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Articles 331 - 360 of 2141

Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Finding Core Members Of A Hedonic Game, Daniele M. Vernon-Bido May 2022

Finding Core Members Of A Hedonic Game, Daniele M. Vernon-Bido

Computational Modeling & Simulation Engineering Theses & Dissertations

Agent-based modeling (ABM) is a frequently used paradigm for social simulation; however, there is little evidence of its use in strategic coalition formations. There are few models that explore coalition formation and even fewer that validate their results against an expected outcome. Cooperative game theory is often used to study strategic coalition formation but solving games involving a significant number of agents is computationally intractable. However, there is a natural linkage between ABM and the study of strategic coalition formation. A foundational feature of ABM is the interaction of agents and their environment. Coalition formation is primarily the result of …

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Complex System Governance Leadership, David C. Walters May 2022

Complex System Governance Leadership, David C. Walters

Engineering Management & Systems Engineering Theses & Dissertations

The purpose of this research was to develop a systems theory-based framework for leadership in governance of complex systems. Recognizing complexity and uncertainty as norms for the environments in which organizations exist encouraged researchers to suggest complexity theory, complex systems, and complex adaptive systems as appropriate for addressing these conditions. Complex System Governance (CSG), based in systems theory, management cybernetics, and governance, endeavors to provide for the design, execution and evolution of functions that provide control, communication, coordination, and integration at the metasystem level to support operations and continued system existence (viability). From a management cybernetics perspective, CSG leadership has …

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An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu Apr 2022

An Elliptical Cover Problem In Drone Delivery Network Design And Its Solution Algorithms, Yanchao Liu

Industrial and Systems Engineering Faculty Research Publications

Given n demand points in a geographic area, the elliptical cover problem is to determine the location of p depots (anywhere in the area) so as to minimize the maximum distance of an economical delivery trip in which a delivery vehicle starts from the nearest depot to a demand point, visits the demand point and then returns to the second nearest depot to that demand point. We show that this problem is NP-hard, and adapt Cooper’s alternating locate-allocate heuristic to find locally optimal solutions for both the point-coverage and area-coverage scenarios. Experiments show that most locally optimal solutions perform similarly …

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The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick Apr 2022

The Traveling Salesman Problem: An Analysis And Comparison Of Metaheuristics And Algorithms, Mason Helmick

Senior Honors Theses

One of the most investigated topics in operations research is the Traveling Salesman Problem (TSP) and the algorithms that can be used to solve it. Despite its relatively simple formulation, its computational difficulty keeps it and potential solution methods at the forefront of current research. This paper defines and analyzes numerous proposed solutions to the TSP in order to facilitate understanding of the problem. Additionally, the efficiencies of different heuristics are studied and compared to the aforementioned algorithms’ accuracy, as a quick algorithm is often formulated at the expense of an exact solution.

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Air Force Specialty Code Assignment Optimization, Rebecca L. Reynolds Mar 2022

Air Force Specialty Code Assignment Optimization, Rebecca L. Reynolds

Theses and Dissertations

Each year, the Air Force Personnel Center determines which career field newly commissioned officers will serve under during their time in the Air Force. The career fields are assigned while considering five priorities, dictated by Headquarters Air Force, Manpower and Personnel: target number of cadets, education requirements, average cadet percentile, cadet source of commissioning, and cadet preference. A mixed-integer linear program with elasticized constraints is developed to generate cadet assignments according to these priorities. Each elasticized constraint carries an associated reward and penalty, which is used to dictate the importance of the constraint within the model. A subsequent analysis is …

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Military Personnel Flight Customer Wait Time Reduction Model Using Simulation, Nicholas C. Anderson Mar 2022

Military Personnel Flight Customer Wait Time Reduction Model Using Simulation, Nicholas C. Anderson

Theses and Dissertations

Customers at Military Personnel Flights (MPFs) have been experiencing long wait times. These customers are typically employees of the United States Air Force and every moment spent waiting for service is a moment they are away from their actual jobs. By reducing the mean wait time of MPF customers, manhours can be saved and customer complaints may be alleviated. This research uses data collected from an MPF to build a discrete-event simulation model of an MPF. A full factorial experimental design was conducted in the model using five factors. The factors included the total number of employees, the total number …

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A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla Mar 2022

A Decision Support Simulation To Analyze Scheduling Alternatives For Applicant Processing At Military Entrance Processing Stations (Meps), Jonathan M. Escamilla

Theses and Dissertations

Applicant processing at Military Entrance Processing Stations (MEPS) is conducted via a batch arrival process by which all applicants arrive at the beginning of the processing day. Pursuit of alternate processing scenarios has never progressed beyond the pilot stage, possibly because the Command lacks a general decision support model to evaluate the impacts of proposed policies on applicant processing operations. This research creates a discrete event simulation of MEPS applicant processing operations and applies the model to three alternative applicant processing scenarios: split-shift, appointment- based, and express-lane. Results are examined and compared to benchmarks using multiple performance measurements.

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An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning, John C. O'Donnell Mar 2022

An Exploratory Analysis Of Time Series Econometric Data For Retention Forecasting Using Deep Learning, John C. O'Donnell

Theses and Dissertations

Officer retention in the Air Force has been researched many times in an attempt to better predict the personnel needs of the Air Force for the future. There has been previous work done in regards to specific AFSCs and how their retention compares to specific yet similar private sector jobs. This study considers different econometric time series statistics as a feature space and an average Air Force officer separation rate as the response variable for the multivariate time series analysis deep learning techniques. The econometric indicators used in this study are New Business Formations, New Durable Good Orders, and the …

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Screening Heuristics For The Evaluation Of Covert Network Node Insertion Scenarios, Andrew E. Pekarek Mar 2022

Screening Heuristics For The Evaluation Of Covert Network Node Insertion Scenarios, Andrew E. Pekarek

Theses and Dissertations

The majority of research on covert networks uses social network analysis (SNA) to determine critical members of the network to either kill or capture for the purpose of network destabilization. This thesis takes the opposite approach and evaluates potential scenarios for inserting an agent into a covert network for information gathering purposes or future disruption operations. Due to the substantial number of potential insertion scenarios in a large network, this research proposes three screening heuristics that leverage SNA measures to reduce the solution space before applying a simple search heuristic.

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Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista Mar 2022

Inverse Optimization: Inferring Unknown Instance Parameters From Observed Decisions, Keith Batista

Theses and Dissertations

The objective of this research is to develop procedures that estimate selected, unknown parameters over an adversary's investment portfolio across a set of new or existing technologies. To solve for the selected unknown parameters, it is assumed that the adversary is maximizing the portfolio optimization problem and investing along the efficient frontier. The first technique is when an unknown risk attitude exists but all other parameters were known (i.e. expected return, variance, covariance). An adaptive line search technique that iteratively solved the portfolio optimization problem until the adversary's risk parameter was found. The second problem that was solved was when …

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Training Logic And Random Forest Models To Predict It Spending, Jacob P. Batt Mar 2022

Training Logic And Random Forest Models To Predict It Spending, Jacob P. Batt

Theses and Dissertations

The Air Force must modernize, but the distribution of funds for technology remains as tight as ever. To this end, the Air Force Audit Agency is looking to utilize machine learning techniques to enhance their capabilities. This research explores Logistic Regression and Random Forest modeling to streamline data collection and cost classification. The final Logistic Regression model identified 4 significant attributes out of the 36 given and was 85 accurate in predicting whether a purchase amount was over or under $10,000. To expand beyond binary classification, a six-category classification Random Forest model was developed. It identified 6 significant attributes and …

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Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell Mar 2022

Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell

Theses and Dissertations

The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …

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The Cyber Wargame Commodity Course Of Action Automated Analysis Method, Alex Hoffendahl Mar 2022

The Cyber Wargame Commodity Course Of Action Automated Analysis Method, Alex Hoffendahl

Theses and Dissertations

In the modern operational landscape, strategic decisions are made and executed, under uncertain conditions, with many potential constraints and limited information. The end goal of these decisions is to minimize and mitigate the effect of adversarial threats, which may or may not act in line with previous assumptions. Wargaming is a powerful tool that allows for the practical implementation of theoretical knowledge into real-world scenarios, enhancing decision-makers critical thinking and problem solving skills. Furthermore, including cyber-effects in a wargame leads to a broader decision scope for an entire operation. This research aims to enhance the analytical capabilities and overall usability …

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Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan Mar 2022

Multiagent Routing Problem With Dynamic Target Arrivals Solved Via Approximate Dynamic Programming, Andrew E. Mogan

Theses and Dissertations

This research formulates and solves the multiagent routing problem with dynamic target arrivals (MRP-DTA), a stochastic system wherein a team of autonomous unmanned aerial vehicles (AUAVs) executes a strike coordination and reconnaissance (SCAR) mission against a notional adversary. Dynamic target arrivals that occur during the mission present the team of AUAVs with a sequential decision-making process which we model via a Markov Decision Process (MDP). To combat the curse of dimensionality, we construct and implement a hybrid approximate dynamic programming (ADP) algorithmic framework that employs a parametric cost function approximation (CFA) which augments a direct lookahead (DLA) model via a …

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Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn Mar 2022

Narrative Analysis Of Open-Source Social Media Activity In The Indopacom Aor, Aaron K. Glenn

Theses and Dissertations

Emotion classification can be a powerful tool to derive narratives from social media data. Recurrent Neural Networks (RNN) can meet or exceed the performance of state-of-the-art traditional machine learning techniques using exclusively open-source data and models. Specifically, these results show that RNN variants can produce more than an 8% gain in accuracy in comparison to Logistic Regression and SVM techniques and a 15% gain over Random Forest when using FastText embeddings. This research found a statistical significance in the performance of a single layer Bi-directional Long Short-Term Memory (Bi-LSTM) model over a 2-layer stacked Bi-LSTM model. This research also found …

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Assessing The United States Foreign Assistance Activities Impact On Violent Conflicts, Daniel F. Feze Mar 2022

Assessing The United States Foreign Assistance Activities Impact On Violent Conflicts, Daniel F. Feze

Theses and Dissertations

The Global Fragility Act, H.R.2116 116th Cong. (2019), “directs the Department of State to establish the interagency Global Fragility Initiative to stabilize conflict-affected areas and prevent violence globally, and establishes funds to support such efforts”. The United States Agency for International Development (USAID) has identified deteriorating economies, weak or illegitimate political institutions, and competition over natural resources as causes of violence, extremism and instability (USAID, 2021). The agency gives priority to mitigating the causes and consequences of violent conflicts, instability and extremism and funds programs and activities to accomplish that (USAID, 2021). With this study, we aim to quantitatively assess …

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Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice Mar 2022

Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice

Theses and Dissertations

We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …

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A Decision Analysis Framework To Consider Space Congestion In Orbit Selection, Anthony J. Correale Mar 2022

A Decision Analysis Framework To Consider Space Congestion In Orbit Selection, Anthony J. Correale

Theses and Dissertations

Low Earth Orbit (LEO) is becoming more congested, which increases the risk to space missions. Decision makers will need to consider this increase in congestion as an increased risk within their mission engineering process. This thesis proposes a methodology to create and implement a value structure that quantitatively scores a range of orbits based on congestion factors of each orbit and how well each orbit meets mission requirements. This thesis demonstrates this methodology on a set of circular LEO orbits defined by altitude and inclination, and scores this illustrative scenario based on notional mission measures and expected number of encounters …

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Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke Mar 2022

Optimal Aircraft Maneuvering Models For Cruise Missile Engagement: A Modeling And Computational Study, Izaiah G. Laduke

Theses and Dissertations

Given the increased threat and proliferation of adversary military capabilities, this research seeks to develop reasonably accurate and computationally tractable models to optimally maneuver aircraft to intercept cruise missile attacks. The research leveraged mathematical programming to model the problem, informed by constraints representing a system of (temporal) difference equations. The research began by comparing six models having alternative representations of velocity and acceleration constraints while analyzing situations with stationary targets. The Multiple Aircraft, Multiple Stationary Target Engagement Problem with Box Constraint Bounds (MAMSTEP-BC) Model yielded superior overall performance and was further analyzed through alternative mathematical programming model enhancements to create …

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Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas Mar 2022

Comparison Of Lightning Warning Radii Distributions, Michael M. Maestas

Theses and Dissertations

Previous research investigating lightning warning radii about the Cape Canaveral space launch facilities have focused on reducing these radii from either 5 nautical miles (NM) to 4 NM or from 6 NM to 5 NM depending on the structures being protected. Some of these findings have suggested the possibility of both a seasonal difference (warm versus cold) and lightning detection events (cloud-to-ground lightning (CG) or total lightning (TL)) impacting these radii and associated risk levels. Utilizing the 2017-2020 data provided by the 45th Weather Squadron at Patrick Space Force Base via the Mesoscale Eastern Range Lightning Information System (MERLIN), this …

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Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller Mar 2022

Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller

Theses and Dissertations

Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …

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Analysis Of Container Shipments For Ustranscom, John N. Campos Y Campos Mar 2022

Analysis Of Container Shipments For Ustranscom, John N. Campos Y Campos

Theses and Dissertations

USTRANSCOM (United States Transportation Command) sends containers to various overseas destinations, mainly commercial container shipping companies. Delivering the containers to the destinations on time is important to support the United States (US) Forces deployed in foreign countries. This study analyzes container shipment records for two years from 2019 to 2021 and prepares insights for USTRANSCOM. This study utilizes descriptive statistics, data visualization, and one-way analysis of variance (ANOVA). According to the records, almost half of the containers (41.25%) were delivered late for one day or longer. The container with the longest delay took 408 days. Major reasons for delays included …

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Strategic Energy Master Planning For Carbon Neutrality, Marie Patterson Jan 2022

Strategic Energy Master Planning For Carbon Neutrality, Marie Patterson

CSU Journal of Sustainability and Climate Change

Universities across the United States are generating goals to be more sustainable and carbon neutral. The energy used in existing buildings on campuses amount to a large volume of greenhouse emissions and must be reduced to help achieve neutrality goals. Strategic Energy Master Plans are instrumental to support these goals through the development of recommendations to reduce energy. Calculating the energy use intensity for existing buildings, a main component of a Strategic Energy Master Plan, can help the campus understand where energy is being used the most. With this information the highest energy consuming buildings can be the focus of …

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Strengthening A Linear Reformulation Of The 0-1 Cubic Knapsack Problem Via Variable Reordering, Richard Forrester, Lucas Waddell Jan 2022

Strengthening A Linear Reformulation Of The 0-1 Cubic Knapsack Problem Via Variable Reordering, Richard Forrester, Lucas Waddell

Faculty Journal Articles

The 0-1 cubic knapsack problem (CKP), a generalization of the classical 0-1 quadratic knapsack problem, is an extremely challenging NP-hard combinatorial optimization problem. An effective exact solution strategy for the CKP is to reformulate the nonlinear problem into an equivalent linear form that can then be solved using a standard mixed-integer programming solver. We consider a classical linearization method and propose a variant of a more recent technique for linearizing 0-1 cubic programs applied to the CKP. Using a variable reordering strategy, we show how to improve the strength of the linear programming relaxation of our proposed reformulation, which ultimately …

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The Product Test Scheduling Problem, Megan Wydick Martin, Cliff Ragsdale, John Fico, Carlos G. Cajica-Sierra, Richard M. Fetcenko Jan 2022

The Product Test Scheduling Problem, Megan Wydick Martin, Cliff Ragsdale, John Fico, Carlos G. Cajica-Sierra, Richard M. Fetcenko

International Journal of Applied Management and Technology

This research focused on product test scheduling in the presence of in-process and at-completion inspection constraints. Such testing arises in the context of the manufacture of products that must perform reliably in extreme environmental conditions. Often, these products must receive a certification from prescribed regulatory agencies at the successful completion of a predetermined series of tests. Operational efficiency is enhanced by determining the optimal order and start times of tests so as to minimize the makespan while ensuring that technicians are available when needed to complete in-process and at-completion inspections. We refer to this as the product test scheduling problem. …

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An Exploratory Assessment Of Small Group Performance Leveraging Motion Dynamics With Optical Flow, Joshua Desantiago Jan 2022

An Exploratory Assessment Of Small Group Performance Leveraging Motion Dynamics With Optical Flow, Joshua Desantiago

Electronic Theses and Dissertations, 2020-2023

Understanding team behaviors and dynamics are important to better understand and foster better teamwork. The goal of this master's thesis was to contribute to understanding and assessing teamwork in small group research, by analyzing motion dynamics and team performance with non-contact sensing and computational assessment. This thesis's goal is to conduct an exploratory analysis of motion dynamics on teamwork data to understand current limitations in data gathering approaches and provide a methodology to automatically categorize, label, and code team metrics from multi-modal data. We created a coding schema that analyzed different teamwork datasets. We then produced a taxonomy of the …

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Exact Algorithms For Practical Instances Of The Railcar Loading Problem At Marine Container Terminals, Manwo Ng, Dung-Ying Lin Jan 2022

Exact Algorithms For Practical Instances Of The Railcar Loading Problem At Marine Container Terminals, Manwo Ng, Dung-Ying Lin

Information Technology & Decision Sciences Faculty Publications

With the growth in global trade and its environmental footprint, sustainable modes of freight movement are increasingly important in today’s globalized world. This study focuses on on-dock rail, where the rail terminal is located within the marine container terminal. On-dock rail has in recent years become an essential mode of transportation to move containers out of congested marine container terminals. This study contributes to the literature by presenting tailored exact solution algorithms for a recently proposed optimization model to optimize the loading of double-stack trains. In particular, a 3-stage solution framework is presented for the case when rail cars have …

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Evolution And Diffusion Of Icts In The Indian Railways: A Historical Analysis, Ramesh Subramanian Jan 2022

Evolution And Diffusion Of Icts In The Indian Railways: A Historical Analysis, Ramesh Subramanian

Journal of International Technology and Information Management

The Indian Railway system is one of the largest socio-technical systems in the world. It has existed for over 160 years, starting from the British Colonial times. It continues to play a critical role in present-day India. It’s continued functioning is dependent not only on the personnel who are employed in the railways, but also the technologies that go into the system. A critical technology in the functioning of the railway system is information and communications technologies (ICTs). ICTs are deployed in almost every facet of the railway system. But these ICTs did not manifest themselves recently. They have been …

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Jitim Table Of Contents - Vol. 31 Issue 2 - 2022 Jan 2022

Jitim Table Of Contents - Vol. 31 Issue 2 - 2022

Journal of International Technology and Information Management

JITIM ToC

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Assessing Performance Impact Of Digital Transformation For Instructors In The Covid-19 Era, Shailja Tripathi Dr., Shubhangi Urkude Dr. Jan 2022

Assessing Performance Impact Of Digital Transformation For Instructors In The Covid-19 Era, Shailja Tripathi Dr., Shubhangi Urkude Dr.

Journal of International Technology and Information Management

Digital transformation has evolved as the main issue for higher education institutions (HEIs) across the globe due to the Covid-19 outbreak. The purpose of this study is to investigate the performance impacts of digital transformation for instructors of HEIs during the pandemic. The technology-to-performance chain (TPC) model pursues to predict the influence of an information system on the performance of an individual user. Hence, TPC model is used to evaluate the performance of instructors due to digital transformation in the institutions during the Covid-19 pandemic. The data is collected from instructors of higher educational institutions. Recently, partial least squares path …

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