Department of Management Studies

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Occupant behavior influences energy savings in intelligent buildings over and above the advanced technologies deployed. IoT based interconnected sensors, along with personal devices such as mobile phones, wearables and virtual assistants, can assist building management systems with occupant behavior information paving the way for personalized comfort coupled with energy savings. This work investigates the occupant adoption of such an IoT climate control service in the context of Indian office spaces by examining four theories viz., TRA, TPB, TAM and VAM. The results indicate that TAM and VAM have higher explanatory power among the models considered. Further, TAM’s constructs 1. Perceived benefits, viz., improvement in comfort, productivity and wellbeing, and 2. Perceived ease of use, viz., access convenience to climate control in offices are identified as the most significant causal constructs. The results can pave way for IoT players to formulate business and technology strategies for product management and targeting specific customer segments. © 2020, IFIP International Federation for Information Processing.

World University root node

IFIP Advances in Information and Communication Technology

Occupant Adoption of IoT Based Environment Service in Office Spaces: An Empirical Investigation

Amyloids are a group of proteins that are capable of forming aggregated amyloid fibrils, which is responsible for many neurodegenerative diseases including Alzheimer's disease (AD). In our previous study, synthesis and characterization of star-shaped poly(D,L-lactide)-b-gelatin (ss-pLG) have been reported. In the present work, we have extended our work to study ss-pLG against protein aggregation. To the best of our knowledge, this is the first report on the inhibition of amyloid fibrillation by protein grafted poly(D,L-lactide). Bovine serum albumin (BSA) was chosen as the model protein, which readily forms fibril under high temperature. We found that ss-pLG efficiently suppressed the fibril formation of BSA compared with gelatin (Gel), which was supported by Thioflavin T assay, circular dichroism (CD) spectroscopy and atomic force microscopy (AFM). In addition, ss-pLG significantly curtailed amyloid-induced hemolysis. We also found that incubation of ss-pLG with neuroblastoma cells (MC65) protected the cells from fibril-induced toxicity. The rescuing efficiency of ss-pLG was better than Gel, which could be attributed to the reduced lamella thickness in branched ss-pLG. These results suggest the significance of gelatin grafting, which probably allows gelatin to interact with the key residues of the amyloidogenic core of BSA effectively. © 2020 Wiley Periodicals LLC

Department Of Biotechnology

Biopolymers

Gelatin grafted poly(D,L-lactide) as an inhibitor of protein aggregation: An in vitro case study

Many real-world systems involve higher-order interactions and thus demand complex models such as hypergraphs. For instance, a research article could have multiple collaborating authors, and therefore the co-authorship network is best represented as a hypergraph. In this work, we focus on the problem of hyperedge prediction. This problem has immense applications in multiple domains, such as predicting new collaborations in social networks, discovering new chemical reactions in metabolic networks, etc. Despite having significant importance, the problem of hyperedge prediction hasn’t received adequate attention, mainly because of its inherent complexity. In a graph with n nodes the number of potential edges is , whereas in a hypergraph, the number of potential hyperedges is . To avoid searching through the huge space of hyperedges, current methods restrain the original problem in the following two ways. One class of algorithms assume the hypergraphs to be k-uniform where each hyperedge can have exactly k nodes. However, many real-world systems are not confined only to have interactions involving k components. Thus, these algorithms are not suitable for many real-world applications. The second class of algorithms requires a candidate set of hyperedges from which the potential hyperedges are chosen. In the absence of domain knowledge, the candidate set can have possible hyperedges, which makes this problem intractable. More often than not, domain knowledge is not readily available, making these methods limited in applicability. We propose HPRA - Hyperedge Prediction using Resource Allocation, the first of its kind algorithm, which overcomes these issues and predicts hyperedges of any cardinality without using any candidate hyperedge set. HPRA is a similarity-based method working on the principles of the resource allocation process. In addition to recovering missing hyperedges, we demonstrate that HPRA can predict future hyperedges in a wide range of hypergraphs. Our extensive set of experiments shows that HPRA achieves statistically significant improvements over state-of-the-art methods.<h2>Supplemental Material</h2>

Department of Computer Science and Engineering

Department of Ocean Engineering

12th ACM Conference on Web Science

HPRA: Hyperedge Prediction using Resource Allocation

Purpose: Staged financing is a prominent feature of the venture capital investment process. With staged financing, venture capitalists (VCs) may choose to either make an investment or delay it at each round. The purpose of this paper is to investigate the influence of market uncertainty, project-specific uncertainty and agency problems on these decisions. Design/methodology/approach: The study uses data from Indian firms that received venture capital funding between 2000 and 2017. The duration between funding rounds is analysed using survival analysis. An accelerated failure time model is used to estimate the influence of market uncertainty, project-specific uncertainty and agency problems on the length of time between funding rounds. Findings: VCs delay investment when there are high levels of uncertainty in the market; if market uncertainty increases by 1%, delay in funding increases by more than 6% (almost a month) on average. There is no statistically significant relationship found between the funding duration and project-specific uncertainty. Agency problems motivate VCs to invest sooner. An increase in agency problems results in a reduction of 55% (almost five months) in the length of time before the next funding round. Practical implications: This study has useful business policy implications. It provides VCs with real option value drivers such as market uncertainty, agency problems, which influence the timing of decisions in staged investment processes. It will help to make the choice between investing and delaying at each round of financing more robust. Further, it is useful for VCs to differentiate between market uncertainty and agency problems against the backdrop of their different implications for staging decisions. Originality/value: Few studies have examined staging decisions from a real options perspective in the context of a developed economy and very few from a developing economy perspective. This study increases understanding of staging decisions in the Indian context. © 2020, Emerald Publishing Limited.

Management Research Review

An analysis of timing decision in venture capital staged financing: evidence from India

2020 has been a year of unprecedented disruption for the IS community. College campuses have been closed, instruction moved to online, and conferences are virtual. Early indications suggest significant disruption of budgetary and operating norms. At the same time, we are witnessing the miracle of digital technologies that allow us to satisfy our professional obligations and personal needs. Most businesses have figured out ways to continue to operate. Collectively these point to the possibility of significant challenges and opportunities for the IS community. Leveraging content from an AIS online forum, this panel is the first of a three-panel series at ICIS 2020 that is focused on the impacts and implications of the COVID-19 pandemic for the IS discipline and academic community. This panel will explore the issues from the perspectives of IS faculty, focusing primarily on their views about the likely consequences for IS teaching and research. © ICIS 2020. All rights reserved.

International Conference on Information Systems, ICIS 2020 - Making Digital Inclusive: Blending the Local and the Global

IS faculty perspectives on the impacts and implications of the COVID-19 pandemic for IS teaching and research

With the advent of wearable devices, we leave a huge digital footprint with every step taken in our daily lives. Though these devices positively impact health and lifestyle of users, violations of health information privacy have become ubiquitous, diverting academic attention towards these issues. This study focuses on understanding the coping behavior of fitness tracker users when confronted with the fear appeal of data privacy breach. A survey is conducted with 225 fitness tracker users using an adapted multi-item scale. A conceptual model drawn from Extended Parallel Process Model, privacy concern, and coping behavior literature is tested using SEM. The study shows, privacy concern has a strong influence on an individual's threat perception, affecting one's choice of coping behavior. The novelty of the study lies in the understanding of the impact of fear over loss of one's health-data privacy and the resulting shift in the attitude towards the technology itself. © 2020 26th Americas Conference on Information Systems, AMCIS 2020. All rights reserved.

26th Americas Conference on Information Systems, AMCIS 2020

Are you coping or copping out? Wearable users' information privacy perspective

This study investigates the dynamic impact of global and regional liquidity along with volatility on the liquidity of emerging Asian equity markets. Further, we empirically disentangle the effects of volatility and liquidity. We find that the external liquidity factors have a higher impact on domestic liquidity as compared to volatility. The impact of global volatility shocks was witnessed only during the Global Financial Crisis. Global factors have a higher influence on developed markets such as Japan and Singapore, while regional factors have a higher influence on emerging markets. These results indicate that liquidity serves as the channel of regional integration in Asia. The findings of this study provide useful insights to cross-sections of stakeholders in the investment industry.&nbsp;

Journal of Emerging Market Finance

Global Financial Crisis: Dynamics of Liquidity Risk in Emerging Asia

In this work, we consider the Vehicle Routing Problem with Simultaneous Delivery and Pickup, and constrained by time windows, to improve the performance and responsiveness of the supply chain by transporting goods from one location to another location in an efficient manner. In this class of problem, each customer demands a quantity to be delivered as a part of the forward supply service and another quantity to be picked up as a part of the reverse recycling service, and the complete service has to be done simultaneously in a single visit of a vehicle, and the objective is to minimize the total cost, which includes the traveling cost and dispatching cost for operating vehicles. We propose a Mixed Integer Linear Programming (MILP) model for solving this class of problem. In order to evaluate the performance of the proposed MILP model, a comparison study is made between the proposed MILP model and an existing MILP model available in the literature, with the consideration of heterogeneous vehicles. Our study indicates that the proposed MILP model gives tighter lower bound and also performs better in terms of the execution time to solve each of the randomly generated problem instances, in comparison with the existing MILP model. In addition, we also compare the proposed MILP model (assuming homogeneous vehicles) with the existing MILP model that also considers homogeneous vehicles. The results of the computational evaluation indicate that the proposed MILP model gives much tighter lower bound, and it is competitive to the existing MILP model in terms of the execution time to solve each of the randomly generated problem instances. © 2019, Indian Academy of Sciences.

GENERAL

Fulltext

Sadhana - Academy Proceedings in Engineering Sciences

A mixed integer linear programming model for the vehicle routing problem with simultaneous delivery and pickup by heterogeneous vehicles, and constrained by time windows

The management of inventory in a divergent supply chain involves inventory allocation/rationing in addition to the determination of order policy parameters. In the case of a stock point feeding product(s) to several downstream members, rationing mechanism can be viewed as a special case of the allocation mechanism. In a supply chain with multi-period ordering cycles, a rationing decision ensures that the entire inventory available with the feeder stock point is rationed to downstream members, whereas an allocation decision need not allocate the entire inventory available, and it is at the discretion of the decision maker at the feeder stock point to retain inventory for possible high priority demands in future periods. In any supply chain permitting backordering of demands from downstream members, the clearing of backorders is a matter of concern. This study addresses the said issue by ensuring that the feeder stock point considers the current period demand for fulfilment only after clearing the backorders with respect to the downstream members. Through this study, an attempt is made to develop mathematical models for supply chains operating with installation-specific costs (holding and shortage) and ordering policy (base stock) over a finite time horizon with and without clearing backorders in the case of rationing as well as allocating inventory to downstream members. Specifically, this work appears to be the first comparative study on allocation and rationing mechanisms in association with/without backorder clearing mechanisms in divergent supply chains, and their impact on the total supply chain cost. © 2019, Indian Academy of Sciences.

A comparative study on allocation/rationing mechanisms operational with/without backorder clearing in divergent supply chains

In this paper, the permutation flowshop scheduling problem with the objective of minimising the completion time variance (CTV) of jobs is considered, and a simulated annealing algorithm (SA) and two modified SAs (MSA1 and MSA2) are proposed. In the first phase, the proposed algorithms are used to minimise CTV of jobs without any right shifting of completion times of jobs on the last machine (RSCT). As followed in the literature some times, the RSCT (except that of the last job) is attempted in the second phase, and in the third phase, we convert sequences so as to follow the V-shaped property with respect to processing time of jobs on the last machine, followed by RSCT except that of the last job, so that the makespan and the machine utilisation in the shop floor remain the same. We present an extensive computational evaluation of the existing and the proposed heuristic algorithms. © The Author(s) 2019.