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The purpose of this paper is to analyse data literacy in the new Digital Competence Framework for Citizens (DigComp 2.2). Mid-2022 the Joint Research Centre of the European Commission published a new version of the DigComp (EC, 2022). This new version focusses more on the datafication of society and emerging technologies, such as artificial intelligence. This paper analyses how DigComp 2.2 defines data literacy and how the framework looks at this from a societal lens.

This study critically examines DigComp 2.2, using the data literacy competence model developed by the Knowledge Centre for Digital and Media Literacy Flanders-Belgium. The examples of knowledge, skills and attitudes focussing on data literacy (n = 84) are coded and mapped onto the data literacy competence model, which differentiates between using data and understanding data.

Data literacy is well-covered in the framework, but there is a stronger emphasis on understanding data rather than using data, for example, collecting data is only coded once. Thematically, DigComp 2.2 primarily focusses on security and privacy (31 codes), with less attention given to the societal impact of data, such as environmental impact or data fairness.

Given the datafication of society, data literacy has become increasingly important. DigComp is widely used across different disciplines and now integrates data literacy as a required competence for citizens. It is, thus, relevant to analyse its views on data literacy and emerging technologies, as it will have a strong impact on education in Europe.

This chapter highlights how implementing circular economy principles can help companies working with sustainability to move from a reductionist and waste management approach to marketing competitive circular value propositions that intentionally design out waste (e.g. emissions and pollution) by rethinking, reinventing and redesigning the value chain. Schijvens, a Dutch family-owned corporate fashion textile company, acts as a case for exemplifying successful implementation of circular economy principles as a marketing strategy in a sector that struggles with finding solutions to the ethical challenges of producing and marketing textile fashion. The textile industry has, for many years, been accused of production that is based on environmentally harmful processes and conditions that are not socially fair. Circular economy principles provide a range of suggestions to address the ethical challenges occurring from covering the human needs of having clothes to wear. Yet, implementing circular economy principles is not a panacea. It is not only a question of delivering a technological quick fix but also a question of managing the new processes and human mindset guiding the actions in the value chain. This chapter, therefore, outlines reasons for a different perspective on the traditional linear value chain and related implications managers face when undertaking a journey from sustainability based on a reductionist approach to a closed-loop approach. It is argued that implementing circular economy principles by pro-actively managing the value chain processes based on eco-centric dynamic capabilities can provide even more radical changes than the incremental reductionist approach often associated with being a green sustainable company.

The purpose of this paper is to analyse the individual’s experience during the use of Pinterest in a marketing learning process. This experience is a fundamental starting point from which to develop marketing learning processes that flow naturally. Thus, it is necessary to examine the components that determine the individual’s experience and to explore consequences such as collaborative learning and marketing learning performance.

To conceptualise the individual’s experience, this study focuses on her/his state of cognitive absorption (CA) and establishes a second-order formative structure made up of five components: heightened enjoyment, curiosity, control, temporal dissociation and focused immersion. The model is estimated with partial least squares modelling, using SmartPLS 2.0 software.

The results confirm the significant weights of the components, with the exception of focused immersion, and support the influence of overall CA on the proposed outcomes. They also confirm that collaborative learning exerts a positive influence on the individual’s performance.

This study makes three contributions. First, it holistically examines the individual’s experience during marketing learning and the importance of its constituent components. Second, it establishes what the consequences of the marketing learning experience are, taking into account both social and individual factors, that is, collaborative learning and individual performance. Third, Pinterest is proposed as a social network with great potential in marketing learning. It is a well-known network which includes very interesting features for learning contexts. Nevertheless, it has been little studied in research.

El objetivo de la presente investigación es analizar la experiencia del individuo durante el uso de Pinterest en un proceso de aprendizaje de marketing. Este experiencia es un punto de partida fundamental para que el proceso de aprendizaje de marketing se desarrolle de manera fluída. Así, es preciso examinar los componentes que determinan la experiencia del individuo y explorar las consecuencias, como por ejemplo, el aprendizaje colaborativo y los resultados del aprendizaje de marketing.

Con el objeto de conceptualizar la experiencia del individuo, este studio centra su atención en la absorción cognitiva (AC) y propone una estructura formativa de segundo orden compuesta por cinco componentes: mayor disfrute, curiosidad, control, disociación temporal e inmersión enfocada. El modelo es estimado mediante el uso de Modelización de Mínimos Cuadrados Parciales, empleando el software SmartPLS 2.0.

Los resultados confirman el significativo peso de los componentes, con la excepción de la inmensión enfocada, y apoya la influencia de la AC general sobre las consecuencias propuestas. Estos resultados también confirman que el aprendizaje colaborativo tiene una influencia positiva sobre los resultados del individuo.

Este estudio ofrece tres contribuciones. En primer lugar, se examina de manera holística la experiencia del individuo durante el aprendizaje de marketing y la importancia de sus componentes. En segundo lugar, se establece cuales son las consecuencias de la experiencia de aprendizaje de marketing, teniendo en cuenta factores sociales e individuales, es decir, aprendizaje colaborativo y resultados individuales. En tercer lugar, se propone a Pinterest como una red social con un gran potencial en el aprendizaje de marketing. Se trata de una conocida red que incluye interesantes características para los contextos de aprendizaje. A pesar de ello, ha sido escasamente estudiada por los investigadores.

Experiencia, Absorción cognitiva, Pinterest, Resultados de aprendizaje de marketing, Redes sociales

Artículo de investigación

The study investigated teaching research data management (RDM) courses in higher learning institutions (HLIs) in Tanzania to enable postgraduate students to work with their research data.

The study triangulated research methods. Postgraduate students were investigated using survey questionnaires to learn about their needs and perceptions of the teaching RDM courses in HLIs. Key informants (academicians, information and communication technologists and library staff) were also investigated using in-depth interviews to explore their experiences and knowledge of teaching RDM courses. SPSS statistical software was used for analysing quantitative data; qualitative data were analysed thematically.

A total of 70 questionnaires were distributed to postgraduate students with a returning rate of 44 (69%). On the other hand, 12 key informants were interviewed. A low level of RDM literacy was revealed among 38 (86%) respondents. Most respondents 40 (91%) reported the need for HLIs to start teaching RDM courses. A lack of skills and knowledge in teaching RDM courses was revealed among key informants. The competency-based, adaptive and constructive teaching techniques were selected for teaching RDM courses, whereas intensive training and online tutorials were revealed as teaching formats.

This study focused on teaching RDM courses in HLIs. The survey questionnaires were distributed to all 2nd year postgraduate students, however, the findings cannot be generalised to all postgraduate students due to the response rate obtained. The findings obtained from key informants can also not be used as a basis for generalization across HLIs.

This study concluded that postgraduate students need to be well equipped with skills and knowledge on RDM and its related concepts; teaching RDM courses should be regarded as a continuous programme for benefit of students, researchers and the community at large.

Appropriate teaching of RDM courses among students not only ensures that students meet the funders’ and publishers’ requirements, but also encourages students to store and share their research among researchers worldwide; thus increasing collaboration and visibility of the datasets and data owners through data citations and acknowledgements.

This is a comprehensive study that provides findings for HLIs to teach RDM courses in HLIs, especially for postgraduate students. The findings revealed the need for teaching RDM courses in HLIs. The study provides the basis for further RDM research in HLIs and research institutions.

This study examines various artificial intelligence (AI) models for predicting financially distressed firms with poor profitability (“Zombie firms”). In particular, we adopt the Explainable AI (“XAI”) approach to overcome the limitations of the previous AI models, which is well-known as the black-box problem, by utilizing the Local Interpretable Model-agnostic Explanations (LIME) and the Shapley Additive Explanations (SHAP). This XAI approach thus enables us to interpret the prediction results of the AI models. This study focuses on the Korean sample from 2019 to 2023, as it is expected that the COVID-19 pandemic increases the number of zombie firms. We find that the XGBoost model based on a boosting technique has the best predictive performance among several AI models, including the traditional ones (e.g. the logistic regression). In addition, by using the XAI approach, we provide visualized interpretations for the prediction results from the XGBoost model. The analysis further reveals that the return on sales and the selling, general and administrative costs are the most impactful variables for predicting zombie firms. Overall, this study focusing on several AI models not only shows the improvement for the prediction of zombie firms (relative to the traditional models) but also increases the reliability of the prediction results by adopting the XAI approach, providing several implications for market participants, such as financial institutions and investors.

The extra-low minimum wage for US restaurant workers has remained unchanged for over 30 years. Periodic campaigns have brought this wage, and its connection to the perpetuation of inequality and exploitative work, to public attention, but these campaigns have met resistance from both employers and restaurant workers. This article draws on a workplace ethnography in a restaurant front-of-house, and in-depth interviews with tipped food service workers, to examine the tipped labour process and begin to answer a central question: why would any workers oppose a wage increase? It argues that the constituting of tips as a formal wage created for workers a two-employer problem, wherein customers assume the role of secondary, unregulated, employers in the workplace. Ultimately, the tipped wage poses a longer-term strategic obstacle for workers in their position relative to management and ability to organize to shape the terms and conditions of their work.