Research and development project selection in the public sector

1998 ◽  
Vol 17 (4) ◽  
pp. 621-638 ◽  
Author(s):  
Nicholas S. Vonortas ◽  
Henry R. Hertzfeld
Keyword(s):  
Public Sector ◽  
Research And Development ◽  
Project Selection ◽  
Development Project ◽  
The Public

Negotiating Food Heritage Interpretations: Experiences of a Project at the Estonian National Museum

2021 ◽  
Vol 15 (2) ◽  
pp. 112-134
Author(s):  
Anu Kannike ◽  
Ester Bardone
Keyword(s):  
Research And Development ◽  
Cultural Heritage ◽  
Development Project ◽  
Food Culture ◽  
National Museum ◽  
Public Forum ◽  
Non Profit ◽  
The Public

Abstract The article examines varied interpretations of food heritage in contemporary Estonia, relying on the authors’ experiences of a three-year research and development project at the Estonian National Museum (ENM). The study focuses on the museum researchers’ collaboration with different stakeholders, representing small entrepreneurs and the public and non-profit sectors. The authors tackle the partners’ expectations and outcomes of diverse cooperational initiatives and the opportunities and challenges of a contemporary museum as a public forum for discussions on cultural heritage. The project revealed that diverse, complementary, and contested food heritage interpretations exist side-by-side on the Estonian foodscape. Additionally, the project enabled the authors to become better aware of the researcher’s role in the heritagisation process and of the museum as a place for negotiating the meanings and values of food culture.

scholarly journals New Closeness Coefficients for Fuzzy Similarity Based Fuzzy TOPSIS: An Approach Combining Fuzzy Entropy and Multidistance

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Mikael Collan ◽  
Mario Fedrizzi ◽  
Pasi Luukka
Keyword(s):  
Research And Development ◽  
Fuzzy Topsis ◽  
Project Selection ◽  
Development Project ◽  
Fuzzy Entropy ◽  
Selection Problem ◽  
Aggregation Process ◽  
Owa Operator ◽  
Fuzzy Similarity

This paper introduces new closeness coefficients for fuzzy similarity based TOPSIS. The new closeness coefficients are based on multidistance or fuzzy entropy, are able to take into consideration the level of similarity between analysed criteria, and can be used to account for the consistency or homogeneity of, for example, performance measuring criteria. The commonly known OWA operator is used in the aggregation process over the fuzzy similarity values. A range of orness values is considered in creating a fuzzy overall ranking for each object, after which the fuzzy rankings are ordered to find a final linear ranking. The presented method is numerically applied to a research and development project selection problem and the effect of using two new closeness coefficients based on multidistance and fuzzy entropy is numerically illustrated.

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