R. P. Sundarraj

Hub location at Digital Equipment Corporation: A comprehensive analysis of qualitative and quantitative factors

Abstract The economic growth of countries in the Asia–Pacific (AP) region has caused many US-based businesses to consider the strategic initiative of setting up facilities therein. In this paper, we describe a study to locate a repair-parts warehouse for Digital Equipment Corporation, a world leader in the computer and electronics market. Digitals management was charged to consider not only the long-term strategic (or qualitative) issues typical of such problems, but they also had to ensure that any facility that is located would also be viable from a freight-cost (or quantitative) perspective. We show how the analytical network process (ANP) model combined with an optimization model can be used to conduct a comprehensive evaluation of these varied issues.

Evaluation of enterprise information technologies: a decision model for high-level consideration of strategic and operational issues

Despite the possibility of short-term financial losses and concerns by executive management of potential failure, enterprise information technologies (EITs) are being implemented by a growing number of Fortune 100 and midsize corporations in the hope of acquiring long-term benefits. EITs, expensive and risky information technology assets, must be evaluated on the basis of both their productivity gains and their support for corporate reengineering through integration of business processes. In this paper, we propose a two-stage methodology (involving a combination of the analytical network process and integer programming) to conduct a high-level evaluation of an interdependent set of tangible, intangible, strategic and operational factors that should be considered in EIT evaluation. We perform sensitivity analyses and conduct tests with real-world data to show the robustness of our methodology and the resulting managerial implications.

Using information-systems constructs to study online- and telephone-banking technologies

The research literature has seen a number of studies aimed at understanding customer attitudes towards banking technologies, and thereby providing implications for developmental planning and marketing. However, even though banking technologies have a significant amount of information systems (IS) component to them, there is a paucity of research that considers them from the IS perspective. In this paper, we fill this gap by considering three constructs, namely usefulness, ease of use and usage, that are all rooted in the IS literature. We study users perceptions of these constructs, as well as the relationships among them, for both online and telephone banking.

A decision model for strategic evaluation of enterprise information technologies

Abstract Enterprise information technologies (EITs), which are strategic systems seeking to integrate the processes and databases of the entire organization and beyond, require a significant investment of money and human resources in return for the promise of a global business model and its associated far-reaching benefits. Their evaluation/justification must be completed with organizational goals and requirements included in the decision, or the organization could lose financially and competitively. Besides traditional financial models, e.g., ROI (return on investment), that are primarily meant for short-term financial justification purposes, there is a paucity of methods for the evaluation of the strategic and intangible costs and benefits that EITs afford organizations as a whole. This article introduces the use of a robust quantitative technique called the analytical hierarchy process (AHP) that can integrate a diverse range of factors (strategic and operational, and tangible and intangible) into one model. the approach can be easily understood by managers and analysts and has a history of application to other types of strategic justification decisions.

A multi-period optimization model for the procurement of component-based enterprise information technologies

Abstract Today, timely sharing and coordination of information across the supply chain are key factors to improving the performance of an organization. Although single-vendor enterprise information technologies (EITs) are seen as enablers for accomplishing this goal, a number of organizations are concerned about the high cost and time involved in such a solution. An alternative new paradigm has emerged in the form of componentized EITs, which are stand-alone software components that can be easily integrated with one other, and which provide the advantages of easing cash-flow problems and of decreasing customization times. Research in the evaluation of componentized EITs lacks objective assessment tools that simultaneously consider both procurement and inter-component integration issues. This paper fills this gap by proposing a multi-period integer-programming model to assist decision-makers in the procurement of componentized EITs. We consider component costs as well as inter-component integration costs over a given planning horizon and provide managerial insights based on different experiments with the model.

Evaluating Componentized Enterprise Information Technologies: A Multiattribute Modeling Approach

Corporations are increasingly implementing enterprise information technologies (EITs), because of the costs of maintaining legacy systems and the lack of fit of such systems for organization-wide information sharing. A new type of EIT that is being introduced in major corporations (such as Dell Computers), is based on the idea of component systems, which are stand-alone software programs that can integrate with other such components with relative ease. Given the financial outlay for EITs, the evaluation and adoption of these systems is not something that can be completed haphazardly. This requirement is complicated by the relative infancy of models for the evaluation of componentized EITs. To this end, in this paper, we introduce a managerial multistage multiattribute decision model, consisting of the Analytical Hierarchy Process (AHP) model and the Supermatrix approach (also defined as the Analytical Network Processes (ANP) approach). This combination of models builds on earlier work that validates the Supermatrix approach for evaluating traditional EITs at a Fortune 100 organization. The aggregation of these benefits is then measured against the costs of systems, thereby arriving at a ranking of alternatives for each functional area. We illustrate the model with an example and draw managerial implications.

Learning algorithms for single-instance electronic negotiations using the time-dependent behavioral tactic

Negotiator often rely on learning an opponents behavior and on then using the knowledge gained to arrive at a better deal. However, in an electronic negotiation setting in which the parties involved are often unknown to (and therefore lack information about) each other, this learning has to be accomplished with only the bid offers submitted during an ongoing negotiation. In this article, we consider such a scenario and develop learning algorithms for electronic agents that use a common negotiation tactic, namely, the time-dependent tactic (TDT), in which the values of the negotiating issues are dependent on the time elapsed in the negotiation. Learning algorithms for this tactic have not been proposed in the literature. Our approach is based on using the derivatives of the Taylors series approximation of the TDT function in a three-phase algorithm that enumerates over a partial discretized version of the solution space. Computational results with our algorithms are encouraging.

Application of an Extended TAM Model for Online Banking Adoption: A Study at a Gulf-region University

The understanding of factors leading to the acceptance or rejection of information systems IS is important and relevant. Although there have been studies examining the adoption of Internet Banking IB, research on this topic in the Gulf context and from an IS perspective is lacking, even though societal factors are acknowledged as having an impact on technology adoption. To fill this gap, this paper uses a version of the Technology Acceptance Model TAM, extended by the compatibility and trust constructs. An empirical study, using students from a large university in the region, validates the research model.

Decisions, Models and Opportunities in Cloud Computing Economics: A Review of Research on Pricing and Markets

Cloud computing has emerged as a key information technology and systems model over the last few years. Major organizations have developed and delivered cloud computing solutions and continue to do so. Consequently, a number of strides were made in the advancement of technology leading to a growth in the adoption of cloud computing. The growing recognition of cloud computing services necessitates a focus on the business aspects of cloud. However, we feel that research in this area is scant. To this effect, we performed a systematic review of cloud computing literature and reviewed 2891 abstracts and 157 articles published until the year 2012. Based on the findings of the review, we establish a framework for organising the extant research on cloud business aspects. Using the framework, we find cloud economics to be the most widely researched business aspect. In this paper, we provide a detailed review of the application of decision models in the context of cloud economics, with a specific focus on pricing and markets. The proposed framework and review results serve as a reference to IS researchers and practitioners to understand decision situations, models and opportunities.

Strategic Bidding for Cloud Resources under Dynamic Pricing Schemes

Cloud computing offers computing and storage services which can be dynamically developed, composed and deployed on virtualized infrastructure. Cloud providers holding excess spare capacity, incentivize customers to purchase it by selling them in a market (spot market), where the prices are derived dynamically based on supply and demand. The cloud providers allow clients to bid on this excess capacity by allocating resources to bidders while their bids exceed a intermittently changing dynamic spot price. In this paper we have used game theory to model the bidding strategies of bidders in a spot market who are attempting to procure the cloud instances, as a prisoner dilemma game. We then analyze real time data from Amazon EC2 spot market to validate this model. In a single shot prisoner dilemma game mutual defection is the Nash equilibrium. We find that a majority (approx. 85%) of bidders choose to Defect which is in-line with the single shot classical prisoner dilemma game. However considering that most bidders in a spot market are repetitive bidders, we propose a Co-operation strategy which is in-line with the Iterated Prisoner Dilemma Game.