Mediation analysis with contemporaneously observed multiple mediators is a significant area of causal inference. Recent approaches for multiple mediators are often based on parametric models and thus may suffer from model misspecification. Also, much of the existing literature either only allow estimation of the joint mediation effect or estimate the joint mediation effect just as the sum of individual mediator effects, ignoring the interaction among the mediators. In this article, we propose a novel Bayesian nonparametric method that overcomes the two aforementioned drawbacks. We model the joint distribution of the observed data (outcome, mediators, treatment, and confounders) flexibly using an enriched Dirichlet process mixture with three levels. We use standardization (g-computation) to compute all possible mediation effects, including pairwise and all other possible interaction among the mediators. We thoroughly explore our method via simulations and apply our method to a mental health data from Wisconsin Longitudinal Study, where we estimate how the effect of births from unintended pregnancies on later life mental depression (CES-D) among the mothers is mediated through lack of self-acceptance and autonomy, employment instability, lack of social participation, and increased family stress. Our method identified significant individual mediators, along with some significant pairwise effects.

Outliers present in a data set can severely impact the statistical analysis and lead to erroneous conclusions. Hence, outlier identification is an important task before analysis of data is undertaken. Outliers being different from the rest of the observations in a data set may contain valuable information which can be obtained by carefully examining the identified outliers. While several methods of outlier identification exists for univariate and multivariate data, not that many methods exist for functional data. In sequential identification of outliers from a set of functional data, the corresponding estimation of covariance operator is affected by the outliers that are still present in the data. This leads to degradation in performance of these methods when the proportion of outliers in the data set increases. In this paper we propose a new outlier detection algorithm that uses an adaptive and data driven approach of dimension selection. The proposed method is seen to have better efficiency in an extensive simulation exercise in comparison to the existing method. Three illustrations with real life environmental data sets are also reported.

Hyperparameter tuning in the area of machine learning is often achieved using naive techniques, such as random search and grid search. However, most of these methods seldom lead to an optimal set of hyperparameters and often get very expensive. The hyperparameter optimization problem is inherently a bilevel optimization task, and there exist studies that have attempted bilevel solution methodologies to solve this problem. These techniques often assume a unique set of weights that minimizes the loss on the training set. Such an assumption is violated by deep learning architectures. We propose a bilevel solution method for solving the hyperparameter optimization problem that does not suffer from the drawbacks of the earlier studies. The proposed method is general and can be easily applied to any class of machine learning algorithms that involve continuous hyperparameters. The idea is based on the approximation of the lower level optimal value function mapping that helps in reducing the bilevel problem to a single-level constrained optimization task. The single-level constrained optimization problem is then solved using the augmented Lagrangian method. We perform extensive computational study on three datasets that confirm the efficiency of the proposed method. A comparative study against grid search, random search, Tree-structured Parzen Estimator and Quasi Monte Carlo Sampler shows that the proposed algorithm is multiple times faster and leads to models that generalize better on the testing set.

We present a bottom-up marketing approach as a pathway to addressing the grand challenge of poverty and inequality for the marketing discipline. We derive this approach from the research stream on radically different contexts of subsistence marketplaces. Research on subsistence marketplaces has typically explored micro-level phenomena but also traversed upward and explained aggregate phenomena at higher levels. We present a conceptual framework to encapsulate general and granular elements of the bottom-up marketing approach. Study 1 demonstrates general elements of the framework through a retrospective examination of the global diffusion of a marketplace literacy program. Study 2 demonstrates the more granular elements of the framework through a qualitative analysis of five case studies of social enterprise start-ups. Though presenting a complementary counter-perspective to conventional thinking, we embed the process of interweaving the bottom-up with the macro level to present an actionable approach. We conclude with insights for marketing research and practice.

The purpose of this paper is to suggest an accounting framework for India for implementation of its nationally determined contributions (NDCs) and design the appropriate modality for reporting its capacity building needs and priorities in a manner that is in consonance with the provisions of the Paris Rule book from the perspective of a developing country. The suggested accounting methodology considers India's national greenhouse gas (GHG) inventory and climate mitigation policies. The Key Category Analysis concept of the Intergovernmental Panel on Climate Change for accounting GHG inventory estimation at the national level is used to identify and rank the key inventory categories for India. Accounting of various national level mitigation policies is undertaken by assessing their impact on the key categories, subsequently recognizing 'Key Policies' in accordance with the provisions of the Paris rulebook. 'Key Policies' are found to have a definite role in driving the progress of implementation of NDCs. The study recommends a modality that developing countries can use to report their needs for capacity building support for full implementation of their 'key policies' while accounting their future NDCs, using the flexibilities provided under the Paris Rule book.

Objective: To analyse the spatial variation and risk factors of the dual burden of childhood stunting and wasting in Myanmar.Design: Analysis was carried out on nationally representative data obtained from the Myanmar Demographic and Health Survey conducted during 2015-2016. Childhood stunting and wasting are used as proxies of chronic and acute childhood undernutrition. A child with standardised height-for-age Z score (HAZ) below -2 is categorised as stunted while that with a weight-for-height Z score (WHZ) below -2 as wasted.Setting: A nationally representative sample of households from the fifteen states and regions of Myanmar.Participants: Children under the age of five ( $n$ 4162).Results: Overall marginal prevalence of childhood stunting and wasting was 28 center dot 9 % (95 % CI 27 center dot 5, 30 center dot 2) and 7 center dot 3 % (95 % CI 6 center dot 5, 8 center dot 0) while their concurrent prevalence was 1 center dot 6 % (95 % CI 1 center dot 2, 2 center dot 0). The study revealed mild positive association between stunting and wasting across Myanmar. Both stunting and wasting had significant spatial variation across the country with eastern regions having higher burden of stunting while southern regions having higher prevalence of wasting. Child age and maternal WHZ score had significant non-linear association with both stunting and wasting while child gender, ethnicity and household wealth quintile had significant association with stunting.Conclusion: The study provides data-driven evidence about the association between stunting and wasting and their spatial variation across Myanmar. The resulting insights can aid in the formulation and implementation of targeted, region-specific interventions towards improving the state of childhood undernutrition in Myanmar.

Financial prudence compels businesses to improve their Environmental, Social, and Governance (ESG) performance when the marginal benefits, pecuniary or non -pecuniary, exceed the marginal costs. For many firms, renting green offices is a feasible ESG activity which may increase their willingness to pay higher rents. Analyzing over 17,000 green rental contracts in India between 2010 and 2022, we find that rents in greenlabeled assets and those with health certification command significant premiums between 4 and 21%. However, green rents increased much faster compared to their non -green counterparts, and the propensity to rent green varies significantly across industry segments. We further examine how the market for green offices evolved after a mandatory ESG Disclosure Requirement was enacted in India in 2021. We find that suppliers (landlords) benefited from the regulation by disproportionately increasing rental rates. Existing tenants and foreign firms ended up paying higher rental prices while most other firms, including the assumed target groups of the new policy, redirected their green commitment away from green buildings. Although the policy may yield more positive results in the longer run, a reduced propensity to rent green offices is the opposite of what the ESG Disclosure Requirement tried to achieve.

Biofuels are expected to play a pivotal role in developing economies' transition towards net-zero emissions. However, their promotion can cause multifaceted sustainability concerns. National biofuel policies often align with the optimistic discourse surrounding biofuels but may lack comprehensive measures to simultaneously address all sustainability risks. This study conducts a systematic review to evaluate the sustainability performance of biofuels and examines their implications for advancing the Sustainable Development Goals (SDGs). A total of 12 sustainability indicators were identified as economic, social, and environmental priorities. Biofuel linkages with 8 SDGs, 21 targets, and 22 indicators were mapped. The analysis revealed a wider coverage of sustainability impacts associated with biodiesel compared to ethanol feedstocks for India. Notably, the sustainability effects of biofuels exhibited considerable variability across different spatial scales. Irrespective of the biofuel types, negative sustainability outcomes were found to be associated with socio-economic indicators related to food security, livelihood, and income, and environmental indicators like land use. Positive sustainability effects were observed for environmental indicators like water and soil quality, biodiversity, and ecosystem services. The study identifies policy gaps in addressing localized adverse effects of biofuels, emphasizing the need to align biofuel strategies with SDGs for more comprehensive and sustainable biofuel development in developing countries.

Hub-and-spoke networks play a critical role in reducing cost and enhancing service levels in various infrastructural sectors since hubs act as the consolidation and transshipment points of the flows. The failure of hubs in such a network can cause severe disruptions. While disruptions can be natural or man-made, a disruption by a rational individual or entity can be significantly detrimental to the network and is often studied as an interdiction problem. It is important to take interdiction effects at the design stage; therefore, we study the three-level capacitated hub-and-spoke network design problem from the perspective of a defender who considers the risk of interdiction by a rational attacker. Within the three levels, the upper level represents the network design level, and the lower two levels represent the bi-level hub interdiction problem. The introduction of capacity constraints within an interdiction model dramatically increases the complexity of the problem, as there can be some unfulfilled flows post-interdiction. Moreover, a flow may or may not be fulfilled through the least-cost route using the nearest hubs. This work makes two major contributions: the first contribution is on the efficient handling of the bi-level hub interdiction problem using the Dual-based approach and the Penalty-based approach, and the second contribution is on solving the overall three-level problem using a super valid inequality. These two contributions allow us to solve large-scale versions of the capacitated multiple allocation p-median hub location problem under the risk of interdiction, which is otherwise mathematically intractable and can be handled only using complete enumeration techniques.

PurposeGiven the growing acceptance of cashback offers (e.g. $10 PayPal cashback within 24 hours of the transaction) among retailers, this paper aims to understand how consumers evaluate them vis-& agrave;-vis traditional price-discounts and their subsequent impact on retailers' promotional strategies.Design/methodology/approachSix experimental studies examine if and when consumers can discern differences in the time-of-reward-accrual (i.e. the waiting time associated with receiving promotional savings) of cashbacks and price-discounts. Building on evaluability theory, we propose that the time-of-reward-accrual of promotion is hard-to-evaluate. Put simply, consumers find it hard to assess the duration of waiting time associated with receiving promotions. Consequently, consumers' perceptions of cashbacks vis-& agrave;-vis price-discounts can be influenced by whether they evaluate both promotions simultaneously [joint-evaluation (JE) mode] or independently [single-evaluation (SE) mode].FindingsThe initial four studies show that the time-of-reward-accrual of promotions is hard-to-evaluate. Cashbacks appear just as appealing as price-discounts when consumers evaluate them independently (SE-mode) but lose their appeal when consumers view them alongside price-discounts (JE-mode). The next two studies further enhance the generalizability of our findings by replicating the observed effects for different purchase types (hedonic vs utilitarian) and varying promotional benefit levels (high vs low).Originality/valueBy shedding light on evaluations of time-of-reward-accrual of promotion, this paper adds a new dimension to research on promotions. The paper also extends the application of evaluability theory beyond domains such as hiring, fairness judgments and product bundle assessments. The paper presents evaluation mode as a boundary condition to explain contradictory predictions from prior research for consumers' preferences for delayed vs immediate promotions.

India has committed to reaching net-zero greenhouse gas emissions by 2070. While targets for CO2 capture, utilization and storage (CCUS) technologies are not explicitly set, the Government of India's agencies and public-sector enterprises have mentioned CCUS approaches conditionally subject to availability of feasible technology and financing. This paper aims to examine the gap between the current status of CCUS in India and the levels of deployment as projected by modeling exercises. It takes a Talanoa dialogue approach to answer the following questions on CCUS perspective in India: where are we right now, where do we need to be, and how do we get there. The current status of CO2 capture in India is at the pilot/demonstration stage, with the chemicals and steel sectors, being the most advanced. Emergence of the methanol economy as a key avenue for CO2 utilization may be seen at a large-scale. Geologic CO2 storage is at an advanced planning stage via enhanced oil recovery, and will likely be targeted over this decade. From the current and planned stage, India would likely need 400-800 Mt-CO2/year by 2050 to meet its share of the 1.5 degrees C carbon budget. We suggest several priority research directions for technology development across the CCUS value chain.

The present research delves into the concept of celebrity co-creation from the consumer behavior perspective. It explores the impact of the degree of a celebrity's involvement with a brand (celebrity as an endorser vs. celebrity as a co-creator) on consumers' advertisement and brand-based evaluations (Study 1) and purchase behavior (Study 2). The research subsequently incorporates the mediating effects of consumers' perceived risk (Study 3) and the moderating effect of celebrity expertise (Study 4) in the relationships. Three of the four studies were controlled experiments among nonstudent samples (combined n = 486), while one was a field study. Major findings indicate that a celebrity co-creator is more effective than a celebrity endorser, but both cases of celebrity presence are more effective than the control (Studies 1 and 2). This effect is observed to be mediated by the consumers' perceived risk (Study 3) and moderated by the celebrity's expertise (Study 4). The present research provides a new direction to value co-creation research from the communications perspective and adds to the literature on celebrity endorsements.

The present study builds on the domain of circular economy and its subdomain circular value creation to explore the entrepreneurial process of a small business in India. It aims to find how circular entrepreneurship as a process may unfold and how it may lead to value creation at different levels. The case study method is used to address the research objectives and a case study of a small entrepreneur based in India is selected for the same purpose. The analysis of the case and within case patterns (three subcases) illustrates circular entrepreneurship as a process with motivation, action and value creation as three main stages. The motivation of the entrepreneur leads to several actions related to business processes that are aimed at circular value creation. Subsequently, this leads to value creation at multiple levels such as the economy, business and society. Hence, the findings support the circular economy concept and its role in the creation of value at the small business level. The findings support the theoretical tenets of circular value creation and circular entrepreneurship using an interpretive approach.

Borrowing from paradoxical leadership literature and using the case of a social enterprise formed from a traditional nonprofit, the present study identifies a set of multilevel skills that helped the leader address the two social-business tensions, namely, continuance as a nonprofit and the forming of a social enterprise and the sustenance of a social enterprise and preventing the drift towards a for-profit orientation during the formation of social enterprise and in its sustenance thereafter. The individual-level paradoxical leadership skill of balancing idealism and pragmatism, the organizational-level paradoxical leadership skill of navigating organizing contradictions, and the societal-level skill of gauging societal developments and their organizational implications helped address the two different manifestations of social-business tensions during the formation and sustenance of a social enterprise. Implications for paradoxical leadership, social-business tensions, and social enterprise literature are discussed.

The global building sector, responsible for over 30% of CO2 emissions, necessitates urgent decarbonization efforts. This paper examines residential building decarbonization policies in three major economies-the European Union (EU), China, and India. It provides an overview of diverse policies through policy landscape analysis and delves into the design specifics with a detailed policy intensity analysis of building energy codes, information disclosure, and financial incentives in each region. Our findings reveal a diverse mix of policies targeting residential building decarbonization in all three regions. While the EU and China have long-established diverse policy instruments, India's building energy efficiency policies are relatively recent and limited. Detailed analyses of building energy codes, information disclosure, and financial incentives expose variations in ambition, scope, and implementation, even with shared policy instruments. Significant advancements in building energy codes, particularly in stringency and compliance checks, are evident in the EU and China. Conversely, India faces a notable obstacle with limited adoption of residential building energy codes, impacting its journey towards net-zero. The EU leads in building energy labelling policies, while China and India encounter various challenges hindering widespread implementation. Financial incentives across the three regions predominantly take the form of subsidies, potentially straining public budgets. The study concludes with reflections on the pressing need for future research extending beyond the operational phase of buildings.

This introduction, and the special issue on 'Contesting social responsibilities of business: Experiences in context' it frames, addresses the neglected question of the experience of contestation in the terrain of the social responsibilities of business. It re-conceptualises the social responsibilities of business by advancing research grounded in a relational perspective, exploring and highlighting different forms of contestation of these social responsibilities, and centring the role of context by focusing especially on contestation in overlooked geographical settings and sites of marginalisation. Contextualising contestation in this way centres silenced and/or ignored voices, generates meaningful theory, and offers an innovative critical lens on business-society relations.

We examine behavior in a two -stage group contest where intra-group contests are followed by an inter -group contest. Rewards accrue to the winning group, with winners of the intra-group contest within that group receiving a greater reward. The model generates a discouragement effect, where losers from the first stage exert less effort in the second stage than winners. In contrast to the related literature, we show that a prior win may be disadvantageous, generating lower profits for first stage winners as compared to losers. We consider exogenous asymmetry between groups arising from a biased group contest success function. Although the asymmetry occurs in the second stage, its effect plays out in the first stage, with higher intra-group conflict in the advantaged group. Experimental results support the qualitative predictions of the model. However, losers from the first stage bear a higher burden of the group contribution than the theoretical prediction.

Purpose - This study aims to conduct an extensive bibliometric analysis of research across COVID-19 and human resource management (HRM). It captures an exhaustive conceptual understanding of theoretical foundations, research trends, developments and research directions in the HRM domain. Design/methodology/approach - A set of 505 HRM and COVID-19-specific articles collected from the Scopus database were systematically analyzed using a two-tier method. In the first tier of analysis, the evolution and current state of research are identified using citation analysis. In the second tier, network analysis and content analysis of research clusters and thematic mapping are done to identify the prominent research themes and research gaps and suggest future research directions. Findings - The study highlights the emergence of six research clusters: SHRM and competitive advantage, employer branding and employee engagement, crisis management and resilience, challenges, career shock and job demand resources and burnout. The thematic mapping categorizes the themes into four categories: motor, basic, emerging or declining, and niche research themes published on COVID-19 and HRM. To understand the socio-cultural dynamics and cross-cultural issues during human resource management, the findings emphasized the need for the increased contribution of researchers and practitioners, especially from the developing and emerging nation's context. Increased co-authorship among influential authors and institutions will also help formulate strategies and policies to effectively deal with similar pandemics. Originality/value - Unlike the previous literature review, the present findings provide meaningful insights for formulating people management techniques, policies, and practices in response to COVID-19 or similar pandemics.

This paper employs COVID-19 as a quasi-natural experiment to conduct an analysis of the heterogeneous effects of the pandemic on households' financial vulnerability across districts in India and investigates the role of migration and gender of the household head in moderating financial vulnerability. Using Indian panel household surveys and a difference-in-differences approach with coarsened exact matching, we provide causal evidence of a larger increase in the financial vulnerability index (FVI) of households in Indian districts with a higher incidence of COVID-19 cases per capita. A similar effect is observed when considering satellite-based night-time lights, a proxy for economic activity. Furthermore, during the pandemic, households with an out-migrant family member experienced relatively lower FVI, with a more pronounced effect for female-headed households, likely due to the financial help given by migrants. However, households that had an out-migrant in the pre-pandemic period, but not during the pandemic, were more financially vulnerable. This study provides a novel contribution to the literature through a better understanding of the varied effects of the pandemic-induced health and economic shocks on households' financial vulnerability based on pandemic intensity, migration status, and gender.

Background:Institutional births ensure deliveries happen under the supervision of skilled healthcare personnel in an enabling environment. For countries like India, with high neonatal and maternal mortalities, achieving 100% coverage of institutional births is a top policy priority. In this respect, public health institutions have a key role, given that they remain the preferred choice by most of the population, owing to the existing barriers to healthcare access. While research in this domain has focused on private health institutions, there are limited studies, especially in the Indian context, that look at the enablers of institutional births in public health facilities. In this study, we look to identify the significant predictors of institutional birth in public health facilities in India.Method:We rely on the National Family Health Survey (NFHS-5) factsheet data for analysis. Our dependent variable (DV) in this study is the % of institutional births in public health facilities. We first use Welch's t-test to determine if there is any significant difference between urban and rural areas in terms of the DV. We then use multiple linear regression and partial F-test to identify the best-fit model that predicts the variation in the DV. We generate two models in this study and use Akaike's Information Criterion (AIC) and adjusted R2 values to identify the best-fit model.Results:We find no significant difference between urban and rural areas (P = 0.02, alpha =0.05) regarding the mean % of institutional births in public health facilities. The best-fit model is an interaction model with a moderate effect size (Adjusted R2 = 0.35) and an AIC of 179.93, lower than the competitive model (AIC = 183.56). We find household health insurance (beta = -0.29) and homebirth conducted under the supervision of skilled healthcare personnel (beta = -0.56) to be significant predictors of institutional births in public facilities in India. Additionally, we observe low body mass index (BMI) and obesity to have a synergistic impact on the DV. Our findings show that the interaction between low BMI and obesity has a strong negative influence (beta = -0.61) on institutional births in public health facilities in India.Conclusion:Providing households with health insurance coverage may not improve the utilisation of public health facilities for deliveries in India, where other barriers to public healthcare access exist. Therefore, it is important to look at interventions that minimise the existing barriers to access. While the ultimate objective from a policy perspective should be achieving 100% coverage of institutional births in the long run, a short-term strategy makes sense in the Indian context, especially to manage the complications arising during births outside an institutional setting.