Impacts of Firm Performance on Business Intelligence and Analytics Engagement Strategies

IT innovation is key to firms’ competitive advantage, even survival. We investigated the diffusion of Business Intelligence and Analytics (BI&A) from a performance feedback perspective, a novel perspective on IT innovation diffusion. Drawing on the behavioral theory of the firm (BTOF) and institutionalization literature, we examined how relative performance shortfalls (performance shortfalls relative to their aspirations in terms of shortfalls from their historical performance and shortfalls with respect to comparison firms) affect firms’ BI&A engagement strategies over time. We also examined potential decoupling of firms’ informational (talk about) and material (actual use) engagement with BI&A across early and late diffusion stages. Using a longitudinal sample of 3,311 firm-year observations between 2010 and 2015, we found social aspiration gaps do not exert significantly higher positive impacts on firms’ BI&A engagement than do historical aspirations. Contrary to our prediction that informational engagement with BI&A responds more to social aspiration gaps than material engagement, we found that material engagement with BI&A was influenced more by these gaps than was informational engagement. Last, we observed these relationships to be stronger at early BI&A than at later BI&A diffusion stages

An infrastructure service recommendation system for cloud applications with real-time QoS requirement constraints

The proliferation of cloud computing has revolutionized the hosting and delivery of Internet-based application services. However, with the constant launch of new cloud services and capabilities almost every month by both big (e.g., Amazon Web Service and Microsoft Azure) and small companies (e.g., Rackspace and Ninefold), decision makers (e.g., application developers and chief information officers) are likely to be overwhelmed by choices available. The decision-making problem is further complicated due to heterogeneous service configurations and application provisioning QoS constraints. To address this hard challenge, in our previous work, we developed a semiautomated, extensible, and ontology-based approach to infrastructure service discovery and selection only based on design-time constraints (e.g., the renting cost, the data center location, the service feature, etc.). In this paper, we extend our approach to include the real-time (run-time) QoS (the end-to-end message latency and the end-to-end message throughput) in the decision-making process. The hosting of next-generation applications in the domain of online interactive gaming, large-scale sensor analytics, and real-time mobile applications on cloud services necessitates the optimization of such real-time QoS constraints for meeting service-level agreements. To this end, we present a real-time QoS-aware multicriteria decision-making technique that builds over the well-known analytic hierarchy process method. The proposed technique is applicable to selecting Infrastructure as a Service (IaaS) cloud offers, and it allows users to define multiple design-time and real-time QoS constraints or requirements. These requirements are then matched against our knowledge base to compute the possible best fit combinations of cloud services at the IaaS layer. We conducted extensive experiments to prove the feasibility of our approach

City Data Fusion: Sensor Data Fusion in the Internet of Things

Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. We introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. We then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. Our main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.Comment: Accepted to be published in International Journal of Distributed Systems and Technologies (IJDST), 201

Towards a Classification of the Effects of Disorder on Materials Properties

Many 'interesting; correlated electron materials exhibit an unusual sensitivity of measured properties to external perturbations, and in particular to imperfections in the sample being measured. It is argued that in addition to its inconvenience, this sensitivity may indicated potentially useful properties. A partial classification of causes of such sensitivity is given.Comment: Solid State Communications, in press (Proceedings of the June 2002 Williamsburg conference on Muon Spin Rotation

A Study of Social Chatbots Affordances Mitigating Loneliness

Loneliness is a significant concern and is linked to negative health outcomes such as depression and anxiety. Chatbots are gaining attention as potential companions to militate against loneliness. However, IS studies on the effects of human-AI relationships on mental wellness are limited, leaving unclear what enables humans to find companionship and intimate relationships with chatbots, and under what conditions human-chatbot interaction can alleviate loneliness. This study aims to develop a model of how chatbots alleviate loneliness and test it using a longitudinal study. Specifically, this research argues that shared identity affordance and social support affordance help mitigate loneliness directly and indirectly through enhanced intimacy feeling. The effects of chatbots’ affordances on loneliness and intimacy depend on users’ emotion regulation beliefs. Upon successful completion, this research has the potential to offer insight into the design of chatbots and how to leverage AI for social good

Influence of spin fluctuations near the Mott transition: a DMFT study

Dynamics of magnetic moments near the Mott metal-insulator transition is investigated by a combined slave-rotor and Dynamical Mean-Field Theory solution of the Hubbard model with additional fully-frustrated random Heisenberg couplings. In the paramagnetic Mott state, the spinon decomposition allows to generate a Sachdev-Ye spin liquid in place of the collection of independent local moments that typically occurs in the absence of magnetic correlations. Cooling down into the spin-liquid phase, the onset of deviations from pure Curie behavior in the spin susceptibility is found to be correlated to the temperature scale at which the Mott transition lines experience a marked bending. We also demonstrate a weakening of the effective exchange energy upon approaching the Mott boundary from the Heisenberg limit, due to quantum fluctuations associated to zero and doubly occupied sites.Comment: 6 pages, 3 figures. V3 was largely expande

Whose Talk is Walked? IT Decentralizability, Vendor versus Adopter Discourse, and the Diffusion of Social Media versus Big Data

Discourse plays a central role in organizing vision and computerization movement perspectives on IT innovation diffusion. While we know that different actors within a community contribute to the discourse, we know relatively little about the roles different actors play in diffusing different types of IT innovations. Our study investigates vendor versus adopter roles in social media and big data diffusion. We conceptualize the difference between the two IT innovations in terms of their decentralizability, i.e., extent to which decision rights pertinent to adoption of an organizational innovation can be decentralized. Based on this concept, we hypothesized: (1) adopters would contribute more to discourse about the more decentralizable social media and influence its diffusion more than would vendors; (2) vendors would contribute more to discourse about the less decentralizable big data and influence its diffusion more than would adopters. Empirical evidence largely supported these hypotheses

Direct absorption imaging of ultracold polar molecules

We demonstrate a scheme for direct absorption imaging of an ultracold ground-state polar molecular gas near quantum degeneracy. A challenge in imaging molecules is the lack of closed optical cycling transitions. Our technique relies on photon shot-noise limited absorption imaging on a strong bound-bound molecular transition. We present a systematic characterization of this imaging technique. Using this technique combined with time-of-flight (TOF) expansion, we demonstrate the capability to determine momentum and spatial distributions for the molecular gas. We anticipate that this imaging technique will be a powerful tool for studying molecular quantum gases.Comment: 4 pages, 4 figure