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This study aims to meta-analytically investigate the impact of educational technology interventions on the development of creative thinking in educational settings. In recent years, the debate among researchers has persisted regarding the impact of various educational technologies, including interactive learning environments, digital instruction and platforms, and educational games and robotics, on students' creative thinking in diverse educational settings due to inconsistent findings.

This study, conducting a meta-analysis by synthesizing 35 relevant empirical studies with 2,776 participants, aims to investigate the association between educational technology interventions and the Torrance Tests of Creative Thinking (TTCT) and its subscales (fluency, flexibility, originality and elaboration).

No evident publication bias was found. From a general perspective, the results demonstrate a moderate level of influence of educational technology on the overall TTCT scale, with high heterogeneity attributed to the adopted instruments, mixed methods and target outcomes. Additionally, the results indicate that only three of the TTCT subscales (fluency, flexibility and originality) are influenced by educational technologies. Among the interventions, interactive learning environments yielded medium to the largest mean effect size. Furthermore, moderator analyses suggest that the effects of interventions on two subscales of TTCT (flexibility and originality) are moderated by school types, research design and the duration of intervention. The conclusion drawn is that interventions promoting students' creative thinking in different educational settings are efficacious.

Despite the low homogeneity of the results, which might have influenced the findings, the large fail-safe N suggests that these findings are robust. The study examined potential causes of heterogeneity and emphasized the importance of further research in this area.

This study investigates drivers of local governments’ digitalization, focusing on contextual factors that can help explain the level of e-government development. Concretely, it examines financial, socioeconomic, and political factors that represent the local context where e-government initiatives are implemented.

A composite e-government index was used, adopting a holistic perspective to capture various features of e-government initiatives. The OLS estimator for linear regressions was used for the analysis based on a sample of Italian municipalities in 2023. The Tobit estimator was additionally implemented to check for the robustness of the results.

Empirical findings suggest that municipalities with higher indebtedness tend to show lower digitalization levels. Economic and social variables are also relevant factors, while the political orientation of the governing party is not significant. This indirectly documents that e-government initiatives play a strategic role despite the political ideology.

This study avoids referring to a technological determinism perspective and examines the role of the institutional and operational context, highlighting the need to unveil and explain differences among local governments rather than focusing on similarities.

The objective of this study is to investigate the effect of change management (CM) on employee productivity (EP). A double-layered conceptual model involving resistance to change and emotional intelligence (EI) as moderators and employee engagement (EE) as a mediator between CM and EP.

Four industries from India (education, healthcare, information technology and manufacturing) are selected to test the hypothesized relationships. The data from 406 respondents were collected through a survey instrument and was analyzed using Hayes’s PROCESS macros.

The results reveal that CM is a precursor to EE and EP. The findings also indicate that resistance to change (first moderator) and EI (second moderator) significantly influenced the relationship between CM and EP mediated through EE.

As with any social science research, this study suffers from the limitations of common method bias and social desirability bias. However, the researchers have taken adequate care to minimize these biases. This study has several theoretical and practical implications.

The moderated-mediated model concerning CM is the first of its kind to study in the Indian context and hence makes a substantial contribution to the literature on CM. The implications for theory and practice are discussed.

To address challenges such as inadequate funding and inefficiency in public infrastructure construction, PPPs have gained significant global traction. This study aims to comprehensively assess the impacts and mechanisms of PPPs on the SDI and to provide rational policy recommendations based on the findings.

We collated a dataset from 30 Chinese provinces covering the years 2005–2020 as our research sample. The study’s hypotheses are tested using a double fixed-effects model, a chained mediated-effects model and a multidimensional heterogeneity analysis.

Our findings indicate that PPPs have a facilitating effect on SDI in general. This boost usually lags behind policy implementation and is cyclical in the time dimension. In the spatial dimension, PPPs contribute significantly to SDI in the eastern and western regions, but not in the central region. From the perspective of the dynamics of economic, social and industrial development, PPPs in economically backward areas are difficult to promote SDI, promote it the most in economically medium regions and are slightly less in economically developed regions than in medium regions. This promotion effect has an inverted U-shaped relationship with social development and diminishes with industrial structure upgrading. Finally, due to the negative relationship between PPPs and social development and between social development and SDI, PPPs are shown to contribute to SDI and are identified as critical paths. However, PPPs suppress SDI by inhibiting economic and industrial development.

This study makes three novel contributions to the existing body of knowledge: (1) we innovatively introduce the United Nations Sustainable Development Goals (SDGs) into the field of infrastructure research, offering fresh perspectives on SDI enhancement; (2) revealing the mechanisms by which PPPs affect SDI through the three dimensions of economic, social and industrial development enabling policymakers to better understand and optimize resource allocation and improve planning, design and management of PPP projects for sustainable infrastructure and (3) we assess the spatiotemporal variances of PPPs’ effects on SDI and the diversity across regions at different social, economic and industrial structures developmental stages, offering critical insights to global decision-makers to devise tailored policy measures.

The paper explores the implementation and process of a Participatory Action Research (PAR) project in Jacksonville, Florida. Using PAR principles, we sought to disrupt traditional dynamics in research, co-generating knowledge with the community. We aimed to elevate disenfranchised voices and foster effective solutions for neighborhood revitalization and resilience, which are designed and led by the community. In this paper we explore researcher positionality, examining how engagement with the community context profoundly influences researchers' perspectives and roles, thereby shaping the study trajectory.

We use reflexive and thematic approaches to analyze researcher positionalities and dynamics with the community. Researchers' reflections were scrutinized with a focus on their backgrounds, adaptability to community pace of work, lessons learned and evolving perspectives on community-centered research. We present a comprehensive discussion of emerging themes and emphasize the transformative nature of PAR and the significance of the researcher pursuing a relationship of belonging within the community.

The study uncovered key themes clarifying the transformations experienced by researchers engaged in PAR. We underwent a significant shift from a predetermined, structured PAR model to a more organic, community-driven model. This shift is illustrated under key themes in the paper: being vulnerable, valuing relationships, transforming the sense of self and solidarity, focusing on the process and recognizing and valuing community-derived knowledge. We write about the metamorphosis of researchers' roles from passive observers to active and empathic participants and about the implications for our methodological approach. As a result of this adaptation, the research process was enhanced and a symbiotic learning environment was created between the researchers and the community.

This paper distinguishes itself through its community-centric approach, diverging from traditional research paradigms. It explores how PAR-based community engagement can have a positive impact on those who are involved in PAR themselves, contributing to a better understanding of reciprocal dynamics in community-based research. We hope that our process of reflection can help other disaster researchers to ask better questions of themselves when engaging with communities and be open to following the lead and the pace of the community.

Powder bed additive manufacturing has recently seen substantial growth, yet consistently producing high-quality parts remains challenging. Recoating streaking is a common anomaly that impairs print quality. Several data-driven models for automatically detecting this anomaly have been proposed, each with varying effectiveness. However, comprehensive comparisons among them are lacking. Additionally, these models are often tailored to specific data sets. This research addresses this gap by implementing and comparing these anomaly detection models for recoating streaking in a reproducible way. This study aims to offer a clearer, more objective evaluation of their performance, strengths and weaknesses. Furthermore, this study proposes an improvement to the Line Profiles detection model to broaden its applicability, and a novel preprocessing step was introduced to enhance the models’ performances.

All found anomaly detection models have been implemented along with several preprocessing steps. Additionally, a new universal benchmarking data set has been constructed. Finally, all implemented models have been evaluated on this benchmarking data set and the effect of the different preprocessing steps was studied.

This comparison shows that the improved Line Profiles model established it as the most efficient detection approach in this study’s benchmark data set. Furthermore, while most state-of-the-art neural networks perform very well off the shelf, this comparison shows that specialised detection models outperform all others with the correct preprocessing.

This comparison gives new insights into different recoater streaking (RCS) detection models, showcasing each one with its strengths and weaknesses. Furthermore, the improved Line Profiles model delivers compelling performance in detecting RCS.

This study aims to explore the impact of architecture on digital communication mediums, focusing on how social media shapes the public perception and discussion of architectural spaces. It specifically examines the case of the Basilica Cistern/Istanbul, analysing social media interactions post-restoration.

Using newspaper archive scanning and survey technique, this study observed public content on Instagram focusing on the post-restoration period of the Basilica Cistern. 406 (283 valid) people who visited the Cistern and shared their experiences on Instagram between August 2022 and January 2023 participated in a survey. The analysis utilized Python for advanced correlation studies, enabling an in-depth exploration of the interplay between architectural features and social media sharing behaviours.

The analysis revealed that historical significance, lighting elements, role as a photographic backdrop significantly influenced sharing behaviours. Correlations were found between specific spatial features of the cistern and various sharing motivations, such as communication with people, personal gain, and popularity. The study highlights a diverse spectrum of motivations among users, emphasizing the relationship between these motivations and spatial features.

This study underscores the necessity for further inquiry into the intricate dynamics among digital communication, architectural spaces, and user motivations. Limitations include potential challenges in gathering data from social media due to concerns of cyber fraud and the misuse of hashtags.

This research offers novel insights into the interplay between digital communication and architecture. It underscores the potential of digital platforms as valuable data sources for architectural theorizing and practice, particularly in understanding how restorations and architectural changes are perceived and discussed in the digital space.

The study aims to understand the way metaverse might revolutionize the governance format – precisely the e-government concept – besides underlining the challenges leaving suggestive contours for further research in this realm.

An inductive research approach included the content analysis of relevant literature to identify patterns and generalize them into areas and approaches. Developing a conceptual framework seeks to systematically organize knowledge on metaverse government and provide an understanding of its contributions to enhancing the e-government maturity models.

The authors identified three general areas and approaches – content and data lifecycle management; platforms, tools and services; and infrastructure and computing resources – that shape how challenges of enterprise architecture layers should be resolved in a future research agenda. Integration of these government metaverse areas and approaches is linked with four enterprise architecture layers (technology, applications, data and business) that advance a new e-government meta stage of e-government maturity and the related challenges.

Hitherto, metaverse literature has hinged itself on the benefits and challenges of metaverse in the private sector. However, the exact dimensions have not been probed in the public sector and its e-government domain – the present study seeks to plug this gap.

Despite ChatGPT usage advantages to complete assignments as quickly as possible with detailed information, its adoption risks are crucial factors that may significantly influence student outcomes, like creative skills and achievement levels. Hence, this paper examines the potential effects of ChatGPT adoption risks on students’ cognitive achievement, underpinned by perceived risk theory (PRT). Further, this paper examines the mediating role of creative thinking levels among hospitality college students.

This paper employed a quantitative approach to collect data. Using an online survey, simple random sampling was employed to ensure bias. Hence, 267 faculty members at tourism and hospitality colleges affiliated with Egyptian public universities responded, and their responses were tested using SmartPLS v.4.

Creative thinking partially mediated five potential risks of students’ ChatGPT adoption effects on their cognitive achievement. More specifically, psychological risks of ChatGPT adoption among students are considered one of the most likely to reduce their levels of creative thinking and their ability to achieve achievement.

This paper provides insights for policymakers aimed at enhancing higher education quality in tourism and hospitality colleges. Accordingly, this paper concludes by highlighting the importance of addressing ChatGPT adoption’s psychological risks, integrating strategies to promote creative thinking among students and fostering responsible artificial intelligence usage in higher education.

This paper underscores the critical role of faculty members in navigating and mitigating these risks, fostering a more conducive learning environment for responsible ChatGPT usage.

The article examines how street-level bureaucrats (SLBs) manage the digital bureaucratic relationship in dealing with customer needs and the technological innovations introduced into organisations (digital tools). The topic of technological transformations from a street-level perspective has garnered limited interest so far, especially in Italy. The research question underlying the article is as follows: how does the discretion of SLBs change with the introduction of digital tools within the public administration? We expect that the characteristics of clients on the one hand, and the degree of institutionalisation of the digital tool in question on the other, will change the way in which SLBs exercise their discretion.

The data were collected from two separate research projects in which the authors were involved: (1) the first was a doctoral research project concerning labour inspectors tasked with investigating labour irregularities reported by workers; (2) the second was a research project regarding the relationship between the elderly and public service caseworkers. Information gathered through a series of semi-structured interviews was analysed, with a focus on the digitalisation process. The interviewees included 15 labour inspectors, and 12 long-term care caseworkers. With regard to the interviews conducted with labour inspectors, we examined the online request for action submitted by workers reporting irregularities in their employment relationships. As regards the interviews with caseworkers involved in services for the elderly, the discussion revolved around the option introduced during the pandemic period in 2020, to request access to the services in question through submission of an online form rather than requesting such services in person.

What emerges is that while the introduction of digitalised policies allows SLBs to obtain more information with which to assess the situation of individuals, the discretionary power exercised by front-line workers only results in the partial use of the digital tool, whilst favouring the traditional relationship between bureaucrats and their clients.

We introduce the concepts of “digital discretion” and “analogic discretion” in an attempt to understand how SLBs use their decision-making powers, which may prove to be useful analytical tools for studying the ways in which the discretion of SLBs is realised through new digital practices.