Remote Purchase Environments: The Influence of Return Policy Leniency on Two-Stage Decision Processes

By Stacy L. Wood. 2001

443 citations recorded by the source corpus.

Subfields: Information Systems and Management, Marketing

View Paper: https://www.semanticscholar.org/paper/d6d9a0f6bab4dd8fc0eeb9fe2114b1b25e289b5a

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In Information Systems and Management

1. Dan J Kim
2. Zhi Pei
3. Hongju Liu
4. H. Rao
5. V. Kumar
6. Audhesh Paswan
7. Catherine A. Cole
8. Gal Zauberman

In Marketing

1. Gal Zauberman
2. John G. Lynch
3. Denish Shah
4. Morris George
5. Dan J Kim
6. Zhi Pei
7. Hongju Liu
8. H. Rao

Citations in the corpus

• When do you Want It? Time, Decisions, and Public Policy (2006, background): “Wood (2001) shows that lenient return policies encourage people to buy under the false presumption that they are “trying” rather than committing to a product or service; subsequently, they are as unwilling to reverse a decision as if the return policies had been strict.”
• Consumer Returns Policies and Supply Chain Performance (2009, unknown): “Second, since the returns policy directly determines consumers’ keep-or-return decisions, a higher refund r also induces higher return rates G ( r ); this result was observed in the experimental study by Wood (2001).”
• Perceived Risk, Product Returns, and Optimal Resource Allocation: Evidence from a Field Experiment (2015, background): “…example, research has shown that customers often perceive a strict product return policy as a potential sign of lower product quality because the firm wants to increase the burden of the return cost to the customer with the intent of influencing the customer not to return the product (Wood 2001).”
• Product Returns on the Internet: A Case of Mixed Signals? (2010, background): “…theoretical perspective, not only do we contribute to the growing, but still small marketing literature on return policies as signals of quality (Davis, Hagerty and Gerstner 1998; Kirmani and Rao 2000; Wood 2001), but also we add to the literature on atmospheric effects (Turley and Milliman 2000).”
• A multidimensional trust formation model in B-to-C e-commerce: a conceptual framework and content analyses of academia/practitioner perspectives (2005, background): “…planning (complexity), sales-related service (refund policy, after-sales, etc.), promotions, delivery fulfillment, etc. [36] [82] [85] [99] [109] Technology dimension Information system and software attributes that enable the online exchange to be effective and safe Quality of media…”
• E-tailer׳s return policy, consumer׳s perception of return policy fairness and purchase intention (2014, methodology): “Prior research using signaling theory suggests that a lenient return policy signals a higher quality, which influences consumer's purchase intention (Wood, 2001; Constantinides, 2004; Mukhopadhyay and Setaputra, 2007).”
• Examining relationships between the return policy, product quality, and pricing strategy in online direct selling (2013, unknown): “However, the effect of the retailer's return policy on customer purchase decisions may differ in direct sales compared to brick and mortar stores (Wood, 2001; Huang et al., 2011).”
• Decision Making: Factors that Influence Decision Making, Heuristics Used, and Decision Outcomes (2010, background): “Significant to individuals’ satisfaction is that people are willing to pay a premium for the opportunity to change their minds at a later date (Wood, 2001).”