Pinar Yildirim

The Impact of Advertising on Media Bias

In this study, the authors investigate the role of advertising in affecting the extent of bias in the media. When making advertising choices, advertisers evaluate both the size and the composition of the readership of the different outlets. The profile of the readers matters because advertisers want to target readers who are likely to be receptive to their advertising messages. The authors demonstrate that when advertising supplements subscription fees, it may serve as a polarizing or moderating force, contingent on the extent of heterogeneity among advertisers in appealing to readers having different political preferences. When heterogeneity is large, each advertiser chooses a single outlet for placing advertisements (single-homing), and greater polarization arises in comparison to when the media outlet relies on subscription fees only for revenues. In contrast, when heterogeneity is small, each advertiser chooses to place advertisements in multiple outlets (multihoming) and reduces polarization results.

Credit Scoring with Social Network Data

Motivated by the growing practice of using social network data in credit scoring, we analyze the impact of using network-based measures on customer score accuracy and on tie formation among customers. We develop a series of models to compare the accuracy of customer scores obtained with and without network data. We also investigate how the accuracy of social network-based scores changes when consumers can strategically construct their social networks to attain higher scores. We find that those who are motivated to improve their scores may form fewer ties and focus more on similar partners. The impact of such endogenous tie formation on the accuracy of consumer scores is ambiguous. Scores can become more accurate as a result of modifications in social networks, but this accuracy improvement may come with greater network fragmentation. The threat of social exclusion in such endogenously formed networks provides incentives to low-type members to exert effort that improves everyone’s creditworthiness. We discuss implications for managers and public policy.

Matching Pennies on the Campaign Trail: An Empirical Study of Senate Elections and Media Coverage

We study the strategic interaction between the media and Senate candidates during elections. While the media is instrumental for candidates to communicate with voters, candidates and media outlets have conflicting preferences over the contents of the reporting. In competitive electoral environments such as most US Senate races, this can lead to a strategic environment resembling a matching pennies game. Based on this observation, we develop a model of bipartisan races where media outlets report about candidates, and candidates make decisions on the type of constituencies to target with their statements along the campaign trail. We develop a methodology to classify news content as suggestive of the target audience of candidate speech, and show how data on media reports and poll results, together with the behavioral implications of the model, can be used to estimate its parameters. We implement this methodology on US Senatorial races for the period 1980-2012, and find that Democratic candidates have stronger incentives to target their messages towards turning out their core supporters than Republicans. We also find that the cost in swing-voter support from targeting core supporters is larger for Democrats than for Republicans. These effects balance each other, making media outlets willing to cover candidates from both parties at similar rates.

Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives

Abstract Online promotion helps enhance brand awareness and boost sales. Although it attracts customer traffic, an ill-conceived price promotion has serious repercussions because it disproportionately draws bargain hunters, results in profit erosion and causes operational chaos due to erratic demands. This research proposes a long-term optimization model to help dual channel (click-and-mortar) retailers understand the conditions necessary to promote products online across all markets. When partial markets are recommended, we investigate how to price and select the market portfolio for promotion in each time period. We develop a multi-objective evolutionary algorithm to efficiently solve complex and large-scale problems. Both theoretical analysis and numerical study show that the proposed model outperforms the conventional strategy of promoting online across the board. Due to its dynamic nature, the multi-period recurring promotion problem is difficult to address optimally. Our model is capable of planning for multiple periods, multiple markets, and multiple objectives to maximize long term profitability and competitiveness. Click-and-mortar retailers will find our approach extremely effective for maximizing profit, enhancing brand awareness, and improving customer satisfaction.

Informal Lending and Entrepreneurship

How does the informal economy affect financial inclusion and entrepreneurial activity of consumers? We investigate the impact of informal lending on the types and terms of contracts offered by formal lenders, considering factors that facilitate informal lending activity such as social ties between consumers. The density of the connections between consumers represents the degree to which those with and without wealth mix, indirectly capturing the degree of inequality in a society. We develop a model which relates the density of social connections to the availability of informal lending activity. We show that a low to moderate degree of informal activity in a market can help unwealthy entrepreneurs because it motivates the bank to compete by cutting down the interest rate of unsecured loans offered to these consumers. In turn, the bank faces an overinvestment problem when financial inclusion is higher. As informal borrowing opportunities increase further, lenders’ benefit from increased access to credit diminishes. It earns higher rents by increasing the rates on wealthy low-risk consumers who can informally lend to their social contacts. As a consequence, the overinvestment problem is replaced by an underinvestment problem and creditworthy entrepreneurs are deprived of loans from banks. We argue that although the entrepreneurial investment shrinks, only those projects with the best return are awarded financing, implying that the average investment in the market is now more attractive.

Optimal Network Design for Inducing Effort

Many companies create and manage communities where consumers observe and exchange information about the effort exerted by other consumers. Such communities are especially popular in the areas of fitness, education, dieting, and financial savings. We study how to optimally structure such consumer communities when the objective is to maximize the total or average amount of effort expended. Using network modeling and assuming peer influence through conformity, we find that the optimal community design consists of a set of disconnected or very loosely connected sub-communities, each of which is very densely connected within. Also, each sub-community in the optimal design consists of consumers selected such that their “standalone” propensity to exert effort correlates negatively with their propensity to conform and correlates positively with their propensity to influence others.An increasing number of start-ups create online and offline shared goal communities for individuals with similar goals to work towards them in the company of others. Such platforms allow individuals to connect and share effort information under the premise that it is more likely for consumers to reach their goals if they can gauge their activity in line with others’ activities. We study the problem of designing such social communities. We find that co-action communities can motivate individuals to exert higher effort than they would have on their own, if they are appropriately located in a social network with sufficient social influence. Moreover, such communities can help consumers at a greater extent if they are of larger scale and if consumers in the community maintain sufficient levels of heterogeneity in how much they care about their goal progress individually. Our study also offers a method to determine a locally optimal network to design such communities and develops a model to study the conditions under which consumers can be motivated to exert effort towards a goal.

Connecting People for Nudges: Optimal Design of Networks to Motivate Consumer Behavior

Many companies create and manage communities where consumers observe and exchange information about the effort exerted by other consumers. Such communities are especially popular in the areas of fitness, education, dieting, and financial savings. We study how to optimally structure such consumer communities when the objective is to maximize the total or average amount of effort expended. Using network modeling and assuming peer influence through conformity, we find that the optimal community design consists of a set of disconnected or very loosely connected sub-communities, each of which is very densely connected within. Also, each sub-community in the optimal design consists of consumers selected such that their “standalone” propensity to exert effort correlates negatively with their propensity to conform and correlates positively with their propensity to influence others.An increasing number of start-ups create online and offline shared goal communities for individuals with similar goals to work towards them in the company of others. Such platforms allow individuals to connect and share effort information under the premise that it is more likely for consumers to reach their goals if they can gauge their activity in line with others’ activities. We study the problem of designing such social communities. We find that co-action communities can motivate individuals to exert higher effort than they would have on their own, if they are appropriately located in a social network with sufficient social influence. Moreover, such communities can help consumers at a greater extent if they are of larger scale and if consumers in the community maintain sufficient levels of heterogeneity in how much they care about their goal progress individually. Our study also offers a method to determine a locally optimal network to design such communities and develops a model to study the conditions under which consumers can be motivated to exert effort towards a goal.

Designing Networks for Nudges: Using Social Conformity to Optimize Consumer Behavior

Many companies create and manage communities where consumers observe and exchange information about the effort exerted by other consumers. Such communities are especially popular in the areas of fitness, education, dieting, and financial savings. We study how to optimally structure such consumer communities when the objective is to maximize the total or average amount of effort expended. Using network modeling and assuming peer influence through conformity, we find that the optimal community design consists of a set of disconnected or very loosely connected sub-communities, each of which is very densely connected within. Also, each sub-community in the optimal design consists of consumers selected such that their “standalone” propensity to exert effort correlates negatively with their propensity to conform and correlates positively with their propensity to influence others.An increasing number of start-ups create online and offline shared goal communities for individuals with similar goals to work towards them in the company of others. Such platforms allow individuals to connect and share effort information under the premise that it is more likely for consumers to reach their goals if they can gauge their activity in line with others’ activities. We study the problem of designing such social communities. We find that co-action communities can motivate individuals to exert higher effort than they would have on their own, if they are appropriately located in a social network with sufficient social influence. Moreover, such communities can help consumers at a greater extent if they are of larger scale and if consumers in the community maintain sufficient levels of heterogeneity in how much they care about their goal progress individually. Our study also offers a method to determine a locally optimal network to design such communities and develops a model to study the conditions under which consumers can be motivated to exert effort towards a goal.

Social Media and Political Donations: New Technology and Incumbency Advantage in the United States

Can new technologies increase political competition? We study the impact of adopting Twitter on campaign contributions received by politicians. For identification, we compare donations just before and just after politicians open Twitter accounts in regions with high and low levels of Twitter penetration, controlling for politician-month fixed effects. We estimate that opening a Twitter account amounts to an increase of at least 2-3% in donations per campaign. This effect is stronger for new politicians, who were never elected before, for donations coming from new donors, for politicians who tweet more informatively, and for politicians from regions with lower newspaper circulation.