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Improving business processes provides companies with advantages in terms of efficiency and profitability, as well as competitiveness against other companies in the market. Companies that integrate business processes with enterprise resource planning (ERP) systems into digital platforms also have the opportunity to strengthen their weaknesses by recognizing disruptions and bottlenecks in inefficient business processes thanks to this digital transformation. Descriptive and bibliometric analyses were performed in this study for a systematic evaluation of studies on artificial intelligence (AI) in the ERP literature. The studies in which the keywords determined from the AI literature were firstly used together with ERP were investigated from the Scopus database. 837 publications meeting the search criteria were reached and a descriptive analysis of these publications was presented. Then, bibliometric analysis was performed using common author, common citation, and common keyword analysis methods for 296 publications in the article type. Tsinghua University and Obuda University have the most publications according to the results. The most commonly used AI keywords in the ERP studies were “genetic algorithm”, “fuzzy logic”, and “machine learning”. This study aims to guide future studies by providing a systematic and new perspective to researchers and experts working on ERP-AI.

Enterprise systems are commonly implemented by firms through outsourcing arrangements with software vendors. However, deriving benefits from these implementations has proved to be a challenge, and a great deal of variation has been observed in the extent of value generated for client and vendor firms. This research examines the role of co-specialization as a strategy to make the most out of outsourced enterprise systems. The authors develop hypotheses relating resource co-specialization with two indicators of success for implementation of enterprise software: (1) exchange success and (2) firm growth.

The hypotheses are tested using a unique panel data set of 175 firms adopting Advanced Planning and Scheduling (APS) software, a type of enterprise system used for managing manufacturing and logistics. The authors identify organizational factors that support co-specialization and then examine how co-specialization is associated with enterprise software implementation success, controlling for the endogenous choice to co-specialize.

The empirical results suggest that resource co-specialization is positively associated with implementation success and that the two resource co-specialization pathways that are examined complement each other in providing performance benefits.

This paper contributes to the research literature on outsourcing. The study also provides a new empirical test using a unique data set of 175 firms adopting APS Software.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

The purpose of this study is to explore what design principles need to be considered in Enterprise Resource Planning (ERP) systems for humanitarian organizations (HOs) to enable agile, adaptive and aligned (Triple-A) humanitarian supply chain capabilities and digitize humanitarian operations.

This study follows an embedded case study approach with a humanitarian medical relief organization, Médecins Sans Frontières (MSF), which engaged in a multiyear ERP design at its humanitarian field missions.

This research shows that ERP systems for humanitarian organizations should be designed as unique systems addressing humanitarian organizations' challenges and unique missions, their value generation processes, and resource base in an effort to improve organizational performance. This study presents 12 general design principles that are unique for humanitarian organizations. These design principles provide a high-level structure of guidance under which specific requirements can be further defined and engineered to achieve success.

The results of this study are based on a single case study limiting generalizability. However, the case study was analyzed and presented as an embedded case study with five autonomous subunits using different business processes and following different adoption and implementation approaches. Therefore, the findings are derived based on considerable variance reflective of humanitarian organizations beyond MSF.

This study recognizes that HOs have unique routines that standard commercial ERP packages do not address easily at the field level. The primary contribution of this research is a set of design principles that consider these unique routines and guide ERP development in practice. National and international HOs that are planning to implement information systems, private companies that are trading partners of HOs as well as vendors of ERP systems that are looking for new opportunities would all benefit from this research.

This study fills the gap in the humanitarian literature regarding the design of ERP systems for humanitarian organizations that enable Triple–A supply chain capabilities and it advances the knowledge of the challenges of ERP design by HOs in the context of humanitarian operations.

This paper aims to assess how enterprise resource planning (ERP) performance of Korean small and medium enterprises in manufacturing differs according to different levels of business process reengineering (BPR), information strategic planning (ISP) and ERP customization.

A questionnaire survey was carried out in this research. Responses from 96 small and medium manufacturing companies that have adopted ERP systems were analyzed.

The results of this study suggest that ISP and BPR implementation are positively correlated to ERP performance.

While consulting and customization costs have positive impacts on ERP performance, the level of customization does not influence performance. As one of the pioneering studies that investigate the impact of BPR, ISP and ERP customization on small and medium manufacturing companies, this research contributes to both theory and practice.

In the last years the penetration of enterprise resource planning (ERP) systems within small, medium and large organizations increased steadily. Organizations are forced to adapt their systems and perform ERP upgrades in order to react to rapidly changing business environments, technological enhancements and rising pressure of competition. The purpose of this paper is to focus on the critical success factors for such projects.

The paper is based on a literature review and qualitative interviews with CEOs, CIOs, ERP consultants and project managers who recently carried out ERP upgrade projects in their respective organizations.

This paper identifies 14 critical success factors for ERP upgrade projects. Amongst others, effective project management, external support, the composition of the ERP team and the usage of a multiple system landscape play a key role for the success of the ERP upgrade. Furthermore, a comparison to the critical success factors for ERP implementation projects was conducted, and even though there are many similarities between these types of projects, several differences emerged.

ERP upgrade projects have a huge impact on organizations, but their success and antecedents for it are currently under-researched.

The purpose of this study is to demonstrate that Strategic Enterprise Management (SEM) and Business Intelligence (BI) have the potential to integrate management decisions vertically through an organization’s hierarchy. This study also aims to present a design theory framework and build a model dimension using eight principles serving as mid-range theories.

This study uses a design science perspective to posit how organizations can successfully implement SEMBI (a union of SEM and BI). This study then completes the design theory by building the method dimension using two principles. Finally, the study presents testable hypotheses for the theory and an evaluation using stakeholder attitudes and judgments as proxies for objective measures.

In the search for a prescription for SEMBI success, this study finds that the notion of the Capability Maturity Model (CMM) is a good artifact with which to organize the principles the authors are seeking. CMM has since been adapted to suit different contexts by incorporating relevant principles from those domains. Hereafter, this study refers to SEMBI–CMM as the adapted solution for SEMBI's success.

This study coins and uses the term SEMBI to represent the union of SEM and BI. This term retains its distinct identities and principles and forms a holistic and integrated view of SEM and BI implementation strategies. In an effort to advance this line of research, this study employs a design science perspective to address the question of how an organization can successfully implement SEMBI.

The technical feasibility of using Benford's law to assist internal auditors in reviewing the integrity of high-volume data sets is analysed. This study explores whether Benford's distribution applies to the set of numbers represented by the quantity of records (size) that comprise the different tables that make up a state-owned enterprise's (SOE) enterprise resource planning (ERP) relational database. The use of Benford's law streamlines the search for possible abnormalities within the ERP system's data set, increasing the ability of the internal audit functions (IAFs) to detect anomalies within the database. In the SOEs of emerging economies, where groups compete for power and resources, internal auditors are better off employing analytical tests to discharge their duties without getting involved in power struggles.

Records of eight databases of an SOE in Argentina are used to analyse the number of records of each table in periods of three to 12 years. The case develops step-by-step Benford's law application to test each ERP module records using Chi-squared (χ²) and mean absolute deviation (MAD) goodness-of-fit tests.

Benford's law is an adequate tool for performing integrity tests of high-volume databases. A minimum of 350 tables within each database are required for the MAD test to be effective; this threshold is higher than the 67 reported by earlier researches. Robust results are obtained for the complete ERP system and for large modules; modules with less than 350 tables show low conformity with Benford's law.

This study is not about detecting fraud; it aims to help internal auditors red flag databases that will need further attention, making the most out of available limited resources in SOEs. The contribution is a simple, cheap and useful quantitative tool that can be employed by internal auditors in emerging economies to perform the first scan of the data contained in relational databases.

This paper provides a tool to test whether large amounts of data behave as expected, and if not, they can be pinpointed for future investigation. It offers tests and explanations on the tool's application so that internal auditors of SOEs in emerging economies can use it, particularly those that face divergent expectations from antagonist powerful interest groups.

This study demonstrates that even in the context of limited information technology tools available for internal auditors, there are simple and inexpensive tests to review the integrity of high-volume databases. It also extends the literature on high-volume database integrity tests and our knowledge of the IAF in Civil law countries, particularly emerging economies in Latin America.

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).

This study aims to explain the transformation process from using regular enterprise resource planning (ERP) system into implementing Cloud ERP system in the UAE public sector.

The study uses a qualitative case study and analyzes the primary evidences from in-depth interviews with the case organization’s personnel. It conducts a thematic analysis of the interviews’ findings. Furthermore, the study uses secondary and tertiary resources from published sources comprising the case organization’s website and previous studies.

The findings demonstrated that the transformation process to Cloud ERP could result in different practical benefits in an organization’s controlling system, cost reduction and profitability. Conversely, results revealed that the effectiveness of implementing cloud ERP is dependable on the provider’s professionalism; hence resulting in issues related to minimized organizational independence. In addition, the paper’s findings provide evidenced clarifications about the controversial misconceptions of Cloud ERP’s privacy issues.

The paper is exposed to the regular case studies limitations, as the study is a qualitative research studying one case company. Thus, the study findings should be strengthened by future quantitative researches on more companies with implying more statistical analysis.

The paper has important implications for practitioners and decision-makers, as it presents significant and reality-based information about Cloud ERP implementation’s benefits and drawbacks. It thus enhances decision-makers’ ability to make an appropriate and suitable decision about adopting the Cloud ERP in the public sector.

As Cloud ERP is still emerging, this study is one of the very few case studies that discuss and present some experienced benefits and issues related to Cloud ERP implementation in UAE Government. This study also uses transformation theory to analyze the data.