Social desirability bias in software piracy research: Evidence from pilot studies

2016 ◽  
Author(s):  
Marton Gergely ◽  
V. Srinivasan Rao
Keyword(s):  
Social Desirability ◽  
Research Evidence ◽  
Software Piracy ◽  
Social Desirability Bias ◽  
Pilot Studies

scholarly journals Just Google it: measuring schools' use of research evidence with internet search results

2019 ◽  
Vol 15 (1) ◽  
pp. 103-123 ◽  
Author(s):  
Zachary Neal ◽  
Jennifer Lawlor ◽  
Jennifer Watling Neal ◽  
Kristen Mills ◽  
Kathryn McAlindon
Keyword(s):  
School Districts ◽  
Social Desirability ◽  
Research Evidence ◽  
Public School Districts ◽  
Social Desirability Bias ◽  
Search Results ◽  
Central Focus ◽  
New Strategy ◽  
Collection Methods ◽  
Use Of Research

Measuring the use of research evidence (URE) by schools has become a central focus of education researchers. However, it has proven challenging due to low response rates, social desirability bias, and costly or time-consuming data collection methods. To overcome these challenges and meet the needs of research focused on URE, this paper introduces a non-reactive archival measure: Archival Search of Use of Research Evidence (ASURE). ASURE counts references to research or evidence on a school's or school district's website to capture the extent of its rhetorical use of research evidence. After illustrating the collection of ASURE in all public school districts in Michigan (N = 595), we use data on these districts to show that ASURE is reliable and valid, and thus offers a promising new strategy for measuring URE in schools. We conclude by considering future steps for exploring ASURE, not simply as a measure of URE in schools, but instead as a measurement strategy for assessing URE in a broad range of organisational contexts.

Collecting High-Quality Data

2018 ◽  
Author(s):  
Mary Kay Gugerty ◽  
Dean Karlan
Keyword(s):  
Data Collection ◽  
Social Desirability ◽  
Measurement Errors ◽  
Monitoring And Evaluation ◽  
Quality Data ◽  
Social Desirability Bias ◽  
High Quality ◽  
High Quality Data ◽  
Evaluation Systems ◽  
Demand Effect

Without high-quality data, even the best-designed monitoring and evaluation systems will collapse. Chapter 7 introduces some the basics of collecting high-quality data and discusses how to address challenges that frequently arise. High-quality data must be clearly defined and have an indicator that validly and reliably measures the intended concept. The chapter then explains how to avoid common biases and measurement errors like anchoring, social desirability bias, the experimenter demand effect, unclear wording, long recall periods, and translation context. It then guides organizations on how to find indicators, test data collection instruments, manage surveys, and train staff appropriately for data collection and entry.

Tax compliance and social desirability bias of taxpayers: experimental evidence from Indonesia

2021 ◽  
pp. 1-18
Author(s):  
Endra Iraman ◽  
Yoshikuni Ono ◽  
Makoto Kakinaka
Keyword(s):  
Experimental Evidence ◽  
Social Desirability ◽  
Tax Evasion ◽  
Tax Compliance ◽  
Computer Assisted ◽  
Social Desirability Bias ◽  
Lower Income ◽  
Tax Returns ◽  
List Experiment ◽  
Experiment Technique

Abstract Identifying taxpayers who engage in noncompliant behaviour is crucial for tax authorities to determine appropriate taxation schemes. However, because taxpayers have an incentive to conceal their true income, it is difficult for tax authorities to uncover such behaviour (social desirability bias). Our study mitigates the bias in responses to sensitive questions by employing the list experiment technique, which allows us to identify the characteristics of taxpayers who engage in tax evasion. Using a dataset obtained from a tax office in Jakarta, Indonesia, we conducted a computer-assisted telephone interviewing survey in 2019. Our results revealed that 13% of the taxpayers, old, male, corporate employees, and members of a certain ethnic group had reported lower income than their true income on their tax returns. These findings suggest that our research design can be a useful tool for understanding tax evasion and for developing effective taxation schemes that promote tax compliance.

scholarly journals Google, Tell Me. Is He Gay? Masculinity, Heterosexuality, and Gendered Anxieties in Google Search Queries about Sexuality

2021 ◽  
pp. 073112142110019
Author(s):  
Emma Mishel ◽  
Tristan Bridges ◽  
Mónica L. Caudillo
Keyword(s):  
Social Desirability ◽  
Google Trends ◽  
Social Desirability Bias ◽  
Same Sex ◽  
Search Queries ◽  
Sexual Identities ◽  
Google Search

It is difficult to gauge people’s acceptance about same-sex sexualities, as responses to questionnaires are prone to social desirability bias. We offer a new proxy for understanding popular concern surrounding same-sex sexualities: prevalence of Google searches demonstrating concern over gay/lesbian sexual identities. Using Google Trends data, we find that Google searches about whether a specific person is gay or lesbian show patterned bias toward masculine searches, in that such searches are much more frequently conducted about boys and men compared with girls and women. We put these findings into context by comparing search frequencies with other popular Google searches about sexuality and otherwise. We put forth that the patterned bias toward masculine searches illustrates support for the enduring relationship between masculinity and heterosexuality and that it does so on a larger scale than previous research has been able to establish.

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