Knowledge that Transforms

In this study we examine the effect of customers' participation in a firm's social media efforts on the intensity of the relationship between the firm and its customers as captured by customers' visit frequency. We further hypothesize and test for the moderating roles of social media activity and customer characteristics on the link between social media participation and the intensity of customer-firm relationship. Importantly, we also quantify the impact of social media participation on customer profitability. We assemble a novel data set that combines customers' social media participation data with individual customer level transaction data. To account for endogeneity that could arise because of customer self-selection, we utilize the propensity score matching technique in combination with difference in differences analysis. Our results suggest that customer participation in a firm's social media efforts leads to an increase in the frequency of customer visits. We find that this participation effect is greater when there are high levels of activity in the social media site and for customers who exhibit a strong patronage with the firm, buy premium products, and exhibit lower levels of buying focus and deal sensitivity. We find that the above set of results holds for customer profitability as well. We discuss theoretical implications of our results and offer prescriptions for managers on how to engage customers via social media. Our study emphasizes the need for managers to integrate knowledge from customers' transactional relationship with their social media participation to better serve customers and create sustainable business value.

Internet retailers have been making significant investments in Web technologies, such as zoom, alternative photos, and color swatch, that are capable of providing detailed product-oriented information and, thereby, mitigating the lack of “touch and feel,” which, in turn, is expected to lower product returns. However, a clear understanding of the relationship between these technologies and product returns is still lacking. Our study attempts to fill this gap by using several econometric models to explore the said relationship. Our unique and rich data set from a women's clothing company allows us to measure technology usage at the product level for each consumer. The results show that, in this context, zoom usage has a negative coefficient, suggesting that a higher use of the zoom technology is associated with fewer returns. Interestingly, we find that a higher use of alternative photos is associated with more returns and, perhaps more importantly, with lower net sales. Color swatch, on the other hand, does not seem to have any effect on returns. Thus, our findings show that different technologies have different effects on product returns. We provide explanations for these findings based on the extant literature. We also conduct a number of tests to ensure the robustness of the results.

Social media are fundamentally changing the way we communicate, collaborate, consume, and create. They represent one of the most transformative impacts of information technology on business, both within and outside firm boundaries. This special issue was designed to stimulate innovative investigations of the relationship between social media and business transformation. In this paper we outline a broad research agenda for understanding the relationships among social media, business, and society. We place the papers comprising the special issue within this research framework and identify areas where further research is needed. We hope that the flexible framework we outline will help guide future research and develop a cumulative research tradition in this area.

Companies have increasingly advocated social media technologies to transform businesses and improve organizational performance. This study scrutinizes the predictive relationships between social media and firm equity value, the relative effects of social media metrics compared with conventional online behavioral metrics, and the dynamics of these relationships. The results derived from vector autoregressive models suggest that social media-based metrics (Web blogs and consumer ratings) are significant leading indicators of firm equity value. Interestingly, conventional online behavioral metrics (Google searches and Web traffic) are found to have a significant yet substantially weaker predictive relationship with firm equity value than social media metrics. We also find that social media has a faster predictive value, i.e., shorter “wear-in” time, than conventional online media. These findings are robust to a consistent set of volume-based measures (total blog posts, rating volume, total page views, and search intensity). Collectively, this study proffers new insights for senior executives with respect to firm equity valuations and the transformative power of social media.

We identify two post-acceptance information system (IS) usage behaviors related to how employees leverage implemented systems. Routine use (RTN) refers to employees' using IS in a routine and standardized manner to support their work, and innovative use (INV) describes employees' discovering new ways to use IS to support their work. We use motivation theory as the overarching perspective to explain RTN and INV and appropriate the rich intrinsic motivation (RIM) concept from social psychology to propose a conceptualization of RIM toward IS use, which includes intrinsic motivation toward accomplishment (IMap), intrinsic motivation to know (IMkw), and intrinsic motivation to experience stimulation (IMst). We also consider the influence of perceived usefulness (PU)—a representative surrogate construct of extrinsic motivation toward IS use—on RTN and INV. We theorize the relative impacts of the RIM constructs and PU on RTN and INV and the role of personal innovativeness with IT (PIIT) in moderating the RIM constructs' influences on INV. Based on data from 193 employees using a business intelligence system at one of the largest telecom service companies in China, we found (1) PU had a stronger impact on RTN than the RIM constructs, (2) IMkw and IMst each had a stronger impact on INV than either PU or IMap, and (3) PIIT positively moderated the impact of each RIM construct on INV. Our findings provide insights on managing RTN and INV in the post-acceptance stage.

Digital technologies have made networks ubiquitous. A growing body of research is examining these networks to gain a better understanding of how firms interact with their consumers, how people interact with each other, and how current and future digital artifacts will continue to alter business and society. The increasing availability of massive networked data has led to several streams of inquiry across fields as diverse as computer science, economics, information systems, marketing, physics, and sociology. Each of these research streams asks questions that at their core involve “information in networks”—its distribution, its diffusion, its inferential value, and its influence on social and economic outcomes. We suggest a broad direction for research into social and economic networks. Our analysis describes four kinds of investigation that seem most promising. The first studies how information technologies create and reveal networks whose connections represent social and economic relationships. The second examines the content that flows through networks and its economic, social, and organizational implications. A third develops theories and methods to understand and utilize the rich predictive information contained in networked data. A final area of inquiry focuses on network dynamics and how information technology affects network evolution. We conclude by discussing several important cross-cutting issues with implications for all four research streams, which must be addressed if the ensuing research is to be both rigorous and relevant. We also describe how these directions of inquiry are interconnected: results and ideas will pollinate across them, leading to a new cumulative research tradition.

Privacy is of prime importance to many individuals when they attempt to develop online social relationships. Nonetheless, it has been observed that individuals' behavior is at times inconsistent with their privacy concerns, e.g., they disclose substantial private information in synchronous online social interactions, even though they are aware of the risks involved. Drawing on the hyperpersonal framework and the privacy calculus perspective, this paper elucidates the interesting roles of privacy concerns and social rewards in synchronous online social interactions by examining the causes and the behavioral strategies that individuals utilize to protect their privacy. An empirical study involving 251 respondents was conducted in online chat rooms. Our results indicate that individuals utilize both self-disclosure and misrepresentation to protect their privacy and that social rewards help explain why individuals may not behave in accordance with their privacy concerns. In addition, we find that perceived anonymity of others and perceived intrusiveness affect both privacy concerns and social rewards. Our findings also suggest that higher perceived anonymity of self decreases individuals' privacy concerns, and higher perceived media richness increases social rewards. Generally, this study contributes to the information systems literature by integrating the hyperpersonal framework and the privacy calculus perspective to identify antecedents of privacy trade-off and predict individuals' behavior in synchronous online social interactions.

Diversity is a defining characteristic of global collectives facilitated by the Internet. Though substantial evidence suggests that diversity has profound implications for a variety of outcomes including performance, member engagement, and withdrawal behavior, the effects of diversity have been predominantly investigated in the context of organizational workgroups or virtual teams. We use a diversity lens to study the success of nontraditional virtual work groups exemplified by open source software (OSS) projects. Building on the diversity literature, we propose that three types of diversity (separation, variety, and disparity) influence two critical outcomes for OSS projects: community engagement and market success. We draw on the OSS literature to further suggest that the effects of diversity on market success are moderated by the application development stage. We instantiate the operational definitions of three forms of diversity to the unique context of open source projects. Using archival data from 357 projects hosted on SourceForge, we find that disparity diversity, reflecting variation in participants' contribution-based reputation, is positively associated with success. The impact of separation diversity, conceptualized as culture and measured as diversity in the spoken language and country of participants, has a negative impact on community engagement but an unexpected positive effect on market success. Variety diversity, reflected in dispersion in project participant roles, positively influences community engagement and market success. The impact of diversity on market success is conditional on the development stage of the project. We discuss how the study's findings advance the literature on antecedents of OSS success, expand our theoretical understanding of diversity, and present the practical implications of the results for managers of distributed collectives.

The hypercompetitive aspects of modern business environments have drawn organizational attention toward agility as a strategic capability. Information technologies are expected to be an important competency in the development of organizational agility. This research proposes two distinct roles to understand how information technology competencies shape organizational agility and firm performance. In their enabling role, IT competencies are expected to directly enhance entrepreneurial and adaptive organizational agility. In their facilitating role, IT competencies should enhance firm performance by helping the implementation of requisite entrepreneurial and adaptive actions. Furthermore, we argue that the effects of the dual roles of IT competencies are moderated by multiple contingencies arising from environmental dynamism and other sources. We test our model and hypotheses through a latent class regression analysis on data from a sample of 109 business-to-business electronic marketplaces. The results provide support for the enabling and facilitating roles of IT competencies. Moreover, we find that these dual effects vary according to environmental dynamism. The results suggest that managers should account for (multiple) contingencies (observed and unobserved) while assessing the effects of IT competencies on organizational agility and firm performance.

Information systems must be used effectively to obtain maximum benefits from them. However, despite a great deal of research on when and why systems are used, very little research has examined what effective system use involves and what drives it. To move from use to effective use requires understanding an information system's nature and purpose, which in turn requires a theory of information systems. We draw on representation theory, which states that an information system is made up of several structures that serve to represent some part of the world that a user and other stakeholders must understand. From this theory, we derive a high-level framework of how effective use and performance evolve, as well as specific models of the nature and drivers of effective use. The models are designed to explain the effective use of any information system and offer unique insights that would not be offered by traditional views, which tend to consider information systems to be just another tool. We explain how our theory extends existing research, provides a rich platform for research on effective use, and how it contributes back to the theory of information systems from which it was derived.