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This study aims at assessing item fairness in students' evaluation of teaching based on students' academic college using measurement invariance analysis (MI).

The sample of this study consists of 17,270 undergraduate students from 12 different academic colleges. SET survey consists of 20 Likert-type items distributed to four factors: planning, instruction, management and assessment was used to collect the data. The Lavaan R package with confirmatory factor analysis (CFA) was used to evaluate measurement invariance (MI). Four models of CFA were investigated and assessed: the configural model, the metric model, the scalar model and the residual invariance model. ANOVA was used to test the differences in SET according to academic colleges.

MI analysis showed that the four levels of MI models are supported. ANOVA test showed that means of SET total scores are statistically different according to students' academic colleges. College of “Education” has the highest SET mean (88.64 out of 100), and all the differences between the College of Education’s SET mean and other colleges' SET means are statistically significant.

The study recommends that higher education institutions test the MI of SET according to academic colleges and then use colleges with the highest SET at the university level as internal benchmarking to develop and enhance their teaching practices.

This study is probably the only study that tested MI according to students' colleges before testing the differences between colleges in SET. If MI is not supported, then the comparisons between academic colleges are not applicable.

This paper aims to explore the impact of the data observation period on the computation of altmetric measures like velocity index (VI) and half-life. Furthermore, it also attempts to determine whether article-level computations are better than computations on the whole of the data for computing such measures.

The complete publication records for the year 2016 indexed in Web of Science and their altmetric data (original tweets) obtained from PlumX are obtained and analysed. The creation date of articles is taken from Crossref. Two time-dependent variables, namely, half-life and VI are computed. The altmetric measures are computed for all articles at different observation points, and by using whole group as well as article-level averaging.

The results show that use of longer observation period significantly changes the values of different altmetric measures computed. Furthermore, use of article-level delineation is advocated for computing different measures for a more accurate representation of the true values for the article distribution.

The analytical results show that using different observation periods change the measured values of the time-related altmetric measures. It is suggested that longer observation period should be used for appropriate measurement of altmetric measures. Furthermore, the use of article-level delineation for computing the measures is advocated as a more accurate method to capture the true values of such measures.

The research work suggests that altmetric mentions accrue for a longer period than the commonly believed short life span and therefore the altmetric measurements should not be limited to observation of early accrued data only.

The present study indicates that use of altmetric measures for research evaluation or other purposes should be based on data for a longer observation period and article-level delineation may be preferred. It contradicts the common belief that tweet accumulation about scholarly articles decay quickly.

Several studies have shown that altmetric data correlate well with citations and hence early altmetric counts can be used to predict future citations. Inspired by these findings, majority of such monitoring and measuring exercises have focused mainly on capturing immediate altmetric event data for articles just after the publication of the paper. This paper demonstrates the impact of the observation period and article-level aggregation on such computations and suggests to use a longer observation period and article-level delineation. To the best of the authors’ knowledge, this is the first such study of its kind and presents novel findings.

This paper presents a set of instrumental case studies for the context-based learning of BIM in the milieu of knowledge-based practice in the AEC industry. The study aimed to examine students' actions and perspectives in a simulated learning environment for real-world BIM processes. The core intent was to provide an in-depth understanding of strategic and functional BIM implementation by synthesizing a suggestive pedagogical framework based on context-based learning approaches.

Derived from context-based approaches and experiential learning methods such as role-play, problem-based and active learning, the study involved a set of doctoral-level case studies. In a qualitative research study, these cases were devised and organized around industry-focused simulations on various levels of BIM implementation strategies.

Results from the case studies and the student responses suggest that the comprehensive evaluation of real-world BIM implementation simulations facilitates a solid understanding of the value of BIM. The participation of industry professionals catalyzes the development of strategic and functional BIM competencies.

The study proposes a well-structured and replicable BIM learning framework based on context-based learning approaches. The novel framework is adaptive and flexible for BIM education. It can provide students with the necessary skills, strategic vision and professional competencies for innovative practices in the 21st-century AEC Industry. The simulative learning settings, including the evaluation rubrics and connected instructional methods, can be implemented and further developed for similar education efforts.

The outbreak of the COVID-19 pandemic has significantly impacted healthcare systems, presenting unforeseen challenges that necessitated the implementation of change management strategies to adapt to the new contextual conditions. This study aims to analyze organizational changes within the total hip replacement (THR) surgery pathway at multiple levels, including macro, meso and micro. It employs data triangulation from various sources to gauge the complexity of the change process and comprehend how multi-level decision-making influenced an unexpected shift.

A multicentric, single in-depth case study was conducted using a mixed-methods approach. Data sources included patient-reported outcome measures specific to the THR pathway and carefully structured in-depth interviews administered to managers and clinicians in two healthcare organizations serving the same population.

Decisions made at the macro level resulted in an overall reduction in surgical activities. Organizational changes at the meso level led to a complete cessation or partial reorganization of activities. Micro-level actions for change and adaptation revealed diverse and fragmented change management strategies.

Organizations with segmented structures may require a robust and structured department for coordinating change management responses to prevent the entire system from becoming stuck in the absorptive phase of change. However, it is important to recognize that absorptive solutions can serve as a starting point for genuine innovations in change management.

The utilization of data triangulation enables the authors to visualize how specific changes implemented in response to the pandemic have influenced the observed outcomes. From a managerial perspective, it provides insights into how future innovations could be introduced.

The paper sets out to understand the key issues that the various functions and optimal allocation of NGOs (non-governmental organizations) in the circular economy that provide public services depend not only on external quantities or densities but also on their internal size of human resources.

The paper uses different data samples and models to study the influence mechanism of optimal NGO size of human resources and its differentiated effects on governance quality of entrepreneurship.

The authors find that a reduction in transaction costs and an increase in the aggregation degree of public demand lead to increased human capital and lower financial capital intensity. In addition, the authors find that NGO size of human resources has a relationship that is approximately U-shaped (or inverse U-shaped) with the governance quality of entrepreneurship.

The paper discusses the implications for programs that encourage NGOs to optimally determine their internal size of human resources and further improve the governance quality of entrepreneurship in the circular economy.

The paper reveals the significant nonmonotonic relationship between local governance quality and NGO financial size, even after controlling for other NGO, city and provincial characteristics.

The COVID-19 pandemic has impacted the construction industry, yet still, it is unclear from existing studies about the critical challenges imposed on quality assurance (QA), particularly Cross-border Construction Logistics and Supply Chain (Cb-CLSC). Thus, this study aims to identify and examine the critical challenges of QA of Cb-CLSC during the COVID-19 pandemic.

The aim is achieved via an embedded mixed-method approach pragmatically involving a desk literature review and engaging 150 experts across the globe using expert surveys, and results confirmed by semi-structured interviews. The approach is based on Interpretive Structural Modelling (ISM) as its foundation.

The study revealed ten critical challenges of QA, with the top four including “the shortage of raw construction material (C7)”, “design changes (C6)”, “collaboration and communication difficulties (C1)” and “changes in work practices (C10)”. However, examining the interrelationships among the critical challenges using ISM confirmed C7 and C10 as the most critical challenges. The study again revealed that the critical challenges are sensitive and capable of affecting themselves due to the nature of their interrelationship based on MICMAC analysis. Hence, being consistent with why all the challenges were considered critical amid the pandemic. Sentiment analysis revealed that the critical challenges have not been entirely negative but also positive by creating three areas of opportunities for improvement: technology adoption, worker management, and work process management. However, four areas of challenges in the QA include cost, raw material, time, and work process, including inspection, testing, auditing, communication, etc.

The finding provides a convenient point of reference to researchers, policymakers, practitioners, and decision-makers on formulating policies to enhance the effectiveness of construction QA during the pandemic through to the post-pandemic era.

The study enriches the extant literature on QA, Cb-CLSC, and the COVID-19 pandemic in the construction industry by identifying the critical challenges and examining the interrelationships among them. This provides a better understanding of how the construction QA has been affected by the pandemic and the opportunities created.

The primary objective of this research is to determine critical success factors (CSFs) that enable textile enterprises to effectively implement Kaizen, a Japanese concept of continuous development, particularly during disruptive situations. The study aims to provide insights into how Kaizen is specifically employed within the textile sector and to offer guidance for addressing future crises.

This study employs a structured approach to determine CSFs for successful Kaizen implementation in the textile industry. The Triple Helix Actors structure, comprising business, academia and government representatives, is utilized to uncover essential insights. Additionally, the Matriced Impacts Croises-Multiplication Applique and Classement (MICMAC) analysis and interpretative structural modeling (ISM) techniques are applied to evaluate the influence of CSFs.

The research identifies 17 CSFs for successful Kaizen implementation in the textile industry through a comprehensive literature review and expert input. These factors are organized into a hierarchical structure with 5 distinct levels. Additionally, the application of the MICMAC analysis reveals three clusters of CSFs: linkage, dependent and independent, highlighting their interdependencies and impact.

Major contribution of this study is understanding how Kaizen can be effectively utilized in the textile industry, especially during disruptive events. The combination of the Triple Helix Actors structure, MICMAC analysis and ISM provides a unique perspective on the essential factors driving successful Kaizen implementation. The identification of CSFs and their categorization into clusters offer valuable insights for practitioners, policymakers and academia seeking to enhance the resilience and sustainability of the textile industry.

Organizations have increasingly been compelled to engage in ecological businesses in recent decades, necessitating identifying environmental practices contributing to enhanced sustainability. One of the main reasons for doing this research is to see how far down the path to green transformational leadership (GTFL) in Green Human Resource Management (GHRM) practices in the healthcare industry in Pakistan. Additionally, this research aims to analyze how this change affects the long-term success of businesses in sustainable performance (SP).

To identify factors related to the study variables, the research utilized master journals, as well as the Web of Science and Scopus databases. The ISM-DEMATEL (Interpretive Structural Modeling - Decision Making Trial and Evaluation Laboratory) technique was employed to establish a hierarchical model. This model facilitated the identification of cause-and-effect relationships among factors, which were further elucidated using the DEMATEL interrelationship diagram.

The analysis of the results indicates that Green Training (F4), Green Job Analysis (F1), Intellectual Stimulation (F10), and Green Product Innovation (F9) are the primary factors that have a significant impact on achieving Environmental Policies and Regulations (F13), and Subjective Environment Norms (F14) of SP factors.

The study is implemented in the healthcare industry of Pakistan, with a focus on practical and managerial aspects. It encourages managers to develop and adapt their human resources policies and environmental strategies. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment. The research was carried out during the period of the pandemic. The scope of this study was restricted to the healthcare industry in Pakistan.

In order to improve SP, this study presents a unique strategy combining sustainability into decision-making procedures with the function of GTFL in GHRM. Implementing safety health standards is crucial to mitigate the detrimental effects on the environment.

Art-infusion has become a common practice among brands across the globe. This is because marketers leverage the uniqueness and prestige of arts to earn superior profits. Hence, this research aims to understand and measure consumers' willingness to pay (WTP) for art-infused products.

A questionnaire was designed based on conjoint analysis and was responded to by 470 respondents from India. The estimation of preference functions in conjoint analysis was intended to use orthogonal arrays to measure WTP.

The study reveals consumers' utility and WTP for different art-infused products. The results indicated that consumers have the highest WTP for products that have artwork dominated by the visual elements of colour, shapes and space.

The paper presents valuable findings for marketers to develop their product design and earn superior profits.

This is the first study in the domain of the art infusion phenomenon that measures WTP for non-luxury art-infused products. Also, this is the first study to measure WTP for different kinds of art forms.

The cold supply chain industry is still emerging and digital transformation is in the nascent stage in this industry. This paper argues that there are various barriers to implementing blockchain technology in the cold supply chain and aims to develop and validate a model for overcoming key barriers to implementing blockchain technology in the cold supply chain.

The adoption of blockchain technology was proposed through interpretive structural modeling (ISM) and further it is validated using structural equation modeling (SEM).

In this study, ten key barriers to implementing blockchain technology in the cold supply chain were identified, modelled and analysed. Poor leadership style of top management was found to be the most important barriers to implementing blockchain technology in the cold supply chain. The results of SEM indicate that all the paths are supported. The findings showcase the barriers responsible for the lack of blockchain technology infrastructure that ultimately impacts the cold supply chains.

This study highlights the fact that the fate of blockchain technology infrastructure development depends on the leadership style of top management. Demonstrating good leadership style by top management can help overcome the barriers. A good leader pulls the entire team instead of pushing the team. A good leader can guide the entire team to improve IT governance, financial investment, digital footprint, digital readiness, skills and collaboration with service providers to implement blockchain technology. Not only that, a good leader provides mental strength to the team and helps overcome the fear of implementing blockchain in the cold supply chain. A good leader demonstrates good administrative skills and focus on security and privacy policies.

This is a novel contribution towards analysing the key barriers to implementing blockchain technology in the South African cold supply chain using the integrated ISM–MICMAC and SEM approach.