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Contents lists available at ScienceDirect

Int. J. Production Economics

Int. J. Production Economics 116 (2008) 242–250

0925-52

doi:10.1

� Cor

E-m

journal homepage: www.elsevier.com/locate/ijpe

Examining the mechanism of the value co-creation with customers

Xiang Zhang a,�, Rongqiu Chen b

a School of Management and Economics, Beijing Institute of Technology, Beijing 100081, Chinab School of Management, Huazhong University of Science and Technology, Wuhan 430074, China

a r t i c l e i n f o

Article history:

Received 21 September 2007

Accepted 2 September 2008Available online 25 September 2008

Keywords:

Mass customization

Customerization

Customer participation

Value co-creation system

Open system

73/$ - see front matter & 2008 Elsevier B.V. A

016/j.ijpe.2008.09.004

responding author. Tel./fax: +86 10 6891 2483

ail addresses: zxmb@163.net, xiangzhang@bit

a b s t r a c t

Involving customers to co-create value is an important strategy for businesses

competing to satisfy personalized demands and to gain competitive advantages.

However, the research in the area is still in an early stage. In a search for this new

competitive strategy, the literature on value co-creation largely overlooked the

examination of system mechanism. Using survey data collected in China, this study

provides an empirical examination into the mechanism of the co-creation system and

makes the contribution in the following three aspects. First, this study developed

and assessed the constructs in a value co-creation system. The measures satisfy key

measurement criteria including unidimensionality, convergent validity, discriminant

validity and reliability. Second, this study identified and empirically examined the two

primary principles of value co-creation system with customers. The emphasis of

co-creation with customers may not only positively impact on customerization

capabilities, but also directly impact on service capability. These capabilities are

significantly different from those generated from traditionally isolated value creation

system. Third, the results show that service capability has positive impacts on firm’s

customerization capability. The study helps deepen the understanding of value co-

creation system with customer and facilitates managers to look the new strategy

through new lens.

& 2008 Elsevier B.V. All rights reserved.

1. Introduction

The changes in technology, competition and customerdemand fundamentally alter the way the businessesoperate. Companies relying on conventional company-centric practices find themselves troubled by decreasedcustomer satisfaction and declined profits. The traditionalisolated value creation strategy is losing its utility in theemerging economy. Companies are shifting their focusfrom increasing internal efficiency to leverage externalresources, especially the customer competence, in order togain new competitive advantages in the new economy(Lovelock and Young, 1979; Prahalad and Ramaswamy,

ll rights reserved.

.

.edu.cn (X. Zhang).

2004; Zhang and Chen, 2006; Prahalad and Krishnan,2008). To identify and measure the mechanism to winsuch new competitive advantages is critical to operatio-nalize the new strategy. Despite its importance, researchon co-creation with customers is still in an early stage.The literature largely overlooked constructs development.No study examined the interacting mechanism among theconstructs. From an empirical point of view, the mechan-ism to win the new competence remains an under-researched topic.

This study is an attempt towards this direction. Thepurpose of this paper is to measure the constructs and themechanism of the value co-creation system with custo-mers. To do so, this paper begins by presenting aconceptual model as shown in Fig. 1. The framework inFig. 1 brings together the key constructs of a co-creationsystem and presents a collective logic of interacting

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Fig. 1. Theoretical model.

X. Zhang, R. Chen / Int. J. Production Economics 116 (2008) 242–250 243

mechanism among the constructs. It is governed by twoprimary principles. The first principle relates to theintegration of customers for value co-creation throughinteractive co-creation activities. The second principlerelates to the relationship between the co-creationactivities and new system capabilities. The emphasis ofco-creation with customers may not only positivelyimpact on service capability, but also directly impact oncustomerization capability, which significantly differsfrom the traditional capabilities. This means the focuson the co-creation with customers may gain newcompetence, thus obtaining more competitive advantages.

The discussion that follows defines the constructs andtheoretical propositions further (Section 2). Next, inSection 3, the article describes in details the researchdesign and methodologies. Based on the data collected ina large survey in the middle of China, this paper presentsand discusses the results of analysis in Sections 4 and 5.The article concludes in Section 6 by pointing out thecontributions and future research direction.

2. Theoretical background

Since the popularity of mass customization, firmsincreasingly rely on providing customized product andservice to satisfy customers’ individual demands. How-ever, even the creation of a mass customized product orservice cannot assure firm’s sustainable success becausecompetitive advantage comes from continuously provid-ing the most value for each individual customer through-out the value chain (Pine, 1993). Future competitioncenters on personalized interaction with customers toco-create value (Prahalad and Ramaswamy, 2004; Praha-lad and Krishnan, 2008). Moreover, the customer–firminteraction no longer limits in traditional service sector ormarketing activities. Rather, companies may co-createvalue with customers alone the customer participativechain (Zhang and Chen, 2006), from the co-developmentof new products, to production, assembly, distribution,retail, after sales service and usage (von Hippel, 1988;Ross, 1996; Duray, 2002).

The implementation of customerization strategy pre-sents an opportunity to integrate customer into an

enhanced network of value creation. In the new strategy,firms not only interact with customers for providingcustomized offerings, but also develop and enhance theoperational capabilities (Wind and Rangaswamy, 2001).This is because the emphasis of co-creation activitiesrequires companies to create breakthrough in how theyinteract with customers so as to beat the competition notjust by having a better product but also by being betterin how that product gets fulfilled, sold and serviced(Whiteley and Hessan, 1996).

Customer becomes a value co-creator, resulting in asystem of value co-creation. There are two distinguishingfeatures of such a new system. First, companies takecustomers as a partner or co-producer instead of anexternal element (Firat et al., 1995). The changing role ofcustomer from an external element to a co-producer canbe realized by a series of co-creation activities asillustrated in the customer participative chain (Zhangand Chen, 2006). In contrast to a single application of theone-off customer participation, meaningful co-creationwith customers is a systematical process, which containskey co-creation activities that can most possibly to turncustomers efforts, skills and knowledge into the uniquecompetitive advantages (Zhang and Chen, 2006).

Second, co-creation value with customers becomes anew source of competence for businesses strategies(Prahalad and Ramaswamy, 2004). From operationsmanagement point of view, these new competitivecapabilities include customerization capability and theservice capability. Customerization capability is a primaryconcern in the co-creation process of customerization(Zhang and Chen, 2006). Customerization combines masscustomization and elicitation of individual demandinformation by involving customers and is regarded asthe next generation of mass customization (Pine et al.,1995; Wind and Rangaswamy, 2001). Through customerinteraction, the firm may be able to provide exactly whatcustomers want (Pine et al., 1995), increase collaboration,clean organizational bureaucracy and enable the firm toprecisely target customer groups (Whiteley and Hessan,1996). In the study, this special competence is defined ascustomerization capability, i.e. the unique capabilitiesgenerated during value co-creation process by involvingcustomers during customerization.

Service capability is also important in the co-creationprocess as the production and consumption of service isintegrated when involving customers. In fact, service hasbecome one of the important competitive capabilities(Giffi et al., 1990; Chen, 2002; Lau Antonio et al., 2007)since Fuchs (1968) proposes the arrival of serviceeconomy. Service capability in customerization can bemeasured based on the ability to provide customizedservice during value co-creation with customers. Thesecompetitive advantages are different from those oftraditional isolated operations that performed alone bythe firm, thus forming the new competence for compa-nies.

The emphasis on co-creation with customers cangenerate and enhance firm’s customerization capability.In contrast to traditional way where different functionaldepartments handle different tasks in a fixed order to add

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value, in co-creation system, the company becomes a hubof value creation grid (Wikstrom, 1996). In analysis of howto gain competitive advantages from interactions withcustomers, Zhang and Chen (2006) propose a conceptualframework of customer participative chain model thatshows that company may involve customers at a seriesof co-creating activities, which turn customers inputs(including their efforts, knowledge, even expenses, etc.)into new capability. This leads to a win–win result.Customers obtain their customized products, servicesand experiences by partaking the value co-creationprocess. Meantime, the firm gains new competitivecapabilities, which can precisely target customer and usethe data to create unique approaches (Whiteley andHessan, 1996). As also evidenced in the current practices,when firms emphasize the marketing interactions, themore communication with customers, the more firmsknow about customers’ preferences and needs, the betterfirms provide exactly what customers want and themore difficult for a competitor to take away thosecustomers (Pine et al., 1995). Also, when firm involvescustomers and communicates their needs throughoutthe entire organization, the firm can easily identify thenecessity of optimization in demand fulfillment processand decision process, and hence discards activities andassets that do not add value for customers (Whiteley andHessan, 1996). The above analysis leads to the followinghypothesis.

Hypothesis 1. The emphasis on co-creating activities willhave positive impact on customerization capability.

The co-creation activities can also enhance the servicecapability. The integration of customers through co-creation activities affect the choice of service capabilityowning to the related uncertainty and the dependence oninformation. As Youngdahl (1996) notes that companiesstriving in competing in mass customization recognize theimportance of service capability. Organizations shouldadopt high involvement structures when uncertainty andrelated information dependence are high. The emphasis ofco-creation activities may lead to high involvementstructure, which in turn leads to high emphasis on servicecapability to gain competitive advantages. Good serviceadds value to the physical product (Vickery et al., 2003).Specifically in customerization, the customer–firm inter-action can enable companies to design services thatdifferentiate their offerings (Pine et al., 1995). Theinteractions at marketing, new product development andservice care with a proper participatory managementenable firm to create new and value-adding serviceoffering together with the unique service experience forcustomers, thus enhancing the service capability. Thisleads to the following hypothesis.

Hypothesis 2. The emphasis on co-creating activities willhave significantly positive impact on service capability.

When firms are able to elicit demand information froma customer about her specific needs and preferences byusing customized service, the firms are able to use theincreasingly more detailed feedbacks to find the best

products or services for the individual customer (Pineet al., 1995). Good service contributes to enhancecompany’s operational performance and capability toretain customers (Lim and Palvia, 2001; Yeung et al.,2008). A company that succeeds in enhancing servicecapabilities in customerization will have more opportu-nities to gain an advantage over its rivals because itrepresents an enormous chance for company that cater tocustomers’ individual preferences and to improve systemcapabilities (Pine et al., 1995). This in return enables thefirm to precisely target customer groups and increasecollaboration with customers. Hence the emphasis ofservice capability will enhance firm’s customerizationcapability. The above analysis leads to the followinghypothesis.

Hypothesis 3. The service capability will have signifi-cantly positive impact on customerization capability.

3. Methodologies

This study developed multi-item for each construct inorder to make better distinctions among respondents overthe use of single items (Flynn et al., 1990). Items weregenerated from relevant literature. The key co-creationactivities (KCA) was developed based on Zhang and Chen(2006). The customerization capability (CC) was devel-oped based on Pine et al. (1995), Whiteley and Hessan(1996) and Zhang and Chen (2006). The service capability(SERV) was developed based on Fuchs (1968) and Giffiet al. (1990). The items that measure the KCA werestructured on a 5-point Likert-type scale that ranged from1: not at all important to 5: critically important. Therespondents were asked to indicate the importance thattheir firm emphasized value co-creation with customersat these activities. For the CC as well as the SERV, therespondents were asked to make the comparison withtheir major competitors, where 1: much lower than thecompetitor and 5: much higher than the competitor.Having respondents rate their competitive capabilitiesrelative to their competitors has been widely used inmany previous studies (see for example, Ariss and Zhang,2002; Zhang et al., 2003; Lau Antonio et al., 2007).

During pre-pilot study, these items were grouped intothree constructs based on their theoretical meaning andwere translated into Chinese and then back into Englishby a Ph.D. student till both versions were consideredcompletely interchangeable linguistically to ensure thetranslation quality (Brislin, 1980). These items werefurther used to discuss with two Ph.D. students and threesenior managers, mainly marketing and operations man-agers, in order to provide additional content validity andto suit for local context.

The pilot study was organized among senior managersof 18 companies located in mid-China during theirattendance as EMBA students at the authors’ universities.All respondents are senior managers, having job titlesof Chairman, VP Operations, Manufacturing Manager,or Marketing Manager. Items were firstly purified byusing corrected item-total correlation with all resultsabove 0.50. Secondly, exploratory factor analysis using

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varimax rotation and mean substitution was executedto assess the unidimensionality of the scales. The factorloads were above 0.60 and a values were over 0.7,indicating an acceptable result (Kerlinger, 1978; Nunnally,1978).

In the large-scale survey, 300 companies located in themid-China were randomly selected. The reason for thissampling is that (1) the sample covers wide industriesthat may help generate the research results; (2) most ofthe surveyed respondents have years of managementexperiences that ensure that the respondents know thesituation of customer–firm interaction at their owncompany. The respondents were either called and thensent through E-mail or directly sent through E-mail. TenE-mail deliveries failed due to the changed address.Questionnaires were received in two stages. In the firststage, 97 questionnaires received, among which 95 werevalid. In the second stage, out of 88 questionnairesreceived 79 were valid. Thus, the total 174 valid ques-tionnaires represented a responding rate of 58%. Theintraclass correlation was calculated to assess the inter-rater agreement. The minimum intraclass correlationcoefficients of three constructs were above 85% (signifi-cant at 0.05 level), indicating an acceptable inter-rateragreement (James et al., 1993; Vickery et al., 1994). Inaddition, this study conducted the follow-up interviewsfrom a second respondent at 15 companies at convenienceto further understand the research insights.

The 81.02% of the targeted respondents had manage-ment positions that may help provide more reliableinformation (Phillips, 1981). The distribution of salesvolume of the sample ranges from less than 1 million(10.92%), to 10 million (20.11%), 50 million (25.86%),100million (11.49%), 500million (14.94%), 1 billion(7.47%) and more than 1 billion (6.89%) with 2.3%remaining unspecified. 44.83% of the sampled companieshad employees less than 500, 31.6% less than 5000, 22.41%more than 5000 with 1.15% remaining unspecified.The demographic information of the sample is shown inTable 1.

The response/non-response bias was tested by com-paring earlier returned questionnaire to late returnedones, because the original list did not provide the neededdemographic information. No significant differences werefound in terms of the three measured constructs as well as

Table 1Demographic information of sample

Industry Frequency Percent

Electronic and electric equipment 19 10.92

Telecommunication and related equipment 9 5.17

Retail 15 8.62

Transportation and vehicle manufacturing 10 5.75

Chemical and miscellaneous products 19 10.92

General manufacturing 28 16.09

Other manufacturing 22 12.64

Design and consulting 18 10.34

Real Estate 18 10.34

Others 16 9.2

people, assets and sales volume between the two groupsusing t-tests statistics and po0.05. Corresponding to theresearch emphasis, the unit of analysis was directed atorganizational level.

The common method variances (CMVs), which refer tothe possibility arises from the method variance to inflatethe observed correlations between the variables artifac-tually, are the frequently mentioned concern of research-ers in empirical study (Lindell and Whitney, 2001;Podsakoff et al., 2003; Malhotra et al., 2006). It requiresexamination.

Podsakoff et al. (2003) have categorized four sources ofCMVs: (1) the common rater effects appear whenrespondents purposely answer questions in a sociallydesirable manner; (2) the item characteristic effectsappear when the questions are ambiguously worded orconfusion; (3) the item context effects occur whentoo many questions lead to respondent fatigue; and(4) measurement context effects occur when using asingle respondent at each firm to provide answers to thequestions. In this study, the items examined litter social orpolitical issues about which people can often have verystrong views. As such, the common rater effects are notlikely the issue in this study. Also the questions in thisstudy were developed to measure the specific co-creationactivities and its related capabilities. After the refinementof the questions in the pre-pilot study and the pilot study,respondents were easily to know what the researcherswere actually asking. In comparison with other disciplineslike education and psychology, the questions in this studywere not the abstract ones such as human emotions.Hence the item characteristic effects are not likely theissue in this study. Also the questions in this studyremained in a short list which could hardly lead torespondents fatigue. Hence the item context effects arenot likely the issue either.

Therefore, the extent of CMV in this study could mainlyinvolve measurement context effects of its four sources.This was examined by using both Harman’s Single-Factor(HSF) test proposed by Podsakoff et al. (2003) and themarker technique proposed by Lindell and Whitney(2001) and Malhotra et al. (2006). First, the originalresults of the model were examined without any con-sideration of method biases. Initially, the confirmatoryfactor analysis (CFA) was performed on the data.The results of CFA indicated that the measurement modelwas satisfactory: w2(51) ¼ 63.2, CFI ¼ 0.987, GFI ¼ 0.946,RFI ¼ 0.922, IFI ¼ 0.988 and RMSEA ¼ 0.037. Second, theHSF test was performed via CFA by specifying a hypothe-sized method factor as an underlying driver of all of theitems. The results revealed that the fit of the single-factormodel was extremely unsatisfactory, for the modelw2(54) ¼ 239.8, CFI ¼ 0.811, GFI ¼ 0.777, RFI ¼ 0.720,IFI ¼ 0.813 and RMSEA ¼ 0.141, indicating that CMV wasnot the major source of the variations in the observeditems.

However, the HSF test has limitations and is knownto be highly conservative in detecting biases on howmuch variance the first factor should extract before it isconsidered a general factor (Podsakoff et al., 2003;Malhotra et al., 2006). This study further applied the

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marker-variable technique to assess the CMV. The marker-variable technique can be implemented in both a priorifashion and a post-hoc fashion. This study used a post-hocfashion to assess the CMV as proposed in Lindelland Whitney (2001) and Malhotra et al. (2006).In a post-hoc fashion, although the smallest positivevalue of the correlation among the manifest variableswould be a reasonable representation for CMV, thesecond-smallest positive correlation, rM2, as a moreconservative estimate is advocated, because the smallestcorrelation is possibly capitalized by chance factor (Lindelland Whitney, 2001). In this study, the second-smallestcorrelation, rM2, was 0.08. For factor correlation calcula-tion, according to Malhotra et al. (2006), the uncorrectedestimate rU(KCA, SERV) ¼ 0.447, the CMV-adjusted correla-tion rA(KCA, SERV) ¼ 0.400 with t ¼ 5.689; similarly, rU(KCA,

CC) ¼ 0.482, rA(KCA, CC) ¼ 0.437 with t ¼ 6.352, rU(SERV,

CC) ¼ 0.774, rA(SERV, CC) ¼ 0.754 with t ¼ 15.026. A w2

difference test was performed to compare original andCMV-adjusted correlations. Specifically, the originalcorrelation values were replaced with its CMV-adjustedvalues to see whether the substitution significantlydeteriorated fit, using Dw2(1)43.84, po0.05 (Malhotraet al., 2006). The Dw2(1) ¼ 3.54o3.84. The result indicatedthat the uncorrected estimates were not statisticallydifferent from the adjusted correlations, whichsuggests that CMV does not seriously distort the infer-ences in this study. Taking together with the results of theHSF test, the CMV is not substantially biased the analysisin this study.

4. The results of analysis

According to Venkatraman (1989), this study usedfollowing set of criteria to assess measurement propertiesof constructs: unidimensionality and convergent validity,discriminant validity and reliability. Table 2 provides a listof the scale items.

Table 2Results of EFA

Code Items

KCA1 Involving customers at marketing and sales

KCA2 Involving customers at service care

KCA3 Involving customers at new product developmen

KCA4 Managing customers as partial employee

CC1 precisely target customer groups

CC2 provide exactly what customers want

CC3 identify more market opportunities

CC4 increase collaboration with customers

CC5a Clean organizational bureaucracy

SERV1 The capability to create new service

SERV2 The capability to provide unique service experie

SERV3 The capability to provide multi-kind service

SERV4 The capability to provide customized value-addi

Total variance explained

a Items not entering the final instruments.

Exploratory factor analysis (EFA) with varimax rotationand mean substitution was conducted on items. Itemswith factor loadings below 0.60 or with cross-loadingsabove 0.1 were eliminated. The items of the threeconstructs, i.e. key co-creation activities (KCA), customer-ization competence (CC) and service capability (SERV),were factor analyzed together. Without specifying thenumber, three factors with Eigenvalues greater than 1emerged. All items were loaded on the three factors astheoretically hypothesized, with all loadings above 0.6.The results of factor analysis were consistent with theseprior identified item groupings, as shown in Table 2,which provide evidence of factorial validity (Anderson,1987; Comrey, 1988).

CFA was conducted to examine the associationsbetween items and constructs specified a priori toenhance the result of EFA. This was accomplished byrestricting the items to load on their theoreticallyspecified constructs. The results were acceptable with allloadings of items above 0.5 with t-value above 8.

For convergent validity assessment, a construct with areliability value of at least 0.50 and a significant t-valuefor loadings, i.e. t42, is considered to be convergentlyvalid (Chau, 1997; Hau et al., 2004). The factor loadingsof all items were significant at 0.01 levels, as shown inTable 2. The reliability of each construct was above 0.70,as shown in Table A1. All these results indicated a goodconvergent validity.

Discriminant validity was assessed by the w2 differencebetween fixed and unconstrained correlation models ofthe constructs. The Dw2 of KCA–CC pair was 52.8(Ddf ¼ 1), the Dw2 of KCA–SERV pair was 56.4 (Ddf ¼ 1),and the Dw2 of CC–SERV pair was 15.5 (Ddf ¼ 1), whichwere significant at the po0.01 level, indicating strongsupport for the discriminant validity (Venkatraman, 1989;Fornell and Larcker, 1981). The CC5 was dropped due tothe correlation of error.

This study also assessed the w2 difference between thenew factors and the traditional competitive capabilities,

Mean S.D. KCA CC Serv

4.000 1.000 0.744 0.016 0.103

3.670 1.180 0.719 0.121 0.153

t 3.800 1.080 0.600 0.169 0.102

3.400 1.400 0.688 0.135 0.029

3.393 0.970 0.169 0.843 0.220

3.370 0.910 0.116 0.834 0.203

3.390 1.010 0.072 0.810 0.262

3.200 1.040 0.098 0.745 0.116

3.497 0.970 0.055 0.756 0.189

3.244 1.090 0.137 0.201 0.818nce 3.099 0.990 0.162 0.123 0.850

3.157 1.010 0.020 0.169 0.809ng service 3.135 1.050 0.103 0.136 0.868

30.689 23.877 17.851

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Fig. 2. The results of structural equation modeling.

X. Zhang, R. Chen / Int. J. Production Economics 116 (2008) 242–250 247

i.e. cost, quality, delivery and flexibility that were based onthe items in Miller and Roth (1994) study. The w2

difference of CC–cost pair was 72.5 (Ddf ¼ 1), CC–qualitypair was 30.7 (Ddf ¼ 1), CC–delivery pair was 27.8(Ddf ¼ 1), and the CC–FLEX pair was 22.5 (Ddf ¼ 1). Allthese w2 differences were significant at the po0.01 level,and the similar results were found when assessing theservice capabilities. The w2 difference of relevant factorspair were all significant at the po0.01 level with thechange of one degree of freedom. The results suggest thatthe new competitive advantages were significantly differ-ent from those generated from traditionally isolated valuecreation.

The reliability was measured by using Cronbach’s a.The a values were 0.7343 for KCA, 0.8957 for CC and0.8465 for SERV, as shown in Table A1 in the Appendix A,which indicates satisfactory results (Cronbach, 1951).

The structural model was evaluated and the resultswere shown in Fig. 2. The indices indicate an adequate fitfor the structural portion of the model. The w2 was 63.273,degree of freedom was 51 and the w2/df ratio was 1.240,GFI ¼ 0.946, AGFI ¼ 0.917, CFI ¼ 0.946, NFI ¼ 0.940,IFI ¼ 0.988, RMR ¼ 0.048, RMSEA ¼ 0.037. The data ana-lysis shows an overall well-fitting model.

The structural model showed paths between theexogenous factor and the endogenous factors (see Fig. 2).The test of propositions was based on the paths in thestructural model. The t-values for the path coefficientswere positive and significant, which provides supportingevidence for corresponding hypothesis.

The results of analysis generally provide supportingevidence for the first hypothesis that value co-creationactivities have positive impacts on firm’s customerizationcapability. The relevant path was significant and positive

(r ¼ 0.258; t ¼ 2.649; po0.01). Hypothesis 2 is alsosupported. The relevant path was significant (r ¼ 0.48;t ¼ 4.116; po0.01). The results indicate that KCA hassignificantly positive impact on firm’s service capability.The results of analysis generally provide supportingevidence for the third hypothesis that firms with moreservice capability have better customerization capabilityto meet customer’s individual demand. The relevant pathcoefficient was positive (r ¼ 0.70) and significant(t ¼ 8.258).

5. Discussion

The objective of this study was to examine theconstructs and the mechanism of the value co-creationsystem with customers. By extending customer participa-tive chain model (Zhang and Chen, 2006), this studyidentified and empirically examined the two primaryprinciples of value co-creation system with customers,i.e. the integration of customers for value co-creation, andthe association between the value co-creation activitiesand new capabilities. The interactive mechanism of such aco-creation system was specified in three propositionsand was empirically examined by using structural equa-tion modeling based on the data collected in the middle ofChina. The results of analysis generally provide supportingevidence for the three propositions as illustrated in Fig. 2.The measures satisfy key measurement criteria includingunidimensionality, convergent validity, discriminantvalidity, and reliability. The two constructs of the newcapabilities generated from value co-creation with custo-mer are significantly different from traditional capabilitiesthat generated from isolated value creation by firms alone.

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The relevant path was positive and significant as indicatedin Fig. 2. That means value co-creation activities havepositive impacts on firm’s capabilities and firms withbetter service capability have better customerizationcapability to meet customer’s individual demand. Hencethis study empirically demonstrates that the focus on theco-creation with customers may gain new competence,thus obtaining more competitive advantages.

To the presently best knowledge of the authors, there isno direct operations management literature that can becompared with the results of this study. However, thesefindings are found in compliance with the findings ofother disciplines and could be utilized to further enrichthe understanding of value co-creation system in opera-tions management. Prahalad and Ramaswamy (2004)make conceptual argument that customer as value co-creator can be a new source of competitive advantages.They propose a DART model that stands for dialogue,access, risk assessment of the product, and transparencyto reduce the traditional information asymmetry betweenthe customers and the firm. In this paper, the results ofanalysis provide a different emphasis to achieve suchcompetitiveness, i.e. through the value co-creation me-chanism governed by the two principles.

Yeung et al. (2008) find that leveraging customerknowledge through service contributes to improve opera-tional performance in respect to strategic planningprocess, planning processes and manufacturing processof operational processes. In this study, the emphasis ofservice capability of customerization has positive impacton the customerization capability, thus adding an addi-tional weight on service for firm to enhance its compe-tence.

Firms used to focus on the internal efficiency andsupplier chain coordination to achieve competitive ad-vantages. The results of this study provide a new way thatorganizations can obtain competitive advantages byinvolving customers at the value co-creation process.The results show that the co-creation activities are notrestricted at marketing where money changes hands.Rather the key activities are tightly links with each otherthroughout the value chain of customization. For compa-nies adopting a customer-centered management strategyand aiming at leveraging customer competence, managersshould systematically consider all possible processes andactivities to co-create value with customers. Hence theyshould be considered as synergy strategy. This is also incompliance with the literature. For example, customerservice is essential to the successful marketing outcomesand is strongly influenced by product design and so itshould be evaluated during new product development(Goffin and New, 2001). Also the effect of customerinteraction in new product development is particularrelevant to the developing of marketing thought (Grunerand Homburg, 2000). As many managers said in thefollow-up interviews that ‘‘involving customer is a newstart point to actually leverage customer competence forvalue creation.’’ This strategic importance, coupled withthe multi-functional operations, suggests a strong need oftop management involvement for directing the newstrategy.

In addition to the requirement of top managementinvolvement, several other factors should be consideredbefore or during implementation of such a new strategy.A ready organizational wide co-production managementplan may lead to a more success co-creation system.According to the anecdotal evidence at a sample companyin the follow-up interviews, this study found thatmanagers were sometimes frustrated by the uncertaintiesintroduced during interaction as they were not ready toguide and manage the co-creation process. Customers atthis company participated not only into the value-addedactivities, but also into the non-value-added activities.Hence a ready co-creation management plan is necessaryto have a better co-creation result.

Although every caution had been taken to ensure aproper research design, there might still be limitations.Specifically, the sample might differ from the nationalpopulation although the use of the sample helpedmaintain a broader coverage with relatively high rate ofreturn. While there was no readily apparent bias in termsof the range of respondents, the potential for sample biasdoes represent a minor limitation. To go around thislimitation and control the method bias by self-reporting,the empirical study was carried out based on multiplemethods, multiple respondents, multi-item constructsand supplemented by follow-up interviews. The commonmethod variance was assessed and the results wereacceptable. Thus, the potential problem was controlledin the minimum and the above limitations did notseriously bias the research results.

6. Conclusions

In this study, the constructs of key co-creationactivities, customerization competence and service cap-ability were developed and assessed with respect to thevalidity and reliability, and the two primary principles ofthe mechanism of value co-creation system was examinedusing structural equation modeling. This research makesthe contribution in three aspects: First, this studydeveloped and assessed three constructs in a value co-creation system based on the empirical data. Themeasures satisfy key measurement criteria includingunidimensionality, convergent validity, discriminant va-lidity and reliability. Second, the results of this studyevidence that the emphasis of co-creation with customersmay not only positively impact on customerizationcapabilities, but also directly impact on service capability.These capabilities are significantly different from thosegenerated from traditionally isolated value creationsystem. Third, the study finds the relationship betweenthe customerization capabilities and service capabilities.Service capability has positive impacts on firm’s custo-merization capability. This means the focus on the co-creation with customers may gain new competence, thusobtaining more competitive advantages and providingempirical evidence to the promise of co-creation systemwith customers.

Business competition is shifting from focusing internalefficiency to leverage external competence. Companies

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must not only integrate their resources and processesinternally, but also integrate their internal resources andprocesses with key customers, leading to a co-creationview of value. In analysis of the value co-creationsystem with customers, this study focuses on the assess-ment of system mechanism governed by the twoprinciples and finds the significant differences betweenthe new system capability and traditional capabilities.However, the impact of value co-creation on traditionalcapability was remained untested. This may becomes aninteresting future research topic. In addition, how to makethe mass co-creation happen and optimize such a massco-creation system will also be an interesting researchdirection.

Acknowledgments

The authors would like to thank the anonymousreferee for his/her valuable comments. This study wassupported by the National Natural Science Foundationof China no. 70332001. Dr. Zhang also thanks the supportof the Humanities and Social Sciences Research Fundsfor Young Scholars no. 08JC630007 sponsored by theM.O.E. and the Excellent Young Scholars Research Funds ofBeijing Institute of Technology no. 2007Y0819.

Appendix A

See Table A1 for detailed Questionnaire used in thestudy.

Table A1Questionnaire of the study

Constructs Scale items Reliability

Key co-creation

activities (KCA)

1. Involving customers at

marketing and sales

0.7343

2. Involving customers at service

care

3. Involving customers at new

product development

4. Managing customers as partial

employee

Customerization

capability (CC)

1. Precisely target customer

groups

0.8957

2. Provide exactly what

customers want

3. Identify more market

opportunities

4. Increase collaboration with

customers

Service

capability

(SERV)

1. The capability to create new

service

0.8465

2. The capability to provide

unique service experience

3. The capability to provide

multi-kind service

4. The capability to provide

customized value-adding service

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