Team‐Level Antecedents of Individuals' Knowledge Networks*

Individuals' knowledge networks are widely considered to contribute substantially to the effectiveness and efficiency of organizations. While the positive effects of knowledge networks as a primary driver of social capital have recently received considerable research attention, potential determinants of individuals' network building have not yet been adequately addressed. In this study, we investigate how certain team‐level properties affect team members' development of knowledge networks through the course of a team project. Using data from 430 team leaders and team members pertaining to 145 software development projects, we test cross‐level hypotheses using hierarchical linear modeling (HLM). The results indicate that the team's perception of the organizational knowledge‐sharing climate, the team's networking preference, and the team's perceived importance of networking for project success positively affect individuals' network building. Furthermore, a team's perception of the adequacy of its technical competency and a team's perception of the adequacy of its material resources inhibit team members' individual network development. Theoretical and managerial implications are discussed.     

Estimating Social Influences from Social Networking Sites—Articulated Friendships versus Communication Interactions

Despite the ubiquity of social networking sites, the online social networking industry is in search of effective marketing strategies to better profit from their established user base. Social media marketing strategies build on the premise that the social network of online users can be predicted and social influences among online users can be estimated. However, the existence of various heterogeneous social interactions on social networking sites presents a challenge for social network prediction and social influence estimation. In this article we draw upon the literatures on self‐presentation on social networking sites and signaling in online social networking to categorize six heterogeneous online social interactions on social networking sites into two types—articulated friendships and communication interactions. This article provides empirical evidence for the differences between articulated friendships and communication interactions and the corresponding articulated and communication networks. In order to compare the impacts of the social influences based on these two networks, we utilize support vector machines to build a classifier to predict virtual community membership and we further estimate the marginal effects of these social influences using a two‐stage probit least squares method. We find significant explanatory power of social influences in predicting virtual community membership. Although the communication network is much sparser than the articulated network, social influences based on the communication network achieve similar performance as the articulated network. These findings provide important implications for social media marketing as well as the management of virtual communities.     

Infant and child mortality in India: trends in inequalities across economic groups

This paper examines the trends in economic inequalities with respect to infant and child mortality in India using three rounds of the Indian National Family Health Survey conducted in 1992–1993, 1998–1999, and 2005–2006. The paper uses concentration index, and pooled discrete-time survival regression model to examine the aforementioned trends and regional patterns. The findings suggest a decreasing trend in economic inequality in infant mortality but an upward trend in economic inequality in child mortality in India. Economic inequalities in infant mortality have narrowed in the southern region, whereas they have widened in the western region and risen in the northern region. However, mixed trends in concentration indices were found in the different regions of India in the case of child mortality.     

Development of the India Patriarchy Index: Validation and Testing of Temporal and Spatial Patterning

Social Indicators Research - While existing indices of gender equality measure the role of women’s status and position, they inadequately contextualize the broader construct of patriarchy, a...     

Static and Dynamic Pricing of Excess Capacity in a Make‐to‐Order Environment

We consider a make‐to‐order manufacturer that serves two customer classes: core customers who pay a fixed negotiated price, and “fill‐in” customers who make submittal decisions based on the current price set by the firm. Using a Markovian queueing model, we determine how much the firm can gain by explicitly accounting for the status of its production facility in making pricing decisions. Specifically, we examine three pricing policies: (1) static, state‐independent pricing, (2) constant pricing up to a cutoff state, and (3) general state‐dependent pricing. We determine properties of each policy, and illustrate numerically the financial gains that the firm can achieve by following each policy as compared with simpler policies. Our main result is that constant pricing up to a cutoff state can dramatically outperform a state‐independent policy, while at the same time achieving most of the increase in revenue achievable from general state‐dependent pricing. Thus, we find that constant pricing up to a cutoff state presents an attractive tradeoff between ease of implementation and revenue gain. When the costs of policy design and implementation are taken into account, this simple heuristic may actually out‐perform general state‐dependent pricing in some settings.