While information technology benefits society in numerous ways, it unfortunately also has potential to create new vulnerabilities. This special issue intends to stimulate thought and research into understanding and mitigating these vulnerabilities. We identify four mechanisms by which ubiquitous computing makes various entities (people, devices, organizations, societies, etc.) more vulnerable, including: increased visibility, enhanced cloaking, increased interconnectedness, and decreased costs. We use the papers in the special issue to explain these mechanisms, and then outline a research agenda for future work on digital vulnerabilities spanning four areas that are, or could become, significant societal problems with implications at multiple levels of analysis: Online harassment and incivility, technology-driven economic inequality, industrial Internet of Things, and algorithmic ethics and bias.
Health Information Exchanges (HIE) are becoming integral parts of the national healthcare reform efforts, chiefly because of their potential impact on cost reduction and quality enhancement in healthcare services. However, the potential of an HIE platform can only be realized when its multiple constituent users actively participate in using its variety of services. In this research, we model HIE systems as multisided platforms that incorporate self-service technologies whose value to the users depends on both user-specific and network-specific factors. We develop a model of adoption, use, and involvement of clinical practices in the coproduction of the HIE services. This model is grounded in social network theory, service operations theory, and institutional isomorphism theory. A longitudinal study of actual adoption and use behaviors of 2,054 physicians within 430 community medical practices in Western New York over a three-year period has been carried out to evaluate the proposed model. This study has been supported by HEALTHeLINK, the Regional Health Information Organization of Western New York, which has an extensive database comprising over half a million transactions on patient records by the HIE users. We extracted panel data on adoption, use, and service coproduction behaviors from this database and carried out a detailed analysis using metrics derived from the foundational theories. Positioning practices within two distinct but interrelated networks of patients and practitioners, we show that adoption, use, and service coproduction behaviors are influenced by the topographies of the two networks, isomorphic effects of large practices on the smaller ones, and practice labor inputs in HIE use. Our findings provide a comprehensive view of the drivers of HIE adoption and use at the level of medical practices. These results have implications for marketing and revenue management of HIE platforms, as well as public health and national/regional healthcare policy making.
The ongoing digitization of multiple industries has drastically reduced the half-life of skills and capabilities acquired by knowledge workers through formal education. Thus, firms are forced to make significant ongoing investments in training their employees to remain competitive. Existing research has not examined the role of training in improving firm-level productivity of knowledge firms. This paper provides an innovative econometric framework to estimate returns to such employee training investments made by firms. We use a panel dataset of small- to medium-sized Indian IT services firms and assess how training enhances human capital, a critical input for such firms, thereby improving firm revenues. We use econometric approaches based on optimization of the firm’s profit function to eliminate the endogenous choice of inputs common in production function estimations. We find that an increase in training investments is significantly linked to an increase in revenue per employee. Further, marginal returns to training are increasing firm size. Therefore, relatively speaking, large firms benefit more from training. For the median company in our data, we find that a dollar invested in training yields a return of $4.67, and this effect approximately grows 2.5 times for the 75th percentile-sized firm. A variety of robustness checks, including the use of data envelopment analysis, are used to establish the veracity of our results.
Consumer-generated media, particularly blogs, can help companies increase the visibility of their products without spending millions of dollars in advertising. Although a number of companies realize the potential of blogs and encourage their employees to blog, a good chunk of them are skeptical about losing control over this new media. Companies fear that employees may write negative things about them and that this may bring significant reputation loss. Overall, companies show mixed response toward negative posts on employee blogs- some companies show complete aversion; others allow some negative posts. Such mixed reactions toward negative posts motivated us to probe for any positive aspects of negative posts. In particular, we investigate the relationship between negative posts and readership of an employee blog. In contrast to the popular perception, our results reveal a potential positive aspect of negative posts. Our analysis suggests that negative posts act as catalyst and can exponentially increase the readership of employee blogs, suggesting that companies should permit employees to make negative posts. Because employees typically write few negative posts and largely write positive posts, the increase in readership of employee blogs generally should be enough to offset the negative effect of few negative posts. Therefore, not restraining negative posts to increase readership should be a good strategy. This raises a logical question: what should a firm's policy be regarding employee blogging? For exposition, we suggest an analytical framework using our empirical model
External financing is critical to ventures that do not have a revenue source but need to recruit employees, develop products, pay suppliers, and market their products/services. There is an increasing belief among entrepreneurs that electronic word-of-mouth (eWOM), specifically blog coverage, can aid in achieving venture capital financing. Conflicting findings reported by past studies examining eWOM make it unclear what to make of such beliefs of entrepreneurs. Even if there were generally agreed-upon results, a stream of literature indicates that because of the differences in traits between the prior investigated contexts and venture capital financing, the findings from the prior studies cannot be generalized to venture capital financing. Extant studies also fall short in examining the role of time and the status of entities generating eWOM in determining the influence of eWOM on decision making. To address this dearth of literature in a context that attracts billions of dollars every year, we investigate the effect of eWOM on venture capital financing. This study entails the challenging task of gathering data from hundreds of ventures along with other sources including VentureXpert, surveys, Google Blogsearch, Lexis-Nexis, and Archive.org. The key findings of our econometric analysis are that the impact of negative eWOM is greater than is the impact of positive eWOM and that the effect of eWOM on financing decreases with the progress through the financing stages. We also find that the eWOM of popular bloggers helps ventures in getting higher funding amounts and valuations. The empirical model used in this work accounts for inherent selection biases of entrepreneurs and venture capitalists, and we conduct numerous robustness checks for potential issues of endogeneity, selection bias, nonlinearities, and popularity cutoff for blogs. The findings have important implications for entrepreneurs and suggest ways by which entrepreneurs can take advantage of eWOM.
Online storage service providers grant a way for companies to avoid spending resources on maintaining their own in-house storage infrastructure and thereby allowing them to focus on their core business activities. These providers, however, follow a fixed, posted pricing strategy that charges the same price in each time period and thus bear all the risk arising out of demand uncertainties faced by their client companies. We examine the effects of providing a spot market with dynamic prices and forward contracts to hedge against future revenue uncertainty. We derive revenue-maximizing spot and forward prices for a single seller facing a known set of buyers. We perform a simulation study using publicly available traffic data regarding Amazon S3 clients from Alexa.com to validate our analytical results. Our field study supports our analysis and indicates that spot markets alone can enhance revenues to Amazon, but this comes at the cost of increased risks due to the increased market share in the spot markets. Furthermore, adding a forward contract feature to the spot markets can reduce risks while still providing the benefits of enhanced revenues. Although the buyers incur an increase in costs in the spot market, adding a forward contract does not cause any additional cost increase while transferring the risk to the buyers. Thus, storage grid providers can greatly benefit by applying a forward contract alongside the spot market.
Online retailers are increasingly using information technologies to provide value-added services to customers. Prominent examples of these services are online recommender systems and consumer feedback mechanisms, both of which serve to reduce consumer search costs and uncertainty associated with the purchase of unfamiliar products. The central question we address is how recommender systems affect sales. We take into consideration the interaction among recommendations, sales, and price. We then develop a robust empirical model that incorporates the indirect effect of recommendations on sales through retailer pricing, potential simultaneity between sales and recommendations, and a comprehensive measure of the strength of recommendations. Applying the model to a panel data set collected from two online retailers, we found that the strength of recommendations has a positive effect on sales. Moreover, this effect is moderated by the recency effect, where more recently released recommended items positively affect the cross-selling efforts of sellers. We also show that recommender systems help to reinforce the long-tail phenomenon of electronic commerce, and obscure recommendations positively affect cross-selling. We also found a positive effect of recommendations on prices. These results suggest that recommendations not only improve sales but they also provide added flexibility to retailers to adjust their prices. A comparative analysis reveals that recommendations have a higher effect on sales than does consumer feedback. Our empirical results show that providing value-added services, such as digital word of mouth and recommendations, allows retailers to charge higher prices while at the same time increasing demand by providing more information regarding the quality and match of products.
With the rapid growth of rich-media content over the Internet, content and service providers (SP) are increasingly facing the problem of managing their service resources cost-effectively while ensuring a high quality of service (QoS) delivery at the same time. In this research we conceptualize and model an Internetbased storage provisioning network for rich-media content delivery. This is modeled as a capacity provision network (CPN) where participants possess service infrastructures and leverage their topographies to effectively serve specific customer segments. A CPN is a network of SPs coordinated through an allocation hub. We first develop the notion of discounted QoS capabilities of storage resources. We then investigate the stability of the discount factors over time and the network topography using a test-bed on the Internet through a longitudinal empirical study. Finally, we develop a market maker mechanism for optimal multilateral allocation and surplus sharing in a network. The proposed CPN is closely tied to two fundamental properties of Internet service technology: positive network externality among cooperating SPs and the property of effective multiplication of capacity allocation among several distributed service sites. We show that there exist significant incentives for SPs to engage in cooperative allocation and surplus sharing. We further demonstrate that intermediation can enhance the allocation effectiveness and that the opportunity to allocation and surplus sharing can play an important role in infrastructure planning. In conclusion, this study demonstrates the practical business viability of a cooperative CPN market.
The ability to collect and disseminate individually identifiable microdata is becoming increasingly important in a number of arenas. This is especially true in health care and national security, where this data is considered vital for a number of public health and safety initiatives. In some cases legislation has been used to establish some standards for limiting the collection of and access to such data. However, all such legislative efforts contain many provisions that allow for access to individually identifiable microdata without the consent of the data subject. Furthermore, although legislation is useful in that penalties are levied for violating the law, these penalties occur after an individual's privacy has been compromised. Such deterrent measures can only serve as disincentives and offer no true protection. This paper considers security issues involved in releasing microdata, including individual identifiers. The threats to the confidentiality of the data subjects come from the users possessing statistical information that relates the revealed microdata to suppressed confidential information. The general strategy is to recode the initial data, in which some subjects are "safe" and some are at risk, into a data set in which no subjects are at risk. We develop a technique that enables the release of individually identifiable microdata in a manner that maximizes the utility of the released data while providing preventive protection of confidential data. Extensive computational results show that the proposed method is practical and viable and that useful data can be released even when the level of risk in the data is high.
Advances in online technologies and bandwidth availability have opened new vistas for online distribution of digital goods, but potential benefits for consumers are juxtaposed against challenges for retailers. Here, we investigate one type of digital experience good--music--whose market environment includes the very real presence of online piracy. Although arguments abound for and against online distribution of such digital goods, little research exists in this area. We develop a model of consumer search for such an experience good, and study different emerging market environments for retailers, where consumers can pirate music online. Retailer cost to publishers is modeled using a variety of licensing schemas. Survey results, together with data from online sharing networks, are utilized to validate a key assumption. Finally, computational analysis is used to develop insights that cannot be obtained analytically. Our results indicate that decreasing piracy is not necessarily equivalent to increasing profit, and online selling strategies can provide additional profits for a traditional retailer even in the presence of piracy. We show that leading strategies for business in such goods should include pricing options, provision of efficient search tools, and new licensing structures.
The pervasiveness of software piracy throughout the world is having a profound effect on the software publishing industry and the development of digital intellectual properties and technologies--especially in developing countries, where the piracy rates are extremely high. An economic model is first presented that incorporates the incentive structures for governments, software publishers, and individual consumers. The analytical model provides the economic rationale for the reluctance of a number of governments to aggressively enact and enforce intellectual property rights. An important proposition derived from the analysis states that the government's incentive to enact and enforce copyright laws are closely related to the size of the domestic software industry. The ensuing empirical study provides support for the proposition and further suggests that this relationship holds regardless of the income levels of the countries. Our analysis reveals that alliances between foreign and domestic software publishers through product relationships can be mutually beneficial and will provide an environment of increased copyright enforcement. These results provide a viable strategy to combat global software piracy. With strong policies on copyright enforcement, and a vigorous promotion of alliances between foreign and domestic publishers, a government can increase the net welfare of the country and help establish a strong domestic software industry. Through product relationships with domestic publishers, a foreign publisher can improve profits and operate in an environment of increased intellectual property protection. We then present a general model of ethical behavior related to the impact of behavioral and cultural factors on software piracy. The purpose of this model is to examine whether these determinants of piracy behavior are supranational and transcend cultural and ethical barriers. An empirical study involving U.S. and Indian graduate students suggests that the ge...
In an attempt to protect their intellectual property and compete effectively in an increasingly dynamic marketplace, software publishers have employed a number of preventive and deterrent controls to counter software piracy. Conventional wisdom suggests that reducing piracy will force consumers to acquire software legitimately, thus increasing firm profits. We develop an analytical model to test the implications of antipiracy measures on publisher profits. Our results suggest that preventive controls decrease profits and deterrent controls can potentially increase profits. Empirical results are also presented that support the proposition on the impact of deterrent controls on the extent of software piracy derived from the analytical model.