Efficient Structures for Innovative Social Networks

What lines of communication among members of an organization are most effective in the early, ideation phase of innovation? We investigate this question with a recombination and selection model of knowledge transfer operating through a social network. We measure cost in human time, and seek efficient social network structures in the time--total cost plane (minimize ideation time subject to an upper bound on total cost, or vice versa) and in the time--cost per period plane, with a similar interpretation. Our results suggest that efficiently innovative organizations look nothing like what one intuitively associates with standard formal organizations with strict and unchanging lines of communication, nor do they conform with what one might expect from static social network representations of communication patterns. Rather, ideation is accelerated when people dynamically churn through a large (ideally the entire population) set of conversational partners over time, which naturally begets short path lengths and eliminates information bottlenecks. In organizations with these features group meetings do not help and can hurt the process, because many parallel conversations can achieve the same or better results as one-to-many communications. A family of networks called the complete wheel-stars emerges as an important family on the time-cost efficient frontier. Wheel-star graphs have a completely connected clique of agents at the center, with all other agents connected to the core but not to each other; the star and the complete graph are its extreme elements. We discuss the consequences of these results for organizations and sociometric analyses.http://deepblue.lib.umich.edu/bitstream/2027.42/64992/1/1136_lovejoy.pd

Managing stimulation of regional innovation subjects’ interaction in the digital economy

The reported study was funded by RFBR according to the research project No. 18-01000204_a, No. 16-07-00031_a, No. 18-07-00975_a.Purpose: The article is devoted to solving fundamental scientific problems in the scope of the development of forecasting modeling methods and evaluation of regional company’s innovative development parameters, synthesizing new methods of big data processing and intelligent analysis, as well as methods of knowledge eliciting and forecasting the dynamics of regional innovation developments through benchmarking. Design/Methodology/Approach: For regional economic development, it is required to identify the mechanisms that contribute to (or impede) the innovative economic development of the regions. The synergetic approach to management is based on the fact that there are multiple paths of IS development (scenarios with different probabilities), although it is necessary to reach the required attractor by meeting the management goals. Findings: The present research is focused on obtainment of new knowledge in creating a technique of multi-agent search, collection and processing of data on company’s innovative development indicators, models and methods of intelligent analysis of the collected data. Practical Implications: The author developed recommendations before starting the process of institutional changes in a specific regional innovation system. The article formulates recommendations on the implementation of institutional changes in the region taking into account the sociocultural characteristics of the region’s population. Originality/Value: It is the first time, when a complex of models and methods is based on the use of a convergent model of large data volumes processing is presented.peer-reviewe

Increasing territorial capitalization by incorporation of small enterprises into clusters

Modernization of the Russian national economy depends on small businesses and their involvement in capitalization of the territorial potential. This article discusses methods, models, and mechanisms of territorial capitalization based on incorporation of small business enterprises into clusters along with medium- and large businesses. We propose an optimization model for assessing the efficiency of such clusters: our research has shown that this model can be applied for decision-making in regional strategic planning. Methodologically, this study relies on the theories of industrial development and economic growth, the industrial cluster theory, and the works of Russian and international researchers on mechanisms of management of territorial potential, their establishment and implementation. Capitalization of the region's resource potential manifests itself in the form of static and dynamic effects. We developed models of interaction between small and other businesses and structures within a cluster oriented towards territorial capitalization. We demonstrated that incorporation of a university into a cluster structure increases the innovative capacity of all cluster members. This research may be further expanded to study the mechanisms of involving small businesses operating in peripheral areas into clusters

Measuring social capital and innovation in poor agricultural communities: The case of Cháparra, Peru

In the last decades substantive advance has been made in the measurement and understanding of frontier innovation in highly industrialized settings. However, little research focused on the process of learning and the introduction of novelties in smallholder farming of poor agricultural communities. Considering that 1.5 billion people in developing countries live in such smallholder households this is an essential shortcoming. In addressing three crucial questions about the measurement and promotion of endogenous local development this paper contributes to close this research gap. The three questions are: a) how can we measure social capital and innovation in poor agricultural communities, b) what is the impact of external agents on local structures and c) what are the relations between the social capital and the innovative performance of the farmer. In a first step a comprehensive questionnaire with 89 questions on diverse dimensions of social capital and innovation has been elaborated and applied to the agricultural valley of Cháparra in the South of Peru. The results allow for an indepth analysis of the capabilities, network position and innovative behavior of the farmers. In a second step, we apply social network analysis techniques to analyze the role and position of the relevant actors in the local as well as in the external technical information networks with a special focus on the influence of an external NGO. The analysis reveals a deep structural impact of the NGO and significant correlations between the network position of the farmers and their innovative performance. Three crucial issues for research on smallholder innovation are identified. First, diverse dimensions of social capital and innovation have to be differentiated when studying endogenous development. Second, it has to be assessed to which degree the modification of the existing social structures by external agents can be harmful or beneficial. Third, social network analysis can help us to gain a better understanding of the complex relations between social capital and innovation and how these can contribute to foster sustainable development projects. --social capital,innovation,smallholders,Cháparra,Peru,network analysis

Innovation, skills development and labour: a European perspective

LSE Enterprise was approached by Microsoft, a software developer engaged in lobbying the European Commission and Parliament, to appoint an expert team of academic consultants to research and write a series of four reports on various aspects of innovation. Working with our nominated academic director, LSE Enterprise put together a strong research team, who continue to work closely with the client to deliver each of the reports to a standard suitable for consumption by top EU policy-makers, the client's industry sector, the press and the public. The reports are designed and printed professionally to ensure maximum quality and consistency across the series

Market Structure and Energy Efficiency: The Case of New Commercial Buildings

This is a report on why commercial office buildings aren’t more energy efficient. Several decades of energy efficiency programs have resulted in some gains, but overall increases in the energy efficiency of buildings have fallen far short of the 30 to 50 percent improvement that many efficiency advocates believe is possible. The purpose of this study is to consider the “why” question by empirically examining the dynamics of new commercial building markets. To do so, the authors used multiple research techniques, including qualitative field observation and interview methods that allow for a more in-depth understanding of complicated market processes. Their research focused primarily on new office buildings and centered in four regional markets: Sacramento, San Francisco, Seattle, and Portland. The authors identify key dynamics of commercial office building markets, describe how change and innovation occurs in commercial development, discuss the implications for energy efficiency, and suggest next steps