Recent unveiling of electric semi-trucks by a number of electric vehicle manufacturers indicates that part of the existing long-distance transportation fleets may soon be electrified. Operators of electric fleets will have to select travel routes considering charging station availability and cost of charging in addition to usual factors such as congestion and travel time. This requires combined modeling of transportation and electric power networks. We present such a model that considers interactions between the two networks to develop optimal routing strategies. The problem is formulated as a multi-objective bilevel conic optimization model. The upper level obtains the routing decision by minimizing a function of charging cost and travel time. The routing decision is used in the lower level that solves the AC optimal power flow model, using second order cone constraints, to determine nodal electricity prices. The model is demonstrated using a numerical problem with 24-Node transport network supported by a modified 5-Bus PJM network. The results show that our model yields optimal routes and charging strategies to meet the objectives of fleet operators. Results also indicate that the optimal routing and charging strategies of the electrified transportation fleet can support power networks to reduce nodal prices via demand response. © 2022 Elsevier Ltd

[No abstract available]

The utility of a service or product can be considered as an aggregation of utilities of multiple attributes, that the consumers consider while choosing a product. The two methods used to generate a linear utility function are the logarithmic goal programming model (LGPM) and the conjoint analysis method (CAM). In these two methodologies, the procedures used to collect data and generate the utility function differ significantly. This is possibly the first study to compare the two methods for determining the utility function of a product (here vehicle insurance policy). For this study we will be collecting the data from the same set of respondents (customers) for the same set of five different brands of the product (vehicle insurance policy) available in the market. The similarities and differences among LGPM and CAM approaches are examined to provide useful insights in terms of consistency in consumer behaviour while prioritizing their choices for a product. The study addresses if the priority order of consumer choices for a product remains the same or changes if the methodology changes. Moreover, we apply a multinomial logit choice model to derive a choice probability of the brands available in the market using both approaches. © 2021, Operational Research Society of India.

Using a framework of colonization in science, technology, engineering, and mathematics (STEM), this U.S.-based study examined how seven Native American PhD students/ postdoctoral scholars experienced impostor phenomenon. Participants were identified/ contacted at a national conference on minorities in STEM through purposeful sampling. Surveys computed impostor phenomenon scores on a validated scale, while interviews documented how identity and culture contributed to impostor phenomenon in academia. Using a phenomenological approach, interviews were analyzed inductively using a constant comparative method. Surveys scores indicated high to intense impostor phenom-enon. Interviews with the same participants further identified the following aspects of impostor phenomenon in relation to their minoritized identity: cultural differences and lack of understanding of Indigenous culture, lack of critical mass and fear of standing out, academic environment, family background and upbringing, and looks and diversity status. Developing a diverse and culturally competent STEM workforce requires a deeper understanding of what deters Native American individuals from pursuing a STEM career. They have the lowest college enrollment and retention rates compared with any race in the United States and could be vulnerable to racial bias and discrimination. Understanding impostor phenomenon through culturally relevant experiences would be crucial to broaden participation in STEM careers. © 2022, American Society for Cell Biology. All rights reserved.

Promoting active aging has emerged as a key objective of urban planning and policymaking globally. Our study aims to provide new insights from a time-use perspective. In this paper, we use Hong Kong as a case study to investigate how people aged 60 and older allocate their time in various out-of-home activities. We analyse how personal and household characteristics affect the duration of out-of-home activities among older adults using two decennial time-use surveys. We focus on the influence of employment status and age because of policy relevance, particularly since the Hong Kong Government is considering extending the retirement age from 60 to 65. Comparison of time-use and activity participation between 2002 and 2013 suggests that employment status is positively associated with the duration of out-of-home activities and travel in both cross-sections; it also explains change over time. Findings also underscore the role of gender, age, education, type of housing, tenure of accommodation, household size, and income in determining older people’s activity–travel patterns. Our study shows that government policies to increase the share of employed people in the 60-years-and-older cohort and changes in the sociodemographic makeup of older people owing to various economic or societal forces could alter older people’s time-use and out-of-home activity patterns. Our study suggests that Hong Kong and other cities in the Asian region and beyond must aim at creating inclusive, age-friendly communities with adequate access to various activity opportunities in order to enhance quality of life in an aging society. © 2020 Hong Kong Geographical Association.

Despite income growth, fertility decline, and educational expansion, female labour force participation in rural India dropped precipitously over the last decade. Nation-wide individual-level data allow us to explore if random reservation of village leadership for females affected women’s access to job opportunities, their demand for participation in the labour force, and income as well as intra-household bargaining in the short-and medium term. Gender reservation of local leadership affected female but not male participation in public works and regular labour markets, their income, and their influence on key household decisions with a lag, suggesting that such reservation affected social norms and stereotypes. © 2022 International Bank for Reconstruction and Development/The World Bank.

[No abstract available]

This paper analyses how cultural differences across China, India, and Singapore influence team exploration, exploitation, and innovativeness. Previous cross-cultural and innovation literature mainly focused on Western cultures or East-West comparisons. In this research, we investigate innovation related cultural specifics that differentiate team behavior in China, India, and Singapore (e.g., guanxi, jugaad, and kiasu), and investigate differences in team exploration, exploitation, and innovativeness across those three cultures. We test our model in a survey study with matched answers of team members and their supervisors in innovation teams across China, India, and Singapore. In line with our theorizing, our findings suggest comparably high levels of team exploration in India, and comparably high levels of team exploitation in China. Additionally, we find team exploration, more than team exploitation, relates to team innovativeness in China, India, and Singapore. © 2021 Elsevier Inc.

Bringing down energy system emissions to zero is a key step to restrict the global temperature rise to “well below 2 °C”. Recent studies have extensively discussed the integration of bioenergy with carbon capture and storage (BECCS) in existing energy systems to achieve net-zero emissions. India recently initiated a carbon dioxide-based enhanced oil recovery (CO2-EOR) project in the matured oil wells of western India. Using this project, we propose a bioenergy-CO2-EOR system to study the techno-economic feasibility and potential of BECCS towards net-zero emissions from energy systems. We use mixed integer linear programming for bioenergy and CO2 source-sink matching. The proposed system breaks even, without any carbon price, at an oil price of around 56 USD per barrel (USD/bbl) if using CO2 from bioethanol fermentation and at around 90 USD/bbl for bioelectricity plants. A carbon price between USD 20 to 40 per tonne of CO2 makes the system feasible even below the oil price of 45 USD/bbl for the ethanol route. The system has net negative CO2 emissions after accounting for the lifecycle emissions of produced oil, assuming a sequestration rate of 0.5 tonne of CO2 per barrel of recovered oil. Further, the bioenergy-CO2-EOR system reduces crude oil imports, supports ethanol blending, provides additional income opportunities at local level, and reduces air pollution from crop residue burning in the fields. © 2022 Elsevier Ltd

Artificial neural networks(ANN) have been found to be an effective nonparametric method in many predictive applications. However, they have not been discussed much in the literature for angular data. In this article, we present two separate ANN models for angular-angular and linear-angular regression. We compare the performance of these ANN models with other regression models used in these contexts available in the literature. We find that the presented ANN models perform competitively and sometimes better as a predictive tool. We also propose two new methods for generating prediction intervals for ANN models. We find these prediction intervals provide good coverage probabilities on the Test dataset. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Testing at a mass scale has been widely accepted as an effective way to contain the spread of the SARS-CoV-2 Virus. In the initial stages, the shortage of test kits severely restricted mass-scale testing. Pooled testing was offered as a partial solution to this problem. However, it is a relatively lesser-known fact that pooled testing can also result in significant gains, both in terms of cost savings as well as measurement accuracy, in prevalence estimation surveys. We review here the statistical theory of pooled testing for screening as well as for prevalence estimation. We study the impact of the diagnostic errors, and misspecification of the sensitivity and the specificity on the performances of the pooled as well as individual testing procedures. Our investigation clarifies some of the issues hotly debated in the context of COVID-19 and shows the potential gains for the Indian Council for Medical Research (ICMR) in using a pooled sampling for their upcoming COVID-19 prevalence surveys. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

The case aims to serve as a basis for discussing private equity investment strategies in emerging markets such as India, covering the due diligence process, private equity (PE) exit routes, and associated risks. It also focuses on the conflict-of-interest issues when statutory auditors also assume advisory roles. Copyright 2021 With Intelligence Ltd.

Private equity real estate (PERE) markets suffer from information inefficiency. In this study, we examine if Google Trends could help in partially mitigating the inefficiency issues. Using monthly PERE investment activities in India between 2005 and 2017, and controlling for macroeconomic variables, we show that relevant search trends are significantly associated with future investment activities. Compared to domestic investors, foreign investors are subject to information asymmetry and their investment activity is particularly sensitive to political search trends in the target country. We detect a mutually causal association between investment activity and political searches. Although significant, the effect of political Google Trends on investment activity is short-lived and fades within two months. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

The system aims to propose an efficient pay and park method developed based on use of domains like deep learning, server and app management. The system so developed detects entry of vehicle in parking facility. The database is created and modified with each incoming car and registrations in the system. The user can register his all the vehicles in the system database through an android based PayPark app. The app incorporates Google Pay services to provide the user with a safe and secure payment facility. At the entry and exit of a parking facility, the vehicle is detected along with the time for which it was parked. The corresponding entries are made in the database and saved. Through the PayPark app the charges are deducted from a pre- registered app user. The charges deduction is depending on the time for which the vehicle uses parking facility. © 2022, Springer Nature Switzerland AG.

The banking crisis that played out post 2008–09 is considered a key factor responsible for economic slowdown in India. Several alternative explanations for the banking crisis are presented in the paper. We find that the crisis was primarily exposure-driven and was due to lack of an appropriate credit appraisal process. While the exposure was bank ownership-driven, the rate or incidence of non-performing assets accumulation was ownership-neutral. We also examine the government’s strategy of bank consolidation using the stochastic frontier approach—an econometric tool that is popularly used for a neoclassical production, cost function, etc, along with an efficiency component. Our empirical analysis shows that the merger decisions were not necessarily on efficiency grounds. Post-merger benefits are minimal, and the deteriorating health of the public sector banks is likely to continue. © 2022 Economic and Political Weekly. All rights reserved.

This paper performs a cross-country panel data analysis to determine whether gold holdings of central banks contribute to sovereign creditworthiness. Higher central bank gold holdings are found to reduce sovereign credit default swap (CDS) spreads, a measure of country risk. This effect is stronger during global and country-specific crisis episodes. We account for endogeneity of central bank gold reserves using an instrumental variables approach. Potential economic mechanisms for the baseline findings include lower likelihood of a rating downgrade and reduction in economic uncertainty. The findings suggest central bank gold can mitigate a nation's credit risk amidst an uncertain global environment. © 2021 Elsevier Inc.

Branching process and their variants are a widely used mathematical model in the study of population dynamics, in which all individuals in a given generation produces some random number of individuals for the next generation. In the recent past, branching process has also found applications in areas like operations research, marketing, finance, genetics etc. A problem that has caught attention in the context of coalescence in branching process is as follows: Assume that the branching process is started by one individual in 0th generation and the population size of the tree obtained by branching process in generation n is greater than 1. Next, pick two individuals from n th generation at random and trace their lines of descent back till they meet. Call that random generation by Xn. The objective is to study the properties of Xn. While this problem has been studied by many authors for simple and multitype discrete time branching processes, not much attention has been given for the realistic extension when one individual is allowed to survive for more than one generation and can also give birth more than once. We study this problem for some deterministic and random cases. Explicit expressions about some mathematical properties of Xn have been derived for broad classes of deterministic trees. For random trees, we provide explicit expression for some special cases. We also derive properties of Xn as n goes to infinity. Additionally, simulation analysis has also been performed and some interesting insights are discussed. © 2022 Taylor & Francis Group, LLC.

Is there a liability of foreignness in online crowdsourcing contests for creative work? Digitalization mitigates physical orthodox transaction-based frictions and is therefore expected to reduce the liability of foreignness. However, for creative work sourced digitally across borders, due to the decoupling of the locus of creation from the locus of selection and due to the cognitive nature of creative tasks, we suggest that frictions continue to arise from foreign solvers’ cognitive home biases in creative task generation and from solution-seeker firm managers’ cognitive home biases in creative task selection. These biases manifest as LOF, reducing the likelihood of foreign solvers’ work being selected as winners in online crowdsourcing contests. Furthermore, we argue that as foreign solvers gain both breadth and depth of international experience in prior online contests, and observe host peers in a live contest, the effect of the liability of foreignness is reduced due to the conceptual expansion of solvers’ creative consideration sets. Similarly, the seeker firm’s cognitive openness in selection arising from its being in a technology industry or being a physically international firm reduces the liability’s negative effect on solvers’ success. Our conditional logit estimation with multiway fixed-effects using 558,504 contest-solver observations from 13,993 solution-seeker firms in 102 countries and 11,497 solvers in 124 countries on an online platform broadly supports our hypotheses, suggesting that there are both demand-side and supply-side cognitive sources of LOF even in unblind online crowdsourcing contests. © 2022, Academy of International Business.

The literature on marketing, operations management, and strategy has investigated the impacts of a firm’s supplier network structure and complexity on its financial, environmental, and innovation performance. However, our understanding of how the global supply chain complexities of a multinational enterprise (MNE) affect its international business performance (IBP) is limited. We draw on both the business network theory and information search literature to propose that the various complexity dimensions (e.g., horizontal, vertical, and spatial) of an MNE’s global supply chain have different influences on its subsequent IBP. We argue – and empirically validate – that collaboration, a network orchestration mechanism, enables an MNE to leverage the benefits of complex relationships. Using a dataset of 185 firms taken from multiple industries over 6 years, we show how such complexities have differential effects. In multiple post hoc analyses, we demonstrate how an MNE’s marketing intensity, the interconnectedness among its supply members, and its top management team (TMT)’s international experience all have unique impacts. This study contributes to the existing literature on global supply chain complexity by demonstrating how it can influence MNEs’ IBP. Moreover, we contribute to the strategic IBP literature by outlining effective global supply chain improvement strategies. © 2022, Academy of International Business.

The Better Cotton Imitative (BCI), the world's largest multi-stakeholder initiative (MSI) for sustainable cotton production, is a prime example of a hybrid “cooperation-compliance” model used by some MSIs to engage farmers and on-farm workers in the global South. Using a mixed methods approach, we investigate the impacts of this hybrid model on economic, environmental, and labor conditions of farmers and on-farm workers on irrigated cotton farms in Pakistan and India. In one of few cross-national comparisons of BCI impacts, we find evidence that farmers participating in BCI's “cooperation-compliance” model report (a) higher gross incomes and (b) lower input costs than comparison farmers. However, (c) BCI had no positive impacts upon labor conditions on cotton farms, as compared to conventional peers. Finally, (d) BCI's impacts are mediated by institutional and geographic differences across the study sites. We conclude that effects of MSIs are hard to generalize but can most meaningfully be understood within particular institutional designs, value chains, specific time periods, and institutional contexts. © 2021 The Authors