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. Abstract. Cloud computing is an emerging technology that promises competitive advantages, significant 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 medium-sized enterprises (SMEs). This paper presents a model to support the decision-making process, using a multi-criteria decision method PAPRIKA for the sociotechnical aspects that have an impact on SMEs cloud computing adoption process. Due to the multifaceted nature of the cloud computing adoption process, the evaluation and selection 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 based on their economic values, advantages, compatibility with in-house systems, integrability & manageability, security & privacy concerns, reliability, availability, features & management. The adaptability and the feasibility of the proposed method in cloud computing adoption demonstrated with five real-world cases.