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Due to the unprecedented disruptions in business operations, many organisations are turning to Cloud ERP implementation to ensure employees can access real-time business information from anywhere, enabling the continuity of business activities. As a result, over the past decades, literature on Cloud ERP implementation has seen significant growth across different subject areas. This paper aims to present a systematic literature review (SLR) that consolidates the literature scattered across various multidisciplinary subject areas, explores recent developments and identifies knowledge gaps for more impactful future research.

An SLR approach has been applied to a sample of 73 articles published until 1 February 2022.

Our SLR identifies and consolidates a set of critical enablers and barriers to the implementation of Cloud ERP. What is particularly interesting is that this study established a link between these enablers and barriers and four key innovation outcomes: product, service, process and business model innovations. A rigorous framework has been devised that demonstrates the nexus between enablers and barriers to Cloud ERP implementation and innovation outcomes in an organisation. In addition, this study has recognised several organisational theories from information systems literature that have the potential for future research in this emerging area.

This SLR makes several theoretical contributions to the literature on Cloud ERP implementation and its impact on innovation outcomes.

The review consolidates a wide range of literature to provide decision-makers with an integrated understanding of the most influential factors in Cloud ERP implementation.

SLR provides a comprehensive analysis of the current state of research on the topic, offering unique perspectives on developments in theory and knowledge gaps, as well as identifying future research opportunities in the area.

The purpose of this paper is to explain how enterprise resource planning (ERP) implementation evolves by cloud computing in different industries with different delivery models of cloud ERP. This paper also investigates infrastructure as a service (IaaS) as a delivery approach for cloud ERP. Case research on IaaS is rarely found in the literature. In addition, this paper intends to reveal how this transformation from on-premises to the cloud would influence the ERP implementation process.

A multiple-case study is conducted to identify the different deployed models of cloud ERP systems in the implementation projects. The influences of emerging cloud computing technology on ERP implementation are investigated by interviewing consultants related to the projects.

The findings illustrate that not only software as a service (SaaS) but also IaaS and platform as a service cloud computing services are widely applied in cloud ERP implementation. This study also indicates that certain technical limitations of cloud ERP might have a positive effect on the outcome of ERP implementation.

This study investigates how cloud computing influences ERP implementation from different aspects. The result identifies both SaaS and IaaS as two different approaches widely adopted in cloud ERP implementation. Besides, this study has discussed in-depth and analyzed these two cloud ERP paradigms in five factors, including functionality, performance, portability, security, cost and customization. The classification and suggestions are original to the literature.

Generally, the use of cloud-based services has proliferated all around the world. This tendency increased dramatically during the coronavirus disease 2019 (COVID-19) pandemic when many people were obliged to conduct business remotely. This research study aims to investigate the intentions to adopt (IA) cloud-based enterprise resource planning (ERP) systems in Jordan, as this sort of research is scarce in developing countries. Specifically, this research study combined the model of Diffusion of Innovation (DOI) and the Technology-Organization-Environment (TOE) framework, in addition to looking at COVID-19 as a moderating variable.

Data were collected from 60 participants working in Jordanian companies that currently use, or have the intention to use, cloud-based ERP systems. An online questionnaire was developed and used to collect responses. The study hypotheses were examined statistically using simple regression analysis and hierarchical multiple regression.

The study results clearly indicate that complexity, observability, employee information technology (IT) skills, organizational culture (OC) and top management support significantly affect the intention to adopt cloud-based ERP systems. In contrast, relative advantage (RA), compatibility, trialability, regulatory environment and competitive pressure had no significant effect on adoption intention. Interestingly, the advent of COVID-19 increased the intention to adopt cloud-based ERP systems.

The study's findings will provide theoretical and practical suggestions for the effective adoption of cloud ERP in Jordan, as well as aiding other developing nations in comparable situations in implementing cloud-based ERP systems.

The study enriches the knowledge and further examines the underlying reasons for adopting cloud-based ERP systems in a developing country.

Product Lifecycle Management (PLM) systems have gained wide popularity for their role in manufacturing organizations for creating, managing and distributing product data. These systems are one of various enterprise systems which are required for smooth functioning and meeting the scaling up requirements organization. However, with introduction of cloud technology and other industry 4.0 initiatives, there has been focus on moving the on-premises IT application to the cloud. Such a move needs to be carried out by identifying and evaluating various challenges. This paper aims to discuss the aforementioned objective.

The challenges identified through literature review have also been confirmed to be present via interview, system observation and documentation review through case study-based validation in an automotive component manufacturing industry.

The article identifies needs and challenges of cloud PLM systems and presents a generic framework for developing an approach for cloud PLM journey for an organization. The article also provides an approach for resolving the different challenges to realizing the designed system.

The simplified generic framework has been presented for use by industry professionals and researchers for designing cloud PLM systems that would fulfill expectations of different levels of stakeholders.

Cyber risk has significantly increased over the past twenty years. In many organizations, data and operations are managed through a complex technology stack underpinned by an Enterprise Resource Planning (ERP) system such as systemanalyse programmentwicklung (SAP). The ERP environment by itself can be overwhelming for a typical ERP Manager, coupled with increasing cybersecurity issues that arise creating periods of intense time pressure, stress and workload, increasing risk to the organization. This paper aims to identify a pragmatic approach to prioritize vulnerabilities for the ERP Manager.

Applying attention-based theory, a pragmatic approach is developed to prioritize an organization’s response to the National Institute of Standards and Technology (NIST) National Vulnerability Database (NVD) vulnerabilities using a Classification and Regression Tree (CART).

The application of classification and regression tree (CART) to the National Institute of Standards and Technology’s National Vulnerability Database identifies prioritization unavailable within the NIST’s categorization.

The ERP Manager is a role between technology, functionality, centralized control and organization data. Without CART, vulnerabilities are left to a reactive approach, subject to overwhelming situations due to intense time pressure, stress and workload.

To the best of the authors’ knowledge, this work is original and has not been published elsewhere, nor is it currently under consideration for publication elsewhere. CART has previously not been applied to the prioritizing cybersecurity vulnerabilities.

This paper aims to investigate the impact of integrating Sustainable Enterprise Resource Planning (S-ERP) systems and lean manufacturing (LM) practices on sustainability performance, especially in Egypt as an emerging country.

The authors carried out an experimental study with a sample of 144 professional accountants of MPA, MBA and DBA students at two of the top universities in Egypt.

The results provide significant evidence that the integration of S-ERP systems and LM practices implementation improve sustainability performance. However, there is no significant evidence that S-ERP adoption contributes to the success of LM practices implementation.

Because of the chosen research approach, this study is limited to use of a laboratory experiment design. Empirical evidence based on quasi experiments on a field setting would add value to the current literature.

Findings provide practical insights for the manufacturing sector managers into the benefits of integrating S-ERP systems and LM practices for sustainability performance improvement (e.g. reducing cost and waste, increasing operational efficiency). For ERP vendors, findings highlight how ERP vendors introduce “enablers” that incorporate LM best practices into their ERP systems and also how those vendors conform to the software sustainability criteria in the design of ERP applications.

Contrary to previous studies that addressed the individual impact of S-ERP systems and LM practices on performance, this paper experimentally gives an indication of the impact of concurrent implementation of S-ERP and LM practices on sustainability performance, especially in developing countries.

Technology is widely recognised to be revolutionising the accounting profession, allowing accountants to focus on professional skills and technical knowledge that deliver value for organisational success. Despite the known benefits, it is reported that accountants are not fully leveraging the potential value of certain technologies. To understand why, this study aims to draw on the technology adoption model (TAM) and investigates accounting professionals’ perceptions towards technology, and how these may influence adoption at work.

The study gathered online survey data from 585 accounting managers from organisations of varying sizes and in different sectors in Australia and parts of Southeast Asia. Qualitative data were thematically analysed, and quantitative data were analysed using both descriptive and multivariate techniques.

The study highlighted the pivotal role of staff perceptions on the importance and ease of using technology on the uptake and successful usage. Findings emphasised important opportunities for organisations to educate accounting staff on the value of technology and optimise their confidence and skills through training and support initiatives, particularly smaller businesses. Marked differences in the orientation towards technology among Australian and Southeast Asian participants illuminate how national work culture and practice can influence technology adoption.

The study makes a practical contribution by advancing the understanding of the relative importance and value of certain technologies in different regions and organisation types in the accounting profession. It extends the theoretical understanding of the role of TAM’s core elements to the accounting context, exploring staff’s notions of perceived usefulness and perceived ease of use from the manager’s perspective.

Algorithm bias refers to repetitive computer program errors that give some users more weight than others. The aim of this article is to provide a deeper insight of algorithm bias in AI-enabled ERP software customization. Although algorithmic bias in machine learning models has uneven, unfair and unjust impacts, research on it is mostly anecdotal and scattered.

As guided by the previous research (Akter et al., 2022), this study presents the possible design bias (model, data and method) one may experience with enterprise resource planning (ERP) software customization algorithm. This study then presents the artificial intelligence (AI) version of ERP customization algorithm using k-nearest neighbours algorithm.

This study illustrates the possible bias when the prioritized requirements customization estimation (PRCE) algorithm available in the ERP literature is executed without any AI. Then, the authors present their newly developed AI version of the PRCE algorithm that uses ML techniques. The authors then discuss its adjoining algorithmic bias with an illustration. Further, the authors also draw a roadmap for managing algorithmic bias during ERP customization in practice.

To the best of the authors’ knowledge, no prior research has attempted to understand the algorithmic bias that occurs during the execution of the ERP customization algorithm (with or without AI).

Based on the technology acceptance model theory, this study aims to explore whether perceived usefulness (PU), perceived ease of use (PE) and the availability to embrace technology (AET) influence the intention to accept an enterprise resource planning (ERP) system in Jordanian companies. It also analyses the influence of the intention to accept ERP system on ERP system adoption. More crucially, the current research fills a gap in earlier investigations by exploring the influence of adopting an ERP system on accounting information quality moderated by a company size.

This research seeks to provide evidence about the study context from Jordanian companies, as the research population and sample consist of all companies listed on the Amman Stock Exchange in 2022 (totally 170 companies). This signifies that the research method is a complete survey of the study population. The core data were collected using an online survey via Google Forms. It was emailed to the selected companies’ chief financial officers. Because each company received one online survey questionnaire, this unit of analysis is a company. Finally, 141 questionnaires were returned, reflecting an 82.94% response rate.

Empirically, the findings reveal that PU, PE and AET influence the intention to accept an ERP system, and that there is a positive relation between the intention to accept an ERP system and ERP system adoption. Furthermore, ERP system adoption positively influences relevance and faithful representation of accounting information moderated by company size.

This research adds to the accounting information quality literature by investigating the direct influence of ERP system adoption. Furthermore, the findings show the effectiveness of ERP system adoption and its regulatory roles in companies. Finally, this research was conducted to provide empirical knowledge on ERP system adoption in developing countries, notably Jordan.

Prior research (Harrast, Olsen, & Sun, 2023) analyzes the eight emerging topics to be included in future CPA exams and discusses their importance to career success and appropriate teaching locus in light of survey evidence. They find that the general topic of data analytics is the most important of the eight emerging topics. To further understand the topics most important to career success, this study analyzes subtopics underlying the eight emerging topics. The results show that advanced Excel analysis tools, data visualization, and data extraction, transformation, and loading (ETL) are the most important data analytics subskills for career success according to professionals and that these topics should be both introduced and emphasized in the accounting curriculum. The results provide useful information to educators to prioritize general emerging topics and specific subtopics in the accounting curriculum by taking into account the most pressing needs of the profession.