Evaluation of firms applying to Malcolm Baldrige National Quality Award: a modified fuzzy AHP method View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-03

AUTHORS

Serhat Aydın, Cengiz Kahraman

ABSTRACT

Malcolm Baldrige National Quality Award (MBNQA) is a broadly used performance excellence framework to recognize organizations that have outstanding customer-focused processes. MBNQA system is based on an assessment system using a 0–1000 points scale. However, experts prefer making linguistic assessments rather than exact numerical assignments. Fuzzy set theory presents excellent tools and techniques to capture the vagueness and impreciseness in these assessments. This paper develops a new analytic hierarchy process (AHP)-based fuzzy multi-criteria decision-making approach to measure the performance excellence of firms applying for MBNQA. The proposed approach enables experts to use seven different fuzzy scales to evaluate firms using the MBNQA criteria. These fuzzy scales involve both positive fuzzy numbers and negative fuzzy numbers, and present an easier and efficient alternative to the calculations made in pairwise comparison matrices. In this way, the experts filling in a questionnaire can easily understand the reciprocal scale and establish comparison matrices. Using negative fuzzy numbers in AHP scale is the crucial point of this paper. To show the applicability of the method, a numerical example composed of a four-level hierarchy including seven main criteria, 18 sub-criteria, and three alternatives is also given. We use Buckley’s Fuzzy AHP approach for comparative analysis. Our application reveals that the proposed fuzzy AHP approach efficiently measures the quality performance of the firms applying to MBNQA. More... »

PAGES

53-63

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s40747-018-0069-9

DOI

http://dx.doi.org/10.1007/s40747-018-0069-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101635525


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0103", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Numerical and Computational Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Turkish Air Force Academy", 
          "id": "https://www.grid.ac/institutes/grid.462943.e", 
          "name": [
            "Industrial Engineering Department, National Defense University, Turkish Air Force Academy, 34149, Istanbul, Turkey"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ayd\u0131n", 
        "givenName": "Serhat", 
        "id": "sg:person.010723304545.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010723304545.18"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Istanbul Technical University", 
          "id": "https://www.grid.ac/institutes/grid.10516.33", 
          "name": [
            "Industrial Engineering Department, Istanbul Technical University, 34367, Istanbul, Turkey"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kahraman", 
        "givenName": "Cengiz", 
        "id": "sg:person.010553303271.42", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010553303271.42"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.ijpe.2013.01.015", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003913295"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.omega.2007.07.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1004427730"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2010.02.041", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1005363627"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0019-9958(65)90241-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009640697"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/18756891.2009.9727655", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011988332"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2009.01.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012427445"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/00207543.2014.961207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013202528"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2008.09.045", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016652448"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2008.07.079", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1020486891"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0165-0114(83)80082-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022300824"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0305-0483(97)00008-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023000804"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.camwa.2008.01.019", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023412288"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0263-2373(99)00074-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023886804"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.compedu.2010.01.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024685925"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-2217(99)00315-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025800515"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1108/bij-07-2015-0072", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026157840"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0377-2217(99)00118-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029851232"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2008.06.102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030963087"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-0114(92)90223-q", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034175122"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-0114(92)90223-q", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034175122"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijproman.2014.11.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040228557"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0165-0114(85)90090-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041658930"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ijproman.2007.02.006", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042524041"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1108/03074350410769209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044365235"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cie.2009.10.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1045974608"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eswa.2007.10.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046230497"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.omega.2007.06.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046287334"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0377-2217(95)00300-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047382984"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.seps.2010.12.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047942882"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1074290105", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.12775/jpm.2016.014", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092094823"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ajsl.2017.09.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092229149"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jclepro.2017.10.187", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092409071"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-03", 
    "datePublishedReg": "2019-03-01", 
    "description": "Malcolm Baldrige National Quality Award (MBNQA) is a broadly used performance excellence framework to recognize organizations that have outstanding customer-focused processes. MBNQA system is based on an assessment system using a 0\u20131000 points scale. However, experts prefer making linguistic assessments rather than exact numerical assignments. Fuzzy set theory presents excellent tools and techniques to capture the vagueness and impreciseness in these assessments. This paper develops a new analytic hierarchy process (AHP)-based fuzzy multi-criteria decision-making approach to measure the performance excellence of firms applying for MBNQA. The proposed approach enables experts to use seven different fuzzy scales to evaluate firms using the MBNQA criteria. These fuzzy scales involve both positive fuzzy numbers and negative fuzzy numbers, and present an easier and efficient alternative to the calculations made in pairwise comparison matrices. In this way, the experts filling in a questionnaire can easily understand the reciprocal scale and establish comparison matrices. Using negative fuzzy numbers in AHP scale is the crucial point of this paper. To show the applicability of the method, a numerical example composed of a four-level hierarchy including seven main criteria, 18 sub-criteria, and three alternatives is also given. We use Buckley\u2019s Fuzzy AHP approach for comparative analysis. Our application reveals that the proposed fuzzy AHP approach efficiently measures the quality performance of the firms applying to MBNQA.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s40747-018-0069-9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1136144", 
        "issn": [
          "2199-4536", 
          "2198-6053"
        ], 
        "name": "Complex & Intelligent Systems", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "5"
      }
    ], 
    "name": "Evaluation of firms applying to Malcolm Baldrige National Quality Award: a modified fuzzy AHP method", 
    "pagination": "53-63", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "dae2a4224dde80a748d9fe7c9ee2df00e64ce84d784f56810f464f9db841f675"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s40747-018-0069-9"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1101635525"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s40747-018-0069-9", 
      "https://app.dimensions.ai/details/publication/pub.1101635525"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:23", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000362_0000000362/records_87094_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs40747-018-0069-9"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s40747-018-0069-9'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s40747-018-0069-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s40747-018-0069-9'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s40747-018-0069-9'


 

This table displays all metadata directly associated to this object as RDF triples.

166 TRIPLES      21 PREDICATES      59 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s40747-018-0069-9 schema:about anzsrc-for:01
2 anzsrc-for:0103
3 schema:author Nc31f73fed57f40ed9a1ad7501621e7ff
4 schema:citation https://app.dimensions.ai/details/publication/pub.1074290105
5 https://doi.org/10.1016/0165-0114(85)90090-9
6 https://doi.org/10.1016/0165-0114(92)90223-q
7 https://doi.org/10.1016/0377-2217(95)00300-2
8 https://doi.org/10.1016/j.ajsl.2017.09.001
9 https://doi.org/10.1016/j.camwa.2008.01.019
10 https://doi.org/10.1016/j.cie.2009.10.005
11 https://doi.org/10.1016/j.compedu.2010.01.004
12 https://doi.org/10.1016/j.eswa.2007.10.014
13 https://doi.org/10.1016/j.eswa.2008.06.102
14 https://doi.org/10.1016/j.eswa.2008.07.079
15 https://doi.org/10.1016/j.eswa.2008.09.045
16 https://doi.org/10.1016/j.eswa.2009.01.005
17 https://doi.org/10.1016/j.eswa.2010.02.041
18 https://doi.org/10.1016/j.ijpe.2013.01.015
19 https://doi.org/10.1016/j.ijproman.2007.02.006
20 https://doi.org/10.1016/j.ijproman.2014.11.003
21 https://doi.org/10.1016/j.jclepro.2017.10.187
22 https://doi.org/10.1016/j.omega.2007.06.003
23 https://doi.org/10.1016/j.omega.2007.07.004
24 https://doi.org/10.1016/j.seps.2010.12.003
25 https://doi.org/10.1016/s0019-9958(65)90241-x
26 https://doi.org/10.1016/s0165-0114(83)80082-7
27 https://doi.org/10.1016/s0263-2373(99)00074-2
28 https://doi.org/10.1016/s0305-0483(97)00008-x
29 https://doi.org/10.1016/s0377-2217(99)00118-6
30 https://doi.org/10.1016/s0377-2217(99)00315-x
31 https://doi.org/10.1080/00207543.2014.961207
32 https://doi.org/10.1080/18756891.2009.9727655
33 https://doi.org/10.1108/03074350410769209
34 https://doi.org/10.1108/bij-07-2015-0072
35 https://doi.org/10.12775/jpm.2016.014
36 schema:datePublished 2019-03
37 schema:datePublishedReg 2019-03-01
38 schema:description Malcolm Baldrige National Quality Award (MBNQA) is a broadly used performance excellence framework to recognize organizations that have outstanding customer-focused processes. MBNQA system is based on an assessment system using a 0–1000 points scale. However, experts prefer making linguistic assessments rather than exact numerical assignments. Fuzzy set theory presents excellent tools and techniques to capture the vagueness and impreciseness in these assessments. This paper develops a new analytic hierarchy process (AHP)-based fuzzy multi-criteria decision-making approach to measure the performance excellence of firms applying for MBNQA. The proposed approach enables experts to use seven different fuzzy scales to evaluate firms using the MBNQA criteria. These fuzzy scales involve both positive fuzzy numbers and negative fuzzy numbers, and present an easier and efficient alternative to the calculations made in pairwise comparison matrices. In this way, the experts filling in a questionnaire can easily understand the reciprocal scale and establish comparison matrices. Using negative fuzzy numbers in AHP scale is the crucial point of this paper. To show the applicability of the method, a numerical example composed of a four-level hierarchy including seven main criteria, 18 sub-criteria, and three alternatives is also given. We use Buckley’s Fuzzy AHP approach for comparative analysis. Our application reveals that the proposed fuzzy AHP approach efficiently measures the quality performance of the firms applying to MBNQA.
39 schema:genre research_article
40 schema:inLanguage en
41 schema:isAccessibleForFree true
42 schema:isPartOf N5751ff727d92417ea94921e1c46b46d3
43 N635a04978e56420bb3e79f5157572db3
44 sg:journal.1136144
45 schema:name Evaluation of firms applying to Malcolm Baldrige National Quality Award: a modified fuzzy AHP method
46 schema:pagination 53-63
47 schema:productId N456f35817a5643daadb54153068b82ac
48 N83220d1c375c4f43ba96a885f08f0b9c
49 Nc5816ac2bc43401fa74c30e3ad491b54
50 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101635525
51 https://doi.org/10.1007/s40747-018-0069-9
52 schema:sdDatePublished 2019-04-11T12:23
53 schema:sdLicense https://scigraph.springernature.com/explorer/license/
54 schema:sdPublisher Nd20e429a67be46208978a5aa7760d7b0
55 schema:url https://link.springer.com/10.1007%2Fs40747-018-0069-9
56 sgo:license sg:explorer/license/
57 sgo:sdDataset articles
58 rdf:type schema:ScholarlyArticle
59 N456f35817a5643daadb54153068b82ac schema:name doi
60 schema:value 10.1007/s40747-018-0069-9
61 rdf:type schema:PropertyValue
62 N4cf6f0241aca43a9b67de59de8a00807 rdf:first sg:person.010553303271.42
63 rdf:rest rdf:nil
64 N5751ff727d92417ea94921e1c46b46d3 schema:volumeNumber 5
65 rdf:type schema:PublicationVolume
66 N635a04978e56420bb3e79f5157572db3 schema:issueNumber 1
67 rdf:type schema:PublicationIssue
68 N83220d1c375c4f43ba96a885f08f0b9c schema:name dimensions_id
69 schema:value pub.1101635525
70 rdf:type schema:PropertyValue
71 Nc31f73fed57f40ed9a1ad7501621e7ff rdf:first sg:person.010723304545.18
72 rdf:rest N4cf6f0241aca43a9b67de59de8a00807
73 Nc5816ac2bc43401fa74c30e3ad491b54 schema:name readcube_id
74 schema:value dae2a4224dde80a748d9fe7c9ee2df00e64ce84d784f56810f464f9db841f675
75 rdf:type schema:PropertyValue
76 Nd20e429a67be46208978a5aa7760d7b0 schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
79 schema:name Mathematical Sciences
80 rdf:type schema:DefinedTerm
81 anzsrc-for:0103 schema:inDefinedTermSet anzsrc-for:
82 schema:name Numerical and Computational Mathematics
83 rdf:type schema:DefinedTerm
84 sg:journal.1136144 schema:issn 2198-6053
85 2199-4536
86 schema:name Complex & Intelligent Systems
87 rdf:type schema:Periodical
88 sg:person.010553303271.42 schema:affiliation https://www.grid.ac/institutes/grid.10516.33
89 schema:familyName Kahraman
90 schema:givenName Cengiz
91 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010553303271.42
92 rdf:type schema:Person
93 sg:person.010723304545.18 schema:affiliation https://www.grid.ac/institutes/grid.462943.e
94 schema:familyName Aydın
95 schema:givenName Serhat
96 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010723304545.18
97 rdf:type schema:Person
98 https://app.dimensions.ai/details/publication/pub.1074290105 schema:CreativeWork
99 https://doi.org/10.1016/0165-0114(85)90090-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041658930
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1016/0165-0114(92)90223-q schema:sameAs https://app.dimensions.ai/details/publication/pub.1034175122
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1016/0377-2217(95)00300-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047382984
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1016/j.ajsl.2017.09.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092229149
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1016/j.camwa.2008.01.019 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023412288
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1016/j.cie.2009.10.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045974608
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/j.compedu.2010.01.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024685925
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1016/j.eswa.2007.10.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046230497
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/j.eswa.2008.06.102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030963087
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1016/j.eswa.2008.07.079 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020486891
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/j.eswa.2008.09.045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016652448
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/j.eswa.2009.01.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012427445
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/j.eswa.2010.02.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005363627
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.ijpe.2013.01.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003913295
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.ijproman.2007.02.006 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042524041
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.ijproman.2014.11.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040228557
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.jclepro.2017.10.187 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092409071
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/j.omega.2007.06.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046287334
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/j.omega.2007.07.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004427730
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/j.seps.2010.12.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047942882
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/s0019-9958(65)90241-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1009640697
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/s0165-0114(83)80082-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022300824
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/s0263-2373(99)00074-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023886804
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/s0305-0483(97)00008-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1023000804
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/s0377-2217(99)00118-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029851232
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/s0377-2217(99)00315-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1025800515
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1080/00207543.2014.961207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013202528
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1080/18756891.2009.9727655 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011988332
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1108/03074350410769209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044365235
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1108/bij-07-2015-0072 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026157840
158 rdf:type schema:CreativeWork
159 https://doi.org/10.12775/jpm.2016.014 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092094823
160 rdf:type schema:CreativeWork
161 https://www.grid.ac/institutes/grid.10516.33 schema:alternateName Istanbul Technical University
162 schema:name Industrial Engineering Department, Istanbul Technical University, 34367, Istanbul, Turkey
163 rdf:type schema:Organization
164 https://www.grid.ac/institutes/grid.462943.e schema:alternateName Turkish Air Force Academy
165 schema:name Industrial Engineering Department, National Defense University, Turkish Air Force Academy, 34149, Istanbul, Turkey
166 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...