Before revision:  Moreover, our models incorporate both dynamic busyness factors that depend on the agent workload as well as dynamic factors that depend on the inner-mechanics of the interaction. To understand how well our Hawkes modelsdescribe the message-timestamps, we compare the goodness-of-fit of these models on contact center data from industry .
After revision:  Moreover, our models incorporate both dynamic busyness factors that depend on the agent workload as well as dynamic factors that depend on the services. These models distinguish between the role of the customer and of the agent, reflect the service process's dynamic evolution over time based on its own history, and include additional behavioral and operational aspects, including the agent's number of simultaneous assignments and measures of the amount of information and sentiment each message contains. To evaluate our service co-production models, we apply them to an industry contact center dataset containing nearly 5 million messages .