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Virtual extension

Creating the Experience Economy in E-Commerce

Advances in information technology together with the forces of globalization have accelerated the growth of service industries. In 2003, the OECD reported that service industries now account for over 60% of both employment and the gross domestic product (GDP) of OECD member countries. The U.S Bureau of Labor Statistics (BLS) has forecast strong employment growth in the American service sector between 2004 and 2014. Although service industries are expanding, Gilmore and Pine argue that, the growing commoditisation of services offered has gradually transformed the competition for market share from focusing on the quality of services to the creation of memorable experiences.4 As a consequence, the competitive position of a firm now depends to a large extent on its ability to generate impressive experiences through innovative delivery channels.

In this article, we adopt Gilmore and Pine's view that the economic value of the experience economy lies in co-producing the staging experiences via customer participation and connection.4 Furthermore, we suggest that current technologies and the growth of the Internet have both enabled and strengthened the opportunities for experience-oriented offerings beyond limitations of time and place. In following sections, we first describe the current practice of experience economy in electronic commerce. Taking the iCare health care service as an example, we demonstrate how collaborative pricing over the Internet can further provide added-value to the production of experiences offered in the electronic marketplace.

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Experience Economy in E-Commerce

In discussing the evolution of economies, Pine and Gilmore9 observed that the economic value of a given offering increases as its form changes from a commodity, product or service to an experience. In Pine and Gilmore's view, a product has the highest economic value when it becomes an experience product,9 for example, when consumption of the product focuses on the process of staging a "memorable" experience. Compared with other economic offerings, the creation of experience consumption depends on the extent of a customer's participation and absorption during the consumption process. Therefore, while the key attribute of service product involves focusing on the extent of customization, the dominant element of experience offerings lies on the level of personalization. The more personalization a business manages to create, the more the customer will be prepared to spend. Pine and Gilmore offered a number of examples from the entertainment and retail industries. The leading example is Disneyland, where customers pay to immerse themselves in distinctive and memorable experiences.

In recent years, the Internet and intensified market competition have motivated organizations to pay more attention to the significance of experience offerings. The Internet infrastructure has reduced the cost of coordination, and thereby accelerated the commoditization of services.7 At the same time, competitive pressures continue to press the need for product differentiation and innovation in order to gain a competitive edge in today's fast-moving business environment. Therefore, the business value and potential profits generated by experience offerings are becoming increasingly attractive and vital to firms that endeavor to remain competitive in the global marketplace. As Pine and Gilmore9 note:

"Increased price volatility as market forces take over awaits the sellers of all commoditized goods and services. Companies that stage experiences, on the other hand, increase the price of their offering much faster than the rate of inflation simply because consumer value experiences more highly."9

In this article, we argue that the power and capability of the Internet allows the creation of experience-oriented consumption beyond these limitations, as shown by the implementation of collaborative design and pricing applications on the Internet.

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Collaborative Design in the E-Commerce Environment

Toffler and Toffler11 coined the term "prosumer," a combination of producer and consumer, to describe people who consume the products they create. In electronic commerce, online collaborative design is an example of how the prosumer concept can be used to provide experience offerings. For instance, Koren6 revamped collaborative filtering recommendation approaches by modeling time changing behavior, which can track dynamic customer preferences for products. By creating a process that involves consumers in the design and development of a product, a company can ensure that the product meets the consumers' needs. It would also engender a sense of ownership among customers that leads to intense customer loyalty.10 Many such business strategies have been implemented. For example, an e-interior design service enables designers and customers to co-operate in the interior design of a house.1 Customers can alter their requirements, and the e-interior design service encompasses certain cognitive components (for example, design concepts) to adapt a user's design demands automatically. As a result, through the process of engagement, the customer is given a memorable experience. Nike, the world largest athletic shoemaker, embraced the potential of e-collaborative design in 1999 by offering custom-designed men's and women's shoes over the Internet.

In addition to physical goods, the development of digitized products appears to a great opportunity for implementing experience-centered business models.13 For example, digital content design services empower producers and consumers so that they can effectively co-create digital content in a novel collaborative way without the constraints of time and place. In the entertainment sector, the growing popularity of online interactive gaming also offers experiences unknown to previous economic models. The players come together to enjoy the thrill of interaction in cyberspace. We suggest that the success of YouTube lies in its ability to create a platform that not only allows people to contribute content, but also to immerse themselves in experiences through video created by others in the global community.

These examples demonstrate how customers can actively participate in the consumption process in the virtual world. In this article, we propose the concept of collaborative pricing as an extension of collaborative design to create an experience economy on the Internet. We believe that offering collaborative pricing could create better entertainment and education experiences, and thereby increase the economic value of such offerings in the electronic marketplace.

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Experiencing Collaborative Pricing in E-Commerce

Similar to the concept of collaborative design, collaborative pricing allows customers to become active participants in deciding the prices (for example, the amount they are willing to pay) for services tailored to meet their changing needs. We define collaborative pricing as "a model that allows customers and providers to participate and to jointly decide prices with the underlying objectives of maximizing the willingness-to-pay and optimizing profits."

In the conventional pricing model of electronic commerce, pricing strategies are based primarily on mass customization; allow limited customer participation in price determination (See Table 1). We suggest the current form of information technology also has the potential for creating a collaborative pricing process, which would add to the economic value of digital goods.

The proposed collaborative pricing process involves four steps, namely, setting price differentials, anchoring and collaboration, e-service molding, and price optimization (See Figure 1(a)). In the first step, producers set different prices for various versions of an e-service according mass customization. The consumer then chooses a specific version, which provides the anchor for future collaboration about pricing. The process then elicits consumers' feedback and modifies the services accordingly. This molding phase continues until a consensus is reached, after which an optimal price will be generated.

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iCare: An Example of Collaborative Pricing

We believe that implementing a collaborative pricing model can contribute substantially to experience-generation in the digital entertainment and health care industries. For example, eCare has utilized Web technology to improve the quality of health care via experiences. However, existing aging services (health care or eCare) are mostly oriented towards clinical gerontology (such as, exercise technology, sensor technology) or the neuropsychology of aging (such as, pre-symptomatic diagnosis of age-related cognitive decline, devices for the amelioration of age-related changes in human sensory and motor systems). The present design of eCare lacks quality dimensions, such as community involvement, consumer participation and continuous quality improvement, which are crucially important to increasing the value of care for an aging population.3

We have implemented a platform called iCare (intelligent Care) (see Figure 2),1 which extends eCare technologies to a domain of ambient e-services that addresses the concept of experience offering. The objective is to provide quality e-services to elderly people anywhere-anytime via an iCare home portal. The features of iCare e-services include ambient service accessibility, attentive personalized service provision, innovative life-style creation, precious digital memory, and seamless social connections. The concept of iCare is unique through the provision of attentive personalized service. Such warm-hearted features would not only provide elderly people and their families with essential services, but also allow them to engage in a virtual collective decision-making process about the services they would like to have (via a case-based model, brainstorming model, or garbage can model).

During the process of interaction, the model collaboratively generates bundled services for the elderly to experience and prices the bundled services based on the maximum willingness-to-pay (WTP) and optimal profits. The final price results from the collaborative process, the charges for prototypes and the testing effort involved.

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Collaborative Pricing Process

Here we define a collaborative pricing model (CPM) as a model that has the objectives of optimizing WTP (CUtility) and profits (PProfit), that allows consumers and producers to actively participate and collaborate when pricing products or bundles, and that generates an optimal bundle price at equilibrium.


In iCare, the formulation of prices that the elderly and their family members would be willing to pay is based on the collaborative design and pricing method (see Figure 1(b)). The consumer first chooses the version of bundled services that would satisfy his/her current needs. The interaction with the consumer and the generation of prototypes continues until those needs are met. After this phase has been completed, the collaborative price (CP) will be estimated based on the prototype testing efforts, the design fee for customization, and the cost of the services.

The three principal components of collaborative price (CP) estimation are the design fee, the number of bundles, and test effort involved. The design fee (D) is estimated based on the optimal utility (U); the number of bundles (B) is associated with the test effort (T); and the bundle cost (C) is the cost of the set of services in the bundle. The following formula incorporates the three components:


Using some experimental evaluation, our proposal model (CPM) can be compared against another pricing approach, the expected utility theory (EUT). The optimal willingness-to-pay and profits attempted by CPM can then be evidenced by some experimental evaluation results as benchmarked against EUT (see Table 2). In the experiments, we assume that the number of services in a bundle ranges from 2 to 8 and the outcome probability of choosing a specific service bundle is set to 0.9 to 0.5, which may exceed the average weighting. It is sufficiently high to verify the difference between EUT and CPM, except when the outcome probability is 100%.

When the probability is 0.9, EUT will probably over-estimate the price for 2 services in a bundle and underestimate the price for 5–8 services in a bundle (Table 2(a)). EUT always underestimates prices compared with CPM for bundles of services when the probability is 0.5 (Table 2(b)). The reason is that EUT only considers the final utility and bundle probability, and ignores the efforts of the collaborative process. If a customer is satisfied with the interaction process, the utility will be high, and the price can increase. That is, prices may be under-estimated when the number of services in a bundle is large (such as, 4–8 services when the probability is 0.9) (Figure 3(a)). Prices are always under-estimated when the probability is very low (such as, 0.5), as consumers are not satisfied with, and will not accept, the offered services (Figure 3(c)). The experiment results indicate that EUT generates the highest profits when there are 2 or 3 services in a bundle and the probability is 0.9, and generates the lowest profits when there are 5–8 services in a bundle (see Figure 3(b)). However, EUT only considers the final utility and the probability that a bundle will be chosen, and ignores the effects of the collaborative process. Bundle prices are always under-estimated when the probability is very low (e.g., 0.5) as the provider under-estimates profits (see Figure 3(d)).

In short, the experimental results of utilities for EUT and CPM demonstrate that EUT may over-estimate the utility from the consumer's perspective, whereas CPM can potentially achieve equilibrium (for example, neither over-estimate nor under-estimate the utility). The experiment results demonstrate that EUT either over-estimates or under-estimates prices, resulting in higher or lower prices than those obtained with CPM. The results also indicate that collaborative pricing is profitable from the producer's perspective. In summary, the experiment demonstrates a positive outcome for implementing collaborative pricing in the electronic commerce context.

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The potential economic value of experience-oriented offerings has been demonstrated in the physical marketplace. In this article, we suggest the widespread use of the Internet and existing technologies allow us to extend the experience economy to the virtual marketplace. The growing practice of online collaborative design demonstrates the potential for providing the experience economy via the Internet. Our major contribution is that we propose expanding existing practices by incorporating the concept of collaborative pricing into the design of experience offerings. Moreover, we propose a collaborative pricing model based on a platform called iCare, which can be implemented in the Internet environment. We hope that this article will motivate further research into the development of the experience economy in electronic commerce.

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1. Chang, W. L., Yuan, S. T., and Li, E. iCare home portal: An extended model of quality aging e-services. Comm. ACM 52, 11, (Nov. 2009), 118–124.

2. Chi, H. S. and Yuan, S. T. A design e-service delivery with an ontology-based cooperative/interactive co-evolutionary mechanism. Proc. of conference on E-commerce and Digital life (ECDL2007), March, Taiwan, (2007), 33.

3. Czaja, S. and Hiltz, S. Digital aids for an aging society. Comm. ACM 48, 10, (2005), 43–44.

4. Gilmore, J. and Pine, J. Welcome to the experience economy. Harvard Business Review 76, 4 (1998), 97–105.

5. Klaus, B., Dimitrov, D. and Haake, C. J. Bundling in exchange markets with indivisible goods. Economics Letters 93, (2006), 106–110.

6. Koren, Y. Collaborative filtering with temporal dynamics. Comm. ACM 52, 4, (2010), 89–97.

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8. Martin, S., Strategic and welfare implications of bundling. Economics Letters 62, (1999), 371–376.

9. Pine, J. and Gilmore, J. The Experience Economy, Harvard Business School Press, Boston, MA, (1999).

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11. Toffler, A and Toffler, H. Revolutionary Wealth. Random House, (2006).

12. Varian, H. Versioning Information Goods, The Economics of Digital Information (tentative), Cambridge (MA), MIT Press, (1997).

13. Wu, Y. C. and Yuan, S. T. A collaborative digital content design service marketplace with a semantic-based fuzzy genetic mechanism. Proceedings of conference on E-commerce and Digital life (ECDL2007), March, Taiwan, (2007), 34.

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Wei-Lun Chang ( is an assistant professor at BA Department, Tamkang University.

Soe-Tsyr Yuan ( is a professor and Director of Service Science Research Center, National Cheng-Chi University.

Carol W. Hsu ( is an associate professor in the Department of Information Management at National Taiwan University.

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F1Figure 1. Understanding collaborative pricing

F2Figure 2. The platform architecture of iCare

F3Figure 3. Evaluation results of CPM benchmarked against EUT

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T1Table 1. Conventional and Collaborative Pricing Process

T2Table 2. Evaluation results of CPM benchmarked against EUT

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