Journal of Retailing
Papers
932
Papers 984
1 page of 99 pages (984 results)
Newest
#1Siham El Kihal (Frankfurt School of Finance & Management)H-Index: 1
Last. Bernd Skiera (Goethe University Frankfurt)H-Index: 39
view all 4 authors...
Abstract The product return rate (RR) is an important metric for retailers; even small RR changes can significantly impact retailers’ profit. Companies and researchers typically favor and employ one of three methods to calculate the RR: based on the number of returned items, these items’ revenue, or their profit contribution. Interviews with 24 managers and industry experts reveal that two methods, item-based and revenue-based, are often used. However, little is known about how much the interpre...
Source
#1Guangming Xie (Chengdu University of Information Technology)
#2Kevin Lü (Brunel University London)H-Index: 14
Last. Li Shi (Chengdu University of Information Technology)
view all 5 authors...
Abstract Electronic word-of-mouth (eWOM) dispersion, reflecting the extent of reviewers’ opinion divergence regarding a product, determines consumer decisions. Drawing upon the endowment effect and attribution literature, this research proposes that the endowment effect mediates the influence of eWOM dispersion on attributional inferences, and the display formats of eWOM dispersion (“horizontal bar chart” vs. “eWOM content”) moderate the mediating influence of endowment effect on attributional i...
Source
#1Martin Hirche (University of Cologne)H-Index: 2
#2Paul Farris (UVA: University of Virginia)H-Index: 27
Last. Susan Wei (University of Melbourne)H-Index: 6
view all 5 authors...
Abstract This research presents a retail analytics application which uses machine learning (ML) to identify and predict under- and overperforming consumer packaged goods (CPGs) using retail scanner data. Essential to measuring market performance at the SKU level is the relationship between distribution and market share (the velocity curve). We validate that ML can reproduce the velocity curve, and ML is further used to predict underperforming, in-line performing, and overperforming SKUs relative...
Source
#1Olivia Petit (KEDGE Business School)H-Index: 11
#2Ana Javornik (UoB: University of Bristol)H-Index: 7
Last. Carlos Velasco (BI Norwegian Business School)H-Index: 39
view all 3 authors...
Abstract This research examines how consumers’ intentions to purchase food change depending on the visualisation mode (3D vs. AR) and product format (served vs. packaged). In three studies, we demonstrate that mental simulation of eating experiences (process and outcome) mediate these effects. Study 1 shows that AR visualisation of a served food improves simulation of the eating process over 3D visualisation, with a positive effect on purchase intention. Study 2 reveals that 3D visualisation imp...
1 CitationsSource
#1Kealy Carter (USC: University of South Carolina)H-Index: 3
#2Satish Jayachandran (USC: University of South Carolina)H-Index: 15
Last. Mitchel R. Murdock (UVU: Utah Valley University)H-Index: 3
view all 3 authors...
Abstract The reputation of firms for being environmentally friendly and socially responsible is a key purchase driver for sustainable products. However, the commitment of firms to sustainability varies – some firms are founded on strong environmental and social principles; other more traditional firms are built on strong product/brand focus and are not known for sustainability. In response to market trends, many traditional firms are introducing sustainable products to their portfolios. We argue...
Source
#1Ruth N. Bolton (ASU: Arizona State University)H-Index: 41
#2Anders Gustafsson (BI Norwegian Business School)H-Index: 55
Last. Lars Witell (Karlstad University)H-Index: 34
view all 5 authors...
Abstract This study investigates how retailers can leverage their brand to shape customers’ satisfaction with service encounters. It develops and tests hypotheses about how brand, store, and consumer factors moderate customer responses to experience clues during retail service encounters. Six meta-regression analyses synthesize and compare results from 842 satisfaction equations describing customers’ encounters with a global retailer operating 400 stores in 32 countries. The results show how cus...
1 CitationsSource
#1Jin Ho Jung (College of Business Administration)H-Index: 1
#2Tom J. Brown (OSU: Oklahoma State University–Stillwater)H-Index: 24
Last. Alex R. Zablah (UT: University of Tennessee)H-Index: 20
view all 3 authors...
Abstract This study investigates how customer requests, a common phenomenon, influence frontline employee (FLE) job outcomes. We propose and demonstrate that (1) FLEs possess tendencies to appraise customer requests in both positive (i.e., challenge appraisal tendency) and negative (i.e., hindrance appraisal tendency) ways, (2) higher levels of challenge appraisal tendency result in higher levels of FLE performance and lower levels of turnover (mediated through job engagement), (3) higher levels...
Source
#1Yining Yu (ZJU: Zhejiang University)
#2Xinyue Zhou (ZJU: Zhejiang University)
Last. Qiuzhen Wang (ZJU: Zhejiang University)
view all 4 authors...
Abstract Researchers have recently begun investigating how visual elements affect brand positioning. However, little is known about the effect of brand typeface features on brand premiumness. This paper proposes and verifies that letter case affects consumers’ perceived brand premiumness. Eight experiments, including one eye-tracking experiment, reveal that consumers perceive brands that use all uppercase letters (“uppercase brands”) as more premium than those that use all lowercase letters (“lo...
Source
#2Divya Ramachandran (J. Mack Robinson College of Business)H-Index: 2
Abstract In an environment with digital disruptions, retailers must adopt a customer-centric approach to survive and compete effectively. Retailers need to be agile and forward-looking in adopting the relevant analytics and performance metrics to bring a customer-centric approach across upstream and downstream activities in the retail value chain. However, retailers in emerging markets (EMs) need clarity on the specific analytics and performance metrics in the value chain that will enable them t...
Source
#1Ming-Hui Huang (NTU: National Taiwan University)H-Index: 22
#2Roland T. Rust (UMD: University of Maryland, College Park)H-Index: 75
Abstract We develop a conceptual framework for collaborative artificial intelligence (AI) in marketing, providing systematic guidance for how human marketers and consumers can team up with AI, which has profound implications for retailing, which is the interface between marketers and consumers. Drawing from the multiple intelligences view that AI advances from mechanical, to thinking, to feeling intelligence (based on how difficult for AI to mimic human intelligences), the framework posits that ...
Source
12345678910
Top fields of study
Advertising
Business
Psychology
Economics
Marketing
Perception
Service (business)
Public relations
Commerce