research paper on accounting software

• DOI: 10.25046/AJ060195
• Corpus ID: 233280882

Accounting Software in Modern Business

• L. Marushchak , O. Pavlykivska , +2 authors N. Shveda
• Published 1 February 2021
• Business, Computer Science
• Advances in Science, Technology and Engineering Systems Journal

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Recent trends in accounting and information system research: a literature review using textual analysis tools.

1. Introduction

2. literature analysis, 2.1. materials and methods, 2.2. results, 2.2.1. results for the first period (2000 to 2009).

• The dissemination of information via the Internet, such as web reporting, e-commerce models, or web-based business or services (e.g., [ 43 , 44 , 45 , 46 , 47 , 48 ]);
• The use, implementation, and implications of continuous auditing or continuous monitoring (for instance, [ 49 , 50 ]);
• The use or implementation of languages or taxonomies based on Extensible Markup Language (XML) or Extensible Business Reporting Language (XBRL), sometimes also linked to previous themes (e.g., [ 49 , 51 , 52 , 53 ]);
• The implementation of internal control system models in the IT area, such as control objectives for information and related technology (COBIT), the relevance of IT certification, such as WebTrust, and also the topics from the Information Systems Audit and Control Association (ISACA) curricula (for instance, [ 54 , 55 , 56 ]);
• Finally, although less incipient in this period, some studies on the emerging technologies from the beginning of this century, such as neural networks (e.g., [ 57 ]), or business intelligence (e.g., [ 21 ]).
• Accounting : accounting academics, accounting data points, accounting information, accounting knowledge, accounting research productivity, accounting system design, accounting systems research, accounting tasks , database accounting, differentiating accounting systems , financial accounting literature, leading accounting, managerial accounting perspective, quality accounting publication ;
• Audit : audit automation constructs, audit committees, audit documentation, audit engagement risk, audit opinion, audit trail, audit work, auditing education, auditing literature, computer-assisted auditing techniques, continuous audit, current audit environment , specific auditing concerns, various audit domains;
• Business : business clients, business information , business operations, business organizations, business process diagrams , business process level , business process modelling conventions , business world, Canadian business units, everyday business communications, extensible business, strategic business planning, web-based business;
• Control : control group, control objectives, control relationships, designing control systems , external controls, hierarchical control structures , informal controls, internal control, international control guideline, proper control procedures, using control charts;
• Data : accounting data points , data quality , data streams, data warehouses, electronic data interchange, financial data, including data flow diagrams, normal form data structure , numerical data increases, secondary data analysis, site data, specific data, spending data, underlying data trends, unnormalized data structure , using data;
• Decisions : bonus allocation decisions, decision aid research , decision aid use, decision aids, decision facilitation, decision process , investment decisions, management decision models , multiple decision, novice decision makers, operational decisions, repetitive choice decisions, repetitive valuation decisions, user decisions;
• Environment : alternative environments, continuous reporting environment, current audit environment, external environment, manufacturing environments, traditional reporting environment, virtual team environment;
• Individual : individual characteristics, individual decision-makers, individual determinants, individual faculty members, individual faculty productivity, individual level, individual provider attributes, individual units, judging individuals, perceiving individuals;
• Information : accounting information , advanced information technology , business information , computer-supported information systems , corporate reporting information, decision-making information, emerging information needs, emerging information technologies, financial reporting information, financial statement information, future-oriented information, human information processing, important information processing mechanism , information age, information content, information integrity attributes, information load, information location, information requests, information security, information system designs , information systems research , informationally equivalent, inter-organizational information sharing, low information quality seal , management information systems , management information value chain , nonfinancial information, online information, open information sharing, output information, preliminary information, specific information technology , supporting information technology , varied information, vast information source;
• Knowledge : accounting knowledge , additional knowledge, causing knowledge acquisition, expert-like knowledge structures , feedback impacts knowledge acquisition, filtering knowledge, improving knowledge workers, knowledge management focus , knowledge management practices , knowledge management system , procedural knowledge;
• Management : cost management systems, effective management , hybrid manager profile, impression management, knowledge management focus, knowledge management practices, knowledge management system, management decision models, management information systems, management information value chain , senior managers, top management support;
• Model : business process modelling conventions , conceptual model, contingency model, enterprise modelling, er model, management decision models , mathematical model, research model , residual income valuation model, task circumplex model , theoretical model;
• Performance : firm performance, managerial end-user performance , organisational performance, organizational performance, performance evaluation, performance outcomes, subsequent decision-making performance, superior performance, task performance , traditional performance measures;
• Process : assurance process, business process diagrams, business process level, business process modeling conventions , decision process, event process chains, extensive sample selection process, human information processing, important information processing mechanism , little processing, process level risk assessment, processing view, production processes, stable processes, standard development process;
• Quality : data quality , disseminating quality, low information quality seal , quality accounting publication , quality measurement component, quality outlets, quality perspective, service quality, system quality ;
• Research : accounting research productivity , accounting systems research , additional research, ais research, attitudinal ambivalence research, case research, current research work, decision aid research, development research, empirical research, field research, future research, information systems research , little research, past research, previous research, prior research, recent research, research community, research domain, research findings, research hypotheses, research instrument, research issues, research method opportunities, research model , research propositions, research prototype system , research questions, research survey, rich research opportunities, various research methods;
• System: accounting system design, accounting systems research , alternative measurement systems, automated record system, computer-supported information systems, cost management systems , current system, designing control systems, differentiating accounting systems, electronic audit-work paper system , enterprise systems implementation, expert system groups, expert system types, expert system users, information system designs, information systems research, key system components, knowledge management system, management information systems , medical record system, research prototype system , successful system, system acceptance, system acquisition, system design alternatives, system effectiveness , system implementation changes, system integration, system outputs, system quality , system transformation, system usage, systems design scenarios, tertiary assurance system, work systems;
• Task : accounting tasks , brainstorming tasks, complex tasks, decision-making tasks, financial tasks, optimisation tasks, querying tasks, simple tasks, specific design tasks , task accuracy, task characteristics, task circumplex model , task completion, task force, task performance , task requirements, task routineness;
• Technology: advanced information technology, emerging information technologies, emerging technologies, learning technology, specific information technology, supporting information technology, technological advances, technological determinism, technological discourse, technology complexities, technology features, technology fit, technology medium;
• Use: auditor use , continued use, decision aid use, expert system users , user acceptance, user decisions , user requests, user satisfaction, using activity, using control charts , using data , using eighty-nine, using paper methods.

2.2.2. Results for the Second Period (2010 to 2019)

• Continuous auditing or continuous monitoring (e.g., [ 68 , 69 , 70 , 71 , 72 ]);
• Languages or taxonomies based on XML (less expressive) or XBRL, in a more expressive number than those found in the previous period (e.g., [ 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 ]);
• Business intelligence or business analytics (mostly) (e.g., [ 19 , 81 , 82 , 83 ]);
• Artificial intelligence, data analytics, big data treatment, and the use of machine learning and data mining techniques (mostly), which are sometimes associated with previous themes and, in many cases, dedicated to the definition of processes related to the detection of fraud, misreporting or tax evasion (e.g., [ 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 ]);
• Cloud computing (e.g., [ 67 , 93 , 94 , 95 ]);
• Blockchain-based technologies, which are mostly evidenced at the end of this decade (for instance, [ 96 , 97 ]).
• Accounting : 129 accounting students, accounting benefits, accounting domains, accounting information systems academics , accounting information systems field , accounting journals, accounting literature, accounting processes , accounting publications, accounting researchers , accounting standards , annual bank account balances, especially management accounting, firm accounting performance, outsourcing accounting functions ;
• Audit : audit analytics, audit arena, audit fraud brainstorming , audit process , audit standards , audit support systems , audit team, auditing literature, budgeted audit hours, chief audit executives, computer audit specialist, continuous auditing methodology, current audit practice , financial audits, internal audit function , internal auditing department, prior year audit, reduced audit fee increases , small audit firms , traditional audit paradigm ;
• Business : business networks, business operations, business process agility , business process standards , business value research , computing-related business objectives, existing business processes , extensible business, hindering business efforts, intermediate business processes , overall business performance , reporting business information ;
• Control : control compliance, control issues, corrective controls, effective controls, ineffective controls, informal management control systems , internal control deficiencies, internal control environment, internal control overrides, internal control reporting requirements , internal control weakness, internal control weaknesses, it-related controls;
• Data: applying data mining techniques, corporate data, data analysis tool, data patterns, descriptive data mining approach, descriptive data mining strategy, financial data, global data ecosystem, journal entry data sets, out-of-sample data, panel data, perceptive field survey data, precise data values, prediction data mining techniques, process-level data, procurement data, proprietary data, quantitative data, researching journal entry data mining, semi-monthly data, soft copy data, tagged data, using data;
• Decisions : compared decisions, deception detection decision aid, decision aid reliability, decision aid reliance behavior, decision aids, decision problems, decision processes , decision trees, experimental decision aid research spans , governance decision making , optimal decision, outsourcing decision, reliance decision;
• Disclosure : cybersecurity disclosure guidance , cybersecurity risk disclosure , disclosure credibility, disclosure role, environmental disclosures, extensive disclosure, financial statement disclosures , improving disclosure timeliness, issuing video disclosures, unauthorized disclosure;
• Effective : brainstorming effectiveness, compromising regulation effectiveness, detrimental effect, differential effect, effective controls , halo effect, information environment effects , interactive effect, mean effects, positive effect, profound effect;
• Firm : aggregate firm level, appointing firms, durable goods industry firms, firm accounting performance , firm productivity, firm profitability, firm value , firm years, registered firms, small audit firms , superior firm performance , threatened firms;
• Function : bi-planning functionality, bi-reporting functionality , incompatible functions, internal audit function , outsourcing accounting functions;
• Information: accounting information systems academics, accounting information systems field, bank trading information systems , capturing context information, chief information officer, deceptive information, detail-tagged footnote information, financial reporting information, health information technology expenses , information asymmetry, information environment effects, information quality , information release, information security risk management, information systems professionals, information systems researchers, information technology literature, information technology outsourcing , integrating information, performance measurement information , qualitative information, recent high-profile information security breach incidents, reporting business information, risk information increases , supplemental information displays, ™ information processing costs, user satisfaction measure information system success, using information ;
• Management : bank management, cloud management committee, entail managers, environmental management approach, especially management accounting, informal management control systems, information security risk management , management assertions, management support, managing expectations, resource management;
• Measures : measuring spreadsheet infusion, perceptual measures, performance measurement capabilities, performance measurement information, quality measures , quantitative measure, strategic performance measurement system , subjective measures, user satisfaction measure information system success ;
• Performance : average performance, firm accounting performance, firm-level performance , future performance goals, internal process-level performance , organizational performance, overall business performance, performance measurement capabilities, performance measurement information, strategic performance measurement system, superior firm performance , supply chain performance;
• Process: accounting processes, assurance process, audit process, business process agility, business process standards , close process, decision processes , estimation process, existing business processes , implementation processes, intermediate business processes , labor process, manual process, natural language processing, order fulfilment processes, process efficiency, process level, strategic erm processes, ™ information processing costs , work processes;
• Reporting : annual reports, digital reporting, discretionary reporting, financial reporting information, financial reporting systems, internal control reporting requirements , internet reporting, reporting business information , reporting language, reporting timeliness, required reporting deadlines, standard reports, traditional business-to-government reporting ;
• Research : artificial intelligence research, broad research streams, business value research , collaborative design research, experimental decision aid research spans , expert systems research , future research, multi-method research, potential research, prior research, research discipline, research environments, research methodology, research perspectives, research program, research quality , research settings , researching journal entry data mining , right research, traditional research classification ;
• System : 43 expert systems, accounting information systems academics, accounting information systems field , accounting-related expert systems papers, audit support systems , automated systems, bank trading information systems , computer-mediated communication system, decision-aid system , enterprise resource planning systems adoption, enterprise systems results, expert system publications, expert systems research, financial reporting systems, incentive systems, informal management control systems, information systems professionals, information systems researchers , manual systems, restrictive systems, strategic performance measurement system, system quality , transparent system, user satisfaction measure information system success ;
• Technological: health information technology expenses, information technology literature, information technology outsourcing , supporting technologies, technological competence , technological domain, technological solutions, technology dominance;
• Using : emergent use, managerial use, media use, practice use , spreadsheet use, user satisfaction measure information system success, using activity theory, using data , using a hospital, using information , using responses.

2.2.3. Results for the Latest Period (2020 to 2022)

• Accounting : 136 accounting professionals, accounting context, accounting data, accounting fraud data mining literature, accounting fraud detection models, accounting information systems case study, accounting information systems scholars, accounting literature , aggregated accounting numbers, cloud-based client accounting, developing accounting information systems , different accounting standards, highest-ranked accounting journals, laggard accounting systems, management accounting , professional accounting bodies, recent accounting fraud theory, robust account;
• Audit : 4 audit firms , asset-related audits, audit conclusions, audit fee premiums, audit framework, audit hours, audit personnel, audit practice, audited entity, auditing parties, auditing profession, computer-assisted audit tools, contemporary audit standards, continuous audit procedures, cybersecurity audit effectiveness , digital audit evidence, financial statement audits, improving audit quality , increasing audit productivity, internal control audit work , manual audit procedures, recurring audit deficiencies, relevant audit standards, reliable audit evidence;
• Business : business digitization, business information technology intensity , business model transformation indices, business operations, business processes , business professionals, business rules, general business descriptions, increasing business competition, strategic business partner role;
• Case : accounting information systems case study, compelling use case, in-depth case study, participatory case study, specific case, various use cases;
• Cybersecurity : 52 cybersecurity comment letters, cybersecurity audit effectiveness , cybersecurity breach incidents, cybersecurity incidents, cybersecurity risk disclosure practices , cybersecurity risk disclosure trends , organizational cybersecurity risk exposure, overall cybersecurity risks, proprietary cybersecurity information , regarding cybersecurity;
• Data : accounting data , accounting fraud data mining literature , available data, big data capabilities, big data technologies , climate data, collected data, data analytics, data breach, data processing integrity , data quality research , data standards, data visualization software, financial data, general ledger data, interactive data visualization, interview data, legal-entity data segmentation, novel data analysis technique, novel data mining technique, real-life data, social media data, textual data, unstructured data, using data ;
• Disclosures : corporate disclosures, cryptocurrency disclosures, cybersecurity risk disclosure practices , cybersecurity risk disclosure trends , disclosure location, firm disclosures , remediation disclosures;
• Firms : 4 audit firms , adopting firm, firm disclosures , firm resource, firm samples, firm size, firm tenure, incentivizing client firms, Korean-listed firms;
• Information: accounting information systems, accounting information systems case study, accounting information systems scholars, agricultural information systems , budget information, business information technology intensity , clarifying information, developing accounting information systems , existing information systems, information content, information dissemination, information overload, information processing capabilities, information quality, information systems discipline, information systems theories, information technology experts, integrated information systems, personal information management capabilities , private information, proprietary cybersecurity information , qualitative information, quantitative information, social responsibility information, specific value information, text information;
• Literature : accounting fraud data mining literature , accounting literature , current literature, existing literature, extensive literature review, natural language processing literature , prior literature, research literature, systematic literature review;
• Management: cyber risk management effectiveness, cyber risk management maturity, knowledge management research, management accountants, management accounting, management reporting , personal information management capabilities, supply chain management, top management commitment, top management support, workflow management;
• Model : accounting fraud detection models , business model transformation indices , developed models, digital maturity model, filed model, force field model , model performance, predictive models, proposed model, research model, theoretical model, wave theory life cycle model ;
• Reporting : financial reporting, management reporting , report length, social responsibility reports, unique reporting requirements;
• Research : answering research questions, data quality research , design science research contribution, empirical research, extending research, future research, knowledge management research , prior research, recent research, research initiative, research literature , research model , research studies;
• Risk: cyber risk management effectiveness, cyber risk management maturity, cybersecurity risk disclosure practices, cybersecurity risk disclosure trends, organizational cybersecurity risk exposure, overall cybersecurity risks , regulation risks, risk assessment;
• Service : assurance services, consumer services, payment services, service components, service quality , shared service mode;
• Study: accounting information systems case study , cross-sectional field study, existing studies, in-depth case study , longitudinal study, multi-case study approach, participatory case study, research studies ;
• System: accounting information systems, accounting information systems case study, accounting information systems scholars, agricultural information systems, developing accounting information systems, enterprise resource planning system design agenda, existing information systems, information systems discipline, information systems theories, integrated information systems, intelligent systems, laggard accounting systems, system quality, system usage;
• Technology : above-mentioned technologies, big data technologies, blockchain technology applications, blockchain technology solutions, business information technology intensity , computer technology, emerging technology adoption, information technology experts , learning technologies, ledger technology, past technology experience, technological advancements, technological developments, trending technology;
• Use : compelling use case , cost-effective use , decision-making use, effective use , organizational use, user satisfaction, using data , using DevOps, using propensity score, various use cases .
• A more diversified set of subtopics within the topics found;
• The increasing relevance of matters regarding social responsibility, climate, and budgetary information;
• A more evident link, from the subtopics, identified, between accounting and other social sciences through the consideration or inclusion of a wide-ranging of explanatory factors, such as “individual factors”, “environmental factors”, “organizational complexity factors”, “psychological factors”, and “social-psychological factors”;
• A diverse set of underlying theories and research methods used, particularly those focusing on case and experimental studies, as well as literature reviews (for this reason, “case”, “study”, and “literature” appears as novelties within the most relevant topics, besides those previously found, such as “research” and “model”);
• Besides general references to “emergent technologies” or “trending technologies”, the most significant number of indications on specific uses of those tools as precise topics or subtopics, for instance, “blockchain”, “crypto assets” or “cryptocurrencies”, “intelligent systems”, “cloud-based accounting”, “big data”, “data analytics”, “data mining, “learning technologies”, and “natural language”;
• “Risk”, “cybersecurity” and “tax” are included in the set of main topics, which demonstrates the growing relevance of those topics (the latter as a particular novelty for this period).

3. Discussion

3.1. research limitations, 3.2. future avenues in accounting and information system research, author contributions, data availability statement, conflicts of interest.

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Albuquerque, F.; Dos Santos, P.G. Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools. FinTech 2023 , 2 , 248-274. https://doi.org/10.3390/fintech2020015

Albuquerque F, Dos Santos PG. Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools. FinTech . 2023; 2(2):248-274. https://doi.org/10.3390/fintech2020015

Albuquerque, Fábio, and Paula Gomes Dos Santos. 2023. "Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools" FinTech 2, no. 2: 248-274. https://doi.org/10.3390/fintech2020015

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Impact of Accounting Software for Business Performance

Imperial Journal of Interdisciplinary Research (IJIR) Vol-3, Issue-5, 2017 ISSN: 2454-1362

6 Pages Posted: 14 Mar 2018

Mihiri Wickramasinghe

Rajarata university of sri lanka - faculty of management studies.

Rajarata University of Sri Lanka - Department of Business Management

N. H. K. Cooray

Sulochana dissanayake.

Date Written: 2017

The major problematic source towards the organizations and corporates is the accounting field by the way its intended users need to clarify the accounting softwares which are suitable on the basis of their day today accounting and business needs. Mainly the fact in Anuradhapura area is the incomplete records and unauthorized access of data by unsuitable accounting packages and apps. The fundamental error occurring in all kind of working environment and organizations are not finding the correct solution toward accounting and decision making by the selection of main accounting packages and apps. The key course of action is how to choose accounting software and apps by the businesses in Anuradhapura area. Which influence in decision making process.

Keywords: accounting, business, performance

Suggested Citation: Suggested Citation

Mihiri Wickramasinghe (Contact Author)

Rajarata university of sri lanka - faculty of management studies ( email ).

Mihintale, 10300 Sri Lanka

Pemarathna RMMD

Rajarata university of sri lanka - department of business management ( email ).

Mihintale Sri Lanka

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• Open access
• Published: 04 April 2023

Digitalisation in accounting: a systematic literature review of activities and implications for competences

• Julia Pargmann   ORCID: orcid.org/0000-0003-3616-0172 1 ,
• Elisabeth Riebenbauer 2 ,
• Doreen Flick-Holtsch 3 &
• Florian Berding 1  

Empirical Research in Vocational Education and Training volume  15 , Article number:  1 ( 2023 ) Cite this article

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The digitalisation of processes is a current topic in accounting. New technologies can change activities which in turn may require different skills from accounting graduates. This paper aims to shed light on the changes that digitalisation brings about in various areas of accounting by assessing the types of activities (non-routine and routine) and corresponding competences in the context of progressing stages of digitalisation. In addition, it is analysed how different technologies are used in these activities and where their execution is placed within the supply chain. The systematic literature review shows a lack of expertise in the field of digitalisation that enables graduates and employees to successfully manage respective processes in the workplace. While routine activities are continuously being automated or digitalised, non-routine activities and the corresponding skills have a similarly increasing importance for employees in accounting as the acquisition of general digital competences.

Introduction

In the context of digitalisation, it is part of everyday life for customers to purchase products and services with the aid of an application online and in physical stores. The streams of products and finances within and between companies are also highly interconnected when they are based on digitalised processes (Appelfeller and Feldmann 2018 ). Digitalisation thus encompasses the entire supply chain of a product or service. Accounting is one area of the company that documents these processes with customers and other companies, enables these processes, supports them technically, and connects them with internal and external interfaces (Bleiber 2019 ; Klein and Küst 2020 ). In this context, companies nowadays face the challenge to make decisions on the introduction of new technologies and digitalised business processes into the area of accounting, among others (Appelfeller and Feldmann 2018 ). Digitalisation can address various stages, from substitution (e.g., self-check-out counters in retail shops) to business process innovation (e.g. automated storage and payment with RFID chips; see for these examples e.g. Litfin and Wolfram 2010 ). It is expected that not only costs and productivity are essential decision criteria for the introduction of technologies and digitalised business processes (Ashoka et al. 2019 ; Chen et al. 2012 ) but also the extent to which employees can master and employ technologies and possess the competence to fulfil new or evolving tasks (Aepli et al. 2017 ; Bonin et al. 2015; Cong et al. 2018 ; Egle and Keimer 2017; Seeber and Seifried 2019 ).

In this context, it is necessary to describe how digitalisation affects the requirement profile regarding the competences of employees in accounting. On the general level, the concept of competence is discussed in many ways and often focused on mastering domain-specific tasks and requirements (Hartig et al. 2008 ; Weinert 2001 ). The types of activities themselves range from manual routine tasks (e.g. paper-based bookkeeping) to interactive activities (e.g. solving problems with automated digital bookkeeping) (Seeber et al. 2019 ; Seeber and Seifried 2019 ). Hence, in order to learn more about relevant competences in accounting in a digitalised world, we have to analyse the different tasks and actual accounting activities that result in changing competence requirements as a basis. There are insightful studies available that analyse changes and developments of domain-specific requirements and competences as well as types of activities in the context of digitalisation (Aepli et al. 2017 ; Iten et al. 2016 ; Sachs et al. 2016 ; Seeber et al. 2019 ). However, rather little information is offered by these reports when it comes to accounting and its specific activities as well as technologies as tools for these activities. Thus, we assume that knowledge about these (new) activities in accounting and the corresponding digital technologies provide a good starting point to infer possible changes in necessary competences for acting in professional situations. Thus, our research questions are:

RQ1:Which activities are concerned with digitalisation in which areas of accounting?

RQ2:How do accounting activities differ in their respective stages of digitalisation?

RQ3:Where are these activities placed within the supply chain?

RQ4:Which technologies are used to perform these activities?

RQ5:Which advantages and disadvantages are connected to these activities?

The results aim to provoke further curricular and didactic discussions about learning and teaching accounting in vocational education and training on the one hand and higher education on the other.

Starting from a specification of digitalisation along its stages and types of activities, we explain in the following the approach for the systematic analysis based on a review of relevant literature. To actually gain insight into concrete developments of activities in accounting, we provide a systematic overview of the types of activities and the stages of digitalisation. Moreover, we consider the specific stages of digitalisation in combination with the different types of activities, as we expect differences between certain types of activities (e.g. interactive activities) and specific stages of digitalisation (e.g. innovation). In modern accounting, technologies are the main set of tools accountants use to execute their tasks, much like the tools of a craft. When technologies change, so do activities. Therefore, technologies need to be considered in this review as well. In addition, the placement of activities within the supply chain is included, as different departments require different competences and develop different digitalisation projects since the stakeholders differ. Furthermore, the advantages and disadvantages of digitalisation are to be surveyed since they offer insights why activities are digitalized.

In the German-speaking countries, one’s ability to follow an occupation successfully is described by the concept of vocational action competence. Established competence frameworks usually differentiate between professional, social, and self-competences as major dimensions with methodological and technological competences anchored horizontally across all major dimensions. To decide which competences are needed for which occupation, activities are analysed that allow these competences to be fostered. Thus, it is relevant to analyse activities in accounting to derive necessary changes in curricula. Our research systematises digitalised activities that we employ to draw conclusions for the competence development of future accountants.

Framework for categorising digitalisation and types of activities

When discussing the consequences of digitalisation for accounting activities, at least two aspects must be considered in depth: first, the specific stages of digitalisation and, second, the types of activities.

Figure  1 shows an overview of three different stages of digitalisation in the context of accounting, each of which is disruptive to a different degree for activities and thus competences (Bleiber 2019 ; Hübl 2020 ): substitution , process change, and innovation . While in stage 1 analogue data or activities are substituted by digital ones, new technologies lead to changes in processes in stage 2. Stage 3 addresses innovation, both processes and their respective outcomes are changed.

Stages of digitalisation in accounting

An insightful framework of digitalised activities is suggested by Aepli et al. ( 2017 ), who adopted the classification from Spitz‐Oener ( 2006 ) and validated it in expert interviews. The framework was chosen because digitalisation is more likely to change activities in a profession rather than erase it in their entirety (Aepli et al. 2017 ; Arntz et al. 2016 ; Autor 2015 ; Seeber and Seifried 2019 ; World Economic Forum 2018). In addition, some activities are more prone to digitalisation than others.

Table 1 illustrates this approach using types of activities (left column) which are intended to provide deeper insight into the facets of potentially digitalised activities with generic examples (middle column) and specific accounting-related examples (right column).

Based on Dengler et al. (2014), we suggest to include automated routine activities, even though they are not performed by professionals (e.g. the automatic import of outgoing invoices from invoicing to accounting). Due to the increasing number of automated workflows in accounting, this adaptation provides the ability to better record and illustrate these changes as they reflect all activities that take place in the different areas of accounting. Thus, the six types of activities provide a comprehensive and differentiated range of activities. This categorization of activities will serve as a framework for our literature review in order to establish comparability and transferability to other (commercial) fields and professions as well.

Research design and methodology

A systematic literature review was conducted to find out how the accounting activities of future accounting professionals have changed due to digitalisation. The four-step process (Fig.  2 ) started with (1) the definition of up to fourteen keyword groups consisting of technical search terms in both English and German, which for example include “computer-assisted,” “data processing,” “technological speed of change,” “digitalisation rate,” “ERP,” “enterprise-resource-planning,” “accounting software,” “OCR,” “optical character recognition,” “big data,” “blockchain,” or “process mining.” Since the choice of keywords directly impacts the search hits, we used four strategies to ensure that we were able to use as many relevant terms as possible: (a) We conversed with an accounting professor about trends and current developments regarding digitalisation in the field, (b) we scoped the databases that we used for our full search and analysed the most frequently occurring trends and technologies, (c) we analysed accounting curricula from vocational education and higher education institutions to adjust our concepts of different competence frameworks, and (d) we used a synopsis from different curricula and textbooks to systematise activities. The keywords were grouped because of technical limitations regarding the valid number of connectors, particularly in Google Scholar. To ensure comparability between databases, we used these groups throughout our search.

Flow chart of research design

After the definition of suitable terms, (2) a search was performed in the Google Scholar , ERIC , EBSCO, and Web of Science databases and complemented by specific relevant international journals (“Journal of Accounting Education,” “Journal of Emerging Technologies in Accounting,” “Journal of Information Systems”) which were chosen due to their topicality regarding the research questions. They were selected based on their impact and the number of search hits. Due to the increasing speed of digitalisation, the period between 2000 and 2020 was selected. In the later stages of the study, the research group also decided to include a 2021 article due to its topical suitability.

While performing the content analysis, we applied a strategy that limited the number of hits. Only the first 30 pages of search hits for each keyword group were scoped for relevance. This was necessary because of the broad scope of the search terms. This specific cut-off point was chosen because, in a preliminary scope, the number of potentially useful search hits declined drastically. On average, no more (potentially) relevant hits were identified after 29 to 30 pages, thus setting this number for the full search as well. This process yielded a total of 9,553 potentially relevant hits across all media. A scan of both titles and abstracts resulted in (3) a total of 190 potentially suitable sources of which 72 articles proved relevant to the research questions. Irrelevant publications either referred only to accounting or digitalisation, were purely didactic, or had a general IT-orientation without an accounting focus. If the relevance could not be decided, the full text was scanned for the connection between accounting and digitalisation. The last step (4) was the content analysis. A total of 70 articles were retrievable and thus used in the coding process. The coding manual was developed and completed with appropriate anchor examples to illustrate the variety of possible accounting activities and to align our general understanding of the categories. The coding ensued in pairs to promote discussion.

Analytical framework

The coding tree (Fig.  3 ) consists of (a) publication information, (b) the publication’s main foci and (c) types of activities (automated, manual and cognitive routine activities, manual and analytical and interactive non-routine activities) in different areas of accounting (financial accounting, controlling, balancing, financial forecasting, managerial accounting, ‘other’). Moreover, the coding tree included (d) respective digitalisation stages of the activity (substitution, process change, innovation) as well as (e) advantages and disadvantages of digitalisation in context of the activities (e.g. financial and time-specific aspects, complexity, required expertise, transparency, data protection).

Coding tree with sample sub-categories

As a starting point, a few base publications were chosen to be scanned for relevant aspects regarding the research questions. From these notes and discussions, the coding tree was further developed and adapted after the first publications were coded. Advantages and disadvantages were developed inductively while doing the first base coding. The framework was developed further by using the basic principles of content analysis (Kuckartz 2018 ).

In the course of a special coding training, the final coding tree in the software MaxQDA was then distributed to two coding teams (three and two people each) along with the coding manual (Fig.  4 ). The sub-categories in the main category “Activities in Accounting” were further distinguished according to the aforementioned types of activities (Table 1 ), reaching from automated routine to interactive non-routine activities (Fig.  9 ). This more detailed structure allowed interpretations about the manners in which activities might have changed due to digitalisation.

Overview of the coding manual for accounting activities

To help the coding process, anchor examples were selected for all categories. As this paper is centred around activities, we are going to illustrate this process for the activity-related categories. For example, an automatic activity in accounting is characterised by a fully automated workflow like an automated deduction of worst-case scenarios with algorithms. A manual routine task does not require cognitive activation as its execution is part of the employee’s regular working routine, for example sorting accounting documents by date or verifying by hand if the positions on an invoice are complete and filled in correctly by the software. In contrast to this, a cognitive routine activity is constituted by a cognitive activation as it would be needed for manual corrections in bookkeeping or the adjustment of false journal entries. An analytical non-routine task could, for example, be the preparation and analysis of various financial statements, while manual non-routine activities encompass all tasks that are not part of everyday tasks, like solving technical problems or handling issues regarding hardware maintenance. Lastly, interactive non-routine tasks require a communicative element, like onboarding processes in the division or consultation with management. Thus, there are different levels of activities that need further specification and presumably undergo different changes through digitalisation.

To identify the extent of changes in the field, activities were assigned to a digitalisation stage. Hence, we applied the three aforementioned stages of digitalisation based on Bleiber ( 2019 ) and Hübl ( 2020 ) to identify the scope of changes in accounting: substitution , process change, and innovation (Fig.  1 ).

Stage 1, substitution, is completed whenever analogue data or activities are exchanged for automated or digital ones. Neither process nor output is changed, however. This stage applies to activities using, for example, OCR or robotic process automation (RPA) or whenever the publication implies that a manual activity was exchanged for automation.

In stage 2, process change, workflows, and processes are altered by the use of technology while the output of the process remains the same. This stage applies to all activities that use improved RPA technologies as well as process optimising or mining tools, such as partially automated bookkeeping.

Stage 3, innovation, implies that both processes and their respective outputs are transformed through the use of technology, like artificial intelligence (AI), (deep) learning systems, machine learning, and neural networks. An example of this stage is a fully autonomous bookkeeping workflow.

Bibliographic information and main foci of publications

The majority of publications are in German (n = 51) and in English (n = 19). The dominance of German publications occurred due to the exclusion criteria. In our original set of 190 possibly relevant publications (Fig.  2 ), the distribution was fairly balanced with 98 publications in German and 92 in English. However, we excluded those publications which dealt with IT in a general manner (missing a direct link to accounting) and those which focused on other aspects of accounting but did not explicitly mention accounting activities. Most of these publications were in English, hence the large difference in the final data set. While most publications are either book chapters (n = 22) or journal articles (n = 21), whitepapers (n = 17), books (n = 5), and university publications (n = 5) constitute the minority. Looking at the year of publication, most sources were published between 2015 and 2020 (Fig.  5 ), fewer sources between 2000 and 2005. This rapid increase in publications indicates that digitalisation in accounting has gained popularity within the past five years and is now a leading topic in accounting publications.

Bibliographic information (year of publication, kind of publication and language of publication

The sub-categories in “main focus” could be coded multiple times within the same publication. Besides the technologies and software systems in use, the two most frequently mentioned aspects regarding the main foci are developments in accounting/accounting 4.0 (n = 144) and implications for accounting education (n = 108), a category that describes possible changes in the configuration of activities. (Fig.  6 ). These two categories are future-oriented and involve both the (technical) developments and the industry’s dynamic requirements for accounting graduates and implications for education.

Main foci of publications (number of codes, multiple codes per paper possible)

Regarding the developments in accounting , authors primarily describe processes that are improved and standardised to maximise productivity and the accountant’s value to the company (Baier 2019 ; Müller and Reichmann 2010 ). Especially technologies like advanced analytics and RPA are becoming increasingly important in accounting 4.0 (Egle et al. 2020 ; Koch 2017 ; Losbichler and Gänßlen 2018 ; Satzger et al. 2018 ).

Special aspects that were not mentioned in an educational context, such as the related legal requirements (n = 75) or the generally increasing data availability (n = 39), are shown in separate categories. Several publications also deal with the concrete implementation and procedure of electronic invoices (n = 34). The categories definition of automation (n = 4) and definition of digitalisation (n = 8) are mentioned the least frequently.

RQ 1: Activities concerned with digitalisation in the different areas of accounting

Areas and types of activities in accounting.

A total of n = 285 activities are distributed across six accounting areas including “other” activities (Fig.  7 ). Most frequently mentioned are activities concerning financial accounting (n = 131) and controlling (n = 103). In contrast, all other divisions together make up roughly 25% of the activities described in the publications. The financial accounting code is given to all activities that are rooted in the accounts payable, accounts receivable, banking, payroll, and asset accounting areas (Fig.  8 ). The activities in the area of financial accounting are dominated by accounts payable accounting (n = 98). Many publications focus on e-invoicing, a technology employed to increase productivity in both accounts payable and accounts receivable accounting , the second most mentioned sub-division (n = 23). In addition, OCR and RPA technologies are often used to increase efficiency in both divisions.

Areas of activities in accounting divisions

Areas of activities in financial accounting sub-divisions

The second most frequently mentioned category regarding activities, controlling, mainly encompasses aspects such as reporting, communication, and interpretation of data (Bär et al. 2019 ; Egle and Keimer 2017; Heupel and Lange 2019 ). In contrast to financial accounting, the category of controlling does not focus as much on technologies but rather on specific changes in the job profile (Becker et al. 2020 ; Losbichler and Gänßlen 2018 ; Schindera et al. 2018 ).

The types of activities in the different areas of accounting (Fig.  9 A) are differentiated by their mean of action. More specifically, Fig.  9 A describes what kinds of activities typically occur in the different areas of accounting according to our analyses. In Fig.  9 , those numbers are given as relative numbers because a publication had sometimes multiple codes of the same activity. To account for these duplicates and to maintain proportions, the absolute frequencies are divided by the respective totals per sub-category. As an example, the category financial accounting is mentioned 131 times of which 58 mentions are for automatic activities. Thus, there are automatic activities without manual dimensions and others that are routine activities (manual and cognitive) and non-routine activities (manual, interactive and analytical).

A – C Types of activities in different accounting areas

In the area of financial accounting, most reported activities are either automatic or manual routine activities. Automatic activities are mentioned frequently, for example the automatic recognition of invoices via RPA or their generation directly from the ERP system, although a fully automated process is not common practice yet (Appelfeller and Feldmann 2018 ; Jordanski 2020 ; Kreher 2021 ; Schömburg and Breitner 2010 ; Tanner 2016 ). Instead, some parts of the process are automated and some remain manual. This explains the ratio of manual routine activities, as publications often address the manual correction or computation of invoices (Bernius and Kreuzer 2014 ; Koch 2017 ; Menges 2012 ; Wilczek 2014 ). Other areas of accounting like balancing or controlling display a similar amount of automatic activities that primarily include the use of AI in balancing (Kink 2007 ; Le Guyader 2020 ). Another aspect is the automated detection of variances and automated reporting through machine learning in controlling (Alexander et al. 2019 ; Ashoka et al. 2019 ; Jonen 2020 ). In contrast to publications that focus on financial accounting, authors who address managerial accounting topics identify a high proportion of analytical non-routine activities that primarily include the use of RPA to distribute reports and allocate resources which then have to be analysed by human employees (Langmann and Turi 2020 ).

RQ 2: Accounting activities in different stages of digitalisation

The codes regarding areas of activities in accounting alone, however, do not provide any information regarding the quality of the activities or the respective stages of digitalisation that were presented earlier in this paper. To formulate statements about the quality of accounting activities, it is necessary to analyse the stage of digitalisation and the respective frequencies in publications (Fig.  9 B–C).

Stages of digitalisation in the different areas of accounting

Regarding the stages of digitalisation, the first stage (substitution) is assigned the most across all accounting divisions (Fig.  9 B). Especially activities that remain in the first stage of substitution are attributed to financial accounting. In contrast to this area of accounting, both financial forecasting and managerial accounting areas show a larger proportion of digitalisation that has progressed to stages 2 and 3, process change and innovation. As to managerial accounting, this extends to the integration of a controlling software that introduces innovations in processes in the respective divisions and the implementation of new processes (Kink 2007 ; Raschig and Schulze 2020 ; Selb 2020 ). In financial forecasting, most processes are still in the substitution stage (Klein and Küst 2020 ), but some have progressed to integrate process change or innovation, such as the software-based analysis of reporting data for a proactive controlling approach as shorter product lifecycles necessitate shorter planning horizons (Kink 2007 ; Sledgianowski et al. 2017 ).

Stages of digitalisation in the different activities

In extent to the types of activities (Fig.  9 C), most routine tasks (see Table 1 for these categories) are still mainly in the substitution stage. For instance, RPA technologies are used regularly to substitute manual with automated processes (Gadatsch 2020 ) or electronic invoicing is integrated (Jordanski 2020 ; Klein and Küst 2020 ; Pagel 2019 ; Schömburg and Breitner 2010 ). Approximately one third of automated activities are in the stage 2 of process change, for example when the invoicing process is adapted to a digital format for both incoming and outgoing transactions (Kreher 2021 ).

For non-routine activities , the trend is mostly different. Interactive non-routine activities consist of a larger proportion of stage 2 digitalisation. Those process changes established in the publications include vendor inquiries through automated online portals (Binkow 2015 ) or the supervision of RPA systems or AI algorithms (Hmyzo and Muzzu 2020 ; Klein and Küst 2020 ). Processes need to be standardised to allocate controllers more resources to handle more detailed analyses, interpretations, and communications of results and to minimise their routine activities (Keimer and Egle 2020 ). Schindera et al. ( 2018 ) express that, while the chief financial officer slowly transforms into a chief performance officer, employees in the controlling division are confronted with a changing of roles, too—into that of a business partner. This change is conditioned by the use of big data analytics. Thus, analytical non-routine activities gain in importance. Across the areas of accounting, there is a connection between the kind of activity and its respective stage of digitalisation that has not yet been quantified. While the majority of automatic and routine activities remain in stage 1 digitalisation, interactive non-routine activities predominantly are assigned to stage 2. This finding can be explained by the successful implementation of software solutions and technologies such as AI leading to more activities involving it in the second stage (Chen et al. 2012 ; Heupel and Lange 2019 ; Le Guyader 2020 ; Losbichler and Gänßlen 2018 ).

Analytical non-routine activities, however, show a contrasting result with most activities in stage 1 as employees need to make manual corrections (Jordanski 2020 ). Thus, a human component is required in most processes. However, technologies such as blockchain or AI provide the chance to increase the stage of digitalisation in the future (Chen et al. 2012 ; Grönke and Heimel 2015 ; Trachsel and Bitterli 2020 ). In contrast to manual routine activities (e.g. e-invoicing), the integration of software solutions for analytical non-routine activities requires more resources, hence the lower threshold (Arbeitskreis Externe Unternehmensrechnung der Schmalenbach-Gesellschaft für Betriebswirtschaft e. V. 2018 ; Egle et al. 2020 ; Pagel 2019 ; Weiber et al. 2002 ).

RQ 3: Placement of activities within the supply chain

Different types of the described activities in different accounting areas can be established and interlinked within a company with the aid of interfaces (Fig.  10 ). Within a single company, there can be a multitude of interfaces across divisions and along the supply chain. These interfaces are often connected to the activities, for example internal and external financial accounting, which process inbound and outbound invoices or to the procurement division that interacts with vendors. Most papers address one or more relevant interfaces. Most frequently mentioned are internal interfaces (n = 46), especially regarding the adaptation of accounting and controlling division structures to new business processes or ERP implementation (Binkow 2015 ; Gadatsch 2020 ; Heupel and Lange 2019 ; Najderek 2020 ; Suden 2010 ). The rising focus on process management to increase productivity is depicted in the interfaces; more extensive cooperation between financial divisions due to cross-sectional processes gains in importance (Arbeitskreis Externe Unternehmensrechnung der Schmalenbach-Gesellschaft für Betriebswirtschaft e. V. 2018 ; Bayerl et al. 2020 ). A functioning flow of information and close cooperation between divisions can aid the success of digitalisation projects. Implementing standardised software across the company is identified as a suitable approach to minimise interface issues (Becker et al. 2020 ; Gadatsch 2020 ; Hecht and Scherrer 2020 ).

Interfaces (placement of activities within the supply chain) addressed in the publications

Interfaces with vendors (n = 29) or customers (n = 31) are also mentioned. The main context of vendor interfaces lies in the dimension of electronic invoicing and the conditions for successful implementation as well as specific processes (Appelfeller and Feldmann 2018 ; Klein and Küst 2020 ; Menges 2012 ; Najderek 2020 ; Pagel 2019 ; Suden 2010 ; Tanner 2016 ). It is necessary to harmonise the vendor’s system requirements with the company’s system requirements (Tanner 2016 ). Sometimes, companies establish a supplier self-service that enables the vendors to manage processes such as invoicing or the placement of orders within the company’s interface (Appelfeller and Feldmann 2018 ). At the same time, interfaces with customers are mostly focused on improving their experience by distributing invoices digitally or implementing customer self-service (e.g. checkout via smartphone), thus optimising the company’s commodity, liquidity, or information flows (Appelfeller and Feldmann 2018 ; Binkow 2015 ; Cong et al. 2018 ; Egle and Keimer 2017; Jonen 2020 ; Klein and Küst 2020 ; Nagel 2018 ).

RQ 4: Technologies used to perform the accounting activities

Most publications address one or more technologies in the context of accounting (Fig.  11 ). The specific technologies mentioned most frequently are big data analytics (n = 32), RPA (n = 26) and AI (n = 26). Process mining, which allows companies to analyse their processes through digital technology, is mentioned least frequently (n = 8). This result supports the perception of those technologies as the main disruptors in the industry. Other technologies are mentioned in 44 publications. These are mostly generalised statements that refer to basic technologies and software like ERP systems or technology that can be used to process e-invoices (Gadatsch 2020 ; Koch 2017 ; Schindera et al. 2018 ; Schömburg and Breitner 2010 ; Tanner and Wölfle 2005 ; Wilczek 2014 ).

Frequency of mentioned technologies

Ashoka et al. ( 2019 ) suggest that the use of AI in accounting will free up employees’ time capacities and reduce repetitive activities. They also predict a shift towards internet-based reporting. Egle and Keimer (2017) add that the number of repetitive activities will likely be reduced through AI and big data analytic tools, primarily by minimising the number of manual decisions accountants and auditors have to make in their routine activities. These internal factors are supplemented by external aspects that address the customer journey. Especially, AI is used to improve the customer experience (Appelfeller and Feldmann 2018 ; Bayerl et al. 2020 ; Egle et al. 2020 ). In addition, big data is often mentioned in the context of customers (Gadatsch 2020 ; Losbichler and Gänßlen 2018 ; Schindera et al. 2018 ). Yet, certain advantages for other areas of accounting are made visible as analysis tools may aid, for example, auditors in data management or controllers in forecasting (Pan and Seow 2016 ). This may be the first indication of a shift in the scope of activities in accounting and controlling towards increasing digitalisation.

Especially, repetitive and physical activities such as monthly reporting or e-invoicing profit from the implementation of RPA (Bowles et al. 2020 ; Sandner et al. 2020 ). However, controlling and accounting divisions can be further improved, too (Bayerl et al. 2020 ; Koch 2017 ; Langmann and Turi 2020 ). Through RPA solutions, up to 50% of all back-office tasks—like the synchronisation of supplier and customer accounts—could be automated in the upcoming years (Koch 2017 ). Additionally, the number of employees necessary to manage the workload can be reduced or shifted to new tasks (Kirchberg 2017 ). Up to 36% of companies already use RPA or AI for individual tasks in their accounting department (Kreher 2021 ).

RQ 5: The advantages and disadvantages of digitalised accounting activities

In the review, a variety of advantages and disadvantages of digital technologies in accounting became apparent (Fig.  12 ). In total, we found almost three times as many advantages (n = 618) named than disadvantages (n = 249).

Advantages and disadvantages of digitalisation in accounting (number of publications)

The advantages mentioned most frequently were saving costs (n = 90), increasing efficiency (n = 76), and saving time (n = 73). One example is that digital tools help accountants to manage their workload better and at lower costs (Pan and Seow 2016 ). Keimer and Egle ( 2020 ) state that technologies such as big data analytics or cloud solutions are useful to reduce the susceptibility to errors while simultaneously increasing efficiency in the controlling division. In addition, process automation is perceived as a key aspect of efficiency enhancement in the auditing sector (Werner and Gehrke 2011 ). The advantage of saving time is connected to two time-related opportunities. Firstly, Pagel ( 2019 ) mentions the aspect of processes optimised by digital technologies; lead time for invoices was reduced by up to 15 days, leveraging liquidity on the biller’s side. The freed-up worktime indicates the second perceived opportunity: The specialised workforce in the controlling division can shift their responsibilities to less administrative tasks, thus extending current activities to strategy-oriented areas (Egle and Keimer 2017).

These productivity-related factors are mentioned in half of the publications. The advantages of economies of scale (n = 7) and productivity (n = 11) are only rarely mentioned. For example, Egle and Keimer (2017) discuss productivity as an advantage that results from saved time and error reduction.

“Other” advantages (n = 57) range from employee engagement and motivation (Langmann and Turi 2020 ) to simplified auditing processes (Sledgianowski et al. 2017 ) or improved understanding of financial events (Ashoka et al. 2019 ). But customer satisfaction (Binkow 2015 ) and sustainability-driven aspects such as CO 2 reductions (Bernius and Kreuzer 2014 ) were mentioned as additional aspects as well.

Regarding the disadvantages, content analysis shows the highest risks with digital technologies in accounting in the areas of interface management (n = 40), financial investments (n = 42), and missing expertise (n = 31), mainly with new technologies (Fig.  12 ). Gadatsch ( 2020 ) appoints the central issue of interface management to the complex implementation and its extensive time frame. In addition, data redundancies created by the parallel upkeeping of former and new ERP systems might further increase interface issues, effectively increasing the workload. Thus, there is a need for technological and methodological skills for successful interface management. Schömburg and Breitner’s ( 2010 ) explanations support this result. They identify the main reasons for companies to defer process digitalisation as a lack of expertise, necessary investments, and implementing suitable software. This finding primarily connects to electronic invoicing (Jordanski 2020 ; Koch 2017 ; Nagel 2018 ; Najderek 2020 ; Schömburg and Breitner 2010 ; Tanner 2016 ; Tanner and Wölfle 2005 ) and ERP-specific areas (Appelfeller and Feldmann 2018 ; Binkow 2015 ; Chen et al. 2012 ; Cong et al. 2018 ; Fuller and Markelevich 2020 ; Gadatsch 2020 ; Jonen 2020 ; Wilczek 2014 ). The “other” disadvantages (n = 32) focus on the risks of decentralised innovations that are not implemented company-wide (Schindera et al. 2018 ) as well as the amount of time needed for software maintenance or to train employees (Gadatsch 2020 ). In addition, a few technology-specific disadvantages are mentioned: On the one hand, the implementation of RPA does not require the innovation of new processes, thus old, ineffective processes could stall future changes (Gadatsch 2020 ). On the other hand, blockchain could hinder scalability due to slow transaction speeds and challenging error corrections (Fuller and Markelevich 2020 ).

Discussion and summary

Digitalisation is changing numerous processes in the working lives of accounting professionals. This also applies to processes associated with accounting. Against the background of the question of how accounting graduates will have to be trained in the future, we have identified requirements and activities with the help of a systematic literature review. The literature review was conducted based on a conceptual framework of six types of activities and three stages of digitalisation. Figure  13 gives a condensed overview of the most important findings:

Overview of findings

Regarding the foci of publications dealing with digitalisation in the field of accounting, we found that developments in accounting and implications for accounting education dominate. These findings indicate that the discourse in the field has moved beyond the definitory stages and towards the identification of needs of action, including, among others, the advancement of accounting education and adjustments of curricula.

Results for RQ (1) which deals with activities in the areas of accounting that are subject to digitalisation hint at financial accounting and controlling divisions being the main areas of change. While in financial accounting, there is a focus on technology-based change, the area of controlling mostly encompasses changes in the controller’s job profile that are ensuing due to the increasing digitalisation of current tasks. As most activities in financial accounting are based in the area of accounts payable, the focus on technologies could be connected to efficiency-related opportunities that technological updates may implicate. Out of the six types of activities, analytical non-routine, automatic, and manual routine activities are the predominant categories (see Table 1 for an overview of definitions). This finding can be linked to the different degrees of automation in the different areas: In financial accounting and balancing, a large share of tasks has been automated, for example by RPA. In controlling, financial forecasting, and managerial accounting, however, the leading tasks are data analysis (cognitive routine) and consultancy (analytical and interactive non-routine). These results also provide first hints at the stages of digitalisation in the different areas of accounting (RQ 2).

In RQ (2), we identified different stages of digitalisation in the different areas. The results show that the proportion of digitalised activities is largely dependent on the area, yet most activities currently remain in the substitution stage. This indicates that the integration of technologies and process changes is still underway. The combined analysis of areas, activities, and stages was particularly revealing because it allowed differentiated interpretations. The analysis showed, among other things, that types of activities and different accounting areas are digitalised at different stages. Stage 1 (substitution) is to be expected, for example, in financial accounting and analytical non-routine activities. In contrast, interactive non-routine activities can be found more often in the second stage of digitalisation because current processes are supplemented by new technologies. This finding matches the results from a study by Sachs et al ( 2016 ) who focused on changing job descriptions in the commercial field. Interaction is required to communicate results and consult with management. This leads to expanding job profiles and further required competences that trace back to updates in accounting education.

All the activities we identified require different skill sets and are placed at different interfaces along the entire supply chain (RQ 3). This implies the supply chain’s continuous digitalisation requiring new technical standards and agreements. For example, the increasing popularity of e-invoicing has motivated efforts regarding the standardisation of software and workflows.

Another aspect that shifts competence requirements is the implementation of major technologic trends such as AI and big data analytics in the industry (RQ 4). Frequently mentioned technologies and corresponding business processes need to be integrated into accounting curricula to meet industry needs. On the one hand, technology itself and its evaluation could be addressed. On the other hand, the handling of technology could be prepared when it is integrated into industry practice. Learning materials need to reflect these changes and thus become more digitalised as well.

With RQ (5), we analysed the advantages and disadvantages that the publications under analysis identified during the process of digitalisation in the field of accounting. Even if the advantages mentioned in the publications, such as efficiency reasons, outweighed the disadvantages, risks such as interface management and accounting professionals’ lack of skills and competences must still be considered. In consequence, companies lack the expertise to successfully manage digital transformation processes, underlining the importance of specific competence development. Other factors that are main motivators are of a classic economic nature, such as an increase in overall productivity by saving time and financial resources. Both technologies’ specific disadvantages and the process of digitalisation in accounting more generally suggest the need for improved accounting graduate education and further training or at least for more guidance for both employers and employees. This need applies to concise abilities, such as the assessment of digital technologies and processes, and the criteria-based evaluation of the potential of software implementation. Depending on how quickly corresponding competences can be developed in the company’s workforce, flexibility in competence acquisition for varying technologies and the successful implementation as well as maintenance of technological interfaces is needed. Thus, the field of accounting has reached a level of digitalisation that entails changes in competence profiles to enable both accounting professionals and graduates to manage new demands.

Limitations

Methodological limitations.

Concerning limitations, our paper focuses primarily on results from a literature review and not on the analysis of real company situations or accounting professionals’ reports. The activities, stages, and combinations described in the articles were evaluated according to the number of codes. Whenever a publication mentioned the same code in a different context, it was coded as a new mention. This could potentially distort results. In addition, we did not analyse the extent to which technologies have actually been established in companies and in particularly in accounting. The papers might reflect the past and current states of the discussion.

The next limitations stem from the selection process of publications and their respective language of publication. While there were specific journals in English selected as relevant, we did not select specific German journals. Regarding the dominance of German-speaking publications, it is possible that the databases we used, particularly Google Scholar, produced a bias due to their search algorithms that might include geolocation. To balance this out, we searched for our keywords in both English and German. However, we cannot ignore that this might have implications for the results of our study. In German-speaking countries, accounting methods are rather defensive compared to English-speaking countries, where future-oriented perspectives are more common. In consequence, it is possible that some of our results only pertain to Germany and other German-speaking countries as well as to some to other countries, especially those results that are connected to the flexibility and design of accounting curricula or the stage of digitalisation in the industry.

Content-related limitations

Another limitation is the focus on controlling and financial accounting in the keyword groups as other areas of accounting might have been underrepresented. As for the integration of digitalisation into accounting curricula and learning materials, our paper does not consider external factors that might influence the creation and adaptation of accounting curricula like accountancy professional bodies and other accrediting organisations.

Implications for accounting education and professional practice

The lack of expertise takes a prominent position in our analysis, which is mainly reflected by the prevention of digitalisation processes and innovation of accounting activities. Particularly, technological and methodological skills are needed to integrate new technologies, innovate processes, and, in consequence, produce a shift in activities. The following key implications can be deducted for accounting education and professional practice (see for more details Berding et al. 2022 ):

Adaptation of curricula to reflect the change of focus from financial accounting and routine activities to the area of controlling and non-routine activities (" RQ 1: Activities concerned with digitalisation in the different areas of accounting " and " RQ 2: Accounting activities in different stages of digitalisation " section).

Intensification of the use of technological and analytical tools in accounting education curricula to motivate early contact and contribute to the holistic understanding of processes as the importance of independent reporting and interpretation of financial key figures increases (" RQ 1: Activities concerned with digitalisation in the different areas of accounting " and " RQ 4: Technologies used to perform the accounting activities " section).

Combined focus on technical and professional competences in the different areas of accounting that recognises the increasing importance of meta-competences such as proactive thinking, self-control, creativity, and interdisciplinary action. This is particularly important to ensure that graduates and employees stay capable to navigate the field of accounting and adapt to the changing parameters flexibly (" RQ 2: Accounting activities in different stages of digitalisation " section).

Integration of data and process management and new technologies into compulsory curricula and professional development courses to generate a holistic understanding of processes and manage change across the entire supply chain (" RQ 3: Placement of activities within the supply chain " and " RQ 4: Technologies used to perform the accounting activities " section).

Employees in the areas of accounting and controlling need improved communicative and entrepreneurial skills to market the added value of digitalisation to companies (" RQ 5: The advantages and disadvantages of digitalised accounting activities " section).

Overall, the analysis provides valuable hints for future-oriented accounting education that supports companies in realising a maximum of expertise to manage their digital transformation. This extends to the opportunity to think about implications for professional practices (How digitalised can the field be and how can digitalisation change job profiles?), for accounting students/employees (Am I willing to engage with changing technologies to improve my skill set and potentially work on entirely different activities within the next few years?), and even for society (How can these changes and their implications on competences help in finding creative solutions to 21 st -century challenges?). This review can serve as a starting point for these and similar considerations.

This paper was intended to contribute to the discussion of future (competence) requirements for graduates in accounting. The detailed analyses provide an in-depth insight into six types of activities and the different stages of digitalisation for specific areas of accounting. This systematic and detailed analysis was necessary to gain knowledge on how to initiate concrete improvements in the content and methodology of the education and training of accountants (see for example Author 1 et al. 2022). It became clear, for example, that a deeper look into these areas is valuable as the same technologies are not likely to prevail in all areas at the same stage and for the same types of activities. In the area of financial accounting, for example, the duration of tasks decreases due to the large proportion of routine activities that can be automated or substituted, freeing up time for other activities or areas of accounting. One of these is controlling, where there are more non-routine activities that require new skills. However, it also became clear that interface management in particular is essential for linking the numerous technologies. Against this background, the didactics of accounting are also challenged to educate and train graduates in a differentiated manner.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Artificial intelligence

Enterprise resource planning

Optical character recognition

Robotic process automation

Research question

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Digital data and management accounting: why we need to rethink research methods

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Digitalisation is having profound effects on how enterprises function. Its impact on accounting research is growing as the rise of the internet, mobile technologies and digital economy tools generate depth, breadth and variety of data that far exceed what researchers have had access to in the past. But whilst social scientists interested in organisational issues are starting to question conventional methodological approaches to the study of contexts where digital data forms are drawn upon, little such concern has been voiced in the management accounting literature. This paper seeks to explore the continued applicability of conventional methodological thinking when carrying out investigations within digital data environments to inform management accounting studies. It considers why digitalisation impacts methodological precepts, identifies how descriptive and explanatory modes of questioning which management accountants have conventionally opted for need rethinking, discusses ways in which digital data characteristics alter what can be drawn from empirical studies, and points to the potential offered within digitalised settings for methodological advance. It concludes by highlighting the necessity, where digitalisation exists, to question modes of posing questions and to reconsider the applicability of methodological precepts deployed by management accounting researchers to date.

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1 Introduction

Fifty years ago, the American Accounting Association defined accounting as: “The process of identifying, measuring and communicating economic information to permit informed judgements and decisions by users of the information” (AAA 1966, p. 1). Accounting scholars have since come to regard economic information as just a subset of information relevant to decision making. In relation to management accounting systems, there is widespread documentation that their design and modes of operation are influenced by social, institutional, and other organisational factors and that in different contexts, they deal with much more than just economic information or quantified metrics. Today, this is further changing. Digitalisation is having profound effects on how enterprises function particularly in the production and analysis of big data as part of control systems. The impact on accounting research is palpable as the rise of the internet, mobile technologies and digital economy tools generate depth, breadth and variety of data that far exceed what researchers have had access to in the past.

Social science researchers interested in organisational control dimensions are undertaking an increasingly broad set of investigations given the widened data sources in existence today (Hage 2018 ; Johns 2017 ). It is probably “…without question, social media data have changed the research landscape for social scientists.” (Davis and Love 2019 : 639). All the while, questions over the applicability of conventional methodological presumptions in these emerging research literatures are also being asked (Cade 2018 ; Miller and Skinner 2015 ; Yang and Liu 2017 ). Scholars with an interest in “datafication”, that is the development of activities which can be traced digitally with extreme scale and accuracy and which is reshaping lives and experiences (Lycett 2013 ; Mayer-Schönberger and Cukier 2013 ), show more and more concern with how such investigations should be undertaken (Ausserhofer et al. 2017 ; Dourish and Gómez Cruz 2018 ; Van Es et al. 2018 ; Van Dijck 2014 ). Outside management-focused research, digitisation and datafication are seen to present important practical and theoretical research challenges and opportunities (Gattiglia 2017 ; O’Halloran et al. 2019 ; Qiu et al. 2018 ; Wesson and Cottier 2014 ). The need to be “aware of the limitations of any methodology” and to be “more analytical and less omnipotent” (Boullier 2018 : 11) in the application of epistemological and ontological perspectives drawn from analogue world studies within digital data environments is being expressed.

Just as in the social sciences generally, accounting research has seen many advances in tools of investigation including the use of both quantitative and qualitative computer-based methods to help assess field notes and complex numerical relationships. But as Davis ( 2017 : 2) notes “… innovations in qualitative and quantitative research are all, more or less, linear progressions. Big data is a move in a new direction. Big data isn’t just about answering particular questions better , but about asking questions we didn’t even know we had”. Within the management accounting research literature, what we might seek to conceptualise, how we might do so and whether to question modes of posing questions themselves in the face of the rise of new digital data forms has not been the subject of much discussion. The intention of this paper is to expand the debate on whether management accounting researchers as social scientists now need to question the propriety of continuing to apply conventional methodological precepts in investigating digital data contexts.

The paper first considers how digitalisation impacts management accounting research. It then discusses descriptive versus explanatory research and approaches to methodological positioning. The third section of the paper addresses questions to be asked about digital data. Fourth, the paper looks at how digitalisation enhances research possibilities in management accounting after which some conclusions are drawn.

2 Why digitalisation affects accounting research

New data contexts in which to examine research questions continually arise. Big data is a recent phenomenon that is deeply connected to what was an idea that has “…become the largest sociotechnical assemblage in human history in a little under 30 years” and which affects “… the lives, livelihoods and life chances of over half the world’s population already, and connecting many more every day” (Staab et al. 2019 : 74). It is now the case that we live in an era almost all human activity including organisational life can be recorded digitally (Alvarez 2016 ; Nagle 2017 ). The major mechanisms driving digitalisation today include digital technology innovations such as embedded internet of things devices, cloud computing, digitised supply chains and enterprise ecosystems and social media platforms among others (Blazquez and Domenech 2018 ; Hausberg et al. 2019 ). They give rise to data growth through management information systems processes and the proliferation of social networks, blogs, political discourse, company announcements, digital journalism, mobile messaging, home entertainment, online gaming, online financial services, online shopping, social advertising, and social commerce among others (Bhimani 2020 ; Chang et al. 2014 ). Digitalisation within firms has created very large quantities of data which are continuing to grow at an accelerating pace whilst also becoming more diverse in form making big data forever bigger, wider and more rapidly growing. Accounting academics have in this light recognised and highlighted the many accounting investigation possibilities where datafication prevails or is growing (Applebaum et al. 2017a ; Cockcroft and Russell 2018 ; Gepp et al. 2018 ; Mancini et al. 2017 ; Moll and Yigitbasioglu 2019 ; Raffoni et al. 2018 ; Salijeni et al. 2019 ; Vasarhelyi et al. 2015 ; Warren et al. 2015 ).

There is little doubt that across enterprises and organisational platforms the rise of big data and their impact on management accounting controls and information as well as on decision making is reshaping the managerial reliance placed on more traditional information (Agarwal and Nijhawan 2016 ; Applebaum et al. 2017b ; Bredmar 2017 ; Dagilienė and Klovienė 2019 ; Drew 2018 ). Big data and novel modes of analysis associated with the rise of digital technologies present organisational participants opportunities to utilise both structured and unstructured information for control purposes. Action based on such new information displays an important difference from the reliance on information systems output reflecting sequential and linear linkages that are part of pursued enterprise strategies and operations and attendant decision making that have guided the work of accountants in the past. There is now increased recognition that corporate strategy, organisational arrangements and information systems structures defy conventional ties traditionally seen to have connected them as greater appeal is made to big data based analyses and insights (Bhimani 2015 ; Krahel and Titera 2015 ). Moreover, costing architectures themselves have altered as links between data, information and knowledge have evolved (Al-Htaybat et al. 2017 ; Arnaboldi et al. 2017 ; Bhimani and Willcocks 2014 ; Căpușneanu et al. 2020 ; Richins et al. 2017 ; Rikhardsson and Yigitbasioglu 2018 ; Schneider et al. 2015 ; Troshani et al. 2019 ; Warren et al. 2015 ). Information outputs in organisations have transformed so much that few if any dimensions of business or management control processes today remain divorced from digital technology applications. Certainly, virtually all industrial sectors including manufacturing, transportation, health care, defence, energy, service and public sector activities are affected across economies (Vasarhelyi et al. 2015 ).

The rate at which organisations convert data insights into actions and the pliancy shown toward using heterogeneous data forms derived from diverse economic and social sources as well as the flexibility toward intermingling economic, operational, structured, unstructured, qualitative and numbers-based information has reached unparalleled heights. Enterprises today exercise data reach and plurality of information usages to inform enterprise action and guide operational processes of an order of magnitude never witnessed before in the history of organisational information systems usage. As such, accounting activities reliant only on pre-designed information inputs relating primarily to economic transactions with some coupling with non-financial information pools represents a fraction of control information deployment in digitalised enterprises. All dimensions of managerial action that can be influenced by datafication possibilities can be expected to open up novel control possibilities also.

The argument has been made that the vastness of new data forms does not elevate the rationality of decision making and indeed, that access to more digital data within enterprises “will make people take wrong decisions much more quickly than before” (Quattrone 2016 : 120). What is clear is that scholarly studies in accounting will increasingly explore novel digital data forms, types and usages. As they do, accounting researchers will need also to reflect on the adequacy of the methodological approaches they adopt since their focus on widened data sources perforce embeds epistemological conditions that can alter the object of their investigations and place at risk their ability to develop tenable arguments. The next section identifies two forms of traditional accounting research concerns which have laid the premise for specific methodological presumptions which need to be reconsidered in investigating digitalised contexts.

3 Asking ‘what’ and ‘why’ in management accounting research

One view of information is that its use helps deal with the management of uncertainty (Jauch and Kraft 1986 ). Many management accounting activities in enterprises seek to produce information that lends greater clarity to managerial decision making and that enhances the perception of certainty of actions taken. In organisational environments where complexities grow, the general reaction of management accounting formality has been to re-structure information to enable its continued potential for uncertainty reduction and to aid management decision making. In instances where information structures have been challenged because of a perceived need to enhance organisational decision making clarity, the reaction has been to advance accounting techniques that adopt new formatting, novel structures or altered technical rationales. Managerial action and organisational transformations have reflected environmental changes such as for instance, growing production flexibility, product range increases and deeper and more rapid competitor shifts among others. Increased complexities between business objectives, operational processes and decision making has been responded to by novel management accounting approaches (such as activity based costing, target costing, balanced scorecards, standard costing systems etc.) which have become formalised management control measures in many enterprises. Management accounting changes have thus tended to encompass the adoption of standardised enterprise controls that reflect new information production and exchange needs. As organisational interconnections and risks have grown, new applications have been implemented to aid the management of uncertainty resulting in greater systemic homogeneity of management accounting approaches.

For management accounting scholars, such changes in accounting controls have presented many research opportunities. Some have engaged in descriptive investigations of management accounting techniques take-up by enterprises. Such investigations report on standard techniques usage identifying similarities and differences in adoption rates across firms, industrial sectors and geographies without necessarily seeking to explicate the basis for the reported differences. The descriptive management accounting practices literature has reported on numerous standard techniques in use in companies such as variable and full costing, choice of cost allocation bases, budgetary control practices, variance analysis and standard costing usage, pricing techniques, capital budgeting approaches, transfer pricing methods, activity-based costing applications, as well as balanced scorecards, life-cycle costing, and strategic accounting tools among others (Bhimani et al. 2019 ).

The concern with how techniques show differences and similarities across firms has been complemented by other scholarly studies that investigate why accounting outcomes are what they are. Explanatory research in management accounting attempts to identify causal factors and to offer rationales for the underlying reported differences. Most of these studies tend to posit deductive explanations based on other empirical studies previously undertaken in comparable contexts and/or drawing upon specific conceptual reference frames to demarcate propositions. To take an example, the contingency theory of management accounting has been regarded by some management accounting scholars as offering a theoretical frame for explaining the basis for similarities and difference in modes of organisational control implementations (Chapman 1997 ; Chenhall 2007 ; Gerdin and Greve 2004 ; Otley 2016 ). Some scholars posit an emic rather than an etic approach to contingency based management accounting research (Granlund and Lukka 2017 ) and others critique the determinism grounded in the contingency perspective (Fried 2017 ). Still, the generalist argument advanced within the contingency perspective has been built on the premise that control systems deployment in enterprises is linked to the existence of supra-national forces of change whereby firms become more alike as economies converge over time (Donaldson 1995 ; Hickson et al. 1974 ). So differences become suppressed as homogenising factors inform the architecture of controls within firms (Mueller 1994 ). Scholars who adopt a contingency argument to explain similarities and difference have identified broad environmental factors such as for instance the manner in which managerial hierarchies are structured vis-as-vis the stage within a notional trajectory of industrialisation which an economy finds itself in. Under this perspective, economic transformation drives market, technical, and organisational dependencies which compel firms to arrange their internal structures by reference to a set of functional control possibilities (Otley 2016 ).

Another stance adopted by some scholars is the “political economy” perspective which focuses on contradictions within capitalism that mobilise broadly similar trends in the management and structuring of the labour process. Profit seeking organisations are viewed to exhibit similarities in managerial controls to oversee the conduct of work and the standardisation of tasks (Armstrong 1987 ; Cooper and Hopper 1990 ; Roslender 1996 ; Thompson and Smith 2010 ). The notion that imperatives (either contingency or labour-process based) prevail across social, economic, or political systems and that mould organisational controls within a trajectory of progression enables explanations as to specific functioning modes implemented by organisations and the formal controls they ultimately operationalise. The argument advanced within this conceptual perspective rests on the contention that structural changes over time follow a specific path of evolution and that organisations in the settings under study manifest corresponding likeness.

The premise within both contingency and political economy perspectives is that organisational contexts follow a trajectory that overarches the particularity of enterprise characteristics. As such, advances accord organisations likeness of control approaches that echo the homogenising effects of industrial change. Converging influences manifest whereby technological, market, strategic, labour and other contextual variables exhibit replicating interdependencies in relation to organisational structuring which underpin control changes. Such scholarly explanations as to organisational control operationalisations rest on argumentation that presumes the stability of relationships between environmental characteristics and organisational features and processes including management accounting approaches.

Management accounting research resting on notions of converging influences tied to presumptions of industrial evolution are, within digitalised settings, in need of qualitative re-assessment. The stability of relationships cannot be assumed of emerging business models in the fast transforming digital economy (Wadan et al. 2019 ). The time is also now to questions the applicability of quantitative approaches that have been deployed in studying analogue organisational settings whose information systems are linearly arranged and to ponder their continued appropriateness given the altered process structures of digitalised enterprise contexts. The issue goes beyond the paradigmatic legitimacy of using quantitative research norms drawn from the pure sciences to qualitative investigations (Aguinis et al. 2017 ; Denzin 2010 ; Pratt et al. 2019 ).

As scholars pose research questions, opting for either descriptive or explanatory routes in relation to the study of digitalised enterprise controls, they need to also ponder whether the data from such can be subsumed within traditional methodological conceptions of data inquiry. It may be that the transition from analogue to digital has ushered in different parameters of evolutionary enterprise control structuring which need to be explored. By the same token, it is difficult to contest that digital technologies associated with the production of big data can lead to inferences that “covertly or overtly, consciously or inadvertently” (Robertson and Travaglia 2018 : 2) support specific ideologies. In other words, both quantitative and qualitative methodologies deployed within established management accounting research efforts embed epistemological, ontological and ideological preconceptions that need elaboration. Possibly, “… the change from a largely analogue small data environment to a foundationally digital one has not undermined the pervasive ideologies that the small data paradigm produced and institutionalised” (Ibid.). It becomes therefore essential for management accounting researchers to ponder what conceptions of research become imported into new realms of analyses that rest on vastly different data forms and sources and whether what is interpreted about the new data is aided or obfuscated by past norms of research propriety. The paper turns now to discussing data specific implications of management accounting research focussing on digital contexts.

4 Questions about data that can change the questions we pose

Accounting scholars will continue to explore accounting structures and what underpins their functioning. The underlying forces that tie contextual factors to accounting however are changing and a need exists to reflect on how appropriate it is to adopt conventional research precepts in exploring accounting issues within digitalising environments. A number of issues associated with the nature of data resulting from digitalisation suggest that such reflection has become essential. First, a marked change is in evidence whereby the presumed connections between action and control systems input and their consequences in conventional accounting usage settings have altered. The evolution of digital technologies has upended the sequential linearity which has traditionally directed organisational activities. The pursuit of specific defined organisational strategies can, in some instances, give rise to particular management controls but that logic cannot be assumed to reside in digitalised enterprises. The notion that sequential and traceable paths of effects are present where in fact new inter-dependencies associated with digitalised platform based organisational control models and altered data creation and exchanges are in play no longer hold (Willcocks et al. 2014 ). Contingency reasoning resting on the idea that enterprise strategies sponsor technological responses which yield specific accounting control outcomes has to be questioned since the sequential agency baked into conventional control mechanisms is seemingly absent in digitalised settings (Bhimani and Willcocks 2014 ). Information relevance and the linear sequencing of control information and action drawn upon for information analysis by decision makers is not an essential part of digitalised enterprise activity. Consequently, it is essential to acknowledge that ways in which accounting controls in digitalised organisations differ from traditional settings as data forms and flows have altered. This needs to be reflected in revising the research questions we ask.

Second, datafication has altered the premise on which management accounting justifies its raison d’être . Whilst the objective to provide financial and non-financial decision-making information to managers may seem laudable as management accounting’s primary pursuit, this prescriptive view confines the field to the application of solutions and a focus on data that are no longer hold primacy in many digitalised enterprises. Aside from formal financial data and operational records of processes or economic transactions, digitalised enterprises produce “exhaust data” or “trace data” which are part of the digital records of activities and events that engage information technologies such as data from clickstreams, sensor data, and social media updates. Such data bypasses capture by traditional accounting information systems since they lack any direct link to verifiable economic impact. However, digitalised organisational platforms produce at least some elements of trace as part of log files, documents or communication trails which culminate in data perceived to be of relevance to controls and viewed as a desirable source of business intelligence. Appeal to such additional forms of data, structured and unstructured, have implications for researchers. Different investigatory questions may be posed and studies may benefit from redefinition of scale and scope in the light of more diverse data types. Digitised data may for instance be seen to lag or lead the direction captured by formal data and operational information. They may signify reinforcement or upending of articulated organisational pursuits. Such data, given their abundance and speed of production, may lead researchers to redefine the depth and time focus of their investigations.

Third, digitalised enterprises may exhibit pathways to organisational changes that do not accord with established management theories. This then could confound inference-focused methodologies adopted by accounting scholars. It may be that research methods could be widened drawing from the data sciences (George et al. 2016 ). To take an example, suppose that enterprises reveal that engagement in big data analysis leads to the identification of patterns giving rise to new organisational strategies. This then opens up room for questioning the premise upon which strategic management theorising rests in relation to strategy formulation and formation (Furrer and Goussevskaia 2008 ; Langfield-Smith 1997 , 2006 ; Sminia 2009 ) and the conventional predictions that can be derived from the prior literature (Grattan 2016 ). If it is apparent that new enterprise visibilities based on research data collected can lead to altered strategies that overarch any reference to traditional conceptions of strategic engagement, then one must interrogate whether prior studies supporting linkages between strategy and accounting and the methods adopted therein can reasonably guide research endeavours that rely on data which defy traditionally perceived patterns of flow.

Fourth, research in digitalised organisations, can reveal useful data sources that are ‘found’ rather than produced by design. These can aid enterprise decision making but in contrast to formalised systems derived information that have purposefully ‘generated’ data with specific intents, their provenance is circumstantial. Moreover, trace data are different from many other common forms of social science data in that they are usually “event-based” records of activities and transactions. Additionally, trace data are ordinarily longitudinal and time-stamped sequences of activities. Further still, they may not be cross-sectional and thereby serve a number of alternative and possibly novel research purposes. Recognition that digital data can be a by-product of activities instead of data generated for the purpose of either organisational control or indeed for the research enterprise is important to acknowledge. Importantly, the specific characteristics and properties of digitalisation derived data makes for potentially extremely significant advances in academic research. This is further discussed in the next section.

5 Can digitalisation widen the research potential?

Scholarly claims must align with norms of legitimacy in accounting research. Deviating from these can derail investigations if established research robustness pre-conditions are sidestepped (Creswell 2003 ; Frade 2016 ; McFarland and McFarland 2015 ). But there must also be recognition that approaches to data, method and theorising can be altered and expanded as researchers engage with novel bases of empiricism. Investigations using data from digitalised organisations, whether financial, structured and formally produced or non-financial, unstructured and trace-derived, have the potential to make insightful claims about the technical, organisational and social characteristics of accounting. Digitalisation therefore offers immense opportunities in this respect but requires safeguards to maintain traditionally desirable parameters of research integrity. This has to be balanced with the potential of conceptualisations from research that could not be had by too closely remaining wedded to past ideologies of research integrity. To take an example, within explanatory management accounting research, the tendency has been to demarcate between deductive versus inductive research. Digital data forms enable emancipatory departures from this research divide than before.

The availability of trace data can enable inductively generated novel theorising to emerge. Still, as with the edicts of conventional research legitimacy, one cannot overreach in yielding conclusions from empirics when the data source does not permit. It is important therefore to be mindful that trace data tend not to be generalisable outside of the platforms from which the data originate. This is particularly so when trace data links into social media bases. Participation on digitalised platforms that generate such data is not usually universally representative of the wider population that interacts with an organisation or industrial sector within the object of study. These data sets may also be demographically biased. Access to data or to platforms that create such data may further be infra-structurally constrained. Organisationally linked media data are partial, demographically skewed, and not always consistently available. Consequently, empirical generalisability may not be attainable and theoretical generalisability must not be inappropriately posited. As Davis and Love ( 2019 : 637) warn, researchers must bear in mind that: “Through a mask of objectivity, claims about ‘social life’ derived from social media data present the partial and the skewed as general and universal”.

Trace data assessment can buttress conventional hypothetic-deductive methods but also can lead scholars to build and elaborate theory by subjecting the data to extensive analysis. Importantly, the availability of different data forms that have not been available to researchers before offer the possibility to inductively engage such data within a grounded theoretical frame (Charmaz 2014 ; Glaser and Strauss 1967 ) rather than to pursue hypotheses propositions and testing aligned with deductive methodological convention. Grounded theory that seeks to develop theoretical concepts and relationships can become viable where digitalised data forms, because of their scale and variety and the data characteristics noted above, offer prospects for delving beyond deduction.

Big data analytics using focused computational methods that prioritise speculative data mining to highlight pattern recognition and unexpected correlations can inform the accounting research domain (Appelbaum et al. 2017a , b ; Geppa et al. 2018 ; Schneider et al. 2015 ). Pitfalls nevertheless exist in that simple mining for insights overlooks questions that could be more theoretically informed and to some, the value of such investigations “remains very much open to question” (Goldthorpe 2016 :81). The importance of and the possibilities open to qualitative researchers to “… conduct ‘big qual’ analysis while retaining the distinctive order of knowledge about social processes” remains (Davidson et al. 2019 : 264). There certainly can be continuity in data enabled by the combination of qualitative and quantitative methods in the digital world (Venturini et al. 2017 ). Indeed, Halford and Savage ( 2017 : 1133) suggest that researchers might take a ‘symphonic’ approach to big data analysis where “recurring descriptive motifs woven together within a complex temporal narrative” are made visible. They advocate a perspective that combines rich theoretical awareness with data that can address wide questions rather than simply mobilising the ad hoc mining of large data sets in search of inductive patterns where “hermeneutic and critical analysis” are displaced. A precaution is for the data set assessed not to be short period collections of say purchasing patterns and production activities over limited time and context spans but wider ranges of points over extended time frames. The intent should not be to have the data infer associations based purely on detected correlations but to use concepts and theorising that connect to recurring motifs such that there emerges a broader narrative. Certainly, studies must not abandon traditionally important considerations of social science research including data representativeness and sampling biases and it is important that conclusions that relate to a whole population are not based on results gathered from partial analyses reliant on narrow data sets (Hargittai 2018 ; Lazer et al. 2009 , 2014 ). The preferred approach should then be to intertwine sound theoretical understanding with wide ranging data that reveal recurring motifs.

Methodologically, some steps that are long established in social science research are important to adhere to. Halford et al. ( 2018 ) advance the need for high transparency as to the data being used. In other words, extreme diligence is required in reporting the way in which data are harvested. This could mean keeping tabs and records of principal metrics that relate to the data set or streams. The possibility of transparency must therefore remain. It is likewise important to understand the limits of the data in terms of what it could reveal and what not. Moreover, the construction of data is important to explain as researchers often organise the data to be analysed to enable a particular questioning slant to be operationalised such as for instance, deliberately biasing the population set to evince more information about an under-represented management control characteristic. This avoids making inferences that supersede the specificity of the data set. The questions to be asked should, in other words, guide the approach and the claims should align with the data selected for analysis.

Whilst methodological fundamentals typical of empirical analyses using data sets for investigation of traditional or big data contexts may have parallels, the availability of digitalised data affords more flexibility to deviate from common research points of departure. In effect, rather than make distinct the starting point of a research endeavour in relation to engaging in deductive or inductive reasoning, what may be sought is abductive reasoning from the outset where tools and data are engaged in within a critical process of interrogation which may change during the investigatory stage. Certainly, “…emic-level empirical analysis at the core of interpretive research is connected to etic-level analysis and knowledge” (Lukka ( 2014 : 561), but in relation to digitalised enterprise contexts, primacy can be given to the “unfolding interplay between data, method and theory and with regard to their co-constitution” (Halford and Savage 2017 : 1143).

Some scholars have argued that digital data has done “nothing less than to revolutionise the social sciences” and is “challenging established paradigms” (Berente et al. 2018 :2). Accounting research is not exempt. The case for re-thinking how legitimate it is to apply conventional methodological precepts in investigating digital data contexts to inform management accounting studies cannot be made too strongly. The paper has discussed digitalisation as having led to massive data growth both from non-formal structures as well as from management information systems producing and processing economic and new forms of data that are structured and unstructured. The impact of digitalisation on management accounting research is growing as we gain access to greater depth, breadth and variety of data. This is creating an investigatory landscape offering exponentially growing qualitative and quantitative research domains. The focus on digitalised data raises issues of method for accounting research given that organisational information platforms now encompass the analysis of data not conventionally part of management control research. Digital data characteristics embed features that can challenge established paradigms about data and lead to altered ontological notions of the informational nature of data. The growth of analysable data, structured and unstructured, as well as formally intended and circumstantial, alters the premise upon which researchers can design their investigative work and the methodological precepts they adopt or indeed, devise.

It might be said that digitalisation within enterprises offers researchers an epochal opportunity to investigate what has not been possible in the history of management accounting investigations. This is because digital data are “more evenly distributed across the span of collective existence of which they therefore offer a more continuous appraisal” (Rogers 2013 : 4). Management scholars have pointed to the handling of big data and how analytical tools provided by data science can be adapted and altered to not only seek better answers to existing questions but also for posing new questions (George et al. 2016 ; Kuo and Kusiak 2019 ; Mikalef et al. 2018 ; Spanaki et al. 2018 ; Tonidandel et al. 2018 ). What may be derived from research using larger volumes of data that emerges faster than ever before and which is more varied in structure whilst also offering specific characteristics such as time-stamping and chronology, goes beyond what has been empirically available to us. Features that characterise digital data alter the potential of investigations in relation to the limits and possibilities of digital empiricism. Along with an unprecedented array of new data, digitalisation has brought with it novel options for how to and what to research, as well as a need to re-assess our conventional conceptions of methods legitimacy and ultimately, what we regard as having scholarly rigour.

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Bhimani, A. Digital data and management accounting: why we need to rethink research methods. J Manag Control 31 , 9–23 (2020). https://doi.org/10.1007/s00187-020-00295-z

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Impact of accounting software for Business Performance

The major problematic source towards the organizations and corporates is the accounting field by the way its intended users need to clarify the accounting soft wares which are suitable on the basis of their day today accounting and business needs. Mainly the fact in Anuradhapura area is the incomplete records and unauthorized access of data by unsuitable accounting packages and apps. The fundamental error occurring in all kind of working environment and organizations are not finding the correct solution toward accounting and decision making by the selection of main accounting packages and apps. The key course of action is how to choose accounting software and apps by the businesses in Anuradhapura area. Which influence in decision making process. Abstract: Accounting, business, performance

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