Investigating the decision criteria used in electronic components procurement

Industrial Marketing Management 33 (2004) 317 – 323

Investigating the decision criteria used in electronic components procurement Neeraj Bharadwaj* Marketing Department, McCombs School of Business, The University of Texas at Austin, 21st and Speedway, CBA 7.256, Campus Mailcode B6700, Austin, TX 78712-1176, USA Received 6 August 2002; received in revised form 23 April 2003; accepted 1 June 2003

Abstract Previous research has reported that the decision criteria used to evaluate suppliers differs by product category. Rather than investigating the ‘‘key buying criteria’’ across the entire gamut of products and services, this research takes a novel approach by investigating the evaluation criteria used in the procurement of component parts. The survey results suggest that the content and structure of the decision criteria used by business customers to assess their suppliers does not differ across an array of electronic components. The business implication is that business customers that formally track the performance of their suppliers along the critical evaluation criteria will be in a better position to gain a competitive advantage by effectively managing the inbound supply chain. D 2003 Elsevier Inc. All rights reserved. Keywords: Organizational buying behavior; Supplier selection; Procurement; Key buying criteria; Performance evaluation; Metrics

1. Introduction In light of the fact that purchasing is directly linked to overall organizational success (Carter & Narasimhan, 1996; Ellram, Zsidisin, Siferd, & Stanley, 2002; Goh, Lau, & Neo, 1999; Tan, Kannan, & Handfield, 1998), senior management directives pertaining to a firm’s procurement activity have become increasingly commonplace in today’s organization (Poirier & Bauer, 2001). Much of this attention is driven by the understanding that initiatives focusing on the inbound supply chain can assist the firm in reducing costs (Ojo & Lamb, 2001; Shirouzu, 2002), increasing velocity to market (Davis, Dibrell, & Janz, 2002; Griffin, 2002; Stalk, 1988; Suri, 1998), and enhancing the value proposition to the end user (Day, 1999; Magretta, 1998; Porter, 2001). Thus, previous writings have clearly articulated that attending to the organizational buying activity can provide a basis for securing a competitive advantage. In an attempt to harness the gains that attending to the inbound supply chain can yield, progressive buying organizations are systematically managing their supplier base by * Tel.: +1-512-471-8312; fax: +1-512-471-1034. E-mail address: [email protected] (N. Bharadwaj). 0019-8501/$ – see front matter D 2003 Elsevier Inc. All rights reserved. doi:10.1016/S0019-8501(03)00081-6

monitoring critical operational (task-related) metrics (Giunipero & Brewer, 1993). A recent study reports that 85% of the firms surveyed have implemented a formal monitoring system to track supplier performance so as to realize cost, time, and quality improvements (Trent & Monczka, 1998). The same study also mentions that 90% of the CEOs and presidents at these firms expressed interest in reviewing and evaluating purchasing performance measures on a regular basis. As such, the question has become one of identifying the metrics that a firm must track in order to realize the full range of benefits that can accrue from effectively managing its supplier portfolio. The supplier selection (or organizational buying) literature has long held that product quality, delivery, price, and service are the key attributes that are used to assess the performance capabilities of vendors (Dempsey, 1978; Dickson, 1966; Evans, 1981; Lehmann & O’Shaughnessy, 1974, 1982; Matthyssens & Faes, 1985; Wilson, 1994). This body of knowledge has readily established that the ‘‘key buying criteria’’ used by a business customer to evaluate a supplier will vary across product categories (e.g., the content and structure of the choice criteria utilized by firms to acquire forklifts will differ in relation to the factors that will influence the purchase of MROs). Whether the content and structure of the decision criteria used to evaluate a supplier

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hold within a given product category, however, remains largely unexplored. To this point, some academics have suggested that it may be necessary to develop a theory for each of the various product classes (Choffray & Lilien, 1978). Thus, the aim of this manuscript is to answer this call by investigating whether differences exist within the decision criteria used by manufacturers to evaluate suppliers from whom they purchase an array of component parts ranging from commodities (e.g., fasteners or capacitors) to highly customized inputs (e.g., printed circuit boards). In light of the possibility that the decision criteria used by business customers in evaluating their component parts’ suppliers may vary by industry (Bennion & Redmond, 1994; Giunipero & Brewer, 1993; Jackson, 1985; Oliver, 1997; Sharma & Achabal, 1982), it is necessary to select a homogenous setting so as to reduce the unnecessary noise that may arise from situational idiosyncrasies (Cook & Campbell, 1979). Since electronics manufacturers spend anywhere from 22% to 53% of their annual sales revenues on the procurement of goods and services from suppliers (Anderson, Chu, & Weitz, 1987; Killen & Kamauff, 1995), this effort seeks to advance a purchase evaluation theory for the procurement of component parts within this context.

2. Theoretical development Social exchange theory posits that a business customer is most likely to foster those exchange relations from which it derives the greatest benefits (Thibaut & Kelley, 1959). In commercial exchange relationships, this logic gets reified in the ‘‘key buying criteria’’ that manufacturers deploy in assessing their suppliers. The more optimally a vendor performs along these choice factors, the more likely it is to be retained by the business customer for future transactions (Anderson & Narus, 1984; Anderson & Narus, 1990; Dempsey, 1978; Wind, 1970). The supplier selection literature has traditionally held that quality, delivery, service, and price comprise the choice criteria utilized by business customers to evaluate their suppliers. As noted in one study, the importance of the respective decision criteria has changed over time (Wilson, 1994). While earlier studies reported that delivery and price were most important (Evans, 1981; Lehmann & O’Shaughnessy, 1974), later research found that quality had become most prominent (Lehmann & O’Shaughnessy, 1982; Wilson, 1994). A recent study reaffirms the diminishing importance of price in organizational buying decisions in relation to the other evaluation criteria (Simpson, Siguaw, & White, 2002) (please see Table 1). The supplier selection literature asserts that it is imperative to understand the relative importance of the choice criteria. Although Table 1 provides some directional information regarding the ranking of the choice criteria, the content and structure of the decision criteria may differ across industries (Choffray & Lilien, 1978). For instance, while price may be the most important criterion in industries

Table 1 Decision criteria across studies Study

Lehmann and O’Shaughnessy (1974) Evans (1981) Lehmann and O’Shaughnessy (1982) Wilson (1994)

Rank order of decision criteria 1

2

3

4

Delivery

Price

Quality

Service

Delivery Quality

Price Price

Quality Service

Service Delivery

Quality Service Rank: 1 = most important to 4 = least important

Price Delivery Table adapted from Wilson (1994)

in which the inputs secured are primarily commodities (e.g., the paint industry), product quality and on-time delivery may be more important in other industries (e.g., healthcare). Furthermore, the ranking can differ across product categories. As such, this effort seeks to develop a ranking of the ‘‘key buying criteria’’ utilized by electronics manufacturers in the procurement of component parts (i.e., finished or nearly finished, inputs that are ready for assembly into the manufacturer’s final product). In the ensuing discussion, a set of hypotheses advancing a theorized ranking for the ‘‘key buying criteria’’ is presented. The hypotheses are framed in light of the ability of each choice factor to assist the business customer to gain a competitive advantage through reducing costs, increasing velocity to market, and/or enhancing the value proposition to the end user. Subsequently, whether the ranking of the choice criteria differs between strategic, bigticket components (e.g., printed circuit boards) and smaller more commodity-like inputs (e.g., fasteners or capacitors) is also investigated. Below, the hypotheses are presented. In today’s highly competitive marketplace, companies must deliver goods with a salient advantage in order to drive consumer acceptance. Since the performance and functionality of the input secured from a vendor can impact the perception that the downstream customer possesses about the business customer’s goods (Deming, 1982, 1986; Juran, 1991), a vendor’s product quality should have great bearing on the business customer’s perception regarding the vendor’s operational performance. Indeed, it is widely accepted that superior inputs can enhance how the firm’s throughputs are perceived by end users (e.g., ‘‘Intel inside’’). Conversely, receiving subpar inputs from suppliers may interrupt production processes, introduce unnecessary costs to the value chain, and lead to warranty-related problems (Suri, 1998). Thus, it is expected that H1: A supplier’s product quality will have the greatest impact among the choice criteria. Delivery, which refers to both the supplier’s logistical capabilities as well as the critical activities and processes that it performs from the time that the input is (re)ordered until it arrives at the business customer’s facility (i.e., order fulfillment), can also influence a business customer’s costs,

N. Bharadwaj / Industrial Marketing Management 33 (2004) 317–323

velocity to market, and/or how its value proposition is perceived by the end user. Inaccurate, missed, and/or delayed deliveries can disrupt a business customer’s operational efficiency. In the event that this results in a stockout at the retail level, consumers may turn to competitive offerings instead of waiting. Conversely, prompt delivery of components by suppliers has the potential to drive end user demand for the business customer’s products as downstream consumers are continually looking for products with enhanced features and functionality (Lewis, 1995; Stalk, 1988). The supplier’s order fulfillment activities and processes can also influence costs and velocity to market. If, for instance, the condition of the products on arrival is suspect, then the business customer will incur increased inspection costs. This may require the business customer to carry greater levels of inventory, thereby increasing inventory carrying costs and the likelihood of potential losses from obsolescence and pilferage (Frazier, Spekman, & O’Neal, 1988). Thus, business models based on velocity to market and attention to the removal of non-value-added costs from the value chain, like that of Dell Computer, have tangibly demonstrated the benefits that can accrue from effectively attending to their supplier’s order fulfillment activities and processes (Magretta, 1998). It is, therefore, expected that H2: A supplier’s delivery will constitute the second most important choice criterion. Although earlier studies identified price as the most important factor driving certain purchases (Evans, 1981; Lehmann & O’Shaughnessy, 1974), recent research suggests that price has declined in its relative importance (Jackson, 1985; Wilson, 1994). In fact, one recent study reports that price is no longer the major factor driving procurement decisions as it found that only one fourth of all firms include price as part of their evaluation systems of suppliers (Simpson et al., 2002). Thus, it is predicted that H3: Price will be the penultimate choice criterion used by the business customer to evaluate a supplier. Lastly, postsales service is posited as having the least influence in relation to the other decision criteria. This is expected as this study focuses on assessing the evaluation criteria to be used by business customers in procuring items that end up as inputs into the organization’s finished goods. Regardless of whether it is a strategic component part or a smaller, more standardized item that is being acquired, the item must conform to strict manufacturing standards. Any postsales assistance required is to be considered an undesirable result of deviations from previously agreed upon tolerances. Thus, it is expected that H4: Postsales assistance will be perceived as the least important of the choice criterion. Component parts can range from standardized, commodity type inputs to customized, more strategic type of inputs. It was revealed through one field interview that purchasing

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managers sometimes utilize an ‘‘A’’ versus ‘‘C’’ product classification. Briefly, the classification of each procured input is determined by the percentage of annual material costs that it represents and is based on the Pareto Principle (Deger, 2000). Thus, the most expensive 20% of items that represent 80% of annual material cost are classified as ‘‘A’’ items. These include big-ticket inputs or an outsourced manufacturing subassembly such as a printed circuit board. The remaining 80% of parts that account for the remaining 20% of annual cost are labeled ‘‘C’’ items. These are smaller, more standardized acquisitions (e.g., capacitor or fasteners—screws, eyelets, or Velcro). It is expected that there will be no difference in the rank ordering of the ‘‘key buying criteria’’ as the component part secured, whether it be an ‘‘A’’ or a ‘‘C’’ item, becomes an integral part of the business customer’s finished product. It is imperative that the supplier not deviate from previously agreed upon tolerances so as not to adversely impact either the business customer’s operational efficiency or the value proposition as perceived by the end user. H5: The ranking of the key buying criteria utilized by the business customer will remain unchanged for ‘‘A’’ and ‘‘C’’ items.

3. Methodology A cross-sectional survey was deployed to investigate the preceding purchase evaluation theory and to investigate whether a difference exists in the decision criteria used by electronics manufacturers in procuring ‘‘A’’ versus ‘‘C’’ items. It was determined that firms in SIC codes 3571, 3625, 3632, 3633, 3634, 3651, and 3663 secure a variety of component parts and should comprise the sampling frame (Petska-Juliussen & Juliussen, 1996). Since purchasing agents have been identified as capable of providing accurate and reliable information in previous studies within the electronics industry (Pearson, Ellram, & Carter, 1966), a mailing list of individuals serving in this capacity was acquired from a commercial list broker. The information contained in the extant literature as well as the insight garnered from a series of field interviews provided a list of items that tap into quality, delivery, price, and service. After generating items from previous studies (Barry, Cavinato, Green, & Young, 1996; Dickson, 1966; Goodwin & Ball, 1999; Lehmann & O’Shaughnessy, 1974, 1982; Shapiro, Rangan, & Sviokla, 1992; Wilson, 1994; Wind, 1970), the entire literature-based list was reviewed with purchasing managers within the electronics industry. In several of the preliminary meetings, procurement professionals advised against using too lengthy a list of specific task-related outcomes and processes. This sentiment echoes research which has suggested that most buyers cannot simultaneously handle more than seven to nine factors in evaluating a purchase decision (Gustin,

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Table 2 Decision criteria and specific task-related factors germane to electronics components Decision criteria

Task-related outcomes and processes

Delivery/order fulfillment

1. The supplier’s order cycle time (i.e., lead time between ordering and delivery) 2. The supplier’s on-time delivery performance 3. The supplier’s ability to fill our emergency orders 4. The supplier’s accuracy in our filling orders 5. The supplier’s accuracy in billing and credit 6. The condition of supplier’s products on arrival (i.e., defect rates) 7. The supplier’s product quality (i.e., performance and functionality) 8. The supplier’s postsales assistance and support 9. The supplier’s ability and willingness to assist with the design process 10. Price of supplier’s products and services

Product quality Service

Price

Daugherty, & Ellinger, 1997; Miller, 1956). As such, the objective of the remaining field interviews was to reduce the list by eliminating redundant and/or irrelevant items. The resulting 10 items that appear in Table 2 were chosen as the rational factors that can tap into a business customer’s assessment of a vendor’s quality, delivery, price, and service, respectively. Approximating Dillman’s (1978) approach, a three-wave contacting scheme was used. Prior to commencing the study, half of the participants were apportioned to comment on an ‘‘A’’ item and the other half on a ‘‘C’’ item. Subsequently, a prescreening phone call was made to each potential participant. During the conversation, the individual was asked to identify a specific component that was available from at least three different suppliers. Once they had selected the product, they were asked to comment on one specific supplier from whom they had procured the item and with whom they had engaged in past transactions. For those participants who could not be reached after the third call, a message was left describing the study and informing them that they would be receiving a survey shortly. The second contact was a mailing that included a personalized cover letter on university letterhead, survey, and prepaid postage-paid envelope. The final contact was a post card that was sent one week later. It served as a thank you note to those who had already completed the survey and as a reminder to those who had not complied as of yet. For the total sampling frame, 204 verbally agreed to participate and messages were left for the 262 informants who could not be reached after the third attempt. Using those who verbally agreed to participate in the denominator, the 113 usable surveys that were received yields a response rate of 55.4%.

4. Results A central tenet of the supplier selection literature is that certain task-related performance attributes will be more important than others. Of the 10 task-related items that were

assessed on a seven-point Likert scale, the mean importance ratings for the individual items ranged from 6.51 for ‘‘product quality’’ (i.e., performance and functionality) to 4.50 for ‘‘ability and willingness to assist with the design process.’’ Following an approach utilized in a previous supplier selection study, these 10 items were mapped onto their respective ‘‘key buying criteria’’ and the respective group means were calculated (Lambert, Adams, & Emmelhainz, 1997). As apparent in Table 3, the following ranking resulted for the ‘‘key buying criteria’’ that business customers use to evaluate their suppliers: quality, delivery/order fulfillment, price, and service. Thus, the Waller – Duncan Multiple Comparison Test suggests that hypothesized ranking for the four criteria advanced in Hypothesis 1– 4 is supported. Having identified the ranking of the decision criteria, the next step is to determine whether a difference exists in the ranking of group means between the procurement of ‘‘A’’ items versus the smaller, more standardized ‘‘C’’ items. To

Table 3 Relative importance of the decision criteria Item rank

Attribute

Item mean

1

Supplier’s product quality (Group 1) Product quality 6.51

2 3 4 5 6 8

Supplier’s delivery/order fulfillment Condition of products on arrival On-time delivery performance Accuracy in filling orders Order cycle time Ability to fill emergency orders Accuracy in billing and credit

7

Price (Group 3) Price of products and services

9 10

S.D.

Group meana,b

0.77

6.51

(Group 2) 6.35 0.88 6.34 0.84 5.95 0.95 5.77 1.26 5.71 1.26 5.16 1.22

5.88

5.63

1.12

5.63

Supplier’s postsales service (Group 4) Postsales assistance and support 4.78 Ability and willingness to assist 4.50 with the design process

1.36 1.54

4.64

a ANOVA was used to test the following hypothesis: H0: group mean 1 = group mean 2 = group mean 3 = group mean 4; H1: any group mean is different. ANOVA suggests that there is a significant difference in the pairwise comparisons of the four group means, thereby allowing the null to be rejected ( F ratio = 70.871, P > .000). It should be noted, however, that a significant F test in an omnibus test such as ANOVA only allows one to infer that at least one of the pairwise differences is statistically significant. It is, however, not possible to ascertain which difference(s) across the group means is/are statistically significant. b In order to explore all possible pairs of group means for differences, the Waller – Duncan Multiple Comparison Test, an a posteriori contrast, is deployed. This test is more revealing as it allows one to explore the difference in each of the pairwise comparisons. As such, one can test the six combinations: group mean 1 = group mean 2; group mean 1 = group mean 3; group mean 1 = group mean 4; group mean 2 = group mean 3; group mean 2 = group mean 4; group mean 3 = group mean 4. The Waller – Duncan procedure suggests that at the a=.05 level, all possible pairs of group means are indeed different.

N. Bharadwaj / Industrial Marketing Management 33 (2004) 317–323 Table 4 Means of relative importance of the task-related outcomes and processes Attribute

Product type ‘‘A’’

‘‘C’’

Mean S.D. Rank Mean S.D. Rank 1. Order cycle time 2. On-time delivery performance 3. Ability to fill emergency orders 4. Accuracy in filling orders 5. Accuracy in billing and credit 6. Condition of products on arrival 7. Product quality 8. Ability and willingness to assist with the design process 9. Postsales assistance and support 10. Price of products and services Number of completed surveys received

5.87 6.36 5.75

1.30 0.90 1.36

5 3 7

5.70 6.35 5.67

1.19 0.79 1.20

5 2 6

6.00 5.11 6.47

1.00 1.12 0.70

4 8 2

5.89 5.23 6.21

0.94 1.34 1.03

4 8 3

6.53 4.42

0.75 1 1.51 10

6.51 4.56

0.80 1 1.58 10

4.62

1.50

9

4.93

1.24

9

5.77

1.12

6

5.49

1.10

7

n = 55

n = 58

this end, two-way ANOVA was deployed. Even though there were slight differences in the rank ordering of the 10 individual task-related factors (please see Table 4), there was no statistically significant difference found in the group means (i.e., the ranking remains consistent across components). As such, the results suggest that electronics firms do not use differing criteria in evaluating suppliers who provide a wide array of component parts, thereby offering support for Hypothesis 5.

5. Discussion and business implications The main aim of this research is to explore whether a difference exists in the decision criteria used by electronics manufacturers in procuring differing component parts. The results indicate that the content and structure of the decision criteria utilized to secure component parts is consistent across an array of component parts. While past research has established that the decision criteria differ across product categories (Evans, 1981; Lehmann & O’Shaughnessy, 1974, 1982), the theoretical contribution that this research makes to the supplier selection literature is that it suggests that differences do not exist within the buying criteria used to procure an array of electronic components. This effort sets the stage to carry out more rigorous empirical analysis of the nomological network in which the task-related performance construct is embedded. The first step would be to follow standard psychometric properties in order to develop a reliable and valid scale for task-related performance building upon the items offered here (Churchill, 1979; Gerbing & Anderson, 1988; Peter, 1981). Subsequently, the antecedent, outcome, as well as moderating conditions comprising the nomological network should be specified and tested empirically. One truly fertile area for future research

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would be to explore the extent to which relationship factors interact with rational purchase decision-making factors to influence supplier selection. Another would be to look at how the cost of doing business with a supplier (i.e., total cost of ownership as opposed to focusing solely price) can combine with task-related performance to yield customer loyalty (Ellram, 1995; Ellram et al., 2002; Simpson et al., 2002). Thus, a more holistic view that moves beyond a focus on rational attributes is the logical next step in this research agenda. In addition to the theoretical implications, the findings from this study have important managerial implications for both sides of the buyer – seller dyad. For business customers, the benefits associated with having a formal system in place to identify and continually measure supplier performance are five-fold. For one, these diagnostics offer buyers a tangible means by which to evaluate suppliers. In light of the heterogeneous capabilities of suppliers, the buying organization can objectively assess each supplier interface and detect when corrective action may be necessary. Second, the information can be used to derive baseline levels of acceptable supplier operational performance across all product categories. Being cognizant of these baseline levels for each critical metric can potentially escalate operational performance across the entire supplier portfolio. Third, the information captured can be used to identify ‘‘preferred’’ suppliers (Lewis, 1995). Given that ‘‘preferred suppliers’’ have graduated to that status through their exemplary efforts, more future business can be allocated to them. The implication is that less time and costs will be required to screen and develop new exchange partners. Fourth, tracking these metrics can provide the information necessary to prune underperforming vendors from the supplier base. Given that firms are trying to reduce the breadth of their supplier portfolio in an attempt to increase quality and reduce costs (Hiebeler, Kelley, & Ketteman, 1998; Ojo & Lamb, 2001), operational metrics provide the means to accomplishing that end. Lastly, firms are interested in being perceived as ‘‘fair exchange partners’’ or ‘‘good customers’’ by their suppliers (Goodwin & Ball, 1999). Promoting clearly stated metrics and basing volume allocation decisions on objective measures of operational performance rather than arbitrarily set standards can yield favorable reputational effects. In sum, the aforementioned benefits should provide business customers enough of an impetus to track the critical metrics so that quality, time, and cost improvements can be realized through world-class procurement practices. This research also has implications for the seller side of the dyad. For one, the organizational procurement literature has established that vendors should not only match their task-related performance with the levels desired by the customer, but also be cognizant of the criteria having the greatest influence on buyer decision making. Truly understanding the acceptable levels of operational performance along each task-related performance metric will provide the

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supplier the necessary insight to improve performance along the most desirable attributes, thereby providing the basis for gaining a competitive advantage over other vendors. Furthermore, it will prevent overprovision of unwanted goods and services (Anderson & Narus, 1995). Second, this research reinforces that an enterprise-wide effort is required to create and deliver value for business customers (Ellram et al., 2002; Shapiro, Rangan, & Sviokla, 1992). Indeed, personnel from all departments must attend to critical activities and processes from the time the order is initiated through postsales assistance. Lastly, customer relationship management (CRM) is a term that has entered the popular lexicon (Collins, 2001; Dyche, 2001; Peppers & Rogers, 2001). A central tenet of CRM is being information intensive about present and potential customers. This research offers insight into the task-related performance analytics that can be used to better understand customer requirements, and in turn, customize the value proposition so that more future business, and perhaps even ‘‘preferred supplier’’ status, can be achieved.

6. Conclusion Organizations rely on suppliers for a plethora of inputs. These suppliers can have a tremendous impact on the firm’s bottom line as significant resources are typically devoted to organizational procurement. Moreover, these suppliers can influence the perceptions that downstream consumers hold about the organization’s products as well as the velocity with which products reach the market. Thus, it has become widely accepted that world-class procurement practices can provide a basis for securing a competitive advantage. Lured by this promise, progressive buying organizations are formally monitoring the task-related performance of their entire supplier base. Even though past research reports that the decision criteria may vary across product categories and industries, whether they hold consistent within a product category remains largely unexplored. The results here suggest that the ranking of the decision criteria used by business customers to evaluate the performance capabilities of vendors remains consistent across a broad array of components. The business implication is that those firms that formally track the performance of their suppliers along the critical evaluation criteria will be in a better position to capture the full potential from their electronic components suppliers.

Acknowledgements The author wishes to thank the Institute for the Study of Business Markets for providing critical resources needed to carry out this research, as well as the editor, Peter LaPlaca, Elaine Allen, and the anonymous reviewers for their helpful and detailed suggestions.

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