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.

Businesses today are looking for new ways to acquire and retain customers, by delivering innovative products and services, which serve each customer's individual demands. Fo- cusing on individual customer needs and addressing each request individually with a ser- vice or product that is perceived as being customized has become the focal point of Inter- action Orientation (IO), a firm-level strategic orientation developed by Ramani and Kumar (2008). Entrepreneurial Orientation (EO) is also a firm-level strategic construct, which reflects the "processes, practices, and decision-making activities" that firms use to identify and exploit new business opportunities (Lumpkin & Dess, 1996, p.136). As op- posed to IO, EO is a well-established concept, being one of the most examined topics in entrepreneurship research. However, most studies have focused on cross-sectional de- signs to assess the relationship to firm performance, leading to numerous research calls focusing on the need for more dynamic investigations (Saeed, Yousafzai, & Engelen, 2014). Based on our analysis including 247 S&P500 firms from a variety of industries over a period of three years, this longitudinal study is one of the first to assess the short-term and long-term effects of IO and EO. To establish the firm's levels of IO and EO, we ana- lyze the content of Letters to Shareholders (LtS), as LtS have been widely used to assess different strategic orientations - Market Orientation, Learning Orientation - including EO (Noble et al., 2002; Short, Broberg, Cogliser, & Brigham, 2010; Zachary, McKenny, Short, & Payne, 2011). We relied on multisource secondary data for performance indica- tors and included several control variables: past performance of the firm, firm age, firm size, as well as industry specific effects. Our results confirm that each orientation has a positive impact on the firm's financial suc- cess in the long-term but a combined IO-EO strategy reveals a negative effect on firm performance in the long-term. This study investigates the synergies between IO and EO in a longitudinal setting and using objective financial performance indicators, establish- ing the advantages and disadvantages of implementing a single or combined strategy.

Interaction Orientation (IO), a firm-level strategic orientation developed by Ramani and Kumar (2008), consists of four dimensions: (1) Customer concept - a firm-wide belief that sees the individual customer level as the examination unit and starting point of all company’s activities; (2) Interaction response capacity - the firm’s competency to respond to different customers using multiple means in a timely manner; (3) Customer empowerment - the extent to which a firm encourages customers to share information with the firm or with other customers; and (4) Customer value management - the capacity to keep an overview of how much revenue each customer generates, facilitating an efficient resource allocation. Current research states that IO represents a source of competitive advantage and leads to higher financial and non-financial performance. Past studies have only focused on cross-sectional data. However, a strategic orientation is a deeply embedded and gradually progressing organizational characteristic and, in order to establish a cause-effect relationship with performance, a longitudinal design is needed (Noble, Sinha, & Kumar, 2002). This study is the first to analyze the effects of IO longitudinally, including 247 S&P 500 firms from a variety of industries over a period of three years. To establish the firm's level of IO, we analyze the content of Letters to Shareholders (LtS). LtS are widely used to assess different strategic orientations, such as Entrepreneurial Orientation, Market Orientation or Learning Orientation (Noble et al., 2002; Short, Broberg, Cogliser, & Brigham, 2010; Zachary, McKenny, Short, & Payne, 2011). A sentence-by-sentence coding procedure was implemented (Keusch, Bollen, & Hassink, 2012;), where each sentence was examined for evidence of the four IO dimensions. We relied on multisource secondary data for performance indicators and on the American Customer Satisfaction Index (ASCI) for measuring customer satisfaction. We included the effects of competitive intensity and market turbulence, as well as several control variables: past performance of the firm, firm age, firm size, as well as industry specific effects. The results confirm the short and long term benefits of implementing IO, including higher financial performance and increased customer satisfaction, especially in a turbulent market. This study lays the foundation of a new approach for measuring IO in a longitudinal setting and using objective financial performance indicators.