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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.

We use design thinking in the context of accounting pedagogy to exploit recent advances in cybernetics in the form of generative artificial intelligence technology. Relying on the intuition that supplementing or augmenting human argumentation (natural intelligence or NI) with parallel AI output can produce better student written assignments, we posit the “augmentation premise,” that is, ((NI + AI) > AI > NI). To test the augmentation premise, we compare student written submissions in an Accounting Information Systems (AIS) course with and without the benefit of parallel generative AI output. We then evaluate how the generative AI output enhances student-crafted revisions to their initial submissions. Using a summative quality improvement index (QII) consisting of quantitative and qualitative assessments, we present preliminary evidence supporting the augmentation premise. The augmentation premise likely extends to other accounting subdisciplines and merits generalization for enriching accounting pedagogy.

This paper aims to investigate the influence of sustainable enterprise resource planning (S-ERPs) systems implementation on sustainability performance.

A 1 × 2 experiment was conducted, involving a sample of 72 professional accountants enrolled in MPA, MBA and DBA programs at two prominent Egyptian universities. Simple linear regression was used to analyze the data.

The results reveal positive relationships between the implementation of S-ERPs and economic, environmental and social sustainability performance.

Considering the research methodology used, which relies on a laboratory experiment design; nevertheless, empirical data derived from a quasi-experiment conducted in a real-world context would offer valuable insights into the existing literature.

For manufacturing sector managers, the results offer value as organizations can benefit from S-ERP adoption in the internal and external integration of sustainability functions. The findings also provide decision-makers in the manufacturing context, particularly in emerging countries, with tangible reasons to consider S-ERP adoption for holistic sustainability benefits including waste management, resource consumption reduction and management of sustainable supply chain complexities. Further, the findings provide valuable insights for ERP vendors on how they can develop their ERP packages to align with software sustainability criteria.

This study is among the few that experimentally investigates the influence of S-ERPs implementation on sustainability performance within the manufacturing sector, especially in an emerging context such as Egypt. This unique contribution provides valuable insights into the complex connection between technology adoption and sustainability outcomes.

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.

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).

Organizational technologies can be classified according to the roles they play as either commodity or strategic. Commodity technologies support common operations, while strategic technologies address perceived threats to competitiveness, often identified by strategic foresight. These must go through an adoption process before playing an effective role in strategy execution. The adoption process includes known activities, ranging from sourcing (itself from in-house development to turn-key acquisition) to operational integration. This paper aims to reveal strategic technology adoption risks that arise during strategy execution.

A gradually developed causal loop diagram model, supported by general literature, introduces three general classes of technology adoption risks: mismatched requirements, supplier dependence and unmanaged life cycles.

Rather than managed, these risks are incurred or avoided depending on decisions made during the adoption process.

Despite the scarce literature coverage for the approach, examples revealing the presence of adoption risks are nevertheless available in the well-documented history of enterprise resource planning (ERP).

Although ERP is presented as a general-purpose strategic technology, the unique business features of maritime container terminals pose serious challenges to its adoption, which provides additional support to the discussion and reinforces the conclusions.

The approach to identifying risks in strategic technology adoption departs from the current risk paradigm in two significant ways. First, it emphasizes policy decision-making rather than external events. Second, it views risks as systemic rather than occurring independently.

In a conventional sense, information technology has frequently been considered a source of Lean waste management. However, as the corporate world evolves, new models that provide a competitive edge by merging technical breakthroughs with the Lean paradigm must be developed. Enterprise resource planning (ERP), which is such technological advancement, is found to be highly influential for Lean implementation. However, there is a dearth of literature on the adaptability of ERP to minimise Lean waste in the construction industry. This paper, therefore, aims to investigate the possibility of applying ERP to minimise Lean waste in the construction industry.

The study used a qualitative approach, consisting of fifteen (15) expert interviews and code-based content analysis was used to analyse the empirical data.

The findings revealed the challenges faced when applying ERP with the Lean concept and the strategies that would help overcome the challenges. Most of the challenges could be overcome through training and awareness programmes and proper team management. The study also found that ERP could be applied with Lean to eliminate waste generation in the construction industry.

This paper contributes to the theory by providing an evaluation of the possibility of adopting ERP to eliminate Lean waste in the construction industry. The study will contribute to new knowledge related to strategies for proper use of ERP for Lean waste minimisation, which will be useful for future researchers in the area.

This paper aims to propose a theoretical extension of the information system success model (ISSM) to evaluate enterprise resource planning (ERP) success at an organizational level in Jordan. It explores whether information quality, system quality and service quality have a positive impact on both perceived usefulness and user satisfaction as antecedents of organizational impact.

A questionnaire was undertaken to gather data from chief information officers among Jordanian firms, with a total of 134 valid returns tested via partial least squares structural equation modeling.

The results showed that most of the research hypotheses proposed are empirically supported, with the exception of the influence of service quality on user satisfaction which was extremely low.

To the best of the authors’ knowledge, this is the first empirical work that measured ERP success from an organizational perspective in Jordan. It also provides insight into how the factor of perceived usefulness is incorporated into ISSM in the mandatory system case and its influences on organizational benefits.

The present study shows that the implementation and development of enterprise resource planning (ERP) systems as a technological innovation provide a competitive advantage that helps to improve the functionality of business intelligence (BI) systems in the digital transformation of manufacturing companies, in addition to improving overall firm performance.

The research uses the structural equation approach based on PLS-SEM technique with a sample of 120 firms in the manufacturing industry in Coahuila, Mexico.

The paper provides empirical insights into how the interaction of ERP systems and innovation significantly affects the functionality of BI Systems and has a substantial effect on overall firm performance.

Empirical evidence of how advanced digital management systems (ERP and BI) impact digitalization processes in organizations by improving performance is still scarce.