Economic forecasting with evolved confidence indicators

We present a machine-learning method for sentiment indicators construction that allows an automated variable selection procedure. By means of genetic programming, we generate country-specific business and consumer confidence indicators for thirteen European economies. The algorithm finds non-linear combinations of qualitative survey expectations that yield estimates of the expected rate of economic growth. Firms’ production expectations and consumers’ expectations to spend on home improvements are the most frequently selected variables – both lagged and contemporaneous. To assess the performance of the proposed approach, we have designed an out-of-sample iterative predictive experiment. We found that forecasts generated with the evolved indicators outperform those obtained with time series models. These results show the potential of the methodology as a predictive tool. Furthermore, the proposed indicators are easy to implement and help to monitor the evolution of the economy, both from demand and supply sides.     

现代电子商务给企业信息管理带来的机遇与挑战

物联网、移动互联网和云计算为现代电子商务的发展带来了不可多得的机遇。电子商务有助于企业在提高企业信息管理水平方面获得长足进步。而凭借全球最大的互联网和移动互联网网民数量,中国势必在不久的将来出现类似腾讯、百度的全球性互联网巨人。     

商务英语专业创业教育与专业教育一体化研究

本文研究商务英语专业创业教育融入专业教育的有效途径,改进教师教学理念及方法,优化课程设置,构建基于内容依托教学的创业教育与专业教育一体化有效模式。     

High-growth recoveries, inventories and the Great Moderation

We present evidence about the disappearance of the high-growth recoveries from recessions with intense job creation typically observed until the eighties. This result matches the belief that recessions now have an L-shape as opposed to the old-time recessions that always had a V-shape. We also show how this change in business cycle dynamics can explain part of the Great Moderation. We postulate that these two phenomena may be due to changes in inventory management brought about by improvements in information and communications technologies.     

Applicability of the M5 to Forecasting at Walmart

The M5 Forecasting Competition, the fifth in the series of forecasting competitions organized by Professor Spyros Makridakis and the Makridakis Open Forecasting Center at the University of Nicosia, was an extremely successful event. This competition focused on both the accuracy and uncertainty of forecasts and leveraged actual historical sales data provided by Walmart. This has led to the M5 being a unique competition that closely parallels the difficulties and challenges associated with industrial applications of forecasting. Like its precursor the M4, many interesting ideas came from the results of the M5 competition which will continue to push forecasting in new directions.In this article we discuss four topics around the practitioners view of the application of the competition and its results to the actual problems we face. First, we examine the data provided and how it relates to common difficulties practitioners must overcome. Secondly, we review the relevance of the accuracy and uncertainty metrics associated with the competition. Third, we discuss the leading solutions and their implications to forecasting at a company like Walmart. We then close with thoughts about a future M6 competition and further enhancements that can be explored.     

Evaluating quantile forecasts in the M5 uncertainty competition

Probabilistic forecasts are necessary for robust decisions in the face of uncertainty. The M5 Uncertainty competition required participating teams to forecast nine quantiles for unit sales of various products at various aggregation levels and for different time horizons. This paper evaluates the forecasting performance of the quantile forecasts at different aggregation levels and at different quantile levels. We contrast this with some theoretical predictions, and discuss potential implications and promising future research directions for the practice of probabilistic forecasting.     

高等商学教育国际标准的变化趋势——AACSB新标准对中国商学教育的启示

介绍了AACSB标准变化情况,通过对AACSB新旧标准的对比研究,分析高等商学教育国际标准的变化趋势,指出未来我国的商学教育发展需要强调创新与特色、重视教学与科研的平衡与联系、重视学术与实践的联系、重视社会影响与商业伦理.     

从一则商业秘密纠纷谈竞业禁止的必要性

本文从一起医药行业的商业秘密纠纷案谈起,详细分析了商业秘密保护与劳动权的冲突与协调、竞业禁止的正当性与必要性等问题,肯定了应将补偿金视为竞业禁止合同的有效要件。在充分强调研发和创新的制药行业,运用好竞业禁止具有非常深远的意义,因为只有实现商业秘密权和劳动者就业权的利益平衡才能保证行业健康发展。     

Entering the mobile service market via mobile platforms: Qualcomm's BREW platform and Nokia's Preminet platform

The mobile telecommunication market has evolved from simple voice to multimedia services. In the past, the primary players in mobile services were local operators in different countries; international telecommunication vendors, such as Qualcomm and Nokia, were seldom involved in the mobile service market. In order to enter this market, Qualcomm and Nokia have separately introduced their mobile application platforms, called respectively BREW and Preminet. This paper examines how the two companies attempt to share the mobile service market through their mobile platforms and internationalized business models. This paper also analyzes their mobile platforms’ business models and their strategic implications.     

Analysis of sectoral credit default cycle dependency with wavelet networks: Evidence from Turkey

In this paper, we investigate the relationship between industrial production and sectoral credit defaults (non-performing loans ratio) cycle by wavelet network analysis in Turkey over the period January 2001–November 2007. We use feedforward neural network based wavelet decomposition to analyze the contemporaneous connection between industrial production cycles and sectoral credit default cycles at different time scales between 2 and 64 months. The main findings for Turkey indicates that industrial production cycles effect the sectoral credit default cycles at different time scales and thus indicate that the creditors should consider the multiscale sectoral cycles in order to minimize credit default rates.