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Previous mental health studies have shown higher levels of anxiety, stress, and depression symptoms among university music students. In general, some similar findings have been observed for Malaysian music university students. In diagnosing the complications of mental health, there is consensus that it is essential to develop and evaluate a model oriented toward mental health illness prevention and treatment. To date, a suitable pattern for estimating mental health in terms of anxiety, stress, and depression among music university students is lacking. To fill this gap, we collected the necessary data from 691 music and 871 general students who were students for one year. The introduced pattern includes socioeconomic status, fear of COVID-19, nomophobia, sleep quality, loneliness, and mental health. Our data analysis proved that the levels of anxiety, depression, and stress of music students were lower than those of general students. Unlike some previous studies, in this study, the fear of COVID-19 and nomophobia didn’t have the most significant impact on mental health. The most significant impacts were related to sleep quality and loneliness. These findings have the potential to inform health promotion and services in the music education system.

Bayesian Structural Equation Modeling (SEM-Bayesian) was applied across different research areas to model the correlation between manifest and latent variables. The primary purpose of this study is to introduce a new framework of complexity to adolescent obesity modeling based on adolescent lifestyle through the application of SEM-Bayesian. The introduced model was designed based on the relationships among several factors: household socioeconomic status, healthy food intake, unhealthy food intake, lifestyle, body mass index (BMI) and body fat. One of the main contributions of this study is from considering both BMI and body fat as dependent variables. To demonstrate the reliability of the model, especially in terms of its fitting and accuracy, real-time data were extracted and analyzed across 881 adolescents from secondary schools in Tehran, Iran. The output of this study may be helpful for researchers who are interested in adolescent obesity modeling based on the lifestyle and household socioeconomic status of adolescents.

The emergency transition from physical to online learning during COVID-19 has affected university students in various aspects, especially their academic performance. It can be caused by many factors, such as individual, environmental and social factors. Therefore, this study aims to determine the impact of fear, stress, well-being, teacher and parents’ support (independent variables) on undergraduates’ academic performance (dependent variable) during the COVID-19 pandemic. A structured online questionnaire has been developed and administered to 400 undergraduates. A structural equation model that integrated all variables under investigation was built and statistically validated using AMOS. The results demonstrated that well-being, teacher emotional support and teacher academic support have the highest significant impact on the respondents’ academic performance. It can be concluded that teachers’ support is the most substantial influence in ensuring student learning sustainability during the COVID-19 pandemic.

Background Since the last decade, postpartum depression (PPD) has been recognized as a significant public health problem, and several factors have been linked to PPD. Mothers at risk are rarely undetected and underdiagnosed. Our study aims to determine the factors leading to symptoms of depression using Structural Equation Modeling (SEM) analysis. In this research, we introduced a new framework for postpartum depression modeling for women. Methods We structured the model of this research to take into consideration the Malaysian culture in particular. A total of 387 postpartum women have completed the questionnaire. The symptoms of postpartum depression were examined using the Edinburgh Postnatal Depression Scale (EPDS), and they act as a dependent variable in this research model. Results Four hundred fifty mothers were invited to participate in this research. 86% of the total distributed questionnaire received feedback. The majority of 79.6% of respondents were having depression symptoms. The highest coefficients of factor loading analysis obtained in every latent variable indicator were income (β = 0.77), screen time (β = 0.83), chips (β = 0.85), and anxiety (β = 0.88). Lifestyle, unhealthy food, and BMI variables were directly affected by the dependent variable. Based on the output, respondents with a high level of depression symptoms tended to consume more unhealthy food and had a high level of body mass indexes (BMI). The highest significant impact on depression level among postpartum women was unhealthy food consumption. Based on our model, the findings indicated that 76% of the variances stemmed from a variety of factors: socio-demographics, lifestyle, healthy food, unhealthy food, and BMI. The strength of the exogenous and endogenous variables in this research framework is strong. Conclusion The prevalence of postpartum women with depression symptoms in this study is considerably high. It is, therefore, imperative that postpartum women seek medical help to prevent postpartum depressive symptoms from worsening.

As postpartum obesity is becoming a global public health challenge, there is a need to apply postpartum obesity modeling to determine the indicators of postpartum obesity using an appropriate statistical technique. This research comprised two phases, namely: i) development of a previously created postpartum obesity modeling, ii) construction of a statistical comparison model and introduction of a better estimator for the research framework. The research model displayed the associations and interactions between the variables that were analyzed using the Structural Equation Modeling (SEM) method to determine the body mass index (BMI) levels related to postpartum obesity. The most significant correlations obtained were between BMI and other substantial variables in the SEM analysis. The research framework included two categories of data related to postpartum women: living in urban and rural areas in Iran. The SEM output with the Bayesian estimator was 81.1%, with variations in the postpartum women&rsquo, s BMI, which is related to their demographics, lifestyle, food intake, and mental health. Meanwhile, the variation based on SEM with partial least squares estimator was equal to 70.2%, and SEM with a maximum likelihood estimator was equal to 76.8%. On the other hand, the output of the root mean square error (RMSE), mean absolute error (MSE) and mean absolute percentage error (MPE) for the Bayesian estimator is lower than the maximum likelihood and partial least square estimators. Thus, the predicted values of the SEM with Bayesian estimator are closer to the observed value compared to maximum likelihood and partial least square. In conclusion, the higher values of R-square and lower values of MPE, RMSE, and MSE will produce better goodness of fit for SEM with Bayesian estimators.

This study proposes a group of indicators in the analysis of port performance. This paper presents a new model of analysis to evaluate how the port cargo openness, the productivity level, the cargo expansion, and the technological change adaptability can affect directly on the marginal productivity growth rate and performance of a port. This new model, The Ports Efficiency Performance Model (PEP-Model) is intended to offer policy makers and researchers an additional analytical tool to study the impact of dynamic changes such as change in international trade trends and the impact of technology or competition on port performance from a new perspective.

In obesity modelling studies, researchers have been seeking to identify the effective indicators of obesity by using appropriate statistical or mathematical techniques. The main objective of the present study is addressed in three stages. First, a new framework for modelling obesity in university students is introduced. The second stage involves data analysis based on Bayesian Structural Equation Modelling (BSEM) for estimating the Body Mass Index (BMI) (representative of the obesity level) of students at three university levels: Bachelor, Master and PhD. In the third stage, the highest significant correlation is determined between the BMI and other variables in the research model that were found significant through the second phase. The data for this study were collected from students at selected Malaysian universities. The results indicate that unhealthy food intake (fast food and soft drinks), social media use and stress exhibit the highest weightage contributing to overweight and obesity issues for Malaysian university students.

Background: Pregnancy has become the main constituent for women to become overweight or obese during the postpartum phase. This could lead women to suffer from postpartum depression as well. Information technology (IT) has become more prevalent in the healthcare industry. It offers patients the opportunity to manage their health conditions via the use of several applications, one being the mHealth applications. Objective: The main purpose of this study is to experiment and understand the effects the mHealth applications (i.e., fitness and nutrition applications) have on the body mass index (BMI) and depression levels amongst postpartum women. Methods: Online questionnaires were sent to postpartum women within one year after their pregnancy, of which 819 completed questionnaires were returned. The frequency of the mHealth applications usage was categorized into daily, weekly, rarely and never streams. Therefore, the frequency of use of the mHealth applications for BMI and depression levels was analyzed based on the available statistical data. Descriptive statistics, ANOVA, and Dunnet tests were applied to analyze the experimental data. Results: Out of 819 respondents, 37.9% and 42.1% of them were overweight and obese, respectively. Almost 32.9% of the respondents were likely depressed, and 45.6% were at an increased risk. This study reports that only 23.4% and 28.6% of respondents never used the fitness and nutrition applications. The impact of the frequency of using the fitness applications on BMI and depression levels was obvious. This means that with the increased use of the fitness applications, there was also a significant effect in maintaining and decreasing the BMI and depression levels amongst Malaysians postpartum women. However, from the data of weekly and daily use of fitness applications, we found that the contribution toward the BMI and depression levels was high (p = 0.000). However, nutrition applications amongst the users were not significant within the main variables (p &gt, 0.05). From the Dunnet test, the significance of using the fitness applications within the depression levels started from daily usage, whereas for BMI, it started from weekly usage. Conclusion: The efficiency of the fitness applications toward the BMI and depression levels has been proven in this research work. While nutrition applications did not affect the BMI and depression levels, some of the respondents were still categorized as weekly and daily users. Thus, the improvements in BMI and depression levels are associated with the types of mHealth app that had been used.

The main objective of this paper is to bring a model for firm sustainability performance index by applying both classical and Bayesian structural equation modeling (parametric and semi-parametric modeling). Both techniques are considered to the research data collected based on a survey directed to the China, Taiwan, and Malaysia food manufacturing industry. For estimating firm sustainability performance index we consider three main indicators include knowledge management, organizational learning, and business strategy. Based on the both Bayesian and classical methodology, we confirmed that knowledge management and business strategy have significant impact on firm sustainability performance index.

Structural Equation Modeling (SEM) has been used extensively in sustainability studies to model relationships among latent and manifest variables. This paper provides a tutorial exposition of the SEM approach in food security studies and introduces a basic framework based on family food security and children’s environment sustainability. This framework includes family food security and three main concepts representing children’s environment, including children’s BMI, health, and school performance. A detailed description is provided of how SEM is applied in this type of study. The proposed model contains dependent, independent, mediator, and moderator variables. Three latent variables categorized include family food security, children’s health, and children’s school performance, and two manifest variables are children’s body mass index and children’s gender. The samples for this study involve 452 Chinese children aged 7–12. The data analysis outcome indicates that the introduced model is capable of estimating the impact of family food security on children’s environment. The results from this study confirm that the combination of children’s body mass index with children’s health acts as a strong mediator in the relationship between family food security and children’s school performance.

Structural equation modelling (SEM) is an estimation method that can handle a large number of exogenous and endogenous factors as well as unobserved (latent) variables that are specified as linear combinations of observed (measurement) factors. This paper presents a SEM procedure with latent variables for estimating the financial and non-financial performance in airline companies. The model includes independent, mediator and dependent latent variables. The sample for this research comprises 214 airline companies. The results indicate that the model is capable of estimating performance with respect to the economic situation and it has also been determined that two types of constructs affect performance. One type is the economic situation acting as an initial construct and the other is the internal operation acting as the mediator in the research model.

Building materials have become increasingly diverse and flexible regarding their shapes, colours and texture. These include the use of highly reflective materials for facade (e.g. glass or metal claddings) which becomes a popular concept for high-rise buildings. However, these reflective materials contribute to an increasing number of feedbacks on discomfort associated with reflected glare at the pedestrian’s level and the surrounding environment. This study aims to evaluate the impact of reflected glare from the reflective building facade on pedestrians’ visual comfort in Kuala Lumpur city area. The relationship between pedestrians and reflected glare issues is determined by applying Structural Equation Modelling (SEM) between male and female. Total of 500 questionnaires is distributed at four different locations. The six-modelled fitting test was tested and within an acceptable range. For both male and female models shows that age significantly affects sensitiveness toward reflected glare.

The main objective of this study is to apply moderation analysis in structural equation modeling (SEM) to compare management information system (MIS) and enterprise resource planning (ERP). This comparison study is implemented in the relationship among, organizational learning, innovation, and performance. 168 companies in food production factories were selected from Malaysia, China, and Taiwan. The results show that even the implementation cost between MIS and ERP is quite different, but there is no significant difference between two systems in their innovation models.

The current study mainly aimed at validating the model of End User Computing Satisfaction (EUCS) in Enterprise Resource Planning (ERP) system in food production companies. In the EUCS model a Logit model on the seven items was applied. The tool used for the study was a questionnaire. A total of 126 questionnaires were collected from the ones given to ERP end users from food manufacturing in Malaysia, Taiwan, and China.

The purpose of this research article is to give a conceptual model of innovation management in food production industry in east of Asia. The researchers create and propose a conceptual model rooted in past research on innovation management, performance and organization culture (OC). The data for the research were obtained by surveys given to 168 Chinese, Taiwanese and Malaysian companies. Structural equation modeling (SEM) methodology was used in this study. The results of the study show that in food production firms OC and organizational innovation (OI) have positively direct impacts on organizational performance (OP). These results have useful implications for the companies specially those involved in food production which tries to win competitions and also positively respond to the environmental changes through successful applications of innovation. Findings also stress that systems used and applied to stimulate and boost an organizational innovative culture would most probably make the processes of introducing, adopting, and diffusing innovation simpler which would by itself read to higher OP.

Learning is an intentional activity, with several factors affecting students’ intention to use new learning technology. Researchers have investigated technology acceptance in different contexts by developing various theories/models and testing them by a number of means. Although most theories/models developed have been examined through regression or structural equation modeling, Bayesian analysis offers more accurate data analysis results. To address this gap, the unified theory of acceptance and technology use in the context of e-learning via Facebook are re-examined in this study using Bayesian analysis. The data (S1 Data) were collected from 170 students enrolled in a business statistics course at University of Malaya, Malaysia, and tested with the maximum likelihood and Bayesian approaches. The difference between the two methods’ results indicates that performance expectancy and hedonic motivation are the strongest factors influencing the intention to use e-learning via Facebook. The Bayesian estimation model exhibited better data fit than the maximum likelihood estimator model. The results of the Bayesian and maximum likelihood estimator approaches are compared and the reasons for the result discrepancy are deliberated.

This paper is about to examine the relationship of organisational learning (OL) with knowledge management (KM) and their effect on organisational performance (OP) in food industries. The conceptual framework proposed in this research is a creative model that contributes to relevant theories of KM, OL, and OP literature. 168 companies in food industry were selected in China, Taiwan, Malaysia, and structural equation modelling (SEM) is applied to test the hypotheses in our research model. The research model includes three constructs including KM, OL and OP, and three measurement variables include firm age, size, and type. The results show that KM and OL have positive effect on OL and OL is a mediator in the relationship between KM and OP. Moreover, firm age, size, and type are moderators in the relationship among three constructs in the research model.

The main objective of this paper is to find out the impact of organizational learning (OL) and organizational innovation (OI) on organizational performance (OP) in Asia manufacturing food industries. This study explores those linkages using structural equation modelling (SEM) with data from 172 companies in food manufacturing companies was selected from Taiwan, China, and Malaysia. The research model includes three latent variables including OL, OI, and OP. The results showed that OL and OI have positive effect on OP.

The main purpose of this study to find out the relationship among transformational leadership (TL), organizational learning (OL), and organizational innovation (OI) in manufacturing food industry in east of Asia countries include China, Taiwan, and Malaysia. Structural equation modeling (SEM) was used to test the research hypotheses from168 manufacturing food companies. Our research model contains three constructs, and the results showed there is positive impact between constructs. Also, Organizational learning is a mediator in the linkage between transformational leadership and organizational innovation.

There are many factors which could influence the sustainability of airlines. The main purpose of this study is to introduce a framework for a financial sustainability index and model it based on structural equation modeling (SEM) with maximum likelihood and Bayesian predictors. The introduced framework includes economic performance, operational performance, cost performance, and financial performance. Based on both Bayesian SEM (Bayesian-SEM) and Classical SEM (Classical-SEM), it was found that economic performance with both operational performance and cost performance are significantly related to the financial performance index. The four mathematical indices employed are root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error to compare the efficiency of Bayesian-SEM and Classical-SEM in predicting the airline financial performance. The outputs confirmed that the framework with Bayesian prediction delivered a good fit with the data, although the framework predicted with a Classical-SEM approach did not prepare a well-fitting model. The reasons for this discrepancy between Classical and Bayesian predictions, as well as the potential advantages and caveats with the application of Bayesian approach in airline sustainability studies, are debated.

The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child’s food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM) concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China) were considered. The framework includes two categories of data comprising the normal body mass index (BMI) range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment.

Sustainability has gained as much importance as management in business. Sustainable pavement development as a business practice should involve making evaluations according to the triple bottom line in the pavement life-cycle. Despite the current approaches to evaluating the social as well as economic and environmental feasibility of pavement projects (involving highway and airport infrastructure), there has recently been a lack of consensus on a methodology to guarantee sustainability upon assessment and analysis during the pavement life-cycle. As sustainability is a complex issue, this study intends to further explore sustainability and elaborate on its meaning. The second step involves a general depiction of the major sustainability appraisal tools, namely cost-benefit analysis, life-cycle cost analysis, life-cycle assessment, multi-criteria decision-making, environmental impact assessment and social life-cycle assessment, and an explanation of their cons and pros. Subsequently, the article addresses the application of an organized methodology to highlight the main factors or concepts that should be applied in sustainable pavement development and, more specifically, in sustainable pavement management. In the final step, research recommendations toward sustainability are given. This study is aimed to assist decision-makers in pavement management to plan sustainability frameworks in accordance with probable boundaries and restrictions.

This paper focuses on the application of mathematical theories in the study of information system (IS) success factors. The main objective is to apply Delone and McLean’s IS success model for radio-frequency identification (RFID) sustainability in Malaysian university libraries. Two approaches are applied to estimate user satisfaction, such as the Bayesian and maximum likelihood estimation approaches. In order to identify the best approach, four mathematical indices are used, namely root mean squared error, absolute error, mean absolute percentage error, and the coefficient of determination. The results reveal that Bayesian estimation provides good fit to the data, unlike the model with the maximum likelihood estimator. This study addresses the causes for this difference between the two approaches, as well as the potential merits and shortcomings of the maximum likelihood approach. The current study presents a novel and practical modeling and prediction concept for researchers and experts in the field of computer science.

Through public health studies, specifically on child obesity modeling, research scholars have been attempting to identify the factors affecting obesity using suitable statistical techniques. In recent years, regression, structural equation modeling (SEM) and partial least squares (PLS) regression have been the most widely employed statistical modeling techniques in public health studies. The main objective of this study to apply the Taguchi method to introduce a new pattern rather than a model for analyzing the body mass index (BMI) of children as a representative of childhood obesity levels mainly related to social media use. The data analysis includes two main parts. The first part entails selecting significant indicators for the proposed framework by applying SEM for primary and high school students separately. The second part introduces the Taguchi method as a realistic and reliable approach to exploring which combination of significant variables leads to high obesity levels in children. AMOS software (IBM, Armonk, NY, USA) was applied in the first part of data analysis and MINITAB software (Minitab Inc., State College, PA, USA) was utilized for the Taguchi experimental analysis (second data analysis part). This study will help research scholars view the data and a pattern rather than a model, as a combination of different factor levels for target factor optimization.

With the rapid growth and use of modern architecture practices for high-rise buildings, highly reflective materials have been adopted extensively for aesthetical reasons. However, outdoor glare from highly reflective facades might cause thermal and visual problems towards the occupants of neighbouring buildings and outdoor dwellers, particularly pedestrians. In tropical countries, this negative impact can be greater due to the higher solar radiation received throughout the year. At the present, there are few building guidelines limiting outdoor glare, or daylight reflectance from a building facade. This study aims to introduce a framework for outdoor glare studies that focus on perceived glare from highly reflective facades by pedestrians in Singapore. The introduced framework includes age, glare time, glare duration, avoidance and sensitiveness. For this study, the survey is carried out with the application of Structural Equation Modelling (SEM). This paper is helpful for planners, designers, and engineers to estimate the sensitivity of pedestrians' discomfort glare and towards the creation of sustainable architecture in Singapore.

The main purpose of this research is to illustrate that school size a moderator can effect on the relationship among principal’s leadership style (PLS), principal's decision making style (PDMS), and teacher job satisfaction (TJS). Moreover, in this article, some hypotheses have been proposed to verify the existing relations among TJS, PLS, and PDMS. Based on samples randomly chosen from primary, secondary and high schools in Chinese educational systems in China, the required data are gathered through a mail survey, and the proposed hypotheses are tested via moderation analysis and structural equation modeling.

Two of the essential IT investment options that managers resort are supply chain management and enterprise resource planning. These options are known in the relevant literature as factors contributing to the enhancement of organizational performance. The objective of this study is to investigate the enterprise resource planning adoption and its influence on organizational performance through supply chain management. This article suggests a new model which applies enterprise resource planning with supply chain management to optimal organizational performance. Structural equation model was utilized to test the model fitting level and the four proposed hypotheses. The required data for this research was collected from 174 companies in Malaysia through prepared surveys. The results support, through empirical evidences, the existence of positive effects of enterprise resource planning on the supply chain which ultimately results in improved overall performance of the studied organizations.

This paper focuses on the application of latent variables in assessing airline performance. There is a gap in literature of airline performance modelling. This paper, based on latent variable model attempts to introduce a new framework for airline assessment modelling. In this regard, organisational assessment was used as theoretical framework. Four constructs and thirteen measurements are illustrated for airline assessment model.

This paper offers an integrated investigation of the interrelations among economic performance, organizationalcapacity, and organizational capability in airline industry. Airline capacity and capability are measured based onorganizational capacity & capability theories and examined this relationship with structural equationmodelingfrom209 airline companies annual report data. The research findings demonstrate the significant andintertwined roles of economic performance in enhancing the airline capacity and capability.

Several factors may influence children’s lifestyle. The main purpose of this study is to introduce a children’s lifestyle index framework and model it based on structural equation modeling (SEM) with Maximum likelihood (ML) and Bayesian predictors. This framework includes parental socioeconomic status, household food security, parental lifestyle, and children’s lifestyle. The sample for this study involves 452 volunteer Chinese families with children 7–12 years old. The experimental results are compared in terms of root mean square error, coefficient of determination, mean absolute error, and mean absolute percentage error metrics. An analysis of the proposed causal model suggests there are multiple significant interconnections among the variables of interest. According to both Bayesian and ML techniques, the proposed framework illustrates that parental socioeconomic status and parental lifestyle strongly impact children’s lifestyle. The impact of household food security on children’s lifestyle is rejected. However, there is a strong relationship between household food security and both parental socioeconomic status and parental lifestyle. Moreover, the outputs illustrate that the Bayesian prediction model has a good fit with the data, unlike the ML approach. The reasons for this discrepancy between ML and Bayesian prediction are debated and potential advantages and caveats with the application of the Bayesian approach in future studies are discussed.

The purpose of this approach is to establish the twin impacts of organizational innovation (OI) with organizational learning (OL) in the relation between knowledge management (KM) and organizational performance (OP). 168 companies of manufacturing Food Company were chosen from Malaysia, Taiwan, China and path analysis is used to analyse the underlying hypotheses. The research framework under study contain four latent variables (OP; OL; KM; OI) and three observed indicators (firm type; firm size; firm age). Structural equation modelling include mediation and moderation analysis were used in this study. The obtained results support the literature regarding the relationship among these four constructs and prove that the combination of OI and OL is mediator in the linkage between KM and firm performance. Moreover, firm age, size and type are acting as moderators among the research latent variables. The introduced model can be consider as a basic framework for technology management modelling studies. Limitation and implications for future studies are discussed.

Highlights • We apply structural equation modelling and moderation analysis to estimate airline performance. • We define three main constructs; economic situation, internal operation, and performance. • The results show that firm age is a moderator in the relationship among the three constructs., The ways in which airline performance depends on the economic situation and internal operation are well established in the literature. One of the contextual factors that may change the nature of these relationships is firm age. As such, the aim of this study is to investigate the moderating influence of firm age on airline performance outcomes. Thirty airline companies from the Asia Pacific region were selected, and relevant data from 2006 to 2011 were collected. It can be deduced that company experience or firm age can help in taking control of the relationship between the constructs; thus, this measurement acts as a moderator in the research model.

Nowadays, many companies are using Enterprise Resource Planning (ERP) as one of the comprehensive integrated systems. This study focuses on various aspects of the ERP utilized in Small and Medium Enterprises (SMEs) in Malaysia in three phases. The success and the failure factors of ERP in SMEs were identified in the first phase. A comparison between different ERP training methods was carried out in the second phase. Based on the findings in the first two phases, a new training method was developed in the third phase, so that ERP users may have a more effective ERP training system in the SMEs in Malaysia. The research method applied to the current research is case study in which the required data was collected from different SMEs in Malaysia. The data collection was mainly based on the surveys and interviews, and the results of the data analysis were used to improve a client-based training system. The achieved results indicate that the application of this kind of system which is based on a combination of On-the-job training and Computer-based training system would considerably reduce the time and money spent on learning and training plans, while, at the same time, it would increase the user’s proficiency and knowledge concerning in the ERP system.