The Experts below are selected from a list of 22575 Experts worldwide ranked by ideXlab platform
Yuserrie Zainuddin - One of the best experts on this subject based on the ideXlab platform.
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Customer accounting information Usage and organizational performance
Business Strategy Series, 2012Co-Authors: Hamzah Al-mawali, Yuserrie ZainuddinAbstract:Purpose – This paper aims to shed light on the consequences of Customer accounting (CA) information Usage for strategic purposes on organizational performance.Design/methodology/approach – This is an empirical study with data from 106 Jordanian services organizations. Quantitative data were obtained to investigate the relationship between CA information items and organizational performance in the context of Jordan.Findings – The results show that the level of CA information Usage (Customer profitability, lifetime Customer profitability analysis and valuation of Customers as assets) impacts on organizational performance. CA information Usage leads to better organizational performance. Also, the findings demonstrate a different effect of CA information items on diverse dimensions of organizational performance.Originality/value – The findings will help academics and managers to achieve higher organizational performance.
Hamzah Al-mawali - One of the best experts on this subject based on the ideXlab platform.
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Customer accounting information Usage and organizational performance
Business Strategy Series, 2012Co-Authors: Hamzah Al-mawali, Yuserrie ZainuddinAbstract:Purpose – This paper aims to shed light on the consequences of Customer accounting (CA) information Usage for strategic purposes on organizational performance.Design/methodology/approach – This is an empirical study with data from 106 Jordanian services organizations. Quantitative data were obtained to investigate the relationship between CA information items and organizational performance in the context of Jordan.Findings – The results show that the level of CA information Usage (Customer profitability, lifetime Customer profitability analysis and valuation of Customers as assets) impacts on organizational performance. CA information Usage leads to better organizational performance. Also, the findings demonstrate a different effect of CA information items on diverse dimensions of organizational performance.Originality/value – The findings will help academics and managers to achieve higher organizational performance.
Jeuyih Jeng - One of the best experts on this subject based on the ideXlab platform.
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an upselling pricing model using sdp based rating mechanism with dynamic weight
Proceedings of the The 3rd Multidisciplinary International Social Networks Conference on SocialInformatics 2016 Data Science 2016, 2016Co-Authors: Wanhsun Hu, Fangsun Lu, Jeuyih JengAbstract:With the launching of 4G services and evolving in mobile technology, data-hungry applications are ubiquitous and embraced by more and more Customers. It is obvious that Customers are more likely to run out of their monthly data allowance when using these applications. Therefore, network operators introduce many feasible upselling products for Customers to extend their monthly data allowance. However, the price of upselling products is usually higher than expected. Customers would rather stop consuming data Usage or use limited-speed networks instead of purchasing these upselling products. Furthermore, the price of upselling products has no differentiation or Customer segmentation, such as a heavy data Usage Customer or a light data Usage one. In this paper, we proposed an upselling pricing model using Smart Data Pricing (SDP) based rating mechanism with dynamic weight, which determines the price of upselling products depending on Customers' not only real-time information but also different historical Usage patterns for each charging factor. Compared to a typical SDP scheme with fixed weight that takes real-time information as charging factors, better historical Usage patterns for operators (e.g., higher Average Revenue Per User (ARPU) or more Usage in off-peak time) are also taken into account so that Customers can get lower price than ordinary ones. The price should try to better Customers' intention in purchasing the upselling products and to increase the revenue and Customer satisfaction for network operators. Thus, our approach can encourage Customers to stay with existing service operator to get lower price of upselling products and reduce the churn rate. Evaluation indicates that our approach can increase Customers' willingness to purchase upselling products and increase the revenue of network operators.
Wanhsun Hu - One of the best experts on this subject based on the ideXlab platform.
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an upselling pricing model using sdp based rating mechanism with dynamic weight
Proceedings of the The 3rd Multidisciplinary International Social Networks Conference on SocialInformatics 2016 Data Science 2016, 2016Co-Authors: Wanhsun Hu, Fangsun Lu, Jeuyih JengAbstract:With the launching of 4G services and evolving in mobile technology, data-hungry applications are ubiquitous and embraced by more and more Customers. It is obvious that Customers are more likely to run out of their monthly data allowance when using these applications. Therefore, network operators introduce many feasible upselling products for Customers to extend their monthly data allowance. However, the price of upselling products is usually higher than expected. Customers would rather stop consuming data Usage or use limited-speed networks instead of purchasing these upselling products. Furthermore, the price of upselling products has no differentiation or Customer segmentation, such as a heavy data Usage Customer or a light data Usage one. In this paper, we proposed an upselling pricing model using Smart Data Pricing (SDP) based rating mechanism with dynamic weight, which determines the price of upselling products depending on Customers' not only real-time information but also different historical Usage patterns for each charging factor. Compared to a typical SDP scheme with fixed weight that takes real-time information as charging factors, better historical Usage patterns for operators (e.g., higher Average Revenue Per User (ARPU) or more Usage in off-peak time) are also taken into account so that Customers can get lower price than ordinary ones. The price should try to better Customers' intention in purchasing the upselling products and to increase the revenue and Customer satisfaction for network operators. Thus, our approach can encourage Customers to stay with existing service operator to get lower price of upselling products and reduce the churn rate. Evaluation indicates that our approach can increase Customers' willingness to purchase upselling products and increase the revenue of network operators.
Fangsun Lu - One of the best experts on this subject based on the ideXlab platform.
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an upselling pricing model using sdp based rating mechanism with dynamic weight
Proceedings of the The 3rd Multidisciplinary International Social Networks Conference on SocialInformatics 2016 Data Science 2016, 2016Co-Authors: Wanhsun Hu, Fangsun Lu, Jeuyih JengAbstract:With the launching of 4G services and evolving in mobile technology, data-hungry applications are ubiquitous and embraced by more and more Customers. It is obvious that Customers are more likely to run out of their monthly data allowance when using these applications. Therefore, network operators introduce many feasible upselling products for Customers to extend their monthly data allowance. However, the price of upselling products is usually higher than expected. Customers would rather stop consuming data Usage or use limited-speed networks instead of purchasing these upselling products. Furthermore, the price of upselling products has no differentiation or Customer segmentation, such as a heavy data Usage Customer or a light data Usage one. In this paper, we proposed an upselling pricing model using Smart Data Pricing (SDP) based rating mechanism with dynamic weight, which determines the price of upselling products depending on Customers' not only real-time information but also different historical Usage patterns for each charging factor. Compared to a typical SDP scheme with fixed weight that takes real-time information as charging factors, better historical Usage patterns for operators (e.g., higher Average Revenue Per User (ARPU) or more Usage in off-peak time) are also taken into account so that Customers can get lower price than ordinary ones. The price should try to better Customers' intention in purchasing the upselling products and to increase the revenue and Customer satisfaction for network operators. Thus, our approach can encourage Customers to stay with existing service operator to get lower price of upselling products and reduce the churn rate. Evaluation indicates that our approach can increase Customers' willingness to purchase upselling products and increase the revenue of network operators.
