PRODUCTION AND OPERATIONS MANAGEMENT
Vol. 17, No. 3, May–June 2008, pp. 238–246
issn 1059-1478 eissn 1937-5956 08 1703 0238
POMS
doi 10.3401/poms.1080.0027
© 2008 Production and Operations Management Society
The Emergence of Service Science: Toward
Systematic Service Innovations to Accelerate
Co-Creation of Value
Jim Spohrer, Paul P. Maglio
IBM Almaden Research Center, San Jose, California 95120
{spohrer@almaden.ibm.com, pmaglio@almaden.ibm.com}
The current growth of the service sector in global economies is unparalleled in human history—by scale and
speed of labor migration. Even large manufacturing firms are seeing dramatic shifts in percent revenue
derived from services. The need for service innovations to fuel further economic growth and to raise the quality
and productivity levels of services has never been greater. Services are moving to center stage in the global arena,
especially knowledge-intensive business services aimed at business performance transformation. One challenge
to systematic service innovation is the interdisciplinary nature of service, integrating technology, business, social,
and client (demand) innovations. This paper describes the emergence of service science, a new interdisciplinary
area of study that aims to address the challenge of becoming more systematic about innovating in service.
Key words: service science; service innovation; coproduction; value co-creation
History: Received: May 2005; Revised: February 2006; Accepted: June 2006 by Uday Apte.
1. Introduction: Motivation and Goals
As the service sector of the global economy grows,
the study of services and especially the study of service
innovation are moving to center stage. This paper
shares some first impressions on the study of services
from two relatively new students of it. About five
years ago, we were given the opportunity to study
how we could possibly have an impact on IBM’s huge
services business, and in this article, we detail what
we have been thinking, what we have been doing,
and what we have learned in that time.
First, we need to set the stage. IBM is one of the
largest information technology (IT) companies in the
world. And although IBM is generally thought of
as a systems and software company, in the last 20
years the proportion of revenue from services has
grown dramatically—in 2007, of $99B in total revenue,
$54B came from services (see Figure 1). IBM’s
services business spans IT services, including consulting
and outsourcing, and business services, including
consulting and outsourcing. After IBM acquired
PriceWaterhouseCoopers Consulting in 2002 and created
what became the IBM Global Business Services
division, we found ourselves—IBM Research, a world
leader in technology and product innovation—with
little experience and capability in service innovation,
the kind of innovation that seemed to matter more
and more to our business. IBM Research needed to
change.
What constitutes a service at IBM? To start, we think
services require clients and providers to work together
to transform some state, such as material goods, information
goods, or organizations, that is owned or controlled
by the client (Hill 1977, Gadrey 2002). In general,
services require the application of competencies,
capabilities, or resources by the provider for the
benefit of the client (Vargo and Lusch 2004). IBM
focuses on Business Performance Transformation Services
(see http://www.ibm.com/investor/viewpoint/
features/2005/24-08-05-1.phtml)—using knowledge,
skills, and resources first to help clients understand
their businesses (component by component) and then
to help clients transform their businesses.
What constitutes service innovation at IBM? Consider
that business service operations at IBM can
often be improved through organizational innovations,
educational innovations, or technological
innovations—or through combinations of these. Innovations
often lead to increases in productivity: doing
the same work but with less effort. The importance of
this can be shown with a simple example. IBM’s 2007
Annual Report describes gross profit margins for different
parts of the business. Software had gross margins
of 85%, whereas services had margins of only
27%. Doubling service productivity would result in
margins of more than 60%, and improving productivity
by 10 times would result in margins of more
than 90%.
238
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society 239
Figure 1 Increase in Service Revenue at IBM
0
20
40
60
80
100
1982 1988 1994 1998 2004 2006 2007
Year
Services
Revenue($B)
Software
Systems Financing
Source. IBM Annual Reports.
Change is not easy, but we discovered that this
was not the first time IBM Research had to adapt to
changes in the business environment. A huge transformation
occurred in the 1970s when software systems
research was added to an organization that
had been composed primarily of physicists, chemists,
electrical engineers, and mathematicians. During that
transformation, computer science PhDs joined the
organization in large numbers. This is only fitting,
as IBM had played a major role in helping to establish
the discipline of computer science in the 1950s
(Asprey and Williams 1994).
So the question arose with services: what new types
of PhDs might be needed to build a world-class, corporate
services research organization? A quick survey
of the PhDs within IBM’s services division revealed
a three-way split among technology, business-related,
and social science PhDs. Also, it was clear that
the existing research organization was dominated by
technology PhDs. For a research organization focused
on technology systems, the shift to services would
require a shift toward innovation aimed at improving
sociotechnical business systems (Trist 1981). For
example, nowadays clients rarely buy an IT system
simply because of its technical capabilities (faster,
more capacity, etc.) but instead require a business
model (return on investment) and an organizational
change model (reengineered processes and job roles)
that will make the technology an effective solution to
their business problems. In a nutshell, this is the reason
for IBM’s transition from a company specializing
in systems and software to a company specializing
in combining services with systems and software to
co-create the transformation of client businesses.
Some colleagues in IBM and in academia advocated
a bold approach—creating a new academic discipline
called service science (Chesbrough 2004, 2005;
Horn 2005), which aims theories and methods from
many different disciplines at problems that are unique
to the service sector. At the start, the particular disciplines
(including some engineering, social science,
and management disciplines) and the particular problems
(e.g., improving service innovation and service
productivity) were not clear. However, this idea of
an integrated service science was particularly appealing
to us, as we found that the number of separate
PhDs required to form a suitable services research
organization had grown to nearly a dozen! We had
recruited PhDs in anthropology, cognitive psychology,
computer science, cognitive science, education,
human factors, industrial engineering, and organizational
psychology, among others. The communication
challenge alone of getting such a diverse population
of scientists to speak a common language around
“service innovation” required training everyone in
each others’ disciplines to some extent, as well as
injecting new, practical concepts fresh from the front
lines of our own services business.
In what follows, we first lay out some background
on the service economy and on the growing demand
for service innovations. Next, we describe some of
the current educational and academic focus on services.
Finally, we suggest what we might find if we
can coordinate and align business, academic, and
government players toward the common objective of
understanding and increasing service innovation by
developing a service science.
2. Economic Shifts
The macroeconomics are clear. As Figure 2 shows,
the economies of the world are shifting from agriculture
and manufacturing to services, as measured
by the percentage of the workforce employed in each
sector. Columns show the percentage of the world’s
labor force in each country; the percentage of the
labor force employed in agriculture, goods production,
and services; and the percent change in services
in the last 25 years. Put simply, the economies of
the world are becoming one large service system. In
1800, approximately 90% of the labor in the United
States worked on farms. Today, fewer than 3% work
on farms—and that 3% feeds a much larger population
than before. This decrease in labor represents a
millionfold increase in productivity. The International
Labour Organization (2007) reported that for the first
time in 2006, more people worked in the service sector
worldwide than in either the manufacturing or
agricultural sectors.
According to the Clark-Fisher hypothesis (Clark
1957), labor migrates from high-productivity, lowvalue
portions of the economy to low-productivity,
high-value portions of the economy. Value is determined
largely by supply and demand: low supply
and high demand creates economic value. Productivity
increases result largely from technology, specialization,
and new processes for performing activities.
Productivity increases create leisure time in individuals
and higher returns for businesses, both of
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
240 Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society
Figure 2 World Economies Are Shifting from Agriculture and
Manufacturing to Service
25-year
World Agriculture Goods Services increase in
Nation labor (%) (%) (%) (%) services (%)
China 21 50 15 35 191
India 17 60 17 23 28
United States 4 8 3 27 70 21
Indonesia 3 9 45 16 39 35
Brazil 3 0 23 24 53 20
Russia 2 5 12 23 65 38
Japan 2 4 5 25 70 40
Nigeria 2 2 70 10 20 30
Bangladesh 2 2 63 11 26 30
Germany 1 4 3 33 64 44
Note. Data compiled from national labor statistics and other sources in 2003.
which get invested in new endeavors creating new
areas of demand. Although Baumol and Bowen (1968)
identified lagging productivity in the service sector,
information technology and the Internet have begun
to pay off with a surge in service sector productivity
(Brynjolfsson and Hitt 2000, Hilsenrath 2003, Triplett
and Bosworth 2004). The recent rise in outsourcing
services to low-cost geographies has also provided a
boost to service sector productivity.
There are many ways of telling the remarkable
story of the growth of the service sector. Bryson et al.
(2004) may have the beginnings of a deep theory
that might underlie a service science in their recent
book, Service Worlds. However, there are many other
perspectives as well. For instance, Fuchs (1968) may
have been the first to define services in terms of
coproduction. An excellent background can be found
in texts by Fitzsimmons and Fitzsimmons (2005) on
service management and by Sampson (2001) on service
operations. Tien and Berg (2003) demonstrate
the need for service systems engineering. From an
economic perspective, Clark (1957) notes the rise of
the service sector; Porat and Rubin (1977) refer to
the rise of the information economy; Herzenberg
et al. (1998) characterize the shift to a new economy;
Bell (1999) refers to the post-industrial society; Pine
and Gilmore (1999) describe the experience economy;
Karmarkar (2004) tracks the industrialization of services
globally; Paloheimo et al. (2004) describe industrial
services; Tanninen-Ahonen (2003) shows the rise
of knowledge-intensive business services; and Sen
(1999) argues that increases in freedoms will increase
value in the service economy.
Earlier, we defined services as clients and providers
working together to transform some client-controlled
state. However, it turns out that defining services is
not easy. Consider just this small sample of definitions
available in the literature:
• deed, act, or performance (Berry 1980);
• an activity or series of activities provided as
solution to customer problems (Gronroos 1990);
• all economic activity whose output is not physical
product or construction (Baruch et al. 1987);
• intangible and perishable created and used
simultaneously (Sasser et al. 1978);
• a time-perishable, intangible experience performed
for a customer acting in the role of coproducer
(Fitzsimmons and Fitzsimmons 2005);
• a change in condition or state of an economic
entity (or thing) caused by another (Hill 1977);
• characterized by its nature (type of action and
recipient), relationship with customer (type of delivery
and relationship), decisions (customization and
judgment), economics (demand and capacity), mode
of delivery (customer location and nature of physical
or virtual space) (Lovelock 1983);
• deeds, processes, and performances (Zeithaml
and Bitner 1996);
• application of competencies for the benefit of
another entity (Vargo and Lusch 2004).
For conciseness, we think pay for performance is a
reasonable definition of a service—in that this phrase
captures the idea that what the provider does for the
client is essential, as opposed to exchange of an artifact
or a good being essential. However, combining
Fitzsimmons and Fitzsimmons’s definition with Hill’s
definition, a time-perishable, intangible experience performed
for a client who is acting as a coproducer to transform
a state of the client, reveals some other essential
characteristics of services: namely, that the client plays
a key role in coproduction activities (the client has
responsibilities) and in the co-creation of value (transformed
state of the client) (see also Sampson and
Froehle 2006). To understand the notion of responsibility
in a coproduction activity, consider a teacher
telling a student to read a book and work a problem
set (exercises) or a doctor instructing a patient
to eat certain foods and exercise more. In both cases,
the providers perform certain activities, but the clients
must also perform activities that transform their own
states or else the benefit or value of the service will
not be fully attained. In business services, if the client
does not install the new IT systems and train the necessary
people in the reengineered process, the client
will not receive the benefit of the service. Thus, the
provider in many cases must negotiate to monitor
and assess that the client is performing adequately
on the client’s responsibilities, and, of course, the
client needs to determine that the provider is likewise
applying satisfactory effort and quality controls in
the performance of the provider’s tasks. These issues
become of paramount importance in outsourcing services,
when a client may outsource a component of
its business to a provider that is in a different country
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society 241
with different government regulations and national
culture of the employees.
In viewing services as pay for performance in which
value is coproduced by client and provider, there are
at least three types of performance of interest to
providers: high talent performance (trained chef),
high technology performance (ordering dinner from
a website), and routine performance supported by
superior environment (service personnel with average
abilities, a good cookbook, and a well-equipped
kitchen). When thinking about getting more systematic
about service innovation, firms can invest in
talent, invest in technology, or provide a superior
environment for performance. Talent allows for the
opportunity to provide the widest range of services
for a client with the greatest levels of unique customization.
Technology allows for the greatest efficiencies
to be achieved for highly standardized or
well-scoped alternative configurations. Environmental
supports allow for the greatest flexibility on the
part of the provider in finding employees who can
perform well for clients with some degree of customization.
Of course, a service provider may use all
these approaches on different client segments.
One misconception about the growth of the service
sector is that it is creating more low-skill, lowvalue
jobs than high-skill, high-value jobs. In fact,
the evidence is to the contrary. Figure 3 shows the
distribution of jobs in the United States by work
system (and by sector: all sectors, service sector,
and goods manufacturing sector). Tightly constrained
jobs, such as those found in call centers, and human
labor-intensive jobs, such as child care, account for
fewer than a third of service jobs. More autonomous
sorts of jobs, such as managers and engineers, account
for the vast majority of service jobs. Recently, the U.S.
Bureau of Labor Statistics (2005) has begun to project
that job growth in the United States will be based
entirely on service sector jobs and will grow most for
high value professional and business service jobs.
In part because high technology performance
and superior environment performance require
specialists—not to mention that high talent performance
also requires specialists—services tend to creFigure
3 Percent Employment by Work System in the United States
1996 (%)
All Services Goods Examples
Tightly constrained 5 4 10 Call center, fast food
Unrationalized 25 26 15 Maid, child care
labor-intensive
Semi-autonomous 30 29 34 Admin., manager
High-skill autonomous 41 40 40 Executive, engineer
Note. Adapted from Herzenberg et al. (1998).
ate good entry-level jobs (average ability in superior
environment) and then provide growth paths that
lead to high talent or jobs associated with high technology
performance. Moreover, the information services
sector is growing dramatically (Apte and Nath
2007). Many studies link the growth of information
and communication technologies (ICT) in an economy
to the growth of the service sector and the growth of
GPD per capita (Colecchia et al. 2002, Pilat 2003, Porat
and Rubin 1977). Although speculating about causal
relationships is always risky, we think it is safe to
say that technology, business, and work innovations
coevolve.
3. Academic Shifts
Academic interest in services has been growing
slowly and steadily, with more and more disciplines
rethinking their curricula and research agendas in
light of the growth of services. Nevertheless, most
academics and government policy makers are still
operating in a manufacturing paradigm rather than
in a service paradigm. Change is slow, and this
has a negative impact on service innovation rates.
At the national level, Germany, Denmark, Finland
(Paloheimo et al. 2004), Norway (Hauknes 1996), the
United Kingdom (Tidd and Hull 2003), and Canada
have made significant efforts over the last decade to
rectify this situation. There are many reasons why the
shift to a new logic based on services has been slow
to happen (Vargo and Lusch 2004), although probably
the greatest single cause is simply inertia. Nevertheless,
pioneers in service research are showing
increasing confidence that the tipping point has been
reached, and they are calling for a wider range in service
research (Rust 2004).
In addition to economists and specific service
professions, business schools have often been the
schools in universities to begin offering servicerelated
courses. Marketing departments saw the
rise of service marketing, and strategies based on
taxonomies of services and deeper understanding of
the special characteristics of a service relationship
emerged (Lovelock 1983). Operations Management
departments have been paying increasing attention
to the management of service operations since the
seminal work of Chase (1978) and Chase and Tansik
(1983). Operations Research departments sometimes
associated with Management Science departments in
business schools, or Industrial and Systems Engineering
departments in science and engineering schools,
have recently seen the rise of service operations,
service engineering, service systems engineering
(Tien and Berg 2003), and enterprise transformation
departments (Rouse 2004). Recently, undergraduate
majors have also begun to show the shift towards
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
242 Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society
service, such as the recently revised ORMS major at
University of California, Berkeley (see http://www.
ieor.berkeley.edu/AcademicPrograms/Ugrad/ORMS.
pdf) and the Service Systems Engineering program at
Michigan Technological University (see http://www.
sse.mtu.edu/). In business schools, Finance departments
have begun shifting toward more focus on
activity-based costing (Roztocki 1998), reflecting the
shift towards activity-based economic transactions
and the firm operations inherent in services. Also,
Professional Science Masters (PSM) programs have
begun to appear, mixing science, business, and
mathematics (Jones 2004).
Computer Science departments are seeing the
growth of services-related curriculum elements,
including service-oriented architectures (SOA), Web
services, and service computing (McAfee 2005,
Newcomber 2002). Agent-based modeling techniques
first developed for artificial intelligence are now being
applied in new areas, such as computational organization
theory (Carley 2002) and agent-based computational
economics (Tesfatsion 2002).
Social science schools are seeing the shift towards
services not only in economics but also in areas
such as anthropology, in its shift to the study of
cultures in business settings rather than in remote
jungles (Baba 1995). Organization theory, which is
taught both in social science schools and in business
schools, and decision science, which is closely aligned
with operations research, are seeing similar shifts
toward more service content in curricula elements as
well as toward more service-oriented research questions.
Organization theory and coordination theory
Figure 4 Changes in Academic Courses and Programs over the Past 100 Years
Technology
Business
Social-
organizational
5
1
9 25
27
14
28
10
26
24
8
4
4. Service marketing
5. Social complexity
6. Agent-based computational
economics
7. Computational organization
theory
3. Service engineering
2. Service ops and mgmt
1. Information sci and sys
2
3
6
7
11
12
13
15
16
17
18
19
20
21
11. Management of
information systems
8. Management of innovation and
tech (MoT)
9. Experimental economics
10. AI and Games
12. Computer supported
collab. work (CSCW)
13. Performance support systems
in business and organization
22
14. Computer and information
sciences
16. Organization theory
15. Human capital
management (HCM)
20. Game theory
21. Industrial engineering
22. Marketing
23. Managerial psychology
19. Management science
18. Systems engineering
17. Operations research
23
1990–2004
1960–1990
1900–1960
Before 1900
24. Business administration
(MBA)
25. Economics
26. Law
27. Sociology
28. Education
are essential for understanding the decisions made
in organizations and the evolution of work systems
(Malone et al. 2003; Malone 2004; March and Simon
1993; March 1988, 1999).
Overall, we see certain academic disciplines revising
content based on the shift to services in the economy.
Our own assessment of the content of course
shifts over the last 100 years—toward more balance
among human, technical, and business concerns—
bears this out. Figure 4 shows academic courses
and programs over the last 100 years plotted along
three axes, roughly by the amount of concern for
technology, business, and social-organizational matters.
The years associated with these fields are only
rough estimates meant to illustrate the point: over
time, we see courses converging toward the center—
toward a balance among these three concerns. Moreover,
this convergence is now being documented by
others at information schools (Glushko 2008), business
schools (Davis and Berdrow 2008), engineering
schools (Larson 2008), and elsewhere (see, for
instance, Hefley and Murphy 2008).
At an even higher level, the need for government
investment in services is significant, and the few programs
that exist need to be greatly expanded. In addition,
the government needs to expand its efforts in
measurement of services in the economy as well as
to consider ways to increase the number of patents in
the service innovation area. The benefits of industry,
academic, and government collaboration to increase
knowledge and competitive advantage are becoming
well documented, and the effects can last for decades
(Murmann 2003).
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society 243
4. Research Agenda
A central problem in service science is likely to be
related to understanding service system evolution.
After all, service innovation—our ultimate goal—
creates changes to a service system, which is made
up of clients and providers co-creating value and
which has a direct impact on the evolution of the
system (Spohrer et al. 2007). One measure of value
is as a measure of the differential between supply
and demand (low supply plus high demand equals
potential for high value). Specialization is one of the
key mechanisms for creating value. If two entities
have different abilities for achieving a goal (supply
diversity), then under certain conditions they can
specialize in what they do best and create an overall
increase in productivity, which leads to increased
profits that are then invested in new goals (demand
diversity). From the provider perspective, specialization
can lead to high talent, high technology, or superior
environment-enabled performances for creating
value. Specialization leads to the need for trusting
others and coordinating activity across potentially
vast networks (with or without central control). As
a result, service system evolution is a special case of
meaning-creation in sociotechnical system evolution,
in which value is one locus of meaning and design
(Trist 1981, Engelbart 1963, Simon 1996). The types
of service businesses and their capabilities are also
evolving (Hofferberth 2004).
By understanding where demand is likely to head
(consumer preference knowledge) as well as opportunities
and challenges created by the other players
and resources on the field (environmental resources
and risks knowledge), many service providers seek
to maximize returns from profits by investing in
innovation and other practical change to grow revenue,
cut costs, and improve relationships that cocreate
more profits and value (production capability
knowledge). One thing that makes decision making
difficult is anticipating the actions of others
(Brandenburger and Nalebuff 1995). In a service system,
economic entities lie along a continuum from
self-sufficient interactions with the environment to
highly specialized production-consumption relationships
with others (Hawley 1986, Seabright 2004,
Prahalad and Ramaswamy 2004). Improving the productivity
of interactions (Butler et al. 1997, McAfee
2005) and labor productivity (Lewis 2004, Patterson
2001, Gilbert 1978) are key targets of service innovation,
including innovation in measuring productivity
(Triplett and Bosworth 2004, Brynjolfsson and
Hitt 2000).
Decisions that clients and providers make in a service
system largely determine the way the service
system evolves (assuming a stable environment, as
well as many other assumptions dealing with complex
adaptive system evolution). For example, Oliva
(2001) and Oliva and Sterman (2001) examine service
systems in which demand increases can lead to
a number of alternative provider responses, such as
service personnel increasing effort, personnel cutting
corners, or management investing in more capacity.
Some service system designs allow service personnel
to make the decision to invest in increasing
capacity. Understanding service system dynamics and
service system evolution at the level of the model
presented by Oliva and Sterman is still relatively
rare. There are tremendous opportunities for service
researchers to develop models with high relevance
to service operations. For example, understanding an
optimal investment strategy between high talent, high
technology, and superior environment would be of
enormous value to service providers. Other fundamental
investment choices are between exploitation
and exploration (March 1999) and between generalists
and specialists in an organization (Cataldo et al. 2000).
Figure 5 presents a model for understanding work
evolution in a service system, a type of sociotechnical
system. Under certain conditions work systems
can evolve from fully human systems (people working
together) to technology augmented systems (people
using tools), to delegation across firm boundaries
(outsourcing process), to fully automated (technologyonly)
processes. The trick lies in understanding or
predicting when or how each of the transitions may
be made. In this model, the choice to change work
practices requires answering four key questions: (1)
Should we (what is the value)? (2) Can we (do
we have the technology)? (3) May we (do we have
Figure 5 Framework for Thinking About Work Evolution in Service
Systems
Human system
Collaborate Augment
Automate
(self-service)
Delegate
(outsource)
Help me
by doing
some of
it for me
Organize people
(Socioeconomic models
with intentional agents)
Harness nature
(Technoscientific models
with stochastic parts)
43
21
Z
Collaborate
(1970)
Augment
(1980)
Automate
(2010)
Example: Call centers
Tool system
(tool)(incentives)
Help me
by doing
all of it
for me
Delegate
(2000)
Note. Based on Englebart’s 1963 notion of human augmentation or human
systems and tools systems’ coevolution.
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
244 Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society
authority or governance)? (4) Will we (is this one of
our priorities)? For example, consider the way call
centers have evolved over the decades. Early technology
call centers in the 1970s were often staffed with
the actual developers and key technologists who had
developed a technology. This is sometimes still the
case when calling a young start-up company for technical
support. However, as demand rises, it makes
sense to provide average performers with a superior
environment (e.g., computers with a Frequently
Asked Questions tool). Later, as demand continues to
rise and competition increases, it may be possible to
outsource or delegate the call center component of
the business to a service provider in India. Finally, as
technology advances, websites and automated speech
recognition systems can provide automated or selfservice
assistance to clients with questions. A parametric
model of work evolution, like the Oliva and
Sterman (2001) model of service quality erosion, is
another challenge for service scientists to undertake.
One other major area that should not be neglected
in this discussion of service science research questions
deals with results from historical economics as well as
experimental economics related to perceptions of trust
and fairness (Seabright 2004). Because service systems
can evolve into highly interdependent collections of
entities, possibly dependent on global-scale “service
value chains,” understanding the evolution of trust
and mechanisms for supporting and enforcing trust
are of great interest (e.g., eBay’s reputation system).
The importance of trust is another reminder that service
systems are a special type of sociotechnical system
in which construction of meaning is focused on
value, such as that created by imbalances in supply
and demand.
The range of research questions with scientific and
practical importance for service scientists to tackle is
extensive. The literature on service research and service
science is now growing (e.g., Hefley and Murphy
2008, Maglio and Spohrer 2008, Spohrer and Riecken
2006). As the community of interest in service science
grows, we will expect to begin to see a systematic
enumeration of service research questions and
answers (Gupta et al. 2006, Smith et al. 2007). But this
has only just begun.
5. Concluding Remarks
The growth of the service sector of the economy
is truly a wonder of human history, on par with
the agriculture revolution and the industrial revolution.
But is it too broad and diverse to be a suitable
area of scientific study? Or is it possible to understand
the evolution of service systems in terms of a
few simple principles that provide powerful frameworks
to explore core research questions? For example,
can service systems be understood in terms of
specialization to create value networks and the cost
of allocating knowledge among high talent, high technology,
and superior environment portions of the system?
Or can they be understood in terms of the
unequal evolution of know-how in different industry
sectors (Nelson 2003)? Will new agent-based simulation
tools reveal the secrets of service system
evolution, in terms of industry evolution and organizational
change? Will greater knowledge of service
systems lead to a more disciplined and systematic
approach to service innovation?
Now, many people at IBM and elsewhere talk about
an even broader approach: service science, management,
and engineering (SSME), which is defined as
the application of scientific, management, and engineering
disciplines to tasks that one person, organization,
or system beneficially performs for and
with another person, organization, or system (Maglio
et al. 2006). This expanded name for service science
is useful, as it indicates directly the need for
an integrated approach that spans not only existing
discipline-based silos within academic organizations
(i.e., marketing, operations, and human resource management
within a business school) but also across
academic organizations (i.e., business, engineering,
and liberal arts). An interesting phenomenon occurs
when interdisciplinary efforts lead to generalists that
after some time become the new specialists (Spohrer
et al. 2006). Something like this happened in computer
science, which combined software and algorithm
complexity theory as well as hardware and
logic design into a new specialty that increased our
understanding of computation in technological systems.
Perhaps service science will combine multiple
disciplines to form a new specialty that increases our
understanding of value co-creation in sociotechnical
systems. Ultimately, this deeper understanding of service
system evolution could lead to more systematic
approaches to service innovation. Service innovations
have the potential to impact service productivity, service
quality, and rates of growth and return for service
systems.
Acknowledgments
The authors thank Wendy Murphy, the SSME Project
Manager, and everyone else in Almaden Service Research
for their many insights as the authors have learned about
services together (see http://www.almaden.ibm.com/asr/).
Rob Barrett was instrumental in helping the authors
define the need for a new research group, and Robert
Morris was instrumental in creating it. Henry Chesbrough
and Paul Horn moved the idea of a science of service
forward; their efforts were assisted by Rosanne Mehelas,
John Zuk, Gerry Mooney, Ed Bevan, Chuck Rieger,
Jean Paul Jacob, Brenda Dietrich, Dan Connors, Stu
Feldman, Irving Wladawsky-Berger, Ruoyi Zhou, Lilian
Wu, Matt Berry, George Pohle, Doug McDavid, Jeanette
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society 245
Blomberg, Jane Harper, Jim Cortada, Laura Anderson, Ben
Amaba, Gina Poole, Dianne Fodell, and other colleagues
at IBM (see http://www.ibm.com/university/ssme). The
authors have learned a lot from workshops held on this
topic over the last several years, including March 2003:
IBM-Berkeley Day: Technology At Your Service! (see
http://www.eecs.berkeley.edu/IPRO/IBMday03/), September
2003: Coevolution of Business-Technology Innovation
Symposium (see http://www.almaden.ibm.com/
coevolution/), April 2004: Almaden Institute: Work
in the Era of the Global, Extensible Enterprise (see
http://www.almaden.ibm.com/institute/2004/), May 2004:
“Architecture of On Demand” Summit: Service science: A
new academic discipline? (see http://www.almaden.ibm.
com/asr/SSME/facsummit.pdf), and November 2004:
Service Innovations for the 21st Century (see http://www.
almaden.ibm.com/asr/events/serviceinnovation). In particular,
Mike Radnor, Ram Akella, Uday Apte, Uday
Karmarkar, Jim Fitzsimmons, Jim Tien, Daniel Berg, Roland
Rust, Mark Davis, Scott Sampson, Bob Lusch, Tarek Khalil,
Matthias Hild, Bill Rouse, Nirmal Pal, Jim Thomas, John
Sargent, Bob Lusch, Steve Vargo, Sheila Tobias, Carl
Schramm, Marco Iansiti, Tom Malone, Mary Jo Bitner, Steve
Brown, Suvrajet Sen, Matthew Realff, Hal Varian, Drew
Isaacs, and Rhonda Righter have provided crucial insights
and help. This article was improved with the comments of
two anonymous reviewers. Finally, the authors especially
thank Jim March for needed encouragement and inspiration
at the outset of this endeavor and for his continuing wise
counsel and perspective.
References
Apte, U. M., H. K. Nath. 2007. The size, structure and growth of the
U.S. information economy. U. M. Apte, U. S. Karmakar, eds.
Managing in the Information Economy Current Research Issues.
Springer, Norwell, MA, 1–28.
Asprey, W., B. O. Williams. 1994. Arming American scientists: NSF
and the provision of scientific computing facilities for universities,
1950–1973. IEEE Ann. Hist. Comput. 16(4) 60–74.
Baba, M. L. 1995. The cultural ecology of the corporation: Explaining
diversity in work group responses to organizational transformation.
J. Appl. Behav. Sci. 31(2) 202–233.
Baruch, J. J., J. B. Quinn, P. C. Paquette. 1987. Technology in services.
Sci. Amer. 257(2) 50.
Baumol, W. J., W. G. Bowen, 1968. Performing Arts: The Economic
Dilemma. MIT Press, Cambridge, MA.
Bell, D. 1999. The Coming of Post-Industrial Society A Venture in Social
Forecasting. Basic Books, New York.
Berry, L. L. 1980. Services marketing is different. Business
(May–June) 24–29.
Brandenburger, A. M., B. J. Nalebuff. 1995. The right game:
Use game theory to shape strategy. Harvard Bus. Rev. 76(3)
57–71.
Brynjolfsson, E., L. M. Hitt. 2000. Beyond computation: Information
technology, organizational transformation and business performance.
J. Econom. Perspectives 14(4) 23–48.
Bryson, J. R., P. W. Daniels, B. Warf. 2004. Service Worlds People,
Technology, Organizations. Routledge, London.
Bureau of Labor Statistics, U. S. Department of Labor. 2005.
Occupational Outlook Quart. 49(4, Winter 2005-6), http://www.
bls.gov/opub/ooq/2005/winter/contents.htm.
Butler, P., T. W. Hall, A. M. Hanna, L. Mendonca, B. Auguste,
J. Manyika, A. Sahay. 1997. A revolution in interaction.
McKinsey Quart. 1 4–23.
Carley, K. M. 2002. Smart agents and organizations of the future.
L. Lievrouw, S. Livingstone, eds. The Handbook of New Media.
Sage, Thousand Oaks, CA, 206–220.
Cataldo, M., K. M. Carley, L. Argote. 2000. The effect of personnel
selection schemes on knowledge transfer. Presentation, 9th
Internat. Conf. Comput. Anal. Soc. Organ. Systems, July 22,
Center for Computational Analysis of Social and Organizational
Systems, Pittsburgh.
Chase, R. B. 1978. Where does the customer fit in a service operation?
Harvard Bus. Rev. 56(6) 137–142.
Chase, R. B., D. A. Tansik. 1983. The customer contact model for
organization design. Management Sci. 29(9) 1037–1050.
Chesbrough, H. 2004. A failing grade for the innovation academy.
Financial Times (September 25) 6.
Chesbrough, H. 2005. Toward a science of services. Harvard Bus.
Rev. 83(2) 16–17.
Clark, C. 1957. The Conditions of Economic Progress. Macmillan,
New York.
Colecchia, A., D. Guellec, D. Pilat, P. Schreyer, A. Wyckoff. 2002.
A New Economy The Changing Role of Innovation and Information
Technology in Growth. Organisation for Economic Co-operation
and Development, Paris.
Davis, M. M., I. Berdrow. 2008. Service science: Catalyst for change
in business school curricula. IBM Systems J. 47(1) 29–40.
Engelbart, D. C. 1963. A conceptual framework for the augmentation
of man’s intellect. P. W. Howerton, D. C. Weeks, eds. Vistas
in Information Handling. Spartan Books, Washington, D.C., 1–29.
Fitzsimmons, J. A., M. J. Fitzsimmons. 2005. The Role of Services in
an Economy. Service Management Operations, Strategy, and Information
Technology, 4th ed. McGraw-Hill, New York.
Fuchs, V. R. 1968. The Service Economy. National Bureau of Economic
Research, New York.
Fuchs, V. R. 1985. An agenda for research on the service sector. R. P.
Inman, ed. Managing the Service Economy Prospect and Problems.
Cambridge University Press, Cambridge, UK, 319–326.
Gadrey, J. 2002. The misuse of productivity concepts in services:
Lessons from a comparison between France and the
United States. J. Gadrey, F. Gallouj, eds. Productivity, Innovation
and Knowledge in Services New Economic and Socio-Economic
Approaches. Edward Elgar, Cheltenham, UK, 26–53.
Gilbert, T. F. 1978. Human Competence Engineering Worthy Performance.
McGraw Hill, New York.
Glushko, R. J. 2008. Designing a service science discipline with discipline.
IBM Systems J. 47(1) 15–28.
Gronroos, C. 1990. Service Management and Marketing. Lexington
Books, Lexington, MA.
Gupta, S., R. Verma, L. Victoriano. 2006. Empirical research published
in Production and Operations Management (1992–2005):
Trend and future directions. Production Oper. Management 15(3)
432–448.
Hauknes, J. 1996. Innovation in the service economy. STEP
report, ISSN 0804-8185. STEP Group, Oslo, http://www.step.
no/reports/Y1996/0796.pdf.
Hawley, A. H. 1986. Human Ecology A Theoretical Essay. University
of Chicago Press, Chicago.
Hefley, B., W. Murphy. 2008. Service Science, Management and
Engineering Education for the 21st Century. Springer, New York.
Herzenberg, S. A., J. A. Alic, H. Wial. 1998. New Rules for a New
Economy Employment and Opportunity in Post-Industrial America.
Cornell University Press, Ithaca, NY.
Hill, T. P. 1977. On goods and services. Rev. Income Wealth 23(4)
315–338.
Spohrer and Maglio: Toward Systematic Service Innovations to Accelerate Co-Creation of Value
246 Production and Operations Management 17(3), pp. 238–246, © 2008 Production and Operations Management Society
Hilsenrath, J. E. 2003. Behind surging productivity sector: The service
sector delivers. Wall Street Journal (November 7) 1.
Hofferberth, R. D. 2004. Service Execution and Control Market
Analysis Enterprise Solutions Respond to Meet the Needs of a
Global Service Economy. Aberdeen Group, Boston.
Horn, P. 2005. The new discipline of services science. BusinessWeek
(January 21). http://www.businessweek.com/technology/
content/jan2005/tc20050121_8020.htm.
International Labor Organization. 2007. Global Employment Trends
Brief, January 2007. http://www.ilo.org/public/english/
employment/strat/download/getb07en.pdf.
Jones, D. 2004. Add science, business, mathematics and stir. New
degree offers career outside labs. USA Today (July 19) 1B.
Karmarkar, U. 2004. Will you survive the services revolution?
Harvard Bus. Rev. 82(6) 100–107.
Larson, R. C. 2008. Service science: At the intersection of management,
social, and engineering sciences. IBM Systems J. 47(1)
41–52.
Lewis, W. W. 2004. The Power of Productivity Wealth, Poverty, and the
Threat of Global Stability. University of Chicago Press, Chicago.
Lovelock, C. H. 1983. Classifying services to gain strategic marketing
insight: The diversity of service sector makes it difficult
to come up with managerially useful generalizations concerning
marketing practice in service organizations. J. Marketing 47
9–20.
Maglio, P. P., J. Spohrer, eds. 2008. Special issue: Service science,
management, and engineering. IBM Systems J. 47(1) 1–192.
Maglio, P. P., S. Srinivasan, J. T. Kreulen, J. Spohrer. 2006. Service
systems, service scientists, SSME, and innovation. Comm. ACM
49(7) 81–85.
Malone, T. W. 2004. The Future of Work How the New Order of Business
Will Shape Your Organization, Your Management Styles, and
Your Life. Harvard Business School Press, Cambridge, MA.
Malone, T. W., R. Laubacher, M. S. S. Morton. 2003. Inventing the
Organizations of the 21st Century. MIT Press, Cambridge, MA.
March, J. G. 1988. Decisions and Organizations. Blackwell, Oxford,
UK.
March, J. G. 1999. The Pursuit of Organizational Intelligence.
Blackwell, Oxford, UK.
March, J. G., H. A. Simon. 1993. Organizations, 2nd ed. Blackwell,
Cambridge, MA.
McAfee, A. 2005. Will web services really transform collaboration?
MIT Sloan Management Rev. 6(2) 78–84.
Murmann, J. P. 2003. Knowledge and Competitive Advantage The
Coevolution of Firms, Technology, and National Institutions.
Cambridge University Press, Cambridge, UK.
Nelson, R. R. 2003. On the uneven evolution of human know-how.
Res. Policy 32 909–922.
Newcomber, E. 2002. Understanding Web Services XML, WSDL,
SOAP, and UDDI. Addison-Wesley Professional, New York.
Oliva, R. 2001. Tradeoffs in responses to work pressure in the service
industry. California Management Rev. 43(4) 26–43.
Oliva, R., J. D. Sterman. 2001. Cutting corners and working overtime:
Quality erosion in the service industry. Management Sci.
47(7) 894–914.
Paloheimo, K. S., I. Miettinen, S. Brax. 2004. Customer Oriented
Industrial Services. BIT Research Centre, University of
Technology, Helsinki. http://www.hcl.hut.fi/docs/Customer_
Oriented_Industrial_Services.pdf.
Patterson, F. 2001. Developments in work psychology: Emerging
issues and future trends. J. Occupational Organ. Psych. 74
381–390.
Pilat, D. 2003. ICT and Economic Growth Evidence from OECD
Countries, Industries, and Firms. Organisation for Economic Cooperation
and Development, Paris.
Pine, II, B. J., J. H. Gilmore. 1999. The Experience Economy Work
Is Theatre and Every Business a Stage. Harvard Business School
Press, Cambridge, MA.
Porat, M. U., M. M. Rubin. 1977. The Information Economy, Vol. 9.
Office of Telecommunications Special Publication 77-12, U.S.
Department of Commerce, Washington, D.C.
Prahalad, C. K., V. Ramaswamy. 2004. The Future of Competition
Co-Creating Unique Value with Customers. Harvard University
Press, Cambridge, MA.
Rouse, W. B. 2004. Embracing the enterprise: Industrial and systems
engineering must step up to a larger challenge. Indust. Engineer
(March) 32–35.
Roztocki, N. 1998. Introduction to Activity Based Costing (ABC).
Internet ABC Online Presentation. http://www.pitt.edu/
∼roztocki/abc/abctutor/.
Rust, R. 2004. A call for a wider range of service research. J. Service
Res. 6(3) 211.
Sampson, S. E. 2001. Understanding Service Businesses Applying Principles
of Unified Services Theory, 2nd ed. John Wiley & Sons,
New York.
Sampson, S. E., C. M. Froehle. 2006. Foundations and implications
of a proposed unified services theory. Production Oper. Management
15(2) 329–343.
Sasser, E., R. P. Olsen, D. Wyckoff. 1978. Management of Service Operations.
Allyn and Bacon, Boston.
Seabright, P. 2004. The Company of Strangers A Natural History of
Economic Life. Princeton University Press, Princeton, NJ.
Sen, A. 1999. Development as Freedom. Random House, Anchor
Books, New York.
Simon, H. A. 1996. The Sciences of the Artificial. MIT Press,
Cambridge, MA.
Smith, J. S., K. R. Karwan, R. E. Markland. 2007. A note on the
growth of research in service operations management. Production
Oper. Management 16(6) 780–790.
Spohrer, J., D. Riecken, eds. 2006. Special section on services science.
Comm. ACM 49(7) 31–90.
Spohrer, J., P. P. Maglio, J. Bailey, D. Gruhl. 2007. Steps toward a
science of service systems. Computer 40(1) 71–77.
Spohrer, J., P. P. Maglio, D. McDavid, J. W. Cortada. 2006. Convergence
and coevolution: Towards a services science. W. S.
Bainbridge, M. C. Rocco, eds. Managing Nano-Bio-Info-Cogno
Innovations Converging Technologies in Society. Springer, New
York, 227–253.
Tanninen-Ahonen, T. 2003. Professional Business Services The Key to
Innovation. Institute for the Future (IFTF) 2003 Ten-Year Forecast,
Menlo Park, CA.
Tesfatsion, L. 2002. Agent-based computational economics: Growing
economies from the bottom up. Artificial Life 8(1) 55–82.
Tidd, J., F. M. Hull. 2003. Service Innovation Organizational Responses
to Technological Opportunities and Market Imperatives. Imperial
College Press, London.
Tien, J. M., D. Berg. 2003. A case for service systems engineering.
J. Systems Sci. Systems Engrg. 12(1) 113–128.
Triplett, J. E., B. P. Bosworth. 2004. Productivity in the U.S. Services
Sector New Sources of Economic Growth. Brookings Institution
Press, Washington, D.C.
Trist, E. L. 1981. The sociotechnical perspective: The evolution of
sociotechnical systems as a conceptual framework and as an
action research program. A. H. Van De Ven, W. F. Joyce, eds.
Perspectives on Organization Design and Behavior. John Wiley &
Sons, New York, 19–75.
Vargo, S. L., R. F. Lusch. 2004. Evolving to a new dominant logic
for marketing. J. Marketing 68 1–17.
Zeithaml, V. L., M. J. Bitner. 1996. Services Marketing. McGraw-Hill,
New York.