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.     

A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

盾构机自动控制技术现状与展望

随着我国社会主义市场经济的迅速发展以及科技水平的不断提升,交通运输行业得到了蓬勃发展。当前,随着我国地下隧道等各项工程建设数量的不断上升,盾构机的重要性不言而喻。加强对盾构机自动控制技术的研究工作,不断解决该技术应用过程中存在的问题,才能有效地促进技术应用,为提升我国地下工程施工安全性能奠定技术支持。     

基于旅游者和日常访问者人群行为的城市型景区“共处”空间研究

针对城市型景区内旅游者和日常访问者相互影响的现象，提出“共处”空间概念，从“空间-行为”关系视角总结“共处”空间的时空特性，形成“共处”空间判别依据。基于计算机视觉技术，通过问卷调查，将人群行为划分为互不干扰、围观及参与、干扰及冲突3类，从空间优化与管理角度对列入公园年票体系中的城市型景区提出建议，梳理2类人群关系，提高游憩体验质量。     

我国港机CAD的应用与发展

港口装卸机械产品计算机辅助设计简称港机ＣＡＤ，本文介绍了港机ＣＡＤ１５年来发展的历程和取得的成绩，指出了港机ＣＡＤ今后的研究方向与课题。     

广州-茂名铁路换碴施工技术

文章介绍了有关在广州-茂名铁路运用大型养路机械进行更换石碴施工的技术和经验。     

论我国物流机械制造企业技术真空的形成及解决途径

阐述了当前我国物流机械制造业所面临的问题和现状,分析并提出了物流机械制造企业今后努力及其发展方向。     

组织愿景导航基业长青

本文回顾了理论界对一个组织或企业基业长青的探索过程 ,论述愿景与基业长青的关系 ,提出构建一个组织构建愿景的方法体系 ,内容包括“三个主题”、“四方面构架”和“五步骤操作”等。     

昌黎缝纫机零配件产业集群发展策略研究

产业集群作为一种新兴的经济发展模式和区域经济的基础特征,已经成为区域竞争优势的重要支点。本文介绍了昌黎缝纫机零配件产业集群的基本情况,指出了其发展过程中的一些问题,就此提出了发展策略。     

基于模糊控制的三相异步电动机的软起动系统

本系统主要通过对模糊控制器的设计 ,将异步电动机的起动电流既限制在了一定的范围内 ,又可得到较大的起动力矩。由于又采用了参数自调整作为辅助控制 ,不但改善了起动时的动态性能 ,而且改善了稳定运行时的静态性能