Network Externalities and Technology Use: A Quantitative Analysis of Intraorganizational Blogs

We examine the role of network externalities on the use of blogs in an organization. Prior research has considered social influences such as peer pressure, but there is little prior work on how the extent of others’ actual usage can influence an individual’s use of technology. We also examine how technology usage is influenced by positive feedback from others. Finally, we look at how the relation between technology usage and network effects is moderated by demographic variables such as age and gender. the results of the study show that usage of blogs within an individual’s network is associated with an increase in one’s own usage. We also show that network effects are stronger for younger generations and that this relation is nonmonotonic with age. this is interesting considering that prior research suggests that social influences are stronger for older employees. Our results also show that network effects are stronger for women than for men. Further, we show that the impact of age on blog usage in not linear. We also find that feedback or appreciation from others is associated with higher blog usage by an individual. Finally, we subdivide the network effects into various subtypes and find that network effects are strongest for relational networks, and that use of blogs by an employee’s managers is associated with higher usage by the employee. Key WordS and PhraSeS: corporate blogs, network externalities, social computing, social networks, technology usage. organizationS exPend conSiderable reSourceS to evaluate, adopt, and assimilate new technologies. however, previous research suggests that a majority of technology initiatives either fail or remain underutilized. Employee adoption and continued use of technologies or lack thereof has been frequently cited as one of the leading causes of failure of new technologies [32]. therefore, this topic has been a subject of enduring interest to both researchers and practitioners over a considerable period of time [8, 16, 19, 57, 58, 67]. research in this area can be broadly classified into two categories: 1. utility-oriented models stemming from the theory of reasoned action (tra) [20], innovation diffusion [57], and the technology acceptance model [15]. these studies emphasize the importance of employees’ individual characteristics, their perceived behavioral control, and perception regarding the innovation’s attributes such as ease of use, usefulness, and complexity. Similarly, task–technology fit theories [24] focus on the perceived compatibility of the new information technology (It) with employees’ and organizations’ task characteristics. 2. Social influence models [36, 56] that examine the role of formal and informal social networks on an individual’s use of a technology. these theories focus less on the value of a technology but place greater importance on the normaNEtWOrk ExtErNalItIES aND tEchNOlOGy uSE 147 tive influences and social processes of the organizational environment through which employees learn about and adopt new technologies [21]. In this paper, we extend the latter perspective to examine the role of network externalities on the use of social computing technologies in an organization. Social influence models have been extensively examined from both sociological and economic perspectives. research with a sociological perspective has been driven by a variety of theoretical frameworks. For instance, the theory of social learning [5] suggests that attitude toward new technologies is not only predicated on individuals’ direct experience but also on their ability to observe and learn from the consequences of others using the technology. this allows individuals to avoid needless and often costly errors. Similarly, social information–processing models [59] suggest that information passed through individuals’ social networks influences their perceptions of technology, and such influences are stronger in cohesive networks [11]. Social influence also refers to how an individual conforms to the expectations of others by performing a certain action (e.g., using a new technology). In short, the mechanisms of social influence could vary under different circumstances. Deutsch and Gerard [17] formalized this difference by suggesting that there exist two mechanisms of social influence—informational influence (when an individual witnesses benefits firsthand from others’ adoption and use) and normative influence (when an individual is obligated to use the system if others use the same). researchers with an economic perspective have used the term network externali‐ ties to capture the broad range of social processes that influence individual behavior. Network externalities arise when the value of participating in a network increases as more people participate in the network [44]. Network externalities introduce dynamic considerations for potential users because users must predict the size of the network in the future to avoid adopting a technology that might not provide the expected benefits owing to the low installed base. Network externalities are evident in areas such as video game markets (where game developers are more likely to develop games for systems that are popular, such as xbox or PlayStation, and the availability of more games on a system increases the popularity of these systems even further) or technologies (where more independent developers develop widgets, games and applications for popular technologies such as Flickr and iPhone, which makes these technologies even more popular). researchers have examined the effect of network externalities in areas such as technology adoption, pricing, and competitive dynamics [33, 45]. Social computing tools such as blogs, wikis, discussion boards, and social networking sites are especially suited to study network effects. these tools are highly interconnected and, unlike traditional technologies, are essentially social in nature. In an organizational context, these tools are used for both formal and informal communication as well as collaboration. For instance, if an employee requires clarification on a work-related problem, he or she can post the query on a blog or a social networking platform and attract instant responses from employees in various corners of the organization. Similarly, employees can use these tools to create personal profiles 148 Wattal, rachErla, aND MaNDVIWalla and find as well as interact with other employees who share similar interests and lifestyles. recent evidence suggests that social computing tools are also being used to develop collaborative spaces within organizations and gradually replace knowledge management systems [25]. Extant research on network effects and technology usage in organizations presents certain interesting limitations: 1. the aforementioned theories have been predominantly applied in the context of traditional organizational technologies such as personal computers/productivity tools [63], groupware technologies [41], and enterprise-level systems [72]. these technologies are essentially top-down in nature in the sense that they are mandated by management and employees have to make a decision whether or not to assimilate them into their day-to-day work. On the other hand, new technologies with a completely different design, such as social computing, are emerging in the business landscape, and it is important to understand their relevance and examine their use within organizations. 2. Prior studies (e.g., [36, 55]) have generally measured network externalities as a function of the cumulative installed base of users within the social networks of individual employees. consequently, these studies do not consider the actual usage to measure network effects and social influences. We contend that although the overall user base is an important consideration for potential adopters, it is the actual usage by important members in the social network that signals the utility of the new technology. 3. another type of social influence that is unique to social computing technologies is the potential to receive feedback or appreciation from others when an individual uses the technology. For example, in case of consumers writing online reviews (amazon.com), replying to questions on discussion boards, or writing a blog, readers have the option to express gratitude for contributions that they find particularly helpful. Prior literature has looked at the perceived benefits of using a technology in general, but there has been little research on the role of feedback from others on an individual’s use of a technology. With these motivations, we propose the following research questions: RQ1: Do network externalities play a role in influencing the use of social comput‐ ing technologies in organizations? RQ2: How do individual characteristics such as age and gender moderate the effect of network externalities on use of social computing technologies? RQ3: What is the effect of positive feedback from others on the use of social computing technologies in organizations? Our study attempts to answer these questions by analyzing the use of corporate blogs in a large u.S.-based multinational firm. We capture information on blog usage by employees, their demographic characteristics, whether an employee received positive feedback on his or her blog posts, and the contribution by other employees in the network. Our results show that network effects play a significant role in usage of NEtWOrk ExtErNalItIES aND tEchNOlOGy uSE 149 blogs by employees and that the relation is moderated by demographic variables such as age and gender. younger employees are likely to contribute more to blogs and are also more influenced by others’ usage, though the relation is not strictly monotonic. Gender does not play a direct effect on blog usage, but moderates the relation between network effects and blog use. We find that positive feedback from others is associated with more blog posts. the results show that usage by managers has a significant effect on blog usage by an individual, suggesting that even though blogs are bottom-up technologies, managers are likely to influence others’ use by their own participation. Moreover, we found that the higher the blog usage by others in an employee’s relational network, the higher the blog usage by that employee. usage in positional and spatial networks did not have a significant effect on blog usage. this study is closely related to prior literature on the role of network externalities on technology use [36]. Our main contribution is that we extend this literature in several ways. First, we extend the theory of network externalities to complement the explanatory power of various social influence theories. We also study how individual characteristics such as age and gender moderate the role of network externalities on technology use and how positive feedback from others influences an individual’s continued use of a technology. Further, we apply these theories to a new technology such as blogging as opposed to previous studies that have typically examined traditional organizational technologies. Second, we examine the effect of positive feedback from peers on an individual’s usage of blogs in an organization. Prior work on reinforcement theory in organizations has mainly examined the role of formal mechanisms in influencing individual behavior. third, we consider the asymmetric nature of network externalities by examining the relative importance of different social groups such as managers, work groups, peers in the organizational hierarchy, as well as location. Fourth, we examine actual usage within the networks as opposed to perceptual measures (e.g., [55]) or overall installed base in the networks (e.g., [36]). Finally, although kraut et al. [36] studied the role of network externalities on use of communication technologies, there is little research on network externalities in the context of other information systems (IS) (e.g., knowledge management systems).