Achieving customer satisfaction through product–service systems

Accepted Manuscript

Achieving Customer Satisfaction through Product-Service Systems Jeh-Nan Pan , Hung Thi Ngoc Nguyen PII: DOI: Reference:

S0377-2217(15)00390-2 10.1016/j.ejor.2015.05.018 EOR 12942

To appear in:

European Journal of Operational Research

Received date: Accepted date:

3 September 2014 4 May 2015

Please cite this article as: Jeh-Nan Pan , Hung Thi Ngoc Nguyen , Achieving Customer Satisfaction through Product-Service Systems, European Journal of Operational Research (2015), doi: 10.1016/j.ejor.2015.05.018

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ACCEPTED MANUSCRIPT Highlights

We propose an approach for achieving customer satisfaction in manufacturing firms. The key criteria can be identified through an integrated BSC and MCDM approach. A questionnaire survey was conducted in 24 manufacturing firms from 3 countries. The results show that various customer perspectives need to be further improved. We provide a procedure for identifying key criteria and their interrelationships.

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ACCEPTED MANUSCRIPT Achieving Customer Satisfaction through Product-Service Systems Jeh-Nan Pan*a and Hung Thi Ngoc Nguyenb a b

Department of Statistics, National Cheng Kung University, Tainan 70101, Taiwan, ROC.

Institute of International Management, National Cheng Kung University, Tainan, Taiwan. Abstract

The purpose of this research is to help manufacturing companies identify the key

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performance evaluation criteria for achieving customer satisfaction through Balanced Scorecard (BSC) and Multiple Criteria Decision Making (MCDM) approaches. To explore the causal relationships among the four dimensions of business performance in Balanced Scorecard as well as their key performance criteria, a MCDM approach combining DEMATEL and ANP techniques is adopted. Subsequently, the MCDM framework is tested

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using Delphi method and a questionnaire survey is conducted in 24 manufacturing firms from Taiwan, Vietnam and Thailand.

The research findings indicate that manufacturing companies should focus more on improving customer perspectives such as customer satisfaction and customer loyalty by integrating products and services innovation and providing diversified value-added productIn

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service offerings as well as developing close long-term partnership with customers.

addition, the classification of importance and improvability into four strategic planning zones

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provide practicing managers with a decision making tool for prioritizing continuous improvement projects and effectively allocating their resources to those key criteria identified

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in the strategic map for business performance improvement. By identifying critical criteria and their interrelationships, our research results can help

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manufacturing companies enhance their business performance in both financial and nonfinancial perspectives. They can also serve as valuable guidelines and references for manufacturing companies to achieve better customer satisfaction through sustainable

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product-service system practices.

Keywords: Product-service system, Customer satisfaction, Balanced scorecard, DEMATEL, ANP.

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Corresponding author. Tel: +886 6 2757575; fax: +886 6 2342469 E-mail address: [email protected] (J.N. Pan), [email protected] (H. T. N. Nguyen) Postal address: No.1, University Road, Tainan City 701, Taiwan (R.O.C.)

ACCEPTED MANUSCRIPT 1. Introduction In recent years, the discussions on the topic of “transition to service” by manufacturing companies have been growing rapidly, not only in academia, but in business practices as well. This is a result of dramatic changes in customer expectations, the destruction of product margin, together with pressures from intense competition and environmental movement that have driven many manufacturing companies to shift their business focus from a traditional pure product orientation approach to an integrated product-service system in order to secure

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their profits and actively manage their sustainability (Ahamed, Inohara, & Kamoshida, 2013). The concept of product-service system (PSS) can be referred to as a solution to integrate services with products through alternative product-uses and adding more value to customers. Its ultimate objective is to improve a company’s profitability and competitiveness, as well as to satisfy customers’ needs while minimizing environmental impact (Manzini & Vezzoli,

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2003). Basically, there are three main categories of PSS -- Product-oriented, Use-oriented and Result-oriented as suggested by Tukker (2004). Firstly, Product-Oriented Services refer to mainly a supply of products sold with extra added services which are necessary during the products’ usage period, and involves two sub-categories: (1) product-related services like

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insurance or maintenance contracts, and (2) advice or consultancy. This is very common in business-to-business markets where providers offer extra services like maintenance and repair

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terms to customers in supporting their sales functions. The second type is Use-Oriented Services which mainly focus on selling the use or availability of products together with valueadded services as a package while the asset ownership remains with the providing companies.

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Examples of this include product leasing, sharing, and product pooling such as car sharing or rental services. Furthermore, Result-Oriented Services focus on the result or competency

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consented by both the service provider and customer without a pre-determined product involvement; product ownership also remains with the company. These services comprise of

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activity management or outsourcing (cleaning service), pay-per-service unit (e.g., photocopy service, self-service clothes washing), or functional result. According to Baines et al. (2007), PSS not only causes minimum negative environmental

impact but also further reaches sustainability by maximizing social well-being and optimizing economic added value. Furthermore, pursuing servitization or product-service system strategies may also lead to significant transformation in firms’ organizational structures, business capabilities improvements and relationships with customers as well as suppliers (Neu & Brown, 2008). Therefore, these would require manufacturers to take proactive action in improving the business’s learning capability, enhancing internal processes and efficiently

ACCEPTED MANUSCRIPT managing customer relationships in order to maximize service output and achieve customer satisfaction. Recently, Vasantha et al. (2012) presented a good literature review of productservice systems’ design methodologies. Their review showed that the field of PSS design is still at an initial stage of development and substantial research is required to develop an efficient PSS design methodology. Li et al. (2014) considered a product-service supplier chain that comprises of a manufacturer and a retailer. They treated PSS as a market proposition that extends the traditional functionality of a product by incorporating additional

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services. Zhang et al. (2015) examined the pricing of product and value-added services and their study show that a manufacturer choosing a pricing strategy should consider consumers’ initial expectations regarding the value-added service quality. Ding et al. (2015) discussed an environmental and economic sustainability-aware resource service scheduling problem during the product-service delivery phase of industrial PSS.

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Although there is a high demand for deeper insight into the business benefits of sustainable PSS from a quantitative point-of-view, most of the literature found on this topic only emphasize on case studies, reviews, or qualitative assessments, while comprehensive quantitative research methods like statistical analysis on survey data are still lacking. The

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goal of our paper is to fill this research gap. Balanced Scorecard, which is widely used as a helpful performance indicator, was suggested as a good evaluation tool for the PSS approach

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(Jiang, Luh, & Kung, 2010). However, when assessing the effectiveness of a sustainable product-service system in manufacturing firms, besides considering factors and sub-factors

investigation.

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affecting performance, the degree of influence of these factors are also in need of

Hence, this paper aims to adopt the Balanced Scorecard model which integrates the four

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perspectives of business performance (financial, customer, internal process, and learning and growth) with support of the Multiple Criteria Decision Making (MCDM) approach

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combining DEMATEL and ANP techniques to provide a better analysis of the key criteria in measuring business performance with real applications in manufacturing firms in three countries – Taiwan, Vietnam and Thailand. The objectives are to identify the performance evaluation criteria for manufacturing companies to pursue higher customer satisfaction through product-service system (PSS) practices. Moreover, it is necessary to determine the relative weights of the criteria as well as the degree and direction of influence among the perspectives of the Balanced Scorecard (BSC) and their corresponding criteria through a MCDM approach. 2. Literature review

ACCEPTED MANUSCRIPT 2.1 Theoretical background The contingency theory suggests that there is a relationship between the organizational performance and the alignment of three factors: environment, strategy, and organizational design (Neu & Brown, 2005). Therefore, the transition from product to service focus will require transformation in the entire organizational structure, operations, and strategies which should all align with changes in the relevant marketplace. On the other hand, the resource-based view argues that superior firm performance is

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attributable to superior resources, and resources both tangible and intangible can be strategically managed to create more competitive advantages for companies (Schmidt & Keil, 2013). Compared to pure service companies, manufacturing firms may have different ranges of relevant resources, some of which can become advantageous for them when shifting from a product-focus to service orientation.

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Furthermore, the economies of scale and scope from both customers’ and manufacturers’ perspectives strongly indicate that customers will tend to purchase associated services from the same product manufacturer. Therefore, a sustainable product-service system can open up new business opportunities for manufacturing firms to achieve higher competitive advantage

2.2 Balanced scorecard approach

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and sustain the entire business in the long run (Akan, Ata, & Lariviere, 2011).

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This paper employs Balanced Scorecard as the framework for the evaluation of productservice system and business sustainability. Balanced Scorecard, proposed by Kaplan and

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Norton (1992), comprises of four dimensions: financial, customer, internal process, and learning and growth perspectives. It is an effective management tool that links operational and non-financial organization’s activities and assesses them using causal relationships with

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the company’s long-term strategies. These not only significantly influence the economic success of a business but also help to integrate environmental and social concerns into the

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organization’s management, similar to the three main goals of a sustainable product-service system. According to Kaplan and Norton (2004), there are causal relationships among the four dimensions; for example, the performance of the learning and growth perspective will lead to the improvement of the internal process to meet a company’s strategies in terms of financial and customer perspectives. For any profit-seeking organization, the ultimate goal is a significant increase in economic values through two approaches: revenue growth and productivity (Kaplan & Norton, 2001). The financial perspective of Balanced Scorecard emphasizes how the sustainable product-

ACCEPTED MANUSCRIPT service system strategy accommodates the shareholders’ financial expectations in fostering growth, profitability and productivity which can be represented by some criteria such as revenue growth rate, return on investment and asset utilization. Besides aiming for profits, to secure business sustainability, all companies have to continuously maintain a high level of customer satisfaction. Many firms are adopting different types of product-service systems to extend their existing offerings to customers, focusing on some important factors such as customer satisfaction, customer loyalty or

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retention, customer referrals, and price relative to competition (Papalexandris, Ioannou, Prastacos, & Eric Soderquist, 2005).

Once the organization has decided the customer needs and financial performance targets, it can determine the corresponding methods to achieve a different value proposition for the customers and obtain higher financial performance. The internal process perspective is meant

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to propose valid objectives to track firm activities which cover: (1) Operations management, (2) Customer management, (3) Innovation and (4) Regulatory and social measures (Kaplan & Norton, 2001; Niven, 2006).

The learning and growth perspective is the last region of Balanced Scorecard, in which

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managers describe the employee capabilities and skills, information technology and organization environment necessary to support a strategy (Kaplan & Norton, 2001). Shifting

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an entire business from a product-based system to a product-service system implicates dramatic changes in the company and requires the involvement of employees from all levels

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of the organization.

3. Research design and methodology

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3.1 Questionnaire design and sampling plan The questionnaires were designed in two stages as follows. In stage 1, a number of industry experts were asked to answer the questionnaire and important criteria were selected

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afterwards. In stage 2 of the questionnaire design, the results of stage 1 were adopted. Moreover, the combination of DEMATEL and ANP methods was also integrated. The purpose of this stage’s survey is to determine the weights of the important criteria in four (4) dimensions of BSC and to reach consensus among answers using Delphi method. The four (4) dimensions of the business performance based on Balanced Scorecard concept are known as: (A) Financial Perspective, (B) Customer Perspective, (C) “Internal Process” with sub-dimensions of Operations Management, Customer Management and Innovation, and lastly, (D) “Learning and Growth” with sub-dimensions of Human Capital, Information

ACCEPTED MANUSCRIPT Capital and Organization Capital. Based on the literature review for sustainable productservice system and Balanced Scorecard practices, the research framework was designed with twenty-three (23) criteria corresponding to these four (4) dimensions and sub-dimensions as shown in Figure 1. The questionnaire was designed in parallel translation (English, Chinese and Vietnamese) and distributed in printed version, online or direct interviews. The target respondents are high-level managers who are currently working in manufacturing firms in Taiwan, Vietnam, Thailand and have professional knowledge as well as managerial

Goal

Dimensions

Sub-dimensions

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C1: Customer Satisfaction C2: Customer Loyalty C3: Customer Referrals C4: Customer Partnership C5: Price Relative to Competition

B: Customer Perspective

OM: Operations Management CM: Customer Management

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C: Internal Processes Perspective

IN: Innovation

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Business Performance

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RS: Regulatory and Social

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Criteria

F1: Revenue Growth Rate F2: Return on Investment F3: Asset utilization

A: Financial Perspective

D: Learning and Growth Perspective

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experience related to product-service system and Balanced Scorecard implementation.

HC: Human Capital

OM2: Defect Rate OM1: Transaction Cost Reduction CM1: Customer Data Availability CM2: Effective Problem Solving Management IN1: Product and Service Diversification IN2: Product/Service Innovation RS1: Relationship with External Stakeholders RS2: Environmental Emissions RS3: Waste Reduction HC1: Employee Education HC2: Employee Professional Ability

IC: Information Capital

IM1: Knowledge Sharing

OC:Organization al Capital

OC1: Employee Satisafaction OC2: Product/Service Learning OC3: Organizational Alignment

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Balanced Scorecard Dimensions

Figure 1. Multiple criteria decision-making framework 3.2 DEMATEL method Decision Making Trial and Evaluation Laboratory (DEMATEL) is a powerful method which can deal with large problems of group decision-making by assessing the direct and indirect relationships among all elements as well as studying the direction and intensity of the relationships among already-defined components at the same time (Chen, Hsu, & Tzeng, 2011). The results of DEMATEL can be transferred into a visual causal diagram, called

ACCEPTED MANUSCRIPT impact-relation map (IRM), showing the interrelation among components. IRM can also help decision makers discover which factors or sub-factors influence each other and develop a complete decision model to solve the identified problems. Listed below are the calculation procedure of DEMATEL method adapted from Ou Yang, Shieh, Leu, and Tzeng (2008) and Yeh and Huang (2014): Step 1: Calculate the Initial Average Matrix. The respondents were asked to indicate the degree of influence factor i has on factor j

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(denoted as aij) corresponding to the five scales: 0: No impact; 1: Low impact; 2: Medium impact; 3: High impact; 4: Very high impact, then pairwise comparisons among criteria was measured to determine the initial average matrix A. Step 2: Normalize the Initial Direct Influence Matrix.

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The normalized initial influence matrix (X) showing the direct influence that a criterion exerts or receives from another, can be obtained by multiplying the average matrix A by k value: 𝑋 =𝑘×𝐴 1

, i, j = 1, 2,...., n

𝑛 1≤𝑥≤𝑛 ∑𝑗=1 𝑎𝑖𝑗

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and lim𝑚→∞ 𝑋 𝑚 = [0]𝑛×𝑛 ,

(2)

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𝑘 = max

(1)

where 𝑋 = [𝑥𝑖𝑗 ]𝑛×𝑛 , 0 ≤ 𝑥𝑖𝑗 < 1, 0 < ∑𝑛𝑗=1 𝑥𝑖𝑗 , ∑𝑛𝑖=1 𝑥𝑖𝑗 ≤ 1 , and only one row sum or

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column sum equals 1.

Step 3: Calculate the Total-influence Matrix.

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The total influence matrix is the summation of the direct and indirect effects of problems decreased along the powers of X, noted as: 𝑇 = 𝑋(𝐼 − 𝑋)−1

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(3)

and lim𝑚→∞ 𝑋 𝑚 = [0]𝑛×𝑛 , where 𝑇 = [𝑡𝑖𝑗 ]𝑛×𝑛 , i, j = 1, 2, ….., n This can be formed as the row sums and column sums of the matrix T which represents the direct and indirect effects of criterion i on other criteria. 𝑑 = (𝑑𝑖 )𝑛×1 = [∑𝑛𝑗=1 𝑡𝑖𝑗 ]

𝑛×1

(4)

ACCEPTED MANUSCRIPT 𝑟 = (𝑟𝑗 )𝑛×1 = (𝑟𝑗 )′1×𝑛 = [∑𝑛𝑖=1 𝑡𝑖𝑗 ]1×𝑛

(5)

When i = j, 𝑑𝑖 and 𝑟𝑖 can perform as a good index representing the strength of the influences given and taken by a criterion as summarized in Table 1: Table 1 Summary of the Prominence and Relation Index Meaning

Indication

(𝒅𝒊 + 𝒓𝒊 )

Degree of relationship criterion i has How much importance the criterion has with other criteria

(𝒅𝒊 − 𝒓𝒊 )

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Index

The gap between given and taken Can divide criteria into cause and effect groups influence The criterion influences others

The criterion belongs to the cause group

(𝑑𝑖 − 𝑟𝑖 ) <0

The criterion is influenced by others

The criterion belongs to the effect group

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(𝑑𝑖 − 𝑟𝑖 ) >0

Notes: d – row sum, r – column sum of the total-influence matrix T

Step 4: Set a Threshold and Acquire the Impact-Relation Map (IRM) It is necessary to set a threshold value to limit the number of factors shown in IRM by

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eliminating the ones with minor effect. According to Sumrit and Anuntavoranich (2013), the threshold value 𝛼 can be calculated by taking the average of all factors in total-influence

𝑛 ∑𝑛 𝑖=1 ∑𝑗=1[𝑡𝑖𝑗 ]

𝑁

, where

(6)

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𝛼=

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matrix T:

N denotes the total number of factors in matrix T

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Any factor that is smaller than 𝛼 would be eliminated while the bigger ones would be kept for drawing impact-relation map. Thus, these causal diagrams will provide better insights about the interrelationship among criteria.

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3.3 Analytic Network Process (ANP) technique Analytic Network Process (ANP) is a good approach which helps decision makers deal with

both dependence of criteria within a cluster and among different clusters. However, these criteria are usually interdependent and are hard to acquire individual weights. Therefore, our study adopts the DANP technique aiming to acquire a more accurate evaluation of firms’ performance by using DEMATEL to produce a relationship diagram for product-service system oriented firms’ performance evaluation and employing ANP to obtain the weights of the evaluated criteria and then rank them respectively.

ACCEPTED MANUSCRIPT Based on the results obtained from DEMATEL, the procedures of ANP calculations are continued by the following steps: Step 5: Establish Unweighted Supermatrix by Pairwise Comparisons. The total influence matrix T for criteria obtained from DEMATEL results is adopted in ANP process to determine the initial supermatrix and calculate the unweighted supermatrix 𝑊𝑢 . The weighted supermatrix is obtained by transforming the sum of each column into unity = 1. Each element in a column is divided by the number of clusters so that the column sum

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will be exactly unity (=1).

Step 6: Obtain the Weighted Supermatrix by Multiplying the Normalized Matrix Acquired from DEMATEL.

Since the influence of each cluster on the others may not be the same, the weighted supermatrix (𝑊𝑤 ) is then determined by multiplying the unweighted supermatrix for criteria

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𝑊𝑢 and the transposition of the normalized 𝛼-cut total influence matrix for dimensions 𝑇𝑠 .

(7)

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𝑡 𝑠 11 × 𝑊11 … 𝑡 𝑠 𝑖1 × 𝑊12 … 𝑡 𝑠 𝑛1 × 𝑊1𝑛 ⋮ ⋮ ⋮ 𝑠 𝑠 𝑠 𝑡 × 𝑊 … 𝑡 × 𝑊 … 𝑡 × 𝑊𝑖𝑛 , 𝑊𝑤 = 1𝑗 21 𝑖𝑗 𝑖𝑗 𝑛𝑗 ⋮ ⋮ ⋮ 𝑠 𝑠 𝑠 [𝑡 1𝑛 × 𝑊𝑛1 … 𝑡 𝑖𝑛 × 𝑊𝑛𝑗 … 𝑡 𝑛𝑛 × 𝑊𝑛𝑛 ]

where 𝑡 𝑠 𝑖𝑗 = 𝑡 𝛼 𝑖𝑗 /𝑑𝑖 denotes a normalized 𝛼-cut total influence matrix and 𝑊𝑖𝑗 denotes an

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unweighted supermatrix for criteria 𝑊𝑢

Step 7: Obtain a Long-Term Stable Supermatrix by Limiting The Weighted Supermatrix.

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Raise the weighted supermatrix to a sufficiently large power k until the weights have converged and stabilized (i.e. the weight values of the same rows in the stable supermatrix

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are all the same). The long-term stable supermatrix is given as lim𝑘→∞ 𝑊𝑤𝑘

(8)

3.4 Delphi method

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Delphi method was adopted to verify the respondents’ answers by repeatedly collecting

experts’ answers via interview or questionnaire survey until a consensus on resolving problems is reached (Linstone & Turoff, 1975). To achieve a more reliable consensus among an expert group, the following three phases were carried out: (1) brainstorming or collecting a list of relevant factors and asking experts for validation, (2) narrowing down the factor list obtained from Stage 1 survey to a manageable size based on the rating of importance from respondents, and (3) conducting the Stage 2 survey to rank relevant factors and reach a consensus.

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4. Research results and data analysis 4.1 Data collection The data collection process was carried out within three months beginning March 4th to May 31st, 2014. A list of 23 criteria for evaluating manufacturing firms’ improvement performance was collected from a comprehensive literature review, and then narrowed down to 18 in Stage 1 survey by asking the experts’ opinions on the relative importance of given criteria

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(the higher score indicates greater importance in a scale ranging from 0 to 10). In this stage, six (6) industry experts (4 from Taiwan, 1 from Vietnam and 1 from Thailand), who are managers in manufacturing companies with experiences in implementing Balanced Scorecard and service practices, were invited to fill out the questionnaires. According to Saaty (1980), good consistency and the effectiveness of the pair-wise comparisons can be ensured by

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limiting the number of criteria. Following Pareto’s 80/20 principle and the criteria suggested by Chen et al. (2011), 18 out of a total 23 performance criteria with means of 7.5 and above were selected, which accounted for 80.98% of the cumulative percentage (see Table 2 and Table 3 for details). The difference between 18 criteria and 19 criteria has been further verified using a statistical comparison test. The result indicated that there is a significant difference between

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these two groups at the significance level of α = 0.2 (Glickman, Rao, & Schultz, 2014) with p = 0.165 < α = 0.2. According to the comparison test result, five items with lower importance scores were

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deleted. Thus, after performing a pair-wise comparison test, the number of key performance criteria can be further narrowed down to 18 after Stage 1 survey and these 18 criteria can be grouped into

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their respective dimensions/perspectives accordingly.

Then, the Stage 2 questionnaires were designed based on Stage 1’s results. Combining the

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DEMATEL and ANP methods, we compared the paired results of the criteria importance and reached a consensus among answers in two rounds using Delphi method. A total of 30 valid questionnaires were acquired from managers of different levels in 24 manufacturing

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companies with experiences in implementing BSC and product-service practices in three countries: Taiwan (70%), Vietnam (20%) and Thailand (10%). After the first round surveys for Stage 2 was done, another round of questionnaires were distributed to our respondents. The statistical inconsistency test showed that the responses of all experts were consistent and that there were no significant differences among these countries. The inconsistency rates of these questionnaires were 0.825% and 1.716% respectively, which indicated that the judgment matrix reached a reasonable level of consistency (Saaty & Vargas, 1991). The corresponding credibility percentage were 99.175% and 98.284% respectively. According to

ACCEPTED MANUSCRIPT Mitha et al. (2012), group consensus can be achieved if 70% of experts’ agreement is reached. In this study, the results of two rounds surveys showed that the change in rates was less than 1%, which meant the consensus was 99% approx. Therefore, this study is considered to achieve opinion stability and there is no need to conduct another round of survey. Table 2

Standardized

Importance

Important values

Customer satisfaction

9.833

2.235

Return on investment

9.167

1.385

Price relative to competition

9.000

1.173

Customer partnership

8.833

Revenue growth rate

8.667

Defect rate

8.667

Customer data availability

8.667

Customer loyalty

8.500

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Effective problem-solving

8.500

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management

Percentage

Cumulative

(%)

Percentage (%)

5.291

5.291

4.933

10.224

4.843

15.067

0.960

4.753

19.821

0.748

4.664

24.484

0.748

4.664

29.148

0.748

4.664

33.812

0.536

4.574

38.386

0.536

4.574

42.960

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Level of

Criteria

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List of Criteria Ordered by Level of Importance

Employee professional ability

8.333

0.323

4.484

47.444

Product/service learning

8.000

-0.102

4.305

51.749

8.000

-0.102

4.305

56.054

Product/service innovation

7.833

-0.314

4.215

60.269

Employee satisfaction

7.833

-0.314

4.215

64.484

7.667

-0.526

4.126

68.610

7.667

-0.526

4.126

72.735

Environmental emissions

7.667

-0.526

4.126

76.861

Waste reduction

7.667

-0.526

4.126

80.987

Employee education

7.500

-0.739

4.036

85.022

Knowledge sharing

7.333

-0.951

3.946

88.969

Customer referrals

7.000

-1.376

3.767

92.735

6.833

-1.588

3.677

96.413

6.667

-1.801

3.587

100.000

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Organizational alignment

Transaction cost reduction Product and service

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diversification

Relationship with external stakeholders Asset utilization

ACCEPTED MANUSCRIPT Level of

Standardized

Percentage

Cumulative

Importance

Important values

(%)

Percentage (%)

Average

8.080

0.000

Maximum

9.833

2.235

Minimum

6.667

-1.801

Standard deviation

0.785

1.000

Criteria

Note: Level of importance > 7.5 and cumulative percentage ≈ 80% are used for selecting important

Table 3 List of the 18 Remained Criteria after Stage 1 Survey Perspective Finance

Customer

Internal Process

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Criteria

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criteria as suggested by Chen et al. (2011).

Operations Management Revenue growth rate

Customer satisfaction

(C1)

(C3)

Return on investment (C2)

Customer loyalty (C4)

(C5)

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Price relative to

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competition (C6)

Defect rate (C8)

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Customer partnership

Transaction cost reduction (C7)

Learning and Growth

Human Capital Employee professional ability (C15) Organizational Capital

Customer Management

Employee satisfaction (C16)

Customer data availability (C9)

Product/service learning (C17)

Effective problem-solving

Organizational alignment

management (C10)

(C18)

Innovation Product and service diversification (C11) Product/service innovation (C12) Regulatory and Social Environmental emissions (C13) Waste reduction (C14)

4.2 Analysis of DEMATEL results DEMATEL method was adopted in this study to determine the key criteria for business performance related to a product-service system and also to measure the relationships among dimensions and their respective criteria. The experts were asked to evaluate the direct impact

ACCEPTED MANUSCRIPT of any two criteria/dimensions using pairwise comparison following the five leveled scales of 0 (indicates “no impact”) to 4 (indicates “very high impact”). Based on the data collected in the first and second rounds, the DEMATEL and ANP calculations were used to compare the weight changing rates from both rounds of surveys. The DEMATEL calculations were proceeded for both dimensions and criteria. Following step 1 to step 4, the total influence matrix T and the Impact Relation Map (IRM) representing the

Table 4 Total Influence Matrix (𝑇𝐷 ) among Dimensions A

B

C

D

Finance (A)

4.051

4.369

4.393

4.025

Customer (B)

4.527

4.329

4.618

4.247

Internal Process (C )

4.585

4.662

4.454

4.352

Learning and Growth (D)

4.199

4.273

4.349

3.768

r

17.363

17.815

16.393

Note: T = 𝑋(𝐼 − 𝑋)

and lim𝑚→∞ 𝑋

17.632 𝑚

17.721 18.053 16.590

= [0]𝑛×𝑛 , where 𝑇 = [𝑡𝑖𝑗 ]𝑛×𝑛 , i, j = 1, 2,…..,n

D

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B

AC

16.838

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−1

d

AN US

Dimensions

CR IP T

relationships among dimensions are shown in Table 4 and Figure 2, respectively.

C

B

A

A: Finance C: Internal Process

C

D

A

B: Customer D: Learning and Growth

Figure 2. The impact relation map among four dimensions (threshold value 𝛼 = 4.325)

Following step 1 to step 3, the total influence matrix for all 18 criteria is obtained in Table 5. Table 5 Total-Influence Matrix among Criteria C1

C2

C3

C4

C5

C6

C7

C8

C9

C10

0.431

0.462

0.478

0.468

0.444

0.439

0.414

0.45

0.349

0.468

0.457

0.479

0.273

C17

C18

d

0.343

0.473

0.396

0.434

0.409

7.667

C2

0.461

0.36

0.429

0.421

0.402

0.399

0.385

0.413

0.313

0.425

0.415

0.439

C3

0.471

0.423

0.399

0.459

0.431

0.412

0.383

0.437

0.342

0.464

0.432

0.457

0.248

0.32

0.432

0.359

0.396

0.378

6.996

0.256

0.313

0.457

0.374

0.413

0.382

C4

0.461

0.416

0.46

0.383

0.424

0.408

0.371

0.425

0.339

0.453

0.427

7.306

0.452

0.25

0.308

0.443

0.365

0.405

0.375

C5

0.442

0.403

0.437

0.427

0.346

0.39

0.359

0.402

0.324

0.431

7.167

0.406

0.43

0.239

0.295

0.427

0.348

0.389

0.357

C6

0.431

0.394

0.412

0.407

0.384

0.323

0.358

0.385

0.3

6.85

0.4

0.391

0.417

0.231

0.297

0.405

0.328

0.365

0.336

6.565

C7

0.415

0.386

0.388

0.377

0.362

0.365

0.294

0.37

C8

0.448

0.413

0.443

0.429

0.402

0.393

0.369

0.352

0.282

0.382

0.371

0.39

0.229

0.297

0.395

0.323

0.363

0.339

6.327

0.299

0.415

0.4

0.425

0.243

0.321

0.435

0.359

0.402

0.368

C9

0.348

0.313

0.347

0.34

0.323

0.304

0.28

6.916

0.295

0.216

0.336

0.323

0.343

0.188

0.235

0.334

0.274

0.312

0.28

C10

0.461

0.421

0.465

0.451

0.425

0.401

5.391

0.377

0.411

0.336

0.388

0.425

0.451

0.255

0.322

0.457

0.376

0.419

0.379

C11

0.451

0.411

0.436

0.428

0.404

7.22

0.395

0.368

0.399

0.323

0.425

0.359

0.443

0.241

0.305

0.439

0.352

0.41

0.365

6.953

C12

0.478

0.441

0.463

0.457

C13

0.271

0.25

0.259

0.254

0.429

0.423

0.389

0.426

0.347

0.455

0.446

0.405

0.264

0.326

0.472

0.381

0.436

0.39

7.428

0.238

0.236

0.23

0.241

0.187

0.255

0.242

0.263

0.134

0.219

0.275

0.22

0.247

0.229

C14

0.341

0.321

0.317

4.251

0.311

0.294

0.302

0.295

0.32

0.235

0.323

0.306

0.324

0.218

0.212

0.348

0.275

0.317

0.288

C15

0.473

0.435

5.346

0.465

0.449

0.429

0.414

0.397

0.437

0.338

0.465

0.445

0.474

0.278

0.352

0.409

0.392

0.433

0.398

C16

0.397

7.482

0.361

0.38

0.372

0.349

0.334

0.323

0.357

0.277

0.379

0.355

0.381

0.222

0.278

0.391

0.275

0.356

0.336

C17

6.122

0.435

0.401

0.421

0.412

0.392

0.375

0.365

0.402

0.314

0.424

0.415

0.438

0.252

0.322

0.434

0.358

0.344

0.364

6.868

C18

0.409

0.376

0.385

0.377

0.353

0.339

0.336

0.366

0.28

0.383

0.366

0.388

0.228

0.289

0.397

0.336

0.362

0.289

6.258

r

7.623

6.987

7.383

7.224

6.83

6.653

6.293

6.89

5.4

7.272

6.979

7.397

4.249

5.353

7.423

6.09

6.804

6.264

119.114

M

ED

PT

C11

CE

Note: 𝑇 = 𝑋(𝐼 − 𝑋)−1 and lim𝑚→∞ 𝑋 𝑚 = [0]𝑛×𝑛 , where 𝑇 = [𝑡𝑖𝑗 ]𝑛×𝑛 , i, j = 1, 2,…..,n

AC

C12

C13

C14

C15

C16

AN US

Tc C1

CR IP T

ACCEPTED MANUSCRIPT

ACCEPTED MANUSCRIPT The row and column sums, d and r, represent the strength of influence that a criterion/dimension has given to and taken from others. The summation (d+r) indicates the correlation intensity or prominence of the criterion element. The summation with higher value means stronger effect. The difference (d-r) shows the direction of the relationship of one criterion towards other criteria. Positive (d-r) means that the criterion is the cause of other criteria while negative value indicates that the criterion is affected by other criteria. Hence,

Table 6

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the row and column sum values for all dimensions and criteria can be summarized in Table 6.

Summary of the influences given and received among dimensions and criteria Row Sum

Column Sum

Prominence

Relation

d

r

d+r

d-r

17.363

34.201

-0.524

Dimension A

16.838

Revenue growth rate

C1

7.667

7.623

15.29

0.044

Return on investment

C2

6.996

6.987

13.983

0.009

Customer

B

17.721

17.632

35.353

0.089

Customer satisfaction

C3

7.306

7.383

14.689

-0.077

Customer loyalty

C4

7.167

7.224

14.391

-0.058

Customer partnership

C5

6.85

6.83

13.681

0.02

Internal Process

C

18.053

17.815

35.868

0.239

Price relative to competition

C6

6.565

6.653

13.218

-0.088

C7

6.327

6.293

12.62

0.034

C8

6.916

6.89

13.805

0.026

C9

5.391

5.4

10.791

-0.009

C10

7.22

7.272

14.492

-0.052

C11

6.953

6.979

13.932

-0.026

C12

7.428

7.397

14.825

0.032

Environmental emissions

C13

4.251

4.249

8.499

0.002

Waste reduction

C14

5.346

5.353

10.699

-0.007

D

16.59

16.393

32.984

0.197

Employee professional ability

C15

7.482

7.423

14.906

0.059

Employee satisfaction

C16

6.122

6.09

12.212

0.033

Product/service learning

C17

6.868

6.804

13.672

0.065

Organizational alignment

C18

6.258

6.264

12.522

-0.006

13.235

0

Defect rate

PT

Customer data availability Effective problem-solving management

CE

Product and service diversification

AC

Product/service innovation

Learning & Growth

Mean

M

ED

Transaction cost reduction

AN US

Finance

ACCEPTED MANUSCRIPT The results show that Revenue growth rate (C1) has the strongest effects on other criteria with highest impact degree of (d+r) = 15.29, followed by Employee Professional Ability (C15) (14.906), Product/Service Innovation (C12) (14.925), Customer Satisfaction (C2) (14.689) and Effective Problem-Solving Management (C10) (14.492). The lowest influence value is Environmental Emissions (C13) with 8.499, indicating the least important factor towards business performance. The causal diagram among the dimensions and criteria are drawn accordingly using the

influences between the two elements.

CR IP T

values of (d+r) and (d-r) as shown in Figure 2, where double arrows indicate mutual

C5

C1

C1

C5

C4

C2

C2

AN US

C4

C3

C1: Revenue Growth Rate

C2: Return on Investment

C3: Customer Satisfaction C5: Customer Partnership

(1) Cause and effect diagram for Finance Perspectives

C13

C7

C12 C8

C9

C12

C17

C8

C13

C14 C11

C4: Customer Loyalty C6: Price Relative to Competition

(2) Cause and effect diagram for Customer Perspectives

M

C7 C14

C17 C15

C15 C16

C16 C11 C10

C8: Defect Rate C10: Effective Customer Problem Solving Management C12: Product/Service Innovation C14: Waste Reduction

PT

C7: Transaction Cost Reduction C9: Customer Data Availability C11: Product and Service Diversification C13: Environmental Emissions

ED

C9 C10

C18

C15: Employee Professional Ability C17: Product/Service Learning

C18 C16: Employee Satisfaction C18: Organizational Alignment

(4) Cause and effect diagram for Learning and Growth Perspectives

CE

(3) Cause and effect diagram for Internal Process Perspectives

C3

C6

C6

Figure 3. Cause and effect diagrams for the criteria in various dimensions

AC

According to DEMATEL results, Finance (A), Customer (B) and Internal Process (C) perspectives are mutually interrelated, which are denoted by the double side arrows connecting the three dimensions in Figure 2. A high financial performance would have good impact on the results of customer perspectives and internal processes. On the other hand, empowered customer indicators and effective internal processes may help to improve the financial results. Moreover, the enterprise’s internal processes have positive influence on customer management and vice versa. At the same time, good performance on learning and growth results in better improvement in internal processes. The findings obtained in this study are mostly consistent with the framework proposed by Kaplan and Norton (2004)

ACCEPTED MANUSCRIPT related to the Balanced Scorecard strategy maps linking intangible assets and value creating processes. However, while the study by Kaplan and Norton only showed a one-way effect of the relationships, our findings indicated that these dimensions actually can mutually influence each other. Overall, as can be seen in Table 6 and Figure 3, Revenue Growth Rate (C1) is the most important factor with influence strength index (d+r) of 15.290, followed by Employee professional ability (C15), Product/Service Innovation (C12) and Customer Satisfaction (C3),

CR IP T

with each criterion belonging to one dimension. On the other hand, three criteria of Internal Processes including Environmental Emissions (C13), Waste Reduction (C14) and Customer Data Availability (C9) have the least influence on other criteria. The total difference-relation index also shows that two criteria of Learning and Growth Perspectives (D) including Product/Service learning (C17) and Employee Professional Ability (C15), have the greatest

AN US

direct impact on other criteria with highest values of (d-r) = 0.065 and 0.059, respectively. Three criteria of Customer (B) including Price Relative on Competition (C6), Customer Satisfaction (C3) and Customer Loyalty (C4), on the other hand, are the most easily influenced by other criteria with the negative values of (d-r) = -0.088, -0.077 and -0.057,

4.3 Analysis of DANP results

M

correspondingly.

ED

After determining the interrelationships among criteria and dimensions of the business performance resulted from DEMATEL, the DANP technique is then continued to acquire the

PT

criteria’s relative influence weights following ANP procedures. The interactions among criteria can be determined from the unweighted supermatrix. However, in order to investigate

CE

the impact of all criteria and dimensions at the same time, it is necessary to obtain the weighted supermatrix, the limits of which can be used to determine the global weights for all criteria. Following step 5 to step 7, the results of weighted supermatrix and long-term stable

AC

supermatrix can be obtained and summarized in Table 7 and 8. Hence, the global weight for each criterion can be obtained from the long-term stable supermatrix. Dimension weights, local weights and their rankings were calculated respectively based on the acquired global weights, which are listed in Table 9.

CR IP T

ACCEPTED MANUSCRIPT

Table 7 Weighted Supermatrix-DANP C1

C2

C3

C4

C5

C6

C7

C8

C9

C10

C11

C12

C13

C14

C15

C16

C17

C18

C1

0

0

0.177

0.177

0.176

0.175

0.132

0.132

0.134

0.133

0.133

0.132

0.132

0.131

0

0

0

0

C2

0

0

0.159

0.159

0.16

0.161

0.122

0.122

0.12

0.121

0.121

0.122

0.122

0.123

0

0

0

0

C3

0.13

0.129

0.075

0.088

0.088

0.087

0.067

0.069

0.068

0.069

0.068

0.068

0.068

0.067

0

0

0

0

C4

0.128

0.127

0.087

0.073

0.086

0.086

0.065

0.066

0.067

0.067

0.066

0.067

0.066

0.066

0

0

0

0

C5

0.121

0.121

0.081

0.081

0.069

0.081

0.063

0.062

0.063

0.063

0.063

0.063

0.062

0.062

0

0

0

0

C6

0.12

0.121

0.078

0.078

0.078

0.068

0.063

0.061

0.06

0.06

0.061

0.062

0.062

0.064

0

0

0

0

C7

0.064

0.065

0.043

0.042

0.043

0.044

0.028

0.032

0.031

0.031

0.032

0.031

0.032

0.033

0.124

0.125

0.124

0.127

0.033

0.034

0.034

0.034

0.034

0.035

0.137

0.139

0.137

0.139

0.024

0.028

0.028

0.028

0.026

0.026

0.106

0.108

0.107

0.106

0.037

0.032

0.037

0.037

0.036

0.036

0.146

0.147

0.145

0.145

0.036

0.035

0.031

0.036

0.034

0.034

0.14

0.138

0.142

0.139

0.038

0.038

0.038

0.033

0.037

0.036

0.149

0.148

0.149

0.147

0.021

0.021

0.021

0.021

0.021

0.019

0.024

0.087

0.086

0.086

0.086

0.028

0.026

0.027

0.026

0.026

0.031

0.023

0.11

0.108

0.11

0.11

0.067

0.067

0.068

0.068

0.068

0.068

0.068

0

0

0

0

0.07

0.07

0.049

0.048

0.048

0.048

0.035

0.031

C9

0.054

0.053

0.038

0.038

0.038

0.037

0.027

0.026

C10

0.073

0.072

0.052

0.051

0.051

0.049

0.036

0.036

C11

0.071

0.07

0.048

0.048

0.048

0.048

0.035

0.035

C12

0.074

0.074

0.051

0.051

0.051

0.051

0.037

0.037

C13

0.042

0.042

0.028

0.028

0.028

0.029

0.022

C14

0.053

0.054

0.035

0.035

0.035

0.037

0.028

C15

0

0

0

0

0

0

0.067

C16

0

0

0

0

0

C17

0

0

0

0

0

C18

0

0

0

0

0

Sum

1

1

1

1

1

AC

ED 0

0.055

0.055

0.055

0.056

0.054

0.055

0.055

0.054

0

0

0

0

0

0.062

0.062

0.063

0.062

0.063

0.063

0.061

0.062

0

0

0

0

0

0.058

0.057

0.056

0.056

0.056

0.056

0.057

0.056

0

0

0

0

1

1

1

1

1

1

1

1

1

1

1

1

1

PT

CE

Note: 𝑊𝑤 = 𝑊𝑢 × 𝑇𝑠 , 𝑇𝑠 = (𝑇𝛼 )′

M

C8

AN US

Ww

Table 8 Long-term Stable Supermatrix-DANP

CR IP T

ACCEPTED MANUSCRIPT

C1

C2

C3

C4

C5

C6

C7

C8

C9

C10

C11

C12

C13

C14

C15

C16

C17

C18

C1

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

0.106

C2

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

0.097

C3

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

0.079

C4

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

0.077

C5

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

0.073

C6

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

0.072

C7

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

0.051

C8

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

0.055

C9

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

C10

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

0.058

C11

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

0.056

C12

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

0.059

C13

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

0.034

C14

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

0.043

C15

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

0.027

C16

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

0.022

C17

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

0.025

C18

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

0.023

Sum

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

1

M

ED

PT CE AC

AN US

lim 𝑊𝑤𝑘

𝑘→∞

ACCEPTED MANUSCRIPT

4.4 Summary of the research findings The research findings were summarized in Table 9. From Table 9, the strength of influence and direction of the relationships both inside and outside the performance dimensions were obtained from DEMATEL results. Combined with relative weights determined by ANP, they can provide insights for companies in determining the criteria that most significantly influence other criteria’s

CR IP T

performance. To improve and sustain the business performance, improvability degrees were obtained by taking the mean of the experts’ opinions on levels of improvability for each criterion.

Table 9

AN US

Summary of the Research Findings Local Dimensions/criteria

(d+r)

(d-r)

weights (ranks)

(C1) Return on investment (C2) Customer (B) Customer satisfaction

Customer loyalty (C4)

(C5)

Price relative to

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competition (C6)

Internal Processes (C)

Transaction cost reduction (C7) Defect rate (C8) Customer data availability (C9)

Improvability

(ranks)

Weights

(ranks)

(GW)

(SW)

Standardized Improvability (SI)

15.290(1)

0.044

0.021

0.106(1)

2.02

6.037(10)

-0.194

13.983(7)

0.009

0.02

0.097(2)

1.65

6.570(3)

0.886

6.304(2)

35.353(2)

0.089

0.301(2)

14.689(4)

-0.077

0.024

0.079(3)

0.93

6.241(9)

0.219

14.391(6)

-0.058

0.023

0.077(4)

0.87

6.345(7)

0.429

13.681(10)

0.02

0.022

0.073(5)

0.7

6.345(6)

0.43

13.218(12)

-0.088

0.022

0.072(6)

0.65

5.586(16)

-1.108

35.868(1)

0.239

0.400(1)

12.620(13)

0.034

0.02

0.051(11)

-0.2

5.862(14)

-0.549

13.805(9)

0.026

0.022

0.055(10)

0

6.034(11)

-0.2

10.791(16)

-0.009

0.017

0.043(12)

-0.49

5.655(15)

-0.968

CE

Customer partnership

Global

0.203(3)

PT

(C3)

weights

-0.524

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Revenue growth rate

Standardized

34.201(3)

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Finance (A)

Global

6.129(3)

5.970(4)

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Local Dimensions/criteria

(d+r)

(d-r)

weights (ranks)

Global

Standardized

weights

Global

Improvability

(ranks)

Weights

(ranks)

(GW)

(SW)

0.11

Standardized Improvability (SI)

Effective problemsolving management

14.492(5)

-0.052

0.023

0.058(8)

5.931(12)

-0.409

13.932(8)

-0.026

0.022

0.056(9)

14.825(3)

0.032

0.024

0.059(7)

8.499(18)

0.002

0.014

0.034(14)

10.699(17)

-0.007

0.017

32.984(4)

0.197

0.096(4)

14.906(2)

0.059

0.003

0.027(15)

-1.14

6.793(2)

1.337

12.212(15)

0.033

0.002

0.022(18)

-1.35

6.357(5)

0.454

13.672(11)

0.065

0.002

0.025(16)

-1.23

6.429(4)

0.599

-1.32

5.929(13)

-0.414

Product/service innovation (C12) Environmental emissions (C13) Waste reduction (C14) Learning and Growth (D) Employee professional ability (C15)

Product/service learning (C17) Organizational alignment (C18) Average Maximum

0.15

7.286(1)

2.334

-0.86

5.250(18)

-1.788

5.464(17)

-1.354

0.043(13)

-0.51

6.377(1)

0.002

0.023(17)

13.235

0

--

0.056

6.133

15.29

0.065

0.106

7.286

8.499

-0.088

0.022

5.25

0.025

0.494

AC

Standard deviation

0.289

-0.006

CE

Minimum

6.276(8)

12.522(14)

PT

(C16)

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Employee satisfaction

0.02

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diversification (C11)

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Product and service

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(C10)

According to Table 9, Internal Process (C) has the most powerful strength of influence with

highest (d+r) value of 35.868. The second highest is Customer Perspectives (B), with a considerably high value of 35.353. Finance (A) comes the third and Learning and Growth (D) is the last, which was also reflected in the dimension’s local weight rankings. In terms of the degree of importance for criteria represented by global weights, the highest weight is 0.106, which means that Revenue Growth Rate (C1) is the most important criteria and Employee Satisfaction

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(C16) is the least important with lowest weight of 0.022. On the other hand, in terms of level of improvability, the average score is 6.333 (ceiling limit of 10), with the maximum point being Product/Service Innovation (C12) at 7.286, indicating that there is still a big space for companies to improve in innovating products and services. Moreover, Environmental Emissions (C13) has a medium point of improvability at 5.250, which is the smallest compared to that of others.

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Adopting the idea of four planning zones proposed by Pan and Chen (2012), we have further classified the importance and improvability of all criteria into the following four strategic planning zones as shown in Figure 4: (1) Priority zone – high importance (in terms of high standardized global weights index) and high improvability (in terms of high standardized improvability index). (2) Long-term zone – high importance and low improvability (in terms of

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low standardized improvability index). (3) Contingency zone – low importance (in terms of low standardized global weights index) and high improvability. (4) Non-priority zone – low importance and low improvability.

Contingency Zone

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C2

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Revenue growth rate (C1) Return on investment (C2) Customer satisfaction (C3) Customer loyalty (C4) Customer partnership (C5) Price relative to competition (C6) Transaction cost reduction (C7) Defect rate (C8) Customer data availability (C9) Effective problem-solving management (C10) Product and service diversification (C11) Product/service innovation (C12) Environmental emissions (C13) Waste reduction (C14) Employee professional ability (C15) Employee satisfaction (C16) Product/service learning (C17) Organizational alignment (C18)

Q1: High Importance, High Improvability

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Q3: Low Importance, High Improvability

Priority Zone

AC

CE

C1

Q4: Low Importance, Low Improvability

Non-Priority Zone

Q2: High Importance, Low Improvability

Long-term Zone

Figure 4. The classification of four planning zones based on the level of importance and improvability

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Based on the above research findings, it can be concluded that manufacturing companies should focus on improving the criteria listed in Quadrant Q1 which involves: (a) Return on Investment (C2) in Finance perspectives, (b) Three criteria in Customer perspectives including Customer Satisfaction (C3), Customer Loyalty (C4) and Customer Partnership (C5), and (c) Two criteria from

Internal

Process

perspective

including

Product/Service

Diversification

(C11),

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Product/Service Innovation (C12). Under these criteria, the standardized global weights indicating importance level and standardized improvability representing possibility for improvement are both positive, which means high importance and high possibility for improvement.

On the other hand, firms should consider gradually improving three criteria in Quadrant Q2 due

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to their high importance but difficulty for improvement, such as Revenue Growth Rate (C1), Price Relative to Competition (C6) and Effective Problem-Solving Management (C10). Besides, most of the criteria in Learning and Growth perspectives, which belong to Quadrant Q3: Employee Professional Ability (C15), Employee Satisfaction (C16) and Product/Service Learning (C17), showed less importance compared to other criteria. However, they are the

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easiest ones to improve; these criteria can serve as the foundation for supporting other internal processes, customer management and financial performance. The remaining criteria in Quadrant

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Q4, which do not show significant importance compared to others and are hard to change, include Transaction Cost Reduction (C7), Defect Rate (C8), Customer Data Availability (C9), Environmental Emissions (C13), Waste Reductions (C14) and Organizational Alignment (C18).

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They should also be considered for future improvement when other criteria are satisfied.

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5. Theoretical and Managerial Implications By integrating Balanced Scorecard with DEMATEL technique, this research has identified the

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causal relationships among the four dimensions and their respective criteria. Then, the corresponding global and local weights are calculated through ANP, which are not to be done by Balanced Scorecard alone. Based on the top 10 key criteria ranked by ANP weights and impact relationship map acquired from DEMATEL results, a strategic map as shown in Figure 5 can be constructed from the network relationship map illustrated in Figure 2 and 3. Following the strategy map, practicing managers may form a strategic plan with detailed implementation procedures for improving business performance in their manufacturing firms.

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Finance

Revenue Growth Rate

Return on Investment

Customer Satisfaction

Customer Loyalty

Customer Partnership

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Customer

Price Relative to Competition

Internal Processes

Defect Rate

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Product/Service Innovation

Product/Service Diversification

Learning and Growth

Effective Customer Problem Solving Management

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Develop people, technology and culture to be aligned with company
s strategies

Figure 5. Strategy map for improving business performance in manufacturing firms

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This strategy map is consistent with the relationships among four dimensions as suggested by Kaplan and Norton (2004). It indicates that “Learning and Growth” as the base of business

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strategy will influence the performance of “Internal Processes”, which leads to higher customer management performance and better financial results. This paper has highlighted the key criteria

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and their interrelationships among the dimensions, offering a more comprehensive decision making model and can be served as a reference for manufacturing companies who are pursuing a sustainable product-service system strategy.

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By identifying the respective global weights and levels of improvability for key business performance criteria, one can categorize the evaluation criteria of a product-service system performance into four strategic planning zones as: (1) Priority zone: special attention should be paid to performance evaluation criteria in this area and firms should come up with immediate measures to improve these key factors. (2) Long-term zone: companies should take pro-active actions and develop long-term planning to improve the corresponding criteria in this area. (3) Contingency zone: depending on the situations and strategic requirements of the company at a

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certain time period, the criteria in this area can be readjusted to match with firm’s objectives. (4) Non-priority zone: the criteria in this area do not directly affect the business performance and manufacturers may consider these criteria only when the factors of other criteria have been satisfied. To further help manufacturing firms identify the key performance criteria for achieving

criteria are summarized based on our research results.

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customer satisfaction, the following step-by-step procedures for selecting key performance

Step 1: Collect a list of factors/criteria relevant to the product-service system and Balanced Scorecard practices. Confirm them with the experts using Delphi method, then narrow down the list to a manageable size according to respondents’ importance rating scores obtained from

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respondents’ pairwise comparison.

Step 2: Perform DEMATEL method (see guidelines stated in section 3.2) to clarify the important criteria for business performance and measure the strength of influence among dimensions as well as their respective criteria reflected in causal diagrams. Step 3: Employ ANP method (see section 3.3 for details) to obtain the relative influence

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weights of the evaluation criteria based on DEMATEL results and rank them respectively. Step 4: Classify the selected key performance criteria into four strategic quadrants based on

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their importance and improvability results. Then, evaluate the appropriateness of the classification of these four strategic planning zones accordingly. Note that the classification of importance and improvability into four strategic quadrants will

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help manufacturing firms in prioritizing their business improvement projects while coming up with a detailed implementation procedure to enhance overall business competitiveness. This

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approach not only will help manufacturing firms to allocate their resources more effectively, but also provide some guidelines for their continuous improvement to achieve superior customer

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satisfaction by applying sustainable product-service system practices. 6. Conclusions and Discussions Product-Service System is a new business strategy that, if implemented appropriately, could

result in significant benefits for manufacturing firms. To help manufacturing firms identify the key performance criteria for achieving customer satisfaction, this paper proposes an integrated Balanced Scorecard and MCDM approach. To explore the causal relationships among the four dimensions of business performance in Balanced Scorecard as well as their key performance

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criteria, a MCDM approach combining DEMATEL and ANP techniques is adopted. Then, the MCDM framework is tested using Delphi method and a questionnaire survey was conducted in 24 manufacturing firms from Taiwan, Vietnam and Thailand. The research findings indicate that among the top ten key performance criteria, two of them belong to the dimension of Finance Perspectives (A), four belong to Customer Perspectives (B),

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the rest of the four belong to Internal Processes (C) and none under Learning and Growth (D). Evidently, Internal Processes (C) has the strongest relationship towards other perspectives because most managers pay great attention to their operational processes and target customers’ satisfaction especially when manufacturing firms desire to transform from pure productorientation to service-orientation. Furthermore, intangible assets such as employee ability or

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organizational learning ability criteria under Learning and Growth (D) rarely have direct impact on financial performance; however, these improvements can help manufacturing firms enhance process quality and lead to higher customer satisfaction and better customer relationships, which will result in sales increase in the long run.

In addition, the classification of importance and improvability into four strategic planning

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zones provides practicing managers with a decision making tool for prioritizing continuous improvement projects and effectively allocating their resources to those key criteria identified in

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the strategic map for business performance improvement and continuously meeting the expectations of target customers. The results of our strategic planning zone analysis also indicate six of the top ten key performance criteria listed in Q1/Priority Zone encompass: Return on

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Investment (C2) in Finance perspectives, three criteria under Customer perspectives including Customer Satisfaction (C3), Customer Loyalty (C4) and Customer Partnership (C5); and two

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criteria under Internal Process perspective including Product/Service Diversification (C11), Product/Service Innovation (C12). Thus, it is suggested that manufacturing companies should

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focus more on improving customer satisfaction and customer loyalty by integrating products and services innovation and providing diversified value-added product-service offerings as well as developing closer long-term partnerships with customers. Moreover, a standard operating procedure for selecting the key performance criteria and

exploring their interrelationship is provided. Hopefully, it can be served as a useful guideline for practicing managers in different industries to identify key performance criteria for achieving customer satisfaction and thereby enhancing their business competitiveness through sustainable

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product-service system practices. Finally, it is worthwhile to mention that as the global competition in manufacturing industries intensifies in today’s dynamic business environment, it is imperative for manufacturers to develop value-added services to increase their competitiveness. But, different manufacturers may have different organizational structures and available resources. These external influential factors

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need to be considered in future research. A comparative study can then be done to further explore the differences among various industries. Acknowledgements

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We are grateful for the two anonymous reviewers for their constructive comments. The first author would like to gratefully acknowledge financial support from the Ministry of Science and Technology of Taiwan, ROC. References

Ahamed, Z., Inohara, T., & Kamoshida, A. 2013. A strategic journey of firm transformation towards a new framework for implementing servitization strategy. International Journal for Infonomics (IJI), 6(1/2), 692-707.

M

Akan, M., Ata, B., & Lariviere, M. A. 2011. Asymmetric information and economies of scale in service contracting. Manufacturing & Service Operations Management, 13(1), 58-72.

ED

Baines, T. S., Lightfoot, H. W., Evans, S., Neely, A., Greenough, R., Peppard, J., et al. (2007). State-of-the-art in product-service systems. Proceedings of the Institution of Mechanical

PT

Engineers, Part B: Journal of Engineering Manufacture, 221(10), 1543-1552. Chen, F.-H., Hsu, T.-S., & Tzeng, G.-H. 2011. A balanced scorecard approach to establish a

CE

performance evaluation and relationship model for hot spring hotels based on a hybrid MCDM model combining DEMATEL and ANP. International Journal of Hospitality Management, 30(4), 908-932.

AC

Ding, K., Pingyu, J. & Zheng, M. 2015. Enviromental and economical sustainability-aware resource service scheduling for industrial product service systems. Journal of Intelligent Manufacturing, 1-14.

Glickman, M. E., Rao, S. R., & Schultz, M. R. (2014). False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. Journal of Clinical Epidemiology, 67(2014), 850-857.

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Jiang, T.-J., Luh, D.-B., & Kung, S.-F. 2010. Balanced scorecard as an evaluation tool for product service system strategy development. The Global Studies Journal, 3(4), 85-102. Kaplan, R. S., & Norton, D. P. 1992. The balanced scorecard-Measures that drive performance. Harvard Business Review, 70(1), 71-79. Kaplan, R. S., & Norton, D. P. 2001. Transforming the balanced scorecard from performance

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measurement to strategic management: Part I. Accounting Horizons, 15(1), 87-104. Kaplan, R. S., & Norton, D. P. 2004. Strategy Maps: Converting Intangible Assets into Tangible Outcomes. Boston, MA: Harvard Business School Press.

Li, G., Huang, F.F., Cheng, T.C.E., Zheng, Q., & Ping, J. 2014. Make-or-buy service capacity decision in a supplier chain providing after-sales service. European Journal of

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Operational Research, 239, 377-388.

Linstone, H. A., & Turoff, M. 1975. The Delphi Method: Techniques and Applications. Boston, MA: Addison-Wesley Publishing.

Manzini, E., & Vezzoli, C. 2003. A strategic design approach to develop sustainable product service systems: Examples taken from the ‘environmentally friendly innovation’ Italian

M

prize. Journal of Cleaner Production, 11(8), 851-857.

Mitha, A., Boulyana, M., Hue, V., Pruvost, I., Martinot, A., & Dubos, F. (2012). Consensus in

ED

diagnostic definitions for bone or joint infections in children by a Delphi method with European French‐speaking experts. Acta Paediatrica, 101(8), e350-e356.

PT

Neu, W. A., & Brown, S. W. 2005. Forming successful business-to-business services in goodsdominant firms. Journal of Service Research, 8(1), 3-17.

CE

Neu, W. A., & Brown, S. W. 2008. Manufacturers forming successful complex business services: Designing an organization to fit the market. International Journal of Service Industry Management, 19(2), 232-251.

AC

Niven, P. R. 2006. Balanced Scorecard Step-By-Step: Maximizing Performance and Maintaining Results. New Jersey: John Wiley & Sons.

Ou Yang, Y.-P., Shieh, H.-M., Leu, J.-D., & Tzeng, G.-H. 2008. A novel hybrid MCDM model combined with DEMATEL and ANP with applications. International Journal of Operations Research, 5(3), 160-168. Pan, J.N., & Chen, S.C. 2012. A new approach for assessing the correlated risk. Industrial Management & Data Systems, 112(9), 1348-1365.

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Papalexandris, A., Ioannou, G., Prastacos, G., & Eric Soderquist, K. 2005. An integrated methodology for putting the balanced scorecard into action. European Management Journal, 23(2), 214-227. Saaty, T. L. 1980. The Analytic Hierarchy Process. New York: Mc Graw-Hill. Saaty, T. L., & Vargas, L. G. 1991. Prediction, Projection, and Forecasting: Applications of The

Netherlands: Kluwer Academic Publishers.

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Analytic Hierarchy Process in Economics, Finance, Politics, Games, and Sports.

Schmidt, J., & Keil, T. 2013. What makes a resource valuable? Identifying the drivers of firmidiosyncratic resource value. Academy of Management Review, 38(2), 206-228.

Sumrit, D., & Anuntavoranich, P. 2013. Using DEMATEL method to analyze the causal relations

AN US

on technological innovation capability evaluation factors in Thai technology-based firms. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 4(2), 81-103.

Tukker, A. 2004. Eight types of product–service system: Eight ways to sustainability? Experiences from SusProNet. Business Strategy and the Environment, 13(4), 246-260.

M

Vasantha, G.V.A., Roy, R., Lelah, A. & Brissaud, D. 2012. A review of product-service systems design methodologies. Journal of Engineering Design, 23(9), 635-659.

ED

Yeh, T.-M., & Huang, Y.-L. 2014. Factors in determining wind farm location: Integrating GQM, fuzzy DEMATEL, and ANP. Renewable Energy, 66(0), 159-169.

PT

Zhang, X., Han, X., Liu, X., Liu, R. and Leng, J. 2015. The pricing of product and value-added service under information asymmetry: a product life cycle perspective. International

AC

CE

Journal of Production Research, 53(1), 25-40.