The new wave of AI-powered luxury brands online shopping experience: The role of digital multisensory cues and customers’ engagement

Academic literature retains a dearth of empirical evidence of the cutting-edge aspect of artificial intelligence (AI)-powered digital assistance and digital multisensory cues, despite the prospect of these factors on real-life customers' luxury brand online shopping experience. Thus, the aim of this study is to examine the significant pathway and effects of AI-powered digital assistance toward customers’ luxury brand online shopping experience. Drawing on S–O-R (Stimulus, organism, and response) and TRAM (Technology Readiness and Acceptance Model) paradigm, a multi-method research design was deployed to investigate constructs. Firstly, semi-structured interviews were utilized to explore customers' online behavior under the luxury brands and information technology aspect. Secondly, survey data were collected and analyzed by using partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The PLS-based analysis of quantitative data confirmed the exploratory insights of qualitative findings, establishing the connections of AI-powered digital assistance, customer engagement, and customers' luxury brand online shopping experience. Research findings also suggest that customer engagement plays a mediation role in the relationship between AI-powered digital assistance and customers' luxury brand online shopping experience. Besides, digital multisensory cues moderate the relationship between AI-powered digital assistance and customer engagement. Further, fsQCA complements the findings of PLS-SEM that reveal the significant combination of factors that lead to the perceptions of customers' luxury brand online shopping experience.     

城市基础设施与居民消费水平——基于线上线下协同的促进机制

优化城市基础设施对于提升居民消费水平具有积极意义。交通与通讯两类基础设施对居民线上、线下消费的影响存在差异。在普及网购的同时改善城市居民出行条件，使实体店在展示产品、现场体验等方面与电商形成互补，将有助于实现线上、线下渠道的积极互动。以2011—2016年全国近300个地级市构建的面板数据进行计量分析，验证了基础设施对居民消费的促进作用，并发现当前交通、通讯两类设施的交互作用主要体现为协同效应。进一步的研究表明，以完善基础设施支持线上、线下渠道共同发展，还能够适应居民家庭年龄结构变化的新特点。上述结论说明,以完善基础设施促成渠道协同，将对全面优化消费者体验、提升居民消费水平产生重要作用。     

网约车双边用户信任机制的构建研究

目前我国网约车行业呈迅速上升之势,但在发展过程中出现了很多亟待解决的问题。本文首先介绍了我国网约车行业的背景及其发展现状,然后概述了我国网约车行业的发展历程,接着应用案例分析法对滴滴出行案例的几个社会事件进行了分析,阐述了当前网约车行业所面临的问题,最后分别从监管、技术、价格三方面提出建立用户与平台之间基于制度、认知、计算三种信任的相关建议。     

欧盟视阈下在线平台中个人数据的增值税处理

近年来,在线平台的迅猛发展推动了全球经济数字化加速转型,但同时也引发了包括增值税政策适用在内的诸多挑战.通过研究《欧盟增值税指令》和欧州法院的判例法,以及分析个人数据与在线平台运行之间的关系可以推断出,个人数据是在线平台提供访问服务构成的增值税应税范围内的供应,且与消费者是否向在线平台支付金钱形式的对价无关.在实践中,使用客观价值方法来确定在线服务供应的应税金额存在实际困难,而使用直接联系标准解决易货交易问题,会导致增值税税基在本质上得到扩张.因此,建议当前不要将在线平台访问服务的供应视为一项应税交易.此外,对于商家为获得消费者数据而向平台付款的情形,因其不符合直接联系标准,也不应被视为服务对价.     

Drivers of consumer adoption of e-Commerce: A meta-analysis

E-commerce has significantly reshaped consumers’ shopping processes and habits. The need to understand the key drivers of online shopping has received keen attention and fueled a rich strand of studies. To help managers and researchers synthesize this growing body of evidence, we conducted a comprehensive meta-analysis to unearth the factors that influence consumers’ online shopping. Our main takeaways reveal that the most important drivers of online shopping (a) conform to the TAM and TPB theories, in addition to (b) website characteristics and past experience. In particular, the multiple predictors are strongly related to online purchase intentions and purchase behavior, where attitude and convenience show the strongest impact. Furthermore, moderator analyses indicate that cultural traits have specific moderating effects on the links between purchase intention and some of its drivers. For instance, power distance and uncertainty avoidance have a positive effect, while individualism, indulgence and masculinity have a negative one. Finally, we apply meta-analytic structural equation modeling to test a conceptual framework including four groups of drivers (consumer–channel interactions, website characteristics, social influence, and consumer characteristics) and different aspects of online shopping. The findings provide valuable insights for online shopping research and practice.     

Analyzing online reviews in hospitality: data-driven opportunities for predicting the sharing of negative emotional content

Hospitality is one of the sectors that are nowadays most heavily characterized by consumers’ tendency to share online reviews on dedicated digital platforms. While most past work has focused on understanding the effect of online reviews and ratings on consumers’ evaluation and purchase decisions, this research tackles the issue of what drives the sharing of certain types of online content. Specifically, we investigate the sharing of user-generated content characterized by negative emotional valence, and study the effect of two factors on the extent to which user-generated content contains negative emotions. One such factor is reviewer's expertise, while the other is hotel quality. Our analysis of 1200 TripAdvisor reviews on Italian hotels located in three major Italian cities confirm our hypothesis that expert reviewers might share reviews containing less intense negative emotional content compared to less expert reviewers especially when the hotel is of high quality. To support our hypothesis, we build on the research on psychological antecedents of word-of-mouth behaviour suggesting that expert consumers are particularly reluctant to share negative word-of-mouth to avoid projecting a negative image of themselves in social contexts, thus possibly damaging their reputation.     

In the city: The John Lewis partnership and planned shopping centres

A defining feature of large-scale retailing during the period 1950–1980 was the emergence and evolution of planned shopping centres. During the 1950s, department stores in the United States were in the vanguard of this phenomenon. In contrast, British department stores continued operating from traditional high street sites, and had limited opportunities for expansion within planned shopping centres until the 1970s. This paper addresses the connection between department store retailing and the development of the planned shopping centre in Britain from the perspective of one enterprise: the John Lewis Partnership. The article demonstrates that the Partnership was willing to operate department stores within centrally located shopping centres, but was circumspect about operating stores in non-centrally located shopping centres.     

Comparing consumer-produced product reviews across multiple websites with sentiment classification

ABSTRACT

Online consumer reviews have been extensively studied. However, existing literature analyzing online consumer review data mostly relies on a single data source, resulting in potentially biased analytics conclusions. Many websites encourage consumers to post reviews of their purchased products, so that new consumers can evaluate these reviews for the same product across different websites to help them make purchasing decisions. Confusions often arise in this process, because there often exist substantial discrepancies in customer reviews across different retailers on the same product. Clarifying such confusions can help consumers reduce concerns to make up their mind for their purchases, therefore benefiting both consumers and retailers. Through text analytics and sentiment analysis, we comparatively examine the underlying patterns of online consumer reviews of three large retailers including Sears, Home Depot, and Best Buy for a same product. Afterward, we combine online consumer reviews from these large retailers and conduct an overall text analytics and sentiment analysis. The overall results are further compared with the results from individual retailers. The findings show that the sentiment of the online consumer reviews could vary substantially so relying on a single data source to make purchase decision is not a wise idea. Based on the results, we further devise a framework to comparatively examine and integrate multiple data sources for social media analytics of online consumer reviews. This study offers important managerial implications and identifies several new research directions for social media analytics.     

Platform coopetition in the tourism industry: conflicts and tensions caused by the closure of Booking.com in Turkey

In March 2017, as a result of a precautionary interim decision made by the courts based on the case relating to ‘unfair competition practices’, Booking.com closed its platform for inbound tourism in Turkey and ceased operations. This was the first instance of an online booking platform halting access for inbound bookings for the domestic market. This platform-based relationship involves both cooperation and competition, and thus this paper identifies this relationship as platform coopetition. Based on the governance network theory and employing a case-study approach, the Booking.com case is examined from the viewpoint of tourism coopetition from two perspectives: industry-wide and agent-specific. The paper provides an analysis of these perspectives and the past and on-going process of Booking.com’s platform closure. The constitutive dynamics this case endangers the coopetitive environment of the tourism industry and thus creates destructive uncertainties, especially for small hotels. This analysis also reveals the issues in terms of political representation for digital service platform companies.     

To tell or not to tell? The roles of perceived norms and self‐consciousness in understanding consumers' willingness to recommend online secondhand apparel shopping

Secondhand apparel shopping resides in a domain characterized by used goods traditionally associated with financially marginalized consumers. Acknowledging the elusive psychological barriers associated with preowned apparel, this study explores mechanisms that facilitate consumers' willingness to recommend online secondhand apparel shopping. Results from three experimental studies and a cross‐sectional survey of online secondhand shoppers in the United States reveal that hedonic and ethical benefits influence recommendation behavior via perceived norms, whereas economic benefit directly influences consumers' willingness to recommend. Moderated mediation analyses further demonstrate that self‐consciousness alters the strength of the indirect effects, such that consumers with lower self‐consciousness displayed greater willingness to recommend compared to highly self‐conscious consumers. Findings contribute to a greater theoretical understanding of the roles perceived norms and self‐consciousness play in facilitating or inhibiting recommendation behavior in a context that implicitly involves self‐disclosure of one's secondhand purchase behavior. Managerial implications offer insights on salient benefits that can be leveraged to influence word‐of‐mouth recommendation.