A research note on the article of “Quality framework in education through application of interpretive structural modeling”

2019 ◽  
Vol 31 (1) ◽  
pp. 3-10 ◽  
Author(s):  
Kosar Roshani ◽  
Mohammad S. Owlia ◽  
Mohammad H. Abooie
Keyword(s):  
Structural Modeling ◽  
Research Note ◽  
Administrative Staff ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Reachability Matrix ◽  
Counter Example ◽  
Correct Analysis ◽  
Quality Framework ◽  
Design Characteristics

Purpose This paper is a research note on “Quality framework in education through application of Interpretive Structural Modeling” (Sahney, S., Banwet, D.K. and Karunes, S. (2010), Quality framework in education through the application of Interpretive Structural Modeling: an administrative staff perspective in the Indian context, The TQM Journal, 22(1)). Sahney et al. applied Interpretive Structural Modeling (ISM) to prioritize, sequence and categorize elements critical to quality management in education; however, it seems that the final reachability matrix, and consequently the results, may not be true as some transitivity was not incorporated. So, the purpose of this paper is to apply a method to develop a transitive and compatible reachability matrix. Design/methodology/approach A counter-example was used to show that the final reachability matrix was incorrect, and then, based on Warfield’s studies, a transitive and compatible reachability matrix was developed directly. Findings As high priority should be placed on tackling the design characteristics which have a high driving power and thus possessing the capability to influence other elements, the correct analysis of ISM and its consequences is important to the priorities. The results from this study differed from the results of the Sahney et al. to a large extent. According to their analysis, all attributes were in the linkage area which has high driving power and high dependence. However, the authors reached different values for the relative importance and the interdependencies among the elements resulting in three different clusters. Originality/value This note clarifies and corrects the way the ISM methodology can be applied.

Modeling Deming’s quality principles to improve performance using interpretive structural modeling and MICMAC analysis

2019 ◽  
Vol 36 (7) ◽  
pp. 1159-1180 ◽  
Author(s):  
Nishant Mukesh Agrawal
Keyword(s):  
Manufacturing Industry ◽  
Structural Modeling ◽  
Total Quality ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Practical Applications ◽  
Micmac Analysis ◽  
Significant Relationships ◽  
Quality Principles ◽  
Quality Framework

Purpose The purpose of this paper is to study the 14 principles of Edwards Deming and create significant relationships between them. No research has been reported on the implementation of Total Quality Management (TQM) using Deming’s 14 principles. To fill this gap, Interpretive Structural Modeling (ISM) and MICMAC analysis have been developed to understand mutual interactions among variables and find both the dependence and driving power of these variables. Design/methodology/approach The research paper discusses a blend of practical applications and introduces a theoretical framework. An ISM-based methodology is used to study and examine interactions between identified variables, while MICMAC analysis is used to identify the dependence and driving power. Findings This research utilizes Deming’s 14 quality principles, with experts from academia and industry consulted to identify contextual relationships among variables. The result shows that the stated principles “take action to accomplish the transformation,” “institute training,” “encourage education to employees” and “institute leadership” are strategic requirements, while “drive out fear,” “break down barrier between staff areas” and “eliminate numerical quotas” are tactical requirements. “Adopt the new philosophy,” “create constancy in improvement of product and service” and “cease dependence on mass inspections” are operational requirements for TQM applications. Originality/value An ISM-based quality framework, dependence power and driving power of variables using MICMAC analysis have been recommended to the service and manufacturing industry as a new focus area in the implementation of TQM.

Analysis of interaction among the barriers to 5S implementation using interpretive structural modeling approach

2017 ◽  
Vol 24 (7) ◽  
pp. 1834-1853 ◽  
Author(s):  
Rajesh Attri ◽  
Bhupender Singh ◽  
Sunil Mehra
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Modeling ◽  
Equation Modeling ◽  
Successful Implementation ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Modeling Approach ◽  
Manufacturing Organizations ◽  
Top Management Commitment

Purpose The purpose of this paper is to ascertain and analyze the interactions among different barriers of 5S implementation in manufacturing organizations. Design/methodology/approach In this paper, 15 barriers affecting the implementation of 5S in manufacturing organizations have been identified from literature analysis and discussion with academic and industrial experts. Afterwards, identified barriers were validated by using nation-wide questionnaire-based survey. Then, interpretive structural modeling (ISM) approach has been utilized to find out the interaction among the identified barriers in order to develop hierarchy-based model. Findings The research identifies several key barriers which have high driving power and weak dependence power. In this concern, these barriers entail extreme care and handling for successful implementation of 5S. Financial constraints, lack of top management commitment, and no proper vision and mission are found to be the key barriers. Research limitations/implications The developed ISM model is based on experts’ opinion. This developed hierarchy-based model requires further validation by using structural equation modeling approach or by performing detailed case studies. Originality/value In this paper, ISM-based structural model has been recommended for Indian manufacturing organizations, which is a novel exertion in the area of 5S implementation.

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.

An integrated interpretive structural modeling and a graph-theoretic approach for measuring the supply chain complexity in the Indian automotive industry

2018 ◽  
Vol 29 (3) ◽  
pp. 478-514 ◽  
Author(s):  
Kavilal E.G. ◽  
Shanmugam Prasanna Venkatesan ◽  
Joshi Sanket
Keyword(s):  
Supply Chain ◽  
Automotive Industry ◽  
Structural Modeling ◽  
Theoretic Approach ◽  
Passenger Vehicle ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Graph Theoretic ◽  
Graph Theoretic Approach ◽  
Numerical Index

Purpose Easily employable quantitative supply chain complexity (SCC) measures considering the significant dimensions of complexity as well as the drivers that represent those dimensions are limited in the literature. The purpose of this paper is to propose an integrated interpretive structural modeling (ISM) and a graph-theoretic approach to quantify SCC by a single numerical index considering the interdependence and the inheritance of the SCC drivers. Design/methodology/approach In total, 18 SCC drivers identified from the literature are clustered according to the significant dimensions of complexity. The interdependencies established through ISM and inheritance values of SCC drivers are mapped into a Variable Permanent Matrix (VPM). The permanent function of this VPM is then computed and the resulting single numerical index is the measure of SCC. Findings A scale is proposed by computing the minimum and maximum threshold values of SCC with the help of expert opinions of the Indian automotive industry. The complexity of commercial and passenger vehicle sectors within the automotive industry is measured and compared using the proposed scale. From the results, it is identified that the number of suppliers, increase in spare-parts due to shortened product life-cycle and demand uncertainties increase the SCC of the passenger vehicle sector, while number of parts, products and processes, variety of products and process and unreliability of suppliers increase the complexity of the commercial vehicle sector. The result indicates that various SCC drivers have a different impact on determining the SCC level of these two sectors. Originality/value The authors propose an integrated method that can be readily applied to measure and quantify SCC considering the significant dimensions of complexity as well as the interdependence and the inheritance of the SCC drivers that contribute to those dimensions. This index further helps to compare the complexity of the supply chain which varies between industries.

Modelling strategic orientation dimensions and performance of small and medium enterprises

2019 ◽  
Vol 14 (3) ◽  
pp. 754-772 ◽  
Author(s):  
Seemant Kumar Yadav ◽  
Vikas Tripathi ◽  
Geetika Goel
Keyword(s):  
Small And Medium Enterprises ◽  
Structural Modeling ◽  
Strategic Orientation ◽  
Decision Makers ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Manufacturing Performance ◽  
Different Dimensions ◽  
And Performance ◽  
Medium Enterprises

Purpose The purpose of this paper is to identify and rank different dimensions of strategic orientation and firm’s performance using the approach of interpretive structural modeling. Design/methodology/approach The study uses interpretative structural modeling and the MICMAC technique to establish a hierarchical relationship among different dimensions of entrepreneurial orientation and manufacturing performance of Indian SMEs. Findings The final outcome of interpretative structural modeling and the MICMAC analysis revealed a relationship between the variables under study along with the categorization of all in two different categories, depending upon their driving power and dependency, which decision-makers can also use while devising their strategy to improve performance. Originality/value To date, to the best of the authors’ knowledge, no significant contribution about such interrelationship was reported; therefore, this study is one of its types to fill this gap.

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

2020 ◽  
Vol 14 (3) ◽  
pp. 471-490
Author(s):  
Manimay Dev ◽  
Dinesh Kumar ◽  
Dharmendra Patel
Keyword(s):  
Health Care ◽  
Health Insurance ◽  
Urban Areas ◽  
Developing Economies ◽  
Health Care Systems ◽  
Healthcare Providers ◽  
Structural Modeling ◽  
Insurance Companies ◽  
Interpretive Structural Modeling ◽  
Content Type

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.

Modeling the performance measures of world class manufacturing using interpreting structural modeling

2015 ◽  
Vol 10 (1) ◽  
pp. 4-22 ◽  
Author(s):  
Abhijeet Keshaorao Digalwar ◽  
Anil Jindal ◽  
Kuldip Singh Sangwan
Keyword(s):  
Performance Measures ◽  
Model Performance ◽  
Structural Modeling ◽  
Decision Makers ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Practical Applications ◽  
Manufacturing Organizations ◽  
World Class ◽  
World Class Manufacturing

Purpose – The purpose of this paper is to study the performance measures of world class manufacturing (WCM) and to establish relationship among them using interpretive structural modeling (ISM). Design/methodology/approach – The research paper presents a blend of theoretical framework and practical applications. In the paper, 16 performance measures are identified from literature survey and experts’ opinion, and then these are validated by questionnaire survey in India. Finally, ISM is used to obtain structural relationship among these performance measures of WCM. Findings – The results of the survey and the ISM methodology have been used to evolve the mutual relationships among these performance measures. Practical implications – The adoption of such an ISM-based model on WCM performance measures in manufacturing organizations would help managers, decision-makers and practitioners of WCM in better understanding of these performance measures and to focus on appropriate performance measures while implementing WCM in their organizations. Originality/value – Performance measures are of paramount importance for the implementation of WCM practices. Knowing the key performance measures and relationship among them can help many organizations to implement WCM practices. It is one of the foremost attempts to model performance measures of WCM. The paper provides useful insights into the WCM practitioners, consultants and researchers.

Total Interpretive Structural Modeling (TISM): approach and application

2017 ◽  
Vol 14 (2) ◽  
pp. 162-181 ◽  
Author(s):  
J. Jena ◽  
Sumati Sidharth ◽  
Lakshman S. Thakur ◽  
Devendra Kumar Pathak ◽  
V.C. Pandey
Keyword(s):  
Design Methodology ◽  
Matrix Multiplication ◽  
Structural Modeling ◽  
Decision Makers ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Mutual Dependence ◽  
Step Procedure ◽  
Power And Dependence ◽  
Practical Implications

Purpose The purpose of this paper is to elucidate the methodology of total interpretive structural modeling (TISM) in order to provide interpretation for direct as well as significant transitive linkages in a directed graph. Design/methodology/approach This study begins by unfolding the concepts and advantages of TISM. The step-by-step methodology of TISM is exemplified by employing it to analyze the mutual dependence among inhibitors of smartphone manufacturing ecosystem development (SMED). Cross-impact matrix multiplication applied to the classification analysis is also performed to graphically represent these inhibitors based on their driving power and dependence. Findings This study highlights the significance of TISM over conventional interpretive structural modeling (ISM). The inhibitors of SMED are explored by reviewing existing literature and obtaining experts’ opinions. TISM is employed to classify these inhibitors in order to devise a five-level hierarchical structure based on their driving power and dependence. Practical implications This study facilitates decision makers to take required actions to mitigate these inhibitors. Inhibitors (with strong driving power), which occupy the bottom level in the TISM hierarchy, require more attention from top management and effective monitoring of these inhibitors can assist in achieving the organizations’ goals. Originality/value By unfolding the benefits of TISM over ISM, this study is an endeavor to develop insights toward utilization of TISM for modeling inhibitors of SMED. This paper elaborates step-by-step procedure to perform TISM and hence makes it simple for researchers to understand its concepts. To the best of the authors’ knowledge, this is the first study that analyzes the inhibitors of SMED by utilizing TISM approach.

Understanding determinants of social networking service fatigue: an interpretive structural modeling approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lin Xiao ◽  
Ting Pan ◽  
Jian Mou ◽  
Lihua Huang
Keyword(s):  
Social Networking ◽  
Impression Management ◽  
Structural Model ◽  
Structural Modeling ◽  
Extensive Literature ◽  
Privacy Concern ◽  
Social Networking Service ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Factors Influencing

PurposeThe purpose of this paper is to build a comprehensive structural model to demonstrate the interrelationships of factors influencing social networking service (SNS) fatigue and to identify the varying degrees of influence.Design/methodology/approachA total of 14 factors influencing SNS fatigue are identified through an extensive literature review. Interpretive structural modeling (ISM) and Matrice d'Impacts Croisés Multiplication Appliqué à un Classement (MICMAC) analysis are employed to build a hierarchical model and classify these factors into four clusters.FindingsThe results revealed that ubiquitous connectivity and immediacy of feedback are key factors contributing to SNS fatigue through their strong influence on other factors. Privacy concern, impression management concern and work–life conflict lead directly to SNS fatigue. In contrast, system feature overload and system pace of change are relatively insignificant in generating SNS fatigue.Originality/valueThis study represents an initial step toward comprehensively understanding the interrelationships among the factors leading to SNS fatigue and reveals how determinants of SNS fatigue are hierarchically organized, thus extending existing research on SNS fatigue. It also provides logical consistency in the ISM-based model for SNS fatigue by grouping identified factors into dependent and independent categories. Moreover, it extends the applicability of the integration of the ISM and MICMAC approaches to the phenomenon of SNS fatigue.

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