Online consumer activities have increased considerably since the COVID-19 outbreak. For the products and services which have an impact on everyday life, online reviews and recommendations can play a significant role in consumer decision-making processes. Thus, to better serve their customers, online firms are required to build online-centric marketing strategies. Especially, it is essential to define core value of customers based on the online customer reviews and to propose these values to their customers. This study discovers specific perceived values of customers in regard to a certain product and service, using online customer reviews and proposes a customer value proposition methodology which enables online firms to develop more effective marketing strategies. In order to discover customers value, the methodology employs a text-mining technology, which combines a sentiment analysis and topic modeling. By the methodology, customer emotions and value factors can be more clearly defined. It is expected that online firms can better identify value elements of their respective customers, provide appropriate value propositions, and thus gain sustainable competitive advantage.

The goal of this study is to get a better understanding of the relationship between online customer reviews (OCRs), product returns and sales after returns in online fashion. Furthermore, we generate deeper insights about the moderating role of mobile shopping usage, product involvement and brand equity in this context. We answer our research questions by empirically analyzing a unique data set from a European fashion e-commerce company. This study links a wide range of transaction data (2.5 billion page clicks, 46 thousand different products, 700 brands, 40 product categories, 72 million sold and 33 million returned items) with a large set of OCRs (0.9 million). Our results show that positive OCRs can lead to higher sales, lower returns, and better conversion rates. Considering higher search costs on mobile devices, we reveal a weaker impact of OCRs in the mobile than in the desktop sales channel. Furthermore, in line with involvement theory, we see a significant impact of product involvement in this context such as the influence of positive OCRs is stronger for high-involvement products than vice versa. Moreover, we find strong support for statements from brand signaling literature, that OCRs matter more for weak than for strong brands.

E-commerce is a global phenomenon that reshapes retailing and the appropriate multinational corporations. The goal of this study is to get a better understanding of the relationship between online customer reviews (OCRs), sales and sales after returns in the cross-national and cross-cultural context. We discuss our hypotheses by empirically analyzing a large and unique data set from a European fashion e-commerce company. This study links a wide range of transaction data (0.8 billion page clicks, 17 thousand different products, 499 brands, 50 product categories, 22 million sold and 11 million returned items) from six different countries (Austria, France, Germany, Italy, Netherlands, Poland) with a large set of OCRs (0.7 million). Our results show that positive OCRs can lead to higher sales and sales after returns with considerable cross-country differences. We argue that differences in culture provide a substantial explanation for these effects by using Hofstede's cultural framework.