Anchored in the resource-based view theory, the objective of this research is to empirically analyse the behavioural factors affecting the green supply chain management (GCSM) performance in a fast-growing emerging economy by taking an empirical data set of 101 responses from personnel in the mining sector. Behavioural factors in green supply chains are still a critical challenge-not yet a well-explored academic subject-when the focus is on the mining industry of emerging economies like India; the lack of studies in this field could be a factor preventing the Indian mining industry becoming more green. In terms of methodology, original survey data were processed through AMOS 4.0, adopted for assessing the causal connection among the six constructs, that is, top management support, teamwork, workplace culture, resistance to change, green innovation, and green motivation. We further explore the input from the human side of GCSM by highlighting that top management support and green motivation are the most crucial behavioural factors that influence GCSM in the Indian mining sector. The study will be helpful for mining companies because it will enable them to identify the areas that require their attention for enhancing GCSM performance related to behavioural aspects.
One of the most common symptoms observed among most of the Parkinson’s disease patients that affects movement pattern and is also related to the risk of fall, is usually termed as “freezing of gait (FoG)”. To allow systematic assessment of FoG, objective quantification of gait parameters and automatic detection of FoG are needed. This will help in personalizing the treatment. In this paper, the objectives of the study are (1) quantification of gait parameters in an objective manner by using the data collected from wearable accelerometers; (2) comparison of five estimated gait parameters from the proposed algorithm with their counterparts obtained from the 3D motion capture system in terms of mean error rate and Pearson’s correlation coefficient (PCC); (3) automatic discrimination of FoG patients from no FoG patients using machine learning techniques. It was found that the five gait parameters have a high level of agreement with PCC ranging from 0.961 to 0.984. The mean error rate between the estimated gait parameters from accelerometer-based approach and 3D motion capture system was found to be less than 10%. The performances of the classifiers are compared on the basis of accuracy. The best result was accomplished with the SVM classifier with an accuracy of approximately 88%. The proposed approach shows enough evidence that makes it applicable in a real-life scenario where the wearable accelerometer-based system would be recommended to assess and monitor the FoG.
Purpose – The purpose of this paper is to identify the success factors for supply chain in Indian small- and medium-scale enterprises (SMEs) and establish a causal relationship among them. In the present scenario, the SMEs are under huge pressure to achieve the supply chain competitive advantage and to improve operation and logistic effectiveness and, at the same time, remain tractable to the demand uncertainty and volatility in the market. To enhance the performance of supply chain in SMEs, the managers need to identify the internal as well as the external factors that affect the supply chain performance of SMEs in India. They need to understand the causal relationship of these factors. Design/methodology/approach – There may be a number of factors that are critical for achieving acceptable supply chain performance, and these factors have been identified by principal component analysis (PCA). In all, 29 factors have been identified by using PCA and the dominating 29 factors are categorized into 6 constructs, and finally, the structural equation modelling (SEM) methodology using the AMOS 4.0 program has been adopted as the primary methodology for this paper to assess the causal relationship among six constructs. Findings – In this paper, the authors analyzed the structural relations among information technology (IT), logistic effectiveness, operational effectiveness, customer relationship, supplier relationship and SCM competitive advantage. Results indicate that IT holds the key to achieve the SCM competitive advantage in SCM practices of SMEs in India. Research limitations/implications – The proposed models for enabling factors are tested in firms with a limited numbers of factors in highly competitive environment. More factors may be incorporated, which will help for a clear understanding and establishing the causal relationship among the various enabling factors. Practical implications – Although managers of Indian SMEs are aware of various enabling factors, a systematic approach is required for identifying enabling factors, and as these factors may have complex interrelation between them for analyzing supply chain performance in SMEs, it is essential that such an approach is in place. The paper presented here will help the SMEs managers in identifying the areas in which they need to focus their attention to improve SCM practices. A structural equation modelling is developed to show the complex relationship between the factors that affect the performance. In addition to that, the proposed structural equation model acts as a good guideline to improve the performance of the supply chain in India. Originality/value – The paper provides a structural equation model to develop a map of the causal relationships and magnitude among identified enabling factors.
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