1,722,893 research outputs found
sj-docx-1-pie-10.1177_09544089231190223 - Supplemental material for Investigation of physical, chemical and mechanical behaviour of nano-ZrO<sub>2</sub>-based dental composite
No full textSupplemental material, sj-docx-1-pie-10.1177_09544089231190223 for Investigation of physical, chemical and mechanical behaviour of nano-ZrO2-based dental composite by Shiv Ranjan Kumar, Hari Om Sharma, Sachin Kumar and Dinesh Kumar Patel in Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering</p
sj-pptx-1-tct-10.1177_15330338221080981 - Supplemental material for Analysis of miR-375-3p, miR-197-3p, and miR-15a-5p Expression and Their Clinical Relevance as Biomarkers in Lung Cancer
No full textSupplemental material, sj-pptx-1-tct-10.1177_15330338221080981 for Analysis of miR-375-3p, miR-197-3p, and miR-15a-5p Expression and Their Clinical Relevance as Biomarkers in Lung Cancer by Sachin Kumar, Jyoutishman Saikia, Surender K. Sharawat, Prabhat S. Malik, Sunil Kumar and Anant Mohan in Technology in Cancer Research & Treatment</p
Big green journey : developing a scaling up framework for green livelihood initiatives
No full textShailendra Singh Bisht, Gururaja Budhya, Mandvi Kulshreshtha, Sachin Kumar, Sandeep Kuma
A conceptual framework for blockchain‐based sustainable supply chain and evaluating implementation barriers: A case of the tea supply chain
No full textBUSINESS STRATEGY AND THE ENVIRONMENTThe increasing population and income inequality in the last decades have made it necessary to focus on the concept of sustainability. In the changing world order, with economic crises, instabilities, pandemics, and social media, sustainability awareness differs significantly from past years. In addition, developing new technologies and concepts (big data, blockchain, IoT, robotic, etc.) plays a crucial role in meeting social awareness in terms of sustainability. Food sustainability is also one of the most important pillars in this concept. The integration of new technologies in agriculture and food chains will enable the current world population to use resources more efficiently and sustainably. Blockchain, one of the technologies that emerged with the arrival of Industry 4.0, is a technology that can be used effectively in many sectors. Particularly in supply chain networks, it is seen as a technology that supports the sustainability concept due to its features such as decentralization, reliability, transparency, consensus standards, and traceability. However, since blockchain is an immature and new technology, there are some challenges with integrating it into existing conventional systems. This study aims to present a conceptual framework for the integration of blockchain technology to establish a sustainable tea supply chain, define possible actions, and prioritize the possible risks that may arise in this integration process; this will be done through the Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) approach. In this context, initially, the current tea supply chain will be considered and the activities carried out will be defined in terms of technological, environmental, and strategic sustainability. Then, the design that includes the integration of all activities with blockchain technology is presented. The proposed design covers the entire tea supply chain from end to end and is considered with regard to all sustainability dimensions. In the proposed framework, barriers that may be encountered and risks that may arise at each stage of the tea supply chain process are identified; managerial implications are then presented to eliminate these risks. To enhance the use of the recommendations made, risks and barriers are prioritized with SF-AHP management. Thus, the problems that need to be solved primarily in the technological transformation process can be evaluated more clearly. The proposed theoretical framework is expected to extend to all agricultural practices and support technological advances throughout the agricultural sector
A decision support system for selection and risk management of sustainability governance approaches in multi-tier supply chain
Full text linkLower-tier suppliers' sustainability noncompliance and focal company's failure at meeting the expectations of the stakeholders to extend sustainability towards lower-tier suppliers carry multiple risks, tangible and intangible, to the focal company. It is expected that extending sustainability to suppliers at lower tiers through effective sustainability governance approaches (SGAs) can reduce these risks for focal companies. The existing literature lacks research on decision support tools using management science techniques to help decision makers choose the most suitable SGA/SGAs in a given situation and the risk management of SGAs in multi-tier supply chain. The present study develops a model-driven decision support system (DSS) using Bayesian network (BN) that can assist operations managers in selecting the most effective SGA/SGAs in multi-tier supply chain considering each situation. The developed DSS includes contingency factors and risk variables and their relationships which are identified through a systematic literature review and is applied to the multi-tier, sustainable supply chain of a multinational company operating in China to demonstrate its practical applicability. The DSS is then used in the risk management of the SGAs in multi-tier supply chain, which includes core steps such as identification of the contingency factors and risk variables, the prioritisation of the contingency factors and risk treatment. By Prioritising the basic contingency factors, ‘‘Focal company's sustainability knowledge’’ and ‘‘The specific nature of the materials sourced from lower-tier supplier’‘, and ‘‘First-tier supplier's possession of internal resources'’ and ‘‘First-tier supplier's sustainability training’’ were identified as the two most important factors regarding their impact on the effectiveness of the direct and indirect approaches respectively. Detailed managerial implications related to the development and implementation of the DSS and the risk management process are also provided
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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