Machine Learning in Management Accounting Research : Literature Review and Pathways for the Future

This paper explores the possibilities of employing machine learning (ML) methods and new data sources in management accounting (MA) research. A review of current accounting and related research reveals that ML methods in MA are still in their infancy. However, a review of recently published ML research from related fields reveals several new opportunities to utilize ML in MA research. We suggest that the most promising areas to employ ML methods in MA research lie in (1) the exploitation of the rich potential of various textual data sources; (2) the quantification of qualitative and unstructured data to create new measures; (3) the creation of better estimates and predictions; and (4) the use of explainable AI to interpret ML models in detail. ML methods can play a crucial role in MA research by creating, developing, and refining theories through induction and abduction, as well as by providing tools for interventionist studies.© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.fi=vertaisarvioitu|en=peerReviewed

Proceedings, MSVSCC 2014

Proceedings of the 8th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 17, 2014 at VMASC in Suffolk, Virginia

Deep Model for Improved Operator Function State Assessment

A deep learning framework is presented for engagement assessment using EEG signals. Deep learning is a recently developed machine learning technique and has been applied to many applications. In this paper, we proposed a deep learning strategy for operator function state (OFS) assessment. Fifteen pilots participated in a flight simulation from Seattle to Chicago. During the four-hour simulation, EEG signals were recorded for each pilot. We labeled 20- minute data as engaged and disengaged to fine-tune the deep network and utilized the remaining vast amount of unlabeled data to initialize the network. The trained deep network was then used to assess if a pilot was engaged during the four-hour simulation

Land change dynamics in the Brazilian Cerrado: the interaction of biofuels, markets, and biodiversity

Doctor of PhilosophyDepartment of GeographyMarcellus M. CaldasBiofuel ethanol has been proposed as the most viable solution to mitigate greenhouse gas emissions (GHG) from the transportation sector; however, the impact of such production on the environment is not completely known. Environmental impacts are of more concern when ethanol production occurs in areas of high biodiversity value such as the Cerrado (Brazilian savanna). The Cerrado is a global biodiversity hotspot and an important breadbasket—at the same time, it is on a path to becoming the major sugarcane ethanol-producing region in Brazil. The main goal of this dissertation is to examine the impacts of sugarcane expansion on farmers’ land use decision processes in the Cerrado and to consider its consequences on biodiversity and the impacts of climate change. In the following chapters, land change dynamics are investigated using a combination of theory and methods from geography, GIScience, economics, and ecology. Chapter 2 presents an examination of the drivers for the sugarcane expansion. The findings suggest that the Cerrado attracted mills because of the good agricultural conditions, affordable land prices, and favorable state-level fiscal incentive policies, while factors that have prevented traditional sugarcane-producing regions from meeting the increasing demand for ethanol. Chapter 3 develops a procedure to identify intensification and extensification responses at the field level. The main finding is that extensification is the main response. Additionally, this response has a higher probability of occurrence the farther an area is from a mill. Chapter 4 applies the partial adjustment framework to understand farmers’ land use decisions regarding sugarcane production. Estimates found that price of cattle have the largest cross-price elasticity with sugarcane acreage. In addition, the results suggest that acreage of sugarcane and soybean double-crop are positively correlated. Chapter 5 focuses on the impacts of climate change on land suitability for sugarcane and amphibian species. The findings show that land suitability for sugarcane is vulnerable to climate change and that the Brazilian zoning policy for sugarcane is not addressing this issue. Additionally, amphibians are affected by climate change and conflict with areas suitable for sugarcane in climate change scenarios

AI and blockchain adoption in corporate governance

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonPurpose The purpose of this doctoral thesis sets out to explore and elaborate on the impact of artificial intelligence (AI) and blockchain adoption in corporate governance from ethical perspectives. Positioned within the corporate governance domain, this study adopts an explicit business perspective to study corporate governance change with emerging AI and blockchain technological tools in general and focuses on the ethical use of technologies specifically. As such, this empirical investigation aims to help organizations understand the ethical benefits and ethical dilemmas of using AI and blockchain in businesses and draw plans on how to govern these technologies ethically for the benefit of the business and society. Design/Methodology/Approach: This study adopts specific techniques and a pragmatic, step-by-step netnography approach to investigate online traces from social media sites and extends these online explorations with online semi-structured interviews. The research design of this investigation follows step-by-step procedures that are methodologically sound to ensure rigor in this investigation to enhance the trustworthiness of this study. In total, this research collects an abundance of data: 34 LinkedIn Posts with Comments; 12 Webinars; 22 YouTube Videos; 19 Videos; 10 Podcasts, and 17 semi-structured interview videos. The video, audio, and interview data have been transcribed into textual data total of 453065 words for thematic analysis using NVivo software. Enough time has been allocated to the iterative process of data collection and data analysis. The analysis moves back and forth to the point when theoretical saturation is achieved. The data structure extracts from data in this study illustrate the analytic claims that match the analysis and data together, to ensure a good fit between described method and reported analysis are consistent. Findings: This study develops a thematic framework that constitutes the corporate governance transformation with the ethical use of AI and blockchain technology. This framework provides a holistic understanding of why corporate governance needs to change, especially with the emergence of blockchain and AI technologies, what changes will corporate governance encounter, and how corporate governance can imperatively respond to the ethical use of these technologies. Specifically, it explicitly provides comprehensive understanding of the ethical benefits and ethical concerns of using AI and blockchain technologies in corporate governance, and reveals how companies can govern the use of these technologies ethically. In general terms, the findings of this study support the notion of corporate governance change to transform business models and processes to leverage the new capabilities of AI and blockchain technologies, to priories creativity, speed, and accountability, to replace the old business model, to foster agile or collaborative governance to deal with uncertainty, agility, adaptiveness, and cooperation in the digital world, to foster a network and platform strategies to drive success. This study goes beyond the extant corporate governance scholarship to assess the technological impact to capture values for companies in ethical ways to sustain future growth. Additionally, the notion of corporate governance is further specified and significantly expanded by this study to assess the adoption of AI and blockchain as new corporate governance tools or mechanisms, to enhance ethical benefits when used properly, and mitigate ethical dilemmas with proper checks and balances, safeguards in place, to help organizations stay relevant in this digital transformation and be ethical and sustainable. This study empirically corroborates that in theory, the use of blockchain and AI can enhance ethical practice by detecting fraud and anomaly activities, due to the unique capabilities of blockchain and AI technologies. Further, this research adds depth and specificity by identifying the ethical concerns of using blockchain and AI in corporate governance. The study empirically reveals the ethical concerns of privacy issues, unethical use of data, job transformation and replacement, and algorithm bias that companies will encounter when they use these technologies. In addition, the findings of this study suggest how companies can ethically govern the use of these technologies in socially responsible ways as they transform digitally. Originality/Value: The emergent thematic framework is constructed from the empirical and analytical procedures specifically and purposely designed for this study. This study makes theoretical contributions to knowledge and enriches the extant works of literature, and also provides practical contributions to the ethical use of disruptive technologies, future workforce, and regulations. However, the study was conducted within certain theoretical, methodological, empirical, and pragmatic conditions, which might constitute particular limitations and constraints. Therefore, the last section of this thesis elucidates and suggests the directions for future research

The regional security puzzle around Afghanistan: bordering practices in Central Asia and beyond

"Western military presence wanes in Afghanistan and a transformed security environment challenges borders and stability in Central Asia. This book examines how the tensions relating to the reorganization of external military presence interact with regional states’ ambitions and challenge the borders already contested by numerous dividing lines. It studies a complex political landscape across which radical Islam connected with international terrorism is feared to spread as the international mission initiated in the wake of the 9/11 attacks winds down. As Western military presence wanes in Afghanistan a transformed security environment challenges borders and stability in Central Asia. In this region former Soviet republics seek to consolidate their position by extending their control over politically problematic borderlands, setting up borders in areas where livelihood connections and transborder communities belie such bounding, and by seeking to maximize the independence of their foreign policies in relation to the integration processes led by Russia. This collection examines how the geopolitical tensions relating to the reorganization of external military presence and the opportunities to gain resources from the region-wide economic cooperation initiated with 'new Silk Roads' ideas interact with regional states' policies and actions. It explains how state borders are challenged by the practices of both non-state agencies and groups of people as well as the policies of extra-regional powers to pursue spaces for defense, resources and influence. Applying pragmatist insights, the contributions discuss the complexity of borders in the region and argue that the predominant role of the state border in all discourse and policies on borders eclipses other border-making practices, and that this limitation of perspectives deepens the security problems in the region's troubled border spaces." (author's abstract

The Regional Security Puzzle around Afghanistan

Western military presence wanes in Afghanistan and a transformed security environment challenges borders and stability in Central Asia. This book examines how the tensions relating to the reorganization of external military presence interact with regional states’ ambitions and challenge the borders already contested by numerous dividing lines. It studies a complex political landscape across which radical Islam connected with international terrorism is feared to spread as the international mission initiated in the wake of the 9/11 attacks winds down

Applications of Blockchain in Business Processes: A Comprehensive Review

Blockchain (BC), as an emerging technology, is revolutionizing Business Process Management (BPM) in multiple ways. The main adoption is to serve as a trusted infrastructure to guarantee the trust of collaborations among multiple partners in trustless environments. Especially, BC enables trust of information by using Distributed Ledger Technology (DLT). With the power of smart contracts, BC enforces the obligations of counterparties that transact in a business process (BP) by programming the contracts as transactions. This paper aims to study the state-of-the-art of BC technologies by (1) exploring its applications in BPM with the focus on how BC provides the trust of BPs in their lifecycles; (2) identifying the relations of BPM as the need and BC as the solution with the assessment towards BPM characteristics; (3) discussing the up-to-date progresses of critical BC in BPM; (4) identifying the challenges and research directions for future advancement in the domain. The main conclusions of our comprehensive review are (1) the study of adopting BC in BPM has attracted a great deal of attention that has been evidenced by a rapidly growing number of relevant articles. (2) The paradigms of BPM over Internet of Things (IoT) have been shifted from persistent to transient, from static to dynamic, and from centralized to decentralized, and new enabling technologies are highly demanded to fulfill some emerging functional requirements (FRs) at the stages of design, configuration, diagnosis, and evaluation of BPs in their lifecycles. (3) BC has been intensively studied and proven as a promising solution to assure the trustiness for both of business processes and their executions in decentralized BPM. (4) Most of the reported BC applications are at their primary stages, future research efforts are needed to meet the technical challenges involved in interoperation, determination of trusted entities, confirmation of time-sensitive execution, and support of irreversibility

Hybrid Differential Software Testing

Differentielles Testen ist ein wichtiger Bestandteil der Qualitätssicherung von Software, mit dem Ziel Testeingaben zu generieren, die Unterschiede im Verhalten der Software deutlich machen. Solche Unterschiede können zwischen zwei Ausführungspfaden (1) in unterschiedlichen Programmversionen, aber auch (2) im selben Programm auftreten. In dem ersten Fall werden unterschiedliche Programmversionen mit der gleichen Eingabe untersucht, während bei dem zweiten Fall das gleiche Programm mit unterschiedlichen Eingaben analysiert wird. Die Regressionsanalyse, die Side-Channel Analyse, das Maximieren der Ausführungskosten eines Programms und die Robustheitsanalyse von Neuralen Netzwerken sind typische Beispiele für differentielle Softwareanalysen. Eine besondere Herausforderung liegt in der effizienten Analyse von mehreren Programmpfaden (auch über mehrere Programmvarianten hinweg). Die existierenden Ansätze sind dabei meist nicht (spezifisch) dafür konstruiert, unterschiedliches Verhalten präzise hervorzurufen oder sind auf einen Teil des Suchraums limitiert. Diese Arbeit führt das Konzept des hybriden differentiellen Software Testens (HyDiff) ein: eine hybride Analysetechnik für die Generierung von Eingaben zur Erkennung von semantischen Unterschieden in Software. HyDiff besteht aus zwei parallel laufenden Komponenten: (1) einem such-basierten Ansatz, der effizient Eingaben generiert und (2) einer systematischen Analyse, die auch komplexes Programmverhalten erreichen kann. Die such-basierte Komponente verwendet Fuzzing geleitet durch differentielle Heuristiken. Die systematische Analyse basiert auf Dynamic Symbolic Execution, das konkrete Eingaben bei der Analyse integrieren kann. HyDiff wird anhand mehrerer Experimente evaluiert, die in spezifischen Anwendungen im Bereich des differentiellen Testens ausgeführt werden. Die Resultate zeigen eine effektive Generierung von Testeingaben durch HyDiff, wobei es sich signifikant besser als die einzelnen Komponenten verhält.Differential software testing is important for software quality assurance as it aims to automatically generate test inputs that reveal behavioral differences in software. The concrete analysis procedure depends on the targeted result: differential testing can reveal divergences between two execution paths (1) of different program versions or (2) within the same program. The first analysis type would execute different program versions with the same input, while the second type would execute the same program with different inputs. Therefore, detecting regression bugs in software evolution, analyzing side-channels in programs, maximizing the execution cost of a program over multiple executions, and evaluating the robustness of neural networks are instances of differential software analysis with the goal to generate diverging executions of program paths. The key challenge of differential software testing is to simultaneously reason about multiple program paths, often across program variants, in an efficient way. Existing work in differential testing is often not (specifically) directed to reveal a different behavior or is limited to a subset of the search space. This PhD thesis proposes the concept of Hybrid Differential Software Testing (HyDiff) as a hybrid analysis technique to generate difference revealing inputs. HyDiff consists of two components that operate in a parallel setup: (1) a search-based technique that inexpensively generates inputs and (2) a systematic exploration technique to also exercise deeper program behaviors. HyDiff’s search-based component uses differential fuzzing directed by differential heuristics. HyDiff’s systematic exploration component is based on differential dynamic symbolic execution that allows to incorporate concrete inputs in its analysis. HyDiff is evaluated experimentally with applications specific for differential testing. The results show that HyDiff is effective in all considered categories and outperforms its components in isolation