The Dynamic Influence of ICT on Modern Logistic Industry in Developing Economy and CO2 Emission Using ARDL Approach: A Case of Pakistan

Artificial intelligence applications have opened new opportunities for the development of the modern logistics industry. Accordingly, Information and Communication Technology (ICT) concerning economic growth and carbon emission need comprehensive insight into the logistic industry— an area mainly analyzed from a general perspective by existing literature. Against this backdrop, this paper analyzes the short-run and long-run effects of dynamic variables and their interaction on investment in the logistics industry in connection with economic prosperity, Information and communication technology (ICT), trade, and carbon emission. Accordingly, the autoregressive distributive lag model (ARDL) is applied to observe a close regional perspective of a developing economy like Pakistan using time-series data from 1990 to 2019. The study findings observe a unidirectional long-run causality running from economic prosperity, logistics industry, Information and communication technology (ICT), and trade development to carbon emission. Moreover, regional economic growth exerts a significant demand-pull effect on corresponding regional economic development. These findings imply that high-income geographical regions will continue to face the higher long-run futuristic risks of the contemporary investment in logistic industry development when adhering to ever-evolving carbon emission standards under regional preferences. Accordingly, these regions should be given urgent attention concerning high-technology and artificial intelligence applications in developing economies. Given the availability of technological and general resource efficiencies in developing economies, such applied business-oriented scope of this statistical analysis might facilitate geo-specific strategies concerning future outcomes of current investment in the traditional logistic industry in those countries. We believe the overall analysis can be applied to other developing economies to facilitate sustainable development goals.