组织信息化环境下知识流动对组织创造力的影响

通过解析知识流动和组织信息化环境的内部构成，探究知识溢出/知识扩散、高管支持/ICT应用对组织创造力的差异性影响，以及不同组织信息化环境对知识流动与组织创造力关系的调节作用。利用信息化程度较高的企业数据，使用层级回归分析进行实证检验。结果表明：组织创造力受知识流动的正向影响，知识扩散对其的正向影响更强；组织信息化正向影响组织创造力，相比ICT应用，高管支持对组织创造力的正向影响更强；高管支持在知识溢出/知识扩散与组织创造力之间的正向调节作用显著；ICT应用对知识扩散与组织创造力的强化作用显著强于对知识溢出与组织创造力之间的调节作用。     

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.     

Some Potential Linkages for Input-Output Analysis with Flow-of-Funds

Three major, interrelated accounting statements, at the frontiers of quantitative economic analysis, are three interrelated systems, namely: (1) National income and product accounts (NIPA), (2) The input-output tableaux, (IO), and (3) flow-of- funds accounts (FF). The third-mentioned system is somewhat less available and used in only limited areas of macroeconomic analysis. This paper is mainly concerned with use of FF accounting systems. This system shows where financial resources originate, and where they go in support of real capital formation. In this respect, interest rates and other market-based financial rates are of key importance. While much macroeconomic analysis is based on the rates that fit the yield curve, showing the interest rate structure over various maturities of debt associated with a given degree of risk. In contrast, the FF accounts throw light on the whole spectrum of interest rates, across maturities and debt qualities. For example, in analysis of the real estate market and funding of capital formation there, it is important to have a full understanding of the course of mortgage rates of different maturities and qualities. In short, it is necessary to develop a full appreciation of supply and demand forces in the mortgage market, which often is not obviously related to movements of the operative rate for monetary policy, such as very short-term inter bank rates or call money rates. This paper attempts to provide material from the flow-of-funds accounts that would make it possible to analyze the movement of relevant mortgage rates or whatever other rates are needed to understand the financing of capital formation in real estate.     

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.     

现金流对上市公司投资行为的影响分析

本文采用实证方法，检验我国上市公司融资约束、现金流与投资决策之间的关系。以沪深300指数样本上市公司为基础，结合面板数据和时间数据，利用线性回归方法检验公司投资行为与现金流量、营业收入、负债率、托宾Q等财务指标的关系，并进一步分析上市公司的投资与现金流量等指标的敏感性。     

知识型员工流动动因分析

知识型员工的流动受多种因素的影响，如年龄、性别、知识拥有水平、工作满意度、薪酬水平、组织承诺、工作自主性、职业发展等。本文从经济学和组织行为学的角度分析了知识型员工流动影响因素，对知识型员工的流动动因进行理论分析。