Seventeen cases worldwide of the use of smart cards in public transport.

1. European Journal of Information Systems (2009) 18, 38–51
& 2009 Operational Research Society Ltd. All rights reserved 0960-085X/09
www.palgrave-journals.com/ejis/
Information capability and value creation
strategy: advancing revenue management
through mobile ticketing technologies
Ting Li, Abstract
Using the process-oriented view and resource-based theory, we investigate
Eric van Heck and
how mobile ticketing technologies can successfully enable revenue manage-
Peter Vervest ment. We collect data from 17 cases worldwide in which smart cards and
mobile devices have been adopted in the public transport industry over the last
Department of Decision and Information decade. The use of these technologies allows service providers to capture real-
Sciences, RSM Erasmus University,
time and complete information of customers’ actual travel. This enables service
The Netherlands
providers to employ advanced price differentiation and service expansion
Correspondence: Ting Li, Department of strategies and achieve new ‘best practice’ in revenue management. The results
Decision and Information Sciences, RSM demonstrate that service providers that use more sophisticated mobile
Erasmus University, P.O. Box 1738, ticketing technologies are more likely to adopt advanced strategies to create
3000 DR Rotterdam, The Netherlands. value. Further, they are more likely to achieve higher performance gains.
Tel: þ 31 0 10 408 1961; European Journal of Information Systems (2009) 18, 38–51. doi:10.1057/ejis.2009.1;
Fax: þ 31 0 10 408 9010; published online 17 February 2009
E-mail: tli@rsm.nl
Keywords: information capability; mobile ticketing; public transport; revenue manage-
ment; smart cards; value creation
Introduction
The past decade has witnessed an increase in the application of revenue
management. Firms use various quantitative analysis techniques such as
customer segmentation and pricing optimization to allocate capacity and
manage demand. The success of firms such as American Airlines (Smith
et al., 1992) and National Car Rental (Geraghty & Johnson, 1997) has
encouraged scholars (Talluri & van Ryzin, 2004; Garrow et al., 2007) and
practitioners (Riddell, 2006) to explore the possibilities of leveraging
detailed customer data for revenue management. This process is further
accelerated by the increased implementation of advanced information
technologies (IT). For example, using mobile ticketing technologies
enabled by smart card and mobile devices, firms can learn about customer
behavior with far more precision. This permits them to adjust their services
and prices to improve their revenues and operations. Hence, there
has been a growing interest in information systems (IS) research to
study revenue management supported by mobile ticketing technologies
(Elmaghraby & Keskinocak, 2003; Talluri & van Ryzin, 2004).
Recently, strategic pricing decisions in the presence of IT has become an
Received: 18 February 2008
active area in the IS discipline (Brynjolfsson & Smith, 2000; Clemons et al.,
Revised: 1 July 2008
2nd Revision: 15 October 2008 2002; Bergen et al., 2005; Oh & Lucas, 2006; Kauffman & Wood, 2007).
3rd Revision: 17 November 2008 Earlier research has provided evidence of the important role that IT plays
4th Revision: 2 January 2009 in supporting pricing-related decisions. On the demand side, IT increases
Accepted: 12 January 2009 market transparency by lowering customers’ search costs for product

2. Information capability and value creation strategy Ting Li et al 39
and service information (Bakos, 1997). On the supply propositions. Then, we introduce our research methodol-
side, IT creates opportunities for firms to adjust their ogy and construct measurement. Subsequently, we
pricing decisions (Bergen et al., 2005; Kauffman & Wood, present the analysis and results. Finally, we conclude
2007). IT enables companies to set prices with higher with discussions and directions for future research.
precision, segment customers more accurately, track
customer behavior, and adjust prices promptly. Pricing Theoretical perspective
strategies present a rich opportunity to apply IT and IS to In this section, we present and discuss the process-
create and sustain competitive advantage. Earlier research oriented view, resource-based theory, and revenue man-
suggests that the increased adoption and development of agement literature. These theoretical perspectives help us
dynamic pricing and revenue management can be identify a basis for formulating our conceptual model and
attributed to the increased availability of demand data, propositions.
the ease of changing prices due to IT, and the availability
of decision-support tools that handle large-scale optimi- A process-oriented view of business value of IT
zation (Elmaghraby & Keskinocak, 2003). The business value of IT has long been a subject for
Though the role of IT in revenue management is often research and intensive debate (Brynjolfsson & Hitt, 1996;
acknowledged (Kimes, 2001; Elmaghraby & Keskinocak, Dewan & Kraemer, 2000). Using production theory,
2003; Talluri & van Ryzin, 2004), we have found limited previous research has demonstrated the payoffs of IT
systematic research examining the impacts of the use of investment at the firm level (Brynjolfsson & Hitt, 1996;
customer demand data on the performance of revenue Gurbaxani et al., 2000; Duliba et al., 2001), the industry
management strategies. Our research addresses this void level (Devaraj & Kohli, 2003), and the economy level
by empirically studying the business value of IT in (Dewan & Kraemer, 2000). Recent IS studies have
revenue management. Specifically, we are motivated by reframed the discussion, from the direct performance
the recent adoption of smart cards and mobile technol- impact of IT investment (Brynjolfsson & Hitt, 1996; Hitt
ogies (Turban & Brahm, 2000), and by calls from scholars & Brynjolfsson, 1996) to how and why IT shapes the
(Shugan, 2004; Talluri & van Ryzin, 2004; van Ryzin, higher-order process capabilities that create performance
2005). We explore the following research questions: What gains for firms (Barua et al., 2004). Using the process-
is the business value of mobile ticketing technology? How and oriented view, this stream of literature focuses on the
why does the improved IT and customer information advance usage and value creation of IT innovations (Zhu &
firms’ revenue management? Consequently, what are the Kraemer, 2005). The process-oriented view suggests that
impacts on firm performance? firm level impact of IT can only be measured through its
Using the process-oriented view, we argue that firms intermediate process contributions (Barua et al., 2004).
that use smart cards and mobile technologies will create a The argument here is that IT is deployed in support of
higher-order process capability (i.e., value creation strat- specific activities and purposes, and therefore, the impact
egy), which then leads to performance gains for them. In of IT should be assessed at the place where the first-order
particular, we suggest that the use of mobile ticketing effects are expected to be realized.
technologies enables firms to benefit from revenue This approach is also consistent with a second stream
management. We employ a multiple case study approach of research that takes a contingency approach, suggesting
(Eisenhardt, 1989) and test our arguments through a that the need is to consider other variables that may
study of 17 cases in which mobile ticketing technologies mediate or moderate firm performance. Firms first focus
were implemented over the last decade. The results pro- on their business strategies and then allocate IT resources
vide evidence that firms using detailed customer beha- to support their core competencies. IT is viewed as an
vior information are able to use very advanced price enabler of specific strategies designed to achieve superior
differentiation and service expansion strategies. Further, performance (Fairbank et al., 2006).
these firms are most likely to achieve higher performance.
We chose the public transport industry (including bus, Resource-based theory
tram, metro, and railway) as our research setting for two Strongly based on the strategic management literature,
reasons. First, the increased adoption of IT, such as smart the resource-based view of the firm posits that firms
cards and mobile technologies in the last decade has compete on the basis of unique corporate resources that
allowed public transport operators (PTOs) to explore are valuable, rare, difficult to imitate, and non-substitu-
opportunities of revenue management that were not table by other resources. In the IS literature, resource-
possible earlier. Second, there is a strong need for PTOs to based view has been used to analyze IT capabilities
seek for solutions to reduce the concentrations of peak and to explain how IT business value resides more in
travel, which causes problems such as over-crowding, the organization’s skills to leverage IT in the key acti-
dissatisfied customers, low capacity utilization, and low vities in a firm’s value chain (Bharadwaj, 2000). The
revenue. greater the use, the more likely the firm is to deve-
The remainder of this paper is organized as follows. lop unique capabilities, and the firm’s core IT infra-
First, we introduce our main theoretical perspectives. structure generates higher value (Bharadwaj, 2000; Zhu &
Next, we explain our conceptual model and develop the Kraemer, 2005). According to Zhu & Kraemer (2005),
European Journal of Information Systems

3. 40 Information capability and value creation strategy Ting Li et al
Information Capability
Mobile Ticketing Technology
-Smart Card
-Mobile Technology
Value Creation Strategy
P1 -Baseline (access control) P2 Firm Performance
-Price differentiation
Customer Behavior Information -Service expansion
-Who: Customer
-What: Ticket type
-Where: Origin and destination
-When: Departure and arrival time
-How: Travel mode
Figure 1 Conceptual model.
resource-based theory provides a theoretical basis for should have relatively high fixed costs but low marginal
linking IT use and value creation. costs of production. Last, a firm should have the capacity
to capture abundant customer data via IT. Advanced
Revenue management theory infrastructure is needed to collect and store demand data
Revenue management deals with selling the right product and automate pricing decisions.
to the right customers at the right time for the right price
to maximize firm revenue (Kimes, 2001). There are two Conceptual model and propositions
main methods in revenue management: quantity-based Using the process-oriented view and resource-based
and price-based revenue management (Talluri & van theory, we now develop a conceptual model to explore
Ryzin, 2004). Quantity-based revenue management fo- the use and value of mobile ticketing technology in
cuses on optimal product allocation. Price-based revenue developing revenue management strategies. We present
management mainly deals with the demand side of the our conceptual model (see Figure 1), explain the key
supply-demand equation. In the public transport indus- elements of the model, and propose two propositions.
try, the price-based method (i.e., price and service
differentiation) is more appropriate. This is because by Information capability
using mobile ticketing technologies, PTOs can easily set We define information capability as a firm’s ability to
and adjust prices at minimal costs while at the same time capture the complete customer behavior information. In
receiving customers’ instantaneous feedback. Further, our research context, customer behavior information
Talluri & van Ryzin (2004) suggest that the price-based refers to the customer (who), the ticket type (what), the
method is the most preferred approach to revenue origin and destination (where), the departure and arrival
management. time (when), and the travel mode (how). This is measured
Not all firms are able to employ revenue manage- by the ability of the IT to capture the dimensions and
ment strategies in their business. The ones where such attributes of customer behavior information that be-
strategies are possible have the following characteristics. comes available.
First, on the demand side, the higher the customer Mobile ticketing refers to the process whereby customers
heterogeneity, the more potential there is to exploit this order, pay for, obtain, and validate tickets using mobile
heterogeneity strategically and tactically to improve devices or contactless technologies such as smart cards. In
revenues (Talluri & van Ryzin, 2004). Demand should the public transport industry today, four types of
exhibit some kinds of variation, such as variations due to technologies are commonly used: paper tickets, magnetic
weather, changing patterns on holidays, and time-of-day cards, smart cards, and mobile phones. Paper tickets are
or day-of-week. Second, on the supply side, a firm should the most basic form and are used by a large number of
operate with a relatively fixed and inflexible capacity and PTOs. Dating back to 1960, magnetic cards, together with
production constraints. It may not be able to cope with electronic gates, were introduced to the transportation
variations in demand. Further, the products and services systems to provide customer access control. Since 1997,
it offers should be perishable and cannot be held in smart cards have become increasingly popular and are
inventory. Third, in a cost and pricing structure, firms gradually replacing magnetic cards. When a customer
European Journal of Information Systems

4. Information capability and value creation strategy Ting Li et al 41
uses a smart card, either to make a trip or to purchase a public transport industry in the past decade. With
travel product, the product details are captured and advanced IT, PTOs are able to learn about their customers’
linked to the card. If the customer has registered the card travel behavior in regard to the location to and from
under his name, all product and trip details will be added which they travel, what time they travel, how frequently
to this individual customer’s record. Mobile technology they travel, and what ticket they purchase, in (nearly)
is being adopted at an accelerated rate. For example, real-time. This permits the PTOs to explore the possibi-
Tokyo’s ‘Mobile SUICA,’ which includes a RFID chip is lities of developing revenue management strategies that
embedded into i-mode FeliCa’s mobile handsets. The were not possible earlier.
device was introduced in January 2006 in Tokyo and
gained more than 20,000 subscribers within a week
(SUICA, 2008). Value creation strategy
Rather than IT itself, information has been argued to be According to Porter (1996), a firm’s value creation strategy
the source of competitive advantage for firms. Despite a is defined as a set of value creation activities it carries out
considerable number of theoretical and empirical works in order to create and deliver value. We distinguish three
on the role of IT in creating competitive advantage, the value creation strategies that PTOs use: baseline strategy,
literature has identified a consistent lack of success by price differentiation strategy, and service expansion
firms in achieving business value through their IT strategy. This distinction is consistent with the two broad
investments, and in particular the difficulties in obtain- strategy categories that are discussed in the strategy
ing a sustained competitive advantage (Earl, 1989, 1992; literature (Porter, 1980): low cost leadership, which is our
Clemons & Row, 1991; Powell & Dent-Micallef, 1997). baseline strategy, and differentiation, which is price
The notion that IT per se does not generate sustainable differentiation or service expansion strategy.
performance advantage has received increasing support Baseline strategy refers to basic value creation, which
in the IS literature (Earl, 1989, 1992; Clemons et al., is the reason why PTOs implement mobile ticketing
1993). The ‘strategic necessity hypothesis’ (Clemons systems in the first place. Fare fraud is very costly for
et al., 1993) argues that firms cannot expect IT to produce PTOs, for example, it has been estimated to cost
sustainable advantage because most IT are readily avail- Metropolitan Atlanta Rapid Transit Authority an esti-
able to all firms – competitors, buyers, suppliers, and mated $10 million per year (Donsky, 2006). The primary
potential new entrants – in competitive markets. IT, reason for most PTOs to adopt mobile ticketing is to
hence, becomes a ‘strategic necessity’ but not a source of control customer access, prevent fare evasion, and reduce
competitive advantage. The exception is when firms use fraud. Of course, mobile ticketing also provides ease of
IT to leverage or exploit firm specific intangibles (Powell use for customers, improves passenger flows, reduces
& Dent-Micallef, 1997) to obtain sustained profits. ticket-purchasing queues, and reduces PTOs’ operating
Yet, despite the success in industries such as airlines costs through accelerating ticket purchase and reducing
and car rentals, the public transport industry faces clerical work.
difficulties in fully taking advantage of revenue manage- Differentiation strategy includes price differentiation
ment. The reasons are twofold. First, PTOs have limited and product/service differentiation. Porter (1980) argues
information about their customers’ actual travel beha- that differentiation strategy is an effective approach to
vior. Operations of the public transport are largely based create and sustain a firm’s competitive advantage. Service
on an open-access system that limits PTOs’ ability to providers that use differentiation strategy are able to
obtain customers’ information. In this situation, PTOs provide products and services that customers perceive to
mainly depend on in-vehicle counting and periodic be unique (Soh et al., 2006). An example familiar to most
survey to obtain customer behavior information. How- is airline ticketing. Airlines dynamically vary ticket prices
ever, these methods are usually expensive, labor-inten- and associated conditions based on real-time demand
sive, and time-consuming, and hence, customer travel and available capacity at any given departure time.
information largely remains outdated, inaccurate or even Service expansion strategy is also rooted in the strategy
unknown. Second, partially due to the limited informa- literature. It resembles the concept of virtual value chain
tion, PTOs have limited ability to predict the variable orchestration as discussed by Hinterhuber (2002). Service
demand. As opposed to airlines, PTOs do not have expansion strategy is a way to create and capture value
reservation systems that allow them to predict customer by structuring, coordinating, and integrating the activ-
arrivals. Thus, they are challenged in estimating the ities of previously separate markets. By relating these
demand variations of their heterogeneous customers. activities effectively to in-house operations, firms are
A senior manager, whom we interviewed stated that ‘it is able to develop a network of activities that create new
difficult to implement a profitable operating environ- markets. Service expansion is useful in this context
ment where our entire business strategy is based on an because electronic ticketing systems can provide micro-
‘open access’ system for flexible traveling, and revenue payment infrastructures that permit other service provi-
management is nearly impossible for us.’ ders to adopt them. As a result of this, service providers
This situation has started to change with the increased can increase their transactional efficiencies and expand
implementation of mobile ticketing technologies in the their services quickly into other industry sectors.
European Journal of Information Systems

5. 42 Information capability and value creation strategy Ting Li et al
Firm performance with a higher information capability are
Using mobile ticketing for value creation leads to changes more likely to use an advanced value
in PTOs’ cost structure, revenue, and customer volume. creation strategy (i.e. price differentiation
What is even more important is the reputation that PTOs or service expansion) than firms with a
create. Given PTOs’ social responsibility and public lower information capability.
pressure through governmental regulation, PTOs who
fail to justify the impacts of pricing strategies will receive
heavy criticism from the public and politicians (Li & Value creation strategy and firm performance
Wong, 1994; Link, 2004). Customers may express objec- Quantifiable results from revenue management are found
tions to crowding, unfairness, and fare complexity. in both management practice (Cross, 1997) and business
Consequently, this will lead to changes in customers’ solutions (McCartney, 2000). Bill Brunger, Continental
willingness-to-pay. Customers may even shift to other Airlines’ pricing guru (McCartney, 2000), pointed out
transport modes. For example, in December 2002, that ‘revenue management is all of our profit, and more.’
Deutsche Bahn (DB), using revenue management strat- Revenue management success stories are encouraging.
egy, launched a program to reform its fare structure, American Airlines had an estimated benefit of $1.4
focusing on the long-distance passenger market (Link, billion over a period of 3 years and an annual revenue
2004). Within half a year after the introduction the contribution of over $500 million (Smith et al., 1992).
program failed. This failure, in part, was caused by low National Car Rental improved revenue by $56 million in
acceptance and widespread criticism of the new pricing the first year after a successful implementation of a
structure. In the words of DB customers: ‘the price change revenue management system (Geraghty & Johnson,
is opaque and unfriendly,’ ‘the new price scheme is 1997).
confusing,’ and ‘the whole fare structure is in need of Grounded in the economics literature, price differen-
simplification to make it readily comprehensible and tiation is the most important revenue management
usable by staff and passengers.’ technique. It can date back to the concept of price
discrimination (Pigou, 1932). Price differentiation refers
Information capability and value creation strategy to any pricing policy under which a seller sets different
Information processing in organizations is generally prices on various units of the same or a similar product. It
defined as the gathering of data, the transformation of extracts a higher price from existing customers while
data into information, and the communication and extending sales to new customers who would otherwise
storage of information in the organization (Egelhoff, not be served with uniform pricing. Economic theory
1982). The conceptual underpinning of information indicates that price differentiation is inherently good for
processing theory is to enhance the capability to handle the profitability of the firm, because it allows the firm to
information flow and thereby reduce uncertainty. capture a larger share of the consumer surplus. The
Previous research suggests that the most effective orga- economics of revenue management suggests that the
nizational strategies are those that recognize an appro- more prices are differentiated by a firm the more revenue
priate fit between an organization’s ability to handle will be generated (Talluri & van Ryzin, 2004). Thus, we
information and the amount and type of information present our second proposition as follows (P2):
that is available or required (Tushman & Nadler, 1978;
Egelhoff, 1982). Mobile ticketing technology provides Proposition 2: (The Value Creation Strategy and Firm
PTOs with detailed customer behavior information that Performance Proposition): Firms that
was only partially attainable through traditional travel use a more advanced value creation strategy
surveys. Using this information, PTOs can derive the cost (i.e. price differentiation and service expan-
that customers are willing to pay in different market sion) will outperform firms that use a
segments. In contrast to time-consuming surveys, mobile baseline strategy.
ticketing technology gives almost instantaneous consu-
mer feedback. The improvement in information quantity
and information quality significantly reduces demand Research method
uncertainty. The information-processing notion of the We employ a multiple case study method (Benbasat et al.,
firms allows us to hypothesize a relationship between a 1987; Yin, 2002) to study large scale mobile ticketing
firm’s information capability and its choice of appro- systems that use smart cards in the public transport
priate value creation strategy. PTOs, who recognize the industry. Our study is focused on the time period
opportunities that the improved information capability between 1997 and 2006. This research design has several
provides, will align their activities to create value. Thus, advantages. First, the utilization of multiple cases allows
we present our first proposition as follows (P1): for cross-case analysis, which significantly improves the
investigation of the proposed research model (Benbasat
et al., 1987). Second, we control for industry variations
Proposition 1: (The Information Capability and Value related to performance by focusing on smart card
Creation Strategy Proposition): Firms adoption in the public transport industry. Smart card
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6. Information capability and value creation strategy Ting Li et al 43
adoption in other industries exhibits different perfor- introduction. Fourth, we are interested in the large-scale
mance levels, hence controlling for industry is necessary. smart card implementation in public transport, however
Third, studying the population in an industrial sector is technology adoption is an ongoing process and it is
useful, given the relatively small numbers of selected difficult to obtain the total number of cards that are sold
PTOs of this type. Using this research design we do not and in use. Thus, we used the population of the location
sample, but study all comparable PTOs in the industry. as a proxy for the size of a given smart card implementa-
As such, we study the entire population. tion. The argument here is that in large metropolitan
cities public transport is more important than in smaller
cities, where daily ridership is not so high. Fifth, for some
Case selection
cases, where more than one smart card is used, we
Contactless smart cards used to transfer electronic
eliminated the secondary card of the two. Although the
payments have gained widespread implementation in
directory listed 139 smart card cases worldwide, only 17
the public transport industry in the last decade and will
cases met our criteria: four cases in the United States, 10
become increasingly important for banks and retailers
cases in Asia, and three cases in Europe (see Table 1 for a
alike (Olsen, 2007). We used the ‘List of Smart Card’
list of the selected cases).
directory in Wikipedia (2008) to identify relevant cases.
We believe this list to be comprehensive and accurate for
two reasons. First, we have followed smart card develop- Data collection
ment over the past few years, and all the major initiatives Data were collected from various data sources using
that we are aware of are included. Second, we used different data collection methods with the objective of
alternative search methods (e.g., Google searches, and triangulation (Eisenhardt, 1989). Data collection was
industry magazine listings) to identify possible missing conducted in two phases. In the first phase, we selected
cases and no additional cases were added. three representative cases and collected data through
We used five criteria to select our cases. First, we only unstructured and semi-structured interviews, firm archi-
included cases from North America, Asia, and Europe, val data, public reports, and email exchanges. We did this
which cover more than 90% of the world-wide smart card at the beginning in order to establish a good under-
implementation. Second, the list we adopted is compre- standing of smart card adoption related to revenue
hensive and includes various types of smart card management and pricing decisions. We chose the
implementations. We only included cases where a smart Octopus card in Hong Kong, the Oyster card in London,
card is used for public transport (usually through and the OV-chipkaart in the Netherlands for three
different modes of transport) and excluded cases where reasons. First, these three cases employ different value
smart card is only used for retail or identification creation strategies. Octopus uses a service expansion
purposes. Third, we chose cases where the smart card strategy, Oyster uses price differentiation strategy, and
was introduced between 1997 and 2006. The year 1997 OV-chipkaart uses the baseline strategy. Second, this
was when the first smart card – the Octopus card in sample represents different stages of smart card adoption.
Hong Kong – was introduced. We thus excluded cases Octopus was the first and most successful adoption in the
where we did not have information on the time of world so far (Chau & Poon, 2003). Oyster reached a high
Table 1 Worldwide large-scale smart card technology adoption (selected cases)
Introduction Place Transportation service provider/issuing authority Name of smart card
1997 Hong Kong Octopus Cards Limited Octopus
1999 Washington DC Washington Metropolitan Area Transit Authority SmarTrip
1999 Shanghai Shanghai Public Transportation Card Co. Shanghai Public Transportation Card
2001 Singapore EZ-Link Private Ltd. EZ-Link
2001 Tokyo JR East and other 5 operators Suica
2001 Guangzhou Yang Cheng Tong Corporation Yang Cheng Tong
2001 Moscow Moscow Metro Transport Card
2002 Taipei Taipei Smart Card Corporation EasyCard
2002 Chicago Chicago Transit Authority Chicago Card
2004 Bangkok Bangkok Metro Bangkok Metro Smart Card
2004 London Transport for London Oyster Card
2004 Seoul Korea Smart Card Co. Ltd. T-money
2004 Shenzhen Shenzhen TransCard Corporation Shenzhen TransCard
2005 Atlanta Metropolitan Atlanta Rapid Transit Authority Breeze Card
2006 Beijing Beijing Municipal Administration and Communications Card Co. Yikatong
2006 Boston Massachusetts Bay Transportation Authority Charlie Card
2006 The Netherlands Trans Link Systems OV-chipkaart
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7. 44 Information capability and value creation strategy Ting Li et al
Table 2 Overview of interviewees ticketing technologies in terms of product characteristics,
process characteristics, and usability. Second, on the
Cases Number of Business unit/functions spectrum of customer behavior information, we analyzed
respondents
the data attributes that could be obtained from each
Octopus 6 General Manager mobile ticketing technology. Depending on the unique
Marketing Department (department characteristics of the type of technology and the number
manager) of data attributes that it captures, we distinguished
Operations Department (department between high and low levels of information capability.
manager) Ten PTOs had high information capability whereas seven
Strategy Development Department PTOs had relatively low information capability.
(department manager)
Value creation strategy PTOs or issuing authorities of
Oyster 3 Pricing Department (researcher)
smart cards pursue either a baseline strategy (access
Transport Research (consultants)
control/fare collection) or a differentiation strategy (i.e.,
OV-chipkaart 7 Business Development Department revenue management strategy and service expansion).
(department manager) We examined the purpose of smart card implementation
Tariff and Pricing (project manager) for each case and determined the construct of value
Marketing Research and Advice creation strategy.
(senior project leader) We identified a case as a baseline case if the PTOs or
Revenue Management (department issuing authorities use smart cards primarily for access
manager) control, providing convenience to customers, and redu-
Independent Research Firms cing operational costs, but not for pricing-related strate-
(independent consultants) gies. We identified the degree of use of price
differentiation strategy using the total number of pricing
schemes that PTOs employ as a proxy. Price differentia-
tion is very challenging to measure because nearly all
penetration rate within a relatively short period of time. PTOs use some form of differentiated pricing. Thus, it is
OV-chipkaart is the first nation-wide implementation, difficult to determine to what extent a PTO uses price
though it is still in its early phases of development. differentiation. Based on the price discrimination litera-
Further, these three cases also had large societal impacts ture (Pigou, 1932; Png, 1999), we developed a taxonomy
and received widespread media attention. In total, we to characterize the pricing practices in the public
conducted 16 interviews for these three cases (see Table 2). transport industry (Li et al., 2007). According to this
The interviewees are managers in strategy, pricing taxonomy, we coded each pricing scheme that each
and revenue management, and business development PTO uses, and then computed a differentiation score by
in three geographically different locations. Each step of summing the value of each pricing scheme that we
the research process is well documented, which enhances evaluated. If a PTO actively uses more than four types of
the reliability of our approach (Yin, 2002). pricing, we coded the case as actively exercising price
In the second phase of the data collection process, we differentiation. We identified service expansion strategy
collected archival data for the remaining cases from through the use of smart cards for multiple purposes,
company websites, corporate brochures, newspapers, and such as retail, library, and identification, rather than only
magazine reports. We reviewed relevant web pages from for transportation purposes (including highway toll gates,
press releases that made reference to any of the 17 cases. parking, and ferries). We found that six PTOs use a
We also reviewed news articles relating to the service baseline strategy, six PTOs use price differentiation, and
providers from LexisNexis Academic and some local news five PTOs use service expansion.
sources, such as Boston Globe. Capturing data both from
the firm as well as from external reports increases validity Firm performance We developed three qualitative indi-
and reliability in our data collection process. cators of firm performance based on the revenue manage-
ment and transportation literature (Talluri & van Ryzin,
Constructs and measurements 2004). These indicators are growth in revenue and
In this section, we define the constructs and measure- customer volume (Weatherford & Bodily, 1992), reputa-
ments used to operationalize our conceptual model. tion (Soh et al., 2006), and longevity (Soh et al., 2006). We
Table 3 summarizes the description of and coding for calculated ordinal measures for each performance con-
each construct. struct between 1997 and 2006, and we constructed a
performance index from the sum of these measures.
Information capability As discussed earlier, the four Growth in revenue and passenger volume measures how
types of technology commonly used in public transport much new revenue and how many new customers have
are paper tickets, magnetic cards, smart cards, and mobile been attracted. Reputation is computed based on the
technology. First, we analyzed these four types of mobile positive or negative information stated in the press
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8. Information capability and value creation strategy Ting Li et al 45
Table 3 Construct, definition, and measurement
Construct Definition Measurement
Information A firm’s ability to capture the 0 – Low: If less sophisticated information technology is being used and limited
capability complete behavior information in customer behavior information is captured
regard to what, where, when, how, 1 – High: If more sophisticated information technology is being used and
and whom of their customers (nearly) complete customer behavior information of actual travel is captured in
real-time
Mobile ticketing The sophistication of the mobile Product
technology ticketing technologies that are being Usage mechanism (1 – Contactless; 0 – Contact)
used, which is measured as the Memory (1 – High; 0 – Low)
unique characteristics of each Durability (1 – Durable; 0 – Low, easily damaged)
technology Data security (1 – High; 0 – Low)
Process
Obtainment (1 – Internet; 0 – Ticket office)
Transaction (1 – Can be viewed; 0 – Cannot be viewed)
Replenishment (1 – Can be reloaded; 0 – Cannot be reloaded)
Usability
Convenience (1 – High; 0 – Low)
Speed (1 – Fast; 0 – Slow)
Personalization (1 – Yes; 0 – No)
Customer behavior The completeness of the customer Number of data attributes that are captured by each mobile ticketing
information information of actual travel technology: for example, the location to and from which the customer travel,
frequency of travel, etc.
Value creation Value creation strategy that is used by 0 – Baseline: Smart card is primarily used for access control, fare collection, and
strategy the service provider providing speedy and convenient services
1 – Price differentiation: If there are more than four types of pricing schemes
used
2 – Service expansion: Besides public transport (including highway toll gates,
parking, and ferry), smart card is also widely used for retail, library,
identification, and other purposes
Price differentiation Price differentiation that the service Number of pricing schemes offered to the customers, minimum 0 and
provider uses maximum 8.
Uniform pricing
Profile-based pricing
Usage-based pricing
Distance-based pricing
Time-based pricing
Route-based pricing
OD-based pricing
Mode-based pricing
Firm performance The performance impact of the Sum of coded values for revenue growth/operational excellence, reputation,
service provider, in terms of revenue/ and longevity:
customer volume growth, reputation, Minimum of 0
and longevity Maximum of 6
Revenue/customer The increase in revenue and/or 0 – reduced
volume customer volume of the service 1 – no change
provider 2 – improved
Reputation The reputation among customers, 0 – negative
politicians, and general public 1 – neutral
2 – positive
Longevity Number of years since the adoption 0 – 0–2 years
of smart card of the service provider 1 – 3–5 years
2 – 6 years or above
European Journal of Information Systems

9. 46 Information capability and value creation strategy Ting Li et al
Table 4 Frequency cross-tabulation
Information capability Performance Value creation strategy
Baseline Price differentiation Service expansion Total
High High 0 4 5 9
Low 1 0 0 1
Low High 0 0 0 0
Low 5 2 0 7
Total 6 6 5 17
Table 5 Mobile ticketing technology comparison
Paper ticket Magnetic card Smart card Mobile
Product view
Usage mechanism Purchase ticket Contact: card has to be Contactless: card can be Contactless: card is
before/while traveling inserted into slot read in proximity embedded into mobile
Memory None Limited High, allow innovative Very high, allow interaction
pricing policy with other technology
Durability Low Easily damaged Low Durable (plastic) Durable
Data security Low (lost, stolen) (information lost through Medium (encryption, value High (mature security
demagnetization) could be retrieved if card is technology from telecom)
lost)
Process view
Obtainment Ticket office Ticket office Ticket office Internet
Ticket vending Ticket vending machine Ticket vending machine
machine Internet Internet
Transaction None Transactions can not be Transactions can be viewed Transactions can be viewed
viewed online on the mobile or online
Payment can be incorporated
into one single mobile bill
Replenishment None Card can not be reloaded Card can be reloaded online Automatic replenishment
Options are also available for
automatic replenishment
Usability
Convenience Low (cumbersome Medium High (avoid ticket Very high (no additional card
cash handling, purchasing) needed)
requires exact
change)
Speed (boarding Slow Slow Fast, speed up journey Fast, speed up journey
time)
Personalization No No Yes Yes
possibility
articles of the PTOs that we studied. Because PTOs have variables of the three dimensions. The indices show a
strong public roles, they cannot simply focus on revenue fair degree of variance from 0 to 6. Eight PTOs have a
maximization. They need to satisfy customers and score between 0 and 3, and seven PTOs have a score
politicians. Given the same increase in revenue and between 4 and 6.
customer volume, a firm with a better reputation may be Table 4 summarizes the frequency distribution of the
considered to be more successful than those with worse 17 PTOs by information capability, value creation
reputations. Longevity is computed from the number strategy, and performance.
of years since the introduction of the smart card, as stated
on the service providers’ website. This measure is Analysis and results
consistent with Soh et al. (2006). We computed an overall As suggested by the literature, we employed nonpara-
performance index for each PTO by summing the metric statistics rather than inferential statistics to validate
European Journal of Information Systems

10. Information capability and value creation strategy Ting Li et al 47
the propositions (Soh et al., 2006). Nonparametric Table 7 Validation of proposition 1
methods are preferable for three reasons. First, although
Value creation strategy Information capability
the number of selected cases is relatively small, we study
the whole population of the large-scale smart card High Low
adoptions in the public transport industry and thus do
Mean rank 11.65 5.21
not need to make assumptions relating to the population
Sum of ranks 116.50 36.50
distribution. Therefore, the distribution-free nature of the Count 10 7
nonparametric method is more appropriate for the Mann-Whitney U 8.50
analysis of the whole population than the small sample Wilcoxon W 36.50
size. Second, the ordinal scale of our construct measure- Test P-value** 0.006*
ment calls for the use of a nonparametric method, which
* Po0.01 (Higher rank indicates higher levels of value creation strategy).
yields higher power than the corresponding parametric ** Significant level.
tests. Third, rank-based nonparametric statistical tests are
not affected by outliers (Hollander Wolfe, 1999), and
hence are more suitable for the analysis of PTOs, where Table 8 Firm performance and value creation strategy
outliers are common. For example, Octopus is a clear crosstabs
outlier based on adoption rates and transaction volumes.
Value creation strategy Total
Baseline Price differentiation Service expansion
Information capability Firm performance
To operationalize the conceptual model, we first looked Low 6 2 0 8
at different types of mobile ticketing technologies used High 0 4 5 9
by PTOs. We then analyzed different data attributes of
customer behavior information that could be obtained Total 6 6 5 17
through mobile ticketing systems. We summarized the
differences among paper tickets, magnetic cards, smart
cards, and mobile technologies based on the unique
characteristics of product, process, and usability (see Information capability and value creation strategy
Table 5). Next, we examined the different data attributes Our validation of proposition 1 suggests that IT that
obtained by each mobile ticketing technology. We provides effective customer information allows PTOs to
categorized them into different information dimensions develop advanced value creation strategies (i.e., price
including service, purchasing, personal, temporal, and differentiation and service expansion). Table 6 shows
spatial. We found that paper tickets include the most that nine out of 10 PTOs that have high information
basic information on buying dimension (i.e., travel capability implemented revenue management strategy
product purchase time/date, location, and price) and with price differentiation or service expansion. By
service dimension (i.e., travel mode and vehicle type). contrast, five out of seven PTOs that have low informa-
Additionally, magnetic cards can capture temporal di- tion capability used a baseline strategy. We used the
mension information (i.e., time and date of departure). Mann-Whitney U test to examine the differences in value
Furthermore, smart cards add a detailed personal dimen- creation strategy between high and low information
sion (i.e., name, age, gender, address, and profession), capability. We tested against the null hypothesis of equal
whereas mobile technology includes full spatial dimen- value creation strategy for both high and low informa-
sional information (i.e., route and origin/destination) tion capability. We concluded that value creation strategy
and permits PTOs to easily and precisely capture the full is significantly different across the information capability
route and complete information of customer travel in the (P ¼ 0.006). Table 7 summarizes the results of our
entire transportation networks. nonparametric tests.
Table 6 Value creation strategy and information Value creation strategy and firm performance
capability crosstabs Our validation of proposition 2 suggests that service
providers are more likely to succeed with a value creation
Information capability Total strategy of price differentiation or service expansion.
Low High Table 8 shows that all high performance PTOs implement
either price differentiation or service expansion. The fact
Value creation strategy that two PTOs that use price differentiation are also low
Access control 5 1 6 performers is not inconsistent with our argument. A good
Price differentiation 2 4 6
strategy does not guarantee success – many other factors
Service expansion 0 5 5
influence success. In contrast, none of the baseline PTOs
Total 7 10 17
exhibited high performance. We validated proposition 2
using the same procedure used to validate proposition 1.
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11. 48 Information capability and value creation strategy Ting Li et al
Table 9 Validation of proposition 2
Firm performance Value creation strategy Value creation strategy Value creation strategy
Baseline Price differentiation Baseline Service expansion Price differentiation Service expansion
Mean rank 4.50 8.50 3.50 9.00 5.17 7.00
Sum of ranks 27.00 51.00 21.00 45.00 31.00 35.00
Count 6 6 6 5 6 6
Mann-Whitney U 6.00 0.00 10.00
Wilcoxon W 27.00 21.00 31.00
Test P-value 0.019* 0.002* 1.174
The main difference here is that we tested firm perfor- differentiation and/or service expansion strategies are
mance across the three value creation strategies. We more likely to have higher performance gains compared
concluded that PTOs that use price differentiation and to the ones that use only the baseline strategy.
service expansion outperform those with baseline strate- As theorized in the revenue management literature
gies (P ¼ 0.019 and 0.002). Table 9 summarizes the results (Talluri van Ryzin, 2004), the service providers that use
of the pair-wise comparison using Mann-Whitney tests. price differentiation tend to achieve higher performance.
Although ticketing systems are often seen as expensive
Findings and discussion investments in infrastructure, they can improve PTOs’
access control and enhance their operational efficiency.
Major findings and interpretations Further, the systems also provide improved information
The empirical validation of our propositions leads to two on customer behavior, which creates an opportunity to
major findings. optimize and individualize their service offerings. Im-
Finding 1: Service providers that use more sophisti- proved products and service offerings can justify the
cated mobile ticketing technologies (such as smart card investment premium. Our results suggest that the service
and mobile technology) and have real-time and complete providers that use price differentiation and service
information on customers’ actual travel, are more likely expansion strategy have a greater chance to be successful.
to adopt price differentiation and service expansion
strategy. Implications
From a product, process, and usability viewpoint, we The findings of our study have several implications for
examined the unique characteristics of three commonly- researchers and managers. For researchers, our study
used mobile ticketing technologies and compared them proposed and empirically tested a model that encom-
to paper tickets. Combined with the analysis of the data passes information capability, value creation strategy, and
attributes captured by each technology, we observed firm performance. Past research has suggested that actual
different levels of information capability among the usage may be an important link to IT value (Devaraj
selected cases. When a ticketing system is implemented Kohli, 2003). However, this link has been missing in the
by a PTO, the first goal is to reduce fare evasion and literature and much of the work has typically focused on
achieve operational efficiency. When PTOs start using ‘adoption vs non-adoption’ (Zhu Kraemer, 2005; Zhu
more advanced mobile ticketing technologies such as et al., 2006). Our model moves beyond the adoption
smart cards or mobile devices, they are soon able to phase and accounts for the actual usage as a critical stage
obtain more detailed individual customer behavior of value creation. As a result, we are able to better
information. This information allows them to employ understand the post-adoption variations of mobile tick-
price differentiation strategies. Further, because smart eting technology.
cards and mobile devices move customers quickly through Further, in contrast to prior studies that have largely
the payment process, they are particularly attractive to focused on revenue management practice in the airline
retail segments where speed and convenience of payment industry, our study sheds light on the less understood
are essential. The technology adoption in the public possibilities of revenue management in the public
transport industry creates a large customer installed base; transport industry. Previously, PTOs had limited informa-
this makes it easier for the service providers to expand into tion about their customers’ actual travel behavior and
other markets. The empirical results provide strong limited ability to predict variable demand. As a result,
support for proposition 1. It suggests that service providers revenue management was considered ‘nearly impossible’
that have a higher information capability are more likely for them. Our study examined the usage of mobile
to use price differentiation and service expansion strate- ticketing technologies and explained how PTOs can
gies, compared to the ones that have a lower information leverage these technologies to enable and advance their
capability. revenue management practices.
Finding 2: Service providers that adopt advanced For managers of firms in the public transport industry,
mobile ticketing technologies and employ price the results underline the value of understanding how
European Journal of Information Systems

12. Information capability and value creation strategy Ting Li et al 49
PTOs create value through the use of customer behavioral and service profile, among other considerations. These
information. PTOs who seek and actively engage in limitations suggest avenues for further research: we offer
exploring their information capability and employing some specific suggestions. The measures of key variables
price differentiation and service expansion strategies are such as firm performance supplemented by objective
more likely to succeed compared to the ones who only performance data could be much refined in the future
use the baseline strategy. This difference in performance research by controlling for the characteristics and
has important implications for revenue models, pricing commercial objectives of the service providers. Future
structure, and the overall service operation strategies for research can conduct more in-depth interviews to find
PTOs. More importantly, PTOs who can make better use out the evolution of smart card usage and value.
of customers’ travel behavior information can adjust This study was motivated by the process-oriented view
their products and services quickly and effectively, and of the business value of IT. It is grounded in the revenue
improve their revenue and service operations. management literature and resource-based theory. It has
Further, it is important for PTOs to recognize the theoretically developed and empirically evaluated a
important role that customers play in their service research model that examines the use and impact of
operations. The public transport industry is (partially) mobile ticketing technology and improved customer
subsidized by government and has very strong social behavior information at the firm level. Using multiple
responsibilities. The primary reasons for government to cases, this study investigates the value creation process of
pay subsidies are to provide transport services to the mobile ticketing technologies and their enablement to
public, alleviate congestion, reduce pollution, and pro- revenue management strategies.
mote economic growth. Thus, there is a limit to how far This study shows that mobile ticketing technologies
PTOs can practise revenue management. Instead of using have unique product, process, and usability character-
a profit-maximization approach as many other industries istics compared with the traditional ticketing channel.
do, PTOs are more likely to benefit from using a These technologies increase firms’ information capability
customer-focused approach. On the one hand, they need in terms of both information quantity and information
to pay special attention to the effects of price increase quality. It finds evidence that firms create value through
and tariff structure adjustments, and the impacts of seat the use of mobile ticketing technologies in three ways.
availability and service punctuality, which might lead to First, benefiting from the installed electronic gating
crowding and discomfort. On the other hand, PTOs can infrastructure, mobile ticketing technologies reduce fare
benefit from engaging in activities that improve custo- evasion, offer customer convenience, and reduce opera-
mer satisfaction, for example designing and delivering tional costs. Second, the technologies enable firms to
value added services to meet customer needs, such as real- collect more detailed customer information, which
time travel information. increases firms’ abilities to design price and service
differentiation strategies to create value. Third, mobile
ticketing systems provide micro-payment infrastructures
Future research and conclusion that permit other service providers to adopt them. As a
This study makes several contributions to the IS literature result of this, service providers can increase their
by examining the use of modern IT in the development transactional efficiencies and expand their services
of revenue management. Nevertheless, the findings quickly into other industry sectors.
should be evaluated in light of the limitations. First, the This study finds that service providers using more
measures of revenue and customer volume as well as sophisticated mobile ticketing technologies and have
reputation for performance impacts were subjective in real-time and complete information on customers’ actual
the sense that we relied on the available data from press travel will also use price differentiation and service
releases and news articles that were read by the authors. expansion strategy. Moreover, these providers have
While we have been careful in assessing the potential relatively higher performance gains. Although we used
biases inherently associated with such data, it would have the public transport industry as our research context, we
been desirable to have more objective measures of perfor- acknowledge that in an exploratory sense, this study
mance. Second, this study does not distinguish between indicates a potential model applicable across domains
the operating environments of the service providers. It and which can be applied to companies that are
could be that some service providers have more com- examining modern technologies to develop revenue
mercial freedom compared to others, and this would lead management strategies.
to a different (non)-profit-maximization agenda and
operational boundaries. Further, we find that some
performance effects cannot be explained by the choice Acknowledgements
of value creation strategy. Some choices of value creation The authors thank the anonymous reviewers and associate
strategy cannot be explained by the change in informa- editor of this journal and the conference participants of the
tion capability. They may be driven by other competitive Academy of Management Meeting 2008 for their helpful
considerations, including organizational capabilities, comments. The authors gratefully acknowledge support
sophistication of competition, a firm’s chosen price, from Erasmus Research Institute of Management.
European Journal of Information Systems

13. 50 Information capability and value creation strategy Ting Li et al
About the authors
Ting Li is an assistant professor of Decision and Management (ERIM) in Rotterdam. He conducts research
Information Sciences at Rotterdam School of Manage- and teaches on the strategic and operational use
ment Erasmus University, where she also received of information technologies for companies and markets.
her Ph.D. Her main research interests include the E-mail: evanheck@rsm.nl
strategic use of information technology, competitive Peter Vervest is a professor of business networks at the
strategy and economics of information systems, pricing Rotterdam School of Management, Erasmus University,
and revenue management, and business networks. and partner of D-Age, corporate counsellors and invest-
E-mail: tli@rsm.nl ment managers for digital age companies (London –
Eric van Heck is a professor of information management Amersfoort – Sunnyvale). His specific field of research
and markets at the Department of Decision and Informa- concerns the development and application of enabling
tion Sciences of RSM Erasmus University and director of technologies for smart business networks. E-mail: pvervest
doctoral education at Erasmus Research Institute of @rsm.nl
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