Barriers to adoption of reverse logistics: a case of construction, real estate, infrastructure and project (CRIP) sectors

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sudhir Ambekar ◽  
Dipayan Roy ◽  
Amit Hiray ◽  
Anand Prakash ◽  
Vishal Singh Patyal

PurposeThis study attempts to identify and analyse the barriers to implementing a reverse logistics (RL) system in Indian Construction, Real estate, Infrastructure and Project (CRIP) sectors and present a structured model to identify interdependencies among them.Design/methodology/approachThe barriers to implementing RL in CRIP sectors in India were identified using a Delphi study. The interdependencies were identified using Interpretive Structural Modeling (ISM). Further, using the Matriced' Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis, the barriers were classified on the basis of their driving power and interdependencies.FindingsThe study has identified ten barriers that can hamper the application of an RL system in CRIP sectors. The finding of the ISM model shows that macro level barriers such as lack of awareness of reverse logistics, insufficient government policies and unavailability of standard codes stimulate each other and also drive all other barriers. The organization-specific barriers operating at the strategic/tactical level, namely, company's rigid mechanism, lack of awareness of economic profits, inadequate company’s organizational policies and lack of training, reluctance from stakeholders, scarcity of resources and finance from company are found at the intermediate level of hierarchy and they can be influenced by the barriers at the lower level and influence the barriers on the and higher levels. The operational level barrier namely “Inadequate Information Technology system” is at the top of the hierarchy and can be driven by all the barriers at the lower level.Research limitations/implicationsThe present findings are based on the opinions of experts only from Indian CRIP sectors so the results may require to be validated in other contexts.Practical implicationsThe structural model presenting the interdependencies will be a guide for the CRIP supply chain professionals in understanding and ranking the barriers they may face while implementing the RL system.Originality/valueThe study contributes to the existing literature by providing a set of barriers and their interdependencies faced during the implementation of an RL system implementation in CRIP sectors. It is one of the first studies which identifies barriers applicable to the CRIP firms in India and models their inter-dependencies. Additionally Consequently, these firms can make a move forward towards a circular economy by overcoming these interlinked barriers.

2017 ◽  
Vol 24 (7) ◽  
pp. 1834-1853 ◽  
Author(s):  
Rajesh Attri ◽  
Bhupender Singh ◽  
Sunil Mehra

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.


2018 ◽  
Vol 25 (8) ◽  
pp. 2589-2610 ◽  
Author(s):  
Rakesh Raut ◽  
Bhaskar B. Gardas

PurposeThe reduction of food wastage at every stage of a fresh produce supply chain helps in achieving balance among all three dimensions (social, ecological and economic) of the sustainability and helps in stimulating the growth and development in the agricultural domain. The purpose of this paper is to address the causal factors of post-harvesting losses (PHLs) occurring in the transportation phase.Design/methodology/approachThrough exhaustive literature survey and expert opinions, 12 crucial barriers to sustainable transportation of fruits and vegetables (F&V) are identified. The interpretive structural modeling (ISM) methodology, a multi-criteria decision-making (MCDM) approach, is employed for developing a structural model of the identified barriers.FindingsThe results of the analysis highlighted that two factors, namely, the non-availability of refrigerated vehicles, and excessive loading on the vehicles, are the most significant barriers to sustainable transportation which are found to have the highest driving power.Research limitations/implicationsThe results of the present research are applicable to the F&V supply chains only. The established interrelation among the identified factors depends on the judgments given by the experts which could be biased. The developed ISM model is intended to guide the policy and decision makers for formulating the policies for the performance improvement of the fresh produce value chain.Originality/valueIt is the first research of its kind focusing on the model development of critical factors causing PHLs in the transportation phase of the agricultural fresh produce supply chain using MCDM process.


2020 ◽  
Vol 11 (6) ◽  
pp. 1141-1173
Author(s):  
Senthil Kumar D. ◽  
S. Vinodh

Purpose The purpose of this paper is to present the analysis of barriers affecting the adoption of lean concepts to electrical and electronics component manufacturing. Design/methodology/approach Lean concepts are being increasingly applied by electrical and electronics component manufacturers to enhance product value through streamlined process. To facilitate smooth adoption of lean concepts, barriers need to be analyzed and prioritized. In this context, a structural model of 24 barriers is developed through total interpretive structural modeling (TISM) approach. Findings ‘Changing governmental policies,’ ‘poor selection of change agents and improvement teams,’ ‘lack of top management commitment understanding and support of the system,’ ‘lack of team autonomy,’ ‘lack of flexibility and versatility’ and ‘lack of customer focus/involvement’ are found to be the dominant barriers based on TISM study. Interpretation statements are being derived from TISM model. Cross-impact matrix multiplication applied to classification analysis is conducted. Research limitations/implications In the present paper, 24 barriers are considered. In future, additional barriers could be considered to deal with managerial advancements. Practical implications The paper reports the practical case of analysis of barriers to lean adoption in electronics component manufacture. Hence, the inferences have practical relevance. Originality/value The development of structural model for the analysis of barriers to lean implementation in electronics component manufacturing small- and medium-sized enterprises is the original contribution of the authors.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lin Xiao ◽  
Ting Pan ◽  
Jian Mou ◽  
Lihua Huang

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.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nisha Bamel ◽  
Umesh Bamel

PurposeThis paper aims to identify the big data analytics (BDAs) based enablers of supply chain capabilities (SCCs) and competitiveness of firms. This paper also models the interaction among identified enablers and thus projects the relationship strength of these enablers with SCC and a firm's competitiveness.Design/methodology/approachIn order to achieve the research objectives of this paper, we employed fuzzy total interpretive structural modeling (TISM), an integrated approach of an interpretive structural model and TISM.FindingsResults suggest that BDA-based enablers namely, IT infrastructure for BDA; leadership commitment; people skills for use of BDA and financial support for BDA significantly enable SCC and enhance firm competitiveness.Practical implicationsResults of the present study have implications for researchers and practitioners; the results will enable them to design policies around identified enablers of BDA initiatives.Originality/valueThe present paper is one of a few early efforts that address the role of BDA in augmenting SCC and subsequently a firm's competitiveness from a resource-dynamic capability perspective.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shalini Menon ◽  
M. Suresh

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vishal Ashok Wankhede ◽  
Vinodh S.

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.


2014 ◽  
Vol 9 (2) ◽  
pp. 127-140 ◽  
Author(s):  
Varinder Kumar Mittal ◽  
Kuldip Singh Sangwan

Purpose – This paper aims at developing an interpretive structural model of drivers for environmentally conscious manufacturing (ECM). It will demonstrate how interpretive structural modeling (ISM) supports policy makers in the government and industry in identifying and understanding interdependencies among drivers for ECM. Interdependencies among drivers will be derived and structured into a hierarchy to derive subsystems of interdependent elements with corresponding driving power and dependency. Design/methodology/approach – ISM has been used to identify hierarchy and inter-relationships among drivers for ECM adoption and to classify the drivers according to their driving and dependence power using MICMAC analysis. The drivers for ECM adoption are identified through the review of literature followed by developing a model of drivers using ISM. Findings – The main findings of the paper include the development of an ISM model of drivers for ECM adoption. The developed model divided the identified drivers into five levels of hierarchies showing their inter-relationship and depicting the driving-dependence relationship. These five levels have been classified into four categories – awareness, external, organizational and benefits. Originality/value – The developed ISM model is expected to provide a direction to the policy makers in the government and industry and the top management of the organizations to leverage their resources in a timely manner to adopt ECM successfully.


2020 ◽  
Vol 37 (6/7) ◽  
pp. 1007-1031 ◽  
Author(s):  
Vimal Kumar ◽  
Pratima Verma ◽  
Sachin Kumar Mangla ◽  
Atul Mishra ◽  
Dababrata Chowdhary ◽  
...  

PurposeThe paper aims to identify key human and operational focused barriers to the implementation of Total Quality Management (TQM). It develops a comprehensive structural relationship between various barriers to successfully implement TQM for sustainability in Indian organizations.Design/methodology/approachWith the help of expert opinions and extant literature review, we identified the case of TQM failure companies and barriers to implement TQM effectively. Interpretive Structural Modeling (ISM) and fuzzy MICMAC techniques are employed to develop a structural model and the identified barriers are categorized based on their dependence and driving power in the various categories.FindingsFrom the intensive case analysis, we identify fourteen barriers that constrain the successful implementation of TQM. The findings also provide a hierarchy of barriers in which the absence of top management involvement and ineffective leadership are the human barriers having the highest dependence.Research limitations/implicationsThe critical inputs show the implementation of TQM in the firms being more proactive and well prepared in the selected five companies. The study's emphasis on barriers will help organizations in implementing TQM for better sustainability in an organizational context.Originality/valueIn the successful implementation of TQM, barriers need to be identified because failure has often eliminated the organizations from the market. Thus, TQM is the source of strength to achieve higher productivity, profitability, and sustainable business performance. The barriers must be identified to improve organizational performance to contribute to sustainable development.


2020 ◽  
Vol 19 (02) ◽  
pp. 309-341
Author(s):  
Muhammad Waqas ◽  
Dong Qianli ◽  
Naveed Ahmad ◽  
Yuming Zhu ◽  
Muhammad Nadeem

Due to industrialization, increasing solid waste is affecting environmental integrity globally. Reverse logistics (RL) has become a significant tool to deal with environmental degradation issues, and it is being implemented in developed countries. However, RL is at the infancy stage in developing countries especially in Pakistan due to different obstacles. This study aims to identify and analyzes the interrelationship between barriers affecting RL implementation in Pakistani manufacturing industry using an integrated methodology of Interpretive Structural Modeling (ISM) and MICMAC approach. Results of ISM and MICMAC identified organizational, financial, and technological barriers as dependent barriers. However, lack of government policy incentives, lack of responsiveness about RL, lack of enforceable laws on product return, changing in regulations due to political changes, lack of environmental law awareness and lack of corporate social responsibility emerged out as top-ranked barriers driving other barriers that need to be addressed. An inter-relationship based structural model will be helpful for supply chain and RL professional in understanding major obstacles to RL implementation and develop a strategy to promote RL in the manufacturing industry.


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