ON THE FINANCIFICATION OF CLOUD COMPUTING: AN AGENDA FOR PRICING AND SERVICE DELIVERY MECHANISM DESIGN RESEARCH

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1 ON THE FINANCIFICATION OF CLOUD COMPUTING: AN AGENDA FOR PRICING AND SERVICE DELIVERY MECHANISM DESIGN RESEARCH Robert J. Kauffman (a), Dan Ma (a), Richard Shang (b), Jianhui Huang (c), Yinping Yang (a,d) (a) School of Information Systems, Singapore Management University, Singapore (b) School of Business, Public Admin. and Info. Sciences, Long Island University Brooklyn, NY, USA (c) The Conference Executive Board Asia Pte. Ltd., Singapore (d) Institute of High Performance Computing (IHPC), A*STAR, Singapore {rkauffman, Abstract Pricing approaches to cloud computing services balance risks and interests between vendor and client, and optimize supply and consumption in terms of cost, uncertainty and economic efficiency. They also leverage the benefits of various services delivery mechanisms for reserved, on-demand, spot-price, and re-sold services in markets that have learned how to transact in full contracts and services instances. This is like a financial market: with services supply and demand, and opportunities to supply and purchase services with spot prices, or to sell or buy contracts for the delivery of future services. Our research suggests that the financification of the cloud computing services market represents a fundamental shift from the traditional model of software sales and large contracts outsourced to services vendors, to short-term contracts and computing capacity provision mechanism designs that are evolving similar to financial markets. We develop this perspective to explain the cloud vendor market, the provision of services, and the ways in which the financification of cloud computing will shape future offerings and the structure of the market. We see these changes in the market in the many ways that vendors offer cloud services of high value to organizations, while making more profitable business models possible. Keywords: Cloud computing, economics, financification, intermediation, IT services, mechanism design, pricing, research directions, risk management, stakeholders. 1. INTRODUCTION Cloud computing is a means of providing commercial information technology (IT) services to customers and organizations. In traditional IT markets, CPUs, networks, data storage and software applications are sold as products. Customers own a perpetual license after a one-time payment, but they have to pay for upgrades and other in-house IT costs. In the past decade, many IT services vendors have turned to cloud computing: they adjusted their services provision and pricing schemes to permit pay-as-you-go access so that customers are able to pay for usage or subscribe to the computing resources they need. The underlying technologies that empower cloud computing services are not entirely new. They originated from the idea of computation as a public utility in the 1960s (Garfinkel 2011). Virtual private network (VPN) services in the 1990s and grid computing in the early 2000s were predecessors of today s cloud computing services. Amazon played a key role in the development of cloud computing by providing cloud services to external customers and launching Amazon Web Services (AWS) on a utility computing basis in With the entry of many IT giants such as Google, Microsoft, Oracle, and IBM, the cloud services market has become prosperous but more competitive. Initially, there were three main types of cloud computing services in the market: infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a-service (SaaS). As the cloud market matured, more categories emerged, such as data storage-as-a-service (DSaaS), hardware-as-a-service (HaaS), desktop-as-a-service (DaaS), business process-as-a-service (BPaaS), data analytics-as-a- Service (DAaaS) and others (Rimal et al. 2009). Some industry reports have suggested the huge market potential for cloud computing services. The New Yorkbased 451 Research (2013) forecasted that the cloud computing market revenue would grow at a compound rate of 36% to US$20 billion by the end of Gartner (2012) reported that annual IT spending on cloud service brokerage services would have reached US$100 billion by late In addition, Transparency Market Research (2011) reported that the cloud computing services market was valued at US$79.6 billion in 2011, and would grow at a compound annual growth rate (CAGR) of 23.21% and hit US$

2 billion in 2014, higher than Gartner s estimate. It also forecasted that the market value of services production would reach US$205.4 in 2018, based on a slower CAGR of 8.39%. There are conflicting viewpoints on costs, performance, compliance and management, about whether cloud services are a better alternative to in-house systems, however. Prior research has pointed out that the monetary cost of running scientific data-intensive applications using Amazon.com s Simple Storage Service (S3) is out of reach for some clients, because the storage services including availability, durability, and access performance can be expensive and not altogether necessary (Palankar et al. 2008). This has been especially true for small and medium enterprises (SMEs). Deelman et al. (2008) presented other results though: with storage cost reductions, using cloud services is cheaper than in-house systems for data-intensive applications. Different concerns have been raised regarding the pricing of cloud computing services (Yeo and Buyya 2007). Should the services be simple or complex? The menu of available services now has become quite complex. Instead of only fixed-price, fixed-menu items, today vendors are permitting their services to be offered in highly customizable configurations for customers with different profiles. The granularity of selectable service components that are charged separately has become smaller too: from the size of storage to the number of read/write operations. Clients who prefer this may know how to configure the services to achieve customization. But this also increases the difficulty of cost estimation, because the prices will change with the configurations. So clients who want simple services offerings that come with simple fixed-prices may not want this. Furthermore, the fact that clients have to put all or part of their data on the cloud has created concerns about the control and security of sensitive data that reside there. Clients will not be able to access their data if the cloud computing services are down, and they have not backed them up properly. Sometimes it may be impossible to back up in a timely way: this is because of the size of the data and the limitations on the network bandwidth. Previous studies have recognized the complexity and importance of appropriate pricing strategy (Demirkan et al. 2008, Durkee 2010, Marston et al. 2011). The changing cloud services industry invites fuller investigation of pricing strategies to identify factors that reflect vendor concerns when they make pricing decisions and evaluate their services. Some key considerations may be missing in current industry practice. This research aims to provide insights to help managers understand the complex ecosystem of the cloud computing services market. We also will make meaningful predictions about future changes in vendor pricing and services provision. We ask: (1) What factors are driving the emergence of the new services practices? (2) What characteristics of pricing and services provision are likely to persist in the market? (3) And what are the potential directions for future market services provision and pricing mechanisms? In this article, we argue that financification, which has been discussed in the context of IT outsourcing by Bardhan et al. (2010a), is also suitable for cloud computing services and other new kinds of IT services. Financification refers to the technology-enabled practices associated with financial market operations, revenue yield management and financial risk management. With respect to cloud computing services, it is intended to mean that cloud services vendors and clients will be increasingly subject to financial market-like conditions. Services will have bid and ask prices, just like financial securities assets and derivatives in the stock market. Similar to the risks that participants in a financial market face (securities buyers and sellers, and financial intermediaries), vendors, clients and cloud services intermediaries also face multiple sources of risk related to the provision, use, and management of IT services that are similar to financial market-like operations. Cloud services vendors, in particular, face uncertainty in services demand, and their clients have to balance the benefits of cloud computing services with the risks related to control and information security, continuity of services, and integration with other software applications. On the other hand, cloud computing services are built on advanced IT, so many heretofore manual processes can be automated. This makes it possible for vendors and clients to rapidly adjust and create value amid the emerging changes and risks. It also opens up the possibility for cloud intermediaries to add value in the market. This article makes three contributions to research on cloud computing services. (1) Based on financial market concepts and theory, we provide an analysis of the cloud computing services market and identify key elements that are present that make it like a financial market. (2) We assess the paths for the future development of the cloud computing services market, based on its increasing financification. (3) We also offer research directions that will support the achievement of best practices and good market design. 2. FINANCIFICATION AND THE DESIGN OF MARKET-BASED ECONOMIC EXCHANGE IN IT SERVICES We next discuss characteristics of cloud services, the functioning of the related services market, and the ways in which it has become increasingly financified in other words, more and more like a real-world financial market CLOUD COMPUTING SERVICES: CHARACTERISTICS IT services facilitate the processing, manipulation and managerial use of information with the help of computers, networks, communication devices, and technologies that interoperate all these devices and networks. Leavitt and Whisler (1958) defined IT services in terms of the technologies used for processing large amounts of information, applying statistical and mathematical methods to decision- 2

3 making, and simulating mental processes with computers. The definition highlights the role of IT, and IT services by association, in enhancing the capability of human beings to rapidly process large amounts of complex data. Cloud computing technology enables software applications to be easily scaled up and down, and allow companies to gain agility in prototyping, developing, testing, and deploying new applications and services. They include technologies that enable data and application portability. They also comprise virtualization and parallelization techniques that enable better computing power utilization (Williams et al. 2012), web-scale resources and data management technologies (Birman et al. 2009). Finally, they cover largescale event notification and multi-tenancy technologies (Zhou et al. 2010), service-oriented architecture (Bardhan et al. 2010a) and web services (Newcomer and Lomow 2004). Cloud computing technology has created new possibilities for IT services provision and business operation in ways that are dramatically different from what was available before. Cloud computing services have some important characteristics. First, they are similar to information goods: the cost of providing an additional unit of services is negligible. This is true for an additional hour of cloud services or a new client. Such an approach compares favorably to the large investment that is required in the infrastructure to power the services (Varian 1995). Cloud computing services are also similar to experience goods: clients have imperfect information about services until they have tried them out (Shapiro 1983). In addition, cloud vendors sell services in units that are charged based on the amount of time a client uses them, making the services similar to perishable goods, whose value diminishes over time and cannot be restored (Bardhan et al. 2010a). Finally, unlike electrical and water utilities, cloud computing services address multiple purposes. They take various forms, including storage, computation, networking and applications, and can be consumed separately and jointly A PROFILE OF THE CLOUD COMPUTING MARKET The cloud computing services market is an ecosystem that includes different stakeholders that play several different kinds of roles, including component, service provision, and infrastructure roles (Adomavicius et al. 2008). The IT services industry supports the operation and management of clusters of computers and servers with specialized code that enables the efficient allocation of computing resources. These key components make cloud computing possible. An example of related stakeholders that play the component provision role in cloud computing is virtualization solution providers. They have the technical and technology capabilities to help organizations build their own data centers and private clouds. The players include VMware, Citrix, Oracle, and Microsoft Virtual, and others. A difference between cloud computing and traditional IT services is that they are delivered via networks, including the Internet, mobile networks, and private networks. Network services providers operate local or wide area networks, mobile networks, satellite networks, or other types of networks through which clients can transfer data. Other firms, such as telecom and broadband services companies, satellite operators, and so on also play the role of infrastructure providers. A third role that we observe is application services providers. Stakeholders in this role are services providers that directly interact with cloud computing clients. They mainly are software application providers that deploy products on cloud platforms enabled by different infrastructure technologies. Clients subscribe to applications provided by these stakeholders, and they address clients business needs, computing requirements, in multiple industry settings. The coverage spans online gaming to scientific computing, and more. When cloud services providers initially emerged, they used delivery and pricing mechanisms in a pull-and-lock mode. Clients locked the resources for however long a period they needed once they successfully launched a service instance in the cloud. Later, the services began to be provided in a pull-and-lose mode. This enabled the vendor to sell idle computing resources in a cheaper but more flexible way. A downside was that clients might lose access to computing resources even though they launched service instances. The vendor could redirect the resources wherever they provided a higher return. On the pricing side, cloud computing services vendors employ a number of different pricing mechanisms, including usage-based, subscription-based, and a hybrid mix of fixed-price and usage-based pricing. Even for a specific type of pricing though, variations exist in the market. For example, cloud services subscription plans can differ in the length of the subscription period (a month, a quarter, or a year), the limit on the number of user accounts that can access the cloud within a subscription plan, and the number of applications that can be hosted. Prices have been decreasing over the last decade, suggesting evidence for the growth and maturation of the cloud computing services business. For example, Amazon Web Services (AWS), the dominant vendor in the market, has reduced the prices of its services offerings many times (Lauchlan 2013). Amazon successfully promoted cloud services and achieved a 30% market share by 2013, with more than US$1 billion in revenues in a market with high estimated annual growth (Nichols 2014). Another sign of the industry becoming more competitive is the price war that arose between Amazon and Google, shortly after Google introduced its own Compute Engine in March 2014 (Jackson 2014). In this competitive context, clients face the challenge of being aware of which types of tasks cloud computing services suit the best. They might be unclear about the total cost of cloud computing services adoption (Durkee 2010). It also is not easy for clients to monitor their cloud services 3

4 usage, and know the total payments due to the uncertain demand and complex pricing structures of cloud services (Weinhardt et al. 2009). These things have slowed down the adoption of cloud computing services (Perry 2010) THE FINANCIFICATION OF THE CLOUD MARKET Our observations on the cloud computing services market have focused on new services delivery, pricing mechanisms, and new stakeholders. Industry surveys from the Cloud Information Forum (2011, 2012) have suggested that the primary drivers of the adoption of cloud services are flexibility, cost savings and low adoption cost, while the major obstacles are concerns about data security and privacy, reliability and contractual liability. So cloud services providers need to meet their customers needs and requirements with a more flexible and collaborative approach. There is also a need to address the vendor and client risks better, so it is possible to optimize supply in the presence of shifting demand, and new pricing and services delivery mechanisms. They motivate us to explain how the financification of the cloud services market is progressing in a fuller way. To understand this perspective, consider some of the key features of financial markets: (1) bid and ask prices for securities; (2) spot, forward and futures prices; (3) liquidity versus depth; and (4) hedging and risk management. Seeing these in the cloud computing market will suggest a progression toward financification. We have already discussed bid and ask prices, and the different ways in which cloud computing services prices can be quoted. Note that there is currently no cloud services market exchange that handles cloud computing futures contracts, as are handled by financial market exchanges when futures contracts for foreign exchange (FX), derivatives or other financial instruments are involved. There are some hints that options and forward contracts for cloud computing may be coming though (Rogers and Cliff 2012b), with recent research on market mechanisms and demand revelation in IT services (Rogers and Cliff 2010, 2012c; Wu et al. 2008). Related issues have been explored before for options on IT resources (Clearwater and Huberman 2005, Yeo and Buyya 2006) and grid computing (Clearwater and Huberman 2005, Sandholm et al. 2006). Some of these approaches have been conceptualized similar to financial options and forward contracts on FX, for example, which trade in the over-the-counter (OTC) market between broker-dealers based on bilateral negotiation, but not as standardized contracts in financial market exchanges. Other related issues that have been studied include financial risk management for IT services resources, and the benefits associated with matching risks between the vendor and client sides (Benaroch et al. 2010) include, for example, the technology-enabled practices associated with resource management, revenue yield management, and risk management of IT services (Benaroch et al. 2010, Rogers and Cliff 2010, Kauffman and Sougstad 2008a, 2008b). This is like portfolio management, the focus on asset pricing, and the emphasis on financial risk in investments and markets, only for the IT services market (Bardhan et al. 2010a, 2010b). In addition, we view the cloud computing services market as an IT services ecosystem that consists of interdependent stakeholders that have created the conditions for the emergence of a near-financial market in this services arena. There are cloud computing services vendors, cloud technology services providers, services brokerages, application service providers, and services clients. Services vendors provide the major categories of cloud computing services, including IaaS, PaaS, SaaS, and other X-as-a-service offerings. Cloud technology services providers further include vendors that offer the technologies that enable cloud computing. They use virtualization technologies, application parallelization, large-scale storage solutions, monitoring and billing technologies, and other capabilities. Vendors and clients exchange value to achieve joint economic gain. In addition, market intermediaries and brokers, similar to those in financial markets, facilitate the search for and matching of clients with appropriate services vendors, smooth transaction handling, and offer peripheral services (Huang 2013, Huang et al. 2013b). The financification of the cloud computing services market supports effective practices to enhance market performance and avoid market failure (Shang et al. 2012, 2013). The mobilization of cloud services resources and their allocation to productive uses can be coordinated via vendor pricing that permits clients to discover their willingness-topay, much the same as what occurs in financial markets and with revenue management (Kauffman and Ma 2013). In addition, new instruments, similar to financial instruments in financial markets, can be created to support the transfer of cloud services resources from one client to another, a broker to another broker, and so on. Spot prices for services that change in the market based on supply and demand, and longer-term lock-in of the services provide this kind of flexibility (Huang 2013). This form of economic exchange via trading will help to increase the liquidity of cloud computing services, creating fuller utilization and greater marketgenerated welfare (Huang et al. 2013a, 2013b). This also provides more flexibility for when, how, and how many resource units are consumed in the market, and permits conversion of unutilized resources into money. We also are observing new forms of intermediation in cloud services, similar to other e-commerce markets (Cartlidge and Clamp 2014, Rogers and Cliff 2012a). Cloud services brokerages have emerged as digital intermediaries in the services market, creating value for both cloud clients and vendors (Gartner 2012). A recent industry article reported on 35 cloud brokerage firms (Panettieri 2013). They generate value for clients by supporting cloud services intermediation, aggregation, and arbitrage. They also offer value-added customization services, making cloud computing frictionless and refined. They also facilitate its integration with a firm s internal software systems, reducing the 4

5 risk of mistaken adoption for clients, similar to what we observed in the 2000s for electronic markets (Dai and Kauffman 2004). Cloud computing services also can be tweaked to meet clients needs and still be profitable for the vendor. 3. STATE-OF-THE-ART IN CLOUD COMPU- TING PRICING AND SERVICES PROVISION To get a comprehensive view of the cloud services market, we examined 19 cloud services vendors and 27 services offerings that they provide. They include four major types of cloud computing services: IaaS, PaaS, SaaS, and brokered cloud services. IaaS delivers computer infrastructure based on virtualization technology. PaaS has an additional layer on which clients can run applications without knowing how the underlying infrastructure is implemented. SaaS provides application services that function as locallyinstalled software (Vaquero 2008). Cloud services intermediaries, aggregators, and arbitrageurs provide brokered cloud services in the market as well (Gartner 2012). (See Appendix A.) We reviewed the cloud computing services offerings and collected pricing information from the major market players. Our criteria for selecting a vendor were: (1) the vendor must have made pricing information on all its services available on its official web site; and (2) the vendor must have been selected at least once for review in Gartner s Magic Quadrant Report (Leong and Chamberlin 2010, 2011; Leong et al. 2012, 2013). The reports list cloud computing services vendors that are leaders in the market, in terms of revenue and market share. This is useful information. It helps to ensure that we are sampling from an appropriate set of cloud services vendors in the market, so the right kinds of firms are represented, which makes our results more meaningful. We next offer our reading on the state-of-the-art in the cloud computing services market, inclusive of current services provision and pricing mechanisms, and their trends, based on our observations and analysis SERVICES DELIVERY AND PRICING MECHANISMS Table 1 shows that most PaaS, SaaS, and cloud brokerage services vendors offer reserved services delivery. Cloud computing services with reserved resources are precommitted resources for clients by the vendor. Clients can choose from several options for the length of the reservation period predefined by the services vendor. For example, Amazon EC2 offers clients with reserved compute instances for a period of one year or three years. From the vendors point of view, reservations benefit them by reducing their demand uncertainty. Any pre-paid reservation fees can enhance a vendor s cash flow, and generate lock-in with clients. Associated with the reserved services is reservationbased pricing, which varies with the type of services offered. Reservation-based pricing has been popular in the restaurant and hotel industry; it typically results in increased vendor revenue (Alexandrov and Lariviere 2008). In the case of hotel reservations, rooms usually are scarce in popular attraction areas, so travelers must be willing to pay for reservations. The same rationale does not hold in cloud services though. Computing capacity is expandable at a relatively low cost. So clients have little incentive to reserve services (Meinl et al. 2010). The situation will change when the cloud services market becomes more competitive and new demand emerges due to advances in related technologies though. These will include sensor technologies that enable wearable devices connected to cloud-based health informatics services, and web-based data analytics that help companies gain insight into their operations, customers and the marketplace for their products. Reserved services delivery Ondemand services delivery Spot-price services delivery Brokered services delivery Table 1. Services delivery and pricing mechanisms RESERVA- TION- BASED PRICING Amazon, Google, Microsoft, Rackspace, GoGrid, Joynet, HP FlexiScale, PiCloud, CloudSigma, ProfitBricks USAGE-BASED PRICING FIXED PRICE Amazon, Google, Microsoft, Rackspace, GoGrid, Joynet, HP, FlexiScale, SPOT PRICE Amazon TECHNICAL SUPPORT- BASED PRICING Amazon, Google, Microsoft, Rackspace, GoGrid, Joynet, HP, FlexiScale, On-demand services delivery, which provides reserved resources based on pay-per-use, also has been widely adopted in the cloud computing services market. On-demand services delivery performs in an interesting way. Once a client launches a job, the vendor will set aside capacity for the job until the client terminates it. Clients are charged based on the usage of services, as well as by the amount of time that the services are used. Usage-based pricing is optimal for information goods that have negligible marginal production costs (Maskin and Riley 1984), such as movie CDs or software apps. Most IaaS vendors in our survey employ usagebased pricing. The prevalence of usage-based pricing among IaaS offerings is inconsistent with the findings in Fishburn et al. (2000) and Sundararajan (2004), though it matches the findings in an earlier study by Maskin and Riley (1984). The key difference in these studies is whether the transaction costs associated with usage-based pricing are negligible. IaaS vendors commonly implement highly automated management systems, which generally have low transaction costs. So it is reasonable for IaaS vendors to adopt a pure usage-based pricing scheme. 5

6 Prior research suggests that fixed-fee pricing together with usage-based pricing always outperforms pure usagebased pricing (Sundararajan 2004). Such two-part tariff pricing is never worse than any non-linear pricing strategy (Masuda and Whang 2006, Png and Wang 2010). These findings are consistent with pricing practices in the cloud market also. Many PaaS and SaaS vendors have adopted the two-part tariff pricing model, for example. Clients typically pay a monthly subscription fee for pre-assigned usage quotas, and pay an additional price if the usage exceeds them. The resource acquisition and allocation of spot-price services delivery differ from those of reserved resources. There is no commitment on the part of the vendor to guarantee access at a given time, other than via the client s willingness to pay the spot-market price for services. The acquisition of resources for spot-price services varies according to a client s bid price valuation and the changing relationship between supply and demand. Clients submit bids representing the maximum unit prices they are willing to pay for a predefined type of spot-price service. As soon as the service price in the spot market goes above the client's bid price, the vendor will terminate its in-process services. As a result, computing tasks running as spot-price services may occasionally be interrupted due to price spikes in the market. Clients will receive service allocations that are affected by the interplay between supply and demand, and bear risks of service termination that are not controllable by themselves. On the other hand, spot-price services are cheaper most of the time, spot-price services represent less than 25% of all tasks that use reserved resources. The cost savings from using spot-price resources are attractive for clients who need cloud services for compute-intensive but time-insensitive tasks, such as scientific computing, web crawling, and data analytics. A variety of resource allocation approaches have emerged recently, involving predictive analytics, machine learning, and other models that support value-conscious use of limited server resources (Das et al. 2011, Mazzucco and Dumas 2011). Empowered by these resource management techniques, brokered services delivery is able to provide less costly and more reliable services to clients. For example, PiCloud (now owned by DropBox), a computing services broker that connects clients to Amazon s cloud services, emphasizes a positive customer experience. It delivers results 33% faster and meanwhile saves clients 65% in total costs compared to spot-price purchases, while still running 85% of jobs as Amazon spot-price services instances (Elliott 2012). Brokered services delivery can be provided in various ways, such as management services provided as subscription plans that support day-to-day management of cloud computing services from various vendors, or valueadded services that are charged by usage. Clients usually do not have full control of the resources. Instead, services brokers make it transparent to clients how they acquire, integrate and manage resources from different services vendors. They also provide clients with interfaces to configure and manage their usage. Most major vendors apply technical support-related pricing to different technical support plans with different levels of expertise for client engagement. In general, SaaS vendors provide greater flexibility in technical support options, while IaaS and PaaS vendors offer more limited options for their clients. This may be due to the relative simplicity of IaaS and PaaS services. For example, IaaS clients can terminate the services and shift to other vendors anytime without incurring high costs. In contrast, SaaS services typically contain functions that are provided only by a particular vendor. More technical support from the vendor is needed when problems occur, and a switch to other SaaS vendors is generally difficult SERVICES DELIVERY AND PRICING INNOVATIONS Amazon has been an innovator in cloud computing services delivery and pricing mechanisms. It first introduced its Elastic Compute Cloud (EC2) services in 2006, and used an on-demand services delivery with a pay-per-use pricing mechanism. Payments were based on actual usage, charged by the hour. Since then, Amazon and its competitors introduced a series pricing innovations in the market. In 2009, Amazon announced two other new services delivery mechanisms: EC2 reserved instances and EC2 spot instances. With the reserved services delivery mechanism, a client must pay a fixed fee up front to reserve services. The client still needs to pay for actual usage, but the per-hour rate will be lower than that in the on-demand pay-per-use model that Amazon introduced in Spot-price services delivery uses a different pricing model that is auction-based. The major difference between spot-price services and the other options that Amazon offered was that the spot-price services were subject to interruption initiated by the vendor. This pricing mechanism allowed Amazon to ration its idle computer resources based on client willingness-to-pay. In spite of its innovative services and pricing design, Amazon has more or less locked itself into a specific billing cycle: it always charges clients by the hour. Others are pricing their services in a more innovative way. For example, in 2011, CloudSigma, a Zurich-based IaaS vendor, announced a burst-pricing scheme that had a billing cycle as short as five minutes. This is similar to the practices that some telecom services firms used. They initially offered monthly subscription plans only, and then started to offer per-second billing. It is likely that the cost associated with metering and billing in such a short interval is lower now. In 2012, Pi- Cloud offered its clients even more value by providing a usage-consolidation service. A client could use 1,000 compute instances, each active for one second only, and then pay the price for using one compute instance for 1,000 seconds. This would have cost the client 1,000 instance hours via Amazon EC2. The emergence of configurable cloud computing services offerings reflects advances in managing 6

7 virtualized computing resources. Cloud vendors can now give more flexibility to their clients than ever before. 4. NEXT-GENERATION MECHANISMS In the cloud computing services market today, we observe the pull-and-lose mode of services delivery that emerged after the pull-and-lock mode, which was the default in the early days for cloud computing services. This change in the services delivery mechanisms reflects the needs of services vendors for more flexibility in selling and re-allocating their resources, and their desire to penetrate the IT services market. On one hand, a large investment in infrastructure puts pressure on cloud services vendors to recover their investment. On the other hand, cloud computing services still are underused, despite their capability to accommodate all kinds of client needs. We can see this hold-up based on different concerns in adopting cloud computing expressed by leaders in sectors that rely on or heavily use IT services, such as financial services and healthcare. Cloud computing services are still in the process of maturing and fast growth. New functionalities are being added to existing services offerings, and totally new services are being introduced. In the process, some clients will naturally be resistant to trying out cloud computing services, unless there are more options that mitigate both the operational and financial risks for them. They also will need more support to transition from legacy systems to the cloud, a big challenge for many organizations. We next will offer insights on new services provision and the kinds of pricing mechanisms needed for the future development of cloud computing services QUANTITY DISCOUNTED PRICING: TRADE COST REDUCTION WITH DEMAND UNCERTAINTY It is common in pricing strategy that a services vendor uses quantity discounts to give buyers incentives to purchase greater than the usual quantity. Research has shown that second-degree price discrimination, especially nonlinear pricing strategies such as quantity discounts, is an effective way for vendors to segment clients, gain market power and obtain higher profit (Goldman et al. 1984, Monahan 1984). In the current cloud market, only storage service vendors provide quantity discounts in the form of ladder-shaped tariffs. They offer clients who use the services bigger discounts on the unit prices. Other than that, quantity discounts are rarely used in any other categories of cloud services. For example, for an Amazon EC2 on-demand standard instance (small) running on Linux or Unix, the price is fixed at $0.06 per instance-hour. There is no unit price difference for a customer who runs 10 instance-hours versus one who runs 10,000 instance-hours. For information goods, past research indicates that usage-based pricing with a quantity discount strategy is optimal when there are no transaction costs (Maskin and Riley 1984). So it will be an option for cloud vendors to use quantity discount pricing to incentivize their clients to consume more services SLA-BASED SERVICES DELIVERY: FLEXIBLE QUAL- ITY GUARANTEES, COSTS AND COMPENSATION Cloud services are experience goods: their tangible features do not fully reveal their true value. Software outsourcing contracts have a similar issue due to information asymmetry (Dey et al. 2010). Enhancing the completeness of the contract can potentially overcome this problem, but at a high cost (Hart and Moore 1999). In the practice of software outsourcing contracting, most vendors specify the penalties applicable when delivery is delayed (Whang 1992). Clients also have the right to terminate their contracts, although this may be explicitly priced in a way that the vendor can assure it will not be left with idle capacity that it spent money to create (Benaroch et al. 2010). In cloud computing, service level agreements (SLA) serve as incomplete contracts between a client and a services vendor, similar to other IT and grid computing services (Li and Gilliam 2009, 2010; Li et al. 2010). Service uptime guarantees are often stipulated in an SLA, like an uptime guarantee of 99.9%, and terms specifying service characteristics and penalties. In current practice, many IaaS and PaaS vendors include both uptime guarantee and penalty terms in their SLAs; few SaaS vendors do this though. All the vendors we reviewed, except for Salesforce, provide uptime guarantees. And some IaaS vendors are offering different uptime guarantees for different types of services. For example, Amazon provides a 99.9% uptime guarantee for S3, and a 99.95% uptime guarantee for EC2. Rackspace provides a 99.9% uptime guarantee for storage services and a 100% uptime guarantee for network availability. Most of the SLAs include uniform penalties that the vendor must pay to all sorts of clients. Some issues are ignored by this penalty design approach though. For example, client attitudes toward the risk of services downtime differ across applications and periods. Mission-critical enterprise applications typically carry a much higher cost for services downtime than non-critical applications (Hiles 2005). To meet the diverse expectations, the vendor may wish to consider including customized penalty terms that are expected to outperform uniform penalties. It may be mutually beneficial to provide functions for negotiating penalty terms to satisfy different types of clients. With the technology affordance of SLA-oriented resource management of cloud vendors, future services delivery will differentiate among and satisfy service requests based on the desired utility of users, balancing risk concerns and service costs. 7

8 4.3. CLOUD COMPUTING SERVICES MARKET EVOLU- TION: TOWARD FINANCIFICATION Next, we discuss how the cloud computing services market has been changing, and how the financification of the cloud market will reshape and guide its future evolution. When usage-based ondemand services were first introduced in the market, they nicely addressed the early adopters uncertainty about services quality, and to what extent users needed cloud resources. With the pay-asyou-go mechanism, users were subject to potential risk of the unavailability of cloud resources when they needed them, and the potential for price increases in the future. With the financification of the cloud, we expect an options and futures contract market for cloud services to emerge so users of on-demand services will be able to hedge their risks. In the context of IaaS, Rogers and Cliffs (2012b) proposed a pricing method that combines options contracts with on-demand purchasing. They show that options contracts can provide clients with flexibility and cost-savings, as well give the vendor improved server utilization. Later, with the improvement of service quality and adoption of cloud, reservation-based services were introduced to users who wanted to avoid the uncertainty of availability and price fluctuation. They were subject to the risk of being locked in and not being fully satisfied with the services, and they also may have over-estimated their cloud resources needs. It is conceivable that the financification of the cloud will also address these additional problems. Exchange-like markets for cloud services will likely emerge so users of reserved services can resell unutilized resources. With the huge investments in cloud computing capacity that have been made since Salesforce.com emerged, many vendors now face the spectre of unutilized capacity due to shifting supply and demand. Spot-price services were introduced as a way for vendors to monetize their unutilized capacity. The services were subject to interruption risk though. So today, the logical next stage of evolution that will occur in an increasingly financified market is the further development of cloud brokerage services, which will provide leverage for more economical use of spot-price services. An example of this is Amazon s 2013 launch of its EC2 Reserved Instance Marketplace, in which users can resell their unutilized balance of reserve instances to other clients. Looking toward the future, we expect to see further development and evolution of the cloud computing services market, related to its technical aspects, and the mechanisms that structure the offering, pricing, purchase, and delivery of services. See Figure 1 for a summary. Although the figure may be misinterpreted as suggesting that the cloud computing services market is an integrated market, it actually is quite fragmented. There are variations in how services are provided and consumed, and how vendors compute what their clients will pay. Thus, there is potential for a more efficient services market that subsidizes new clients who have uncertainty about adoption, use and workload management, and have to deal with contingent conditions in their day-to-day operations. In addition, the current marketplace has many constraints on what resources are available and how they can be traded between clients. Take Amazon s EC2 Reserved Instance Marketplace as an example. Users can resell their unutilized instances to other users. However, in the current practice, the time available to consume a reserved instance often is rounded to the nearest month, and the marketplace will charge a service fee of 12% on the price. These constraints mitigate the marketplace s ability to fluidly facilitate the trading of unutilized resources, reducing their market liquidity. We believe that a future financial market exchange-like marketplace will be needed to optimize resource allocation and re-allocation to effectively promote the adoption of cloud computing services. Finally, because IT services are subject to risk for quality, cost, delivery, availability, it is likely that insurancerelated products will emerge for them in the future (Accenture 2010, Cohen 2013). The establishment of cloud services benchmarks (Yi et al. 2010) and the maturation of actuarial analysis of cloud services risks will support this future development, similar to what we have seen with other IT services (Bardhan et al. 2010a, Gillam et al. 2013, Kauffman and Sougstad 2008a). An example is CloudInsure 8

9 ( com), a Rye, New York-based cloud computing insurance administrator that specializes in IT services risk transference. Another is MSP Alliance s ( managed services insurance, which offers vendors indemnification against liabilities from providing cloud services. 5. RESEARCH DIRECTIONS FOR CLOUD COMPUTING MECHANISM DESIGN The range of issues that are related to the financification of cloud computing deserve closer scrutiny. This can be achieved by laying out a research agenda related to the fundamental mechanism design issues for cloud computing services. The issues identified are: the supply and demand relationship and demand estimation; services offerings and the structure of market prices; contracting, incentive-making, and risk mitigation; third-party services and the value of intermediated cloud services; and future innovations that have the potential to reshape the entire market. We begin with the first issue in this research direction on the supply and demand of cloud computing services: Research Direction 1 (Supply and Demand of Cloud Computing Services in the Market). Understanding the future functioning of the cloud computing services market requires a basic knowledge of how supply and demand interact with one another. An important research direction to pursue involves developing theoretical models and empirical studies that will enable senior management to obtain more knowledge of how supply and demand will play out in the future, as the conditions, competition and capabilities in the market change. Since production and consumption of cloud computing services are growing globally, it is important for researchers to assist industry and government observers to establish measurements and estimates of this area of services in the economy. For example, Gartner s estimates on cloud services were recently expanded to US$180 billion by 2015 (Flood 2013). Seagate estimated that US$79 billion in cloud computing hardware and equipment will ship by The healthcare industry, for example, will use cloud computing for 600 million images processed each year, and move from only 15% today to 50% of diagnostic images stored in the cloud by 2016 (Cox 2013). These statistics are just the tip of a big iceberg though, and other issues deserve attention (Woods 2014). Key considerations are building models for national-level cloud computing services growth both in terms of what is demanded and what is supplied. Some observers view rapid growth of cloud computing as inevitable (Mason 2013, Weinman 2009). Within specific industries, there exists the issue of how different business processes and computing workloads will be affected by cloud computing services growth. How much money will be saved? Will downsizing of organizations occur, shifting cloud computing demand? And how long will it take to reap business value from cloud computing, and what can be done to accelerate it? Research Direction 2 (Services Offerings and the Structure of Market Prices). There is a need to pursue new bases for innovation related to cloud computing services and market mechanism design, and pricing and quality strategies. This will be a fruitful research direction because it is necessary and valuable to develop and test new business models, pricing approaches, and mechanism design algorithms. The demand for cloud computing services is driven by the variety of the client needs and the quality of the services that are offered, the price structures and price levels at which they are offered, and the mechanism designs that meter their delivery. This opens up a broad spectrum of issues for research. For example, what future business models are likely to be effective in supporting services that will create higher demand? Will they be private-label services with branded performance and unique qualities? Or will they be more commoditized services whose provision is driven by the cost leadership of large-volume, high service-scope vendors? The financification of the cloud computing services market is likely to be driven toward greater service commoditization, thinner margins where the services are provided without recognizable innovations that create value, and increasing homogeneity in the functionality of the services that are offered. There are opportunities to conduct analytical and computational modeling research to assess the relative performance of different kinds of mechanisms under different assumptions about future growth and demand. It will be especially useful to understand the extent to which prices are dispersed or concentrated across different vendors who offer similar services. Also, managers will find it beneficial to understand more fully how to do effective statistical modeling of spotprice cloud computing instances in public markets (Javadi et al. 2011) and how spot prices change in these kinds of market environments (Javadi et al. 2013). In future markets, data analytics for different kinds of cloud computing instances, and how demand and supply interact over time in the presence of managerial choices on pricing for them, will become strategic capabilities for cloud computing vendors and their clients. Cloud computing services should be built on vendor, client, and market informedness (Li et al. 2014), so that it is possible to gauge prices under normal operating conditions, as well as for peak loads in the market (Mattess et al. 2010). Research Direction 3 (Incentives, Contracting, and Risk Mitigation). These issues motivate another research direction that involves economic analysis of incentives, assessment of information asymmetries for SLA contracts, statistical analysis of the sources of risk, and financial economic modeling of risk and re- 9

10 turn. Incentives, contracts and risk mitigation are different facets of the same basic problem in cloud computing services. Vendors need to design services and operate mechanisms, supported by effective and balanced contracts, so that it is possible for the client side to believe that there is fair play with the sharing of the benefits and value arising from services provision. For example, a vendor may grant its client a real option involving the right but not the obligation to switch from fixed-price contracted services to spot-price instance purchases. Benaroch et al. (2010, p. 319) argued: When an IT services vendor permits a client firm to exercise its flexibility to switch sourcing modes, it essentially is offering an opportunity to the client to achieve a marginal cost advantage per IT service unit at varying demand levels. There may be a loss of business for the vendor and a value gain for the client.... For the client, there will be the irreversible switching costs of searching for a new vendor, and whatever recontracting costs arise in the process... Thus, switching between sourcing modes presents a trade-off The research on IT services beyond cloud computing services, especially for outsourcing and fixed services contracting has explored a number of modeling perspectives that are likely to be useful in the cloud computing context. An example is the work of Alvarez and Stenbacka (2007). They explored how to model IT sourcing and backsourcing decision-making, so that it is possible to adjust the contractual acquisition of services when services demand falls in a flexible way, with a fair price charged by the vendor. Techopitayakul and Johnson (2001) studied another research context: application service provider (ASP) operations. They modeled decision-making under uncertainty for the value of the software that is used, the number of users, and the overall usage level. They assessed a vendor s offering, including usage-based pricing versus a flat subscription fee, back-sourcing to in-house computing, and contract abbreviation. The research is especially interesting for its inclusion of how learning effects from service consumption for the vendor and client play into the valuation of contract terms for IT services. Research like this offers tremendous motivation to researchers and managers to port some of these ideas from statistical analysis, risk management, and financial economics into cloud computing consulting and services management practice (Bardhan et al. 2010). Due to the information asymmetries that are present in cloud computing, the vendor sees the market as a whole but the client only knows its own demand (Stantchev and Tamm 2012). There are ample opportunities for process-perfecting third-party information and data analytics providers to enter the market, increase vendor and client informedness, and improve their welfare (Knapper et al. 2011). Research Direction 4 (Third-Party Services and the Value of Intermediated Cloud Services). Digital intermediation in the cloud computing services market is a key target for mechanism design innovations. The creation of new knowledge about the industrial organization and optimization of IT services and cloud computing intermediation will offer high scientific payoffs and positive business returns on investment for research that deals with the hard problems in this context. An intermediary s position in a technology ecosystem is determined by its viability and sustainability. The intermediary will demonstrate viability when it creates economic value for other participants in the ecosystem (e.g., buyers and suppliers in supply chain management, or clients and vendors in cloud computing) in excess of the value produced in its absence. This value difference must be sufficient for the intermediary to earn a profit, so it will maintain its incentive to participate and supply services (Kauffman et al. 2010). The intermediary will demonstrate sustainability when it is continuously able to create value over time through the service transactions it supports to generate profits that cannot be achieved without similar market organization. Beyond these basic observations though, how will we know which intermediated solutions will work in the market, and which will not? For example, will it be market structure, competitive positioning, service pricing strategy, service quality, or information security that will be the foremost considerations? What kinds of models and business policies, and what kinds of empirical evidence and business results will make it clear what works and what does not? Cloud computing technology platforms will do well when their installed base of clients is high, the demand for their services is relatively stable, and their growth trajectory looks positive for the future. But investments in cloud services intermediation, similar to every other facet of business in a modern economy, will be subject to the vagaries of competition, vendor strategy errors, sufficient compatibility, and mistaken services and mechanism designs. As a result, undertaking research that provides a deeper understanding of how cloud computing services firms need to design and operate their businesses also has the potential to produce useful new knowledge about their market performance. Research Direction 5 (Future Innovations in Technologies, Services and Infrastructures). Research that identifies the basis for future innovations in the cloud computing services market will be of high value, especially if it is possible to explain and predict how and why, and under what circumstances, the changes are likely to be observed. Technology and technology-based services forecasting are among the most difficult tasks that business and technology analysts need to undertake in the current business environment. One perspective on future innovations and markets for cloud computing services is that technological 10

11 innovation will be supply-led, with the innovations on the vendors side, with market demand being transformed in the process (Adomavicius et al. 2011). Another related perspective is that cloud computing services innovation will be demand-led: the more the market demonstrates its willingnessto-pay for new services, the harder will vendors work to innovate and drive profit from the new business. So an important research direction for cloud services is to study, forecast and analyze how future innovations will take place and what are their possible adoption and diffusion paths. 6. CONCLUSION This article offers useful contributions for research and practice. On the research side, it shares a new perspective for the organization of cloud computing services markets, supply and demand for services, market mechanisms and pricing approaches, contracts and incentives, and third-party intermediation. The cloud computing services market exhibits key features of financial markets, including: (1) bid and ask prices for services; (2) spot, forward and futures prices; (3) services liquidity and services depth; and (4) opportunities to apply hedging and risk management. We illustrated this with spot prices and dynamic prices, with cloud computing insurance, with brokered cloud services, and other compelling examples. Our central goal in this article was to demonstrate a practice-led set of scientific observations that can be interpreted from the perspective of relevant theory from financial economics and its ties to related markets. We are pleased to offer the financification of the cloud computing services market contribution to managerial understanding of a leading example of the dramatic changes made possible due to a revolution in technology computing in the cloud and the continuing evolution of the IT services practices that have occurred around it. Through the lens of financification that we have offered, managers and consultants who are trying to understand current and future markets for cloud computing will be empowered to make more confident predictions and thoughtful explanations for what is to come. A number of future challenges based on our perspective are likely. How far will cloud computing services go in terms of the extent of financification we will see? Technological, economic, business, and competitive factors are all likely to play a role in the future. We have not answered all of the questions that an informed group of researchers and practitioners are likely to ask. Nevertheless we have offered a practice-led view of what is likely to happen in a marketplace that is subject to the inexorable forces that all financial markets have experienced as we have seen in other sectors with perishable services, including the hospitality, air travel, temporary labor services, and television and radio entertainment sectors. 7. ACKNOWLEDGMENTS The authors acknowledge Singapore s Agency for Science Technology and Research (A*STAR) for its generous support of this research, as well as the following individuals at the Institute for High Performance Computing (IHPC) for their input: Terence Hung, Li Xiaorong, Henry Palit, and Qin Zeng. We benefited from the comments of the International Journal of Cloud Computing editors, Hemant Jain of the University of Wisconsin, Milwaukee, and Rong Chang, at IBM s T.J. Watson Research Center, and an anonymous member of the journal s editorial board. Huang Jianhui thanks the Ph.D. Program in the School of Information Systems at Singapore Management University, and Singapore s Ministry of Education for doctoral fellowship funding from 2009 to In addition, Yang Yinping benefited from the funding provided by her Independent Investigator research grant at A*STAR. 8. REFERENCES 451 Research. (2013) Market monitor: cloud computing. White paper, New York, NY. 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Symp., IEEE Comp. Soc. Press, Washington, DC, Appendix We reviewed 19 cloud computing services vendors that offer 27 types of services, including 15 IaaS, 6 PaaS, 7 SaaS, and 3 cloud services brokerage services. (See Table A1.) Table A1. Cloud services vendors selected for this study TYPE NAME VENDOR URL Amazon EC2 On-Demand Instance Amazon goo.gl/fezld Amazon EC2 Reserved Instance Amazon goo.gl/fezld Amazon EC2 Spot Instance Amazon goo.gl/fezld Amazon S3 Amazon goo.gl/bcg1n Infrastructure-as-a-Service Alatum goo.gl/w0b9d Enterprise VM Hosting ngrid goo.gl/iheui CloudSigma CloudSigma goo.gl/20mev IaaS Cloud Servers GoGrid goo.gl/6z4bo Joyent Cloud Joyent goo.gl/xkcwa Rackspace Cloud Servers RackSpace goo.gl/cszea FlexiScale public cloud FlexiScale goo.gl/i9rwe IaaS ProfitBricks goo.gl/weh6l Google Compute Engine Google goo.gl/rehh4 HP Cloud HP goo.gl/zv3fo CloudLayer Computing SoftLayer goo.gl/8vkj3 PaaS SaaS Cloud Brokerage Google App Engine Google goo.gl/rltg8 CloudFare CloudFare goo.gl/jqt9q Force.com Salesforce goo.gl/lo8jj Microsoft Windows Azure Microsoft goo.gl/rdwp5 Microsoft SQL Azure Microsoft goo.gl/rdwp5 Amazon Beanstalk Amazon goo.gl/tpu0e Service Cloud Salesforce goo.gl/7sjjf Sales Cloud Salesforce goo.gl/pkojz Chatter Salesforce goo.gl/g7lqq Jigsaw Salesforce bit.ly/g6i6um Google App for Business Google goo.gl/kxkez NetSuite Financial Management NetSuite goo.gl/dtqth Office 365 Microsoft goo.gl/au3tm PiCloud Public Cloud PiCloud goo.gl/jgbkt RightScale Cloud Comm. Edition RightScale goo.gl/pddwl Integration Cloud Boomi goo.gl/oo3lz Note: All information was collected from the vendors official websites in October 2013, and updated as of October Vendors may have changed their website structures and content related to their services pricing after we completed our update. 13

14 Authors Robert J. Kauffman is Associate Dean (Research), Deputy Director of the Living Analytics Research Center, and Professor of IS at Singapore Management University. His graduate degrees are from Cornell and Carnegie Mellon. He is an expert in technology and strategy, financial IS, IT services, and the economics of IT. Dan Ma received her Ph.D. from the Simon School of Business at the University of Rochester. She is an Assistant Professor of IS and Management at the School of Information Systems, Singapore Management University. Her expertise is in economics and IS, IT services, cloud computing, and game theory. Richard Di Shang is an Assistant Professor of MIS at the School of Business, Public Admin. and Info. Sciences, Long Island University Brooklyn. He received his Ph.D. in Business (IS) from City University of New York. He previously was a Scientist at Singapore s Agency for Science, Technology and Research (A*STAR). He applies experiments to test insights from economics for IT services, information goods, and e-marketplaces. Jianhui Huang is a Senior Research Analyst at the Corporate Executive Board Asia Pte. Ltd. His Ph.D. degree is from the School of Information Systems, Singapore Management University. His research interests include the economics of IT, business model in IT services, the impact of cloud computing, and IT value cocreation. Yinping Yang is a Scientist and Capability Group Manager at the Institute of High Performance Computing (IHPC), A*STAR, Singapore. She is affiliated with the School of Information Systems of Singapore Management University as an Adjunct Faculty. She received her Ph.D. in IS from National University of Singapore. Her research brings design science and behavorial science to the study of electronic negotiation systems, social networking sites and IT services. 14