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.

TISM-based analysis of important factors for additive manufacturing in healthcare:a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
S. Logesh ◽  
S. Vinodh
Keyword(s):  
Health Care ◽  
Additive Manufacturing ◽  
Structural Model ◽  
Matrix Multiplication ◽  
Extensive Literature ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis ◽  
Factors Influencing

Purpose This paper aims to focus on developing a theoretical framework for the analysis of factors influencing additive manufacturing (AM) in the health-care domain. Design/methodology/approach A total of 18 factors are considered through extensive literature review and the relationship between each factor is studied using total interpretive structural modeling (TISM) and the model is logically developed. TISM model is developed using appropriate expert inputs. In addition, cross-impact matrix multiplication applied to classification (MICMAC) analysis is conducted to group the factors. Findings It was found that “ease of design” and “research and development” are the two most important factors with the highest driving power and dependencies. Through MICMAC analysis, the significance of factors is studied. Practical implications The study has been done based on inputs from academic experts and industry practitioners. The inferences from the study have practical relevance. Originality/value The development of a structural model for the analysis of factors influencing AM in the health-care domain is the original contribution of the authors.

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.

A fuzzy interpretive structural modeling approach for evaluating the factors affecting lean implementation in Indian healthcare industry

2019 ◽  
Vol 11 (2) ◽  
pp. 376-397 ◽  
Author(s):  
Puneeta Ajmera ◽  
Vineet Jain
Keyword(s):  
Healthcare Professionals ◽  
Structural Modeling ◽  
Healthcare Sector ◽  
Equation Modeling ◽  
Healthcare Industry ◽  
Interpretive Structural Modeling ◽  
Lean Implementation ◽  
Content Type ◽  
Lean Principles ◽  
Factors Influencing

Purpose Lean concept is implemented in healthcare organizations, as it deals with improvement processes so that best services may be provided to the patients and competitive advantage may be achieved. The purpose of this paper is to evaluate the important factors which influence implementation of lean principles in the healthcare industry. Design/methodology/approach The factors influencing lean implementation in the healthcare industry have been determined through literature review and results of a survey where questionnaires were distributed among 325 healthcare professionals. Fuzzy Interpretive Structural Modeling (FISM) approach has been used to analyze the interrelationships among these factors. A FISM model has been developed to extract the key factors influencing lean implementation. Findings Results of the survey and model show that lean leadership, professional organizational culture and teamwork and interdepartmental cooperation are the top level factors. Clarity of organizational vision, communication of goals and results, follow up and evaluations are the factors with strong driving as well as strong dependence power. Even a slight action taken on these factors will have a significant impact on other factors. Practical implications The healthcare professionals and managers can acquire information from the drive power dependence matrix so that they can thoroughly understand the relative importance, interdependencies and relationships among these factors. The model will help in determining the hierarchy of various actions and activities which may be taken by the management for managing the factors that remarkably affect the lean management in hospitals. Social implications In this paper, only 15 variables appropriate for the Indian healthcare industry have been identified. The model developed in the present research has not been validated statistically which can be done by structural equation modeling (SEM). Originality/value Though there are various studies which depict that lean principles have been implemented successfully in various industries, there are few studies specifying the application of lean principles in healthcare sector in India. This paper is an attempt to identify various factors which are important for application of Lean concept in the healthcare sector.

Analysis of the barriers in implementing environmental management system by interpretive structural modeling approach

2017 ◽  
Vol 40 (12) ◽  
pp. 1316-1335 ◽  
Author(s):  
Fan Yang ◽  
Xiongfei Zhang
Keyword(s):  
Environmental Management ◽  
Management System ◽  
Panel Discussion ◽  
Structural Modeling ◽  
Environmental Management System ◽  
Extensive Literature ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Textile And Apparel ◽  
Apparel Companies

Purpose This paper aims to identify the most influential barriers for environmental management system (EMS) adoption and determine the interactions of these factors in the context of Chinese textile and apparel industries. Design/methodology/approach The study has conducted two different research phases, namely, the identification of 13 barriers from the extensive literature available and expert panel discussion and using interpretive structural modeling (ISM) to investigate the complex relationships among these barriers and partition the barriers into a hierarchical structure to facilitate strategic analysis. Findings The obtained result demonstrates that insufficient information about customer’s demand is the most influential barrier. Furthermore, by analyzing the interrelationships among the barriers, management will become more aware of the barriers’ relative importance and focus on the barriers with stronger influence. Originality/value This work may help practitioners, academicians and regulators to focus their efforts toward implementation of EMS on various levels in business, especially for these textile and apparel companies operating in China.

Factors influencing organizational agility in higher education

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shalini Menon ◽  
M. Suresh
Keyword(s):  
Higher Education ◽  
Organizational Structure ◽  
Human Resource ◽  
Structural Model ◽  
Readiness To Change ◽  
Matrix Multiplication ◽  
Extensive Literature ◽  
Organizational Agility ◽  
Interpretive Structural Modeling ◽  
Content Type

PurposeThe purpose of this paper is to explore the factors that can facilitate agility in higher education and to analyze the interrelationship between the factors.Design/methodology/approachA structured model of factors facilitating agility in higher education was developed using total interpretive structural modeling (TISM). Cross-impact matrix multiplication (MICMAC) analysis helped in classifying the factors on the basis of their driving and dependency power.FindingsAn extensive literature review and expert opinion helped in identifying eight enablers that can promote agility in higher education. The ability to sense the environment, organizational structure, adoption of ICT, organizational learning, human resource strategies, leadership, readiness to change and collaboration with the stakeholders were the eight factors identified. The structural model revealed leadership as the most crucial enabler followed by human resource strategies and organizational structure.Research limitations/implicationsThe model has incorporated and prioritized all the crucial drivers of agility that can help universities and colleges design, adopt and implement policies and practices that would facilitate agility.Originality/valueSo far, the research on agility in higher education has looked into each factor in isolation. This research provides a comprehensive list of the factors and establishes the interplay between the factors making this study new and original.

Application of total interpretive structural modeling for analyzing factors of additive manufacturing and industry 4.0 integration

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vishal Ashok Wankhede ◽  
Vinodh S.
Keyword(s):  
Additive Manufacturing ◽  
Industry 4.0 ◽  
Structural Model ◽  
Matrix Multiplication ◽  
Structural Modeling ◽  
Influential Factors ◽  
Time Data ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Micmac Analysis

Purpose The purpose of this paper is to develop a model based on the total interpretive structural modeling (TISM) approach for analysis of factors of additive manufacturing (AM) and industry 4.0 (I4.0) integration. Design/methodology/approach AM integration with I4.0 is attributed due to various reasons such as developing complex shapes with good quality, real-time data analysis, augmented reality and decentralized production. To enable the integration of AM and I4.0, a structural model is to be developed. TISM technique is used as a solution methodology. TISM approach supports establishing a contextual relationship-based structural model to recognize the influential factors. Cross-impact matrix multiplication applied to classification (MICMAC) analysis has been used to validate the TISM model and to explore the driving and dependence power of each factor. Findings The derived structural model indicated the dominant factors to be focused on. Dominant factors include sensor integration (F9), resolution (F12), small build volumes (F19), internet of things and lead time (F14). MICMAC analysis showed the number of driving, dependent, linkage and autonomous factors as 3, 2, 12 and 3, respectively. Research limitations/implications In the present study, 20 factors are considered. In the future, additional factors could be considered based on advancements in I4.0 technologies. Practical implications The study has practical relevance as it had been conducted based on inputs from industry practitioners. The industry decision-makers and practitioners may use the developed TISM model to understand the inter-relationship among the factors to take appropriate measures before adoption. Originality/value The study on developing a structural model for analysis of factors influencing AM and I4.0 is the original contribution of the authors.

Exploring and establishing the barriers to sustainable humanitarian supply chains using fuzzy interpretive structural modeling and fuzzy MICMAC analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Haidar Abbas ◽  
Zainab Asim ◽  
Zuhaib Ahmed ◽  
Sanyo Moosa
Keyword(s):  
Structural Modeling ◽  
The Body ◽  
The Other ◽  
Performance Measurement System ◽  
Future Research ◽  
Extensive Literature ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Sustainable Solutions ◽  
Practical Implications

Purpose The continual onset of natural and manmade disasters propels the humanitarian supply chain (HSC) efforts (by organizations, groups and individuals) to always be on a stand-by mode with more and more sustainable solutions. Despite all the sincere and coordinated efforts from all the humanitarian agents and bodies, the likely sustainable outputs are hampered by certain barriers (impediments) which exist at different levels of the HSCs. A better understanding of such barriers and their mutual relationship is deemed helpful in improving the outcomes of humanitarian efforts. Thus, the purpose of this paper is to explore, refine, establish and classify these barriers which thwart the sustainable efforts of the HSCs individually as well as collectively. Design/methodology/approach An extensive literature review is conducted to identify these barriers which were followed by soliciting the experts’ inputs to update, refine and retain the contextually relevant ones. The opinions about the nine identified and refined barriers are taken from eight experts based in the Northern India who are having at least five years of experience in humanitarian operations. Fuzzy interpretive structural modeling (FISM) is used to examine and establish a hierarchical relationship among these barriers, whereas fuzzy Matrice d’impacts croisés multiplication appliquée á un classment analysis is carried out to further classify these barriers into dependent, autonomous, linkage and dependent barriers. Findings The analysis led to the formation of a FISM model where the operational challenges affecting the performance occupy the topmost position in the hierarchy. The results reveal that inconsistent motives, coordination and communication and operational challenges affecting the performance are the dependent, poor strategic planning, capacity-related challenges and poor performance measurement system are the autonomous, and financial challenges, locational challenges and lack of proper awareness are the independent barriers. Research limitations/implications The focus of the researchers was to study and examine these barriers to sustainable HSCs with special reference to the epidemics and pandemics (especially COVID-19), and it sheds light particularly arising during and post disaster phases. Practical implications The structural model contributed by this study is expected to be meaningful for practitioners besides enriching the body of literature. In the context of pandemics, it distinguishes itself from the other available frameworks. Social implications As this research has been carried out in the context of the novel COVID-19, the framework is expected to assist policymakers in comprehending the issues impeding the sustainability of noble humanitarian efforts. Thus, ultimately it is expected to contribute to the ultimate cause of society at large. Originality/value This research endeavor distinguishes itself from the other accessible published resources in terms of the specific context, the methodological approach and the nature of respondents. This paper concludes with the practical implications and directions for future research.

Benchmarking model for factors influencing creation of negative electronic word of mouth

2018 ◽  
Vol 25 (9) ◽  
pp. 3592-3606 ◽  
Author(s):  
Sushant Kumar ◽  
Shankar Purbey
Keyword(s):  
Social Networking Sites ◽  
Word Of Mouth ◽  
Structural Model ◽  
Anxiety Reduction ◽  
Dominant Factor ◽  
Electronic Word Of Mouth ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Factors Influencing ◽  
Different Levels

Purpose The purpose of this paper is to develop a structural framework for factors influencing the creation of negative electronic word of mouth (WOM) at online forums, review portals, social networking sites or any other internet-based platform. Consumers frequently talk about consumption through WOM. With the unprecedented progress in digitalization of world, consumers usually tell stories about a product or service experience online. The study aims to identify the antecedents for negative electronic WOM (EWOM) and develop a structural model with different levels of factors. Design/methodology/approach Literature review and group judgment techniques are used to identify the factors responsible for negative WOM. The study uses interpretive structural modeling approach to develop a structural model representing interrelationships among factors. The model also represents the factors at different levels along with most and least dominant factors responsible for EWOM. Findings Seven factors responsible for negative electronic WOM are identified which are spread over three levels. First level of factors includes anxiety reduction, advice seeking, exertion of power (over companies) and social benefits (received), whereas the second level of factors includes altruism (negative WOM) and economic rewards. The most dominant factor identified is vengeance, which is at level three. Practical implications The study identified three levels of factors responsible for negative EWOM. Companies can strategies their resources to ensure that no consumer reaches beyond level one. Beyond level one, the involved factors may jeopardize the brand value and brand image of the company. Originality/value The study contributes to the literature by providing a structural model for negative EWOM. This model identifies the most and least dominant factors and guides managers to take necessary action to prevent negative EWOM.

Barriers analysis for customer resource contribution in value co-creation for service industry using interpretive structural modeling

2020 ◽  
Vol 15 (3) ◽  
pp. 1137-1166
Author(s):  
Ranjit Roy Ghatak
Keyword(s):  
Structural Model ◽  
Service Industry ◽  
Structural Modeling ◽  
Service Industries ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Management Framework ◽  
Creation Process ◽  
Resource Contribution ◽  
Successful Integration

Purpose Co-creating services with the customer has recently appeared as an alternative strategy to achieve competitive advantage. Developing and sustaining a gainful experience requires sharing of knowledge, skills and resources between the firm and its customers. Managing value co-creation throws substantial challenge and difficulties. This study aims to investigate the barriers to customer resource contribution in value co-creation in service industries and find their interrelationships for developing an effective management framework for removal of those barriers. Design/methodology/approach A systematic literature review led to the identification of 26 barriers, which were further confirmed through expert opinion. The study used interpretative structural modeling (ISM) approach and Matrice d’Impacts croises-multipication applique (MICMAC), for analyzing the contextual relationships and develop a hierarchical model of the barriers. Findings ISM approach led to the development of a 13-level structural model. The barriers were further classified into autonomous, driver, linkage and dependent barriers using the MICMAC analysis. The framework offers a means to fulfill the expectations of the customers, thus leading to successful integration of the customer in the value creation process. Removal of the barriers has also been discussed. Practical implications The framework provides a direction and a tool to meet the expectations of the customers and lead to successful integration of the customer. Originality/value The study addresses a gap in the literature for the need of a structured framework for managing the value co-creation process in the service industry

Analysis of enablers for vertical integration to enhance rural employability

2019 ◽  
Vol 34 (4) ◽  
pp. 690-702 ◽  
Author(s):  
Rahul Priyadarshi ◽  
Srikanta Routroy ◽  
Girish Kant
Keyword(s):  
Vertical Integration ◽  
Rural Areas ◽  
Structural Model ◽  
Aloe Vera ◽  
Structural Modeling ◽  
Value Addition ◽  
Interpretive Structural Modeling ◽  
Content Type ◽  
Fuzzy Matrix ◽  
The Right

Purpose The purpose of the paper is to identify, analyze and select the enablers for vertical integration of Aloe vera supply chain (AVSC) so that rural employability will be enhanced in the context of Rajasthan, India. Design/methodology/approach Interpretive structural modeling (ISM) was proposed to develop a structural model to identify the right enablers for enhancing the rural employability and business prospects. Also, fuzzy-matrix cross-reference multiplication applied to classification (F-MICMAC) was applied to segregate the enablers into four clusters on the basis of their driving and dependence power. Finally, the significant enablers were selected. Findings Out of identified 13 enablers, three enablers (i.e. institute for training and research, transportation infrastructure and government incentives for value addition) were appearing at the bottom of the ISM structural model and also in the driving quadrant of driver-dependent diagram. Therefore, they are the significant enablers for vertical integration of AVSC to enhance the rural employability in the context of Rajasthan, India. Research limitations/implications The interactions among enablers are not statistically validated. However, the empirical analysis and total interpretive structural modeling may be used for this purpose. Practical implications The outcomes of the study will provide the guidelines for implementation of vertical integration at the village level to enhance rural employability in the context of Rajasthan, India in specific. Originality/value Although a few studies have been reported in the literature related to value-addition process (vertical integration), but the modeling of enablers to segregate and identify the appropriate enablers for vertical integration of AVSC for enhancing employability at the rural areas is unique.

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