WEBSITE USAGE AS A CRITICAL SUCCESS FACTOR FOR FIRM INNOVATION AND MARKET VALUE

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1 WEBSITE USAGE AS A CRITICAL SUCCESS FACTOR FOR FIRM INNOVATION AND MARKET VALUE Fang Wang Wilfrid Laurier University Bixia Xu Wilfrid Laurier University Abstract Firm websites are among the most visible information technology (IT) applications and the primary platforms to conduct e-commerce or online strategy. This research examines the critical role of firm website usage in facilitating innovation success and market value and the potential firm heterogeneity of the effect. With a sample of 2,840 U.S. firms, we report that firm website usage can significantly moderate the firm innovation performance relationship. In addition, the moderating effect is heterogeneous, depending on customer type and capital intensity, and is greater for business-to-consumer firms and firms with high capital intensity. Further clustering analysis identifies that the firm size based heterogeneity exists under the combinations of firm size with customer type and capital intensity. The findings of this study suggest that firm website usage conveys important valuation relevant information that aids investor anticipations of firm innovation success and market value. JEL: M15, M41, O32, O34 Keywords: Innovation; IT; Website usage; Firm performance; Moderating effect 1. Introduction Firm innovation generates multiple attributes that are valued by capital market participants (Palmon 2012). Firms rely on innovation to survive and win out over the competition (Madsen and Leiblein 2015). Empirical research has long confirmed that firm innovation drives firm outputs and market value (Thornhill 2006; Rubera et al. 2016). To the extent innovation is costly, a key interest of accounting research and communities is to identify factors that enhance firm innovation success and leverage the firm innovation performance relationship. In light of information technology (IT) research, we investigate whether and how information embodied in firm IT applications can assist investors to comprehend firm innovation that maps into firm value. Innovation is the design, invention, development and/or implementation of new or altered products, services, processes, systems, organizational structures, or business models for the purpose of creating new value for customers and financial returns for the firm (The Advisory Committee on Measuring Innovation in the 21 st Century Economy, p. i). Commonly discussed in the business literature are product and process innovations. Product innovations enable firms to offer new products through new product development, while process innovations create new methods for performing business activities that can reduce costs and/or generate new revenue streams (Davenport 1993; Kleis et al. 2012). Among the factors that affect firm innovation, information technology (IT) is increasingly considered as a major enabler (Jao-Hong et al. 2014). 1

2 The past three decades have witnessed the continuous emergence of new technologies and applications, from and CAD to web-based tools and complex collaborative platforms. The adoption of these IT applications has ignited continuous process innovations and facilitated product innovations. Abundant anecdotal evidence suggests that IT has fundamentally changed the innovation landscape of the business world (Brynjolfsson 2011). Despite the importance of IT to innovation, empirical research has only recently begun addressing this issue (Bardhan, Krishna and Lin 2013). While a large body of research has investigated direct impact of IT on firm performance (Brynjolfsson and Hitt 1996; Dos Santos et al. 2012), the underlying mechanism of IT s impact on firm value, especially that through innovation, is largely under-researched (Bardhan, Krishna and Lin 2013). This study contributes to the understanding of this mechanism by exploring the moderating effect of firm website usage on firm innovation performance relationship. The limited empirical research on the role of IT in innovation has taken two approaches: (1) examining how adoptions of IT applications affect innovation (Higon 2011; Joshi et al. 2010; Koellinger 2008) and (2) investigating how IT investments overall affect innovation (Brynjolfsson and Hitt 1996; Huang and Liu 2005, Bardhan, Krishna and Lin 2013). Studies from both approaches suggest that IT adoptions or investments enhance innovation process and market success. Compared with the second approach, which considers firm overall IT spending and does not differentiate effects of individual IT projects, the first approach credits firm innovation success and directs management attention to specific IT applications. Following the direction of the first approach, we examine the impact of firm website, a major IT application, on firm innovation success and market valuation. Different from previous studies and in consideration of the wide adoption of firm website, we focus on firm website usage intensity, instead of mere adoption. The rationale behind our investigation lies in the vital interaction between firms and firm website users in business success. Specifically, we investigate the role of firm website usage intensity in affecting the firm innovation performance relationship from the following distinctive perspective. First, the IT application we investigate is the firm website. Firm websites are among the most visible IT applications serving as a major portal for firm customer interactions. To the best of our knowledge, their role in innovation has been rarely examined. Second, in contrast with previous studies that focus on firm adoptions of IT applications, we examine the effect of the extent to which IT is actually used, i.e., the firm website usage intensity and its impact on firm innovation. With the wide diffusion of IT in business practice, businesses have passed or are passing the adoption stage of most major IT applications. Thus, research attention needs to shift from IT adoption to its actual usage. Third, in addition to the general effect of firm website usage relationship, we further explore the potential heterogeneity of this moderating effect for a more complete understanding. In particular, based on the degree of firm reliance on website for innovation management, we investigate whether the moderating effect is differential depending on firm customer type, capital intensity, and size. We compile a comprehensive database of 2,840 public firms in North America, by combining data from (i.e., firm financial data) and Alexa.com (i.e., firm website traffic ranking). 2

3 Because large firms have more web visits, we derive and use a size-free firm website usage measure by adjusting firm website traffic ranking collected from Alexa.com for firm size. We find that firm website usage intensity significantly enhances the market return on firm innovation investments. In addition, the impact of firm website usage intensity on the innovation performance relationship is greater for business-to-consumer (B2C) firms and firms with high capital intensity. The difference in this impact between small and large firms conditions upon customer type and capital intensity. Firm website usage is more important for small B2C firms and small firms with higher capital intensity. This study provides several theoretical and practical contributions. It contributes to the literature by identifying whether and how IT usage (i.e., websites usage in the context of this study) enhances firm innovation success and market valuation. Practically, it provides insights into managerial web strategy and management control. For investors, it suggests that web usage is a critical value driver that they need to take into account when evaluating firm innovation and value. 2. Hypotheses In this study, developed from the extant literatures, we test the following hypotheses pertaining to website usage and firm innovation success H1. Firm website usage intensity moderates the relationship between firm innovation and performance. H2. The moderating effect of firm website usage relationship is greater for B2C than B2B firms. H3. The moderating effect of firm website usage relationship is greater for capital intensive firms than for labor-intensive firms. H4. The moderating effect of firm website usage relationship is greater for small than large firms. 3. Methodology We collected firm financial data, including R&D expenditures, for the period from the North American database. We collect firm web traffic ranking data from Alexa.com in 2011 and adjust it for firm size to measure firm website usage. We conduct cross-sectional regressions to examine the moderating effect of firm website usage intensity on the firm innovation performance relationship. Our baseline testing model is: TOBINQ = F(RD, WEBSITE, RD*WEBSITE, RD*WEBSITE*D, Control variables), Table 1 summarizes all the variables. [Insert Table 1 Here] 4. Results Results of hypotheses testing are reported in Table 2 and Table 3. As the regression 3 of Table 2 shows, this interaction term of RD*WEBSITE is positively significant, indicating that website usage intensity positively moderates the innovation performance relationship. H1 is supported. Table 3 reports the cross-sectional regression results for H2, H3, and H4. In these hypotheses, we further argue that the moderating effect of WEBSITE can be differential depending on the customer type (DB2C), capital intensity (DCAPIT), and firm size (DSIZE). As the table shows, the interaction term, RD*WEBSITE*DB2C is significantly positive, suggesting that the moderating effect of firm website usage intensity is greater for B2C than B2B firms and supporting H2; the coefficient of 3

4 RD*WEBSITE*DCAPIT is significantly positive, indicting the moderating effect of website usage intensity is stronger for capital-intensive firms than others and supporting H3; the coefficient of RD*WEBSITE*DSIZE is insignificant, indicating that the moderating effect of firm website usage relationship is similar for small and large firms and not supporting H4. [Insert Tables 3 and 4 Here] Figure 1 Research framework. TABLE 1 Variable descriptions 4

5 Variable Description Source Variables Under Study TOBINQ WEBSITE Tobin s q is calculated by (market value + book value of total liabilities)/book value of total assets. Firm website usage intensity measured by web traffic ranking adjusted for firm size Alexa and RD The ratio of R&D expenditure to sales DB2C DSIZE DCAPIT A customer type dummy variable with the value of 1 for B2C firms and 0 otherwise. A firm size dummy variable with the value of 1 for firms with sales exceeding the median value of the sample and 0 otherwise. A firm capital intensity dummy variable with the value of 1 for firms with the ratio of total fixed assets to total assets higher than the median value of the sample and 0 otherwise. Control Variables AD ASSEF Advertising intensity is measured by the ratio of advertising expenditure to total sales. Assets efficiency is measured by sales over average total assets. Average total assets are calculated as prescribed by accounting practice, which is the sum of beginning total assets and end-ofperiod total assets divided by 2. GROW Growth ratio is the ratio of sales to sales of the previous year LEV Financial leverage is the ratio of long-term debt to total assets. SIZE Firm size is measured by natural log of sales of previous year. 5

6 TABLE 2 Effect of website usage Equation Regression Constant 1.53*** 1.69*** 1.62*** RD * * 1.05*** WEBSITE *.19*** RD*WEBSITE 1.18*** SIZE ** ** -.19*** AD ** ** 2.70*** ASSEF * *.25*** GROW *.30*** LEV * -.17 # of Obs. 2,840 Max VIF 3.10 Adj. R Notes: DV: TOBINQ; VIF: variance inflation factor. * p<0.10; ** p<0.05; *** p<0.01. TABLE 3 Heterogeneity in the effect of website usage Equations Overall Constant 1.57*** 2.21*** 1.62*** 2.17*** RD 1.03***.73*** 1.07***.74*** WEBSITE.16***.15***.20***.15*** RD*WEBSITE 1.05***.71*** 1.22***.62** RD*WEBSIT*DB2C.64**.68** RD*WEBSIT*DCAPIT 1.12** 1.16*** RD*WEBSIT*DSIZE DB2C DCAPIT SIZE -.18*** -.26*** -.19*** -.26*** AD 2.65*** 2.62** 2.69*** 2.52*** 6

7 ASSEF.24***.09**.25***.09** GROW.31***.34***.30***.35*** LEV *** *** # of Obs. 2,840 2,840 2,840 2,840 Max VIF Adj. R Notes: DV: TOBINQ; VIF: variance inflation factor. * p<0.10; ** p<0.05; *** p<0.01 7