Morteza Nagahi - Academia.edu (original) (raw)

Papers by Morteza Nagahi

Systems, 2021

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2021

Although the application of systems thinking (ST) has become essential for practitioners when dea... more Although the application of systems thinking (ST) has
become essential for practitioners when dealing with turbulent and
complex environments, there are limited studies available in the
current literature that investigate how the ST skills of practitioners
vary with regard to demographic factors and personality types
(PTs). To address this gap, this article uses a structural equation
modeling approach to explore the relationship between practitioners’ST skills, PT, and a set of demographic factors. The demographic
factors included in the study are education level, the field of the
highest degree, organizational ownership structure, job experience,
and current occupation type. A total of 99 engineering managers, 104
systems engineers (SEs), and 55 practitioners with other occupations participated in this article. Results showed that the education
level, the field of the highest degree, PT, organizational ownership
structure, and current job experience of practitioners influenced
their level of ST skills. Additionally, the current occupation type of
practitioners partially affects their level of ST skills. An in-depth
analysis was also conducted using multiple group analysis to show
how seven ST skills of the practitioners vary across their level of
education. Taken together, the findings of the study suggest that
PT and a set of demographic factors—the education level, the field
of the highest degree, organizational ownership structure, current
job experience, and current occupation type—influence the overall
ST skill of the practitioners.

The academic performance of engineering students continues to receive attention in the literature... more The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.

Quality defects are a significant source of the costs and challenges of project management in the... more Quality defects are a significant source of the costs and challenges of project management in the construction industry. Due to the project delivery nature of on-site construction, they occur inevitably and are the primary causes of project schedule and cost overruns. A construction product manufacturer determined customer satisfaction warranty-based feedback can be a solution to mitigate the defects in the sense that it can help to identify the root causes of defects more systematically. The motivation of this study is to analyze and improve a quality control program for a major construction system manufacturer based on customer satisfaction warranty-based feedback. Customer satisfaction feedback was obtained on a 10-point Likert scale and analyzed. Statistical process control techniques were applied to check for root causes of defects. Analysis of contractor experience within the data set supports the principle of Best Value Procurement Information Systems (BV PIS), which emphasizes contractor performance and experience to manage project risks. The case study finding provides support that the warranty-based quality control system can enhance project efficiency. The study concludes with a description of the main findings, which can be efficient and effective when implemented in the construction industry.

This research paper presents the approach of machine learning analysis techniques on education. F... more This research paper presents the approach of machine learning analysis techniques on education. For the large dataset, data mining techniques are used to extract hidden information and create insight. We hypothesized that the prediction algorithm and dimensional reduction algorithm could be used on an educational dataset to extract the hidden information and analyze the information to create insight. Machine learning algorithms can be used to predict student academic performance. Since some of the features in our dataset are correlated so, before applying the prediction algorithm, we applied the dimensional reduction algorithm to reduce the dimension of our dataset and extract the important features. For the prediction analysis, we used three supervised machine learning algorithms, namely K-Nearest Neighbors (KNN), Decision Tree, and Logistic Regression. Before we applied these machine learning algorithms, we applied the dimension reduction algorithm for the feature extraction purpose using two algorithms, namely Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). We compared the performance of these machine learning algorithms. For the student academic performance, their final Examination result was taken as the target value, which was predicted by using the above-mentioned supervised algorithm. Our work shows that the dimensional reduction algorithm, followed by the prediction algorithm, achieved the acceptable prediction accuracy for determining student academic performance. Our result also highlights the advantage of employing machine learning techniques on educational data and explains how it helps to provide engineering education insight for the sustainable development of Engineering education as a whole.

Academic performance of engineering students continues to receive attention in the literature. Ho... more Academic performance of engineering students continues to receive attention in the literature. However, the literature lacks studies that investigate the simultaneous relationship between students' systems thinking (ST) skills, and Five-Factor Model (FFM) personality traits and proactive personality scale, and their potential impact on academic performance across gender. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, were administrated for data collection. A web-based cross-sectional survey using Qualtrics was developed to gather data from engineering students. To show the prediction power of the ST skills, FFM traits, and proactive personality on the academic performance of engineering students, Multiple Group Structural Analysis was applied. The study findings show how key skills and characteristics impact engineering students' academic performance and also how gender moderates these relationships. This study can provide important implications and contributions to engineering education and complex systems bodies of knowledge. First, the study will provide a better understanding of engineering students' academic performance across gender. This intent is to help educators, teachers, mentors, college authorities, and other involved parties to understand students' individual differences for a better training and guidance environment. Second, a closer look at the level of systemic thinking and its connection with FFM traits and proactive personality would assist in understanding engineering students' skillset better in the domain of complex systems.

Determinants of students' systems thinking continue to receive attention in the literature. Howev... more Determinants of students' systems thinking continue to receive attention in the literature. However, there is a lack of studies that assess students' systems thinking (ST) skills, along with their proactive personality in the aspect of academic performance. The relationship between ST and proactive personality is somewhat complex, although a high level of the overview might have been provided, the in-depth analysis has not been adequately investigated in the literature. The aim of the research paper is (1) to examine the ST skills and proactive personality of engineering students and (2) to find the relationship between students' proactive personality and the level of ST skills. This research paper would provide important implications and contributions to the body of knowledge of engineering education. First, the research will provide a better understanding of students' thinking and personality. This intent is to help educators, teachers, mentors, college authorities, and others involved parties to understand students' individual differences for a better training and guidance environment. Second, a closer look will be provided to better understand the relationship between the level of systemic thinking and the proactive personality of engineering students and how they influence each other in the complex system problem domain.

Journal of Functional Morphology and Kinesiology, 2020

In this research paper, we implemented a mixed factor design in order to investigate the effect o... more In this research paper, we implemented a mixed factor design in order to investigate the effect of four anthropometries: height, weight, lower-arm dimensions, and upper-arm dimensions on the muscle activation level of participants when interacting with three types of moderators: experiment expertise, task type, and muscle type. The research paper focused on two levels of expertise (novice and expert), two tasks (deck-building and picket installation), and four arm muscles (Brachioradialis (BR), Extensor Carpi Ulnaris (ECU), Flexor Carpi Radialis (FCR), and Flexor Carpi Ulnaris (FCU)), which resulted in 16 (2×2×4) groups. For each of the 16 groups, the data were analyzed in order to investigate the relationship between the four anthropometries and the four muscle activation levels of the participants. Amos software (IBM, Armonk, NY, USA), along with multiple group structural equation modeling, was used to test a total of 16 direct relationships, as well as the moderation effects in the designed experiment. The results show that the participants' expertise can moderate the relationship between their height and muscle activation levels, the relationship between their weight and muscle activation levels, and the relationship between their lower arm dimensions and muscle activation levels. Moreover, the findings of this research paper demonstrate that the relationship between the lower arm dimensions and muscle activation levels, and the relationship between weight and muscle activation levels are moderated by the type of muscle used by the participants (i.e., BR, ECU, FCR, and FCU).

Systems Research and Behavioral Science, 2020

The current body of literature lacks studies related to organizational managers' classification o... more The current body of literature lacks studies related to organizational managers' classification of systems thinking (ST) skills based on both their overall systemic tendency and the organizational ownership structure. The purpose of this study is to assess and classify the ST skills of senior managers who currently work in a complex business environment. Initially, we clustered managers' overall systemic thinking (OST) using the Bayesian latent class analysis (BLCA) method into two distinct clusters: managers with upper OST (holistic thinker) and managers with lower OST (reductionist thinker). Further, we classified managers' ST skills into two predefined classes to understand the characteristics of each group better. A total of 51 senior managers from two different organizational structures participated in this study. Results show that the ST skills of managers in public are more towards the upper OST/holistic cluster, whereas managers from the private sector have an inclination towards the lower OST/reductionist cluster.

Int. J. System of Systems Engineering, 2020

As organisations operate in turbulent and complex environments, it has become a necessity to asse... more As organisations operate in turbulent and complex environments, it has become a necessity to assess the systems thinking (ST) skills, personality types (PTs), and demographics of practitioners. In this study, we investigated the relationship between practitioners' ST profile, their PTs profiles and demographic characteristics in the domain of complex system problems. The objective of this study is to address the current gap in the literature-lack of studies dedicated to predicting practitioners' ST profile based on their PTs and demographics characteristics. A total of 258 practitioners with different demographics and PTs provided the data. The results show that (1) practitioners can be classified based on their ST skills scores into two clusters: holistic and reductionist (that is, ST profile), (2) each cluster has different PTs profiles and demographic characteristics, and (3) practitioner's ST profile can be predicted, with good accuracy, based on their PTs profile and demographic characteristics.

Quality defects are a significant source of the costs and challenges of project management in the... more Quality defects are a significant source of the costs and challenges of project management in the construction industry. Due to the project delivery nature of on-site construction, they occur inevitably and are the primary causes of project schedule and cost overruns. A construction product manufacturer determined customer satisfaction warranty-based feedback can be a solution to mitigate the defects in the sense that it can help to identify the root causes of defects more systematically. The motivation of this study is to analyze and improve a quality control program for a major construction system manufacturer based on customer satisfaction warranty-based feedback. Customer satisfaction feedback was obtained on a 10-point Likert scale and analyzed. Statistical process control techniques were applied to check for root causes of defects. Analysis of contractor experience within the data set supports the principle of Best Value Procurement Information Systems (BV PIS), which emphasizes contractor performance and experience to manage project risks. The case study finding provides support that the warranty-based quality control system can enhance project efficiency. The study concludes with a description of the main findings, which can be efficient and effective when implemented in the construction industry.

2020 International Conference on Decision Aid Sciences and Application (DASA) , 2020

The academic performance of engineering students continues to receive attention in the literature... more The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.

2020 International Conference on Decision Aid Sciences and Application (DASA) , 2020

This research paper presents the approach of machine learning analysis techniques on education. F... more This research paper presents the approach of machine learning analysis techniques on education. For the large dataset, data mining techniques are used to extract hidden information and create insight. We hypothesized that the prediction algorithm and dimensional reduction algorithm could be used on an educational dataset to extract the hidden information and analyze the information to create insight. Machine learning algorithms can be used to predict student academic performance. Since some of the features in our dataset are correlated so, before applying the prediction algorithm, we applied the dimensional reduction algorithm to reduce the dimension of our dataset and extract the important features. For the prediction analysis, we used three supervised machine learning algorithms, namely K-Nearest Neighbors (KNN), Decision Tree, and Logistic Regression. Before we applied these machine learning algorithms, we applied the dimension reduction algorithm for the feature extraction purpose using two algorithms, namely Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). We compared the performance of these machine learning algorithms. For the student academic performance, their final Examination result was taken as the target value, which was predicted by using the above-mentioned supervised algorithm. Our work shows that the dimensional reduction algorithm, followed by the prediction algorithm, achieved the acceptable prediction accuracy for determining student academic performance. Our result also highlights the advantage of employing machine learning techniques on educational data and explains how it helps to provide engineering education insight for the sustainable development of Engineering education as a whole.

Proceedings of the American Society for Engineering Management 2020 International Annual Conference, 2020

System engineering (SE) is a structured systematized methodology that deals with designing, manag... more System engineering (SE) is a structured systematized methodology that deals with designing, managing, and optimizing systems performance. System engineers use the perspective of system thinking to make the successful use and retirement of engineering systems. Since the role of system engineers ranges widely from technical support to customer interaction, system design to management, there is a demand to develop a cadre of effective systems engineers. However, two critical questions are not well-defined in the extant body of SE literature: (1) What are the fundamental attributes of systems engineering that would influence the effectiveness of individual systems engineers? (2) What are the corresponding leading indicators for appraising the performance of an individual systems engineer? To respond to these questions, this paper proposes a new instrument to evaluate the performance of the system engineers and subsequently identifies their strengths and weakness within the complex system domain. The implication of this study would assist systems engineers in strengthening their system skills and reflects a state that can be improved through training, workshops, and education to prepare them to face the complex situations originating from the problem domain.

The aviation maintenance sector is an example of a large complex system since it integrates sever... more The aviation maintenance sector is an example of a large complex system since it integrates several systems and their sub-components that require frequent updates and maintenance. A survey of the literature shows that aviation maintenance documentation is preserved using an outdated paper-based approach, making the maintenance process more difficult for all stakeholders involved. In response, to ensure the accuracy of a system's specifications and documentation, we propose a systemic approach to support the design process of complex systems. This study develops a modelling approach using Systems Modeling Language (SysML) as a way to document maintenance procedures for an important military aircraft-the EA-6B. Structural and behavioral aspects of the model are developed to examine the use of a model-based approach in aviation maintenance documentation. In addition, a demonstration of the documentation steps of the nose radome assembly of the EA-6B aircraft and different SysML diagrams are discussed. The proposed alternative to the current paper-based approach to record maintenance would serve as a roadmap for practitioners who intend to document the detail of aviation maintenance using a model-based methodology.

International Journal of Engineering Education, 2020

The concepts and topics of manufacturing systems design and analysis are usually taught using tra... more The concepts and topics of manufacturing systems design and analysis are usually taught using traditional lecturing, in-class problem solving, and project-based approaches. These concepts are not easy to grasp and can be tedious when taught by traditional methods. This study presents an innovative virtual reality (VR) based approach to teach manufacturing systems concepts. To illustrate the efficacy and effectiveness of VR technology in enhancing students learning concepts, a VR queuing theory teaching module is developed. The efficacy and effectiveness of the VR module are then analyzed for male and female participants to investigate the impact of the VR environment on female engineers in science, technology, engineering, and mathematics (STEM). Simulation sickness, system usability, and user experience tools were used to assess the efficacy of the VR module, and the queuing theory quiz, NASA TLX assessment, and post-motivation measures were applied to evaluate the effectiveness of the developed VR module. Both males and females indicated higher user satisfaction in terms of system usability. Female participants perceived higher user experience than their male counterparts. Both male and female participants experienced similar simulation sickness symptoms throughout the study. The quiz score indicated that students performed well in the conceptual section for both genders. The NASA TLX results suggested that participants required low perceived work effort in regard to performing the tasks in the module. The post motivation results confirmed that the VR module created positive motivation in learning the queueing theory for both male and female students. Overall, the efficacy and effectiveness measures affirm that both male and female participants perceived a similar experience in the developed VR teaching module.

The 14th Annual IEEE international Systems Conference, 2020

The field of supply chain management (SCM) is recognized as a key element of the stalwart busines... more The field of supply chain management (SCM) is recognized as a key element of the stalwart businesses and economic growth. Organizations have begun to implement sustainable supply chain management due to several reasons, including environmental regulations, international laws, and adherence to compliance. As a consequence, organizations are progressively framing decisions that adequately address all the aspects of sustainability-social, environmental, and economical by considering customer satisfaction and financial growth of the company. However, assessing social sustainability pertaining to the supply chain network has been relatively less addressed in the extant literature. Social sustainability of the supply chain network assures the longstanding viability of the business and ensures the establishment of best management practices on a long-term basis to an organization or a community. This paper identifies the salient factors of the social sustainability criteria pertaining to a healthcare supply chain network with an illustrative case study. Sustainability factors are further quantified using a Bayesian network approach to assess the overall social sustainability of the supply chain network. Advanced analysis, such as by belief propagation techniques, is also conducted to provide better insight regarding the result of the model.

Journal of Management Analytics, 2020

Today's rapid proliferation of information and technological advancements has led to complex and ... more Today's rapid proliferation of information and technological advancements has led to complex and uncertain modern systems environments. The problems resulting from this increased complexity may surpass engineers' current capacity to perform effectively within the domain of complex systems. In response to this situation, the concept of Systems Thinking (ST) has been advanced as an aid to building a mental map that offers a robust conceptual understanding to offset the challenges of modern system of systems (SoS) problems. Although there has been some research regarding the effect of age and gender on ST preferences, there is still a lack of studies investigating how an individual's ST skills preferences in system of systems (SoS) domain vary across educational qualifications. In addition, most of the extant literature focuses on one or two measures to assess the individual ST; thus, there is a need to include the full spectrum of ST measures to assess the ST skills preferences of an individual in the domain of complex systems. To address these gaps, this research uses an established ST skills preferences instrument to gauge an individual's ST skills preferences in the SoS domain based on the educational qualifications. Two hundred and fifty-eight participants with educational qualifications ranging from non-degree to graduate degree participated in the research. The analysis of the responses was performed by a post-hoc test to show which groups differ significantly. From the results obtained through aggregate individual responses, we conclude that each group (i.e bachelor, masters and phD), possesses a different ST skills preference profile on average, and the educational qualifications in the SoS environment has a moderation impact on individuals' system skills preferences.

Systems, 2020

Systems thinking (ST) is an interdisciplinary domain that offers different ways to better underst... more Systems thinking (ST) is an interdisciplinary domain that offers different ways to better understand the behavior and structure of a complex system. Over the past decades, several publications can be identified in academic literature, focusing on different aspects of systems thinking. However, two critical questions are not properly addressed in the extant body of ST literature: (i) How to conduct the content analysis exclusively to derive the prominent statistics (i.e., influential journals, authors, affiliated organizations and countries) pertaining to the domain of ST? (ii) How to get better insights regarding the current and emerging trends that may evolve over time based on the existing body of ST literature? To address these gaps, the aim of this research study is to provide a comprehensive insight into the domain of systems thinking through bibliometric and network analysis. Beginning with over 6000 accumulated publications, the analysis narrowed down to 626 prominent articles with proven influence published over the past three decades. Leveraging rigorous bibliometric tools analysis, this research unveils the influential authors, leading journals and top contributing organizations and countries germane to the domain of systems thinking. In addition, citation, co-citation and page rank analysis used to rank top influential articles in the area of systems thinking. Finally, with the aid of the network analysis, key clusters in the existing literature are identified based on the research areas of systems thinking. The findings of this research will serve as a bluebook for practitioners and scholars to conduct future research within systems thinking context.

Engineering Management Journal, 2020

10 Abstract: In this study, we used a structural equation model-ing method to investigate the rel... more 10 Abstract: In this study, we used a structural equation model-ing method to investigate the relationship between systems engineers and engineering managers' Systems-Thinking (ST) skills preferences and their Personality Traits (PTs) in the domain of complex system problems. As organizations operate 15 in more and more turbulent and complex environments, it has become increasingly important to assess the ST skills preferences and PTs of engineers. The current literature lacks studies related to the impact of systems engineers and engineering managers' PTs on their ST skills preferences, and this study 20 aims to address this gap. A total of 99 engineering managers and 104 systems engineers provided the data to test four hypotheses posed in this study. The results show that the PTs of systems engineers and engineering managers have a positive impact on their level of ST skills preferences and that the 25 education level, the current occupation type, and the managerial experience of the systems engineers and engineering managers moderate the main relationship in the study.

Systems, 2021

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2021

Although the application of systems thinking (ST) has become essential for practitioners when dea... more Although the application of systems thinking (ST) has
become essential for practitioners when dealing with turbulent and
complex environments, there are limited studies available in the
current literature that investigate how the ST skills of practitioners
vary with regard to demographic factors and personality types
(PTs). To address this gap, this article uses a structural equation
modeling approach to explore the relationship between practitioners’ST skills, PT, and a set of demographic factors. The demographic
factors included in the study are education level, the field of the
highest degree, organizational ownership structure, job experience,
and current occupation type. A total of 99 engineering managers, 104
systems engineers (SEs), and 55 practitioners with other occupations participated in this article. Results showed that the education
level, the field of the highest degree, PT, organizational ownership
structure, and current job experience of practitioners influenced
their level of ST skills. Additionally, the current occupation type of
practitioners partially affects their level of ST skills. An in-depth
analysis was also conducted using multiple group analysis to show
how seven ST skills of the practitioners vary across their level of
education. Taken together, the findings of the study suggest that
PT and a set of demographic factors—the education level, the field
of the highest degree, organizational ownership structure, current
job experience, and current occupation type—influence the overall
ST skill of the practitioners.

The academic performance of engineering students continues to receive attention in the literature... more The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.

Quality defects are a significant source of the costs and challenges of project management in the... more Quality defects are a significant source of the costs and challenges of project management in the construction industry. Due to the project delivery nature of on-site construction, they occur inevitably and are the primary causes of project schedule and cost overruns. A construction product manufacturer determined customer satisfaction warranty-based feedback can be a solution to mitigate the defects in the sense that it can help to identify the root causes of defects more systematically. The motivation of this study is to analyze and improve a quality control program for a major construction system manufacturer based on customer satisfaction warranty-based feedback. Customer satisfaction feedback was obtained on a 10-point Likert scale and analyzed. Statistical process control techniques were applied to check for root causes of defects. Analysis of contractor experience within the data set supports the principle of Best Value Procurement Information Systems (BV PIS), which emphasizes contractor performance and experience to manage project risks. The case study finding provides support that the warranty-based quality control system can enhance project efficiency. The study concludes with a description of the main findings, which can be efficient and effective when implemented in the construction industry.

This research paper presents the approach of machine learning analysis techniques on education. F... more This research paper presents the approach of machine learning analysis techniques on education. For the large dataset, data mining techniques are used to extract hidden information and create insight. We hypothesized that the prediction algorithm and dimensional reduction algorithm could be used on an educational dataset to extract the hidden information and analyze the information to create insight. Machine learning algorithms can be used to predict student academic performance. Since some of the features in our dataset are correlated so, before applying the prediction algorithm, we applied the dimensional reduction algorithm to reduce the dimension of our dataset and extract the important features. For the prediction analysis, we used three supervised machine learning algorithms, namely K-Nearest Neighbors (KNN), Decision Tree, and Logistic Regression. Before we applied these machine learning algorithms, we applied the dimension reduction algorithm for the feature extraction purpose using two algorithms, namely Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). We compared the performance of these machine learning algorithms. For the student academic performance, their final Examination result was taken as the target value, which was predicted by using the above-mentioned supervised algorithm. Our work shows that the dimensional reduction algorithm, followed by the prediction algorithm, achieved the acceptable prediction accuracy for determining student academic performance. Our result also highlights the advantage of employing machine learning techniques on educational data and explains how it helps to provide engineering education insight for the sustainable development of Engineering education as a whole.

Academic performance of engineering students continues to receive attention in the literature. Ho... more Academic performance of engineering students continues to receive attention in the literature. However, the literature lacks studies that investigate the simultaneous relationship between students' systems thinking (ST) skills, and Five-Factor Model (FFM) personality traits and proactive personality scale, and their potential impact on academic performance across gender. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, were administrated for data collection. A web-based cross-sectional survey using Qualtrics was developed to gather data from engineering students. To show the prediction power of the ST skills, FFM traits, and proactive personality on the academic performance of engineering students, Multiple Group Structural Analysis was applied. The study findings show how key skills and characteristics impact engineering students' academic performance and also how gender moderates these relationships. This study can provide important implications and contributions to engineering education and complex systems bodies of knowledge. First, the study will provide a better understanding of engineering students' academic performance across gender. This intent is to help educators, teachers, mentors, college authorities, and other involved parties to understand students' individual differences for a better training and guidance environment. Second, a closer look at the level of systemic thinking and its connection with FFM traits and proactive personality would assist in understanding engineering students' skillset better in the domain of complex systems.

Determinants of students' systems thinking continue to receive attention in the literature. Howev... more Determinants of students' systems thinking continue to receive attention in the literature. However, there is a lack of studies that assess students' systems thinking (ST) skills, along with their proactive personality in the aspect of academic performance. The relationship between ST and proactive personality is somewhat complex, although a high level of the overview might have been provided, the in-depth analysis has not been adequately investigated in the literature. The aim of the research paper is (1) to examine the ST skills and proactive personality of engineering students and (2) to find the relationship between students' proactive personality and the level of ST skills. This research paper would provide important implications and contributions to the body of knowledge of engineering education. First, the research will provide a better understanding of students' thinking and personality. This intent is to help educators, teachers, mentors, college authorities, and others involved parties to understand students' individual differences for a better training and guidance environment. Second, a closer look will be provided to better understand the relationship between the level of systemic thinking and the proactive personality of engineering students and how they influence each other in the complex system problem domain.

Journal of Functional Morphology and Kinesiology, 2020

In this research paper, we implemented a mixed factor design in order to investigate the effect o... more In this research paper, we implemented a mixed factor design in order to investigate the effect of four anthropometries: height, weight, lower-arm dimensions, and upper-arm dimensions on the muscle activation level of participants when interacting with three types of moderators: experiment expertise, task type, and muscle type. The research paper focused on two levels of expertise (novice and expert), two tasks (deck-building and picket installation), and four arm muscles (Brachioradialis (BR), Extensor Carpi Ulnaris (ECU), Flexor Carpi Radialis (FCR), and Flexor Carpi Ulnaris (FCU)), which resulted in 16 (2×2×4) groups. For each of the 16 groups, the data were analyzed in order to investigate the relationship between the four anthropometries and the four muscle activation levels of the participants. Amos software (IBM, Armonk, NY, USA), along with multiple group structural equation modeling, was used to test a total of 16 direct relationships, as well as the moderation effects in the designed experiment. The results show that the participants' expertise can moderate the relationship between their height and muscle activation levels, the relationship between their weight and muscle activation levels, and the relationship between their lower arm dimensions and muscle activation levels. Moreover, the findings of this research paper demonstrate that the relationship between the lower arm dimensions and muscle activation levels, and the relationship between weight and muscle activation levels are moderated by the type of muscle used by the participants (i.e., BR, ECU, FCR, and FCU).

Systems Research and Behavioral Science, 2020

The current body of literature lacks studies related to organizational managers' classification o... more The current body of literature lacks studies related to organizational managers' classification of systems thinking (ST) skills based on both their overall systemic tendency and the organizational ownership structure. The purpose of this study is to assess and classify the ST skills of senior managers who currently work in a complex business environment. Initially, we clustered managers' overall systemic thinking (OST) using the Bayesian latent class analysis (BLCA) method into two distinct clusters: managers with upper OST (holistic thinker) and managers with lower OST (reductionist thinker). Further, we classified managers' ST skills into two predefined classes to understand the characteristics of each group better. A total of 51 senior managers from two different organizational structures participated in this study. Results show that the ST skills of managers in public are more towards the upper OST/holistic cluster, whereas managers from the private sector have an inclination towards the lower OST/reductionist cluster.

Int. J. System of Systems Engineering, 2020

As organisations operate in turbulent and complex environments, it has become a necessity to asse... more As organisations operate in turbulent and complex environments, it has become a necessity to assess the systems thinking (ST) skills, personality types (PTs), and demographics of practitioners. In this study, we investigated the relationship between practitioners' ST profile, their PTs profiles and demographic characteristics in the domain of complex system problems. The objective of this study is to address the current gap in the literature-lack of studies dedicated to predicting practitioners' ST profile based on their PTs and demographics characteristics. A total of 258 practitioners with different demographics and PTs provided the data. The results show that (1) practitioners can be classified based on their ST skills scores into two clusters: holistic and reductionist (that is, ST profile), (2) each cluster has different PTs profiles and demographic characteristics, and (3) practitioner's ST profile can be predicted, with good accuracy, based on their PTs profile and demographic characteristics.

Quality defects are a significant source of the costs and challenges of project management in the... more Quality defects are a significant source of the costs and challenges of project management in the construction industry. Due to the project delivery nature of on-site construction, they occur inevitably and are the primary causes of project schedule and cost overruns. A construction product manufacturer determined customer satisfaction warranty-based feedback can be a solution to mitigate the defects in the sense that it can help to identify the root causes of defects more systematically. The motivation of this study is to analyze and improve a quality control program for a major construction system manufacturer based on customer satisfaction warranty-based feedback. Customer satisfaction feedback was obtained on a 10-point Likert scale and analyzed. Statistical process control techniques were applied to check for root causes of defects. Analysis of contractor experience within the data set supports the principle of Best Value Procurement Information Systems (BV PIS), which emphasizes contractor performance and experience to manage project risks. The case study finding provides support that the warranty-based quality control system can enhance project efficiency. The study concludes with a description of the main findings, which can be efficient and effective when implemented in the construction industry.

2020 International Conference on Decision Aid Sciences and Application (DASA) , 2020

The academic performance of engineering students continues to receive attention in the literature... more The academic performance of engineering students continues to receive attention in the literature. Despite that, there is a lack of studies in the literature investigating the simultaneous relationship between students' systems thinking (ST) skills, Five-Factor Model (FFM) personality traits, proactive personality scale, academic, demographic, family background factors, and their potential impact on academic performance. Three established instruments, namely, ST skills instrument with seven dimensions, FFM traits with five dimensions, and proactive personality with one dimension, along with a demographic survey, have been administrated for data collection. A cross-sectional web-based study applying Qualtrics has been developed to gather data from engineering students. To demonstrate the prediction power of the ST skills, FFM traits, proactive personality, academic, demographics, and family background factors on the academic performance of engineering students, two unsupervised learning algorithms applied. The study results identify that these unsupervised algorithms succeeded to cluster engineering students' performance regarding primary skills and characteristics. In other words, the variables used in this study are able to predict the academic performance of engineering students. This study also has provided significant implications and contributions to engineering education and education sustainable development bodies of knowledge. First, the study presents a better perception of engineering students' academic performance. The aim is to assist educators, teachers, mentors, college authorities, and other involved parties to discover students' individual differences for a more efficient education and guidance environment. Second, by a closer examination at the level of systemic thinking and its connection with FFM traits, proactive personality, academic, and demographic characteristics, understanding engineering students' skillset would be assisted better in the domain of sustainable education.

2020 International Conference on Decision Aid Sciences and Application (DASA) , 2020

This research paper presents the approach of machine learning analysis techniques on education. F... more This research paper presents the approach of machine learning analysis techniques on education. For the large dataset, data mining techniques are used to extract hidden information and create insight. We hypothesized that the prediction algorithm and dimensional reduction algorithm could be used on an educational dataset to extract the hidden information and analyze the information to create insight. Machine learning algorithms can be used to predict student academic performance. Since some of the features in our dataset are correlated so, before applying the prediction algorithm, we applied the dimensional reduction algorithm to reduce the dimension of our dataset and extract the important features. For the prediction analysis, we used three supervised machine learning algorithms, namely K-Nearest Neighbors (KNN), Decision Tree, and Logistic Regression. Before we applied these machine learning algorithms, we applied the dimension reduction algorithm for the feature extraction purpose using two algorithms, namely Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). We compared the performance of these machine learning algorithms. For the student academic performance, their final Examination result was taken as the target value, which was predicted by using the above-mentioned supervised algorithm. Our work shows that the dimensional reduction algorithm, followed by the prediction algorithm, achieved the acceptable prediction accuracy for determining student academic performance. Our result also highlights the advantage of employing machine learning techniques on educational data and explains how it helps to provide engineering education insight for the sustainable development of Engineering education as a whole.

Proceedings of the American Society for Engineering Management 2020 International Annual Conference, 2020

System engineering (SE) is a structured systematized methodology that deals with designing, manag... more System engineering (SE) is a structured systematized methodology that deals with designing, managing, and optimizing systems performance. System engineers use the perspective of system thinking to make the successful use and retirement of engineering systems. Since the role of system engineers ranges widely from technical support to customer interaction, system design to management, there is a demand to develop a cadre of effective systems engineers. However, two critical questions are not well-defined in the extant body of SE literature: (1) What are the fundamental attributes of systems engineering that would influence the effectiveness of individual systems engineers? (2) What are the corresponding leading indicators for appraising the performance of an individual systems engineer? To respond to these questions, this paper proposes a new instrument to evaluate the performance of the system engineers and subsequently identifies their strengths and weakness within the complex system domain. The implication of this study would assist systems engineers in strengthening their system skills and reflects a state that can be improved through training, workshops, and education to prepare them to face the complex situations originating from the problem domain.

The aviation maintenance sector is an example of a large complex system since it integrates sever... more The aviation maintenance sector is an example of a large complex system since it integrates several systems and their sub-components that require frequent updates and maintenance. A survey of the literature shows that aviation maintenance documentation is preserved using an outdated paper-based approach, making the maintenance process more difficult for all stakeholders involved. In response, to ensure the accuracy of a system's specifications and documentation, we propose a systemic approach to support the design process of complex systems. This study develops a modelling approach using Systems Modeling Language (SysML) as a way to document maintenance procedures for an important military aircraft-the EA-6B. Structural and behavioral aspects of the model are developed to examine the use of a model-based approach in aviation maintenance documentation. In addition, a demonstration of the documentation steps of the nose radome assembly of the EA-6B aircraft and different SysML diagrams are discussed. The proposed alternative to the current paper-based approach to record maintenance would serve as a roadmap for practitioners who intend to document the detail of aviation maintenance using a model-based methodology.

International Journal of Engineering Education, 2020

The concepts and topics of manufacturing systems design and analysis are usually taught using tra... more The concepts and topics of manufacturing systems design and analysis are usually taught using traditional lecturing, in-class problem solving, and project-based approaches. These concepts are not easy to grasp and can be tedious when taught by traditional methods. This study presents an innovative virtual reality (VR) based approach to teach manufacturing systems concepts. To illustrate the efficacy and effectiveness of VR technology in enhancing students learning concepts, a VR queuing theory teaching module is developed. The efficacy and effectiveness of the VR module are then analyzed for male and female participants to investigate the impact of the VR environment on female engineers in science, technology, engineering, and mathematics (STEM). Simulation sickness, system usability, and user experience tools were used to assess the efficacy of the VR module, and the queuing theory quiz, NASA TLX assessment, and post-motivation measures were applied to evaluate the effectiveness of the developed VR module. Both males and females indicated higher user satisfaction in terms of system usability. Female participants perceived higher user experience than their male counterparts. Both male and female participants experienced similar simulation sickness symptoms throughout the study. The quiz score indicated that students performed well in the conceptual section for both genders. The NASA TLX results suggested that participants required low perceived work effort in regard to performing the tasks in the module. The post motivation results confirmed that the VR module created positive motivation in learning the queueing theory for both male and female students. Overall, the efficacy and effectiveness measures affirm that both male and female participants perceived a similar experience in the developed VR teaching module.

The 14th Annual IEEE international Systems Conference, 2020

The field of supply chain management (SCM) is recognized as a key element of the stalwart busines... more The field of supply chain management (SCM) is recognized as a key element of the stalwart businesses and economic growth. Organizations have begun to implement sustainable supply chain management due to several reasons, including environmental regulations, international laws, and adherence to compliance. As a consequence, organizations are progressively framing decisions that adequately address all the aspects of sustainability-social, environmental, and economical by considering customer satisfaction and financial growth of the company. However, assessing social sustainability pertaining to the supply chain network has been relatively less addressed in the extant literature. Social sustainability of the supply chain network assures the longstanding viability of the business and ensures the establishment of best management practices on a long-term basis to an organization or a community. This paper identifies the salient factors of the social sustainability criteria pertaining to a healthcare supply chain network with an illustrative case study. Sustainability factors are further quantified using a Bayesian network approach to assess the overall social sustainability of the supply chain network. Advanced analysis, such as by belief propagation techniques, is also conducted to provide better insight regarding the result of the model.

Journal of Management Analytics, 2020

Today's rapid proliferation of information and technological advancements has led to complex and ... more Today's rapid proliferation of information and technological advancements has led to complex and uncertain modern systems environments. The problems resulting from this increased complexity may surpass engineers' current capacity to perform effectively within the domain of complex systems. In response to this situation, the concept of Systems Thinking (ST) has been advanced as an aid to building a mental map that offers a robust conceptual understanding to offset the challenges of modern system of systems (SoS) problems. Although there has been some research regarding the effect of age and gender on ST preferences, there is still a lack of studies investigating how an individual's ST skills preferences in system of systems (SoS) domain vary across educational qualifications. In addition, most of the extant literature focuses on one or two measures to assess the individual ST; thus, there is a need to include the full spectrum of ST measures to assess the ST skills preferences of an individual in the domain of complex systems. To address these gaps, this research uses an established ST skills preferences instrument to gauge an individual's ST skills preferences in the SoS domain based on the educational qualifications. Two hundred and fifty-eight participants with educational qualifications ranging from non-degree to graduate degree participated in the research. The analysis of the responses was performed by a post-hoc test to show which groups differ significantly. From the results obtained through aggregate individual responses, we conclude that each group (i.e bachelor, masters and phD), possesses a different ST skills preference profile on average, and the educational qualifications in the SoS environment has a moderation impact on individuals' system skills preferences.

Systems, 2020

Systems thinking (ST) is an interdisciplinary domain that offers different ways to better underst... more Systems thinking (ST) is an interdisciplinary domain that offers different ways to better understand the behavior and structure of a complex system. Over the past decades, several publications can be identified in academic literature, focusing on different aspects of systems thinking. However, two critical questions are not properly addressed in the extant body of ST literature: (i) How to conduct the content analysis exclusively to derive the prominent statistics (i.e., influential journals, authors, affiliated organizations and countries) pertaining to the domain of ST? (ii) How to get better insights regarding the current and emerging trends that may evolve over time based on the existing body of ST literature? To address these gaps, the aim of this research study is to provide a comprehensive insight into the domain of systems thinking through bibliometric and network analysis. Beginning with over 6000 accumulated publications, the analysis narrowed down to 626 prominent articles with proven influence published over the past three decades. Leveraging rigorous bibliometric tools analysis, this research unveils the influential authors, leading journals and top contributing organizations and countries germane to the domain of systems thinking. In addition, citation, co-citation and page rank analysis used to rank top influential articles in the area of systems thinking. Finally, with the aid of the network analysis, key clusters in the existing literature are identified based on the research areas of systems thinking. The findings of this research will serve as a bluebook for practitioners and scholars to conduct future research within systems thinking context.

Engineering Management Journal, 2020

10 Abstract: In this study, we used a structural equation model-ing method to investigate the rel... more 10 Abstract: In this study, we used a structural equation model-ing method to investigate the relationship between systems engineers and engineering managers' Systems-Thinking (ST) skills preferences and their Personality Traits (PTs) in the domain of complex system problems. As organizations operate 15 in more and more turbulent and complex environments, it has become increasingly important to assess the ST skills preferences and PTs of engineers. The current literature lacks studies related to the impact of systems engineers and engineering managers' PTs on their ST skills preferences, and this study 20 aims to address this gap. A total of 99 engineering managers and 104 systems engineers provided the data to test four hypotheses posed in this study. The results show that the PTs of systems engineers and engineering managers have a positive impact on their level of ST skills preferences and that the 25 education level, the current occupation type, and the managerial experience of the systems engineers and engineering managers moderate the main relationship in the study.

Mississippi Academy of Science, 2019

Abstract—The complex and turbulent nature of the business environment is increasing with the comp... more Abstract—The complex and turbulent nature of the business environment is increasing with the complexity in solving problems and making accurate decisions. In response, system thinking has been considered as a potential solution that offers a comprehensive understanding of organizational structures. Addressing problems in complex systems requires not only technical and business knowledge but also appropriate amount of job experience. This research assesses individuals’ systems thinking (ST) skills based on their job experience in a complex organizational structure. A cross-sectional survey was administrated between managers with different years of job experience, followed by a multi-group structural equation modeling and post-hoc Tukey HSD tests to compare an individual’s systems thinking skills across three different groups. Research results provide some insights on how job experience moderate an individual’s systems thinking aptitude toward problem-solving in complex systems.

INFORMS 2017 Annual Conference in Houston, TX, USA, October 22-25, 2017., 2017

The Instrument to Assess Capacity for Systems Thinking was developed to measure individual system... more The Instrument to Assess Capacity for Systems Thinking was developed to measure individual systems thinking capacity, providing a useful baseline to facilitate agent-assignments, training, and education for effective complex systems problems. The research-based instrument generates systems thinking profiles by capturing the state of individual inclination toward systemic thinking as well as a preference for engaging and solving complex system problems. Researchers perform confirmatory factor analysis to verify the factor structure of the construct and evaluate construct validity.

The 13th Annual IEEE International Systems Conference, 2019

The turbulent nature of the business environment is increasing with the complexity in solving pro... more The turbulent nature of the business environment is increasing with the complexity in solving problems and making accurate decisions. In response, system thinking has been considered as a potential solution that offers a comprehensive understanding of organizational structures. Addressing problems in complex systems requires not only technical and business knowledge but also years of managerial experience. This research assesses individuals’ systems thinking (ST) skills based on their managerial experience in a complex organizational structure. A cross-sectional survey was administrated between managers with different years of experience, followed by a multi-group structural equation modeling and post-hoc Tukey HSD tests to compare an individual’s systems thinking skills across three different groups. Research results provide some insights on how managerial experience moderate an individual’s systems thinking aptitude toward problem-solving.