Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
Collaboration with Customers – Understanding the Effect of Customer-Company Interaction in new Product Development Per Kristensson Karlstad University Service Research Center
[email protected]
Anders Gustafsson Karlstad University Service Research Center
[email protected]
Abstract Customer co-creation is becoming increasingly popular among companies, and intensive communication with the customer is generally seen as a determinant of new product success. However, there is still limited insight into what interaction with customers really is. The most recent thinking argues for an understanding of value-in-context in order to co-create value with customers. The question, then, is how value-in-context can be captured and how this knowledge can be beneficial in the development process. In essence in order to capture this type of information a company needs to interact and communicate with their customers. However, this communication process has not been properly analyzed. In the present study we analyze customer collaboration based on four separate dimensions – frequency, direction, modality, and content – in order to understand the value of customer collaboration. The data comes from a survey of 207 managers with experience of new service and product development. The paper concludes that three of the four dimensions of customer collaboration have a significant positive effect on New Product Development performance and Market Share development.
1.
Introduction
“You know better than anyone else what you want from Starbucks. So tell us. What’s your Starbucks Idea? Revolutionary or simple – we want to hear it” (www.starbucks.com). This is one of many examples of how companies are trying to involve their customers in the co-creation or co-development of new services [44]. These companies view their customers as important resources when they develop new products [31]. Many companies rely on the competencies of their customers or users, including Dell, P&G and Google; these companies would not resort to customer co-creation if they did not feel that it benefited their innovation efforts. Despite this trend, research has only superficially addressed the process through which
Lars Witell Karlstad University Service Research Center
[email protected]
customers co-create with companies. There is a general agreement that co-creation with customers is beneficial, but there is a lack of agreement regarding how and why. Furthermore, when describing the essence of the Service-Dominant Logic, [21] contended that collaboration with customers for the purposes of innovation is a foundational part of marketing today and that the collaboration regards “shared inventiveness” (p. 11). This indistinctness is also seen in [31], who concluded that “informed, networked, empowered, and active consumers are increasingly co-creating value with the firm” (p. 1). The specific actions and behaviors that make up the collaboration are yet to be fully addressed [44]. Consequently, it is important to research this question since knowledge about customers is gained in the collaboration processes between organizations and their customers [19]. The process of communication and the socially richer interactions has been argued to be one of the determinants for new product success [14, 22]. The focus in this paper is on how this communication process with customers should be managed in order to improve product and market success. Consequently, the purpose of this study is to gain a better understanding of the process of customer collaboration in the development process. This is done by applying an established four dimensional model that have been used previously to analyze marketing channel communication (see, e.g., [25] and [3]). The four dimensions are frequency, direction, modality, and content. Although the importance of communication both with customers and within companies have been stressed in previous research (eg. [14], [15], and [19]) we have not found any empirical investigations of customer collaboration where theories from the literature on communication have been used to get a deeper understanding of the empirical phenomenon. This article starts by describing some recent work on value-creation before providing a conceptualization of the dimensions that underlie customer collaboration. Then, because of the claimed relationship between co-creation and customer knowledge, the article also examines how the
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
dimensions given by the conceptualization influence the performance of the development process.
2.
Conceptual framework
2.1 Understanding value-creational processes From the service-dominant logic perspective, a market offering is attractive if it captures an offering’s value-in-context [40]. The focus, therefore, is not on the offering per se but on the customers’ value creation process, in which value for customers emerges [13]. [40] claimed that value is not created until the customer integrates and applies the resources of the service provider with other resources in their own context. Value is always contextually specific and is always determined by the beneficiary or the customer. Consequently, the value-creation process should be the focal point during the development of new offerings. Accordingly, companies have started to treat their customers as active collaborators when developing various offerings. This contrasts with the traditional view of customers as passive informants from whom information can be extracted by means of surveys or focus groups. In line with this, [44] showed that new offerings developed through market research techniques based on collaboration with customers are more profitable than those developed with traditional market research techniques. In order to understand this conceptually, one of the distinctions made in the literature is between responsive and proactive market orientation [29]. A responsive market orientation refers to a business’s attempt to understand and satisfy its customers’ expressed or spoken needs, whereas a proactive market orientation refers to attempts to discover, understand and satisfy customers’ latent needs. Expressed needs may have either expressed or latent solutions. [29] suggested that companies that apply proactive market orientation work more closely with their customers. Proactive market orientation can be accomplished by working closely with lead users or by conducting market experiments in order to discover future needs that are typically difficult to foresee or articulate [18, 34, 2, 33]. Given that certain customer needs are often difficult to identify or express [34], the present paper infers that collaboration in development projects is typically dependent on opportunities for interaction and communication. Three terms are used to capture the more active role of consumers: prosumption, co-production and cocreation [39, 41, 31, 32]. It has been argued that customers co-create for their own consumption [46]. The service-dominant logic [41] defines co-production and co-creation as phenomena that are connected to the
production and delivery of a service; in other words, how firms deal with their customers through customer participation in the joint creation of service value [41]. [41] claim that regardless of the service offer’s degree of tangibility, “The customer is always a co-creator of value”. Previous research has shown that it can be difficult to understand value-creation processes. It follows explicitly from the Service-Dominant Logic that value-creation processes are inherently subjective and must be understood in relation to each specific time and place [21]. In a similar fashion, scholars such as [43] have reached the same conclusion, explaining that customer value is “sticky information,” which is costly to transfer from place to place because it is tacit [5]. The implication is that a company knows more about its solution than it does about the customer’s needs for the same solution. Hence the company must communicate with customers in the development process in order to understand how the solution can be applied to satisfy the customer’s needs [30]. Furthermore, [6] described what they refer to as “absorptive capacity” as a major challenge for companies that are developing new offerings. Absorptive capacity is the company’s capacity to assimilate customer needs. [27] found that effective cooperation with all parts of a network (including customers) is essential in order to promote effective competition (i.e., an attractive offering). In line with this, [14] showed that frequent customer interaction leads to innovation success. Based on a literature review, [14] concluded that there is general agreement that intensive communication with customers is a determinant of new product success. They concluded that previous studies had provided a “limited insight into the interaction with customers.” Based on these reports, the present paper concludes that since valuecreation processes are difficult to understand. Consequently, it is essential to collaborate with customers during the development process. Companies must also know more about customer interaction, i.e. the communication process involved in applying a collaborative process.
2.2 Customer collaboration as communication and interaction with customers In the organizational communication literature, [25] have established specific dimensions that influence the quality or richness of the communication. [3] showed that the communication literature offers a novel and valuable opportunity to examine the quality of the communication in New Product Development (NPD), particularly with regard to need-related
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
information that, as already have been pointed out, can be difficult to transfer from a customeer to a company. Based on the organizational communiccation literature, [25] and [3] analyzed markketing channel communication in terms of its frequuency, direction, modality and content. The presennt article uses marketing channel communication as a framework for understanding how collaboration betw ween a company and its customers during the develoopment process results in a deeper understanding of ussers’ needs. The idea is that intense collaboration leads to better innovation, as depicted in our conceeptual model as shown Figure 1.
the paper considers passive collaaboration to be less frequent, unidirectional, electron nic and anonymous communication in which therre is an uneven distribution of initiative and crreativity and as a consequence is less beneficial for th he NPD process.
2.3
Development of hypotheeses
The hypotheses build on o the framework presented in [25] and the four dimeensions developed in this. Frequency refers to the amou unt of time for which communication occurs between thee involved parties. In the context of customer collaboratiion, frequency refers to aspects such as the amount off on-going feedback between a company and its custtomers. It may also concern the number of mutual experiments or the amount of iteration that takes pllace with customers during the development of a specific version of the offering within a developmentt project [7, 38]. Frequency can also refer to the extent to which a learning process about customerss’ needs occurs and leads to the generation of new ideas in a development project [9, 24]. Given the frameework in [25], it is reasonable to expect that a relatio onship with a higher frequency of collaboration will reesult in an increased likelihood of ‘new product successs’ and ‘market share performance.’ Accordingly, the firrst hypothesis of this paper is: H1: Collaborative processses characterized by a high frequency will lead to inccreased new product success and increased market sharee performance.
Figure 1 Conceptual model The four parameters result inn an interactive communication climate that is more orr less conducive to the learning, sharing and understandding of customer needs. It seems reasonable to expect thhat frequent and active communication is more likkely to enable bidirectional trust and high qualiity information exchange about customers’ nneeds. Active communication enables customers annd companies to meet and exchange information about needs that may otherwise be difficult to express or trannsfer. Therefore, collaboration with customers concerns the provision of qualitatively good opportunities for interaction and communication. This conceptual framework usess the four abovementioned parameters from communiccation theory in order to understand how companies intteract to develop offerings that will later result in valuee-creation that is co-created by users. More precisely, thiis article defines customer collaboration as a communnication process that is frequent, bidirectional and face-to-face in attempts at creative problem solvingg. Consequently,
Direction refers to the deemocratic aspect of communication; namely the extentt to which one party exerts power over the other(s)). This could, for example, apply to such issues as whether w both parties are equal in taking the initiative to t interact and share approximately the same workloaad. With regard to customer collaboration, direction is expected to be important when it is difficult to estimate future her words, when it is customer usability [16, 26]. In oth difficult to foresee value-creation n, there must be an even distribution of communication between parties in mer needs [3]. In order to envision future custom addition, when there is an ev ven distribution of communication and interaction, both b parties can be expected to contribute to the end result, r which should lead to more novel ideas [42]. In sum, the present paaper assumes that democratic dialogue results in processes that are beneficial for the outcome of dev velopment processes. Too often, companies take an oveerly dominating role, so the second hypothesis statess that more evenly
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
distributed initiatives will lead to more beneficial outcomes of new product development. H2: A collaborative process characterized by direction, i.e. an evenly distributed two-way communication, is expected to influence new product success and market share performance. Modality refers to how information is transmitted. It may, for example, apply to cues such as whether the communication takes place face-to-face or whether it is possible to provide immediate feedback. It may also apply to the degree to which communication is focused on a specific recipient [12]. With regard to collaboration with customers, modality means the extent to which communication takes place face-toface or otherwise (i.e., electronically) and the extent to which a customer receive opportunities to deal directly with critical aspects in a development project. This paper makes an implicit assumption that when communication takes place electronically, it typically addresses many recipients. Research confirms that group decision making is hampered in electronic communication as compared to face-to-face communication [16]. Also, if customers are excluded from any part of the development project, it is most likely the critical ones for which customer input might have the greatest impact. The third hypothesis predicts that collaborative processes, such as face-to-face communication and openness in critical aspects of a project, will facilitate the success of future products and services: H3: Collaborative processes characterized by high modality will lead to new product success and market share performance. Content refers to what is being transmitted during communication [25]. In the present paper’s context of collaboration between a company and its customers, content can pertain to whether the focus is on customer needs and difficulties related to value-creation. By way of comparison, customers may sometimes be invited to companies with the purpose of strengthening the relationship rather than to improve the outcome of the development processes. This paper focuses on whether companies make it possible for customers to share their inventiveness at the locations where their needs are most likely to be present in the future (i.e., without trying to determine them in a superficial laboratory, for example). The reason for this is related to the often documented difficulty of expressing needs [43, 28]. Latent needs are assumed to be more easily detected if a search is being conducted at the same time as the user experiences them [20]. Hypothesis 4, below, predicts that new offerings will be more successful if they
account for needs that have been identified from use experiences [23]. In addition, if customer inventiveness is shared at the location where needs are present, then other resources that are typically used in combination with the potential solution that the company offers will increase the likelihood of fully understanding customer needs[5]. This, in turn, should lead to new product success and market share performance [21]. The fourth hypothesis is: H4: When collaborative work is focused on content related to context, it will be more beneficial in terms of new product success and market share performance.
3.
Method
3.1 Sample A paper-based survey was sent to the product or service development managers of certain European firms that were selected from an externally purchased database. It was not possible to screen firms in advance to determine which firms had a development organization. Accordingly, managers were asked to participate only if their organization conducted development projects. If they for some reason could participate in the survey, either because they had no experience of NSD or that the person included in the sample no longer was with the company, they were asked to notify either the data collection company or the researchers. This was done by 16.4 percent of the respondents for the total sample. Reminders were sent to non-respondents one and two weeks after the initial mailing, which yielded a response rate of usable responses of 20.0 percent. Following the procedure recommended by [1], the tests indicated that there were no statistically significant differences between early and late respondents in terms of the survey data. Usable responses were received from 334 firms. Complete data was obtained for manufacturing and service firms in industries such as the machine industry, pulp and paper, fabricated metal goods, machinery and equipment, renting and real estate, construction services, consumer services, and business services. All questions in the survey were asked at the project level, including those regarding activities and performance. The research issue in this manuscript investigates customer collaboration in projects that intended to accomplish incremental innovations. This important distinction resulted in the analysis of a subsample of 207 responses. The other projects either related to product improvement or radical innovations, in which the four dimensions of customer collaboration
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
behave differently. Further research is needed to understand customer collaboration in such projects.
3.2 Measures and descriptive statistics The survey instrument was developed on the basis of previous questionnaires and with the help of consultants. Twenty items were used to operationalize the six latent constructs. Each item was scored on a 10point scale that ranged from “completely disagree” to “completely agree” (except for a section containing background variables for categorizing the organization). Item selection and generation for the four dimensions of customer collaboration was guided by theory. The scales that were used can be found in Appendix 1; included in the appendix are also mean values, standard deviations and loadings for each item. As Appendix I also shows, frequency and content were operationalized as a four-item construct, while direction and modality were operationalized as threeitem constructs. Business performance was measured by a scale developed by [36, 37] that captured the market acceptance of the developed innovation. Specifically, market acceptance was measured by a three-item scale that assessed the market share of the new product relative to competitor’s products and the firm’s own products [36, 37]. The study’s constructs for product performance and market performance were measured indirectly by asking the management of the participating organizations. Subjective measures of performance are commonly used in research into companies and business units of large companies.
3.3 Analysis There are strong correlations between many of the communication practices that organizations use, which can obscure the relationships between practices and performance. Structural equation modeling is well suited to handle such situations [35]. The present study used the partial least squares (PLS) method, a causal modeling method that is particularly suited to operationalizing models such as that illustrated in Figure 1 [15]. PLS is an estimation procedure that integrates aspects of principal-components analysis with multiple regression [45]. The procedure essentially extracts the first principle component from each subset of measures for the various latent constructs and uses these principle components within a system of regression models. The algorithm then adjusts the principle-component weights to maximize the predictive power of the model. All constructs were modeled using reflective indicators (in other words, the indicators are created based on the assumption that they all reflect the same underlying phenomenon [4]). Jackknife estimates were
generated in order to evaluate the significance of the paths in the model [4]. Jackknifing generally involves deleting every nth case or observation, estimating the model parameters and repeating this sample-resample procedure in order to generate a set of standard errors for the model parameters [10]. Simple t-statistics are then computed to determine whether the parameters are different from zero. Following Tukey’s guidelines, five percent of the sample was removed during the resampling procedure, which resulted in 20 sub-samples per model.
Frequency Frequency
Direction
Modality
Content
NP success
Market share
0,80
Direction
0,39
0,72
Modality
0,40
0,57
0,83
Content
0,52
0,45
0,65
0,81
NP success
0,32
0,31
0,27
0,34
0,88
Market share
0,34
0,31
0,26
0,38
0,78
0,85
Table 1 Assessment of the validity of the model (AVE) To check the validity of the model, the Average Variance Extracted (AVE) is used [12]. The AVE measures the amount of variance that is captured by the constructs in relation to the amount of variance due to measurement error [11]. To ensure discriminant validity of the constructs, the AVEs of the latent variables should be greater than the square of the correlations among the latent variables [4]. In PLS, the correlation matrix of the latent constructs, where the diagonal elements are replaced by the square root of the computed AVEs, is used to make this comparison. Higher values for the diagonal elements compared to the off diagonal elements suggest good discriminant validity. As can be seen in Table 1 this is the case for the model, which ensures that the model show good discriminant validity. Two control variables were introduced in the model; size of the business unit (1-4 scale, mean value= 3.19, std = 0.69) and experience of the respondent. Experience was measured by two variables; experience with NPD projects (mean=12.14 years, std = 8.23) and how long the respondent have been with the company (mean=13.46 years, std = 9.24). The result were equal or similar to those before the control variables were added.
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Proceedings of the 44th Hawaii International Conference on System Sciences - 2011
4.
Results
The proposed model was estimaated using PLS across firms. The first step in assessing the measurement models involves testing tthe reliability of each measured variable to ensure that tthe measurement variables (MVs) accurately apply tto their related constructs. Overall, the MV loadings w were all relatively large and positive. As seen in the appenndix; most of the loadings exceeded the recommended thhreshold value of 0.707 [17]. The research practice, how wever, is to keep the item in the analysis if the loading exceeds 0.5, as long as there is a good theoretical reasson for doing so. In this case, the study built on establlished scales for market success, which made it approppriate to keep all measures in this scale. Figure 2 presennts the results of the analysis. The model explains 61 percent of the variation in market success and 17 percent of the variation in product success. All but oone of the paths are significant (using adjusted t-tests annd p< 0.05). The significant path coefficients were 0.15000 for frequency, 0.1651 for direction and 0.205 for coontent. The nonsignificant path is modality.
Figure 2 Conceptual model with resu ults
5.
Discussion
This article viewed customer coollaboration as a communication process that is frequeent, bidirectional and face-to-face in attempts at crreative problem solving. From such a perspective, com mmunication and interaction becomes one of the most im mportant aspects when co-creating with customers. A model from research on market channel comm munication was
applied in order to understand the impact that different h on product and aspects of customer collaboration have market success. The four differeent dimensions that originated from [25] and [3] were frequency, f direction, modality and content. Our results contributes with a deeper o developed understanding into why new offerings through market research tech hniques based on collaboration with customers are more m profitable than those developed with traditionaal market research techniques (see e.g. [44]). For NS SD projects aimed at accomplishing incremental innovations, three dimensions of customer collaboraation were more or less equally important for product and market success. o collaboration with The reason for the good results of customers can be found in frequ uency, direction and content. This means that a compaany can improve the results of the development projecct by spending more time on communication with customers. This communication should be dem mocratic, i.e. the communication should be between two parties of equal power and we should focus on speccific types of content during communication. In addition n, our results support that how the information between the t customer and the company do not explain why collaboration with performs better than traditionaal market research techniques. From a managerial perspeective, this suggests that it is beneficial when workin ng with incremental innovation to spend a lot of time with w the customers or become immersed in the customerr’s context as much as possible. The research also su uggests that treating customers as more equal partners in n the process is good for product and market success. The research also nformation involving supports previous findings that in customer contexts or the transfer of o sticky information is important in the development process. p The results point towards the need for an incrreased understanding of the circumstances surrounding th he customers’ valuecreation processes. The study sug ggests that increased collaboration with customers is a key to successful development.
6.
References
[1] J.S. Armstrong, and T.S. Overto on, “Estimating Non-response Bias in Maiil Surveys”, Journal of Marketing Research, Vol. 14 (August), 1977, pp. 396–402. y, and E.M. Olson, [2] K. Atuahene-Gima, S.F. Stanley “The Contingent Value off Responsive and Proactive Market Orientattions for New Product Program Performaance”, Journal of Product Innovation Manag gement, Vol. 22 (6), 2005, pp. 464–482.
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[3] J.M. Bonner, “Customer interactivity and new product performance: Moderating effects of product newness and product embeddedness”, Industrial Marketing Management, Vol. 39 (3), 2010, pp. 485–492. [4] W.W. Chin, “The partial least squares approach to structural equation modeling”, In Marcoulides, G.A. (Ed.), Modern Methods for Business Research, LEA, Mahwah, NJ, 1998. [5] C. Luthje, C. Herstatt, and E. von Hippel, “Userinnovators and ‘local’ information: The case of mountain biking”, Research Policy, Vol. 34 (6), August, 2005, pp. 951–965. [6] W.M. Cohen, and D.A. Levinthal, “Absorptive capacity: a new perspective on learning and innovation”, Administrative Science Quarterly, 35(1), 1990, pp. 128–152. [7] R.G. Cooper, “Overhauling the new product process”, Industrial Marketing Management, Vol. 25 (6), 1996, pp. 465–482. [8] R.L. Daft, and R.H. Lengel, “Organizational information requirements: media richness and structural design”, Management Science, Vol. 32 (5), 1986, pp. 554–571. [9] G. S. Day, ”The capabilities of market-driven organizations”. Journal of Marketing, Vol. 56, No. 5, pp. 37-52, 1994. [10] B. Efron, and R.J. Tibshirani, An Introduction to the Bootstrap, Chapman & Hall, London, 1993. [11] C. Fornell and J. Cha, Partial least squares. In: R. P. Bagozzi (Ed.), Advanced methods of marketing research ( pp. 52–78). Cambridge, MA: Blackwell, 1994. [12] C. Fornell and D. Larcker, Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 1981, 39–50. [13] C. Grönroos., Service Management and Marketing: A Customer Relationship Management Approach, John Wiley & Co, London, 2000. [14] K.E. Gruner, and C.Homburg, “Does Customer Interaction Enhance New Product Success?” Journal of Business Research, Vol. 49 (1), 2000, pp. 1–14. [15] A. Gustafsson, and M.D. Johnson, “Bridging the quality-satisfaction gap”, Quality Management Journal, Vol. 4, 1997, pp. 27– 43. [16] R.S. Hiltz, Johnson, K. and Turoff, M., “Experiments in group decision making communication process and outcome in faceto-face versus computerized conferences”, Human Communication Research, Vol 13, No. 2, pp. 225–252, 1986.
[17] J. Hulland, “Use of partial least squares (PLS) in strategic management research: a review of four recent studies”, Strategic Management Journal, Vol. 20, 1999, pp. 195–204. [18] B.J. Jaworski, A.K. Kohli, and A. Sahay, “Market-Driven Versus Driving Markets”, Journal of the Academy of Marketing Science, Vol. 28 (1), 2000, pp. 45–54. [19] A.W. Joshi, and S. Sharma, “Customer Knowledge Development: Antecedents and Impact on New Product Performance”, Journal of Marketing, Vol. 68, 2004, pp. 47– 59. [20] P. Kristensson, A. Gustafsson, and T.Archer, “Harnessing the Creative Potential among Users”, Journal of Product Innovation Management, Vol. 21 (1), 2004, pp. 4–14. [21] R.F. Lusch, S.L. Vargo, and M. O’Brien, “Competing Through Service: Insights from Service-Dominant Logic”, Journal of Retailing, Vol. 83 (1), 2007, pp. 5–18. [22] A. Lundkvist., and Yakhlef, A., (2004). “Customer Involvement in New Service Development”. Managing Service Quality, 14 (2/3), 249-257. [23] P. Magnusson, P. Kristensson, and C. Hipp, “Exploring the Ideation Patterns of Ordinary Users”, International Journal of Product Development, Vol. 11 (3/4), 2010, pp. 289– 309. [24] J. Matthing., Sandén, B. and Edvardsson, B., “New Service Development: Learning From and With Customers”, International Journal of Service Industry Management, Vol. 15, No. 5, pp. 479-498, 2004. [25] J. Mohr and J. Nevin, “Communication Strategies in Marketing Channels: A Theoretical Perspective”, Journal of Marketing, 50 (October), 1990, pp. 36–51. [26] J.J. Mohr and Sohi R.S, “Communication flows in distribution channels: Impact on assessments of communication quality and satisfaction”, Journal of Retailing, Vol. 71, No. 4, pp. 393-415, 1995. [27] R.M. Morgan, and S.D. Hunt, “The Commitment-Trust Theory of Relationship Marketing”, Journal of Marketing, 58(3), 1994, pp. 20–38. [28] P.D. Morrison, J.H. Roberts, and E. von Hippel, “Determinants of User Innovation and Innovation Sharing in a Local Market”, Management Science, 46 (12), 2000, pp. 1513–1527. [29] J.C. Narver, S.F. Slater, and D.L. MacLachlan, “Responsive and Proactive Market Orientation and New Product Success”,
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[30]
[31]
[32]
[33] [34]
[35]
[36]
[37]
Journal of Product Innovation Management, Vol. 21 (5), 2004, pp. 334–347. S. Ogawa, “Does Sticky Information Affect the Locus of Innovation? Evidence from the Convenience-Store Industry”, Research Policy, Vol. 26, 1998, pp. 777–790. C.K. Prahalad, and Ramaswamy, V., The Future of Competition: Co-Creating Unique Value with Customers, Harvard Business School Press, Boston, 2004. R. Ramirez, “Value Co-Production: Intellectual Origins and Implications for Practice and Research”, Strategic Management Journal, Vol. 20 (1), 1999, pp. 49–65. E.M. Rogers., Diffusion of Innovations (3rd Ed.), The Free Press, New York, 1962, 1995. S.F. Slater and J.C. Narver, “Customer-Led and Market-Oriented: Let’s Not Confuse the Two”, Strategic Management Journal, Vol. 19 (10), 1998, pp. 1001–1006. J.E.M. Steenkamp, and H.C.M. van Trijp, “Quality Guidance: A Consumer-Based Approach to Food Quality Improvement Using Partial Least Squares”, European Review of Agricultural Economics, Vol. 23, 1996, pp. 195–215. X.M. Song, and M.E. Parry, “A Cross-National Comparative Study of New Product Development Processes: Japan and the United States,” Journal of Marketing, Vol. 61 (2), 1997a, pp. 1–19. X.M. Song, and P.E. Mark, “The Determinants of Japanese New Product Successes”, Journal
[38] [39] [40]
[41] [42] [43]
[44]
[45]
[46]
of Marketing Research, Vol. 34 (1), 1997b, pp. 64–76. S. Thomke, , Experimentation matters, Harvard Business School Press, USA, 2003. A. Toffler., The Third Wave, Bantam, New York, 1980. S.L. Vargo, F.W. Morgan, M.Akaka, and Y. He, “The Service-Dominant Logic of Marketing: A Review and Assessment.” Review of Marketing Research, Vol. 6, 2009 S.L. Vargo, and R.F. Lusch, “Evolving to a New Dominant Logic for Marketing”, Journal of Marketing, Vol. 68 (1), 2004, pp. 1–17. E. von Hippel., Democratizing Innovation, MIT Press, Cambridge, MA, 2005. E. von Hippel, “‘Sticky Information’ and the Locus of Problem Solving: Implications for Innovation”, Management Science, Vol. 40 (4), 1994, pp. 429-439. L. Witell, P. Kristensson, A. Gustafsson, and M. Löfgren, “Idea Generation: Customer Cocreation versus Traditional Market Research Techniques,” forthcoming in Journal of Service Management, Vol. 22 (2), 2011. H. Wold., “Systems under indirect observation using PLS”, in Fornell, C. (Ed.), Second Generation of Multivariate Analysis Methods, Praeger, New York, 1982. C. Xie, Bagozzi, R.P., and Troye, S.V., “Trying to Prosume: Toward a Theory of Consumers as Co-Creators of Value,” Journal of the Academy of Marketing Science, Vol. 36 (1), 2007, pp. 109–122.
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Appendix I
Loadings 0.71
Mean 5.20
Standard deviation 2.97
Many ideas were tested
0.80
5.18
2.70
Multiple experiments
0.83
4.99
2.88
Learning process of customer needs
0.86
4.42
2.60
Direction Communication and interaction leading to novel ideas
0.82
4.92
2.61
To reduce lead time we have focused on collaboration
0.73
6.49
2.50
Open innovation system
0.61
2.40
1.91
Modality We solve critical aspects together with customers
0.82
4.43
2.76
Frequency Ongoing feedback from customers
A high degree of face-to-face communication
0.90
4.45
2.91
Customer suggest solutions to problems
0.78
5.17
2.88
Content Active customer involvement
0.84
5.05
2.95
Customers were involved early in the development process
0.81
4.40
2.88
Inspired by customer settings to generate ideas
0.83
6.88
2.62
Used customer feedback
0.77
6.69
2.59
New Product Success Sales volume
0.88
6.14
1.97
Overall profitability
0.88
6.22
1.94
Profitability compared to goal
0.89
6.33
2.09
Market Share Market share compared to other own products
0.92
6.09
2.03
Market share compared to competitors
0.91
6.57
1.99
Market share compared to goals
0.68
6.38
2.75
9
