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The purpose of this study is to numerically model the rigid pavement resting on two-parameter soil and to examine its modal parameters.

This study is carried out using a one-dimensional beam element with three rotational and three translational degrees of freedom based on the finite element method. MATLAB programming is used to perform the free vibration analysis of the rigid pavement.

Cyclic frequency and their corresponding mode shapes were determined. It has been investigated how cyclic frequency changes as a result of variations in the thickness, span length of pavement, shear modulus, modulus of subgrade, different boundary conditions and element discretization. Thickness of the pavement and span length has greater effect on the cyclic frequency. Maximum increase of 29.7% is found on increasing the thickness, whereas the cyclic frequency decreases by 63.49% on increasing span length of pavement.

The pavement's free vibration is the sole subject of the current investigation. This study limits for the preliminary design phase of rigid pavements, where a complete three-dimensional finite element analysis is unnecessary. The current approach can be extended to future research using a different method, such as finite element grilling technique, mesh-free technique on reinforced concrete pavements or jointed concrete pavements.

The finite element approach adopted in this paper involves six degrees of freedom for each node. Furthermore, to the best of the authors’ knowledge, no prior study has done seven separate parametric investigations on the modal analysis of rigid pavement resting on two-parameter soil.

Knowledge is a vital strategic resource for multinational enterprises (MNEs). As MNEs expand internationally, knowledge transfer through expatriates is a crucial part of the value proposition of outward foreign direct investment. However, this is undermined if knowledge is hidden rather than shared. Given the scarcity of research on knowledge hiding in MNEs, this paper aims to investigate this phenomenon among expatriates and develops a new framework to analyze knowledge hiding.

Survey data from 201 Chinese MNE expatriates is collected and analyzed using Partial Least Squares – Structural Equation Modeling to test the relationships between knowledge hiding, organizational practices, cultural intelligence and job embeddedness. Relevant organizational practices based on the ability-motivation-opportunity enhancing framework were identified, based on 24 semi-structured qualitative interviews which guided the quantitative analysis.

The direct effects of organizational practices on all types of knowledge hiding are limited. However, organizational practices’ influence on knowledge hiding is mediated by the cultural intelligence of expatriates, and this relationship is moderated by job embeddedness.

The research advances current thinking about knowledge management and outlines both theoretical and practical implications at organizational and societal levels. It explores the mechanisms for remedying knowledge hiding through organizational practices, including the interactive effects of cultural intelligence and job embeddedness among expatriates. Organizational knowledge management strategies in MNEs need to recognize cultural differences and improve job embeddedness to form the basis of successful knowledge transfer.

The purpose of this paper was to examine the nexus between conditional exchange rate volatility and economic growth in BRICS countries. Further, the dynamic causation between economic growth and exchange rate volatility is also examined.

We employed three techniques, namely, dynamic panel models, static panel models and Dumitrescu and Hurlin (DH) panel causality test to examine the economic growth–conditional exchange rate volatility nexus in BRICS countries.

The overall results showed that conditional exchange rate volatility has a negative and significant effect on economic growth. Interestingly, the results showed that whenever the exchange rate volatility exceeds the 0–1.54 range, the economic growth of BRICS is reduced, on average, by 5%. Further, the results of the causality test reconciled with that of ARDL wherein unidirectional causality from exchange rate volatility, exports, labour force and gross capital formation to economic growth was found.

The urgent recommendation is to develop and align fiscal, monetary, trade and exchange rate policies, either through creating a common currency region or through coordinated measures to offset volatility and trade risks in the long run. Further, to offset the impact of excessive exchange rate changes, BRICS economies can set up currency hedging systems, implement temporary capital controls during periods of extreme volatility or create currency swap agreements with other nations or regions. Last, but not least, investment and labour policies that are coherent and well-coordinated can support market stabilisation, promote investment and increase worker productivity and job prospects.

Researchers hold contrasting views regarding the effect of exchange rate volatility on economic growth. Some researchers claim that exchange rate volatility reduces growth, and several shreds of empirical evidence claim that lower exchange rate volatility is linked with an increase in economic growth, at least in the short run. However, the challenge lies in establishing the optimal range beyond which exchange rate volatility becomes detrimental to economic growth. The present study contributes to this aspect by seeking to identify the optimal spectrum beyond which excessive shifts in exchange rate volatility negatively affect economic growth, or endeavors to define the acceptable spectrum within which these fluctuations actually boost growth. To the best of our knowledge, this study is the first to analyse the given research area. The present study used a dummy variable technique to capture the impact of permissible exchange rate band on the economic growth.

When the reinforced concrete beams are reinforced by bonding steel plates to the bottom, excessive use of steel plates will make the reinforced concrete beams become super-reinforced beams, and there are security risks in the actual use of super-reinforced beams. In order to avoid the occurrence of this situation, the purpose of this paper is to study the calculation method of the maximum number of bonded steel plates to reinforce reinforced concrete beams.

First of all, when establishing the limit failure state of the reinforced member, this paper comprehensively considers the role of the tensile steel bar and steel plate and takes the load effect before reinforcement as the negative contribution of the maximum number of bonded steel plates that can be used for reinforcement. Through the definition of the equivalent tensile strength, equivalent elastic modulus and equivalent yield strain of the tensile steel bar and steel plate, a method to determine the relative limit compression zone height of the reinforced member is obtained. Second, based on the maximum ratio of (reinforcement + steel plate), the relative limit compression zone height and the equivalent tensile strength of the tensile steel bar and steel plate of the reinforced member, the calculation method of the maximum number of bonded steel plates is derived. Then, the static load test of the test beam is carried out and the corresponding numerical model is established, and the reliability of the numerical model is verified by comparison. Finally, the accuracy of the calculation method of the maximum number of bonded steel plates is proved by the numerical model.

The numerical simulation results show that when the steel plate width is 800 mm and the thickness is 1–4 mm, the reinforced concrete beam has a delayed yield platform when it reaches the limit state, and the failure mode conforms to the basic stress characteristics of the balanced-reinforced beam. When the steel plate thickness is 5–8 mm, the sudden failure occurs without obvious warning when the reinforced concrete beam reaches the limit state. The failure mode conforms to the basic mechanical characteristics of the super-reinforced beam failure, and the bending moment of the beam failure depends only on the compressive strength of the concrete. The results of the calculation and analysis show that the maximum number of bonded steel plates for reinforced concrete beams in this experiment is 3,487 mm². When the width of the steel plate is 800 mm, the maximum thickness of the steel plate can be 4.36 mm. That is, when the thickness of the steel plate, the reinforced concrete beam is still the balanced-reinforced beam. When the thickness of the steel plate, the reinforced concrete beam will become a super-reinforced beam after reinforcement. The calculation results are in good agreement with the numerical simulation results, which proves the accuracy of the calculation method.

This paper presents a method for calculating the maximum number of steel plates attached to the bottom of reinforced concrete beams. First, based on the experimental research, the failure mode of reinforced concrete beams with different number of steel plates is simulated by the numerical model, and then the result of the calculation method is compared with the result of the numerical simulation to ensure the accuracy of the calculation method of the maximum number of bonded steel plates. And the study does not require a large number of experimental samples, which has a certain economy. The research result can be used to control the number of steel plates in similar reinforcement designs.

Food waste constitutes a critical global dilemma, presenting substantial environmental, economic and social challenges, with around one-third of all food intended for human use being discarded annually. This waste depletes essential resources, increases greenhouse gas emissions and intensifies food poverty. Comprehending the factors contributing to food waste is crucial for formulating effective methods to alleviate this issue.

The responses have been collected from Indian households using longitudinal techniques. In Study 1, 481 respondents responded to the questions, and in Study 2, finally, 453 respondents responded.

This study examines the relationship between attitudes about food waste, intents to mitigate waste and several influencing factors like price sensitivity, altruistic behavior, awareness of food waste and societal norms.

The study seeks to elucidate consumer behavior by analyzing these relationships and identify practical interventions that can encourage a more sustainable food consumption approach, thereby aiding in the reduction of food waste and the promotion of responsible consumption practices.

Managerial “awareness” of supply chain management (SCM) principles is a key antecedent of SCM adoption. However, supply chain awareness (SCA) provides fertile ground for further development. The authors combine extant research with the attention-based view of the firm to further develop SCA and theorize about its effect in an understudied context.

The authors combine SCA with supply chain orientation, of which awareness is central. The authors combine qualitative and archival data for a 10-year period to test SCA in nonprofits. SCA was measured unobtrusively to avoid respondent bias; then, the authors explore how SCA relates to revenue generation from services provided.

SCA correlates positively with revenue generation. Drawing on a contingency perspective, the authors test two moderators relevant to nonprofits. The positive effect of SCA on revenue is stronger for nonprofits collocated in cities with corporate headquarters but weaker for those with larger boards.

The study further advances the notion of awareness for studying SCM phenomena and provides evidence of its relevance in the unexamined context of human services nonprofit organizations (NPOs). This work has implications for how attention to SCM principles shapes organizational outcomes, the factors that moderate these relationships and the importance of unobtrusively measuring awareness in SCM research. The authors used WayBack Machine to harvest websites. However, the quality and depth of text obtained prior to 2008 were lower than those of later years. Additionally, archival data for NPOs are limited.

Findings inform about the fit between nonprofit resources, type of board and fit with how to fund operations. This research provides an alternative way for policy makers to assess NPO capacity by focusing on the fundamental SCM concepts.

The authors contribute to the dialogue about NPOs developing financial independence through revenue generation from services sold to end customers.

NPOs are seldom studied in SCM. This is an attempt to study NPOs by combining qualitative and quantitative data.

This study is based on the extended theory of planned behavior (TPB) and attempts to shed light on what influences restaurant consumers’ intentions to eat locally sourced meals.

Data from 698 respondents were gathered through a web-based survey employing a quantitative methodology.

The findings indicated that several motivating factors, subjective norms and perceived behavioral control positively influence respondents’ attitudes toward dining at restaurants serving meals that are obtained locally. Also, attitudes significantly predicted intentions and mediated the relationship between the motivating factors and intention to consume local meals. Furthermore, subjective norms and perceived behavioral control moderated the relationship between attitude and intention.

The study offers implications for both theory and practice. In the context of Egypt in particular, this study advocates for sustainable food production and consumption in restaurants. The study focused only on consumers; it suggests that subsequent research should examine the restaurant operators’ perspective.

To draw in and please more locavores, restaurant management can use buzzwords like “safe food,” “fresh food” and “environmental labels.” They should also provide their consumers with the backstory of menu items, including where food comes from, how it’s made and how it gets transported.

This study tests an adapted model built on TPB and advocates for sustainable production and consumption in line with the United Nations 2030 Agenda for Sustainable Development Goals.

Sustainable building materials (SBMs) have recently been promoted to foster sustainable construction. While previous studies successfully presented the broad picture of SBM adoption, the question ‘What is the current state of SBM adoption in construction firms?’ was unanswered. Moreover, there is a lack of studies that investigate the impact of firm size on the adoption of SBMs. Therefore, this study aims to examine the level of readiness for SBM adoption in construction firms of different sizes.

Drawing on theoretical lenses and a review of previous studies, the study identified 20 factors affecting the readiness for SBM adoption. These factors were then grouped into market, organization, and employee readiness. Using the questionnaire survey, 229 valid responses were collected. The multiple pairwise comparison test showed significant differences in readiness for SBM adoption in firms of different sizes. The Fuzzy Synthetic Evaluation (FSE) analysis was then used to assess the level of readiness for SBM adoption in construction firms of different sizes.

The analysis of FSE showed that large-sized companies demonstrated the highest level of readiness for SBM adoption, followed by medium-sized and small-sized firms, respectively. These findings imply that larger construction firms may have more resources and organizational capacity to adopt SBMs. Conversely, smaller firms may require additional support or incentives to enhance their readiness for SBM adoption. It also highlights the need for targeted interventions and policies to promote SBM adoption across medium-sized and small-sized firms. Moreover, while market readiness emerged as the least critical category, the findings highlight the pivotal role of employee readiness across all firm sizes.

These findings underscore the importance of prioritizing employee readiness initiatives to facilitate the successful adoption of SBMs. Policymakers and industry stakeholders may need to focus on developing training programs and awareness campaigns tailored to employees, ensuring they are equipped with the necessary knowledge and skills. Moreover, strategies to enhance market readiness should also be explored through regulatory measures and incentives to encourage the adoption of SBMs. Additionally, fostering collaboration and networking among stakeholders can further promote market readiness and accelerate the uptake of SBMs in the construction industry.

The purpose of this study is to explore the influence of the regulatory environment on the efficiency of transparency within Islamic finance practices. It specifically examines how the determination of Shariah compliance, corporate governance and auditing standards is shaped by regulatory frameworks and their effects on the level of transparent financial reporting.

The research path was defined, and the research hypotheses were evaluated in the model using partial least squares structural equation modeling. The study collected data through structured surveys from 203 respondents.

The results of the PLS analysis demonstrate that Shari’ah compliance practices enhance transparency by making it difficult to breach ethical or social norms. These practices also infuse the presence of good corporate practices and quality audits that promote a culture of financial accountability, which is key for market and stakeholder confidence. The regulatory environment adds a critical moderating influence in these relationships by providing the oversight and enforcement capability required to ensure uniformity in the application of Shari’ah adherence and set transparency standards across borders.

The findings of this study have practical implications for those who implement policies, develop regulatory structures and study Islamic finance, underscoring the importance of achieving robust governance and regulatory frameworks. However, the study admits weaknesses, such as limited geographical coverage, reliance on preexisting data and the use of a cross-sectional analysis. Future research directions should include longitudinal and cross-comparative designs, the effects of modern technologies and the integration of qualitative methods alongside quantitative ones.

Technology-enabled healthcare focuses on providing better information flow and coordination in healthcare operations. Technology-enabled health services enable hospitals to manage their resources effectively, maintain continuous patient engagement and provide seamless services without compromising their perceived quality.

This study investigates the role of technology-enabled health services in improving perceived healthcare quality among patients. Data are collected from the users (n = 418) of health platforms offered in multi-specialty hospitals. Multiple learners are employed to accurately represent the users' perceived quality regarding the perceived usefulness of the features provided via these digital health platforms.

The best-fitted model using a decision tree classifier (accuracy = 0.86) derives the accurate significance of features offered in the digital health platform in fostering perceived healthcare quality. Diet and lifestyle recommendations (30%) and chatting with health professionals (11%) are the top features offered in digital health platforms that primarily influence the perceived quality of healthcare among users.

The predictability of perceived quality with the individual features existing in the digital health platform, the significance of the features on the perceived healthcare quality and the prediction rules showing the combined effect of features on healthcare quality can help healthcare managers accelerate digital transformation in hospitals by improving their digital health platform, designing and offering new health packages while strengthening their e-infrastructure.

The study represents perceived healthcare quality with the features offered in digital health platforms using machine learners based on users' post-pandemic experience. By advancing digital platforms with more patient-centric features using emerging technologies, this model can further foresee its impact on the perceived quality of healthcare, offering valuable directions to healthcare service providers. The study is limited to focusing on digital health platforms that can deal with people's general healthcare needs.