Search results

This chapter reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy and review the methodological approaches available for personalization. We discuss scalability, generalizability, and counterfactual validity issues and briefly touch upon advanced methods for online/interactive/dynamic settings. We then summarize the three evaluation approaches for static policies – the Direct method, the Inverse Propensity Score (IPS) estimator, and the Doubly Robust (DR) method. Next, we present a summary of the evaluation approaches for special cases such as continuous actions and dynamic settings. We then summarize the findings on the returns to personalization across various domains, including content recommendation, advertising, and promotions. Next, we discuss the work on the intersection between personalization and welfare. We focus on four of these welfare notions that have been studied in the literature: (1) search costs, (2) privacy, (3) fairness, and (4) polarization. We conclude with a discussion of the remaining challenges and some directions for future research.

Every year, tonnes of flower waste from religious places is dumped into India’s holiest river Ganges, polluting it to virtual death. Pesticides and insecticides used in growing these flowers mix with the water, affecting millions of lives through water-borne diseases. Most others may just lament these facts, Ankit Agarwal and Karan Rastogi, childhood friends from Kanpur, used them as inspiration to innovate. Two years of relentless experimentation led to a brilliant idea; that of recycling the flower waste. They founded HelpUsGreen® in 2014 to convert the waste into bio-fertilisers and lifestyle products. Widely appreciated and heavily awarded now, success has not come easy for this well-educated duo. HelpUsGreen® processes hundreds of kilos of flower waste, creating employment for hundreds of underprivileged women. An entirely bootstrapped project with no carbon foot print, the venture hopes to revive the Ganges through Flowercycling®. Currently at 8.5 tonnes per day and at the tipping point of scaling, HelpUsGreen® hopes to process over 50 tonnes of flower waste per day by 2020. Apart from the environmental impact, HelpUsGreen® has achieved huge societal impact, employing over a thousand women who did not previously have formal employment. What also makes the social entrepreneurs stand apart is their entrepreneurial market savviness. They have positioned their products not at the sympathy market but at the high-end premium market. Their products sell under the name ‘Phool’. HelpUsGreen® has set its eyes firmly on spreading operations across 2,000 kilometres along the Ganges and creating over 25,000 jobs for women.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

This chapter presents the historical process of the Urban Agriculture (UA) at Rosario, in search of a socio-productive model with a high component of social inclusivity. It considers the first glimpses in 1987 through the conformation of the first Urban Group Farm until the present day where UA has become a public policy. This process has created its own dynamics under the different organisational structures of the municipality, by successfully integrating the production, the circulation and the consumerism of healthy products through fairs and community-based organisations; also incorporating the different suburbs of the city. Agroecology is presented as the conceptual and methodological framework. The systematisation of this experience aims to make visible the course pursued by the UA in Rosario offering a description which allows to understand its processes and to obtain more specific details of the bases and principles of Agroecology. The main results that are highlighted from this process are (1) Consolidation of a municipal public policy of urban agriculture, which guarantees democratisation and access to means of production for agroecological food cultivation, its commercialisation and distribution in the different districts of the city; (2) Social transformation of neighbours who found in the horticultural identity a personal and collective life project, consolidated as reference in the city, the country and the region; (3) Presence of a critical citizenship that is identified as a protagonist, through different roles on sustainability of the Urban Agriculture Programme.

The Sundarbans is a unique ecosystem, the most expansive mangrove system in the world covering the Ganga–Brahmaputra–Meghna delta system and spread over 10,000 sq.km across India and Bangladesh. The Indian Sundarbans have been witnessed to large-scale conversion of mangroves to settled agriculture and steady growth of population over the decades. With time, while population growth has taken place, there has been no significant change in the development scenario, as the agriculture and fishing dependent communities have remained trapped in the vicious cycle of poverty. Its deltaic location and its position in the path of cyclones, tidal surges and seasonal floods have made the people and landscape of Sundarbans more vulnerable than ever before. Cyclones affecting this region have grown both in frequency and intensity over the years and have caused devastation to the land, homes, lives and livelihoods. The problem of salinity has also affected the region relentlessly. Given this scenario, scenario of progressing vulnerabilities, livelihood losses have led to a gradual increase in out-migration of the adult male population. This disaster-led outmigration from Sundarban region as a whole has affected the social fabric of displaced communities to a great extent. This chapter makes an attempt to discuss results of sample surveys across six villages in three CD Blocks of Sagar, Gosaba and Kultali to trace the nature and dimension of the migration patterns of the region.