Managing return policies with consumer resale

2021 ◽  
Author(s):  
Yong Lei ◽  
Qian Liu ◽  
Stephen Shum
Keyword(s):  
Return Policies

Migration and family change in Egypt: a comparative approach to social remittances

2013 ◽  
Vol 10 (1) ◽  
pp. 71-80 ◽  
Author(s):  
Lucile Gruntz ◽  
Delphine Pagès-El Karoui
Keyword(s):  
Public Discourse ◽  
Comparative Approach ◽  
Structural Factors ◽  
Host Countries ◽  
Return Policies ◽  
Social Remittances ◽  
Power Set ◽  
Gender Ideals ◽  
Gulf States ◽  
And Gender

Based on two ethnographical studies, our article explores social remittances from France and from the Gulf States, i.e. the way Egyptian migrants and returnees contribute to social change in their homeland with a focus on gender ideals and practices, as well as on the ways families cope with departure, absence and return. Policies in the home and host countries, public discourse, translocal networks, and individual locations within evolving structures of power, set the frame for an analysis of the consequences of migration in Egypt. This combination of structural factors is necessary to grasp the complex negotiations of family and gender norms, as asserted through idealized models, or enacted in daily practices in immigration and back home.

scholarly journals Pricing and Return Policies in a Competitive Market: A Consumer-Valuation Based Analysis with Valuation Uncertainties

2021 ◽  
Vol 13 (3) ◽  
pp. 1432
Author(s):  
Huifang Jiao ◽  
Xuan Wang ◽  
Chi To Ng ◽  
Lijun Ma
Keyword(s):  
Competitive Market ◽  
Two Dimensional ◽  
Competitive Markets ◽  
Return Policies ◽  
Numerical Investigations ◽  
Return Policy ◽  
Consumer Valuation ◽  
Competition Models ◽  
Monopoly Market ◽  
Duopoly Market

In this study, we develop a series of consumer-valuation-based models to investigate the pricing and return policies of the sellers in a competitive e-commerce market. Differing from the competition models in literature, a novel two-dimensional valuation structure is built, which considers the valuations of a consumer on two products and the valuation differentiation of all consumers on each product. We consider both monopoly and duopoly (competitive) markets. In each market, two models are respectively developed, one with and one without the return policies. We derive the solutions for the four models, and conduct some analytical and numerical investigations. The results show that return policy with a partial refund is always chosen by the sellers in both monopoly and duopoly markets. Return policy benefits the seller in a monopoly market, but may not benefit the sellers in a duopoly market. In the duopoly models, one seller can be considered as a monopoly seller who meets a new competitor. Our results show that the monopoly seller will reduce its price by no more than 20% when there comes a competitor, and, counter-intuitively, it will meanwhile adopt a severer return policy to the consumers.

Can collaborative buffering strategies reduce distribution costs while improving product returns?: A case of an Asian e-retailer

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bhavin Shah ◽  
Gaganpreet Singh
Keyword(s):  
Customer Value ◽  
Time Windows ◽  
Value Added ◽  
Revenue Sharing ◽  
Content Type ◽  
Profit Margins ◽  
Return Policies ◽  
Buffer Time ◽  
Proposed Model ◽  
The Impact

PurposeIn order to achieve competitive advantage over the physical marketplace, the e-retailers are insisted on endowing with lenient return policies. The piece-wise returns-and-reordering process incurs excessive buffering and unwanted logistics costs which raises overall fulfillment charges. The objective of this study is to re-design e-retail distribution policy by providing temporal storage at logistics service provides' (LSP) location. The impact of recurrent returns on pricing and profit margins are also investigated over time continuum.Design/methodology/approachA framework is developed to reduce the non-value added (NVA) storage and distribution efforts by providing collaborative buffering between LSP and e-retailer. The knapsack based buffering approach is tested and compared with traditional e-retail distribution practices. The revenue sharing concept is mathematically modelled and implemented in GAMS, which finally validated through multiple return scenarios.FindingsThe proposed model outperforms the existing one under all scenarios with different configuration settings of re-ordering, profit margins, and buffer time windows. The distribution cost is found, linearly related to the necessary product buffering space. The findings help to re-design sustainable return policies for individual products so that maximum customer value can be yield with minimum costs.Research limitations/implicationsThis study helps to determine the NVA efforts incurred while storing and delivering multi-time returned products to ensure desired service levels. The revenue sharing model provides pricing strategies for e-retail practitioners deciding which product should store in what quantity for how much time at the shipping agency location so that it fulfils the re-ordering at least waiting and sufficient buffering.Originality/valueThe proposed model extends the role of LPSs as temporary buffer providers to reduce returns-and-reordering fulfilment efforts in the e-retail network. This Collaborative framework offers an opportunity to amend the distribution contracts and policies time by time that enhances e-retailer's performance and customer satisfaction.

Consumer Contracts

2018 ◽  
Author(s):  
Eyal Zamir ◽  
Doron Teichman
Keyword(s):  
Bounded Rationality ◽  
Behavioral Analysis ◽  
Return Policies ◽  
Limited Availability ◽  
Consumer Contracts ◽  
The Law

This chapter presents an overview of the behavioral analysis of the law of consumer contracts. The chapter reviews various marketing techniques that build upon consumers’ bounded rationality, including the manner of presenting information, limited availability, low-ball and bait-and-switch techniques, and lenient return policies. It also analyzes several pricing techniques, such as price framing, multidimensional prices, deferred and contingent payments, and odd pricing. The chapter then turns to examining the content of consumer contracts, and highlights how pricing methods, non-salient clauses, and modifications might also exploit consumers’ limited rationality. In light of this overview, the chapter examines market-based (primarily competition and reputation) and legal solutions (primarily disclosure and mandatory regulations) to the challenges posed by consumer contracts.

scholarly journals Return Mode Selection and Pricing Strategy for a Dual-Channel Retailer

2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Xiaojian Hu ◽  
Shuai Feng ◽  
Jiqiong Liu ◽  
Aifeng Yang ◽  
Guanxiong Wang ◽  
...  
Keyword(s):  
Rapid Development ◽  
Mode Selection ◽  
Return Rate ◽  
Return Policies ◽  
Customer Preferences ◽  
Dual Channel ◽  
Business Operations ◽  
Customer Returns ◽  
The Difference ◽  
Channel Preferences

With the rapid development of e-commerce and the economy, an increasing number of retailers are adopting a dual-channel retail strategy (DCRS), which allows customers to return unsatisfactory products, provided that their complaints are reasonable, and receive a full refund. This paper studies the pricing strategies of an integrated dual-channel retailer (DCR) when it provides return policies to customers, including original channel return, fixed cross-channel return, and relaxed cross-channel return. The relationship between the DCR’s system performance and channel pricing is impacted by customer channel preferences, and the return rates of different channels are discussed. The results show that the greater the difference in customer preferences between channels is, the greater the profitability of the DCR will be. A fixed cross-channel return model should be selected when the return rate in the online channel is higher or the cross-channel return rate is lower; otherwise, the original channel return model should be selected. When the return rate of a certain channel is high, the retailer should increase the price in that channel and reduce the pricing of its competing channel to compensate for the loss caused by the returns and transfer sales between channels. A selective return policy can not only improve the flexibility of business operations and enhance competitive advantage but also provide convenient customer returns and enhance consumers’ sense of security.

Intelligent Agents for E-Commerce

2001 ◽  
pp. 101-120 ◽  
Author(s):  
Merrill Warkentin ◽  
Vijayan Sugumaran ◽  
Ravi Bapna
Keyword(s):  
Information Exchange ◽  
Business Models ◽  
New Technologies ◽  
Intelligent Agent ◽  
Data Representation ◽  
Decision Criteria ◽  
Return Policies ◽  
New Business ◽  
The Creation ◽  
Price Comparisons

A characteristic feature of the explosive growth in electronic commerce is the rapid innovation and adoption of new technologies, which results in the creation of new business relationships between consumers, firms, and markets. One such technology that is profoundly changing the dynamics of the electronic marketplace is ‘intelligent agent’ technology. Agents have the ability to autonomously carry out various activities on behalf of their principals. At a micro-economic level, agents can help buyers and sellers achieve greater efficiencies of information exchange in the electronic business-to-consumer and business-to-business domains. Additionally, they facilitate the creation of vertically integrated portals that have a significant impact on the macroeconomic landscape. Using many real-world examples, we characterize the different roles that software agents play in the various e-commerce business models and also touch upon their impact on creation of new market structures. We address price-matching versus price-comparison agents. We highlight the various purchase decision criteria evident in various vertical markets and suggest the need for a cross-industry product (and service) attribute data representation model, based on the expanded capabilities of XML. We contrast the autonomous price comparisons enabled by agents with the expanded criteria comparisons facilitated by the e-commerce rating sites. We discuss the public policy implications of these second-generation e-commerce agents with regard to data representation standardization and consumer information privacy. We present future directions for intelligent agent functions that encompass standard representation of decision criteria such as delivery and payment options, return policies, service, quality, trust, and reputation.

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