Admissions to academic programs often involve filling a number of seats by making offers to a ranked list of qualified candidates over a finite number of rounds. Two sources of uncertainty need consideration when making admission offers: first, a random fraction of offers is accepted by applicants; and second, a random fraction of applicants who initially indicate acceptance subsequently withdraw. We develop a binomial decision-tree model to determine the number of admission offers to be made while considering (a) the expected costs of exceeding or falling short of target enrollment, and (b) the fact that the more competitive students are also less likely to enroll. Insights from the model are validated using a multi-year empirical dataset of admission offers, acceptances and post-acceptance withdrawals for an MBA program. We find that having multiple rounds to make offers helps admissions offices achieve enrollment targets with greater precision. Additional rounds are particularly valuable when the uncertainty of yield rate is high. In a counterintuitive result, we identify conditions under which the recommended number of offers increases with the uncertainty in yield. We also show that it might be possible to improve the quality of an admitted class by sending out more offers sooner. © 2021 Wiley Periodicals LLC.

We consider partially observed binary matched-pair data. We assume that the incomplete subjects are missing at random. Within this missing framework, we propose an EM-algorithm based approach to construct an interval estimator of the proportion difference incorporating all the subjects. In conjunction with our proposed method, we also present two improvements to the interval estimator through some correction factors. The performances of the three competing methods are then evaluated through extensive simulation. Recommendation for the method is given based on the ability to preserve type-I error for various sample sizes. Finally, the methods are illustrated in two real-world data sets. An R-function is developed to implement the three proposed methods. © The Author(s) 2021.

Operations research (OR) has been at the core of decision making since World War II, and today, business interactions on different platforms have changed business dynamics, introducing a high degree of uncertainty. To have a sustainable vision of their business, firms need to have a suitable decision-making process at each stage, including minute details. Our study reviews and investigates the existing research in the field of decision support systems (DSSs) and how artificial intelligence (AI) capabilities have been integrated into OR. The findings of our review show how AI has contributed to decision making in the operations research field. This review presents synergies, differences, and overlaps in AI, DSSs, and OR. Furthermore, a clarification of the literature based on the approaches adopted to develop the DSS is presented along with the underlying theories. The classification has been primarily divided into two categories, i.e. theory building and application-based approaches, along with taxonomies based on the AI, DSS, and OR areas. In this review, past studies were calibrated according to prognostic capability, exploitation of large data sets, number of factors considered, development of learning capability, and validation in the decision-making framework. This paper presents gaps and future research opportunities concerning prediction and learning, decision making and optimization in view of intelligent decision making in today’s era of uncertainty. The theoretical and managerial implications are set forth in the discussion section justifying the research questions. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.

A considerable body of research on inequality in India has focused on consumption inequality. This article compares inequality in consumption expenditure and income, using two waves of the India Human Development Survey. We find that while income inequality increased marginally, expenditure inequality remained stable. The article also undertakes the decomposition of income inequality by sources and finds that wage and agricultural incomes contribute most to inequality in rural areas whereas wage and business incomes are the major contributors in urban areas. Wages and government transfers arse found to be inequality-decreasing sources of income, and agricultural income is found to be inequality-increasing. While government transfers benefit low-income households, there is potential for increasing their efficacy and for attaining a more egalitarian distribution of income by better targeting. Further, we examine how expenditure and income are associated with the ownership of household assets. Our findings suggest that low consumption is a better indicator of material well-being than low income. © 2022 SAGE Publications.

How does sentiment in a pitch affect an entrepreneur's fundraising outcomes? Although research suggests that negativity in entrepreneurial “pitches” to investors adversely impacts resource acquisition, there is a lack of empirical research showing whether, and to what extent, this is true. We study over 30,000 entrepreneurial loan requests from one of the largest loan marketplaces to understand how the sentiment in text-only pitches to investors affects fundraising. In contrast to prior literature, we find that negatively-worded pitches are funded faster than positively-worded ones. We also find that negatively-worded pitches result in lower interest rates to entrepreneurs. Finally, we find that negatively-worded loans default less, suggesting that the benefits of negativity are not one-sided but two-sided: negativity helps both resource seekers and resource providers. Collectively, the results from our study reveal how negativity can be beneficial in impression management and offer fresh insights for the psychological foundations of entrepreneurship. © 2021

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.

India's mass vaccination efforts have been slow due to high levels of vaccine hesitancy. This study uses data from an online discrete choice experiment with 1371 respondents to rigorously examine the factors shaping vaccine preference in the country. We find that vaccine efficacy, presence of side effects, protection duration, distance to vaccination centre and vaccination rates within social network play a critical role in determining vaccine demand. We apply a non-parametric model to uncover heterogeneity in the effects of these factors. We derive two novel insights from this analysis. First, even though, on average, domestically developed vaccines are preferred, around 30% of the sample favours foreign-developed vaccines. Second, vaccine preference of around 15% of the sample is highly sensitive to the presence of side effects and vaccination uptake among their peer group. These results provide insights for the ongoing policy debate around vaccine adoption in India. © 2022 Elsevier Ltd

The world is witnessing a growth in economic nationalism, especially in countries like the United States and United Kingdom, where this would scarcely have been predicted a few years ago. These developments threaten the internationalization of services and gains made through various global trading arrangements. Moreover, there are concerns that the COVID-19 pandemic will further undermine supranational forms of governance and nurture the trend towards protectionism and economic nationalism. We undertake a systemic literature review on economic nationalism and services internationalization to identify research themes. The findings of the study have implications for policymakers, and we provide directions for future research. © 2022 Elsevier Inc.

This study posits that executive attention can significantly influence the impacts of customer-facing electronic business (e-Business) systems on firm performance. Using the exploration–exploitation perspective (EEP) as an overarching theoretical framework, and the theoretical lens of attention-based view (ABV), we develop an integrated model to provide insights into the impacts of customer-facing e-Business systems on firm performance. We categorize the capabilities of customer-facing e-Business systems into e-Transaction and e-CRM (customer relationship management) capabilities as exploitation and exploration capabilities, respectively. Further, following ABV, we conceptualize focused and expansive attentions as two different types of executive attention that also incorporate exploitation and exploration orientations. We hypothesize e-Transaction and e-CRM capabilities to have nuanced interactive effects with focused and expansive attention on firm performance measured using return on sales and Tobin's Q. We use a panel dataset with 484 firm-year observations from 180 firms to test our hypotheses. We estimate our models using a two-step generalized method of moments (GMM) approach to address issues relating to endogeneity, heteroskedasticity, and serial correlation, and to produce efficient estimates. The results provide broad support for the hypotheses and are robust to the alternative measurement of dependent variables, alternative econometric model specification, and potential endogeneity from omitted covariates. The integrated model developed and empirically validated in this study serves to provide a deeper understanding of the impacts of customer-facing e-Business systems on firm performance. The study also highlights the need for dual attention processes on the part of senior executives to fully realize the benefits offered by these systems. © 2022 Production and Operations Management Society.

Women entrepreneurship literature has unveiled the gendered assumptions of entrepreneurship. More recently, critical woman entrepreneurship literature is increasingly focusing on the neoliberal discourses in women entrepreneurship. What remains relatively under-explored is how women entrepreneurs experience the tensions amidst neoliberal and gendered experiences especially in the context of the Global South. Based on the narratives of middle to upper-middle-class women entrepreneurs in India, I find that being middle to upper-middle-class, women entrepreneurs shared a sense of attaining a neoliberal agency through entrepreneurship, so much so that they ignored, denied, or naturalized the gendered constraints in entrepreneurship. However, soon their accounts reflected an underlying tension as they admitted facing gendered constraints while previously denying them. I contribute to the literature of women entrepreneurship by theorizing the conflicting narratives of women entrepreneurs using the concept of liminality. In doing so, I extend the concept of liminality as an in-between position of neoliberal and gendered experiences. © 2022 John Wiley & Sons Ltd.

Identity narratives enhance the understanding of women’s leadership, but there exist very few in-depth analyses of negative identity tensions that influence agency. In this study, we examine the negative identity tensions of well-to-do women from small towns in India, who hold two leadership positions: organizational and social movement. We borrow from the discourse on well-to-do women’s participation in social movements in India to draw on the notions of identity, perceptions of feminism, and patriarchal challenge. Our data are derived from 49 in-depth interviews with women leaders. Findings from qualitative analysis and creation of a composite narrative show that negative identity tensions arising from two leadership positions are gendered in nature. Furthermore, agency is (i) contingent on one’s reflection on challenges, (ii) rooted in an underlying principle, and (iii) practiced through the mechanisms of “managing femininity,” a concept that is widely discussed in the Western paradigms of postfeminism and neoliberalism. This paper contributes to the feminist dialog on the global South in the context of gender, class, and geographical location intersection by revealing certain non-Western ways of managing femininity. However, in the process, the hegemony of Indian men remains intact. © 2021 John Wiley & Sons Ltd.

Twin support vector machine (TSVM) is an effective machine learning tool for classification problems. However, TSVM classifier works on empirical risk principle only and also while training, each sample contributes equally, even if it is a noise or an outlier. It does not incorporate the uncertainties associated with data into modeling and hence its generalization ability declines. To address these issues, intuitionistic fuzzy regularized least square twin support vector machine having intuitionistic fuzzy network has been proposed in this paper. The non-parallel classifiers are obtained by solving two systems of linear equations only rather than the solution of two quadratic programming problems as in TSVM, which leads to speed up the training process. Moreover, the method follows both structural risk and empirical risk minimization principles. In order to de-escalate the effect of pollutant patterns, their contribution of the patterns into learning the decision function has been made according to their importance in the classification. The significance of the training patterns is measured in terms of intuitionistic fuzzy numbers based on their geometrical locations and surroundings. The method is further extended to find non-parallel decision planes in the feature space using nonlinear kernel function, which also gives rise to the solution of two systems of linear equations. To show the efficacy of the proposed method, computer simulations on fourteen standard and six big UCI datasets using linear and Gaussian kernels are performed and their results have been compared with well-established methods in the literature. The experimental results are represented in terms of accuracy, computational time, F-measure, sensitivity and specificity rates. The outcomes demonstrate that the proposed method outperforms the existing methods and is also feasible for big datasets. The comparison and statistical inferences using two non-parametric: Friedman and Nemenyi tests, conclude that the proposed approach is fast and yields better generalization. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Extant approaches to information provisioning to farmers to improve agricultural productivity, and thereby alleviate poverty have relied on top-down external expert-driven knowledge. Such external knowledge involves decontextualised content and the use of technical language, and is resource-intensive. An alternative view emphasises the need to explore indigenous knowledge exists in rural communities, which, in contrast, requires the use of local resources, is easily understandable, and has greater potential for adoption. This paper explores how information and communication technologies, specifically videos, can be leveraged to curate such indigenous knowledge and convert it to knowledge commons. Adopting a case study approach that involved multiple sources of data collection over a nine-year period, we unearthed a dynamic process model that we labelled as knowledge commoning. It is a process through which latent-action-oriented knowledge from high-yield farmers embedded within its social context is made available as commons. The creation of knowledge commons is an iterative process between knowledge curation and knowledge dissemination, and is guided by the demand and uptake potential within local farming communities. Further, we describe how socio-cultural barriers in knowledge commoning can be overcome through scaffolding, involving the concealment of social transformation objectives within another goal desired by the community. Technological challenges can be overcome through the process of technoficing, which encompasses pursuing social objectives using technology that is appropriate for the purpose. Building on our process model, we offer contributions to theory, practice, and policy. © 2022 Elsevier Ltd

Using a sample of 39,297 father-son pairs from Indian Human Development Surveys (IHDS), we examine whether migration experienced during child schooling affects the relationship between parent and child education. We relax the co-residency restriction for father-son pairs to obviate coresident sample selection bias in our mobility estimates. The panel structure of data enables us to identify children who were enrolled in school at the time when their families migrated. We find that migration experienced during schooling increases downward mobility. In particular, those children who were young at the time of migration tend to have poor educational outcomes. We show that widely cited aggregate measures of mobility provide an incomplete representation of intergenerational persistence in India, as most of the persistence originates from the tails of the educational distribution. The sons of the least educated fathers have poor prospects of upward mobility and face a glass ceiling in higher education. We use heteroscedasticity-based identification and Rosenbaum?s sensitivity analysis to account for unobserved heterogeneity. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Count data are observed by practitioners across various fields. Often, a substantially large proportion of one or some values causes extra variation and may lead to a particular case of mixed structured data. In these cases, a standard count model may lead to poor inference of the parameters involved because of its inability to account for extra variation. Furthermore, we hypothesize a possible nonlinear relationship of a continuous covariate with the logarithm of the mean count and with the probability of belonging to an inflated category. We propose a semiparametric multiple inflation Poisson (MIP) model that considers the two nonlinear link functions. We develop a sieve maximum likelihood estimator (sMLE) for the regression parameters of interest. We establish the asymptotic behavior of the sMLE. Simulations are conducted to evaluate the performance of the proposed sieve MIP (sMIP). Then, we illustrate the methodology on data from a smoking cessation study. Finally, some remarks and opportunities for future research conclude the article. © 2022 John Wiley & Sons Ltd.

Global competition means that firms are under pressure to systematically develop the efficiency of their manufacturing processes. However, little has been said in the international business literature about how firms, especially those subject to severe barriers, can search for knowledge within and across national boundaries to help in the development of process innovation. We build on key aspects of the innovation and search strategy literature to develop our conceptual model and hypotheses, which we test in the context of a less-developed, isolated, and closed economy, using data from 171 automotive component suppliers in Iran. We find that foreign knowledge search is positively related to process innovation, even in an economy that operates under severe economic sanctions. This contributes to the international business field by providing evidence that, while economic sanctions are increasingly used in modern geopolitics by the world's most powerful countries, these actions may fail to achieve their goals with respect to individual businesses. © 2021 Elsevier Ltd

Purpose: Social enterprises (SEs) have experienced unprecedented uncertainty due to COVID-19, and it has challenged the fundamental assumptions underlying the SEs. Little is known about the strategic response of SEs when their fundamental characteristics are being challenged. The purpose of this paper is to explore – how do SEs respond to a crisis caused by the pandemic? Design/methodology/approach: This paper adopts a case study approach and reports the response strategy of impulse social enterprises (ISE) from India. Data were collected through interviews, Webinars and organizational reports. To analyze the data, the authors examined the fundamental assumption on SE that was challenged by the pandemic. Findings: The response strategy of ISE is driven by social and substantive rationality focusing on the relationship with the community and doing what is good for them. The role of communication was vital in gathering support and resources to continue with their function. ISE adapted a mindset of mission agility and created an alternative market for its product. Originality/value: This study highlights the response strategy of SE in an emerging economy like India, which experienced one of the stringent lockdowns. It is probably one of the few studies that examined the responses of SE under a crisis that challenged their fundamental attributes by adopting the framework of Bacq and Lumpkin (2021). © 2022, Emerald Publishing Limited.

We examine the impact of an extreme monetary shock, India's demonetization of 2016, on domestic agricultural trade. Using data from around 3000 regulated markets for 35 major crops, we find that trade value fell by 16.3–16.8% in the short run, settling at 11.8–12.1% after eight months, driven primarily by a decline in prices. Triple difference estimates suggest sharpest impacts for kharif crops, perishables and crops with minimal government intervention. Markets far away from banks fared worse. Our results suggest that the implosion of value of agricultural trade domestically persisted two growing seasons beyond the one that coincided with the shock, whereas existing findings suggest that the negative impact on the economy as a whole dissipates in that time. © 2022 Agricultural & Applied Economics Association.

Recently, many developing countries have implemented several bioeconomy plans to transform their rural economies and improve food security at local, national, and regional levels. Yet, there are limited success stories and examples of a competitive bioeconomy in Africa while levels of poor and food food-insecure populations remain high. Drawing on the novel concepts of biomass value-web, national innovation system and Porter's Diamond model, this paper analyses the emerging biomass opportunities and institutional challenges limiting sustainable bioeconomy growth in Africa. Using the Nigerian maize sector as a case study, qualitative data obtained from 54 stakeholders through 14 interviews, six focus group discussions, and six Net-maps served as a foundation for our network and content analyses. Results revealed numerous opportunities to further upgrade the current maize biomass value-web. However, the challenges of low farm productivity, inadequate infrastructure, low biomass demand and utilization by industrial firms at the mid-stream, deficient innovation and support systems and inconsistent government plans pivoted on several institutional challenges such as weak and uncoordinated institutional arrangements and an unfavorable institutional environment to limit competitive bioeconomy growth in the sector. The study concludes that important institutions in various innovation subsystems would need to actively perform harmonizing activities within a favorable institutional environment before competitive bioeconomy growth can be attained in Africa. © 2021 Institution of Chemical Engineers

[No abstract available]