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This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms.

This paper describes a pedagogical approach that uses a data science framework the research team developed to assist teachers in providing data science instruction to elementary-aged students. Using phenomenological case study methodology, the authors use classroom observations, student focus groups, video recordings and artifacts to detail ways learners engage in data science practices and understand how they perceive their engagement during activities and learning.

Findings suggest student engagement in data science is enhanced when data problems are contextualized and connected to students’ lived experiences; data analysis and data-based decision-making is practiced in multiple ways; and students are given choices to communicate patterns, interpret graphs and tell data stories. The authors note challenges students experienced with data practices including conflict between inconsistencies in data patterns and lived experiences and focusing on data visualization appearances versus relationships between variables.

Data science instruction in elementary schools is an understudied, emerging and important area of data science education. Most elementary schools offer limited data science instruction; few elementary schools offer data science curriculum with embedded CT practices integrated across disciplines. This research assists elementary educators in fostering children's data science engagement and agency while developing their ability to reason, visualize and make decisions with data.

This study explores the role of organisational culture in promoting collective coping strategies in construction project teams in the United Arab Emirates (UAE). Three collective coping strategies were examined, including problem-focused, relationship-focused and emotion-focused coping strategies.

O'Reilly et al.’s (1991) organisational culture profile (OCP) assessed organisational culture values. Data were collected through an online questionnaire from practitioners in the United Arab Emirates (UAE) construction organisations.

The findings show a high correlation between competitiveness culture values and problem-focused team coping strategy. Relationship-focused team coping strategy was found to have a high correlation with emphasis on rewards and performance orientation values. Conversely, an emotion-focused team coping strategy correlates highly with competitiveness, supportiveness and emphasis on rewards cultural values.

The cross-sectional design of the survey and the UAE context may present limits to the generalisability of findings.

Limited attempts have been made to study collective coping in construction project teams. The study paves the path for exploring emergent socio-psychological concepts in construction organisations, including the impact of organisational culture on team collective coping with adverse events.

Understanding the pivotal impact of culture on successful team coping provides managers with valuable insights into managing situational adversity in construction project teams.

This study empirically tests a model of human capital (HC) factors affecting the organisational competitiveness (OC) of automotive parts suppliers in the Industry 4.0 framework, including concepts such as Toyota Kata (TK), Kaizen and Quality 4.0, during the coronavirus disease 2019 pandemic.

An instrument was created to measure emotional intelligence (EI) and analytical skill (AS) as input variables and OC as the output variable. The instrument was distributed electronically to Tier 1 non-technical employees in Nuevo León and Querétaro, México. A total of 195 surveys were obtained. The instrument used stepwise multiple linear regression.

This study proposes a model to strengthen the OC of Tier 1 automotive parts supply industry from the perspective of HC factors. Furthermore, it is shown that EI and AS have a positive and significant impact on OC.

From an HC perspective, this study provides a useful basis to improve OC for researchers, industry experts and managers at different levels of the automotive industry, including the triple helix (academia, industry and the government).

No studies simultaneously test the relationship of EI and AS to OC; therefore, this study fills a gap in the literature. Furthermore, the study explored the literature on individual Kaizen (IK) and TK, leading to a contrast between the definitions of EI and AS. Finally, for EI, a reference to motivation was found in the IK. In the case of AS, an orientation to ability of problem solving was found in TK.

The purpose of this study is to empirically examine how individuals’ hybrid entrepreneurial venturing activities (HEVA) influence key characteristics associated with one’s wage work, namely creativity and job satisfaction.

Through a cross-sectional self-administered survey design, data were gathered from 465 US-based useable responses via Amazon Mechanical Turk and analyzed using structural equation modeling (SEM).

Findings show individuals reporting higher levels of HEVA – such as creating, founding, starting or running – tend to also exhibit higher levels of creativity and job satisfaction in their workplaces. Findings further reveal that income negatively moderates the relationship between creativity and wage work job satisfaction.

By providing a better understanding of how engaging in HEVA can impact creativity and job satisfaction, this study has important implications for (1) managers seeking to influence key employee outcomes and (2) employees considering such entrepreneurial activities.

This paper adds to the growing scholarly and practitioner interest in hybrid entrepreneurship and its outcomes. Specifically, the paper adds new insights regarding how engaging in HEVA can influence individual skills (i.e. creativity) or organizational goals (i.e. employee job satisfaction). In doing so, the paper also uses insights from the intrinsic/extrinsic motivation literature to suggest how extrinsic motivators (such as income) can interact with intrinsically motivated behaviors (such as creativity) in influencing employee outcomes in wage work. Finally, the paper contributes to the growing interest in applying the empowerment perspective within entrepreneurship research by exploring where and how empowerment may occur.

With the rise in demand and adoption of smart city initiatives, it is imperative to plan the railway infrastructure, as it will have a huge positive impact if adequately integrated into the planning process. Given the complexities involved, a whole systems thinking framework provides a useful platform for rail transport planners.

This paper proposes a simple, adoptable framework utilising systems thinking concepts and techniques taking into cognisance the key stakeholders. Milton Keynes in the United Kingdom is the adopted case study.

Selected systems thinking tools and techniques are adopted to develop a framework for mapping stakeholders and attributes when developing sustainable rail transport systems, taking note of their core functionalities and the complex systems wherein they exist.

The desire to build future (smart) cities is to effectively match infrastructural resources with a rapidly growing population, and the railway sector can play a strategic role in building a much more competitive low-carbon-emission transport system, which is a driving force for sustainable development.

The urban rail service has become vital to urban development as railway stations serve as hubs for sustainable mobility to meet local requirements. Moreover, it takes extra effort to input railway development into smart city plans, as it is a herculean task to get governments to focus on it with clarity of purpose in passing legislation.

The developed framework reduces complexities when planning and designing rail transport systems compared to many of the existing reductionist planning approaches. The simplicity of the framework would also make it easily adoptable by a wide range of users.

This study proposes a garment modularization model based on an interactive genetic algorithm. The suggested model consists of extraction and identification of parts and the determination and implementation of connections. Rules and corresponding mathematical equations have been formulated for the part's extractions from the discarded products and connections for the redesigned products.

Sustainability entices scholars and practitioners while referring to reducing waste to control environmental degradation. One of the ways to safeguard natural resources is to increase the reuse of old or discarded products. The current study focuses on the redesign process to improve the reuse of products.

The intelligent system proposed based on the modularization techniques is expected to simplify and quantify the redesign process. The model can further help in the minimization of wastage and environmental degradation.

Presently, manual decisions are taken by the designers based on their memory, experience and intuition to extract and join the parts.

This study aims to explore the transformative potential of integrating artificial intelligence (AI) and the metaverse into academic libraries, envisioning a future where personalized, immersive and accessible user experiences redefine the traditional concept of libraries. The purpose is to analyse the synergy between AI and the metaverse in enhancing library services and user interactions.

The study uses a literature review approach to synthesize current knowledge on AI, the metaverse and their integration into academic libraries. It delves into the functionalities of AI in cataloguing, personalization and predictive analysis, coupled with the immersive experiences offered by the metaverse. The design envisions metaverse-infused academic libraries as digital spaces hosting AI-driven virtual assistants, personalized learning paths and collaborative environments.

The integration of AI and the metaverse in academic libraries presents opportunities for personalized learning experiences, efficient resource management and global collaboration. The findings suggest that the synergy enhances accessibility, inclusivity and efficiency in library services, albeit with challenges such as the digital divide, privacy concerns and technical complexities.

This study contributes to the discourse on the future of academic libraries by proposing a comprehensive vision of metaverse-infused libraries empowered by AI. It underscores the originality and value of the integration, emphasizing the potential for personalized, interactive and globally accessible learning and research environments.

Drawing on expectancy violation theory, this study aims to assess the impact of corporate environmental irresponsibility (CEI) on workplace deviant behaviors (WDB) of Generation Z and Millennials through the mediation of moral outrage.

The data were collected from 328 nonmanagerial employees working in the refinery, petroleum and power distribution companies who have been convicted for committing environmental irresponsibility by a court of law. Multigroup analysis (MGA) was used to estimate the hypothesized relationships.

Results revealed that CEI affects WDBs positively. Moreover, the MGA results demonstrated that the deviant behavior of Generation Z in response to environmental irresponsibility is higher than of the Millennials.

Theoretically, the findings implicate that harming the environment will cost organizational performance through deviant behaviors.

This study provides a new lens for the executive management that eliminating social irresponsibility is more important than incurring sustainability initiatives, especially from the new generation’s perspective.

The originality of this study is that it confirmed the impact of CEI on employees’ deviant behaviors; and extended the scope of expectancy violation theory to the field of human resources.

This study aims to investigate how and to what extent structural network properties affect dyadic negotiation behavior in tourism destination ecosystems. Specifically, this study addresses negotiation behavior in terms of problem-solving and contending, because these two key strategies reflect the integrative and distributive aspects of dyadic interactions.

This study relies on network data and dyadic survey data from nine mountain tourism destinations in Southeastern Norway. The structural network properties the authors research are triadic closure – the extent to which a dyad has common ties to other actors – and structural equivalence – the similarities in networking patterns that capture firms’ competition for similar resources. In addition, the authors also study a possible effect of relationship duration on negotiation behavior.

Triadic closure and relationship duration have positive effects on problem-solving, and structural equivalence tends to decrease problem-solving, although the effect is inconsistent; none of these three independent variables was found to affect contending negotiation behavior.

This study shows that a dyad’s structural network embeddedness has implications for negotiation behavior. Further research is encouraged to develop this theoretical perspective.

This study is a pioneering investigation of how structural network properties affect dyadic negotiation behavior in ongoing coproducing relationships in real-world destination ecosystems.

Being acquainted with both lean and action learning in theory and in practice, this study finds that the theoretical complementarity of these two research streams has traditionally been underexploited. In this conceptual paper, this study aims to advance the theoretical understanding of lean by exploring the complementarity of lean thinking and action learning leading to a proposed integrated theory of these two research streams. Target audience is the operations management research community.

By deliberately adopting a process of theorising, this paper explores, reflects upon and combines individual experiences of researching, teaching and engaging in lean and action learning as operations management scholars.

Having taken a gemba walk through the literature and practices of lean and action learning, this study views and notices a systematic and complementary relationship between the two domains. The overlapping theoretical and practical complementarities of lean and action learning suggest that these two research streams are ripe for synthesis into an integrated theory. This finding provides an opportunity to (1) progress towards an integrative design of interventions leading to more sustainable lean system adoptions and (2) add new depth to our theoretical explanation of the success and failures of lean system adoptions.

This paper contributes an original integrated theory perspective on lean and action learning.