18 November 2009

Call for papers: Application of Multivariate Techniques in Decision Making Models for Customer Service in Supply Chain

A special issue of International Journal of Electronic Customer Relationship Management

Customer service is widely understood as an important profit generating mechanism for a successful organisation. In the early days, customer service was viewed as a vision behind corporate success. The visionary concept has evolved to be seen as a day-to-day process towards market success. A process view has taken center-stage and treats customer service as an outcome from wide-spectrum of activities. The approach also assumes customer service as a package of diverse service elements. The majority of practitioners and educationists believe that most of the service elements are unexplored. The passage of time has brought several important customer service elements to the light. A few service elements such as quality at source and on-time delivery are focused in academic and industry circles. The remaining service elements such as customer support, after-sales services, lead time, environmental concerns, condition of goods/services, quantity of goods/services, and value added services are left unscathed and overlooked despite their importance.

Recent studies underscore customer service from logistics perspective. Improving customer service is an ongoing focus of the logistics community. Logistics is understood as market winner in the industry. The term ‘logistics’ denote the systematic and planned movement of organisational resources to attain competitive advantage. Organisational resources include men, material and information that satisfy customers. Organisations mobilise these resources through a wide range of activities called processes. In essence, industry views customer service as processes to move organisational resources. Therefore, the logistics perspective culminates into a process-centric approach for customer service. This study is deeply rooted on process-driven approach for customer service in the premises of logistics. The ultimate aim of logistics is to create customer value and deliver good customer service through processes and systems.

Successful firms prove the value of long-term customer relationships and the importance of customer retention. Emulating successful firms, companies brace for customer retention methods to obviate the cost of customer acquisition. The philosophy that emphasises customer retention through relationship building is known as ‘customer relationship management’ ( CRM ). Value-added customer services ensure the organisational efforts towards building long-term customer relations. Latest CRM practices advocate post-purchase services to create customer value.

Emerging market trends visualise a strong requirement for improved customer service and support in developing markets. Industries offer customer support through a network of service centers.

This special issue intends to improve customer support performance and it is relevant to the above deliberations in following ways.
  • Identifying analytical models to improve the customer service and support process.
  • Analytical modelling in the premises of market knowledge to improve the customer service and support process.
  • Identifying country and industry-specific variables that impact customer service and support operations.
Other streams of interest will be practical applications in the form of quantitative and qualitative case studies based on customer service support in supply chain.

Finally, papers must have real value relevance, be primarily focused on real time implementation, and the target audience are researchers, managers, practitioners and consultants.

Contributors are encouraged to submit original manuscripts that have practical relevance, case studies, and focus on the following or other areas related to customer service support in manufacturing and service industries, but are not limited to:
  • Customer service in manufacturing supply chain
  • Customer service in services supply chain
  • Multivariate techniques for customer service
  • Multicriteria decision making models for customer service
  • Analytical models for customer service and support
  • Process of customer value creation
  • Marketing and logistics elements of customer service
  • Transaction and augmented product concept in customer service
  • Information integration for customer service
  • Service quality models focusing customer support
  • Queuing models for customer service
  • Stochastic models for customer service
  • Mathematical models for customer service
  • Simulation and optimiSation for customer service
  • After-sale services models
Important Dates
Manuscript submission: 15 March 2010
Notification of initial decision: 15 May 2010
Submission of revised manuscript: 15 June 2010
Notification of final acceptance: 15 July 2010
Submission of final manuscript: 15 August 2010

1 comment:

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