R P Sundarraj

Investing in cloud computing technology is one of the latest trends in IT. This is a multi criteria investment decision involving many stakeholders and a sequence of coordinated assessment activities that are strategic, qualitative (technical) and quantitative (financial) in nature. This paper integrates an information system (IS) success model with preference elicitation techniques drawn from the multi-criteria decision-making literature. We also show how this decision model can be extended as a vendor negotiation tool. Finally, we describe a prototype Decision Support System (DSS) featuring this model.

The role of anger in negotiation is explored in considerable depth in many papers in the literature. In the electronic negotiation situation, one way to express anger (in addition to plain textual messages) is through the use of emoticons and para-linguistic cues. Cue usage by angry negotiators under different levels of anger is unexplored in negotiation literature. In this paper, we address this gap by conducting a distributive electronic negotiation experiment and studying the usage of cues (statements and para-linguistic cues including emoticons) by angry negotiators while interacting with their counterpart (computer). We report that participants tend use more para-cues, especially emoticons, as their anger intensity increases and that emoticons have the ability to replace other para-cues while composing angry messages. The findings provide promising inputs on design of user interfaces for electronic negotiation systems.

Electronic Procurement Systems (EPS) are being acknowledged by researchers as promising technological enablers for achieving a responsive supply chain, and thereby, for gaining a competitive advantage in today’s global marketplace. A number of empirical studies have focused on the adoption of EPS in different countries. There is, however, a scarcity of work related to EPS adoption in India, even though information technology and the Internet play a significant role in that country. To fill this gap, we first discuss the potential supply chain benefits of EPS, especially as they relate to large multinational companies. Then, we specifically consider the Indian context. We highlight several firms whose innovative logistics operations permit the respective supply chains to function, uniquely blending Indian customs with modern business practices.We report on an empirical survey, as well as three case-studies relating to the importance and impact of EPS adoption in India.

Healthcare organizations (HCO) adopt emerging technology solutions such as Healthcare Analytics (HA) to improve the quality and efficiency of their operations, patient care, and clinical decisions. While their intent is to adopt HA, many of them are unsure of their organizational readiness for that adoption. There is a paucity of research on HA pre-adoption readiness assessment techniques and tools, which can be leveraged by hospitals, to make well-informed decisions. In this paper, we fill this gap, by proposing a prototype design of an instrument based on the design science approach. We base the constructs used in our artifact on our findings from the multi-case study analysis of three hospitals, which we also discuss briefly. The key contribution of this research is the process that we followed in integrating the case study approach with DSRM in the area of HA adoption.

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. © Springer International Publishing Switzerland 2014.

In electronic negotiations, buyers and sellers are represented by negotiating agents and it becomes imperative for the negotiating agents to acquire user's preferences to be able to negotiate better. In this paper we present the design of a web based engine to capture a buyer's choices over time through a preference elicitation tool known as Time - Tradeoff sequence(TTO Sequence). Preferences thus elicited are used by buyer's electronic agents to negotiate price and date of movie tickets with cineplex owners. Further, we illustrate with an example that negotiation outcome is affected by the timepreference of the buyer. © Springer International Publishing Switzerland 2014.

The adoption of analytics solutions in hospitals is a recent trend aimed at fact-based decision making and data-driven performance management. However, the adoption of analytics involves diverse stakeholder perspectives. Currently, there is a paucity of studies that focus on how the practitioners assess their organizational readiness for health analytics (HA) and make informed decisions on technology adoption given a set of alternatives. We fill this gap with our study by designing a strategic assessment framework guided by a DSRM approach that iteratively extends our past artifact. Our approach first entails the use of many in-depth case-studies, as well as embedded experts from the industry to inform the objective setting and design process. These inputs are then supported by two multi-criteria decision-making methods. We also evaluate our framework with healthcare practitioners for both design validity and future iterations of this project. Implications of our work for theory of design and action are also highlighted.

This work aims at creating a user recommender system that recommends relevant people to follow for twitter users. We propose to use a novel topic modeling method Biterm Topic Model (BTM) to profile users into vectors of bag of words. We then propose an algorithm that uses both social network relationship information and the user-generated content modeled through BTM to recommend twitter followees. A preliminary evaluation is carried out on the implementation of this technique that shows BTM performs well in making valid recommendations to twitter users. We also found that considering both user generated content and social relationships for recommending followees helped improve the results.