SiBW 2018 144 How to support transformation from on-premise products to SaaS? Position paper for future research Teppo Yrjönkoski Tampere University of Technology, Pori, Finland teppo.yrjonkoski@nelnastori.fi Abstract. This paper reviews academic knowledge for software-intensive busi- ness firms’ approaches to support transition from on-premise solutions to SaaS. The aim is to increase preunderstanding for future research and review the trans- formation’s impact on business models. The study is restricted to the small and medium-sized software vendors. In addition, embedded software vendors are ex- cluded from the research. In preliminary unsystematic literature review, several business model specifications and canvases used to address the transformation were identified. Firstly, a few of the papers were concentrating on huge software- intensive companies like Oracle, Siebel etc. and comparing their business mod- els. Secondly, other studies were analyzing technology changes as well as threats and the lifecycle of technology. Thirdly, researches were analyzing SaaS plat- forms like (Microsoft’s) Azure or (Amazon’s) AWS. The review shows that few works focused on how the smaller enterprise software companies did the transfer, which covers for example personnel, product portfolio, distribution network, market segmentation and revenue model or why they have not even started. This study shows that there is lack of studies addressing this issue and propose further research on the issues, which would benefit small- and medium-sized software- intensive firms. Keywords: Cloud Computing, Software-as-a-Service, business model in soft- ware business, from on-premise to Software-as-a-Service, Software-intensive business. 1 Introduction Cloud computing and Software-as-a-Service (SaaS) paradigm have gained remarkable popularity in the software industry. According to NIST [37] definition, cloud compu- ting refers to “enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applica- tions, and services) that can be rapidly provisioned and released with minimal man- agement effort or service provider interaction”. There are several different service models inside the cloud computing paradigm; however, most often used are IaaS (In- frastructure-as-a-Service), PaaS (Platform-as-a-Service), and SaaS (Software-as-a-Ser- vice). SaaS refers to “[…] capability provided to the consumer is to use the provider’s applications running on a cloud infrastructure” [37]. SiBW 2018 145 For a customer as well as a software vendor, cloud computing and SaaS solutions offer clear benefits. On one hand, a customer will be using the same software version as everyone else. Consequently, there will be less bugs, less maintenance, faster product development for the customer etc. The negative point is that there are no or only a few alternatives to adjust or tailor the software to fit specific customer needs. On the other hand, the vendor has just one main version to develop, update and keep updated compared to an on-premise alternative, where there may be two versions under support and one new version under development. The positive impact of these all is the improved speed of product development and cost savings because of less concurrent work. The negative impact is, firstly, minor customer requirement coverage. Secondly, this may need increased attention to product management and product marketing. If there is a lack of those activities, it may lead the customer choosing another vendor. Due to the rising popularity of SaaS solutions, several software companies have changed their business model from selling on-premise products to providing cloud- based solutions. As a notable example, for instance Microsoft has transformed its Of- fice tools from on-premise installed products towards SaaS-like solutions with the new Office 365 service. In addition, it is likely that there are plenty of companies, which are planning of following the same path. However, the transformation process from offering an on-premise installed product to a solution offered as a service in a cloud is not straightforward. In top of technical challenges, this kind of a transformation process naturally creates change pressures to the company itself and its business model. For example, how an organization, which previous on-premise software product has generated income with both license and sup- port sales, should manage changes in the cash flow when a new SaaS version generates stable, yet in the beginning smaller, revenue stream? This position paper focuses to study what do academic literature report of this kind of transformation processes. Our focus is specifically on the changes in the business model as well as in the financing of a software-intensive vendor. The aim of the paper is to create a starting point for further studies in this area as well as propose some lines of research. This position paper uses unstructured literature review method [23] to col- lect relevant primary studies for the starting point. Based on the findings of the literature review, we discuss on potential areas for future work. The digital transformation impacts the whole industrial world. Because the digital transformation will be everywhere, there will be a risk open the limitations too much towards generic digital disruption. For this paper, we restrict our attention to software- intensive companies, and especially small and mid-size software vendors. The target group is enterprise software vendors and non-software companies have leaved out. The rationality is that large software vendors might have enough knowledge, capital and resources to manage the transition whereas small- and mid-size enterprises might not have capital required nor enough human resources for a new project. Furthermore, we exclude embedded software vendors as their main revenue flow often does not come from selling software licenses. That is, the transition might not create similar changes to their business model. The remaining of this paper is organized as follows. Section 2 gives an overview of cloud computing research and defines the complex concept of business models. Section SiBW 2018 146 3 presents finding from the literature review regarding different cloud business models and business model elements. The fourth section discusses about the directions of fur- ther research and the final section concludes the study. 2 Background 2.1 Cloud computing The paradigm shift, from on-premise software solutions toward SaaS solutions, seems to be reality nowadays. The SaaS trend seems to be a de facto standard or at least ap- proaching the de facto on consumer software solutions. [38] On enterprise business software, the picture is not yet the same as in the consumer software. Marston [33] pointed out two fundamental classification dimensions approaching to study cloud computing: i) business issues, and ii) technology issues. However, as this study focuses on the business issues, the issues belonging into the technical perspective will be excluded for keeping the target clear and tight. Therefore, for example issues belonging in the following areas will be excluded from the research: 1. Software product development; 2. Core technologies like virtualization, multitenancy and web services; 3. Software product modulization, product structures and product modules; and 4. Software development methodologies The consumer software, like mobile phone software, are today more or less plat- forms where different vendors are producing their applets. Consumers are paying monthly fee or limited purchase price and at the same time, the software vendor pays a fee to the platform owner. In business software, above mentioned operation model is similar, for example, like SAP has, called SAP EcoHub an online solution partner marketplace. There a single software vendor has a possibility put their software (applet) for purchase by end user. Remarkable is that is only possible for SAP end users who are running it in SaaS format, not on-premise SAP product owners. Other big actors in the field, like Microsoft and Oracle have similar concepts. Of course, for example, SAP is investing huge amounts of resources to go towards SaaS, but it will take several years until the whole on-prem- ise product is rewritten. The headache with smaller software firms differs a lot. They have existing product, existing customer base and no platform. The question how jump into SaaS world, might be a question of dead or life. Roughly, based on author’s over 20 years’ experience of software industry and empirical research, the companies planning to promote a new SaaS product to a market, may be divided into four categories: 1. The first ones have started with something very new without legacy systems head- ache. 2. The second ones have fight with existing customers with their on-premise installa- tions as well as at the same time try to develop modern cloud-based solutions with new functionalities. SiBW 2018 147 3. The third type of company believes that the momentum is not right to convert the business model because of huge existing cash flow. 4. The fourth have not even started to consider the threats of market change. In the remaining of this work, we will take a look how academic literature guides the companies belonging into the first two groups. Fig. 1. Osterwalder and Pigneur's business model canvas [32] 2.2 Business model A business model is an important concept for this study. As it’s seen in the Figure 1 the business model consists of several factors. Later it will be other descriptions of business model like Table 1 and Table 2. Whenever a business transformation is under discus- sion, it will always lead to a new business model. On practical level, for example the following question will raise: The firstly what the new revenue model shall be? Sec- ondly, is there a need for a new kind of partnering? Thirdly, what are the products and services in offered portfolio? Fourthly, what are the key resources, do those already exists or will it be the starting point to find right resources first? Osterwalder and Pigneur's [32] presented a framework for analyzing business model and the changes in business model. Their model is nowadays widely known as the Busi- ness Model Canvas. While Osterwalder and Pigneur’s canvas is not the only one, it is SiBW 2018 148 the most well-known in both academia as well as industrial world. The canvas is pre- sented in Figure 1. In the Business Model Canvas, there are nine factors which all must be analyzed separately and compared to today’s status versus future status. After indi- vidual factor analysis, the results should be crosschecked. Osterwarlder and Pigneur’s model is not the only one. Juntunen [21] have analyzed different authors and their opinion of business model elements. Juntunen’s summariza- tion of the main work on business models is presented in Table 3. It is noteworthy that there are several different works aiming to define the business model and there are different numbers of components from which a business model has been defined from. Furthermore, most of these works have been published in the during a relatively short time period: during 1998–2002. Furthermore, Da Silva et al. [14] has characterized business models and its elements in five categories. The elements, which they identified to belong in a business model logic, are presented in Table 2. Da Silva’s approach differs somewhat from the other approaches, yet there are common elements such as value proposition and earning logic. It is easily possible to see all shown frameworks for business models vary from each other as well all has its own logic. Table 1. Business model elements (adapted from [21]). Authors Business model elements Number of elements Timmers Product/service information flow architecture, business 5 (1998) actors and roles, actor benefits, revenue sources, and marketing strategy Chesbrough & Value proposition, target markets, internal value chain 6 Rosenbaum structure, cost structure and profit model, value net- (2000) work, and competitive strategy Hamel (2001) Core strategy, strategic resources, value network, and 4 customer Interface Amit & Zott Transaction content, transaction structure, and transac- 3 (2001) tion governance Weill & Vitale Strategic objectives, value proposition, revenue sources, 8 (2001) success factors, channels, core competencies, customer segments, and IT infrastructure Rayport & Ja- 4 Value cluster, market space offering, resource system, worski and financial model (2001) Afuah & Tucci Customer value, scope, price revenue, connected activi- 8 (2001) ties, implementation, capabilities, and sustainability Dubosson- 4 Torbay, Products, customer relationship, infrastructure and net- Osterwalder & work of partners, and financial aspects Pigneur (2002) SiBW 2018 149 Table 2. Elements that reflect the business model logic (adapted from [14]). Element Logic Customer value proposition Understanding and creating products and ser- vices that meet customers' needs and help them fulfil their goals. Earning logic Designing a revenue model leading towards a sustainable business. Value network Designing value-added relationships with partners that represent the extended enter- prise of the organization. Resources and capabilities Leveraging and repurposing existing or ac- quiring new resources and capabilities to cre- ate products and services of value to custom- ers and generate consequent revenue. Strategic decisions Decisions aimed at creating a sustainable competitive advantage. Luoma [28] pointed out that the determination which IT company is service firm, which is product firm, may be complex. There might be a product firm whose revenue just 20% are license sales and the rest 80% of revenue are services like designing, im- plementing or operation. The term product or service company is still unclear and requires deeper research. The most important factor may be is there a common model how those companies be- have. Rather often companies have either product or service operations in place. The most of companies have both operations. When investigating the transfer of business model change from on-premise to SaaS it must be sure are people talking about product or service company. For example, if the company A turnover split is:  20% license sales  40% consultancy sales  40% maintenance Compared to company B:  60% license sales  40% services. The operational business structure will vary remarkable depending the level of product / service allocation 3 Results Cloud computing start to be common nowadays. A lot of research work has done to justify what is cloud computing. However, the main target in this research is to review what is known on enterprise software firms and how the business model has changed by moving from on-premise to SaaS business model. SiBW 2018 150 For this study, an unstructured literature review [23] was selected as the method. The justification was that the authors were unaware whether there would be enough primary studies for a full-scale systematic literature review. Therefore, a lightweight unsystem- atic literature review was used to map the current status of the field for further analyses. Based on this unstructured review, a systematic literature review could be implemented later, and the findings of this study can be used as a control group for the review. The unsystematic literature review was performed so that the authors searched pri- mary articles with different keywords and their combinations. The used keywords in- cluded e.g., cloud computing, SaaS, business model, transformation, change. The searches were done with, e.g., Google Scholar, IEEE Xplorer, ACM Portal and Sci- enceDirect publication databases. Articles which were found relevant for this study was selected and read through. If a primary study referred to another primary study, that was not included into, the other primary was acquired and included into the review. We included also other than re- search articles (e.g., reviews in magazines) if they were finding to belong in the target group. The final set of selected articles are [1-10, 12-22, 24-30, 35-36]. By doing unstructured literature analysis, it was found that there are several alterna- tive approaches to narrow the business model in this context. One fact was already now rising: The business model will be the most important factor if the transfer will be suc- cessful or not. In the following, we will review the literature what was found in the unstructured review. For example, Boilat and Legner [3] has done a research of Enterprise software and cloud computing. They summarized existing research in a table (c.f. Table 1). Their findings were noticeable: “From multiple case studies covering traditional and pure cloud providers, we find that moving from on-premise software to cloud services affects all business model components, that is, the customer value proposition, resource base, value configuration, and financial flows” [3]. However, it is worthy to note that their study did not explicitly focus on how to carry out transformation from an on-promise setting to a SaaS solution. Yet, their findings emphasize the importance of business model in understanding the cloud computing paradigm shift in software-intensive busi- nesses. In addition, existing research divides SaaS environments into subclasses. One alter- native for dividing SaaS solutions is based user involvements as Luoma et al [29] have done. They have found three classifications: • Enterprise SaaS • Pure play SaaS • Self-Service SaaS All those three classifications they have analyzed by financial, resource-base and customer-facing elements. Boilat and Legner [3] used the same division and classified business model element according to these (c.f. Table 3). Regarding more general business-oriented research on cloud computing and SaaS, there are many studies. Thus, SaaS has started to be commodity. For example, a widely known model how to analyze different factors in cloud computing is a Cloud Cube Model from the Jericho Forum [20]. It has developed targeting to understand different factors around the cloud operations. Cloud Cube Model is illustrated in Figure 2. SiBW 2018 151 Cloud Cube Model has been further analyzed and developed by Chang [7]. Their specialty was identifying different sorts of business types and strengths and weaknesses of each business types in cloud computing. Chang [7] classified cloud computing busi- ness models and found eight business types: 1. Service Provider and Service Orientation, 2. Support and Service contracts, 3. In-House Private Clouds, 4. All-in-One Enterprise Clouds, 5. One-Stop Resources and Services, 6. Government Funding, 7. Venture Capitals, and 8. Entertainment and Social Networking. Fig. 2. Cloud Cube Model [20] SiBW 2018 152 Table 3. Existing research on enterprise software and cloud computing (adapted from [3]). Authors Focus Customer Vendor perspective Per- spective Benlian et al. SaaS adoption by firms X (2009) Choudhary (20079 Switch from perpetual software (X) X licensing to SaaS and its impact on software quality Ellahi et al. (2011) Cloud deployment models, issues X of moving enterprise applications to the cloud, and the market evolution for enterprise cloud computing Janssen & Joha SaaS doption in public sectors X (2011) (ministries, public agencies, municipalities) Katzan (2009) Cloud computing from a business X X and architecture perspective Khajeh-Hosseini et Research challenges for cloud X X al. (2010) computing from an enterprise or organizational perspective Liao (2010) SaaS business model for X X enterprise software Luoma et al. ASP and SaaS firms’ business X X (2012) models Leimeister et al. Actors, roles, and business X (X) (2010) aspects of cloud Loebbecke et al. Practical case of cloud computing X (2012) assessment Mangiuc (2011) Challenges and risks of moving X applications to the cloud Marston et al. Overview of cloud computing; SWOT X (X) (2010) analysis from a business perspective SiBW 2018 153 Table 4. SaaS solutions classification (adapted from [29]). Element Element Enterprise Pure play SaaS Self-service SaaS group SaaS A mass-cus- tomized but Value Horizontal, stand- A very simple applica- complex appli- proposi- ardized web-native tion that is easy to cation that also tion application adopt requires sup- port services Larger enter- prises and their SMEs, middle Adopted first by end Customer IT managers management and users and individual segments and top execu- end users consumers, then SMEs tives Customer- High-touch, Less human con- facing ele- trust-enchant- tact in deployment Fully automated self- ments Customer ing customer required than tra- service; as little interac- relation- relationships ditionally, owing a tion with the customer ship with tailored simpler applica- as possible contracts tions Outbound and viral Sales channel is marketing used to at- Perform per- push-oriented, and tract customers to the sonal sales and Channels SaaS firms engage vendor’s homepage. employ chan- in inbound, high- Landing page critical in nel partners pressure sales turning prospects into customers. Both domain ex- Possess do- pertise (to include Key re- main expertise best practices into sources and utilize an Close to zero marginal the application) Resource- and activ- ecosystem of costs and application base and ities companies as a development capa- value con- resource bilities figuration User partners elements IT service provid- to deliver Key part- ers for infrastruc- value-adding N/A ners ture and support applications services and services Vendors Use of freemium charge an entry Revenue Small entry fee model, ad-based reve- fee, recurring streams and a recurring fee nues or small recurring fees, and ser- fees vices fees Financial Have varying elements Initial develop- marginal costs, ment costs may be Cost owing to the high, but firms N/A structures long sales cy- aim for minimal cles and re- marginal costs quired support SiBW 2018 154 In a business model transformation, personnel are one of the most critical factors. In computing world and all high-tech industry, there is huge lack of competent people [39]. A business model change to adopt into the requirements of a modern business world is necessary for a company, eventually. At least in Scandinavian, software-inten- sive firms are not able to change all resources and at same time and start a new product development project with fresh resources. Personnel is a big part of success. Thus far, only Sultan [36] addressed organizational culture in a cloud computing setting. Yet, their focus is on the organizations and their culture, not guiding how to manage trans- formation as a software-intensive firm. Transformation from on-premise to SaaS moves the business logic from product business to service business. Cusumano’s recent work [12, 13] covers that area; how- ever, he does not give practical guidelines for companies, but instead focus on market- level discussion. Da Silva [14] has analyzed the impact of disruptive technologies to business model comparing Siebel and Sales Force as well as Amazon and Sales Force. It is worthy to note that those companies are huge compared to target firms in this po- sition paper. Finally, Juntunen [21] has looked the transformation issue by using dynamic capa- bility view and Chesbourgh [9] is more concentrating on innovations in business model. Marston [30] has a business perspective approach for the subject. However, also these studies do not focus on giving practical guidelines for a software-intensive firm. 4 Discussion The aim of this position paper was to review the current knowledge of academic liter- ature on guiding small and medium-sized software-intensive businesses for transform- ing their business model from on-premise products to SaaS solutions. In the unstruc- tured literature research, it was found that there are several investigations and research results comparing companies, their status in cloud development and their product port- folios. Mainly the studies in the extant literature have been focused huge companies like Oracle and SAP. However, there seems to be lack of research to comparing companies how they have done the technology and business model transformation from on-premise to SaaS busi- ness. Specifically, there is a lack of studies how smaller firms have achieved the goal. While it is possible that there is such research available; however, there are lack of understanding to support the companies in this kind of transformation and this requires do more detailed research. Thus, this position paper requires further research concentrating on small and midsize software companies, who are on their way to transfer their on-premise product range to SaaS software. The main goal of this kind of research should be to answer to the following questions:  How software-intensive firms have handled the transformation and what has been the lessons learned?  What are the required steps in transformation?  What has been the critical factors in business model transformation? SiBW 2018 155  What guidelines could research give to companies that are planning of transforming their product offering and business model?  How a software-intensive business can satisfy simultaneously both its current cus- tomer base, with on-premise installations, as well as the new customers, with wishes for new functionalities in a SaaS solution? Based on the unstructured literature analysis there are few main limitations that should be acknowledged in the research. Firstly, what is the impact of product / service allocation in business model and business model transformation for a software-inten- sive business? Secondly, what is the impact of company size for this kind of a transfor- mation? Thirdly, what is the impact of life cycle status, is the company well established or a start up, to the transformation? The continuation of this literature research will be to find out candidate companies and then for example, analyze their cloud computing business models and do the clas- sification like Chang [7]. 5 Conclusion This study focused on searching what the extant knowledge reports on transforming a business model of a software-intensive business from an on-premise product to a SaaS solution. Considering the researched material, there were several studies reporting dif- ferences caused by an adaptation of a cloud computing-bases business model. However, most of the review work focused on large-sized companies, which have resources to manage the transformation. On the contrary, there are not much reported on small and medium-sized companies. Limitations of the paper are lacking systematic literature review and other method- ology. Ecosystems business model should need more attention timely and rigour aca- demic literature. With the studied reference literature, this study has shown that there is a need to research how to support a small or midsize enterprise software company, which is plan- ning to change the business model from on-premise to a SaaS business model. References 1. Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., Lee, G., Patter- son, D., Rabkin, A., Stoica, I. O. N., & Zaharia, M. (2010). A View of Cloud Computing. Communications of the ACM, 53, 50-58. 2. Bensinger, G. (2012). Competing With Amazon on Amazon. Wall Street Journal. Retrieved from http://online.wsj.com/arti- cle/SB10001424052702304441404577482902055882264.html 3. Boillat, T., Legner. C. From On-Premise Software to Cloud Services: The Impact of Cloud Computing on Enterprise Software Vendors' Business Models 4. Boulton, C. (2012). Oracle Customers Rankled by Product Roadmap. WSJ Blogs - The CIO Report. Retrieved from http://blogs.wsj.com/cio/2012/04/02/oracle-customers-growing-an- grier/ SiBW 2018 156 5. Braganza, A., Awazu, Y., & Desouza, K. C. (2009). Sustaining innovation is challenge for incumbents. Research-Technology Management, 52(4), 46–56. 6. Casadesus-Masanell, R., & Ricart, J. E. (2011). How to design a winning business model. Harvard Business Review, 89(1/2), 100–107. 7. Ghang,V, Bacialupo,D, Wills, G. De Roure, D. A Categorisation of Cloud Computing Busi- ness Models 8. Chesbrough, H. Business Model Innovation: It's not just about Technology Anymore, Strat- egy & Leadership, vol. 35, no. 6, pp. 12-17, 2007. 9. Chesbrough, Henry. (2010). Business Model Innovation: Opportunities and Barriers. Long Range Planning, 43(2–3), 354–363. doi:10.1016/j.lrp.2009.07.010 10. Choudhary, V. Software as a Service: Implications for Investment in Software Development, in Proceedings of the 40th Annual Hawaii International Conference on System Sciences, Waikoloa, 2007, pp. 209a 11. Christensen, C. M. (1997). The innovator’s dilemma: when new technologies cause great firms to fail. Harvard Business Press. 12. Cusumano, M. The Changing Software Business: Moving from Products to Services, Com- puter, vol. 41, no. 1, pp. 20-27, 2008. 13. Cusumano, M. (2010). Cloud computing and SaaS as new computing platforms. Communi- cations of the ACM, 53(4), 27–29. 14. DaSilva, C.M., Trkman, P., Desouza, K., Lindič, J. Disruptive Technologies: A Business Model Perspective on Cloud Computing Technology Analysis & Strategic Management, 2013 15. A. Dubey, D. Wagle, Delivering software as a service, The McKinsey Quarterly (May 2007) 1–12. 16. Ellahi, T., Hudzia, B., Li, H., Lindner, M.A., Robinson, P. The Enterprise Cloud Computing Paradigm. USA: John Wiley and Sons, 2011. 17. Gartner. (2012, November) Gartner: Top 10 Key Technology Trends for 2013. CloudTimes. [Online]. Available:http://cloudtimes.org/2012/11/06/gartner-top-10-key-technology- trends-for-2013/. 18. Hugos, M. H., & Hulitzky, D. (2010). Business in the Cloud: What Every Business Needs to Know About Cloud Computing (1st ed.). Wiley. 19. Irwin, S. (2012). Enterprise 2.0: Freemium first, enterprise second (Part 1 of 3). GigaOM. Retrieved October 30, 2012, from http://gigaom.com/2012/04/28/enterprise-2-0-freemium- first-enterprise-second-part-1-of-3/ 20. Jerico Forum “Cloud Cube Model: Selecting Cloud Formations for Secure Collaboration Version 1.0”, Jerico Forum Specification, April 2009 21. Juntunen, M., Business model change as a dynamic capability. Doctoral thesis. University of Oulu 2017 22. Kim, W. C., & Mauborgne, R. (2005). Blue Ocean Strategy: How to Create Un-contested Market Space and Make Competition Irrelevant (1st ed.). Boston: Harvard Business Press. 23. Kitchenham,B., Charters,S., (2007): Guidelines for Performing Systematic Literature Re- views in Software Engineering. Version 2.3, Technical Report, Software Engineering Group, Keele University and Department of Computer Science, University of Durham. 24. Leimeister, S., Riedl, C., Bõhm, M., Krcmar, H. The Business Perspective of Cloud Com- puting: Actors, Roles, and Value Networks in Proceedings of the Eu-ropean Conference on Information Systems 2010, Pretoria, 2010. 25. Lin, A., & Chen, N.-C. (2012). Cloud computing as an innovation: Percepetion, attitude, and adoption. International Journal of Information Management, (0). doi:10.1016/j.ijinfo- mgt.2012.04.001 SiBW 2018 157 26. Low, C., Chen, Y., & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management & Data Systems, 111(7), 1006–1023. 27. Luoma, E., Rönkkö, M., Tyrväinen, P. Current Software-as-a-Service Business Models: Ev- idence from Finland, Software Business, vol. 114, no. 2, pp. 181-194, 2012. 28. Luoma, E., Examining Business Models of Software-as-a-Service Companies. Doctoral Thesis University of Jyväskylä 2013. 29. Mahowald, R.P., Konary, A., & Sullivan C.G. (2011). Market Analysis Perspective: World- wide Saas & Cloud Services, 2011: New Models for Delivering Software. http://www.idc.com/getdoc.jsp?containerId=232239. 30. Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2010). Cloud computing- The business perspective. Decision Support Systems. 31. Mayer, M. K. Future trends in model management systems: parallel and distrib-uted exten- sions, Decision Support Systems 22 (4) (1998) 325–335. 32. Osterwalder, A., Pigneur, Y. Business Model Generation: A Handbook for Vision-aries, Game Changers, and Challengers. New Jersey: Wiley, 2010. 33. Rahikkala, J., Hyrynsalmi, S., Leppänen, V., Porres, I. The Role of Organisational Phenom- ena in Software Cost Estimation: A Case Study of Supporting and Hindering Factors. E- Informatica Software Engineering Journal, Volume 12, 2018, pages 167-198, DOI 10.5277/e-Inf180101 34. Robinson, D. K. R., Le Masson, P., & Weil, B. (2012). Waiting games: innovation impasses in situations of high uncertainty. Technology Analysis & Strategic Management, 24(6), 543– 547. doi:10.1080/09537325.2012.693661 35. Rymer, J. R., Staten, J., Wang, C. (2012, May) Achieve Cloud Economics for Op-erations and Services, Forrester Research. [Online]. Available: http://www.for- rester.com/Achieve+Cloud+Economics+For+Operations+And+Services/fulltext/-/E- RES61602. 36. Sultan, N., & van de Bunt-Kokhuis, S. (2012). Organisational culture and cloud computing: coping with a disruptive innovation. Technology Analysis & Strategic Management, 24(2), 167–179. doi:10.1080/09537325.2012.647644 37. Mell, P. & Grance, T. (2013) The NIST Definition of Cloud Computing. NIST Special Pub- lication 800-145. National Institute of Standards and Technology. U.S. Department of Com- merce. 38. Buxmann, P., Diefenbach, H. & Hess, T. (2013) The Software Industry: Economic Princi- ples, Strategies, Perspectives. Springer: Berlin. 39. Hyrynsalmi, S.M., Rantanen, M.M, & Hyrynsalmi, S. (2018) Do we have what is needed to change everything? HCC13 2018. IFIP Advances in Information and Communication Tech- nology, vol 537. pp. 111-122. Springer, Cham.