Suchergebnisse

Abstract
This paper provides an empirical investigation of the hypothesis that companies engage in corporate social responsibility (CSR) in order to offset corporate social irresponsibility (CSI). We find general support for the relationship that when companies do more "harm," they also do more "good." The empirical analysis is based on an extensive 15-year panel dataset that covers nearly 3,000 publicly traded companies. In addition to the overall finding that more CSI results in more CSR, we find evidence of heterogeneity among industries, where the effect is stronger in industries where CSI tends to be the subject of greater public scrutiny. We also investigate the degree of substitutability between different categories of CSR and CSI. Within the categories of community relations, environment, and human rights—arguably among those dimensions of social responsibility that are most salient—there is a strong within-category relationship. In contrast, the within-category relationship for corporate governance is weak, but CSI related to corporate governance appears to increase CSR in most other categories. Thus, when CSI concerns arise about corporate governance, companies seemingly choose to offset with CSR in other dimensions, rather than reform governance itself.

Abstract

Objectives
Smartphones are increasingly used to collect real-time information on time-varying exposures. We developed and deployed an application (app) to evaluate the feasibility of using smartphones to collect real-time information on intermittent agricultural activities and to characterize agricultural task variability in a longitudinal study of farmers.


Methods
We recruited 19 male farmers, aged 50–60 years, to report their farming activities on 24 randomly selected days over 6 months using the Life in a Day app. Eligibility criteria include personal use of an iOS or Android smartphone and >4 h of farming activities at least two days per week. We developed a study-specific database of 350 farming tasks that were provided in the app; 152 were linked to questions that were asked when the activity ended. We report eligibility, study compliance, number of activities, duration of activities by day and task, and responses to the follow-up questions.


Results
Of the 143 farmers we reached out to for this study, 16 were not reached by phone or refused to answer eligibility questions, 69 were ineligible (limited smartphone use and/or farming time), 58 met study criteria, and 19 agreed to participate. Refusals were mostly related to uneasiness with the app and/or time commitment (32 of 39). Participation declined gradually over time, with 11 farmers reporting activities through the 24-week study period. We obtained data on 279 days (median 554 min/day; median 18 days per farmer) and 1,321 activities (median 61 min/activity; median 3 activities per day per farmer). The activities were predominantly related to animals (36%), transportation (12%), and equipment (10%). Planting crops and yard work had the longest median durations; short-duration tasks included fueling trucks, collecting/storing eggs, and tree work. Time period-specific variability was observed; for example, crop-related activities were reported for an average of 204 min/day during planting but only 28 min/day during pre-planting and 110 min/day during the growing period. We obtained additional information for 485 (37%) activities; the most frequently asked questions were related to "feed animals" (231 activities) and "operate fuel-powered vehicle (transportation)" (120 activities).


Conclusions
Our study demonstrated feasibility and good compliance in collecting longitudinal activity data over 6 months using smartphones in a relatively homogeneous population of farmers. We captured most of the farming day and observed substantial heterogeneity in activities, highlighting the need for individual activity data when characterizing exposure in farmers. We also identified several areas for improvement. In addition, future evaluations should include more diverse populations.