School of Business Scholarly Works

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https://hdl.handle.net/1808/132

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Influence of demonetization on various sectors of the Indian economy
(SCIndeks, 2023-01-17) Prasad, Anita; Goswami, Anandajit; Gurtu, Amulya
Background: India demonetized the currency in November 2016, scrapping 86.9 percent of the currency in circulation. This policy disrupted most economic activities because India was predominantly a cash economy. Purpose: The study aims to analyze the impact of demonetization on the informal-formal sector and the Indian stock markets, where investment reflects investors' confidence. Another purpose is to know the usefulness of demonetization in the proliferation of digitalization. Study design/methodology/approach: The study incorporates primary data to determine the impact on informal and formal workers' income and the acceptance of digitalization in rural-urban areas in Faridabad, Haryana. A survey was conducted, and samples for informal-formal workers and rural-urban households were collected and analyzed using the F test and the ANOVA model using an independent dummy or qualitative variables. The secondary data of the Indian stock market were empirically tested and forecasted using the Autoregressive Conditional Heteroskedasticity (ARCH) model. Finding/Conclusions: The empirical analysis reveals that after demonetization, informal workers' earnings dropped significantly, and there is a substantial income disparity between informal-formal workers. A wide gap persists in adopting digital transactions due to low awareness of digital instruments in rural areas compared to urban areas. On the contrary, no significant impact is noticed in the Indian stock market as the forecasted value of shares trading depicts positive growth. The study identifies the gaps in policy implementation. It exposes the implementation of macroeconomic policies ensuring the protection of the interest and livelihood of economically vulnerable populations. The spread of awareness towards electronic transactions may help to promote digitalization Limitations/future research: The study is limited to a few areas. Hence, the scope of future research rests on macro-level data where comparison could be conducted between rural and urban areas across various states in India.
Exploring Transparency– Sustainability Linkage: Analysis of CSR Disclosures
(Spectrum Journals, 2023) Calderon, Ricardo T.; Gurtu, Amulya; Holly, Michael A.
Corporate social responsibility (CSR) reporting is a strategy for communicating sustainability data to stakeholders. Sharing data with stakeholders is the key to the effectiveness and validity of CSR. However, the often-voluntary nature of CSR disclosure reporting results in perceived bias. Consequently, the relationship between CSR disclosure transparency and the sustainable character of a company remains unclear. The article suggests a methodology for evaluating corporate transparency through t-value analysis. The t-value analysis of CSR reports from Corporate Knights’ 2021 Global 100 Most Sustainable Corporations quantifies the total number of negative disclosures in a CSR report. This research shows a lack of correlation (p value = .805) between observable levels of transparency and third-party sustainability rankings amongst the sustainability elite of the corporate world.
Paper and packaging industry dynamics during COVID-19 and their strategies for the future
(SCIndeks, 2022-06-13) Gurtu, Amulya; Johny, Jestin; Buechse, Oliver
Background: The paper examines the "mysterious case of the disappearing toilet paper" during the COVID19 pandemic. Purpose: This paper describes the strategic impacts on paper and packaging supply chains due to the pandemic. Study design/methodology/approach: Structured interviews and qualitative discussions with organizational and supply chain management leaders. Findings/conclusions: Several "behind the scenes" and less well-documented supply chain impacts in the paper and packaging, and logistics industries were discovered. The critical effects observed are: (1) Impact on the manufacturing side was mitigated mainly by implementing CDC guidelines and by the willingness of industry leaders to go above and beyond to shield their employees from economic hardships. (2) The transportation sector has experienced a more severe workforce shortage, amplified by government actions before and during the pandemic. (3) Product specialization, a pre-pandemic strategy for industry participants, turned into a weakness during the pandemic due to unprecedented shifts in demand across sectors. (4) Traditional "lean" supply chain thinking is increasingly making way for a more interconnected "risk avoidance" strategic model. Limitations/future research: The research is limited to organizations in Midwest U.S.A. and one organization in Europe.
Rural Energy Transition for Cooking in India—Revisiting the Drivers
(MDPI, 2023-05-06) Goswami, Anandajit; Bandyopadhyay, Kaushik Ranjan; Singh, Preeti; Gurtu, Amulya
The recent analysis from IEA (International Energy Agency) on energy transition in India highlights that cooking continues to be the weakest link in the energy transition process for rural households and that rural energy transition of households to cleaner fuel is nonlinear in nature. Several programs have been designed to plague the voids and address this nonlinearity, but the transition to cleaner alternatives for cooking did not happen in the pace it should ideally have. Therefore, an empirical exercise was carried out at a national level to revisit the disconnect between the income growth and energy transition and identify the drivers of the energy transition process in cooking at the national as well as at the subnational state level for a developing country. The paper adds to the current scholarship on drivers of household energy transition by analyzing the relationship between household energy choices and non-income determinants and proves the nonlinearity in energy consumption of rural households of Bihar. Analyzing unit level record from National Sample Survey, an empirical exercise was carried out by using multinomial logit model to identify the potential determining factors at the individual household and group level. The group effect analysis through fixed and random effect has been conducted purposely to understand if social and cultural norms or community level factors within a village society have any effect on the cooking energy transition of rural households and if that offsets the effect of household income in energy transition for cooking. Furthermore, to statistically examine the perceived non-linearity in the consumption of cooking fuel such as firewood by rural households, Brock–Dechert–Scheinkman (BDS) test was conducted for rural households of 38 districts of Bihar. The analysis helps in inferring that subsidy on modern fuel and/or other cooking alternatives alone may not suffice to drive the transition process, but more targeted intervention rooted in the local cultural context in consonance with social and cultural norms or community level factors could be more effective for sustained rural energy transition.
Emissions Reduction Policies and Their Effects on Economy
(MDPI, 2022-09-11) Gurtu, Amulya; Gurtu, Apoorva; Vyas, Vidhisha
The two broad carbon-reducing policies, carbon tax and cap-and-trade, have been implemented at various national and sub-national levels. This paper examines the relationships between emissions-reducing policies and their effect on the country’s economic growth (GDP) using carbon tax and CO2 emission as explanatory variables and population and R&D as control variables. The study employs Granger causality analysis (GCA) and panel data regression analysis to find the relationships between GDP, emissions, and carbon tax. GDP usually increases as a country’s carbon emissions, carbon tax, R&D, and population increase. The analysis of carbon reduction policies, especially carbon tax and their general impact on a country’s economy, is a unique contribution of this study. The applications of this study are to motivate governments to form a national carbon abatement policy and encourage corporate leaders to invest in clean technology to grow the economy.
Optimization of Inventory Holding Cost Due to Price, Weight, and Volume of Items
(MDPI, 2021-02-04) Gurtu, Amulya
The inventory carrying cost has been assumed uniform for all products in an organization or a warehouse. This assumption is not valid for a diversified range of items in an organization or warehouse. This paper tested this hypothesis of variations in inventory holding costs in a warehouse in two industries based on the physical nature and the price of products. It is found that organizations with a wide variety of products need to calculate the inventory holding cost for each item (SKU) rather than using an average percentage cost of inventory. Inventory holding costs of items in two different organizations were calculated based on the various factors, including the actual cost of space due to the voluminous nature of the items with their existing inventory policies. A variation in inventory holding costs for each item was observed. The variation was small for an organization with homogeneous input costs, and it was large for a multi-product organization. The overall savings in the inventory holding cost due to adjusting the inventory policies through this methodology was found to be about 3%, which is significant for a big organization. This analysis will affect the decision the determining inventory carrying cost, inventory policies (e.g., stocking levels), and pricing policies (e.g., quantity discounts) for retail organizations.
Supply Chain Risk Management: Literature Review
(MDPI, 2021-01-06) Gurtu, Amulya; Johny, Jestin
The risks associated with global supply chain management has created a discourse among practitioners and academics. This is evident by the business uncertainties growing in supply chain management, which pose threats to the entire network flow and economy. This paper aims to review the existing literature on risk factors in supply chain management in an uncertain and competitive business environment. Papers that contained the word “risk” in their titles, keywords, or abstracts were selected for conducting the theoretical analyses. Supply chain risk management is an integral function of the supply network. It faces unpredictable challenges due to nations’ economic policies and globalization, which have raised uncertainty and challenges for supply chain organizations. These significantly affect the financial performance of the organizations and the economy of a nation. Debate on supply chain risk management may promote competitiveness in business. Risk mitigation strategies will reduce the impact caused due to natural and human-made disasters.
Supply Chain Management and the United Nations Sustainable Development Goals
(OSCM, 2022) Gurtu, Amulya; Vyas, Vidhisha; Srivastava, Ashutosh
This paper explored the relationships between the United Nations Sustainable Development Goals (UNSDG) and social sustainability in supply chain management (SCM). Sustainable development is a philosophy that seeks to achieve human development goals while protecting the ability of natural systems to provide natural resources and ecosystems for all economies and societies. The desired state of society is where living conditions and resources meet human needs while preserving the integrity and stability of the natural systems. Most of the work on sustainability in SCM is on economic and environmental sustainability. Only eight papers were found that reflected social sustainability. Nevertheless, social sustainability significantly impacts supply chain management, such as employee engagement, which leads to a decrease in waste, and a shorter lead time from manufacturing locations to markets. The study is based on an analysis of bibliometric data published in the Scopus database between 1991 and 2020. This study will help researchers get new perspectives on sustainable supply chains. Societal well-being is the goal of the UN SDGs. Organizations and countries can address them by recognizing the connections between UNSDGs and SCM. This is the first study to explore the literature available on UNSDG and its relationship with supply chain management.
Offshoring Decisions: A Comprehensive and Conceptual Framework
(OSCM, 2019-12-03) Gurtu, Amulya; Saxena, Ramesh; Sah, Nilesh
The paper presents complexities involved in offshoring decisions and provides a comprehensive framework for making a reliable decision for offshoring. There is a need for a holistic approach to offshoring decisions. The paper identifies various drivers, categorizes them as revenue or cost drivers, and analyzes their impact on the offshoring outcomes. The framework rationalizes the extremes of unprecedented successes and unexpected failures among organizations engaged in offshore outsourcing. The proposed framework is expected to improve the quality of offshoring decisions. The proposed framework approaches offshore outsourcing decisions at a strategic level and will improve organizations’ performance on the triple bottom line.
Computing the decomposable entropy of belief-function graphical models
(Elsevier, 2023-07-13) Jiroušek, Radim; Kratochvíl, Václav; Shenoy, Prakash P.
In 2018, Jiroušek and Shenoy proposed a definition of entropy for Dempster-Shafer (D-S) belief functions called decomposable entropy (d-entropy). This paper provides an algorithm for computing the d-entropy of directed graphical D-S belief function models. We illustrate the algorithm using Almond's Captain's Problem example. For belief function undirected graphical models, assuming that the set of belief functions in the model is non-informative, the belief functions are distinct. We illustrate this using Haenni-Lehmann's Communication Network problem. As the joint belief function for this model is quasi-consonant, it follows from a property of d-entropy that the d-entropy of this model is zero, and no algorithm is required. For a class of undirected graphical models, we provide an algorithm for computing the d-entropy of such models. Finally, the d-entropy coincides with Shannon's entropy for the probability mass function of a single random variable and for a large multi-dimensional probability distribution expressed as a directed acyclic graph model called a Bayesian network. We illustrate this using Lauritzen-Spiegelhalter's Chest Clinic example represented as a belief-function directed graphical model.
On conditional belief functions in directed graphical models in the Dempster-Shafer theory
(Elsevier, 2023-07-04) Jiroušek, Radim; Kratochvíl, Václav; Shenoy, Prakash P.
The primary goal is to define conditional belief functions in the Dempster-Shafer theory. We do so similarly to probability theory's notion of conditional probability tables. Conditional belief functions are necessary for constructing directed graphical belief function models in the same sense as conditional probability tables are necessary for constructing Bayesian networks. We provide examples of conditional belief functions, including those obtained by Smets' conditional embedding. Besides defining conditional belief functions, we state and prove a few basic properties of conditionals. In the belief-function literature, conditionals are defined starting from a joint belief function. Conditionals are then defined using the removal operator, an inverse of Dempster's combination operator. When such conditionals are well-defined belief functions, we show that our definition is equivalent to these definitions.
Making inferences in incomplete Bayesian networks: A Dempster-Shafer belief function approach
(Elsevier, 2023-09) Shenoy, Prakash P.
How do you make inferences from a Bayesian network (BN) model with missing information? For example, we may not have priors for some variables or may not have conditionals for some states of the parent variables. It is well-known that the Dempster-Shafer (D-S) belief function theory is a generalization of probability theory. So, a solution is to embed an incomplete BN model in a D-S belief function model, omit the missing data, and then make inferences from the belief function model. We will demonstrate this using an implementation of a local computation algorithm for D-S belief function models called the “Belief function machine.” One advantage of this approach is that we get interval estimates of the probabilities of interest. Using Laplacian (equally likely) or maximum entropy priors or conditionals for missing data in a BN may lead to point estimates for the probabilities of interest, masking the uncertainty in these estimates. Bayesian reasoning cannot reason from an incomplete model. A Bayesian sensitivity analysis of the missing parameters is not a substitute for a belief-function analysis.
Injury Care: A Missing Piece in the December 15th, 2022 US-Africa Leaders’ Summit
(University of Kansas Medical Center, 2023-02-21) Epie, Terrence B.; Patel, Ojas; Ayres, Jack; Haley, Albers; Reddy, Ravali; Metumah, Wendy; Gartner, Austin; Dallman, Johnathan; Heddings, Archie
Discovery of associative patterns between workplace sound level and physiological wellbeing using wearable devices and empirical Bayes modeling
(Nature Research, 2023-01-13) Srinivasan, Karthik; Currim, Faiz; Lindberg, Casey M.; Razjouyan, Javad; Gilligan, Brian; Lee, Hyoki; Canada, Kelli J.; Goebel, Nicole; Mehl, Matthias R.; Lunden, Melissa M.; Heerwagen, Judith; Najafi, Bijan; Sternberg, Esther M.; Kampschroer, Kevin; Ram, Sudha
We conducted a field study using multiple wearable devices on 231 federal office workers to assess the impact of the indoor environment on individual wellbeing. Past research has established that the workplace environment is closely tied to an individual’s wellbeing. Since sound is the most-reported environmental factor causing stress and discomfort, we focus on quantifying its association with physiological wellbeing. Physiological wellbeing is represented as a latent variable in an empirical Bayes model with heart rate variability measures—SDNN and normalized-HF as the observed outcomes and with exogenous factors including sound level as inputs. We find that an individual’s physiological wellbeing is optimal when sound level in the workplace is at 50 dBA. At lower (<50dBA) and higher (>50dBA) amplitude ranges, a 10 dBA increase in sound level is related to a 5.4% increase and 1.9% decrease in physiological wellbeing respectively. Age, body-mass-index, high blood pressure, anxiety, and computer use intensive work are person-level factors contributing to heterogeneity in the sound-wellbeing association.
The Impact of Quality Perception and Consumer Valuation Change on Manufacturer's Optimal Warranty, Pricing, and Market Coverage Strategies
(Wiley, 2018-08-13) Li, Kunpeng; Wang, Lan; Chhajed, Dilip; Mallik, Suman
We consider a manufacturer who produces and sells a new product in a monopoly market. The new product quality is unobservable to consumers before purchase. Consumers make purchase decisions based on their perception of product quality. In addition, consumer valuation toward the product will be reduced if a product failure is experienced. We formulate a two-period model to analyze the impact of consumer quality perception and consumer valuation change on manufacturer's optimal decisions over quality, warranty, price, and market coverage strategies. We find that it is optimal for the manufacturer to offer warranty compensation that is higher than the purchase price when he has a low quality reputation but is offering a high-quality product. We also identify the optimal strategy for the manufacturer in terms of market coverage. Specifically, when the consumer valuation discount factor due to product failure experience is high, it is optimal for the manufacturer to serve only the high segment in the second period. Otherwise, serving both the high and the low segments generates more profit. We further investigate consumer welfare and identify win-win conditions, where the optimal strategy of the manufacturer benefits the consumers as well.
Managing Television Commercial Inventory under Competition: An Equilibrium Analysis
(Wiley, 2018-06-28) Geng, Qin; Mallik, Suman
We develop a game theoretic model for managing prime time on-air ad inventory in the television industry. The ad inventory in this industry is priced based on rating points or the number of viewers that watch a commercial. The rating points are sold through two distinct processes: the upfront, which occurs before the broadcast season, and the scatter, which occurs throughout during the broadcast season. Television networks need to allocate their total rating points inventory to these two markets before knowing either the performance rating of their shows or the scatter market price, both of which are ex ante uncertain. The television networks offer performance guarantees on the inventory that is sold in the upfront market while such guarantees are not offered in the scatter market. We consider the inventory competition between two television networks under such a setting. To the best of our knowledge, ours is the first article to consider competition in media revenue management. We establish the existence of unique Nash equilibrium under quantity competition and describe the sensitivity of the equilibrium outcome with respect to various problem parameters. We show that choosing quantity over price during the upfront is a dominant strategy for a television network. We compare our competitive model with a centralized system and discuss the managerial implications for our work.
Socially Optimal Contracting between a Regional Blood Bank and Hospitals
(Wiley, 2018-10-20) Paul, Anand; Rajapakshe, Tharanga; Mallik, Suman
Motivated by the operational challenges faced by a Regional Blood Bank (RBB) in distributing the blood (and related products) among the hospitals in its service area, we study socially optimal contracting decisions of an RBB serving multiple hospitals. The supply of blood can be uncertain and insufficient to satisfy the total orders from hospitals. In the face of supply uncertainty, hospitals tend to over-order to compensate for a potential supply shortfall. When all hospitals inflate their order quantities, overall allocation of blood suffers and ultimately inflates the total cost of blood, which in turn lightens the wallets of patients. We model the blood bank as a social planner with the objective of minimizing the total cost of shortages and outdates throughout the supply chain. We assume hospitals need some economic incentive to report demand honestly when multiple hospitals compete for limited blood supply. We show that if the blood bank offers a suitable per unit subsidy for every unit of shortage experienced by a hospital, then hospitals would be induced to report demand to the blood bank without inflation. We also investigate whether or not a consignment contract can be consistent with uninflated ordering by hospitals. Finally, we perform a detailed numerical study based on real demand and supply data to investigate the impact of over-ordering by hospitals on shortages and outdates in the supply chain, and the role of the appropriate contracts and allocation policies in obviating the concomitant social costs.
Pipelines and Their Portfolios: A More Holistic View of Human Capital Heterogeneity Via Firm-Wide Employee Sourcing
(Academy of Management, 2019-06-11) Brymer, Rhett A.; Chadwick, Clinton D.; Hill, Aaron D.; Molloy, Janice C.
Scholars use the term pipelines to encapsulate many ways that firms target talent sources. Yet pipeline scholarship is fragmented to date, so we have few answers for several salient questions: Why do pipelines exist? What are their attributes? And what are their implications for firms? In this paper, we explore these questions. Based on an extensive literature review, we first distill the commonalities and core attributes of pipelines and then develop a theory-driven typology to ensure a consistency in understanding. Next, we suggest that a common theoretical justification runs through the uses of pipelines: Pipelines address labor market imperfections confronted by firms when they staff positions, counterbalancing the seemingly detrimental reduction in candidates that pipelines engender. We use this insight to theoretically delineate why different types of pipelines exist. Finally, we discuss how firms develop unique combinations, or portfolios, of pipelines to ameliorate the range of imperfections that they face to manage talent sourcing across the enterprise. In total, our paper describes how firms strategically manage pipeline portfolios, why firms turn to them to accumulate talent, and how they create between-firm heterogeneity of human capital resources.
Depreciation Choice and Future Operating Performance
(Macrothink Institute, 2019-01-20) Caylor, Marcus L.; Whisenant, Scott
In this study we test the argument that information asymmetry and the problems of adverse selection provide incentives for managers to use accounting choices to signal relatively higher future prospects. Specifically, we contend that firms use accelerated depreciation to credibly signal higher future earnings and cash flows, consistent with signaling theory. Compared to straight-line depreciation, accelerated depreciation reduces earnings in the earlier years of asset lives and produces more variability in earnings. Despite these drawbacks, hundreds of firms voluntarily use accelerated depreciation for at least some of their depreciable assets. Our results indicate that the use of accelerated depreciation foreshadows higher future earnings and cash flows for horizons of one, two, and three years ahead.
Clipping Coupons: Redemption of Offers with Forward-Looking Consumers
(Economics Bulletin, 2019-07-07) Joseph, Kissan; Loginova, Oksana
Consumer redemption behavior pertaining to coupons, gift certificates, product sampling, rebates, and the like, has been the focus of much scholarly inquiry and the extant literature has documented two noteworthy empirical regularities - a bump in redemptions close to offer expiry and greater redemption with shorter redemption windows. In the extant work, these phenomena have been explained by invoking myopic consumers. Against this backdrop, we ask a simple question: can these phenomena survive if we assume rational, forward-looking consumers? Accordingly, we develop a model consisting exclusively of forward-looking consumers and incorporate two constructs highlighted in the literature - forgetting and stochastic redemption costs. We derive consumers' period-by-period redemption rule and subsequently illustrate the emergence of the two aforementioned empirical regularities.

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