DSS Value and Time-Constrained Decision Making

This paper examines an important source of the value of decision support systems (DSS), namely, decision flexibility. It proposes a framework for systematically analyzing, understanding, and possibly quantifying flexibility resulting from the use of DSS in decision situations with time constraints, based on real options theory. The proposed framework is compared with anecdotal evidence of DSS value from the MIS literature. This framework has interesting implications for DSS developmen

A Framework for Managing Flexibility in the Information Systems Function

Competitive pressures are forcing organizations to be agile and flexible. Response to changing environmental conditions is an important factor in determining corporate performance. Organizational flexibility is in turn closely related to the management of information systems. Organizations with flexible IS functions are in a position to be more responsive and take advantage of changes in both their internal and external environments. Conversely, inflexibility in IS can inhibit organizational growth and put a company in a competitive disadvantage. This paper argues that IS flexibility is a multidimensional concept. Grounded theory methodology is used to empirically derive a taxonomy of several types of flexibility and flexibility management strategies

Investigating Determinants of Project Portfolio Management Adoption

Recently, there has been an emphasis on managing projects strategically within the organization using project portfolio management (PPM). However, the extent of adoption of this innovation and the enabling factors are not well understood in academics and practice. This research-inprogress investigates a model of PPM adoption using data being collected from project managers. The model identifies a total of nine variables capturing various environmental, PPM, and organizational factors that could potentially impact the adoption decision of PPM. The survey is hosted on the Project Management Institute’s (PMI) website in order to collect data from PMI members worldwide. The data will be analyzed using logistic regression to identify the factors that have a significant impact on PPM adoption. This research is part of a larger multi-method research of PPM adoption and infusion and the results of this research will help practitioners and researchers better understand factors that impact PPM adoption decisions

An Effective Deep Learning Based Multi-Class Classification of DoS and DDoS Attack Detection

In the past few years, cybersecurity is becoming very important due to the rise in internet users. The internet attacks such as Denial of service (DoS) and Distributed Denial of Service (DDoS) attacks severely harm a website or server and make them unavailable to other users. Network Monitoring and control systems have found it challenging to identify the many classes of DoS and DDoS attacks since each operates uniquely. Hence a powerful technique is required for attack detection. Traditional machine learning techniques are inefficient in handling extensive network data and cannot extract high-level features for attack detection. Therefore, an effective deep learning-based intrusion detection system is developed in this paper for DoS and DDoS attack classification. This model includes various phases and starts with the Deep Convolutional Generative Adversarial Networks (DCGAN) based technique to address the class imbalance issue in the dataset. Then a deep learning algorithm based on ResNet-50 extracts the critical features for each class in the dataset. After that, an optimized AlexNet-based classifier is implemented for detecting the attacks separately, and the essential parameters of the classifier are optimized using the Atom search optimization algorithm. The proposed approach was evaluated on benchmark datasets, CCIDS2019 and UNSW-NB15, using key classification metrics and achieved 99.37% accuracy for the UNSW-NB15 dataset and 99.33% for the CICIDS2019 dataset. The investigational results demonstrate that the suggested approach performs superior to other competitive techniques in identifying DoS and DDoS attacks

Diffusion Dynamics of Open-Source Software in the Presence of Upgrades: An Agent-Based Computational Economics (ACE) Approach

Researchers have identified numerous factors that impact the diffusion of open source software (OSS). This paper proposes an integrated model that studies how key factors affect the diffusion dynamics of OSS. Specifically, we investigate the role of software upgrade cycle in the diffusion of OSS. We also incorporate factors such as variability in OSS support costs, interoperability issues and network structure that have not been systematically studied in prior OSS research. Our results demonstrate interesting effects of these factors on diffusion dynamics of OSS. Variability of OSS support costs, length of upgrade cycle and interoperability costs are identified as major determinants of OSS diffusion. The results illustrate that a proprietary software (PS) vendor should consider several other strategic variables besides price such as interoperability costs and upgrade cycle that affect OSS diffusion. The proposed model can be used as a building block to model competitive dynamics in software markets

Retinopathy of prematurity: incidence and risk factors: a hospital based study from Shimla, Himachal Pradesh, India

Background: The blindness due to retinopathy of prematurity (ROP) is avoidable, if it is detected in time by screening. With increasing survival of preterm and low birth weight newborns in neonatal units, who are on prolonged oxygen therapy and mechanical ventilation; ROP is bound to affect these babies. This study was planned to investigate the incidence and the risk factors of ROP in a tertiary care institute in Himalayan region of north India.Methods: This was a hospital based prospective study, conducted at neonatal intensive care units at IGMC, Shimla, from June 2011 to July 2012. 64 premature and low birth weight neonates born or admitted for neonatal intensive care unit (NICU) were screened for ROP using indirect ophthalmoscope. Cases found positive for ROP were closely followed up and managed as per international guidelines.Results: Out of 64 neonates, 14 were lost to follow up and 50 babies were enrolled in the study. Out of them 21 were males and 29 were females. Among them 3 male and 5 female newborns developed ROP. Mean gestational age of babies with ROP was 30.63 weeks. ROP was significantly associated with oxygen administration (p=0.027), RDS (p=0.003), septicaemia (p=0.028) and exchange transfusion (p=0.003). Apneic spells, surfactant administration, hyperbilirubinemia, phototherapy, blood transfusion and maternal factors were not associated with increased risk of ROP.Conclusions: For premature infants with birth weight less than 1200 grams, who has received prolonged oxygen therapy, associated respiratory distress and had received exchange transfusion the screening of ROP should be done at most appropriate time that is 32 - 40 weeks of gestational age. Timely referral of detected ROP cases for early treatment prevents blindness. There is a need for the obstetricians, neonatologist and ophthalmologist to work in close co-operation to prevent blindness due to ROP

Parameterizing the modified water cloud model to improve soil moisture data retrieval using vegetation models

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Understanding the Information Technology Growth Options: Effects of Gender and Experience on Option Exercise Decisions

To account for managerial decision flexibility in risky IT investments, Real Option Valuation (ROV) has been advocated. ROV formalizes managers’ intuition, thus creating a disciplined decision making process. However, evidence suggests that ROV is usually utilized intuitively by professionals, in the form of “Real Option Thinking”, and is subject to various judgmental biases. We focus on growth options for this study. Prior research has shown that, while valuing projects with real options, managers ascribe the greatest importance to projects with growth options. Similar results hold for IT projects, where IT managers perceive a growth option as adding more value to the project. This perception of growth options might suggest their vulnerability to the IT managers’ risk preferences, through Prospect Theory. By conducting a survey-based experiment among 150 IT professionals, our results indicate that gender and experience impact biases in growth option exercise decisions significantly, depending on project size. However, we also observe some exceptions

Examining Real Options Exercise Decisions in Information Technology Investments

Researchers have advocated real options thinking (ROT) for evaluating and managing risky IT investments to account for managerial decision flexibility. Effective ROT is a three-step process that requires managers to recognize, value, and exercise options embedded in IT projects. Prior research has illustrated the existence of managerial bias in the recognizing and valuing real options. However, little research has examined real options exercise decisions. Hence, we use prospect theory to examine whether IT managers demonstrate systematic biases while exercising real options in IT projects and portfolios. We also study whether one can control or mitigate such biases. We found evidence of biased (suboptimal) real option exercise decisions in IT projects and in IT portfolios. However, we found differences in biased decision making between a single project and a portfolio scenario. We also found that project scale and real option type influenced vulnerability of a project to biased decision making. In addition, simplifying the presentation of the net effects of real options exercise decisions can help reduce bias, especially for large project portfolios. We discuss the implications of these results on theory and practice