Decision making on adoption of cloud computing in e-commerce using fuzzy TOPSIS

© 2017 IEEE. Cloud computing promises enhanced scalability, flexibility, and cost-efficiency. In practice, however, there are many uncertainties about the usage of cloud computing resources in the e-commerce context. As e-commerce is dependent on a reliable and secure online store, it is important for decision makers to adopt an optimal cloud computing mode (Such as SaaS, PaaS and IaaS). This study assesses the factors associated with cloud-based e-commerce based on TOE (technological, organizational, and environmental) framework using multi-criteria decision-making technique (Fuzzy TOPSIS). The results show that Fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach proposes software-as-a-service (SaaS) as the best choice for e-commerce business

Selecting Cloud Deployment Model Using a Delphi Analytic Hierarchy Process (DAHP)

Cloud computing is a significant paradigm shift in information technology (IT) service offerings that has been receiving enormous attention in academic and IT industry. Recent years has seen exponential growth in cloud use adoption, where many organizations are moving their IT resources into cloud due to flexibility and low-cost. However, on account of rapid innovation and growth in cloud technologies and service providers, selecting the right cloud services, provider and strategy is becoming increasing a common challenge to organization during cloud adoption. In an attempt to address this challenge, we propose application of Delphi Analytic Hierarchy Process (DAHP) method in selecting cloud deployment model. There are several cloud deployment models and organizations must identify the right model that best suits their business needs. The proposed approach facilitates a collaborative decision making process, consisting a number of decision makers whom, with consensus facilitated by the DAHP process, identifies feasible approaches, decision making factors and ultimate selection of a cloud deployment model alternative that is based on organizational business needs and capabilities. The DAHP process is illustrated by a means of a case study. The DAHP result analysis, as was illustrated in the case study, helps in explaining and justifying the choice selected as the best cloud deployment model

A Decision Making Model for the Adoption of Cloud Computing in Jamaican Organizations

Cloud computing is the current technological silver bullet that has been proposed for solving a variety of Information Systems (IS) problems facing organizations in developing countries including bridging the digital divide. However, the large number of cloud options available can make determining the most applicable solution to an organization non-trivial. This paper looks at these options and the barriers to adoption facing Small/Medium Enterprises (SMEs) in Jamaica. A Simple Additive Weighting (SAW) model which can be used in the cloud adoption decision process is then developed and tested using an example

Cloud computing adoption decision modelling for SMEs: a conjoint analysis

Cloud computing is an emerging technology that promises competitive advantages, cost savings, enhanced business processes and services, and various other benefits to enterprises. Despite the rapid technological advancement, the adoption of cloud computing is still growing slowly among small and mediumsized enterprises (SMEs). This paper presents a model to support the decisionmaking process, using a multi-criteria decision method PAPRIKA for the socio-technical aspects influencing SMEs cloud adoption decision. Due to the multifaceted nature of the cloud computing adoption process, the evaluation of various cloud services and deployment models have become a major challenge. This paper presents a systematic approach to evaluating cloud computing services and deployment models. Subsequently, we have conducted conjoint analysis activities with five SMEs decision makers as part of the distribution process of this decision modelling based on predetermined criteria. With the help of the proposed model, cloud services and deployment models can be ranked and selected

A Framework to support cloud adoption decision-making by SMEs in Tamil Nadu

Cloud computing is a disruptive technology which represents a paradigm shift in the way computing services are purchased and maintained within organisations. Due to its benefits like low capital, scalability and high reliability, the cloud infrastructure has the features and facilities to speed up Information Technology (IT) adoption in developing countries. However, moving data and applications to a cloud environment is not straightforward and can be very challenging as decision makers need to consider numerous technical and organisational aspects before deciding to adopt cloud infrastructure. There are existing models and framework available to support different stages of the cloud adoption decision making process. However, they are developed for technologically developed countries and there has been very little investigation done to determine whether the factors that affect cloud adoption are any different for a technologically developing country like India. This research aims to provide a framework to aid cloud adoption among SMEs in Tamil Nadu, a southern state of the Indian Union. The major contribution to knowledge is the framework, based on Scientific Decision Making (SDM) which has been developed to support SME decision makers at all the different stages of the cloud adoption decision making process. The theories of technology adoption like Diffusion of Innovation (DOI), Technology, Organisation and Environment (TOE) framework along with Multi Criteria Decision Making (MCDM) forms the theoretical underpinnings of the research. The primary data was collected via two web-based questionnaire surveys among SME decision makers from Tamil Nadu. Six determinants of cloud adoption such relative advantage, compatibility, innovativeness, organisation size, external issues and industry type were identified. The findings identify that 12 organisational factor specific to SME location is a very important decision factor while planning cloud adoption. The proposed cloud adoption decision support framework (CADSF) includes two tools namely; cloud suitability assessment and cloud service identification. The framework provides a preliminary structure for developing a knowledge driven Decision Support System (DSS) to support cloud adoption among SMEs in Tamil Nadu. Finally, based on the findings of the research, it is expected with developments to the existing cloud infrastructure, especially the availability of reliable internet and increased awareness, more SMEs in Tamil Nadu would adopt the cloud computing infrastructure

A Holistic Decision Framework to Avoid Vendor Lock-in for Cloud SaaS Migration

Cloud computing offers an innovative business model to enterprise for IT services consumption and delivery. Software as a Service (SaaS) is one of the cloud offerings that attract organisations as a potential solution in reducing their IT cost. However, the vast diversity among the available cloud SaaS services makes it difficult for customers to decide whose vendor services to use or even to determine a valid basis for their selections. Moreover, this variety of cloud SaaS services has led to proprietary architectures and technologies being used by cloud vendors, increasing the risk of vendor lock-in for customers. Therefore, when enterprises interact with SaaS providers within the purview of the current cloud marketplace, they often encounter significant lock-in challenges to migrating and interconnecting cloud. Hence, the complexity and variety of cloud SaaS service offerings makes it imperative for businesses to use a clear and well understood decision process to procure, migrate and/or discontinue cloud services. To date, the expertise and technological solutions to simplify such transition and facilitate good decision making to avoid lock-in risks in the cloud are limited. Besides, little investigation has been carried out to provide a comprehensive decision framework to support enterprises on how to avoid lock-in risks when selecting and implementing cloud-based SaaS solutions within existing environments. Such decision framework is important to reduce complexity and variations in implementation patterns on the cloud provider side, while at the same time minimising potential switching cost for enterprises by resolving integration issues with existing IT infrastructures. This paper proposes a holistic 6-step decision framework that enables an enterprise to assess its current IT landscape for potential SaaS replacement, and provides effective strategies to mitigate vendor lock-in risks in cloud (SaaS) migration. The framework follows research findings and addresses the core requirements for choosing vendor-neutral interoperable and portable cloud services without the fear of vendor lock-in, and architectural decisions for secure SaaS migration. Therefore, the results of this research can help IT managers have a safe and effective migration to cloud computing SaaS environment

SMEs Adoption of SaaS Cloud Services:A Novel Ontological Framework(Nigeria as a case Study).

The future of Information Technology lies in cloud computing, whose primary objective is to reduce the cost of IT services while increasing production output, availability, reliability, flexibility as well as a decrease in processing time. Owing to few exploratory studies that explain the adoption of cloud services, this research tends to understand the factors affecting cloud service adoption decision by SMEs in Nigeria. Also, it proposes a solution based framework to tackle the identified factors in view of promoting cloud service adoption by Nigerian SMEs. In view of the above, this thesis investigates the reason for slow adoption of cloud services with specific emphasis on Nigeria SMEs. Firstly, the existing literature in cloud service adoption by SME is examined based on Systematic Literature Review (SLR) method. This helps to inform the research gap in relation to cloud service adoption technique. Secondly, the thesis uses a mixed method approach integrating quantitative and qualitative methods to gather data through four stages of data gathering approach. The primary data gathering is based on quantitative (survey) stage 1 and qualitative (Focus Group) stage 2, which involves the studies identifying the cloud service adoption challenges specific to Nigeria SMEs. Furthermore, a solution framework CLOUDSME which includes an ontologically developed Decision Support System(DSS) is proposed to tackle the challenge identified in Primary data gathering stage 1and 2. The proposed framework consists of four phases: The first phase deals with gathering information on how various cloud services address dynamic SME user requirements identified in the primary data gathering stage, this phase forms the building block through which the framework is built upon. The second phase which is the prioritisation phase Adopts Analytical Hierarchical Process (AHP) approach to deal with the issue of complex comparison, also the third stage of data gathering (quantitative) is performed whereby a group interview is carried-out to compare and assign weights to service provider offering in addressing user requirements using pairwise comparison scale. The Third phase addressing the issue of cloud service ranking. In this phase, the major contribution of this research is introduced, whereby a new formalism is proposed using rational relationships to tackle the issue of rank reversal associated with the traditional AHP approach. The fourth phase of the framework is the development of the ontological proposed DSS which comprises of the information gathered in phase 1, 2 and 3. The proposed DSS promotes cloud service Knowledge management, service recommendation and service ranking toward cloud service adoption decision making by SME managers. The final stage of the research is the validation phase which comprises of construct validation. As well as user opinion and expert opinion and researcher opinion validation based on a survey (Quantitative) which makes up the fourth stage of the data gathering stages. The findings from the user opinion evaluation and validation prove the CLOUDSME has the capability to tackle the slow adoption of cloud services by Nigeria SMEs

A Systematic Literature Review on IT Outsourcing Decision and Future Research Directions

During the recent decades, some academic research on the subject of information technology outsourcing (ITO) decision has appeared in different outlets, which may impede the use of such resources and as a result, repetition of research by various researchers is very likely. The purpose of this paper is then to conduct a systematic literature review (SLR) pertaining to research on ITO decision. Then, this review intends to 1) classify ITO decision literature, 2) provide a list of factors affecting ITO decision, and 3) identify ITO strategies. To this end, 91 ITO articles published between 2000 and 2018 in 51 unique journals were reviewed. The results yielded three kinds of descriptive, relational, and comparative ITO decision studies. The determinants of ITO decisions are classified into technological, organizational, environmental and user adoption factors. Furthermore, the trend of studied ITO strategies in the reviewed literature is analyzed, and future sourcing varietals are proposed. Finally, some insights and future research directions are proposed based on the review results.During the recent decades, some academic research on the subject of information technology outsourcing (ITO) decision has appeared in different outlets, which may impede the use of such resources and as a result, repetition of research by various researchers is very likely. The purpose of this paper is then to conduct a systematic literature review (SLR) pertaining to research on ITO decision. Then, this review intends to 1) classify ITO decision literature, 2) provide a list of factors affecting ITO decision, and 3) identify ITO strategies. To this end, 91 ITO articles published between 2000 and 2018 in 51 unique journals were reviewed. The results yielded three kinds of descriptive, relational, and comparative ITO decision studies. The determinants of ITO decisions are classified into technological, organizational, environmental and user adoption factors. Furthermore, the trend of studied ITO strategies in the reviewed literature is analyzed, and future sourcing varietals are proposed. Finally, some insights and future research directions are proposed based on the review results