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The purpose of this study is to investigate the post–enterprise resource planning (ERP) issues and challenges in the context of Saudi Arabia. There is a lack of research in the context of developing countries regarding post-ERP implementation issues and challenges. The high failure rate of the ERP system is a reflection of many management issues that occurred at different phases of ERP implementation. Previous research indicated that even after a successful implementation, the ERP system was unable to sustain itself in the organizations.

An exploratory case study design was adopted to proceed with this research process at two organizations in Saudi Arabia. The interviews of the top and middle management are conducted and transcribed. These case studies were further analyzed using the Creswell approach to generate several themes, and descriptions provided a deeper understanding of the post ERP implementation issues and challenges.

Research findings show that for successful ERP implementation, identified factors are top management support, integration, strategy, employee resistance, BPR, change management, vendor selection, team formation and culture. Moreover, factors for the post-ERP implementation that led to sustainability are top management support, training, system adoption, system testing, data migration, cost overrun, employee retention and post-implementation support.

This study is unique in its type to examine the issues and challenges organizations face after deploying ERP initiatives. This research's findings were useful and supportive for the senior management interested in successfully sustaining such an initiative in the organization.

This article aims to systematically review the literature published in recognized journals focused on cognitive heuristic-driven biases and their effect on investment management activities and market efficiency. It also includes some of the research work on the origins and foundations of behavioral finance, and how this has grown substantially to become an established and particular subject of study in its own right. The study also aims to provide future direction to the researchers working in this field.

For doing research synthesis, a systematic literature review (SLR) approach was applied considering research studies published within the time period, i.e. 1970–2021. This study attempted to accomplish a critical review of 176 studies out of 256 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioral finance domain-related explicitly to cognitive heuristic-driven biases and their effect on investment management activities and market efficiency as well as on the origins and foundations of behavioral finance.

This review reveals that investors often use cognitive heuristics to reduce the risk of losses in uncertain situations, but that leads to errors in judgment; as a result, investors make irrational decisions, which may cause the market to overreact or underreact – in both situations, the market becomes inefficient. Overall, the literature demonstrates that there is currently no consensus on the usefulness of cognitive heuristics in the context of investment management activities and market efficiency. Therefore, a lack of consensus about this topic suggests that further studies may bring relevant contributions to the literature. Based on the gaps analysis, three major categories of gaps, namely theoretical and methodological gaps, and contextual gaps, are found, where research is needed.

The skillful understanding and knowledge of the cognitive heuristic-driven biases will help the investors, financial institutions and policymakers to overcome the adverse effect of these behavioral biases in the stock market. This article provides a detailed explanation of cognitive heuristic-driven biases and their influence on investment management activities and market efficiency, which could be very useful for finance practitioners, such as an investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making their financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on cognitive heuristic-driven biases displayed by investors. The current study is original in discussing the role of cognitive heuristic-driven biases in investment management activities and market efficiency as well as the history and foundations of behavioral finance by means of research synthesis. This paper is useful to researchers, academicians, policymakers and those working in the area of behavioral finance in understanding the role that cognitive heuristic plays in investment management activities and market efficiency.

This study aims to identify the impact of ethical leadership on ethical voice by determining two paths covering relational identification and psychological safety. The first path focused on relational identification and psychological safety. Alternatively, the second path focused on organizational identification and psychological ownership leading to ethical voice. The specific objective of the study is to develop and test an integrated model of ethical leadership.

The objectives were achieved through the adoption of quantitative research techniques. Two hundred forty-eight samples were collected from the banking sector using quantitative research techniques, and data was gathered through a self-administrated questionnaire. Exploratory and confirmatory factor analyses were used through AMOS to generate the results and test hypotheses.

The results suggested a significant impact of ethical leadership on ethical voice, while the other paths’ results, such as relational identification, psychological safety, organizational identification and psychological ownership, suggested partial mediation. The study result adds new insights into ethical leadership and social exchange theory since it tested overlooked paths in the literature, such as relational identification and psychological safety.

The research highlights the significance of ethical voice as a desirable organizational behavior. Ethical voice contributes to a culture of accountability, transparency and ethical decision-making. Organizations should establish channels and platforms for employees to voice ethical concerns and suggestions. This may involve regular feedback sessions, anonymous reporting mechanisms and protection policies for whistleblowers. Leaders should actively encourage and value ethical voices as a valuable contribution to the ethical climate of the organization.

The study found that ethical leaders influence their followers in such a way that they adopt ethical behavior. It is also validated that organizational ethics are shared by employees who interact with ethical leaders. So, departments should train such leaders because ethical leadership positively affects followers’ attitudes and behaviors, and organizations should encourage ethical behavior in supervisors and subordinates. The study also found that relational and organizational identification helps employees develop psychological capabilities, which leads to reporting workplace misconduct. The current study tested these mechanisms collectively and found that ethical leadership significantly contributes to ethical voice.

The current study highlighted the role of ethical leaders in promoting ethical behavior, improving employee well-being and engagement, cultivating collaboration and inclusion, and making a contribution to the overall ethical climate within organizations and society as a whole. Organizations can have a positive impact on the social fabric by cultivating a culture of ethics, respect and social responsibility if they make these considerations their top priorities.

The current study is unique since it is intended to develop and test an integrated model of ethical leadership and ethical voice. This research combines an integrated model, focusing on employees’ identities and self-concepts and examining ethical voice as a behavioral outcome.

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 aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

This chapter offers a comprehensive review the literature on authentic leadership (AL). The authors employ a bibliometric approach to identify, classify, visualise and synthesise relevant scholarly publications and the work of a core group of interdisciplinary scholars who are key contributors to the research on AL. They review 264 journal articles, adopting a clustering technique to assess the central themes of AL scholarship. They identify five distinct thematic clusters: authenticity in the context of leadership; structure of AL; social perspectives on AL; dynamism of AL; and value perceptions of AL. Velt and Sinkovics assert that these clusters will help scholars of AL to understand the dominant streams in the literature and provide a foundation for future research.

This study aims to present a research model to investigate the potential impact of human capital, structural capital and social capital on e-banking proactiveness. In addition, it reveals the potential impact of e-banking proactiveness on competitive intelligence and competitive agility. Also, it aims to explore the impact of competitive intelligence on competitive advantage and competitive agility. Finally, the impact of competitive agility on competitive advantage will be examined.

In order to gather data, a questionnaire was prepared and administered to 211 respondents in Jordan. The research model and hypotheses were then assessed using Structural Equation Modeling – Partial Least Squares (SEM-PLS).

The study demonstrated a significant impact of human capital, structural capital and social capital on e-banking proactiveness. The findings confirm that e-banking proactiveness significantly impacts competitive intelligence and achieving competition. Moreover, the findings confirm that competitive intelligence significantly impacts competitive agility. Also, the findings revealed a substantial relationship between competitive intelligence and competitive advantage. Finally, the results discovered that competitive agility significantly impacts competitive advantage.

The research gives valuable insights into the elements that drive e-banking proactiveness, which can beautify the proactiveness literature is well-known. By uncovering the position of intellectual capital in fostering proactiveness, this examination contributes to deeper information on the way financial institutions can successfully respond to market modifications, patron needs and technological advancements. Future scholars can build upon these findings to discover proactiveness in different sectors and industries, thereby broadening the understanding of proactive behaviors throughout numerous contexts.

This research aims to examine the effects of corporate digital transformation on firm value, with a particular focus on the mediating roles played by cost leadership and differentiation strategies.

This study employs word frequency analysis to create corporate digital transformation indicators and determine how corporate digital transformation impacts firm value. The data used in the analysis comes from 2,056 listed manufacturing enterprises in China between 2010 and 2019.

This study demonstrates that digital transformation has a favorable impact on firm value, and that cost leadership strategy and differentiation strategy significantly mediate the relationship between both of them.

This study utilized word frequency analysis to assess the state of corporate digital transformation. It lacked a more thorough description of internal production processes, operational efficiency, and the pace of digital transformation.

The results of this study can not only promote the digital transformation and firm value, but also provide a theoretical basis for enterprises to choose a reasonable competitive strategy in the digital transformation.

This study contributes significantly to the field of firm value research by including digital transformation as a fundamental component. Furthermore, it investigates how cost leadership strategy and differentiation strategy play mediating roles, providing a new perspective and explanatory mechanism for understanding the influence of digital transformation on firm value.

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 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.