Service provider

About: Service provider is a research topic. Over the lifetime, 55107 publications have been published within this topic receiving 894381 citations. The topic is also known as: external service provider & internal service provider.

The Role of Gender in Reactions to Service Failure and Recovery

Abstract: Male and female consumers place different emphasis on elements of the service recovery process. Perceptions were influenced by gender of the service provider and by a match of customer and service provider gender. The study, an experimental design with 712 respondents, found that when service providers, irrespective of gender, display concern and give customers voice and a sizable compensation, both men and women reported more positive attitudes compared with when this was not so. Combinations of high voice with high outcome and high voice with high concern were especially important in positively influencing perceptions of effort, regardless of gender. However, the authors also found that there were significant differences between male and female respondents regarding their perceptions of how service recovery should be handled. Women want their views heard during service recovery attempts and to be allowed to provide input. Men, in contrast, do not view voice as important.

Bridging the service divide through digitally enabled service innovations: evidence from indian healthcare service providers

Abstract: The digital divide is usually conceptualized through goods-dominant logic, where bridging the divide entails providing digital goods to disadvantaged segments of the population. This is expected to enhance their digital capabilities and thus to have a positive influence on the digital outcomes (or services) experienced. In contrast, this study is anchored in an alternative service-dominant logic and posits that viewing the divide from a service perspective might be better suited to the context of developing countries, where there is a huge divide across societal segments in accessing basic services such as healthcare and education. This research views the prevailing differences in the level of services consumed by different population segments (service divide) as the key issue to be addressed by innovative digital tools in developing countries. The study posits that information and communication technologies (ICTs) can be leveraged to bridge the service divide to enhance the capabilities of service-disadvantaged segments of society. But such service delivery requires an innovative assembly of ICT as well as non-ICT resources. Building on concepts from service-dominant logic and service science, this paper aims to understand how such service innovation efforts can be orchestrated. Specifically, adopting a process view, two Indian enterprises that have developed sustainable telemedicine healthcare service delivery models for the rural population in India are examined. The study traces the configurations of three interactional resources--knowledge, technology, and institutions--through which value-creating user-centric objectives of increasing geographical access and reducing cost are achieved. The theoretical contributions are largely associated with unearthing and understanding how the three interactional resources were orchestrated for service-centric value creation in different combinative patterns as resource exploitation, resource combination, and value reinforcement. The analysis also reveals the three distinct stages of service innovation evolution (idea and launch, infancy and early growth, and late growth and expansion), with a distinct shift in the dominant resource for each stage. Through an inductive process, the study also identifies four key enablers for successfully implementing these ICT-enabled service innovations: obsessive customer empathy, belief in the transformational power of ICT, continuous recursive learning, and efficient network orchestration.

Multi-source bridge content distribution system and method

Abstract: A multi-source bridge content distribution system links multiple content owners with access network operators or content distribution providers leasing space on access networks so that multi-media content can be provided from multiple content owners to consumers through a multi-source bridge or data center. Content files and associated content owner preference settings are provided from a plurality of content sources or providers to the multi-source data center. Files stored at the data center or locally at an access network are provided to subscribers through the local access network Content files are provided if the content owner preference settings are a sufficient match with service provider access network preference settings set up by the service provider using the access network to provide content to subscribers.

Research on cloud storage architecture and key technologies

Abstract: This paper proposes a general architecture of cloud storage system, analyzes the functions of the components, and discusses the key technologies, etc. Cloud storage is a novel storage service mode which the service providers supply storage capacities and data storage services through the Internet to the clients; meanwhile, the clients needn't know the details and lowered structures and mechanisms. The proposed architecture of cloud storage is layered and cooperative, and the discussed key technologies involve deployment, storage virtualization, data organization, migration, security, etc. The operation mechanism including ecology chain, game theory, ant colony optimization, data life cycle management, maintenance and update, convergence and evolution mechanisms are analyzed too. So an overall and new viewpoint to cloud storage system is illustrated.

Machine Learning Meets Computation and Communication Control in Evolving Edge and Cloud: Challenges and Future Perspective

Abstract: Mobile Edge Computing (MEC) is considered an essential future service for the implementation of 5G networks and the Internet of Things, as it is the best method of delivering computation and communication resources to mobile devices. It is based on the connection of the users to servers located on the edge of the network, which is especially relevant for real-time applications that demand minimal latency. In order to guarantee a resource-efficient MEC (which, for example, could mean improved Quality of Service for users or lower costs for service providers), it is important to consider certain aspects of the service model, such as where to offload the tasks generated by the devices, how many resources to allocate to each user (specially in the wired or wireless device-server communication) and how to handle inter-server communication. However, in the MEC scenarios with many and varied users, servers and applications, these problems are characterized by parameters with exceedingly high levels of dimensionality, resulting in too much data to be processed and complicating the task of finding efficient configurations. This will be particularly troublesome when 5G networks and Internet of Things roll out, with their massive amounts of devices. To address this concern, the best solution is to utilize Machine Learning (ML) algorithms, which enable the computer to draw conclusions and make predictions based on existing data without human supervision, leading to quick near-optimal solutions even in problems with high dimensionality. Indeed, in scenarios with too much data and too many parameters, ML algorithms are often the only feasible alternative. In this paper, a comprehensive survey on the use of ML in MEC systems is provided, offering an insight into the current progress of this research area. Furthermore, helpful guidance is supplied by pointing out which MEC challenges can be solved by ML solutions, what are the current trending algorithms in frontier ML research and how they could be used in MEC. These pieces of information should prove fundamental in encouraging future research that combines ML and MEC.