Showing papers by "Chandrasekharan Rajendran published in 2020"

Relating Environmental, Social, and Governance scores and sustainability performances of firms: An empirical analysis

Abstract: Environmental, Social, and Governance (ESG) scores can act as an indicator for sustainability performance of organizations. This paper explores an empirical evidence for the relationship binding ESG scores and sustainability performances of firms. We observe and evaluate the ESG performance scores of 1,820 firms globally for 5 years, from 2014 to 2018 on 10 major themes and over 400 different indicators, as listed by Thomson Reuters and is captured from the Bloomberg terminal data. We posit five hypotheses to check the relations binding ESG scores and the total sustainability performances of firms. A Partial Least Square (PLS) analysis and standard bootstrapping using Smart PLS 3.0 software is used to observe the results and to evidence the direct and moderating effects among latent variables contributing to sustainability performances. We observe a significant and negative moderating effect of ESG performances, independently over the all direct relations, considering their relationship to ESG performances. One of the major implications of this research is in the direction of assigning priorities while considering environmental‐, social‐, and governance‐related themes in the implementation of any strategies or policies into practice.

Permutation flowshop scheduling to obtain the optimal solution/a lower bound with the makespan objective

Abstract: This paper focuses on developing the optimal solution or a lower bound for N-job, M-machine Permutation Flowshop Scheduling (PFS) problem in a manufacturing system with the objective of minimizing the makespan using Lagrangian Relaxation (LR) technique. Even though LR technique is considered, in general, as a good method to obtain a lower bound, research in this direction with respect to our problem under study appears scarce. We address this gap by developing two MILP based Lagrangian Relaxation models, namely, Lagrangian Relaxation Method 1 (called Proposed Lagrangian Lower Bound Program (PLLBP)) and Alternate Lagrangian Relaxation Method 1 (called ALR) to find the optimal solution or a lower bound on the makespan. Basically, we develop these LR methods to overcome the possible limitation of the general LR procedure involving the sub-gradient approach. Benchmark PFS problem instances are used to evaluate the performance of these methods. It is observed that the PLLBP outperforms the ALR, and it provides better lower bounds than the lower bounds (in most instances) reported in the literature. Even though the PLLBP is superior in terms of solution quality, it has a limitation in that it cannot execute problem instances beyond 500 jobs due to the associated computational effort.

Characterizing and Distinguishing ‘Innovative Start-ups’ Among Micro, Small and Medium Enterprises (MSME):

Abstract: Start-ups are entrepreneurial ventures, having a high risk of failure (Bortolini et al., 2018; Spender et al., 2017). The risk of failures of Start-ups can be minimized if they are characterized we...

Branch-and-bound algorithms for scheduling in an m-machine no-wait flowshop

Abstract: In this paper, we develop branch-and-bound algorithms for objectives such as sum of weighted flowtime, weighted tardiness and weighted earliness of jobs, for an $$m-$$ machine no-wait (continuous) flowshop. We believe that there has been no prior work on exact algorithms for this problem setup with a variety of objective functions. For the interest of space, we confine our discussion to a subset of certain combination of these objectives and the extension to other objective combinations is quite straight-forward. We explore the active nodes of a branch-and-bound tree by deriving an assignment-matrix based lower bound, that ensures one-to-one correspondence of a job with its due date and weight. This idea is based on our earlier paper on general $$m-$$ machine permutation flowshop (Madhushini et al. in J Oper Res Soc 60(7):991–1004, 2009) and here we exploit the intricate features of a no-wait flowshop to develop efficient lower bounds. Finally, we conclude our paper with the numerical evaluation of our branch-and-bound algorithms.