Online social interactions are known to be useful to improve business performances. As l ocal business retailers have limited resources in marketing, they can benefit by using onli ne social interactions for their business performances. In the same line of purpose, the ret ailers also exploit an online platform, such as discount coupon sites: they sell online coup ons for their offline products and services in the platform. Notably, the online platform ca n play an important role in generating online social interactions as well as final sales arou nd the retailing brands. It also provides a distinctive setting for consumers in that they pur chase products and services online only to consume their use offline. Given that consume rs are motivated by different purposes, their online social interactions may differ in the di sparity of purchasing online and consuming offline. Previous studies have witnessed the r elationship between social interactions and sales, but the relationship between environme ntal influences and social interactions remains unexplored. In this paper, we focus on the influences of online and offline environments where consumers are situated with the online platform on generating online social interactions as well as final sales. To this end, we look into two types of social interactions, i.e., product discussion and social referral, and two distinctive environmental influences, i.e., the influences from the same product page and from the local retail revenue where the focal business is located. Using data on online social interactions and offline retail revenues around a major coupon site in South Korea, our empirical analysis demonstrates interesting findings. The two types of social interactions and final sales respond in different way to the environmental influences. To be specific, in the online purchase context, the absolute influence lowers the generation of product discussion and sales while promoting social referrals. In the offline consumption context, however, the proportionate influence plays a role in driving these three outcomes. Our findings suggest that local business retailers should deploy their online platform strategies by concerning online and offline environments, in accordance with the specific marketing objectives regarding social interactions and sales.

Social interactions have been established as a means to help promotions and sales for manufacturers and retailers. Word-of-mouth (WOM), in particular, is proven to increase awareness and drive purchases. Given that small offline retailers have limited resources in marketing, online WOM can play a key role for their offline business performance. In this paper, we focus on two types of online WOM, public discussion and social referral, and study their generation processes by taking into account the multichannel context of both online purchases and offline consumption. To this end, we combine data from three sources: product (or deal)-level sales from a major deal site in South Korea, social interaction records collected by web crawling, and retail revenues at a district level from Korea National Statistical Office. We use a multivariate poison lognormal model to estimate three equations in the same structure with correlated errors, which only differs by the following dependent variables: number of product discussion, number of social referral, and the number of social coupons sold. Our empirical analyses suggest the following. First, the two types of WOM respond in opposite directions for the influencers in the multichannel sales context: the greater number of co-located online deals decreases public discussion but increases social referral. Next, the larger offline retail size increases public discussion, but has no significant effect on social referral. Finally, the results provide practical insights that small offline retailers can improve sales in the multichannel context by effectively managing the generation of different types of online WOM.

We investigate the effect of offline social interactions on online shopping demand and the moderating role of online channel preference in this offline-online relationship. To be specific, we intend to obtain empirical evidence by answering the following questions. First, do offline social interactions affect online demand? Second, to what degree do the active versus passive kinds of offline social interactions have the differential influence on online shopping demand? Third, how does online channel preference affect the effect of offline social interaction on online shopping demand? Drawing on the related literature in the fields of social interactions and Internet retailing, we hypothesize that the active kind of offline social interactions exerts positive influence on online shopping demand whereas the passive kind of offline social interactions has negative effects. We further hypothesize that online channel preference weakens the influence that offline social interactions has for online shopping demand. Both the positive impact of active interactions and the negative impact of passive interactions diminish in determining online shopping demand as online channel preference gets greater. We obtained sales data between January 2008 and April 2010 from a leading Internet retailer that sells baby products in the U.S. The data includes the information of zip codelevel sales and shipping days. We merged this proprietary data with the following three commercial datasets purchased from ESRI (Environmental Systems Research Institute): (1) 2011 Civic Activities Market Potential, (2) 2011 Internet Market Potential, and (3) 2011 Baby Products Market Potential). Each of these datasets includes the information of offline social interactions, online shopping preferences and offline baby product sales, respectively. Finally, as we focus on the zip code-level interplay between offline social interactions and online demand, we control for regional demographics and market condition. As such, we obtained the 2010 Census data and 2009 ACS (American Community Survey) data to account for overall local environments (e.g. population density of children aged less than five years, percentage with college education). Our empirical analyses and hypotheses testing provide the following important findings. First, active offline social interactions have positive effects on online shopping demand. This indicates that active social interactions reflect information exchange among long ties, and this informational influence in turn reduces any risk and uncertainty associated with online shopping. Second, passive offline social interactions have negative effects on online shopping demand. This suggests that passive social interactions take place among local ties and generate normative influence to conform to the expectations of others about shopping behavior, making online shopping as a new channel less attractive there. Third, online channel preference is significantly positive on online shopping demand, confirming prior studies on the relationship between channel preference and demand (Changchit et al. 2014; Valentini et al. 2011). Fourth, the positive effect that active offline social interactions have for online shopping demand decreases as online channel preference increases. Regions with strong online channel preference are likely to have well-established channel propensity and the informational influence of social interactions in reducing uncertainty becomes weaker. As such, social interactions do not play a role in spreading information about the online marketplace in regions where online channel benefits are well understood (Burt 1992, 2005; Harrigan et al. 2012). Lastly, the negative influence of passive offline social interactions gets smaller as online channel preference gets greater. Online channel preference reflects the locally-determined attractiveness of the online marketplace, and this in turn weakens normative influence to conform to the expectations and shopping behaviors of local ties.