Name
Abstract | ||
|---|---|---|
E-tailers normally have more accurate information regarding their products and services than consumers due to the nature of online transactions. To reduce consumers' concerns of hidden information, e-tailers can use lenient return policies to attempt to signal high product and service quality. This research proposes a model to investigate the signaling effect of two components of return policy, return windowshort return window vs. long return window and return depthfull refund vs. partial refund, on product quality and service quality. Data was collected using an online survey and analyzed using structural equation modeling. The results show that both a long return window and a full refund signal high service quality, which then positively affects purchase intention. When it comes to product quality, return window does not have a signaling effect, while the signaling effect of return depth is moderated by service quality. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1080/08874417.2016.1183989 | JOURNAL OF COMPUTER INFORMATION SYSTEMS |
Keywords | Field | DocType |
E-tailers,purchase intention,return policy,signaling theory | Actuarial science,Signalling,Structural equation modeling,Service quality,Computer science,Marketing | Journal |
Volume | Issue | ISSN |
57.0 | 3.0 | 0887-4417 |
Citations | PageRank | References |
2 | 0.36 | 16 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jie Zhang | 1 | 312 | 9.33 |
| Han Li | 2 | 235 | 10.29 |
| Ruiliang Yan | 3 | 72 | 8.31 |
| Chuck Johnston | 4 | 2 | 0.36 |