We know the importance of efficient, sustainable supply chain operations to the growth of the economy and to service the daily needs of industry and consumers. Our relationship with the Chartered Institute of Purchasing and Supply, as well as the Chartered Institute of Logistics and Transport, keeps our thinking relevant, meaningful and clear. It’s not thinking in a bubble; it’s thinking about business. Our academic work is led by your industry needs. Our research solves real challenges and our knowledge transfer activity helps you advance your business operations. Competitive advantage in your market is our goal.


Centre for Supply Chain Improvement

Recent Submissions

  • Using entropy and AHP-TOPSIS for comprehensive evaluation of internet shopping malls and solution optimality

    Kumar, Anil; Dash, Manoj Kumar; Seharawat, Ritu; University of Derby; Indian Institute of Information Technology and Management, Gwalior, India (Inderscience, 2017-02-21)
    Consumers are switching from offline to online to buy everything due to this reason nowadays Internet shopping malls (ISMs) are setting up a very crucial role in the economy. For assessment and ranking are basically a critical work which could be exploitation of Internet shopping malls information resources when consider in a scientific way, there are many methods for the evaluation and ranking of e-commerce sites. Taking into consideration Traffic Rank, Inbound Links, Competition, Speed, and Keyword Statistics, in literature Multi Criteria Decision Making (MCDM) methods are rarely used by the researchers to find the rank of Internet Shopping Malls (ISMs) on the basis of primary/secondary data of these influencing factors. This study, therefore, is unique to narrow down the gap in literature by employing MCDM methods i.e. Entropy and Analytic Hierarchy Process (AHP) to collect the weight of influencing factors and Technique for Order Preference by Similarity to Ideal (TOPSIS) to find the rank of Internet Shopping Malls (ISMs). After finding out the rank of selected criteria, solution optimality needs to be done to find the average ideal solution matrix. Conclusion and managerial implications of the study are also discussed.
  • Evaluating innovation capabilities of real estate firms: a combined fuzzy delphi and dematel approach.

    Kumar, Anil; Kaviani, Mohamad Amin; Hafezalkotob, Ashkan; Zavadskas, Edmundas Kazimieras; University of Derby; Islamic Azad University, Shiraz, Iran; Islamic Azad University, Shiraz, Iran; Vilnius Gediminas Technical University; BML Munjal University; Islamic Azad University; Islamic Azad University; Vilnius Gediminas Technical University (Taylor and Francis., 2017-12-20)
    Due to strong competition, numerous technology advancements and the monetary policy of the government, the survival of Indian real estate firms now depends on their capacity to measure their existing innovation capabilities, rebuild them and adopt new ones. The aim of this study is to evaluate the technology and human resources innovation capabilities of Indian real estate firms by applying fuzzy Delphi and DEMATEL techniques. After identifying the innovation capabilities through an extensive literature review, a questionnaire is designed based on fuzzy linguistic scales to manage any vagueness of information received. Data has been collected from experts in the field, with capabilities then finalized by using a fuzzy Delphi method. To establish cause-effect relationships among capabilities, a DEMATEL method is applied to the data collected from a second questionnaire. Analysis of the data divides capabilities into two groups i.e. cause and effect. The results show that innovation management, robustness of product and process design capability, strategic planning and knowledge resources fall in the cause group; these are critical findings given the effect on the other capabilities. The study outcomes can help real estate firms to enhance their capabilities with the proposed model providing guidelines and direction in this regard.
  • Causal modelling and analysis evaluation of online reputation management using Fuzzy Delphi and DEMATEL

    Kumar, Anil; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology and Management, Gwalior; School of Management, BML Munjal University, Gurgaon, India; Behavioural Economics Experiments and Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India (IGI Global, 2017-01)
    Online reputation management (ORM) is a significant and proactive tool that can reinforce the credibility of the service provider. Literature existing today on this topic has rarely reported on the causal modeling analysis from an ORM perspective. Therefore, the objective of this paper is to build a factor structure of ORM and to build the inter-relationship map amongst the criteria of each factor. To allow for vague human judgment, a fuzzy concept is employed in a form of Fuzzy Delphi. The DEMATEL technique has been used to develop a Network Relationship Map (NRM) among the criteria of each factor. Data has been gathered through a structured questionnaire conducted with a survey of experts. The study divided the criteria of each factor into cause-effect criteria. Findings of the study show that criteria such as distributed reputation system, trust, online competitive branding, website management, customer relationship, search engine optimization, corporate social responsibility, users' reach, competition/page views, purchase discounted products and cash back or money back fall under the cause group of ORM's factors. The results of this study can not only help service providers to enhance their reputation but can also guide them towards targeting their customers in an online platform.
  • Using Fuzzy Delphi and Generalized Fuzzy TOPSIS to Evaluate Technological Service Flexibility Dimensions of Internet Malls

    Kumar, Anil; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology & Management, Gwalior (Springer, 2017-02-20)
    The expanding development of technology and availability of the internet is leading a consumer shift from offline to online activity. This shifting behavior shows positive signs for the growth of the e-commerce market but also increases the challenges for the online service provider to provide satisfaction and loyalty to consumers when there is no personal interaction between buyer and seller. In these circumstances, quality, in terms of technology services i.e. web/transaction, can play a significant role for the service provider, especially for internet shopping malls. But there is little material available in current literature to build a theoretical model for web/transaction flexibility dimensions and to rank internet shopping malls on their provision of services to customers. The vagueness of the available information can be tackled by fuzzy theory by employing a Fuzzy Delphi method to finalize technological service dimensions and lead to development of a research model. The final ranking of internet malls has been achieved by utilizing Generalized Fuzzy TOPSIS. The findings of this study can be useful for internet shopping malls in devising strategies to provide a better quality of web/transaction service to customers.
  • Fuzzy Delphi and hybrid AH-MATEL integration for monitoring of paint utilization

    Kumar, Anil; Mussada, Eswara Krishna; Ashif, Mohammed; Tyagi, Divakar; Srivastava, Ashish Kumar; BML Munjal University (University of Maribor, 2017-03-07)
    This study investigates the unattended aspects of paint utilization selection criteria in industries. In today competitive business environment almost all companies focus towards sustainable manufacturing. The utilization evaluation and selection criteria for paint and its consumption reduction is the top priority for industry. Especially in automotive industries, paint shop stands as a centre for hazardous waste due to wastage of paint and thinner during the painting process. This research work focuses on optimizing consumption of paint by finding most important criteria affecting paint consumption and optimizing the same to achieve maximum paint yield. The study uses the routes of Delphi technique in a fuzzy environment to find out the most important criteria for paint utilization selection, so that maximize utilization and minimize consump-tion reduction of paint has been achieved. An integrated approach of AHP and DEMATEL methods has been implemented to prioritize the criteria and to familiarize the relationship within criteria. The outcomes of the study substantiate and proves that this study is the best way to select a particular paint utilization selection criteria for the paint shop and also to anticipate the optimal level of paint utilization.
  • Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

    Kumar, Anil; Kabra, Gaurav; Mussada, Eswara Krishna; Dash, Manoj Kumar; Rana, Prashant Singh; Xavier Institute of Management, Bhubaneswar, India; BML Munjal University; Indian Institute of Information Technology & Management, Gwalior (Madhya Pradesh), India; Thapar University Patiala, Punjab, India (Springer, 2017-05-30)
    A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.
  • Capturing user sentiments for online Indian movie reviews.

    Trivedi, Shrawan Kumar; Dey, Shubhamoy; Kumar, Anil; Indian Institute of Management Sirmaur, Sirmaur, India; Indian Institute of Management Indore, Indore, India; University of Derby; Department of IT and Systems, Indian Institute of Management Sirmaur, Sirmaur, India; Department of Information Systems, Indian Institute of Management Indore, Indore, India; Department of Decision Science, BML Munjal University, Gurgaon, India (Emerald Insight, 2018-08-06)
    Sentiment analysis and opinion mining are emerging areas of research for analysing Web data and capturing users’ sentiments. This research aims to present sentiment analysis of an Indian movie review corpus using natural language processing and various machine learning classifiers. In this paper, a comparative study between three machine learning classifiers (Bayesian, naïve Bayesian and support vector machine [SVM]) was performed. All the classifiers were trained on the words/features of the corpus extracted, using five different feature selection algorithms (Chi-square, info-gain, gain ratio, one-R and relief-F [RF] attributes), and a comparative study was performed between them. The classifiers and feature selection approaches were evaluated using different metrics (F-value, false-positive [FP] rate and training time).The results of this study show that, for the maximum number of features, the RF feature selection approach was found to be the best, with better F-values, a low FP rate and less time needed to train the classifiers, whereas for the least number of features, one-R was better than RF. When the evaluation was performed for machine learning classifiers, SVM was found to be superior, although the Bayesian classifier was comparable with SVM. This is a novel research where Indian review data were collected and then a classification model for sentiment polarity (positive/negative) was constructed.
  • Environmental, social and economic growth indicators spur logistics performance: from the perspective of South Asian Association for regional cooperation countries.

    Khan, Syed Abdul Rehman; Jian, Chen; Zhang, Yu; Golpîra, Hêriş; Kumar, Anil; Sharif, Arshian; School of Economics and Management, Tsinghua University, Beijing, China; School of Economics and Management, Chang'an University, Xi'an, Shaanxi, 710064, China; Department of Industrial Engineering, Sanandaj Branch, Islamic Azad University, Sanandaj, Iran (Elsevier., 2019-03)
    This article examines the association between green logistics operations, social, environmental and economic indicators of SAARC (South Asian Association for Regional Cooperation) countries. The research used GMM (Generalized Method of Moments) and FGLS (Feasible Generalized Least Squares) two methods to tackle the problems of heterogeneity, serial correlation and heteroskedasticity. The findings show that fossil fuel consumption is at the heart of logistics operations; the more fossil fuel and non-green energy resources that are used, the more negative effects on society and environmental sustain-ability result from this. A lower quality of transport-related infrastructure and logistics services is negatively correlated with fossil fuel usage, carbon emissions, health expenditure, greenhouse gas emissions and political instability of SAARC countries. Conversely, efficient customs procedures and greater information sharing among supply chain partners increase trade opportunities and also improve environmental sustainability in terms of minimum carbon emissions due to the shorter waiting and queue times involved. Further, the application of green energy resources and green practices can mitigate negative effects on social and environmental sustainability due to better logistics operations while improving financial performance in terms of higher GDP per capita, trade openness and greater export opportunities around the globe. As there is very limited research using green practices relationship with macro-level indicators in current literature, this research will assist both practitioners and policy makers to understand the roles of green supply chain and green logistics in enhancing environmental sustain-ability, social improvement and economic growth for a better future.
  • Performance Efficiency Measurement of Airports: A Comparative Analysis of Airports Authority of India and Public Private Partnership

    Kumar, Anil; Dash, Manoj Kumar; Sahu, Rajendra; University of Derby; BML Munjal University, Gurgaon, India; Indian Institute of Information Technology and Management, Gwalior, India; School of Management, BML Munjal University, Gurgaon, India; Behavioural Economics Experiments and Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India; Indian Institute of Information Technology and Management, Gwalior, India (IGI Global, 2018-04)
    This article describes how to improve the overall efficiency and effectiveness of the aviation sector and also to source extra funding, the Government of India has paved the way for private investors through to a Public Private Partnership (PPP) model since the 1980s. This liberalization step in the Indian aviation market has minimized the institutional barriers which have hindered the freedom and flexibility of air transport operations among private investors. Now, competition within the aviation sector has become fiercer; the Airports Authority of India (AAI) and Public Private Partnership (PPP) in Indian airports are not only providing varied services, but also attracting consumers with new infrastructure and full modern facilities. The importance of this article is because after privatization, no studies have been conducted to examine the efficiency of Indian airports by using Data Envelopment Analysis (DEA). An output-oriented DEA model is employed to determine the efficiency score of airports by taking a sample of 15 airports, including airports run by PPP, for comparison. Output-oriented DEA calculates the efficiency by maximizing the outputs for a given level of inputs. Therefore, this article contributes to the existing literature on Indian airports. Based on available data, three variables - length of runways, terminal size and number of check-in counters, are used as inputs and two variables - passenger movement and aircraft movement, are used as outputs.
  • Measuring and improving customer retention at authorised automobile workshops after free services.

    Kumar, Anil; Luthra, Sunil; Khandelwal, Dinesh Kumar; Mehta, Rajneesh; Chaudhary, Nityanand; Bhatia, Sukhdev; BML Munjal University; Government Engineering College, Nilokheri, India (Elsevier, 2017-07-29)
    Customer retention is vital for businesses with much research literature now available. But nothing has been investigated regarding measuring and improving customer retention at authorised automobile workshops after free services. Even after providing extensive warranties and other free service benefits, customers don’t use authorised workshops although their vehicles are still under warranty. By not arranging regular maintenance services, customers lose warranty benefits, with product performance and safety related awareness undermined; companies lose huge business potential. Therefore, this study aims to measure and improve customer retention at authorized automobile workshops after free services. To achieve this, a four-phased study has been conducted. In phase one, a combination of a literature review and expert opinions is used to identify customers’ retention factors. The second and third phases describe how data is collected from industry experts and customers. Analytical Hierarchy Process (AHP) and Decision Making Trial & Evaluation Laboratory (DEMATEL) are used to prioritise and examine inter-relationships among factors. In the last phase, the study recommends three business strategies to help a company to improve customer retention and make their Annual Maintenance Contract (AMC) product more customer friendly.
  • A circularity measurement toolkit for manufacturing SMEs.

    Garza-Reyes, Jose Arturo; Valls, Ailin Salomé; Nadeem, Simon Peter; Anosike, Anthony; Kumar, Vikas; University of Derby; University of Warwick; University of the West of England (Taylor and Francis, 2018-12-24)
    The development and adoption of the concept of circular economy in the last two decades have been remarkable. However, despite its widespread adoption, little progress has been made regarding its measurement, especially in manufacturing SMEs. This paper, therefore, proposes a Circularity Measurement Toolkit (CMT) which enables the assessment of the degree of circularity in manufacturing SMEs. A conceptual CMT framework, which provided the basis for the proposed tool and that defined the different types of circular practices and a classification or levels of circularity was developed from an extensive literature reviewed. To ensure the structure’s accuracy of the proposed CMT in terms of requirements to be measured, the monitoring process and actions involved, the tool was verified through a Delphi-study. Furthermore, its practicality was validated through a case study approach in a manufacturing SME. This paper contributes by filling a gap in the CE measurement field through the proposal of the CMT. Besides providing an evaluation of the degree of circularity in the practices of manufacturing SMEs, companies can also employ the proposed CMT to identify corrective actions or future efforts for the adoption of CE practices.
  • Developing textile entrepreneurial inclination model by integrating experts mining and ISM-MICMAC

    Kapse, Chanduraj Pious; Kumar, Anil; Dash, Manoj Kumar; Zavadskas, Edmundas Kazimieras; Luthra, Sunil; Government Polytechnic, Nagpur, India; BML Munjal University; Indian Institute of Information Technology and Management; Vilnius Gediminas Technical University; State Institute of Engineering & Technology,Nilokheri, India; Department of Textile Manufacturing, Government Polytechnic , Nagpur, India; School of Management, BML Munjal University , Gurgaon, India; Behavioural Economics Experiments & Analytics Laboratory, Indian Institute of Information Technology and Management, Gwalior, India; Faculty of Civil Engineering, Institute of Sustainable Construction, Vilnius Gediminas Technical University, Vilnius, Lithuania; State Institute of Engineering & Technology (Formerly known as Government Engineering College) , Nilokheri, India (Taylor and Francis, 2018-03-05)
    The Indian textile industry is lacking in an entrepreneurial inclination of a skilled young generation; because of this, the industry is facing a challenge to achieve sustainable development and growth. To overcome this problem, the goal of this work is to build an entrepreneurial inclination model in the context of the textile industry. For achieving this goal, a combined approach of an extensive literature review and experts mining has been used to establish the entrepreneurial inclination factors in phased of the study. In the second phase, an Interpretive Structural Modelling (ISM) with Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) has been applied to build a structural model and to find the driving force factors and dependence power. The results show that effective entrepreneurship courses, institutional policy, training and internship, institutional corporation and the involvement of institutional heads play a very significant role in encouraging youth towards entrepreneurship. The outcomes of the study can help both the government and academic institutes to draw up effective policy and develop an entrepreneurial culture which can help to create more entrepreneurs in the textile field.
  • Predicting changing pattern: building model for consumer decision making in digital market

    Kumar, Anil; Mangla, Sachin Kumar; Luthra, Sunil; Rana, Nripendra P.; Dwivedi, Yogesh K.; BML Munjal University; Graphic Era University, Dehradun, India; State Institute of Engineering and Technology, Nilokheri, India; Swansea University; BML Munjal University, Gurgaon, India; Department of Mechanical Engineering, Graphic Era University, Dehradun, India; Department of Mechanical Engineering, State Institute of Engineering and Technology, Nilokheri, India; Emerging Markets Research Centre (EMaRC), School of Management, Swansea University, Swansea, UK; Emerging Markets Research Centre (EMaRC), School of Management, Swansea University, Swansea, UK (Emerald Insight, 2018-09-10)
    Purpose Consumers have the multiple options to choose their products and services, which have a significant impact on the pattern of consumer decision making in digital market and further increases the challenges for the service providers to predict their buying pattern. In this sense, the purpose of this paper is to propose a structural hierarchy model for analyzing the changing pattern of consumer decision making in digital market by taking an Indian context. Design/methodology/approach To accomplish the objectives, the research is conducted in two phases. An extensive literature review is performed in the first phase to list the factors related to the changing pattern of consumer decision making in digital market and then fuzzy Delphi method is applied to finalize the factors. In the second phase, fuzzy analytic hierarchy process (AHP) is employed to find the priority weights of finalized factors. The fuzzy set theory allows capturing the vagueness in the data. Findings The findings obtained in this study shows that consumers are much conscious about innovative and trendy products as well as brand and quality; therefore, the service providers must think about these two most important factors so that they can able to retain their consumer in their online portal. Practical implications The analysis shows that “innovative and trendy” is the first priority factor for the consumers followed by “brand and quality” and “fulfilment and time energy.” The proposed model can help the marketers and service providers in predicting customers’ preferences and their changing pattern efficiently under vague surroundings. The outcomes of this research work not only help the service provider to update their products and services according to consumers’ needs but can also help them to increase profit and minimize their risk. Originality/value This work contributes to consumer research literature focusing on problem evaluation in the context of changing pattern of consumer decision making in digital era.
  • Sustainable stochastic production and procurement problem for resilient supply chain.

    Kaur, Harpreet; Singh, Surya Prakash; Garza-Reyes, Jose Arturo; Mishra, Nishikant; Birla Institute of Management Technology; Indian Institute of Technology Delhi; University of Derby; University of Hull (Elsevier, 2018-12-06)
    Traditionally business organizations take production and procurement decisions independently. First, the decision is made on product mix and then procurement plan is developed. However, procurement for all the dependent items is computed using bill of material information of independent items. Any market uncertainty in demand of independent items does not only affects production plan but also the procurement process. Also, sustainability is an essential business aspect and must be considered in production and procurement decisions. Hence, there is a need to develop a resilient integrated production and procurement model capable to capture the fluctuating market demand and also uncertainties in production, supplier & carrier capacities. The paper proposes an independent and integrated production and procurement model considering sustainability and uncertainty for a resilient supply chain. Various possible uncertainties such as market demand, machine capacity, supplier and carrier capacities in the presence of carbon emissions is also considered in the proposed models. The paper also proposed a supplier selection model under uncertainty using Fuzzy-MCDM techniques. The proposed models are MILP & MINLP, and are demonstrated using numerical illustrations solved in LINGO 10. The performance analysis is also conducted and it is found that the integrated model will always provide a more efficient optimal solution while traditional independent production & procurement models may even lead to infeasible solution.
  • Construction of capital procurement decision making model to optimize supplier selection using Fuzzy Delphi and AHP-DEMATEL

    Kumar, Anil; Pal, Amit; Vohra, Ashwani; Gupta, Sachin; Manchanda, Suryakant; Dash, Manoj Kumar; BML Munjal University; Indian Institute of Information Technology and Management; BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; MBA-Hero Lead, BML Munjal University, Gurugram, India; Indian Institute of Information Technology and Management, Gwalior, India (Emerald, 2018-07-02)
    Purpose – Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. Therefore, the aim of this study is the construction of capital procurement decision making models to optimize supplier selection in the Indian automobile industry. Design/methodology/approach – To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings – The results show that the total cost of ownership is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, total cost of ownership, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value – The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.
  • Investigating the role of social media in polio prevention in India: a Delphi-DEMATEL approach

    Kumar, Anil; Kaviani, Mohamad Amin; Bottani, Eleonora; Dash, Manoj Kumar; Zavadskas, Edmundas Kazimieras; BML Munjal University, Gurgaon, India; Islamic Azad University; University of Parma; Indian Institute of Information Technology & Management; Vilnius Gediminas Technical University; School of Management, BML Munjal University, Gurgaon, India; Young Researchers and Elite Club, Shiraz Branch, Islamic Azad Universtiy, Shiraz, Iran; Department of Engineering and Architecture, University of Parma, Parma, Italy; Indian Institute of Information Technology and Management, Gwalior, Madhya Pradesh, India; Institute of Sustainable Construction, Faculty of Civil Engineering, Vilnius Gediminas Technical University, Vilnius, Lithuania (Emerald, 2018-05-08)
    Abstract Purpose- This study aims to evaluate the role of social media (SM) tools in the polio prevention in an Indian context, using a hybrid Delphi-DEMATEL approach. Design/methodology/approach- A preliminary list of suitable evaluation criteria was derived from an extensive literature review. Ten experts were then contacted to collect data and finalize the most prominent criteria using the Delphi method. To establish cause-effect relationships among the criteria, further data were collected from twenty-one experts. The decision-making trial and evaluation laboratory (DEMATEL) method was applied to process and interpret the data collected. Findings- The analysis grouped criteria into two sets, i.e. cause and effect. The results show that awareness of social cause and government utilization of resources fall into the cause group; these elements are critical since both directly affect the remaining criteria. These outcomes can help government and businesses to utilize SM for public health surveillance, e.g. to promote schemes/initiatives through sites concerning polio or related health issues. Practical implications- The findings of this research are useful for governments and individual companies to conceive their marketing initiatives akin to polio prevention issues using SM. Originality/value- Despite the emergence of SM, there has been little discussion in existing literature on their role for polio prevention; however, measuring such role could be useful in practice, to help decision makers (DMs) exploiting the potential of SM in the healthcare context. To fill this gap, this study aims to measure the role of SM in polio prevention in the Indian context and to create a cause-effect evaluation model. Using an integrated Delphi-DEMATEL framework for decision-making in the healthcare context is another novelty of this study.
  • Measuring the lean readiness of Kuwaiti manufacturing industries.

    Al-Najem, Mohammed; Garza-Reyes, Jose Arturo; ElMelegy, Ahmed; Gulf University for Science and Technology; University of Derby (Inderscience, 2018-10-04)
    The purpose of this paper is to measure the readiness of the Kuwaiti small and medium sized manufacturing industries to implement the lean system through an evaluation of their existing quality practices, and compare such readiness among different product sectors and ownership types. This study adopts the measurement framework developed by Al-Najem et al. (2013), which establishes six constructs related to lean quality practices, namely: process, planning and control, customer relations, suppliers relations, HR, and top management and leadership. Data were collected from a survey of 50 Kuwaiti small and medium sized manufacturing industries operating in different industrial sectors. One research question and two hypotheses were developed and tested using t-test and Levene’s test, descriptive analysis, and one-way ANOVA. The results demonstrate that the Kuwaiti small and medium sized manufacturing industries are far from being ready to implement lean. In addition, the study found that product sector and ownership type have no significant impact on the lean readiness in the Kuwaiti small and medium sized manufacturing industries. This research provides insight into preparing Kuwaiti, and other small and medium sized manufacturing industries, to implement the lean system by creating an assessment of their existing lean practices and lean readiness. This research is among a limited number of studies that have addressed lean within the Arab region, and only the second to examine the level of lean readiness of the Kuwaiti small and medium sized manufacturing industries. It expands the literature on lean in developing countries, particularly in the Arab region, and can provide guidance to research within other countries in the region.
  • Exploring industry 4.0 technologies to enable circular economy practices in a manufacturing context: a business model proposal.

    Nascimento, D.L.M; Alencastro, V; Quelhas, O.L.G; Caiado, R.G.G; Garza-Reyes, Jose Arturo; Tortorella, G.L; Federal Fluminense University; Pontifical Catholic University of Rio de Janeiro; University of Derby; National Polytechnic Institute (CINVESTAV); Federal University of Santa Catarina (Emerald, 2018-10)
    Purpose - The purpose of this study was to explore how rising technologies from Industry 4.0 can be integrated with circular economy (CE) practices to establish a business model that reuses and recycles wasted material such as scrap metal or e-waste Design/methodology/approach – The qualitative research method was deployed in three stages. Stage one was a literature review of concepts, successful factors, and barriers related to the transition towards a CE along with sustainable supply chain management, smart production systems, and additive manufacturing. Stage two comprised a conceptual framework to integrate and evaluate the synergistic potential among these concepts. Finally, stage three validated the proposed model by collecting rich qualitative data based on semi-structured interviews with managers, researchers, and professors of operations management to gather insightful and relevant information. Findings – The outcome of the study is the recommendation of a circular model to reuse scrap electronic devices, integrating web technologies, reverse logistics, and additive manufacturing to support CE practices. Results suggest a positive influence from improving business sustainability by reinserting waste into the supply chain to manufacture products on demand. Research implications/originality – The impact of reusing wasted materials to manufacture new products is relevant to minimizing resource consumption and negative environmental impacts. Furthermore, it avoids hazardous materials ending up in landfills or in the oceans, seriously threatening life in ecosystems. In addition, reuse of wasted material enables the development of local business networks that generate jobs and improve economic performance.
  • Evaluating the human resource related soft dimensions in green supply chain management implementation

    Kumar, Anil; Kumar Mangla, S; Luthra, Sunil; Ishizaka, Alessio; University of Derby; University of Plymouth; Government Polytechnic, Jhajjar-124103; University of Portsmouth (Taylor and Francis, 2018)
    Due to increased carbon emissions, environmental protection initiatives have gained significant attention at global level. One of the major initiatives taken by the industrial sector to minimise the negative environmental effect of the value chain activities is Green Supply Chain Management (GSCM). In industry, soft (human resource-related) dimensions influence the implementation of GSCM process greatly. In the literature, relatively less discussion is provided on assessing the significance of soft dimensions in efficient GSCM acceptance in industry. The present work is an attempt to construct a structural framework for assessing the significance of the soft dimensions in adopting GSCM concepts by taking a case of automotive company in India. A hybrid approach of Best Worst Method (BWM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is employed in this work. BWM is used to prioritize the GSCM oriented soft dimensions, and DEMATEL is employed to extract interrelationships among them. The result shows that ‘Top management commitment’, ‘Employee involvement’, ‘Organizational culture’ and ‘Teamwork’ are the highly prioritized causal soft dimensions in efficient GSCM adoption. This research work would help industry managers and practitioners to decide where to concentrate for GSCM concepts in context of soft dimensions for sustainable business development.
  • When risks need attention: adoption of green supply chain initiatives in the pharmaceutical industry

    Kumar, Anil; Zavadskasb, Edmundas Kazimieras; Mangla, Sachin Kumar; Agrawal, Varun; Sharma, Kartik; Gupta, Divyanshu; University of Derby; Vilnius Gediminas Technical University; University of Plymouth; BML Munjal University (Taylor & Francis, 2018-11-19)
    The pharmaceutical industry is very important in delivering life-saving products/services to society. There are many ways for materials/products/services concerned with pharmaceuticals to influence the environment; these include improper disposal of pills/tablets by patients, expired and unused medications, improper release of drugs by pharmacies or household sewage mixed with surplus drugs. In view of this, the present work seeks to integrate green supply chain (GSC) concepts in the pharmaceutical sector in a developing economy Indian context. In so doing, managers need to determine the potential risks in adopting GSC initiatives to achieve sustainability in operational perspectives. In this sense, this work seeks to distinguish the potential risks in adopting GSC initiatives within the pharmaceutical industry. This work uses a literature review and fuzzy Delphi approach in finalising the risks. This research also uses fuzzy Analytical Hierarchy Process (AHP) for prioritisation of the risks under vague and unclear surroundings. According to the findings, cold chain technology and supply risks categories are highly prioritised. This work can assist practising managers and government authorities in effectively developing and managing GSC initiatives in line with sustainable development goals in the context of the pharmaceutical industry. Finally, a sensitivity test is applied to evaluate the stability of ranking of risks.

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