The purpose of this study is to create a value variation measurement model to define the relationship among various roles in resource management within a service system; and divide value creation into two states (i.e. cocreation and codestruction) and use them as crucial indicators for value variation by adopting the service-dominant logic and using the Markov switching model.
This study proposed that variations in value are similar to changes in economy because both are abstract, indefinable and not easy to identify. Therefore, this study used the Markov switching model to define the state of value through value cocreation and codestruction; analyze value variations in a service system; and provide a numerical evaluation method by using the concept of probability to depict state transitions. In addition, open data from the Kaohsiung City Government’s 1999 call center were collected to address the aforementioned research objectives. The 1999 call center (service provider) offers citizens (customers) efficient consultant services to help them solve problems regarding the city government’s affairs or policies. Thus, this call center can be considered a complex service system.
This study revealed that the call center can utilize the analysis results of the Markov switching model on answer rates to predict service quality patterns. In addition, most first call resolution rates occurred under State 1 (value cocreation). To address problems caused by accidental or rare events, the call center should formulate policies to increase people and technical resources and improve service system effectiveness.
Enterprises currently focus on catering to customers’ needs and offering services through comprehensive service procedures to sustainably generate multiple values for customers, helping them to create values. Previous studies have mostly focused on analyzing the values of a service system and have failed to extensively explore actual value variations. Thus, the value variation measurement model proposed in the present study was able to analyze value variations of a set of call center data and illustrate value variations by using state transitions.
Journal of Business & Industrial Marketing 32(8) ,p.1159-1171