Solid waste generation in Malaysia is one of the challenging environmental issues which are often neglected by local households. The main purpose of this research is to ascertain the mediating effect of environmental concerns (i.e., egoistic, altruistic, and biospheric concerns) between households’ descriptive norm and injunctive norm to practice the segregation-at-source of solid waste. A total of 400 residents living in townships in nine districts in the state of Selangor were selected via a multi-stage sampling method. A self-administrated bilingual questionnaire was used to collect the research data. As for the mediation test, the present research found that egoistic concern and altruistic con-cern mediated the significant relationship between injunctive norm and intention to practice the seg-regation-at-source of solid waste among the households in Selangor. The present research con-cludes with research implications and provides several avenues for future research in order to create a comprehensive understanding of the segregation-at-source of solid waste policy among Malaysian citizens.

The aim of this research is to investigate the gap or SERVQUAL scale amongst the findings of the previous studies for missing investigations and the impression to apply for overall standard quality management of three variables such as independent variable (Service quality), mediator variable (Patients’ Satisfaction) and dependent variable (Patients’ Loyalty) in Jordanian health care sector. Moreover, the current study aims to clarify the effects of the Total Quality Management (TQM) represented collectively by a specific strategy, leadership management, human resource focus information, client focus, method management, and analysis method management on customer loyalty. In order to test the objectives, a random sample size consisting of 800 national and international patient’s expectations from the private and public hospitals in the central region of Jordan was collected. The quantitative analysis was designed to conduct the survey, questionnaires, and gather the primary information to determine the category of data and techniques of data collection. The response data were analyzed using the IBM SPSS 19.00 version and Amos 20.00 version to assess the response value, descriptive statistic, screenings of the data composed of linearity and homoscedasticity, correlations, reliability, and validity. Multiple reliability results indicated that the dimensions of each experimental variables were considered reliable and satisfactory. Based on the outcome, this study verified that customer satisfaction carries a weak mediating effect. Moreover, the results exhibited that TQM had had a significant impact on both customer loyalty and customer satisfaction.

Most global studies have, to a greater extent, underscored the importance of Total Quality Management (TQM) practices and some marketing aspects concerning the organizational performance. Most studies have focused on establishing the level to which TQM practices influence customer satisfaction and not the whole organization. There is also little evidence on how marketing practices influence organizational performance. This study therefore seeks to assess the impact of TQM practices and marketing on organizational performance. Data was collected from a sample size of 289 respondents who were employees of the different manufacturing industries in Saudi Arabia. Data was analyzed using SPSS and Pearson’s rank correlation coefficient was used to establish the relationship between study variables. The study findings confirmed the presence of a relationship between TQM practices and organizational performance. Similarly, there was a positive relationship between marketing practices and organizational performance. The study concluded that the TQM practices and marketing are great influencers of quality hence should always be applied in organizations.

This study aims to investigate the effect of green value on attitude and sustainable transportation engagement and the mediating role of attitude on the relationship between green value and sustainable transportation engagement. A survey was carried out on students in a public university. A sample of 107 students was obtained for this study. The data was analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings show that green value and attitude had a significant influence on sustainable transportation engagement. In addition, attitude played a mediating role in the relationship between green value and sustainable transportation engagement. The study provides valuable contributions for both theory and practice in the area of eco-campus. Theoretically, the study extends the value-attitude-behavior model in the context of sustainable transportation and adds to the body of literature of eco-campus. This is among the first studies conducted in Malaysia that investigates factors that contribute towards sustainable transportation engagement among students. In terms of managerial significance, the results provide guidance to policymakers to help them plan for strategies to enhance students’ engagement in sustainable transportation in the future.

Idiosyncratic deals have been used by many organizations to achieve desirable employees’ behavior and work-related positive outcomes. Drawing upon the social exchange theory, this study aims at investigating the connections between idiosyncratic deals and work engagement. Besides, this study also scrutinizes the mediating role of psychological empowerment in the relationship between idiosyncratic deals and work engagement. This study applied smart PLS-SEM v.3.2 for the data analysis to ascertain the relationship between the study variables. Using an online survey, data are collected from 310 academicians working in the public higher education institutions of Pakistan. The finding of this study shows a significant positive relationship between idiosyncratic deals and work engagement. Furthermore, finding of the study also divulges that psychological empowerment mediates the relationship between idiosyncratic deals and work engagement. Hence the management and the policy makers in the public higher education institutions should focus on the provision of idiosyncratic deals based on the personal and professional needs of academicians to strengthen their feeling of psychological empowerment which subsequently results in fostering their engagement at work.

The field of strategic innovation (SI) has been garnering increasing research interest, with studies adopting and employing varying definitions and creating different methods for its measurement. Despite the innumerable studies, few have addressed manufacturing and small and medium-sized enterprises (SMEs), particularly those focused on Middle East countries, in light of the relationship between structural capital (SC) and SI. Hence, the present work is primarily aimed at examining the role of SC in SI and the performance of manufacturing SMEs. It employed the survey method to gather data from the study sample of 284 Yemeni manufacturing SMEs and the hypotheses were tested using Partial Least Squares-Structural Equation Modelling (PLS-SEM). On the basis of the results, there is a significant influence of SI on performance; SC also has a moderating role of on this relationship. The present study is expected to contribute to the creation of a measurement system for SI in SMEs, stressing each component of SI in enhancing the performance of such enterprises.

Ratcheting is a second failure mode in low cycle fatigue loading where plastic strain accumulates in each cycle. It is difficult to precisely estimate component deformation due to the complexities of cyclic hardening. In order to study the deformation, all types of hardening rules must be determined priorly. In this study, the determination procedures of combined hardening parameters are presented using Abaqus software. The experiment data of API-5L X80 from the past research have been utilized. Lastly, the different inputs of non-linear kinematic hardening choices are analyzed and presented.

COVID-19 has spread to more than a hundred countries worldwide since the first case reported in late 2019 in Wuhan, China. As one of the countries affected by the spread of COVID-19 cases, the local government of Malaysia has issued several policies to reduce the spread of this outbreak. One of the measures taken by the Malaysian government, namely the Movement Control Order, has been carried out since March 18, 2020. In order to provide precise information to the government so that it can take the appropriate measures, many researchers have attempted to predict and create the model for these cases to identify the number of cases each day and the peak of this pandemic. Therefore, hospitals and health workers can anticipate a surge in COVID-19 patients. In this research, confirmed, recovered, and death cases prediction was performed using the neural network as one of the machine learning methods with high accuracy. The neural network model used is the Multi-Layer Perceptron, Neural Network Auto-Regressive, and Extreme Learning Machine. The three models calculated the average percentage error (APE) values for 7 days and obtained APE values for most cases less than 10%; only 1 case in the last day of one method had an APE value of approximately 11%. Furthermore, based on the best model, then the forecast is made for the next 7 days. In conclusion, this study identified that the MLP model is the best model for 7-step ahead forecasting for confirmed, recovered, and death cases in Malaysia. However, according to the result of testing data, the ELM performs better than the MLP model.

The Combinatorial Optimization Problem (COPs) is one of the branches of applied mathematics and computer sciences, which is accompanied by many problems such as Facility Layout Problem (FLP), Vehicle Routing Problem (VRP), etc. Even though the use of several mathematical formulations is employed for FLP, Quadratic Assignment Problem (QAP) is one of the most commonly used. One of the major problems of Combinatorial NP-hard Optimization Problem is QAP mathematical model. Consequently, many approaches have been introduced to solve this problem, and these approaches are classified as Approximate and Exact methods. With QAP, each facility is allocated to just one location, thereby reducing cost in terms of aggregate distances weighted by flow values. The primary aim of this study is to propose a hybrid approach which combines Discrete Differential Evolution (DDE) algorithm and Tabu Search (TS) algorithm to enhance solutions of QAP model, to reduce the distances between the locations by finding the best distribution of N facilities to N locations, and to implement hybrid approach based on discrete differential evolution (HDDETS) on many instances of QAP from the benchmark. The performance of the proposed approach has been tested on several sets of instances from the data set of QAP and the results obtained have shown the effective performance of the proposed algorithm in improving several solutions of QAP in reasonable time. Afterwards, the proposed approach is compared with other recent methods in the literature review. Based on the computation results, the proposed hybrid approach outperforms the other methods.

The power-law memory effect is taken into consideration in a generalisation of the economic model of natural growth. The memory effect refers to a process's reliance on its current state and its history of previous changes. However, the study that focuses on natural growth in economics considering the memory effect with fractional order-linear differential equation model is still limited. The current investigation seeks to solve the natural growth with memory effect in the economics model and decide the best model using fractional differential equation (FDE), namely Adomian Decomposition and Variational Iteration Methods. Also, this study assumes the level of consumer loss memory during a certain time interval denoted by a parameter (α). This study showed the model of loss memory effect with 0 < α ≤ 1 given a slowdown in output growth compared to a model without memory effect. Besides that, this study also found that output Y(t) is growing faster with the Variational Iteration method compared to the Adomian decomposition method. Also, using graphical simulation, this study found the output Y(t) is closer to the exact solution with α=0.4 and α=0.9. In conclusion, this study successfully solved natural growth with memory effect in economics and decided the best model between FDE, namely Adomian decomposition and Variational iterative methods using numerical analysis.