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TV Advertising and Online Sales: A Case Study of Intertemporal Substitution Effects for an Online Travel Platform
Get PDFDigital technologies lead consumers to engage with companies online after they see TV ads, and firms increasingly wish to coordinate TV advertising in real time with online marketing activities. As a result, firms are keen to measure how TV advertising affects consumers' online behavior, but a key question is over what window of time to measure this effect. The standard industry practice of using short attribution windows around an ad to measure a causal effect may miss the possibility that consumer behavior shifts over time due to, for example, intertemporal substitution. We collaborate with an online travel platform and evaluate the results of a field test where part of the country was exposed to TV ads while another part of the country formed a control group. Using the synthetic difference-in-differences approach, we find TV advertising leads to an instantaneous increase in online browsing and sales. However, we also document evidence for intertemporal substitution: consumers appear to move their online activities forward in time in response to TV advertising, leading to lower browsing and lower sales at times when no ad is airing. We further explore the effects of TV advertising on channel choices, device choices and promotion usage and discuss the implications for advertisers and the ad-measurement industry
Crowd-Judging on Two-Sided Platforms: An Analysis of In-Group Bias
Get PDFDisputes over transactions on two-sided platforms are common and usually arbitrated through platforms’ customer service departments or third-party service providers. This paper studies crowd-judging, a novel crowdsourcing mechanism whereby users (buyers and sellers) volunteer as jurors to decide disputes arising from the platform. Using a rich data set from the dispute resolution center at Taobao, a leading Chinese e-commerce platform, we aim to understand this innovation and propose and analyze potential operational improvements with a focus on in-group bias (buyer jurors favor the buyer, likewise for sellers). Platform users, especially sellers, share the perception that in-group bias is prevalent and systematically sways case outcomes as the majority of users on such platforms are buyers, undermining the legitimacy of crowd-judging. Our empirical findings suggest that such concern is not completely unfounded: on average, a seller juror is approximately 10% likelier (than a buyer juror) to vote for a seller. Such bias is aggravated among cases that are decided by a thin margin and when jurors perceive that their in-group’s interests are threatened. However, the bias diminishes as jurors gain experience: a user’s bias reduces by nearly 95% as experience grows from zero to the sample median level. Incorporating these findings and juror participation dynamics in a simulation study, the paper delivers three managerial insights. First, under the existing voting policy, in-group bias influences the outcomes of no more than 2% of cases. Second, simply increasing crowd size through either a larger case panel or aggressively recruiting new jurors may not be efficient in reducing the adverse effect of in-group bias. Finally, policies that allocate cases dynamically could simultaneously mitigate the impact of in-group bias and nurture a more sustainable juror pool
Robust combination testing: methods and application to COVID-19 detection
Get PDFSimple and affordable testing tools are often not accurate enough to be operationally relevant. For COVID-19 detection, rapid point-of-care tests are cheap and provide results in minutes, but largely fail policymakers' accuracy requirements. We propose an analytical methodology, based on robust optimization, that identifies optimal combinations of results from cheap tests for increased predictive accuracy. This methodological tool allows policymakers to credibly quantify the benefits from combination testing and thus break the trade-off between cost and accuracy. Our methodology is robust to noisy and partially missing input data and incorporates operational constraints-relevant considerations in practice. We apply our methodology to two datasets containing individual-level results of multiple COVID-19 rapid antibody and antigen tests, respectively, to generate Pareto-dominating receiver operating characteristic (ROC) curves. We find that combining only three rapid tests increases out-of-sample area under the curve (AUC) by 4% (6%) compared with the best performing individual test for antibody (antigen) detection. We also find that a policymaker who requires a specificity of at least 0.95 can improve sensitivity by 8% and 2% for antibody and antigen testing, respectively, relative to available combination testing heuristics. Our numerical analysis demonstrates that robust optimization is a powerful tool to avoid overfitting, accommodate missing data, and improve out-of-sample performance. Based on our analytical and empirical results, policymakers should consider approving and deploying a curated combination of cheap point-of-care tests in settings where `gold standard' tests are too expensive or too slow
Sources and Transmission of Country Risk
Get PDFWe use textual analysis of earnings conference calls held by listed firms around the world to measure the amount of risk managers and investors at each firm associate with each country at each point in time. Flexibly aggregating this firm-country-quarter-level data allows us to systematically identify spikes in perceived country risk (“crises”) and document their source and pattern of transmission to foreign firms. While this pattern usually follows a gravity structure, it often changes dramatically during crises. For example, while crises originating in developed countries propagate disproportionately to foreign financial firms, emerging market crises transmit less financially and more to traditionally exposed countries. We apply our measures to show that elevated perceptions of a country’s riskiness, particularly those of foreign and financial firms, are associated with significant falls in local asset prices, capital outflows, and an increased likelihood of a sudden stop
Network referrals and self-presentation in the high-tech labor market
Get PDFThe practice of recruiting job candidates sourced through social contacts (i.e., referrals) is pervasive in the labor market. One reason employers prefer to recruit through referrals is that these candidates often present resumes that are perceived to be a better fit for the role. While existing research attributes this pattern to how individuals who make referrals (i.e., referrers) select individuals to refer, we propose a new mechanism: differences in self-presentation. We argue that referral ties increase the candidates’ propensity to engage in self-presentation work, motivating and assisting candidates in presenting their backgrounds to convey fit. We examine this claim by utilizing unique data from an applicant tracking system containing job applications to positions at U.S.-based high-tech firms between 2008 and 2012. A candidate-fixed effects specification reveals that when a candidate applies to a firm via a referral, they tend to showcase a rendition of their career history that better matches the target job than when they pursue positions without such ties. Several mechanism checks, combined with supplementary survey evidence, further indicate that the presence of referral ties to the target firm is associated with greater motivation to engage in self-presentation work as well as the provision of different forms of assistance in that work
Happy Talk: Is Common Diversity Rhetoric Effective Diversity Rhetoric?
No full textDespite their prevalence, diversity initiatives do not necessarily motivate employees to facilitate diversity goals. We advance understanding of diversity rhetoric—defined as how leaders talk about diversity and its effects—as a tool for motivating employees to foster diversity and inclusion. Prior work has investigated rhetoric that emphasizes diversity in organizations is necessarily beneficial (value-in-diversity rhetoric), which is puzzling given the reality that diversity can have positive or negative consequences. We introduce the construct of contingent-diversity rhetoric, which emphasizes that diversity is beneficial if its challenges are overcome, and thus captures the reality of diversity’s effects. Drawing from the psychology of the self, we theorize that leaders use contingent-diversity rhetoric less commonly than value-in-diversity rhetoric, due to fear of appearing prejudiced. Drawing from the psychology of employee motivation, we theorize that contingent-diversity rhetoric results in more diversity effort among employees than value-in-diversity rhetoric does because contingent rhetoric increases perceptions that diversity goals are difficult to achieve. Four multimethod studies support the proposed descriptive–prescriptive paradox: contingent-diversity rhetoric is descriptively less common, but prescriptively more effective, than value-in-diversity rhetoric. Our research advances theory on fostering diversity and inclusion in organizations and suggests that leaders can increase employees’ diversity effort by changing the way they talk about diversity
EU non-bank finance returns to growth
No full textNon-bank financial intermediation is playing a growing role in providing credit to the real economy and the financial sector, and 2023 saw the market return to its growth trajectory. Market-based sources of financing are urgently needed in Europe, but this trend can bring risks to financial stability especially when non-bank entities use leverage, are exposed to liquidity mismatches or are highly interconnected with the rest of the financial system. This paper reviews structural features and risks to the EU financial system, such as the international dimension of the money market fund sector, as well as recent developments related to private finance and crypto assets. As current discussions on the Savings and Investments Union and the macroprudential approach for non-banks progress, a system-level view of non-bank finance in the EU points to the potential but also to the diversity and complexity of the markets and institutions
A longevity revolution
No full textWith global life expectancy now exceeding 70 years old, we need to change how we age, not how long we age, says Andrew Scot
A Strengthened Primal-Dual Decomposition Algorithm for Solving Electricity Market Pricing with Revenue-Adequacy and FFR constraints
No full textEfficient nodal pricing models and short-term unit commitment planning face continuous needs for improvement as operational requirements evolve. This paper develops a Bilevel Security-Constrained Unit Commitment (BL-SCUC) model to include both revenue-adequacy and Fast Frequency Reserve (FFR) constraints. The upper level of the BL-SCUC model represents the non-convex UC decisions as well as the revenue-adequacy constraints of the market participants (generators, loads, and battery-storage owner). The lower level is a convex economic dispatch model which produces the nodal electricity prices. To solve the proposed BL-SCUC model, it is first reformulated as a single-level Mixed-Integer Linear Program (MILP) using the standard strong-duality approach. The resulting MILP model is hard to solve using standard off-the-shelf solvers such as Cplex, partly because the Big-M parameters’ optimal tuning for linearization in the strong duality method is NP-hard. To solve this, we propose a strengthened Primal-Dual Decomposition (PDD) algorithm, which takes benefit from both Benders-like and Lagrange Dual-like algorithms. The new PDD algorithm eliminates the Big-M parameters without affecting optimal values. Accordingly, the computational burden and optimal solution sensitivity resulting from Big-M parameters are mitigated. Results from the modified IEEE 24-bus system demonstrate the effectiveness of the proposed BL-SCUC model with its PDD algorithm, whilst results from the IEEE 118-bus system show the superiority of the proposed strengthened PDD algorithm over the classic Benders algorithm
