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With increased focus on data literacy and data science education in K-12, little is known about what makes a data set preferable for use by classroom teachers. Given that educational designers often privilege authenticity, the purpose of this study is to examine how teachers use features of data sets to determine their suitability for authentic data science learning experiences with their students.

Interviews with 12 practicing high school mathematics and statistics teachers were conducted and video-recorded. Teachers were given two different data sets about the same context and asked to explain which one would be better suited for an authentic data science experience. Following knowledge analysis methods, the teachers’ responses were coded and iteratively reviewed to find themes that appeared across multiple teachers related to their aesthetic judgments.

Three aspects of authenticity for data sets for this task were identified. These include thinking of authentic data sets as being “messy,” as requiring more work for the student or analyst to pore through than other data sets and as involving computation.

Analysis of teachers’ aesthetics of data sets is a new direction for work on data literacy and data science education. The findings invite the field to think critically about how to help teachers develop new aesthetics and to provide data sets in curriculum materials that are suited for classroom use.

This chapter discusses conceptual links among Hazel Kyrk’s A Theory of Consumption (1923), the overall work of Thorstein Veblen, and Wesley C. Mitchell’s essays on spending and money. The three authors are concerned with transformations in production, related changes in the organization of consumption, and the effects on people. The approach is based on reading of Kyrk’s book in light of an integrated view of Veblen’s overall work. This chapter explains how Mitchell’s essays on money and spending built on Veblen’s work and discusses their relevance for understanding Kyrk’s book as conceptually linked to institutional economics. This chapter delineates the following commonalities: conception of living humans and money as an institution; distinction between business and industrial concerns; connection between distribution, waste, and consumption; and Veblen’s “machine process” of standardization in production and its relation to consumption. This chapter brings more detail in the conceptual and theoretical discussion of Veblen’s influence on Kyrk’s book.

Business leaders are facing a change of role as digitalization continues to intensify in organizations. As technological change is bringing back supposedly old virtues of leadership, this study aims to explain the impact digital transformation has on leadership due to organizational size.

Cross-border study with experts from multinational enterprises (MNEs) in Austria and small and medium companies (SMEs) in Italy.

With increasing digitalization, leadership is becoming more important. In times of social distance, it is essential that leaders actively foster the management of relationships with their employees, manage social processes in their teams and shape change processes. This requires a bundle of skills consisting of effective leadership skills, strong change management skills and conceptual digitization skills.

Digital transformation is not mainly about implementing new technologies; it is about developing an appropriate strategy in which people are key. Organizations regardless of size need to recognize that digital transformation requires not less, but even more active shaping of the relationships between leaders and their team members. Consequently, they need active leaders who drive, communicate and implement technological change. As leadership and change require time, resources and, above all, attention, executive selection and qualification are critical for the broad integration of digitalization ideas into an organization.

People, not technology, drive digital transformation, and organizations require leaders, not necessarily technological specialists, to manage the complex changes that comprise an organization’s digital transformation. Technical and methodological skills can be substituted with the use of new technologies, but leaders’ interactional, social, strategic and conceptual skills are gaining in importance.

The introduction of robots as value-adding “workers” on the shop floor triggers complex changes to manufacturing work. Such changes involve highly entangled relationships between technology, organisation and people. Understanding such entanglements requires a holistic assessment of contemporary robotised manufacturing work, to anticipate the dynamically emerging opportunities and risks of robotised work.

A systematic literature review of 87 papers was conducted to capture relevant themes of change in robotised manufacturing work. The literature was analysed using a thematic analysis approach, with Checkland’s soft systems thinking as an analytical framework.

Based on the literature analysis, the authors present a systemic conceptualisation of robotised manufacturing work. Specifically, the conceptualisation highlights four entangled themes of change: work, organisation of labour, workers’ (experiences) and the firm’s environment. Moreover, the authors discuss the complex patterns of interactions between these objects as relationships that defy straightforward cause–effect models.

The findings draw attention to complex interactions between robotisation and manufacturing work. It can, therefore, inform strategic decisions and support projects for robotisation from a holistic perspective.

The authors present a novel approach to studying and designing robotised manufacturing work as a conceptual system. In particular, the paper shifts the focus towards crucial properties of the system, which are subject to complex changes alongside the introduction of robot technology in manufacturing. Soft systems thinking enables new research avenues to explain complex phenomena at the intersection of robotisation and manufacturing work.

Sustainable tourism will be an appropriate strategy to be promoted during the post COVID-19 pandemic, as this is a turning point for the tourism industry to grab the unique chance to have a true reset by focussing on achieving long-term sustainability and a shift from a ‘me to we’ economy. To support sustainable tourism and foster future success in the tourism industry, the process of integrating green knowledge and knowledge management can begin with entrepreneurial education in higher education institutions (HEIs). However, empirical research on university students' green entrepreneurial intention in sustainable tourism has not been exhaustively studied. Additionally, there is a need to further explore knowledge management process and entrepreneurial learning in HEIs. Hence, the aim of this study is to analyze knowledge management as a technique to explore the green entrepreneurial intention of students in HEIs in sustaining Malaysia's tourism post COVID-19 pandemic. Exploratory research with quantitative analysis was conducted through partial least squares structural equation modelling (PLS-SEM). The findings reveal that there is a positive and significant relationship between green entrepreneurial knowledge and green entrepreneurial intention in sustainable tourism among university business students. Additionally, knowledge revision and conceptual change positively and significantly influence green entrepreneurial knowledge and green entrepreneurial intention in sustainable tourism. However, knowledge application has no impact on green entrepreneurial knowledge and green entrepreneurial intention. The results of this study also reveal that green entrepreneurial knowledge does not have a mediation effect on green entrepreneurial intention. The present work contributes by going beyond the study of entrepreneurial intention, as the research focusses on interconnection among these three major areas: knowledge management, sustainable tourism, and entrepreneurship education post COVID-19 pandemic. Hence, the combination of these diverse aspects in this study provides insights to educators and policy makers to investigate the importance of green entrepreneurial knowledge and benefits of knowledge management that can be integrated into entrepreneurship education for current and future sustainable tourism development.

This conceptual paper focusses on climate change as a social issue and therefore as a social scientific problem. According to young climate activists, Greta Thunberg being the most widely known, climate change is specifically a problem of generations. Typically, the discourse on responsibility focusses on the technical and philosophical questions posed by the study into “intra-” and “inter-generational justice”. It is the purpose of this paper to present sociological conceptual tools with which to both analyze and propose solutions to specific social problems caused by current generations that will affect future generations.

Figurational process sociology develops and tests models of long-term, unplanned developments, which produce the conditions in which short-term practices of informing and planning social interventions are bound up.

The paper reveals the significance of sociological models that can describe and explain social processes and long-term developments in human habitus that have important explanatory value for understanding contemporary social problems such as human-caused climate change.

The concepts and analytical frames of reference provided by figurational process sociology provide crucial insights into the problem of generations and can help reveal how this social dynamic contributes to challenges facing young climate activists calling for rapid “ecologization” processes and increased human restraint with regard to the natural environment.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

The purpose of this paper is to inquire into how conceptualising is done in the industrial network approach (INA).

The description and analysis of conceptualising is based on key INA references and an example illustrating the characteristics of conceptualising in individual studies.

The paper concludes that there is an open and interactive way of conceptualising in the INA. The empirical and theoretical grounding achieved through combining concepts in individual empirical studies interplays with conceptual development in the research community over time.

Three paradoxes are suggested for further discussion of conceptualising as a key element in theorising in the INA community.

By explicating how INA researchers engage in conceptualising both in individual empirical studies and as a community, the authors identify characteristics similar to the empirical phenomena in focus of the research: interaction, combining and heterogeneity of concepts.

The scientific community shares a heritage of knowledge generated by several different fields of research. Identifying how scientific interest evolves is relevant for recording and understanding research trends and society’s demands.

This article presents SciBR-M, a novel method to identify scientific interest evolution from bibliographic material based on Formal Concept Analysis. The SciBR-M aims to describe the thematic evolution surrounding a field of research. The method begins by hierarchically organising sub-domains within the field of study to identify the themes that are more relevant. After this organisation, we apply a temporal analysis that extracts implication rules with minimal premises and a single conclusion, which are helpful to observe the evolution of scientific interest in a specific field of study. To analyse the results, we consider support, confidence, and lift metrics to evaluate the extracted implications.

The authors applied the SciBR-M method for the Educational Data Mining (EDM) field considering 23 years since the first publications. In the digital libraries context, SciBR-M allows the integration of the academy, education, and cultural memory, in relation to a study domain.

Cultural changes lead to the production of new knowledge and to the evolution of scientific interest. This knowledge is part of the scientific heritage of society and should be transmitted in a structured and organised form to future generations of scientists and the general public.

The method, based on Formal Concept Analysis, identifies the evolution of scientific interest to a field of study. SciBR-M hierarchically organises bibliographic material to different time periods and explores this hierarchy from proper implication rules. These rules permit identifying recurring themes, i.e. themes subset that received more attention from the scientific community during a specific period. Analysing these rules, it is possible to identify the temporal evolution of scientific interest in the field of study. This evolution is observed by the emergence, increase or decrease of interest in topics in the domain. The SciBR-M method can be used to register and analyse the scientific, cultural heritage of a field of study. In addition, the authors can use the method to stimulate the process of creating knowledge and innovation and encouraging the emergence of new research.

This study aims to explore how manufacturing firms master customer lock-in through value creation by servitization innovation strategies from the perspective of asset specificity.

A multiple case study with triangulation fashion is adopted to identify servitization innovation strategies. Several manufacturing firms were investigated, which are distributed in different positions of the value chain. Content analysis and abductive approaches are adopted to analyze the data. Moreover, an in-depth interview and participatory observation were conducted to refine the analysis results.

This study identified four different focusing points of servitization operations. Based on these, the paper further induces an innovative servitization strategy matrix of customer lock-in, concerning communion, intellectual, existential and insubstantial strategies. Furthermore, a conceptual model of customer lock-in by servitization innovation from the perspective of asset specificity is elaborated. It is suggested that companies can use tangible or intangible resources by sharing or storing operations to create servitization value.

This study theoretically proposes a conceptual model to extend servitization innovation as an intangible asset and adopt the new perspective of asset specificity to illustrate the value creation in servitization to generate customer lock-in.