Linking supply chain management superiority to multifaceted firm financial performance.
Existing research indicates that supply chain (SC) effectiveness can lead to increased firm financial performance (Craighead, Huh and Ketchen 2009). AMR Research (2010), a Boston-based research firm that conducts independent research on supply chains, has shown that organizations with superior supply chain performance outperform their competitors in earnings per share, return on assets and profit margins (Caruso 2004). When firms choose to manage their supply chains and focus on enhancing overall capabilities, the results have yielded increased performance because of enhanced business strategies and practices. Indeed, research indicates that firm financial performance can be increased due to effective supply chain management (SCM). Firms that have invested in improved IT-based SCM systems (Dehning, Richardson and Zmud 2007) became more capital efficient (Hartley-Urquhart 2006), became more customer and supplier oriented (Tan, Kannan and Handfield 1998; Tracey, Lim and Vonderembse 2005), implemented effective quality management practices (Kaynak and Hartley 2008; Lo, Yeung and Cheng 2009), improved logistics performance (Green, Whitten and Inman 2008; Joong-Kun Cho, Ozment and Sink 2008; Toyli, Hakkinen, Ojala and Naula 2008) and leveraged innovation, cost, and knowledge among members in the supply chain.
Even though existing research indicates that supply chain superiority can lead to an increase in firm financial performance, the results are puzzling. Current research studies each define firm performance in their own way. For example, firm performance has been defined as cost reduction, increase in revenues and higher prices (Kaynak and Hartley 2008), return on assets and Altman's Z (Craighead et al. 2009), profitability, productivity and growth (Toyli et al. 2008), and gross margins, return on sales, inventory turnover, market share, and reduction in general, sales and administrative expenses (Dehning et al. 2007). The most comprehensive definition was found in Kim (2009) in which firm performance was defined as market share growth, total cost reduction, return on investment, return on assets, financial liquidity, and net profit. This study builds on present research by investigating supply chain effectiveness and its relationship to a broader definition of firm financial performance indicators by including other financial variables such as maturing obligations and cost ratios.
In analyzing financial data, analysts use various devices to bring out the comparative and relative significance of the financial information presented. Among others, ratio analysis is a common device. Ratios can be classified into four major types: profitability ratios, activity ratios (also called turnover or efficiency ratios), liquidity ratios, and coverage ratios (also called leverage or capital structure ratios). Profitability ratios measure the degree of success or failure (in profits) of a given firm. Activity ratios measure how effectively the firm is using the assets it has invested in. Both liquidity ratios and coverage ratios provide a measure for leverage (credit risk), with liquidity ratios measuring the company's short-run ability to service (pay) its short-term debts (maturing obligations).
Current research also fails to comprehensively identify supply chain leader firms. For example, existing studies use self-report survey data from SCM professionals (Craighead et al. 2009), American Society for Quality members (Kaynak and Hartley 2008), a Lexis/Nexus and Factiva newswire search for firms that use IT-based SCM systems (Dehning et al. 2007), firms that are members of the Finnish Association of Logistics and the Federation of Finnish Enterprises (Toyli et al. 2008), and firms selected from Korea's listed and registered corporations and member firms from Japan's national logistics professional association (Kim 2009). Although these studies contribute to our understanding of SCM effectives and firm financial performance, they are not comprehensive in their analyses of financial performance and they do not identify firms as supply chain leaders. We investigate the robustness of the relationship between supply chain effectiveness and the overall financial performance of firms viewed as supply chain leaders by using AMR's supply chain top 25 list. Using AMR's list of supply chain leaders, we investigate the overall financial performance of these leader firms beyond the financial metrics used by AMR. It is important to note that our intent is not to dispute AMR's list of leader firms, but simply to use their list of companies to further analyze firm financial performance by assessing other internal firm performance indicators. We wish to determine if the AMR top 25 supply chain leaders will perform equally well on other efficiency based ratios beyond those used by current researchers and AMR.
We are also motivated to perform this research study on supply chain leader firms because we know that winning awards or being labeled "best" for strategic initiatives is not necessarily indicative of a firm's financial health. For example The Wallace Company, a 1990 Baldrige winner, filed for Chapter 11 bankruptcy in 1992 only a few years after winning the prestigious quality award. Other Baldrige winners such as Armstrong World Industries, Inc. and Dana Corporation, the parent company of two Baldrige award recipients--Spicer Driveshaft division and Dana Commercial Credit Corp.--also filed for bankruptcy within a relatively short period after having won the award.
Supply chain management and increased operational performance can be explained by the resource-based view (RBV) (Barney 1991) and resource advantage theory (R-A theory) (Hunt 2000). R-A theory argues that the value of a resource to a firm is based on its potential to yield competitive differentiation that ultimately enhances performance. The RBV suggests that firms can achieve sustainable competitive advantage through the acquisition and control over resources and capabilities as long as the resources are valuable, rare to come by, imperfectly mobile, not imitable by competitors and not substitutable (Barney 1991; Grant 1991). Barney 1991; Rungtusanatham, Salvador, Forza and Choi 2003; and Hunt and Davis 2012 argue that the tangible and intangible resources and capabilities created from the inter-firm relationships and knowledge creation gained from managing the supply chain are rare, valuable, not imitable by competitors, and not substitutable. Both R-A theory and RBV help explain how these bundles of resources and capabilities provide firms with a competitive advantage that translates into increased firm financial performance.
The aim of this study was to determine the overall financial health of supply chain leader firms and whether they demonstrate more financial health compared with nonsupply chain leader firms. Our findings will lend support to the linkage between supply chain superiority and firm performance making it more comprehensive and robust. Using select control firms from the Research Insight database, we match and compare overall firm financial performance of SC leader firms and that of non-SC leader firms using activity, liquidity, and cost ratios. The remaining sections of this note describe the relationship between supply chain effectiveness and firm performance, the process AMR uses to determine its Supply Chain Top 25, hypothesis development, the methodology and the results of our analysis.
SUPPLY CHAIN EFFECTIVENESS AND FIRM PERFORMANCE
To increase firm performance many firms have sought to be proactive and manage their supply chains. Supply chain management is defined as the systematic, strategic coordination of the traditional business functions within a particular company and across businesses within the supply chain, for the purposes of improving the long-term performance of the individual companies and the supply chain as a whole (Mentzer, DeWitt, Keebler, Min, Nix, Smith and Zacharia 2001, p. 18). Strategic improvements can occur upstream and/or downstream as products, services, capital, and information flow through the supply chain. Given the potential complexity and depth of a supply chain, when organizations seek to improve supply chain effectiveness there can be a broad range of changes which can be enacted across all relevant business functions (Chen and Paulraj 2004).
Early SCM efforts have focused on increasing efficiency and reducing cost. Efficiency, responsiveness, and reliability of supply chains are seen as key drivers of a firm's profitability (Radjou 2002; Kigore 2003). Ketchen, Rebarick, Rebarick, Huh and Meyer (2008) suggest that firms in search of the "best value supply chains" are focusing on the total value added to the customer. Hence, their supply chains must perform according to four competitive priorities: speed, cost, quality, and flexibility. Speed or cycle time is the time it takes to initiate and fulfill or complete the customer's needs. Quality refers to the reliability of the supply chain to consistently perform supply chain activities. Cost refers to a firm's ability to enhance value by reducing expenses or increasing customer benefits for the same cost. Flexibility refers to the supply chain's ability to respond to changes in customer needs.
Ketchen et al. (2008) point out that for firms to meet these competitive priorities, they must use strategic SCM that coordinates logistics management, relationship management, supply chain information systems, and strategic sourcing. It follows then that when firms successfully manage their supply chains and focus on the total value added to the customer, overall firm financial performance should increase.
Indeed, research has established a linkage between logistics management (Joong-Kun Cho et al. 2008; Toyli et al. 2008; Wallenburg 2009), trust-base relationship, and quality management (Kaynak and Hartley 2008; Lo et al. 2009), IT-based SCM systems (Vickery, Jayaram, Droge and Calantone 2003; Chae, Yen and Sheu 2005; Dehning et al. 2007) and strategic sourcing (Droge, Jayaram and Vickery 2004; Monczka, Trent and Handfield 2005; Kim 2009; Bustinza, Molina and Gutierrez-Gutierrez 2010; Liao, Hong and Rao 2010; Reuter, Foerstl, Hartmann and Blome 2010) supply chain practices and firm performance. As an example, a common supply chain practice is the implementation of IT-based SCM systems. These systems assist firms in coordinating and integrating the flow of materials, information, and finances by allowing transparency and enhanced communication among the supplier, manufacturer, wholesaler, retailer, and end consumer. In that sense, IT-based SCM systems contribute to the firm's profits by improving quality and cycle times and by reducing coordination cost and transaction risks (Vickery et al. 2003; Bush, Tiwana and Rai 2010). When firms invest in IT-based supply chain systems, research suggests that their efforts result in increased gross margins, inventory turnover, market share, return on sales and more (Denning et al. 2007).
AMR SUPPLY CHAIN TOP 25 RANKINGS
Since 2004, AMR, a Boston-based research firm, has published a list of companies which it believes are the 25 firms with the best operating supply chains for that year (AMR Research 2010). AMR indicates that its research is about leadership by stating the following on its website, "We research trends and technology in the global supply chain for our members because they are accountable to their customers, investors, and executive management for bringing innovation and leadership to operations. We publish 'The Supply Chain Top 25' each year to recognize the companies that take this leadership farthest" (AMR Research 2010, p. 1). For example, companies recently recognized include Wal-Mart, Dell, Nokia, and Johnson Controls. Although AMR's methodology has changed over the years (AMR Research 2010), to be considered for AMR's list each firm must make Fortune's Global 500 and Fortune 1000's annual ranking. It is from this list of companies that AMR selects its top 25. There is a requirement of a minimum of $10 Billion in revenue. The list is then pared down to just manufacturers, retailers, and distributors. Industries for which there are unavailable financial data are eliminated. In 2009, there was a list of 242 companies in the AMR data set (Friscia, O'Marah and Hoffman 2010).
AMR uses a composite score to determine their rankings. A weighted 60 percent of the total score is based on financial data, which represents past performance. The financial metrics used are weighted as 25 percent return on assets (previous year net income/previous year total assets-3 year weighted average), 25 percent inventory turnover (previous year cost of goods sold/previous year year-end inventory-1 year quarterly average), and 10 percent revenue growth (previous 2 years of revenue-3 year weighted average).
The remaining 40 percent of the total score is based on opinion from selected panel members. A weighted 20 percent is derived from 20 AMR research opinion voting panelists that consist of both industry and functional analysts. The remaining weighted 20 percent is derived from a peer opinion panel, which consists of supply chain professionals across manufacturing and retail businesses. Any supply chain professional working for a manufacturer or retailer is eligible to be on the panel, and only one panelist per company is accepted. Excluded from the panel are consultants, technology vendors, and people who are not working in supply chain roles.
It is important to note that AMR's ranking methodology is not without criticism. Some suggest that companies can be overlooked because the ranking methodology requires that a company must make Fortune's rankings and receive at least one point from the opinion panel to qualify for the top 25. Others have suggested that the top 25 methodology favors those industries that are closer to and more visible to the consumer, such as retail and electronics (Friscia et al. 2010), and others point out that a company's position in the ranking can be elevated solely by opinion versus performance variables (Hoffman and O'Marah 2009). Such criticisms suggest a weakness in AMR's ranking methodology and encourage us to be suspect about generalizing and blindingly accepting their results. However, regardless of their methodological flaws, our objective is to utilize their list to further determine the robustness of their results.
Supply chain interactions and linkages can be seen as a form of inter-firm relationships (Carter and Ellram 1994). Inter-firm relationships can create dynamic capabilities that are unique "resources" to a firm. These resources, both tangible and intangible can generate unique processes, routines, and special knowledge in supply chains (Teece, Pisano and Shuen 1997). Supply chain management functions, such as purchasing, can create inimitable partnerships that contain superior capabilities, access to global markets and other advantages resulting in a relational collaborative competence (Priem and Swink 2012). When these capabilities are built "organically" within the boundaries of a firm they can be used to gain competitive advantages (Barney 2012).
Both R-A theory and the RBV contribute to our understanding of SCM and firm performance (Hunt and Davis 2012; Priem and Swink 2012). R-A is a competition-based theory that suggests that each organization will have at least some unique resources that will constitute a comparative advantage that could lead to positions of competitive advantage and ultimately increased firm performance (Hunt and Davis 2008). In R-A theory, resources are defined as the "tangible and intangible entities available to the organization that enable it to produce efficiently and/or effectively a market offering that has value for some market segment" (Hunt and Davis 2008, p. 13). That is, it is only a resource if it enables a firm to produce a market offering that has value in the market. R-A theory places these resources into seven major categories: financial, physical, legal, human, organizational, informational, and relational. R-A theory's rich view of resources includes relational ties with stakeholders, such as customers, suppliers, competitors, government agencies, and unions. Supply chains with rich relationships are likely to achieve higher levels of cooperation and coordination, which can lead to improved value creation across the supply chain (Uzzi 1996) and likely firm performance. R-A theory also includes organizational resources such as policies, culture, and competencies (Hunt 2000). Supply chains will differ among organizations in their abilities to establish organizational resources and overall competencies. Such differences can explain why some supply chains have better firm performance.
The RBV (Barney 1991; Grant 1991), which is based on efficiency in managing a firm's resources, suggests that firms can achieve a sustainable competitive advantage from acquiring and controlling (managing) their resources. Resources include both tangible (equipment, plant, and raw material) and intangible (knowledge, reputation, and brand image) assets that assist in the value creation of goods and services. The RBV suggests that firms can establish competitive advantage when organizational resources are valuable, rare, difficult to imitate and nonsubstitutable (Barney 1991; Conner 1991; Schulze 1994). When firms manage their supply chains and establish trust-based working relationships with suppliers, the results can be "supply chain" capabilities or intangible resources that are so unique to that company that it gives them an advantage that ultimately increases firm performance.
Supply chain linkages and inter-firm relationships create a unique set or bundle of resources that leads to a positive difference in the firms' ability to produce goods and services (Conner 1991). Moreover, the capabilities generated, such as supplier selection (Lee, Ha and Kim 2001), information gathering, inventory management, logistics management, and process improvement add tremendous value (Grant and Baden-Fuller 1995). For example, when firms engage in knowledge sharing among supply chain members or creative sourcing arrangements, they are developing capabilities that are valuable to the firm. Moreover, these resources and capabilities can be rare to come by, imperfectly mobile, not imitable by competitors, and not substitutable, which will provide the firm with a sustainable competitive advantage (Barney 1991).
R-A theory combines both demand side (customer) and RBV (firm) perspectives (Hunt and Davis 2008). Linking both the demand and supply side makes it fundamental to SCM strategy because firms that have a better understanding of the needs and wants of their target markets compared to rival firms in the same industry are likely to achieve superior financial performance.
Consequently, based on R-A theory and the RBV, we state that firms that are successful in creating superior supply chain resource capabilities, in turn will enjoy superior financial performance and result in increased firm revenues, decreasing firm costs, and efficiencies that benefit the firm at large. This directly leads us to the following hypotheses:
H1: Supply chain leader firms will be associated with significantly lower cost ratios than nonsupply chain leader firms in the same industries.
H2: Supply chain leader firms will be associated with significantly more efficient activity ratios than nonsupply chain leader firms in the same industries.
H3: Supply chain leader firms will be associated with significantly more efficient liquidity ratios than nonsupply chain leader firms in the same industries.
Sample and Data Collection
To identify firms with superior SC capability within an industry, the rankings were taken from AMR's annual Research Supply Chain Top 25 lists. Each year since 2004, AMR has published an annual listing of firms identified as the supply chain leaders. Using the rankings of SC leaders from 2004 through 2009, (1) a sample comprising all firms that were ranked as SC leaders in any of the 5 years was first created. This yielded a list of 42 unique firms, of which 11 were ranked as SC leaders in only one of the 5 years, 8 firms in two of the 5 years, 4 firms in three of the 5 years, 9 firms in four of the 5 years, and 10 firms in all 5 years. To develop a more robust sample of SC leaders, the sample was further restricted to firms that were selected as SC leaders in at least three of the 5 years. Although this reduced the sample to 23 firms (130 firm years (2)), it resulted in a sample with more enduring SC leadership.
We then created a matching set of control firms drawn from the Research Insight (Compustat) database. The following procedure was used for selecting the control sample. First, the SC leaders were grouped into different industry categories based on their four digit primary SIC. Second, control firms were then extracted from Research Insight (Compustat) based on industry. We restricted the control sample to an exact match based on the four-digit SC leader firm's industry sector code to strengthen the inferences about any relationships found. Any control firm that did not have complete financial data for each of the relevant years was eliminated from the sample.
The Wilcoxon signed-ranks test (matched sample comparison group methodology) was then employed to empirically identify any financially based differences of SC leaders and their non-SC leader firms (see Bharadwaj (2000), Kalwani and Narayandas (1995) and Santhanam and Hartono (2003) for examples of the application of this approach). The results from such strictly matched control sample firms serves as a benchmark and help remove the confounding effects of extraneous variables and other market forces that could influence firm performance. Several measures (ratios) were used in this study to capture firm accounting based performance, and are summarized in Table 1.
TABLE 1 Summary of Ratios Used to Measure Accounting Based Firm Performance Cost Ratios measure management's ability to control expenses Ratio Type Measurement Measurement Objective Cost to sales [Cost of goods Measures the sold]/[sales] proportion of sales that covers the cost of the inventory sold Selling, admin & [Selling, admin & general Measures the general expenses to expenses]/[sales] proportion of sales sales that are committed to operating expenses Activity Ratios provide information about management's ability to control expenses and to earn a return on the resources committed to the business Receivables turnover [Credit Sales]/[average Measures how many total receivables] times, on average, receivables are collected during the year Total assets turnover [Sales]/[average total Measures sales volume assets] in relation to the investment in assets. Operating cycle Accounts receivable Measures the time turnover in days + between the inventory turnover in acquisition of days inventory and the realization of cash from sales of inventory Trading cycle (days in [Average inventory/cost Measures how inventory) of goods sold]/360 efficient a firm is in its core trading activities. Less inclusive than the operating cycle as it only considers conversion of inventory to cash and not management of trading based receivables or payables Liquidity Ratios measure a firm's ability to meet its short-term obligations Current ratio [Current assets]/[current Measures the liabilities] sufficiency of current assets to pay current liabilities as they become due Cash turnover ratio [Net sales]/[cash] Measures how effective a company is utilizing its cash
Tables 2-4 present the results of the matched sample procedure with control firms selected based on their four digit SIC codes and further restricted to firms within the same four-digit industry sector. The Z-statistic is derived from the Wilcoxon signed-ranks test. The Wilcoxon signed-rank test is a nonparametric statistical hypothesis test used when comparing two related samples or repeated measurements on a single sample to assess whether their population mean ranks differ (i.e., it's a paired difference test). It is the preferred method as an alternative to the paired t-test when the population cannot be assumed to be normally distributed or the data are on an ordinal scale. It resembles the median-test in scope, but it is much more sensitive. In fact, for large numbers it is almost as sensitive as the two-sample t-test.
Cost Ratios (H1)
The results presented in Table 2 show support for Hypothesis 1. The cost ratios yielded varied significance levels with the SGA/SALES ratios being significantly lower (p < 0.01) for SCM leader firms and the COGS/SALES marginally significantly lower (p < 0.10). These results mirror those found by Bharadwaj (2000) when evaluating IT superiority for IT leader firms versus control firms matched by four-digit SIC codes.
TABLE 2 Comparison of Cost Ratios for Supply Chain Leader Firms and Control Firms Matched by Specific SIC Classification (Four Digit) and Industry Sector N Mean Median Z COST2SALE Leader 90 0.577 .60 3.155(c) 1.876 (a) Control 1,824 6.21 .54 SGA2SALE Leader 87 0.244 .21 2.71(c) 6.721 (c) Control 1,700 4.36 .37 (a.) Significant at the 10 percent level of significance. (b.) Significant at the 5 percent level of significance. (c.) Significant at the 1 percent level of significance.
Activity Ratios (H2)
Hypothesis 2 was also supported (p < 0.01). Table 3 shows that each of the ratios used in the analysis was superior for the SCM leader firms than for the control firms with an exception of the trading cycle, which is significantly shorter for the control firms than it is for the SCM leader firms. A ratio that afforded similar interpretation is the operating cycle. The results show that the average operating cycle for SCM leader firms is significantly shorter than that of the control firms. Further analysis indicates that the SCM leader firms had a significantly lower median trading cycle than control firms. Overall, Hypothesis 2 is supported.
TABLE 3 Comparison of Activity Ratios for Supply Chain Leader Firms and Control Firms Matched by Specific SIC Classification (Four Digit) and Industry Sector N Mean Median Z RECTVR Leader 90 57.119 8.78 -1.032 -4.325 (c) Control 13.09 6.64 OPCYCLE Leader 90 96.069 90.58 4.663 (c) -7.795 (c) Control 1,790 199.82 145.04 TRDCYC Leader 90 40.978 37.19 2.109 (b) -7.532 (c) Control 1,778 81.32 89.01 (a.) Significant at the 10 percent level of significance. (b.) Significant at the 5 percent level of significance. (c.) Significant at the 1 percent level of significance.
Liquidity Ratios (H3)
Hypothesis 3 was tested based on two ratios: the current ratio and the cash turnover ratio. The results of the two ratios are presented in Table 4. Results show that leader firms have a significantly lower current ratio (1.592:1 for leader firms versus 4.20:1 for control firms) than the control firms. A current ratio of 2:1 is considered the ideal ratio against which other current ratios are compared. A current ratio for leader firms that is closer to that benchmark is reflective of management's efficiency in balancing its needs for supporting short-term recurring obligations as compared to the extra liquid resources held up in current assets by control firms.
TABLE 4 Comparison of Liquidity Ratios for Supply Chain Leader Firms and Control Firms Matched by Specific SIC Classification (Four Digit) and Industry Sector N Mean Median Z CR Leader 90 1.592 1.20 19.536 (c) -9.175 (c) Control 1,861 4.20 2.88 CASHTVR Leader 90 21.092 8.43 -1.074 -8.876 (c) Control 1,841 17.84 2.44 (a.) Significant at the 10 percent level of significance. (b.) Significant at the 5 percent level of significance. (c.) Significant at the 1 percent level of significance.
In this study, we investigate the linkages between firm supply chain leadership and overall accounting-based financial performance. We hypothesized that firms identified as SC leaders will financially outper-form non-SC leader firms in the same industry sector. Our overall results indicate that firms identified as SC leaders consistently outperformed their non-SC leader peers in accounting-based cost, activity, and liquidity ratios. Financial measures are valuable to a firm because they capture the economic costs of business decisions. Cost, activity, and liquidity ratios indicate the overall "health" of a firm. The results of this study suggest that the decisions that supply chain managers make have an impact on the financial health of the firm. For example, supply chain managers make decisions on warranty cost, transaction accuracy (shipping documents, export documents) and exchange rate controls. These decisions have a role in determining selling, administrative, and general expenses, which will have an impact on the firm's cost ratios. Supply chain managers also make everyday decisions that have a direct impact on activity ratios and working capital, which affects the financial viability and performance of the firm. For example, sourcing time, theft, obsolescence and holding costs affect inventory days. Bad debt, inability to ship due to nonpayment and exchange rate changes affect accounts receivable days. Both inventory days and accounts receivable days directly impact the firm's working capital and the firm's activity ratios.
The results of our study suggest that supply chain leader firms are significantly better in making supply chain decisions that relate to cost, liquidity, and activity than nonsupply chain leader firms. The results also suggest that supply chain leader firms are making good strategic decisions and creating resource capabilities that are enhancing the overall financial health of the firm better than rival firms.
In addition, our findings offer empirical support for R-A theory and RBV and their connection to SCM. To achieve more financial success than its rival firms and to have better working capital, cost, liquidity, and activity ratios, supply chain leader firms must have a better understanding of the needs and wants of their target markets because they are creating and delivering products that have value (Hunt and Davis 2012). In addition, supply chain leader firms must also have a better ability to "organically" create relational collaborative competence (Priem and Swink 2012). Although our study does not allow us to pin point specific SCM strategies that are leading to better financial performance, we know that all SCM strategies require integration to some degree. Given that, it is necessary that supply chain leader firms create and develop relational capabilities and competence.
LIMITATIONS AND CONTINUED RESEARCH
It is important to recognize some basic limitations inherent with ratio analysis. While ratio analysis is convenient and simple to understand, the interpretations are only as good as the data from which they are computed and the information with which they are compared. Ratios may utilize data that are based on estimates, such as depreciation expenses, and as such the results may be biased by these internal estimates. Also, historical data are used to estimate ratios and so the fair value of a firm's performance may not be interpreted quite accurately. In addition, other nonquantitative events, such as management changes, internal reorganization, and employee skill-level, are not captured by ratio analysis that is purely based on quantitative data. Nevertheless, ratio analysis provides a strong basis for decision-making and making conclusions about a firm's financial or operational efficiency.
Superior SCM has long been recognized as a contributor to firm performance (Caruso 2004). Such outcomes have been the result of lower cost and increased efficiency in the supply chain process. However, the full extent of this relationship has yet to be studied. Our study contributes to this growing area of knowledge by further investigating the overall health of firms that are seen as supply chain leaders. Our study goes beyond profit ratios and investigates the financial health of supply chain leaders by comparing activity, cost, and liquidity ratios. Our results suggest that firms identified as supply chain leaders not only demonstrate enhanced overall firm financial performance but also show increased efficiency in management of firm resources. Such findings are consistent with both R-A theory and the RBV. Our results reveal that supply chain leadership is of only one benefit that these firms enjoy over competitor firms. Firms identified as supply chain leaders have lower cost ratios, are better able to balance their needs for supporting short-term recurring obligations and have a shorter operating cycle. Such information indicates that firms that are supply chain leaders are benefitting from their overall operational efficiencies, building resource capabilities and also providing quality management practices throughout their businesses.
AMR Research. http://www.amrresearch.com (accessed June 28), 2010.
Barney, J. "Firm Resource and Sustained Competitive Advantage," Journal of Management, (17), 1991, pp. 99-120.
Barney, J. "Supply Chain Management and Competitive Advantage," Journal of Supply Chain Management, (48:2), 2012, pp. 3-6.
Bharadwaj, A.S "A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation," MIS Quarterly, (24:1), 2000, pp. 169-196.
Bush, A.A., A. Tiwana and A. Rai. "Complementarities Between Product Design Modularity and IT Infrastructure Flexibility in IT-enabled Supply Chains," IEEE Transactions on Engineering Management, (57:2)2010, pp. 240-254.
Bustinza, 0.F., L.M. Molina and L.J. Gutierrez-Gut-ierrez. "Outsourcing as Seen from the Perspective of Knowledge Management," Journal of Supply Chain Management, (46:3), 2010, pp. 23-39.
Carter, J.R. and L.M. Ellram. "The Impact of Inter-organizational Alliances in Improving Supplier Quality," International Journal of Physical Distribution and Logistics Management, (24), 1994, pp. 15-23.
Caruso, D. 2004. "Supply Chain Excellence Means Superior Financial Performance," Reed Business Information. http://www.msimag.com/currentissues/2004/nov/ops10.asp, accessed November 20, 2010.
Chae, B., H.R. Yen and C. Sheu. "Information Technology and Supply Chain Collaboration: Moderating Effects of Existing Relationships Between Partners," IEEE Transactions on Engineering Management, (52:4), 2005, pp. 440-448.
Chen, J. and A. Paulraj. "Understanding Supply Chain Management: Critical Research and a Theoretical Framework," International Journal of production Research, (42:1), 2004, pp. 131-163.
Conner, K.R. "A Historical Comparison of Resource-based Theory and Five Schools of Thought within Industrial Organization Economics: Do We Have a New Theory of the Firm?" Journal of Management, (17), 1991, pp. 121-154.
Craighead, C.W., G.T. Huh and D.J. Ketchen, Jr. "The Effects of Innovation-cost Strategy, Knowledge, and Action in the Supply Chain on Firm Performance," Journal of Operations Management, (27), 2009, pp. 405-421.
Dehning, B., Richardson, V.J. and R.W. Zmud. "The Financial Performance Effects of IT-based Supply Chain Management Systems in Manufacturing Firms," Journal of Operations Management, (25), 2007, pp. 806-824.
Droge, C., J. Jayaram and S.K. Vickery. "The Effects of Internal Versus External Integration Practices on Time-based Performance and Overall Firm Performance," Journal of Operations Management, (22), 2004, pp. 557-573.
Friscia, T., K. O'Marah and D. Hoffman. "The AMR Research Supply Chain Top 25 for 2009." 2010, http://www.amrresearch.com/content/view.aspx?compURI=tcm7-43469 (accessed February 1, 2010).
Grant, R.M. "The Resource-Based Theory of Competitive Advantage: Implications for Strategy Formulation," California Management Review, (33), 1991, pp. 114-135.
Grant, R.M. and C. Baden-Fuller. "A Knowledge-Based Theory of Inter-firm Collaboration," Academy of Management Best Papers Proceedings, 1995, pp. 17-21
Green, K.W. Jr, D. Whitten and R.A. Inman. "The Impact of Logistics Performance on Organizational Performance in a Supply Chain Context," Supply Chain Management: An international Journal, (13:4), 2008, pp. 317-327.
Hartley-Urquhart, R. "Managing the Financial Supply Chain," Supply Chain Management Review, September (10:6), 2006, pp. 18-25.
Hoffman, D. and K. O'Marah. "The Supply Chain Top 25 Ranking: The Next 25." 2009, http://www.amrresearch.com/content/view.aspx?compURI=tcm7-37942 (accessed April 28, 2009).
Hunt, S.D. A General Theory of Competition: Resources, Competences, Productivity, Economic Growth, Sage Publications, Thousand Oaks, CA, 2000.
Hunt, S.D. and D.F. Davis. "Grounding Supply Chain Management in Resource-Advantage Theory," Journal of Supply Chain Management, (48:2), 2008, pp. 10-21.
Hunt, S.D. and D.F. Davis. "Grounding Supply Chain Management in Resource-Advantage Theory: In Defense of a Resource-Based View of the Firm," Journal of Supply Chain Management, (44:1), 2012, pp. 14-20.
Joong-Kun Cho, J., J. Ozment and H. Sink. "Logistics Capability, Logistics Outsourcing and Firm Performance in an E-commerce Market," International Journal of Physical Distribution and Logistics Management, (38:5), 2008, pp. 336-359.
Kaiwani, M. and N. Narayandas. "Long-Term Manufacturer-Supplier Relationships: Do They Pay off for Supplier Firms," Journal of Marketing, (59:1), 1995, pp. 1-17.
Kaynak, H. and J.L. Hartley. "A Replication and Extension of Quality Management into the Supply Chain," Journal of Operations Management, (26), 2008, pp. 468-489.
Ketchen, D., Jr, W. Rebarick, W. Rebarick, G.T. Huh and D. Meyer. "Best Value Supply Chains: A Key Competitive Weapon for the 21st Century," Business Horizons, (51), 2008, pp. 235-243.
Kigore, M. "Mitigating Supply Chain Risks," White paper, Chainalytics LLC, Atlanta, GA, 2003.
Kim, S.W. "An Investigation on the Direct and Indirect Effect of Supply Chain Integration on Firm Performance," International Journal of Production Economics, (119), 2009, pp. 328-346.
Lee, E.K., S. Ha and S.K. Kim. "Supplier Selection and Management System Considering Relationships in Supply Chain Management," IEEE Transactions on Engineering Managements, (48:3), 2001, pp. 307-318.
Liao, Y., P. Hong and S.S. Rao. "Supply Management, Supply Flexibility and Performance Outcomes: An Empirical Investigation of Manufacturing Firms," Journal of Supply Chain Management, (46:3), 2010, pp. 6-22.
Lo, C.K., A.C. Yeung and T.C. Cheng. "ISO 9000 and Supply Chain Efficiency: Empirical Evidence on Inventory and Account Receivable Days," International Journal Production Economics, (118), 2009, pp. 367-374.
Mentzer, J.T., W. DeWitt, J.S. Keebler, S. Min, N.W. Nix, C.D. Smith and Z.G. Zacharia. "Defining Supply Chain Management," Journal of Business Logistics, (22:2), 2001, pp. 1-25.
Monczka, R.M., R.J. Trent and R.B. Handfield. Purchasing and Supply Chain Management, Southwestern, Mason, OH, 2005.
Priem, R.L. and M. Swink. "A Demand-side Perspective on Supply Chain Management," Journal of Supply Chain Management, (48:2), 2012, pp. 7-13.
Radjou, N. "Adapting to Supply Network Change," Report, Forester Research Inc., Cambridge, MA, 2002.
Reuter, C., K. Foersti, E. Hartmann and C. Blome. "Sustainable Global Supplier Management: The Role of Dynamic Capabilities in Achieving Competitive Advantage," Journal of Supply Chain Management, (46:2), 2010, pp. 45-63.
Rungtusanatham, M., F. Salvador, C. Forza and T.Y. Choi. "Supply-Chain Linkages and Operational Performance: A Resource-based-view Perspective," International Journal of Operations & Production Management, (23:9), 2003, pp. 1084-1099.
Santhanam, R. and E. Hartono. "Issues in Linking Information Technology Capability to Firm Performance," MIS Quarterly, (27:1), 2003, pp. 125-153.
Schulze, W.S. "The Two Schools of Thought in Resource-Based Theory: Definitions and Implications for Research," in P. Shrivastava, A.S. Huff and J.E. Dutton (Eds.), Resource-Based Views of the Firm, JAI Press, Greenwich, CT, 1994.
Tan, K.C., V.R. Kannan and R.B. Handfield. "Supply Chain Management: Supplier Performance and Firm Performance," International Journal of Purchasing and Materials Management, Summer, (34:3), 1998, pp. 2-9.
Teece, D.J., G. Pisano and A. Shuen. "Dynamic Capabilities and Strategic Management," Strategic Management Journal, (18), 1997, pp. 509-533.
Toyli, J., L. Hakkinen, L. Ojala and T. Naula. "Logistics and Financial Performance: An Analysis of 424 Finnish Small and Medium-sized Enterprises," International Journal of Physical Distribution & Logistics Management, (38:1), 2008, pp. 57-80.
Tracey, M., J.S. Lim and M.A. Vonderemhse. "The Impact of Supply-chain Management Capabilities on Business Performance," Supply Chain Management: An International Journal, (10:3), 2005, pp. 179-191.
Uzzi, B.U. "The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect," American Sociological Review, (61:4), 1996, pp. 674-698.
Vickery, S.K., J. Jayaram, C. Droge and R. Calantone. "The Effects of an Integrative Supply Chain Strategy on Customer Service and Financial Performance: An Analysis of Direct Versus Indirect Relationships," Journal of Operations Management, (21), 2003, pp. 523-539.
Wallenhurg, C. "Innovation in Logistics Outsourcing Relationships: Proactive improvement by Logistics Service Providers as a Driver of Customer Loyalty," Journal of Supply Chain Management, (45:2), 2009, pp. 75-93.
(1.) Excludes 2006 since rankings were not done that year.
(2.) 23 firms with 3 year rankings (23 x 3), plus 4 firms with 4 year rankings (4 x 4), plus 9 firms with 5 year rankings (9 x 5).
BERTIE M. GREER AND PETER THEURI
Northern Kentucky University
Bertie M. Greer (Ph.D., Kent State University) is an associate professor of management in the Haile/US Bank College of Business at Northern Kentucky University in Highland Heights, Kentucky. Her research interests focus on the areas of supply chain management, supplier diversity, project management and the implementation of change. Dr. Greer has industry experience as an engineer and supervisor with Timken Roller Bearing, Ford Motor Company and Chrysler/Jeep in process improvement, buyer-supplier relationships, manufacturing and quality management. She has published articles in Interfaces, the Journal of Operations Management, the Journal of Business Logistics, and the Journal of Applied Behavioral Sciences, among other outlets.
Peter Theuri (DBA, Mississippi State University) is a professor of accounting in the Haile/US Bank College of Business at Northern Kentucky University in High-land Heights, Kentucky. He teaches financial accounting at both the graduate and undergraduate levels, and has won several teaching awards. Dr. Theuri has published work in academic as well as practitioner business journals, and has developed academic cases related to financial statement analysis. He also is a licensed CPA.
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|Author:||Greer, Bertie M.; Theuri, Peter|
|Publication:||Journal of Supply Chain Management|
|Date:||Jul 1, 2012|
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