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.     

Institutional context as a moderator of the relationship between board structure and acquirer returns

The objective of this paper is to contribute to the understanding of the supervisory role of the board of directors in the context of mergers and acquisitions (M&As). We focus our study on the European case, for which there is no previous exhaustive evidence on this topic. Using information on 985 mergers and acquisitions carried out over the period 2003–2016 by companies in the major European countries, we analyze the influence of supervisory capacity of the board (small size, higher proportion of outsiders and separated Chairperson-CEO positions) on acquirer returns, differentiating between Anglo-Saxon and continental European contexts. Our results confirm that the effectiveness of corporate governance practices depends strongly on their fit with the broader institutional context. Specifically, we find that a smaller size of the board of directors and the separation of the positions of Chairperson and CEO lead to higher acquirer returns in European Anglo-Saxon countries. By contrast, we do not find evidence that any proxy of supervisory capacity of the board significantly improves acquirer returns in the rest of countries.     

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.     

Social Scientific Explanations?

Generally valid scientific explanations of observable social phenomena are still hardly available. By applying philosophical insights generated by Quine and derived from semiotics to social research methodology three kinds of context dependencies accompanying theory formation within social science are identified. The third context dependency is mostly not attended in theory formation about social phenomena thereby producing a ``connotation fallacy', which leaves almost all social theories undetermined and fallible. These context dependencies should be taken into account in the research design and be tested for using statistical criteria comprising a new methodology presented in this article.     

Optimising a Probabilistic Model of the Development of Play in Soccer

We present a probabilistic model based on the one developed by Hernández Mendo and Anguera (Revista de Psicologíca Social, 16(1), 71–93, 2001). Here we have tried to break down the interaction contexts that the opposing teams are able to generate and transform during the game. We are aware that a given player or team does not produce consistent behaviour in similar situations. However, a degree of uncertainty is assumed to exist regarding whether the results obtained are a specific function of the analysis used. In order to carry out this research a category system which optimized that used in the previous model was developed. This system should enable the interaction between teams to be observed within the actual play of a soccer game. A lag sequential analysis was performed on the basis of a coding of the behavioural flow. After describing the behavioural patterns obtained a probabilistic model of the development of play in soccer is proposed.     

Connecting ‘talent’ meanings and multi-level context: a discursive approach

Abstract

Through an in-depth, multilevel case study of a professional services firm, this paper illuminates what stakeholders mean when they use the term ‘talent’. The paper underlines how various contextual factors including, workforce composition, ownership structures and individual perceptions influence talent meanings within an organisation. Our analysis of talent phenomena at a multiplicity of levels illustrates that it is not only about the words, phrases, and terms employed when talking about talent that requires examination. There is a need to deliberate on the meanings that underpin the talk because while stakeholders may talk the same way they may mean different things. The paper makes a key theoretical contribution through specific recognition of the importance of thoughtful reflection of how stakeholders discursively construct meanings because ‘talent’ is a concept, which requires translation via talk to become meaningful within the material world and these meanings are influenced by context. Thus, we cannot infer, that talent meanings radiate within organisations, nor across organisational boundaries, industries or countries because discourses arise and materialise within specific contexts and we must acknowledge that talent discourses can not be removed from the context in which they operate.