“一带一路”沿线省域生产性服务业与制造业联动融合关系辨析

选择"一带一路"沿线18个省域生产性服务业与技术或资本密集型装备制造业动态互动关系为研究对象,运用向量自回归(VAR)模型进行4个细分服务业和装备制造业脉冲响应比较研究,探究其双向互促性、行业异质性及长短期差异性。结果表明:二者虽然有长期均衡关系,但是互促作用具有非对称性。装备制造业对生产性服务业发展的总体拉动力强劲。但无论辅助联动式或价值链嵌入式生产性服务,都只是短期助推装备制造业发展,仍难以构成高端服务能力和发挥显著的规模经济效应,其长期匹配及推动作用较小。长期以来,装备制造业对知识密集型服务业需求程度不高,导致装备制造业对其拉动作用不明显,二者互动关联性较弱。不同互动机理及动态匹配方式下细分服务业与装备制造业互动效应差异性显著。装备制造业来自于自身内部的信息变动影响显著。应加强装备制造业创新投资引资、提升装备制造业产业集群创新竞争力、促使生产性服务业高质量发展、提高高层次人才培养引进效率,以促进沿线省域两大产业高层级耦合互动发展。     

MULTIDIMENSIONAL DYNAMIC RISK MEASURE VIA CONDITIONAL g‐EXPECTATION

This paper deals with multidimensional dynamic risk measures induced by conditional g‐expectations. A notion of multidimensional g‐expectation is proposed to provide a multidimensional version of nonlinear expectations. By a technical result on explicit expressions for the comparison theorem, uniqueness theorem, and viability on a rectangle of solutions to multidimensional backward stochastic differential equations, some necessary and sufficient conditions are given for the constancy, monotonicity, positivity, and translatability properties of multidimensional conditional g‐expectations and multidimensional dynamic risk measures; we prove that a multidimensional dynamic g‐risk measure is nonincreasingly convex if and only if the generator g satisfies a quasi‐monotone increasingly convex condition. A general dual representation is given for the multidimensional dynamic convex g‐risk measure in which the penalty term is expressed more precisely. It is shown that model uncertainty leads to the convexity of risk measures. As to applications, we show how this multidimensional approach can be applied to measure the insolvency risk of a firm with interacting subsidiaries; optimal risk sharing for ‐tolerant g‐risk measures, and risk contribution for coherent g‐risk measures are investigated. Insurance g‐risk measure and other ways to induce g‐risk measures are also studied at the end of the paper.     

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.     

服务型企业-员工互动关系管理:员工买入和雇主品牌化

伴随着内外部营销相结合的平衡视角的推广应用,员工得到更多关注和研究,而雇主品牌建设也成为重要议题.文章首先强调了服务业中员工的重要性.然后,主张在企业-员工互动关系管理中,一方面要鼓励员工买入-知识买入和情感买入,另一方面要重视雇主品牌化和提高雇主吸引力.     

基于“服务交互”视角“中国服务”的餐饮特色培育研究

培育中国特色的餐饮服务对于本土餐饮品牌的经营与发展意义重大。本文在"中国服务"的内涵基础上,阐明"中国服务"的餐饮特色的内涵与特征;明确使"中国服务"成为走向世界的、独具中国特色的服务品牌,是培育"中国服务"的餐饮特色的核心目标,也是餐饮业发展的长远之计;基于"服务交互"的视角,为培育"中国服务"的餐饮特色,打造中国特色餐饮品牌的管理实践提供方法指导。旨在为餐饮业服务品质的提升,尤其是为本土中高端餐饮品牌的健康发展提供有益的参考。     

Impact of auditory sense on trust and brand affect through auditory social interaction and control

Voice assistants—or voice-enabled artificial intelligence—have changed the way people interact with their surroundings dramatically. Utilizing an enactive view of social cognition theory, this study demonstrates how voice assistants can act as [semi] autonomous agents to hold instantaneous social interactions with consumers. This research employed two experimental studies. Study 1 used two voice assistant mobile applications, Microsoft Cortana and Google Assistant, and Study 2 used Amazon Alexa and Microsoft Cortana. The contributions this paper makes are two-fold. First, the results illustrate how perceived auditory sense drives perceived auditory control through auditory social interactions with a voice assistant that lead to brand affect and consumers’ trust in the voice assistant. Second, results shed light on the role of surprise as a repelling drive that attenuates the effect of perceived auditory control on brand affect.     

Nicknames as identity badges: How self-reflective nicknames can facilitate users’ online social interactions

An Internet nickname is essential in facilitating online interpersonal interactions. It is a pivotal element of interaction that provides other users with an initial impression and affects the decisions and behaviors of users during their online interactions. Although the existing literature has found that nicknames are relevant to users’ psychology and behavior, direct research on the motivation for and the effect of choosing a particular Internet nickname has been very limited. Borrowing from relevant theories on avatars, this paper summarizes the motivations behind Internet nickname choices in terms of three aspects: virtual exploration, social navigation and contextual adaptation. Moreover, from the perspective of collective self-esteem (CSE) and group identification, this research explores the influence mechanism between the motivations underlying Internet nickname choices and users’ online social interactions. A total of 394 samples were obtained from online communities in China to test our research model. We found that virtual exploration, social navigation and contextual adaptation are three motivations for creating Internet nicknames, and they have direct effects on the online social interactions of users. CSE has a full mediating effect between virtual exploration and online social interaction and acts as a mediated variable between social navigation and online social interaction. Group identification fully mediates the relationship between social navigation and online social interaction as well as that between contextual adaptation and online social interaction. The conclusion of this paper provides not only a new perspective for the study of Internet nicknames but also a potentially feasible way to stimulate users’ online social interactions.     

A neural network based price sensitive recommender model to predict customer choices based on price effect

The impact of price and price changes should not be ignored while designing algorithms for predicting customer choice. Consumer preferences should be modeled with consideration of price effects. Businesses need to consider for efficient prediction of an individual's purchase behaviour. Personalized recommendation systems have been studied with machine learning algorithms. However, the price-aware personalized recommendation has received little attention. In this paper, we attempt to capture insightful economic results considered in the marketing and economics disciplines by employing modern machine learning architecture for predicting customer choice in a large-scale supermarket context. We extract personalized price sensitivities and examine their importance in consumer behaviour. The employed data collected from a supermarket chain in Germany consists of implicit feedback based on customer-product interactions and the price of every interaction. We propose a two-pathway matrix factorization (2way-MF) model that is price-aware and tries to memorize customer-product interaction's implicit feedback. The proposed models achieve better model performance than standard Matrix Factorization models widely used in the industry. The approach was re-validated with data from supermarket chain in Taiwan. Other industries can adopt the proposed framework of modeling customer's preferences based on price sensitivity. We suggest that further research and analyses could help understand the cross-price elasticities.     

Social capital,user motivation,and collaborative consumption of online platform services

Collaborative consumption is broadly defined as sharing, obtaining, and giving access to products and services through peer networks online. As it is expected to resolve the societal and environmental problems, quite a few studies investigated consumers’ motivations that lead to positive attitudes and intention for collaborative consumption. This paper aims to study the determinants that motivate participants to perceive a positive attitude towards collaborative consumption focusing on three salient traits of social capital (shared goal, social interaction tie, and norms of reciprocity). The study found that social capital exerts a more substantial influence on intrinsic motivation (enjoyment and sustainability) than extrinsic motivation (economic benefit). The study also found that different social capital traits display different effects on motivation. In particular, the shared goal was a key determinant of both intrinsic and extrinsic motivation. And all three motivations positively affect collaborative consumption attitudes.     

Managing interaction for learning and value creation in exchange relationships

Firms create value by establishing and maintaining appropriate exchange relationships. However, beyond the generally recognized importance of trust and commitment, there is a lack of specific cues as to how such value creation can be managed. In an attempt to gain more insight this study examines the success formulas in three different types of interactions in exchange relationships. The purpose is to investigate how different types of interactions can be managed so that buyer firms make important contributions to the development of their suppliers' capabilities. The study empirically examines how inter-organizational management facilitates value creation in three different types of interactions in exchange relationships: unilateral learning, unilateral development, and bilateral learning. This study uses a partial least squares analysis (PLS) to analyze survey data from 142 exchange relationships in the seafood industry. The main contribution to the literature is the assessment of how various types of inter-organizational management promote value-creation initiatives (such as information supply and coaching), and ultimately, value creation.