73,368 research outputs found
Strategic Predictors of Successful Enterprise Systems Deployment
Purpose The delivered wisdom to date has enterprise system purchase and implementation as one of the most hazardous projects any organization can undertake. The aim was to reduce this risk by both theoretically and empirically finding those key predictors of a successful enterprise system deployment.
Design/methodology/approach A representative sample of 60 firms drawn from the Fortune 1000 that had recently (1999-2000) adopted enterprise resource planning (ERP) systems was used to test a model of adoption performance with significant results.
Findings Leadership (social learning theory), business process re-engineering (change the company not the technology) and acquisition strategy (buy, do not make) were found to be significant predictors of adoption performance (final model R 2=43 percent, F=5.5, pp
Originality/value The âfour factorâ model we validate is a robust predictor of ERP adoption success and can be used by any organization to audit plans and progress for this undertaking
An assessment of the ability of BartlettâLewis type of rainfall models to reproduce drought statistics
Of all natural disasters, the economic and environmental consequences of droughts are among the highest because of their longevity and widespread spatial extent. Because of their extreme behaviour, studying droughts generally requires long time series of historical climate data. Rainfall is a very important variable for calculating drought statistics, for quantifying historical droughts or for assessing the impact on other hydrological (e. g. water stage in rivers) or agricultural (e. g. irrigation requirements) variables. Unfortunately, time series of historical observations are often too short for such assessments. To circumvent this, one may rely on the synthetic rainfall time series from stochastic point process rainfall models, such as Bartlett-Lewis models. The present study investigates whether drought statistics are preserved when simulating rainfall with Bartlett-Lewis models. Therefore, a 105 yr 10 min rainfall time series obtained at Uccle, Belgium is used as a test case. First, drought events were identified on the basis of the Effective Drought Index (EDI), and each event was characterized by two variables, i.e. drought duration (D) and drought severity (S). As both parameters are interdependent, a multivariate distribution function, which makes use of a copula, was fitted. Based on the copula, four types of drought return periods are calculated for observed as well as simulated droughts and are used to evaluate the ability of the rainfall models to simulate drought events with the appropriate characteristics. Overall, all Bartlett-Lewis model types studied fail to preserve extreme drought statistics, which is attributed to the model structure and to the model stationarity caused by maintaining the same parameter set during the whole simulation period
Strategic Predictors of Successful Enterprise Systems Deployment
Purpose The delivered wisdom to date has enterprise system purchase and implementation as one of the most hazardous projects any organization can undertake. The aim was to reduce this risk by both theoretically and empirically finding those key predictors of a successful enterprise system deployment.
Design/methodology/approach A representative sample of 60 firms drawn from the Fortune 1000 that had recently (1999-2000) adopted enterprise resource planning (ERP) systems was used to test a model of adoption performance with significant results.
Findings Leadership (social learning theory), business process re-engineering (change the company not the technology) and acquisition strategy (buy, do not make) were found to be significant predictors of adoption performance (final model R 2=43 percent, F=5.5, pp
Originality/value The âfour factorâ model we validate is a robust predictor of ERP adoption success and can be used by any organization to audit plans and progress for this undertaking
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Validation of Finite Element Modelling of Multielectrode Capacitive System for Process Tomography Flow Imaging
Finite element modelling of process tomography sensor systems is necessary for their CAD both for performance evaluation and design optimization. This paper involves the validation of finite element models of a 12-electrode capacitive sensor system for multiphase flow imaging. Various results of modelling have been compared in the form of standing mode capacitances and sensor sensitivity distribution with experimental data obtained from UMIST. There is good agreement between simulation results and experiments especially for high sensitivity regions inside the pipe
EDI and intelligent agents integration to manage food chains
Electronic Data Interchange (EDI) is a type of inter-organizational information system, which permits the automatic and structured communication of data between organizations. Although EDI is used for internal communication, its main application is in facilitating closer collaboration between organizational entities, e.g. suppliers, credit institutions, and transportation carriers. This study illustrates how agent technology can be used to solve real food supply chain inefficiencies and optimise the logistics network. For instance, we explain how agribusiness companies can use agent technology in association with EDI to collect data from retailers, group them into meaningful categories, and then perform different functions. As a result, the distribution chain can be managed more efficiently. Intelligent agents also make available timely data to inventory management resulting in reducing stocks and tied capital. Intelligent agents are adoptive to changes so they are valuable in a dynamic environment where new products or partners have entered into the supply chain. This flexibility gives agent technology a relative advantage which, for pioneer companies, can be a competitive advantage. The study concludes with recommendations and directions for further research
A selected glossary of electronic data interchange and related terms
School of Managemen
Decentralized Event-Triggered Consensus of Linear Multi-agent Systems under Directed Graphs
An event-triggered control technique for consensus of multi-agent systems
with general linear dynamics is presented. This paper extends previous work to
consider agents that are connected using directed graphs. Additionally, the
approach shown here provides asymptotic consensus with guaranteed positive
inter-event time intervals. This event-triggered control method is also used in
the case where communication delays are present. For the communication delay
case we also show that the agents achieve consensus asymptotically and that,
for every agent, the time intervals between consecutive transmissions is
lower-bounded by a positive constant.Comment: 9 pages, 5 figures, A preliminary version of this manuscript has been
submitted to the 2015 American Control Conferenc
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