Aligning marketing strategies throughout the supply chain to enhance performance

Industrial Marketing Management 41 (2012) 1008–1018

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Industrial Marketing Management

Aligning marketing strategies throughout the supply chain to enhance performance Kenneth W. Green Jr. a b c

a,

⁎, Dwayne Whitten b, 1, R. Anthony Inman c, 2

Department of Management, Marketing, and Management Information Systems, College of Business, Southern Arkansas University, P.O. Box 9410, Magnolia, AR 71754, USA Texas A&M University, Mays School of Business, Information and Operations Management Department, Mailstop 4217, College Station, TX 77843, USA College of Administration and Business, P.O. Box 10318, Louisiana Tech University, Ruston, LA 71272, USA

a r t i c l e

i n f o

Article history: Received 6 October 2010 Received in revised form 5 January 2012 Accepted 5 January 2012 Available online 25 February 2012 Keywords: Supply chain management Marketing strategy alignment Supply chain performance Organizational performance Structural equation modeling

a b s t r a c t A marketing strategy alignment model that incorporates marketing strategy alignment, supply chain performance, and organizational performance constructs is proposed and assessed. Data collected using an e-mail, Internet-based methodology from a sample of 117 managers with knowledge of their organizations supply chain activities are analyzed using a structural equation methodology. The data collected reflect the perceptions of the managers concerning the extent to which their firms have aligned marketing strategies with supply chain partners. Findings indicate that alignment of the marketing strategies by the partners throughout the supply chain is positively associated with supply chain performance and that supply chain performance is positively associated with organizational performance. Because this is an early study based on a relatively small, diverse sample, the findings of the study are considered preliminary. Based on the results, managers seeking to improve the performance of their organizations should work with supply chain partners to align marketing strategies throughout entire the supply chain. This is one of the first empirical studies to assess the relationships among marketing strategy alignment, supply chain performance, and organizational performance constructs. © 2012 Elsevier Inc. All rights reserved.

1. Introduction Supply chains are value chains that extend from supplier's supplier to ultimate customer. Supply chain management requires integration and coordination of business processes throughout the supply chain for the purpose of satisfying and responding to changes in the demands of ultimate customers (Lambert & Cooper, 2000; Vokurka & Lummus, 2000). The business processes that must necessarily be integrated and coordinated include: purchasing, manufacturing, marketing, logistics, and information processes. As Jarratt and Fayed (2001, p. 71) state, “The development of integrated supply systems moves competition into a new phase, with systems competing against systems to create efficiency and client value at each point in the system.” Heizer and Render (2006) identify the key to successful supply chain management as the ability to develop long-term, strategic relationships with supply chain partners. The quality of the supply chain relationships directly impacts the performance of the supply chain (Fynes, de Búrca, & Marshall, 2004). Effective supply chain management maximizes value to the ultimate customers of the supply chain in terms of both satisfaction with the product and/or services and a relatively low total cost of the product and/or service. Supply

⁎ Corresponding author. Tel.: + 1 870 235 4317 (Office); fax: + 1 870 235 4800. E-mail addresses: [email protected] (K.W. Green), [email protected] (D. Whitten), [email protected] (R.A. Inman). 1 Tel.: + 1 979 845 2919 (Office); fax: + 1 979 845 5653. 2 Tel.: + 1 318 257 3568 (Office); fax: + 1 318 257 4253. 0019-8501/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2012.02.003

chain managers are responsible for reconciling supply and demand issues within value chains (Rainbird, 2004b). Traditional supply processes focus on efficiency in support of lower costs, while traditional demand processes focus on effectiveness with the aim to please customers (Rainbird, 2004b). Rainbird (2004a) asserts that this process fusion can be a source of dynamism rather than dysfunction, although such fusion is difficult to achieve. Existing research supports the general proposition that the alignment of systems throughout the supply chain enhances organizational performance (Green & Inman, 2005). In particular, Seggie, Kim, and Cavusgil (2006) argue for and find empirical support for positive impact of IT system integration throughout the supply chain on market performance through brand equity. Richey, Tokman, and Skinner (2008, p. 847) similarly argue and find support for their proposition that retail managers will “reap superior gains” from technology collaborations with suppliers. Powers and Reagan (2007) contend that supply chain partners, in particular buyers and sellers, derive competitive advantage from strong, long-term relationships and empirically identified relatively more important relationship factors. The integration and coordination of marketing processes throughout the supply chain has received little attention (Jüttner, Christopher, & Godsell, 2010). Flint (2004) argues that the superior marketing strategies of the future will necessarily be those that are more fully integrated across the supply chain. The ability to integrate and coordinate becomes paramount to satisfying the demands of the ultimate customers of the supply chain. While there are costs associated with efforts to coordinate and integrate (Rainbird, 2004b), we argue that the total cost to the

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ultimate customer is minimized through a focused response by all supply chain partners to the changing demands of ultimate customers. The integration and coordination yields overall efficiency and effectiveness improvements that lead to better satisfied ultimate customers (Rainbird, 2004b). Successful supply chains are customer focused, requiring not only that each of the individual firms within the supply chain exhibit a market orientation but that the marketing strategies of the individual firms be integrated and coordinated such that the supply chain, as an entity, exhibits a market orientation (Gundlach, Bolumole, Eltantawy, & Frankel, 2006; Jüttner, Christopher, & Baker, 2007; Min & Mentzer, 2000). Gundlach et al. (2006) argue that the integration and coordination of marketing strategies across the supply chain offers “continued opportunity” for cross-disciplinary research. It should be noted that Fabbe-Costes and Jahre (2008), after reviewing the supply chain integration and performance literature, concluded that more research is necessary before a general conclusion related to the impact of supply chain integration on performance can be drawn. The literature related to the development and implementation of organization level marketing strategies that focus on the satisfaction of immediate customers is relatively well developed (Green, Inman, Brown, & Willis, 2005; Green, McGaughey, & Casey, 2006; Panayides, 2004; Vorhies, Morgan, & Autry, 2009). The supply chain management literature related to the importance of collaboration of supply chain partners to satisfy the ultimate customers of the supply chain is also relatively well developed (Chen & Paulraj, 2004; Ho, Au, & Newton, 2002; Hoyt & Faizul, 2000; Lee, 2004; Whitten, Green, & Zelbst, 2012). This is not the case for the literature supporting the need to integrate and coordinate marketing strategies throughout the supply chain. This theoretical basis for marketing strategy alignment throughout the supply chain has been theoretically argued and is supported anecdotally in the literature (Jüttner et al., 2010). Supporting empirical evidence is not present, however. We theorize a marketing strategy alignment performance model with a marketing strategy alignment construct as antecedent to supply chain performance and organizational performance. This research effort extends and expands the view of marketing strategy alignment from the organization level to the supply chain level. We argue that the organizational strategies of all supply chain partners should be integrated into a supply chain level strategy that focuses on satisfaction of the ultimate customers of the supply chain. The specific research question under investigation is: “Does a supply chain level marketing strategy aimed at satisfying ultimate customers positively influence supply chain and organizational performance?” Generally, we propose that alignment of marketing strategies by the partners throughout the supply chain will positively affect supply chain performance, which will, in turn, positively influence the organizational performance of each of the supply chain partners. We define and describe the marketing strategy alignment construct and recommend a multi-item scale for measurement of the construct. A sample of APICS members with knowledge of their organizations' supply chain management initiatives provided data necessary to assess the marketing strategy alignment model. Perceptions of the responding managers related to the extent to which their individual firms have aligned marketing strategies with supply chain partners are reflected in the dataset. The study scales are carefully assessed for validity and reliability, and the study hypotheses are tested within the context of the marketing strategy alignment model following a structural equation modeling approach. 2. Literature review and hypotheses Manufacturing organizations have generally adopted strategies internally and worked to integrate those strategies across intraorganizational functions (Swink, Narasimhan, & Kim, 2005); those internally integrated strategies have led to the ability to produce relatively high quality and relatively low cost products. It is difficult to

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develop additional competitive advantage through such internal approaches (Cohen & Roussel, 2005). With competition now at the supply chain level (Craighead, Blackhurst, Rungtusanatham, & Handfield, 2007), competitive advantage comes from the ability of supply chain partners to coordinate and integrate strategies aimed at satisfying the ultimate customers of the supply chain at a relatively low total cost (Cohen & Roussel, 2005). Supply chains capable of implementing and executing an integrated and coordinated marketing strategy at the supply chain level focused on the ultimate customers of the supply chain will gain competitive advantage at the supply chain level (Min & Mentzer, 2000). Such competitive advantage must at some point, however, result in improved organizational performance for each of the partners within the supply chain. Manufacturing managers are ultimately held directly accountable for the performance of their organizations, not the supply chains in which their organizations participate. Why then should manufacturing managers concern themselves with making decisions that may support the supply chain but, at least in the short-run, do not seem to directly affect the performance of their organizations? As Kline, Raj, and Straub (2007) argue, decision makers must first do what's best for the supply chain with such supply chain focused decisions ultimately leading to improved organizational performance. Their focus must, therefore, expand from a dyadic focus on relationships with direct suppliers and customers to one that embraces the entire supply chain (Pathak, Day, Nair, Sawaya, & Krystal, 2007). We propose a marketing strategy alignment model with marketing strategy alignment as antecedent to supply chain performance and supply chain performance as antecedent to organizational performance. The model is displayed in Fig. 1. It should be noted that the arrows linking the constructs within the structural model are not intended to imply causality but a dependence ordering of the relationships among the constructs (Shah & Goldstein, 2006). Please note that, within the context of the theorized model, direct links from alignment to financial performance and marketing performance are not included. This is because marketing strategy alignment is a supply chain level phenomenon that is expected to directly affect performance at the supply chain level rather than directly affect organization level performance. Chopra and Meindl (2004) argue that supply chain performance is enhanced when an ‘inter-organizational, inter-functional’ approach is adopted by all supply chain partners. Strategies that serve to strengthen the competitive position of the supply chain directly enhance supply chain performance, which will, in time, positively impact performance at the organization level for each of the supply chain partners (Meredith & Shafer, 2002; Rosenzweig, Roth, & Dean, 2003; Whitten et al., 2012). While alignment of marketing strategies throughout the supply chain should affect organizational performance, the effect is not direct. Instead, the effect of marketing strategy alignment on organizational performance is mediated through supply chain performance. Marketing managers should concern themselves with strengthening the overall supply chain before improvements in the financial and marketing performance of the organization can be expected. Marketing strategy alignment is theorized as indirectly affecting organizational performance through supply chain performance. 2.1. Theoretical foundation Min and Mentzer (2000) argue that adoption of a market orientation at the supply chain level is pivotal to the overall success of the supply chain. A market orientation at the supply chain level depends upon the partnering firms' abilities to develop inter-firm relationships that facilitate information exchange and communication related to the changing demands of the ultimate customers of the supply chain. Relational exchange theory (Griffith, Harvey, & Lusch, 2006; Kaufman & Stern, 1988; Macneil, 1980; Min & Mentzer, 2000) and

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Financial Performance

H3: (+) Marketing Strategy Alignment

H1: (+)

Supply Chain Performance

H4: (+)

H2: (+)

Marketing Performance

Fig. 1. Theorized marketing strategy alignment model with hypotheses.

the customer focused view of the firm (Kohli & Jaworski, 1990), therefore, serve as the theoretical underpinnings of this study. To satisfy the ultimate customers of the supply chain, the partnering firms must adopt and coordinate a market orientation at the supply chain level and execute that market orientation through strong, long-term relationships. According to Keith, Lee, and Lee (2004, p. 7), “relational exchange is characterized by extensive communications, commitment, and a long-term orientation.” Supply chain partners must develop marketing strategies that focus on the needs of the ultimate customers of the supply chain and align those strategies effectively throughout the supply chain. Such alignment requires establishing a set of norms (Macneil, 1980) along the supply chain related to the integration and coordination of marketing strategies and activities (Min & Mentzer, 2000) and requires information exchange that facilitates response to changes in the demands of ultimate customers (Green, Whitten, & Inman, 2007). In this study, relational exchange theory serves as the basis for the integration and coordination of marketing strategies and processes throughout the supply chain. Marketing strategies based on a market orientation may be either market driven or market driving (Jaworski, Kohli, & Sahay, 2000). While the focus in each case is on customer satisfaction, the market driven approach requires that market participants react to changes in customer demand, as compared to the driving markets approach in which markets take a more proactive approach to shaping changes in customer demand (Jaworski et al., 2000). Jaworski et al. (2000, p. 47) argue that markets may be driven “jointly by several organizations.” Supply chain partners work together to develop and implement an integrated and coordinated marketing strategy (relational exchange theory) that satisfies the changing demands of ultimate customers whether the changes are derived directly from the customers or influenced by the supply chain level marketing strategy (customer focused view). 2.2. Marketing strategy alignment Marketing strategy alignment is defined as the development and implementation of a supply chain level marketing strategy by supply chain partners for the purpose of providing the highest total value to the supply chain's ultimate customers (Cavinato, 1992; Min & Mentzer, 2000; Natarajan & Weinrauch, 1990). Successful marketing strategy alignment requires that marketing representatives of the organization collaborate with supply chain partners to: 1) plan and execute the conception of new products and services for ultimate customers, 2) plan and execute pricing, promotion, and distribution strategies for the sale of products and services to ultimate customers,

3) develop integrated processes that create value for ultimate customers, and 4) develop integrated processes that communicate the value developed to ultimate customers (Chen & Paulraj, 2004; Ho et al., 2002; Keefe, 2008). Marketing strategy alignment is relatively difficult to achieve because it is difficult to determine what the ultimate customer of the supply chain values and to effectively communicate changing customer demands to all supply chain partners. In summarizing the results of the 2003 PDMA Best Practices Study, Barczak, Griffin, and Kahn (2009) state that the “best firms” in terms of sales and profits, from new products, exhibit higher levels of intra-organizational collaboration and inter-organizational collaboration. These “best firms” have developed collaborative capabilities that position them relatively better than their competitors to identify and respond to changes in customer demands.

2.3. Supply chain performance For the purposes of this study, we take the extended view of the supply chain from “suppliers' suppliers to ultimate customer” that focuses on the ability to satisfy the ultimate customer in terms of both quality and cost (Chen & Paulraj, 2004; Ho et al., 2002; Hoyt & Faizul, 2000; Zelbst, Green, Baker, & Sower, 2010). Although organizational managers are ultimately held accountable for organizational performance, organizational success depends upon the performance of the supply chains in which the organization functions as a partner (Rosenzweig et al., 2003). Supply chain performance is dependent on the supply chain partners' ability to adapt to a dynamic environment (Vanderhaeghe & de Treville, 2003). Previous research has defined supply chain performance as the ability of the supply chain to 1) deliver quality products and services in precise quantities and at precise times, and 2) to minimize total cost of the products and services to the ultimate customers of the supply chain (Green & Inman, 2005).

2.4. Organizational performance Measures of both the financial and marketing performance of organizations are incorporated in this study. Financial performance focuses on the organization's profitability and ability to generate returns on investment and sales as compared to the industry average (Green & Inman, 2005). Marketing performance focuses on the organization's ability to generate sales as compared to the industry average (Green & Inman, 2005).

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2.5. Hypotheses 2.5.1. Marketing strategy alignment and supply chain performance Satisfaction of the ultimate customers of a supply chain requires that supply chain partners integrate and coordinate marketing strategies from end to end throughout the full extension of the supply chain. Marketing strategy alignment requires that supply chain partners align marketing strategies to enhance the supply chain's capabilities to deliver zero-defect products, precisely on-time, and in the precise quantities desired by ultimate customers of the supply chain. Further, marketing strategy alignment should enhance the supply chain's capabilities to deliver value-added services, to eliminate late, damaged, or incomplete orders, and to quickly solve customer problems. These capabilities improve the supply chain's ability to satisfy final customers at a relatively low total cost. Supply chain marketers work with other supply chain partners to conceive of new products and services and to execute integrated pricing, promotion, and distribution strategies that build value for and communicate value to ultimate customers. Such compatible marketing strategies should improve the performance of the overall supply chain. Barczak et al. (2009) report the results of a survey of practitioner members of the Product Development and Management Association, finding that best firms in terms of sales and profits from new product successes exhibit the ability to effectively collaborate with supply chain partners to satisfy ultimate customers. By definition, supply chain management is the integration and coordination of business processes throughout the supply chain. Supply chain performance depends upon the ability of the supply chain partners to align strategies, because, if the interests of a single firm in the supply chain are not aligned with its supply chain partners, the supply chain's performance cannot be maximized (Lee, 2004). H1. Marketing strategy alignment positively and directly affects supply chain performance. 2.5.2. Supply chain performance and organizational performance Managers are charged with and held accountable for improving the performance of the organizational entity for which they are directly responsible. Within a supply chain context, however, organizational managers should adopt an external focus and consider the impact of organizational strategies on supply chain partners. Attempts to directly optimize organizational performance may prove to have a detrimental impact on overall supply chain performance, thus damaging the competitive advantage of the chain (Chopra & Meindl, 2004; Meredith & Shafer, 2002). Chopra and Meindl (2004) argue that supply chain performance is optimized only when an ‘inter-organizational, inter-functional’ strategic approach is adopted by all partners operating within the supply chain. Optimization at the supply chain level maximizes the supply chain surplus available for sharing by all supply chain partners. Strategies that strengthen the competitive position of the supply chain serve to directly enhance supply chain performance, which will, in time, positively influence performance at the organizational level for each supply chain partner. D'Avanzo, von Lewinski, and Van Wassenhove (2003) investigated the link between supply chain and financial performance and found a statistical correlation between companies' financial success and the depth and sophistication of their supply chains. Bowersox, Closs, Stank, and Keller (2000) surveyed 306 senior North American logistics executives and concluded that cuttingedge supply chain practices result in improved financial performance for the organization. Green, Whitten, and Inman (2009) surveyed manufacturers and found that supply chain productivity, a construct similar to supply chain performance, positively impacts organizational performance. H2. Supply chain performance positively and directly affects marketing performance of the organization.

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H3. Supply chain performance positively and directly affects financial performance of the organization. 2.5.3. Marketing performance and financial performance Managers work to improve marketing performance in terms of sales and market share growth. Such marketing-related growth should impact financial performance through improved revenue numbers. Increased market share enhances sales revenues resulting in improved profitability and return on investment. Greater market share may also lead to economies of scale that result in a reduction of the average cost per unit sold, thereby enhancing profitability. Anderson, Fornell, and Lehmann (1994) found that marketing performance, as measured by customer satisfaction, positively impacts financial performance, as measured by return on investment. Schramm-Klein and Morschett (2006, p. 283), in their study of retailers, hypothesized that “marketing performance has a positive effect on company performance” and found that sales performance positively influenced financial performance. Green, Whitten, and Inman (2008) surveyed plant and operations managers working for large U.S. manufacturers and found a strong positive relationship between the marketing performance of the organization and the financial performance of the organization. MartinezLorente, Dewhurst, and Gallego-Rodriguez (2000) surveyed industrial companies with factories in Spain and found that market share growth and operational profits are positively related. H4. Marketing performance of the organization positively and directly affects financial performance of the organization. 3. Methodology 3.1. Construct measurement The marketing strategy alignment performance model (Fig. 1) displays relationships among four constructs: marketing strategy alignment, supply chain performance, marketing performance of the organization, and financial performance of the organization. The marketing strategy alignment scale is newly developed. The supply chain performance scale has been previously used by Zelbst et al. (2010). The financial performance scale was originally developed and assessed by Claycomb, Dröge, and Germain (1999), and the marketing performance scale was developed and assessed by Green and Inman (2005). Both the financial and marketing performance scales were subsequently used by Inman, Sale, Green, and Whitten (2011). Taking direction from Germain, Dröge, and Daugherty (1994), the control variable organization size is measured by the natural logarithm of the number of employees. The items in the marketing strategy alignment measurement scale were developed based on a thorough review of the related literature; the scale was pretested as recommended by Churchill (1979). The pre-test sample was too small to allow purification as per Churchill's paradigm. The results of a full assessment of the scales validity and reliability are described in Section 4.1. The items in the marketing strategy alignment measurement scale are based upon the necessity to align, integrate, and coordinate marketing processes (Ho et al., 2002; Min & Mentzer, 2000; Natarajan & Weinrauch, 1990) and the 1985, 2004, and 2007 definitions of marketing from the American Marketing Association. The marketing strategy alignment scale is designed to elicit responses from managers concerning their perceptions of the extent to which their firms align marketing strategies with supply chain partners. Items in the supply chain performance measurement scale focus on the ability of the supply chain to 1) deliver quality products and services in precise quantities and at precise times, and 2) to minimize total cost of the products and services to the ultimate customers of the supply chain (Zelbst et al., 2010). This specific scale was selected because it attempts to capture performance of the fully extended supply chain (suppliers' suppliers forward to ultimate customers), rather

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than the more constrained view of the supply chain including only the focal organization with first tier suppliers and immediate customers. Items in the financial performance scale focus on the organization's average return on investment, average profit, and average return on sales as compared to the industry average (Claycomb et al., 1999). Items in the marketing performance scale focus on the organization's average market share growth, average sales volume growth, and average sales (in dollars) growth as compared to the industry average (Green & Inman, 2005). These scales were selected because they measure the marketing and financial performance at the organization level. To determine if the overall survey instrument and the specific measurement items contained in the instrument are reasonable and realistic, a pre-test was conducted as recommended by Mentzer and Flint (1997). One hundred supply chain management professionals were identified in the Manufacturer's News, Inc. database. Using a two wave mailing methodology, the supply chain management professionals were asked to complete a supply chain performance survey that included the study scales. Twenty-one of the identified professionals responded. Because the pre-test included only 21 respondents, formal statistical analysis was not possible. It was possible, however, to determine if the survey instrument was generally effective and if any of the specific items were problematic. The item completion rate for the pre-test was 99.4% indicating that respondents were relatively comfortable with the survey instrument overall and the measurement items specifically. This pre-test approach is similar to the one adopted by Ahire, Golhar, and Waller (1996) where they initially surveyed 100 plants with representatives from 20 responding. All scale items are displayed in Table 1. 3.2. Data collection process All respondents are APICS members representing a broad array of manufacturing, oil and gas, and logistics firms. The vast majority of the respondents are plant and operations managers, supply chain managers, and logistics managers. The APICS group was identified as group representing manufacturing managers with knowledge of the supply chain management efforts of their organizations. This group was targeted because we believe they are familiar with concepts related to supply chain management and the supply chain management initiatives of their organizations. The data collected represent the perceptions of the respondents. Because this is one of the first studies to focus on the effect of marketing strategy alignment across the supply chain on supply chain and organizational performance, it must be considered somewhat exploratory, thereby providing preliminary results. Care must, therefore, be taken when generalizing beyond the sample and the population it represents (Mentzer & Flint, 1997). Data were collected using an e-mail, Internet-based methodology from a sample of 117 managers with knowledge of their organizations supply chain activities. The survey instrument was developed by the authors and the data collection process was administered in three waves by APICS. The successive wave approach was used in an attempt to increase the response rate and to facilitate assessment of non-response bias as recommended by Lambert and Harrington (1990). A total of 1527 email messages were sent to APICS members. One hundred five messages were returned as undeliverable, resulting in 1482 messages delivered to the recipients. Of those, 328 (23%) of the messages were opened. One hundred seventeen recipients further completed the instrument. Thus, 8.2% of the 1422 who were sent the email message responded, while 35.7% of those opening the message responded. Respondents have been in their current positions an average of 4.82 years and work for organizations with an average of 4297 employees and average annual revenues of $18.3 billion. Respondents worked for a broad array of manufacturing, oil and gas, and logistics

Table 1 Measurement scales (* indicates items removed during assessment process). Marketing strategy alignment Please indicate the extent to which you agree with each statement (1 = strongly disagree, 7 = strongly agree). 1. *This organization and its supply chain partners have compatible marketing philosophies and work together to satisfy ultimate customers at a profit. 2. The marketing representatives of this organization work with supply chain partners to plan and execute the conception of new products and services for the ultimate customers of the supply chain. 3. The marketing representatives of this organization work with supply chain partners to plan and execute a pricing strategy for the sale of products and services to the ultimate customers of the supply chain. 4. The marketing representatives of this organization work with supply chain partners to plan and execute a promotion strategy for the sale of products and services to the ultimate customers of the supply chain. 5. The marketing representatives of this organization work with supply chain partners to plan and execute a distribution strategy for the sale of products and services to the ultimate customers of the supply chain. 6. The marketing representatives of this organization collaborate with supply chain partners to develop integrated processes that create value for the ultimate customers of the supply chain. 7. The marketing representatives of this organization collaborate with supply chain partners to develop integrated processes that communicate the value developed for the ultimate customers of the supply chain to those customers. 8. *The marketing representatives of this organization collaborate with supply chain partners to develop integrated processes that deliver promised value to the ultimate customers of the supply chain. Supply chain performance Please indicate the extent to which you agree with each statement as the statement relates to your organization's primary supply chain (1 = strongly disagree, 7 = strongly agree). 1. This organization's primary supply chain has the ability to deliver zero-defect products to final customers. 2. This organization's primary supply chain has the ability to deliver value-added services to final customers. 3. This organization's primary supply chain has the ability to eliminate late, damaged and incomplete orders to final customers. 4. This organization's primary supply chain has the ability to quickly respond to and solve problems of the final customers. 5. *This organization's primary supply chain has the ability to deliver products precisely on-time to final customers. 6. This organization's primary supply chain has the ability to deliver precise quantities to final customers. 7. This organization's primary supply chain has the ability to deliver shipments of variable size on a frequent basis to final customers. 8. This organization's primary supply chain has the ability to deliver small lot sizes and shipping case sizes to final customers. 9. This organization's primary supply chain has the ability to minimize total product cost to final customers. 10. This organization's primary supply chain has the ability to minimize all types of waste throughout the supply chain. 11. This organization's primary supply chain has the ability to minimize channel safety stock throughout the supply chain. Organizational performance Please rate your organization's performance in each of the following areas as compared to the industry average (1 = well below industry average, 7 = well above industry average). Financial performance 1. Average return on investment. 2. Average profit. 3. *Profit growth. 4. Average return on sales. Marketing performance 5. Average market share growth. 6. Average sales volume growth. 7. Average sales (in dollars) growth.

firms. Thirty-three percent of the respondents are plant and operations managers, 22% are logistics managers, 12.4% are supply chain managers, 8% are purchasing managers, and 7.6% are planners and project managers. The remaining 17% hold various other management positions, such as general manager, operational excellence manager, and senior account executive. There is concern that managers in the different categories may not have the same knowledge of supply chain activities. Statistical

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comparisons across the general categories of managers (plant and operations managers, logistics managers, supply chain managers, purchasing managers, planners/project managers, and other managers) revealed no significant differences in the category means for any of the measurement scales items. This lack of significant differences suggests that the respondent, irrespective of their positions within the organizations, generally have the same knowledge of supply chain activities. To assess for non-response bias the means of the demographic variables, supply chain marketing, supply chain performance, and organizational performance items were compared across the three waves using ANOVA. No significant differences in means for the three waves were identified. Non-respondents have been found to resemble late respondents (Armstrong & Overton, 1977). This finding of general equality across the means for the three successive waves indicates that non-response bias does not negatively impact the data set. Item completion rate can be used to measure survey effectiveness and is defined as the proportion of survey items answered as compared to the total number of survey items (Klassen & Jacobs, 2001). The item completion rate is relatively high at 99%. Since one of the main reasons that respondents leave items blank is that they do not understand the meaning of the items, this high completion rate indicates that respondents were comfortable enough with the meanings underlying the items to respond. 3.3. Common method variance assessment When data for the independent and dependent variables are collected from single informants, common method bias may lead to inflated estimates of the relationships between the variables (Podsakoff & Organ, 1986). Podsakof, MacKenzie, Lee, and Podsakoff (2003) recommend precautions that can be taken to reduce the potential for common method bias when constructing a survey instrument. Based on this recommend care was taken to: 1) incorporate scale items that are simple and unambiguous, 2) format the survey such that scales representing dependent constructs appeared before those representing independent constructs (financial performance appears before marketing performance, marketing performance appears before supply chain performance, and supply chain performance appears before marketing strategy alignment), 3) separate the marketing strategy alignment scale from the supply chain performance scale and separate the supply chain performance scale from the marketing performance scale by other scales not related to this study, 4) use various instruction sets and anchor combinations for the study scales, and 5) ensure respondent anonymity. Although common method variance can be of concern in samesource, cross-sectional data, there is no current consensus that it necessarily exists at a biasing level in data (Richardson, Simmering, & Sturman, 2009). Sharma, Yetton, and Crawford (2009) argue that common method bias cannot be evaluated within single studies but must be evaluated using a meta-analysis methodology. Richardson et al. (2009) recommend use of the CFA marker technique to determine if common method variance is present in the data. This method requires that a measurement scale for a marker construct be included in the survey. A marker construct is theoretically unrelated to the study constructs. Unfortunately, no such scale was included in the survey thus precluding assessment of common method bias using the marker technique. We assess the impact of common method variance using three post hoc approaches. First, Harman's one-factor test was used post hoc to examine the extent of the potential bias (Podsakoff & Organ, 1986). As prescribed by Harman's test, all variables were entered into a principal components factor analysis. Results of the factor analysis identify four factors combining to account for 73% of the total variance. The first factor accounts for only 45% of the total variance. With a varimax rotation, the scale items loaded on the four factors as anticipated

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with the supply chain marketing, supply chain performance, marketing performance, and financial performance items loading on separate factors. As an additional test for common method bias, a single factor confirmatory factor analysis was also completed (Mossholder, Bennett, Kemery, & Wesolowski, 1998). This analysis with all items loading on one factor does not fit the data well with a relative chi-square value of 9.70, an NFI of .758, NNFI of .767, a CFI of .785, an IFI of .785, a GFI of .333, an RSMEA of .274, and an SRMR of .178. Thus, common method bias does not negatively impact the dataset. Finally, when a marker scale has not been included in the data collection, Malhotra, Patil, and Kim (2007) recommend taking an approach described by Lindell and Whitney (2001) in which the second smallest correlation between the study variables is adopted as a conservative estimate of common method variation. Malhotra et al. (2007) note that use of the second smallest rather than smallest correlation overestimates the variance. Following this post-hoc approach, the second smallest correlation is .304 between supply chain performance and financial performance. The other three correlations representing associations in the structural model are: .549 for marketing strategy alignment and supply chain performance, .555 for marketing performance and financial performance, and .478 for supply chain performance and marketing performance. Substituting these correlations into the formulas provided by Malhotra et al. (2007), the computed z-score for the marketing strategy alignment and supply chain performance correlation of .549 is 4.00. For the supply chain performance and marketing performance correlation of .478, the computed z-score is 2.74. For the marketing performance and financial performance correlation of .555, the computed z-score is 4.15. These computed z-scores correspond with significance at the .01 level. Considering that the second smallest correlation is a conservative proxy for common method variance, this approach indicates that the correlations between marketing strategy alignment and supply chain performance, supply chain performance and marketing performance, and marketing performance and financial performance are not artifacts of common method variance. Based upon the results of Harman's one-factor test (Podsakoff & Organ, 1986), the single factor confirmatory factor analysis (Mossholder et al., 1998), and the Malhotra et al. (2007) post-hoc common method variance estimation approach problems associated with common method bias are not considered significant (Podsakoff & Organ, 1986). 3.4. Statistical analysis All measurement scales are assessed for reliability and validity individually (Garver & Mentzer, 1999) and within a measurement model context (Koufteros, 1999). Non-response bias and common method bias are assessed. Summary variables are computed and descriptive statistics and correlations computed. The theorized model is assessed following a structural equation modeling methodology. We assess the measurement and structural models using item level data with LISREL software to obtain the important model fit information and information necessary to evaluate the individual hypotheses. This two-stage approach of first evaluating the measurement model and then the structural model is recommended by Koufteros (1999). This approach allows further assessment of the measurement scales within the context of the full model prior to assessment of the structural model. Hair, Black, Babin, Anderson, and Tatham (2006) indicate that structural equation modeling analysis using the maximum likelihood estimation procedure has been found to provide valid results with sample sizes from 100 to 150. They further argue that samples sizes in the 100 to 150 range are sufficient if structural model under consideration contains five or fewer constructs, each with three or more measurement items, and item communalities that are .6 or higher. In this case, four constructs are embedded in the theoretical model (see Fig. 1), each of the measurement scales for the constructs

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contains three or more items (see Table 3), and all item communalities are greater than .6 (see Table 3).

Table 3 Measurement model results. Chi-square ratio = 2.123; SRMR = .063; RMSEA = .098; NFI = .906; NNFI = .928; CFI = .937; IFI = .937. Construct/measures

4. Results Measurement scales are assessed for validity and reliability and the measurement model is assessed for good fit using item level data. Descriptive statistics and correlations based on summary variables are presented. The structural model is then assessed for fit using itemlevel data and the results related to the study hypotheses are then presented. Because this is an early study based on a relatively small, diverse sample, the findings of the study should be considered preliminary. 4.1. Measurement scale assessment Measurement scales must exhibit convergent, discriminant, and predictive validity and reliability (Ahire et al., 1996; Garver & Mentzer, 1999), and the measurement model must fit the data relatively well (Koufteros, 1999). The statistical assessment indicated that items MSA1 and MSA8 from the marketing strategy alignment scale, items SCP1 and SCP5 from the supply chain performance scale, and item FP3 from the financial performance scale be considered as candidates for removal to improve measurement model fit. Items MSA1 and MSA8 allude to both alignment and performance and were, therefore, removed. Item SCP1 was determined to be an important theoretical component of the supply chain performance scale in that it focuses on the delivery of quality products and was therefore not removed. Item SCP5 was determined to be closely related to SCP6 with both focusing on delivery precision, thereby warranting removal. Item FP3 “profit growth” was removed because it is highly correlated with and replicates item FP2 “average profit.” Statistical results of the measurement scale assessment and measurement model assessment are presented in Tables 2 and 3. 4.1.1. Descriptive statistics and correlations Summary values for the study variables were computed by averaging across the items in the scales for the purpose of reporting descriptive statistics and correlations. Descriptive statistics and the correlation matrix for the summary variables are presented in Table 4. All correlation coefficients are positive and significant at the .01 level. 4.1.2. Convergent validity Ahire et al. (1996) recommend assessing convergent validity using the normed-fit index (NFI) coefficient with values greater

Standardized coefficients

Marketing strategy alignment MSA2 MSA3 MSA4 MSA5 MSA6 MSA7 Supply chain performance SCP1 SCP2 SCP3 SCP4 SCP6 SCP7 SCP8 SCP9 SCP10 SCP11 Financial performance FP1 FP2 FP4 Marketing performance MP1 MP2 MP3 Employees NLEMP

t-values

.88 .94 .94 .90 .94 .94

12.06 13.40 13.49 12.48 13.42 13.42

.67 .72 .83 .81 .86 .77 .73 .72 .70 .69

8.04 8.73 10.83 10.48 11.49 9.62 9.03 8.72 8.54 8.30

.91 .90 .85

12.49 12.24 11.18

.85 .93 .92

11.13 12.91 12.78

1.00

15.23

than 0.90 indicating strong validity. Garver and Mentzer (1999) recommend reviewing the magnitude of the parameter estimates for the individual measurement items to assess convergent validity. A strong condition of validity is indicated when the estimates are statistically significant and greater than or equal to .70. NFI values for the marketing strategy alignment (.944) and supply chain performance (.922) exceed the .90 threshold. The marketing performance scale contains only three items precluding computation of NFI for the scale. All parameter estimates for the marketing strategy alignment scale are significant with values equal to or greater than .70. All parameter estimates for the supply chain performance scale are significant and all but two (SCP1, .67; SCP11, .69) are greater than or equal to .70. Parameter estimates for each of the individual items in the financial and marketing performance scales are all significant and exceed the .70 threshold, with values of .85 or greater. This evidence indicates that all study variables exhibit sufficient convergent validity.

Table 2 Scale assessment results. Dimensionality and convergent validity assessment results Scale

Relative χ2

SRMR

RMSEA

NNFI

CFI

NFI

GFI

Marketing strategy alignment Supply chain performance Financial performance Marketing performance

2.065

.063

.096

.936

.944

.944

.761

3.222

.060

.138

.924

.941

.922

.837

* *

* *

* *

* *

* *

* *

* *

Reliability assessment results Scale

Cronbach's alpha

Construct reliability

Variance extracted

Marketing strategy alignment Supply chain performance Financial performance Marketing performance

.96

.97

.85

.92

.93

.57

.90 .91

.92 .93

.79 .81

⁎Financial performance and Marketing performance are 3-item scales precluding CFA.

Table 4 Descriptive statistics and correlations for summary variables. A. Descriptive statistics Variables

Mean

Std. deviation

Skewness

Kurtosis

Marketing strategy alignment (MSA) Supply chain performance (SCP) Financial performance (FP) Marketing performance (MP)

3.8167

1.54418

−.139

−.856

4.9424 4.9801 5.0798

1.09490 1.08657 1.24695

−.887 −.433 −.363

1.270 .180 −.495

B. Correlations Variables

MSA

SCP

MP

FP

Marketing strategy alignment (MSA) Supply chain performance (SCP) Financial performance (FP) Marketing performance (MP)

1.00 .540⁎⁎ .202⁎ .385⁎⁎

1.00 .324⁎⁎ .478⁎⁎

1.00 .555⁎⁎

1.00

⁎⁎ Correlation is significant at the 0.01 level (2-tailed). ⁎ Correlation is significant at the 0.05 level (2-tailed).

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4.1.3. Discriminant validity Discriminant validity was assessed using a chi-square difference test for each pair of scales under consideration, with a statistically significant difference in chi-squares indicating validity (Ahire et al., 1996; Garver & Mentzer, 1999; Gerbing & Anderson, 1988). All possible pairs of the study scales were subjected to chi-square difference tests with each pairing producing a statistically significant difference indicating that the scales exhibit sufficient discriminant validity. 4.1.4. Predictive validity Predictive validity was assessed by testing whether the scales of interest correlate with other measures as expected (Ahire et al., 1996; Garver & Mentzer, 1999). Taking direction from Germain et al. (1994), predictive validity is assessed by relating study variables with other variables for which there are no study hypotheses. The following additional data were collected: 1) degree to which the competitive focus of the organization is aligned with supply chain partners, 2) how well the overall supply chain performs, and 3) how well the organization performs. Marketing strategy alignment should be positively correlated with the degree of competitive focus alignment between organization and supply chain. The correlation coefficient for the relationship is .51 and is significant at the .01 level. Supply chain performance should be positively correlated with how well the overall supply chain performs. The correlation coefficient for the relationship is .36 and is significant at the .01 level. The financial performance and marketing performance variables should be positively correlated with how well the organization performs. The financial performance correlation is .55 and is significant at the .01 level. The correlation with marketing performance is .36 and is significant at the .01 level. The study variables correlate as expected with the check variables indicating sufficient predictive validity. 4.1.5. Reliability Garver and Mentzer (1999) recommend computing Cronbach's alpha, construct variability, and variance extracted values to assess scale reliability, with alpha and construct variability values greater than or equal to 0.70 and variance extracted values greater than or equal to .50 indicating sufficient reliability. Alpha, construct variability, and variance extracted values for all study measurement scales are displayed in Table 2. All reliability measures exceed the values

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recommended by Garver and Mentzer (1999). Thus, the study scales are sufficiently reliable. 4.1.6. Measurement model assessment Koufteros (1999) recommends that the individual scales be incorporated together in a measurement model and that this model be subjected to an additional confirmatory factor analysis. The results of this confirmatory assessment of the measurement model are displayed in Table 3. Relative chi-square values of less than 2.00 and NNFI and CFI values greater than .90 indicate reasonable fit (Garver & Mentzer, 1999; Koufteros, 1999). Results of the analysis indicate that the measurement model fits the data relatively well with an NNFI of .928, and a CFI of .937. The relative chi-square of 2.12 is slightly higher that the recommended value of 2.00., but is well below the 3.00 level recommended by Kline (1998). The individual measurement scales are considered sufficiently reliable and valid and the fit of the measurement model is considered sufficient to support further analysis. There is some concern that the marketing strategy alignment scale is newly developed and assessment for validity and reliability is based on a single sample. This is due to the lack of a sufficient number of responses in the pre-test sample to support statistical assessment for validity and reliability. While incorporating a new scale within a structural model is not the approach recommended by Churchill (1979), such a method has gained recent acceptance (Inman et al., 2011; Whitten et al., 2012) when the new scale is determined to be sufficiently valid and reliable as is the case for the marketing strategy alignment scale. 4.2. Structural equation modeling results Fig. 2 illustrates the model with the structural equation modeling results. It should be noted that, due to a concern that the impact of organization size in terms of number of employees should be controlled, the natural log of the number of employees was incorporated into the assessment of the structural model. The relative chi-square (chi-square/degrees of freedom) value of 2.03 is slightly higher than the 2.00 level recommended by Koufteros (1999) but less than the 3.00 maximum recommended by Kline (1998). The NNFI (.928) and CFI (.937) exceed the .90 level recommended by Koufteros (1999) and Garver and Mentzer (1999).

Financial Performance

.09 (.92) Marketing Strategy Alignment

.61 (5.75)

Supply Chain Performance

.54 (4.97)

.54 (5.10) Control for Size: NLEMP MSA .20 (2.18) NLEMP SCP -.00 (-0.05) NLEMP OPF -.01 (-.15) NLEMP OPM .11 (1.34)

Marketing Performance

Chi-square ratio = 2.027; SRMR = .064; RMSEA = .094; NFI = .903; NNFI = .928; CFI = .937; IFI = .937 Fig. 2. Marketing strategy alignment model with standardized coefficients and (t-values).

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Three of the four study hypotheses were supported by the standardized estimates and associated t-values. The relationship between marketing strategy alignment and supply chain performance (H1) is positive and significant at the .01 level as hypothesized with an estimate of .61 and t-value of 5.75. The estimate of .57 for the relationship between supply chain performance and marketing performance of the organization (H2) is positive and significant at the .01 level as hypothesized with an associated t-value of 5.10. Although hypothesized as positive, the relationship between supply chain performance and financial performance of the organization (H3) is non-significant with an estimate of .09 and t-value of .92. The relationship between marketing performance of the organization and financial performance of the organization (H4) is positive and significant at the .01 level as hypothesized with an estimate of .54 and an associated t-value of 4.97. Within the context of the structural model, it appears that the effect of marketing strategy alignment on financial and marketing performance of the organization is fully mediated by supply chain performance. Mediation is indicated if the paths from the independent variable (marketing strategy alignment) to the outcome variables (financial performance of the organization and marketing performance of the organization) become non-significant after introduction of the mediator into the model (Baron & Kenny, 1986). It was necessary, therefore, to establish significant direct relationships between marketing strategy alignment and financial and marketing performance. Prior to the introduction of supply chain performance, the direct relationships between marketing strategy alignment and financial performance of the organization has a standardized estimate of .24 with a t-value of 2.52 and between marketing strategy alignment and marketing performance of the organization has a standardized estimate of .43 with a tvalue of 4.48. The direct links are both positive and significant prior to the introduction of supply chain performance as a mediator. Following the introduction of the mediator, the direct relationships become nonsignificant. The claim that supply chain performance fully mediates the effect of marketing strategy alignment on organizational performance is supported. 5. Conclusions Marketing strategy alignment positively affects supply chain performance which positively influences the marketing performance of the organization, and improved marketing performance positively affects financial performance of the organization. Supply chain performance does not directly influence financial performance of the organization as expected, however. The effect of supply chain performance on financial performance is indirect through marketing performance. This indirect, rather than direct, effect on financial performance may be explained by the strong customer focus reflected in the supply chain performance construct and imbedded in the supply chain performance measurement scale. Supply chain performance is decidedly market focused leading to improved marketing performance. While organizations are in business to improve financial position, the ultimate customer of the supply chain must be satisfied before financial gains are realized. Financial success depends upon marketing success. Marketing strategy alignment indirectly affects organizational performance through supply chain performance. 5.1. Contributions of the study Lee (2004) theorized the importance of strategic alignment throughout supply chains and supported this theory with anecdotal evidence. This study provides empirical support for his general strategy alignment theory and specific support for the need to align marketing strategies throughout the supply chain to satisfy the ultimate customers of the supply chain. We theorize and empirically assess a marketing strategy alignment model that incorporates both supply chain

performance and organizational performance constructs. The findings support the efficacy of marketing strategy alignment. Organizations that work to align marketing strategy with supply chain partners to better satisfy the ultimate customers of the supply chain are likely to induce improved supply chain performance yielding improved organizational performance. The results emphasize the need for partners within a supply chain to integrate organization level marketing processes into a combined supply chain marketing strategy aimed at satisfying ultimate customers, thereby reinforcing the need to optimize at the supply chain level, rather than the organizational level. 5.2. Limitations and future research While we believe that the objectives of the study were accomplished, limitations of the study should be noted and recommendations for research efforts described. The measurement scales adopted for this study are based on the perceptions of the respondents. The response rate is relatively low with respondents from firms spread across very different industries. In addition, this is one of the first studies to assess the effect of marketing strategy alignment throughout the supply chain on supply chain and organizational performance. The study must, to a degree, be considered exploratory with preliminary results making a subsequent more solid empirical assessment necessary. All respondents are members of APICS representing manufacturing, oil and gas, and logistics firms and are primarily plant and operations managers, supply chain managers, and logistics managers. While we believe that this group has the requisite knowledge of the supply chain management efforts of their organizations, we recommend that generalization of the results beyond the sample and the population it represents be done with caution (Mentzer & Flint, 1997). Replications of this study using data collected from diverse samples are necessary to provide evidence of statistical generalizability as recommended by Mentzer and Flint (1997). Our development of the marketing strategy alignment scale did not include a large enough first sample to support a full assessment as Churchill (1979) recommends. The pilot study focused on supply chain managers working for large manufacturing companies across the United States. We were only able to identify 100 individuals with the specific “supply chain manager” job title. This small target group produced the small first sample. Time and cost constraints precluded collection of a second pilot sample. This pre-test approach is similar to the one adopted by Ahire et al. (1996) where they initially surveyed 100 plants with representatives from 20 responding. The marketing strategy alignment scale was subsequently fully assessed within the context of the primary study, however, and found to meet the recommended standards for unidimensionality, reliability, and validity. The study would, however, have been improved had the first sample supported a full assessment of the new scale. By its nature, supply chain performance is relatively difficult to measure. With the exception of the Zelbst et al. (2010) scale adopted for this study, supply chain performance scales identified in the literature measured satisfaction of immediate, rather than ultimate, customers. While measurement of satisfaction of the ultimate customer is appropriate, there is concern whether or not a single supply chain manager within an individual company can properly assess both organizational and supply chain performance. Both the marketing alignment and supply chain performance scales measure supply chain level constructs. Measurement of such supply chain level constructs is inherently difficult. This study used single sources with manufacturing organizations to collect both organizational and supply chain related data. These measurement scales are designed to assess the perceptions of managers related to the extent to which their firms have aligned marketing strategies with supply chain partners and the extent to which the ultimate customers of the supply chain are satisfied. An alternate approach requiring

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collection of data from multiple sources along supply chains is desirable. Such an approach is very difficult to implement logistically, however. Future research efforts building on this exploratory study and associated preliminary results should attempt to match supply chain managers from partnering organizations throughout supply chains. 5.3. Implications for practitioners Competitive advantage at the supply chain level depends upon the supply chain's ability to focus on and respond to changes in customer demands. Not only must the individual firms adopt a market orientation but the firms must build relationships with partners that focus the entire supply chain on satisfaction of the ultimate customer at a relatively low total supply chain cost. Based on the results presented in this study, we recommend that marketing managers working for the partnering firms within the supply chain collectively work to integrate and coordinate the marketing strategies of their individual firms to focus on the ultimate customers of the supply chain. In effect, we recommend that they work to develop a “supply chain marketing strategy.” Such a strategy will not directly yield improvements in the marketing and financial performance of the individual firms. Rather, the relationship between marketing strategy alignment and organization performance is mediated by supply chain performance. Marketing managers should “globalize” by focusing on decisions that improve the overall performance of the supply chain in this era of hypercompetition between supply chains. We have established the efficacy of developing a supply chain marketing strategy through a rigorous empirical investigation. Such a declaration belies the difficulty in actually establishing the relationships with supply chain partners necessary to successfully develop and implement such a strategy. The on-going process of strategy alignment is both complicated and complex. While value chains are sometimes simplistically illustrated as the sequential partnering of suppliers, manufacturers, intermediaries, and customers, value chains are more appropriately described as complex network of supply and demand chain partners (Rainbird, 2004a, 2004b). Rainbird (2004b) describes value chains as necessarily combining both supply and demand chains. Friction is created between the efficiency focus of the supply function and the effectiveness focus of the demand function (Rainbird, 2004b). Rainbird (2004b) specifically assigns the responsibility for reconciling these supply and demand issues to management. Lee (2004) provides important direction in terms of how manufacturers should go about creating alignment by recommending that supply chain partners share information, define and assign responsibilities, and align incentives. From a marketing perspective, supply chain partners should adopt a supply chain level market orientation focused on satisfying the changing demands of the ultimate customers of the supply chain. This requires that intelligence related to changes in the demands of the ultimate customers be generated and disseminated to all supply chain partners and that the partners respond to the intelligence collectively within the context of a “supply chain marketing strategy.” References Ahire, S. L., Golhar, D. Y., & Waller, M. A. (1996). Development and validation of TQM implementation constructs. Decision Sciences, 27(1), 23–56. Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. The Journal of Marketing, 58(3), 53–66. Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402. Barczak, G., Griffin, A., & Kahn, K. B. (2009). Trends and drivers of success in NPD practices: Results of the 2003 PDMA Best Practices Study. The Journal of Product Innovation Management, 26(3), 3–23. Baron, R., & Kenny, D. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.

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Kenneth W. Green, Jr. is the LeMay Professor of Technology at Southern Arkansas University. His research appears in the Journal of Operations Management, International Journal of Operations and Production Management, International Journal of Production Research, Industrial Marketing Management, International Journal of Human Resource Management, Supply Chain Management: An International Journal, Production Planning and Control, Industrial Management and Data Systems, Journal of Business and Industrial Marketing, Journal of Computer Information Systems, and Management Research Review.

Dwayne Whitten is an Associate Clinical Professor of Information Systems at Texas A&M University. His research appears in the Journal of Operations Management, Harvard Business Review, European Journal of Information Systems, Decision Sciences Journal, Journal of Strategic Information Systems, Communications of the AIS, Journal of Organizational and End User Computing, Journal of Computer Information Systems, Industrial Management and Data Systems, Journal of International Technology and Information Management, International Journal of Mobile Communications, International Journal of Electronic Healthcare, and International Journal of Human Resource Management.

R. Anthony Inman is the Ruston Building and Loan Professor of Management at Louisiana Tech University. His research appears in the Journal of Operations Management, Decision Sciences, Interfaces, International Journal of Production Research, International Journal of Operations and Production Management, Industrial Marketing Management, Production and Inventory Management Journal, International Journal of Service Industry Management, Production Planning and Control and International Journal of Quality and Reliability Management. He was the recipient of the Shingo Prize for Excellence in Manufacturing: Shingo Prize Research Award for 1993 and was ranked 17th nationally in “POM Research Productivity in U.S. Business Schools,” S.T. Young, B.C. Baird and M.E. Pullman, Journal of Operations Management, Volume 14 Number 1, March 1996, pp. 41–53.