KEY DECISION-MAKING FACTORS FOR ADOPTION OF SAAS IN SMES IN RUSSIA
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INTRODUCTION 7
1. THEORETICAL BACKGROUND 13
1.1. Extant knowledge and research findings 13
1.2. Review of relevant models, frameworks, and research approaches 16
1.3. Identification of research gap for empirical study 28
1.4. Summary of the chapter 29
2. METHODOLOGY AND DATA DESCRIPTION 31
2.1. Scope of research for empirical study 32
2.2. Research hypotheses 34
2.3. Research framework 35
2.4. Description of research methodology 36
2.5. Summary of the chapter 38
3. EMPIRICAL STUDY 39
3.1. Data collection and description of material 40
3.2. Factor analysis 43
3.3. Structural Equation Modelling 48
3.4. Analysis of results 50
3.5. Practical implications and contribution 55
3.6. Research limitations and suggestions for further analysis 55
3.7. Summary of the chapter 57
CONCLUSION 58
LIST OF REFERENCES 61
SUPPLEMENTARY MATERIAL 68
Appendix
1. THEORETICAL BACKGROUND 13
1.1. Extant knowledge and research findings 13
1.2. Review of relevant models, frameworks, and research approaches 16
1.3. Identification of research gap for empirical study 28
1.4. Summary of the chapter 29
2. METHODOLOGY AND DATA DESCRIPTION 31
2.1. Scope of research for empirical study 32
2.2. Research hypotheses 34
2.3. Research framework 35
2.4. Description of research methodology 36
2.5. Summary of the chapter 38
3. EMPIRICAL STUDY 39
3.1. Data collection and description of material 40
3.2. Factor analysis 43
3.3. Structural Equation Modelling 48
3.4. Analysis of results 50
3.5. Practical implications and contribution 55
3.6. Research limitations and suggestions for further analysis 55
3.7. Summary of the chapter 57
CONCLUSION 58
LIST OF REFERENCES 61
SUPPLEMENTARY MATERIAL 68
Appendix
Nowadays, cloud computing solutions are still globally regarded as prospective, as the market is growing rapidly. According to Gartner, the global market of public cloud services was on its way to grow by 17,2% in 2016, from $178 billion to $208,6 billion (Stamford, 2016).
As a model, cloud services have a lot of clear advantages for adopting companies. For instance, they require minimum specific knowledge from users (Safari, Safari, and Hasanzadeh, 2014; Wu, Wan, and Lee, 2011), allow for an access from multiple devices via the web (Bayrak, 2013; Johansson, Ruivo, 2013; Sebesta, 2013) and might offer latest versions of IT-infrastructure components and functionality (Sebesta, 2013; Wu, Wan, and Lee, 2011). What is more, they are often associated with various cost savings (Safari, Safari, and Hasanzadeh, 2014; Sultan, 2011)
The cloud services market in Russia is considered overall as developed. Major segments of the market are SaaS (software as a service - provision enterprise applications via Internet), data storage (provision of cloud storage accessible via Internet) and IaaS (infrastructure as a service - provision of computational resources via Internet) (CNews Analytics, 2016).
Another commonly mentioned segment - PaaS (platform-as-a-service - provision of platforms to deploy own applications on top of them via Internet) (Safari, Safari, and Hasanzadeh, 2014) is also present in the portfolios of services of largest Russian market players as an independent service (IT-GRAD, Softline), but more often considered as a part of IaaS (ActiveCloud, Cloud4Y, DataLine, I-Teco, KROK) (CNews Analytics, 2016). Peculiarities of services within particular segments would be described further in the introductory chapter.
In SaaS, which will be further the focus segment of the study, largest market players by annual revenue in 2016 are concentrated in two locations - Moscow and Saint-Petersburg, two large players also located in Ekaterinburg and Kazan (CNews Analytics, 2016).
Despite the maturity of the cloud services market, service proposition tools are limited to web-pages, where customers can specify particular service used and its parameters, such as a number of licenses or a payment scheme, and then contact sales representatives of a vendor (CNews Analytics, 2016).
The issue of the absence of decision-making support tools outlined above is particularly relevant for small and medium businesses (SMEs) as they are considered to be the major client segment for cloud solution providers due to a lack of resources to create own IT-infrastructure, a necessity to frequently and drastically change its scale, and a low level of expertise of decision makers.
At the same time, SMEs need to make decisions and often conduct their own analysis. Odin in their SMB Cloud Insights Russia 2015 research (Odin, 2016) interviewed more than 400 IT decision makers in order to find out the latest trends in the perception of SaaS, as well as currently most common pluses and minuses. The research indicates, that on average, about half of SMEs prefer to hold own study (58% of microenterprises, 41% of small enterprises, 35% of medium enterprises) or rely upon a trusted advisor (26% of microenterprises, 41% of small enterprises, 35% of medium enterprises) in order to choose business application solutions (Odin, 2016).
In summary, these arguments stipulate for a need of universal, simpler to understand and implement mechanisms and instruments of decision-making.
As a model, cloud services have a lot of clear advantages for adopting companies. For instance, they require minimum specific knowledge from users (Safari, Safari, and Hasanzadeh, 2014; Wu, Wan, and Lee, 2011), allow for an access from multiple devices via the web (Bayrak, 2013; Johansson, Ruivo, 2013; Sebesta, 2013) and might offer latest versions of IT-infrastructure components and functionality (Sebesta, 2013; Wu, Wan, and Lee, 2011). What is more, they are often associated with various cost savings (Safari, Safari, and Hasanzadeh, 2014; Sultan, 2011)
The cloud services market in Russia is considered overall as developed. Major segments of the market are SaaS (software as a service - provision enterprise applications via Internet), data storage (provision of cloud storage accessible via Internet) and IaaS (infrastructure as a service - provision of computational resources via Internet) (CNews Analytics, 2016).
Another commonly mentioned segment - PaaS (platform-as-a-service - provision of platforms to deploy own applications on top of them via Internet) (Safari, Safari, and Hasanzadeh, 2014) is also present in the portfolios of services of largest Russian market players as an independent service (IT-GRAD, Softline), but more often considered as a part of IaaS (ActiveCloud, Cloud4Y, DataLine, I-Teco, KROK) (CNews Analytics, 2016). Peculiarities of services within particular segments would be described further in the introductory chapter.
In SaaS, which will be further the focus segment of the study, largest market players by annual revenue in 2016 are concentrated in two locations - Moscow and Saint-Petersburg, two large players also located in Ekaterinburg and Kazan (CNews Analytics, 2016).
Despite the maturity of the cloud services market, service proposition tools are limited to web-pages, where customers can specify particular service used and its parameters, such as a number of licenses or a payment scheme, and then contact sales representatives of a vendor (CNews Analytics, 2016).
The issue of the absence of decision-making support tools outlined above is particularly relevant for small and medium businesses (SMEs) as they are considered to be the major client segment for cloud solution providers due to a lack of resources to create own IT-infrastructure, a necessity to frequently and drastically change its scale, and a low level of expertise of decision makers.
At the same time, SMEs need to make decisions and often conduct their own analysis. Odin in their SMB Cloud Insights Russia 2015 research (Odin, 2016) interviewed more than 400 IT decision makers in order to find out the latest trends in the perception of SaaS, as well as currently most common pluses and minuses. The research indicates, that on average, about half of SMEs prefer to hold own study (58% of microenterprises, 41% of small enterprises, 35% of medium enterprises) or rely upon a trusted advisor (26% of microenterprises, 41% of small enterprises, 35% of medium enterprises) in order to choose business application solutions (Odin, 2016).
In summary, these arguments stipulate for a need of universal, simpler to understand and implement mechanisms and instruments of decision-making.
The current study is devoted to the research and the analysis of factors, that are related to making decisions about adoption of SaaS solutions in Russian SMEs. Cloud solutions in general are perceived as a useful tool, which may lead to raise of performance of their adopters. They have a lot of advantages for adopting companies, such as ease of use and deployment, sharing and collaboration of data and beneficial payment schemes.
There are as well some controversial factors, that may in different situations result in adoption of cloud computing solutions or make a company to refuse of such an idea. Namely, these are costs associated with solutions, (which in practice of Russian IT companies often aggregated in total cost of ownership), reliability (linked with level of information security and technical support according to service level agreements), and degree of standardization.
The Russian cloud services market exists for more than ten years, but is still considered as developing, showing higher pace of growth than average worldwide. The SaaS is currently a second and most promising segment of the market, with few major players located in Moscow and Saint-Petersburg. Among clients SMEs represent majority by revenue of SaaS vendors, but on average, single SME tends to use only limited amount of basic services. Industry experts explain such a situation with an insufficient IT budget and a lack of the expertise for making rational decisions about the adoption of the SaaS based on actual business needs.
Therefore, this study intends to outline factors, which are important for determining the business need in the adoption of the SaaS. Factors are taken from extant theoretical studies of the decision-making processes of the adoption of IT solutions among various types of companies worldwide, as well as from recent analytical reports and interviews with industry experts in Russia. In addition to this, a broader theoretical background was observed, including key research questions and topics in the area, research subjects, different possible scopes, research models and frameworks, data collection and data analysis methodologies.
In the research area, most of studies are intended to outline factors, attributed to IT- solution, or related to it, which are taken into account by companies, when they make the decision about the adoption of solutions. These factors in general attribute to one or several of the following characteristics: perceived by SMEs as substantially important, making IT-solution objectively fit to needs of SMEs or outlined by expert opinion as essential.
Alongside with the influence of factors on the adoption decision, it was discovered that extant studies focus on their interrelation, which, supported by evidence from industry reviews, resulted into a development of present research question, that is related to the influence of business need (as one factor resulting into adoption) by other factors - previous experience, features and capabilities, reliability, and costs. These factors are claimed as important for Russian SMEs when it comes to the adoption of SaaS solutions.
Several related research questions that contributed to the development of the research were also identified: which frameworks can SMEs employ when they choose cloud services to adopt, how usage of cloud services affect different aspects of performance of SMEs, which SMEs are most likely to adopt cloud services, what should cloud service providers do with their product and proposition in order to attract SMEs.
Therefore, the study analyzes interdependencies between factors and aims at providing both vendors and decision makers in Russian SMEs with a framework of their evaluations and related recommendations. The research framework is based on most relevant studies, which were taken as “benchmarks”. It is focused on determining the strength and the direction of the influence of positive the previous experience from usage SaaS, its features and capabilities, its level of reliability and the cost of ownership on the recognition of the business need in the adoption by Russian SMEs, who are currently using solutions of major Russian SaaS providers.
Factors within the research framework are represented as latent constructs and measured by observable variables in forms of 5-point Likert-scale questions in the survey. In order to obtain results for the survey major Russian cloud services providers were contacted, who then provided opportunity to distribute the questionnaire among their respective clients either by e-mail, by phone or in personal interviews.
In order to justify the measurement of latent constructs with observable variables, factor analysis was performed in IBM SPSS Statistics, with an estimation of validating indicators. As a result, observable variables were valid to represent independent variables of the research model. Variables that are related to the dependent variable (business need) have demonstrated a higher attribution to the positive previous experience and the reliability respectively, which was explained by the implied influence of independent variables on dependent and it was decided to proceed with the structural equation model.
SEM was developed in IBM SPSS AMOS, the model was also adjusted for better overall fit, validity, and reliability of measurements. Changes in the model are justified by relationships between model variables.
Hypothesis testing was performed after adjusting the model.
As a result:
• hypothesis H1 (business need in adoption of cloud solution by SME is positively affected by positive previous experience) is confirmed;
• hypothesis H2 (business need in adoption of cloud solution by SME is positively affected by its actual features and capabilities) is not confirmed;
• hypothesis H3 (business need in adoption of cloud solution by SME is positively affected by its reliability) is confirmed;
• hypothesis H4 (business need in adoption of cloud solution by SME is negatively affected by its total cost of ownership) is confirmed.
While similar findings exist in extant studies for confirmed hypotheses, it cannot be said that for the non-confirmed hypothesis, there are relevant results in other research. Thus, it is suggested as a proposition of further research to conduct a study on how features and capabilities of SaaS are related to recognition of business need in its adoption by Russian SMEs.
In addition to the results of hypothesis testing, the analysis of predictive strengths in IBM Watson Analytics has demonstrated a set of results. Namely, the efficiency of business processes is moderately correlated with the positive previous experience, especially from the same SaaS usage; other components of the business need are slightly correlated with observables.
Furthermore, the number of security incidents, related to a SaaS solution demonstrates no predictive strength for the business need; the level of data protection and the speed of response on service requests and incidents, has demonstrated a moderate predictive strength for the business need; the level of accessibility demonstrates highest strength for all components of the business need;
In addition, components of the business need, that are related to the level of efficiency of business processes and the level of competitiveness slightly correlated with the cost of purchasing licenses and moderately with the cost of the deployment of the SaaS solution; the cost-saving component of the business need is highly correlated with all TCO components.
Overall, this study contributes to the extension of the research area in terms of geography, and interrelations in hypothesis studied. It has also provided another example of applicability of SEM. Practitioners can benefit from the list of potential factors of influence and methodology of their evaluation. Propositions for further research include suggestions to study of between-group differences for SMEs and of mediating variables, such as size, region, and domain of business activities.
There are as well some controversial factors, that may in different situations result in adoption of cloud computing solutions or make a company to refuse of such an idea. Namely, these are costs associated with solutions, (which in practice of Russian IT companies often aggregated in total cost of ownership), reliability (linked with level of information security and technical support according to service level agreements), and degree of standardization.
The Russian cloud services market exists for more than ten years, but is still considered as developing, showing higher pace of growth than average worldwide. The SaaS is currently a second and most promising segment of the market, with few major players located in Moscow and Saint-Petersburg. Among clients SMEs represent majority by revenue of SaaS vendors, but on average, single SME tends to use only limited amount of basic services. Industry experts explain such a situation with an insufficient IT budget and a lack of the expertise for making rational decisions about the adoption of the SaaS based on actual business needs.
Therefore, this study intends to outline factors, which are important for determining the business need in the adoption of the SaaS. Factors are taken from extant theoretical studies of the decision-making processes of the adoption of IT solutions among various types of companies worldwide, as well as from recent analytical reports and interviews with industry experts in Russia. In addition to this, a broader theoretical background was observed, including key research questions and topics in the area, research subjects, different possible scopes, research models and frameworks, data collection and data analysis methodologies.
In the research area, most of studies are intended to outline factors, attributed to IT- solution, or related to it, which are taken into account by companies, when they make the decision about the adoption of solutions. These factors in general attribute to one or several of the following characteristics: perceived by SMEs as substantially important, making IT-solution objectively fit to needs of SMEs or outlined by expert opinion as essential.
Alongside with the influence of factors on the adoption decision, it was discovered that extant studies focus on their interrelation, which, supported by evidence from industry reviews, resulted into a development of present research question, that is related to the influence of business need (as one factor resulting into adoption) by other factors - previous experience, features and capabilities, reliability, and costs. These factors are claimed as important for Russian SMEs when it comes to the adoption of SaaS solutions.
Several related research questions that contributed to the development of the research were also identified: which frameworks can SMEs employ when they choose cloud services to adopt, how usage of cloud services affect different aspects of performance of SMEs, which SMEs are most likely to adopt cloud services, what should cloud service providers do with their product and proposition in order to attract SMEs.
Therefore, the study analyzes interdependencies between factors and aims at providing both vendors and decision makers in Russian SMEs with a framework of their evaluations and related recommendations. The research framework is based on most relevant studies, which were taken as “benchmarks”. It is focused on determining the strength and the direction of the influence of positive the previous experience from usage SaaS, its features and capabilities, its level of reliability and the cost of ownership on the recognition of the business need in the adoption by Russian SMEs, who are currently using solutions of major Russian SaaS providers.
Factors within the research framework are represented as latent constructs and measured by observable variables in forms of 5-point Likert-scale questions in the survey. In order to obtain results for the survey major Russian cloud services providers were contacted, who then provided opportunity to distribute the questionnaire among their respective clients either by e-mail, by phone or in personal interviews.
In order to justify the measurement of latent constructs with observable variables, factor analysis was performed in IBM SPSS Statistics, with an estimation of validating indicators. As a result, observable variables were valid to represent independent variables of the research model. Variables that are related to the dependent variable (business need) have demonstrated a higher attribution to the positive previous experience and the reliability respectively, which was explained by the implied influence of independent variables on dependent and it was decided to proceed with the structural equation model.
SEM was developed in IBM SPSS AMOS, the model was also adjusted for better overall fit, validity, and reliability of measurements. Changes in the model are justified by relationships between model variables.
Hypothesis testing was performed after adjusting the model.
As a result:
• hypothesis H1 (business need in adoption of cloud solution by SME is positively affected by positive previous experience) is confirmed;
• hypothesis H2 (business need in adoption of cloud solution by SME is positively affected by its actual features and capabilities) is not confirmed;
• hypothesis H3 (business need in adoption of cloud solution by SME is positively affected by its reliability) is confirmed;
• hypothesis H4 (business need in adoption of cloud solution by SME is negatively affected by its total cost of ownership) is confirmed.
While similar findings exist in extant studies for confirmed hypotheses, it cannot be said that for the non-confirmed hypothesis, there are relevant results in other research. Thus, it is suggested as a proposition of further research to conduct a study on how features and capabilities of SaaS are related to recognition of business need in its adoption by Russian SMEs.
In addition to the results of hypothesis testing, the analysis of predictive strengths in IBM Watson Analytics has demonstrated a set of results. Namely, the efficiency of business processes is moderately correlated with the positive previous experience, especially from the same SaaS usage; other components of the business need are slightly correlated with observables.
Furthermore, the number of security incidents, related to a SaaS solution demonstrates no predictive strength for the business need; the level of data protection and the speed of response on service requests and incidents, has demonstrated a moderate predictive strength for the business need; the level of accessibility demonstrates highest strength for all components of the business need;
In addition, components of the business need, that are related to the level of efficiency of business processes and the level of competitiveness slightly correlated with the cost of purchasing licenses and moderately with the cost of the deployment of the SaaS solution; the cost-saving component of the business need is highly correlated with all TCO components.
Overall, this study contributes to the extension of the research area in terms of geography, and interrelations in hypothesis studied. It has also provided another example of applicability of SEM. Practitioners can benefit from the list of potential factors of influence and methodology of their evaluation. Propositions for further research include suggestions to study of between-group differences for SMEs and of mediating variables, such as size, region, and domain of business activities.