An Introduction to the MISD Technology

2017 | HICSS | Citations: 0

Authors: Popov, Aleksey

Abstract: The growth of data volume, velocity, and variety will be the global IT challenge ... Expand

Abstract: The growth of data volume, velocity, and variety will be the global IT challenges in the next decade. To overcome performance limits, the most effective innovations such as cognitive computing, GPU, FPGA acceleration, and heterogeneous computing have to be integrated with the traditional microprocessor technology. As the fundamental part of most computational challenges, the discrete mathematics should be supported both by the computer hardware and software. But for now, the optimization methods on graphs and big data sets are generally based on software technology, while hardware support is promising to give a better result. Collapse

Topics: computer hardware enterprise architecture big data IT productivity productivity

Methods: computational algorithm experiment discrete optimization optimization model

Trasactive Memory Systems Virtual Team Training Model

2012 | Americas Conference on Information Systems | Citations: 0

Authors: Hixson, Katharine; Paul, Souren

Abstract: The use of teams, especially virtual teams, is growing significantly in corporat ... Expand

Abstract: The use of teams, especially virtual teams, is growing significantly in corporations, branches of the government and nonprofit organizations. However, despite this prevalence, little is understood in terms of how to best train these teams for optimal performance. Team training is commonly cited as a factor for increasing team performance, yet, team training is often applied in a haphazard and brash manner, if it is even applied at all. Therefore, this paper attempts to identify the flow of a training model for virtual teams. Rooted in transactive memory systems, this theoretical model combines the science of encoding, storing and retrieving information with the science of team training. Collapse

Topics: virtual teamwork team productivity computer architecture

Methods: experiment theory development

Theories: theory of shared mental models

A model for a web-based learning system

2007 | Information Systems Frontiers | Citations: 0

Authors: Carchiolo, Vincenza; Longheu, Alessandro; Malgeri, Michele; Mangioni, Giuseppe

Abstract: The dissemination of knowledge is currently being improved by e-learning, which ... Expand

Abstract: The dissemination of knowledge is currently being improved by e-learning, which consists of a combination of teaching methodologies and computer-based tools. Recently e-learning environments have started to exploit web technology to provide a simple, flexible, distributed and open platform. In this paper we propose a model for an e-learning system, aiming at sharing both course contents and teaching materials, in order to provide students with a single and uniform set of concepts to be learned, and promoting active learning by allowing the construction of courses which are personalized in terms of both contents and teaching materials, selected according to each student’s needs and capabilities. A first, open-source prototype based on the proposed model has been implemented to validate the model. Collapse

Topics: online learning system database system open source programming language personalization

Methods: design artifact

Theories: fuzzy set theory cognitive apprenticeship theory

The Role of Modeling and Asynchronous Distributed Simulation in Analyzing Complex Systems of the Future

2002 | Information Systems Frontiers | Citations: 0

Authors: Ghosh, Sumit

Abstract: The word simulate implies to imitate or to mimic while the word modeling refers ... Expand

Abstract: The word simulate implies to imitate or to mimic while the word modeling refers to a small object, usually built to scale, that represents some existing object. Although the art of mimicking and modeling may be traced back to the beginning of civilization, with the emergence of computers, a few decades ago, the art of modeling and simulation experienced a remarkable transformation. The computational intelligence of the computer imparted the ability to encapsulate and simulate specific characteristics of not only living and inanimate objects but abstract concepts. While the human brain is equally capable of simulating abstract concepts, the precision and speed of the computers are unparalleled and they impart computer modeling and simulation a qualitative jump in its capability and fidelity. Also, while intimately connected to each other, modeling refers to the notion of representing the desired behavior of the target object or idea in the host computer and simulation refers to the execution of the model on a host computer. Today, towards the end of the twentieth century, the nature of modeling and simulation is undergoing another radical transformation. The emergence of economical and powerful computers coupled with the ability to network a large number of computers, promises the ability to model and simulate complex, real-world systems, that are rapidly becoming commonplace in the society, successfully and with a high degree of fidelity. Already, today's real-world systems including complex banking, credit-card transaction, transportation, ground-based communication, and space-based tele-communication systems defy the analytical modeling that had characterized the efforts over the past three decades. Virtually all analytical studies are severely restricted in the number of variables and the number of interacting units that may be modeled. Tomorrow's systems are expected to be far more complex, implying that modeling and large-scale simulation may be the most logical and, often, the only vehicle to study them objectively. This paper presents a fundamental analysis of the nature of complex physical and natural processes that will increasingly constitute the challenging problems of the future. It then develops a set of principles for modeling complex systems. Finally, it examines the role of asynchronous, distributed simulation in the study of a number of real-world systems. In general, modeling and simulation enables one to detect design errors, prior to developing a prototype, in a cost effective manner, identify potential problems during system operation, detect rare and elusive errors, and investigate hypothetical concepts that do not exist in nature. Upon execution, the simulation provides greater quantitative and qualitative insight into the behavior of the actual system. In addition, an asynchronous, distributed simulation, executing on a loosely-coupled parallel processor, closely resembles the actual, operational system, yielding results that potentially reflect reality, as close as possible. Furthermore, elements of the simulation code that emulate the system behavior may be transferred directly onto the operational system with minimal modifications. The knowledge encapsulated in this paper, has been derived from a number of actual case studies involving the modeling and simulation of a number of real-world problems. Collapse

Topics: systems operations operational information system computer hardware computer architecture

Methods: simulation case study design principle

Effective Knowledge Management: Knowledge, Thinking and the Personal—Corporate Knowledge Nexus Problem

2001 | Information Systems Frontiers | Citations: 0

Authors: Benson, Steve; Standing, Craig

Abstract: We argue that the intimate relationship between computer architecture and softwa ... Expand

Abstract: We argue that the intimate relationship between computer architecture and software has produced a professional mindset that is unsuited to the newer, knowledge-based business paradigms. Major software projects are ending in failure or do not yield their maximum potential and we suggest reasons why this is the case. In conclusion, we propose that Management Information Systems Curricula need to be revised to provide students with exposure to and practice in a variety of thinking styles. Organisations must change their structures and management styles if they are serious about managing knowledge. In making our case we briefly review the development of information systems as a discipline and the role of methodologies in the articulation of its paradigm. We end our paper with suggestions for future research. Collapse

Topics: knowledge management organizational memory problem solving spreadsheet organization learning

Methods: qualitative interview pilot survey case study capability maturity model design science

Theories: actor network theory semiotic theory

A Study of Senior Information Systems Managers' Decision Models in Adopting New Computing Architectures

2000 | Journal of the Association for Information Systems | Citations: 9

Authors: Bajaj, Akhilesh

Abstract: There has been considerable interest recently in the promise of new computing a ... Expand

Abstract: There has been considerable interest recently in the promise of new computing architectures such as the diskless computing architecture, which runs applications off a network. In previous theoretical work on Information Systems (IS) adoption, the question of whether classical diffusion variables determine the organizational adoption of IS with low knowledge barriers and low user interdependencies is still unresolved. In the practitioner literature, the discussion on new architectures has focused mainly on the costs of ownership of the architectures.This work proposes a novel methodology for IS adoption studies, using conjoint analysis. Issues such as data collection, data analysis, selecting scales and levels of predictor variables, construct validity, formulating testable hypotheses, and Journal of the Association for Information Systems 2 selecting an appropriate sample size are all discussed. As an example study, factors important to senior IS managers when deciding to adopt a computing architecture for their organization are identified and operationalized. Using conjoint analysis, the relative importance of these factors is measured as well as whether or not the effect of levels of these factors on decision-making is linear.The findings show that technology factors, which are a subset of classical diffusion variables, are sufficient to explain the adoption of computing architectures, which are a type of IS innovation with low impact on organizational processes and low knowledge barriers for end-users. The software quality associated with an architecture is the most important factor considered by IS managers and its effect is linear. The effect of the cost factor is less important, non-linear, and in some cases, unexpected. The effects of centralization, backward compatibility with the organization, and acceptance by third parties are all linear, but less important than software quality.Keywords: Senior IS managers, organizational adoption of IS, technology factors, conjoint analysis, software quality. 5. Select random samples of subjects from population. 6. Administer the study to the subjects. 7. Analyze data, test hypotheses, and present results. Figure D1. List of Steps that Constitute a CA Study Collapse

Topics: IT manager system quality database system digital innovation computer hardware

Methods: qualitative interview statistical hypothesis test conjoint analysis descriptive statistic survey

Theories: information systems theory diffusion of innovations theory

Training to improve virtual team communication

1999 | Information Systems Journal | Citations: 41

Authors: Warkentin, Merrill; Beranek, Peggy M.

Abstract: Abstract. Organizations are utilizing virtual teams, comprising workgroup member ... Expand

Abstract: Abstract. Organizations are utilizing virtual teams, comprising workgroup members who communicate and collaborate with technology, to accomplish tasks. These teams are geographically distributed and communicate via computer-mediated communication systems (CMCS), and may never or rarely meet face-to-face. Relational links among team members have been found to be a significant contributor to the effectiveness of information exchange in the use of CMCS. In most cases, team members receive little or no training to improve the effectiveness of this form of communication. When training is used, it often focuses on software utilization skills, not on interpersonal communication dynamics. This paper discusses the effect of virtual team communication training on group interactions, especially for enhancing these relational links and thereby improving communication and information exchange in virtual teams. It was found that teams that were given appropriate training exhibited improved perceptions of the interaction process over time, specifically with regard to trust, commitment and frank expression between members. Discussion of the role of training on virtual team processes and outcomes is discussed and future research implications are presented. Collapse

Topics: virtual teamwork IT enabled teamwork computer architecture information exchange world wide web

Methods: survey parametric test repeated measures ANOVA personal interview

An Object-Based Infrastructure for IRM

1998 | Information Systems Management | Citations: 0

Authors: Huarng, Adam S.; Krovi, Ravi

Abstract: Information resource management has lost some of its popularity – a victim of th ... Expand

Abstract: Information resource management has lost some of its popularity – a victim of the increasing complexity of both information technology and the models needed to represent it. An object-oriented approach is able to organize the complexity of an information resource management system while retaining an illusion of simplicity with practical benefits for managing information resource consumption, costs, and needs. Collapse

Topics: enterprise information system accounting database system computer architecture

An Applied Framework for Classifying the Complexity of Knowledge-Based Systems

1991 | Management Information Systems Quarterly | Citations: 0

Authors: Meyer, Marc; Curley, Kathleen

Abstract: The development and use of knowledge-based (expert) systems has grown dramatica ... Expand

Abstract: The development and use of knowledge-based (expert) systems has grown dramatically across a broad range of industries. Yet despite its growing importance, the study of expert systems lacks a cohesive framework for differentiating and comparing expert systems initiatives across different applications and in different industrial settings. The problem for IS managers is that a system that works in one situation may not be appropriate for another. This article presents a classification methodology for the systematic evaluation of a broad range of expert systems. Of primary concem in this study is the measurement of the complexity of such systems. Complexity in the area of expert systems consists of two basic dimensions. The first dimension is the complexity of the underlying knowledge residing with the key experts. The second dimension of the framework focuses on the complexity of the technology incorporated into a given system. This framework is then applied to a sample of 50 successfully developed knowledge-based systems. The resuits can be used as a foundation for generating research hypotheses for development time, budget, staffing, organizational control, and organizational participation. Collapse

Topics: expert system database system system integration manufacturing information system knowledge base

Methods: design artifact survey qualitative interview sensitivity analysis