Electronic Business: Concepts, Methodologies, Tools, and Applications (4-Volumes) P13 pptx

54
Semantic E-Business
data repositories. Pollard (2004) states that
knowledge management activities in healthcare
center on acquiring and storage of information,
and lacks the ability to share and transfer knowl-
edge across systems and organizations to support
individual user productivity. In addition the data
acquired and stored in islands clinical informa-
tion systems are in multiple formats. Common
vocabulary to represent data and information
LVQHHGHGIRUHI¿FLHQWNQRZOHGJHPDQDJHPHQW
(Desouza, 2002). The focus has been on building
independent applications to make these systems
talk to each other. The need is for models to in-
tegrate the data and knowledge in these disparate
systems for effective knowledge sharing and use
(Sittig et al., 2002). To serve the needs, relevant
patient-centered knowledge must be accessible
to the person supplying care in a timely manner
LQ WKH ZRUNÀRZ ,QWHURSHUDELOLW\ VWDQGDUGV RI
emerging Semantic Web technologies can en-
able health information integration, providing
the transparency for healthcare-related processes
involving all entities within and between hospi-
tals, as well as stakeholders such as pharmacies,
insurance providers, healthcare providers, and
clinical laboratories. Further research on using
Semantic Web technologies is needed to deliver
knowledge services proactively for improved
decision making. Such innovations can lead to

enhanced caregiver effectiveness, work satisfac-
tion, patient satisfaction, and overall care quality
in healthcare (Eysenbach, 2003).
E-Government
E-government refers to the use of Internet tech-
nologies for the delivery of government services to
citizens and businesses (www.Webster-dictionary.
RUJGH¿QLWLRQ(*RYHUQPHQW7KHDLPRI(JRY-
ernment is to streamline processes and improve
interactions with business and industry, empower
citizens with the right information, and improve
WKHHI¿FLHQF\RIJRYHUQPHQWPDQDJHPHQW*LYHQ
that e-government services extend across different
organizational boundaries and infrastructures,
there is a critical need to manage the knowledge
and information resources stored in these disparate
systems (Teswanich, Anutariya, & Wuwongse,
2002). Emerging Semantic Web technologies have
the ability to enable transparent information and
knowledge exchange to enhance e-government
processes. Klischewski and Jeenicke (2004) ex-
amine the use of ontology-driven e-government
applications based on Semantic Web technolo-
gies to support knowledge management related
to e-government services. Further research to
investigate requirements, design and develop
systems, and examine success factors for systems
development employing Semantic Web technolo-
gies for effective knowledge management within
e-government services is needed.

ORGANIZATIONS AND RESEARCH
GROUPS FOSTERING A SEMANTIC
EBUSINESS VISION
As research in the foundation technologies for the
Semantic Web develops, the application of these
technologies to enable Semantic eBusiness is of
increasing importance to the professional and
academic communities. In this section we would
like to inform the readers of several organizations
that are involved in furthering research related to
Semantic eBusiness.
Association for Information Systems
(AIS) (www.aisnet.org)
A professional organization, the Association for
Information Systems (AIS) was founded in 1994
to serve as the premier global organization for aca-
demics specializing in information systems. This
organization has formed several special interest
JURXSV6,*VWRSURYLGHVXEVWDQWLDOEHQH¿WVWR,6
students, academics, and practitioners by helping
members exchange ideas and keep up to date on
common research interests. The following SIGs
55
Semantic E-Business
FRQWULEXWHVLJQL¿FDQWO\WRDGYDFLQJ6HPDQWLF
eBusiness research:
• Special Interest Group on Semantic Web
and Information Systems—SIG-SEMIS
(www.sigsemis.org): SIG-SEMIS’ goal is
to cultivate the Semantic Web vision in IS.

The main areas of emphasis in this SIG are:
Semantic Web, Knowledge Management,
Information Systems, E-Learning, Busi-
ness Intelligence, Organizational Learning,
and Emerging Technologies. The SIG aims
WR³FUHDWHNQRZOHGJHFDSDEOHRIVXSSRUW-
ing high-quality knowledge and learning
experience concerning the integration” of
the above main areas. This integration will
provide the participants of the SIG an op-
portunity to create and diffuse knowledge
concerning the issues of Semantic Web in
the IS research community.
• Special Interest Group on Agent-Based
Information Systems—SIG-ABIS (www.
agentbasedis.org): SIG-ABIS aims to
DGYDQFH NQRZOHGJH ³LQ WKH XVH RIDJHQW
based information systems, which includes
complex adaptive systems and simulation
experiments, to improve organizational
SHUIRUPDQFH6,*$%,6SURPLVHVWR¿OODQ
H[LVWLQJJDSLQWKH¿HOGDQGWKHUHIRUHLVPRUH
focused on the strategic and business issues
with agent technology and less on the artifact
itself, such as computational algorithms,
which are well investigated by computer
science related research groups.”
• Special Interest Group on Ontology Driven
Information System—SIG-ODIS (aps.cabit.
wpcarey.asu.edu/sigodis/): The objective of

6,*2',6LVWRSURYLGH³DXQLI\LQJLQWHU-
national forum for the exchange of ideas
DERXWWKH¿HOGRIRQWRORJ\DVLWUHODWHVWR
design, evaluation, implementation, and
study of ontology driven information sys-
tems.” In helping develop awareness and
foster research about the role and impact
of computational ontologies on the design,
development, and management of business
information systems, SIG-ODIS also strives
to build bridges between the IS discipline and
other related disciplines, such as computer
science, information science, philosophy,
linguistics, and so forth, that pursue research
in the broad area of computational ontolo-
gies.
• Special Interest Group on Process Au-
tomation and Management—SIG-PAM
(www.sigpam.org): SIG-PAM’s objective
LVWRDGGUHVVWKH³QHHGRI,6UHVHDUFK-
ers and practitioners for information and
knowledge sharing in the areas of process
design, automation, and management in
both organizational and inter-organizational
contexts.” The SIG collaborates with other
QRWIRUSUR¿WRUJDQL]DWLRQVWKDWKDYHUHODWHG
focus on process theories and applications,
VXFKDVWKH:RUNÀRZ0DQDJHPHQW&RDOLWLRQ
:I0&WKH:RUNÀRZDQG5HHQJLQHHULQJ
International Association (WARIA), and the

Computer Supported Collaborative Work
(CSCW) Conference.
Hewlett-Packard (HP) Labs Semantic
Web Research (www.hpl.hp.com/
semWeb/)
The HP Labs Semantic Web research group recog-
nizes that Semantic Web technologies can enable
QHZDQGPRUHÀH[LEOHDSSURDFKHVWRGDWDLQWHJUD-
tion, Web services, and knowledge discovery. The
HP Labs’ investment in the Semantic Web consists
of the development of Semantic Web tools (such as
Jena, a Java framework for writing Semantic Web
applications) and associated technology, comple-
mented by basic research and application-driven
research. HP is also part of several collaborative
ventures, including involvement in W3C initia-
tives (RDF and Web ontologies working groups)
and European projects (Semantic Web Advanced
Development Europe—SWAD-E and Semantic
Web-enabled Web Services—SWWS).
56
Semantic E-Business
World Wide Web Consortium’s
Semantic Web Initiative (www.
w3.org/2001/sw/)
The main goal of the W3C Semantic Web initiative
is to create a universal medium for the exchange
RIGDWD³,WLVHQYLVDJHGWRVPRRWKO\LQWHUFRQQHFW
personal information management, enterprise
application integration, and the global sharing

RIFRPPHUFLDOVFLHQWL¿FDQGFXOWXUDOGDWD7KH
W3C Semantic Web activity has been established
to serve a leadership role in both the design of
VSHFL¿FDWLRQVDQGWKHRSHQFROODERUDWLYHGHYHO-
opment of enabling technology.”
In addition to these organizations, the forma-
tion of this new journal, International Journal on
Semantic Web and Information Systems, provides
an opportunity for the publication and exchange
of research discussions of the Semantic Web in
the context of information systems.
SUMMARY AND RESEARCH
DIRECTIONS
The realization of representing knowledge-rich
processes is possible through the broad develop-
ments in the Semantic Web initiative of the World
:LGH :HE &RQVRUWLXP :H GH¿QHG 6HPDQWLF
H%XVLQHVVDV³an approach to managing knowl-
edge for coordination of eBusiness processes
through the systematic application of Semantic
Web technologies.” Advances in Semantic Web
technologies—including ontologies, knowledge
representation, multi-agent systems, and the Web
services architecture—provide a strong theo-
retical foundation to develop system architecture
that enables semantically enriched collaborative
eBusiness process. Semantic eBusiness architec-
ture enables transparent information and knowl-
edge exchange and intelligent decision support to
enhance online eBusiness processes.

Developments in the availability of content and
business logic on-demand, through technologies
such as Web services, offer the potential to allow
organizations to create content-based and logic-
driven information value chains, enabling the
needed information transparencies for Semantic
eBusiness processes. Research is needed to un-
derstand how conceptualizations that comprise
business processes can be captured, represented,
shared, and processed by both human and intel-
ligent agent-based information systems to create
transparency in eBusiness processes. Further work
on these dimensions is critical to the design of
knowledge-based and intelligence-driven eBusi-
ness processes in the digital economy.
Research is also needed in the development
of business models that can take advantage of
emergent technologies to support collaborative,
knowledge-rich processes characteristic of Se-
mantic eBusiness. Equally important is the adap-
tation and assimilation of emergent technologies
to enable Semantic eBusiness processes, and the
contribution to organizations’ value propositions.
Topics of research directions include the devel-
opment of innovative, knowledge-rich business
models that enhance collaborations in eBusiness
processes, and innovative technical models that
enable the vision of Semantic eBusiness.
One of our current research initiatives in-
volves developing models for the representation

of knowledge, using ontologies and intelligent
agents for semantic processing of cross-enter-
prise business processes over heterogeneous
systems. For the Semantic Web to be a vibrant
and humane environment for sharing knowledge
and collaborating on a wide range of intellectual
enterprises, the W3C must include in its Semantic
Web initiatives research agenda the creation of
policy-aware infrastructure, along with a trust
language for the Semantic Web that can represent
complex and evolving relationships.
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A. Sheth and M. Lytras, pp. 19-35, copyright 2005 by IGI Publishing (an imprint of IGI Global).
59
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Chapter 1.5
The Evolution of ERP and its
Relationship with E-Business
S. A. Alwabel
University of Bradford, UK
M. Zairi
University of Bradford, UK
A. Gunasekaran
University of Massachusetts - Dartmouth, USA
ABSTRACT
Every technical invention is initially designed
and eventually applied to solve a real-world
problem. The evolution of Enterprise Resource
Planning (ERP) is no exception. Owing to its
well-organised success to effectively integrate
isolated multiple
INTRODUCTION
The rapid change in technology and other skills
DGGHGWRFXVWRPHUVUHTXLULQJKLJKO\VSHFL¿FDQG
customised products has led to the need for far
JUHDWHUFRRSHUDWLRQZLWKLQDQGEHWZHHQ¿UPV
This increasing pressure requires companies to
explore a reliable mechanism that makes it easier
to save, store, and share useful information. Con-

sequently, accounting information system (AIS)
was developed to offer a good foundation for
control information and knowledge to contribute
to a company’s success (Wilkinson, 2000).
AIS can be, according to Romney and Steinbart
(1999) , r efer r e d t o a s a t r a n s a c t i o n p r o c e s s i n g s y s -
WHPEHFDXVHLWRQO\GHDOWZLWK¿QDQFLDOGDWDDQG
accounting transactions. It was mainly used as a
reporting tool to perform functions such as payroll
and invoicing. As the power and sophistication
of information technology (IT) continue to grow
up, the coverage potentials of AIS have become
JUDGXDOO\ PRUH LQDGHTXDWH DQG QRW VXI¿FLHQW
for business needs (Romney & Steinbart, 1999).
With the growing requirements for information
RWKHUWKDQ¿QDQFLDOGDWDRUJDQLVDWLRQVEHJDQWR
develop additional information systems. However,
60
The Evolution of ERP and its Relationship with E-Business
the existence of multiple systems creates various
struggles and inadequacies (Romney & Steinbart,
1999). Very often, the same data, for instance a sale
record, must be stored by more than one system.
Therefore, the term ERP (enterprise resource
planning) emerged, which extends AIS to cover
areas like product planning, logistics, accounting
DQG¿QDQFLDOVHUYLFHVKXPDQUHVRXUFHVDQGVDOHV
distribution.
ERP or information systems integration in
general are doubtlessly among the most central

topics arising at the interface of information
systems (IS) and accounting within the past 20
\HDUV%KDWWVWDWHVWKDW³%\DFFHVVLQJ
enterprise-wide information from databases, IS
integration is providing numerous opportunities
to coordinate organisational activities by facili-
tating communication and information exchange
across departments without the need to go up and
down the vertical chain of command. The access
to timely, accurate and consistent information is
crucial in business process improvement and ac-
counting. IS integration, through communication
networks and database systems, enables organisa-
tions to create and sustain process improvement
through timely retrieval of consistent and accurate
information.”
ERP initiated from the large packaged appli-
cation software that had been widespread since
WKH ¶V$PRQJWKH¿UVW SDFNDJHGEXVLQHVV
applications available was material requirement
planning (MRP), introduced in the 1960’s and
proposed by Joseph Orlicky, who was regarded
as the father of MRP in 1960 in the U.S. (Voll-
mann, Berry, & Whybark, 1992). During the
1970’s, the MRP packages were extended, and
further applications were added (Chung & Snyder,
2000). The extended resulted in the introduction
of manufacturing resource planning (MRP II)
systems; this development has been continued
(Koh, Jones, Saad, Arunachalam, & Gunasekaran,

2000). Moreover, these systems later evolved to
enterprise resource planning (ERP) systems, a
term coined by the Gartner Research Group in
1992 and the name can probably be derived from
the MRP and MRPII systems (Klaus, Rosemann,
& Gable, 2000). ERP systems are highly-inte-
grated software packages (Holland. Light, &
Kawalek, 1999). However, ERP systems, like
all information technology, are rapidly chang-
ing. During the 1980’s, this was abandoned and
replaced by the client-server architectures, and
now newly-released Web-enabled versions have
become more and more widespread (Markus &
Tanis, 2000). This paper will mainly focus on
the evolution of ERP in its historical context.
7KLVZLOOEHFODUL¿HGE\¿UVWH[SODLQLQJ053
DQG053,,V\VWHPVDVD¿UVWDQGVHFRQGSKDVH
of ERP systems. Moreover, reasons why MRP
and MRPII implementation fail as well as their
functions and hierarchy will be investigated to
get a clear overview of ERP evolution. Second,
ERP’s feature, advantages, and disadvantages as
well as reasons why ERP implementation fails
will be discussed. Last, the relationship between
ERP and e-business will be presented.
MATERIALS REQUIREMENT
PLANNING (MRP) SYSTEMS
Materials Requirements Planning (MRP, or
MRP-I) system was launched in the mid-1960s
and quickly became popular for providing a logi-

cal, easily understood method for determining
the number of parts, components, and materials
needed for the assembly of each end item in pro-
duction. As computer power grew and demands
for software applications increased, MRP systems
evolved to consider other resources besides ma-
terials. Software modules were added to include
functions such as scheduling, inventory control,
¿QDQFHDFFRXQWLQJDQGDFFRXQWVSD\DEOH
MRP-I system is a computer-based system for
managing inventory and production schedules.
This approach to materials management applies
to large job-shop situations in which many prod-
ucts are manufactured in periodic lots in several
61
The Evolution of ERP and its Relationship with E-Business
processing steps (Bedworth & Bailey, 1987). MRP
and Push systems are often used interchangeably.
Conceptually, MRP can be viewed as a method
for the effective planning of all resources of a
manufacturing organisation (Russell & Taylor,
1998). According to Daft (1991), MRP can be
GH¿QHGDVD³GHSHQGHQWGHPDQGLQYHQWRU\SODQ-
ning and control system that schedules the exact
amount of all materials required to support the
GHVLUHGHQGSURGXFW´³,WLVDQLQYHQWRU\RUGHULQJ
and time-phased scheduling technique, which uses
bill of material, inventory data, and the master
production schedule to calculate requirements
for material and determine when to release the

material replenishment order” (Torkzadeh &
Sharma, 1991). Thus, for the purpose of this
SDSHU053FDQEHGH¿QHGDVDFRPSXWHUEDVHG
planning, scheduling, and control system that
gives management a tool to plan and control its
manufacturing activities and supporting opera-
tions obtaining a higher level of customer service
while reducing costs.
The Purpose of MRP Systems
MRP is primarily used for scheduling high-value
commissioned parts, materials, and supplies when
demand is r easo nably well know n (Bal lou , 1999).
Ballou (1999) further states that precise timing of
PDWHULDOÀRZVWRPHHWSURGXFWLRQUHTXLUHPHQWVLV
the principle behind MRP. According to Chase and
Aquilano (1995), the MRP functionality within
organisations enables:
• full materials planning to ensure the required
inputs into the manufacturing process are
available to meet demand from order pro-
posals;
• planning to be carried out for a single item if
the MRP controller wants to plan a particular
material; and
• a bill of materials sequencing the assembly
SDUWVRIWKH¿QDOSURGXFW
The main function of MRP according to Ballou
(1999) is to monitor stocks and to determine which
material the company needs, in what quantity,
at what time, and to create the corresponding

order proposals automatically. In MRP, the sys-
tem compares available warehouse stock orders
scheduled receipts from purchasing or production
with planned requirements in the net requirements
calculation. In the case of a material shortage,
that is, if available stock is less than the quantity
required, the system creates an order proposal
(Ballou, 1999).
The objectives of MRP are similar to those of
any inventory management system. These objec-
tives are improving customer service, minimising
inventory investment, and maximising production
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According to Torkzadeh and Sharma (1991), MRP
is an inventory control and production planning
system designed for ordering and scheduling
dependent demand of inventory, which includes
the following components: master schedule, bill
RIPDWHULDODQGLQYHQWRU\UHFRUG¿OH
Advantages of MRP Systems
Material requirements planning (MRP) methods
try to avoid, as much as possible, carrying items
in inventory through precise timing of material
ÀRZVWRPHHWUHTXLUHPHQWV%DOORX,WLV
a preferred method when demand is reasonably
known due to the uncertainty of the forecasting
component. If demand is forecasted to change,
MRP planning adapts to this new level of re-
quirement. Nahmias (1997) says that MRP may
be considered a top-down planning system in

that all production quantity decisions are derived
from demand forecasts. Coyle, Bardi, and Langley
(1996) consider a principal advantage of MRP is
the ability to maintain reasonable safety stock
levels and minimise or eliminate inventories
wherever possible. In addition, other advantages,
according to Chase and Aquilano (1995), include
the following:
62
The Evolution of ERP and its Relationship with E-Business
• identify process problems long before they
occur,
• base production schedules on actual demand,
and
• coordinate materials ordering across the
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Disadvantages of MRP Systems
Nahmias (1997) states that, in a push system,
items are produced based on a plan or forecast
and pushed to the next level. Simchi-Levi, Kamin-
sky, and Simchi-Levi (2000) state the following
problems that are associated with push systems:
1. Push systems are slow to react and some
-
times even unable to react to changes in the
market place.
2. Product obsolescence may occur in a push
system as consumer preferences and demand
changes for a certain product.
3. Inventory and carrying costs are generally

higher in a push system (Simchi-Levi et al.,
2000).
However, the trade-off in costs associated
with MRP concepts is between having the ma-
terials arrive before they are needed, in which
case they are subject to a holding charge, and the
expected cost of the materials arriving after they
are needed so the materials are subject to a late
charge. According to Ballou (1999), the challenge
of scheduling models (MRP) is to determine the
optimal time to release the request for materials
ahead of requirements. Moreover, a major problem
with MRP modelling is that not all uncertainties
are taken into account. Uncertainties include
changes in demand that were not captured by the
forecast and the variance in lead-times. Ballou
(1999) further adds that the challenge of MRP is
WR¿QGWKHRSWLPDOUHOHDVHWLPHIRUPDWHULDOVWR
meet requirements. There is uncertainty associ-
ated with the release time as the required time
for the transportation component of the supply
chain may vary between points.
Reasons for the Failures
Many authors state that struggles associated with
MRP systems to be implemented correctly, to a
certain extent, with organisational and behav-
ioural factors (Chase & Aquilano, 1995; Turbide,
1995). Yet, it seems to be generally agreed that
failure of an MRP installation can be traced to
problems such as:

Lack of Top Management Commitment
MRP system requires a major commitment from
top management in order for it to be successful.
This means not only the commitment of resources,
but also the commitment of top management’s
time to ensure the right coordination among the
various functions. A well-functioning schedule
FDQXVHWKH¿UP¶VDVVHWVHIIHFWLYHO\DQGHI¿FLHQWO\
DQGWKLVLQVHTXHQFHZLOOLQFUHDVHWKH¿UP¶VSURI-
its. Thus, MRP should be acknowledged by top
management as a planning tool with particular
UHIHUHQFH WR SUR¿W UHVXOWV &KDVH  $TXLODQR
1995, p. 595). According to Zairi (2000):
The key drivers for adding optimum value to society
DQGWKHFRPPXQLWLHVLQZKLFKVSHFL¿FEXVLQHVV
organisations operate are through having strong
commitment to corporate and social governance,
having an open dialogue with external stake-
holders and having the determination to achieve
environmental sustainability.
Intensive Executive Education is
Needed
In nearly every study conducted, the lack of
proper training is considered a key barrier to MRP
implementation. Raysman (1981) comments that
lack of understanding about systems is frequently
quoted as a reason for failure of companies en-
deavours. Sum and Yang (1993) recognised that
the lack of MRP expertise and training were
main problems facing companies to implement

63
The Evolution of ERP and its Relationship with E-Business
MRP. In a desire to convert to the new system
quickly, there is often an underperformance in
the training of personnel at all levels. However,
proper training is required from the technical
perspective as well as from the users’ perspective.
Thus, the IT department within an organisation
needs to entirely understand all of the technical
characteristics of the system in order to provide
the proper support to the business functions that
use it. Simultaneously, the business functions need
to recognise the different procedures for entering
data and producing reports.
Too Rigid
The aims of the MRP system are to minimising
inventory investment and maximising production
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thus the accuracy of the recorded levels becomes
VLJQL¿FDQW&KDVHDQG$TXLODQRVWDWHWKDW
³3HUKDSVRQHRIWKHELJJHVWFRPSODLQWVE\XVHUV
is that MRP is too rigid. When MRP develops a
VFKHGXOHLWLVTXLWHGLI¿FXOWWRYHHUDZD\IURP
the schedule if need arises.”
MANUFACTURING RESOURCE
PLANNING (MRPII) SYSTEMS
As it was shown, the MRP contains a method for
planning and procuring the materials to support
production. During years of using MRP, the need
for other functions arose that would, together with

MRP, create an actually integrated manufactur-
ing management system. Thus, it was done by
creating a large production control system named
manufacturing resources planning (MRPII).
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Manufacturing resource planning (MRPII) sys-
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Inventory Control Society (APICS) as a system
for the effective planning of all the resources
of a manufacturing business (Higgins, Le Roy,
& Tierney, 1996). It is a direct successor of the
material requirements planning (MRP). MRPII
LVFRQFHUQHGZLWKPDQDJLQJWKHÀRZRIPDWHULDO
into, through, and out of the organisation (Arnold,
1998). Thus, MRPII is a system in which the en-
tire production environment is evaluated to allow
master schedules to be adjusted and created based
on feedback from current production/purchase
conditions (Bedworth & Bailey, 1987).
Functions of MRPII Systems
The functions of MRPII according to Higgins et
al. (1996) can be summarised as follows:
• 7KHRSHUDWLRQDQG¿QDQFLDOV\VWHPDUHWKH
same.
• It has simulation capabilities that enable
predictions to be made beforehand.
• It involves every facet of business from plan-
ning to execution (Higgins et al., 1996).
Although MRPII is an imposing tool when used
properly, there are some considerations that must

be addressed for it to function effectively.
• 7KHIXQFWLRQVZLWKLQD¿UPPXVWEHLQWH-
grated. They must agree on what is being
produced and in what quantities. Often,
organisational boundaries are crossed when
these decisions are being made.
• Stringent data requirements are needed for
MRPII to function properly. Errors in data
FDQEHPDJQL¿HGJUHDWO\E\WKHSURFHVV
• It is extremely important that feedback from
the process is monitored regularly. Informa-
tion that is shared among functions can help
to reduce errors, especially with lead times
(Kessler, 1991).