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"Pay as You Go" or "All You Can Eat"? Pricing Methods for Computing and Information Services
... Safari et al. (2015) [15] developed a continuous time optimal control model for identifying pricing strategies for the web service classes with consideration of the purchase intentions of customers under different service qualities and proposed an algorithm for optimal pricing. Related articles can be found in Liang et al. (2013) [16], Ma (2016) [11] and Bhargava et al. (2016) [17]. ...
... Safari et al. (2015) [15] developed a continuous time optimal control model for identifying pricing strategies for the web service classes with consideration of the purchase intentions of customers under different service qualities and proposed an algorithm for optimal pricing. Related articles can be found in Liang et al. (2013) [16], Ma (2016) [11] and Bhargava et al. (2016) [17]. ...
This paper analyses the optimal pricing strategies of two sales models for a service product: the use-based mode, in which a customer pays for each use, and the prepaid-based mode, in which a customer enjoys a service with a card that represents an up-front payment for a period of time. For the prepaid mode, we analyse a kind of unlimited card, such as a fitness card. With considerations of customers’ perceived value, transfer fees and the time-value of the funds, we establish generalized pricing models of a service product under these two sales modes in a monopoly, and discuss the pricing strategies between two companies using game theory in a duopoly. Research shows that in a monopoly, the optimal use-based price is identical whether the transfer fee exists or not, and the optimal prepaid-based price when the transfer fee exists is lower than when it does not exist. In a duopoly, according to game theory, we can derive two Nash equilibria from nine situations. Lastly, through numerical examples, we verify the effectiveness of the pricing strategy and derive some managerial insights.
... The problem of deciding on a pricing model for cloud providers has been studied in depth [1], [6], [16], [21], [28]. ...
This qualitative literature review examines "The Economics of Auto-Delivery: A Qualitative Exploration of Inventory Management and Profitability in Subscription Services." Auto-delivery systems have gained traction in various industries, offering consumers convenience and suppliers a steady revenue stream. This study synthesizes existing literature to uncover the interplay between inventory management, profitability, and consumer behavior within auto-delivery frameworks. Key findings highlight the importance of advanced inventory strategies, dynamic pricing models, and the role of technology in enhancing operational efficiency. Additionally, the review discusses the implications of consumer behavior on subscription retention and the challenges suppliers face in minimizing churn. The insights derived from this review indicate that effective channel coordination and strategic investment in technology are essential for maximizing the profitability of auto-delivery services. However, the study acknowledges limitations such as the predominance of research in Western markets and the lack of empirical data to support theoretical insights. This review provides a comprehensive understanding of the economics surrounding auto-delivery systems, serving as a foundation for future research in this rapidly evolving domain.
Auto‐delivery is a subscription model widely employed in supply chains, whereby a supplier delivers products to a buyer (or multiple buyers) according to the buyer's choice of a constant shipping quantity to be delivered at prescheduled dates. The buyer enjoys a discount for the auto‐delivery orders and other benefits, including free subscription and cancellation. Because these benefits seem to all accrue to the buyer at the supplier's expense, the rationale for the supplier's decision to offer auto‐delivery and its impact on the profitability of both parties is an intriguing concern. We first develop a model that consists of a supplier and a single buyer, whereby the supplier offers a discount for the auto‐delivery orders and the buyer chooses the auto‐delivery quantity with the flexibility of cancelling the subscription. We derive the two parties' operating characteristics of their inventory systems and examine their optimal decisions. Our analysis shows that buyers benefit from the auto‐delivery discount; the supplier benefits from the demand‐expansion effect and the inventory‐reduction effect, a potential discount on the cost of the auto‐delivery units; and the supply chain benefits from reducing the bullwhip effect. We also find that channel coordination requires the supplier to pass the inventory‐related savings to the buyer through the auto‐delivery discount, which depends on the ratio of the two parties' holding cost rates. Moreover, we examine a model extension whereby the supplier announces a discount that is available for multiple buyers, we show that the supplier's optimal auto‐delivery discount under exponential demand can be determined based on the aggregate‐level demand information from all buyers. Finally, we discuss another model extension whereby the lead time of the supplier's recurring orders for auto‐delivery is longer than that of the regular orders and present a full analysis of the case when the lead time differential is one time period.
Streaming media companies have changed how contents are consumed, produced, and delivered. This research develops a theoretical model on optimal content policies for streaming media companies in order to maximize customer engagement. We have the following interesting findings. First, in contrast to the results in prior literature that firms produce just enough programs and coverage intervals of the programs do not overlap, we show that placing programs closer can be a better policy for engagement‐based firms. Second, more contents are produced under engagement‐based model when the customer value of the content is high. Third, on learning the distribution of the customers, the media firm will always place programs closer when the distribution density is higher such that neighboring programs always have overlapped target audience. Additionally, in facing the tradeoffs of content quality and quantity, the firm should use a high‐quality and low‐variety policy for crowded clusters but a low‐quality and high‐variety policy for niche clusters. Furthermore, when customers consume multiple shows in a period, a good policy is to produce TV shows or series with multiple episodes, whereas individual movies are more suitable for an infrequent watcher market. Our research contributes to the literature on digital media, and the results provide interesting and insightful implications for streaming companies.
We investigate heterogeneous customer choice behavior in the presence of main products—ancillary services with options of pay-per-use and subscription—and outside option. The willingness to pay for a service subscription is derived as a closed-form expression, which enables us to characterize the optimal pricing strategy and the impact of service subscriptions on customer surplus. Analytical results and numerical experiments show that offering service subscriptions may result in “win-win,” “win-win-win,” “win-win-lose,” or “lose-lose-win” scenarios or in other situations for the firm, competitors, and customers in a variety of monopolistic and duopolistic scenarios. The advantages of service subscription still remain with heterogeneous customers differing on multiple dimensions including the nominal utility, uncertainty in the need of ancillary service, and purchase frequency. We find that if the product quality for both firms, measured by nominal utility, is not significantly different, more fierce price competition by offering a service subscription may result in a higher customer surplus, compared with that without a service subscription. Ancillary service subscription can help firms to better price-discriminate heterogeneous customers through different subscription decisions and subsequent purchase behavior.
This paper was accepted by Gad Allon, operations management.
Cellular communication has played an important role in current data transmission networks. Nevertheless, the price of cellular communication service is much higher than wired communication service. Thus each data transmission service provider has to make optimal decisions on cellular data plan to reduce the cost. This work put forward an optimal data cost scheme for the data transmission service in virtualized wireless networks. A formal cost model is put forward and the optimal algorithms have been used to approach the optimal solution. The simulation results show the efficiency and feasibility of proposed optimal algorithms.
Models of nonlinear pricing ignore the monetary, administrative, and managerial costs of screening. As a consequence there is a wide divergence between com-plex theoretical characterization of nonlinear tariffs and the simple tariff options commonly encountered in the business practice. This paper uses an equilibrium model of nonlinear pricing to determine the magnitude of foregone rents due to the implementation of simplified screening mechanisms. I then study the distribution of these foregone rents conditional on observable characteristics of a large sample of independent cellular telephone markets. I also use the estimated overall profitability of each market to analyze in detail the pricing strategies of firms in a monopoly environment, including the number of tariffs and the use of foggy pricing. Estimates reveal that the sample mean of foregone profits for not offering an additional tariff option amounts to 1.32 if firms already offer three tariff options. But these foregone profits only amount to 4% and 0.6% of the profits attainable with a fully nonlinear tariff, respectively. JEL: C39, D43, L96.
Online information servers that provide access to diverse databases where users can search for, browse through, and download the information they need have been rapidly increasing in number in the past few years. Online vendors have traditionally charged users for information on the based on the length of the time they were connected to the databases. With hardware and software advances, many online servers have recently started changing their pricing strategies to search-based and/or subscription-fee pricing. This paper examines the various issues involved in pricing these information products, and presents an economic approach to analyze conditions under which the various pricing schemes may prove optimal for the online servers. Our results show that the variation in consumer expertise and valuation of information affects the choice of a pricing strategy by the server. We present general conditions under which subscription-fee pricing is optimal even when consumer demand is inelastic. We also find that, given the cost structures characterizing the market, undifferentiated online servers can compete and coexist in the market each making positive profits. We show that in a competitive setting an increase in costs of online servers can sometimes benefit them by enabling them to differentiate themselves. Our results offer insights into the trends in pricing strategies and may provide an explanation as to why many servers may persist with connect-time strategies.
In communication, information, and other industries, three-part tariffs are increasingly popular. A three-part tariff is defined by an access price, an allowance, and a marginal price for any usage in excess of the allowance. Empirical nonlinear pricing studies have focused on consumer choice under two-part tariffs. We show that consumer behavior differs under three-part tariffs and assess how consumer demand uncertainty impacts tariff choice. We develop a discrete/continuous model of choice among three-part tariffs and estimate it using consumer-level data on Internet usage. Our model extends prior work in accommodating consumer switching to competitors, thereby capturing behavior in competitive industries more accurately. Our empirical work shows that demand uncertainty is a key driver of choice among three-part tariffs. Consumers' expected bill increases with the variation in their usage, steering them toward tariffs with high allowances. Consequently, demand uncertainty decreases consumer surplus and increases provider revenue. A further analysis of consumers' responsiveness to the different elements of a three-part tariff under the provider's current pricing structure reveals that prices affect a consumer's tariff choice more than her usage quantity and that the allowance plays a strong role in consumer tariff choice. Based on our results, we derive implications for pricing with three-part tariffs.
CLOUD COMPUTING, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service and shaping the way IT hardware is designed and purchased. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about overprovisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or underprovisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get results as quickly as their programs can scale, since using 1,000 servers for one hour costs no more than using one server for 1,000.
Should a firm charge on a per-use basis or sell subscriptions when its service experiences congestion? Queueing-based models of pricing primarily focus on charging a fee per use for the service, in part because per-use pricing enables the firm to regulate congestion--raising the per-use price naturally reduces how frequently customers use a service. The firm has less control over usage with subscription pricing (by definition, with subscription pricing customers are not charged proportional to their actual usage), and this is a disadvantage when customers dislike congestion. However, we show that subscription pricing is more effective at earning revenue. Consequently, the firm may be better off with subscription pricing, even, surprisingly, when congestion is intuitively most problematic for the firm: e.g., as congestion becomes more disliked by consumers. We show that the absolute advantage of subscription pricing relative to per-use pricing can be substantial, whereas the potential advantage of per-use pricing is generally modest. Subscription pricing becomes relatively more attractive if consumers become more heterogeneous in their service rates (e.g., some know they are "heavy" users and others know they are "light" users) as long as capacity is fixed, the potential utilization is high, and the two segments have substantially different usage rates. Otherwise, heterogeneity in usage rates makes subscription pricing less attractive relative to per-use pricing. We conclude that subscription pricing can be effective even if congestion is relevant for the overall quality of a service.
Service providers often offer tariff structures with several two-part tariffs that consist of a fixed fee and a usage price, such that consumers may pick the tariff they prefer. Prices of tariffs have significant impacts on service providers' profit, because they simultaneously influence consumers' tariff choices and their usage. The number of tariffs also plays an important role, because more tariffs segment the market better but also increase the administrative burden and require more marketing effort. This article presents a mixed-integer nonlinear programming optimization problem to determine profit-maximizing tariffs; compares several heuristic search methods, in particular, the gradient method, stochastic search, and simulated annealing, to solve this problem; analyses the profitability of different tariff structures; and outlines the factors that drive differences in profitability across various tariff structures. The results show that especially for large samples of more than 100 consumers, simulated annealing performs best and deviates only 0.2% from the optimum. Structures with fewer two-part tariffs are generally sufficient, because additional two-part tariffs only negligibly increase service providers' profit.
Technology appears to be making fine-scale charging (as in tolls on roads that depend on time of day or even on current and anticipated levels of congestion) increasingly feasible. Such charging also appears to be increasingly desirable, as traffic on roads continues to grow and costs and public opposition limit new construction. Similar incentives towards fine-scale charging also appear to be operating in communications and other areas, such as electricity usage. Standard economic theory supports such measures and technology is being developed and deployed to implement them. But their spread is not very rapid and their prospects for the future are uncertain. This paper presents a collection of sketches, ranging from ancient history to very recent developments, that illustrate the costs that charging imposes. Some of those costs are explicit (in terms of the monetary costs to users and the costs of implementing the charging mechanisms). Others are implicit, such as the time or the mental processing costs of users. These argue that the case for fine-scale charging is not unambiguous and that in many cases such charging may lead to undesirable outcomes.
Most existing frameworks of pricing were developed in the context of consumer goods and, as such, they fail to explain how to price complex service offerings. In this chapter, the authors explain the characteristics of services that make services pricing different from goods. Relying on theory from both the general pricing literature and from services research, they develop a conceptual model of pricing of services. This framework incorporates critical pricing elements from both the consumer's and the service provider's perspective. The authors also explain how consumers form value perceptions in the context of service offerings and how such knowledge can be used for developing pricing strategies for various types of services. The chapter concludes with a discussion on measuring price sensitivity in service, competitive pricing and areas for future research.
A nonlinear pricing schedule refers to any pricing structure where the total charges payable by customers are not proportional to the quantity of their consumed services. we begin the chapter with a discussion of the broad applicability of nonlinear pricing schemes. we note that the primary factor for the use of such schemes is the heterogeneity of the customer base. such heterogeneity of preferences leads customers to choose different pricing plans based on their expected demand. we describe past analytical and empirical research. past analytical work is categorized based on whether it is in a monopoly setting or a more general oligopoly context. most past research has found two-part tariffs to be optimal in many settings. more recent research has begun to investigate the limits of such optimality and when a more general pricing scheme can be optimal. in the summary of empirical research on multi-part tariffs, we note that while nonlinear pricing schemes are popular, any analysis of demand under such schemes is nontrivial. one important reason is the two-way relationship between price and consumption in multi-part tariffs - the pricing scheme infl uences consumption and the level of consumption determines the applicable per-unit price. we describe how researchers have addressed this and other such issues and then show a modeling framework that integrates all the issues. we end by discussing empirical generalizations, which also suggest some promising areas for future research.
Pure bundling and mixed bundling are two popular pricing strategies for information goods. Pure bundling offers only the product bundle, whereas mixed bundling offers both the bundle and the individual components of the bundle. This paper extends prior research on bundling, which usually assumes consumer heterogeneity along a single attribute of the consumer. However, an individual consumer's demand function can be expressed as the interaction of the intercept and the slope of the demand function. We allow for consumer heterogeneity along both these dimensions. The initial willingness-to-pay (IWTP) of a consumer captures the consumer's willingness to pay for the first unit of the product while the appetite (APP) of a consumer captures the quantity consumed when the product is free. We find that these two dimensions of heterogeneity have opposing effects. APP heterogeneity encourages the adoption of mixed bundling while IWTP heterogeneity moderates the relationship between APP heterogeneity and the preference for mixed bundling in favor of pure bundling. Our results also help explain why sellers tend to change pricing schemes over time.
Firms that serve a large market with many diverse consumer types use discriminatory or nonlinear pricing to extract higher revenue, inducing consumers to separate by self-selecting from a large number of tariff options. But the extent of price discrimination must often be tempered by the high costs of devising and managing discriminatory tariffs, including costs of supporting consumers in understanding and making selection from a complex menu of choices. These tariff design trade-offs occur in many industries where firms face many consumer types and each consumer picks the number of units to consume over time. Examples include wireless communication services, other telecom and information technology products, legal plans, fitness clubs, automobile clubs, parking, healthcare plans, and many services and utilities. This paper evaluates alternative ways to price discriminate while accounting for both revenues and tariff management costs. The revenue-maximizing menu of quantity-price bundles can be very (or infinitely) large and hence not practical. Instead, two-part tariffs (2PTs), which charge a fixed entry fee and a per-unit fee, can extract a large fraction of the optimal revenue with a small menu of choices, and they become more attractive once the costs of tariff management are factored in. We show that three-part tariffs (3PTs), which use an additional instrument, the “free allowance,” are an even more efficient way to price discriminate. A relatively small menu of 3PTs can be more profitable than a menu of 2PTs of any size. This 3PT menu can be designed with less information about consumer preferences relative to the menu of two-part tariffs, which, in order to segment customers optimally, needs fine-grained information about preferences. Our analysis reveals a counterintuitive insight that more-complex tariffs need not always be more profitable; it matters whether the complexity is from many choices or more pricing instruments.
Nonlinear pricing is pricing that is strictly proportional to the quantity purchased. For example, railroad tariffs are often based on weight, volume, and distance to be shipped; airlines offer frequent flyer bonuses based on miles flown; electric utilities charge different rates for different amounts of electricity used combined with the time it is used based on peak power demands. The book is divided into two parts. The first in a non-mathematical discussion of nonlinear pricing and the second part is more technical and is intended for readers interested in advanced topics.
Many established industries, such as the online service industry, the telecommunication industry, or the fitness club industry, are access service industries. When using services in these industries, consumers pay for the privilege of accessing the firm's facilities but do not acquire any right to the facility itself. A firm's pricing decisions in access industries frequently come down to a simple choice among flat fee pricing, usage pricing, or two-part tariff pricing. However, it is not so simple for firms in those industries to make this choice. Access service firms typically face a mix of consumers who have intrinsically different usage rates. A key characteristic of access service firms, however, is that the cost of providing an additional minute of usage is typically negligible, as long as the firm has the necessary capacity to serve its customers. Service capacity, which corresponds to the total available time on a firm's system, is often limited.
In this paper, we show that service capacity and consumer usage heterogeneity are two important factors that determine a firm's optimal choice. We develop a model that incorporates these two salient characteristics shared by access industries and study what determines a firm's choice among the three alternative pricing structures (flat fee pricing, usage pricing, or two-part tariff pricing). Our analysis shows that, in the presence of consumer usage heterogeneity, service capacity mediates a firm's optimal choice in a complex, yet predictable way. A firm's choice also hinges on whether heavy or light users are more valuable in terms of their willingness-to-pay on a per-unit-capacity basis. The presence of both consumer usage heterogeneity and capacity constraints prompts a firm to choose its pricing structure to attract a desired customer mix and to price discriminate. As a result, two-part tariff pricing is not always optimal in access industries, and a firm's pricing structure can vary in a complex way with the interaction of those two factors.
Specifically, we show that when light users are more valuable, a firm may use a two-part tariff or a flat fee, depending on whether the firm is constrained by its service capacity, but never charge a usage price alone or offer any signing bonus (a negative flat fee or a flat payment to customers). When heavy users are more valuable, a firm may choose to set a usage price, a signing bonus plus a usage price, or flat fee. Interestingly, regardless of whether heavy or light users are more valuable in an access service industry, only flat rate pricing is a sustainable pricing structure once the industry has developed sufficient excess capacity.
We also show that the optimal pricing strategy in access industries can have some intriguing, nonintuitive implications that have not been explored elsewhere. For instance, when the industry capacity is unevenly distributed between competing firms, the large-capacity firm may well be advised to increase, rather than to decrease, its price to accommodate the small firm. It would be too costly and too tactless for the large firm to do otherwise. In fact, the strategy of accommodation calls on the larger firm to retreat in both light and heavy user markets and leave more of its capacity idle and more of the market demand unmet when the small firm's capacity (hence, the industry capacity) increases. This implies that incremental policy measures that encourage the growth of smaller companies in the presence of a large company can be welfare-decreasing because the growth of smaller firm can force the retreat of a large company at the expense of market coverage.
Today, services account for two-thirds to three-quarters of the GNP, not only in the United States but also in many industrial countries. Access industries are growing rapidly to exert profound impact on today's economy. However, service pricing in general and pricing access services in particular have not received adequate attention in the literature. In this paper, we take the first step in understanding how capacity constraints and consumer usage heterogeneity mediate the choice of pricing structures in both monopolistic and competitive contexts.
The utility business model is shaped by a number of characteristics that are typical in public services: users consider the service a necessity, high reliability of service is critical, the ability to fully utilize capacity is limited, and services are scalable and benefit from economies of scale. This paper examines the utility business model and its future role in the provision of computing services.
Due to the economic characteristics specific to software industry, pricing concepts existing in other industries cannot be transferred without adaptation. Therefore, this article provides an overview of pricing models for software. In this context we discuss the six parameters formation of prices, structure of payment flow, assessment base, price discrimination, price bundling, and dynamic pricing strategies. Furthermore, we refer to recent software delivery models, such as Software as a service. The results are based on literature research and empirical studies.
Currently, the Internet service provider market offers two different types of pricing plans. In the USA, the predominant pricing plan is a flat-rate plan. In Europe and Asia, the predominant one is a per-minute pricing plan. Enrolled in such a pricing plan, users have to pay for the connect time to the Internet. Although Internet Service Providers (ISPs) have competed heavily for users in these last few years, they only have focused on trying to offer the lowest price within such pricing plans. A potentially more profitable and sustainable method of doing business would be for ISPs to differentiate themselves by offering more customized pricing plans for certain user groups. An important question then is whether a pricing plan exists that is attractive to users, but also allows ISPs to build a sustainable business. Based on empirical results of the INDEX project, we discuss a pricing plan for Internet access that appears to be appreciated by Internet users as well as by ISPs. This pricing plan combines the advantages of flat-rate pricing and usage-based pricing. Users will benefit by receiving unlimited access to a basic service with the choice of higher QoS whenever they demand. From the ISPs' perspective, such a pricing plan will help any ISP to focus on certain user groups and to reduce peak network load.
Distributions with an increasing generalized failure rate (IGFR) have useful applications in pricing and supply chain contracting problems. We provide alternative characterizations of the IGFR property that lead to simplify verifying whether the IGFR condition holds. We also relate the limit of the generalized failure rate and the moments of a distribution. Subject classifications: probability distributions. Area of review: Manufacturing, Service, and Supply Chain Operations. History: Received December 2003; revision received April 2005; accepted April 2005.
Information goods vendors offer many different pricing schemes such as per user pricing, site licensing, etc. Why do some firms such as Microsoft offer multiple pricing schemes while others such as Apple's iTunes and Salesforce.com limit themselves to a single pricing scheme? Why do competing sellers adopt different pricing schemes for the same information good? We show that pricing schemes affect buyers' usage levels and thus the revenue generated from them. This is reflected in differences in buyers' demand elasticity under different pricing schemes. We propose and formalize a concept we call Congruousness to measure the level of fit between pricing schemes and buyer segments. We show that firms can use pricing schemes with different congruousness to differentiate themselves from competing firms in a friction-free market for a commoditized informa- tion good. Under conditions that are known to result in the Bertrand equilibrium, we show that an undifferentiated duopoly of sellers can earn substantial profits by using different pricing schemes in a strategic manner. Contrary to prior literature, we show that the strategy of adopting asymmetric pricing schemes can be a Nash equilibrium for information goods with negligible marginal costs of production. We extend our model to the case of information goods that are horizontally differen- tiated and show that sellers will offer a single pricing scheme that is different from its competitor when the sellers are weakly differentiated. When the sellers are strongly differentiated, each seller will offer multiple pricing schemes. We show that it can be optimal for a seller to offer multiple pricing schemes — metered and flat fee pricing schemes even in the absence of transactions costs.
This paper analyzes optimal pricing for information goods under incomplete information, when both unlimited-usage (fixed-fee) pricing and usage-based pricing are feasible, and administering usage-based pricing may involve transaction costs. It is shown that offering fixed- fee pricing in addition to a non-linear usage-based pricing scheme is always profit-improving in the presence of any non-zero transaction costs, and there may be markets in which a pure fixed-fee is optimal. This implies that the optimal pricing strategy for information goods is almost never fully revealing. Moreover, it is proved that the optimal usage-based pricing schedule is independent of the value of the fixed- fee, a result that simplifies the simultaneous design of pricing schedules considerably, and provides a simple procedure for determining the optimal combination of fixed-fee and non-linear usage-based pricing. The introduction of fixed-fee pricing is shown to increase both consumer surplus and total surplus. The differential effects of setup costs, fixed transaction costs and variable transaction costs on pricing policy are described. These results suggests a number of managerial guidelines for designing pricing schedules. For instance, in nascent information markets, firms may profit from low fixed-fee penetration pricing, but as these markets mature, the optimal pricing mix should expand to include a wider range of usage-based pricing options. The extent of minimum fees, quantity discounts and adoption levels across the different pricing schemes are characterized, strategic pricing responses to changes in market characteristics are described, and the implications of the paper's results for bundling and vertical differentiation of information goods are discussed.
The emergence of the software-as-a-service (SaaS) business model has attracted great attentions from both researchers and practitioners. SaaS vendors deliver on-demand information processing services to users, and thus offer computing utility rather than the standalone software itself. In this work, the author propose an analytical model to study the competition between the SaaS and the traditional COTS (commercial off-the-shelf) solutions for software applications. The author show that when software applications become open, modulated, and standardized, the SaaS business model will take a significant market share. In addition, under certain market conditions, offering users an easy exit option through the software contract will help to increase the SaaS vendors' competitive ability.
Information goods have negligible marginal costs, and this will create possibilities for novel distribution and pricing methods. The main concern of this paper is with pricing of goods that are likely to be consumed in large quantities by individuals. For example, will software continue to be sold at a fixed price for each unit, or will it be paid for on the basis of usage? There is substantial evidence both from observing marketplace evolution and from surveys that customers overwhelmingly prefer subscription pricing. It turns out that even if we ignore this factor, peruse pricing is not a clear winner, and therefore when the preference effect is taken into account, subscription pricing is likely to dominate. We model competitive pricing between two companies that supply essentially equivalent services (such as movies or word processing software). One company charges a fixed fee per unit, while the other charges on a per-use basis. Each is interested in maximizing its revenue. We con...
This paper analyzes optimal pricing for information goods under incomplete information, when both unlimited-usage (fixed-fee) pricing and usage-based pricing are feasible. For a general set of customer characteristics, it is shown that in the presence of contract administration costs, offering fixed-fee pricing in addition to a non-linear usage-based pricing scheme is always profit- improving, and there may be markets in which a pure fixed-fee is optimal. Moreover, it is proved that the optimal usage-based pricing schedule is independent of the value of the fixed- fee. These results imply that the optimal pricing strategy is never fully revealing. A procedure for determining the optimal combination of fixed-fee and non-linear usage-based contracts is presented.
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