Assessing Collaborative Capabilities for Sustainability in Interorganizational Networks

Sustainability in interorganizational networks depends on developing collaborative capabilities for this purpose. However, to improve their collaborative capabilities for sustainability (CCS), companies in interorganizational networks need methods to assess them. The existing CCS assessment approaches in the literature do not indicate what capabilities should be improved in an individual company to support collaborative strategies. Addressing this gap, the main contribution of this paper is providing a framework to assess CCS in interorganizational networks, providing support for improving firm-level capabilities. To attain this aim, the framework was based on the graph-theoretic approach (GTA), a multi-attribute technique that captures the interrelationships between elements of a system, providing multi-level and overall assessment. We tested the framework in three hotels from a tourism cluster in Brazil, where sustainability has been an unsettling issue. By applying the assessment framework, it was possible to generate a CCS index for each company and, thereby, to compare the results. Findings from the field confirmed the benefits of using the framework and its utility in assessing CCS and setting priorities for improvement.

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Evaluating the innovation capability of cluster-based firms: a graph-theoretic approach

Journal of Business and Industrial Marketing ◽

10.1108/jbim-11-2020-0521 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Cláudia Fabiana Gohr ◽

Maryana Scoralick de Almeida Tavares ◽

Sandra Naomi Morioka

Keyword(s):

Industrial Cluster ◽

Industrial Clusters ◽

Performance Measure ◽

Northeastern Brazil ◽

Theoretic Approach ◽

Innovation Capability ◽

Assessment Framework ◽

Content Type ◽

Graph Theoretic ◽

Graph Theoretic Approach

Purpose This paper aims to propose an assessment framework to evaluate companies' innovation capability in the context of industrial clusters. Design/methodology/approach The assessment framework was built based on the Graph-Theoretic Approach (GTA) to measure the influence of the factors and sub-factors of innovation capabilities. To quantify the level of interdependence between factors and sub-factors of innovation capability Delphi method was adopted. The authors developed five case studies in firms from an Information and Communications Technology and Creative Economy cluster in Northeastern Brazil to test the framework's applicability. Findings The results showed that identifying and evaluating the factors of innovation capability allows a larger understanding of what affects these capabilities to a greater or lesser extent and contributes to strategic decision-making. Research limitations/implications The framework evaluates the innovation capability of each firm, not providing an index for the whole industrial cluster. Besides, the framework does not consider the innovations developed by the companies through the innovation's capabilities. As the Delphi technique was adopted to analyze the levels of influence or interdependence between factors and sub-factors of innovation capability, different experts may lead to different results. Practical implications Among the managerial implications, the authors can highlight the innovation capability index as a practical performance measure to stimulate improvement initiatives regarding innovations in industrial clusters. Besides, as the proposed framework is generic, research organizations, public institutions and regional governments can adopt it to analyze innovation capabilities in cluster-based companies. Originality/value Previous industrial cluster studies have concentrated on knowledge transfer as the main attribute influencing innovation capabilities. The literature also presents assessment frameworks focusing on qualitative analyses or innovation capabilities outcomes (patents and products). Differently, the authors proposed a quantitative assessment framework considering specific factors (and sub-factors) of innovation capabilities in industrial clusters.

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Graph-Theoretic Approach to Resolving the Accessibility and Site Selection Issues in Real Estate Development`

10.15396/afres2013_116 ◽

2013 ◽

Author(s):

Ayotunde Oni

Keyword(s):

Real Estate ◽

Site Selection ◽

Real Estate Development ◽

Theoretic Approach ◽

Graph Theoretic ◽

Graph Theoretic Approach

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Faculty Opinions recommendation of Functional sites in protein families uncovered via an objective and automated graph theoretic approach.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1012498.185925 ◽

2003 ◽

Author(s):

Janet Thornton

Keyword(s):

Theoretic Approach ◽

Protein Families ◽

Functional Sites ◽

Graph Theoretic ◽

Graph Theoretic Approach

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Optimal Micro PMU Placement in Practical Distribution Network: A Graph Theoretic Approach

2020 IEEE First International Conference on Smart Technologies for Power, Energy and Control (STPEC) ◽

10.1109/stpec49749.2020.9297763 ◽

2020 ◽

Author(s):

Manas Mukherjee ◽

Biman Kumar Saha Roy

Keyword(s):

Distribution Network ◽

Theoretic Approach ◽

Graph Theoretic ◽

Graph Theoretic Approach ◽

Pmu Placement

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Learning rules from numerical data by combining geometric and graph-theoretic approach

Robotics and Autonomous Systems ◽

10.1016/s0921-8890(00)00084-1 ◽

2000 ◽

Vol 33 (2-3) ◽

pp. 135-147

Author(s):

Sukhamay Kundu ◽

Jianhua Chen

Keyword(s):

Numerical Data ◽

Theoretic Approach ◽

Graph Theoretic ◽

Learning Rules ◽

Graph Theoretic Approach

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A Graph-Theoretic Approach to Comparing and Integrating Genetic, Physical and Sequence-Based Maps

Genetics ◽

10.1093/genetics/165.4.2235 ◽

2003 ◽

Vol 165 (4) ◽

pp. 2235-2247

Author(s):

Immanuel V Yap ◽

David Schneider ◽

Jon Kleinberg ◽

David Matthews ◽

Samuel Cartinhour ◽

...

Keyword(s):

Directed Graph ◽

Source Material ◽

Complete Picture ◽

Theoretic Approach ◽

Research Groups ◽

Genome Coverage ◽

Graph Theoretic ◽

Novel Approach ◽

Graph Theoretic Approach ◽

Locus Order

AbstractFor many species, multiple maps are available, often constructed independently by different research groups using different sets of markers and different source material. Integration of these maps provides a higher density of markers and greater genome coverage than is possible using a single study. In this article, we describe a novel approach to comparing and integrating maps by using abstract graphs. A map is modeled as a directed graph in which nodes represent mapped markers and edges define the order of adjacent markers. Independently constructed graphs representing corresponding maps from different studies are merged on the basis of their common loci. Absence of a path between two nodes indicates that their order is undetermined. A cycle indicates inconsistency among the mapping studies with regard to the order of the loci involved. The integrated graph thus produced represents a complete picture of all of the mapping studies that comprise it, including all of the ambiguities and inconsistencies among them. The objective of this representation is to guide additional research aimed at interpreting these ambiguities and inconsistencies in locus order rather than presenting a “consensus order” that ignores these problems.

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