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 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.     

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.     

跨越竞争丛林与范式重构：全球治理改革进程中的疫苗产业创新治理

疫苗作为新冠疫情防控的最关键手段之一，已在各国抗疫中发挥积极影响。疫苗研发、生产、注射意愿以及全球分配的公平性与可及性等一系列问题日益受到世界关注。分析全球治理改革中，疫苗作为一种全球公共产品的创新治理问题，讨论疫苗产业发展特征与创新规律演化，剖析西方国家疫苗产业创新治理困境以及“竞争丛林”逻辑，阐释中国行动方案及对全球治理改革的贡献。最终提出疫苗产业创新治理机制对推动全球治理改革的政策含义。     

Cross-border exchanges and volatility forecasting

We test for the performance of a series of volatility forecasting models (GARCH 1,1; EGARCH 1,1; CGARCH) in the context of several indices from the two oldest cross-border exchanges (Euronext; OMX). Our findings overall indicate that the EGARCH (1,1) model outperforms the other two, both before and after the outbreak of the global financial crisis. Controlling for the presence of feedback traders, the accuracy of the EGARCH (1,1) model is not affected, something further confirmed for both the pre and post crisis periods. Overall, ARCH effects can be found in the Euronext and OMX indices, with our results further indicating the presence of significant positive feedback trading in several of our tests.     

The saving–investment correlation puzzle is still a puzzle

A number of simulation studies claim to have solved the Feldstein–Horioka puzzle by demonstrating that a high time-series correlation between saving and investment naturally arises from business cycle shocks. This paper uses panel data of saving and investment controlled for business cycle shocks to empirically test the significance of cyclical shocks — productivity, fiscal and the terms of trade shocks — in explaining a high saving–investment correlation. The estimation results reveal that conventional aggregate shocks only partially explain the high saving–investment correlation. Moreover, country differences in the size of the GNP and the non-traded sector do not significantly affect the saving–investment correlation. The saving–investment correlation puzzle remains a puzzle after all.     

Parallel sourcing and supplier performance in the Japanese automobile industry

Japanese auto makers are reported to enjoy high supplier performance through long-term relationships, specific investments, and sole sourcing. Quality management consultants in the U.S. have been strongly advocating adoption of these practices. But economic and management theorists would predict that the combination of a high level of relationship-specific investments and sole sourcing will lead to problems with supplier performance. In fact the Japanese auto makers use a hybrid form of organization we term parallel sourcing. We present a transaction costs model that shows how parallel sourcing provides incentives for supplier performance associated with multiple sourcing while preserving claimed benefits of sole sourcing.     

Globalization, marketing resources, and performance: Evidence from China

Two important areas are underexplored in the relationship between marketing resources and performance. First, the subject has been primarily investigated in the context of Western countries, and inadequate attention has been given to emerging economies. Second, despite the recent growth in globalization, the moderating role of globalization on the link between marketing resources and performance has not been investigated. Addressing these important gaps, this article focuses on an emerging economy (China) and explores the moderating effect of globalization on this link. Specifically, the authors develop several hypotheses highlighting the moderating role of globalization activities (global product sourcing, global market seeking, and global partnership) on the link between marketing resources (market orientation, entrepreneurial orientation, and innovative capability) and firm performance. The findings of the moderating role of globalization provide several important implications for marketing theory development and managerial practice. Xueming Luo (luoxm@uta.edu) is an assistant professor in the Department of Marketing in the College of Business Administration at the University of Texas at Arlington. Before joining the University of Texas at Arlington faculty, he was on the faculty of the State University of New York at Fredonia. His research has appeared in various journals, including theJournal of Business Research, the International Journal of Research in Marketing, the Journal of Advertising Research, the Journal of Interactive Advertising, and Industrial Marketing Management. K. Sivakumar (Ph.D., Syracuse University; k.sivakumar@lehigh. edu) is the Arthur Tauck Professor of International Marketing & Logistics and a professor of marketing at Lehigh University. Prior to joining Lehigh in 2001, he spent 9 years at the University of Illinois in Chicago. His research interests include pricing, global marketing, and innovation management. His research has been published or is forthcoming in theJournal of the Academy of Marketing Science, the Journal of Marketing, the Journal of International Business Studies, Decision Sciences Journal, Marketing Letters, the Journal of Business Research, International Marketing Review, the Journal of Product Innovation Management, Pricing Strategy & Practice: An International Journal, Psychology & Marketing, and other publications. He has won several awards for his research (including theDonald Lehman Award) and is on the editorial board of several scholarly journals. He has won outstanding reviewer awards from two journals. Sandra S. Liu (liuss@purdue.edu) is an associate professor in the Department of Consumer Sciences and Retailing at Purdue University. She received her Ph.D. from the University of London, and her current research interest focuses on strategic marketing issues in the context of customer contact, including knowledge management in a corporation in transition and sales management in a knowledge economy. With her extensive industry experience, she has written a number of books and journal articles, which have appeared in theInternational Journal of Research in Marketing, the Journal of Business Research, theEuropean Journal of Marketing, Marketing Intelligence and Planning, among others.     

Rethinking the costs related to global warming: A survey of the issues

One approach to the economic analysis of global warming seeks to balance the costs of damage from or adaptation to it with the costs of mitigating it. The costs of adaptation and damage have been estimated using techniques of environmental evaluation, but are subject to a wide margin of uncertainty. The costs of mitigation, principally by reducing the emissions of CO₂, have been estimated using different kinds of economic models, some of the results of which have suggested that very little abatement of carbon emissions is justified before the costs of abatement exceed the benefits of it in terms of foregone damage and adaptation costs. The paper analyses the extent to which this conclusion is a function of the modelling assumptions and techniques used, rather than likely practical outcomes, with regard to the models' treatment of unemployed resources, revenue recycling, prior distortions in the economy due to the tax system and possible dynamic effects from the introduction of a carbon-energy tax. It concludes that, with different and arguably more appropriate treatment of the above issues, especially when the secondary benefits of reducing CO₂ emissions are also taken into account, it is not clear that even substantial reductions in the use of fossil fuels will incur net costs, especially if there is the prospect of even moderate costs from global warming.     

Combining biodiversity modeling with political and economic development scenarios for 25 EU countries

In the EURURALIS project, a chain of models was used to predict the changes in sustainable development indicators for European human well-being, ecology and economy issues, for four alternative scenarios of the future socio-economic development. This paper describes the biodiversity analysis of the project. Models based on general relationships between environmental factors and biodiversity loss were combined with socio-economic, land-use and environmental models to derive data that were integrated into an interactive tool for policy makers. The biodiversity analysis takes into account the effects of land-use change, climate change, fragmentation by major roads, area of unfragmented patches, nitrogen deposition, forestry and disturbance. Results show that biodiversity is projected to decrease between now and 2030 in most countries for all scenarios, indicating that it is unlikely that the EU will be able to fulfill its commitment to stop biodiversity loss by 2010. This is mainly due to urbanization and increase in stress factors, and outweighs the area increase of nature arising from land abandonment. Merits, limitations and uncertainties of this approach to biodiversity assessment are discussed.