Research based on the Web Shopping service Quality and Customer Satisfaction and Loyalty

The online shopping has changed people＇s traditional mode of shopping. With more and more customers participate in online shopping, and the online shopping service providers need to improve the quality of service to attract customers to improve customer satisfaction. Based on SERVQUAL model, this paper explores the association between various dimensions of service quality of the web-based shopping and customer satisfaction and service loyalty, and gives an analysis of the five dimensions of quality of service in the context of online shopping, the relationship between service quality and customer satisfaction and loyalty, and thus providing the reference for online shopping service.

Classification and quantification of timestamp data quality issues and its impact on data quality outcome

Timestamps play a key role in process mining because it determines the chronology of which events occurred and subsequently how they are ordered in process modelling.The timestamp in process mining gives an insight on process performance,conformance,and modelling.This therefore means problems with the timestamp will result in misrepresentations of the mined process.A few articles have been published on the quantification of data quality problems but just one of the articles at the time of this paper is based on the quantification of timestamp quality problems.This article evaluates the quality of timestamps in event log across two axes using eleven quality dimensions and four levels of potential data quality problems.The eleven data quality dimensions were obtained by doing a thorough literature review of more than fifty process mining articles which focus on quality dimensions.This evaluation resulted in twelve data quality quantification metrics and the metrics were applied to the MIMIC-ll dataset as an illustration.The outcome of the timestamp quality quantification using the proposed typology enabled the user to appreciate the quality of the event log and thus makes it possible to evaluate the risk of carrying out specific data cleaning measures to improve the process mining outcome.

Handling of Customers Satisfaction and Assessment of Service Qualities on Commercial Bank of Ethiopia in Addis Ababa at East District

Banking sector in Ethiopia is dominant and it is a dense competent area.Due to this the bank managements tend to continually found the strategies that enables them to be competent in this dense competition.These strategies often focus on handling of customers satisfaction to be strongly compete and pooling more customers.Because,service quality is relevant to keep up their competitive advantage and improve customer satisfaction.So,this study examine the handling of customers satisfaction and assessment of service qualities on Commercial Bank of Ethiopia(CBE)in Addis Ababa at East District by applying SERVQUAL model.This study used convenient and random sampling technique to select the sample respondents and 400 respondents were selected branches of CBE in Addis Ababa at east district.The data sources for this study are primary and secondary data sources.The questionnaires are used as primary data source,which are contained SERVQUAL model and the agreements were measured by applying the five Likert point scales.The correlation result revealed that all dimensions of service quality have a strong and significant statistical relationship with customer satisfaction.The quality of service offered by CBE no meets with the expectation of customer(customers satisfied in somewhat quality service).So,the bank needs to reform service quality for satisfy and attract unsatisfied customers.

A Bayesian Based Process Monitoring and Fixture Fault Diagnosis Approach in the Auto Body Assembly Process

The auto body process monitoring and the root cause diagnosis based on data-driven approaches are vital ways to improve the dimension quality of sheet metal assemblies. However, during the launch time of the process mass production with an off-line measurement strategy, the traditional statistical methods are difficult to perform process control effectively. Based on the powerful abilities in information fusion, a systematic Bayesian based quality control approach is presented to solve the quality problems in condition of incomplete dataset. For the process monitoring, a Bayesian estimation method is used to give out-of-control signals in the process. With the abnormal evidence, the Bayesian network(BN) approach is employed to identify the fixture root causes. A novel BN structure and the conditional probability training methods based on process knowledge representation are proposed to obtain the diagnostic model. Furthermore, based on the diagnostic performance analysis, a case study is used to evaluate the effectiveness of the proposed approach. Results show that the Bayesian based method has a better diagnostic performance for multi-fault cases.