ERP success prediction: An artificial neural network approach

Rouhani, Saeed; Ravasan, Ahad Zare

doi:10.1016/j.scient.2012.12.006

Cited by 20 publications

(22 citation statements)

References 45 publications

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“…Meanwhile, another approach is required to identify such hidden patterns. Owing to such intricacy, the proposed model should have classification and prediction capabilities, which make artificial neural network (ANN) an appropriate technique to develop expert systems and it is now commonly used in the literature (Rouhani and Ravasan 2013). On this consideration, this paper proposes a NN approach for estimation of S i m p .…”

Section: Proposed Methodologymentioning

confidence: 99%

An Optimization Model for Sustainability Program

Jawahar¹,

Pandian²,

Gunasekaran

et al. 2015

Ann Oper Res

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A sustainability program is about implementing essential sustainability practices at various intensities that will not harm people because of firm actions. This paper formulates an optimization model to identify an optimal intensity of implementation of selected sustainability practices referred as sustainability program for maximising manufacturing industry sustainability performance for a known set of budgetary and minimum thresholds constraints with respect to economic, social and socio-economic criteria. Besides modelling the paper proposes a random search procedure embedding the NN to determine the optimal sustainability program and explains the usefulness with a sample problem. Sensitivity analysis is carried out to understand the behaviour of the model. It is observed that the sustainability performances depend on the constraints such as budget limitation and threshold values of performance criterion.

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Section: Proposed Methodologymentioning

confidence: 99%

An Optimization Model for Sustainability Program

Jawahar¹,

Pandian²,

Gunasekaran

et al. 2015

Ann Oper Res

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“…Their findings were suggestive for an involvement of the auditory cortex in retrieval attempts of vocalized information and approved that adopting retrieval orientation could contribute for retrieval accuracy. Rouhani and Ravasan (2013) discussed the idea of forecasting ERP postimplementation success based on organizational profiles using the Artificial Neural Network (ANN) method to articulate the relationships between some organizational factors and ERP success. Sudhaman and Thangavel (2015) analyzed the efficiency of ERP projects based on their quality measures based on Data Envelopment Analysis model and determined the most efficient ERP projects.…”

Section: Literature Reviewmentioning

confidence: 99%

Recent advances in enterprise resource planning

Orougi¹

2015

10.5267/j.ac

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Enterprise resource planning (ERP) is an integrated system, which consists of various integrated applications. ERP is implemented to collect, store, manage and interpret data from different business activities, including product planning, expenses, production and/or service delivery, sales management, inventory planning, shipping and payment. The study covers the latest studies mostly on detecting factors influencing on the success of ERP implementations. The study has highlighted several factors including top management support, communication, cooperation, training and technological complexity, which were believed to be the most influential factors on development of ERP systems. In addition, several multi criteria decision making systems were used for ranking different software packages for ERP implementation. Moreover, many studies have attempted to consider mathematical methods by considering uncertainty associated with data.Growing Science Ltd. All rights reserved. 5

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“…El alineamiento entre la estrategia de negocios y las tecnologías de información y comunicación (TIC) es un factor clave para mejorar la competitividad de las empresas [1,3]; aunque, no todas las compañías gozan del éxito esperado al momento de incorporar TIC a sus procesos [4], algo en lo que existe consenso es que los entornos en los que compiten las empresas actuales, mayoritariamente mercados altamente dinámicos e inciertos, la tecnología es un factor crítico para alcanzar y sostener una ventaja competitiva [5][6][7][8]. Consecuentemente, la capacidad de incorporar TIC a la estrategia de negocios puede marcar la diferencia entre el éxito y el fracaso [2,[7][8].…”

Section: Introductionunclassified

“…Consecuentemente, la capacidad de incorporar TIC a la estrategia de negocios puede marcar la diferencia entre el éxito y el fracaso [2,[7][8]. Por qué algunas empresas tienen o no tienen éxito al intentar incorporar una TIC ha sido tema de investigación permanente y, como resultado, se han elaborado diversos modelos individuales y organizacionales que buscan responder a esa interrogante.…”

Section: Introductionunclassified

Factores organizacionales y de entorno que predicen el uso de TIC en empresas chilenas: Una aplicación de redes neuronales

Cuello

Barraza

Cataldo

2018

Ingeniare. Rev. chil. ing.

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Factores organizacionales y de entorno que predicen el uso de TIC en empresas chilenas: Una aplicación de redes neuronales Organizational and environment factors that predict the use of ICT in Chilean companies: An application of neural networks RESUMENEste estudio tiene como objetivo explorar cuáles son los factores organizacionales y de entorno que predicen la decisión de usar tecnologías en las empresas. Estos factores se identifican utilizando un enfoque multidisciplinario que integra técnicas de clusterización, redes neuronales artificiales (RNA) y el marco de trabajo Tecnología-Organización-Entorno (TOE). Para desarrollar este estudio se toman en cuenta los resultados de la Encuesta Longitudinal, ELE2, que contiene datos relacionadas con las empresas de Chile. Tomando estos datos, en primer lugar se utiliza la clusterización, mediante el algoritmo K-means, para determinar el perfil de desarrollo tecnológico (T de TOE) de cada empresa a partir de 5.953 empresas chilenas. A continuación, se construye un modelo mediante redes neuronales artificiales (RNA) para predecir T a partir de las otras variables disponibles en la encuesta. La precisión obtenida por la RNA fue del 75%. Al realizar la comprobación de las variables que predicen T con los constructos de OE, se observa que existen variables de la organización y entorno que predicen el perfil de desarrollo tecnológico de las empresas. Además de estos factores OE, también se encontró que otros factores (X) predijeron este perfil, los que se asocian principalmente a características de los administradores de la empresa.Palabras clave: Redes neuronales, K-means, TOE, modelo predictivo. ABSTRACT

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ERP success prediction: An artificial neural network approach

Cited by 20 publications

References 45 publications

An Optimization Model for Sustainability Program

An Optimization Model for Sustainability Program

Recent advances in enterprise resource planning

Factores organizacionales y de entorno que predicen el uso de TIC en empresas chilenas: Una aplicación de redes neuronales

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