Ting-Peng Liang is National Chair Professor in Information Systems and
Director of the Electronic Commerce Research Center of National Sun Yat-sen University in
Mohan
Tanniru is Salter
Distinguished Professor of Management and Technology and the MIS Department
Head in the Eller College of Management at the
Need for New
Generation Information Systems
The rapid
proliferation of the Internet has drastically
changed the nature of business information systems (ISs).
The World Wide Web has become the new paradigm for information capture and
delivery. In addition, it has started to revolutionize many aspects of IS
development and utilization. For example, wikipedia.com has generated eight
times more information content than the Encyclopaedia
Britannica. This would not have been possible without a system development
philosophy and flexible architecture that are customer-centric. Obviously, such
a customer-centric approach to meet the dynamic customer-driven information
capture and dissemination puts enormous pressure on both the demand and supply
side of the systems development equation, and this has not been studied
adequately by academia.
On the on-demand side of development, customers are asking
for a rapid response to their changing information needs during the purchase of
a product or service or a resolution of a problem after sale. Because
satisfying these informational needs, often in the form of
customized products or services, requires interaction across intra- as
well as interorganizational boundaries, organizations
are forced to build agility into their process and technical infrastructure.
Ultimately, the agility with which on-demand information has to meet the needs
of a customer using an organization’s internal process and technology
architecture places an enormous challenge before those who develop IS (i.e.,
the supply side).
The development of IS, for the most part, has focused on
the operational efficiency of business processes, while indirectly meeting
on-demand customer needs. More recently, customer relationship management (CRM)
systems have been used to gather frequently changing customer preference
information, and service-oriented architectures (SOAs)
are being developed to provide certain architectural flexibility.
While CRMs help capture customer
needs on the demand side and SOAs support agility on
the supply side, many of these efforts remain somewhat disconnected. The wave
of customization and personalization, however, requires a new way of thinking.
At the same time, IS development has to take an integrated view of linking
various components of the customer-driven value chain; that is, customer needs,
customized products/services that serve these needs, business processes that
produced these products/services, and technology that enables these
processes.
In other words, while current enterprise-wide
process-oriented IS development is looking out to support customer
needs, the new customer-centric systems development has to be looking
in to configure the value-chain components appropriately to meet changing
customer needs.
Customer-Centricity Defined
Reflecting on the
history of IS development, the
first-generation systems have often focused on technology utilization.
For example, evolution of modeling tools has made designers develop decision
support systems and advances in multimedia technologies that enhance users’
interfaces. These systems were usually proprietary and targeted to meet the
needs of a specific application while meeting the internal requirements of an
organization (e.g., cost reduction, productivity improvement, etc.).
The second-generation systems were process-oriented (e.g.,
SAP’s enterprise resource planning [ERP] system) and
they were built to support a set of general-purpose processes for adaptation
through configuration and reusability. They forced successful decomposition of
large-scale enterprise systems into modules, thus simplifying system
development and deployment. Yet their primary focus is still internal to a
business (e.g., productivity) and organization specific (e.g., cost reduction),
albeit these demands for improvement were customer driven (i.e., faster
response time to customer order or inquiry).
The customer-centric ISs,
we believe, are of the third generation, where the business driver is customer
value (and business competitiveness), and the focus of system development is to
configure various components of the customer driven value chain to meet the
ever-changing customer value proposition.
A customer-centric IS is designed
with customer preference and needs in mind, which makes the system development
a dynamic process. Again, wikipedia.com provides an architectural platform on
which customers work together to determine the final product, and the
organizational processes are set up to support the development of such a
product. Here, customers are an integral and critical component of the IS
development and their involvement and satisfaction enables the system to derive
its value. Another example is the category of the increasingly popular online
recommender systems (e.g., book recommendations at Amazon.com and news
recommendations at Google news), where customer
engagement and architectural flexibility allow the system to react quickly to
discovered customer preferences.
Framework for Customer-Centric Information Systems
A
customer-centric IS can be viewed as one that
is able to configure four major components—customer, process, technology,
and product/service—to satisfy a customer need. The customer is the
kernel and the driving force behind the system.
Customer profiles are analyzed to identify their needs and
develop information requirements (often through customized products or
services). These customized products or services then determine the manner in
which business processes are configured (i.e., designed, assembled, or
adapted). Finally, flexible information technology and system architecture are
used to support process configuration in product/service delivery. Note that
this is a variation of the process, people, and technology model traditionally
used in IS development.
Here, the three organizational components (process,
technology, and product/service) are intended to serve a fourth component—the
customer. Note that such a customer-centric view also makes the systems
development “value driven” as opposed to cost driven, an important ingredient
in making IS development business-centric or supportive of competitive
strategy. Figure 1 illustrates the relationships of these components.
While customer needs typically drive the nature of the
products/services produced, which in turn influences the process and technology
architecture, the reality is that all four factors influence each other. For
example, advanced technologies can create opportunities to make processes
service enabled (e.g., SOA), which can enhance the bundling of products and
services and provide competitive value in customer offerings.
Innovative process improvements (e.g., collaborative
product design and global supply-chain processes) can speed up the development
of new products/services to satisfy customer needs as well as influence the
development of new technologies.
Similarly, new customer products/services (e.g., enabling a
customer to track orders online) may drive process and technology innovation
using radio frequency identification (RFID) technology. Because of such
interplay, the components are shown to be interdependent on each other, all
ultimately driven by a customer need.
Major Components of a Customer-Centric
Information System
Customers
In a customer-centric IS,
the role of customers can be either active or passive. Active
customers are involved in the operation of a system and are an integral part of
its development. Both wikipedia.com and blogs are
examples of customer-centric ISs in which customers
influence the way the system is conceived, developed, and disseminated. The
critical issue in such systems is the effectiveness with which customers are
integrated into the evolution of the system [4].
The passive role of customers is more traditional.
Customers use a system to accomplish their goals and leave certain clues for
the system to capture their implicit preferences and needs. The system can then
tailor its internal processes to meet these evolving customer needs. A key
issue here is the effectiveness with which one can develop customer profiles
and use them to adapt the system. Research in this area includes information
filtering, customer profiling, personalization, and recommendation systems [1,
5].
Processes
In order to meet customers’ changing
needs, the processes in the organization, embedded within the IS or outside the
system, must be flexible enough for easy configuration. The critical issue here
is one of developing architectures that can support on-demand configuration.
The internal process architectures have to be service enabled (akin to
SOA), so they can be configured and integrated on demand flexibly across the
value chain.
Products and Services
Especially critical in the case of passive
customers is a customer-centric IS with process configurability that can
provide customized or personalized products and services. Customization and
personalization are similar and yet distinct. Customization often relies on
customer segmentation based on customer preference information.
Personalization is a special case, or the ultimate goal of,
customization, where products and services are customized for each individual
customer. The critical issues here are the extraction of customer profiles that
can be used to develop products/services and satisfy customer needs as well as
increase their loyalty and retention [1, 2].
Technologies
In order to use process configuration to
develop customized or personalized products/services, innovative information-gathering
and -processing technologies are essential. For example, SOA technology allows
various processes to be implemented as Web services and can be integrated at
the run-time to meet changing needs. User profiling technologies are essential
to collect usage behavior of customers over time to predict their future
behavior. Technologies such as content-based filtering and collaborative
filtering enable many online bookstores and movie rentals to support internal
processing of dynamic information [1, 2].
Another powerful technology is the Web 2.0 framework [3].
This technology enables integration of many factors in the customer-centric
value chain through user participation, decentralized control, and collective
intelligence [4].
Dimensions of Customer-Centricity as Presented in the Special Section
We have selected
four papers to represent various dimensions of
customer-centricity in IS development in this Special Section.
The paper by Christian Wagner and Ann Majchrzak
compares three applications of the wiki technology
for peer production of Web content. Their study indicates that the
customer-centric technology that works well on wikipedia.com may not work in
other domains such as editorial comments. They suggest a model of six
characteristics that affect customer engagement—community custodianship, goal
alignment among contributors, value-adding processes, emerging layers of
participation, critical mass of management, and monitoring activities.
Ting-Peng Liang,
Hung-Jen Lai, and Yi-Cheng Ku’s paper studies the relationship between
personalized content services and user satisfaction. They review theories
related to personalized information services to build an integrated framework
and then use it to study online news. Two experiments were designed to examine
whether personalized content services could accurately predict user profiles
and the relationship between personalized services and user satisfaction. They
find that personalized services can indeed provide accurate news recommendation
and increase user satisfaction. User satisfaction is affected more by the
accuracy of recommendation and the items shown to the user. User motivation has
a moderating effect on recommendation accuracy and user satisfaction.
The paper by Jie “Jennifer”
Zhang, Xiao Fang, and Olivia R. Liu Sheng
investigates the issue of depth of customer search. They build a theoretical
model and use clickstream data from 26 music retailer
Web sites, 24 computer hardware Web sites, and 29 air travel Web sites to
analyze consumers’ search depth. The model suggests that search cost is
inversely correlated with search depth, while consumers’ quality preference is
positively correlated with search depth. Implications for Web site design to
meet customer needs are discussed.
Sunil Mithas, Narayan
Ramasubbu, M.S. Krishnan, and Claes
Fornell study the issue of how Web sites can be
designed to increase customer loyalty. Based on more than 12,000 online
customer surveys for 43 Web sites, their research reveals that Web site domain
and features can affect customer loyalty. The relationship between Web site
features and customer loyalty is stronger for transaction Web sites than for
information Web sites.
Concluding Remarks
As research
trends evolve with technology and application
innovation, this paper has outlined a customer-centric framework for future IS
development. Customer profiles should be the key component of IS. The papers
included in this Special Section have investigated several aspects of
customer-centric IS and can be good pointers to future research in this
direction.
References
1. Liang, T.-P.;
Lai, H.-J.; and Ku, Y.-C. Personalized content recommendation
and user satisfaction: Theoretical synthesis and empirical findings. Journal
of Management Information Systems, 23, 3 (Winter 2006–7), 45–70.
2. Mithas, S.; Ramasubbu, N.; Krishnan, M.S.; and Fornell,
C. Designing Web sites for customer loyalty across business domains: A
multilevel analysis. Journal of Management Information Systems, 23, 3
(Winter 2006–7), 97–128.
3. O’Reilly, T. What Is Web 2.0? Design
patterns and business models for the next generation of software. O’Reilly Media,
4. Wagner, C., and Majchrzak,
A. Enabling customer-centricity using wikis and the wiki way. Journal of Management Information Systems,
23, 3 (Winter 2006–7), 17–44.
5. Zhang, J.; Fang, X.; and Sheng, O.R.L. Online customer search depth: Theories and
new findings. Journal of Management Information Systems, 23, 3
(Winter 2006–7), 71–95.