Optimal Times to Contact Sample Households

Weeks, Michael; Jones, Ben; Folsom, R; Benrud, Charles H.

doi:10.1086/268569

Cited by 37 publications

(26 citation statements)

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“…For example, 80% of the weekday evening cells have an answered rate of 70% or higher compared to only 4% of the weekday daytime cells. This finding has obvious intuitive appeal and is also consistent with Weber andBurt (1972), Fitti (1979), Weeks et al (1980), and Vigderhous (1981). It is also interesting to note that the probability of obtaining a first-call answer tends to increase during the 5:00-10:00 P.M. period as the hour gets later.…”

Section: The Datasupporting

confidence: 85%

“…Monday is significantly higher than any other weekday and not statistically different from Saturday or Sunday. The Saturday result is consistent with Weeks et al (1980), who also found Saturday the best overall "contact" day. From an interviewing perspective, however, Sunday is by far the best overall, statistically significant from all other days, due primarily to high productivity during the afternoon hours.…”

Section: Optimal Timing Of the First Callsupporting

confidence: 84%

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Optimal Call Scheduling for a Telephone Survey

Weeks¹,

Kulka

Pierson

1987

Public Opinion Quarterly

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Contacting a suitable respondent at home and securing the interview is a significant component of the typical household telephone survey. An optimal calling schedule minimizes the number of callbacks required and thus conserves resources. This article presents an analysis of time-of-day and day-of-week effects on the probabilities of obtaining an answered outcome and an interviewed outcome in a large national telephone survey of adult males. The data presented indicate that, at least for the survey population included in this study, the chances of obtaining an answer and conducting an interview on the first call are much better on weekday evenings and on weekends than they are during weekday daytime hours. Moreover, there is some evidence to indicate that this finding also applies to second calls made to firstcall no-answers, at least with regard to contacting efforts. Timeof-day and/or day-of-week effects on first call outcomes appear to be generally consistent with respect to both contacting and interviewing, although Sunday has a decidedly higher interview response rate for answered calls than do the other calling periods analyzed.Contacting a suitable respondent at home and securing the interview is a significant component of the typical household telephone survey. The effort required to accomplish this task, however, can be minimized by calling respondents at optimal times; that is, when the chances are best of finding an eligible respondent at home and willing to be interviewed. An optimal calling schedule minimizes the number of callbacks required and thus conserves labor, time, and money.

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Section: The Datasupporting

confidence: 85%

Section: Optimal Timing Of the First Callsupporting

confidence: 84%

Optimal Call Scheduling for a Telephone Survey

Weeks¹,

Kulka

Pierson

1987

Public Opinion Quarterly

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“…There is less variability later in the evening when many different types of people are likely to be home. These results show a similar pattern to the analyses of U.S. Census Bureau [12] and Weeks et al [14].…”

Section: Resultssupporting

confidence: 90%

Adaptive design research for the 2020 Census1

Konicki

Adams

2016

SJI

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Abstract. The U.S. Census Bureau is researching and testing new methods to reduce the cost of the 2020 Census while maintaining data quality. One of the most costly components of the 2010 Census was Nonresponse Followup. In this operation, enumerators conducted in-person interviews at housing units that did not return a census questionnaire by mail. For the 2010 Census, enumerators were instructed to visit each of these units up to three times until the case was resolved. Additionally, enumerators were to make up to three contact attempts by telephone. In this paper, we present an overview of current research on determining the number of contact attempts that should be made to nonresponding units with an emphasis on cost containment and improved overall productivity. Rather than the fixed contact strategy employed in the 2010 Census, we consider adaptive approaches that maintain the quality of the data. We present initial results of possible approaches using data from the 2010 Census and discuss the implications of the methods. We also discuss modeling contact probabilities for each hour of the day to support the case management system.

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“…and ''How do influences of call characteristics and the initial reactions of the householder change depending on the experience and the tailoring ability of the interviewer?'' Most of the previous research on call record data has focused on ways to establish contact with a household (Durrant et al 2011; Kulka and Weeks 1988;Wagner 2013;Weeks et al 1980). Since the contact and the cooperation/refusal stages are two quite distinct processes (Groves and Couper 1998;Lynn and Clarke 2002;Nicoletti and Perachi 2005), analyzing time to first contact is therefore not of direct relevance here.…”

Section: Sociological Methods and Researchmentioning

confidence: 99%

Doorstep Interactions and Interviewer Effects on the Process Leading to Cooperation or Refusal

Durrant

D'Arrigo

2014

Sociological Methods & Research

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This article presents an analysis of interviewer effects on the process leading to cooperation or refusal in face-to-face surveys. The focus is on the interaction between the householder and the interviewer on the doorstep, including initial reactions from the householder, and interviewer characteristics, behaviors, and skills. In contrast to most previous research on interviewer effects, which analyzed final response behavior, the focus here is on the analysis of the process that leads to cooperation or refusal. Multilevel multinomial discrete-time event history modeling is used to examine jointly the different outcomes at each call, taking account of the influence of interviewer characteristics, call histories, and sample member characteristics. The study benefits from a rich data set comprising call record data (paradata) from several face-to-face surveys linked to interviewer observations, detailed interviewer information, and census records. The models have implications for survey practice and may be used in responsive survey designs to inform effective interviewer calling strategies.

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Optimal Times to Contact Sample Households

Cited by 37 publications

References 0 publications

Optimal Call Scheduling for a Telephone Survey

Optimal Call Scheduling for a Telephone Survey

Adaptive design research for the 2020 Census1

Doorstep Interactions and Interviewer Effects on the Process Leading to Cooperation or Refusal

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