Why are some coalitions more successful than others in setting standards? Empirical evidence from the Blu-ray vs. HD-DVD standard war

Standard-setting coalitions are increasingly composed of rival firms from different sectors and are characterized by simultaneous and/or sequential cooperation and competition among their members. This paper examines why firms choose to belong to two standard-setting coalitions instead of one and what determines the success of a standard coalition. We test empirically for network effect, experience effect, and coopetitive effect in the Blu-ray vs. HD-DVD standard war. We find that the higher the similarity of the members in the coalition, the greater the probability of standard coalition success. Furthermore, relatedness leads to a greater probability of joining both competing coalitions, but at a given degree of knowledge difference, an opposite effect exists.Blu-ray; HD-DVD; coalition; coopetition; standard war

Why are some coalitions more successful than others in setting standards? Empirical evidence from the Blu-ray vs. HD-DVD standard war

Standard-setting coalitions are increasingly composed of rival firms from different sectors and are characterized by simultaneous and/or sequential cooperation and competition among their members. This paper examines why firms choose to belong to two standard-setting coalitions instead of one and what determines the success of a standard coalition. We test empirically for network effect, experience effect, and coopetitive effect in the Blu-ray vs. HD-DVD standard war. We find that the higher the similarity of the members in the coalition, the greater the probability of standard coalition success. Furthermore, relatedness leads to a greater probability of joining both competing coalitions, but at a given degree of knowledge difference, an opposite effect exists

Small-world networks and management science research: a review

This paper reviews the literature on small-world networks in social science and management. This relatively new area of research represents an unusual level of crossdisciplinary research within social science and between social science and the physical sciences. We review the findings of this emerging area with an eye to describing the underlying theory of small worlds, the technical apparatus, promising facts, and unsettled issues for future research

Competitive Brokerage, Information Technology and Internal Resources

To thrive in the current embedded and electronic competitive environment, organizations must achieve advantageous positions within their networks of competition. We strengthen the understanding of the genesis of network structures by examining the IT-enabled capabilities and internal resource endowment that determine an advantageous position in competition networks, which we term as competitive brokerage. We propose that firms should consider their competitive brokerage position to elaborate a successful e-business strategy. We employ a two-stage Tobit regression on a longitudinal competition network that spans 13 industries and demonstrate that commercial, technical and intangible resources influence competitive brokerage. We find that IT-enabled information management capability strengthens the effects of intangible resources to attain a competitive brokerage position. Our study contributes towards the IT business value, resource base view and competitive dynamics literatures. Overall, our results demonstrate that IT plays a critical role in enabling firms to face multi-market competition in the embedded economy

Understanding Hidden Memories of Recurrent Neural Networks

Recurrent neural networks (RNNs) have been successfully applied to various natural language processing (NLP) tasks and achieved better results than conventional methods. However, the lack of understanding of the mechanisms behind their effectiveness limits further improvements on their architectures. In this paper, we present a visual analytics method for understanding and comparing RNN models for NLP tasks. We propose a technique to explain the function of individual hidden state units based on their expected response to input texts. We then co-cluster hidden state units and words based on the expected response and visualize co-clustering results as memory chips and word clouds to provide more structured knowledge on RNNs' hidden states. We also propose a glyph-based sequence visualization based on aggregate information to analyze the behavior of an RNN's hidden state at the sentence-level. The usability and effectiveness of our method are demonstrated through case studies and reviews from domain experts.Comment: Published at IEEE Conference on Visual Analytics Science and Technology (IEEE VAST 2017

Bank lending networks, experience, reputation, and borrowing costs.

We investigate the network structure of syndicated lending markets and evaluate the impact of lenders’ network centrality, considered as measures of their experience and reputation, on borrowing costs. We show that the market for syndicated loans is a “small world” characterized by large local density and short social distances between lenders. Such a network structure allows for better information and resources flows between banks thus enhancing their social capital. We then show that lenders’ experience and reputation play a significant role in reducing loan spreads and thus increasing borrower’s wealth.agency costs, bank syndicate, experience, loan syndication, reputation, small world, social network analysis.

Cluster Emergence and Network Evolution: A longitudinal analysis of the inventor network in Sophia-Antipolis

A widely held view in cluster research is that clusters are characterized by the presence of networks of local collective learning. However, with a growing number of studies indicating this is not necessarily the case, the question arises under which conditions clusters exhibit dense networks of local collective learning. Taking a longitudinal view at the high-tech cluster of Sophia-Antipolis this paper investigates whether and how networks of collective learning among inventors emerged throughout the growth of the cluster from the late 1970s onwards. On the basis of EPO and USPTO patent data we reconstructed co-inventorship networks for the cluster’s two main industries. Detecting a network of local collective learning only in Information Technology, in which growth has been increasingly based on spin-offs and start-ups, and not in Life Sciences, we suggest that the extent and nature of the local concentration of firms over time strongly affect the evolution of local collective learning networks.cluster evolution, network evolution, collective learning, Sophia-Antipolis

SOCIAL NETWORKS AND CONTRACT ENFORCEMENT IN IT OUTSOURCING

Most prior research on Information Technology Outsourcing(ITO) has characterized the dominant governance modes as either ‘Formal’ or ‘Relational,’ which rely on stringent assumptions of perfect foresight or about the extent to which one party can punish unilateral deviations by the other. We propose a third alternative in addition to dyadic measures of inter-firm reputation. The reputation of an actor may be associated with how the firm is positioned in a network, which in turn influences how information about a particular actor flows within the network. Such aspects of structural embeddedness suggest a role in predicting characteristics of inter-firm exchange. The network capital offers a measure to mitigate the uncertainty associated the nature of service outsourced and the service provider. The network of trading partners enables a community enforcement of contracting terms by providing safeguards that may not be offered by traditional measures of formal or relational governance. Based on a large dataset of publicly announced ITO arrangements, we examine the role that structural embeddedness can play in predicting contract duration. Our preliminary results are very encouraging. We find evidence suggesting that network position does matter in predicting contract structure over and above the traditional economic variables