This study investigates the influence of Internet retailing on carbon dioxide (CO2) emission in 77 countries categorized into developed and developing countries during the period of 2000-2013. To realize the aims of the study, a model that represents pollution is established utilizing the panel two-stage least square (TSLS) and the generalized method of moments (GMM). The results for both regressions similarly indicated that GDP growth, electricity consumption, urbanization, and trade openness are the main factors that increase CO2 emission in the investigated countries. Although the results show that Internet retailing reduces CO2 emission in general, a disaggregation occurs between developed and developing countries whereby Internet retailing has a significant negative effect on CO2 emission in the developed countries while it has no significant impact on CO2 emission in the developing countries. From the outcome of this study, a number of policy implications are provided for the investigated countries.
This study attempts to identify the optimum social marketing mix for marketing energy conservation behaviour to students in Malaysian universities. A total of 2000 students from 5 major Malaysian universities were invited to provide their preferred social marketing mix. A choice-based conjoint analysis identified a mix of five social marketing attributes to promote energy conservation behaviour; the mix is comprised of the attributes of Product, Price, Place, Promotion, and Post-purchase Maintenance. Each attribute of the mix is associated with a list of strategies. The Product and Post-purchase Maintenance attributes were identified by students as the highest priority attributes in the social marketing mix for energy conservation behaviour marketing, with shares of 27.12% and 27.02%, respectively. The least preferred attribute in the mix is Promotion, with a share of 11.59%. This study proposes an optimal social marketing mix to university management when making decisions about marketing energy conservation behaviour to students, who are the primary energy consumers in the campus. Additionally, this study will assist university management to efficiently allocate scarce resources in fulfilling its social responsibility and to overcome marketing shortcomings by selecting the right marketing mix.
Carbon dioxide emission is a high-profile issue that can affect both the human economy and human existence, but few scholars have studied the relationship between these two. Therefore, this study constructs the panel threshold regression (PTR) based on the National Bureau of Statistics of China's panel data from 2002 to 2019 in 19 regions. One of the advantages of PTR is to leverage segmented functions, allowing for a more detailed analysis of the data. Besides, by introducing the idea of a threshold, PTR can effectively avoid structural changes in the data. The different between this study and other research is that this study divides 19 regions into two parts: Eastern China and Central China. Based on that, this study researches and compares the different influences of the aging population on carbon emissions in these two regions. The results show that although the Environment Kuznets Curve has been confirmed in both Eastern China and Central China, with the development of the economy, the carbon emissions will increase in Eastern China and decrease in Central China, respectively. In addition, the key factors affecting carbon emissions in Eastern China and Central China are trade dependence and urbanization rate separately. Hence, this study suggests that the regional governments in Eastern China may guide and encourage more international trading companies to move to Central China, and at the same time, the regional governments in Central China should issue more policies to attract these companies, such as: reducing land lease fees and building better transportation infrastructure. Apart from that, the governments in Central China should vigorously increase the rate of urbanization to reduce energy consumption and improve energy efficiency.
Copper (Cu) tolerance was observed by endophytic fungi isolated from the carnivorous plant Nepenthes ampullaria (collected at an anthropogenically affected site, Kuching city; and a pristine site; Heart of Borneo). The fungal isolates, capable of tolerating Cu up to 1000 ppm (11 isolates in total), were identified through molecular method [internal transcribed spacer 4+5 (ITS4+5); ITS1+NL4; β-tubulin region using Bt2a + Bt2b], and all of them grouped with Diaporthe, Nigrospora, and Xylaria. A Cu biosorption study was then carried out using live and dead biomass of the 11 fungal isolates. The highest biosorption capacity of using live biomass was achieved by fungal isolates Xylaria sp. NA40 (73·26 ± 1·61 mg Cu per g biomass) and Diaporthe sp. NA41 (72·65 ± 2·23 mg Cu per g biomass), NA27 (59·81 ± 1·15 mg Cu per g biomass) and NA28 (56·85 ± 4·23 mg Cu per g biomass). The fungal isolate Diaporthe sp. NA41 also achieved the highest biosorption capacity of 59·33 ± 0·15 mg g-1 using dead biomass. The living biomass possessed a better biosorption capacity than the dead biomass (P