Search

This article introduces a number of methods that can be useful for examining the emergence of large-scale structures in collaboration networks. The study contributes to sociological research by investigating how clusters of research collaborators evolve and sometimes percolate in a collaboration network. Typically, we find that in our networks, one cluster among the leading ones eventually wins the growth race by percolating through the network, spanning it and rapidly filling up a significant volume of it. We show how this process is governed by the dynamics of cluster growth in the network. When operating in a percolating regime, this class of networks possesses many useful functional properties, which have important sociological implications. We first develop the methodological tools to perform a study of the intrinsic clustering process. Then, to understand the actual large-scale structure formation process in the network, we apply the theoretical methods to simulate a number of realistic scenarios, including one based on actual data on the collaboration behavior of a sample of researchers. From the perspective of social science research, our methods can be adapted to suit the application domains of many other types of real social processes.

To combat the effects of climate change and meet the need for clean energy, the global power sector, over the past few decades, has been undergoing a major transformation for which all possible renewable energy sources are currently being utilized. To achieve sustainable growth, India, like many other countries, is also in the process of energy transition, aiming to shift to renewable energy-based power generation. In this transition, research in Ocean Renewable Energy (ORE) technologies is rising to rapid prominence. This study examines the state of ORE research in India and compares it with global research activities in this field using a graph-theoretical framework for collaboration co-authorship networks in ORE using bibliometric data on published scholarly articles indexed in two well-known electronic databases covering two 10-year windows: 1999-2008 and 2009-2018, inclusive. A strategic analysis of a number of metrics characterizing the networks’ large-scale structures reveals that the Indian network is highly fragmented, resulting in a singular dearth of large-scale connections for Indian ORE researchers. We recommend effective research policies to improve knowledge generation and dissemination in ORE research collaboration in India (and many other countries in similar situations), based on our findings for Indian networks and pertinent parallels with global ORE. With growing concerns about sustainable energy utilization, our study has policy implications for pressing issues of energy demands in the country. [ABSTRACT FROM AUTHOR]

This paper provides a simulation model for scheduling service task operations and distributing related human resources in dispersed work centres. The managerial concern for the minimisation of temporal overhead costs of task operations in the face of fluctuating, short-term service demands is examined under restrictions imposed by resource availability, work hour flexibility and task-backlog fulfilment. Scheduling strategies are developed directly from the constrained reduction of temporal overheads of appointment and release operations in distributed, non-interlinked work centres. To ensure the model’s structural validity, simulated task backlogs are adjusted to the actual backlog-reducing procedures in real applications. The model provides means for setting up balanced work schedules that can greatly lower temporal overheads of appointment and release operations if workers are selected in accordance with compatible time availability and task qualifications. Direct comparisons of worker productivities in the different centres can also be made, allowing managers to locate bottleneck points of service operations when productivity falls short of desired expectations. The robustness of the model is ensured by finding significant parameter domains through Monte Carlo simulations, centred on data points collected from real-time demand functions in actual service operations. [ABSTRACT FROM PUBLISHER]

This article introduces a number of methods that can be useful for examining the emergence of large-scale structures in collaboration networks. The study contributes to sociological research by investigating how clusters of research collaborators evolve and sometimes percolate in a collaboration network. Typically, we find that in our networks, one cluster among the leading ones eventually wins the growth race by percolating through the network, spanning it and rapidly filling up a significant volume of it. We show how this process is governed by the dynamics of cluster growth in the network. When operating in a percolating regime, this class of networks possesses many useful functional properties, which have important sociological implications. We first develop the methodological tools to perform a study of the intrinsic clustering process. Then, to understand the actual large-scale structure formation process in the network, we apply the theoretical methods to simulate a number of realistic scenarios, including one based on actual data on the collaboration behavior of a sample of researchers. From the perspective of social science research, our methods can be adapted to suit the application domains of many other types of real social processes. [ABSTRACT FROM AUTHOR]