TY - JOUR
T1 - Driving Forces for Business Growth in Saudi Arabia: Industrial Cross-Sectional Analysis
AU - Alojairi, Ahmed Saleh
AU - Amin, SF
AU - Akhtar, N
AU - Basiouni, A
AU - Bahamdan, W
PY - 2020
Y1 - 2020
N2 - The study leads to a multi-group investigation based on enterprises working in the Kingdom of Saudi Arabia using the Net-Enabled Business Innovation Cycle NEBIC model. The study concentrated on the adoption of the NEBIC model among various online sellers (small, medium and large firms, based on a number of employees and sales volume). Convenience sampling was used to collect the data from the proposed sample size of 500. A total of 338 responses were received. The structural equation modelling (SEM) method was used for path analysis via AMOS 21 and results revealed a reasonable fit between data collected and the model used: chi2 (125.292), chi2 / DF (5.221), RMSEA (0.111), CFI (0.969), and TLI (0.941). The model confirmed that there has been high co-linearity exist among all the constructs. The results also revealed that the multi-groups (i.e., sectors with different levels of online selling adoption, firms with different online buying orientations, and firms with different sizes) moderates a significant role on the research model. The multigroup analysis showed significant evidence that smaller firms with no prior online buying in sectors characterized as having lower online selling adoption rates may produce better results in their adoption of online selling. The study is limited to organizations working in Saudi Arabia. Future work will focus on different nations' online businesses to test the multi-group investigation.
AB - The study leads to a multi-group investigation based on enterprises working in the Kingdom of Saudi Arabia using the Net-Enabled Business Innovation Cycle NEBIC model. The study concentrated on the adoption of the NEBIC model among various online sellers (small, medium and large firms, based on a number of employees and sales volume). Convenience sampling was used to collect the data from the proposed sample size of 500. A total of 338 responses were received. The structural equation modelling (SEM) method was used for path analysis via AMOS 21 and results revealed a reasonable fit between data collected and the model used: chi2 (125.292), chi2 / DF (5.221), RMSEA (0.111), CFI (0.969), and TLI (0.941). The model confirmed that there has been high co-linearity exist among all the constructs. The results also revealed that the multi-groups (i.e., sectors with different levels of online selling adoption, firms with different online buying orientations, and firms with different sizes) moderates a significant role on the research model. The multigroup analysis showed significant evidence that smaller firms with no prior online buying in sectors characterized as having lower online selling adoption rates may produce better results in their adoption of online selling. The study is limited to organizations working in Saudi Arabia. Future work will focus on different nations' online businesses to test the multi-group investigation.
M3 - Article
SN - 2056-9122
JO - MANAGEMENT & BUSINESS ACAD
JF - MANAGEMENT & BUSINESS ACAD
ER -