Diese Präsentation wurde erfolgreich gemeldet.
Wir verwenden Ihre LinkedIn Profilangaben und Informationen zu Ihren Aktivitäten, um Anzeigen zu personalisieren und Ihnen relevantere Inhalte anzuzeigen. Sie können Ihre Anzeigeneinstellungen jederzeit ändern.
ADOPTION OF CLOUD-BASED SERVICES BY SMEs
IN DEVELOPING COUNTRIES: DEVELOPMENT OF A
T-O-E BASED MODEL
AMOS WACHANGA WAMBUGU
IT is integral to modern business
…. amongst other key business tasks
(Davenport, 2013; Ong et al, 2016; Tarutėa & Gatauti...
Small & Medium Enterprises
• SMEs play a significant role in the economy,
• but they have limited possibilities while
comp...
Research shows that there is low adoption of IT by
SMEs in developing economies such as Kenya
(KNBS, 2016; Agboh, 2015) Wh...
Challenges of traditional IT environments
• the upfront setup costs and
• the increasingly complex
management issue of
• s...
“a model for enabling very convenient, on-demand
network access to a shared pool of configurable
computing resources
such ...
Reduced costs & Affordability
Setup time and effort
Simplicity
Scalability & Maintainability
Convenience and improved acce...
SMEs could find cloud computing to be an
attractive solution
(Aljabre, 2012; Hassan et al, 2017)
Cloud-based services have...
Cloud Computing Characteristics
Five essential characteristics
that need to exist in an IT
environment for it to be
consid...
Cloud Computing Service Delivery Models
Cloud computing Illustration.
Adapted from (Oguntala, Abd-Alhameed, & Odeyemi, 201...
Cloud Computing Deployment Models
Simplified Overview of Cloud Deployment Models.
Adapted from (Oguntala, Abd-Alhameed, & ...
Cloud Computing Pricing Models
• Per user model especially for Software as a Service solutions or
• Based on usage of comp...
Concerns on Cloud Computing
Information Security &
Privacy
Data residency and
legal jurisdiction
Regulatory compliance Ven...
SMEs Adoption from Literature
Developed Developing Kenya
92% of enterprises made use of
ICTs over the internet
(Eurostat, ...
Adoption by SMEs in Kenya
• Main benefits indicated for adoption of cloud computing were
flexibility, cost savings, better...
Problem Statement
1. SMEs generally are constrained on budgets
2. Most SMEs then resolve to manual processes …….
3. Use of...
Considerations for such a model
• Many factors should be considered which include the Internal and
external environment th...
Theoretical frameworks on Adoption
Theory Level of Analysis Author
Technological Acceptance Model (TAM) Individual Davis (...
Technology-Organization-Environment (TOE) Framework,
helps to analyze adoption of technological innovations
by firms and o...
Objective of the Study
The main objective of this study is:
To understand the adoption of cloud-based services by SMEs
wit...
Methodology
• Research Design - Design Science category of research
• Population and Sampling Design - Convenience samplin...
Research Approach
Literature Review
Initial Model
(based on Theory)
Data Collection
Instruments
Development
Pilot Study
Re...
Tools & Techniques
• Data analysis was done through IBM SPSS Statistics version 23 and
IBM SPSS Amos version 21
• Statisti...
Methodology
• Reliability was tested using Internal Consistency (consistency of data
across responses) because Likert’s sc...
TOE Framework
Source: DePietro et al. (1990)
Adaptation of TOE for Cloud Computing Adoption
Adaptation of TOE for cloud computing Adoption by SMEs
Factors influencing adoption by SMEs
Key Factors Influencing Adoption of ICT and Cloud Computing Illustrative Reference
Ma...
Development of the Questionnaire
Section Number of Questions Questions Adapted From
A: General Information Personal inform...
Responses Received
Total Received Invalid Responses Valid Responses**
50 responses 3 from Government
2 from NGOs
45 respon...
Demographics of Respondents
• Role
• Owner/Management category at 40% (n=18)
• Employees at 29% (n=13)
• IT Personnel at 2...
Demographics of Respondents
• There was an almost evenly
distributed representation of
organizations in relation to
the nu...
Correlation between having qualification in ICT and
Knowledge of cloud-based services
Do you have any
qualification in ICT...
Correlation between ICT Complexity and ICT
Qualification
ICT is complicated, it’s
difficult to understand
what’s going on
...
Reliable with Cronbach alpha of 0.903
No multicollinearity issue was found
(Cohen et al, 2003)
Automated Services in comparison to Cloud Deployed Services
Service
Automated Services Cloud Deployed Services
Frequency (...
Number of offices by amount paid for cloud computing
Satisfaction level by amount spent on cloud computing
Distribution of satisfaction levels based on amount
spent on cloud-based services
Positive significant (r=0.385; p<0.05) r...
Source of Cloud-Based Services Information
Exploratory Factor Analysis
Component
Technology
Relative
Advantage
Environment
Vendor
Readiness
Organization
Readiness and
Size
1 2 3
T_RA_Easier - U...
Rotated Component Matrixa
Component
Environment
Regulations
Environment
Trading
Partner
Pressure
Technology
Accessibility
...
Validity of the Model
Measurement Indices Model Value Recommended Value *
Chi-Square(χ2)/Degree of freedom(DF) 1.243 ≤ 3.0...
Convergent validity tests
CR AVE MSV
Trading Partner Pressure 0.806 0.676 0.153
Relative Advantage 0.841 0.524 0.166
Vendo...
Discriminant Validity
Trading
Partner
Pressure
Relative
Advantage
Vendor
Readiness
Readiness and
Size Regulations Accessib...
Validity of the Model through Expert Reviews
• SME owner highlighted a key strength was that the model was not
looking at ...
Objective 1: Current Adoption Levels of Cloud-Based Services
• ICT was widely available, there was still low use of ICT fo...
[Revisiting] Model based on Literature Review
Adaptation of TOE for cloud computing Adoption by SMEs
Objective 2: Final TOE based model
Objective 3: Validation of the model
• Statistical analysis of the data showed a largely reasonable level of fit
for the i...
Conclusions
• Based on the exploratory nature and the small sample size in
this study, I’m not suggesting the findings to ...
SMEs can make use of the model proposed
Cloud providers, schools and other interested parties
should invest in dissemination of information on cloud
computing
Cloud service providers should invest in business
applications that offer both free & premium services to
cater for smalle...
Governments and policy makers can also make use of
the model to determine the best environment for
enabling SMEs to adopt ...
This research contributes to knowledge of ICT adoption
& cloud computing
Limitations, Recommendations and Future Directions
Limitation Recommendations and Future Directions
Constraints on time an...
Publications
• Refereed Conference Paper
• Wambugu, Amos Wachanga and Ndiege, Joshua Rumo (2018).
Harnessing cloud computi...
Amos Wachanga Wambugu
wachanga@sibasi.com
ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL
ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL
ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL
ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL
ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL
ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL
ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL
Nächste SlideShare
Wird geladen in …5
×

ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL

322 Aufrufe

Veröffentlicht am

Small and Medium Enterprises (SMEs) face numerous challenges in identification, setting up
and making use of Information Technology (IT) as an enabler for business. Cloud computing
could solve this problem by offering ready, low cost of entry IT solutions. Adoption of cloud
computing among the SMEs in developing countries is however low due to a number of
barriers as identified by previous studies. Over the years, research on adoption on innovation
and technology has unveiled a number of theories on adoption which range from Individual
level theories to Organizational level theories and even Market level theories. This study
reviews the various theories, opting to use an organization level theory so that focus on the
SME is emphasized. Analysis of literature renders this study to be based on the Technology-
Organization-Environment (TOE) framework proposed by DePietro et al. (1990). This study
reviews the current adoption levels of cloud computing and proposes a TOE based model for
adoption of cloud-based services by SMEs in developing countries. The study employed
literature review to determine the factors that are applicable for a model on adoption of cloud
computing in the developing countries. Further, the study conducted a survey through a
questionnaire to collect quantitative data to assist in determination of the most applicable
model. Convenience sampling was employed due to the study’s constraints on time and budget.
The study findings revealed that there is low adoption of cloud computing for business
applications by SMEs in Nairobi County, hence confirms the need for the adoption model.
Using Exploratory Factor Analysis (EFA) six components were extracted for the proposed
model which include Relative Advantage, Accessibility, Organization Readiness and Size,
Vendor Readiness, Regulations and Trading Partner Pressure, each with attributes required to
ensure successful adoption of cloud computing. The model was validated through statistical
analysis which confirms a largely reasonable level of fit for the indices and construct validity
conducted through convergent and discriminant validity methods. Further, the model was
subjected to experts’ analysis who concluded that the model is simple, applicable and fitting.
The study finally proposes practical recommendations to governments and policy makers,
educational institutions, software vendors and SMEs based on the model. Further research
areas include subjecting the model to larger sample sizes to confirm its validity and the
preparation of an implementation guideline.

Keywords: Cloud computing, Small and medium enterprises, ICT Adoption, Nairobi Kenya

Veröffentlicht in: Kleinunternehmen & Unternehmertum
  • Loggen Sie sich ein, um Kommentare anzuzeigen.

ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL

  1. 1. ADOPTION OF CLOUD-BASED SERVICES BY SMEs IN DEVELOPING COUNTRIES: DEVELOPMENT OF A T-O-E BASED MODEL AMOS WACHANGA WAMBUGU
  2. 2. IT is integral to modern business …. amongst other key business tasks (Davenport, 2013; Ong et al, 2016; Tarutėa & Gatautis, 2014) Information Storage Information Retrieval Communication Reporting
  3. 3. Small & Medium Enterprises • SMEs play a significant role in the economy, • but they have limited possibilities while competing with the large enterprises, • where low adoption of IT plays a big role (Alshamaileh, 2013; Ong et al, 2016)
  4. 4. Research shows that there is low adoption of IT by SMEs in developing economies such as Kenya (KNBS, 2016; Agboh, 2015) Why?
  5. 5. Challenges of traditional IT environments • the upfront setup costs and • the increasingly complex management issue of • software, • hardware • and networking equipment • which also require specialist staff for implementing and maintaining IT services. (Alshamaila et al, 2013; Tarutėa et al, 2014; Ong et al, 2016) Costs Complexity
  6. 6. “a model for enabling very convenient, on-demand network access to a shared pool of configurable computing resources such as networks, servers, storage, applications, and services, which can be rapidly provisioned and released with minimal management effort or service provider interaction” (NIST, 2011, p. 2). Cloud Computing Definition
  7. 7. Reduced costs & Affordability Setup time and effort Simplicity Scalability & Maintainability Convenience and improved accessibility (Ricketts, 2015) Drivers & Benefits
  8. 8. SMEs could find cloud computing to be an attractive solution (Aljabre, 2012; Hassan et al, 2017) Cloud-based services have been deemed to offer reliable, reasonably priced IT services which businesses need in this age. (Carcary et al, 2014; Widyastuti & Irwansyah, 2018)
  9. 9. Cloud Computing Characteristics Five essential characteristics that need to exist in an IT environment for it to be considered as a Cloud. (Mell & Grance, 2011; Erl, Mahmood, & Puttini, 2013). on-demand self-service, broad network access, resource pooling, rapid elasticity, measured service
  10. 10. Cloud Computing Service Delivery Models Cloud computing Illustration. Adapted from (Oguntala, Abd-Alhameed, & Odeyemi, 2017)
  11. 11. Cloud Computing Deployment Models Simplified Overview of Cloud Deployment Models. Adapted from (Oguntala, Abd-Alhameed, & Odeyemi, 2017)
  12. 12. Cloud Computing Pricing Models • Per user model especially for Software as a Service solutions or • Based on usage of computing resources such as for Platform and Infrastructure as a Service solutions • Classified as Static Pricing or Dynamic Pricing (Kamra et al, 2012). • Static pricing is where the cost per period of time is known and does not change even if there’s more or less usage of the service e.g. Office 365 • Dynamic pricing is where there is a fixed charge and then based on usage, the user attracts an extra cost e.g. Amazon Elastic Cloud (EC2)
  13. 13. Concerns on Cloud Computing Information Security & Privacy Data residency and legal jurisdiction Regulatory compliance Vendor Lock-in Business Continuity due to Internet Connectivity issues
  14. 14. SMEs Adoption from Literature Developed Developing Kenya 92% of enterprises made use of ICTs over the internet (Eurostat, 2017). Only 34% of SMEs makes use of computers while 91% make use of telephones (Olise, Anigbogu, Edoko, & Okoli, 2014). SMEs use of ICT devices is mainly mobile phones (40.7%) only 9.5% make use of computers (KNBS, 2016) Only about one in five makes use of cloud computing with only 8% of SMEs make use of private cloud (Giannakouris & Smihily, 2016). Only about 35% have access to the internet and only 18% have websites (Onyedimewu & Kepeghom, 2013). An average of 85.8% of SMEs had access to internet at their premises (CA & KNBS, 2016). Highest use of cloud-based services by SMEs was email, office software and storage of files and databases (Sánchez, 2016). Only 36% of these indicated they make use of SaaS or IaaS (Hinde & Belle, 2012). Fewer SMEs were using ICT for specialized applications such as orders management (20.9%) or human resource management (28.5%) (CA & KNBS, 2016).
  15. 15. Adoption by SMEs in Kenya • Main benefits indicated for adoption of cloud computing were flexibility, cost savings, better scalability, disaster recovery and complexity reduction • Reason for not using ICT is it’s not needed by the business, is not applicable for them or it’s too costly • Main reasons highlighted for not using cloud computing by SMEs was insufficient knowledge within the organization (CA & KNBS, 2016).
  16. 16. Problem Statement 1. SMEs generally are constrained on budgets 2. Most SMEs then resolve to manual processes ……. 3. Use of cloud services might become a key component for success for SMEs 4. There is low adoption of IT, and more so, low adoption of cloud computing by SMEs in Kenya and in Africa. 5. There is need to research a model that could lead to adoption of cloud-based services by SMEs (Venkatraman & Fahd, 2016; Widyastuti et al, 2018; Agboh, 2015; KNBS, 2016; Oguntala et al., 2017)
  17. 17. Considerations for such a model • Many factors should be considered which include the Internal and external environment the SME is operating in and the Technological context as well as Organizational readiness of the SME. • Theoretical frameworks as basis…. (Borgman, Bahli, Heier, & Schewski, 2013)
  18. 18. Theoretical frameworks on Adoption Theory Level of Analysis Author Technological Acceptance Model (TAM) Individual Davis (1989) Diffusion of Innovation (DOI) Organization or Market Rogers (1995) Theory of reasoned action (TRA) Individual Ajzen and Fishbein (1980) Theory of planned behavior (TPB) Individual Ajzen (1985) Unified Theory of Acceptance and Use of Technology (UTAUT) Individual Venkatesh et al. (2003) Technology Organization Environment (TOE) Organization DePietro et al. (1990) Should build on existing theories and frameworks that have been developed which explain adoption of technology and innovations.
  19. 19. Technology-Organization-Environment (TOE) Framework, helps to analyze adoption of technological innovations by firms and organizations can provide a good basis and a good lens (DePietro, Wiarda, & Fleischer, 1990)
  20. 20. Objective of the Study The main objective of this study is: To understand the adoption of cloud-based services by SMEs within Nairobi County in Kenya, and based on the findings, attempt to propose a model for the adoption of cloud-based services as a solution to better IT strategy by the SMEs
  21. 21. Methodology • Research Design - Design Science category of research • Population and Sampling Design - Convenience sampling strategy • Data Collection Methods - Quantitative methods founded on questionnaire-based surveys since they are the most prevalent methodologies (Kumar, 2017;Alshamaileh, 2013; Carcary, Doherty, & Conway, 2014; Hassan et al, 2017)
  22. 22. Research Approach Literature Review Initial Model (based on Theory) Data Collection Instruments Development Pilot Study Review of the Data Collection Instruments Data Collection Data Analysis and Model Update Validation of Model (Expert Reviews) Final Model Problem Definition
  23. 23. Tools & Techniques • Data analysis was done through IBM SPSS Statistics version 23 and IBM SPSS Amos version 21 • Statistical techniques including descriptive statistics, reliability analysis and factor analysis • Exploratory factor analysis (EFA) using Principal Component Analysis (PCA) and varimax rotation was carried out. (Pallant, 2007; Hair et al, 2010).
  24. 24. Methodology • Reliability was tested using Internal Consistency (consistency of data across responses) because Likert’s scale was largely used (Pallant, 2007) • Cronbach alpha lower limit for this study was 0.7 which is deemed to be moderately reliable (Hinton, 2004; Hair et al, 2010) • Average Inter-Item Correlation used in the study was 0.2 to 0.5 (Clark & Watson, 1995) • Validity of the model was determined by experts review and statistically using CFA to determine the model fit and verification of the construct validity in terms of convergent and discriminant validity
  25. 25. TOE Framework Source: DePietro et al. (1990)
  26. 26. Adaptation of TOE for Cloud Computing Adoption Adaptation of TOE for cloud computing Adoption by SMEs
  27. 27. Factors influencing adoption by SMEs Key Factors Influencing Adoption of ICT and Cloud Computing Illustrative Reference Managerial support, cost of ICT, knowledge capacity of an SME Nduati et al (2015) Top management support, technological readiness, organizations size, trading partner pressure, competitive pressure, relative advantage, complexity of proposed technology Makena (2013) External support, competitive pressure, decision makers level of knowledge on cloud computing and innovativeness, the employees cloud knowledge, information intensity, complexity, compatibility, trialability, cost, security and privacy Tehrani (2013) Complexity, compatibility, trialability, cost and security Alam, (2009) Perceived benefits, cost, ICT information and skill, Outdoor pressure, Government support Miraz & Habib (2016) Relative advantage, uncertainty, geo-restriction, compatibility, trialability, size, top management support, prior experience, innovativeness, industry, market scope, supplier efforts and external computing support Alshamaila, Papagiannidis, & Li (2013) Relative advantage, top management support, firm size, competitive pressure, and trading partner Low, Chen, & Wu (2011)
  28. 28. Development of the Questionnaire Section Number of Questions Questions Adapted From A: General Information Personal information (4 questions) Basic organizational information (8 questions) Alshamaila, Papagiannidis, and Li, (2013); Kumar, (2017); McKinnie, (2016); Tehrani, 2013; Hassan, Nasir, Khairudin, & Adon, (2017) B: Current ICT Setup IT Personnel and Strategy (2 questions) Software systems in place (2 questions) Check on knowledge (1 question) Alshamaila, Papagiannidis, and Li, (2013); Kumar, (2017); McKinnie, (2016); Hassan, Nasir, Khairudin, and Adon, (2017); Tehrani, 2013 C: ICT Use (For those who didn't understand what is cloud computing) Technology factors (4 questions) Organization factors (7 questions) Environment factors (7 questions) Rop, (2015); McKinnie, (2016); Mwai, (2016); and Otieno, (2015); Tehrani, 2013 D: Cloud-based services at the organization (For those who understand what is cloud computing) Overview (4 questions) Technology factors (19 questions) Organization factors (9 questions) Environment factors (12 questions) Alshamaila, Papagiannidis, and Li, (2013); Kumar, (2017); Rop, (2015); McKinnie, (2016); and Hassan, Nasir, Khairudin, and Adon, (2017); Tehrani, 2013
  29. 29. Responses Received Total Received Invalid Responses Valid Responses** 50 responses 3 from Government 2 from NGOs 45 responses Valid Responses were from private businesses with less than 250 employees**
  30. 30. Demographics of Respondents • Role • Owner/Management category at 40% (n=18) • Employees at 29% (n=13) • IT Personnel at 20% (n=9) • Gender • Female were 17 (38%) • Male were 28 (62%) • Age- Groups • “26-35 years” highest representation 31 respondents (69%) • “greater than 45 years” was least represented (2%)
  31. 31. Demographics of Respondents • There was an almost evenly distributed representation of organizations in relation to the number of branches and offices • 9 responses (20%) did not have any knowledge of cloud-based services • There was a correlation between knowledge of cloud computing and ICT qualification Distribution of Respondents' by Number of Branches/Offices
  32. 32. Correlation between having qualification in ICT and Knowledge of cloud-based services Do you have any qualification in ICT? Do you know what cloud-based services are? Do you have any qualification in ICT? Pearson Correlation 1 .433** Sig. (2-tailed) .003 N 45 45 Do you know what cloud- based services are? Pearson Correlation .433** 1 Sig. (2-tailed) .003 N 45 45 **. Correlation is significant at the 0.01 level (2-tailed).
  33. 33. Correlation between ICT Complexity and ICT Qualification ICT is complicated, it’s difficult to understand what’s going on Do you have any qualification in ICT? ICT is complicated, it’s difficult to understand what’s going on Pearson Correlation 1 .726* Sig. (2-tailed) .027 N 9 9 Do you have any qualification in ICT? Pearson Correlation .726* 1 Sig. (2-tailed) .027 N 9 9 *. Correlation is significant at the 0.05 level (2-tailed).
  34. 34. Reliable with Cronbach alpha of 0.903 No multicollinearity issue was found (Cohen et al, 2003)
  35. 35. Automated Services in comparison to Cloud Deployed Services Service Automated Services Cloud Deployed Services Frequency (n) Percentage Frequency (n) Percentage Contact e.g. Email/Website 37 82% 31 86% Accounting 27 60% 9 25% Invoicing 22 49% 4 11% CRM 21 47% 14 39% HR 11 24% 3 8% Payroll 20 44% 5 14% Sales, Marketing 12 27% 6 17% Manufacturing 0 0% 0 0% Business Process Automation 15 33% 6 17% Specialized Software 6 13% 4 11% Inventory Management 10 22% 3 8% Documents Management 18 40% 14 39% Distribution (Supply Chain Management) 0 0% 0 0%(Similar to the CA&KNBS, 2016 paper)
  36. 36. Number of offices by amount paid for cloud computing
  37. 37. Satisfaction level by amount spent on cloud computing
  38. 38. Distribution of satisfaction levels based on amount spent on cloud-based services Positive significant (r=0.385; p<0.05) relationship, although not a very strong relationship, between the amount paid and level of satisfaction from cloud-based services
  39. 39. Source of Cloud-Based Services Information
  40. 40. Exploratory Factor Analysis
  41. 41. Component Technology Relative Advantage Environment Vendor Readiness Organization Readiness and Size 1 2 3 T_RA_Easier - Using cloud-based services makes it easier for us to do our job compared to traditional on-premises software .870 T_RA_Reliable - Cloud-based services are more reliable than traditional on-premises software .848 T_SA_Secure - Cloud-based services are secure .805 T_Compa_Integrated - Cloud-based services can be easily integrated into our existing IT infrastructure .615 T_RA_Efficiency - Using cloud-based services improves operational efficiency, productivity and quality of work in our organization .606 E_VR_Info - Cloud Service Providers provide enough information about the services .907 E_VR_Overall - Overall, Cloud Service Providers are ready with the services they provide .852 E_VR_Capacity – Cloud Service Providers have adequate capacity to run the services .828 O_TR_Ready - Our organization’s management is ready to make use of cloud-based services .830 O_TR_Skills - Most of our employees possess required skills to make use of cloud-based services .814 O_Size - Cloud-based services are applicable for us .688
  42. 42. Rotated Component Matrixa Component Environment Regulations Environment Trading Partner Pressure Technology Accessibility 1 2 3 4 5 6 E_R_Gov - Government Regulations for our business type allow use of cloud-based services .927 E_R_Industry - Our Industry Regulations allow use of cloud-based services .871 E_TPP_Cust - Our customers have forced us to make use of cloud-based services .871 E_TPP_Suppl - Our suppliers have forced us to make use of cloud-based services .771 T_SA_Accessibility – Our internet connectivity allows us to easily use cloud-based services .878 T_SA_Connection – Accessibility on-the-go encouraged us to use cloud-based services .804 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 6 iterations. Cont’d
  43. 43. Validity of the Model Measurement Indices Model Value Recommended Value * Chi-Square(χ2)/Degree of freedom(DF) 1.243 ≤ 3.000 Comparative Fit Index (CFI) 0.903 ≥ 0.9000 Goodness of Fit Index (GFI) 0.757 ≥ 0.9000 Adjusted Goodness of Fit Index (AGFI) 0.649 ≥ 0.8000 Tucker-Lewis Index (TLI) 0.876 ≥ 0.9000 Incremental Fit Index (IFI) 0.913 ≥ 0.9000 * Recommended values adapted from Kumar (2017) Construct validity is evaluated by checking the discriminant and convergent validity of the model.
  44. 44. Convergent validity tests CR AVE MSV Trading Partner Pressure 0.806 0.676 0.153 Relative Advantage 0.841 0.524 0.166 Vendor Readiness 0.888 0.727 0.214 Readiness and Size 0.760 0.546 0.169 Regulations 0.900 0.819 0.106 Accessibility 0.778 0.637 0.214 Composite reliability (CR) values for each construct were found in the range of 0.760 to 0.900 indicating acceptable to a high level of convergent validity (Hair, Anderson, Black, & Babin, 2010). Average variance extracted (AVE) values were found in the range of 0.524 to 0.819 for all constructs. These estimates are found above or equal to the threshold value of 0.50 (Fornell & Larker, 1981; Hair, Anderson, Black, & Babin, 2010). The results confirm the convergent validity.
  45. 45. Discriminant Validity Trading Partner Pressure Relative Advantage Vendor Readiness Readiness and Size Regulations Accessibility Trading Partner Pressure 0.822 Relative Advantage 0.084 0.724 Vendor Readiness 0.391 0.339 0.852 Readiness and Size -0.290 0.065 0.251 0.739 Regulations 0.325 0.318 0.308 0.083 0.905 Accessibility 0.109 0.408 0.463 0.411 0.262 0.798 Note: Bold values across the diagonal indicate the square root of AVE The square root of the AVE of each construct should be larger than all the cross-correlations between the construct and other constructs which is the case for as shown in (Fornell & Larker, 1981; Hair, Anderson, Black, & Babin, 2010; Kumar, 2017). The results of these tests show that each construct nominated in this study is different from other, thereby confirming the discriminant validity.
  46. 46. Validity of the Model through Expert Reviews • SME owner highlighted a key strength was that the model was not looking at only one facet of the ICT adoption • Cloud computing expert suggested a weakness could be the applicability of the model for different types of services but a strength was it encapsulated most of the key areas that she found to be applicable in real life situations • They advised the model should be further adapted into steps which can be a guideline for SMEs that provides a set of instructions
  47. 47. Objective 1: Current Adoption Levels of Cloud-Based Services • ICT was widely available, there was still low use of ICT for day to day operations by businesses (CA & KNBS, 2016) • Communication, that is email and website, was the service mainly used on the cloud (86%) • Larger SMEs generally spent more on cloud-based services as compared to smaller organizations which mainly make use of free services. • There was a tendency that the more money an organization spent on cloud-services, the more satisfied the SME would be. • In summary, it was concluded that there was low use of ICT and cloud computing especially for business applications with the highest use being communication such as email and websites. • This conclusion also informs the need for theoretical models that could ensure successful adoption of cloud computing by SMEs
  48. 48. [Revisiting] Model based on Literature Review Adaptation of TOE for cloud computing Adoption by SMEs
  49. 49. Objective 2: Final TOE based model
  50. 50. Objective 3: Validation of the model • Statistical analysis of the data showed a largely reasonable level of fit for the indices. This indicates good model fit. • Construct validity was also confirmed where both convergent and discriminant validity was confirmed. • The statistical analysis in general concluded that the model was valid and a good fit for its purpose. • The experts in general concluded that the model was valid and a good fit for cloud computing adoption by the SMEs. • The experts advised the need for a guideline.
  51. 51. Conclusions • Based on the exploratory nature and the small sample size in this study, I’m not suggesting the findings to be generalizable. • Nonetheless, the insights gained from this study can provide some interesting findings and basis for further research on cloud computing adoption
  52. 52. SMEs can make use of the model proposed
  53. 53. Cloud providers, schools and other interested parties should invest in dissemination of information on cloud computing
  54. 54. Cloud service providers should invest in business applications that offer both free & premium services to cater for smaller & larger organizations
  55. 55. Governments and policy makers can also make use of the model to determine the best environment for enabling SMEs to adopt cloud computing
  56. 56. This research contributes to knowledge of ICT adoption & cloud computing
  57. 57. Limitations, Recommendations and Future Directions Limitation Recommendations and Future Directions Constraints on time and budget convenience sampling was used in this study. This sampling methodology meant that the results may not be generalized Conduct an external validity which may have representation from various types of organization, in different environments and with different types of representatives as well as a larger sample size SMEs in different contexts may be affected by different factors which was not accounted for The model can be refined to a more generalized model which can be applicable to different environments Need for an implementation guideline Implementation guideline highlighting the expected conditions, factors and issues that could help an SME, governments and other interested parties to be able to use the model to embrace cloud-based services Applicability to other types of organizations Investigated further in relation to different types of industries and organization sizes to determine its usability even for large enterprises, non-governmental organizations and governments Combination of theories to cover more Theories at different analysis levels could help improve the model to cover more dimensions
  58. 58. Publications • Refereed Conference Paper • Wambugu, Amos Wachanga and Ndiege, Joshua Rumo (2018). Harnessing cloud computing by small and medium enterprises in Kenya. In: 12th Egerton University International Conference, 2018 Njoro, Kenya
  59. 59. Amos Wachanga Wambugu wachanga@sibasi.com

×