Using Collaboration to Improve Supply Chain Profitability

David Hakanson

6310 N Camden Ave Apt BKansas City, MO 64151

(816) 804-6108

University of Missouri, Kansas City

djhdc1@umkc.edu

David Hakanson is currently an MBA student at the University of Missouri, Kansas City.

Kansas City, Missouri ChapterFull-Time Graduate

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Using Collaboration to Improve Supply Chain Profitability

E-business has advanced supply chain management to a new level of efficiency

and responsiveness. Even greater improvements are possible through implementation of

e-business systems with collaborative environments including information sharing,

intelligent agents and demo models. Such improvements can dramatically increase supply

chain member profitability and return on investment.

I. INTRODUCTION

E-business has revolutionized global competition. For example, the use of e-

business in supply chain management can dramatically reduce lead times; reductions

from 16 weeks to only a few days are not uncommon. Also, stock-outs can be minimized

while companies are able to reduce safety stock inventory. The result is a supply chain

that is both efficient and responsive, one that reduces cost while improving quality and

value for the customer. E-business in simple terms is the ability for separate links of the

supply chain to communicate electronically. This use of the Internet in a business setting

improves value for both consumer and business. Consumers can use e-commerce to

communicate directly with retailers on the Internet. The result is the ability of consumers

to research, shop, and purchase products without leaving their offices or living rooms. E-

business allows information to be shared more effectively and is used by companies to

improve the overall supply chain, thereby lowering costs while increasing both profits

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and return on investment (ROI). The supply chain used in many industries includes a

supplier, manufacturer, distributor, retailer and customer, as shown in Figure 1.

E-business is not new but has recently become increasingly more important as

electronically enabled global competition drives companies to cut costs and response

times to become more competitive. In fact, supply chain management software is

expected to be the fastest growing e-business software market in 2004 (1). The growth of

uncoordinated e-business solutions by members of a supply often yield suboptimal,

overall effectiveness of the supply chain. For example, companies within a supply chain

may not use the same e-business software therefore adding confusion and the possibility

of integration problems. Several different factors can affect the effectiveness of the

supply chain. The most important of these factors is e-business communication and

collaboration between members of the supply chain.

A supply chain model based on collaboration can help firms achieve increased

profitability. A few steps should be taken to fully realize the value of a collaborative

supply chain. The most important factor in solving supply chain ineffectiveness is a

strong collaborative environment that includes all supply chain members. A collaborative

Supplier

Manufacturer

Distributor

Retailer

Customer

FIGURE 1Supply Chain Design

Information flow

Product flow

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environment requires members of the supply chain to communicate, either verbally or

electronically, to determine the needs of each link in the supply chain and how product

communications can be optimized to improve overall effectiveness. Once a collaborative

environment has been achieved, the use of intelligent agents can be used to add efficiency

and responsiveness. This added efficiency is achieved by allowing different links of the

supply chain to communicate electronically using sophisticated programs, which quickly

gather information and perform supply chain performance assessments. Once supply

chains performance is measurable the use of demo models can help members of the

supply chain to further improve efficiency and responsiveness.

By working with other members of the supply chain, a company can optimize the

supply chain and lower costs while becoming more effective. The discussion in this paper

focuses on how e-business can be augmented with the additional collaboration techniques

of information sharing, intelligent agents, and demo models to achieve improved

customer value and global competitiveness.

II. THE RISE OF E-BUSINESS

Customers are demanding more customized rather than homogeneous products.

The primary task for businesses is to effectively supply these customized products in a

timely manner at low cost. The emergence of Information Technology (IT) has replaced

former methods of business communication including: postal mail, phone calls, and

faxes. As IT has emerged, its value has been realized by corporations trying to gain a

competitive advantage in a global marketplace. Companies have found that IT can be

used in their supply chain to produce a fast, responsive, low cost, and flexible solution to

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meeting customer demands. It has become essential that companies use IT, primarily e-

business, as an integral part of the supply chain design to remain competitive.

Dell Computer Corporation is one example of a company that has used e-business

to improve customer value and efficiency by providing customized computers quickly at

a low price. Dell’s primary advantage is its supply chain design and management which

works to improve overall efficiency while lowering costs (2). Ordering a computer is as

easy as a click of the mouse with the use of e-commerce on the company’s website. Once

the order has been placed, the customized computer is built from parts at Dell’s

manufacturing facility in Texas and then sent to the consumer within days. This process

allows the consumer to receive the product within a week. The custom supply chain also

works well for Dell who has agreements with manufacturers to have parts delivered in a

Just-In-Time (JIT) fashion resulting in low costs of holding a minimal amount of

inventory. If the consumer orders a monitor with their computer, Dell will have the

monitor manufacturer ship the monitor directly to the consumer thus eliminating

inventory needs by Dell. Dell is one example of how a company uses e-business to

greatly improve efficiency while lowering cost for the consumer.

Customer

Supplier

Manufacturer

Information flow

Product flow

FIGURE 2 Dell Supply Chain

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Dell’s use of e-business in their supply chain is not an isolated example. E-

business will continue to grow as global competition drives companies to become lean by

lowering costs. E-business has several advantages to companies which use it effectively.

First, when humans are involved mistakes can be easily made. An e-business supply

chain is an efficient way for communication between links of the supply chain that does

not need the intervention of a human. A second advantage is speed. An e-business

transaction can take place in seconds rather than hours or days when done by phone, fax,

or mail. Wal-Mart uses a custom e-business system that collects the UPC code of every

item sold and places an order to the manufacturer to refill the item when stock gets low.

This almost completely eliminates the need for store clerks to check inventory and allows

employees to focus more on the customer rather than the product. The only time a

manager may need to get involved in the e-business transaction is during a cyclical or

weather-related event that will produce untypical demand.

III. INFORMATION SHARING

In any supply chain, supply is stimulated by demand and the goal is to meet that

demand in a low cost manner without stock outs. The success of a firm depends on a

quick response time in meeting customer demand. In the past, firms have used safety

stock in the event that actual demand was higher than forecasted demand, but now faster

order replenishment times are possible with e-business. The ability to hold less safety

stock reduces cost for the firm while achieving a quick response time. Electronic

information sharing (called e-knowledge) between links in the supply chain makes this

form of e-business possible. A supply chain optimized by e-business can be more

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effective when incorporating collaborative solutions between members in the supply

chain; thereby improving overall supply chain profitability while reducing costs. Table 1

shows how the customer can be positively affected by supply chain e-knowledge, which

decreases the demand uncertainty and stock outs. Average forecast errors, stock-out rates,

and markdowns are greatly reduced with the availability of low demand uncertainty.

TABLE 1Effects of Low Demand Uncertainty

Attribute

Low Implied Uncertainty

High Implied Uncertainty

Profit Margin Low High

Average Forecast Error 10% 40%-100%

Average Stock-out Rate 1%-2% 10%-40%

Average Forced end-season markdown

0% 10%-25%

The Bull-Whip Effect

Before the emergence of e-business, a serious problem found in most supply

chains was the “bull-whip effect.” The “bull-whip effect” occurs due to the order time lag

between supply chain members (3). The “bull-whip effect” is amplified as it goes away

from the consumer and up the supply chain. E-business greatly reduces the “bull-whip

effect” by allowing supply chain members access to demand information quickly. When

the information distortion along the supply chain is reduced, this reduces the possibility

of the “bull-whip effect”.

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Collaborative Networks

E-business supply chain systems using e-knowledge can improve the way supply

chain members work together. A collaborative environment can be created to share

demand forecasts, cyclical factors, and business ideas to achieve synergy along the

supply chain. The goal of using such e-knowledge is the “exchange of strategic

knowledge in order to achieve mutually beneficial objectives” (4). The use of e-

knowledge became possible only a few years ago as a result of evolving collaborative

networks producing, currently accepted platforms for the continuous exchange of

information concerning markets, customers, demand, and inventories. Now, when e-

knowledge is used in a supply chain, the automated exchange of information is

instantaneous to all supply chain members. Toyota has used e-knowledge to increase its

suppliers’ involvement by requiring a collaborative environment in its supply chain (5).

Researchers found that in the Toyota system the suppliers were developing a “dynamic

learning capability” that improves their competitive capabilities. The use of this

collaborative environment to streamline information sharing saves the cost of information

search, evaluation, transactions, and administration. The low costs of Japanese

automobile companies result from economies of scale, repeated transactions with a small

Consumption Consumer Retailer Distributor Manufacturer Supplier

FIGURE 3Bull-whip effect

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group of suppliers, a wide range of information sharing to reduce information asymmetry,

long-term performance orientation, and investments in shared (co-specialized) assets (4).

A collaborative environment can also be used in research and development

(R&D) departments to improve the overall supply chain network. Development of

modular and customized product development systems can be used to improve individual

performance while working with other supply chain members to provide products which

will better suite customer needs. More specifically, the co-engineering infrastructures

built in a collaborative environment enable the firms in the supply chain to provide

customized products, without significant costs and sacrifice of efficiency. Figure 5 shows

how collaboration between supply chain member R&D departments is possible. By using

this model supply chain members work together as a team to complete a common goal

instead of viewing the task as a competition between links. By putting the goal of the

Customer

Retailer

Distributor Manufacturer

Supplier

FIGURE 4Collaborative Network within Supply Chain

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overall supply chain first, the R&D departments focus on a common goal and not the

company’s own interests.

Collaborative Planning Forecasting and Replenishment

A major use of information sharing is the demand forecast. With an accurate

demand forecast, a supplier can produce and transport products to reduce overall costs.

Collaborative sharing of customer’s forecasts to suppliers, a concept called Collaborative

Planning Forecasting and Replenishment (CPFR) provides opportunities for cost savings.

The phrase “partnering” is overused in the retail business but not when it involves CPFR

(6). Since CPFR does not necessarily involve the exchange of money it can be

overlooked. The benefits of CPFR are great and should be viewed as realized revenue.

The goal of CPFR is to ensure that supply walks hand-in-hand with demand. The

inability for a supplier to meet demand of a product will mean a loss of possible revenue.

This loss of revenue does not just impact the retailer but also impacts the whole supply

Distributor R&D

Supplier R&D

Manufacturer R&D

Retailer R&D

Collaboration

FIGURE 5Collaboration for Research and Development

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chain since each firm’s profitability depends on the profitability and revenue of the whole

supply chain.

Information sharing does not just involve the behind-the-scenes members of the

supply chain. Customers also have the advantage of using online ordering and tracking to

add value to their purchase(s). In addition to the cost savings earned by improved supply

chain efficiency, the customer also has the ability to track their package and view order

status from their computer. Information given on a retailer’s website may also save the

customer time when making a purchase. Online customer service and technical support

allow a reduction in customer service costs thus increasing efficiency. While the

increased efficiency may come with an intangible cost of generic answers and slow

response time, the balance of available customer service and online support can provide

both value for the customer and cost savings for the retailer.

Incorporating information sharing, whether within the supply chain or from a

customer standpoint, is only the beginning of what need to be done. Methods, such as

intelligent agents and the use of demo models, exist to build upon the existing

collaborative. Without collaboration in a supply chain, the efficiency of an e-business

supply chain can not be maximized to produce the highest gain for all parties.

IV. INTELLIGENT AGENTS

An intelligent agent (IA) is software that automates information and decision

making based on the available data. In the e-business era speed is focused on as a

competitive advantage. A firm can greatly increase value to the customer if it can share

forecasting information and make decisions quickly and effectively. An information

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sharing environment may consist of meetings, telephone calls, emails, and/or faxes. An

intelligent agent can take parameters given by management and make decisions based on

those parameters. Very important decisions can be flagged and analyzed by senior

management.

FIGURE 6Example of intelligent agent software [7]

Intelligent Agent Software

Figure 6 gives an example of an intelligent agent solution, TradeMatrix Platform,

by the i2 company, which augments information sharing by automating the process. The

TradeMatrix Platform by i2 manages transactions, messaging, and presentation of

information to customers, and integrates with back-end Enterprise Resource Planning

(ERP) systems (7). i2 Technologies states that it “provides a wide variety of collaborative

e-services for both early-stage and next-generation e-business adoption, with each

offering supported by decision optimization, transaction management, and content

management solutions.” An intelligent agent solution like that offered by i2 integrates

into an existing supply chain and does the work of optimizing the supply chain. A

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disadvantage of using a specific intelligent agent software solution is that each supply

chain link is required to have software that communicates efficiently with the intelligent

agent software. This may require members of the supply chain to upgrade and/or install

new and costly software. The installation of software is only the beginning of the

integration since management and forecasters will require training to work with the

system to provide constraints and configure the software to make decisions based on the

company’s needs.

The uses of intelligent agents can already be seen in a customer setting [8].

Websites such as Google (www.google.com), mySimon (www.mysimon.com), and Ask

Jeeves (www.askjeeves.com) work with intelligent agents to search the Internet and

provide valid information based on the search criteria given by the user. When going to

mySimon a consumer can type in the name of a product and the software will search to

find the lowest prices of that product. A search engine such as Google will search its

databases for pages containing the information requested by the user and Ask Jeeves will

provide information based on a question that is typed in by the user. All this information

gathering and reporting is automated and transparent to the user. The intelligent agent

software will do all the work of searching through the information. The artificial

intelligence (AI) module will then determine whether the information found has any

value to the consumer. If so the customer will see a link to the information and will never

see completely invalid information.

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FIGURE 7Sites such as mySimon use AI to find pricing information

Intelligent Agents in the Supply Chain

While the use of AI and intelligent agents may abound in the consumer market, it

is not necessarily the case in the business world. Decisions may place large amounts of

money on the line and if an automated system makes a mistake it will be felt heavily by

all members of the supply chain. Businesses are cautious to use this improvement to

information sharing because the decision is not made by a person but by a machine.

Currently intelligent agents “help to facilitate dynamic trade environments; that is, they

help companies develop custom responses to current demands” (8). In a supply chain

environment that task consists of supporting communication among factories,

warehouses, distribution centers, and retailers, in addition to other members such as

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suppliers, customers, and partners. An example of this is an electronics manufacturer who

dispatches intelligent agents to monitor the progress of contract. The electronics

manufacturer can use automation to check the progress of work and set triggers to contact

a senior manager if the work being done by the outsourced company is falling behind

schedule.

The example of the electronics manufacturer is found in an e-marketplace. In an

e-marketplace, intelligent agents query factory management systems to determine which

manufacturers have the most inventory of a needed item and how fast and costly that

shipment will be. A retailer, for example, may need a fast shipment of 100 computers. By

using intelligent agents the retailer can find the lowest cost supplier with fastest response

time. This reduces the cost to the retailer and provides value to the consumer by better

guaranteeing that the item will be in stock. Before the introduction of intelligent agents,

management would have to analyze inventories and cost of each supplier before making a

decision. With the automation of the process, management is now able to focus on

customer service and other avenues to add value to the consumer.

Intelligent agents can be used in all sections of the business, and not just supplier

intelligence. Factory production, schedules, maintenance and product specifications can

all be influenced by the use of intelligent agent software. Given a set of constraints, the

software can make decisions based on demand, pricing, and availability information

collected from multiple sources. Management overrides can influence decisions but for

most day-to-day operations the intelligent agents can do the work to optimally buy and

purchase goods to meet demand and reduce costs. Using this type of information sharing

tool allows fast and effective decisions to be made without the need of information

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inputted manually by management or the workforce. Figure 8 gives a figure of

information flow using intelligent agents in a retail environment.

Intelligent Agent Concerns

So why doesn’t every business use intelligent agents? There are several factors

that affect the success of this software. Intelligent agents, like all software, should be easy

to use and have an easy to use interface. As intelligent agents have developed for supply

chains the interface has not been the primary focus. Since technological functionality has

been achieved, software developers must focus on the interface and documentation to

provide an easy to install, configure, and maintain system that any manager can use.

Another factor is the collection of possible sensitive information. When

purchasing a product online a customer will not want the whole world to view their credit

card number. This is the same problem that haunts intelligent agents. Since the software

collects information using the Internet other parties seeking this information can read it.

Several solutions exist to this problem but are not trivial. The first and easiest solution

Intelligent Agent(Chooses best Supplier)

Retail facility

Supplier 1

Supplier 2 Supplier 3

Supplier 4

FIGURE 8Use of Intelligent Agents in a Retail Environment

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would be to use a secure network for data collection. If the intelligent agent can gather

information over an encrypted channel, the data will not be available to hackers and other

parties. A possible problem to this solution is that if the data is unencrypted in any area of

the communication, an external source might be able to view all the information. The

second option, while harder to implement, can provide a better solution. Using exclusive

networks can eliminate the possibility of other external entities receiving the information.

An exclusive network contains only the members of the supply chain so that all

information is only passed in that network and not through the Internet.

Another problem found using intelligent agents is the variety of information

standards that exist (9). A software system may store all its demand forecast data in

Microsoft Excel while another software system may provide information in a comma

separated text file. Some software is available to act as a middleman and translate

different formats, but the best solution is a common information storage standard which

is uniformly used. One such format is XML which can be shared by both Windows and

UNIX platforms. Information stored in XML format can easily be parsed by software

systems and is platform independent. The use of this possible standard can make

intelligent agent software implementations easy for most businesses.

Intelligent agents build upon the foundation set using information sharing in the

supply chain. The use of intelligent agents can optimize forecasting but a business must

use trial and error to determine whether the supply chain is optimal or not. The next

section discusses demo models, which can be used in a supply chain environment to

benchmark a supply chain by comparing the results of using different intelligent agents

and collaborative environments.

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V. DEMO MODELS

A demo model is a software program that models the effect of using a new supply

chain configuration. Past demand information coupled with cost variables are used to

determine the return on investment of alternative supply chain configurations. A demo

model allows an organization to simulate the effects of different supply chain

configurations without reconfiguring the actual supply chain. The value of a demo model

is that efficiency and responsiveness can be cost-effectively improved by identifying the

supply chain that best fits the organization. Since supply chain re-configuration costs can

seriously affect the profitability of the supply chain, demo models should be used to find

the configuration that increases profitability and return on investment.

Demo Model Simulation

When simulating a demo model, several variables need to be set. The holding cost

will affect the amount of safety stock held and the response time of the suppliers (10). A

high holding cost will cause a company to ask suppliers to be very responsive whereas a

low holding cost may allow a company to hold more inventories. The order cost will

affect the order quantities and the number of orders placed to suppliers. A higher order

cost may require the company to hold more inventories to reduce the number of orders. A

low order cost will allow the company to place orders whenever new inventories are

needed without the high costs of order placement. The planning horizon and demand

refresh/update period are related to forecasting information. The planning horizon sets

how far in the future to forecast the demand of a product. A shorter planning horizon will

result in a better forecast. The demand refresh/update period reanalyzes the forecast to

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determine whether the forecasting system is accurate. If accurate, the forecast will not

change. However, if the forecast is inaccurate, a new forecasting model may need to be

developed particularly if the forecast starts producing values outside the bounds set by

management. Depending on the company, a sample of past forecasts and demand

information may be used to plug into the demo models. Figure 9 provides a graph of how

demo models can be used to provide management with the optimal supply chain

configuration. With the use of intelligent agents and the variables discussed earlier the

costs of each possibly supply chain configuration can be found and compared to other

demo models. The results can be presented to management in a form that supports more

effective decisions.

The use of these demo models, or simulations, allows management to virtually

use a supply chain with past demand and forecasting data to make decisions concerning

supply chain configuration. Without this type of simulation an organization needs to use

trial and error to find supply chain configurations that yield low costs. The trial and error

method can be very costly to companies. For example, an airplane manufacturer begins

FIGURE 9Use of Demo Models to Find Optimal Model

Management

Analysis of Demo Models

Demo Model 4

Demo Model 3Demo Model 2

Demo Model 1

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using a supply chain that involves shipping parts at low costs from Asia. On paper the

supply chain may look very profitable but initial analysis may not take currency changes,

trade restrictions, or increased response time costs into account when determining overall

profitability. By using demo models, the company can quickly simulate multiple models

using a wide variety of currency changes to view their effect on the supply chain

profitability. So instead of investing millions into an inefficient supply chain the effects

can be bounded by the cost of the simulations. Since a supply chain is the core to a

company’s product delivery, it is very important that alternative supply chain

configurations be tested to find the one that produces the lowest cost, greatest value for

the customer, and highest return on investment.

The role of the demo models is crucial to assuring management that supply-chain-

wide development and optimization is possible (11). Psychological barriers may exist

between members of the supply chain concerning collaboration and decision making.

Demo models allow the simulation of common scenarios so that each member of the

supply chain can view the overall profitability effect, in additional to the cost savings

realized by each member. The use of demo models requires that a collaborative

information-sharing environment exist between members of the supply chain. Once the

foundation is in place, intelligent agents and demo models can be used to find the best

model for all members of the supply chain.

VI. PROPOSED IMPROVED MODEL

Figure 10 gives a proposed update to the supply chain outlined in Figure 1. This

update includes the augmented information flow between supply chain members to

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incorporate a collaborative environment. Thus, as shown in Figure 10, the building of

optimal supply chain models involves collaboration between all members of the supply

chain. Without collaboration, members may work to improve their link of the chain but

will not receive the highest benefits until a system-wide optimal model is identified.

Optimal models can be found by combining intelligent agent software and demo models;

this combination can be used to construct a supply chain effective for all supply chain

partners.

Once an optimal model is found using demo modeling and intelligent agents, the

supply chain configuration is shared with all involved supply chain members in order to

reach a consensus to whether to implement the model or not. Therefore demo models

allow each member to be involved in the supply chain design and formal acceptance; thus

guaranteeing mutual benefits from implementing the new model. Once a new model has

been approved, careful consideration must be made to determine how to best implement

Supplier

Manufacturer

Distributor

Retailer

Customer

FIGURE 10Proposed Supply Chain Design

Information flow

Product flow

CollaborativeEnvironment

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the new model. Collaboration must continue between members to collectively plan an

upgrade or modification of current supply chain models. This process may not be trivial

and may take anywhere from a few months to years. The value realized by the supply

chain model upgrade is worth the implementation costs as new models will yield

significant supply chain wide benefits from initial supplier to final consumer.

VII. CONCLUSION

Once companies begin to realize the value of e-business-enabled supply chain

integration, they often discover entirely new ways of pursuing business objectives,

developing strategies, and business models that were neither apparent nor possible prior

to the Internet (12). E-business allows orders to be received and processed by suppliers

within minutes and allows faster methods of communication. The value of e-business can

be realized by both the consumer and supplier with lower prices and more available

information.

E-business itself cannot fix all problems associated with supply chain models.

Since the profitability of a firm will depend on the overall profitability of the supply

chain an overall integrated solution needs to be created to add value to all supply chain

members. To effectively make this optimization possible, information sharing and

collaboration need to be the foundation of work between members. Without

collaboration, the efforts of each supply chain member cannot be integrated in pursuit of

common purpose. Once a collaborative environment has been created, intelligent agents

can help improve supply chain performance by automating the information gathering and

decision making tasks. Intelligent agent software uses artificial intelligence (AI) to

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search, collect, and analyze demand, inventory, and pricing information. Demo models

can be used to simulate and test possible supply chain models to view performance given

a set of constraints; this allows supply chain performance to be measured before investing

in the new model. Demo models also help bring supply chain members together by

working to run demo tests that will simulate individual supply chain performance. Figure

11 shows the hierarchy of building an optimal supply chain model based on information

sharing.

The advantages of working in a collaborative environment do not only include

lower costs and higher profitability. Collaborative environments foster communications

between supply chain members that may not happen in normal settings. Relationships can

be formed between members that can result in long term contracts between retailers and

suppliers. The improvements of supply chain relationships yield synergies that enable

every member to work more effectively as a group than individually. Once new models

have been explored, firms can be on the leading edge of their industries by providing a

more efficient and responsive supply chain with optimal value for all.

Information Sharing

Intelligent Agents

Demo Models

Optimal Model

Value

++++

+

FIGURE 11Building optimal model based on information sharing

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VII. REFERENCES

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2003, pg. 13.

(2) Fine, Charles (1998), “Clockspeed-Winning Industry Control In the Age of

Temporary Advantage”, Perseus Books, 1998.

(3) Kim, Ki-Chan, and Il Im, (2002), “The Effects of Electronic Supply Chain Design (e-

SCD) on Coordination and Knowledge Sharing: An Empirical Investigation”, Resource

Paper, Annual Hawaii International Conference on System Sciences.

(4) Warkentin, Merrill, Ravi Bapna, and Vijayan Sugumaran, (2001), “E-knowledge

networks for inter-organizational collaborative e-business”, Logistics Information

Management, Vol. 14, pg. 149, 2001.

(5) Dyer, J. H and K. Nobeoka (2000), “Creating and Managing a High-performance

Knowledge Sharing Network: The Toyota Case”, Strategic Management Journal, Vol. 21,

2000, pp. 345-367.

(6) Clark, Ken, (2002), “Collaborators and proud of it”, Chain Store Age, Vol. 78, pg. 76,

March 2002.

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(7) i2 Technologies, Strengthening the Supply Chain, 2001, Dell

http://www1.us.dell.com/content/topics/global.aspx/power/en/ps1q01_i2?

c=us&l=en&s=gen.

(8) Zaniker, Jeff and Jay Holata, (2001) “Intelligent Agents in the B2B Value Chain”,

Resource Paper, Supply Chain e-business, April 2001.

(9) Goodwin, Richard, Pinar Keskinocak, Sesh Murthy, Frederick Wu, and Akkiraju

Rama, (1999) “Intelligent Decision Support for the e-Supply Chain”, Resource Paper,

American Association for Artificial Intelligence.

(10) Wadhwa, S, John Jose, and A. Gandhi (2002) “Managing Innovation in e-Business

Based Supply Chain Structures: Role of Demo Models”, Studies in Informatics and

Control, Vol. 11, No. 3, September 2002.

(11) Wadhwa, S., (2001) “Judicious use of IT in Manufacturing SMEs: Case

Experiences”, Resource Paper, E-Commerce: Opportunities and challenges for SMEs,

APO, Tokyo.

(12) Lee, H and S. Whang, (2001) “E-Business and Supply Chain Integration”, Resource

Paper, Stanford Global Supply Chain Management Forum, Stanford University.

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