Individual cognitive factors affecting unsafe acts among Iranian industrial workers: An integrative meta-synthesis interpretive structural modeling (ISM) approach

2019 ◽  
Vol 120 ◽  
pp. 89-98 ◽  
Author(s):  
Mahnaz Shakerian ◽  
Mehdi Jahangiri ◽  
Moslem Alimohammadlou ◽  
Mohammad Nami ◽  
Alireza Choobineh
Keyword(s):  
Structural Modeling ◽  
Cognitive Factors ◽  
Industrial Workers ◽  
Interpretive Structural Modeling ◽  
Factors Affecting

scholarly journals Factors Affecting the Lut Desert Tourism in Iran: Developing an Interpretive-Structural Model

2021 ◽  
Vol 13 (13) ◽  
pp. 7245
Author(s):  
Beniamino Murgante ◽  
Mohammad Eskandari Sani ◽  
Sara Pishgahi ◽  
Moslem Zarghamfard ◽  
Fatemeh Kahaki
Keyword(s):  
Sampling Method ◽  
Structural Model ◽  
Tourism Development ◽  
Cost Effective ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Factors Affecting ◽  
Purposive Sampling ◽  
Interpretive Structural Model ◽  
Lut Desert

The Lut desert is one of the largest and most attractive deserts in Iran. The value of desert tourism remains unclear for Iran’s economy and has only recently been taken into consideration by the authorities, although its true national and international value remains unclear. This study was aimed at investigating the factors that influence tourism development in the Lut desert. Data collected through the purposive sampling method was analyzed using Interpretive Structural Modeling and the MICMAC Analysis. According to the results, cost-effective travel expenses, security, and safety provided in the desert, together with appropriate media advertising and illustration of the Lut desert (branding) are the leading factors that influence tourism in the Lut desert in Iran. This paper highlighted the importance of desert tourism, especially in this region.

Factors affecting strategic plan implementation using interpretive structural modeling (ISM)

2018 ◽  
Vol 31 (5) ◽  
pp. 406-414 ◽  
Author(s):  
Mohammadkarim Bahadori ◽  
Ehsan Teymourzadeh ◽  
Hamidreza Tajik ◽  
Ramin Ravangard ◽  
Mehdi Raadabadi ◽  
...  
Keyword(s):  
Strategic Planning ◽  
Planning Process ◽  
Strategic Plan ◽  
Structural Modeling ◽  
Interpretive Structural Modeling ◽  
Plan Implementation ◽  
Content Type ◽  
Factors Affecting ◽  
Strategic Planning Process ◽  
The Relationship

PurposeStrategic planning is the best tool for managers seeking an informed presence and participation in the market without surrendering to changes. Strategic planning enables managers to achieve their organizational goals and objectives. Hospital goals, such as improving service quality and increasing patient satisfaction cannot be achieved if agreed strategies are not implemented. The purpose of this paper is to investigate the factors affecting strategic plan implementation in one teaching hospital using interpretive structural modeling (ISM).Design/methodology/approachThe authors used a descriptive study involving experts and senior managers; 16 were selected as the study sample using a purposive sampling method. Data were collected using a questionnaire designed and prepared based on previous studies. Data were analyzed using ISM.FindingsFive main factors affected strategic plan implementation. Although all five variables and factors are top level, “senior manager awareness and participation in the strategic planning process” and “creating and maintaining team participation in the strategic planning process” had maximum drive power. “Organizational structure effects on the strategic planning process” and “Organizational culture effects on the strategic planning process” had maximum dependence power.Practical implicationsIdentifying factors affecting strategic plan implementation is a basis for healthcare quality improvement by analyzing the relationship among factors and overcoming the barriers.Originality/valueThe authors used ISM to analyze the relationship between factors affecting strategic plan implementation.

scholarly journals The COVID-19 Crisis and Complexity in the United States

2021 ◽  
Vol 12 ◽  
Author(s):  
K. Basel ◽  
M. Campos ◽  
G. Handley ◽  
D. Hebert ◽  
E. Melendez ◽  
...  
Keyword(s):  
United States ◽  
Collective Intelligence ◽  
Structural Modeling ◽  
The United States ◽  
Research Process ◽  
Complexity Measure ◽  
Transdisciplinary Research ◽  
Interpretive Structural Modeling ◽  
Factors Affecting ◽  
Cyclomatic Complexity

The main objective of this research is to present a transdisciplinary research process which identifies the complexity of the issues surrounding COVID-19 using collective intelligence through transdisciplinarycollaborative effort. Interpretive Structural Modeling (ISM), a methodology for dealing with complexsystem design and development has been the key component of this research. Building collective intelligence to understand how factors affecting COVID-19 transmission and fatality and their relationships were investigated. The complexity measure of the COVID-19 was investigated by using cyclomatic complexity. The results showed that the complexity of the COVID-19 is difficult to understand and handle.

Lean Enhancement by Application of Total Interpretive Structural Modelling

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Case Studies ◽  
Lean Manufacturing ◽  
Structural Modeling ◽  
Manufacturing Flexibility ◽  
Structural Modelling ◽  
Interpretive Structural Modeling ◽  
Factors Affecting ◽  
Modeling Methodology ◽  
Level Of Automation ◽  
Total Interpretive Structural Modelling

Prioritizing of factors for effective lean manufacturing poses a challenge to management due to complexities in interrelationships. Diligent understanding of measures of lean manufacturing assumes great importance. Essential manufacturing flexibilities take care of uncertainties driven by dynamics of the market. Interrelationship between factors of manufacturing flexibility and lean manufacturing adds to complexity. Judicious analysis of these factors is imperative to understand their effect on lean manufacturing. Total interpretive structural modeling methodology is used for establishing relationships among the factors affecting lean performance. Case studies have been carried out and TISM is applied to understand the dynamism of factors. Study brings out how the organization of the companies and level of automation help in understating the driving and dependence power. The study helps in understanding the influence of hierarchy and level of factors identified by TISM technique on lean performance as also the factors which merit attention of top management to achieve better results

scholarly journals Interactions among Cognitive Factors Affecting Unsafe Behavior: Integrative Fuzzy DEMATEL ISM Approach

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Mahnaz Shakerian ◽  
Alireza Choobineh ◽  
Mehdi Jahangiri ◽  
Moslem Alimohammadlou ◽  
Mohammad Nami ◽  
...  
Keyword(s):  
Threshold Value ◽  
Cognitive Factors ◽  
Fuzzy Decision Making ◽  
Industrial Accidents ◽  
Interpretive Structural Modeling ◽  
Fuzzy Dematel ◽  
Factors Affecting ◽  
Unsafe Behavior ◽  
Unsafe Behaviors ◽  
Human Failure

The prevention of industrial accidents is not completely practical by implementing safety programs unless focusing on protecting vulnerable workers. The unsafe behavior cognitive factors (UBCFs) are essential determinants contributing to human failure. This study aimed at eliciting the most important UBCFs, along with investigating hierarchical cause-effect interactions among them. A qualitative approach using metasynthesis was utilized to extract all essential UBCFs among industrial workplaces. Afterward, the relationships between UBCFs were recognized using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method and rated by an expert panel. Also, a hierarchical model was developed based on the final matrix of DEMATEL by employing the interpretive structural modeling (ISM) method. Ten criteria were extracted as UBCFs through the metasynthesis method. The threshold value was set as 0.175 in DEMATEL following experts’ ideas. Inadequacy of persons’ resilience and habitual rule ignorance were recognized as the most important predictive UBCFs. The developed model was tested through a case study in a petrochemical company. The results of the study can be used to help industrial managers and HSE practitioners to consider workers’ capabilities either cognitively or physically when designing the required tasks to reduce unsafe behaviors. Also, the findings of the study are applicable for other researchers to prioritize the most important factors affecting unsafe behavior in different workplaces.

scholarly journals Applying total interpretive structural modeling to study factors affecting construction labour productivity

2014 ◽  
Vol 14 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Sayali Shrikrishna Sandbhor ◽  
Rohan P. Botre
Keyword(s):  
Factor Analysis ◽  
Labour Productivity ◽  
Structural Modeling ◽  
Construction Site ◽  
Construction Sector ◽  
Interpretive Structural Modeling ◽  
Factors Affecting ◽  
Major Attention ◽  
Negative Factors

Construction sector has always been dependent on manpower. Most of the activities carried out on any construction site are labour intensive. Since productivity of any project depends directly on productivity of labour, it is a prime responsibility of the employer to enhance labour productivity. Measures to improve the same depend on analysis of positive and negative factors affecting productivity. Major attention should be given to factors that decrease the productivity of labour. Factor analysis thus is an integral part of any study aiming to improve productivity.  Interpretive structural modeling is a methodology for identifying and summarizing relationships among factors which define an issue or problem. It provides a means to arrange the factors in an order as per their complexity. This study attempts to use the latest version of interpretive structural modeling i.e. total interpretive structural modeling to analyze factors negatively affecting construction labour productivity. It establishes interpretive relationship among these factors facilitating improvement in the overall productivity of construction site.

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