The rapid pace of technological change has seen information and communication technologies become the digital backbone of developed nations’ economies and a pre-requisite for global trade. Some enterprise systems are...The rapid pace of technological change has seen information and communication technologies become the digital backbone of developed nations’ economies and a pre-requisite for global trade. Some enterprise systems are however more than mere facilitators, they provide the bedrock without which organizations could not function;we term these mandatory systems “non-volitional”(NVS). With hyper-growth in demand for connectivity, telecommunications are typical of sectors where NVS shape the fiercely competitive landscape. Among them, Billing & Revenue Management Systems (BRMS) are a form of credit, providers deliver a service and subscribers later pay for that service. As such, they are “business critical”, meaning failures may affect an organization’s ability to conduct its core business. Failures also impact user satisfaction, a key measure of information systems success. However, relatively few studies empirically test this notion;fewer still evaluate it at organizational (rather than individual) level, while there is a dearth of literature investigating non-volitional systems and, to the best of our knowledge, none whatsoever consider ways of predicting user satisfaction for BRMS. According to a renowned and widely cited conceptual model, user satisfaction is influenced by information, system, and service quality respectively. To test this theory for telecoms BRMS, we applied structural equation modelling to investigate which of these dimensions has the most effect. The results indicate that information quality, system quality, service quality, and user satisfaction are all valid measures of BRMS success. Hypothesized relationships between the four success dimensions were significantly substantiated. The study also identified five measures of information quality, four measures of system quality, four measures of service quality, and four measures of user satisfaction. Once the proposed model had been successfully validated, we tested the level of significance among user satisfaction and the three quality展开更多
文摘The rapid pace of technological change has seen information and communication technologies become the digital backbone of developed nations’ economies and a pre-requisite for global trade. Some enterprise systems are however more than mere facilitators, they provide the bedrock without which organizations could not function;we term these mandatory systems “non-volitional”(NVS). With hyper-growth in demand for connectivity, telecommunications are typical of sectors where NVS shape the fiercely competitive landscape. Among them, Billing & Revenue Management Systems (BRMS) are a form of credit, providers deliver a service and subscribers later pay for that service. As such, they are “business critical”, meaning failures may affect an organization’s ability to conduct its core business. Failures also impact user satisfaction, a key measure of information systems success. However, relatively few studies empirically test this notion;fewer still evaluate it at organizational (rather than individual) level, while there is a dearth of literature investigating non-volitional systems and, to the best of our knowledge, none whatsoever consider ways of predicting user satisfaction for BRMS. According to a renowned and widely cited conceptual model, user satisfaction is influenced by information, system, and service quality respectively. To test this theory for telecoms BRMS, we applied structural equation modelling to investigate which of these dimensions has the most effect. The results indicate that information quality, system quality, service quality, and user satisfaction are all valid measures of BRMS success. Hypothesized relationships between the four success dimensions were significantly substantiated. The study also identified five measures of information quality, four measures of system quality, four measures of service quality, and four measures of user satisfaction. Once the proposed model had been successfully validated, we tested the level of significance among user satisfaction and the three quality
