Multidimensional Targeting Research Articles

Alternative targeting methods for social assistance programs: Evidence from Tunisia

AbstractSocial assistance programmes are crucial in alleviating poverty, reducing inequality, and addressing social exclusion. The efficacy of these programmes hinges on the precision and efficiency of their targeting methods. Governments, especially in developing countries, can enhance the impact of social assistance programmes and ensure equitable resource distribution by accurately identifying the right individuals or households. This paper proposes two approaches to targeting beneficiaries of social benefits in Tunisia, including cash transfers and healthcare programmes. The first approach, a Mixed Means Test, extends the Proxy Means Test model by integrating individual/household assessments with explicit geographical targeting methods. The second is a multidimensional targeting strategy that explicitly considers the various deprivations faced by the households. Utilising data from the 2015 National Survey on Household Budget, Consumption, and Standard of Living, our results indicate that the targeting performance of the Mixed Means Test surpasses existing programmes both nationally and regionally, notably minimising inclusion and exclusion errors in the poorest regions of Tunisia. However, the multidimensional targeting approach identifies a higher number of potential beneficiaries compared to the current selection process in Tunisia. Including these households in social programmes may be hindered by limited monetary resources and the country's financial constraints. To address this, the multidimensional targeting approach enables the categorisation of potential beneficiaries into three mutually exclusive and collectively exhaustive groups based on their degree of deprivation.

Multidimensional Targeting and Consumer Response

Advancements in targeting technology have allowed firms to engage in more precise targeting based on several aspects of consumers’ preferences. Exposed to more targeted ads, consumers are becoming increasingly aware of being targeted and respond accordingly. This paper provides a theoretical analysis of multidimensional targeting under which consumers can draw inferences about multiple components of their utility from the advertised product. We show that the firm can be worse off under multidimensional targeting than under single-dimensional targeting, in which the firm targets consumers based only on a single component of their utility. This is because, with multidimensional targeting, targeted consumers may face greater uncertainty about on which specific dimension(s) they can expect to enjoy the advertised product. Therefore, they may be less willing to exert a costly effort of clicking the ad and making a purchase decision. When this result holds, the firm may want to adopt a single-dimensional targeting strategy. However, we show that the firm cannot credibly commit to such a strategy once given access to multiple dimensions of customer data. Interestingly, a higher unit cost of advertising can mitigate the firm’s commitment problem for using customer data and thus increase the firm’s profit. Moreover, the firm can sometimes lower the price to recover some of, but not entirely offset, the drawbacks of multidimensional targeting. We discuss the implications of our results regarding the current practice of targeted advertising and data privacy protection policies. This paper was accepted by Dmitri Kuksov, marketing. Funding: This work was supported by the Korea Advanced Institute of Science and Technology [Grant G04210017]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4604 .

A Model of Multi-dimensional Targeting

The advancements in targeting technology have allowed firms to engage in more precise targeting based on several distinct aspects of customer preferences. Exposed to more targeted ads, consumers are becoming increasingly aware of being targeted and respond accordingly. In this paper, we provide a theoretical analysis of multi-dimensional targeting in which consumers are aware that ads are targeted and, therefore, draw inferences about their expected utility from the advertised product based on whether or not they are targeted. By comparing single-dimensional and multi-dimensional targeting, we show that the firm can be worse off under multi-dimensional targeting. When this result holds, the firm may want to adopt a single-dimensional targeting strategy. However, we show that the firm cannot credibly commit to such a strategy once given access to multiple dimensions of customer data. We further find that the firm's commitment problem for how to utilize customer data for targeting can be mitigated by a higher advertising cost, and thus the firm's profit can counter-intuitively increase in the advertising cost. We also show that the firm can use pricing as a commitment device and thus recover some of, but not entirely offset, the pitfalls of multi-dimensional targeting. We provide implications of our results to the recently observed practice of more transparency in online targeted advertising.

Redirecting T-Cells Against AML in a Multidimensional Targeting Space Using T-Cell Engaging Antibody Circuits (TEAC)

Background T cell redirection strategies, such as CAR-T and bispecific antibodies (bsAb), are rapidly changing the way in which we approach and treat cancer. While CAR-T and bsAb have shown impressive clinical efficacy in a limited number of cancers, both strategies are ultimately limited by on-target toxicity that currently restricts application to B-cell lineage tumors as the number of genuinely tumor-specific surface antigens is extremely limited. BsAb also suffer from off-target toxicity relating their ability to directly active T-cells severely restricting the therapeutic window. We sought to solve these inherent problems with the current generation bsAb by re-designing the molecule to alter the mechanism of T-cell activation. By splitting the T-cell engaging VHVL antibody paratope between two separate molecules we created two molecules that formed an active T-cell engaging unit through protein domain complementation following proteolytic activation. Each antibody could target independent surface antigens vastly increasing targeting permutations. Thus, these two antibodies functioned as an "antibody circuit" permitting Boolean type logic to precisely control T-cell activation in multi-dimensional targeting space. We selected AML as model cancer to develop T-cell Engaging Antibody Circuits (TEACs) due to the highly characterized surface antigen landscape and the clear challenges and limitations of single-antigen targeting approaches. Results We first screened 10 AML cell lines for candidate surface antigens based upon prior studies of surface antigen display (Perna F et al, 2016) and identified CD33, CD123, CD49d, CD70, CD71, CD38, CLEC12A, Flt3, CD24, CD244, TIM3 and CCR1 as promising targets. We developed a secondary TEACs screening assay where the two TEAC molecules contained either a FITC or biotin binding domain and paired these to commercial FITC or biotin conjugated antibodies targeting the antigens above. We screened 72 TEAC pairs against the 10 cell lines which identified optimal antigen target combinations which included CD33xCD123, CD33xCLEC12A, CD33xCD49d and CD33xCD24. Using a FRET-based fluorescent peptide assay to identify peptide linkers susceptible to proteases we found MMP2 to be highly expressed in AML samples and thus designed all our TEACs with this cleavage site. We next generated IgG4 format TEACs targeting CD33, CD123, CLEC12A and CD24 that included the MMP2 cleavage activation site and tested these as TEAC pairs in vitro. This screen identified the CD123xCD33 as the most active TEAC pair which was active in 9/10 cells lines. To assess potential safety concerns, we tested TEACs and CD123 and CD33 BiTEs individually and as pairs on PBMCs and on plate-immobilized molecules. These data demonstrated that BiTEs were extremely active against healthy monocytes and also activate T-cells non-specifically once plate-immobilized. In contrast CD123xCD33 IgG TEACs pairs did not activate T-cells when plate-immobilized and did not target healthy monocytes.Finally, we examined the activity of both CD33 BiTEs and CD123xCD33 TEACs on primary patient AML samples. We conducted FRET based assays which confirmed high activity of MMP2 cleavage site on all primary AML samples. When we examined T-cell activation, CD123xCD33 TEACs were active in all CD123+ CD33+ AML samples evaluated with an EC50 of 30ug/ml. Conclusion These data suggest T-cell engaging antibody circuits is a new approach that could be safely applied toward AML. TEAC agents do not directly activate T-cells and CD123xCD33 TEAC pairs do not activate PBMC or monocytes. However, CD123xCD33 TEACs show strong activity against AML cell lines and primary CD123+CD33+ AML cells. Disclosures Millar: Revitope Oncology: Equity Ownership. Minshull:Atum Biotechnology: Employment, Equity Ownership. Narayan:Takeda: Other: Employment (spouse); Genentech: Other: Equity ownership (spouse); Merck: Other: Equity ownership (spouse). Graubert:Biogen: Other: Spouse Employee; Calico Life Sciences: Other: Research Support; Janssen Pharmaceuticals: Other: Research Support. Cobbold:Gritstone Oncology: Equity Ownership; Revitope Oncology: Consultancy; Revitope Oncology: Equity Ownership.

An Asset-Based Indicator of Wellbeing for a Unified Means Testing Tool: Money Metric or Counting Approach?

As part of the Europe 2020 strategy, European member states have committed to modernize and harmonize their welfare systems and to improve the quality of the means testing tools adopted to correctly identify the beneficiaries of welfare policies. This study contributes to the literature on means testing by implementing and then comparing two alternative multidimensional targeting approaches: an asset-based money metric and a counting measurement of poverty. The two approaches aggregate poverty dimensions and implement inter-household comparisons of wellbeing differently. The study shows that in terms of targeting efficiency the approach based on the money metric is superior. The comparison is relevant both from an empirical and a policy point of view because a unified means testing tool would pave the road towards harmonized welfare policies across European countries.

Longitudinal changes in activity participation in the first year post-stroke and association with depressive symptoms

Research question: 1. Does activity participation improve over time in the first year after stroke? 2. What is the association of depressive symptoms on retained activity participation 12-months post-stroke adjusting for neurological stroke severity and age? 3. Is an improvement in activity participation associated with a decrease in depressive symptoms between 3- and 12-months post-stroke? Design: Longitudinal observational study of activity participation and depressive symptoms in ischemic stroke survivors. Participants: A total of 100 stroke survivors with mild neurological stroke severity. Methods: A total of 100 stroke survivors were recruited from five metropolitan hospitals and assessed at 3- and 12-months post-stroke using measures of activity participation (Activity Card Sort-Australia (ACS-Aus)) and depressive symptoms (Montgomery–Asberg Depression Rating Scale Structured Interview Guide (MADRS-SIGMA)). Results: There was a significant association between time (pre-stroke to 3-months post-stroke) and current activity participation (−5.2 activities 95% CI −6.8 to −3.5, p < 0.01) and time (pre-stroke to 12-months) and current activity participation (−2.1 activities 95% CI −3.7 to −0.5, p = 0.01). At 12-months post-stroke, a one-point increase in depressive symptoms was associated with a median decrease of 0.3% (95% CI −1.4% to −0.1%, p = 0.02) of retained overall activity participation, assuming similar neurological stroke severity and age. A decrease in depressive symptoms between 3- and 12-months post-stroke was associated with an improvement of 0.31 (95% CI −0.5 to −0.1, p = 0.01) in current activity participation. Conclusions: Activity participation improves during the first year of recovery post-stroke in stroke survivors with mild neurological stroke severity and is associated with depressive symptoms over time and at 12-months post-stroke.Implications for rehabilitationImprovements in participation occur in the first 3-months post-stroke and continue to a lesser degree in the first year after stroke.Depressive symptoms are associated with lower participation at 12-months.A multidimensional approach targeting depressive symptoms and increasing participation in the early months post-stroke and throughout the first-year after stroke is recommended to increase overall recovery following stroke.A focus on increasing leisure activity participation is recommended to improve depressive symptoms. Trial registration: Australian New Zealand Clinical Trials Registry identifier: ACTRN12610000987066.

Testing a Social Innovation in Financial Aid for Low-Income Students: Experimental Evidence from Italy

This paper presents the results of a randomized controlled trial aimed at testing the effectiveness of an innovative intervention of asset building (Percorsi) on high school students' transition to the university. Contrary to most traditional forms of financial aid, the tested intervention is expected to enhance an active involvement of the families and imposes a strong conditionality in the use of the benefits. The experiment, called ACHAB (Affording College with the Help of Asset Building) has been carried out in the province of Torino (Northwest Italy) between 2014 and 2017. For the evaluation purpose, an ad hoc survey has been carried out to collect longitudinal information on enrolment decisions and academic performances (number of exams and persistence) during the first semester and at the beginning of the second year. External data and applicant baseline information were used to perform a multidimensional targeting strategy aimed at identifying the 'target population', i.e. those students who were at risk of giving up their university enrolment decisions because of economic reasons. The experimental results point to the existence of positive and significant effects of the program on university enrolment and sizeable and significant positive effects on academic performance and university persistence. The effects of the program are significantly larger for students coming from vocational schools than for students who completed technical or general secondary schools.

Multidimensional Targeting: Identifying Beneficiaries of Conditional Cash Transfer Programs

Conditional cash transfer programs (CCTs) have two main objectives: reducing poverty and increasing the human capital of children. To reach these objectives, transfers are given to poor households conditioned on investments in their children’s education, health, and nutrition. Targeting mechanisms used by CCTs have been generally successful in identifying the income poor but have not fared as well in identifying households that under-invest in human capital. These mechanisms do not consider the multidimensional aspect of poverty, even when composite measures are used, as they do not capture each dimension-specific deprivation. This paper proposes a multidimensional targeting approach to identifying beneficiaries that explicitly takes into consideration the multiple objectives of CCTs and the multiple deprivations of the poor household. Results indicate that the proposed multidimensional targeting methodology significantly improves the selection of households with children who are most deprived in the dimensions often relevant to CCTs. In the case of Mexico’s Oportunidades, ex-ante evaluation results indicate that the multidimensional identification of beneficiaries increases the impact of transfers on school attendance compared to alternative targeting models.

Multidimensional Targeting and Evaluation: A General Framework with an Application to a Poverty Program in Bangladesh

Many poverty, safety net, training, and other social programs utilise multiple screening criteria to determine eligibility. We apply recent advances in multidimensional measurement analysis to develop a straightforward method for summarising changes in groups of eligibility (screening) indicators, which have appropriate properties. We show how this impact can differ across participants with differing numbers of initial deprivations. We also examine impacts on other specially designed multidimensional poverty measures (and their components) that address key participant deficits. We apply our methods to a BRAC ultra-poverty program in Bangladesh, and find that our measures of multidimensional poverty have fallen significantly for participants. This improvement is most associated with better food security and with acquisition of basic assets (though this does not mean that the cause of poverty reduction was program activities focused directly on these deficits). In general, we find that the BRAC program had a greater impact on reducing multidimensional poverty for those with a larger initial number of deprivations. We also showed how evaluation evidence can be used to help improve the selection of eligibility characteristics of potential participants.

Multidimensional Targeting: Using Physical and Chemical Forces in Unison

Targeted drug delivery has traditionally relied on finding highly specific biochemical markers at a target location. However, recent developments in this area have shown that purely physical and physicochemical factors are as important and can be used to aid in the targeting process. Here, we review the physicochemical factors affecting the targeting and delivery process and their relation to established biochemical markers. We refer to this combined approach as multidimensional targeting (MDT). More specifically, we examine the role of MDT factors across different length scales of relevance to the drug delivery pathway. Finally, we conclude with our perspective on the future of this burgeoning area.

Are Female Orphans at Risk for Early Marriage, Early Sexual Debut, and Teen Pregnancy? Evidence from Sub‐Saharan Africa

Female orphans are widely cited as being at risk for early marriage, early childbearing, and risky sexual behavior; however, to date no studies have examined these linkages using population-level data across multiple countries. This study draws from recent Demographic and Health Surveys from ten sub-Saharan African countries to examine the relationship between orphanhood status and measures of early marriage, early sexual debut, and teen pregnancy among adolescent girls aged 15 to 17. Results indicate that, overall, little association is found between orphanhood and early marriage or teen pregnancy, whereas evidence from seven countries supports associations between orphanhood and early sexual debut. Findings are sensitive to the use of multivariate models, type of orphan, and country setting. Orphanhood status alone may not be a sufficient targeting mechanism for addressing these outcomes in many countries; a broader, multidimensional targeting scheme including orphan type, schooling, and poverty measures would be more robust in identifying and aiding young women at risk.

Recruiting, Retaining, and Advancing Careers for Employees From Underrepresented Groups

In response to the need to increase the number of persons from underrepresented groups working in acute care settings, 2 hospitals in upstate New York implemented a multidimensional workforce development project targeting existing and new employees meeting federally defined poverty levels. The authors describe the project and its outcomes, which surpassed original expectations.