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Collaborative new product development environments: implications for supply chain management.


Much has been written on the subject of supply chain management (SCM) but the reality is that there is a lag between practice and theory (Bagchi and Skjoett-Larsen 2002; Geary, Childerhouse and Towill 2002; Poirier and Quinn 2004). One example is the lack of progress in achieving an integrated approach to new product development (NPD) despite testimony that this objective should be of paramount importance to upper management (Ettlie 1997) and supply chain managers (Anderson and Lee 2001; Rogers, Lambert and Knemeyer 2004). Recent research by Tracey (2004) demonstrates that many manufacturers do not take a genuinely integrative approach to NPD despite the topic's intuitive appeal and the attention it has received in the business literature since the 1980s.

The advantage of nurturing integration across functional areas and firms has been promoted in the business literature for some time (Porter and Millar 1985; Goldhar, Jelinek and Schlie 1991; Hayes and Pisano 1994; Hammer 2001). Integration in the context of SCM is defined as "interaction and collaboration between departments and organizations to achieve shared supply chain goals" (Cooper and Tracey 2005, p. 240). The main goal of providing products and services of value to customers is facilitated through integration of the supply chain (Mentzer 2004; Ross 2006; Walters 2006). Unfortunately, acknowledging and acting on this philosophy of general collaboration with a focus on the customer is difficult for many managers who are traditionally rewarded financially and otherwise by maximizing localized efficiencies (Doll and Vonderembse 1991).

Moving the firm toward genuine SCM requires top management leadership and changes in strategic direction and planning (Hammer 2001; Power 2005). This is the case in attaining an integrated NPD process, which is an important element of successful SCM (Mejza and Wisner 2001; Rogers et. al. 2004). Even an initial step such as integrating suppliers into the process represents a major adjustment to internal attitudes and procedures that must be accepted throughout the organization in advance (Twigg 1998; Handfield, Ragatz, Petersen and Monczka 1999). This research examines the impact of nurturing an organizational setting of internal collaboration and teamwork on integrated NPD, and consequently customer satisfaction. The intention is to supply stimulus for change by demonstrating some of the real advantages to be gained from developing a collaborative NPD environment.


Wynstra, Van Weele and Weggemann (2001) suggest that the extent to which an organization is willing and able to move toward integrated NPD depends on how far it has evolved in terms of overall cross-functional and process thinking. Thus, a major first step for many managers is to effectively coordinate their organizations internally (Bowersox, Closs and Stank 2003; Moberg and Speh 2003; Poirier and Quinn 2004).

Figure 1 provides the explanatory/theoretical model on which this investigation is based. The box on the left (Collaborative NPD Environment) depicts two dimensions that constitute a cooperative workplace within the context of NPD. "Interdepartmental connectedness" is a term referred to by Sethi and Nicholson (2001) to capture the extent to which a firm's culture facilitates communication and contact across functional areas. It is a type of organizational setting characterized by open information sharing, relationships that bridge area boundaries and behavior that conveys other parties are valued members of the enterprise. Such a setting helps generate an overall internal attitude of trust (Fawcett, Magnan and Williams 2004). Interfunctional biases and stereotypes are reduced and organizational members are more receptive to cross-functional arrangements such as a "team approach to NPD," the second dimension. The Collaborative NPD Environment construct may be considered an independent variable that is expected to ultimately explain a portion of the variance in the dependent variable (Customer Satisfaction).

The middle box in Figure 1 (Integrated NPD) depicts three variables expected to capture the extent to which parties that traditionally have not had extensive early participation (i.e., manufacturing, suppliers and customers) are included in the firm's NPD process (Swink 1999; Tracey 2004). If Wynstra et al. (2001) are correct, as an organization generates a more collaborative environment it should realize increased involvement from its manufacturing personnel as well as from its suppliers and customers in NPD. These variables in the middle box may be regarded as intervening because they are anticipated to emerge as functions of the independent variables (i.e., the dimensions of Collaborative NPD Environment). In this way they should help in conceptualizing the relationships between the independent variable and Customer Satisfaction as indicated by six established measurement items.


Hypothesis Development

Figure 2 displays the path model eventually tested via structural equation modeling (SEM) employing LISREL[R] (manufactured by Scientific Software International, Inc., Lincolnwood, Illinois). The "interdepartmental connectedness" and "team approach to NPD" dimensions from Figure 1 are loaded together as one factor, discussed in "Methodology." Accordingly, the first variable at the far left of the proposed path model is labeled Collaborative NPD Environment. LISREL[R] provides total (direct+indirect) effect t-values and coefficients that assist the researcher in appraising the comprehensive impact of one variable on another. The hypotheses that follow are expressed in terms of the anticipated total effect of one variable on another within the context of this model.

The Collaborative NPD Environment variable incorporates two elements: (1) the existence of an open organizational setting that reduces conflict while improving communication and connections across organizational boundaries that (2) encourages the development of cross-functional NPD teams (Sethi and Nicholson 2001). It captures the contextual aspect of an organizational setting conducive to successful NPD--one where any party that can make a contribution is encouraged to participate. It also captures the process aspect of such an environment. That is, the manner in which this expanded NPD group conducts itself: as a team where members cooperate and share information.

Swink (1999) asserts that manufacturing personnel have a critical role in NPD, mainly due to their ability to help in ensuring a balance between what may be marketable and what is technically feasible. Tracey (2004) demonstrates empirically that although their participation is beneficial, there is room for much improvement at many firms. It is anticipated that as firms evolve toward a collaborative NPD environment, they will overcome innate resistance to increasing the involvement of a functional area potentially valuable to the process such as manufacturing (Wynstra et al. 2001).


H1: The extent to which a firm develops a collaborative NPD environment will have a significant total effect on the level of involvement of manufacturing in NPD.

A collaborative NPD environment is also expected to have a positive comprehensive impact on supplier involvement. First, if H1 proves true, then the Collaborative NPD Environment variable is anticipated to have a positive indirect effect on the Supplier Involvement variable via the Manufacturing Involvement variable. Mariotti (1999) asserts that if potential external supply chain partners such as customers and suppliers sense trust, information sharing and genuine cooperation among a firm's internal units, they are more willing to join collaborative arrangements such as NPD teams. Tracey (2004) in fact found that the main beneficial influence of including internal parties such as manufacturing personnel in NPD is their ability to facilitate the increased involvement of suppliers and customers and thus enhance the firm's capacity to produce an advantageous range of new products and product features.

Second, Collaborative NPD Environment is also anticipated to have a direct positive effect on Supplier Involvement. Contemporary concurrent engineering doctrine promotes building competitive advantage through the inclusion of members from every functional area--as well as from suppliers and customers--on the NPD team (Atuahene-Gima and Evangelista 2000). Suppliers in particular are often capable of not only contributing sound product ideas but also supplying creative suggestions on the technical means to realize them (McGinnis and Vallopra 1999; Harmsen, Grunert and Bove 2000). It is expected as firms develop open organizational settings and team approaches to NPI) that include manufacturing, the organizations and their NPD teams will increasingly recognize the wide-ranging advantages of collaborating with suppliers and accept them as legitimate members of the team.

H2: The extent to which a firm develops a collaborative NPD environment will have a significant total effect on the level of involvement of suppliers in NPD.

A collaborative NPD environment is also expected to have a positive comprehensive impact on customer involvement in NPD. The two main reasons for including suppliers given above pertain to including customers as well. In particular, their participation enables the firm to learn the types of product features and product support customers actually value during development, which permits the making of product and process alterations that improve customer satisfaction (Ulrich and Ellison 1999; Goffin and New 2001).

H3: The extent to which a firm develops a collaborative NPD environment will have a significant total effect on the level of involvement of customers in NPD.

A collaborative NPD environment is expected to have a positive comprehensive influence on customer satisfaction. If H2 and H3 prove true, then Collaborative NPD Environment is anticipated to have a positive overall effect on Customer Satisfaction via the Manufacturing Involvement, Supplier Involvement and Customer Involvement variables. The benefits of increased involvement in NPD by manufacturing personnel, suppliers and customers include better decisions concerning new products or features to be pursued, improved technical assessments leading to higher quality, sound make-or-buy decisions concerning the acquisition of components, enhanced supplier and manufacturing operational performance and the reduction of development and production costs and time to market, all of which facilitate higher levels of customer satisfaction (Shin, Collier and Wilson 2000; Kannan and Tan 2002; Tan 2002; Petersen, Handfield and Ragatz 2005).

H4: The extent to which a firm develops a collaborative NPD environment will have a significant total effect on the level of customer satisfaction.


The utilization of composite measures and classical path analysis using LISREL[R] is appropriate for testing the statistical significance and strengths of a priori specified structural relations (Mentzer, Flint and Kent 1999). Reliable and valid measurement scales for each variable needed to be authenticated before the model depicted in Figure 2 could be submitted to LISIEI[R] for analysis. Garver and Mentzer (1999) contended that employing initial statistical analysis to establish the reliability of scales must be conducted before testing their scale validity using more robust techniques. Accordingly, this study follows the scientific methods for exploratory business research suggested by Nunnally (1967), Churchill (1979), Flynn, Sakakibara, Schroeder, Bates and Flynn (1994) and Sekaran (2000).

Instrument Validation

A total of 2,633 persons in the United States, thought to be familiar with their firm/division's product development process, were sent surveys. Approximately 2,500 were employees of manufacturers in a mailing list purchased from InfoUSA[R]. The remaining 133 were selected from a mailing list purchased from Penton Lists[R] of managerial subscribers from manufacturing firms of the Computer-Aided Engineering magazine. Of the 194 surveys returned, 19 were incomplete and eliminated. The remaining 175 usable responses comprised an effective response rate of 6.65 percent. A simple [chi square] test indicated the sample represents the target population (i.e., no nonresponse bias). Further analysis suggested by Armstrong and Overton (1977) also indicated the level of response bias was acceptable. Please see Appendix A for data regarding the respondents.

The respondents were requested to base their answers on the previous 5-year time period due to the notion that many of the benefits to be gained from developing an atmosphere of internal collaboration, a team approach to NPD and a truly integrated NPD process are long term in character (Dowlatshahi 1998; Schilling and Hill 1998; Ulrich and Pearson 1998; Balbontin, Yazdani, Cooper and Souder 2000; Gerwin and Barrowman 2002). Along the same line, Harmsen et al. (2000) point out that the impact of alterations to the NPD process on customer satisfaction is moderated by a number of interrelated competencies that take time to develop and thus require a long-term perspective. It was assumed that respondents who had not been in their current positions for the previous 5 years were sufficiently cognizant of their organizations' histories to answer knowledgeably.

The complete list of the initial items generated for each variable in Figure 2 can be found in Table I. Five-point Likert scales were employed across the survey. The items related to the Collaborative NPD Environment and Manufacturing, Supplier and Customer Involvement variables had the following responses available: 1=not at all, 2=a little, 3=moderately, 4=much, 5=a great deal. The items related to Customer Satisfaction variable had these available: 1 strongly disagree, 2=inclined to disagree, 3=neutral, 4=inclined to agree, 5=strongly agree.

Each scale was purified. First its reliability was appraised by examining the corrected-item total correlations (CITCs) of the items corresponding to a specific variable. An item was retained if its CITC was close to or >0.50, which indicated that it contributed significantly to Cronbach's [alpha] and thus to the internal consistency of the proposed scale. The second phase of purification involved appraising the external consistency of each scale by submitting the items pertaining to a variable to exploratory factor analysis to uncover significant cross-loadings. Retained items were expected to load at least close to 0.60 and not have cross-loadings of 0.40 or greater. Loadings below 0.40 are not reported in Table I to streamline factor interpretation.

Maximum likelihood was utilized as the extraction procedure and the varimax method was used for factor rotation. There was no appreciable difference between the results employing this combination as opposed to some mixture using principal components extraction and/or oblimin rotation (Dillon and Goldstein 1984). The MEANSUB command in SPSS[R] was employed to replace missing values with the variable mean for that item to promote consistency in calculation. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was also calculated to ensure that employing factor analysis in this situation was appropriate. The KMO statistics reported in Table I fall in the range of "good" to "very good" (Kaiser 1974).

Collaborative NPD Environment Scale. Initially this variable was considered to have two dimensions as depicted in Figure 1 The first three items (CE1-CE3) in the upper portion of Table I are from the scale developed by Sethi and Nicholson (2001) to measure "interdepartmental connectedness." The CITC for each of the three items initially ranged from 0.4623 to 0.5533 with a group [alpha]=0.6899, satisfactory for exploratory research. The second grouping of three items (CE4-CE6) was adapted from a scale, again developed by Sethi and Nicholson (2001) to measure a "team approach to NPD." The CIIC for each of the three items initially ranged from 0.5760 to 0.6663 with a group [alpha]=0.7711, very good for exploratory research. Thus, each scale was independently internally consistent. However, when all six items were submitted as a group for exploratory factor analysis, they loaded onto one factor. This new six-item scale has [alpha]=0.8100 as shown in Table I. Item CE3 is retained even though its CITC and loading are slightly below standard. CE3 was thought to be important to the research because while CE1 and CE2 capture the cross-departmental aspect of an open organizational setting, CE3 captures the cross-rank aspect.

The merging of the two initially proposed dimensions of Collaborative NPD Environment does not seem contrary to the work of Sethi and Nicholson (2001) and Wynstra et al. (2001). Their writings imply that as a firm develops a workplace focused on cross-functional and overall process thinking, it is a natural progression for it to begin to adopt a team approach to NPD. This phenomenon may be characterized as an overlapping evolvement of interdepartmental connectedness and a team approach to NPD rather than as a rigid sequence where interdepartmental connectedness must be established before a team approach to NPD can be initiated.

Integrated NPD Scales. The potential items in the middle portion of Table I pertaining to these scales were adapted from the work of Koufteros (1995), Swink (1999) and Tracey (2004). The three items MI1-MI3 were generated to measure the Manufacturing Involvement variable. The CITC for each of the three items and the group [alpha] (0.8333) are very good. Four items were initially generated to measure Supplier Involvement. The one shown as being dropped had a CITC of 0.4039, did not contribute significantly to [alpha] and was also thought to be tapped in the three retained items SI1-SI3. Two items were generated to measure Customer Involvement. Cronbach's [alpha] is a meaningless calculation for a two-item scale, hence the simple correlation is reported (Mentzer et al. 1999). The eight retained items (MI1-MI3, SI1-SI3 and CI1-CI2) loaded cleanly across three factors, confirming the external consistency of the three scales.

Customer Satisfaction Scale. Measuring customer satisfaction with products is continually problematic. Surveying and/or interviewing actual customers can generate results that are often inaccurate or misleading (Ross 2006). Also, capturing the perceptions from a supplier and a customer engaged in a business relationship via a survey is feasible only to a point. In reality it is often difficult to attain responses from one party, much less acquire a corresponding set from the second. Thus the researcher is frequently unable to acquire a significant number of matched pairs to employ anything but relatively unsophisticated statistical techniques.

La Londe, Cooper and Noordewier (1988) and Byrne and Markham (1991) contend that modern business managers must have an accurate sense of their firm's performance regarding customer satisfaction to remain in business, and that their grasp of the situation may be more precise than those of their customers. Furthermore, individual members of a supply chain are both customers and suppliers and they should be able to provide valid perceptions of the effectiveness of supplier-customer linkages. They should also be able to respond intelligently to questions regarding the firm's internal processes. Utilizing single informants enables gathering a suitable number of responses to employ SEM and to produce findings with high generalizability to other organizational settings. SEM is also superior in its ability in representing unobserved concepts and possible relationships among them, even if the variables constituting the model are complex and interrelated, with long-term consequences (Gimenez, Large and Ventura 2005). However, it requires the careful development of reliable, valid scales beforehand, and hence the scale-purification steps employed here.

The potential items in the bottom portion of Table I pertaining to this scale were adapted from the work of Heskett, Jones, Loveman, Sasser and Schlesinger (1994) and Tu, Vonderembse and Ragu-Nathan (2001). The CITC for each of the six items is excellent and the group [alpha] (0.8299) is very good. The six items also loaded cleanly on one factor, confirming the scale's external consistency.

Assessment of Predictive Validity

The use of correlation to assess predictive validity is appropriate when the objective of the research is to understand the pattern of relationships among variables, and not to attempt to explain the total variance of a particular variable (Hair, Anderson, Tatham and Black 1995). Table II was constructed to examine associations among composite measures of the five variables of interest in this study. The means and standard deviations given for the variables are for the items found to be statistically significant indicators, with no provision made for missing values. For example, for Collaborative NPD Environment, the mean (3.95) and standard deviation (0.66) are based on the mean rating assigned by the respondents to items CE1-CE6 (see Table I). The correlations among the five composite measures are significant at [alpha]=0.01 or 0.05. This indicates that many of the variables are statistically related, which validates the possibility of finding meaningful causal relationships during path analysis.

Path Model Evaluation

The model in Figure 2 was submitted to LISREL[R] to evaluate its proposed paths and the hypothesized total effects by employing classical path analysis utilizing the composite measures of the variables mentioned above. The number of usable responses from the survey supports employing this methodology. The model has 12 parameters: five variables and seven proposed paths. The most stringent criterion for an adequate sample size is 10 responses for each parameter (Hair et al. 1995); or in this case, 120 responses, which are adequately covered by the 175 available.


The result of submitting the model to LISREL[R] is shown in Figure 3. The fit indices--goodness of fit=0.97, comparative fit=0.93 and root mean square residual=0.020--indicate that the model's ability to predict the actual data is acceptable (Bollen 1989). The t-values next to the paths indicate each is significant at [alpha]=0.05. The path coefficients ([gamma] or [beta]) provide an indication of the strength of a path relative to the other paths in the model. For example, it would be fair to state that the Collaborative NPD Environment [right arrow] Supplier Involvement path ([gamma]=0.29) is nearly twice as potent as the Supplier Involvement [right arrow] Customer Satisfaction path ([beta]=0.15).


Table III provides total effect t-values and coefficients that are interpreted in the same manner as the individual path statistics. H1 is supported; the extent to which a firm develops a collaborative NPD environment has a significant total effect on the level of involvement of manufacturing in NPD. In this case the path and total effect t-value and coefficient are identical, 6.47 and 0.46, respectively, which is the largest in Table III. An "open" organizational setting in tandem with a team approach to NPD appears to have a meaningful positive impact on increasing the participation of manufacturing personnel.

H2 is also supported; the extent to which a firm develops a collaborative NPD environment has a significant total effect on the level of involvement of suppliers. The total effect t-value of 4.91 indicates such an atmosphere has a meaningful comprehensive positive impact on increasing the participation of suppliers. The direct effect (0.29) is slightly over four times the indirect effect through Manufacturing Involvement (0.36 - 0.29=0.07). This implies that fostering a collaborative NPD environment may encourage the involvement of suppliers, but the inclusion of manufacturing personnel in NPD as well will likely increase the probability of their joining the collaboration.

H3 is supported; the extent to which a firm develops a collaborative NPD environment has a significant total effect on the level of involvement of customers in NPD. The total effect t-value of 4.97 indicates such a workplace has a meaningful comprehensive positive impact on increasing the participation of customers. The total effect coefficient (0.36) is identical to the one related to Supplier Involvement indicating the overall influence of this type of organization setting is equally favorable to the involvement of customers and suppliers. Interestingly, the direct effect of Collaborative NPD Environment on Customer Involvement (0.27) is three times the indirect effect through Manufacturing Involvement (0.36 - 0.27=0.09). This suggests the participation of manufacturing personnel in NPD provides a greater boost to the involvement of customers than suppliers, which is also supported by the respective direct path coefficients ([beta]=0.19 compared with [beta]=0.16).

Finally, H4 is supported; the extent to which a firm develops a collaborative NPD environment has a significant total effect on its level of customer satisfaction. Supplier Involvement ([beta]=0.15) and Customer Involvement ([beta]=0.19) each has a significant positive direct effect on Customer Satisfaction; accordingly, Collaborative NPD Environment has a positive total effect (t-value=3.11) on Customer Satisfaction. Consequently, the theory that an open organizational setting in conjunction with a team approach to NPD has a meaningful positive far-reaching impact on overall customer satisfaction cannot be rejected (Bollen 1989).


The central goal of this study is to investigate the possible influence of nurturing an organizational environment of internal collaboration and teamwork concerning NPD on integrated NPD (in terms of including parties traditionally afforded little to no role), and ultimately on customer satisfaction. Although the results of hypothesis testing using path analysis seem obvious, the results (as described in the ensuing paragraphs) also confirm that many manufacturers are still not taking an integrated approach to NPD.

Table IV was constructed to learn more about the specific outcomes to firms that have cultivated highly collaborative NPD environments with the objective of encouraging their further development at more firms. The 175 firms from the study were placed into "Little-To-Moderate," "Average" and "High" groups based on their mean response to the composite measure of the Collaborative NPD Environment variable. The sample's mean response to the composite measure of the Collaborative NPD Environment variable was 3.95 ([sigma]=0.66) as noted in Table II. Forty-five firms with a mean response [greater than or equal to]4.50 were placed in the High Collaboration group. The mean response for this group is 4.69 ([sigma]=0.18). They were inclined to perceive their firm/division exhibits a great degree of cross-functional/rank communication and behavior indicative of a team approach to NPD (see items CE1-CE6 in Table I).

Ninety-nine firms with a mean response within the 3.50-4.40 interval inclusive were placed in the Average Collaboration group. The mean response for this group is 3.95 ([sigma]=0.28). They were inclined to perceive their firm/division exhibits a typical amount of cross-functional/rank communication and behavior indicative of a team approach to NPD. The remaining 33 firms that had a mean response within the 1.50-3.33 interval inclusive were placed in the Little-to-Moderate Collaboration group. The mean response for this group is 2.88 ([sigma]=0.47). They were inclined to perceive their firm/division exhibits little-to-moderate cross-functional/rank communication and behavior indicative of a team approach to NPD.

The mean score for each composite variable and its related individual items (see Table I) was calculated across the three groups. ANOVA utilizing Tukey's pairwise comparisons was employed to determine if significant differences at [alpha]=0.01 or 0.05 existed among them. The firms in the High and Average groups distinguish themselves from the Little-to-Moderate group at [alpha]=0.01 with regard to involving manufacturing from the early stages of product development, with the same pattern holding mostly true for items MI-MI3. This implies that as firms evolve a collaborative NPD environment, they increase the participation of manufacturing personnel in NPD. Nonetheless, opportunity for intensifying their involvement exists even for the High Collaboration group. Their mean response of 3.70 indicates they generally only moderately agree that they involve them in NPD. It is interesting to note that item MI2 received noticeably higher responses than items MI1 and MI3 across the board. This could be interpreted that while firms facilitate manufacturing playing a strong role at some point in the design of products, they do not always involve them early on, which would maximize their contribution.

The firms in the High ([alpha]=0.01) and Average ([alpha]=0.05) groups distinguish themselves from the Little-to-Moderate group with regard to involving suppliers from the early stages of product development, asking for their input on component parts, and in general making use of their expertise. Significant opportunity is also present for increasing their participation across all the groups. The High group's mean response of 3.06 indicates they are by and large neutral with regard to participation of suppliers in these areas, with the mean responses from the other two groups being markedly lower. The responses to item SI3 do suggest that the High group differentiates itself from both of the other groups by building relationships with suppliers and taking advantage of their expertise even if they do not necessarily involve them early in NPD or ask for their input concerning the design of component parts, which would probably enable them to maximize the level of assistance received from suppliers.

The statistics in the Customer Involvement section of Table IV indicate that firms in the High group clearly distinguish themselves from the

other two when involving customers in the early stages of NPD and when visiting them to discuss product development issues. This suggests firms with cultures that exhibit a great deal of cross-functional/rank communication and behavior indicative of a team approach to NPD are much more likely to reach out to customers during the product development process. This may also help to explain why the High group clearly exceeds the other two concerning their customers perceiving that they receive their money's worth from this group's products (see item CS6, Tables I and IV). Although it seems logical that including customers in product development would enable manufacturing firms to increase their clients' satisfaction with their products, here is another area where room for improvement exists across all groups.

Implications for Senior Managers

The findings reported here indicate an organization that exhibits high levels of cross-functional/rank communication and behavior indicative of a team approach to NPD ultimately perceive elevated levels of customer satisfaction, which is a source of competitive advantage (Day 1994). They also reveal there is opportunity for improvement at many firms as only 26 percent of the respondents perceived high collaboration concerning their firms' NPD environments.

Overcoming resistance to long-established mindsets and individualistic modes of operation is the main challenge facing executives intending to attain genuine SCM. A prime example of this is developing a culture that facilitates the organization in getting past the traditional transactional approach to business arrangements to becoming more skilled in developing and managing cooperative relationships (Kerr 2006). In Mintzberg's (1989) terms this entails evolving from a machine organization where the "strategic apex" rules a top-down approach to control, to an innovative organization where the top management oversees a workplace where process improvement is promoted by involving any member who might make a meaningful contribution.

Such a progression requires upper managers willing to challenge longstanding procedures and the entrenched cultural and political structures within the organization (Lewin and Stephens 1993). This is particularly true in the case of building an integrated NPD process. Efficient NPD today requires ongoing collaboration that cuts across most areas of a business, as opposed to the time-honored "relay" approach dominated by a few functions (Takeuchi and Nonaka 1986; Wheelwright and Clark 1992). Thus the upper management must set the stage for genuine integration at the working level by adopting the appropriate mindsets and behaviors themselves (Suri 1998).

This will often be challenging. Businesses in the United States have historically focused on short-term direct monetary results when allocating resources (Porter 1992), while the benefits of many intangible capabilities, such as integrated NPD processes, are long term in nature and more difficult to evaluate (Ulrich and Smallwood 2004). Consequently, organizations have produced numerous managers who continue to give far more attention to tangible assets such as buildings and machinery than they give to intangible assets such as an ability to respond efficiently to varying customer requirements, which is at the heart of an integrated approach to NPD.

Implications for Supply Chain Managers

Effective SCM requires a workplace that taps into the collective knowledge of all parties capable of providing constructive input (Quinn 2001; Sengupta 2004). Supply chain managers can contribute by encouraging the top management to develop company environments focused on cross-functional contact and information sharing, however difficult this may be. Some of the findings reported here also suggest that opportunities exist for supply managers to have a more immediate impact. First, the concurrent evolution of (1) an open organizational setting and (2) the development of cross-functional team approach to NPD, as opposed to the theorized (1) then (2) sequence, is possible. This implies that supply managers may be able to advance the progression toward open organization settings by supporting team approaches to NPD. By demonstrating that personnel functioning as a team in sharing information and cooperating during the development of a product is not only doable but also beneficial to the firm, supply managers may give impetus to similar types of arrangements at higher levels (e.g., the generation of strategic overall supply chain goals concerning product and service development).

Second, the findings suggest that the early involvement of manufacturing personnel, suppliers and customers in NPD, individually and jointly, have a positive effect on customer satisfaction, which can be expected to favorably impact firm performance (Tracey 2006). They are also consistent with previous work that demonstrates considerable opportunities exist for increasing the initial participation of all three groups. It may be within the realm of supply managers' direct influence to help in alleviating this situation by doing what they can to increase the contributions of these parties from the beginning of the process.


The research of Johnson, Klassen, Leenders and Fearon (2002) suggests a general lack of cooperative arrangements exist across supply chains. This study confirms this is the case concerning integrated approaches to NPD. It verifies that the development of organizational settings that facilitate cross-functional communication and team approaches to the product development process has long-term benefits in terms of increasing the involvement of manufacturing personnel, suppliers and customers, besides ultimately enhancing perceived customer satisfaction. It also validates that practice does not follow theory at many firms.

While it focuses on integrated NPD processes, the findings reported here hint at a wide-ranging scarcity of integration across departments and organizations despite the attention the topic has received. Many firms do not involve their manufacturing area early on in the NPD process, much less suppliers and customers. This is an indication that few firms actually view competition as supply chain versus supply chain and have the ultimate objective of being a member of a chain that generates products and services that outperform existing solutions (Blackwell and Blackwell 1999).

This seems unfortunate given the results of this study. It reveals there are long-term advantages to an organization that progresses in terms of cross-functional and cross-firm thinking concerning NPD processes. It also verifies there are advantages to increasing the early participation of parties in the NPD process that has traditionally been brought in late or not at all. Perhaps most encouraging, it also indicates that achieving both these advances can occur concurrently, with the benefits possibly being reaped in each step along the way.

Opportunities for Future Research

No one methodology is perfect for all situations; often choices have to be made that affect the generalizability of research findings. This empirical study may be considered exploratory. Ketokivi and Schroeder (2004) found perceptual measures of performance to be reliable and valid, which provides support for their use. On the other hand, they also recommend that single-informant studies utilizing the responses of managers to investigate their own internal operations as well as the satisfaction level of their external partners be conducted with great care. The response rate of 6.65 percent, while disappointing, did provide a sufficient number of responses to employ sound scale purification methods and path analysis utilizing composite measures. However, the number of responses did not justify the use of SEM to refine the scales using confirmatory factor analysis or to test a fully specified casual model (Wallenburg and Weber 2005).

This study provides general support for why managers should promote organizational settings that facilitate cross-functional communication and team approaches to a product development process that includes manufacturing personnel, suppliers and customers. Many questions remain to be answered, particularly concerning the how. For example, what tools might managers employ to overcome entrenched cultural/political norms that have traditionally limited cross-functional/rank information sharing and decision making? In other words, how might managers persuade their colleagues to put aside a focus on making their short-term numbers and place some emphasis on the long-term viability of the company by increasing the effectiveness of its NPD process and thus its supply chain? Such questions open the door for cross-functional research in collaboration with experts from the areas of organizational behavior, finance and human resource management, among others.

SCM professionals require more forward-looking useful research as opposed to documentation of their current activities (Aylesworth 2004). A variety of sound research methodologies might be employed to increase our knowledge regarding the issues raised in this study. Lambert and Pohlen (2001) suggest measures of supply chain performance must enable analysis of each link in the supply chain in terms of each supplier-customer pair's ability to create value for the chain. This indicates employing dyads (i.e., supplier-customer pairs) as the unit of measure is a viable approach (e.g., Johnston, McCutcheon, Stuart and Kerwood 2004). Sample size however is frequently in a range that necessitates the use of relatively unsophisticated statistical techniques. Nonetheless, such studies can be extremely useful by delineating important variables that may be associated in some way (e.g., Tracey, Fite and Sutton 2004). For example, this methodology could be employed to learn more about what elements of collaborative NPD arrangements actually lead to higher levels of customer satisfaction based on the joint perceptions of suppliers and customers.

Case studies enable an in-depth analysis of a particular situation relevant to SCM to obtain clues as to the critical factors underlying an area of interest (e.g., Sridharan, Caines and Patterson 2005). Generalizability is restricted to other identical settings, which is seldom the situation in the study of supply chains as their compositions can vary dramatically. Nonetheless, case studies can contribute to the body of knowledge by uncovering useful principles that managers can translate and apply to their own situations, for example, with regard to effectively incorporating suppliers and customers in NPD.

Another possibility is employing an action research methodology where members of an organization and researchers work together to find scientific fundamentals for change through an explicit cyclical process of problem diagnosis, action planning, action taking, evaluation and knowledge specification (Muller 2005). This method may be an especially useful tool for practicing managers and academicians involved in consulting activity who desire to publish constructive research concerning integrated NPD processes.

The model offered here utilized composite measures and path analysis to investigate the consequences of a collaborative NPD environment on the involvement of one internal party (manufacturing), two external parties (suppliers and customers) and finally on customer satisfaction. Future studies should expand the model to contain more variables including constructs that capture the participation of other parties (e.g., marketing, engineering and R & D) and other outcome variables such as cost reduction, flexibility, time-to-market and firm performance. A more complex model would enable the testing of extra paths among these additional variables.

Future studies should also collect more extensive new data to confirm, refine and expand upon the construct measures provided here as well as for any new constructs/variables to be added. A larger sample size would also allow the use of SEM to verify scales utilizing confirmatory factor analysis and to test hypotheses using a fully specified causal model. The data set was limited to manufacturing firms from certain industries located in a particular country. Including manufacturing operations from other industries and/or located outside the United States would enable a broader testing of the generalizability of the results.


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Title Frequency Valid %

Respondent job title
President/GM/CEO/owner 16 9
Vice president (product development, engineering, 27 16
Director (engineering/manufacturing/product 17 10
Manager (product development/engineering/R & D/ 56 33
Chief engineer/senior engineer/engineer 34 26
Designer/drafter 11 6
Missing 4 --

Number of Employees Frequency Valid %

Employees at respondent location
100 or less 37 21
101-500 99 57
501-1,000 12 7
More than 1,000 27 15

Response Frequency Valid %

Type of manufacturing operation
job shop 44 26
Manufacturing cells 42 25
Assembly line 24 14
Flexible manufacturing system 19 11
Custom projects 17 10
Batch processing 10 6
Continuous flow 8 5
High volume, discrete 7 4
Missing 4 --

Industry classification
Fabricated metal products 108 65
Transportation equipment 29 17
Rubber and miscellaneous Plastics 13 8
Measuring and analyzing instruments 9 5
Primary metal 8 5
Missing 8 --

Annual sales
< $10 million 34 20
$10-$50 million 72 41
$50-$100 million 20 11
$100-$250 million 13 7
$250-$500 million 9 5
$500-$1000 million 6 3
More than $1 billion 20 11
Missing 1 --


Chong Leng Tan obtained her PhD in Manufacturing Management and Engineering at the University of Toledo in Toledo, Ohio.

Michael Tracey is an associate professor of operations in the department of management and marketing at Winston-Salem State University in Winston-Salem, North Carolina.

Collaborative NPD Environment* -- One Dimension -- KMO=0.80

Items CITC Factor 1

CE1: In this firm, employees from 0.6545 0.728
 different departments feel
 comfortable contacting each other
 when the need arises
CE2: There is ample opportunity for 0.5194 0.545
 informal "hall talk" among
 individuals from different
 departments in this firm
CE3: In this firm, it is easy to talk 0.4515 [alpha]=0.8100 0.492
 to virtually anyone you need to,
 regardless of their rank or
CE4: Team members are cooperative with 0.6067 0.719
 each other during the development
 of a product
CE5: Product development employees 0.6449 0.763
 work as a team
CE6: Product development group members 0.5644 0.619
 share information

Integrated NPD* -- Three Dimensions (Manufacturing, Supplier and
Customer Involvement) -- KMO=0.72

 Loading Loading Loading
Items CITC Factor 1 Factor 2 Factor 3

MI1: Manufacturing is 0.8080 0.988
 involved in the
 early stages of
 product development
MI2: Manufacturing plays 0.5725 [alpha]= 0.565
 a strong role in 0.8333
 the design of
MI3: Manufacturing 0.7153 0.755
 participate early-
 on in product
 development phases
SI1: Our suppliers are 0.4852 0.618
 involved in the
 early stages of
 product development
SI2: We ask our 0.5057 [alpha]= 0.587
 suppliers for their 0.6706
 input on the design
 of component parts
SI3: We make use of 0.4604 0.618
 supplier expertise
 in the development
 of our products

Dropped: Our suppliers develop the component parts for us. (Tapped in
retained Supplier Involvement items)
CI1: We involve our r=0.6382 0.612
 customers in the
 early stages of
 product development
CI2: We visit our 0.995
 customers to
 discuss product
 development issues

Customer Satisfaction** -- One Dimension -- KMO=0.82

Items CITC Factor 1

CS1: Our customers are satisfied with 0.5820 0.597
 the quality of our products
CS2: Our customers are satisfied with 0.5440 0.583
 the features that our products
CS3: Our customers are loyal to our 0.5660 [alpha]=0.8299 0.594
CS4: Our customers refer new customers 0.5607 0.598
 to purchase our products
CS5: Our customers feel that we offer 0.7215 0.839
 products with high value
CS6: Our customers perceive they 0.6510 0.774
 receive their moneys' worth when
 they purchase our products

*Responses available: 1=not at all, 2=a little, 3=moderately, 4=much,
5=a great deal.
**Responses available: 1=strongly disagree, 2=inclined to disagree,
3=neutral, 4=inclined to agree, 5=strongly Agree.


Construct ([mu], [sigma]) CE MI SI CI

Collaborative NPD Environment --
 (3.95, 0.66)
Manufacturing Involvement 0.464** --
 (3.28, 0.91)
Supplier Involvement 0.360** 0.291** --
 (2.82, 0.80)
Customer Involvement 0.364** 0.321** 0.225** --
 (3.36, 1.00)
Customer Satisfaction 0.350** 0.248** 0.192* 0.217**
 (4.15, 0.52)

**Correlation is significant at the 0.01 level.
*Correlation is significant at the 0.05 level.


 Manufacturing Supplier
Variable/On Involvement Involvement

Collaborative NPD Environment t-value=6.47 t-value=4.91
 Coefficient=0.46 Coefficient=0.36
Manufacturing Involvement -- t-value=1.99
Supplier Involvement -- --
Customer Involvement -- --

 Customer Customer
Variable/On Involvement Satisfaction

Collaborative NPD Environment t-value=4.97 t-value=3.11
 Coefficient=0.36 Coefficient=0.12
Manufacturing Involvement t-value=2.47 t-value=2.36
 Coefficient=0.19 Coefficient=0.12
Supplier Involvement -- t-value=2.06
Customer Involvement -- t-value=2.50


 Little-to-Moderate Average Collaboration
Construct Item Collaboration (n=31) (n=99)

Manufacturing Involvement* 2.56 (0.72) 3.31 (0.83) (b)
 MI1 2.35 (0.71) 3.25 (0.92) (b)
 MI2 3.10 (1.25) 3.62 (1.01) (e)
 MI3 2.23 (0.72) 3.09 (0.96) (b)
Supplier Involvement* 2.43 (0.74) 2.85 (0.74) (e)
 SI1 2.37 (0.96) 2.62 (0.89)
 SI2 2.24 (0.87) 2.65 (0.99)
 SI3 2.68 (1.01) 3.15 (0.93)
Customer Involvement* 2.87 (1.03) 3.26 (0.93)
 CI1 2.68 (1.08) 3.19 (1.06)
 CI2 3.06 (1.15) 3.32 (1.00)
Customer Satisfaction** 3.87 (0.59) 4.14 (0.48) (e)
 CS1 3.98 (0.91) 4.28 (0.67)
 CS2 4.29 (0.64) 4.31 (0.60)
 CS3 3.68 (0.94) 4.08 (0.70) (e)
 CS4 3.54 (0.69) 3.88 (0.78)
 CS5 3.90 (0.79) 4.16 (0.61)
 CS6 3.77 (0.80) 4.06 (0.57)

 High Collaboration
Construct Item (n=45)

Manufacturing Involvement* 3.70 (0.91) (a)
 MI1 3.49 (1.08) (a)
 MI2 4.07 (0.96) (a)
 MI3 3.47 (1.10) (a)
Supplier Involvement* 3.06 (0.86) (a)
 SI1 2.71 (1.00)
 SI2 2.79 (0.98) (f)
 SI3 3.67 (1.14) (a,d)
Customer Involvement* 3.92 (0.88) (a,c)
 CI1 3.91 (0.98) (a,c)
 CI2 3.93 (1.09) (a,d)
Customer Satisfaction** 4.35 (0.46) (a)
 CS1 4.53 (0.63) (a)
 CS2 4.60 (0.54) (d,f)
 CS3 4.13 (0.59) (a)
 CS4 3.95 (0.86) (f)
 CS5 4.42 (0.66) (a)
 CS6 4.41 (0.66) (a,d)

(a) A significant difference exists between the High and Little-to-
Moderate Collaboration groups ([alpha]=0.01).
(b) A significant difference exists between the Average and Little-to-
Moderate Collaboration groups ([alpha]=0.01).
(c) A significant difference exists between the High and the Average
Collaboration groups ([alpha]=0.01).
(d) A significant difference exists between the High and the Average
Collaboration groups ([alpha]=0.05).
(e) A significant difference exists between the Average and Little-to-
Moderate Collaboration groups ([alpha]=0.05).
(f) A significant difference exists between the High and Little-to-
Moderate Collaboration groups ([alpha]=0.05).
*Responses available: 1=not at all, 2=a little, 3=moderately, 4=much,
5=a great deal.
**Responses available: 1=strongly disagree, 2=inclined to disagree,
3=neutral, 4=inclined to agree, 5=strongly agree.
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Author:Tan, Chong Leng; Tracey, Michael
Publication:Journal of Supply Chain Management
Geographic Code:1USA
Date:Jun 22, 2007
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