Application of the Technology Acceptance Model and the Technology–Organisation–Environment Model to examine social media marketing use in the South African tourism industry

Abstract

Background: In tourism, globally there is a growing interest in social media marketing research. However, most previous research on social media marketing has focused on large tourism enterprises such as chain hotels, leaving out small tourism businesses such as travel agencies and tour operators. Objective: The aim of this research was to establish factors that influence attitude towards the use of social media marketing by travel agencies and tour operators in South Africa. Method: The study adopteda quantitative approach through the use of questionnaires. Data used in the analysis were collected from 150 travel agencies and tour operators by means of a structured questionnaire. Multiple regression analysis and one-way ANOVA were used for data analysis. Results: The results showed that managerial support and managers’ level of education are the two main internal factors which influence attitude towards the use of social media marketing. Pressure from competitors, perceived benefits and perceived ease of use were found to be the most prominent external factors which influence the use of social media marketing. The results also revealed that technical knowledge moderates the relationship between attitude towards social media marketing and the level of social media marketing usage. Conclusion: The study concludes with these recommendations: Management of travel agencies, tour operating businesses and the South African government should support the use of social media marketing by small tourism businesses through providing training and workshops on social media marketing for the employees to acquire the required skills.

Spreadsheet-Based Medical and Financial Record in the First Level Health Facilities

“…Administration officer is interested in using this application further because this application is useful and facilitates its work. In line with previous research, the perceived usefulness play a significant role in influencing attitude towards applications adoption [15]. The Perception of usefulness was shown to be the strongest predictor of intention to use application [16].…”

Modeling the Measurements of the Determinants of ICT Fluency and Evolution of Digital Divide Among Students in Developing Countries—East Africa Case Study

“…Referring to the previous study, commonly used methods to find the most influential variables and to study the digital divide are Logistic Regression (LR) and Concentration Index (CI), respectively [13,15,16,58]. This paper follows a similar approach to investigate the determinants of technology fluency among the EA undergraduate students by class year (1st year to 4th year) using an LR based model [11,12]. Moreover, it uses CI to model the evolution of digital inequalities [13].…”

“…It compensates the case where the CI cannot be explained by the observation M and W such as [−1,0]. According to Equation (6), Horizontal Inequality (HI) becomes Equations (11) and (12): Estimate CI in Equation (10) 3.Compute HI in Equation 12…”

“…In regard to ICT fluency and digital divide in EA, few studies have been conducted in the context of higher education, but no study predicted the determinants of technology fluency to understand better the influences of EA regional local characteristics on undergraduate students' technology skills. Most of the studies used, instead, empirical descriptive statistic methods that describe the undergraduate students' barriers and enablers to technology skills [10][11][12][13]. This paper claims that further studies are needed to understand the reality better and it steps forward by developing one model to study the determinants of ICT fluency and the other to explore the evolution of digital inequalities by class year (1st year to 4th year).…”

Application of Fuzzy Analytical Network Process (ANP) and VIKOR for the Assessment of Green Agility Critical Success Factors in Dairy Companies

“…In general, technology appropriation is greatly dependent upon and shaped by the surrounding environment, including social and economic forces beyond managerial intent. Matikiti et al [29] believe that considering the social nature of technology and environment-when technology implies the relationship between social actors, and environment represents opportunities and constraints that can potentially promote or thwart an individual's goal attainments-we can understand that there is an interaction between technology and environment in reality. This is because how individuals use appropriate technology for their own goals is dependent on whether or not other social actors can create opportunities and/or remove constraints [27].…”