Differences in forecasting approaches between product firms and product-service systems (PSS)

This paper examines the forecasting implications for Product-Service Systems (PSS) applications in manufacturing firms. The approach taken is to identify the scope of operations for PSS applications by identifying all the activities associated with the total cost of ownership (TCO). The paper then develops a revenue model for manufacturing firms providing PSS applications. The revenue model identifies three generic revenue streams that provide the basis for discussion on the differences in forecasting approaches between product firms and Product-Service Systems (PSS) in manufacturing firms. The forecasting approaches are different due to the nature of customer involvement in the service aspect of PSS applications. This necessitates an understanding of the customer service experience and the factors affecting this such as the service profit chain which links profitability, customer loyalty and service value to employee satisfaction, capability and productivity. The forecasting approaches identified raises forecasting challenges for each of the three generic revenue sources. These challenges vary from the difficulty in obtaining the service user’s viewpoint through to difficulties in determining market acceptance of PSS applications

Queueing models for appointment-driven systems.

Many service systems are appointment-driven. In such systems, customers make an appointment and join an external queue(also referred to as the “waiting list”). At the appointed date, the customer arrives at the service facility, joins an internal queue and receives service during a service session. After service, the customer leaves the system. Important measures of interest include the size of the waiting list, the waiting time at the service facility and server overtime. These performance measures may support strategic decisionmaking concerning server capacity (e.g. how often, when and for how long should a server be online). We develop an ew model to assess these performance measures. The model is a combination of a vacation queueing system and an appointment system.Queueing system; Appointment system; Vacation model; Overtime; Waiting list;

Sistem Informasi Truecare CSR Telkom Berbasis Web Pada PT. Telekomunikasi Indonesia

TrueCare Information System Web-based Telkom CSR on Service Division PT. Telekomunikasi Indonesia. The results showed the application of Information Systems Customer Service Representative (CSR) to support the company in view of the technological and business concepts that are used to run its business processes through interactions with customers. The interaction that occurs between the customer and the company not only through service of course, but also through sales and marketing. In addition, the implementation of CSR Information Systems, supported by information systems and technology infrastructure as supporting its success. Broadly speaking, the application of Information Systems Customer Service Representative (CSR) can members an enhanced service to customers through existing developments, such as the standardization of patterns of Customer Service Representative (CSR), one stop service, utilization of information systems, and the development of service time due to time efficiency through a number of process automation services

FCFS Parallel Service Systems and Matching Models

We consider three parallel service models in which customers of several types are served by several types of servers subject to a bipartite compatibility graph, and the service policy is first come first served. Two of the models have a fixed set of servers. The first is a queueing model in which arriving customers are assigned to the longest idling compatible server if available, or else queue up in a single queue, and servers that become available pick the longest waiting compatible customer, as studied by Adan and Weiss, 2014. The second is a redundancy service model where arriving customers split into copies that queue up at all the compatible servers, and are served in each queue on FCFS basis, and leave the system when the first copy completes service, as studied by Gardner et al., 2016. The third model is a matching queueing model with a random stream of arriving servers. Arriving customers queue in a single queue and arriving servers match with the first compatible customer and leave immediately with the customer, or they leave without a customer. The last model is relevant to organ transplants, to housing assignments, to adoptions and many other situations. We study the relations between these models, and show that they are closely related to the FCFS infinite bipartite matching model, in which two infinite sequences of customers and servers of several types are matched FCFS according to a bipartite compatibility graph, as studied by Adan et al., 2017. We also introduce a directed bipartite matching model in which we embed the queueing systems. This leads to a generalization of Burke's theorem to parallel service systems

Simulation of queueing systems with many stations and of queueing networks using copulas

In this paper we will generate queueing systems with c stations where the inter-arrival time and the c service times depend through a c+1 copula C. We will consider two models: first when the customer does not know the order of service times for the free service channels (he/she chooses the service channel randomly), and the second when he/she knows this order (he/she chooses the fastest free service channel). The marginals can be exponential, Erlang or hyper-exponential.Queueing systems, copula, simulation.