Knowledge that Transforms

Star and Ruhleder’s (1996) influential “relational view” of infrastructure is usually understood as a relation between technologies and organizational practices. However, a significant part of Star and Ruhleder’s original proposal has been overlooked—that infrastructure becomes a home for somebody. In this paper, we give an alternative interpretation of this relational view by focusing on the relation between a person and their infrastructure, rather than on the relation between technologies and practices. We use Heidegger’s (1927/1962) phenomenology in Being and Time to theorize what such a home might entail and a novel data collection method to study infrastructuring empirically from the perspective of a person. On this basis, we offer new theoretically grounded interpretations of infrastructure and infrastructuring. Empirically, we identify two modes of infrastructuring not previously distinguished. The perspective sheds new light on a number of key themes and debates in the literature and on infrastructuring in practice.

This study examines the impact of coordination capabilities provided by enterprise systems (ES), manifested in ES standardization and extensiveness, on merger and acquisition (M&A) outcomes in the short and long term. Specifically, we examine the extent to which the ES standardization and ES extensiveness of the acquiring and target firms contribute to value creation in M&A initiatives. We also study the relationship between the ES standardization and ES extensiveness of the acquiring and target firms and M&A offer premiums. The empirical analysis suggests that the ES standardization of acquirers is related to lower offer premiums and a higher market response to the acquisition for the acquirer. However, it is the ES extensiveness of the acquirer that improves long-term performance i.e., decreases goodwill impairment and increases operating performance. The analysis also indicates that the target’s ES standardization increases the premium for the target firm and generates a positive market response to the acquisition for the target firm. Overall, the analysis indicates that the ES standardization likely affects the integration cost that influences market response to the M&A and to the M&A premium in the short term, but it is ES extensiveness that affects the realized synergy from the M&A that affects long-term performance.

The explosive spread of false news on social media has severely affected many areas such as news ecosystems, politics, economics, and public trust, especially amid the COVID-19 infodemic. Machine intelligence has met with limited success in detecting and curbing false news. Human knowledge and intelligence hold great potential to complement machine-based methods. Yet they are largely underexplored in current false news detection research, especially in terms of how to efficiently utilize such information. We observe that the crowd contributes to the challenging task of assessing the veracity of news by posting responses or reporting. We propose combining these two types of scalable crowd judgments with machine intelligence to tackle the false news crisis. Specifically, we design a novel framework called CAND, which first extracts relevant human and machine judgments from data sources including news features and scalable crowd intelligence. The extracted information is then aggregated by an unsupervised Bayesian aggregation model. Evaluation based on Weibo and Twitter datasets demonstrates the effectiveness of crowd intelligence and the superior performance of the proposed framework in comparison with the benchmark methods. The results also generate many valuable insights, such as the complementary value of human and machine intelligence, the possibility of using human intelligence for early detection, and the robustness of our approach to intentional manipulation. This research significantly contributes to relevant literature on false news detection and crowd intelligence. In practice, our proposed framework serves as a feasible and effective approach for false news detection.

The globalization of work raises important questions related to the employment of workers across geographies and how the complementarity or substitution of workers across country borders influences firm profitability. In particular, tension often exists regarding the substitution or complementarity of workers located outside the U.S. or within the U.S. for American firms. We investigate this question in the context of information technology (IT) professionals and assess how domestic and foreign IT professionals contribute to firm profit by utilizing a rare firm-level dataset with information on the locational composition of IT professionals within and outside the U.S. Exploiting a labor market supply-side exogenous shock induced by the American Competitiveness in the Twenty-First Century Act (AC21), which increased the availability of H-1B visas in the U.S. in 2001, we find that foreign IT professionals located offshore and American IT professionals located onshore complement each other in generating profits. Our model and empirical findings are important both for informing firm choices and for shaping and creating public policies that so far appear to have been informed more by emotion than by data and science.

We study the effect of peer influence on products that exhibit positive network externalities to non-adopters, i.e., products that benefit adopters’ friends even if they do not adopt. In contrast to products that exhibit positive network externalities upon adoption, this structure of incentives likely results in negative peer influence: the more friends that adopt the product, the smaller the incentive to adopt. We measure this effect empirically by using observational data from a large mobile carrier serving 5.7 million users. We estimate the effect of peer influence across five different products of this type. A naive approach to do this results in a positive estimate for peer influence due to unobserved homophily. We follow two approaches to address this issue. First, we suggest using the number of friends that end up adopting a product as a proxy for unobserved user-fixed effects. Second, we control for homophily by applying a shuffle test, i.e., we compare the effect of peer influence from the original data with the effect obtained from comparable randomly generated data without peer influence. We obtain negative estimates from both approaches, which adds robustness to our findings. Finally, we show that even for these products, the effect of peer influence associated with the first friends that adopt the product is positive because they still convey useful information that reduces uncertainty. The negative effect of peer influence arises only for subsequent friends that adopt the product. While these friends are unlikely to convey new information about the product, they decrease the economic incentive to adopt, resulting in a negative aggregate effect of peer influence.

It has been argued that the theory borrowing practices in IS research have become workmanlike—appropriate and effective, but lacking innovation. This concern is particularly salient at a time when digital phenomena are profoundly transforming society. Therefore, it is legitimate to ask: Are our theory borrowing practices hampering our ability to grapple with revolutionary developments in IS, and if so, what can be done? Through an investigation of the field’s borrowing of transaction cost economics theory, we find extant IS research largely (1) borrows for theory testing within the IS context, (2) develops models that uninspiringly reflect the borrowed theory, and (3) treats the IS as an exogenous actor. In this article, we propose an alternative approach to theory borrowing, inspired by conceptual blending theory. Our approach focuses on the structural nature of IS phenomena and borrowed theories. Such a structure-based approach can reveal correspondence between IS phenomena and unexpected reference theories while also highlighting discrepancies that serve as an opportunity for novel integrations of an information system into the reference theory. We contend that this approach can infuse flexibility into our theory borrowing practices in ways that will increase our capacity for developing innovative explanations of emerging phenomena.

Online social networks are increasingly being used to conduct commercial activities, and many online social networking platforms allow users to sell products to their online connections. Although extensive research has been conducted on the interactions among buyers within a social network, interactions among sellers have rarely been explored. Using seller data from a company that sells on a major online social networking platform in China, we empirically examine how sellers’ efforts and sales performance are affected by the efforts and sales performance of other sellers they are connected to (i.e., their inviters and invitees) and the commissions they themselves have received. We find evidence for social influence and competition effects in the “inviter-to-invitee” direction and sellers’ free-riding behavior driven by the commissions they receive from their invitees’ sales. These results extend the social network literature that has largely focused on connected buyers (or users) to connected sellers and offer implications for social networking platforms to promote seller participation.

Performance impacts of investments in information technologies (ITs) are difficult to evaluate. External investors are further constrained by their lack of visibility into the firm’s intangible, complementary actions and capabilities, creating an information asymmetry between them and the firm’s executives. Building on signaling theory and the research on senior executives’ trades in a firm’s stock, this paper addresses the following question: How are the stock trades by a firm’s senior executives before a major IT investment by the firm associated with the future value to the firm from that IT investment? The results based on data on 2,898 publicly announced IT investments from 926 firms during 2002–2016 suggest that (1) the purchasing of a firm’s stock by its senior executives before a firm’s IT investment is associated with the investment’s long-term effect on firm value; (2) such stock purchases by a firm’s senior executives are associated with a stronger positive (negative) relationship between the IT’s newness and the long-term abnormal returns to firms emphasizing a revenue enhancement (cost reduction) IT strategy; (3) for firms pursuing a hybrid strategy, purchases by CIOs but not purchases by CEOs or the newness of IT are associated with firm value, and (4) purchases made by CIOs provide greater information about the IT investment’s impact on firm value than purchases made by CEOs. We further improve our predictive model’s accuracy from 75% for a model including the fit between IT newness and IT strategy to 80% and 91% when considering purchases by CEOs or CIOs, respectively, and 92% when considering purchases by both executives.

It has been argued in recent years that software is a significant value-creating factor within the manufacturing sector, leading to an increased interest in understanding the mechanisms by which firms may benefit from software-based innovation. Empirical work in evaluating these mechanisms, however, remains underdeveloped. In this paper, we examine one such process through which software-based innovation may provide value for information technology hardware firms in the U.S. Specifically, we examine the influence of software patents on the extent to which firms are able to benefit from product differentiation in their product markets. Using data on over 380,000 patent grants for innovations filed by 730 public IT hardware firms over the time period 1996-2015, we find that greater levels of software-based innovation within the firm are associated with higher levels of product differentiation in product markets: increases in the intensity of software patents within the firm’s patent stock, which we refer to as software intensity, are associated with lower total similarity of product offerings, relative to those offered by rivals, as well as fewer effective competitors in the market. Furthermore, using a different dataset consisting of 23,000 new IT hardware product announcements, we show that firms with greater software intensity subsequently launch a higher number of new products. Moreover, these firms are more likely to launch products that are not only differentiated from those of rivals but also distinct from their own product lines. Our research contributes to the emerging literature on software-based innovation by substantiating an important mechanism through which software helps transform industry sectors, specifically through product differentiation.

In today’s environment characterized by business dynamism and information technology (IT) advances, firms must frequently update their enterprise information systems (EIS) and their use policies to support changing business operations. In this context, users are challenged to maintain EIS compliance behavior by continuously learning new ways of using EIS. Furthermore, it is imperative to businesses that employees of a functional unit maintain EIS compliance behavior collectively, due to the interdependent nature of tasks that the unit needs to accomplish through EIS. However, it is particularly challenging to achieve such a collective level of EIS compliance, due to the difficulty that these employees may encounter in quickly learning updated EIS. It is, therefore, vital for firms to establish effective managerial principles to ensure collective EIS compliance of a functional unit in a dynamic environment. To address this challenge, this study develops a research model to explain collective EIS compliance by integrating theoretical lens on social context and performance management context with social capital theory. It proposes that social context, an organizational environment characterized by trust and support, positively affects collective EIS compliance by developing business–IT social capital that enhances mutual learning between business and IT personnel. Furthermore, the performance management context, an organizational environment characterized by discipline and “stretch,” is seen to have a direct and beneficial effect on collective EIS compliance as well as an indirect, moderating effect on the causal chain among social contexts, business–IT social capital, and collective EIS compliance. General empirical support for this research model is provided via a multiple-sourced survey of managers and employees of 159 functional units of 53 firms that use EIS, as well as their corresponding IT unit managers. The theoretical and practical implications of these findings are discussed.