Prediction-Based Prefetch Scheduling in Mobile Service Applications

2016 ◽  
Author(s):  
Michael Borkowski ◽  
Olena Skarlat ◽  
Stefan Schulte ◽  
Schahram Dustdar
Keyword(s):  
Mobile Service

The Effect of Service Quality on Customers' Satisfaction in Mobile Phone Services in the UAE

2020 ◽  
Vol 8 (1) ◽  
pp. 75-94
Author(s):  
Emad Yusuf Masoud
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Mobile Phone ◽  
Service Providers ◽  
Mobile Service ◽  
Behavioural Difference ◽  
Mobile Industry ◽  
Quality Dimensions ◽  
Service Quality Dimensions ◽  
Network Quality

This study aims to determine the dimensions of mobile service quality and to examine their effect on customer satisfaction in UAE mobile phone service providers while also investigating the behavioural differences between mobile phone customers with prepaid and postpaid subscriptions. A combination of the SERVPERF model has been adopted as the main framework for analyzing service quality. A structured questionnaire instrument was designed for data collection. The present study concentrates on the level of customers’ satisfaction for leading service providers in the UAE mobile industry. Etisalat and Du were chosen for this study. A sample of (452) mobile phone users in Abu Dhabi city was selected at random using convenience-sampling. We found a positive effect of both functional and technical service quality (network quality) on customers’ satisfaction. Functional and technical dimensions were good predictors of customer satisfaction and confirmed the multidimensional nature of service quality. Also, the service quality dimensions; reliability, assurances, and responsiveness are found to be significant predictors of customer satisfaction. Behavioural difference between mobile phone customers is also significant in predicting customer satisfaction for postpaid subscribers. However, only reliability and network quality are significant predictors of customer satisfaction for prepaid subscribers. The model developed in this study provides marketers and researchers with a diagnostic tool to assess service quality from the perspectives of customers to meet the customer’s expectations and ensure customer satisfaction.

Task and Design Requirements for an Affordable Mobile Service Robot for Elder Care in an All-Inclusive Care for Elders Assisted-Living Setting

2017 ◽  
Vol 12 (5) ◽  
pp. 989-1008 ◽  
Author(s):  
Michelle J Johnson ◽  
Megan A. Johnson ◽  
Justine S. Sefcik ◽  
Pamela Z. Cacchione ◽  
Caio Mucchiani ◽  
...  
Keyword(s):  
Assisted Living ◽  
Elder Care ◽  
Service Robot ◽  
Mobile Service ◽  
Design Requirements ◽  
Mobile Service Robot

scholarly journals Dynamic Plan Control: An Effective Tool to Manage Demand Considering Mobile Internet Network Congestion

2020 ◽  
Vol 11 (1) ◽  
pp. 91
Author(s):  
Xiaoyu Ma ◽  
Jihong Zhang ◽  
Yuan Cao ◽  
Zhou He ◽  
Jonas Nebel
Keyword(s):  
Programming Problem ◽  
Service Provider ◽  
Service Providers ◽  
Control Method ◽  
Network Capacity ◽  
Mobile Internet ◽  
Mixed Integer ◽  
Mobile Service ◽  
Data Traffic ◽  
Potential Customers

Rapidly increasing mobile data traffic have placed a significant burden on mobile Internet networks. Due to limited network capacity, a mobile network is congested when it handles too much data traffic simultaneously. In turn, some customers leave the network, which induces a revenue loss for the mobile service provider. To manage demand and maximize revenue, we propose a dynamic plan control method for the mobile service providers under connection-speed-restriction pricing. This method allows the mobile service provider to dynamically set the data plans’ availability for potential customers’ new subscriptions. With dynamic plan control, the service provider can adjust data network utilization and achieve high customer satisfaction and a low churn rate, which reflect high service supply chain performance. To find the optimal control policy, we transform the high-dimensional dynamic programming problem into an equivalent mixed integer linear programming problem. We find that dynamic plan control is an effective tool for managing demand and increasing revenue in the long term. Numerical evaluation with a large European mobile service provider further supports our conclusion. Furthermore, when network capacity or potential customers’ willingness to join the network changes, the dynamic plan control method generates robust revenue for the service provider.

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