The natural disaster response efforts are time-constrained, requiring quick and on-the-fly development and the adoption of technological innovations to meet the ever-changing contextual requirements. However, there are limited available insights on implementing and managing those 'invented-on-the-fly' innovations. This study draws upon sensemaking and technological frames to examine the adoption process of an on-the-fly developed mobile app in the context of the Gaja cyclone in India. Our findings inform that the adoption of technological innovation in disaster response is linked to its 'features' that actors draw upon in their sensemaking process and forming their technological frames. Initial sensemaking and technological framing may involve 'concrete features'. However, the later sensemaking of evolving contingencies may include discovering various 'abstract features' in action. Discoveries of abstract features in action trigger reframing, leading to a congruent technological frame and better exploitation of innovations. Given that natural disasters are occurring more frequently, findings from our study provide critical insights into managing technology innovations in these contexts. The revelation of the role of features in technological (re)framing also enriches the analytical power of the technological frame lens.

Three-dimensional (3D) printing technology has opened up possibilities for product design collaborations between device providers and customers. To enable an environment of cocreation, device providers are now renting 3D printers via the 3D-as-a-Service (3DaaS) model. Although prior research has examined pricing and quality issues in the traditional manufacturing setup, these studies have not analyzed such decisions in the 3D printing supply chain setting, where end users possess the ability to customize product designs. Therefore, several important questions remain unanswered from the perspective of the 3D printing device provider. For example, what is the appropriate pricing model for providing 3DaaS? How do factors such as the extent of design customization and the complexity influence the pricing strategy of the 3DaaS firm? Our analysis shows that if the customers' impact on the product quality is relatively high or low, the pay-per-build pricing model generates a higher profit than the fixed-fee pricing model. Interestingly, we also find that if customers frequently print highly intricate product designs, the firm might choose the pay-per-build pricing model, only if the likelihood of design failure for these complex structures is low. Otherwise, the firm might opt for the fixed-fee pricing model.

This paper provides a characterization of a recent rule called the unanimity with status quo. The rule designates a specific alternative as the status quo, selecting it in all profiles except where another alternative is unanimously ranked first by all agents, in which case the unanimous alternative is chosen. Our characterization relies on the solidarity axiom of welfare dominance under preference replacement, in combination with unanimity and tops -only. The significance of this characterization lies in the demonstration of the axioms' independence and the tightness of the characterization, meaning that weakening any axiom results in the emergence of additional rules. We also characterize the rule in the dynamic settings where new agents may enter the economy. Additionally, we examine the relationship between the two versions of solidarity axioms and the fairness axiom of anonymity.

It is often of primary interest to analyze and forecast the levels of a continuous phenomenon as a categorical variable. In this paper, we propose a new spatio-temporal model to deal with this problem in a binary setting, with an interesting application related to the COVID-19 pandemic, a phenomena that depends on both spatial proximity and temporal auto-correlation. Our model is defined through a hierarchical structure for the latent variable, which corresponds to the probit-link function. The mean of the latent variable in the proposed model is designed to capture the trend and the seasonal pattern as well as the lagged effects of relevant regressors. The covariance structure of the model is defined as an additive combination of a zero-mean spatio-temporally correlated process and a white noise process. The parameters associated with the space-time process enable us to analyze the effect of proximity of two points with respect to space or time and its influence on the overall process. For estimation and prediction, we adopt a complete Bayesian framework along with suitable prior specifications and utilize the concepts of Gibbs sampling. Using the county-level data from the state of New York, we show that the proposed methodology provides superior performance than benchmark techniques. We also use our model to devise a novel mechanism for predictive clustering which can be leveraged to develop localized policies.

We investigate the adoption of cashless payment systems by small retailers and their upstream suppliers (wholesalers, distributors, and manufacturers) serving the bottom-of-the-pyramid customers in India. We use the Technology-Organization-Environment framework to hypothesize how relative advantage, perceived barriers, firm size, firm scope, and competition influence the adoption of cashless payment systems. We collected data from 392 small retailers and 269 upstream suppliers from urban, semi-urban, and rural India. The results indicate that perceived barriers, firm scope, firm size, and competition influence the adoption of cashless payment systems. Upon further investigation, we found that all five factors influence retailers' adoption of cashless payment systems, but only firm scope and competition are significantly related to adoption for upstream suppliers. These results highlight that the factors influencing the adoption of cashless payment systems may also depend on supply chain position. We discuss the theoretical and practical implications of these results. We also validate the findings from our quantitative analysis by presenting excerpts from interviews with the merchants.

Although the scholarly debate on industrial relations (IR) transformation is inclined toward the conclusion that the IR transformation is bound to take place with changes in the surrounding business environment, we observe a few exceptions in each economy. The current study investigates one of such curious IR contexts, that is, the Indian coal sector. We rely on the 'logic of the action' framework and the IR transformation measures to assess the sector at an aggregate and micro level. The coal sector in India consists of a mix of both permanent and informal workforce. With respect to the permanent workforce, we analysed the collective bargaining agreements spanned over five decades (1975-2021). For the informal workforce, we analysed the recommendations of the HPC on wages and working conditions, the provisions of relevant legislation, internal circulars of coal companies and important judicial pronouncements. Our analyses revealed vast differences in wages and working conditions between the permanent and informal workforce. Despite a significant decline in the permanent workforce, they could negotiate better terms as the growing size of the informal workforce was yet to form a collective bargaining mechanism for better wages and working conditions. These results are indicative of a paradox which needs to be explored further. Our study advances the thesis of adaptive state capitalism in the coal sector through functional and numerical flexibility despite a politicised multi-union model in India.

Kumbh-Mela of Prayagraj, India, a festival of faith and belief, is one of the many significant gathering events worldwide. Pilgrims arrive from different places to take a holy bath at the confluence point of 3-rivers the Ganges, Yamuna, and Sarasvati. The police department is assigned a major role of handling and managing the dense traffic of pilgrims in this event to avoid unwanted situations. The primary surveillance points are the intersecting junctions and bathing zones. In addition, the authorities make crowd movement plans with different route diversion schemes and sets bathing time intervals to maintain crowd density at the Kumbh Mela site. Significantly, we must test these crowd management plans for a realistic assessment of population count, density maintenance, and time management. In this paper, we have created a model utilizing a micro-modeling agent-based approach that incorporates the virtual environment of the site. We have used AnyLogic, a ABMS tool, to incorporate social forces and stochastic behavior among the synthetic agents. The model simulates different crowd movement plans according to real behavioral scenarios. In the simulation, we have considered the whole bathing procedure as a halt time in the area. We have utilized our model to evaluate the time consumed by the pilgrims to reach Ghat. Also, to count the number of pilgrims that took a bath in 12 hours on different time intervals set for bathing. The significance of performing these evaluations is to assess the effect on density at the site during the whole arrival, bathing, and departure process.

The paper analyzes the performance of tandem network of polling queue with setups. For a system with two-products and two-stations, we propose a new approach based on a partially-collapsible state-space characterization to reduce state-space complexity. In this approach, the size of the state-space is varied depending on the information needed to determine buffer levels and waiting times. We evaluate system performance under different system setting and comment on the numerical accuracy of the approach as well as provide managerial insights. Numerical results show that approach yields reliable estimates of the performance measures. We also show how product and station asymmetry significantly affect the systems performance.

Most residential homes in developing countries such as India sell before construction is complete. Completed or move-in ready homes command a premium because of the compounded cost of capital and uncertainty costs incurred over time from holding under-construction homes. In this paper, we use listing data from India's six largest urban agglomerations (UAs) between 2010-2012 and show that sellers expect 2-15% move-in ready premia in five UAs. Moreover, in four UAs, individuals reselling homes expect five to eight percentage points higher move-in ready premia than developers selling new homes because of additional costs incurred by individuals from holding under-construction homes. We do not find any evidence of substantial speculative gains among individual resellers. At mean listed prices, the expected move-in ready premium is 383% of an average household's annual income in Mumbai, India's most expensive city. Our findings indicate that within the context of a developing country, lengthy construction times and expensive capital exacerbate already poor affordability conditions.

PurposeScholars have highlighted personal interactions between employees and their leaders in an increasingly distributed and hybrid work environment as an essential mechanism that engages employees toward organizational goals. Enhanced employee engagement significantly contributes to sustained organizational performance and growth. While Artificial Intelligence (AI) applications in the HR domain are increasing, research to understand the implication of AI-based virtual assistants on enabling trust and managing human resources is, at best, limited.Design/methodology/approachDrawing on the social response theory and the social exchange theory, and based on a multi-source, time-lagged field study spanning over ten months, we investigated the impact of AI-based virtual assistants on employee attitudes, namely perception of fairness and employee engagement.FindingsThe usage of AI-based virtual assistants is associated directly with employee engagement and indirectly through employees' perceptions of fairness. While employees' past performance moderates the relationship between perceived fairness and employee engagement, the interaction effect becomes non-significant with AI-based virtual assistants.Research limitations/implicationsOur study contributes to the emerging literature on AI-based virtual assistants in HRM and employee engagement. The virtual assistants' use to enhance employee engagement emerges as an opportunity for task substitution and augmentation. Our study demonstrates that AI-based virtual assistants can enhance employee engagement and help build perceptions of fairness among employees.Originality/valueWith the emerging importance of AI, there is an increasing interest in explaining human-computer interactions and their effect on employee engagement. Our study is among the early empirical studies examining the implications of AI-based virtual assistants on employee outcomes.

How are identity narratives maintained over one's lifetime when neither the enactment of one's work role nor the organised holding environments can be assumed? In his autobiography, Ahluwalia continues to narrate himself as a mountaineer, despite the end of his mountaineering career following a war-induced disability. Locating his account alongside the existent literature on identity work within holding environments, I clarify the processes through which different holding environments- the interpersonal and the relatively impersonal- can facilitate the maintenance of individuals' identity narratives and how the environments themselves may be shaped over time. (c) 2024 Published by Elsevier Ltd on behalf of Indian Institute of Management Bangalore. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/)

PurposeThe importance of mental wellbeing and the need for organizations to address it is increasing in the post-pandemic context. Although Artificial Intelligence (AI) is increasingly being adopted in HRM functions, its adoption and utility for enabling mental wellbeing is limited. Building on the Open System Theory (OST) and adopting the technology-in-practice lens, the authors examined the roles of human and technology agencies in enabling mental wellbeing.Design/methodology/approachThe study was conducted in two stages; in Stage 1, the authors adopted a case methodology approach to examine the feasibility of a technology company's offerings to assess mental wellbeing. In Stage 2, the authors followed the grounded theory approach and interviewed 22 key stakeholders and HR leaders of diverse organizations. The authors used Gioia's approach to analyze the data.FindingsThe study demonstrates the interdependence and inseparability of human activity, technological capability and structured context. Specifically, the authors observe that AI adoption is pushing the boundaries of how organizations could support employees' mental health and wellbeing. These technological advancements and adoption are likely to facilitate the evolution of agentic practices, routines and structures.Research limitations/implicationsThis study carries two important implications. While the advent of cutting-edge technologies appears to affect employees' mental wellbeing, the study findings indicate the assistive role of technology in supporting mental wellbeing and facilitating changes in organizational practices. Second, the ontology of technology-in-practice shows how human-machine agencies gain newer relevance from the interactions that unite them. Specifically, per OST, technology (from an external context) can potentially change how mental wellbeing practices in organizations are managed. The authors extend the existing literature by suggesting that both human agents and internal contexts effectively limit the potential of technology agents to change existing structures significantly.Originality/valueThe authors address the need for more research on the technology-management interface, and the boundaries of technology-enabled wellbeing at work. While AI-HRM scholarship has primarily relied on micro-level psychological theories to examine impact and outcomes, the authors borrow from the macro-level theories, such as the OST and the technology-in-practice to explain how AI is shifting the boundaries of human and machine agencies for enabling mental wellbeing.

Medical crowdfunding has gained significant popularity and importance, yet researchers argue that it might not offer equitable financial assistance to vulnerable groups. Studies in Western countries have highlighted disparities in medical crowdfunding based on racial, ethnic, and socioeconomic dimensions. Despite this, the equity implications of crowdfunding in India have not been thoroughly investigated. We present the initial empirical evidence indicating caste-based inequalities in medical crowdfunding within India. Leveraging a comprehensive dataset comprising 5527 medical crowdfunding campaigns from one of India's largest platforms, we evaluate the impact of the recipient's caste identity on campaign outcomes. Our methodology utilises administrative data to deduce caste from the recipient's surname. Campaigns by individuals from dominant caste groups tend to garner higher funds compared to those from marginalised castes, largely due to higher average donations. Furthermore, individuals from Scheduled Castes and Scheduled Tribes (marginalised groups in India) initiate disproportionately fewer campaigns than dominant castes. Our findings remain robust across various performance metrics and alternative model specifications, even after adjusting for multiple campaign features and recipient locations. In summary, our study highlights how crowdfunding on for-profit platforms may exacerbate existing caste-related health disparities in India by disproportionately favouring privileged groups.

Delivering healthcare services to cancer patients during COVID-19 lockdown posed several challenges; however, lack of reporting and concerned reviews made it imperative to understand the nuance of narratives among cancer patients across country. The COVID-19 pandemic has had a severe effect on the entirety among cancer patients in the continuum of care. In this regard, this article aims to investigate the challenges and hard times faced by cancer patients due to mismanagement and lack of health system planning during COVID-19 lockdown in India. A total of 46 newspaper articles with distinct cases of patients suffering from different types of cancer were collected between 24 March 2020 and July 2020 lockdowns in India. We analyse the online news reports and articles of cancer patients facing regular services and treatment challenges during the country's lockdown following an inductive approach. We conducted the content analysis that chose online news articles across states/union territories, leading to the creation of a conceptual diagram for our article. From all the articles, most articles reported challenges like poor governance of cancer patients (63%) and lack of timely treatment (37%) from the supply-side issues, whereas from the demand-side constraints, such as fear of transmission (10%), financial issues (10%) and accommodation problems (5%), were reported. The broad thematic categories that evolved from our content analysis are patient-centred related factors, healthcare management-related factors or supply-side factors and detrimental impacts of lockdown with the poor governance of cancer patients. Further, the findings revealed through different sets of narratives that involved a range of multiple factors such as service interruption, delays and altered modes of screening, diagnosis and treatment as well as follow-up and palliative care during the critical time of COVID-19 lockdowns in India. The interruption of service delivery mechanisms due to poor health management, deficits of health workforce, infrastructural lacunae and fear of COVID-19 infection placed unprecedented challenges to cancer patients across the country in seeking healthcare services. Therefore, the government must be regularly vigilant and give priority under these emergency circumstances. However, the newly introduced National Digital Health Mission (NDHM) by the Government of India might be a catalyser that provides the necessary support for the integration of digital health infrastructure in the country even after such a pandemic havoc in the future.

To fulfil its commitments towards sustainable development, India is transitioning from fossil fuels to renewables in the energy sector, trying to shift consumption and cropping practices in the agriculture sector, and promoting alternative fuel vehicles in the transport sector. In this study, we analyse the current state of energy, agriculture, and transport policies using the triple bottom line approach and provide a strategic framework that offers a mechanism and a longterm roadmap for a sustainable future by integrating the synergies between these three key sectors. Decentralised production and consumption of resources holds the key to economic, environmental, and social sustainability. (c) 2024 Published by Elsevier Ltd on behalf of Indian Institute of Management Bangalore. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/)

This paper examines the impact of substituting regular classroom programmes with online classes on students' academic performance. We compared the change in the delivery mechanism of preparatory courses for two consecutive Master of Business Administration (MBA) batches in one of the top business schools in India. While the first batch studied in a face-to-face classroom setting, the second batch was taught two subjects in an online format, while the third subject continued to be offered in the face-to-face classroom setting. Using a difference-in-difference estimation, we found that the students' performance declined in both the subjects offered online, with the average performance declining by 4.95% and 8.4% in Economics and Accounting, respectively. However, no decline in performance was noted in the third subject of Quantitative Methods, offered in a face-to-face classroom setting. Further, we found a larger drop in scores for students with the lowest academic ability. Our results indicate that a shift to online courses should be accompanied by well-designed pedagogical and curriculum changes to ensure substantive learning, especially for academically weaker students. (c) 2024 Published by Elsevier Ltd on behalf of Indian Institute of Management Bangalore. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/)

Marginal pricing has long been the instrument of choice to address water conservation challenges. More recently, non-price behavioral interventions have emerged as an alternative. However, there is limited data on the relative efficacies of price and non-price interventions. We report results from long-term field experiments studying unit-level water conservation responses to both price and non-price interventions in the same group of households (n = 64 186 household-days). Conservation habits, attitude-action gaps, principal-agent incongruities, and billing cycles help account for the heterogeneity in response between households, and across time. A non-price behavior modification intervention before the introduction of marginal pricing resulted in a large and significant effect on treated households (33%). The subsequent introduction of marginal volumetric pricing also reduced water use (8%, for previously untreated households). However, this average price effect masks how a large share (21%) of households increased water use, or how a mere 12% of the households accounted for all the aggregate reduction in water use. We investigated such heterogeneous responses as a systematic conservation maximization design question beyond statistical variance in individual responses. We used daily water consumption measurements across three years alongside a household survey to delineate structural and agentic barriers to conservation behavior. Our analysis reveals how combining price and non-price behavioral interventions could hold the key to achieving conservation effects that are both large and persistent.

This article aims to understand the influence of strategic posture of a firm on its decision-making orientation related to competitors and partners, and evaluates if such decision-making orientation of firms mediate the relationship between a firm's strategic posture and digitalization. The article uses partial least squares based structural equation modeling technique on primary data from 100 enterprises belonging to manufacturing and electronics sector operating from India. Based on the analysis, the article empirically establishes the linkage between a firm's strategic posture and its decision-making preferences in the contexts related to engaging with competitors and partners, taking digitalization as context. Next, it extends available knowledge on firms' decision-making literature by establishing that a firm's decision-making orientation related to its competitors and partners has direct influence on its degree of digitalization. Finally, it empirically deduces that in the context of digitalization of firms, market-based analysis is the dominant decision-making paradigm as against obtaining stakeholder partnerships or precommitments.