title: Achieving Knowledge Ambidexterity in Small and Medium Enterprises using Cloud Computing
Creators: name: Saratchandra, Minu
Publisher: name: University of Southern Queensland
Year: 2022
Subjects: subject: knowledge ambidexterity; cloud computing; SMEs; technology-driven innovation; ambidextrous learning organisation; knowledge management; design science research
classificationCode: 460908
subject: Information systems organisation and management
valueUri: https://www.abs.gov.au/statistics/classifications/australian-and-new-zealand-standard-research-classification-anzsrc/latest-release
classificationCode: 350302
subject: Business information management (incl. records, knowledge and intelligence)
valueUri: https://www.abs.gov.au/statistics/classifications/australian-and-new-zealand-standard-research-classification-anzsrc/latest-release

description: Knowledge ambidexterity (K-AMB) is a simultaneous process of knowledge exploration and exploitation that can be adopted by organisations for effective knowledge management. Compared with larger organisations, small and medium enterprises (SMEs) have limited K-AMB capability. Cloud computing has emerged as an effective solution for knowledge management in SMEs. Cloud computing can also help SMEs to achieve K-AMB. However, there is a research gap to understand how can cloud computing help SMEs achieve K-AMB. To this end, the primary research questions for this study are: RQ1: What is the role of cloud computing in knowledge management for SMEs? RQ2: How is K-AMB achieved by SMEs from technology-driven innovation using cloud computing? RQ3: How does cloud computing support transformation of SMEs into ambidextrous learning organisations? To answer these research questions, a design science research (DSR) study was executed. A preliminary research artefact, referred to as the knowledge ambidexterity framework (KAF), was developed based on the findings of a systematic literature review (SLR) (Paper 1) and pre-intervention interviews with key stakeholders from seven case study SMEs in India and the United Arab Emirates (UAE). The KAF was then demonstrated using IBM Watson cloud services in 2019. This was followed by artefact evaluation at the seven case studies with two rounds of post-intervention semi-structured interviews in 2020 and 2021, that captured longitudinal data on the impact of the artefact on the case study SMEs. Qualitative data iii captured from interview transcripts were analysed using NVivo to identify emerging themes that were used to discuss the findings to answer RQ2 and RQ3. This study found that SMEs initially operated on a compromised KAMB state where cloud computing is under-utilised, thereby missing out on ambidextrous opportunities. However, after KAF was implemented in SMEs for one year, it was found that SMEs were able to achieve K-AMB supported by technology-driven innovation using cloud computing (Paper 2). This was possible since cloud computing provided a platform for SMEs to simultaneously execute knowledge exploration and exploitation. Furthermore, because of continued collaboration with the case study SMEs, it was found that K-AMB created a continuous learning environment that helped SMEs transform into an ambidextrous learning organisation (Paper 3). In terms of theoretical contribution, this study examined the role of cloud computing on K-AMB capability and associated K-AMB with technology-driven innovation within the SME sector. It was also identified that SMEs that can continuously follow K-AMB processes supported by cloud computing can transform into ambidextrous learning organisations. This study contributes to practice by offering guidelines for SMEs on achieving K-AMB using cloud computing to promote technology-driven innovation and develop a continuous learning culture.