The modern logistics industry has opened new strategic perspectives in establishing its interrelation with economic growth. In recent years, understanding such an overlap has become a policy issue considering ever-increasing factors and their influence on this relation. Most existing studies have explored this interaction from a general perspective, or for developed countries. This paper explores time-series analysis of the dynamic variables and their inter-related influence in both the short and long run on the relationship between modern logistic industry and economic growth—a more specific perspective, particularly for developing countries. Accordingly, we exemplify our analysis by employing the vector autoregression (VAR) model to the most updated time series data of investment in the logistics industry and the economic growth of Pakistan from 1990 to 2018. The empirical findings endorse the previous studies’ outcomes and recognize the importance of sustainable economic development concerning continuously improving the logistics industry. However, a unidirectional relation is observed that economic growth leads to developing the logistics industry—economic growth exerts a significant demand-pull effect on Pakistan’s logistics. It implies that logistic industrial development is comparatively quicker in the geographical areas where economic growth is higher than those areas where economic growth is low. To conclude this study’s findings, logistics industry reforms should prioritize the selected geographical areas in improving the economy that would lead to the modern logistics industry’s development. As the model adopts Pakistan’s context, the overall statistical analysis can be generalized to other developing economies. These results would be of particular interest to strategy makers working in developing countries and help them design and develop modern transportation and logistics, coupled with interlinked technological factors, which would attract investment in the logistics industry for sustainable economic development.

The modern logistics industry in relation to economic growth and carbon emission has opened new strategic perspectives. Recent research work have analyzed such complex interference from a broad perspective. However, analyzing this overlap needs comprehensive insight into the logistics industry while simultaneously estimating its short-run and long-run effects from regional aspects due to continue-evolving factors and their impact on it. This paper competently analyzes logistics industry components in connection with economic prosperity, energy consumption, trade development, and carbon emission from a more specific regional perspective of a developing country. Methodologically, an autoregressive distributive lag model (ARDL) is employed using correlative evaluation of the dynamic factors and their interactive impact in short and long run on this relation, based on time-series data of Pakistan from 1990 to 2019. The study results endorse the previous studies’ outcomes by recognizing that an increase in carbon emission depends on trade development, energy usage, economic development, and the logistics industry’s various components except for air logistics. However, study results show a unidirectional long-run causality directing from economic development, logistics industry, energy utilization, and trade development to carbon emission. Moreover, these results reveal that this emission is the leading factor to introduce stringent emission standards that further overlap with regional demographics trends, i.e., carbon emission implications. These findings imply that economic development applies a substantial demand-pull impact on national logistics, i.e., regional economic development directs to the growth of the logistics industry in the corresponding region. Consequently, high-income geographical regions have higher long-run risk concerning contemporary developmental activities of the logistics industry when adhering to carbon emission standards. Particularly, the influence of upcoming emission standards must be prioritized when planning the future returns of contemporary research and development activities of the logistics industry in a given geographic area, such as CPEC. Given Pakistan’s perspective, the proposed empirical analysis can be exampled to other developing countries. This analysis may facilitate the design and development of strategies for upcoming financial funding in the modern logistics industry to seek its sustainable development-goals in developing economies.

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.