Labor productivity forecasts based on a Beveridge–Nelson filter: Is there statistical evidence for a slowdown?

In this paper, I assess the evidence for a structural break in labor productivity growth in the years before the Great Recession with the use of out-of-sample forecasting exercises for the years 2010 to 2019 and the recently developed Beveridge–Nelson filter. Models based on a Beveridge–Nelson filter with no structural breaks outperform those allowing for a structural break, and there is statistically significant evidence that they outperform the random walk, though all models were too optimistic about labor productivity growth. Recently developed statistical tests do point to the presence of a structural break before the Great Recession, but uncertainty about the data-generating process for labor productivity growth or the timing and magnitude of the break may be too great to be helpful in forecast preparation.     

Alternative balanced scorecards built from paradigm models in strategic HRM and employment/industrial relations and used to measure the state of employment relations and HR system performance across U.S. workplaces

This paper constructs alternative balanced scorecards based on high‐performance work system (HPWS) and employment relations system (ERS) models. The models are depicted and compared in diagrams and used as framework skeletons for building separate HPWS and ERS scorecards, intended to provide a detailed data picture of the operational health and performance of an organization's employment/HR system and its operations, processes, and inputs/outputs. The scorecards are filled in with nationally representative data from 2,000+ U.S. workplaces using more than 50 employment/HR indicators, as reported by separate panels of managers and employees. The indicators for each workplace are aggregated into an overall HR/employment system score, ranked from low‐to‐high, and graphed as frequency distributions. These distributions provide a unique snapshot picture of the mean and dispersion of the state of employment relations and HR system performance for companies across the United State. They also reveal that “models matter” since the HPWS and ERS scorecards provide distinctly different evaluation assessments.     

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.     

Stock market volatility forecasting: Do we need high-frequency data?

The general consensus in the volatility forecasting literature is that high-frequency volatility models outperform low-frequency volatility models. However, such a conclusion is reached when low-frequency volatility models are estimated from daily returns. Instead, we study this question considering daily, low-frequency volatility estimators based on open, high, low, and close daily prices. Our data sample consists of 18 stock market indices. We find that high-frequency volatility models tend to outperform low-frequency volatility models only for short-term forecasts. As the forecast horizon increases (up to one month), the difference in forecast accuracy becomes statistically indistinguishable for most market indices. To evaluate the practical implications of our results, we study a simple asset allocation problem. The results reveal that asset allocation based on high-frequency volatility model forecasts does not outperform asset allocation based on low-frequency volatility model forecasts.     

零售企业敏捷供应链系统CSS-SCM的研究

供应链核心在于实现供应链环节中的信息沟通，数据互换和协同工作，改造和整合企业的业务流程，因此供应链系统模型应该具有动态可重构的特点，系统主体的构成也应反映这种思想，在系统中引入“大规模定制”，“工作流”的新思想和“异构系统兼容”，“通用报表”以及“三层架构应用体系及开发手段”等新技术将使供应链系统更为“敏捷”。     

From the margins: globalization with(out) home economics

Pies and peas, noughts and crosses, fish and chips, chicken and egg, teaching and learning, home economics and . . . globalization? In psychotherapy, this simple technique of providing a word and another automatically coming to mind is called free association and some of the internationally accepted pairings are noted above. Do we want ‘home economics’ and ‘globalization’ to have an automatic association? In this paper, I argue that home economics must make a shift from the margins of patriarchy by re‐thinking the ways in which the field is legitimized and positioned if it is to be a key player in taking on the challenges and dilemmas raised by globalization.     

A conceptual framework of anonymity in Group Support Systems

As the development and use of automated systems for collaborative work grows, the need for a better understanding of these systems becomes more important. Our focus is on one type of system, a Group Support System (GSS) and, in particular, on one important aspect of a GSS—anonymity. A conceptual framework for the study of anonymity in a GSS is presented, which describes the general classes of variables and their relationships. These variables include the factors that influence anonymity in a GSS, types of anonymity, and the effects of anonymity on a message sender, receiver, group process, and outcome. Each of these variables is discussed with working propositions presented for important group process and outcome measures. The objectives of this article are to highlight the importance and complexity of anonymity, to act as a guide for empirical investigations of anonymity, and to influence future GSS development and use.     

Working While the World Sleeps: A Consideration of Sleep and Shift Work Design

The evolution of society and economic pressure has provided the impetus for operating on a 24-hr basis in many industries. This has occurred with relatively little attention toward sleep deprivation and related problems facing shift workers and the organizations employing them. This paper first documents the move toward shift work and some sleep problems associated with it. We then describe sleep disorders that impact job performance. Next, we describe alternative schedules and give suggestions for shift work implementation. Finally, we offer some normative advice regarding the treatment of shift employees.     

Advertising,Price and Quality in Self–regulating Professions: A Survey

This paper surveys the theoretical and empirical literature on the relationship between advertising, fees and quality in the self–regulating professions. Much of the literature is derived from the perspective of advertising as an information–enhancing device, helping to reduce the information asymmetry between professional and client. This is consistent with the majority of the empirical studies which suggest that advertising tends to have a downward effect on professional fees, with little if any adverse effect on quality. There are, however, important issues of method and measurement which may lessen the force of this conclusion     

把握新生的特点加强工作的针对性

新生具有自豪感减退、心态失衡、适应环境的能力差、学习上的盲目性等特点.做好新生工作必须具体分析、因材施教,深入了解、勤于疏导,健全制度、规范管理.