About this Research Topic
Governments throughout the world have continually attempted to derive and apply various metrics and measures to assess and improve their ability to deliver on their respective missions. Within the federal government of the United States, for instance, traditional metrics such as those related to organizational performance measurement have been codified into law and are continually required of all federal agencies (e.g., the Government Performance and Results Act of 1993 and the GPRA Modernization Act of 2010). These metrics and measures have been supplemented by a newer generation of parameters that aim to measure and capture data and information related to various aspects of federal and organizational efficiency, effectiveness, and impact (e.g., FedStat, StateStat, Altmetrics).
Despite the recent explosion in the number of metrics and measures used to assess government efficiency and performance, one area of measurement and analytics remains comparatively under-explored and undocumented: behavioral metrics. This area of assessment represents the most important of all because it attempts to describe and measure (if not predict) human behaviors. The commercial sector utilizes behavioral metrics and measures in a predictive sense. Amazon and Google, for instance, filter content based on an individual user's browsing (i.e., behavioral) history. Conversely and perhaps rather regretfully, there also exist examples of behavioral metrics used inappropriately, that is to say without sufficient internal or organizational controls in place. The most recent example of such inappropriate use is the cautionary tale of Massachusetts-based Cambridge Analytica and the ensuing legal battle that led to the company's eventual demise. In this latter case, procedures regarding informed consent were either lacking or non-existent. Still, these examples illustrate the expanding use of behavioral metrics and measures (e.g., within the commercial arena in the former case and within the political arena in the latter case). Both illustrate the expanding use of this form of measurement and analytics.
The objective of this Research Topic is to catalog and understand the use of behavioral metrics and measures within the area of government (e.g., federal, state, local) and to derive a series of best practices regarding their potential application or use therein. As mentioned in the preceding section above, the private sector (e.g., Amazon and Google) provides an existent and readily available comparative benchmark for the use of such measures. Thus, through the submission of original articles and the associated quantitative/semi-quantitative data related to them, this Topic aims to address the following types of questions:
• How are behavioral metrics and measures used in federal, state, or local government? What empirical or prior studies support their use, adoption, and utility within the government sector? How rigorous, stringent, and reproducible are these studies?
• Given their publicly documented potential for misuse (e.g., Cambridge Analytica), how are behavioral metrics and measures used by government agencies selected, vetted, and subject to stringent internal controls? How do these controls affect the utility of information derived from these measures? Can a balance between control and utility be achieved? Are there best practices that can be derived or applied regarding the appropriate use of behavioral metrics and measures?
• How do behavioral metrics and measures compare with other, more traditional organizational metrics and measures, such as those used to assess performance (e.g., GPRA, GPRAMA measures and CAP Goals) or risk (e.g., key risk indicators)? What specific advantages and disadvantages are associated with their application and use?
Understanding the specific uses of behavioral metrics and measures will ensure their appropriate, evidence-based, and fitness-for-purpose application within the government sector, a sector whose decisions influence the lives of many. The development of such a knowledge base is important given the increasingly widespread use of behavioral metrics in the federal sector despite the lack of sufficient evidence for their adoption (e.g., use of behavior-based screening and interview questions for federal positions).
The themes capable of being addressed by this topic are reflected by and in the specific questions articulated above (see preceding section). To address these themes, the types of manuscripts envisioned and hoped for include: original research articles, meta-analyses, reviews, and commentary with sufficient attribution.
Despite the recent explosion in the number of metrics and measures used to assess government efficiency and performance, one area of measurement and analytics remains comparatively under-explored and undocumented: behavioral metrics. This area of assessment represents the most important of all because it attempts to describe and measure (if not predict) human behaviors. The commercial sector utilizes behavioral metrics and measures in a predictive sense. Amazon and Google, for instance, filter content based on an individual user's browsing (i.e., behavioral) history. Conversely and perhaps rather regretfully, there also exist examples of behavioral metrics used inappropriately, that is to say without sufficient internal or organizational controls in place. The most recent example of such inappropriate use is the cautionary tale of Massachusetts-based Cambridge Analytica and the ensuing legal battle that led to the company's eventual demise. In this latter case, procedures regarding informed consent were either lacking or non-existent. Still, these examples illustrate the expanding use of behavioral metrics and measures (e.g., within the commercial arena in the former case and within the political arena in the latter case). Both illustrate the expanding use of this form of measurement and analytics.
The objective of this Research Topic is to catalog and understand the use of behavioral metrics and measures within the area of government (e.g., federal, state, local) and to derive a series of best practices regarding their potential application or use therein. As mentioned in the preceding section above, the private sector (e.g., Amazon and Google) provides an existent and readily available comparative benchmark for the use of such measures. Thus, through the submission of original articles and the associated quantitative/semi-quantitative data related to them, this Topic aims to address the following types of questions:
• How are behavioral metrics and measures used in federal, state, or local government? What empirical or prior studies support their use, adoption, and utility within the government sector? How rigorous, stringent, and reproducible are these studies?
• Given their publicly documented potential for misuse (e.g., Cambridge Analytica), how are behavioral metrics and measures used by government agencies selected, vetted, and subject to stringent internal controls? How do these controls affect the utility of information derived from these measures? Can a balance between control and utility be achieved? Are there best practices that can be derived or applied regarding the appropriate use of behavioral metrics and measures?
• How do behavioral metrics and measures compare with other, more traditional organizational metrics and measures, such as those used to assess performance (e.g., GPRA, GPRAMA measures and CAP Goals) or risk (e.g., key risk indicators)? What specific advantages and disadvantages are associated with their application and use?
Understanding the specific uses of behavioral metrics and measures will ensure their appropriate, evidence-based, and fitness-for-purpose application within the government sector, a sector whose decisions influence the lives of many. The development of such a knowledge base is important given the increasingly widespread use of behavioral metrics in the federal sector despite the lack of sufficient evidence for their adoption (e.g., use of behavior-based screening and interview questions for federal positions).
The themes capable of being addressed by this topic are reflected by and in the specific questions articulated above (see preceding section). To address these themes, the types of manuscripts envisioned and hoped for include: original research articles, meta-analyses, reviews, and commentary with sufficient attribution.
Keywords: behavior, metrics, measures, measurement, government, improvement
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
