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.     

External pressure or internal culture? An innovation diffusion theory account of small retail businesses’ social media use

COVID-19 put unprecedented external pressure on small businesses to adopt or increase use of social media while not all small businesses are internally ready for this rapid change. This study investigated the roles of external pressures and organizational culture of openness and learning in driving small retail business owners'/managers' social media use decisions by impacting their perceived usefulness and barriers, based on the innovation-decision process model from the diffusion of innovations theory and the theory of reasoned action. An online survey with structured measurements was administered to 411 U.S. small retail business owners/managers. Results from structural equation modeling revealed that external pressures positively influenced small business owners'/managers’ perceived usefulness and barriers and social media use intention. In addition, the culture of openness and learning positively influenced the perceived usefulness while mitigating the perceived barriers, thereby directly and indirectly influencing the social media use intention. Theoretical and managerial implications are discussed.     

时间压力对网络冲动性购买的影响研究：交易效用和感知风险的调节

以往关于时间压力对冲动性购买影响的研究结论具有两面性，即促进或抑制。文章引入交易效用和感知风险两个调节变量，通过两个实验探讨了时间压力对网络冲动性购买倾向影响的边界条件。首先，当交易效用较高时，时间压力的增加会导致其网络冲动性购买倾向的提高；而当交易效用较低时，时间压力的增加会导致其网络冲动性购买倾向的降低（实验一）。其次，当人们感知风险较低时，时间压力的增加会导致其网络冲动性购买倾向的提高；而当人们感知风险较高时，时间压力的增加会导致其网络冲动性购买倾向的降低（实验二）。研究结论可以帮助电商企业进一步了解消费者的冲动性购买行为，充分利用时间压力的影响，制定更灵活有效的促销策略。     

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.     

摩托车单向器自动装配机气动系统设计

针对当前摩托车单向器组件主要采用手工装配、装配效率低、随机性大、无法对装配过程实现有效管理控制的情况,为了易于对零件装配过程进行实时监测和提高生产效率,开发了一种智能摩托车单向器自动装配机。介绍了摩托车单向器自动装配机的上料系统、装配系统、检测系统和落料系统的机械结构,重点阐述了设备的气动系统设计,并进行了实验研究。结果表明,该设备可实现组成单向器的5种零件自动上料和装配,同时降低了操作人员的劳动强度,生产效率提高约50%。其气动系统噪音小、工作可靠,可应用于摩托车单向器的大批量生产。研究结果可为其他相似异形零件自动装配机的开发提供参考。     

对群众体育锻炼中，如何合理安排运动量的探讨

本文在体育锻炼能够增强体质，提高健康水平的生物学基础上和群众体育锻炼与专业训练的区别上，提出群众体育锻炼中如何合理安排运动量。     

石化企业乙烯物料平衡的实例分析

乙烯物料平衡是石化企业的主要物料平衡之一，由于乙烯衍生物的装置较多，影响石化企业乙烯物料平衡的因素也多。在分析了S企业的四个实例后，可以看出，搞好乙烯的物料平衡工作，可以提高乙烯下游装置的开工率和负荷率，从而提高企业的经济效益。     

Accrual accounting and Australian fiscal policy

Australian governments have recently moved from cash accounting to accrual accounting. Accrual accounting has been accompanied at the national government level by the introduction of a new key fiscal policy measure: the ‘fiscal balance’. This paper explains and evaluates this new fiscal measure. It concludes that, given the present fiscal policy of the Australian government, fiscal balance is a superior fiscal policy measure to the ‘cash’ budget balance measure which it replaced. However, from the alternative ‘golden rule’ policy standpoint, fiscal balance is not a meaningful fiscal policy measure — although its stock counterpart, net financial liabilities, certainly is.     

近10年日本宏观经济的理论分析与展望

近10年日本经济停滞不前，一方面对外经济状况不佳：日元对美元汇率技术下跌。且不断加剧；出口增长放缓，贸易顺差连续下滑，另一方面国内宏观经济状况严峻；失业率不断上升，内需不振；通货紧缩逐步加深；工业增长持续低迷，工业生产与效益下降，究其原因，用内外均衡模型理论分析得出，日本经济没有达到均衡的0点，内外均衡遭到了破坏，而展望今后的日本经济和日元走势，基于日本财政状况的恶化及货币政策的失效，估计还不会导致资本的大量外流。也不会对资本流动产生重要的影响，而结构改革也将可能引致日元升值。