Faculty & Research

Research Productive

Show result

Search Query :
Area :
Search Query :
3848 items in total found

Journal Articles | 2021

Passively wait for gridlock, or proactively invest in service? Strategies to promote car-to-transit switches among aspirational urbanites in rapidly developing contexts

Sandip Chakrabarti

Transport Policy

Journal Articles | 2021

Space between products on display: The impact of interspace on consumer estimation of product size

Yuli Zhang, Hyokjin Kwak, Marina Puzakova, and Charles R. Taylor

Journal of the Academy of Marketing Science

This research examines the effect that leaving space between products has on consumers’ estimation of product size. We theorize and empirically confirm that when space is left between products (i.e., the display is interspaced), consumers are better able to distinguish the product from the environment, which results in more attention being devoted to the product, and, in turn, larger estimation of the product’s size. Furthermore, we demonstrate downstream outcomes (i.e., consumer choices, purchase intentions) of the effect of interspatial product display on product size estimates; that is consumers react more favorably to products that are displayed in an interspatial product display when their product usage goals require large-sized products. Meanwhile, non-interspatial product displays are preferred when consumers holding a consumption goal geared to a small product size. Finally, we validate and solidify these novel interspace effects in both advertising and retailing contexts via a series of six studies including five different product types (e.g., shampoo, food, water bottle).

Read More

Journal Articles | 2021

Seasonal time trade-offs and nutrition outcomes for women in agriculture: Evidence from rural India

Vidya Vemireddy and Prabhu L Pingali

Food Policy

Women in agriculture are involved in agricultural activities and are solely responsible for household-level unpaid work. They face severe time trade-offs between agricultural and household activities across crop seasons. Recent literature suggests that these time trade-offs may negatively impact their nutrition. However, there is no quantitative evidence exploring this relationship within an agricultural context. This paper addresses this research gap by analyzing the relationship between women’s time trade-offs and their nutritional outcomes. Using a unique ten-month primary panel data of 960 women from India, our findings show that women are severely time-constrained, as they contribute significantly to agricultural as well as domestic work. Our results show that during peak seasons relative to lean seasons, women’s time trade-offs (rising opportunity cost of time) are negatively associated with the intake of calories, proteins, iron,zinc and Vitamin A. We show that this negative relationship is manifested severely among women who are landless and cultivate paddy alone (food crop) or paddy and cotton (mixed crop). This study highlights the gendered role of agricultural activities in rural households and the need to recognize time as a scarce resource when implementing policies and programs involving women in agriculture. We contribute to the literature of agriculture-nutrition linkages by examining the the time use pathway in detail. Besides providing novel metrics, we discuss several policy implications to reduce women’s time constraints and enhance their nutrition.

Read More

Journal Articles | 2021

Solving bilevel optimization problems using Kriging Approximations

Ankur Sinha and Vaseem Shaikh

IEEE Transactions on Cybernetics

Bilevel optimization involves two levels of optimization, where one optimization problem is nested within the other. The structure of the problem often requires solving a large number of inner optimization problems that make these kinds of optimization problems expensive to solve. The reaction set mapping and the lower level optimal value function mapping are often used to reduce bilevel optimization problems to a single level; however, the mappings are not known a priori , and the need is to be estimated. Though there exist a few studies that rely on the estimation of these mappings, they are often applied to problems where one of these mappings has a known form, that is, piecewise linear, convex, etc. In this article, we utilize both these mappings together to solve general bilevel optimization problems without any assumptions on the structure of these mappings. Kriging approximations are created during the generations of an evolutionary algorithm, where the population members serve as the samples for creating the approximations. One of the important features of the proposed algorithm is the creation of an auxiliary optimization problem using the Kriging-based metamodel of the lower level optimal value function that solves an approximate relaxation of the bilevel optimization problem. The auxiliary problem when used for local search is able to accelerate the evolutionary algorithm toward the bilevel optimal solution. We perform experiments on two sets of test problems and a problem from the domain of control theory. Our experiments suggest that the approach is quite promising and can lead to substantial savings when solving bilevel optimization problems. The approach is able to outperform state-of-the-art methods that are available for solving bilevel problems, in particular, the savings in function evaluations for the lower level problem are substantial with the proposed approach.

Read More

Journal Articles | 2021

How does the adoption of digital payment technologies influence unorganized retailers’ performance? An investigation in an emerging market

Anirban Adhikary, Krishna Sundar Diatha, Sourav Bikash Borah, and Amalesh Sharma

Journal of the Academy of Marketing Science

Unorganized retail dominates the retail landscape across emerging markets (EMs) and is undergoing rapid digitalization. However, the extant literature has not explored the impact of digital payment system adoption on unorganized retailer (UR) performance. By conducting three related studies and relying on the tenets of the resource-based view of firms, we show that digital payment technologies’ adoption increases economic performance (i.e., revenue) for a sample of 403 EM URs. This effect is enhanced by such retailers’ prioritization of technological investments and attenuated by their credit facilities. We find that card-based and app-based technologies positively impact UR performance. URs can maximize their performance by adopting two technologies, and there is a synergistic effect between card-based and account-based technologies. On average, adoption increases a UR’s economic performance by 9.6%. We present a nuanced understanding of whether, how much, and which digital payment technologies should be adopted by EM URs.

Read More

Journal Articles | 2021

Competitive hub location problem: Model and solution approaches

Richa Tiwari, Sachin Jayaswal, and Ankur Sinha

Transportation Research Part B: Methodological

In this paper, we study the hub location problem of an airline that wants to set up its hub and spoke network, in order to maximize its market share in a competitive market. The market share is maximized under the assumption that customers choose amongst competing airlines on the basis of utility provided by the respective airlines. We provide model formulations for the airline’s problem for two alternate network settings: one in the multiple allocation setting and another in the single allocation setting. Both these formulations are non-linear integer programs, which are intractable for most of the off-the-shelf commercial solvers. We propose two alternate approaches for each of the formulations to solve them optimally. The first among them is based on a mixed integer second order conic program reformulation, and the second uses Kelley’s cutting plane method within Lagrangian relaxation. On the basis of extensive numerical tests on well-known data-sets (CAB and AP), we conclude that the Kelley’s cutting plane within Lagrangian relaxation is computationally the best for both the single and multiple allocation settings, especially for large instances. We are able to solve instances upto 50 nodes from AP data-set within 120 and 10 minutes of CPU time for single and multiple allocation settings, respectively, which were unsolved by mixed integer second order cone based reformulation or Kelley’s cutting plane algorithm in the maximum allowed CPU time (3 hours for single allocation and 1 hour for multiple allocation).

Read More

Journal Articles | 2021

Optimal monopoly mechanisms with demand uncertainty

James Peck and Jeevant Rampal

Mathematics of Operations Research

This paper analyzes a monopoly firm’s profit-maximizing mechanism in the following context. There is a continuum of consumers with a unit demand for a good. The distribution of the consumers’ valuations is given by one of two possible demand distributions/states. The consumers are uncertain about the demand state, and they update their beliefs after observing their own valuation for the good. The firm is uncertain about the demand state but infers it from the consumers’ reported valuations. The firm’s problem is to maximize profits by choosing an optimal mechanism among the class of anonymous, deterministic, direct revelation mechanisms that satisfy interim incentive compatibility and ex post individual rationality. We show that, under certain sufficient conditions, the firm’s optimal mechanism is to set the monopoly price in each demand state. Under these conditions, Segal’s optimal ex post mechanism is robust to relaxing ex post incentive compatibility to interim incentive compatibility.

Read More

Books | 2021

Hospitality financial management and contextualized decision making

Nan Hua, Barry Bloom, Agnes DeFranco, Toni Repetti, Twila Mae Logan, Dipendra Singh Mann, Peng Liu, Prashant Das and Arun Upneja

Kendall Hunt

Books | 2021

The Black Box: Innovation and public policy in India

Rakesh Basant

Penguin Random House

Journal Articles | 2021

The implications of economic uncertainty for bank loan portfolios

Sanket Mohapatra and Siddharth M. Purohit

Applied Economics

This paper analyses the impact of economic uncertainty on the composition of bank credit across household and firm loans. Using bank-level data spanning 40 developed and developing countries, we find that higher economic uncertainty is associated with an increase in the relative share of household credit in the loan portfolio of banks. This change in composition of credit may result from banks efforts to reduce the overall riskiness of their loan portfolios, since corporate loans are generally viewed as riskier than household loans. This shift is more pronounced for weakly-capitalized banks, which may face greater risks during economic shocks, and for larger banks, which may be riskier due to complex business models and more market-based activities. The variation in our main findings by banks capitalization and size suggests that they arise from changes in bank credit supply in response to greater uncertainty. The baseline results hold for a range of robustness tests. Our study highlights the role of aggregate uncertainty in micro-level outcomes and are relevant for bank capital regulation and the conduct of macroprudential policy.

Read More
IIMA