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This paper aims to propose a new deep learning technique to detect the type of material to improve automated construction quality monitoring.

A new data augmentation approach that has improved the model robustness against different illumination conditions and overfitting is proposed. This study uses data augmentation at test time and adds outlier samples to training set to prevent over-fitted network training. For data augmentation at test time, five segments are extracted from each sample image and fed to the network. For these images, the network outputting average values is used as the final prediction. Then, the proposed approach is evaluated on multiple deep networks used as material classifiers. The fully connected layers are removed from the end of the networks, and only convolutional layers are retained.

The proposed method is evaluated on recognizing 11 types of building materials which include 1,231 images taken from several construction sites. Each image resolution is 4,000 × 3,000. The images are captured with different illumination and camera positions. Different illumination conditions lead to trained networks that are more robust against various environmental conditions. Using VGG16 model, an accuracy of 97.35% is achieved outperforming existing approaches.

It is believed that the proposed method presents a new and robust tool for detecting and classifying different material types. The automated detection of material will aid to monitor the quality and see whether the right type of material has been used in the project based on contract specifications. In addition, the proposed model can be used as a guideline for performing quality control (QC) in construction projects based on project quality plan. It can also be used as an input for automated progress monitoring because the material type detection will provide a critical input for object detection.

Several studies have been conducted to perform quality management, but there are some issues that need to be addressed. In most previous studies, a very limited number of material types were examined. In addition, although some studies have reported high accuracy to detect material types (Bunrit et al., 2020), their accuracy is dramatically reduced when they are used to detect materials with similar texture and color. In this research, the authors propose a new method to solve the mentioned shortcomings.

The purpose of this paper is to present results of a study that operationalizes the construct of disruptive innovation activities (DIA) at managerial level and to examine its validity.

A sequential mixed method approach is adopted in this study where a Likert-type scale to measure DIA is developed basing on the interviews of thirteen managers and conceptualization of disruptive innovation at manager level. Later, the scale validity and reliability are examined through quantitative data from 390 managers. The data are analyzed using IBM SPSS 23 and AMOS 21.

The findings of the study indicate that managers' DIA are spread across four phases of the disruptive innovation process, i.e. initiation, introduction, evolution and convergence. Furthermore, the reliability measures, exploratory factor analyses, confirmatory factor analysis and subsequent convergent and discriminant validity tests support the DIA scale. Nomological validity of DIA is also presented which demonstrates its predictive validity.

Limitations include research methods used in this study, such as cross-sectional design and nonprobabilistic sampling technique. Implications for future research are also provided.

Despite highlighting the importance of managers regarding disruptive innovation outcomes, prior research lacked to provide empirical foundations to understand the phenomenon from managerial perspective. This study fills this gap in the literature by providing a measure of DIA at manager level and distinguishing it from similar constructs. The construct validity of DIA can help measure an organization's disruptive potential in terms of its key human resource. Moreover, the DIA scale can be used to substantiate the alignment of the managerial activities with the innovation roles in organizational settings and to develop more relevant incentive plans.

This paper aims to detail the human resource management practices that have helped Majan College, Oman, to win a string of prizes for total quality management.

The paper outlines the characteristics of four main leadership styles – transformational, authoritarian, participative and delegative – and describes the benefits the college has gained by, in the main, practicing transformational leadership.

The paper shows that, when transformational leadership is practiced, team members believe that their leaders care about them as people, rather than as a means to an end; leaders pay close attention to team members' need for achievement and personal growth, creating an environment in which team members feel that they are pursuing meaningful goals; and leaders gain credibility and respect by “walking the talk”.

The paper provides useful information on the advantages and disadvantages of various leadership styles, when practiced in an academic environment.

The paper reveals that other leadership styles also have their part to play. In particular, authoritarian leadership can help when there is an urgent need to: ensure tasks are completed on time and within the financial budget; meet accreditation and quality requirements; and meet student needs.

Despite its devastating nature, the COVID-19 pandemic has also catalyzed a substantial surge in the adoption and integration of technological tools within economies, exerting a profound influence on the dissemination of information among participants in stock markets. Consequently, this present study delves into the ramifications of post-pandemic dynamics on stock market behavior. It also examines the relationship between investors' sentiments, underlying behavioral drivers and their collective impact on global stock markets.

Drawing upon data spanning from 2012 to 2023 and encompassing major world indices classified by Morgan Stanley Capital International’s (MSCI) market and regional taxonomy, this study employs a threshold regression model. This model effectively distinguishes the thresholds within these influential factors. To evaluate the statistical significance of variances across these thresholds, a Wald coefficient analysis was applied.

The empirical results highlighted the substantive role that investors' sentiments and behavioral determinants play in shaping the predictability of returns on a global scale. However, their influence on developed economies and the continents of America appears comparatively lower compared with the Asia–Pacific markets. Similarly, the regions characterized by a more pronounced influence of behavioral factors seem to reduce their reliance on these factors in the post-pandemic landscape and vice versa. Interestingly, the post COVID-19 technological advancements also appear to exert a lesser impact on developed nations.

This study pioneers the investigation of these contextual dissimilarities, thereby charting new avenues for subsequent research studies. These insights shed valuable light on the contextualized nexus between technology, societal dynamics, behavioral biases and their collective impact on stock markets. Furthermore, the study's revelations offer a unique vantage point for addressing market inefficiencies by pinpointing the pivotal factors driving such behavioral patterns.

This research aims to present the results of a study that operationalizes the construct of perceived work identity deprivation (PWID) and examines its validity.

The authors adopted a mixed method design in this study where a Likert-type scale to measure PWID was developed based on the interviews of 40 workers and the questionnaires of 625 participants successively. Later, the generalizability of the scale was tested through quantitative data from 412 workers. Finally, validity analysis was conducted based on 380 usable questionnaires. Data were analyzed using IBM SPSS 24 and Mplus 7.0.

The findings of the study indicate that the reliability measures, exploratory factor analyses, confirmatory factor analysis and subsequent convergent and discriminant validity tests support the PWID scale. The nomological validity of PWID is also presented, which demonstrates its predictive validity.

Despite highlighting the importance of work identity, prior research lacked to provide empirical foundations to understand this perception. This study fills this gap in the literature by providing a measure of PWID, distinguishing it from similar constructs and establishing convergent, discriminant and nomological validity. Moreover, by extending the range of theoretical and measurable deprivation of work identity, the authors hope to allow research to take into account a more complete picture of it. PWID scale can be used to develop more relevant suppression plans.

From 1979 to 2023, the takaful structure has been adopted in many jurisdictions, making the documenting of its early days of establishment relatively difficult and somewhat unreliable. This is unlike conventional insurance, where the history and legislation are well documented and archived in various research (Hellwege, 2016; Marano and Siri, 2017). The purpose of this paper is to provide a chronology for the establishment and development of takaful via the takaful establishment in each jurisdiction, documenting its first takaful operator and first takaful regulation.

This paper has used a qualitative method in the form of reviewing literature and available data such as journals, books and official resources. The data is thoroughly analysed in order to build the chronology for takaful. It adopted an exploratory research design, which is deemed suitable in situations where few works of literature have examined the subject (Neuman, 2014). The paper explores the establishment and non-establishment of takaful in 57 countries. The paper categorises the countries into seven regions starting with the GCC, Levant, Asia, Central Asia, Africa, Europe and Others.

The takaful chronology presented in this paper shows that takaful operations exist in 47 jurisdictions, starting from Sudan and the UAE in 1979, with the most recent adopters being Morocco and Iran in December 2021. It is found that 22 jurisdictions do not have takaful regulations, and the Takaful Act 1984, issued in Malaysia, is considered the first takaful regulation that sets the basis for other regulations that follow.

The paper contributes to the literature by providing a comprehensive chronology of takaful, especially as the few existing timelines have been found to be incomplete and consist of contradictory information.

This paper aimed to examine the role of knowledge sharing among member enterprises between collaborative innovation activities and innovation performance and between building information modeling (BIM) application and innovation performance in the construction supply chain.

The structural equation model was used in this study. First, the hypothesis of the relationship between collaborative innovation activities, BIM application, knowledge sharing and innovation performance in the construction supply chain was proposed based on experience; then, the research data were collected by investigation; finally, this hypothesis was tested through data analysis.

(1) Collaborative innovation activities in the construction supply chain had a positive impact on explicit knowledge sharing, tacit knowledge sharing and innovation performance. (2) BIM application had a positive impact on explicit knowledge sharing and innovation performance, while it had no significant impact on tacit knowledge sharing. (3) Explicit knowledge sharing had no positive effect on innovation performance, while tacit knowledge sharing had positive effect on organizational performance. (4) Tacit knowledge sharing produced partial mediating effect between collaborative innovation activities, BIM application and innovation performance, while explicit knowledge sharing produced complete mediating effect between BIM application and tacit knowledge sharing.

A relationship model among collaborative innovation activities, BIM application, explicit and tacit knowledge sharing and innovation performance in the construction supply chain was proposed, and the rationality of the model was verified by empirical analysis. Discovering the relationships between these factors can be not only conducive to mastering the effect of explicit and tacit knowledge sharing in the collaborative innovation process of construction supply chain, but also play a guiding role for the function development of BIM.

This study aims to delve into the coupled mixed convective heat transport process within a grooved channel cavity using CuO-water nanofluid and an inclined magnetic field. The cavity undergoes isothermal heating from the bottom, with variations in the positions of heated walls across the grooved channel. The aim is to assess the impact of heater positions on thermal performance and identify the most effective configuration.

Numerical solutions to the evolved transport equations are obtained using a finite volume method-based indigenous solver. The dimensionless parameters of Reynolds number (1 ≤ Re ≤ 500), Richardson number (0.1 ≤ Ri ≤ 100), Hartmann number (0 ≤ Ha ≤ 70) and magnetic field inclination angle (0° ≤ γ ≤ 180°) are considered. The solved variables generate both local and global variables after discretization using the semi-implicit method for pressure linked equations algorithm on nonuniform grids.

The study reveals that optimal heat transfer occurs when the heater is positioned at the right corner of the grooved cavity. Heat transfer augmentation ranges from 0.5% to 168.53% for Re = 50 to 300 compared to the bottom-heated case. The magnetic field’s orientation significantly influences the average heat transfer, initially rising and then declining with increasing inclination angle. Overall, this analysis underscores the effectiveness of heater positions in achieving superior thermal performance in a grooved channel cavity.

This concept can be extended to explore enhanced thermal performance under various thermal boundary conditions, considering wall curvature effects, different geometry orientations and the presence of porous structures, either numerically or experimentally.

The findings are applicable across diverse fields, including biomedical systems, heat exchanging devices, electronic cooling systems, food processing, drying processes, crystallization, mixing processes and beyond.

This work provides a novel exploration of CuO-water nanofluid flow in mixed convection within a grooved channel cavity under the influence of an inclined magnetic field. The influence of different heater positions on thermomagnetic convection in such a cavity has not been extensively investigated before, contributing to the originality and value of this research.

The purpose of this study was to review the information on the scientific efforts and achievements in sustainable industrial textile applications of natural colourants. Then the paper suggests the ways of improving the industrial textile applications of plant-based colourants.

The literature on the chemistry, sources and extraction of plant-based natural colourants was reviewed. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested. Lastly, the current situation of industrial application of natural dyes in textiles is presented.

Despite the scientific achievement to overcome the challenges of natural colourants for textiles, the global industrial application of natural colourants is still low. Inadequate knowledge of the dyers results into poor performance of the natural dyed textile. The natural dyed textiles are expensive due to the scarcity of raw materials for manufacturing of natural colourants. The selection of suitable extraction, application methods and type of substrate should consider the chemistry of the particular colourant. The society should be educated about the benefits of natural dyed textiles. Cultivation of colourant-bearing plants should be promoted to meet the industrial material demand.

The paper provides a synthesized collection of information about the source, chemistry, extraction, textile application and challenges of plant-based natural colourants. The reviewed information was analysed and synthesised to provide techniques for selecting sustainable extraction methods, possible sustainable textile applications of natural colourants and the challenges which hinder industrial textile applications of plant-based natural colourants. The ways of overcoming the challenges of the industrial textile applications of plant natural colourants were suggested.

This study aims to systematically review the current academic literature on the role of technologies in low-carbon supply chain management (SCM), identify and analyse critical themes and propose an integrated conceptual model.

A systematic literature review of 48 papers published between 2010 and 2022 was conducted. A conceptual model was advanced.

Based on the analysis and synthesis of the reviewed papers, this review provides an initial attempt to integrate technology adoption and low-carbon SCM by developing a diffusion of innovation model of technology-enabled low-carbon SCM within the technology–organisation–environment (TOE) framework, in which drivers, enablers and barriers to technology adoption practices are identified. The environmental, economic and social outcomes of adoption practices are also identified.

This study provides a novel and comprehensive roadmap for future research on technology-enabled low-carbon SCM. Furthermore, policy, as well as managerial implications, is presented for policymakers and managers.