Wits Business School (ETDs)

Permanent URI for this communityhttps://hdl.handle.net/10539/37941

Browse

Filters

2022 - 20242

Settings

Subject: search.filters.subject.Experience

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Attitude and acceptance of Artificial Intelligence technologies in the South African financial services. industry
    (University of the Witwatersrand, Johannesburg, 2024) Wotela, Ruth Rumbidzai; Maier, Christoph
    Despite Artificial Intelligence (AI) being topical, the successful adoption of AI technologies within organisations has been slower than expected. Literature and past research highlights the mixed and contradictory views and findings regarding employees’ attitude and acceptance of AI technologies, which challenge the successful implementation and use of AI technologies. Further, research on employees’ attitude and acceptance of AI technologies in emerging market economies, such as South Africa, and specifically within mandatory settings is limited. The purpose of this research was to investigate and determine factors influencing employees’ attitude and acceptance of AI technologies amongst employees within the financial services industry, where the use of AI technologies is mandatory. The Technology Acceptance Model (TAM) and the Technology-Organisation-Environment (TOE) framework were integrated and extended. This quantitative research study used a cross-sectional design. An online survey was distributed to employees within financial services organisations. A total of 410 valid responses were analysed using descriptive statistics, correlation analysis and regression analysis. Textual responses from the open-ended questions were categorised and presented visually in the form of word clouds. The research results indicate that each of the technological, individual, organisational, and environmental factors have a significant positive effect on attitude towards use of AI technologies. Multiple regression and stepwise regression analysis were used to identify the most influential determinants of attitude towards use of AI technologies from all the technological, individual, organisational and environmental factors. The results indicate that employee wellbeing, competitive pressure, perceived usefulness, management support, perceived ease of use, organisational justice and customer pressure are key determinants of attitude towards the use of AI technologies. The attitude-acceptance relationship is confirmed, as attitude towards use of AI technologies positively influences the acceptance of AI technologies. Although employees’ job roles do not moderate the relationship between attitude and acceptance of AI technologies, their experience with using AI technologies does. Based on these findings the ITOE model for implementing AI technologies is developed, and can be used to facilitate the successful implementation and use of AI technologies. The implications of this research, as well as recommendations for organisations and future research are also discussed.
  • Thumbnail Image
    Item
    Developmental finance institutions’ decision-making criteria and the financing of new ventures in South Africa
    (University of the Witwatersrand, Johannesburg, 2022) Mtsewu, Samkelisiwe; Murimbika, Edward
    The South African government has established Development Finance Institutions to increase entrepreneurial activity and to aid in bridging the financial gap confronted by entrepreneurs. Despite the government’s initiatives to bridge the financial gap, total early-stage entrepreneurship activity rates are low. The Global Entrepreneurship Monitor (2020) reported that South Africa has one of the lowest total early-stage entrepreneurship activities, with lack of funding and education being cited as some of the contributing factors. The study aimed to determine the extent to which the entrepreneurs’ human capital attributes significantly impact the decision-making criteria of Development Finance Institutions in South Africa. The human capital attributes reviewed in this study were the level of education, experience, skills and knowledge. The study aids in filling the gap that exists in Development Finance Institutions financing criteria in developing economies thereby contributing to budding entrepreneurs for funding their new ventures. A cross-sectional quantitative research methodology as adopted with convenience and snowball non-probability sampling methods used for data collection using an online questionnaire. Out of 118 responses that were received from small to medium enterprises, 74 were usable and indicated that they had been funded by government-owned Development Finance Institutions. Correlations test analyses were used to determine the significance of the relationship between identified constructs. The study revealed that there is a positive relationship between the entrepreneurs’ human capital and the DFIs’ decision to finance, however, this relationship was not statistically significant. The findings assert that human capital does serve as a signal when funders are deciding to fund. The study contributes towards reducing the gap in the body of knowledge on the decision-making of DFIs. Thus, the study implicates and provides direction to the government and or policymakers to draft policies that will improve human capital levels of the population to enable increased entrepreneurship participation and contribute to the growth of the economy