Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.     

The scope and scale of the informal food economy of South African urban residential townships: Results of a small-area micro-enterprise census

Growing urbanisation in South Africa is reflected in burgeoning Working class and informal township settlements on the fringes of its major towns and cities. Paired with this is an increasing reliance on cash as the primary means of economic transaction, which has in turn stimulated the growth of micro-enterprise business activities within the township context. This article discusses the findings of an eight-township small-area census which occurred between 2010 and 2013 in Cape Town, Johannesburg, Ekurhuleni and Durban townships representing 250 000 residents. The researchers were able to establish the scope and scale of informal food and drink retailing in these localities. Of the 10 049 micro-enterprises located in the study, some 3966 (or 39% of the total) trade in food. These include enterprises in primary production, fresh produce retailing, grocery retailing from house and spaza shops, and informal foodservice enterprises. Food is the basis for much township informal business and plays an important role in making food increasingly affordable and locally accessible, and in creating cash employment. The article builds on the knowledge base of the township informal economy role in bolstering food security needs for the marginalised.     

后疫情下休闲体育产业高质量发展的推进策略

新冠疫情以来,人们的健康意识觉醒,体育产业越来越受重视,本文通过对疫情期间体育产业受到的影响进行分析,从体育消费、体育产品中小企业、体育赛事几个方面阐述了疫情以来体育产业受到的阻碍。凡事都有两面性,疫情也为体育产业带来了新的机遇,"线上+线下"融合、新兴产业的崛起、人们健康意识的加强都因为疫情带来了新的发展动力。在后疫情时代,政府应该推出新的政策与措施鼓励体育产业发展,市场则应该抓住机遇实现体育产业的供给侧改革,通过与新兴产业、互联网等的结合,推动体育产业的转型升级。     

The impacts of value chain upgrading on the export of processed food

Upgrading in global value chains (GVCs) is an important path for developing countries to move along to capture higher benefits. Several qualitative studies of GVCs have identified two main upgrading types: economic (product, process, functional, and inter-sectoral) and social upgrading. The upgrading concept is widespread in productive sectors such as processed food, which has become a key export for developing countries. However, they have confronted multiple product standards required by global buyers. This study uses a case study of Thailand’s processed food exports (TPFEs). Although Thailand is a leading exporter of processed food, the country needs to upgrade in many areas related to production to meet global product standards and requirements. If Thailand fails to comply with global product standards, it will lose its export competitiveness. This study uses a gravity model to evaluate the impact of economic and social upgrading (EUP and SUP) on TPFEs. Our results show that upgrading types are significant in TPFEs, particularly for exports to developed countries. Process upgrading has a negative impact on TPFEs because of increased production costs to comply with product standards. However, process upgrading can lead to increased producers’ and exporters’ knowledge about how to comply with international standards. Consequently, process upgrading exhibits a lagged positive effect on TPFEs.     

经济新常态下煤炭企业发展战略研究

着眼于当前我国煤炭企业的新环境,我们要转变视角,致力于探索推动我国煤炭行业发展的新途径和新方法,为了更好地保护矿工的合法权益,保障煤炭行业的可持续发展,煤炭企业需要引进一些创新性技术和先进管理理念。论文主要基于关心矿工生命安全和煤炭企业安全发展的角度,对目前我国煤炭企业的发展提出一些思考和策略。     

基于GM(1,1)模型的造纸业上市公司财务研究——以冠豪高新为例

财务风险是企业调整发展战略、提升管理水平的重要参考指标之一。财务风险预测模型的建立能够预测企业在中短期内的财务风险,为企业敲响警钟。以造纸业上市公司冠豪高新为例,选取近五年财务杠杆系数为风险指标,建立GM(1,1)风险预测模型,结果显示该公司短期内财务风险呈下降趋势,调查发现这主要得益于产品成本的降低以及营销策略的改变。     

Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities

Artificial intelligence (AI) has captured substantial interest from a wide array of marketing scholars in recent years. Our research contributes to this emerging domain by examining AI technologies in marketing via a global lens. Specifically, our lens focuses on three levels of analysis: country, company, and consumer. Our country-level analysis emphasizes the heterogeneity in economic inequality across countries due to the considerable economic resources necessary for AI adoption. Our company-level analysis focuses on glocalization because while the hardware that underlies these technologies may be global in nature, their application necessitates adaptation to local cultures. Our consumer-level analysis examines consumer ethics and privacy concerns, as AI technologies often collect, store and process a cornucopia of personal data across our globe. Through the prism of these three lenses, we focus on two important dimensions of AI technologies in marketing: (1) human–machine interaction and (2) automated analysis of text, audio, images, and video. We then explore the interaction between these two key dimensions of AI across our three-part global lens to develop a set of research questions for future marketing scholarship in this increasingly important domain.     

Consequences of a green image of drone food delivery services: The moderating role of gender and age

Drone food delivery services play a significant role in protecting the environment, because the services are operated by batteries that can be charged with electricity. Therefore, this study tried to examine a green image in the context of drone food delivery services. More specifically, this study proposed that a green image of drone food delivery services plays an important role in the formation of attitude toward using the services. In addition, it was hypothesized that the attitude has a positive influence on behavioral intentions including intentions to use, word‐of‐mouth intentions, and willingness to pay more. Lastly, the moderating role of gender and age was proposed during the theory‐building process. A theoretical model, which included 12 hypotheses, was developed and tested using a total of 427 samples collected in Korea. The data analysis results showed that a green image of drone food delivery services has a positive influence on attitude toward using the services, which in turn positively affects three subdimensions of behavioral intentions. Furthermore, gender and age played partly as a moderator. The current paper was the first to study the green image of drone food delivery services, so the findings of this study mean a lot to the theoretical aspect.