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People with intellectual disability face extensive health inequality and premature mortality. Medical students have reported that they lack the skills, knowledge and confidence to work with those with intellectual disability and autism. This emphasises the need for tomorrow’s doctors to be adequately trained. This study aims to investigate students’ knowledge, skills and attitudes towards people with intellectual disability and autism, examining whether these outcomes change following curricula re-design and with implementation of an e-learning module.

The university curricula in intellectual disability and autism were re-designed and an e-learning module developed using co-production. This was delivered to fourth-year medical students with a subgroup receiving the additional e-learning. A controlled trial evaluated students’ knowledge, skills and attitudes using pre- and post-questionnaires. Statistical tests of difference were used to the scores obtained.

This study showed an improvement in knowledge, skills and attitudes with intellectual disability and autism after curricula engagement, with an incremental benefit observed for students also completing the e-learning module. There was significant difference in pre-and-post placement scores assessing student attitudes towards intellectual disability and autism teaching.

This study highlights the importance of a multi-faceted, co-produced curricula re-design in intellectual disability and autism. The benefit of the e-learning module holds hope that the newly introduced mandatory Oliver McGowan training will be beneficial in the development of tomorrow’s doctors. Effective training in intellectual disability and autism is vital to improve the care and support delivered and reduce unnecessary deaths.

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.

Output from the Irish Dairy Industry has grown rapidly since the abolition of quotas in 2015, with processors investing heavily in capacity expansion to deal with the extra milk volumes. Further capacity gains may be achieved by extending the processing season into the winter, a key enabler for which being the reduction of duration of the winter maintenance overhaul period. This paper aims to investigate if Lean Six Sigma tools and techniques can be used to enhance operational maintenance performance, thereby releasing additional processing capacity.

Combining the Six-Sigma Define, Measure, Analyse, Improve, Control (DMAIC) methodology and the structured approach of Turnaround Maintenance (TAM) widely used in process industries creates a novel hybrid model that promises substantial improvement in maintenance overhaul execution. This paper presents a case study applying the DMAIC/TAM model to Ireland’s largest dairy processing site to optimise the annual maintenance shutdown. The objective was to deliver a 30% reduction in the duration of the overhaul, enabling an extension of the processing season.

Application of the DMAIC/TAM hybrid resulted in process enhancements, employee engagement and a clear roadmap for the operations team. Project goals were delivered, and original objectives exceeded, resulting in €8.9m additional value to the business and a reduction of 36% in the duration of the overhaul.

The results demonstrate that the model provides a structure that promotes systematic working and a continuous improvement focus that can have substantial benefits for wider industry. Opportunities for further model refinement were identified and will enhance performance in subsequent overhauls.

To the best of the authors’ knowledge, this is the first time that the structure and tools of DMAIC and TAM have been combined into a hybrid methodology and applied in an Irish industrial setting.

The objective of this study is to explore the structural attributes of the pharmaceutical industry before the onset of the COVID-19 pandemic by examining the relationship between inventory and firm performance and developing a taxonomy of pharmaceutical firms based on the earns-turns matrix.

This study examines the inventory–firm performance linkage, considering both total inventory and its discrete inventory components in pharmaceutical firms. In addition, this research develops a new taxonomy of pharmaceutical firms based on the earns-turns matrix. A large panel dataset of firms in the US pharmaceutical industry was collected for the period 2000–2019.

The results reveal that strategic groups identified based on this taxonomy show different levels of profitability and inventory turns in the earns-turns matrix. Most pharmaceutical firms moved from the low-right to the top-left section in the earns-turns matrix, indicating that these firms have generally pursued profitability rather than effective inventory management.

This study explores the structural attributes of the pharmaceutical industry using the earns-turns matrix. This two-dimensional analysis may not, however, capture the full complexity of inventory–firm performance dynamics.

The mapping of strategic groups on the earns-turns matrix provides a useful tool for visual representations of the dynamics of strategic groups in terms of financial performance and inventory management performance. Practitioners can use the earns-turns matrix to benchmark their firm's position against their competitors.

This study broadens the scope of operations management research by introducing the earns-turns matrix as an empirical validation tool for operational and strategic management theories. This study emphasizes the effectiveness of the earns-turns matrix in analyzing strategic groups of pharmaceutical firms.

This study aimed to investigate the ecological validity of sponsorship effectiveness by examining the visual attention paid to sponsorship at a live sporting event and the subsequent impact of that attention on cognitive outcomes using eye tracking in a natural, real-world environment.

Two logistic regression analyses (i.e. sponsor recall and sponsor recognition) were conducted to evaluate the impact of sponsorship exposure time, fixation duration and fixation frequency on viewer attention.

The preliminary investigation unveiled that longer exposure, strategic placement and brand repetition led to more frequent and extended fixations. The statistical examination demonstrated that a greater fixation frequency yielded a higher probability of explicit memory. However, the amount of time did not appear to influence viewers’ explicit memory. Further, females exhibited a higher probability of explicit memory compared to their male counterparts. Finally, age emerged as a significant determinant of explicit memory.

The significance of conducting eye-tracking studies within an authentic sport environment enhances ecological validity, leading to the development of practical and realistic approaches to boost consumers' explicit memory of sponsors. Further, the tangible evidence of how sponsorship information is processed can inform and modify sport marketing strategies to enhance the effectiveness of sponsorships.

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications.

This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns.

The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication.

Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.

The personalities of the design team members constitute one of the factors that influence team effectiveness. In this study, 223 members of the “American Institute of Architects” who are employed by the largest architectural design firms in the United States of America were categorized according to their personality types by using “The Enneagram Personality Type Model.” Also, the respondents’ opinions about eight team effectiveness outcomes were recorded in order to explore the relationship between team members’ personality types and team effectiveness outcomes.

The information was collected by a questionnaire where the first part included 144 pairs of statements that were used to identify respondents’ personality types. The second part sought designers’ opinions about the importance of eight team effectiveness outcomes rated on a Likert scale ranging from 1 to 5. The results were assessed by performing the Kruskal–Wallis test first and Dunn’s post-hoc test with Bonferroni adjustment subsequently.

The findings highlight the significance of personality types in effective design teams. While Type 6 (loyalist and skeptic) and Type 3 (achiever and performer) architects prioritize team effectiveness the most, Type 7 architects (enthusiasts and epicureans) assign the lowest importance. However, the presence of Type 1 (reformist and perfectionist) and Type 8 (challenger and protector) architects within the same design team may involve challenges or conflicts.

The primary contribution of this study is that it is the first study in the construction management literature that utilizes The Enneagram of Personality Test to understand the relationship between team members’ personality types and team effectiveness outcomes. This study is of direct relevance to practitioners and could be utilized in design team-building activities.