Abstract
The importance of marketplaces in e-commerce has increased. More and more merchants are trying to use e-commerce platforms as a distribution channel. With the increasing competition, merchants are faced with the challenge of continuing to sell their products to consumers through marketplaces at a profit. This is especially true if the consumer has already chosen a certain product and now only decides from which merchant to buy the product. This chapter therefore examines for different customer segments which merchant-related factors — also and in particular apart from the price — influence the purchase decision. After reviewing relevant literature, various factors are identified through structured interviews. An online survey is then used to simulate a total of 3,485 purchase decisions with different factor characteristics. In addition to the price, the ratings of a merchant and the delivery time are identified as central factors influencing the purchase decision.
TopIntroduction
For many years now, Internet-supported retail, including online trade or e-commerce, has been growing worldwide and at a disproportionately high rate compared to stationary retail (HDE & IfH Cologne, 2020; U.S. Department of Commerce, 2020). In the U.S., for example, e-commerce accounted for about 15.1 percent of total retail sales in the second quarter of 2020 (U.S. Department of Commerce, 2020).
In line with the growth of e-commerce in general, the importance of online marketplaces as e-commerce platforms, in particular, is growing. These marketplaces act as intermediaries between supply and demand. Thus, they offer a platform for business transactions to traders who either do not want to or cannot operate their own online store. In Switzerland, for example, 35 percent of all retailers already sell via these e-commerce platforms, and another 20 percent plan to do so in the future (Swiss Post & ZHAW, 2020).
The online marketplace Amazon plays a decisive role in this context. Amazon dominates the market in the western world and profits in a double sense from a network effect. For consumers, the attractiveness of the platform increases with the range of goods available. As a result, the attractiveness of the marketplace for other, additional merchants increases with every transaction. In Germany, for example, Amazon has a market share of around 38 percent in e-commerce. With a turnover of 22.23 billion euros in 2019, more than every third euro in Germany was spent on the e-commerce platform in 2019 (Amazon, 2020; HDE & IfH Cologne, 2020).
While some merchants use the marketplace primarily as an additional business to their own online store, other merchants use the marketplace to supplement their traditional stationery business. Digitization, in particular, is putting increasing pressure on the stationary retail sector. As a result, retailers are increasingly looking for opportunities to take advantage of digitization (Wohllebe, Dirrler, & Podruzsik, 2020). Retailers also seem to be focusing more and more on one or just a few marketplaces as a distribution channel. Marketplaces are also becoming increasingly relevant in the business-to-business sector: Around two-thirds of all German dealers in the B2B sector state that they also want to link their ordering systems to a marketplace or have already done so (ECC Köln & IfH Köln, 2014).
The overall increase in the number of dealers in marketplaces is also increasingly intensifying competition. Driven by high price transparency, consumers can thus benefit from low prices. Therefore, retailers who sell on e-commerce platforms face a business challenge that is particularly serious due to price transparency. On the one hand, costs must be covered and profits generated. But, on the other hand, price is a very important factor in the consumer's buying decision process. For retailers, this raises the pressing question of how to differentiate themselves from the competition in order to be able to generate sales even if they cannot offer the most favorable price. This question is particularly relevant if the (potential) customer has already made the selection for a certain product and is now only looking for the right retailer in a marketplace for the purchase decision.
Key Terms in this Chapter
E-Commerce: E-commerce is the term used to describe the initiation, negotiation, and processing of transactions via the Internet. In the context of this book chapter, this includes, unless otherwise stated, especially transactions between companies and consumers (business-to-consumer/B2C).
Merchant: A merchant in the narrower sense is a company whose business model consists of trading goods, in particular physical goods. For this book chapter, the term “merchant” refers to all types of companies that offer their products in a marketplace.
Consumer Decision Process: The consumer decision process describes consumers' decision-making process, typically in terms of purchasing decisions and weighing several alternatives. The consumer decision process is very close to the buying behavior of consumers or the buying process of consumers and can often be used synonymously in the context of this book chapter.
Buying Behavior: Buying behavior is the cognitive process that a consumer - or, more broadly, a company - goes through to decide to make a purchase.
Ratings: Ratings—here on a marketplace—are the evaluations that a merchant receives from consumers on a marketplace, often following a completed transaction.
Delivery Speed: The delivery speed or delivery time is the time that elapses in e-commerce between ordering a (physical) product and delivery to the customer. Unless explicitly stated otherwise, the term “customer” in this document refers to the consumer.
Platform: A platform is a non-physical digital place that provides several companies with the technological infrastructure to offer or provide their products and services.
Logistic Regression: A logistic regression describes a regression analysis in which the dependent variable is discrete. In the logistic regressions performed in this book chapter, the dependent variable is scaled binary - purchase or non-purchase.