Strategic Choice of Electronic Marketplace Functionalities: A Buyer-Supplier Relationship Perspective
A PhD student in the Management Science & Information Systems Area at the Michael G. DeGroote School of Business, McMaster University, Canada. Her research interests include business-to-business electronic commerce and Internet-based electronic marketplaces. She holds a BA in Economics from Wuhan University, China, and an MA in Economics from Queen's University, Canada
A professor emeritus in the DeGroote School of Business, McMaster University, Canada. He is also a special advisor to MeRC (McMaster eBusiness Research Center) and ORNEC (Ontario Research Network in Electronic Commerce). He is the former Director of MeRC and the former holder of the Wayne C. Fox Chair in Business Innovation. His research interests are in topics that relate to e-business, including business-to-business implementations, mobile commerce, intelligent agents, knowledge management, and the human-computer interface. He has published in a number of journals, including Internet Research, International Journal of Management Theory and Practice, IEEE Transactions on Systems, Man, and Cybernetics, International Journal of Human-Computer Studies, International Journal of Technology Management, and many others.
Address: DeGroote School of Business, McMaster University, Hamilton, ON L8S 4M4 Canada. Tel: 905-525-9140, ext. 26183.
Address: DeGroote School of Business, McMaster University, Hamilton, ON L8S 4M4 Canada. Tel: 905-525-9140, ext. 23944.
This paper explores the important factors affecting the choice of electronic marketplace (EM) functionalities. We propose that buyer-supplier relationship-related factors, such as transaction uncertainty, transaction specific investment, transaction frequency, complexity of product description, and non-contractible factors, can affect the choice of different EM functionalities. A case study method was employed to verify these propositions. We found that transaction frequency and non-contractible factors were two strong indicators of EM functionality choice, and transaction specific investment is a weak indicator. Depending on different types of transaction uncertainty, companies will choose different EM functionalities. Complexity of product description was low in all the cases we studied, and did not appear to affect functionality choice. An additional finding was that supplier power could influence a buyer's choice of different functionalities.
1 Business-to-business electronic marketplaces (EMs) are “open electronic platforms facilitating activities related to transactions and interactions between multiple companies” (Holzmuller & Schlechter 2002). EMs have progressed from the early days when they were solely used for aggregating buyers and sellers, and they now offer a wide variety of functionalities. The initial competitive functionalities offered by EMs, such as catalogue sourcing and auctions, are still available. But more and more EMs have begun to facilitate interaction and collaboration between companies. This has led to a new name, “collaboration electronic marketplace,” being adopted for such EMs (Christiaanse & Markus 2003). The dominant mode of business product exchange has traditionally tended to be more networked and collaboration-oriented. Even with the availability of EMs, which promise a market with more transparent information and lower search costs, companies were still not willing to give up their pre-existing long-term business relationships with trading partners. This explains why collaboration EMs have proliferated to the point where some EMs now support only collaborative business relationships.
The adoption of EMs is an urgent issue since most EMs are still struggling for liquidity. However, when a company chooses to join an EM, it is in fact choosing to use a specific service (functionality). If an EM only offers one functionality, a company chooses functionalities by choosing EMs. Dai and Kauffman (2002) suggested that, since EMs increasingly offer diverse functionalities, the choice of functionalities is a critical decision. “The fundamental issue here (in EMs) is to be able to tell when you will need exchanges and when you will need explicit channel coordination”.
Researchers have begun to examine the contingencies that could affect the choice of IT-supported market mechanisms. Chouldhury (1997) examined the role of uncertainty in the choice of inter-organizational systems (IOSs), and Mahadevan (2002) investigated complexity of product description and asset specificity in the choice of different market mechanisms. Garcia-Dastugue & Lambert (2003) suggested that the properties of product description complexity, asset specificity, transaction risk, operational performance risk, frequency of purchase, and item value in different Internet enabled coordination mechanisms. Mithas, Jones, and Mitchell (2003) surveyed the explanatory power of asset specificity and non-contractible factors in predicting a company's intention to use reverse auctions.
The impact of these contingencies is rooted in transaction cost theory (TCT), and they are frequently used to explain the optimal buyer-supplier relationship strategies that a company can choose. Thus, a buyer-supplier relationship perspective is very important in explaining a company's choice of different functionalities. Rational choice is also an important assumption for this research. Companies always choose functionalities that benefit them most. Despite the research that has appeared in the literature, we have found that announced conclusions were either without empirical data support (Garcia-Dastugue & Lambert, 2003), or contradicted each other (e.g., (Choudhury & Hartzel, 1998, Mahadevan, 2002, and Mithas, Jones, & Mitchell, 2003 on asset specificity), or considered only one EM mechanism (Mithas et al., 2003 on reverse auctions only and Choudhury, 1997 on product listing only) or one contingency (e.g., Choudhury, 1997 on transaction uncertainty only). This paper will explore a number of important contingencies underlying buyer-supplier relationships and will investigate their predictive power in a company's choice of EM functionalities. It is usual to assume that there are three kinds of EM: public, consortia-based and private EMs. We will focus on the first two types of EM in this paper. A case method is employed to verify the proposed constructs and their relationships.
Theoretical Background: Markets, Hierarchies and Network Organizations
The theoretical foundation of this research is transaction cost theory (TCT) and network organization theory. TCT helps to define the boundary between markets and hierarchies, which are two major governance structures of firms. A market is a means by which the exchange of goods and services takes place. In a perfect market, price is assumed to convey all the information necessary for a transaction, and the price mechanism is the most important instrument for coordinating and allocating information (Milgrom, 1992). A hierarchy is an internal organization or hierarchical relationship characterized by division of tasks, a pyramidal organizational structure, an authority mechanism, and limits to autonomy (Thompson, 1971).
According to TCT, firms choose either hierarchies or markets (often referred to as “make or buy” decisions) by comparing the transaction costs of employing either of these choices. Transaction cost usually includes the expense of searching for a trading partner, specifying the products to be traded, negotiating and fulfilling contracts, and handling problems with delivery, payment and quality control (Coase, 1991). Williamson (1975) suggested that transaction cost should also include intangible costs caused by bounded rationality of humans and trading partner opportunistic behavior.
When a firm calculates the transaction cost of employing different governance structures, it is more interested in knowing which conditions lead to lower costs. Williamson (1975; 1985; 1991) suggested three contingencies: transaction uncertainty, transaction-specific investments, and transaction frequency. Malone, Yates and Benjamin (1987) suggested that complexity of product description (the amount of information needed to specify the attributes of products) played a role in a firm's choice of governance structures. When a product is hard to describe, it is more easily acquired through hierarchies, due to the tighter communication structures in hierarchies. Such communication may even be eliminated when suppliers become familiar with buyers' product requirements.
However, the dichotomous classification of governance structure was criticized for its over-simplicity. Some researchers suggested that middle forms of organizations along the continuum of markets and hierarchies were more popular (Bakos & Brynjolfsson, 1993; Clemons, Reddi, & Row, 1993; Powell, 1990; Williamson, 1985). These middle forms of organizations are also called “network organizations,” and characterized by goal convergence, trust, and reciprocal interactions (Powell, 1990). One of the advantages of adopting network organizational structures is their ability to support non-contractible factors (Bakos & Brynjolfsson, 1993). Non-contractible factors, such as quality, trust, information sharing, responsiveness, and innovativeness are contingencies that cannot be specified in contracts. Non-contractible factors sometimes require trading partners to make relationship-specific investments. For buyers to access these non-contractible factors, they normally build trusted long-term relationships with their suppliers, to provide incentives to make the necessary investments.
Defining Buyer-Supplier Relationships
Buyer-supplier relationships are inter-organizational strategies employed by buyers and suppliers to exchange goods and services. Based on the literature review of governance structure, we classify buyer-supplier relationships as either short-term or long-term. Short-term relationships are adversarial and arms-length (MacDuffie & Helper, 2003). These relationships are characterized by price reduction, low relationship-specific investment, little trust and information sharing, and lack of commitment from both parties to the relationship. Long-term relationships are collaborative partnership-like relationships (MacDuffie & Helper, 2003). These relationships are usually characterized by resource dependency, much information sharing, high relationship-specific investments, and high trust from both parties (Buvik & Gronhaug, 2000; Cousins, 2002; Jap, 2001). If we describe them by the language of the literature, the characteristics of short-term relationships are closer to open markets, while long-term relationships tend to be better served by network organizations and hierarchies. In the purchasing environment, for example, short-term relationships are involved in one off purchasing and short-term contracts, and long-term relationships involve preferred suppliers, single source contracts, and other collaborative initiatives.
Functionalities of Electronic Marketplaces
Functionalities are the solutions that an EM operator offers to its clients in order to facilitate transactions and interactions between them. They are similar to market mechanisms in the wider business-to-business (B2B) e-commerce literature (Garcia-Dastugue & Lambert, 2003; Mahadevan, 2002), but are more detailed. For example, channel coordination is broken down into more detailed functionalities such as private catalogues, collaborative planning, forecasting and replenishment (CPFR), etc. in our paper. We classify EM functionalities as either market-oriented or collaboration-oriented, based on the buyer-supplier relationships they support (see Table 1).
Table 1. Functionalities of electronic marketplaces
1. Company directory 2. Public product catalogues 3. Product listing
9. Collaborative product development 10. Collaborative Planning, Forecasting and Replenishment (CPFR)
8. AeroXchange 9. WWRE
Market-oriented functionalities focus on creating a competitive market. These functionalities may include facilitating searches, making market information available to competitive buyers and sellers, helping contract negotiations, and providing pricing mechanisms. Such activities support arm-length and adversarial relationships between buyers and sellers.
There are two kinds of market-oriented functionalities: aggregation and market matching (Andrew, Blackburn, & Sirkin, 2000; Bakos 1998; Kerrigan, Roegner, Swinford, & Zawada, 2001). In aggregation, EMs support the collection of multiple buyers and suppliers into one online site, and provide product catalogues and search facilitation. Examples of such functionalities are company directories, product listings, and public product catalogues that can be accessed by all EM participants. Market matching functionalities help participants to locate appropriate trading partners (Bakos, 1998), and to negotiate contract terms such as prices. Compared with aggregation, market matching implies a more active role in EM operations. Applications that support market matching include auctions, RFx (requests for quote, requests for information, requests for bid, etc.), and real-time bid and ask (Andrew et al., 2000).
Collaboration-oriented functionalities support and streamline the business processes between business partners (Andrew et al., 2000; Phillips & Meeker, 2000). These functionalities facilitate collaborative long-term relationships, because streamlining business processes requires trust, investment, and commitment that are only available in long-term relationships.
There are two levels of collaboration-oriented functionalities: transactional level and strategic level (Phillips & Meeker, 2000). Transactional level collaboration functionalities focus on streamlining the order fulfillment process, such as order placement, order management, payment, and order tracking. This functionality is currently offered by most EMs, and is frequently seen in private catalogue and transaction facilitation (also described as “private aggregation” in Dai & Kauffman, 2000). Private catalogues differ from public product catalogues due to their customized pricing and access that is restricted to only a specific buyer (Arvin, Beall, Carter & Hoffman, 2002). This is always coupled with transaction facilitation to achieve operational efficiency. Through private catalogues, buyers pursue operational efficiency and reduced administrative costs, while forgoing the benefits of searching. But public catalogues can benefit users by facilitating search for lower prices or specific products among a larger pool of potential trading partners.
Strategic level collaboration functionalities facilitate collaborative initiatives between trading partners. Different industries have different collaboration needs, so the applications of such functionalities differ from one EM to another (Andrew et al., 2000; Phillips & Meeker 2000). For example, CPFR is offered by EMs in the retail industry to reduce inventories and out-of-stock risk; project management is offered in the construction industry to coordinate building activities; collaborative product development in the aerospace and defense industry facilitates the design of aircraft and parts. The detailed design of these applications depends on specific industries, and demands a high degree of domain expertise (Andrew et al., 2000; Arvin et al., 2002; Chow, Ghani, Miller, & Takeda, 2000; Phillips & Meeker 2000).
Market-oriented functionalities are increasingly seen as a necessary offering for EMs, while collaboration-oriented functionalities provide opportunities for EMs to gain competitive advantage (Andrew et al., 2000). Notice that there is no clear boundary between market-oriented and collaboration-oriented functionalities. For example, reverse auctions (market-oriented) can be used to negotiate long-term contracts (collaboration-oriented). This situation will be taken into account later in the paper.
We assume that companies that use long/short-term relationships will perceive collaboration/market-oriented functionalities to be compatible with their relationship strategy, respectively. Given this implication, it should be possible to predict when companies would choose market- or collaboration-oriented functionalities, since a company's choice of long/short-term relationships will very likely affect its adoption of different functionalities. Based on TCT and network organization theory, we propose that transaction uncertainty, transaction specific investment, transaction frequency, complexity of product description, and non-contractible factors will affect a company's choice of EM functionalities (Figure 1).
Uncertainty refers to a situation where a company is unable to specify in advance every contingency of a contract. Facing high uncertainty, a company will favor hierarchies because of their ability to adapt to the future business environment without opportunistic haggling from its trading partners. There is a controversy regarding the effects of transaction uncertainty on the adoption of EMs. Some researchers have suggested that products with highly variable demand and supply are especially suitable for market-oriented EMs, such as commodities, used products and AOG (Airplane on Ground) parts (Choudhury & Hartzel, 1998; Dai & Kauffman, 2000; Kaplan & Sawhney, 2000). However, according to TCT, when faced with highly variable demand, companies tend to develop long-term relationships with their business partners (Buvik and Gronhaug, 2000). By this logic, companies facing high transaction uncertainty will tend to choose collaboration-oriented functionalities.
A reasonable speculation is that some uncertainties lead to the use of market-oriented functionalities, and some uncertainties lead to the use of collaboration-oriented functionalities. Choudhury (1997) observed that there were three kinds of market uncertainties: technological uncertainty (low predictability of what products to purchase), demand uncertainty (low predictability of how many to order), and market variability (the rate of supplier and price change). If a company cannot predict what product it needs (for example, the company changes its product specification a lot and tends to buy a large range of products, with each in small volume), it tends to buy from several long-term suppliers that can cover the range of products that it normally needs. Based on these arguments, high technological uncertainty leads a company to choose collaboration-oriented functionalities. If a company cannot predict how many it is going to purchase, it tends to purchase from single source long-term suppliers, to get the benefit of rush orders or JIT (just-in-time) inventory fill. Demand uncertainty is also moderated by absolute order volume since, the bigger the volume, the worse the consequences of order fluctuation (such as stock-outs and excess inventories). When market variability is high, price and suppliers tend to change frequently. Short-term relationship strategies and market-oriented functionalities are usually employed to handle these uncertainties.
Williamson's TCT provides a potential theoretical justification for the arguments above, suggesting that uncertainty can be absorbed through long-term relationships only when they are available (Williamson, 1975). There are two situations where long-term relationships are not available. First, when a company cannot predict what it needs, it tends to buy from several long-term suppliers that can cover the range of products that it normally needs. But for products that long-term suppliers don't offer and that are only occasionally needed by the company, the company has to purchase from short-term suppliers. In the second situation, when market variability is high, there is no stable supplier set (for example, many companies can serve as possible occasional suppliers, as in the used vehicle parts market) and prices are highly volatile (each product price is negotiatiable). In this situation, the probability of long-term relationships is low since a buyer can not even specify in advance the supplier of this product and what the product price will be. EMs can help alleviate the problem of high market variability by setting prices and supporting the search for new suppliers/buyers. The foregoing discussion leads to Propositions 1a and 1b:
Proposition 1a: A company is more likely to choose market-oriented functionalities when it faces low transaction uncertainties, or when transaction uncertainty is high but no long-term relationships are available to absorb this uncertainty.
Proposition 1b: A company is more likely to choose collaboration-oriented functionalities when it faces high transaction uncertainties, and long-term relationships are available to absorb this uncertainty.
Transaction-specific investments refer to the transferability of assets that support a given transaction. A firm is highly asset specific if the input used by the firm cannot be used readily by other firms. Due to the low transferability of highly specific assets, the switching cost of the party making this transaction-specific investment is high. So the other party may exploit this high switching cost opportunistically if pure market coordination is employed. When transaction-specific investments are needed, parties to the transaction maintain long-term relationships for two reasons: to maintain incentives for the investment, and to guard against opportunistic behavior (Williamson, 1975). In this case, companies are more likely to be involved in collaboration-oriented functionalities (Mahadevan, 2002). This leads to:
Proposition 2: A company involved in relationships that require high transaction-specific investments tends to choose collaboration-oriented functionalities when adopting an EM. Otherwise, it will prefer using market-oriented functionalities.
If products are needed repetitively, using a sequence of discrete short-term contracts through market-oriented functionalities will result in high transaction costs, including frequent search and negotiation costs. So long-term contracts are likely to be preferred by companies in order to reduce the cost of frequent search and negotiation, thus reducing transaction costs and deriving volume discounts (Williamson, 1991). It is also a common practice for companies to routinize high volume purchases (Choudhury & Hartzel, 1998). Furthermore, high transaction frequency can justify the cost of building a specific governance structure (Williamson, 1985). This discussion on transaction frequency is summarized in Proposition 3:
Proposition 3: A company purchasing a product frequently will prefer using collaboration-oriented functionalities in an EM. Otherwise, it will prefer using market-oriented functionalities.
Complexity of Product Description
Complexity of product description refers to the amount of information required to specify the attributes of a product, and it is closely related to the describers' domain knowledge. For example, a machine that is hard to describe for an outsider may be very easy to understand and communicate by a person in the industry. In our discussion, complexity of product description is the product complexity perceived by a person in the industry. In market-oriented functionalities, product information needs to be communicated frequently to a large number of new partners, so product description needs to be simple (Kenjale & Phatak, 2001; Mahadevan, 2002). When product descriptions are complex, companies tend to procure through long-term relationships since the suppliers with long-term relationships already have a good understanding of the idiosyncrasy of the products under consideration, making communication much easier (Malone et al., 1987; Truong, Le, & Rao, 2002). The above association between the complexity of product description and EM functionalities is summarized in Proposition 4.
Proposition 4: Companies purchasing products with complex descriptions tend to choose collaboration-oriented functionalities. Otherwise, they will choose market-oriented functionalities.
Companies that value non-contractible factors, such as trust, quality, information sharing, supplier innovativeness and responsiveness, will prefer using collaboration-oriented functionalities with suppliers that can provide such factors. Mithas et al. (2003) found that non-contractible factors were more important than transaction-specific investments in explaining why companies tend not to like using reverse e-auctions, a market-oriented functionality. We propose:
Proposition 5: Companies for which non-contractible factors are important will prefer collaboration-oriented functionalities. Otherwise they will tend to choose market-oriented functionalities.
The case research method was used as a primary tool for examining constructs and propositions in this research. Case research is the most suitable method for new phenomena for which new theories need to be generated, or constructs need to be polished in a real life setting (Benbasat, Goldstein, & Mead, 1987; Eisenhardt, 1999; Lee, 1989; Miles & Huberman, 1994; Spencer, Ritchie, Lewis, & Dillon, 2003; Yin, 1994). EMs are relatively new and the services they provide continue to evolve, and they must be studied in a real inter-organizational setting, so a case study approach is suitable. A positivist philosophy was adopted for this study. This assumes that reality is objectively given and can be described by measurable properties that are independent of the observer (researcher) and his/her instruments (Benbasat & Zmud, 1999). Predefined constructs were used to guide our inquiries.
Five EMs in five industries were studied, and telephone interviews were the primary source of data collection. All five EMs are located in North America, and are successful EMs in the sense that all have received second round funding. 34 people were interviewed, including 5 EM operators, 16 buyers, and 13 suppliers. Interviewees selected were familiar with the use of the targeted EM, and buyer or supplier participants had used the EM of interest frequently.
A questionnaire consisting of semi-structured and structured parts was used to guide the inquiry. In the semi-structured part, participants were asked about their use of different functionalities, the products and relationships involved, and why they chose to use the functionalities or relationships. In the structured part of the questionnaire, participants were required to evaluate each construct identified in section 5 on a five point Likert scale. Table 2 provides an overview on how constructs were operationalized in the structured part of the questionnaire. Since it is self evident, Table 2 is not explained here. EM operators were not asked the structured questions, so there were 27 completed structured questionnaires. Each interview lasted 30-45 minutes. Two interviewers were present in each interview. Conversations were recorded for transcription purposes. A summary relating to each EM was e-mailed to the appropriate participants to check the validity of interpretation. Triangulation of qualitative and quantitative data and pattern matching was employed. Nvivo, a computer-aided qualitative text analysis software package, was used in data analysis (Miles & Huberman, 1994; Gibbs, 2002). The results of the data analysis follow.
The following presents an overview of the individual EMs, including industry setting, and functionalities and relationships involved.
EM A is a promotional products EM established by an influential promotional product association to support its supplier and distributor members in the promotional products industry. EM A aggregates supplier catalogues and makes them available to both distributors and end users. There are two layers of catalogues in EM A. One layer is the supplier-distributor catalogue, which is accessible only by distributors, and the other is the distributor-end user catalogue. Product pricing in the two layers is different, with wholesale pricing in the supplier-distributor catalogue and retail pricing in the distributor-end user catalogue. EM A catalogues support both long- and short-term relationships. These long- and short-term relationships are not managed by a control mechanism, but by voluntary behavior of distributors. When a distributor uses the EM A catalogue to search for new suppliers, it is obviously supporting potential short-term relationships. However, distributors do not always search for new products or suppliers. Most of the time what they want are digital pictures of products from known suppliers to show to their end-customers. In this way, EM A saves on production and mailing of catalogues, and allows distributors to have instant access to the catalogues online.
EM B is an online auction website for purchasing and selling used heavy construction equipment. The major functionality offered by EM B is anonymous forward auctions. Auctions are hosted every two weeks. Auction information is posted two weeks prior to the auction date, so that buyers can review equipment inspection reports and decide whether or not to bid. These guaranteed inspection reports are a major value-added service offered free by EM B to online buyers. They include detailed onsite inspection results by EM B inspectors. EM B takes the responsibility for the contents of the inspection reports. Most buyers and sellers welcome this inspection service. EM B operates as a pure competitive marketplace since it supports only spot purchases, and buyer-supplier relationships through this EM are one off relationships.
EM C was founded by several major medical-surgical suppliers to facilitate the purchase of healthcare supplies. The functionality offered by EM C is mainly private catalogues and transaction facilitation. These catalogues are not open sourcing catalogues but are mainly used to validate orders transmitted to suppliers. Suppliers have full control of their catalogues, and these are a private catalogue application because only contracted buyers are allowed to access them. Transaction facilitation consists of order placement, order acknowledgement, order tracking, invoicing and payment, etc., and also provides participants the option of integration and connectivity. In order to prepare participants for system connection, EM C helps suppliers to clean their data and standardize their catalogues, and helps hospitals to clean the item masters in their internal ERP (enterprise resource planning) systems. All EM C buyers that we interviewed pursue a long-term relationship strategy with suppliers, where long-term contracts normally lasting 3-5 years are negotiated offline.
EM D is a private company founded in mid-2000 by some large mining, mineral and metal companies. The products involved are mining supplies and services. EM D participants normally use two kinds of functionalities: private catalogue and transaction facilitation, and reverse auctions. Transaction facilitation is based on offline-negotiated contracts and mainly used to streamline the ordering process. Different levels of system integration and connectivity exist among participants. A companion component of transaction facilitation is that buyers and suppliers are usually involved in contractual long-term relationships. Some participants also used reverse auctions. We found that reverse auctions, unlike forward auctions, were being used to support both long- and short-term business partner relationships. The trend is toward more use of reverse auctions as a support for long-term relationships, since setting up reverse auctions is time consuming. If transaction volume is not high enough, neither EM operators nor buyers were interested in using reverse auctions.
EM E was established in 2000 and sponsored by several big retailers. This is a very successful EM in the retail industry, and offers a wide spectrum of services. We studied three major functionalities of EM E. The first is e-negotiation, including reverse auctions and RFP/RFQ (request for proposal or request for quote), CPFR, and collaborative product development. E-negotiations conducted through EM E are invitation-only, and EM E provides training to participants on how to use these tools. E-negotiation generally involves both long- and short-term relationships between buyers and suppliers. CPFR normally refers to a standard collaborative process for the retail industry advocated by the VICS (Voluntary Interindustry Commerce Standards) committee.1 However, in EM E, CPFR applications are customized to each participant, and some clients use only one component of CPFR such as forecasting or replenishment. CPFR involved top-tier suppliers and strategic long-term relationships between trading partners. The third functionality that EM E offers is collaborative product development. It is currently in use by a limited number of users. A supermarket retailer and its suppliers use it to exchange product development information on private label products, such as nutrition and label information. Collaborative product development is normally used by buyers and suppliers that have strategic long-term relationships.
A Continuum of Functionalities
We found that the functionalities provided by the five EMs were not dichotomous and exclusive categories of market-oriented and collaboration-oriented functionalities. The functionalities together form a continuum, with extremely market-oriented functionalities located at one end of the continuum, and pure collaboration-oriented functionalities located at the other end of the continuum. This matches well the continuum of governance structure with markets and hierarchies at the two extremes, as indicated in Figure 2.
The findings about the continuum of functionalities do not invalidate the propositions formulated above, which were based on a suggested dichotomy of functionality classifications. Market-oriented and collaboration-oriented functionalities are still valid classifications, and they are used as in Figure 2 to represent the location of functionalities on the continuum. Our propositions will be validated in the next section, using this continuum. At the same time, noticing that reverse auctions tend to be in the middle of the continuum, it is expected that this will be a transitional area for most relationship contingencies. Although RFP/Qs and collaborative product development were mentioned in Figure 2, they will not be included in the following analysis, due to limited participant usage.
Based on individual case description, we will focus on finding cross-case patterns and matching these patterns with our propositions in this section. The findings are summarized in Figure 3. In the figure, a contingency is summarized in a row, and each column indicates the functionality and the relationship it supports, which appear at the bottom of the figure. Since the functionalities are organized according to the combination of the detailed functionality and relationship they support, it is possible that one functionality can appear in more than one column (such as product catalogues in EM A), and two EMs in two different industries can appear in the same column. For example, both EMs D and E offer reverse auctions, and reverse auctions involve both long and short-term relationships, so the combination of reverse auctions and long-term relationships is explained in one column and the combination of reverse auctions and short-term relationships is explained in another. In each cell of Figure 3, the fractional number in the bracket is the number of cases reporting a high/low value/the total number of cases studied for each functionality. The exceptional cases are transaction uncertainty, transaction frequency and non-contractible factors. For transaction uncertainty, we provide a brief description of the uncertainty. For transaction frequency, we provide a brief description as well as a fractional number indicating the percentage of cases reporting such a high/low value. For non-contractible measures, we provide in the bracket the median value of the five items (see Table 2) used to gather data from interviewees on the level of non-contractible factors for each functionality, based on a five point Likert scale.
In each of the following sub-sections, we will explain the propositions according to where in the figure the functionality is located. If it is to the left of column 4, it represents more market-oriented functionalities, and if it is to the right of column 4, it represents more collaboration-oriented functionalities. Finally, column 4 includes reverse auctions with long-term relationships, which represent a transitional area where mixed responses can occur.
We examined three kinds of uncertainties for each functionality: Predictability of the products to purchase, predictability of how many to purchase (exaggerated by order quantities since the bigger the quantity, the worse the consequences of order fluctuation) and market variability (measured by the rate of price and supplier change, which are often seen in fragmented industries because they are more dynamic and less stable than concentrated industries). Row 2 of Figure 3 provides a comprehensive view of the transaction uncertainty involved in each functionality, derived from the more detailed view of Table 3.
Table 3. Transaction uncertainty in EMs
Predictability of what to buy
Predictability of how many to buy
Unpredictable (Products change from one customer to another)
Unpredictable (Depends on end users; order changes can be 50-60%)
Predictable (Can predict what machine they will buy)
Predictable (The number of machines they are going to buy is controlled by the budget)
Predictable (All normally used medical-surgical products)
Unpredictable (Daily or weekly prediction) (Fluctuates by numbers of incoming and outgoing patients) (Order size varies)
Prices and suppliers stable (Concentrated on supply side)
Predictable (Normally used mining supplies such as welding gases, industrial tools)
Unpredictable (Big variation)
Prices and suppliers stable (Fragmented on supply side)
Reverse auctions (Short-term)
Reverse auctions (Long-term)
Predictable (6 months)
Some predictable and some unpredictable
Prices and suppliers stable (Fragmented on supply side)
Most are predictable (Months-Years out) small order fluctuation, big size orders
Prices and suppliers stable (Slightly concentrated on supply side)
Predictable (Months-multiple years)
Less predictable, (Week- 3 months); huge order fluctuations (25%-300%); big order size
We found that market variability was low for most EMs except for EM B, which sells used heavy construction equipment. The price of used equipment changes from one machine to another, and the supplier set for used heavy construction equipment is not stable. Many companies, such as financial and construction companies, can temporarily serve as suppliers when they have used equipment to liquidate. Dealers also enter and exit this market frequently. Before dealers and end users actually see a used machine, they are not sure what the price will be and from whom they will buy. In the following we will focus on examining the uncertainty caused by the predictability of what and how many to buy.
To the left of column 4, the predictability of what and how many to buy is low except for the EM A product catalogue. In EM A, since each promotional product is custom made, the distributor cannot predict what artwork (e.g., logos) the end user may require. Sometimes, even clients are not sure about the artwork. They may ask for distributor suggestions, and then decide what to buy. This causes great uncertainty for distributors. At the same time, the size of orders fluctuates a lot from one order to the other, and they are “all over the place.”2 This further increases distributor uncertainty. Most of the time, distributors handle demand uncertainty by purchasing from long-term suppliers. When long-term suppliers do not offer the products, distributors purchase from short-term suppliers.
To the right of column 4, the predictability of what to buy is high but companies are uncertain of how many to buy. In EMs C and D transaction facilitation and EM E CPFR, the traded products are either consumables or retail products that are needed on a daily basis. The specifications of these products are set in advance, but the quantities fluctuate according to current needs, production schedules, and seasonality. The high demand for these products also intensifies order fluctuation.
In column 4, when reverse auctions are used to negotiate long-term contracts with suppliers in EMs D and E, in most situations, buyers can predict what and how many they are going to need at least six months out. “In most of the buyers that we dealt with, they pretty much know twelve months out, now its time to buy this, now its time to buy that, and this is when I do this kind of item.” Only one buyer who dealt through EM D suggested that some products were predictable and some were not predictable.
According to Proposition 1, we should see in Figure 3 low transaction uncertainty3 to the left of column 4 and high transaction uncertainty to the right of column 4. Since the trend in Figure 3 matches Propositions 1a and 1b well, this leads to the conclusions that a company is more likely to use market-oriented functionalities when it faces low transaction uncertainty (columns 1 and 3), or when transaction uncertainty is high but no long-term relationships are available to absorb this uncertainty (column 2). In contrast, a company is more likely to adopt collaboration-oriented functionalities when it faces high transaction uncertainty, and long-term relationships are available to absorb this uncertainty (columns 5, 6, and 7).
Proposition 2 indicates that collaboration-oriented functionalities are more likely than market-oriented functionalities to involve transaction specific investments. From row 3 of Figure 3 we see such a pattern with the exception of EM A product catalogues.
In EM A, no participating companies reported transaction-specific investments in long-term relationships with their trading partners. Although promotional products are customized to each order, supplier production is mass customized so that every distributor can access it without supplier-specific investments. This property applied between trading partners with both long- (column 5) and short-term (column 2) relationships.
The data from other EMs matches our propositions well. First, to the left of column 4, when forward auctions (EM B) and reverse auctions are used to support short-term relationships, there is no specific investment made. Especially for EM B forward auctions, buyers and sellers do not necessarily know each other when purchasing online, so of course no specific investment is made.
To the right of column 4, all the participants observed transaction-specific investments of some kind, including proprietary knowledge about suppliers, supplier-specific information system investments, specific production equipment, specific human resources, warehouse investments, and the resources needed to set up CPFR initiatives. “We brought in people to specifically work with them through EM D to make this happen.”“This particular customer is what we call an anchor customer. That is, we have a location in that city because this customer is there… If that customer wasn't there, we probably wouldn't be located there….”
For column 4 reverse auctions, we found mixed evidence of both high and low specific investments. Specific investments in the reverse auction-long-term relationship combination were high, since five out of seven cases reported such investments as warehouses, information systems, specific knowledge, and special production capacity. Among these, four cases were investments made by suppliers. We therefore believe that suppliers seem to be at a greater disadvantage in reverse auctions than normally considered. Reverse auctions not only reduce supplier margins, but also appear to make suppliers even more “captive” to the relationships.
Examining the functionalities across the different columns of row 3 in Figure 3, we see that there is an approximate association between functionalities and transaction-specific investments except for the product catalogues in EM A. Therefore, proposition 2 appears to be confirmed. A company involved in relationships that require high transaction-specific investments (columns 5 and 7) tends to use EM collaboration-oriented functionalities. Otherwise, it tends to adopt market-oriented functionalities (columns 1, 2, and 3).
Row 4 of Figure 3 demonstrates an overview of the entire transaction frequency picture. Transaction frequencies tend to be higher in collaboration-oriented functionalities (columns 5, 6, and 7) than market-oriented functionalities (columns 1, 2, and 3).
To the left of column 4, EM A distributors order from short-term trading partners infrequently when those products are not available from their long-term suppliers. For EM B forward auctions for used heavy equipment, and EM D reverse auctions supporting short-term relationships, both involve one off purchases. Thus the transaction frequency is low.
For row 4 functionalities to the right of column 4, all involve high transaction frequencies. In EM A, the incentive for distributors to purchase from long-term suppliers frequently is to obtain volume discounts. Products are ordered daily or weekly through the transaction facilitation functionality of EMs C and D. One EM C participant called these products “high volume movers.” There are three reasons why such “high volume movers” use transaction facilitation and long-term relationships: (1) This avoids time consuming and frequent negotiations, and saves staff time for more productive work; (2) It consolidates transactions to fewer strategic suppliers; (3) It motivates buyers to follow company purchasing policy and reduce maverick purchases. In CPFR, as conducted through EM E, products involved are either branded products or promotional products. These are high demand consumer products, so they need to be re-ordered frequently.
As for reverse auctions used to support long-term relationships (column 4), we found extreme mixed evidence for transaction frequencies. On one hand, as a buyer commented, “the more we're using them on a daily basis, the easier it is for us to be able to roll it into reverse auctions because we've got bigger volumes associated with it.” On the other hand, some buyers were testing most of the product lines to see if they were suitable for reverse auctions. For them, “everything is possible in reverse auctions,” and the transaction frequency ranged from very low to very high.
Proposition 3 is therefore confirmed, with the conclusion that transaction frequency is a strong indicator of a company's choice of collaboration vs. market-oriented functionalities. Reverse auctions used to manage long-term relationships seem to serve as a transitional area between market-oriented and collaboration-oriented functionalities, in terms of transaction frequency.
Complexity of Product Description
Proposition 4 suggests that products with simple descriptions are more likely to be transacted through market-oriented functionalities, and products with complex descriptions are more likely to be transacted through collaboration-oriented functionalities. Unfortunately, no such pattern was found in the data analysis, since all the functionalities involved products that were standard and easy to describe (row 5 of Figure 3).
The following products were traded through the five EMs: (1) EM A promotional products. Although promotional products tend to be highly customized, the base products advertised are quite standard and easy to describe. (2) EM B used heavy construction equipment. These items are complex from the average consumer's point of view, but they are standard and easy to describe for dealers and other people in this industry. (3) Medical-surgical products in EM C transaction facilitation, welding gases and mining supplies in EM D transaction facilitation, and packaged consumer goods in EM E. Most are standardized and easily to describe.
A few non-standardized products were also traded: (1) In EMs C and D transaction facilitation functionalities, two suppliers offered nonstandard capital goods, normally perceived to be hard to describe. However, suppliers suggested that complex products were not suitable for transaction facilitation functionalities. (2) In EMs D and E reverse auctions, both easy-to-describe and complicated products were involved, such as store construction contracts and employee compensation insurance. But most of the products tended to be simple and standardized and, according to interviewee comments, more complicated products do not lend themselves to reverse auctions as much as easy-to-describe products.
From the general overview of row 5 in Figure 3, the complexity of product description was found to be low in most cases. Proposition 4 about the complexity of product description could therefore not be confirmed. It seems that easy-to-describe products are more suitable for both market-oriented and collaboration-oriented functionalities than are complicated products.
From row 6 of Figure 3, we can see that there is a difference in the level of non-contractible factors, such as trust, quality, information sharing, supplier innovativeness, and supplier responsiveness, between collaboration-oriented and market-oriented functionalities.
To the left of column 4, in EM A product catalogues and EM D reverse auctions supporting short-term relationships, and EM B forward auctions, the level of non-contractible factors is low. One exception is that buyers or sellers working with EM B value quality and supplier responsiveness. In the used heavy construction equipment market, quality is very important for safety and construction delay reasons. However, in EM B, equipment quality is controlled by inspections or onsite checks, not a specific governance structure such as long-term relationships. Suppliers were reported to be responsive to buyer requirements. A preliminary explanation is that in a competitive business environment, where the buyers have more and more power, suppliers are more responsive to customer requirements due to competitive pressures.
Moving to the right of column 4, in EM A product catalogues, suppliers valued non-contractible factors for reasons of trust, assured quality, favours for rush orders, and ease of getting credit. For EM C transaction facilitation, (1) mutual trust and level of information sharing between these business partners are high due to the high transaction volume involved and the use of zero inventory practice; (2) Quality is very important for hospitals since “hospitals are not dealing with products, but patients.” The ordering of low quality or legally unproved products could lead to severe consequences; (3) New medical tools and medicines are introduced frequently due to advances in the medical field (an average of every 18 months). Supplier innovativeness is important to hospitals in order to serve their patients better; (4) Sharing information and synergies with suppliers was important, especially for research-oriented hospitals.
EM E CPFR is used only when the business partners have trusting relationships. Participating suppliers are usually innovative and responsive to buyer requirements, and they supply higher quality products to these buyers. Information sharing is intense in CPFR since it is the basic requirement of CPFR.
In column 4, the highly ranked non-contractible factors were counter-intuitive for reverse auctions used to support long-term relationships, since reverse auctions are often treated as a tool that causes distrust and disincentive between buyers and sellers. The following are some explanations. First, trust and quality is important to buyers, since reverse auctions are often used to buy “quite important things.” Second, suppliers become more flexible and innovative, not because of greater incentives in strategic long-term relationships, but because of competitive pressure and the hope of doing more business with the buyers. In some reverse auctions, buyers took into account the disincentives to suppliers in making their decisions. Buyers seemed to take measures to avoid disincentive problems such as: (1) doing invitation-only reverse auctions; (2) offering longer-term contracts; (3) in evaluating the bids, considering factors other than just pricing.
Considering the pattern shown by row 6 of Figure 3 for non-contractible factors, it is clear that the level of non-contractible factors differs between market-oriented and collaboration-oriented functionalities. The conclusion is, in agreement with Proposition 5, that companies valuing non-contractible factors tend to use collaboration-oriented functionalities. Otherwise, they tend to choose market-oriented functionalities.
Our first finding is that EM functionalities cannot be classified as dichotomous or exclusive categories. They should be treated as being positioned on a continuum between market-oriented and collaboration-oriented functionalities. When a functionality is located closer to the market-oriented extreme, it has a more competitive element to it. An EM, and even a functionality, can support a continuum of relationships. For example, many researchers treat reverse auctions as a pure market-oriented functionality (Mithas et al., 2003), but this research suggests it is a hybrid functionality with elements of both competition and collaboration. Jap (2003) also recognized the role of reverse auctions in supporting long-term relationships. Public product catalogues, such as those appearing in EM A, support more than short-term relationships and search. This finding is also somewhat different from the literature, since the aggregation of many product catalogues is considered to be a reflection of increased market efficiency (Anonymous, 2000; Bakos, 1998).
The case analysis confirmed Proposition 1a and 1b about transaction uncertainty, Proposition 2 about transaction specific investment, and Proposition 3 about transaction frequency. However, the complexity of product description proposition (Proposition 4) was not confirmed. It seems that simple products tend to be transacted in all the functionalities we studied, instead of just market-oriented functionalities. RFP and product co-development are two functionalities that tend to involve complex products. These functionalities appeared frequently, but were not studied, due to the lack of usage among participants. Our disconfirmation of Proposition 4 does not agree with some of the literature such as Mahadevan (2002), who argued that complex products tended to be traded in collaboration-oriented functionalities and simple products tended to be traded in market-oriented functionalities. But our outcome is in accordance with (Garcia-Dastugue & Lambert, 2003) who argued that closed auctions (similar to RFP) involved complex products, and most other functionalities only dealt with simple products.
Non-contractible factors, such as trust, information sharing, quality, supplier responsiveness and innovativeness, were confirmed as strong indicators of which functionalities to choose (Proposition 5). This finding is in accordance with Bakos and Brynjolfsson (1993), but differs from Mithas et al. (2003). Mithas et al. studied the explanation power of asset specificity and non-contractible factors in the choice of using or not using reverse auctions, and concluded, “even after controlling for asset specificity, buyers prefer to avoid reverse auctions if they value supplier investments in non-contractible factors such as quality, supplier innovation, information sharing, trust and flexibility.” However, this study sometimes showed that, even if buyers valued non-contractible factors, they still used reverse auctions. This discrepancy can be explained by:
(1) Reverse auctions are a new type of tool that buyers are in the process of testing. Most users were among the first movers in using reverse auctions, and they could be overly optimistic about the value of non-contractible factors in their relationships with suppliers.
(2) Some buyers may attempt to use reverse auctions due to their benefit of price reduction, even if they value non-contractible factors.
(3) Some buyers appear to be taking cautious measures to control the incentive aspects of reverse auctions, such as providing longer-term contracts and considering factors other than price. As a result, most of the time, incumbent suppliers win the contracts.
(4) Competitive elements are seen more and more to be introduced in the long-term relationships in EMs. Even in CPFR, some buyers introduce competitive bidding for product slots in collaboration with strategic suppliers (mentioned as “direction of auction” by one participant). Reverse auctions can be viewed as a technique used by buyers, both to apply competitive pressure and to nurture long-term relationships, in the purchase of important products. In this study, we have seen that, because of the competitive pressure on suppliers participating reverse auctions, they may have to provide non-contractible benefits to buyers, as well as transaction-specific investment.
Another conclusion from this study, in accordance with Mithas et al. (2003), is that non-contractible factors are stronger indicators of the functionality choice than asset specificity. This conclusion arises from the transaction specificity proposition (Proposition 3) that was confirmed with less confidence.
Supplier Power in the Strategic Choice of Different Functionalities
The data analysis also revealed that supplier power played a role in buyer choice of functionalities. For all the participants studied, supplier power comes from two aspects: brand image and the supplier's volume of sales to the buyer (Porter & Millar, 1985). For example, in CPFR, brand image is a major consideration of buyers with whom to implement CPFR, because branded suppliers are important to competitive advantage. However, in reverse auctions, buyers always appear to choose those suppliers that can be replaced easily without significant loss.
“It's a bit different from that, the online negotiation (auctions) is usually used for things where you've got a couple of different possibilities for who you're going to buy it from. Whereas the more CPFR-like applications are entirely focused on branded goods.”“Ordinarily a big driver is how much of my business is with this supplier, and how important is this supplier to my performance in this category. So there's a revenue number that starts it out, and then within that, the retailer will usually look at how well I collaborate with this supplier today.”
Power is the political aspect of buyer-supplier relationships. Benson (1975) and Reve and Stern (1979) suggested that buyer-supplier relationships have two aspects, economic and political. TCT theory focuses on economic efficiency comparisons, and the political aspect refers to the power and cooperative/conflicting atmosphere among trading partners. Power is recognized as an important factor that affects the adoption of IOSs (interorganizational information systems), such as EMs. The effect of buyer power on EM adoption is not discussed in this paper, since buyer power has more effect on the adoption of an EM than on the strategic choice of the different functionalities, the focus of this paper. Supplier power tends to affect buyer choice of which functionality a buyer would prefer. In fact, supplier power has also been related to some transaction cost-related research, such as Lieberman (1991), Murray, Kotabe, and Wildt (1995), Kraut, Steinfield, Chan, Butler, and Hoag (1998), and Iskandar, Kurokawa, and LeBlanc (2001). Since supplier power is a newly found construct in this research, future research should consider including it as a formal contingency that affects buyer choice of EM functionalities.
Conclusions and Future Research
This research has offered an overview of the strategic choice of different EM functionalities, from the buyer-supplier perspective. We found that transaction frequency and non-contractible factors were strong indictors of which functionalities to choose. As far as transaction uncertainty is involved, firms need to discriminate among the kinds of uncertainty that lead to the choice of market-oriented/collaboration-oriented functionalities. However, the degree of complexity in product description does not appear to affect a firm's choice of functionalities. On average, both simple and complex products are traded through EMs, but simple products are traded in much higher volume than complex products. Some specific functionalities, such as RFP/Q and product co-development, can handle complex products better than other functionalities.
In our research, we noticed that reverse auctions were being used more and more to support long-term relationships (where transaction-specific investments and non-contractible factors are high), and some collaborative functionalities, such as CPFR, can involve competition. This offers some future research opportunities, since reverse auctions are a new type of tool and many users are still experimenting with it. Some possible research questions are “Can reverse auctions support long-term relationships well?” and “In what circumstance can reverse auctions perform well in the support of long-term relationships?” Also, due to the “direction of auctions” in using CPFR, “Does the use of EMs impact market structure by favouring markets instead of hierarchies?” Due to the limited scope of this research and the limitation of case methods, we could not answer these questions, but they are future research topics of interest.
Italicized non-bold text in this section indicates comments from interviewees.
An exception would be the unavailability of the long-term relationships.
Content within brackets in this row is a brief description of transaction uncertainty.
Content within brackets in this row is the number of cases reporting a high/low value/total cases studied. The same notation applies for complexity of product description.
Content within brackets in this row is a brief description of the transaction frequency (the number of cases reporting a high/low value/total cases studied).
Content within brackets in this row is the median value of the five items (see Table 2) used to measure the level of non-contractible factors for each functionality, based on a five point Likert Scale. Because all EM A participants reported their usage to support long-term buyer-supplier relationships in the structured questionnaire, the median value for EM A product catalogues-short-term relationships combination is not available.
Participants were first asked to identify a specific trading partner they dealt through this EM, and all the questionnaire items were related to online transactions with this specific trading partner.