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The 2020–2021 COVID-19 pandemic spurred change across multiple healthcare industries. This study explores how managing vaccination data in the United States of America required cooperation among many different organizations necessitated by an emergency response. We studied how individual states interacted with the federal government to address the need for vaccination-related information during the pandemic.

In total, 11 interviews were conducted with individuals responsible for collecting vaccination data and reporting it to the US Federal Government. Seven of those individuals were directors of USA jurisdictional Immunization Information Systems (IIS). Archival data were also combined with the interview responses to inform the analysis and development of guidelines.

States across the USA had different ways of tracking and storing immunization data that was heavily influenced by state-level and federal legislation. The lack of a universal patient identifier made cross-state patient identification difficult. Federal requirements for reporting dictated much of how the different state-level entities collected, stored and reported data.

This study highlights the importance of data interoperability and data sharing by exploring how a loosely coupled set of entities without direct top-down control or a profit motive can govern data effectively. Our analysis provides greater clarity about the interactions between different stakeholders in a complex system.

This study presents primary interviews of 11 individuals, each responsible for tracking and reporting immunization information. Analysis of the data expands existing research on IIS on data sharing, system interoperability and dynamic pandemic responses.

The purpose of this paper is to investigate what factors can affect individuals’ knowledge sharing on social media from the perspectives of personality traits and social capital.

A theoretical model was developed with reference to the personality traits theory and the social capital theory. Accordingly, a questionnaire was designed to collect the individuals’ ideas on knowledge sharing on social media and further test the model. The questionnaire was then distributed to two LINE groups. Finally, the collected data were analyzed using the partial least squares (PLS) approach.

Personality traits not only directly affect knowledge sharing, but also indirectly influence it via social capital. Of all personality traits, agreeableness, openness and extraversion directly and indirectly influence knowledge sharing.

Knowledge sharing is undertaken by individuals and social groups. It starts with individuals and then diffuses to other members of a group.

Group managers have to identify the members who are friendly, open-minded or extroverted and encourage them to act as the bellwethers for knowledge sharing under an effective regulatory regime, through which intra-group knowledge sharing can be promoted.

This study introduces a new model to explore knowledge sharing on social media from individual and social perspectives. It illustrates what will affect individuals’ knowledge sharing on social media.

The purpose of this study is therefore to detail an additive manufacturing process for printing TiD parts for implant applications. Titanium–diamond (TiD) is a new composite that provides biocompatible three-dimensional multimaterial structures. Thus, the authors report a powder-deposition and print optimization strategy to overcome the dual-functionality gap by printing bulk TiD parts. However, despite favorable customization outcomes, relatively few additive manufacturing (AM) feedstock powders offer the biocompatibility required for medical implant and device technologies.

AM offers a platform to fabricate customized patient-specific parts. Developing feedstock that can be 3D printed into specific 3D structures while providing a favorable interface with the human tissue remains a challenge. Using laser metal deposition, feedstock powder comprising diamond and titanium was co-printed into TiD parts for mechanical testing to determine optimal manufacturing parameters.

TiD parts were fabricated comprising 30% and 50% diamond. The composite powder had a Hausner ratio of 1.13 and 1.21 for 30% and 50% TiD, respectively. The flow analysis (Carney flow) for TiD 30% and 50% was 7.53 and 5.15 g/s. The authors report that the printing-specific conditions significantly affect the integrity of the printed part and thus provide the optimal manufacturing parameters for structural integrity as determined by micro-computed tomography, nanoindentation and biocompatibility of TiD parts. The hardness, ultimate tensile strength and yield strength for TiD are 4–6 GPa (depending on build position), 426 MPa and 375 MPa, respectively. Furthermore, the authors show that increasing diamond composition to 30% results in higher osteoblast viability and lower bacteria count than titanium.

In this study, the authors provide a clear strategy to manufacture TiD parts with high integrity, performance and biocompatibility, expanding the material feedstock library and paving the way to customized diamond implants. Diamond is showing strong potential as a biomedical material; however, upscale is limited by conventional techniques. By optimizing AM as the avenue to make complex shapes, the authors open up the possibility of patient-specific diamond implant solutions.

The governance of our towns and cities requires an approach that connects people with nature and places. Digital technology can be the glue that does this, if it serves the needs of the various stakeholders, including urban communities. It means identifying the potential connections across people, digital, and place themes, examining successful approaches, and exploring some of the current practice (or lack of it) in spatial planning and smart cities. This can be considered using a range of Internet of Things (IoT) technologies with other methodologies which combine the use of socioeconomic and environmental data about the urban environment. This ambient domain sensing can provide the ecological and other data to show how digital connectivity is addressing the placemaking challenges alongside providing implications for urban governance and communities.

To analyse the reasons for acceptance and rejection of insect consumption among urban Mexican consumers based on their perceptions and levels of food neophobia and neophilia.

A questionnaire was distributed online to 415 people. The Food Neophobia Scale was used, measured on a four-point Likert scale, and consumers were grouped according to their level of neophobia. The Free Word Association technique was used to determine participants’ perceptions of “edible insects”, and the words obtained were categorised according to synonyms. The Chi-square test per cell made it possible to determine the statistical significance of each group in relation to the categories and was confirmed by a correspondence analysis. The economic aspects of the groups were analysed using the Chi-square and the Z-test with the Bonferroni method.

Three groups of consumers have been identified: neophilic, intermediate and neophobic. Participants mentioned 1,235 words, which were grouped into 16 categories. For neophilics, edible insects are a familiar product; intermediates are curious and neophobics are afraid of consumption.

The paper contributes to the analysis of the aspects that influence the acceptance and rejection of insect consumption among urban consumers by considering the degree of food neophobia and the participants’ perceptions.

External institutional policy and its impact on corporate social responsibility (CSR) have been widely discussed by researchers, but its effect still remains controversial. This study aims to use the minimum wage policy as an illustrative example to analyze its impact on the corporate social responsibility (CSR) of tourist enterprises. Furthermore, the research seeks to examine the boundary conditions that influence the minimum wage’s effect on CSR.

This paper takes the data of 42 listed tourism companies from 2010 to 2020 in China as samples and uses the mixed OLS regression method and the fixed effects panel model to examine the effect of the minimum wage on CSR.

Findings show that increasing wages has a significantly negative impact on their total CSR investment. Also, low-operating-capacity enterprises and private enterprises will react more adversely when faced with increasing minimum wages. And found that the increase of minimum wage has no significant negative impact on the strategic social responsibility of tourism enterprises; however, it has a significantly negative impact on their tactical social responsibility. In addition, as far as employees’ rights and interests are concerned, the minimum wage increase has effectively increased employee salaries, but the nonsalary benefits of the employees have significantly decreased.

The contribution of this paper not only expands the research on the antecedents and boundary mechanisms of CSR but also clarifies the specific effect of the rise of the minimum wage on corporate social responsibility; it further deepens the impact of institutional policy factors on CSR, which also opens new perspectives for policy evaluation and provides a theoretical basis for government policymakers.

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment effectiveness (OEE) tool to enhance the process performance and establish Fourth Industrial Revolution (I4.0) platform in small and medium enterprises (SMEs).

This work utilised plan, do, check, act Lean methodology to create a digital twin of each machine in a smart manufacturing facility by taking the Lean tool OEE and digitally transforming it in the context of I4.0. To demonstrate the effectiveness of process digitisation, a case study was carried out at a manufacturing department to provide the data to the model and later validate synergy between Lean and I4.0 platform.

The OEE parameter can be increased by 10% using a proposed digital twin model with the introduction of a Level 0 into VM platform to clearly define the purpose of each data point gathered further replicate in projects across the value stream.

The findings suggest that researchers should look beyond conversion of stored data into visualisations and predictive analytics to improve the model connectivity. The development of strong big data analytics capabilities in SMEs can be achieved by shortening the time between data gathering and impact on the model performance.

The novelty of this study is the application of OEE Lean tool in the smart manufacturing sector to allow SME organisations to introduce digitalisation on the back of structured and streamlined principles with well-defined end goals to reach the optimal OEE.

This study aims to examine living preference and tenure among millennials, with a particular focus on the impact of ethnic and cultural diversity on housing outcomes including observed homeownership inequalities.

Using the individual panel data from three waves in American Housing Survey, 2015–2019, this study compares the likelihood of co-residing among Asian and Hispanic millennials with non-Hispanic white millennial peers. Furthermore, this study estimates the effect of co-residence on homeownership across generational and ethnic backgrounds.

This study finds a preference for coresident adult familial households among foreign-born Asian and Hispanic millennials, and US-born Hispanic millennials when compared to their non-Hispanic white millennial peers. The results are robust after considering neighborhood selection bias, affordability and education. The effect of co-residence on ownership is significant and positive, suggesting this living arrangement contributes to homeownership across all generational and ethnic groups.

Housebuilders should be aware of Asian and Hispanic millennials’ increased appetite for extended family living arrangements and consider increasing the physical size of affordable or workforce-oriented rental housing and new single family construction to accommodate more adult co-living arrangements.

This study provides a more comprehensive understanding of the role ethnic and cultural diversity has on millennial adult living preferences and its generational differences, which is not just “boomeranging” as identified by previous literature, contributing to the growing interest in the housing research on the effect of ethnic diversity and culture on millennials’ homeownership rates.

Given the existing quality concerns of higher education (HE), particularly in the global South, the integration of Artificial Intelligence (AI) has been seen as a panacea to improve the quality of teaching learning in HE. AI Chatbots, like ChatGPT, have created profound resonance across HE systems with both positive and negative impacts. Within HE, expectations and concerns related to the quality of HE in general, and teaching learning in particular, loom. It is yet to be investigated how university teachers use AI chatbots in their teaching inside classrooms and its potential to enhance the quality of teaching learning in HE. This chapter sheds light on these questions based on in-depth qualitative interviews with faculty members from six universities in Pakistan. Using a thematic analysis approach, the findings highlight both positive and negative aspects of ChatGPT when used for teaching in HE. Based on the findings, we developed a four-stage framework highlighting faculty members' response to integrating ChatGPT for transforming teaching learning activities. We explain that transformation of teaching learning with AI requires educators to rethink teaching and learning – navigative response – and assess its integration – evaluative response. In conclusion, we discuss how the adoption of AI chatbots provides educators with authentic assessment but will certainly require skills to properly navigate. We further discuss the findings in literature around the quality of HE making some plausible predictions regarding whether chatbots can serve as a quality enhancement tool, mainly in the global South.

The composition of author teams is a significant factor affecting the novelty of academic papers. Existing research lacks studies focusing on institutional types and measures of novelty remained at a general level, making it difficult to analyse the types of novelty in papers and to provide a detailed explanation of novelty. This study aims to take the field of natural language processing (NLP) as an example to analyse the relationship between team institutional composition and the fine-grained novelty of academic papers.

Firstly, author teams are categorized into three types: academic institutions, industrial institutions and mixed academic and industrial institutions. Next, the authors extract four types of entities from the full paper: methods, data sets, tools and metric. The novelty of papers is evaluated using entity combination measurement methods. Additionally, pairwise combinations of different types of fine-grained entities are analysed to assess their contributions to novel papers.

The results of the study found that in the field of NLP, for industrial institutions, collaboration with academic institutions has a higher probability of producing novel papers. From the contribution rate of different types of fine-grained knowledge entities, the mixed academic and industrial institutions pay more attention to the novelty of the combination of method indicators, and the industrial institutions pay more attention to the novelty of the combination of method tools.

This paper explores the relationship between the team institutional composition and the novelty of academic papers and reveals the importance of cooperation between industry and academia through fine-grained novelty measurement, which provides key guidance for improving the quality of papers and promoting industry–university–research cooperation.