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2.1 Product Service System (PSS)

2.1.5 PSS Evaluation

The sustainable or effective Product Service System (PSS) depends upon the evaluation phase.

This phase is a complex activity because PSS development involves many variables (Vasantha et al., 2015). Researchers focused on measuring and assessing customer needs, product/service requirements, PSS solutions, implementation and performances within the PSS evaluation literature.

About customer requirements evaluation, Song et al. (2013) proposed an industrial customer activity cycle to capture customers’ re uirements which could be vague and sub ective (Song et al., 2013). Their study integrates rough set theory and analytic hierarchy process approach for evaluating PSS requirements. Geng et al. (2011) emphasized PSS planning evaluation by mapping customer requirements to engineering requirements. Engineering requirements consist of product-related and service-related engineering characteristics. A series of approaches were used in their studies, such as the Analytic Network Process, Quality Function eployment, ata Envelopment rocess and u y ano’s uestionnaire (Geng et al., 2011).

Xing et al. (2013) proposed a value assessment model for product-service development. In their proposed value assessment model, measures of technical performances, cost and environmental impacts were considered. The net present value and lifecycle assessment approaches were utilized. In the study conducted by Xing et al. (2013) a solar heating system was considered to demonstrate the proposed value assessment model. Authors argue that it supports selecting and evaluating several product-service developments (Xing et al., 2013). However, the value assessment model is only applicable to the product-oriented type of PSS.

To assess sustainable PSS, Chou et al. (2015) argue that criteria of customer perception, social impact or value and employee perception are missing in measuring the performance of a PSS solution (Chou et al., 2015). To address these concerns, the authors developed multiple criteria of specifications in a hierarchical structure. They defined the efficiency of sustainable PSS as the ratio of product-service value and sustainable impact. Product-service value could be measured by the category of customer and employee perceptions. Similarly, the sustainable impact could be measured by working conditions, cost and consumption. The factors of customer perception category are tangibles, interactions, sustainability and prices. In contrast, commitment falls under the employee perception category. The assessment of a sustainable PSS considers environmental and socio-economic issues along with employee’s perceptions.

Lee et al. (2015) focused on measuring the PSS functional performances through a system dynamics approach. In general, system dynamics comprise conceptualization, formulation, testing and analysis (Lee et al., 2015). Based upon these, the authors proposed an analytic scheme of PSS functional dynamics that consist of five steps. Lee et al. (2015) defined PSS functional dynamics as “The functional performance of SS over time, depicting how the SS functions and changes over time”. In their proposed analytic scheme, the first step is to identify the functional structure of PSS, which is achieved by drawing a functional dependency network of PSS. The second step is to identify intensifying and weakening factors of each function. The third step covers specifying key policy issues, that could be achieved using a causal loop diagram. The fourth step is analyzing the functional dynamics of PSS. Assessing the functionality of PSS and setting the goal and strategy of the firm is the fifth step. However, their study restricts only to the economics of PSS functional performances.

From the viewpoint of customers and providers, Yoon et al. (2012) present an evaluation method for designing a PSS. It involves quantitative and qualitative approaches and is demonstrated using a car-sharing service example. The evaluation factors considered in their study are expected value, intention to adopt and preferred use of service. The evaluation factors for providers are economic, political and technological feasibility, environmental and relationships with competitive providers. Service model feasibility tests and survey methods were employed to present an evaluation guideline for designing a new PSS. The results highlighted that minimizing the usage of car rate could reduce the consumption of fossil fuel, the number of private cars could be reduced by an increase in the number of customers opting for car-sharing services (Yoon et al., 2012).

To validate the performance of a car-sharing service model, Alfian et al. (2014) used simulation techniques and fuzzy classification. The objectives in their study were to provide the best service to customers and maximize the income for car-sharing service providers (Alfian et al., 2014). The criteria for service providers are profit per day, utilization ratio and acceptance ratio. Service models include destination service (round trip, one-way, undeclared) and relocation technique (static inventory balancing, static shortest time, rebalancing). The simulation results highlighted those service models offering the round trip, one-way and static shortest time is the best service to customers. However, the limitation of their study is that considering few relocation techniques and comparison with existing transportation is missing.

In service engineering, contents and channels are the fundamental concepts of services (Shimomura et al., 2008). The functional and entity importance, which are the service’s structural elements, could be measured quantitatively. Therefore, Shimomura et al. (2008) proposed a service evaluation method using Quality Function Deployment (QFD) and demonstrated using a cloth washing service. The method consists of seven steps, such as (i) establishing the importance of receiver’s state by analytic hierarch process; (ii) creating a service quality table which will be similar to the QFD; (iii) structuring the receivers state parameters and obtaining importance; (iv) obtaining the content of parameters, which is parameters that change in receiver’s situational; (v) considering indirect interactions using the DEMATEL method; (vi) obtaining service channel parameters; (vii) deploying the service functions.

An integrated service evaluation framework and a service process model was proposed by Watanabe et al. (2012). The service process model was developed for car-rental service and bike-rental service. In their proposed service process model covers elements such as consumer, organization, natural resources and environment. In addition, a simulation tool to evaluate service processes was presented quantitatively (Watanabe et al., 2012). Determining the meaningful activities of different stakeholders in the simulation process was not considered in their study. To evaluate a PSS, Sun et al. (2012) proposed a product-service performance method. They mentioned that the interrelationship between PSS provider and receiver is referred to as product-service relationships (Sun et al., 2012). Product-Service relationships were described based upon product-service network and product-service chain. The factors considered in their study were time, cost, quality, stability and reliability to measure the product-service performance.

Kimita et al. (2009) proposed a method to measure customer satisfaction in the early stages of PSS, which could aid designers in comparing PSS design solutions (Kimita et al., 2009). To achieve this purpose, the authors proposed two models: the view model and the satisfaction- attribute function (Kimita et al., 2009). The view model is about identifying the customer’s state after experiencing the product or services. At the same time, the satisfaction-attribute function was used to quantify customer satisfaction. The satisfaction-attribute function is expressed through regression analysis from survey data. The function parameters considered in their study were expectations, uality and satisfaction. ere, designer’s emphasi e customer expectations and utilize them in the iterative design process at the conceptual stages. However, customer importance could change over time. Customer’s product and service experiences may differ from the competitive advantage available in the market. Their proposed method restricts considering a single case study to express customer satisfaction.

Table 2.6: PSS evaluation perspectives, methods and case studies PSS evaluation


PSS evaluation methods Case example References Customer requirements Rough set theory and Analytic

Hierarchy Process

Air compressors system

Song et al. (2013) Customer requirements Analytic Network Process (ANP).

Quality Function Deployment (QFD), Dara Envelopment Process, fu y ano’s uestionnaire

Metering pumps and related services

Geng et al. (2011)

Customer satisfaction Questionnaire survey, non-linear function

Domestic in-flight service

Kimita et al.

(2009) Customer acceptance System dynamics (functional

dependency network and casual loop diagrams)

u-healthcare system Lee et al. (2015)

Product-Service performance


Product-Service network and chain

Aviation product and related services

Sun et al. (2012) Service assessment Simulation Rental services (car

and bike)

Watanabe et al.

(2012) Service assessment Questionnaire, QFD, DEMATEL Cloth washing


Shimomura et al.

(2008) Service assessment Service model feasibility test,


Car sharing service Yoon et al. (2012) Service assessment Simulation techniques and fuzzy


Car sharing service Alfian et al. (2014)

Sustainability Questionnaire Conceptual Chou et al. (2015)

Sustainability Net Present Value and life Cycle Assessment (LCA)

Solar heating system Xing et al. (2013)

Table 2.6 represents the evaluation of PSS perspectives, methods and case studies in the literature. Here we can interpret that most of the evaluation or assessment was adopted from the customer perspective, although PSS design involves several stakeholders. Moreover, the

methodology applied in evaluating PSS studies were questionnaire, survey and multi-criteria decision-making methods.