Why adopt social enterprise software? Impacts and benefits

Abstract

This paper explores the performance impacts and benefits of the adoption of Social Enterprise Software (SES). SES forms a nested innovation, given that its adoption requires an already established infrastructure of Information and Communication Technology. To control for induced sample selection, we use a two-step estimation procedure. Based on German firm-level data our results confirm that firms which use business-to-business (B2B) e-commerce applications are more likely to adopt SES. The estimated correlations also provide weak evidence for complementarity between B2B e-commerce and SES. We show that two measures of firm performance, i.e. sales and labor productivity, are highest for firms using SES and B2B e-commerce applications in conjunction.

Introduction

In recent years, social software, e.g. wikis, blogs, microblogs or social networks, has increasingly appeared in both public dialogues and press releases. Social software is already extensively used in private households and increasingly adopted by firms. As for firms, more than 80% of the top 100 companies in the Fortune 500 maintain a presence on social network sites (Gartner, 2012). However, currently a new type of business software is emerging, which interrelates recent social software and firms’ established enterprise systems, e.g. Enterprise Resource Planning (ERP), Supply Chain Management (SCM), Customer Relationship Management (CRM). This so called Social Enterprise Software (SES) links firms’ enterprise software systems and social software applications as in, e.g., social CRM solutions.

Overall, SES offers benefits in the areas of business-to-customer (B2C) and business-to-business (B2B). For B2C, SES supports tracking data from customer surveys, customer feedback, reviews or user profiles on social networks or blogs, thereby enabling firms to identify new customers, new market segments and observe recent trends. SES packages additionally feature various communication channels allowing for a two-way interaction between companies and their customers, by offering them a direct channel for providing their feedback. With specific customer data collected and direct customer interaction SES might facilitate the development of new products as it allows firms to observe customer tastes and build up meaningful customer profiles.

In the B2B segment benefits of SES emerge in form of enhanced collaboration and communication as employees and partners are connected in a way they can exchange information fast and freely. Stakeholders have real-time access to all areas they are interested in and can monitor and directly access interactions and inputs of others. SES further enhances process management and knowledge sourcing as knowledge consumers, like sales teams, can access information from knowledge providers, like product developers, in real-time saving time for each employee. With partners and clients of the utilizing firm connected, the benefits of SES are not limited to the boundary of the firm but may spread onto other business contacts.

Up to now there are no empirical studies on the emerging phenomenon of SES although these software packages began to come up in 2008 (Chess Media Group, 2010). Consequently, as SES is still an uncertain new technology in its infancy, empirical evidence about determinants of its adoption and its potential impacts on firm performance is still lacking. Also, up to now it is still unclear which distribution segment, i.e. B2B or B2C, benefits the most once SES is adopted.

We aim at filling this research gap by empirically evaluating the determinants of SES adoption and exploring its impacts on firm performance. In the analysis, we distinguish between benefits and impacts in the area of B2B and B2C. Our analysis is based on a unique database consisting of German manufacturing and service firms. Since SES requires a firm to first adopt particular Information and Communication Technology (ICT) before it can upgrade them to SES, it represents a so-called “nested innovation” (Greenstein and Prince, 2007). This “nested” structure induces sample selection which has to be taken appropriately into account in the estimation procedure.

Our study adds to the empirical literature in a number of ways. To our knowledge we are the first to explore the performance impacts of most recent SES and investigate the determinants of its adoption. Second, considering that ICT might act as complements (Aral et al., 2012) or even substitutes (Kretschmer et al., 2012) in their impact on performance our results offer a weak test for complementarity based on correlations between the usage of established ICTs, i.e. B2B e-commerce applications, and the adoption of most recent ICTs, i.e. SES. Third, our paper presents a valid empirical method with which to model the data generating process in the case of a “nested innovation”, i.e. the probit with sample selection (Berinsky, 2004, Gourieroux and Jasiak, 2007)

Our results show that firms using B2B e-commerce applications are more likely to adopt SES. B2C e-commerce applications fail to impact the adoption decision. The estimated correlations also provide weak evidence for complementarity between B2B e-commerce applications and SES. Concerning impacts on firm performance, we show that mean sales and labor productivity are highest for firms using SES and B2B e-commerce applications in conjunction.

The paper proceeds as follows: Section 2 summarizes the empirical literature of ICT, its complementarities and performance impacts and explains SES, its classification as a “nested” ICT innovation and its benefits. Section 3 presents the dataset whereas Section 4 highlights the empirical model. Section 5 provides a detailed explanation of the selected exogenous variables and the necessary exclusion restriction. The estimation results and additional robustness checks to clarify the validity of the results are presented in Section 6. Finally, Section 7 concludes.