Jatinder Gupta | University of Alabama in Huntsville (original) (raw)
Papers by Jatinder Gupta
Journal of International Technology and Information Management
Prior research has mostly focused on transaction cost economics (TCE) to interpret the effect of ... more Prior research has mostly focused on transaction cost economics (TCE) to interpret the effect of information systems (IS) on organizational governance structures. A TCE based approach predicts that information technology (IT) will lead to increased use of electronic markets to coordinate economic transactions from electronic hierarchies. However, there is contradictory evidence in the literature regarding the rise and importance of cooperative relationships, joint ventures, and value-added partnerships integrated through information systems. To reconcile these contradictions, this paper analyzes the effect of IT on governance structures based on the TCE, social network theory, and the resource based view (RBV) of the firm. The most important aspect of this paper is that instead of overemphasizing the economic perspective, as has been done in prior IS research, it pays equal attention to economic, social, and knowledge perspectives of the firm. By considering variables such as product demand uncertainty, human specificity, task complexity, and frequency of interaction, the effect of IT on governance structure has been analyzed. In this paper, we suggest that, in knowledge intensive companies, a greater degree of outsourcing will take place, not through markets as hypothesized by earlier researchers, but through an increasing number of social networks. This differentiation can not be understood in simple economic terms because social networks are not based on contracts. Therefore, we suggest that the integration of IT-enabled social networks with the TCE and RBV of the firm leads to a better understanding and improvement of decision-making and corporate governance structures in knowledge intensive firms.
Asia-Pacific Journal of Operational Research, 2019
This paper investigates the ability of a combined buy-back (BB) and revenue sharing (RS) contract... more This paper investigates the ability of a combined buy-back (BB) and revenue sharing (RS) contract to improve the efficiency of a supply chain involving a risk-neutral supplier and a risk-averse retailer facing stochastic demand. We show that the combined contract can coordinate the supply chain under mild conditions. Further, the effects of risk aversion and contract parameters on the agents’ decision-making are analyzed when the retailer’s risk aversion is modeled by the conditional value-at-risk (CVaR) criterion. In contrast to individual BB and RS contracts, the combined contract is able to mitigate the effect of risk-aversion and allow the supplier to obtain higher expected profit. Moreover, situations exist where the combined contract can coordinate the supply chain when neither the BB nor the RS contract can coordinate it. Numerical experiments conducted further confirm the analytical results derived.
Harnessing Social Media as a Knowledge Management Tool
Technical solutions to security have been suggested but found lacking and it has been recognized ... more Technical solutions to security have been suggested but found lacking and it has been recognized that security is a people issue as well, and behavioral research on information security is critical. Individual learning about cybersecurity is not formal and linear, but complex and network based. In this paper we develop a model of how social media characteristics impact cybersecurity knowledge transfer using technology threat avoidance theory. In developing the conceptual model we seek to answer the following questions. How do users discover cybersecurity knowledge on social media platforms? What are the platform and interaction characteristics that enable them to find cybersecurity knowledge and share this knowledge with others? In doing so we consider the impact of the threat and protection context on cybersecurity knowledge transfer which is different from knowledge transfer in the other contexts.
Business and information systems professionals continue to struggle to address the complex issues... more Business and information systems professionals continue to struggle to address the complex issues involved in determining payoffs from information technology (IT) investments in e-business environment. The business value returned by IT investments in E-business environment is being viewed with increasing skepticism by researchers and practitioners. Quantifying the IT investments payoff has always been subject to debate because measurements and real value delivered some time can not be expressed in typical IT metrics like response time and hardware utilization etc. Aligning IT measurements with the business measurements is critical to establishing the business value of IT investments. In this paper we suggest a framework that identifies not only the components where IT investment payoff could be measured for e-commerce initiatives but also provides a guidance about how and where to measures for business value from the perspective of management and endusers in e-business environment.
Handbook of Research on Information Security and Assurance
The purpose of the information security policy is to establish an organization-wide approach to p... more The purpose of the information security policy is to establish an organization-wide approach to prescribe mechanisms that help identify and prevent the compromise of information security and the misuse of organization's data, applications, networks, and computer systems to define mechanisms that protect the organization from its legal and ethical responsibilities with regard to its networks' and computer systems' connectivity to worldwide networks. Most of the organizations worldwide already have formulated their information security policies. Having a security policy document in itself is not enough, the document must be complete. This paper examines security policies of 20 different academic organizations with standard security policy framework and attempts to answer questions such as: are these security policy documents complete? Are they fully up to date? Does the precept match the practice? These are kind of questions that are addressed in this study.
Proceedings of the 2001 ACM symposium on Applied computing, 2001
This work investigates the use of neural networks to schedule flow shops with dynamic job arrival... more This work investigates the use of neural networks to schedule flow shops with dynamic job arrival. The objective of such scheduling is to determine both sequence and lot-sizes concurrently that minimize a makespan. We present a multi-neural network architecture for simultaneous lot-sizing and sequencing neural-network learning. Our experimental study shows that our multi-neural networks can learn both lot-sizing and sequencing decisions, and outperform a sequencing-only neural network.
Engineering Applications of Artificial Intelligence
Proceeding of Flexible Automation and Integrated Manufacturing 1994
International Journal of Production Research
Flexible Services and Manufacturing Journal
Renewable and Sustainable Energy Reviews
Journal of Parametrics, 1984
The number of evidences found in a digital crime scene has burgeoned significantly over the past ... more The number of evidences found in a digital crime scene has burgeoned significantly over the past few years. In addition, the demand for delivering accurate results within a given time deadline has increased. The major challenges coinciding with these aforementioned objectives are to investigate the right set of evidences and to allocate appropriate times for their investigation. In this paper, we present a mixed integer linear programming (MILP) model to analyze the problem of allocating optimal investigation times for evidences involving a single investigator. The objective is to maximize the overall effectiveness of a forensic investigation procedure. We particularly focus on the time critical digital forensic cases, in which results have to be finalized in a court of law within a specified time deadline. While the general problem is NP-hard, two special cases are illustrated to be optimally solvable in polynomially computational effort. Two heuristic algorithms are proposed to so...
Journal of Parametrics, 1985
Computers & Industrial Engineering, 2021
Journal of Parametrics, 1985
Journal of the Operational Research Society, 2019
For effective modelling of flowshop scheduling problems, artificial neural networks (ANNs), due t... more For effective modelling of flowshop scheduling problems, artificial neural networks (ANNs), due to their robustness, parallelism and predictive ability have been successfully used by researchers. These studies reveal that the ANNs trained with conventional back propagation (CBP) algorithm utilising the gradient descent method are commonly applied to model and solve flowshop scheduling problems. However, the existing scheduling literature has not explored the suitability of some improved neural network training algorithms, such as gradient descent with adaptive learning (GDAL), Boyden, Fletcher, Goldfarb and Shanno updated Quasi-Newton (UQ-N), and Levenberg-Marquardt (L-M) algorithms to solve the flowshop scheduling problem. In this article, we investigate the use of these training algorithms as competitive neural network learning tools to minimise makepsan in a flowshop. Based on training and testing measures, overall results from extensive computational experiments demonstrate that, in terms of the solution quality and computational effort required, the L-M algorithm performs the best followed by the UQ-N algorithm, GDAL algorithm, and the CBP algorithm. These computational results also reveal that the average percent deviation of the makespan from its best solution obtained by using the ANN trained with the L-M algorithm is the least among all examined approaches for the benchmark problem instances.
Computers & Industrial Engineering, 2019
Integrating preventive maintenance activities to the no-wait flow shop scheduling problem with de... more Integrating preventive maintenance activities to the no-wait flow shop scheduling problem with dependent-sequence setup times and makespan minimization,
Journal of International Technology and Information Management
Prior research has mostly focused on transaction cost economics (TCE) to interpret the effect of ... more Prior research has mostly focused on transaction cost economics (TCE) to interpret the effect of information systems (IS) on organizational governance structures. A TCE based approach predicts that information technology (IT) will lead to increased use of electronic markets to coordinate economic transactions from electronic hierarchies. However, there is contradictory evidence in the literature regarding the rise and importance of cooperative relationships, joint ventures, and value-added partnerships integrated through information systems. To reconcile these contradictions, this paper analyzes the effect of IT on governance structures based on the TCE, social network theory, and the resource based view (RBV) of the firm. The most important aspect of this paper is that instead of overemphasizing the economic perspective, as has been done in prior IS research, it pays equal attention to economic, social, and knowledge perspectives of the firm. By considering variables such as product demand uncertainty, human specificity, task complexity, and frequency of interaction, the effect of IT on governance structure has been analyzed. In this paper, we suggest that, in knowledge intensive companies, a greater degree of outsourcing will take place, not through markets as hypothesized by earlier researchers, but through an increasing number of social networks. This differentiation can not be understood in simple economic terms because social networks are not based on contracts. Therefore, we suggest that the integration of IT-enabled social networks with the TCE and RBV of the firm leads to a better understanding and improvement of decision-making and corporate governance structures in knowledge intensive firms.
Asia-Pacific Journal of Operational Research, 2019
This paper investigates the ability of a combined buy-back (BB) and revenue sharing (RS) contract... more This paper investigates the ability of a combined buy-back (BB) and revenue sharing (RS) contract to improve the efficiency of a supply chain involving a risk-neutral supplier and a risk-averse retailer facing stochastic demand. We show that the combined contract can coordinate the supply chain under mild conditions. Further, the effects of risk aversion and contract parameters on the agents’ decision-making are analyzed when the retailer’s risk aversion is modeled by the conditional value-at-risk (CVaR) criterion. In contrast to individual BB and RS contracts, the combined contract is able to mitigate the effect of risk-aversion and allow the supplier to obtain higher expected profit. Moreover, situations exist where the combined contract can coordinate the supply chain when neither the BB nor the RS contract can coordinate it. Numerical experiments conducted further confirm the analytical results derived.
Harnessing Social Media as a Knowledge Management Tool
Technical solutions to security have been suggested but found lacking and it has been recognized ... more Technical solutions to security have been suggested but found lacking and it has been recognized that security is a people issue as well, and behavioral research on information security is critical. Individual learning about cybersecurity is not formal and linear, but complex and network based. In this paper we develop a model of how social media characteristics impact cybersecurity knowledge transfer using technology threat avoidance theory. In developing the conceptual model we seek to answer the following questions. How do users discover cybersecurity knowledge on social media platforms? What are the platform and interaction characteristics that enable them to find cybersecurity knowledge and share this knowledge with others? In doing so we consider the impact of the threat and protection context on cybersecurity knowledge transfer which is different from knowledge transfer in the other contexts.
Business and information systems professionals continue to struggle to address the complex issues... more Business and information systems professionals continue to struggle to address the complex issues involved in determining payoffs from information technology (IT) investments in e-business environment. The business value returned by IT investments in E-business environment is being viewed with increasing skepticism by researchers and practitioners. Quantifying the IT investments payoff has always been subject to debate because measurements and real value delivered some time can not be expressed in typical IT metrics like response time and hardware utilization etc. Aligning IT measurements with the business measurements is critical to establishing the business value of IT investments. In this paper we suggest a framework that identifies not only the components where IT investment payoff could be measured for e-commerce initiatives but also provides a guidance about how and where to measures for business value from the perspective of management and endusers in e-business environment.
Handbook of Research on Information Security and Assurance
The purpose of the information security policy is to establish an organization-wide approach to p... more The purpose of the information security policy is to establish an organization-wide approach to prescribe mechanisms that help identify and prevent the compromise of information security and the misuse of organization's data, applications, networks, and computer systems to define mechanisms that protect the organization from its legal and ethical responsibilities with regard to its networks' and computer systems' connectivity to worldwide networks. Most of the organizations worldwide already have formulated their information security policies. Having a security policy document in itself is not enough, the document must be complete. This paper examines security policies of 20 different academic organizations with standard security policy framework and attempts to answer questions such as: are these security policy documents complete? Are they fully up to date? Does the precept match the practice? These are kind of questions that are addressed in this study.
Proceedings of the 2001 ACM symposium on Applied computing, 2001
This work investigates the use of neural networks to schedule flow shops with dynamic job arrival... more This work investigates the use of neural networks to schedule flow shops with dynamic job arrival. The objective of such scheduling is to determine both sequence and lot-sizes concurrently that minimize a makespan. We present a multi-neural network architecture for simultaneous lot-sizing and sequencing neural-network learning. Our experimental study shows that our multi-neural networks can learn both lot-sizing and sequencing decisions, and outperform a sequencing-only neural network.
Engineering Applications of Artificial Intelligence
Proceeding of Flexible Automation and Integrated Manufacturing 1994
International Journal of Production Research
Flexible Services and Manufacturing Journal
Renewable and Sustainable Energy Reviews
Journal of Parametrics, 1984
The number of evidences found in a digital crime scene has burgeoned significantly over the past ... more The number of evidences found in a digital crime scene has burgeoned significantly over the past few years. In addition, the demand for delivering accurate results within a given time deadline has increased. The major challenges coinciding with these aforementioned objectives are to investigate the right set of evidences and to allocate appropriate times for their investigation. In this paper, we present a mixed integer linear programming (MILP) model to analyze the problem of allocating optimal investigation times for evidences involving a single investigator. The objective is to maximize the overall effectiveness of a forensic investigation procedure. We particularly focus on the time critical digital forensic cases, in which results have to be finalized in a court of law within a specified time deadline. While the general problem is NP-hard, two special cases are illustrated to be optimally solvable in polynomially computational effort. Two heuristic algorithms are proposed to so...
Journal of Parametrics, 1985
Computers & Industrial Engineering, 2021
Journal of Parametrics, 1985
Journal of the Operational Research Society, 2019
For effective modelling of flowshop scheduling problems, artificial neural networks (ANNs), due t... more For effective modelling of flowshop scheduling problems, artificial neural networks (ANNs), due to their robustness, parallelism and predictive ability have been successfully used by researchers. These studies reveal that the ANNs trained with conventional back propagation (CBP) algorithm utilising the gradient descent method are commonly applied to model and solve flowshop scheduling problems. However, the existing scheduling literature has not explored the suitability of some improved neural network training algorithms, such as gradient descent with adaptive learning (GDAL), Boyden, Fletcher, Goldfarb and Shanno updated Quasi-Newton (UQ-N), and Levenberg-Marquardt (L-M) algorithms to solve the flowshop scheduling problem. In this article, we investigate the use of these training algorithms as competitive neural network learning tools to minimise makepsan in a flowshop. Based on training and testing measures, overall results from extensive computational experiments demonstrate that, in terms of the solution quality and computational effort required, the L-M algorithm performs the best followed by the UQ-N algorithm, GDAL algorithm, and the CBP algorithm. These computational results also reveal that the average percent deviation of the makespan from its best solution obtained by using the ANN trained with the L-M algorithm is the least among all examined approaches for the benchmark problem instances.
Computers & Industrial Engineering, 2019
Integrating preventive maintenance activities to the no-wait flow shop scheduling problem with de... more Integrating preventive maintenance activities to the no-wait flow shop scheduling problem with dependent-sequence setup times and makespan minimization,