Mapping the relationships among product complexity, information technology, and transaction governance structure.

ABSTRACT

Transaction governance structure (TGS) mediates exchanges of goods or services between businesses. In recent years, we have observed broad shifts of TGS such as a large-scale integration among banks, security firms, and insurance companies and a continuous migration toward market TGS in the computer industry. To understand the underlying factors associated with TGS shifts is of central significance in management, economics, and governmental policy.

In this paper, we develop the construct of product complexity based on the theory of complexity (Simon, 1962) and the concept of modularity (Baldwin & Clark, 1997; Sanchez, 2000). We propose that product complexity is a primary factor in shaping TGS and that information technology has a moderating effect.

1. INTRODUCTION

Transaction governance structure (TGS) mediates exchanges of goods or services between businesses. In recent years, we have observed broad shifts of TGS such as a large-scale integration among banks, security firms, and insurance companies (Hess & Kemerer, 1994; Pinckney, 2000) and a continuous migration toward market TGS in the computer industry (Langlois & Robertson, 1992). Some firms move away from end-to-end integration to focus on a segment of the market, while others use enterprise-to-enterprise e-commerce architecture to collaborate in the design, manufacture, and delivery of products across different industry segments. In addition to integration and disintegration, the Internet disintermediates supply chains by eliminating middle layers and reintermediates them by creating new intermediaries. For instance, Yahoo! and Expedia.com are types of intermediaries that could not have existed before the time of the Internet (Wyckoff & Colecchia, 1999).

Confronted with broad shifts of TGS and challenged by the new environment, researchers and practitioners are raising questions. Why are TGS changes in different directions? What are the influential factors associated with these changes? Answers to these questions are of central significance to organizational theorists, economists, sociologists, and others concerned with the structure of society and the functioning of economic systems. A significant amount of research has been directed toward predicting shifts in TGS; however, the discussions are inconclusive, and the predictions are contradictory (Clemens, Reddi, & Row, 1993; Malone, Yates, & Benjamin, 1987).

2. LITERATURE REVIEW

A distinction between organizing mechanisms and institutions has to be made before addressing different theoretical approaches. Hierarchy and the price system are two mechanisms for organizing transactions within certain types of institutions. Market and hierarchy are two types of institutions that use one or both of these mechanisms. In this paper, we focus on market and hierarchy as institutions and refer an institution's use of market and hierarchy as TGS.

Traditional transaction cost theory classifies TGS into market and hierarchy (Coase, 1937; Williamson, 1979). A selection of TGS is based on comparisons of costs between market and hierarchy. Market transaction costs are incurred because of opportunism in the market and limitations of decisionmakers in solving complex problems and processing information. Hierarchy transaction costs are based on agency costs associated with controlling, monitoring, and coordinating agents' activities within a transactional hierarchy. In turn, it is argued that the attributes of a transaction (i.e., asset specificity, frequency, and uncertainty) determine the nature of costs and the choice of TGS. Generally, when the asset specificity of a transaction is low, market TGS is more economical. When the asset specificity is high, hierarchy has the advantage of lower governance costs. A significant amount of research has produced results consistent with transaction cost theory (Walker & Poppo, 1991).

Recent studies (Malone et al., 1987; Clemons et al., 1993) have expanded the traditional dichotomy into a continuum with market and hierarchy as extreme points and a wide spectrum of cooperative relationships in the middle. The focus of these studies has been on the shifts of TGS along the continuum toward market or toward hierarchy. One school of thought develops that TGSs are "shifting toward the market" because markets are more communication intensive than hierarchies, and markets benefit more from communication cost reductions. The net result is a shift toward market TGS as information technology (IT) advances (Malone et al., 1987).

Another research stream predicts that TGSs will "move to the middle"--a) away from a vertical integration to a higher degree of outsourcing and, at the same time, (b) away from impersonal market relations toward cooperative partnerships (Clemons et al., 1993). It is argued that hierarchy TGSs benefit from IT facilitating explicit coordination and providing more effective monitoring and incentive systems. Firms are likely to maintain a few close cooperative relationships to prevent opportunism and to improve the quality of supplies.

Complementary to transaction cost theory, institutional theory explains human behavior such as opportunism from a social point of view. It states that human behavior is influenced by socially constructed norms and rules of acceptable conduct. The driving force behind organizational action is a desire to achieve a fit with the organization's normative context (Martinez & Dacin, 1999). Institutional theory emphasizes norm and trust in shaping TGS. Neither perspective has the capacity to provide a full explanation of the TGS shift. The complementary nature of the two theories enables us to identify the conditions in which they operate with the greatest resonance. In our case, we predominantly rely on transaction cost theory.

3. OUR CONTRIBUTIONS AND APPROACH

After reviewing the previous studies, we believe that we can contribute toward a better understanding of TGS in the following areas.

3.1 Product Approach

Although industries, markets, and TGSs are designed around producing, trading, and distributing products, little or no attention has been paid to the properties of the products in association with TGS. A major concern of previous analysts has been on transaction process properties (costs, norm, trust, asset specificity) in determining the selection of TGS (Martinez & Dacin, 1999; Ouchi, 1980; Langlois & Robertson, 1992; Walker & Poppo, 1991). The focus of this study is on product properties, specifically, the product's complexity in relation to TGS. The concept of product complexity can be applied to both product and service.

3.2 Extension from Previous Studies

Malone et al. (1987) developed the concept of product description complexity. They stated that products with complex descriptions of product features were likely to be associated with hierarchies due to communication costs. Their analysis has two shortcomings. First, the domain of a transaction process is narrowly focused at the point of exchange. Secondly, product descriptions cannot sufficiently surrogate information exchange during a transaction process. In this study, we define transaction process as having six stages from product identification to after-sale services. We also extend the domain of information beyond product descriptions to include product information and process information. These extensions should increase the effectiveness of our research model in capturing influential effects on TGS.

3.3 Theory Building

Rapid IT developments challenge researchers and management with new concepts, e.g., electronic markets, electronic hierarchy, and e-commerce. They need new theories to help them to explain the new phenomena and to manage transactions in the new environment. The primary contributions of this study are (a) construct development--identifying and defining the salient dimensions of product complexity; (b) theory building--providing a framework to map the relationships among product complexity; (c) TGS; and (d) IT.

3.4 Information Approach

The prominent choice among independent variables in previous studies has been cost. A cost approach can be problematic because market and hierarchy are associated with different types of costs. If a specific type of cost is chosen, the conclusion on the shifts of TGS can be biased toward market or hierarchy. For example, emphasizing IT's influence on economies of scale may favor a conclusion of shifting toward market; while stressing IT's role in reducing monitoring costs may support a prediction of moving toward hierarchy.

IT might reduce costs through facilitating information processing, storage, and distribution. We argue that high information intensity might be a necessary condition for IT to have any significant effect on cost reduction. In other words, information intensity might be an antecedent variable to the various cost reductions, which in turn shift TGS. in contrast to the cost approach, we take an information approach in defining product complexity by using information intensity as one of the subdimensions. The information approach may be able to reconcile some of the discrepancies among the previous studies and to reach a better understanding of the shifts in TGS.

4. DEVELOPMENT OF THE CONSTRUCTS

This section presents the theoretical foundation and definition of each construct in the research model.

4.1 Product Complexity

We develop the concept of product complexity based on the theory of complexity (Simon, 1962). In developing his theory, Simon identified some common properties of complex systems such as hierarchy, interaction, and embedded coordination. We will define the construct of product complexity based on these three common properties of complex systems.

Hierarchy is a common property of complex systems regardless of the specific content or type of system (social, biological, or mechanical). A hierarchical system is composed of subsystems that, in turn, have their own subsystems. According to Simon (1962), a high level of hierarchy decreases the complexity of a system and facilitates the growth of the system. In his words, "hierarchic systems will evolve far more quickly than non-hierarchic systems of comparable size," (Simon, 1962).

The second property of complex systems is interactions within and among subsystems. The nature of interactions among the subsystems determines the properties of system at an aggregated level. Similarly, the level of complexity of the interactions among subsystems defines the level of complexity of the whole system.

The third property of complex systems is embedded coordination, which means that interactions within a subsystem are confined. For instance, in a hierarchical organization, intradepartmental interactions are confined and interdepartmental interactions are weak but not negligible. A high level of embedded coordination decreases the level of complexity of a system.

The construct of product complexity is defined based on the three properties of complex systems identified by Simon. We use product modularity to capture the concepts of hierarchy and embedded coordination and use information intensity to surrogate the properties of interaction. Figure 1 illustrates the dimensions and scales of product complexity.

[FIGURE 1 OMITTED]

Product modularity is defined in terms of product hierarchy and embedded coordination. A high level of modularity has a high level of hierarchy and embedded coordination. Product modularity is negatively correlated with product complexity, i.e., high modularity is associated with low product complexity.

Information intensity has two categories--product information intensity and process information intensity. High information intensity is associated with a high level of product complexity. In the following sections, we will discuss the theoretical foundation and definition of each construct.

4.2 Product Modularity

Schilling (2000) defines modularity as the degree to which a system's components can be separated and recombined without losing the synergy, functionality, or performance of the total system. He argues that a system might migrate along the continuum of modularity toward increasing modularity or integration. Baldwin and Clark (1997) provide a more operational definition of modularity, i.e., independently designed and manufactured components fit together into a complex functioning product.

Sanchez (2000) develops the association between modularity and structure. He argues that to a significant extent, product designs constrain feasible choices of organizational structure. A product's modular structure leads to modular organization designs and modular supply chain structures (Sanchez, 2000). Parallel to product decomposition in modularization, the processes of manufacturing, trading, and distributing can also be decomposed into loosely coupled modular activities. We draw upon these literatures to develop the concept of product modularity and its association with TGS.

We define product modularity in terms of degree of product hierarchy and degree of embedded coordination. The degree of hierarchy is the degree to which a product can be decomposed into a hierarchy of components with little loss of functionality to the overall product. The degree of embedded coordination is the degree to which the coordination within a component is confined, and the interactions among the components are limited but not negligible. High modularity is associated with low product complexity.

Product hierarchy is achieved by decomposing a product into subsystems. An automobile, for example, has a hierarchy of interrelated subsystems such as a cooling system, a brake system, a steering system, etc. A cooling system, in turn, has its own subsystems such as a water pump, a radiator, and a temperature-control system.

Embedded coordination is achieved by designs of component interfaces. Interfaces standardize and minimize interactions between components, so that a modification in one component does not require modifications in others as long as the modification remains within the range of interface specification. For instance, a PCI (peripheral component interconnection) slot is a standard interface for installing a peripheral board in a personal computer (PC). A modem manufacturer can change the design of a modem board as long as it conforms to PCI interface specifications. Four variations in the combinations of product hierarchy and embedded coordination are illustrated in Table 1.

Both PCs (Cell 11) and automobiles (Cell 21) have high levels of modularity. PCs maintain standard component interfaces. Components, such as the mouse, modem, or disk drive, can be manufactured by multiple manufacturers as long as the components conform to interface specifications. In the case of automobiles, interfaces vary depending on vehicle model, make, and year. Most automobile parts are not interchangeable except tires.

Electrical wiring of a house (Cell 12) is typically an integrated design with customized wiring in each room. The distinctions of interfaces between wiring are unidentifiable. An example of an integrated design with a standardized interface is the stacked modular complex building called "Habitat 67" in Montreal, Canada (Cell 21). The building is assembled from prefabricated concrete building modules, ingeniously stacked in varying combinations to give privacy and view to each unit.

4.3 Information Intensity

4.3.1 Interaction and information. In Simon's (1962) theory of complexity, interaction is a common property of complex systems. A system can be mechanical or social, thus interaction can be mechanical, biological, or social. This study focuses on social interaction. In communication theory, interaction is a reciprocal or mutual influence in an intra--or interpersonal form. In social studies, interaction refers to "people doing things together or with respect to one another with accompanying action, communication, and thought processes" (Strauss & Corbin, 1990, p.158).

Information exchange may be a necessary, but not a sufficient, condition for interaction. For interaction to occur, information exchange must be followed by an increase in awareness of a situation, a change in psychological state, a decision, or an action (Mortenson, 1972). However, information exchange is a fundamental process in interaction. In this study, we use information intensity to surrogate interaction intensity. We define and measure information intensity with two subdimensions--product information intensity and process information intensity.

4.3.2 Product information. Most products consist of both physical and information components. A physical component is any tangible material of which a product is made. Some information goods (e.g., on-line newspapers) have few or no physical components, while some physical goods (e.g., coal or other commodities) have limited information components. Information components can be further classified into content information and product information.

Physical component and content information will not be investigated in this study. In defining product complexity, we only consider product information.

We adopt Porter and Millar's (1985) definition of product information and Malone et al.'s (1987) definition of product description to explain the concept of product information. We define product information as the information that specifies the product's characteristics, use, and service and support. Product characteristic information specifies the attributes of a product and enables potential buyers to make purchasing decisions. Product use information specifies the uses of a product. Product service information specifies the service and support of a product.

A product with high product information requires a large quantity of information in selling, has many alternative uses, requires buyer training and after-sale service and support, and requires substantial information processing and learning to understand its operation. These products are usually nonstandardized and innovative or are sold to buyers with high information-intense businesses.

4.3.3 Process information. A process is a specific ordering of work activities across time and place, with a beginning, an end, and clearly identified inputs and outputs (Davenport, 1993). Palmer and Griffith (1998) define process information in the context of a value-added chain. They conceptualize a value-added chain as connected links, which coordinate production, marketing, delivery, and service activities among suppliers, vendors, and customers. Each link has information and physical components. The information component is the process information that is captured, analyzed, and disseminated to perform linking activities.

Transaction activities occur across multiple stages. The various stages of transaction processes have been identified in the literature and classified into six major categories: (a) identification, (b) selection, (c) negotiation, (d) execution, (e) authentication, and (f) after-sale services (Choudhury, Hartzel, & Konsynski, 1998).

Drawing upon this literature, we define process information as the information generated and consumed in monitoring, coordinating, and integrating the processes of identification, selection, negotiation, execution, authentication, and after-sale services in a transaction. High process information exists when a large number of suppliers or customers is involved; a product line has many distinct varieties and is composed of many parts; a large number of steps is involved in a manufacturing process; a long cycle time occurs between the initial order and the delivered product; and a product requires frequent redesign or modification or a process involves customer participation. Table 2 presents a typology of products based on product information and process information.

4.3.4 Information intensity. In defining information intensity, Glazer (1991) first measures the value of information in the context of an entire value-added chain and then derives information intensity from normalizing the value of information by either the revenues of the firm or the total assets of the firm. To obtain Glazer's information intensity, one has to assess the dollar value of information, which may prove difficult. To make it easier to operationalize the construct, we define information intensity in terms of the amount and richness of the information.

The amount of information is partly associated with the degree of uncertainty. From the transmission perspective in communication research, information is measured in terms of the reduction in uncertainty or the changes in an individual's degree of belief (Shannon, 1949). From an organizational point of view, Galbraith's position (1977) is that uncertainty is the absence of information, and uncertainty is the difference between the amount of information required to perform a task and the amount of information already possessed by the organization. However, Fox (1983) argues against correlating uncertainty with amount of information. His argument is that a piece of information may increase uncertainty if the information is conflicting. These approaches, however, can potentially be reconciled.

Daft and Lengel (1986), in developing the concept of richness of information in addition to amount of information, argue that richness of information reduces equivocality. Equivocality occurs when multiple and conflicting interpretations of a situation exist. Rich information gives multiple cues and immediate feedbacks and provides a capacity to process complex, subjective messages.

Drawing upon these distinctions, we define information intensity in terms of amount and richness of information. The amount of information is the quantity and frequency of information generation and dissipation. The richness of information is the ability of information to change understanding within a time interval. It can be measured by the number of cues, channels utilized, personalization, language variety, and capacity of immediate feedback. The concept of information intensity applies to both product information and process information. Each type of information shall take its own measurement in information intensity. Table 3 presents a typology of products based on information intensity and modularity.

4.4 Information Technology

The presence of IT can be measured at different levels such as the technical level, the semantic level, and the effectiveness level. The literature identifies six levels. These levels are system quality, information quality, usage, user satisfaction, individual impact, and organizational impact (DeLone & McLean 1992). At the technical level, we define IT as a technology that facilitates information processing, storage, and communication (Yates & Benjamin, 1991). To measure the presence of IT, we measure IT usage, which is defined as the IT application within an organization's operational and strategic activities. More specifically, IT usage involves the extent to which IT takes the form of cost reduction, management support, strategic planning, and competitive thrust applications (Boynton, Zmud, 8, Jacobs 1994).

4.5 Transaction Governance Structure

TGS is a mechanism that mediates exchanges of goods or services between business entities. Four key dimensions of TGS have been identified--ownership, number of suppliers, length and completeness of contracts, and explicit coordination (Clemons et al., 1993; Klein, Crawford, & Alchian, 1978; Treleven & Schweikhart, 1988; Williamson, 1979).

Ownership refers to the formal right to control a firm and to appropriate the firm's profits. Instead of explicitly specifying a list of individual rights over an asset, we use residual right to define ownership of an asset. Residual right is the right to control all aspects of an asset that have not been explicitly given away by contract (Grossman & Hart 1986). Ownership can be gained through purchasing of residual rights. A firm may purchase its supplier, thereby remove the residual rights of control from the owner of the supplying company. Residual right can be gained or lost through mergers, joint ventures, spin-offs, or outsourcing. A high level of ownership is associated with a high level of hierarchy TGS.

The number of suppliers is the number of firms that supply one type of product or service. Decisions regarding the number of suppliers can have a significant impact on the degree of collaboration with suppliers and the level of competition among suppliers. A small number of suppliers provides a sense of security to suppliers. It encourages suppliers to invest capital and human assets into the transaction relationship. A general view is that firms seek a balance between the level of competition among suppliers to achieve economic efficiency and the level of cooperation with suppliers to control the reliability and quality of supplies. The number of suppliers is used as an indicator for level of market orientation of the TGS. The large number of supplier is associated with high level of market TGS. The logic is that when many suppliers are small in relation to the demand of the buyer, no one can "fix the price" or to disengage the market price mechanism (Case & Fair, 2001).

Another dimension of TGS is the length and the completeness of contracts. A complete and enforceable contract is difficult to write, especially when the nature of a transaction becomes complicated. A long and incomplete contract is associated with uncertainty and is likely to be fulfilled under a hierarchical structure such as with an employment contract. A short and complete transaction contract is likely to be carried out in a market, for instance, buying and selling food and clothing commodities.

Explicit coordination involves negotiation and two-way communication between parties to achieve integration among economic activities that are not jointly owned and to address issues that cannot be managed through independent actions or implicit coordination. Implicit coordination occurs when firms' behaviors become patterned, predictable, and matched with expectation or behavior of others. Therefore, communication or explicit attempts to coordinate those behaviors become unnecessary (Galbraith, 1977). A high level of explicit coordination is associated with a high degree of hierarchy.

5. PROPOSED THEORETICAL FRAMEWORK

5.1 Relationship Between Product Complexity and TGS

We propose that product complexity is an influential factor in selecting an appropriate TGS, and that IT has a moderating effect. The propositions regarding relationship between product complexity and TGS are:

1. If a product has a low level of product complexity (low information intensity and high product modularity), then TGS of the product is likely to be more market-oriented.

2. If a product has a high level of product complexity (high degree of information intensity and low product modularity), then TGS of the product is likely to be more hierarchy-oriented.

For Proposition 1, our argument is that low product complexity is associated with relatively high modularity and low information intensity. High product modularity encourages autonomous innovation and decentralized manufacturing in a market-oriented environment. Market relies on price mechanisms to balance supply and demand and to coordinate transaction activities (Case & Fair, 2002). Such mechanisms may not be sufficient to generate and dissipate intensive information among market players, thus market may be suitable for mediating products with low information intensity.

For Proposition 2, our argument is that hierarchical TGS provides a capacity for processing rich information and an environment for collaborations among the partners to deliver integrated products across multiple segments. Hierarchy TGS may be suitable for handling transactions of complex products, which have high information intensity and low product modularity.

5.2 Moderating Effect of IT on TGS

In studying IT, the technological imperative approach views the external forces, such as IT, as causes of organizational change and sought IT-induced centralization or decentralization of organizational structure. The findings are contradictory in both centralization and decentralization authorities (Klatzky 1970; Whisler 1970, Stewart 1971, Foster & Flynn 1984). The studies of IT investment have also failed to provide evidence indicating that IT investment generates positive financial returns (Weill 1992, Brynjolfsson & Hitt 1996).

Different from the imperative approach, we evaluate IT's impact on TGS from a contingency perspective (Robey 1977, Tushman & Nadler 1978). We develop that IT will not transform TGS in one direction or another; rather IT is flexible enough to implement either market or hierarchy depending on the particular industry's contingencies. Like a catalysis process whereby the rate of a particular chemical reaction is hastened, sometimes enormously so, by the presence of a catalyst, the process of shifting TGS may also be accelerated by the presence of IT. However, the primary reaction is between product complexity and TGS. IT acts as the catalyst and has a moderating effect on TGS shifts.

IT catalyzes the shifts of TGS toward market in some cases and accelerates movements toward hierarchy TGS in others. For example, IT facilitates the process of identifying and selecting flights and promotes the transition of travel services from travel agent-based to Internet-based. On the other hand, IT supports integrated product designs and facilitates delivery of complete solutions to customers. For instance, checking service is no longer limited to check processing, but now include a package of services including ATM, debit and credit card services, and automatic debits and credits from utility companies and employers. Internet technology has enabled a world of change in the financial services industry. With the integration from retail financial services to wholesale and commercial markets, IT is making it easier to deliver services as well as reducing the cost of providing them. Regarding the IT moderating effect, we propose that IT has a moderating effect on TGS, i.e., IT can potentially facilitate the process of shifting TGS toward market or toward hierarchy if the contingency exists for the primary reaction between product complexity and TGS. The primary reaction determines if a shift will occur and in which direction.

We have constructed and defined the independent variable (product complexity), moderating variable (IT), and dependent variable (governance structure) and have integrated them into the research model. Figure 2 shows the overall research model.

[FIGURE 2 OMITTED]

6. CONCLUSION

As stated in the beginning, researchers and management are confronted with broad shifts of TGS and are challenged by new concepts such as electronic markets, electronic hierarchy, and e-commerce. In an effort to gain a better understanding of the behavior of economic systems in this new environment, we have developed the construct of product complexity and proposed a framework for selecting TGS based on product complexity and for predicting shifts of TGS based on the combination effect of IT and product complexity.

The proposed framework may open a new area of research. Future research efforts can be directed toward distinguishing the characteristics between e-commerce TGS and traditional TGS and in determining what types of products are suitable to be distributed in electronic markets and what types of products are suitable to be mediated in traditional markets.

More focused studies may be conducted in important industries such as automobile manufacturing. Since the designs of automobiles have become progressively modular, TGS among suppliers of automobile parts and assemblies should have shifted toward market. The same shift should be observed in the PC industry.

It might be strategically important for manufacturers to design products with different degrees of product complexity. Automakers may want to decrease product complexity of certain parts (such as the alternator, bearings, etc.) to take the advantage of market specialization and production efficiency. On the other hand, automakers may want to increase the product complexity of engines or to increase the levels of integration in the overall designs of vehicles. Product complexity may reinforce the deployment of hierarchy TGS and maintain automakers' market share.

A design of a product, a selection of TGS, and fitness between product complexity and TGS may be critical for the success of an organization and for the effectiveness of government agencies in creating policies providing infrastructures for industries to manufacture products and provide services.

TABLE 1.
VARIATIONS IN PRODUCT MODULARITY

Embedded coordination   Product Hierarch
                        Modular design      Integrated design
Standardized interface  C11 IBM computers   C12 Stacked modular
                                            complex building
Customized interface    C21 Automobiles     C22 Electrical wiring of a
                                            house

TABLE 2. TYPOLOGY OF PRODUCTS IN TERMS OF PRODUCT INFORMATION AND
PROCESS INFORMATION

Process       Product Information
Information   High                 Low
High          Banking services     Petroleum, steel
Low           Technical know-how   Paper clips

TABLE 3. TYPOLOGY OF PRODUCTS IN TERMS OF INFORMATION INTENSITY AND
PRODUCT MODULARITY

Product      Information   Intensity
Modularity   High          Low
High         Automobile    PCs
Low          Petroleum     Paper clips

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Aimao Zhang, Georgia Southern University

Arlyn Melcher, Southern Illinois University

Ling Li, Old Dominion University

8. AUTHOR PROFILES

Dr. Aimao Zhang earned her Ph.D. at Southern Illinois University in Carbondale, IL. Currently, she is an assistant professor of information systems at Georgia Southern University. She has broad interests in teaching and research. Her publications include book chapters, papers in refereed journals, and national conferences.

Dr. Arlyn Melcher earned his Ph.D. at the University of Chicago in Chicago, IL. Currently, He is professor of management at Southern Illinois University. Publications include four books on organizational theory, articles on leadership, organization analysis, strategy formulation, production and theory building methodology. He holds membership in the Network Register. International Directory of Business and Management Scholars and Research.

Dr. Ling Li has her Ph.D. in Business Administration, major in production and operations management from the Ohio State University. Currently, she is an assistant professor of information systems and decision sciences at Old Dominion University. She is a Certified Fellow in Production and Inventory Management (CFPIM) by American Production and Inventory Control Society (APICS). Dr. Li's research interests include supply chain management, Enterprise Resource Planning, the impact and application of information system on operations management, E-business, knowledge-based system, production planning and control, and health service management.