High Prediction Accuracy and Low Error for ERP User Satisfaction by Hybrid of ANFIS and KNN Classification

The incoming era is becoming more friendly and dependent on Information Technology. Enterprise Resource Planning (ERP) Systems are one of the most widely used latest examples of Information Systems (IS) technology. They provide a single window system to the organizations by integrating the whole functions of them. Today, all enterprises are rapidly adopted ERP systems. But, their adoption and implementation is not being without any problem. The implementation process of ERP is also a very challenging, time consuming and costly task. Therefore, instead of many efforts if the implementation process is failed. Then it will be a big failure for the organization. Hence, to overcome this failure and increase the success rate of ERP projects we need to develop a robust, reliable and accurate predictor. This will help us to redirect the projects far better in advance. The success of ERP systems depends on many factors. US is one of the important factor among them. Hence, we develop an efficient predictor of US using hybrid of ANFIS and KNN. We were used this method first time in literature related to prediction of US in ERP. The Hybrid method increases the prediction accuracy more comparatively than previous reported techniques ANN, ANFIS and KNN. The RMSE using Hybrid method is 0.167629 and for KNN, ANFIS and ANN is 0.5, 0.486185, and 0.590329 respectively

User Satisfaction Prediction in ERP using KNN Classifier for high Prediction Accuracy

Abstract—ERP (Enterprise Resource Planning) systems are widely used in organizations; because, ERP provides a single platform to manage all the processes and functions of organizations. This single platform improves their productivity, business performance, decision making capabilities and efficiency. However, to achieve a proper level of ERP success depends on various factors e.g. organization, technology, environment and User Satisfaction etc. ‘User Satisfaction’ (US) is most important factor to make ERP successful. US refer the user’s comfort and acceptability of ERP system during the use and interaction with the ERP system. This paper deploys the conceptual model for US prediction by considering Human, Technological and Organizational factors as predictors. In this report, we proposed K-Nearest Neighbor (KNN) Classification method first time in literature to predict the US and we compare it with ANFIS and ANN. We calculated average error for all test cases and demonstrate that KNN gives high predication accuracy in most of the cases and low average error (0.25) in comparison ANFIS (0.3378) and ANN (0.6053) methods. So our approach is novel and using KNN, prediction accuracy can be further improved for US to make successful ERP

Using attitudes and green consciousness as a determinant of travel behaviour and market segmentation

L'abstract è presente nell'allegato / the abstract is in the attachmen

Investigating End User Satisfaction in ERP Systems: An Analytical Approach

Measuring the end user satisfaction is an important issue reported in many decades in ERP systems success and its implementation. Hence, instead of many success stories the failure is also reported many times about the ERP implementation process. It provides many benefits to the organizations i.e. central storage/backup, modular software, efficiency, easier, and collaboration between various departments. Therefore, it is widely used by many types of organizations to provide a single platform to them. Despite this, its adoption and implementation in not without problems. Ignoring many important factors is also a reason of failure of ERP implementation. So, this paper is focusing on three main factors to investigate the success of ERP systems that are human, technological and organization. A survey tool is used for the study as questionnaire. An analytical approach is proposed to investigate the success of ERP systems by explaining that which factor is more important for end user satisfaction in ERP. Analysis is done on the basis of variance explained by each critical success factor. More variance shows that the factor impacts more the success of ERP system. As a result, three factors are very important for successful ERP implementation which are training and support for users, to facilitate changes in the organizational structure, in the legacy systems and in the IT infrastructure and having external consultants

Validating Italian General Ecological Behaviour Questionnaire of Travellers using Dichotomous Rasch Model

Ecological behaviour and the impact on environment are subjects of public concern and understanding individual behavioural measures to induce sustainable lifestyles is of extreme importance for policy makers to assess and promote sustainable mobility. To this end, a questionnaire with highly reliable items, evaluation of determinants and accurate measurement of ecological behaviour is a precondition for understanding the levers for a behavioural change. This paper aims at understanding whether the dichotomous Rasch model provides a legitimate measurement of General Ecological Behaviour (GEB) using a 26 items questionnaire as a valid tool to assess pro-environment behaviour of a large sample of users. A web questionnaire was administered using the snowball sampling plan in the Piedmont region (Italy) reaching out a sample of 4473 respondents. Results suggest that using the dichotomous Rasch model, proposed questionnaire is able to effectively measure pro-environment behaviour of travellers. Unidimensionality, perfect level of item reliability of 1, very high item separation of 34.22, absence of larger differential item functioning, and local independence are all good indicators of a valid model. This research shows how a good, validated, and reliable measurement of ecological behaviour would support public bodies to plan environment focused transport policies thanks to the knowledge of which variables determine the pro-environment behaviour. In addition, the proposed approach allows also to measure the efficacy of the adopted policies

Diagnosis of Bearing Fault Using Morphological Features Extraction and Entropy Deconvolution Method

It is observed that the bearing failure of rotating machinery is a pulse in the vibration signal, but it is mostly immersed in noise. In order to effectively eliminate this noise and detect pulses, a novel an image fusion technology based on morphological operators inference is proposed. The correctness of morphological operators lies in the correct selection of structural elements (SE). This report presents an effective algorithm for SE selection based on kurtosis, which makes the analysis free empirical method. When analyzing three different groups of faults, the results show that this method effectively and robustly generates impulse. It enables the algorithm to detect early faults too. Recently, minimum entropy deconvolution (MED) was introduced to the machine in the field of condition monitoring, to enhance the detection of rolling bearing and gear failures. MED analysis helps to extract these pulses and diagnose their source, namely defects bearing components. In this research, MED will be reviewed and reintroduced, Application in fault detection and diagnosis of rolling bearings. MED parameters are selected and its combination with pre-whitening. Test cases are presented to illustrate benefits of MED technology. The simulation has been done on MATLAB and a graphical user interface has been created for analysis of bearing and detection of bearing faults using morphological features

A Review on Prediction of ERP Outcome Measurement and User Satisfaction by Use of AI (Fuzzy Logic and Neural Networks)

ERP (Enterprise Resource Planning Systems) comprises of a commercial software package that promises the seamless integration of all the information flowing through the company-accounting, human resource supply chain and the consumer information. Enterprise Resources Planning systems are computer depended systems designed to process an organisation's transaction and facilitate integrated and real time planning, production and customer response. Fuzzy logic has emerged as a profitable tool for the controlling and steering of systems and many critical organizational procedures, like for household and entertainment electronics, as well as other expert systems and uses. In this research work we try to investigates the factors that impact user satisfaction in ERP implementations, a conceptual framework that determine the critical factors which influence user's satisfaction in the ERP implementation will be developed. Although ERP implementation is costly and time consuming and it can also lead to loss of many valuable resources of the organisations in case of wrong methods and not efficient way of implementation. Hence it is critically important for the organisations to understand and clearly realise all the values achieved from ERP initiatives

Validating Italian General Ecological Behaviour Questionnaire of Travellers Using Dichotomous Rasch Model

Ecological behaviour and its impact on the environment are subjects of public concern and understanding individual behavioural measures to induce sustainable lifestyles is of extreme importance for policy makers to assess and promote sustainable mobility. To this end, a questionnaire with highly reliable items, evaluations of determinants and accurate measurements of ecological behaviour is a precondition for understanding the levers of behavioural change. This paper aims at an understanding of whether the dichotomous Rasch model provides a legitimate measurement of General Ecological Behaviour (GEB) using a 26-item questionnaire as a valid tool to assess the pro-environment behaviour of a large sample of users. A web questionnaire was administered using the snowball sampling plan in the Piedmont region (Italy), with a sample of 4473 respondents. The results suggest that using the dichotomous Rasch model, the proposed questionnaire is able to effectively measure the pro-environment behaviour of travellers. Unidimensionality, the perfect level of item reliability of 1, the very high item separation of 34.22, the absence of larger differential item functions, and the local independence are all good indicators of a valid model. This research shows how a good, validated, and reliable measurement of ecological behaviour would support public bodies in planning environment-focused transport policies thanks to the knowledge of which variables determine pro-environment behaviour. In addition, the proposed approach also allows us to measure the efficacy of the adopted policies