Achieving Mass Customization Through Modularity-Based Manufacturing Practices: A Customer-Driven Perspective

As uncertainty in markets and technology intensifies, organizations are adopting modularity-based manufacturing practices to achieve mass customization and cope with demands for increasingly customized products. Modularity-standardization and substitution principle to product and process design to create modular components and processes that can be configured into a wide range of end products to meet specific customer needs. This study defines customer closeness and modularity-based manufacturing develops instruments to measure these factors, builds a framework that relates customer closeness, modularity-based manufacturing practices, and mass customization, and tests structural relationships in this framework using LISREL

Systemic Risk of Contract

Complexity and uncertainty define our world, now more than ever. Scholars and practitioners have celebrated modular contract design as an especially effective tool to manage these challenges. Modularity divides complex structures into relatively discrete, independent components with simple connections. The benefits of this fundamental drafting approach are intuitive. Lawyers divide contracts into sections and provisions to make them easier to understand and reduce uncertainty. Dealmakers constructing complex transactions use portable agreements as building blocks to reduce drafting costs and enable innovation. Little attention, however, has been paid to the risks introduced by modularity in contracts. This Article demonstrates how this touted and now-ingrained drafting approach introduces new forms of the very costs it seeks to minimize. The Article is the first to identify the types of risks introduced by modularity at the intra-contract level, among provisions, and the inter-contract level, among agreements that constitute deals. The Article groups these risks into three categories: First, intertextualism, which occurs when the operation of a discrete, or even standard, provision seems clear in isolation but is made uncertain by the presence of other discrete terms. Second, modular drift, which occurs when drafters transplant provisions specific to one transactional context into another transactional context, introducing uncertainty. Third, latent triggers, which occur when compartmentalization invite s error or obscures a nuance in the interaction among discrete provisions. The Article urges courts to articulate distinctions between contract types and offers tools to contract drafters to mitigate uncertainty. It also makes a theoretical contribution with implications for contract doctrine and contract innovation. It shows how modularity can disrupt seemingly stable, standardized provisions, diminishing their certainty and imposing information costs on future drafters who seek to rely on precedent provisions or agreements. It thereby identifies a critical dimension of contract risk that complicates the balancing of standardization and private choice in contracts

Median evidential c-means algorithm and its application to community detection

Median clustering is of great value for partitioning relational data. In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical framework of belief functions is proposed. The median variant relaxes the restriction of a metric space embedding for the objects but constrains the prototypes to be in the original data set. Due to these properties, MECM could be applied to graph clustering problems. A community detection scheme for social networks based on MECM is investigated and the obtained credal partitions of graphs, which are more refined than crisp and fuzzy ones, enable us to have a better understanding of the graph structures. An initial prototype-selection scheme based on evidential semi-centrality is presented to avoid local premature convergence and an evidential modularity function is defined to choose the optimal number of communities. Finally, experiments in synthetic and real data sets illustrate the performance of MECM and show its difference to other methods

Ideological and Temporal Components of Network Polarization in Online Political Participatory Media

Political polarization is traditionally analyzed through the ideological stances of groups and parties, but it also has a behavioral component that manifests in the interactions between individuals. We present an empirical analysis of the digital traces of politicians in politnetz.ch, a Swiss online platform focused on political activity, in which politicians interact by creating support links, comments, and likes. We analyze network polarization as the level of intra- party cohesion with respect to inter-party connectivity, finding that supports show a very strongly polarized structure with respect to party alignment. The analysis of this multiplex network shows that each layer of interaction contains relevant information, where comment groups follow topics related to Swiss politics. Our analysis reveals that polarization in the layer of likes evolves in time, increasing close to the federal elections of 2011. Furthermore, we analyze the internal social network of each party through metrics related to hierarchical structures, information efficiency, and social resilience. Our results suggest that the online social structure of a party is related to its ideology, and reveal that the degree of connectivity across two parties increases when they are close in the ideological space of a multi-party system.Comment: 35 pages, 11 figures, Internet, Policy & Politics Conference, University of Oxford, Oxford, UK, 25-26 September 201