Search results

This paper aims to review the elements of facilities condition index (FCI) as one of the most widely used metrics for describing the physical condition of facilities and as a measure of financial indicator related to maintenance activity. This research will benefit future studies that focus on implementation of FCI and encourage the best practice when assessing the physical condition to evaluate the performance of facilities as well as to plan for maintenance action to be taken and financial implication involved based on the findings from FCI.

A total of 33 studies from 2012 to 2022 were identified and extracted from four academic databased, named Scopus, Google Scholar, Web of Science and Mendeley. These published studies were selected because it matches with the inclusion requirements for research question, “What are the elements of facilities condition index discussed in the literature from 2012 to 2022?”. To answer the research question, the studies in ATLAS.ti were grouped into five major themes based on the codes and categories found.

This paper presents the findings of a thematic analysis of the current literature discussed about FCI. A total of 33 studies from 2012 to 2022 were identified and extracted from four academic databased, named Scopus, Google Scholar, Web of Science and Mendeley. A themed review was conducted, and five themes were identified as elements of FCI, which are named as follows: “Condition Assessment”, “Deferred Maintenance”, “Facilities Performance”, “Financial and Fund Allocation” and “Decision Making”.

This paper fulfils the fundamental elements on current FCI practices as well as intended to highlight existing practices that are essential to evaluate facilities performance and planning for maintenance strategies.

Buoyed by the increasing demand for improved productivity and environmentally conscious manufacturing, research in the area of lean production and green manufacturing has experienced significant growth since Dües et al. (2013). Taking the latter as the point of reference, a review of recent developments in the complementary and conflicting areas between lean production and green manufacturing that has been missing is presented.

A systematic search was done to identify articles on lean production and green manufacturing from Scopus, Web of Science and Google Scholar. The population-intervention-outcome format was used to develop and answer the research questions. ATLAS.ti 22 was used to analyse 141 qualifying papers and identify the research themes.

Lean production and green manufacturing have strong synergy, and when integrated, they tend to deliver superior organisational performance than their individual implementations. This is consistent with the pre-2013 results, and other areas of synergy and divergence were also identified.

The study considers only papers published in the manufacturing sector after Dües et al. (2013). A review of lean production and green manufacturing in integrated product-service systems may also be relevant, especially due to the continuing trend since its introduction.

Any new adopter of lean production should consider implementing it simultaneously with green manufacturing.

This study establishes the persistence of the pre-2013 patterns of synergy and divergence between lean production and green manufacturing, and identifies new considerations for their joint implementation.

This qualitative study assesses the enablers of the work of a novel, self-managing digital pedagogy peer support team in a Finnish higher education institution.

This study employs a qualitative methodology with in-depth interviews of five digital pedagogy facilitators. The data collected are analyzed with the ATLAS.ti software. The analytical approach follows a deductive method, applying the categories derived from Magpili and Pazos (2018) who investigated the input variables of self-managing teams through their extensive literature review.

The primary findings underscore the suitability of Magpili and Pazos' variables for evaluating the performance enablers of self-managing teams. Furthermore, the findings emphasize the significance of leadership and effective communication as essential prerequisites for achieving elevated performance levels.

This study focuses on the enablers of team performance from the perspective of the team members. To enhance comprehensiveness, subsequent phases should incorporate viewpoints from clients, namely peer instructors, and focus on the mediator and outcome aspects of the team effectiveness framework.

This study offers actionable recommendations for higher education institutions aiming to adopt a peer mentor model akin to the one delineated in the study.

This study analyzes a collaborative approach to advancing digital pedagogy within higher education institutions and discusses the enablers for successful performance within self-managing teams.

This study aims to investigate how early and late adopters of Quality 4.0 (Q4.0) differ in terms of organizational performance.

The authors employed a grounded theory approach for interviewing 15 senior managers from diverse organizational contexts throughout the globe as part of their qualitative research methodology.

The research's findings were analyzed based on four types of performance: operational, financial, environmental and social. It was clear that early adopters of Q4.0 were sustaining superior performance in quality over time, even though their investment was significantly higher than that of late adopters. From a financial viewpoint, it was evident that early adopters had a competitive edge over their rivals compared to late adopters. Late adopters have utilized the notion of the circular economy (CE) more effectively than many early adopters in the context of environmental performance in order to establish a green economy and sustainable development.

Although the results of the interview indicate that Q4.0 is having some positive effects on social performance, in the authors' view, it is still least understood from an empirical standpoint.

The study's findings assist organizations in comprehending the performance differences between Q4.0 early adopters and late adopters.

The purpose of the paper is to predict mapping of areas vulnerable to flooding in the Ourika watershed in the High Atlas of Morocco with the aim of providing a useful tool capable of helping in the mitigation and management of floods in the associated region, as well as Morocco as a whole.

Four machine learning (ML) algorithms including k-nearest neighbors (KNN), artificial neural network, random forest (RF) and x-gradient boost (XGB) are adopted for modeling. Additionally, 16 predictors divided into categorical and numerical variables are used as inputs for modeling.

The results showed that RF and XGB were the best performing algorithms, with AUC scores of 99.1 and 99.2%, respectively. Conversely, KNN had the lowest predictive power, scoring 94.4%. Overall, the algorithms predicted that over 60% of the watershed was in the very low flood risk class, while the high flood risk class accounted for less than 15% of the area.

There are limited, if not non-existent studies on modeling using AI tools including ML in the region in predictive modeling of flooding, making this study intriguing.

Although numerous studies have been conducted to explore the impact of various factors on employees' turnover intention and intention to remain with the organization, the relationship between these two constructs remains largely unexplored. Considering the significance of these constructs, particularly in the context of the COVID-19 pandemic, the authors aimed to investigate their association within an academic environment using a dynamic modeling approach.

This study follows a quantitative approach and utilizes a longitudinal survey design. The authors utilized a cross-lagged panel model (CLPM) and employed the parametric efficient partial least squares (PLSe2) methodology to estimate the dynamic model using data gathered from lecturers associated with both public and private universities in Malaysia. In order to offer methodological insights to applied higher education researchers, the authors also compared the results with maximum likelihood (ML) estimation.

The findings of the authors' study indicate a reciprocal relationship between turnover intention and intention to remain with the organization, with intention to remain with the organization being a stronger predictor. Moreover, situational factors were found to have a greater influence on eliciting turnover intention within academic settings. As anticipated, the use of the PLSe2 methodology resulted in higher R² values compared to ML estimation, thereby reinforcing the effectiveness of PLS-based methods in explanatory-predictive modeling in applied studies.

The authors' findings suggest prioritizing policies that enhance training and consultation sessions to foster positive attitudes among lecturers. Positive attitudes significantly impact judgment-driven behaviors like turnover intention and intention to remain with the organization. Additionally, improving working environments, which indirectly influence judgment-driven behaviors through factors like affective work events, affect and attitudes, should also be considered.

This study pioneers the examination of the causal relationship between turnover intention and intention to remain with the organization, their stability over time and the association of changes in these variables using a dynamic CLPM in higher education. It introduces the novel application of the cutting-edge PLSe2 methodology in estimating a CLPM, providing valuable insights for researchers in explanatory-predictive modeling.

The purpose of this study is to critically analyze the key factors contributing to gender disparities in the science, technology, engineering and mathematics (STEM) fields and propose creative solutions to mitigate these differences. Despite the significance of this issue, it has not received sufficient attention owing to the absence of clarity regarding the factors that exacerbate the gender gap.

This study used a qualitative methodology that combined the viewpoints of social psychology and educational research to pinpoint and evaluate essential elements. Using a grounded theory approach, semistructured interviews were analyzed, and the obtained data were coded and categorized using ATLAS.ti software.

This qualitative research identified three key areas: internal and external factors influencing the gender gap, as well as strategic actions within higher education to address these disparities. The innovative contribution of this study lies in its development of a comprehensive theoretical framework that enables the diagnosis, quantification and understanding of these factors and proposes practical measures to mitigate these gender disparities. By promoting greater gender diversity, the proposed model can contribute to more inclusive and sustainable development, which is consistent with the 2030 agenda.

This study highlights the need for a multidimensional approach to address the gender gap in higher education, fills a crucial knowledge gap and provides a theoretical model to guide effective university policies.

Despite the growing interest in the field, the literature overlooks how supply chains influence or interact with the United Nations (UN) Sustainable Development Goals (SDGs). To fill this gap, this study aims to assess the influences of Sustainable Supply Chain Management (SSCM) on the implementation of the UN SDGs.

A systematic literature review of 97 publications was carried out by using the Web of Science database and the support of ATLAS.ti software. In addition, this research also explored how the top 20 Forbes companies are aligned with the SDGs by analysing their sustainability reports.

The findings suggest that the literature and the analysed companies primarily concentrate on certain SDGs while neglecting others, revealing potential areas of interest for future research. Based on the findings, the study provides valuable insights into the connections between SSCM and the UN SDGs, highlighting the potential benefits of SSCM in reducing environmental, social and economic pressures and contributing to sustainable development. It also identifies areas where further research and policy development are needed to maximise the potential benefits of SSCM.

To the best of the authors' knowledge, no other studies have conducted a comprehensive exploration of the literature linking SSCM and the SDGs framework. Moreover, the study differs from others since it combines research data with practical information from company reports, to identify specific issues related to supply chain management.

Employers increasingly require students to possess competences that go beyond theoretical knowledge and academic expertise, such as lifelong learning skills. To equip students with these competences, higher education institutes have introduced coaching as part of their teaching programs. The present study qualitatively evaluates a career coaching practice in higher education.

We conducted semi-structured interviews with graduates who had participated in career coaching activities at a Dutch university (N = 12). The interviews were conducted between February and May 2022. Atlas.ti version 9 was used to analyse the interviews.

Results revealed that graduates believed that career coaching helped them to adjust to the workplace. They indicated that the coaching practice helped them to acquire reflection skills, which was considered the main mechanism for adjustment to the workplace.

These results add to the transition-related literature by identifying one way that graduates successfully adjust to the workplace.

The results also provide insight into how higher education can best prepare students for their transition to the workplace.

As the education-to-work transition does not end upon graduation, this research focusses on graduate employees’ work adjustment as an important phase in the transition process.

Social media has revolutionized marketing communication (MC). Rugby is South Africa’s most professionalized sport, leading the industry in its business management structure as well as its high-performance achievements. However, below the professional level, local rugby clubs face a large disparity compared to their professional counterparts, often relying on volunteers or part-time employees to manage the organizations. Therefore, the purpose of this study is to investigate how non-professional rugby clubs use social media as a MC tool.

The study was exploratory, and a cross-sectional sample of twelve organizations was selected and employed a multiple case study approach. Club managers responsible for MC or social media participated in semi-structured interviews. The qualitative data analysis software, ATLAS.ti, facilitated the researchers’ use of an inductive approach to develop codes and themes for further analysis.

The findings revealed a high level of adoption of social media by the multiple cases (i.e. rugby sports club respondents), with only slight variations in the usage of specific social media applications (viz., Facebook, Instagram, Twitter, and WhatsApp). The sports clubs perceived that employing social media added substantial value to their MC. There were six emergent themes related to the organization’s perceived benefits from adopting social media MC, namely: brand awareness, relationship-building, player recruitment, attracting sponsors, storytelling, and information sharing.

The study makes a novel contribution in terms of how rugby clubs use social media as an MC tool. The paper advances scant knowledge and awareness of the relationship between South Africa’s sports marketing and social media. The conclusions will aid non-professional sports organizations in enhancing the effectiveness of their social media marketing by ensuring that their objectives and target audiences are well-defined.