To be published in Service Science, ISSN (Online) 978-1-4276-2090-3, ISSN (Print) 978-1-4276-2091-0
1Wei-Lun Chang and 2Yen-Hao Hsieh
1Associate Professor, Dept. of Business Administration, Tamkang University, Taiwan, firstname.lastname@example.org
2Assistant Professor, Dept. of Information Management, Tamkang University, Taiwan, email@example.com
The service mindset gradually becomes more and more important in the twentieth century. The shift focus of service from 1980’s to 2000’s has addressed that IT not only lowers the cost of service but creates avenues to enhance revenue through service. Enterprises expand revenue through IT–based service nowadays. For instance, e-service has several features including mobile, flexible, interactive, and interchangeable. Additionally, e-services have much to offer in overcoming obstacles faced by traditional service industry. The concept of Service Science was proposed by IBM which combines several issues into traditional service management. Moreover, the paradigm of service also transferred from traditional service industry to IT-based service industry. FedEx is an excellent example that successfully transfers to paradigm of e-service, including self-service, customization, search engine, flexibility, and automatic response. Google is another great example of enterprise to provide IT-based services (e.g., e-services) in the new paradigm.
Service-dominant (SD) logic can be considered as a new direction for enterprises to get high competency in dynamic service contexts. Accordingly, SD logic based service mining, which is novel, addressing several research areas from the viewpoints of technology, model, management, and application. SD logic based service mining is defined as a systematical process including service discovery, service experience, service recovery and service retention to discover unique patterns and exceptional values within the existing service pool. The goal of SD logic based service mining is similar to data mining, text mining or web mining which aims to detect something new from the service pool. The major difference is the feature of service which is quite distinct to mining target such as data or text. In other words, service is a process of value co-creation and different by various perception of customer. In the concept of SD logic based service mining, the mining target is not only the traditional services but also IT-based services.
As aforementioned, SD logic based service mining covers a process of discovering patterns, such as service discovery, service experience, service recovery, and service retention. According to the four steps of SD logic based service mining process, the concept covers from service exploratory to service maintenance. Furthermore, SD logic based service mining covers beyond the existing service management and is considered as a branch of Service Science.
In addition, SD logic based service mining covers four dimensions: technology, model, management, and application. This special issue is to devote to the exploration from four dimensions across different disciplines with regard to the issue of mining “services” under Service Science. With the growth of the significant revenue of service industry around the world, SD logic based service mining is worth investigating to help enterprises to gain and create values with customers from now on. Hence, we seek high-quality, unpublished contributions on the following and other related topics:
- Technology: Service Value Networks, service system complexity, service system scalability, service infrastructure
- Model: Service computing, system configuration, service system reconfigurability
- Management: Service cooperation, service branding, service pricing, service innovation, service recovery, service sustainability, service experience
- Application: Social network services, web services, e-services, traditional services
The contributors to this special issue will be asked to explain how and what SD logic based service mining positions, giving a tentative answer to the following questions:
- What are the keys to build a quality mechanism of SD logic based service mining?
- What are useful service mining mechanisms to systematically explore the appropriate service?
- How can stakeholders accurately deliver/require suitable services?
- What are core values by using mining approaches in services?
- How can stakeholders effectively co-create values in services?
- How can stakeholders apply and put SD logic based service mining into practice?
- What contributions will bring stakeholders to SD logic based service mining?
- What role can SD logic based service mining play in Service Science?
Submission of full paper: January 31, 2013
Notification of acceptance: April 30, 2013
Final papers due: June 30, 2013
Tentative publication date: October 31, 2013
Papers must not have been published, accepted for publication, or presently be under consideration for publication elsewhere. A standard double-blind review process will be used to select papers for the special issue. All submissions must be made electronically at http://mc.manuscriptcentral.com/serv .
For any questions and article submissions, please contact:
Prof. Wei-Lun Chang (firstname.lastname@example.org) and Prof. Yen-Hao Hsieh (email@example.com)
Guest editors, Service Science
No.151, Yingzhuan Rd., Danshui Dist., New Taipei City 25137, Taiwan (R.O.C.)
For more information on the Journal visit the Service Science web site: