Customer Experience Hierarchy Model: Based on the Theory of Customer Value Hierarchy

2008 ◽  
Author(s):  
Hong-Li Guo
Keyword(s):  
Customer Value ◽  
Customer Experience ◽  
Model Based ◽  
Hierarchy Model ◽  
Value Hierarchy

Telecommunication Customer Demand Management

2010 ◽  
pp. 1112-1126
Author(s):  
Jiayin Qi ◽  
Yajing Si ◽  
Jing Tan ◽  
Yangming Zhang
Keyword(s):  
Information Systems ◽  
Customer Value ◽  
Demand Management ◽  
Demand Analysis ◽  
Competitive Environment ◽  
Customer Demand ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Hierarchy Model ◽  
Value Hierarchy

In the highly competitive environment, the real-time and dynamic customer demand analysis technology is required by the enterprise information systems in order to respond to customer demand efficiently and automatically. Based on a customer value hierarchy model, this chapter proposes a customer demand analysis method and proposes ways to capture customer demand knowledge. Then, we present a novel product recommendation approach, which involves the customer value hierarchy model into traditional recommender systems. Through the above steps, the telecom operators can get their customer demand and respond to their demand automatically.

Telecommunication Customer Demand Management

2010 ◽  
pp. 364-378
Author(s):  
Jiayin Qi ◽  
Yajing Si ◽  
Jing Tan ◽  
Yangming Zhang
Keyword(s):  
Information Systems ◽  
Customer Value ◽  
Demand Management ◽  
Demand Analysis ◽  
Competitive Environment ◽  
Customer Demand ◽  
Enterprise Information ◽  
Enterprise Information Systems ◽  
Hierarchy Model ◽  
Value Hierarchy

In the highly competitive environment, the real-time and dynamic customer demand analysis technology is required by the enterprise information systems in order to respond to customer demand efficiently and automatically. Based on a customer value hierarchy model, this chapter proposes a customer demand analysis method and proposes ways to capture customer demand knowledge. Then, we present a novel product recommendation approach, which involves the customer value hierarchy model into traditional recommender systems. Through the above steps, the telecom operators can get their customer demand and respond to their demand automatically.

The Structural Relationship Information Technology Used and Risk toward Banking Customer Satisfaction during Covid19, Indonesia

2021 ◽  
Vol 12 (4) ◽  
pp. 1618-1630
Author(s):  
Surachman Surjaatmadja, Et. al.
Keyword(s):  
Information Technology ◽  
Customer Satisfaction ◽  
Technology Use ◽  
Perceived Risk ◽  
Customer Value ◽  
Customer Experience ◽  
Structural Relationship ◽  
Service Development ◽  
Functional Quality ◽  
Number Of Customers

Investigation on the structural relationship of  information technology functional quality, customer value, technology used, risk perception and customer experience of banking customer satisfaction during covid19 pandemic is very important to provide significant benefits to increase the number of customers. This research design uses a quantitative approach through a questionnaire survey conducted on banking customers in Indonesia. Data analysis was performed using statistical software, namely LISREL Version 8.0. The results of the analysis show that functional quality, perceived customer value, technology use, perceived risk and customer experience have a significant relationship with banking customer satisfaction  during the covid19 pandemic. In detail, the functional quality of banking technology is considered to have contributed 39% to  customer satisfaction when implementing health protocols. Customer value contributes to customer satisfaction, technology used  contributed to the customer satisfaction and perceived risk shaping customer satisfaction. In addition customer experience when implementing health protocols during the covid19 pandemic influence to customer satisfaction.  In conclusion, functional quality, customer value, technology used, perceived risk and customer experience show the most significant contribution to banking customer satisfaction  when implementing health protocols during the covid19 pandemic and create good acceptance of banking service performance from the aspects of empathy, physical evidence, reliability, fast response, time saving and cost-effectiveness and the new service development. 

scholarly journals EFFECT OF CUSTOMER VALUE AND CUSTOMER EXPERIENCE ON CUSTOMER SATISFACTION AND LOYALTY PT MERATUS SAMARINDA

2020 ◽  
Vol 4 (01) ◽  
Author(s):  
Hasfar M ◽  
Theresia Militina ◽  
Gusti Norlitaria Achmad
Keyword(s):  
Customer Satisfaction ◽  
Customer Loyalty ◽  
Customer Value ◽  
Structural Equation ◽  
Customer Experience ◽  
Statistical Test ◽  
Statistical Hypothesis ◽  
Equation Modeling ◽  
Value Effect ◽  
Customer Satisfaction And Loyalty

This study aims to determine the effect of customer value and customer experience to customer satisfaction and loyalty PT Meratus. The population in this study are customers of PT Meratus by the number of 80 customers. Methods of data collection is done by providing a list of questions or the questionnaire respondents who are customers of PT Meratus, where questionnaires were distributed to such subscribers. This study uses data analysis tool which Partial Least Square (PLS), then this study using structural equation modeling analysis method or path analysis to determine the causal relationship between the latent variables contained in the structural equation. While testing the hypothesis tested boost strap resampling method developed by Geisser and Stone. Statistical test used statistical test t or t test, with statistical hypothesis. The tools used in processing the data using PLS Smart program. The results of this study indicate that 1) customer experience influence positive and significant to customer satisfaction, 2)) customer experience influence positive and significant customer loyalty, 3) customer value effect on positive and significant to customer satisfaction, 4) customer value effect positive but are not with significant customer loyalty, 5) customer satisfaction and significant positive effect on customer loyalty.

Data Mining Models as a Tool for Churn Reduction and Custom Product Development in Telecommunication Industries

2014 ◽  
pp. 511-537 ◽  
Author(s):  
Goran Klepac
Keyword(s):  
Expert System ◽  
Product Development ◽  
New Product Development ◽  
Customer Value ◽  
Model Development ◽  
Business Case ◽  
Customer Segmentation ◽  
Fuzzy Expert System ◽  
Analysis Model ◽  
Model Based

This chapter represents the business case in the telecommunication company called Veza, in domain of churn prediction and churn mitigation. The churn project was divided into few stages. Due to limited budget and cost optimization, stage one was concentrated on prospective customer value calculation model based on fuzzy expert system. This helps Veza company to find most valuable telecom subscribers. It also helped company to better understand subscriber portfolio structure. Developed fuzzy expert system also helped Veza company in detection of soft churn. Stage two is profiling and customer segmentation based on time series analysis which provided potential predictors for predictive churn model. The central stage was concentrated on developing traditional predictive churn model based on logistic regression. This calculated probability that subscribers will make churn in next few months. The final stage was dedicated to SNA (Social Network Analysis) model development which found out the most valuable customers from the perspective of existing subscriber network. This model gave the answer that subscribers have the greatest influence on other subscribers in a way what is dangerous if they leave Veza company because they will motivate other subscribers to do the same thing. All three stages made complete churn detection/mitigation solution which take into consideration past behaviour of subscribers, their prospective value, and their strength of influence on other subscribers. This project helped Veza company to decrease churn rate and it gave directions for better understanding customer needs and behaviour which were the base for new product development.

Model-based Validation of Business Processes

2012 ◽  
pp. 165-183 ◽  
Author(s):  
Alireza Pourshahid ◽  
Liam Peyton ◽  
Sepideh Ghanavati ◽  
Daniel Amyot ◽  
Pengfei Chen ◽  
...  
Keyword(s):  
Data Warehouse ◽  
Business Process ◽  
Information Exchange ◽  
Customer Value ◽  
Data Exchange ◽  
Business Processes ◽  
Business Strategies ◽  
Legal Compliance ◽  
Critical Elements ◽  
Model Based

Validation should be done in the context of understanding how a business process is intended to contribute to the business strategies of an organization. Validation can take place along a variety of dimensions including legal compliance, financial cost, customer value, and service quality. A business process modeling tool cannot anticipate all the ways in which a business process might need to be validated. However, it can provide a framework for extending model elements to represent context for a business process. It can also support information exchange to facilitate validation with other tools and systems. This chapter demonstrates a model-based approach to validation using a hospital approval process for accessing patient data in a data warehouse. An extensible meta-model, a flexible data exchange layer, and linkage between business processes and enterprise context are shown to be the critical elements in model-based business process validation.

Data Mining Models as a Tool for Churn Reduction and Custom Product Development in Telecommunication Industries

2015 ◽  
pp. 559-585
Author(s):  
Goran Klepac
Keyword(s):  
Expert System ◽  
Product Development ◽  
New Product Development ◽  
Customer Value ◽  
Model Development ◽  
Business Case ◽  
Customer Segmentation ◽  
Fuzzy Expert System ◽  
Analysis Model ◽  
Model Based

This chapter represents the business case in the telecommunication company called Veza, in domain of churn prediction and churn mitigation. The churn project was divided into few stages. Due to limited budget and cost optimization, stage one was concentrated on prospective customer value calculation model based on fuzzy expert system. This helps Veza company to find most valuable telecom subscribers. It also helped company to better understand subscriber portfolio structure. Developed fuzzy expert system also helped Veza Company in detection of soft churn. Stage two is profiling and customer segmentation based on time series analysis which provided potential predictors for predictive churn model. The central stage was concentrated on developing traditional predictive churn model based on logistic regression. This calculated probability that subscribers will make churn in next few months. The final stage was dedicated to SNA (Social Network Analysis) model development which found out the most valuable customers from the perspective of existing subscriber network. This model gave the answer that subscribers have the greatest influence on other subscribers in a way what is dangerous if they leave Veza Company because they will motivate other subscribers to do the same thing. All three stages made complete churn detection/mitigation solution which take into consideration past behaviour of subscribers, their prospective value, and their strength of influence on other subscribers. This project helped Veza Company to decrease churn rate and it gave directions for better understanding customer needs and behaviour which were the base for new product development.

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