Is lean synergistic with sustainable supply chain? An empirical investigation from emerging economy

© 2018 Elsevier B.V. In the extant literature some researchers have agreed upon the nature of inter-relationship between lean and green as synergistic whereas other have termed it as coincidental or even dichotomous. We submit that the inconclusiveness in the relationship between lean and green arises from not investigating it from a holistic standpoint. In this study, we address this gap by adjudging the relationship of lean systems with holistic supply chain context which includes sourcing, production and logistics. The proposed hypotheses are grounded in the resource-based view of the firm. We examine the relationship in the context of emerging economy such as India. Results obtained using structural equation modelling method indicates that lean implementation positively influences the implementation of sustainability practices for supplier selection and production but negatively impacts sustainability practices for delivery and logistic services. We conclude that the relationship between lean management and sustainable supply chain management is not straightforward. Gain at some place may cause loss at other places. Therefore, the net impact must be seen in totality and segmented analysis is the cause of inconclusive findings

Optimal number of remanufacturing in a circular economy platform

In reducing waste and protecting natural resources benefits in a circular economy platform, performing remanufacturing tasks are complex, as it may be associated with costs such as investment, setup and disposal cost. Thus, many studies those aims to find the optimal number of remanufacturing has been investigated whether it is an infinite or a constant number of remanufacturing via trial-and-error method. During the investigation, the disposal rate is assumed as a fixed value for each unique case, which needs further focus. The current study aims to propose a novel decision model to figure out an optimal number of remanufacturing regarding to the various ratio of used units returned for recovery. The proposed model was extended in context of remanufacturing opportunities of PVC products. The obtained findings are useful for companies in managing remanufacturing processes by knowing optimal remanufacturing times, and results in enhanced economic–ecological–social gains in the circular economy

Taking Ecological Function Seriously: Soil Microbial Communities Can Obviate Allelopathic Effects of Released Metabolites

Allelopathy (negative, plant-plant chemical interactions) has been largely studied as an autecological process, often assuming simplistic associations between pairs of isolated species. The growth inhibition of a species in filter paper bioassay enriched with a single chemical is commonly interpreted as evidence of an allelopathic interaction, but for some of these putative examples of allelopathy, the results have not been verifiable in more natural settings with plants growing in soil.On the basis of filter paper bioassay, a recent study established allelopathic effects of m-tyrosine, a component of root exudates of Festuca rubra ssp. commutata. We re-examined the allelopathic effects of m-tyrosine to understand its dynamics in soil environment. Allelopathic potential of m-tyrosine with filter paper and soil (non-sterile or sterile) bioassays was studied using Lactuca sativa, Phalaris minor and Bambusa arundinacea as assay species. Experimental application of m-tyrosine to non-sterile and sterile soil revealed the impact of soil microbial communities in determining the soil concentration of m-tyrosine and growth responses.Here, we show that the allelopathic effects of m-tyrosine, which could be seen in sterilized soil with particular plant species were significantly diminished when non-sterile soil was used, which points to an important role for rhizosphere-specific and bulk soil microbial activity in determining the outcome of this allelopathic interaction. Our data show that the amounts of m-tyrosine required for root growth inhibition were higher than what would normally be found in F. rubra ssp. commutata rhizosphere. We hope that our study will motivate researchers to integrate the role of soil microbial communities in bioassays in allelopathic research so that its importance in plant-plant competitive interactions can be thoroughly evaluated

When strategies matter: Adoption of sustainable supply chain management practices in an emerging economy's context

© 2018 Over the past few years, a growing concern has been noticed among society, government and non-government organisations for conserving the environment and adopting Sustainable Supply Chain management (SSCM) practices. However, it is not simple for industries to develop sustainability in their business operations and activities especially in emerging economies. In this sense, the purpose of present research is to recognise and analyse various strategies to implement SSCM practices in Indian context. Present research has recognized nine key strategies. Due to qualitative nature of research, Interpretive Structural Modelling (ISM) methodology integrated with fuzzy MICMAC analysis to further refine the hidden relationship between strategies has been attempted. The identified SSCM strategies have been categorized based on their dependence and driving power. ISM methodology offers merely binary relationship among strategies, whereas fuzzy MICMAC analysis gives accurate investigation related to dependence and driving power of strategies. Findings reveals that ‘Management involvement, support and commitment’; ‘Understanding of the sustainability impacts of their supply chain’ and ‘Establishing a vision and objectives for supply chain sustainability’ are the strategies with the topmost independence powers. The developed model will help in uncovering the interaction and dependence among the identified strategies in implementation of SSCM practices from industrial viewpoint. The inputs of experts from academia and Indian automotive manufacturing firms have been used in this research. The present work will facilitate automotive and related firms in prioritisation of strategies and managing resources in a most sustainable way in an emerging economy context

Big data driven supply chain innovative capability for sustainable competitive advantage in the food supply chain: Resource‐based view perspective

AbstractThe food supply chain (FSC) is becoming more sustainable as companies aim to meet demand with lower waste and emissions. Big data analytics (BDA) can help achieve sustainability goals by extracting meaningful information from past data to help create sustainable strategies. However, in the sustainability literature, BDA's role in enabling sustainable FSC innovations is not explored. Thus, this study investigates how data‐driven analytics might improve FSC innovation by adopting creative tactics in every triple bottom line (TBL) component – green, corporate social responsibility (CSR), and financial – to gain a competitive edge. A resource‐based view (RBV) perspective was used to evaluate the links between supply chain (SC) innovation capabilities and competitive advantage (CA) in FSC innovation and sustainability. Indian food processing enterprises were surveyed using a questionnaire to collect data from 200 respondents. Adopting a structural equation modelling (SEM) approach, six hypotheses were evaluated for significance on the surveyed data using AMOS V.20. Since both goodness and badness fit indices were above cut‐off values, the measurement model was robustly evaluated and found to fit the survey data well. Structural model findings supported all study hypotheses. The results indicate that BDA strongly impacts food supply chain TBL and FSC innovation. Data‐driven innovative TBL methods were shown to boost FSC competitiveness. With the growing demand for value‐added innovation in FSC sustainable development, this study uniquely contributes to the current literature by linking BDA and TBL practice innovation to FSC CA.</jats:p

Risks to Big Data Analytics and Blockchain Technology Adoption in Supply Chains

Supply chains (SCs) are susceptible to risks because of their dynamic and complex nature. Big data analytics (BDA) through blockchain technology (BCT) can significantly contribute to managing SC risks. However, to date, the combined effect of BDA-BCT for SC risks has not been investigated extensively in the literature. This paper aims to identify the risk factors of the BDA-BCT initiative for Indian manufacturing organisations. Through the literature and experts’ judgments, sixteen risk factors were identified. Data was collected from machine tool, automobile component, and electrical manufacturing organisations. Further interrelations between risk factors were evaluated using the grey DEMATEL approach. The results show that ‘supply chain visibility risks’, ‘infrastructure and development costs’, ‘demand forecasting and sensing risks’, ‘data privacy and security risks’, ‘policy and legality related risks’, and ‘supply chain resilience’ were identified as common factors in the adoption of BDA-BCT practices by the three organisations. The cause-effect relationship between risk factors can assist managers, suppliers, service providers, and policymakers in the significant adoption of BDA-BCT in the context of manufacturing organisations. The study provides a novel way to utilise BDA-BCT in minimising supply chain risks. Limitations of the study are that it was conducted only for Indian organizations. In the future, the findings of the study can be validated through empirical analysis