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This study determines the critical success factors of teaching mathematics to special education (SPED) students wherein a list of success factors is identified through a literature survey and analyzes the causal relationships among the identified factors to evaluate the key success factors using the integration of the grey system theory and decision-making trial and evaluation laboratory (DEMATEL), named as the grey-DEMATEL. Results reveal that professional development (PD), institutional support (IS), and individual factors (IF) are categorized as net causes. They influence other factors considered as net effects, including mentoring, self-efficacy, teaching capacity, student feedback, teaching knowledge, instructional accommodation, and use of technology. Among those net causes, only PD yields as the key factor, while IS and IF are the minor key factors. Thus, decision-makers must allocate resources that provide PD to teachers in delivering SPED mathematics teaching. A sensitivity analysis suggests these findings are robust to linguistic evaluation scale changes. The insights outlined in this study would aid educational managers and decision-makers of educational institutions in carefully designing initiatives to improve the quality of mathematics education provided to SPED students. Some potential directions for future research agenda are also discussed.

Flipped classrooms serve as a new pedagogical approach for teaching and learning, which involves switching from the traditional teacher-centred academic agenda. Unlike the traditional classroom model, the flipped classroom enables students to understand the lesson better while learning at their own pace and enhancing their communication skills among peers. At the same time, lecturers are provided with an opportunity to extend the discussion time in class through a more interactive session between students. While research works regarding the success of implementing flipped classrooms have been widely undertaken in the literature, only a few of these works considered exposing such models to secondary students. Engaging secondary students in the flipped classroom and investigating its impact on students paves the way for preparing an academic environment for students' advanced courses in the future. In this work, a case study was conducted at Barstow High School (Barstow, California) to evaluate the implementation of flipped classrooms in Mathematics education from an interplay of factors such as gender, ethnicity, and students' attitude. The students showed positive usability of the model from the end-activity evaluation and further noted an improved communication channel inside the classroom, allowing them to pace their own learning.

The factors influencing consumer purchase decisions in electronic commerce platforms and the interrelationships of each element are prevalent in the domain literature. However, a comprehensive analysis of the complex interrelationships among the success factors remains unexplored, especially in a social commerce context. To address the gap, this work evaluates the relationship structure and determines the critical factors using interpretive structural modelling (ISM). On the other hand, the Matrice d’Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) is introduced to analyse the interaction of the factors and recognise the most relevant among them. In demonstrating the ISM-MICMAC analysis, this work performed a case study evaluating 13 factors of social commerce success for food products derived from a previous study. The findings of this work suggest that timeliness, data privacy policy, and Internet connectivity drive most other factors. Thus, focusing the resources on augmenting these factors consequently improves other factors. These findings suggest that sellers must streamline their overall service chain to maintain timeliness in their transactions, safeguard consumers’ data privacy, and uphold consumer communication efficiency to maximise Internet connectivity. These insights provide useful information to help decision-makers in the food industry allocate resources and encourage more consumers for social commerce. Several managerial insights were discussed.

Alongside the current demand for advanced degrees, teachers are often compelled with the professional duty to study further. Since motivation is a critical concept in understanding the participation of these individuals in pursuing advanced learning, this exploratory research aims to provide a deeper understanding of the motivational dynamics of the graduate students of education (GSEs) through the hedonic and eudaimonic lenses, which is a relatively new setting for this idea. The self-determination theory juxtaposed this in a simple query about whether graduate students are studying for pleasure, virtue, or both. The method in this work is described in two parts. First, the hedonic and eudaimonic motivation of 594 samples of GSEs was measured through a developed Integrated Hedonic--Eudaimonic Motivation Scale. Second, cluster analysis of the survey results was employed with K-means clustering and ANOVA to determine the distinct groups of GSEs and their characteristics. The findings of this study suggest that GSEs, in general, have a high level of both hedonic and eudaimonic motivation and, thus, classified under the "flourishing" typology. Based on their characteristics, the cluster analysis generated three distinct clusters: passionate cluster, progressive cluster, and struggling cluster. Using ANOVA, the following variables were identified as the major contributors to the distinction of the three clusters: hedonic motivation, age, master's degree major, doctor's degree institution, doctor's degree program, sources of funding, the support given to parents, and net income.

As a foundational approach in inferential statistics, hypothesis testing (HT) is considered as one of the most challenging topics for teaching and learning. A promising approach is through the consideration of students' learning modalities, as demonstrated in vast applications; however, contentions that surround the use of learning modality in education exist in recent debates. The cause of this unrest is the lack of robust empirical evidence on the efficacy of learning modalities in education. Thus, this work attempts to contribute to this debate and investigates whether sensory modality does influence learning. It develops an approach for teaching HT to college students via learning modality. Results show that learning modalities have a positive impact on students' performance on competencies in learning HT. Furthermore, it was found out that some learning modalities work together on learning specific competencies. Lastly, the task-dependency of learning modalities was observed in the results of the experiment.

This work offers a structural model that explains farm tourist revisit intention (RI), which highlights place attachment (PA) and memorable tourism experience (MTE) in addition to tourist satisfaction, perceived risks (PR), and tourism destination image (TDI) as antecedents. Partial least squares–structural equation modelling was used to evaluate their theoretical relationships. Findings suggest that MTE and PA are the strongest predictors of RI, with satisfaction also influencing RI. The mediation analysis shows that PA partially mediates satisfaction and RI, and satisfaction partially mediates TDI and RI. This work also frames a new theoretical lens on the relationship of PR with satisfaction, TDI, and RI in the farm tourism literature. It provides farm tourism sites a better understanding of tourist behavioural intention to revisit, inputs to the design of initiatives for tourism marketing, and aids in short- and medium-term planning and resource allocation decisions. [ABSTRACT FROM AUTHOR]

This work holistically evaluates the factors that can aid decision makers in finding the optimal location for food businesses in developing economies. It integrates the analytic hierarchy process (AHP) in determining criteria weights (i.e. benefit, opportunity, cost, risk) and the newly introduced three-way decision – Technique for Order Preference by Similarity to Ideal Solution (3WD-TOPSIS) method in identifying the priority factors. Applying the AHP yields the assignment of more priorities to benefits and opportunities rather than costs and risks, reflecting the benefit – or opportunity-oriented attitudes of food businesses. Meanwhile, the implementation of 3WD-TOPSIS results in the identification of government regulations and restrictions, proximity to consumers, parking capacity, supply chain strategy, and socio-economic status as the most crucial location decision factors. Findings from the comparative analyses show a high agreement between the results and those of other comparable methods. Managerial insights from these findings are outlined in this work. [ABSTRACT FROM AUTHOR]

In the unit-load warehouse (UW) design, the aisle design problem dealing with storage space layout is the first among the three main problems. Several conventional and non-conventional designs have been proposed in the literature. In general, the assessment of UW designs is commonly carried out using analytical approaches. However, such an approach may be inadequate due to assumptions or approximations, making results unrealistic. Aiming to bridge this gap, this research develops an assessment framework that employs the FlexSim software for simulating the conventional, Flying-V and Fishbone designs based on a real case from a Philippine manufacturing company. Using a computer simulation, this research investigates factors not yet tractable with present analytical methods. The factors employed for the comparative assessment are “picking run-time”, “travel distance”, and “capacity”. The results suggest that the Fishbone design provides the most advantage compared to the Flying-V and other conventional designs. With the proposed Fishbone design, the company is expected to save, on average, 52.39% of picking run-time, 32.25% travel distance, and increase storage capacity by 7.5%. The research findings are compared to previous studies based on analytical approaches.

This work explores how social capital impacts community resilience via the community development framework, with dimensions spanning trust, cooperativism, volunteerism, reciprocity, and interpersonal relationships in mitigating climate change impacts. With flooding impacts as a case, a mixed method approach was used, purposely recruiting 24 research cooperators in one of the suburban villages in the central Philippines. Results show that key components in disaster mitigation plans include help-seeking behavior, community responses, social relations, and resource allocation within communities. Findings demonstrate that social capital has proven invaluable in mobilizing resources, building resilience, disseminating information, mediating conflict resolution, providing psychological support, and improving livelihoods within communities. By exploring the role of social capital in community development, this study sheds light on its importance for climate change mitigation and disaster risk reduction initiatives. Policymakers, development practitioners, and community leaders can frame these findings to effectively harness social capital and foster community participation. [ABSTRACT FROM AUTHOR]

The need to address the impediments to teaching numeracy in early childhood education necessitates a comprehensive approach, as an evident lack of exploration of impediments and their intertwined relationships exists in the domain literature. Thus, this work advances such agenda by utilizing the decision‐making trial and evaluation laboratory (DEMATEL) approach with q‐rung orthopair fuzzy sets (q‐ROFSs), referred to as q‐ROF‐DEMATEL. Unlike other fuzzy set extensions, q‐ROFS offers a larger decision space, providing the capability to handle information with greater ambiguity. The proposed q‐ROF‐DEMATEL is applied to identify the critical factors impeding effective instruction of numeracy skills to early childhood learners. The findings suggest that the prominent impediments include inadequate teaching time, lack of teaching knowledge, and underestimation of learners' knowledge. Moreover, among the identified impediments, the lack of teaching knowledge emerges as the key impediment, while language barriers, inadequate teaching time, and lack of educational resources are identified as minor key impediments. These findings could guide decision makers in academic institutions to allocate resources effectively, pool human resources strategically, and develop appropriate strategies to augment teaching numeracy. Investing in professional development opportunities, incorporating visual representations and culturally relevant materials, and seeking community partnerships for resources are some recommended initiatives to address these challenges. Insights for future work were outlined. [ABSTRACT FROM AUTHOR]

Warehouses are crucial infrastructures in supply chains. As a strategic task that would potentially impact various long-term agenda, warehouse location selection becomes an important decision-making process. Due to quantitative and qualitative multiple criteria in selecting alternative warehouse locations, the task becomes a multiple criteria decision-making problem. Current literature offers several approaches to addressing the domain problem. However, the number of factors or criteria considered in the previous works is limited and does not reflect real-life decision-making. In addition, such a problem requires a group decision, with decision-makers having different motivations and value systems. Analysing the varying importance of experts comprising the group would provide insights into how these variations influence the final decision regarding the location. Thus, in this work, we adopted the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to address a warehouse location decision problem under a significant number of decision criteria in a group decision-making environment. To elucidate the proposed approach, a case study in a product distribution firm was carried out. Findings show that decision-makers in this industry emphasise criteria that maintain the distribution networks more efficiently at minimum cost. Results also reveal that varying priorities of the decision-makers have little impact on the group decision, which implies that their degree of knowledge and expertise is comparable to a certain extent. With the efficiency and tractability of the required computations, the TOPSIS method, as demonstrated in this work, provides a useful, practical tool for decision-makers with limited technical computational expertise in addressing the warehouse location problem.

As Industry 4.0 offers significant productivity improvements, its relevance has grown across various organisations. While it captures the attention of both the industry and the academia, very few efforts have been made to streamline useful indicators across stages of its implementation. Such work facilitates the development of strategies that are appropriate for a specific stage of implementation; therefore, it would be significant to a variety of stakeholders. As a result, this paper aims to establish an indicator system for adopting Industry 4.0 within the context of the three stages of the innovation adoption: (i) pre-adoption, (ii) adoption, and (iii) post-adoption. First, a comprehensive review was performed with a search expanding into the literature on innovation and technology adoption. Second, the resulting indicators were filtered for relevance, redundancy, description, and thorough focus discussions. Finally, they were categorised by their stage of adoption. From 469 innovation adoption indicators found in the literature, this work identified a total of 62 indicators relevant for the Industry 4.0 adoption, in which 11, 14, and 37 of them comprised the three stages, respectively. Case studies from two manufacturing firms in the Philippines were reported to demonstrate the applicability of the proposed indicator system. This work pioneers the establishment of an indicator system for the Industry 4.0 adoption and the classification of such indicators into three stages — pre-adoption, adoption, and post-adoption — which would serve as a framework for decision-makers, practitioners, and stakeholders in planning, strategy development, resource allocation, and performance evaluation of the Industry 4.0 adoption.

Technical skills related to basic mathematics in higher education have been a key foundation for further allied courses across primary programmes. While the traditional learning strategies appear to be inadequate to enhance the basic mathematics skills of university students, digital mathematical games pose the potential to improve such a set of skills by means of mobile learning. This work focuses on investigating the influence of digital mathematical games on students' basic mathematics skills under four various academic programmes. To illustrate the proposed scheme, a case study is conducted in a state university in the Philippines across undergraduate programmes in information technology, hospitality management, industrial engineering, and education. It was found that the use of digital games can improve the skills of students in basic mathematics. Thus, the educational system may be redesigned along with the positive effects of digital games on traditional skill enhancement initiatives. [ABSTRACT FROM AUTHOR]