Fraudulent Return Problem - Management Assignment Help

Assignment Task :

1. Introduction 

One of the main challenges for online fashion retailer is high percentages of product returned, and it has been counted around 30% of the total order was being returned (de Leeuw et al., 2016). Apparel, shoes, and accessories that are categorized as fashion product have been made up the most returned products compared to consumer electronics, home products, and another type of products, and fashion product was counted as high as 54% return in 2017 (Narvar, 2018). Although it is called as free returns, it is not free in the retailers’ side. It has been forecasted that return deliveries will cost $550 billion by 2020 in the U.S. area only (Orendorff, 2019). Huge returns handling costs and transportation costs occurred in each return cycle (Hjort & Lantz, 2016). ABC News shows that The Iconic has not been making a profit from their free returns policy as it cost them 30 percent higher compared to their 2018 data (Chalmers, 2019). As The Iconic shows that they have been struggling to turn their return policy become their profit, Amazon and ASOS are currently showing the similar issues regarding their return rates and took a severe approach to control their customer. Amazon had begun banning their customers who made too many returns (Safdar & Stevens, 2018) and this step was followed by ASOS that have started shutting down some of their customers account regarding their returns rate (Duribe, 2019). However, their system is not perfect yet for detecting unnecessary product returns, and it was resulting in misidentify fraudulent returners and banned their loyal customers without clear justification (Safdar & Stevens, 2018). ASOS banning action results in complaints, threat to boycott the brands (Duribe, 2019) and even might result in future fraudulent return (Dailey & Ülkü, 2018). 

Based on the returned products, 70% did not have any problems and classified as unnecessary product returns (de Araújo et al., 2018). Fraudulent returns played specific roles in unnecessary product returns that calculated about 50% (Harris, 2010). According to the National Retail Federation, fraudulent returns cost retailers $16 billion a year (Kang and Johnson, 2009). Based on the high percentage of fraudulent return and high cost associated with it, 82% of retailers consider it as a significant problem (Harris, 2010). However, solving a fraudulent return problem seems to be challenging because the fraudulent return rate is still high over time, and this might happen because of the emergence of the online channel platform and the lenient return policy (Fu et al., 2016; Hjort & Lantz, 2016). The reason behind buying with the intention to return the product are varies. 41% of customers bought multiple versions of an item with the intention to try it and return the rest that didn’t fit (Narvar, 2018). Some of the customers are doing returns to use it for a while and keep the tag of the cloth to make it seamless (Rosenbaum, Kuntze & Wooldridge, 2011). Retailers need a better understanding of the customers to address fraudulent return issues better. Different types of customers might do a fraudulent return with entirely different factors. Lenient and free return policy might result in a fraudulent return for highly autonomous customers that are seeking valued outcomes. However, being strict and banned highly reactance customers might result in future fraudulent returns (Dailey & Ülkü, 2018). Understanding the different factors behind many type of customers might give insights for the retailer to customize their return policy and prevent a fraudulent return to happen. 

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