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01 March 2021
Innovative Data Sources in Management Accounting Research and Practice
In recent years, we have seen considerable increases in the sources of data as well as in the techniques available to create and analyse data. These new opportunities present researchers with novel research questions and with enhanced abilities to answer open questions. At the same time, the increasing interest in data driven decision making in practice makes it crucial for researchers to embrace these trends in order to stay connected with corporate practice. Moreover, understanding how subordinates and supervisors utilize and respond to this shift is imperative. Our aim is to provide a forum for researchers to contribute innovative and rigorous research that utilizes new data sources, applies innovative analysis techniques, and/or investigates how the use of new data in organizations influences the future development of planning, performance measurement, and control.
TOPICS: Scholars from all regions of the world are invited to submit research on any aspect of planning, performance measurement, or control that utilizes innovative data and/or data analysis techniques or describes how behaviour in organizations changes due to innovative use of data.
All research methods are welcome and topic areas of interest include, but are not limited to:
- Field studies of companies that make use of new data sources/data analytics
- Textual analysis of proxy statements (e.g. to measure internal auditing/control or value based management)
- Analysis of data from government sources (for example employer or employee panels or data from city authorities, see, e.g., NYC open data)
- Analysis of new data sources in healthcare (e.g. measurement and reporting of hospital quality)
- Machine learning approaches to improve forecast accuracy
- Performance measures for digital businesses and platform businesses (such as customer growth and churn rates, customer acquisition costs, available compatible products of third parties etc.)
- The value of customer data
- The impact of real time data on performance management and control
- The analysis of big data for decision making
- The acceptance of “black box” algorithms by decision makers
- Causal inference with new data sources
- Quantitative analysis of value drivers / profitability analytics
- Analysis of unstructured data, such as texts and videos
- Implications for monitoring (e.g. continuous monitoring of employees, GPS data)
- Privacy issues
- Shifts in power between workers and management
- Implications for society when firms become “creative” in using new data sources
Any other topics related to the Special Issue theme can also be considered.
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Manuscripts should follow EAR submission guidelines. When submitting, authors should clearly indicate in the EAR platform that they are submitting to the Special Issue. Manuscripts that pass the initial screening will have a maximum of two rounds of reviews. Rejected manuscripts may continue as regular submissions if specifically recommended in the Special Issue rejection letter. This is likely if a manuscript is found to possess a strong likelihood of acceptance but is deemed to either be a poor fit with the theme of the Issue or requires revisions that are unlikely to be accomplished within the Special Issue accelerated review schedule.
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