In Saudi Arabia, limited studies have developed models related to measuring the impact of the digital economy on the labor market. This model concerns the agricultural, service, and industrial sectors in Saudi Arabia. This study further investigates the relationship between digitalization, labor productivity, and unemployment using the ARDL error correction method for time-series data obtained from the World Bank database for the period of 2001–2019. The findings of this study illustrate, digital variables such as fixed broadband subscriptions (LNFBS), mobile cellular subscriptions (LNMCS), and computer, communications, and other services (LNCCO) do not significantly affect the labor market in the agricultural sector. LNMCS and LNCCO do not influence the service sector. However, they are negatively influencing the industrial sector and labor productivity. In contrast, LNFBS has a positive impact on both the service and industrial sectors. Interestingly, all three digital variables significantly reduce unemployment in the long run in Saudi Arabia. However, in the short run, digitalization does not have a positive impact on the economy. This study hopes to benefit policymakers in considering how to reorganize the socioeconomic infrastructure to balance economic growth through greater technology and the utilization of the country’s human resources.

Social commerce is getting popular all over the world including in the middle eastern countries. The main objective of this work is to identify the factors that influence the purchasing intention and the behavior among the Y generation and millennials in the Kingdom of Saudi Arabia. For this purpose, a hypothetical conceptual model was developed based on proven theories and well-established literature. To test this model, data were collected from 178 university students using an online questionnaire. Data were analyzed using SPSS 25. The validity and the reliability of the questionnaire items were determined through factors analysis and Cronbach Alpha. All hypotheses were supported in linear regression analysis, however, the stepwise multiple regression analysis which shows the simultaneous effects of the independent variables, resulted in that out of 11 hypotheses 3 were not supported. Based on the findings a discussion was developed at the end of the paper.