The connection between training, electronic ordering, strategic alliances and supply chain procurement efficiency: an empirical study.
While the firm develops and maintains the overall business strategy which focuses the direction of the firm, a supply chain strategy will focus on how the supply chain will operate in a competitive environment while contributing to the overall goals of the entire supply chain. It is important that the supply chain strategy involve comparison of the costs and benefits of the operational choices. This study examines several supply chain operational choices; procurement employee training, Electronic Data Interchange purchasing, and purchasing via strategic alliances, to determine whether the commitment to and the application of these activities and practices improve supply chain efficiency. These activities were chosen based upon a review of the extant literature and lack of literature findings that relate these activities to supply chain efficiency.
To operate successfully in a competitive environment, a firm should develop a competitive advantage. By identifying strategies to suit the particular environments, resources and capabilities of the company, firms can achieve a competitive advantage. The proper choice and alignment of the activities and practices of the firm's supply chain play an important role in developing a competitive advantage. The success of the firm depends on the success of the whole supply chain, which in turn depends on multiple outside companies and internal company functions. Porter's work does not specifically refer to the "supply chain," but his theories address the importance of management choices which are represented by supply chain activities and practices (Porter, 1980; 1985).
This study stems from the research question: what is the connection between employee training and supply chain procurement efficiency, as measured by total procurement spending per procurement employee. This study also examines that relationship with the expectation that corporations that allocate more resource dollars to employee training will experience positive effects on supply chain efficiency.
Porter's (1980) five forces framework has been criticized for its promotion of analyses at the industry level rather than the firm level. Rumelt (1991) argues that "firm-specific factors" are more relevant to profitability predications and outcomes and outweigh the importance of industry-wide factors. However, McGahan, and Porter's (1997) research refutes Rumelt in studies that provide support for industry-level analysis. In an interview with Stonehouse and Snowdon (2007), Porter addressed the ongoing industry/firm debate, noting that in his early body of work he intended to focus on the industry structure as support for competitive advantage. Although Porter continues fully to support the importance of industry-level analysis, his future work did move toward a greater firm-level focus, specifically the "value chain" concept.
He declared that firms do not have "production functions" that operate in isolation. Rather, firms consist of a whole series of interdependent "production functions" (Stonehouse & Snowdon, 2007). Porter (1985) may speak of the firm, but he actually describes the relevance of the firm in terms that support his commitment as still rooted within macro-level confines. Researchers observe that Porter's original view of competitive advantage was from the "outside-in," whereas others view competitive advantage from the "inside-out" focusing more on core competencies, knowledge, and organizational learning with a recognition that both views are necessary (McKiernan, 1997; Prahalad & Hamel, 1990; Senge, 1990; Stonehouse & Snowdon, 2007).
There is no single school of thought regarding micro- versus macro-level study of competitive advantage. However, there is recognition that both views are necessary. Although much discussion centers on which views best support competitive advantage, a cohesive thread fails to unite the literature related to the effects of specific supply chain practices on efficiency at the industry-level. Therefore, the industry is the level of analysis for this study (Reference).
Porter (1985) asserts that regardless of a firm's commitment to a cost leadership focus, firms work in general to choose activities and practices that improve efficiency. The literature is inconsistent in connecting specific industry supply chain activities and practices to supply chain efficiency. This study contributes to the practice of supply chain management by providing empirical evidence about supply chain activities so that resources can be better allocated to specific supply chain practices.
The application of supply chain activities and/or practices in order to develop competitive strategies can be summarized by Skinner's (1969) operational priorities. Skinner recognized that the application of the appropriate operational priorities will contribute to the overall corporate strategy goals. He also noted that managers should be prepared for tradeoffs in efficiency, cost, and productivity in pursuit of the corporate strategy. Other researchers have concurred with Skinner's (1969) seminal work, recognizing the importance of operational priorities and tradeoffs (Adam & Swamidass, 1989; Hayes & Wheelwright, 1984; Walker & Ruekert, 1987).
More recently, still focusing on Skinner's original work, researchers have stressed the importance of operational priorities such as cost, delivery, quality and flexibility in corporate strategy (Butler & Leong, 2000; Ward, McCreery, Ritzman & Sharma, 1998). In the pursuit of a competitive advantage through potential cost reductions, the efficiency of the buying firm's supply chain is tied to the efficiency of the firms in the supply chain. Some supply chain activities and/or practices that Skinner described as operational priorities focus on more than the original buying company. In an attempt to develop a seamless and productive supply chain, companies may choose to allocate resource dollars to electronic data interchange (EDI), employee training, and the development of strategic alliances that focus on broader operational priorities, thereby spreading any potential benefit throughout the supply chain.
In a large-scale study, Li, Ragu-Nathan, B., Ragu-Nathan, T.S., and Rao, (2006) surveyed 3,137 senior and executive level managers. Using structural equation modeling, the goal was to determine if supply chain management practices have a direct impact on the overall financial and marketing efficiency of a firm. Li's study used the following supply chain management practices: strategic supplier partnership, customer relationship, level of information sharing, quality of information sharing, postponement to test the relationships between supply chain management practices and competitive advantage, and firm efficiency. They determined that higher levels of supply chain management practices lead to enhanced competitive advantage and improved firm efficiency. Competitive advantage was measured by the firm having one or more of the following capabilities when compared to its competitors: lower prices, higher quality, higher dependability, and shorter delivery time. Efficiency was measured by market share and return on investment.
Specific supply chain management practices have been clearly recognized in the literature as having an effect on firm efficiency. Tan's (2002) research associated supplier evaluation practices with increased efficiency. Earlier studies positively associated the application of quality management plans, supplier base management and customer satisfaction practices with increased firm efficiency (Tan, Kannan, Handfield, & Ghosh, 1999).
Based on the literature review of cost efficiency and the establishment of operational priorities, the authors of this study contend that companies with limited resource dollars must carefully choose activities and practices to improve efficiency and ultimately contribute to competitive advantage. The authors further contend when companies allocate resource dollars to broader operational priorities such as electronic data interchange (EDI), employee training, and the development of strategic alliances; the benefits are realized throughout the supply chain.
The Supply Chain and Procurement Employee Training
A complete evaluation of the success of supply chain management activities and practices must include top management's commitment to provide employee training to facilitate the implementation of leading-edge practices. Research suggests that the effectiveness of supply chain management practices has been limited by firm implementation barriers and could be improved by enhancing the human resource factors (Bubshait & Farooq, 1999; Dooley & Fryxell, 1999). Bubshait and Farooq point out that management tends consistently to focus on "cost, time, and quality" in its evaluation of efficiency while paying little attention to the human resource factors. Yet omitting the consideration of human resource factors can significantly affect "cost, time and quality."
The majority of training research takes a human capital perspective in which training is regarded as an investment increasing worker productivity, where the primary objective of training is to establish or reinforce basic skills. According to de Koning (1993), employers may be compelled to offer training if the initial quality of the labor pool is poor, or it improves the skills of those employees seeking more responsible positions within the firm. Human capital theory postulates that education and training increase efficiency. Even though managers report that training programs are a good investment in human capital, these same managers perceive that training programs return very little in monetary value to their firms (Au, Altman, & Roussel, 2008).
From this perspective, managerial support for additional training resources is questionable. In his 1962 seminal work on human capital, Becker distinguished between general and specific training claiming that general training is useful for many firms and therefore is transferable (Sieban, 2007). Managers could discourage training in cases where it may be considered transferable since operational benefits may not be captured by the firm providing the training. This would be a managerial trade-off between the cost of the training (with an anticipation of improved operational efficiency) and the risk of employees transferring the knowledge to another firm.
The implementation of supply chain management activities and practices (such as alliance building and e-business) frequently requires changes in the status quo within the firms. Information and knowledge-sharing through employee training in the respective areas of specific change can frequently soften any employee dissent, resulting in a quicker, easier implementation (Dooley & Fryxell, 1999). By 1999, in anticipation of gaining a competitive advantage, supplier relationships and alliances were significantly increased by Ford, GM, Daimler-Chrysler, Renault, Peugeot, Volkswagen, Wal-Mart, Kmart, Home Depot, Proctor and Gamble (Gowen & Tallon, 2003). However, all of these firms report that they expect that successful alliance relationships will be dependent on the implementation of successful employee training.
Corporate universities" have increased from 400 in 1988 to over 1600 by 2003 as an indication of the corporate commitment to and investment in training and development (Gowen & Tallon, 2003). However, even with the increased commitment to employee training, there has been little research examining the relationship between better human resource management (HRM) and supply chain efficiency. One possibility for the lack of research in this area stems from the origin of the supply chain concept. Seen from the vantage of production and logistics, the supply chain is many times viewed narrowly as solely related to operational issues and not to human resource issues.
In a 1987 study cited by Gowen and Tallon (2003), Ernst and Whinney, in collaboration with the Council of Logistics Management, determined that firms regarded as "excellent" in their ability to apply supply chain management practices also emphasize the training (and re-training) of their workforces. The study determined that progressive 'best practice' firms treated training and human resource development as a strategic need and not as a discretionary budget item of which funding can be reduced during difficult times. The study noted that change is becoming routine and that training will be a future source of competitiveness. A follow-up study in 1992 directly addressing the "development of human resources as a major factor in the evolution of what was termed a 'total quality firm'; determined that these world-class firms have made a strong commitment to employee participation, education and training (Gowen & Tallon, 2003).
Although the literature recognizes the importance of employee training, little research has been completed to examine the relationship between training and supply chain efficiency. This study addresses that relationship and expects that corporations that allocate more resource dollars to employee training will experience positive effects on supply chain efficiency.
The Supply Chain and Strategic Alliances
Much has been written about the need for integration between all parties within the supply chain. In fact, the development of the definition of supply chain management includes the management of integrated behaviors among parties (Bowersox & Closs, 1996). Developing a set of activities and practices to improve a firm's supply chain efficiency should coordinate and encourage cooperation among the supply chain partners, to meet the customers' demands and ensure long term supply chain efficiency. If each member of the supply chain focuses on a compatible set of objectives, redundant activities and duplicated effort can be reduced, resulting in cost savings.
The supply chain is dependent on the co-existence, not competition, of the member firms. There is a linkage between all of the departments within a firm and among its suppliers, supplier's suppliers, customers, customer's customers, and third and fourth party providers (Lummus & Vokurka, 1999). The influence of supply chain thought on organizational strategy is increasing, and many authors claim that competitive advantages accrue at the supply chain level today as opposed to the individual firm level (Dyer & Ouchi, 1993; Houlihan, 1985; Li, et. al. 2006; Sengupta, Heiser, & Cook, 2006). Therefore, to establish a competitive advantage, firms depend heavily on collaboration and relationships built among the parties. When the supply chain is viewed as a unit, the core competencies of the individual firms are combined and used to create a competitive advantage at the supply chain level.
Spekman, Kamauff, and Myhr (1998) state competition is "evaluated as a network of cooperating companies competing with other firms along the entire supply chain" (p. 38). They use the following analogy:
Simply, Ford Motors is as successful as its ability to co-ordinate the efforts of its key suppliers (and its suppliers' suppliers) as steel, glass, plastic, and sophisticated electronics systems are transformed into an automobile that is intended to compete in world markets against the Japanese, the Germans, and other U.S. manufacturers (p. 38).
However, while Spekman et al. (1998) espouse the benefits of cooperative relationships, an earlier study by Spekman, Isabella, MacAvoy, and Forbes (1996) reported dismal results about the state of collaborative relationships. They conducted an in-depth interview study of 31 managers in 12 companies. These alliances characterized a spectrum of strategic activities ranging from offensive alliances to defensive alliances and to alliances intended to reduce costs. While the respondents seemed to favor alliances for a variety of perceived reasons (emphasis added), the results show that approximately 60% of all alliances fail.
Krause and Ellram (1997) conducted a survey of 1,504 high-level purchasing executives, members of the National Association of Purchasing Management (NAPM), representing a variety of manufacturing and non-manufacturing industries. Electrical/electronic equipment, miscellaneous manufacturing, chemicals, fabricated metals, health service and food industries were most widely represented in the respondent group. With a 35% return rate resulting in 527 responses, 295 respondents characterized the results of their companies' supplier development efforts as exceeding or greatly exceeding expectations.
A group of 225 respondents characterized the results of their firms' supplier development effort as neutral or having fallen short of expectations. Upon further investigation Krause and Ellram found that the respondents reporting efforts as exceeding or greatly exceeding expectations manifested a more proactive approach to alliance management than the neutral or having fallen short of expectations group of respondents. Although the initial results of this survey show that the perceived success of supply chain alliances was only about 56, if one group was more proactive in their management style the results would be affected.
Thomas (1999) reports that according to a recent Deloitte Consulting survey, 91% of North American manufacturers rank supply chain management as very important or critical to their companies' success; yet only 2% of the manufacturers in the same survey rank their supply chains as world class. Almost 50% of the companies surveyed have no formal supply chain strategy. Jim Kilpatrick, senior manager in Deloitte's Consulting Supply Chain Results Practice, advises that without a formal supply chain strategy, random application of supply chain activities and practices are not likely to succeed. Kilpatrick argues that top management does not fully comprehend the importance of supply chain issues. Earlier discussions in this study emphasized the importance of the incorporation of the supply chain process into the overall firm strategic plan. Although the alignment and the incorporation of the strategic plan is not the direct focus of this study, it is necessary in the success of the application of activities and practices chosen.
Choi and Hartley (1996) surveyed 733 purchasing agents in various levels of the automotive industry to compare supplier-selection practices. Using multivariate analysis of variance (MANOVA), they found that the practice of hiring suppliers for potentially establishing a cooperative, long-term relationship was equally important to both suppliers and buyers. There were no significant differences between the suppliers and the buyers for the level of importance placed on consistency of quality and delivery, reliability, relationship, flexibility, price, and service. Statistically significant differences were found between the buyer and supplier on the importance placed on technological capability and financial issues. The work of Choi and Hartley focuses on one industry, but they recommend that future research be conducted to determine whether these results can be generalized across industries. This study examines the relationship between the formation of alliances and consortiums and supply chain efficiency across industries.
Vonderembse and Tracey (1999) used a five-point Likert scale to survey 2,000 purchasing agents from various discrete part manufacturing industries. Discrete part manufacturers produce distinct items such as transportation equipment, computer and electronic products, industrial and electrical equipment, medical equipment and supplies, fabricated metal, furniture, and recycling. The purpose of the survey was to determine to what extent manufacturing firms use supplier selection criteria and involve suppliers in product design and continuous improvement practices as presented in figure 1.
The survey measured the importance of supplier selection criteria as represented by product quality, product availability, delivery reliability and product efficiency, and supplier involvement as represented by supplier membership on product design teams and continuous improvement teams. Vonderembse and Tracey found few significant correlations between supplier selection and supplier efficiency. The respondents disagreed with the statement that suppliers are members of product design teams, but the reported representation of suppliers on continuous improvement teams was higher.
In a longitudinal study of British firms, Stuart (1997) surveyed 89 purchasing agents and collected data on buyer/supplier relationships in order to evaluate the impact from firms' initiatives in developing strategic supplier alliances on the significance of supply management in the corporate hierarchy. Stuart divided responses into three categories according to the supplying firm's current relationship to the buying firm: those in a passive mode, those pursuing an integrative (alliance type) mode and those considered to be in a supportive/independent mode. The results of his correlation analysis show that the passive and integrative groups varied significantly in the following constructs: top management recognition of potential purchasing impact, management support, and the strategic involvement of purchasing. The integrative (alliance) type experienced competitive gains in their purchasing efforts, higher top management support, increased resource commitment, and a stronger strategic profile within the company.
Reinforcing the results of Choi and Hartley (1996) and Stuart (1997), Carr and Pearson (1999) found that strategic long-term relationships with a firm's major suppliers have a positive impact on the firm's efficiency. Cooper, Ellram, Gardner, and Hanks (1997) posit that since the supply chain is a synergistic structure, a "dyadic management approach" will improve competitiveness. In this approach, close working relationships with immediate members facilitates the spread of management practices throughout the entire supply chain, dyad by dyad, ultimately improving the competitiveness of the entire supply chain. Cooper et al. 1997, note that both Xerox Corporation and Honda of America apply this dyadic approach and have benefited significantly.
In a cross-industry study, Handfield and Bechtel (2002) surveyed 500 purchasing managers responsible for managing a primary supplier relationship. The survey included manufacturing firms from the automotive, computer, chemical, consumer products, electronics, industrial equipment, pharmaceutical, and steel industries. Their model measured supply chain responsiveness in relation to buyer-dependence, supplier human asset investments, and trust. The results suggest that even in cases when buyers do not have a great deal of control over their suppliers, working to build trust within the relationship can improve supplier responsiveness.
The evaluation of the benefits of strategic alliances has produced mixed results. Founded on theoretical grounds, literature espousing the benefits of cooperation, coordination, relationship building and alliance formation, is not supported by empirical evidence. The lack of supporting empirical evidence may result from the complex nature of the supply chain and the difficulties in measuring the benefits of the variety of alliances practiced. This study contributes to the literature by empirically testing the relationship between the establishment of supply chain alliances and supply chain efficiency. It is expected that the establishment of alliances will have a positive effect on supply chain efficiency.
The Supply Chain and E-Commerce
According to the U.S. Census Bureau (2008), e-commerce is the value of goods and services sold online whether over open networks such as the Internet, or over proprietary networks running systems such as EDI. Using a case study in Japan, Gunasekaran, and Ngai (2004) concluded that the emergence of e-commerce and information communication technologies has enabled companies to be flexible and responsive to changing market requirements. Johnson and Whang (2002) classify e-business applications as e-commerce, e-procurement, and e-collaboration. E-commerce facilitates coordination among supply chain partners and enables them to identify and respond quickly to changing customer demand. E-procurement enables companies to use the internet for procuring direct or indirect materials. E-collaboration facilitates coordination of various decisions and activities beyond transactions among the supply chain partners, including other suppliers and customers influencing the supply chain management.
According to Presutti (2003), 70% of a firm's sales revenues are typically spent on supply chain-related activities. E-commerce strategies need to be sold by supply managers to top management by using economic value added (operating profit after taxes--cost of capital) to make their case. Using a field-based survey, Soliman and Janz (2004) found that the factors that significantly affect the adoption decision of Internet-based inter-firm information systems are pressures felt from trading partners, pressure felt from competitors, costs of establishment, network reliability, data security, scalability, complexity, support from top management, and trust between trading partners. Zank and Vokurka (2003) surveyed 250 manufacturers, 300 distributors, and 1,200 industrial customers in the U.S. and found that members of the supply chain believed that e-commerce had a slightly positive impact on their efficiency. Despite the expected cost advantages, they found that e-commerce capability was not always an important criterion when selecting distributor partners.
E-commerce can become a basis for competitive advantage particularly if it lowers costs and/or improves efficiency. According to Barnes, Hinton & Mieczkowska (2003), achieving an advantage requires the integration of operations management and information systems both within the firm and with supply chain partners. Using stepwise regression to analyze the results of a survey of 416 customers of a major Internet retailer, Boyer & Olson (2002) found internet specific factors improved efficiency. In their study they identified two measures of efficiency: cost of purchasing and improved accounting accuracy. In particular, they found that perceived usefulness, defined as a potential user's subjective views of the new technology as offering benefits relative to alternative methods, had the largest impact. Surveying 1,000 members of the Council of Logistics Management, Lancioni, Smith, & Schau (2003) found that internet usage within supply chains is maturing, resulting in increased productivity, reduced costs and increased profit for participating firms.
The use of e-commerce can overcome some traditional management problems, including the need for real-time inventory information and data entry point conflicts (Johnson & Whang, 2002). Frohlich and Westbrook (2002) investigated the relationship between the extent to which Internet-enabled demand and supply chain strategies and efficiency are related in manufacturing and service sectors. They found strong evidence that demand chain management, which coordinates the supply chain from end-customers backwards to suppliers, led to the highest efficiency in manufacturing. Companies that had high levels of supply or demand internet-enabled management strategies outperformed those with low levels of internet-enabled integration strategies. Craighead, Patterson, Roth, and Segars (2006) surveyed 336 manufacturing firm members of the Association for Operations Management; they found that supply chain management systems applications incorporating electronic data interchange increased customer responsiveness and product quality, and decreased inventory cost and data errors.
Using data from 752 small businesses with less than 250 employees, Burke (2005) found that slight differences in firm size generate various patterns of adoption for several types of small business information systems. According to the findings, smaller sized firms are less likely to report internet computer use than even incrementally larger businesses. In addition size accounts for significantly more predictive responses than CEO or industry factors.
Although the literature generally supports the claims that e-business conducted through supply chain activities can enhance coordination, increase responsiveness and supply chain flexibility, resulting in cost savings, other studies offer conflicting claims. This study contributes to the literature by empirically testing the relationship between the establishment of e-business activities and supply chain efficiency. It is expected that the establishment of e-business activities will have a positive effect on supply chain efficiency.
OBJECTIVES AND HYPOTHESES OF THE STUDY
This study develops stems from the research question: what is the connection between training, electronic ordering, strategic alliances and supply chain procurement efficiency, as measured by total procurement spending per procurement employee. The implementation of supply chain management activities and practices (such as alliance building and e-business) frequently requires intra-firm changes that depend on training efforts. Although the literature claims that employee training is important, little research has been conducted to examine the relationship between employee training and supply chain efficiency. This study examines that relationship with the expectation that corporations that allocate more resource dollars to employee training will experience positive effects on supply chain efficiency. This research proposes the following hypothesis:
Hypothesis H1: A relationship exists between the level of procurement spending per procurement employee (dependent variable) and the average annual spending on training per procurement employee (independent variable).
E-commerce facilitates coordination among supply chain partners, enabling them to identify and respond quickly to changing customer demand. E-procurement enables companies to use the internet for procuring direct or indirect materials. E-collaboration facilitates activities beyond the transactions among the supply chain partners by including other suppliers and customers that influence supply chain management. E-commerce can become a basis for a firm's competitive advantage particularly if it lowers costs and/or improves efficiency.
The literature is inconsistent in its support or refutation of the relationship between the establishment of e-business activities and supply chain efficiency. Despite the disparities found in the literature regarding extent of the application of e-activities, the results of the reviewed literature tend to support the claims that e-business activities conducted within the supply chain can enhance coordination and increase responsiveness and supply chain flexibility, resulting in cost savings. This research proposes the following hypothesis:
Hypothesis H2: A relationship exists between the level of procurement spending per procurement employee (dependent variable) and the percent of procurement spending via Electronic Data Interchange (EDI) (independent variable).
The supply chain depends on the cooperative existence of the member firms rather than competitive existence. In addition, a linkage is established among the procurement related departments within an organization and its suppliers (and the supplier's suppliers), customers (and the customer's customers), and third and fourth party providers. To compete successfully, organizations depend heavily on collaboration and relationship building among the parties. When the supply chain process is viewed as a unit, the core competencies of the individual firms are combined to create a supply chain competitive advantage. The literature lacks consensus regarding the extent of the advantage. This research proposes the following hypothesis:
Hypothesis H3: A relationship exists between the level of procurement spending per procurement employee (dependent variable) and the percent of total spending via strategic alliances (independent variable).
Sample and Data Collection
This study uses data from the Center for Advancing Purchasing Studies (CAPS) industry level research surveys. The CAPS is jointly sponsored by the Institute for Supply Management (ISM) and the W.P. Carey School of Business at Arizona State University. The CAPS survey used in this study is the result of an on-going, long-term project that has extended over two decades.
This study uses responses from a CAPS survey that is called a "benchmark" survey. In this context, the term "benchmark" is used broadly in the sense that responding firms provide information related to supply chain activities or practices. The survey is conducted at least two times a year and is distributed to firms within various industries. The primary purpose is the collection and publication of metrics for particular industries from aerospace to utilities which are presented in Table 1.
Individual firms are asked to provide information that relates to specific characteristics and activities or practices. These characteristics and activities or practices are not identified as "best practices," nor are ideal values provided. Although the survey is described as a "benchmark survey," the result is an aggregated industry summary. To the extent that one firm in an industry can compare its own metrics to the aggregated industry summary; the CAPS survey is a "benchmark survey."
The CAPS survey aggregates information related to management practices in the purchasing area. The literature includes studies of various supply chain activities and practices, but not all purchasing activities are measured in the CAPS survey. Since the survey includes metrics of current interest to purchasing professionals, the inclusion of questions varies among data collection periods. Over time, some questions are adjusted by CAPS, in consultation with industry leaders and study participants, to better represent practice categories and the interest of purchasing professionals and to be of particular interest to managers of the large firms within industry sectors. So, even though the included categories are the same (or at least very similar), the wording of the questions may change.
The CAPS survey is completed by individual firms within all industries and the responses are aggregated to the industry level. However, not all firms within an industry provide data for each survey. For some collection periods, insufficient responses are reported within an industry to report results. Although CAPS has compiled a time series of information for multiple industries, the observations used in this study include approximately 30 industries, but an aggregated summary is not available for each industry in each time period.
Aggregated industry summaries used in this study represent results from nineteen surveys from 2001 to 2007. A total of 185 aggregated industry survey summary responses were reviewed for this study. Some original aggregated summaries were unusable due to missing data. The final data set includes 132 observations for Y aggregated industry survey responses. Figure 2 uses two industries to show the flow of the data from the CAPS survey for a single survey time period.
Center for Advancing Purchasing Studies Survey
The CAPS survey solicits data from many industries. Thirty-three industries having complete and consistent survey responses were included in this study. The industries included in this study are shown in Appendix A. The CAPS is a professional research organization operating in association with a premier professional organization, The Institute of Supply Management (ISM), and Arizona State University, which is renowned in the field of supply chain management research. The CAPS survey data is taken from an on-going, long-term project that strives for continuous improvement in its data gathering and compilation processes and, thus, the survey data is of high quality. Survey questions are determined in direct consultation with supply chain management professionals. The survey consistently tracks similar areas of importance to the supply chain management process, and the questions are improved regularly. The CAPS research team has a vested interest in the quality and accuracy of its data and relies upon it for the determination of further studies.
As noted earlier, the data is collected at the firm level and aggregated to the industry level. Each survey could include data from various participating firms. The data are systematically collected over time constituting a high quality time series, cross sectional data set.
The specific objective of this study is to identify and test the strength of any relationship between total procurement spending per procurement employee (Y) and three particular supply chain practices (independent variables or Xs). To learn more about the relationship between total procurement spending per procurement employee and the three independent or predictor variables, this study estimates a least squares multiple regression model. The three independent or predictor variables are the average annual spending on training per procurement employee ([X.sub.1]), the percent of procurement spending via E-Activities ([X.sub.2]), and the percent of procurement spending via strategic alliances ([X.sub.3]). The dependent or criterion variable (Y, representing the supply chain efficiency indicator) is the total procurement spending per procurement employee.
The goal of this study is to provide supply chain managers empirical information about the effectiveness of particular activities and practices. In developing the supply chain management strategy, firms will want to identify the supply chain management practices that have an acceptable positive impact on supply chain efficiency. At the firm level, supply chain managers can more effectively make a case for a greater share of corporate resources if they can provide evidence that the application of particular supply chain practices have been shown to enhance the supply chain's efficiency in their industry.
This study seeks to identify the "relationships between given variables," using a quantitative approach (Creswell, 2003). The extant literature supports analysis at the firm level or the industry level. This study uses firm level data aggregated to the industry level. Although firm level analysis is important in understanding the supply chain phenomena, it does not provide evidence of effectiveness and efficiency at the industry level. Industries are significantly affected by the effectiveness of inter-organizational relationships in which firm performance is directly linked to the success of the entire supply chain. Competitive advantage is no longer determined at the firm level (Li, et al., 2004; Sengupta, et al., 2006), and a broader examination of the effectiveness of supply chain activities and practices will inform the supply chain field.
THREATS TO VALIDITY
The validity and reliability of research is important. Validity determines the accuracy of the method of measurements made and determines whether the method measures what it is intended to measure. Validity is associated with accuracy.
Internal validity is assumed to exist if a causal link exists between the independent variable(s) and the dependent variable(s). The variation in the dependent variable(s) can only be attributed to the manipulation of the independent variable(s), and the results can be replicated. Replication for internal validity requires that the results can be reproduced under the same conditions using the same variables (Campbell & Stanley, 1963).
External validity requires that the results are able to be both replicated and generalized beyond the current application. Replication for external validity requires replications to be conducted in other settings, with other subjects, but can include related variables. Replication conducted under various circumstances is necessary before the results can be considered theoretically sound. Reliability is determined through the ability to replicate the results of the measurements. Reliability is associated with replication (Campbell & Stanley, 1963).
The CAPS data used in this study are taken from an on-going, long-term project that strives for continuous improvement in its data gathering and compilation processes. The CAPS research team has a vested interest in the quality and accuracy of its data upon which it relies for determination of further studies by its organization. Therefore, the threats to validity are considered to be minimal in regard to the source of the data.
Validity of the data collected can be impacted by the respondents' understanding and interpretation of the survey as well as their honesty in answering the questions. The CAPS researchers consult directly with supply chain management professionals in order to determine specific areas of supply chain interest, as well as solicit input to improve question clarity. However, invalid data may result from any survey if questions are misunderstood or falsely answered.
With the use of self-reported measures, respondents may confuse reality with aspirations, believing their situations to be different than their actual case. Since CAPS researchers work directly with the participants who hope to gain beneficial supply chain management information from the shared proprietary results, it appears that the self-reported measures may be more reliable in this case and reduce the threat to validity.
During the CAPS data verification process, some participants are asked to review information for completeness and correctness. The data collected is not verified or validated as being correct beyond this process. Ratios are developed to test specific information to identify data anomalies or statistical outliers. In those cases, participants were again asked to review specific data for correctness. This set of checks and balances serves to add validity to the data.
As noted earlier, the data is collected (not reported) at the firm level and aggregated to the industry. The validity of the data is not affected by this aggregation since an industry level focus is the intent of the survey. In addition, each survey collection period may include data from various participating firms. Nonetheless, the data are systematically collected over time.
The purpose of this study at the broadest level is to provide supply chain managers necessary information about the effectiveness of particular activities and practices. At a more specific level, the objective is to identify and test the strength of any relationship between the supply chain efficiency indicator and the three particular supply chain practices. At the firm level, supply chain managers can more effectively make a case for a greater share of corporate resources if they can provide evidence that the application of particular supply chain practices have been shown to enhance the supply chain's efficiency in their industry. The analysis of the findings includes the descriptive statistics, correlation matrices and regression results. The data are analyzed and a discussion of the results is provided.
The descriptive statistics are shown in Table 2 and are used to describe the basic features of the data in the study. Following the table is a detailed discussion of the descriptive statistics.
Procurement spending per procurement employee was, on average, $20.2 M per industry, ranging from an industry low of $4 M (DOE Contractors) to an industry high of maximum of $57.9 M (Beverages). On average, aggregated industries spent $1,169.40 annually on training per procurement employee, ranging from a minimum of $386.00 (Mining) to a maximum of $3,240.00 (Petroleum). Aggregated industries also spent on average 6.68% of total procurement spending via e-activities ranging from a minimum of 0.11% (Engineering/Construction) to a maximum of 24.20% (Pharmaceutical). They likewise averaged 17.29% of total procurements spending via strategic alliances ranging from a minimum of 0.00% (State/County Governments) to a maximum of 47.93% (Beverages).
This study estimates a multiple least squares regression model to determine the relationship between three independent or predictor variables and one dependent or criterion variable. The model estimated is shown below.
Y = [b.sub.0] + [b.sub.1][X.sub.1] + [b.sub.2][X.sub.2] + [b.sub.3][X.sub.3]
Y = Total procurement spending per procurement employee;
[X.sub.1] = Average annual spending on training per procurement employee;
[X.sub.2] = Percent of procurement spending via Electronic Data Interchange;
[X.sub.3] = Percent of procurement spending via strategic alliances.
The correlation determines the type and strength of the linear relationship between variables. Correlation values range from -1.00 (for a perfect negative, or inverse relationship) through 0 (no relationship) to +1.00 (for a perfect positive, or direct relationship). The closer the correlation coefficient is to either -1.00 or +1.00, the stronger the relationship.
Correlations are used to identify any potential multicolinearity that could result in biased estimates of coefficients and thus invalid hypothesis tests. Multicolinearity occurs when two or more variables are highly correlated with one another. When multicolinearity is a problem, the standard errors associated with the slopes may become enormous (highly inflated), which leads to incorrect conclusions from the significance tests of the slopes. The correlation matrix showed no multicolinearity between the independent variables.
The regression analysis is used to predict any causal relationship between the dependent and the independent variables. The regression results for the model are shown in table 3. The regression model is significant, as indicated by the "F" value of 20.76. Because the calculated t-values of the coefficients exceeds the critical tabular value of 1.96, the coefficient values are significantly different from zero at the 99% level and have significant power in explaining the variation in procurement spending per procurement employee (Y). About one third of the variation in Y is explained by the independent variables as indicated by the adjusted [R.sup.2] of 31%.
According to the results for the model, the greater the industry average annual spending on training per procurement employee, the larger the total procurement spending per procurement employee. For every $1,000 increase in average annual spending on training per procurement employee, total procurement spending per procurement employee rises by $11.80. This is consistent with the expectation that more training will enable a procurement employee to purchase more, resulting in greater efficiency and the need for fewer employees.
The larger the proportion of industry electronic data interchanges, the lower the procurement spending per procurement employee. For every 1% increase in percent of procurement spending via electronic data interchange, total procurement spending per procurement employee falls by $42.55. The assumption is that any additional EDI spending would occur through a procurement employee. Thus, the relationship should be positive if EDI spending is quicker and easier. Since it is negative, either EDI spending does not occur through a procurement employee (an unlikely prospect) or the EDI process is (at least for now) more complicated for procurement employees, takes longer, and results in less spending per employee.
It was expected that the use of electronic activities would improve procurement ability per procurement employee, since normally we would expect more electronic procurements to improve the procurement ability. The unexpected result may be explained by particular complications related to variations in electronic procurement.
The larger the proportion of industry procurement spending that occurs through strategic alliances, the larger the total procurement spending per procurement employee. For every 1% increase in industry procurement spending that occurs through strategic alliances, total procurement spending per procurement employee rises by $21.42. This is consistent with the expectation that the more dollars spent through strategic alliances will enable a procurement employee to purchase more, resulting in greater efficiency and a need for fewer employees. This is also an expected result indicating that the greater the strength of strategic alliances, the more efficient the supply chain.
This study supports the hypothesis that there is a relationship between the procurement spending per procurement employee and the average annual spending on training per procurement employee. It provides evidence that industry annual spending on training per procurement employee has a positive effect on total procurement spending per procurement employee: this is supply chain efficiency.
The training variable in this study does not identify the type of training, and thus training could vary according to the responding firm, affecting the results. In addition, the responses may include a type of routine training that is no longer as valuable as it once was or is no longer relevant for the specific kinds of purchasing.
This study supports the existence of a relationship between the procurement spending per procurement employee and the percent of procurement spending via Electronic Data Interchange (EDI). It is assumed that EDI spending is executed by a procurement employee. If EDI spending is quicker and easier when there is a larger percent of procurement spending via EDI, procurement spending per procurement employee could be expected to rise, resulting in a positive relationship. The results of this study provide evidence that a larger proportion of industry spending through electronic data interchanges has a negative effect on the procurement spending per procurement employee. The coefficient for percent of procurement spending via EDI would be negative if EDI spending does not occur through a procurement employee (unlikely) or if there is less spending per procurement employee when EDI is more prevalent. The latter would occur if the EDI spending process is more complicated for procurement employees, taking more time and resulting in less spending per procurement employee. Less spending per procurement employee requires more procurement employees to execute the same level of spending, resulting in reduced efficiency.
This study provides evidence that the larger the proportion of industry spending occurring through strategic alliances, the larger the procurement spending per procurement employee. Strategic alliances enable procurement employees to purchase more, requiring fewer employees to purchase the same volume, resulting in greater efficiency.
This study provides evidence that the larger the proportion of industry spending occurring through strategic alliances, the larger the procurement spending per procurement employee. Strategic alliances enable procurement employees to purchase more, requiring fewer employees to purchase the same volume, resulting in greater efficiency. This study has provided evidence of a relationship between three supply chain practices and supply chain efficiency. It suggests that the development and implementation of a supply chain practice should rely on a strategic planning process. Managers increasingly need to accept that "popular" activities and practices may not result in greater efficiency within their firm. When a particular supply chain practice shows a greater positive effect on supply chain efficiency, the results should be compared to those of another practice and additional resources committed to those practices resulting in the largest return. Supply chain managers can more effectively make a case for a greater share of corporate resources if they provide evidence that particular supply chain practices have been shown to enhance supply chain efficiency in their industry.
Adam, E.E., & Swamidass, P.M. (1989). Assessing operations management from a strategic prospective. Journal of Management, 15(2), 181-203.
Au, A.K.M., Altman, Y., & Roussel, J. (2008). Employee training needs and perceived value of training in the Pearl River Delta of China: A human capital development approach. Journal of European Industrial Training, 32(1), 19-31.
Barnes, D., Hinton, M., & Mieczkowska, S. (2003). Competitive advantage through e-operations, TQM & Business Excellence, 14, 659-75.
Bowersox, D.J., & Closs, D.J. (1996). Logistical Management: The Integrated Supply Chain Process. New York, NY: McGraw-Hill.
Boyer, K. K., & Olson, J. R. (2002). Drivers of internet purchasing success. Production and Operations Management, 11, 480-98.
Bubshait, A.A., & Faroog, G. (1999). Team building and project success. Cost Engineering, 41(7), 34-38.
Burke, K. (2005). The impact of firm size on internet use in small businesses. Electronic Markets, 15, 79-93.
Butler, T.W., & Leong, G.K. (2000). The impact of operations competitive priorities on hospital performance. Health Care Management, 3(3), 227-235.
Campbell, D., & Stanley, J. (1963). Experimental and Quasi-Experimental Designs for Research. Chicago, IL: Houghton-Mifflin.
CAPS (Center for Advancing Purchasing Studies) (various dates). Institute of Supply Chain Management. Retrieved November 07, 2007, from: http://www.capsresearch.org/
Carr, A.S., & Pearson, J. N. (1999). Strategically managed buyer-supplier relationships and performance outcomes. Journal of Operations Management, 17, 497-515.
Choi, T.Y., & Hartley, J. L. (1996). An exploration of supplier selection practices across the supply chain. Journal of Operations Management, 14 (4), 333-343.
Cooper, M. C., Ellram, L.M., Gardner, J.T., & Hanks, A.M. (1997). Meshing multiple Alliances. Journal of Business Logistics, 18(1), 67-89.
Craighead, C. W., Patterson, J. W., Roth, P. L., & Segars, A. H. (2006). Enabling the benefits of supply chain management systems: An empirical study of Electronic Data Interchange (EDI) in manufacturing. International Journal of Production Research, 44 (1), 135-157.
Creswell, J.W. (2003). Research Design: Qualitative, quantitative, and mixed methods approaches (2nd edition). Thousand Oaks, CA: Sage Publications.
de Koning, J. (1993). Evaluating training at the company level. International Journal of Manpower, 14(2/3), 85.
Dooley, R.S., & Fryxell, G.E. (1999). Attaining decision quality and commitment from dissent: The moderating effects of loyalty and competence in strategic decision-making teams. Academy of Management Journal, 42(4), 389-402.
Dyer, J.H., & Ouchi, W.G. (1993). Japanese-style partnerships; giving companies a competitive edge. Sloan Management Review, 53, 51-63.
Frohlich, M. T., & Westbrook, R. (2002). Demand chain management in manufacturing and services: Web-based integration, drivers and performance, Journal of Operations Management, 20, 729-45.
Gowen, C.R., & Tallon, W.J. (2003). Enhancing supply chain practices through human resource management. The Journal of Management Development, 22(1/2), 32-44.
Gunasekaran, A., & Ngai, E. (2004). Virtual supply chain management. International Journal of Production Planning and Control, 15, 584-595.
Handfield, R.B., & Bechtel, C. (2002). The role of trust and relationship structure in improving supply chain responsiveness. Industrial Marketing Management, 4(31), 367-382.
Hayes, R.H., & Wheelwright, S.C. (1984). Restoring our competitive edge: Competing through manufacturing. New York, NY: Wiley.
Houlihan, J.B. (1985). International supply chain management. International Journal of Physical Distribution and Management, 15, 22-38.
Johnson, M., & Whang, S. (2002). E-business and supply chain management: An overview and framework. Production & Operations Management, 11, 413-423.
Krause, D. R., & Ellram, L. M. (1997). Success factors in supplier development. International Journal of Physical Distribution & Logistics Management, 27(1), 39-52.
Lancioni, R. A., Smith, M. F., & Schau, H. J. (2003). Strategic internet application trends in supply chain management, Industrial Marketing Management, 32, 211-17.
Li, S., Ragu-Nathan, B., Ragu-Nathan, T.S., & Rao, S.S. (2006).The impact of supply chain management practices on competitive advantage and organizational performance. The International Journal of Management Science, 34,101-124.
Lummus, R. R., & Vokurka, R. J. (1999). Defining supply chain management: A historical perspective and practical guidelines. Industrial Management & Data Systems, 99(1), 11-17.
McGahan, A., & Porter, M.E. (1997). How much does industry matter, really? Strategic Management Journal, 18(Special Summer Issue), 15-30.
McKiernan, P. (1997). Strategy past; Strategy futures. Long Range Planning, 30, 690-708.
Porter, M.E. (1980). Competitive strategy: Techniques for analyzing industries and competitors. New York, NY: The Free Press.
Porter, M.E. (1985). Competitive advantage: Creating and sustaining superior performance. New York, NY: The Free Press.
Prahalad, C., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68 (3), 79-91.
Presutti, Jr., W. D. (2003). Supply management and e-procurement: Creating value added in the supply chain. Industrial Marketing Management, 32, 219-26.
Rumelt, R.P. (1991) How much does industry matter? Strategic Management Journal, 12(3), 167-185.
Senge, P. (1990). Building learning organizations. Sloan Management Review, 16(3), 48-56.
Sengupta, K., Heiser, D.R., & Cook, L.S. (2006). Manufacturing and service supply chain performance: A comparative analysis. Journal of Supply Chain Management, 42(4), 4-15.
Shaffer, K.J., & Dalton, M.M. (2012). Can adopting specific supply chain management practices improve supply chain efficiency? International Journal of Business, Marketing and Decision Sciences, 5(2).
Sieben, I. (2007). Does training trigger turnover--or not? Work, Employment & Society, London, 2(3), 397.
Skinner, W. (1969). Manufacturing: Missing link in corporate strategy. Harvard Business Review, 47(3), 136-146.
Soliman, K. S., & Janz, B. D. (2004). An exploratory study to identify the critical factors affecting the decision to establish internet-based inter-organizational information systems. Information & Management, 41, 697-706.
Spekman, R.E., Forbe, T.M., Isabella, L.A., & MacAvoy, T.C. (1998). Alliance management: A view from the past and a look to the future. Journal of Management Studies, 35(6), 747-772.
Spekman, R. E., Kamauff, J. W., & Myhr, N. (1998). An empirical investigation into supply chain management: A perspective on partnerships. Supply Chain Management, 3(2), 53-67.
Stonehouse, G., & Snowdon, B. (2007). Competitive advantage revisited: Michael Porter on strategy and competitiveness. Journal of Management Inquiry, 16(3), 256-273.
Stuart, F. I. (1997). Supply-chain strategy: Organizational influence through supplier alliances. British Journal of Management, 8(3), 223-236.
Tan, K.C. (2002). Supply chain management: Practices, concerns and performance issues. The Journal of Supply Chain Management, 38(1), 42-53.
Tan, K.C., Kannan, V. R., & Handfield, R.B. (1998). Supply chain management: Supplier performance and firm performance. International Journal of Purchasing and Materials Management, 34(3), 2-9.
Thomas, J. (1999). Why your supply chain doesn't work. Logistics Management and Distribution Report, 38(6), 42-44.
U.S. Census Bureau, (2008). Annual Survey of Manufacturers (ASM) Retrieved July 05, 2008 from: http://www.census.gov/mcd/asm-as1.html
Vonderembse, M.A., & Tracey, M. (1999). The impact of supplier selection criteria and supplier involvement on manufacturing performance. Journal of Supply Chain Management, 35(3), 33-39.
Walker, O.C., & Ruekert, R.W. (1987). Marketing's role in the implementation of business strategies: A critical review and conceptual framework. Journal of Marketing, 51(3), 55-33.
Ward, P.T., McCreery, J.K., Ritzman, L.P., & Sharma, D. (1998). Competitive priorities in operations management. Decision Sciences, 29(4), 1035-1046.
Zank, G. M., & Vokurka, R. J. (2003). The internet: Motivations, deterrents, and impact on supply chain relationships, SAM Advanced Management Journal, 68, 33-40.
Kathie J. Shaffer
Peggy M. Dalton
Frostburg State University
Kathie J. Shaffer is a tenured professor of accounting and Chair of the Department of Accounting in the College of Business at Frostburg State University of the University System of Maryland. Dr. Shaffer has a B.S. degree in accounting and MBA from FSU and a PhD in management (University of Maryland). She is a Certified Management Accountant (CMA) and is a consultant in the field of operations and supply chain management.
Peggy M. Dalton is professor emeritus of economics in the College of Business at Frostburg State University of the University System of Maryland. Dr. Dalton has a B.S. degree in Resource Economics (University of New Hampshire), an M.S. degree in Applied Economics (University of Minnesota), and a PhD in Economics (West Virginia University).
Table 1 Industries Surveyed in this Study 1. Aerospace/Defense 12. Machinery 23. Petroleum 2. Banking 13. Industrial 24. Pharmaceutical 3. Beverage Manufacturing 25. Restaurants--Leisure 4. Carbon Steel 14. Healthcare 26. Semiconductor 5. Chemical Products 27. Shipbuilding 6. Computer Hardware 15. Engineering/ 28. State/County 7. Computer Software Construction Governments 8. Diversified 16. Electronics 29. Steel Production Beverages and Foods 17. Electrical 30. Telecommunication 9. Diversified Computer Equipment Services Equipment & Services 18. Manufacturing 31. Textiles/Apparel 10. Diversified Foods 19. Metal and 32. Transportation 11. DOE Nnsa Mining Services Contractors 20. Mining 33. Utilities 21. Municipal Governments 22. Paper Source: CAPS (Center for Advancing Purchasing Studies) (various dates). Retrieved November 07, 2007, from: http://www.capsresearch.org/ Table 2 Descriptive Statistics from 2001-2007 over All Industries Total Average Percent of Percent of procurement annual total total spending per spending on procurement procurement procurement training per spending via spending via employee procurement e-activities strategic (Y) employee ([X.sub.2]) alliances Statistic (millions) ([X.sub.1]) ([X.sub.3]) Mean $20.20 $1,169.40 6.68% 17.29% Standard Error of the mean 1.1 52.8 0.005 0.009 Standard Error 13.0 607.0 0.058 0.103 Sample Var. 168.0 368393.9 0.003 0.011 Range $53.9 $2,854.0 24.09% 47.93% Minimum $4.0 $386.0 0.11% 0.00% Maximum $57.9 $3,240.0 24.20% 47.93% Count 132 (a) 132 132 132 Table 3 Regression Results Y--Procurement Spending per Procurement Employee Variable Coefficient t-value p-value value (standard error) Intercept 6.62500 2.514 0.01320000 (2.51000) Average annual spending on training per procurement employee 0.010800 ([X.sub.1]) (0.00156) 6.982 0.00001924 Percent of total procurement spending via -42.54600 e-activities ([X.sub.2]) (16.27000) -2.615 0.00999000 Percent of total procurement spending via strategic alliances 21.42000 ([X.sub.3]) (9.15500) 2.339 0.02086500 Note. n = 132; df= 128; Adjusted [R.sup.2] = 31%; F = 20.76
|Printer friendly Cite/link Email Feedback|
|Author:||Shaffer, Kathie J.; Dalton, Peggy M.|
|Publication:||International Journal of Business, Marketing, and Decision Sciences (IJBMDS)|
|Date:||Jun 22, 2014|
|Previous Article:||California proposition thirty seven: implications for genetically modified food labeling policy.|
|Next Article:||The moderating role of country institutional profile on the entrepreneurial orientation--performance relationships in the service industry.|