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Existing labor estimation models typically consider only certain construction project types or specific influencing factors. These models are focused on quantifying the total labor hours required, while the utilization rate of the labor during the project is not usually accounted for. This study aims to develop a novel machine learning model to predict the time series of labor resource utilization rate at the work package level.

More than 250 construction work packages collected over a two-year period are used to identify the main contributing factors affecting labor resource requirements. Also, a novel machine learning algorithm – Recurrent Neural Network (RNN) – is adopted to develop a forecasting model that can predict the utilization of labor resources over time.

This paper presents a robust machine learning approach for predicting labor resources’ utilization rates in construction projects based on the identified contributing factors. The machine learning approach is found to result in a reliable time series forecasting model that uses the RNN algorithm. The proposed model indicates the capability of machine learning algorithms in facilitating the traditional challenges in construction industry.

The findings point to the suitability of state-of-the-art machine learning techniques for developing predictive models to forecast the utilization rate of labor resources in construction projects, as well as for supporting project managers by providing forecasting tool for labor estimations at the work package level before detailed activity schedules have been generated. Accordingly, the proposed approach facilitates resource allocation and enables prioritization of available resources to enhance the overall performance of projects.

Algorithm bias refers to repetitive computer program errors that give some users more weight than others. The aim of this article is to provide a deeper insight of algorithm bias in AI-enabled ERP software customization. Although algorithmic bias in machine learning models has uneven, unfair and unjust impacts, research on it is mostly anecdotal and scattered.

As guided by the previous research (Akter et al., 2022), this study presents the possible design bias (model, data and method) one may experience with enterprise resource planning (ERP) software customization algorithm. This study then presents the artificial intelligence (AI) version of ERP customization algorithm using k-nearest neighbours algorithm.

This study illustrates the possible bias when the prioritized requirements customization estimation (PRCE) algorithm available in the ERP literature is executed without any AI. Then, the authors present their newly developed AI version of the PRCE algorithm that uses ML techniques. The authors then discuss its adjoining algorithmic bias with an illustration. Further, the authors also draw a roadmap for managing algorithmic bias during ERP customization in practice.

To the best of the authors’ knowledge, no prior research has attempted to understand the algorithmic bias that occurs during the execution of the ERP customization algorithm (with or without AI).

The purpose of this study is to assess a novel method for creating tangible three-dimensional (3D) morphologies (scaled models) of neuronal reconstructions and to evaluate its cost-effectiveness, accessibility and applicability through a classroom survey. The study addresses the challenge of accurately representing intricate and diverse dendritic structures of neurons in scaled models for educational purposes.

The method involves converting neuronal reconstructions from the NeuromorphoVis repository into 3D-printable mold files. An operator prints these molds using a consumer-grade desktop 3D printer with water-soluble polyvinyl alcohol filament. The molds are then filled with casting materials like polyurethane or silicone rubber, before the mold is dissolved. We tested our method on various neuron morphologies, assessing the method’s effectiveness, labor, processing times and costs. Additionally, university biology students compared our 3D-printed neuron models with commercially produced counterparts through a survey, evaluating them based on their direct experience with both models.

An operator can produce a neuron morphology’s initial 3D replica in about an hour of labor, excluding a one- to three-day curing period, while subsequent copies require around 30 min each. Our method provides an affordable approach to crafting tangible 3D neuron representations, presenting a viable alternative to direct 3D printing with varied material options ensuring both flexibility and durability. The created models accurately replicate the fidelity and intricacy of original computer aided design (CAD) files, making them ideal for tactile use in neuroscience education.

The development of data processing and cost-effective casting method for this application is novel. Compared to a previous study, this method leverages lower-cost fused filament fabrication 3D printing to create accurate physical 3D representations of neurons. By using readily available materials and a consumer-grade 3D printer, the research addresses the high cost associated with alternative direct 3D printing techniques to produce such intricate and robust models. Furthermore, the paper demonstrates the practicality of these 3D neuron models for educational purposes, making a valuable contribution to the field of neuroscience education.

Kerala, being the most literate state in India, has at least one newspaper being subscribed to every household and thus the Print industry in Kerala is doing a commendable job. Labour welfare as a part of industrial relation is assuming greater significance with the growth of industrialization. An industry today is a co-operative undertaking with both the capital and the labour as equal partners. The workers in the modern context are not simply a marketable commodity to be purchased by the owners, but human beings with their own needs, emotions and aspirations who invest their labour in making the industry a success. It is normally believed that the model employer maintains harmonious relation with the employees. Considering the conflicts are usually natural, the employer always tries to minimize the disputes by offering the right mix of labour welfare measures and ensure the loss of man days and the loss of production to the lowest possible extent. This article delineates the industrial relations in Kerala newspaper industry. The data were analyzed related to age, occupation, region of working, education and experience on the leaders' attitude on various factors related to labour welfare. The primary data collected from the trade union leaders were analyzed using the statistical computer package SPSS. Appropriate tests were used for analysis. It can be seen that the leaders were not at all satisfied with any of the facilities except for safety practices for the employees and the grievance handling process since they were directly involved.

Several studies have addressed the use of four-dimensional (4D) building information modeling (BIM) for construction management. However, the automation of the processes for generating 4D models and their integrated use with Location-Based Planning and the Last Planner® System is not well discussed. Therefore, this paper aims to develop a method for automating the generation and use of 4D BIM models integrated with Location-Based Planning and Last Planner® System supporting project control cycles.

The research strategy adopted was Design Science Research. The automated method for using the 4D models was developed and refined in two residential building projects in Brazil, along with 31 meetings and involving 11 direct users. The assessment of the proposed method focuses on four constructs: the impact of process automation, the impact on the identification and assessment of site progress and the planning process, ease of adoption and utility of the proposed method.

The results of this paper indicated increased adherence between planned and executed through an automated method for using the 4D models. The established routines enabled automating the link between the planning levels and the three-dimensional (3D) model, providing a more agile and updated data source and achieving 92.8% of user satisfaction regarding the deadline and frequency of delivery of the 4D model reports. Moreover, this study identified the relationships between the processes of the method proposed and Digital Models.

The primary scientific value achieved in this study is creating a method for automating processes and simplifying steps for the generation and use of 4D BIM models in the production planning and control cycles during the construction phase.

The purpose of this study was to investigate the impact of using a jigsaw learning strategy integrated with computer simulation (JLSICS) on the academic achievement and attitudes of students, along with exploring the relationships between them in the process of learning about acids and bases.

The research design used in the study was quasi-experimental, using non-equivalent comparison groups for both pre- and post-tests. A quantitative approach was used to address the research problem, with three groups involved: two experimental and one comparative group. The treatment group, which received the JLSICS intervention, consisted of two intact classes, while the comparison group included one intact class. Data collection involved achievement tests and attitude scale tests on acid and base. Various statistical analyses such as one-way analysis of variance, one-way multivariate analysis of variance, Pearson product-moment correlation, mean and standard deviation were used for data analysis.

The study’s results revealed that the incorporation of the JLSICS had a beneficial influence on the academic achievement and attitudes of grade 10 chemistry students towards acid and base topics. The JLSICS approach proved to be more successful than both conventional methods and the standalone use of the jigsaw learning strategy (JLS) in terms of both achievement and attitudes. The research demonstrated a correlation between positive attitudes towards chemistry among high school students and enhanced achievement in the subject.

The study only focused on one specific aspect of chemistry (acid and base chemistry), which restricts the applicability of the findings to other chemistry topics or subjects. In addition, the study used a quasi-experimental design with a pretest-posttest comparison group, which may introduce variables that could confound the results and restrict causal inferences.

This study addresses the gap in instructional interventions and provides theoretical and practical insights. It emphasizes the importance of incorporating contemporary instructional methods for policymakers, benefiting the government, society and students. By enhancing student achievement, attitudes and critical thinking skills, this approach empowers students to take charge of their learning, fostering deep understanding and analysis. Furthermore, JLSICS aids in grasping abstract chemistry concepts and has the potential to reduce costs associated with purchasing chemicals for schools. This research opens doors for similar studies in different educational settings, offering valuable insights for educators and policymakers.

The originality and value of this study are in its exploration of integrating the jigsaw learning strategy with computer simulations as an instructional approach in chemistry education. This research contributes to the existing literature by showing the effectiveness of JLSICS in improving students’ achievements and attitudes towards acid and base topics. It also emphasizes the importance of fostering positive attitudes towards chemistry to enhance students’ overall achievement in the subject.

The study's objective was to address the factors impacting the employability attributes of fresh graduates in the Kingdom of Bahrain while considering the various challenges. This study used a quantitative approach which employed the questionnaire tool, and data were collected by using a convenience sampling method. The study sample comprised n = 385 respondents from different industries, including manufacturing, banking and finance, hospitality, healthcare, oil and gas, and real estate sectors of Bahrain. Data gathered from questionnaire were analyzed using Statistical Package for the Social Sciences (SPSS), where descriptive and inferential statistics was used to analyze the data. The results of the study showed for the major Hypothesis 1 that the demographic variables have no significant statistical impact on employment attributes of the new fresh graduates. Moreover, findings suggest that null hypothesis for major Hypothesis 2 has been rejected as applied academic skills and critical thinking skills have no significant impact on employability attribute of fresh graduates in the Kingdom of Bahrain. Null hypothesis for major Hypothesis 3 has been accepted as findings suggest that technology use skills (β ₁ = 0.080), system thinking skills (β ₂ = 0.210), communication skills (β ₃ = 0.402), and information skills (β ₄ = −0.100) which are an antecedent of workplace skills, have significant statistical impact on employability attribute of fresh graduates in Kingdom of Bahrain. Lastly, null hypothesis for major Hypothesis 4 has been accepted as findings suggest that interpersonal skills (β ₅ = 0.229) which are an antecedent of effective relationship have significant statistical impact on employability attribute of fresh graduates in the Kingdom of Bahrain.

This study analyzes sustainable practices adopted by Italian firms to enhance the circularity of packaging and related results in terms of environmental improvements.

The authors developed an empirical analysis using publicly available data from the National Consortium of Packaging (CONAI) in Italy, which consists of 603 circular packaging projects. The authors ran both descriptive and prescriptive analyses to determine individual sustainable practices and portfolios adopted to enhance packaging circularity and to verify related reductions in terms of CO2 emissions as well as energy usage and water consumption.

The findings reveal that firms are more accustomed to focusing on single sustainable practices than on portfolios of practices to achieve packaging circularity. Raw material saving and logistics optimization are the most frequent sustainable practices adopted by firms to improve circularity of packaging. The reuse of packaging allows firms to simultaneously reduce CO2 emissions, energy usage and water consumption. Preferences in terms of portfolio of sustainable practices are strictly linked to the types of materials used for packaging and environmental targets.

The authors investigate environmental practices that firms adopt to support packaging circularity, and the authors detect portfolios of sustainable practices that positively impact environmental performance indicators. This research extends a significant glimpse into the portfolio of sustainable practices for packaging in the circular economy implemented by firms, filling academic gaps and indicating business opportunities and avenues for economic development.

This study aims to explore computer-assisted language learning (CALL) activities to improve the English essay writing of Pakistani university students. It highlights the role of CALL in the language proficiency model cognitive academic language proficiency (CALP), which can enable second language learners to engage in more critical thinking skills effectively. Furthermore, it aims to explore English language teachers’ experience about the use of CALL-based activities in English language classrooms or labs.

This study followed a pre-post study design to examine whether the structure of an essay and computer-based activities helped to improve English language proficiency among non-native speakers. This design is adopted to investigate the effects of CALL activities on students’ English essays. This study used data from 198 students and after this, four English teachers were interviewed to know their opinions and observations about these CALL-based activities and students’ essay writings. Pre- and post-test data was analysed in percentages and further examined through a t-test. The findings of teachers’ interviews were further analysed through Nvivo software to develop an understanding of research questions through significant themes.

The pre-test results confirmed that students’ language proficiency is underdeveloped and informal. Students needed help constructing introductory paragraphs with the reader’s hook, background information, three-point thesis statement and transitional hook. Whereas, post-test results showed that students’ English language proficiency in essay writing was found improved with the use of technological tools and CALL-based activities. Furthermore, it was observed that structure and teacher feedback in essay writing are vital for English proficiency.

This study benefits English language teachers, administrators, language policymakers and syllabus designers at colleges and universities. The debate over how to improve English language proficiency and academic achievement presents diverse challenges across several countries. Non-native speakers, at an undergraduate level, can significantly improve academically and become proficient in English essay writing with the help of structural guidelines and the use of educational technology. This article demonstrates a two-way process to improve an objective definition of English language development, which is conceivable if the technology is adopted.

Micro, small and medium-sized enterprises (MSMEs) are vital for economic growth in developing countries. Yet, little research has explored the link between Islamic principles and MSME performance, especially in Uganda. This study aims to investigate the relationship between Islamic financial principles and MSMEs’ performance in Makindye Division Kampala – Uganda.

This study used a correlational research design involving 86 respondents from 30 MSMEs between January and May 2023. Data collected through questionnaires was analyzed with Statistical Package for Social Sciences, examining three independent variables: ethicality, Halal investment and prohibition of riba, in relation to MSME performance.

The results revealed significant relationships between these variables and MSME performance. Prohibition of riba (r = 0.296, n = 86, p = 0.006), Halal investments (r = 0.308, n = 86, p = 0.004) and ethical principles (r = 0.283, n = 86, p = 0.008) all exhibited a statistically significant relationship. Regression analysis with R = 0.405, R² = 0.164 and adjusted R² = 0.134 indicated that all hypothesized variables were significant predictors of MSME performance. Based on findings, this study rejected the null hypothesis, confirming a moderately positive and significant relationship between Islamic financial principles and MSME performance.

This study underscores the importance of active involvement from key stakeholders such as the Uganda Halal Bureau, Uganda Muslim Supreme Council, Islamic financial institutions and government agencies in integrating robust support mechanisms for MSMEs into their strategic frameworks. Such efforts could enhance Uganda’s economic landscape, aligning with the experiences of Malaysia and Indonesia in leveraging Islamic principles for economic growth.