaviour research that leads to future expansion of this research domain.

Post-COVID-19, public K–12 schools are still facing the consequences of the years of interrupted learning. Schools serving minoritized students are particularly at risk for facing challenges with academics, behavior and student social emotional health. The university counseling programs are in positions to build capacity in urban schools while also supporting counselors-in-training through service-learning opportunities.

The following conceptual manuscript demonstrates how counselor education counseling programs and public schools can harness the capacity-building benefits of university–school partnerships. While prevalent in fields like special education, counselor educators have yet to heed the hall to participate in mutually beneficial partnership programs.

Using the multi-tiered systems of support (MTSS) and the components of the university–school partnerships, counselor educators and school stakeholders can work together to support student mental health, school staff well-being and counselor-in-training competence.

The benefits and opportunities within the university–school partnerships are well documented. However, few researchers have described a model to support partnerships between the university counseling programs and urban elementary schools. We provide a best practice model using the principles of university–school partnerships and a school’s existing MTSS framework.

The study explores how Taiwan’s electronic health data systems can be used to build algorithms that reduce or eliminate medical errors and to advance precision medicine.

This study is a narrative review of the literature.

The body of medical knowledge has grown far too large for human clinicians to parse. In theory, electronic health records could augment clinical decision-making with electronic clinical decision support systems (CDSSs). However, computer scientists and clinicians have made remarkably little progress in building CDSSs, because health data tend to be siloed across many different systems that are not interoperable and cannot be linked using common identifiers. As a result, medicine in the USA is often practiced inconsistently with poor adherence to the best preventive and clinical practices. Poor information technology infrastructure contributes to medical errors and waste, resulting in suboptimal care and tens of thousands of premature deaths every year. Taiwan’s national health system, in contrast, is underpinned by a coordinated system of electronic data systems but remains underutilized. In this paper, the authors present a theoretical path toward developing artificial intelligence (AI)-driven CDSS systems using Taiwan’s National Health Insurance Research Database. Such a system could in theory not only optimize care and prevent clinical errors but also empower patients to track their progress in achieving their personal health goals.

While research teams have previously built AI systems with limited applications, this study provides a framework for building global AI-based CDSS systems using one of the world’s few unified electronic health data systems.