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.
China is the largest producer of cotton crop, followed by the United States of America. China's 52% cotton is produced in Xinjiang Region. The agricultural sector depends on the climate, and it is substantially susceptible to future climate changes. Climate factors directly affect cotton production and, therefore, assessing the influence of these factors on the cotton output is imperative. This study empirically investigated the relationship between climate and non-climate variables on Xinjiang Region's cotton production over the last three decades. To this end, an econometric technique was employed and the "Autoregressive Distributed Lag Model" (ARDL) was used to analyze the long-run and short-run relation between the selected variables. Empirical results revealed that a 1% decrease in average temperature, labor force, and rainfall could decrease cotton production by 0.18, 1.94, and 0.18%, respectively, due to the significant negative relation. However, this study depicted 1% rise in average temperature, technological changes, and the cultivated area will increase cotton production by 0.07, 0.05, and 0.23%, respectively. In conclusion, the regional climate changes significantly affect cotton crop. Although the study analyzed the data from XUAR Region, this model can be applied to all developing countries. This research helps the policymakers and the respective government department to introduce, promote, and subsidize environment-friendly production inputs and make the long-term plan for farmers and stakeholders to educate, spread awareness, and help to adopt new skills to gain sustainable regional cotton productivity.
With the rapid development of electric vehicles (EV), more and more EV batteries will intensively face the retirement. If they are treated improperly, EV batteries might pose a serious threat to human health and environment. Therefore, recycling spent EV battery is full of significance. However, the recycling system and specific policies have not be well established in China. This paper aims to evaluate several recycling subsidy policies being considered and tested in China for their influences on recycling effect and economic benefits. We first establish a system dynamics model with game characteristics to describe and analyse the triple-channel (i.e. manufacturer, retailer, and third-party recycler) recycling system. Recycling subsidy policy and technological progress are then introduced. The game equilibrium and evolution of the system under different scenarios are investigated. Results show that: 1) both recycling subsidy and advancement in technology could improve total recycling rate and profit. 2) Particularly, the former can improve recycling rate of manufacturer while the latter can raise the interest of retailer and third-party recycler in spent EV battery recycling. 3) Even with gradual withdrawal of recycling subsidy, the system could still maintain steady growth as long as the technology advances to a higher level. The results could provide support to manufacturer in managing the multi-channel recycling system and the government agencies in optimizing the recycling policy. The hybrid method, game theory combined with system dynamics, can improve the limitations of these two methods and can be applied to other complex systems with game traits.
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