Manufacturing wastes analysis in lean environment: an integrated ISM-fuzzy MICMAC approach

Patidar, Lakhan; Soni, Vimlesh Kumar; Soni, Pradeep Kumar

doi:10.1007/s13198-017-0669-6

Cited by 26 publications

(16 citation statements)

References 38 publications

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“…(2) Var16 (tourism development master plan); It should be mentioned that Var37 (quality of wellbeing) and Var38 (tourism facilities and services) were almost identical, and it can be proved that Var37 was inherent to the Var38 for the purpose of the study, so Var37 was eliminated. The results confirmed that certain variables (key variables) that were previously considered unimportant, actually play a leading role in developing Southeast Asian tourism in Iran (Arcade et al, 1999;Asan and Asan, 2007;Dewangan et al, 2015;Godet et al, 2008;Nematpour and Faraji, 2019;Patidar et al, 2017;Villacorta et al, 2014). As the Iranian tourism system is based on instability, the sustainability of the development of the tourism market must be considered as a fundamental concept of any strategic and action plan in Iran.…”

Section: Theoretical Implicationssupporting

confidence: 68%

“…A cross-impact analysis using MICMAC was used to validate the integrated structural analysis, based on the influence and dependence of the tourism development variables identified from the stabilized fuzzy matrix (Dewangan et al, 2015;Patidar et al, 2017). Tourism managers can get an idea of these tourism development variables and understand 2) as some of the main findings of this analysis are presented in Table 6.…”

Section: Study Indicators and Sub-indicatorsmentioning

confidence: 99%

“…In this study, five variables are strongly dependent on other tourism development variables. Their high dependency indicates that they require all the independent variables to minimize the impact of dependent variables on tourism development (Patidar et al, 2017). In re-evaluating the clustered region of the chart/map, due to high dependencies, Var1 (modern marketing) and Var27 (new technologies in the tourism industry) may have been considered in the third cluster and much influenced by the system.…”

Section: Tourism Developmentmentioning

confidence: 99%

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Structural analysis of the development of the Iranian tourism market employing a MICMAC approach: a new long-range planning method to attract the ASEAN international tourist market

Nematpour

Khodadadi

Rezaei³

et al. 2020

JHTI

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PurposeAs tourism development is an unquestionable part of every national growth policy, this study aims to introduce an integrated method employing MICMAC analysis for understanding the key strategic variables of Iran's tourism development system.Design/methodology/approachThe structural analysis with MICMAC method was used to determine the classification of variables, aimed at structuring ideas to deal with complex decision-making and help planners and policymakers formulate future-based strategies.FindingsThe cross-impact matrix was used to identify the development variables having the greatest impact on the development of Southeast Asian tourism to Iran. The results showed that among 43 variables, 10 have great potential as key variables in the future of Iran's tourism development.Research limitations/implicationsMICMAC, as a structural analysis technique, is regarded as being the most appropriate to identify the key variables in the development of the Iranian tourism system. The limitation was that the other tourism markets, apart from ASEAN tourists, and the tourism demand-side were excluded from this study.Practical implicationsThe present study indicates that identifying key factors that influence the supply side of Iran's tourism system is worthwhile. Consequently, the findings show how these key factors can play a vital role in long-range economic sustainability and lead to the development of Iran's tourism market to enhance globally its competitiveness as a destination to attract international ASEAN tourists.Originality/valueThis study is one of the first papers to focus on the development of Iran's tourism market from a supply-side through structural analysis. Its findings are valuable as they can be used by the tourism authorities in the process of developing future tourism scenarios for Iran.

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Section: Theoretical Implicationssupporting

confidence: 68%

Section: Study Indicators and Sub-indicatorsmentioning

confidence: 99%

Section: Tourism Developmentmentioning

confidence: 99%

See 1 more Smart Citation

Structural analysis of the development of the Iranian tourism market employing a MICMAC approach: a new long-range planning method to attract the ASEAN international tourist market

Nematpour

Khodadadi

Rezaei³

et al. 2020

JHTI

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“…However, the manufacturing sector faces several ambiguities about how to identify, classify, manage and eliminate waste to improve production performance (Patidar et al, 2017).…”

Section: Discussion Of Resultsmentioning

confidence: 99%

Fuzzy Model for Lean Manufacturing Level Assessment in a Small Metallurgical Industry

Silva

Leite

Nascimento³

et al. 2021

Exacta

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Small companies find it difficult to implement production management systems. This causes problems of overproduction, high inventory and high rates of defective products. Lean Manufacturing acts as a methodology to achieve waste elimination. It is important that companies identify their current level of Lean to improve their operations. This work aims to present a model using fuzzy logic, applied in a small metallurgical industry. A Fuzzy inference model was specified and modeled on the software fuzzy toolbox MATLAB R2013a®. The simulation performed on the model took into account the current reality of the company, noting that there are no Lean metrics in its processes. A great advantage of the model is the possibility of adjustments for any type of organization since the input and output variables can receive other linguistic values.

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“…FMICMAC analysis is an extension of traditional MICMAC analysis and takes into account the qualitative consideration of communication among enablers on a scale of 0-1. ISM and FMICMAC analysis have also been used in manufacturing sector of India in identifying innovation enablers (Dewangan et al, 2015), in identifying enablers in knowledge flow in the supply chain (Bhosale and Kant, 2016) and in the identification of waste in lean manufacturing (Patidar et al, 2017), used in agile manufacturing system in inspecting the design and implementation model (Sindhwani and Malhotra, 2017) among several others.…”

Section: Literature Surveymentioning

confidence: 99%

Coordination between hospitals and insurers in developing economies: an interpretive structural modeling approach

Dev

Kumar

Patel

2020

IJPHM

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Purpose The purpose of this paper is to identify the factors that influence hospitals’ selection by health-care insurers in India and to establish a hierarchical model representing the relationship among different factors and their influence on the entire scenario. Design/methodology/approach A survey with a set of questionnaires was conducted with different health-care insurer executives of reputed health insurance companies. The data has been gathered by using a five-point Likert scale. Their opinions were converted into a reachability matrix and an interpretive structural modeling was constructed. The final results obtained were verified by using fuzzy Matriced Impacts Croises-Multiplication Applique and Classement analysis. Findings The results suggested three key driving factors, National Accreditation Board for Hospitals & Healthcare Providers accreditation of the hospital, purchasing power of people in the region and national and international recognition of the hospital among the eleven factors selected for the study. Research limitations/implications The research mainly focuses on the health insurance benefits provided by privately owned insurance companies and do not comment on any government’s mass health insurance scheme. Practical implications With a small proportion of people under the umbrella of health insurance in India, these factors will assist and expedite insurer’s effort to penetrate deep into rural and urban areas enhancing availability and escalating affordability. Originality/value This paper presents key factors responsible for better coordination between health-care systems and insurance companies.

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Manufacturing wastes analysis in lean environment: an integrated ISM-fuzzy MICMAC approach

Cited by 26 publications

References 38 publications

Structural analysis of the development of the Iranian tourism market employing a MICMAC approach: a new long-range planning method to attract the ASEAN international tourist market

Structural analysis of the development of the Iranian tourism market employing a MICMAC approach: a new long-range planning method to attract the ASEAN international tourist market

Fuzzy Model for Lean Manufacturing Level Assessment in a Small Metallurgical Industry

Coordination between hospitals and insurers in developing economies: an interpretive structural modeling approach

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