Search results

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.

The purpose of this study is to address a critical gap in enterprise resource planning (ERP) implementation process for small and medium-sized enterprises (SMEs) by acknowledging and countering cognitive biases through a cognitive bias awareness matrix model. Cognitive biases such as temporal discounting and optimism bias often skew decision-making, leading SMEs to prioritize short-term benefits over long-term sustainability or underestimate the challenges involved in ERP implementation. These biases can result in costly missteps, underutilizing ERP systems and project failure. This study enhances decision-making processes in ERP adoption by introducing a matrix that allows SMEs to self-assess their level of awareness and proactivity when addressing cognitive biases in decision-making.

The design and methodology of this research involves a structured approach using the problem-intervention-comparison-outcome-context (PICOC) framework to systematically explore the influence of cognitive biases on ERP decision-making in SMEs. The study integrates a comprehensive literature review, empirical data analysis and case studies to develop the Cognitive Bias Awareness Matrix. This matrix enables SMEs to self-assess their susceptibility to biases like temporal discounting and optimism bias, promoting proactive strategies for more informed ERP decision-making. The approach is designed to enhance SMEs’ awareness and management of cognitive biases, aiming to improve ERP implementation success rates and operational efficiency.

The findings underscore the profound impact of cognitive biases and information asymmetry on ERP system selection and implementation in SMEs. Temporal discounting often leads decision-makers to favor immediate cost-saving solutions, potentially resulting in higher long-term expenses due to the lack of scalability. Optimism bias tends to cause underestimating risks and overestimating benefits, leading to insufficient planning and resource allocation. Furthermore, information asymmetry between ERP vendors and SME decision-makers exacerbates these biases, steering choices toward options that may not fully align with the SME’s long-term interests.

The study’s primary limitation is its concentrated focus on temporal discounting and optimism bias, potentially overlooking other cognitive biases that could impact ERP decision-making in SMEs. The PICOC framework, while structuring the research effectively, may restrict the exploration of broader organizational and technological factors influencing ERP success. Future research should expand the range of cognitive biases and explore additional variables within the ERP implementation process. Incorporating a broader array of behavioral economic principles and conducting longitudinal studies could provide a more comprehensive understanding of the challenges and dynamics in ERP adoption and utilization in SMEs.

The practical implications of this study are significant for SMEs implementing ERP systems. By adopting the Cognitive Bias Awareness Matrix, SMEs can identify and mitigate cognitive biases like temporal discounting and optimism bias, leading to more rational and effective decision-making. This tool enables SMEs to shift focus from short-term gains to long-term strategic benefits, improving ERP system selection, implementation and utilization. Regular use of the matrix can help prevent costly implementation errors and enhance operational efficiency. Additionally, training programs designed around the matrix can equip SME personnel with the skills to recognize and address biases, fostering a culture of informed decision-making.

The study underscores significant social implications by enhancing decision-making within SMEs through cognitive bias awareness. By mitigating biases like temporal discounting and optimism bias, SMEs can make more socially responsible decisions, aligning their business practices with long-term sustainability and ethical standards. This shift improves operational outcomes and promotes a culture of accountability and transparency. The widespread adoption of the Cognitive Bias Awareness Matrix can lead to a more ethical business environment, where decisions are made with a deeper understanding of their long-term impacts on employees, customers and the broader community, fostering trust and sustainability in the business ecosystem.

This research introduces the original concept of the Cognitive Bias Awareness Matrix, a novel tool designed specifically for SMEs to evaluate and mitigate cognitive biases in ERP decision-making. This matrix fills a critical gap in the existing literature by providing a structured, actionable framework that effectively empowers SMEs to recognize and address biases such as temporal discounting and optimism bias. Its practical application promises to enhance decision-making processes and increase the success rates of ERP implementations. This contribution is valuable to behavioral economics and information systems, offering a unique approach to integrating cognitive insights into business technology strategies.

The study aims to drive conceptual clarity around resistance to information technology projects, integrating multiple facets of the phenomenon from earlier studies.

The study conducts a meta-synthesis of qualitative studies on resistance to technology projects; it analyzes those studies at a case-specific level, compares and contrasts emergent concepts against each other, and “translates” those to the rest of the studies. The study uses the seven-step meta-ethnography method by Noblit and Hare to reciprocally translate emergent concepts to construct the conceptual model.

Through meta-synthesis, the study derives a new conceptual model for resistance to information technology projects, exemplifying how the identified antecedents create user resistance and how the phenomenon progresses within organizations.

This study enriches the observations and conclusions of past individual studies while explicating various facets of the mechanisms that generate and progress technology resistance within organizations. It offers fresh insights into the equivocal nature of the phenomenon and the distinctive ways it progresses from individual to group level.

Many ambitious and costly digital transformation efforts do not succeed due to user resistance. Understanding the mechanisms that create user resistance can help organizations manage technology projects better, thereby reducing the technology assimilation gap and protecting returns on related investments.

There have been extensive studies on technology acceptance (enablers) within organizations, while those relating to technology inhibitors are somewhat limited. However, the symmetry of understanding between enablers and inhibitors is vital for organizations to assimilate promising technologies and transform their business models. This model uses a new lens of sensemaking theory to explain how the antecedents trigger perceived threats and resistance behavior; it highlights the nuances around the development of resistance within individuals and its progression to groups. The resultant model offers better generalizability in organizational contexts.

Drawing on institutional theory analytical perspectives of theorisation and translation, this study aims to explore the institutionalisation of eXtensible Business Reporting Language (XBRL) in Indonesia from a regulatory and filer perspective.

The Indonesian capital market offers a unique case of the integration of XBRL regulatory reporting between multiple regulators and a transfer from capital market regulation to state-level regulation. This study uses semi-structured interviews with key actors employed with Indonesian XBRL-regulatory bodies and listed companies (filers).

External pressures, monitoring issues and tensions in the implementation process were instrumental in the theorisation and translation of XBRL in Indonesia. Specifically, the findings show that choices made with respect to XBRL regulation and implementation created tensions between XBRL reporting fulfilling a monitoring purpose and serving stakeholders’ interests. The findings also indicate that the Indonesian approach to XBRL regulation and implementation had distinct characteristics compared to XBRL implementation in other jurisdictions.

This study emphasises the necessity for robust regulatory support and strict enforcement to navigate the complexities and tensions arising from a multi-regulatory approach. Additionally, it stresses the importance of firms’ readiness and expertise in XBRL as more sophisticated implementation strategies are considered.

Using the analytical lens of theorisation and translation, the study provides a deeper understanding of how a globally diffused accounting technology was institutionalised and legitimised in a developing country. Specifically, this study explains why a conversion approach to XBRL implementation was favoured and how XBRL implementation and reporting were managed and coordinated between different Indonesian regulators.

Although much attention has been paid to understanding employee resistance to reform, little study has been done to explore the effect of employee resistance to public service units' (PSUs) reform in China. To address this need, this work aims to investigate the antecedents of employee resistance to PSUs' reform, especially from the perspective of the heterogeneity of the employees' age.

This study considers the PSUs in Harbin, China, as an example and uses survey questionnaires to analyze the factors influencing employees' resistance when PSUs reform. Besides, the authors developed a research model based on the status quo bias theory, the equity-implementation model.

According to the applied research model, employee resistance to PSU change is primarily influenced by perceived switching costs and benefits. According to their age, this survey also confirms how the employees responded to the reform implementation.

The results of this empirical study inform suggestions for the sustainable development of PSUs and organizational transformations. Overall, this work advances the theoretical understanding of employees' resistance to PSUs’ reform, thereby offering practical insights for managing employee resistance during organizational change.

Overall, given that employee resistance emotion exists in an organization, this study offers theoretical and practical implications for change management strategies.

This study aims to examine the relationship between institutional logics and specifications quality, and how this relationship is mediated by the legitimacy of the procurement process and stewardship behaviour.

This study draws on insights from institutional logics theory, and legitimacy and stewardship behaviour literature. We conducted an extended literature review to gain a comprehensive understanding of “institutional logics” and their manifestations in organizational contexts, utilizing the 2000–2024 data collected from the EBSCO, Scopus and Web of Science databases, complemented with Google Scholar. We gather that institutional logics manifest in several forms, and that while some organizations may thrive on a single logic, in certain contexts institutional logics can manifest in combinations – “multiple logics or hybrids”. Based on this understanding, we developed testable research hypotheses, predicting the influences of institutional logics – professional logic, efficient service logic and delivery (market) logic, on legitimacy, stewardship behaviour and specifications quality. We then carried out an empirical study, adopting a quantitative cross-sectional survey design with a self-administered questionnaire to test the hypothesized relationships. The empirical data were obtained from 162 procuring and disposing entities in Uganda and analyzed using the partial least squares structural equation modelling technique.

The study findings reveal that institutional logics exert a strong positive effect on the legitimacy of the procurement process and on stewardship behaviour, which, in turn, both positively influence specifications quality.

The study findings have implications for theory and practice. The study findings provide useful insights that support the conceptual and theoretical development of institutional logics theory and applications in procurement literature. In addition, the study findings enhance procurement managers’ understanding of the mechanisms through which institutional logics can foster specifications quality. However, considering the fact that the study was conducted in a single country context, and focused on the public sector only, the findings of the study might not be generalizable globally.

This study contributes to established knowledge about quality management and procurement by examining the legitimacy of the procurement process and stewardship behaviour of those involved in procurement processes as mechanisms through which procuring entities are able to use institutional logics to enhance specifications quality. In addition, the study highlights areas for future research that may be explored to increase understanding of the value of institutional logics in ensuring specifications quality, and the link between specifications quality and the general performance of procuring entities.

This study aims to provide a nuanced understanding of the relationship between task-technology fit and employee innovative behavior, as well as the role of creative self-expectations.

Hierarchical regression analysis was used to test the proposed multilevel model on a sample of 407 employees working in Chinese companies.

Task-technology fit stimulates employee innovative behavior through the regulation of creative self-expectations and positive emotions. When creative self-expectations is low, the promoting effect of task-technology fit on innovative behavior is enhanced. However, when creative self-expectations is too high, this effect is reversed due to employees’ preference for challenging and complex work.

In the process of enterprise digital transformation, managers should not only focus on the alignment between employees' skills and individual task expectations, but also pay attention to employees' emotions and individual trait differences, to enhance the likelihood of innovative behavior occurrence and achieve successful enterprise digital transformation.

This study enriches the research on task-technology fit and provides recommendations for organizations to achieve digital transformation.

The objective of this research is to identify and prioritize the critical factors that influence the adoption of blockchain technology within the banking sector.

A well-known theoretical framework, the “Technology Organization Environment (TOE),” was chosen to analyze what criteria and sub-criteria affect blockchain adoption in the banking sector after a thorough assessment of the prior literature. Following that, 3 evaluation criteria and 14 sub-criteria were selected and verified using expert opinion. A survey design was created, and data for the study has been collected from various information technology (IT) managers/officers in the banking sector. A fuzzy analytic hierarchy process (Fuzzy-AHP) was then used to meet the purpose of the research.

The study identified that the organizational dimension is the most significant criteria for blockchain adoption in the banking sector, followed by the environmental dimension. In contrast, the technological dimension is the least influential criterion. Clientele pressure, IT resources, financial resources, pressure from competitors and relative advantage are the most influential sub-criteria for blockchain adoption.

This study provides valuable insights to bank managers, blockchain and IT developers, third-party service providers and policymakers. For instance, adopting the same blockchain platform is easier for both large and small banks for banking operations by using third-party service provider. At the same time, banks should have the banks' own core team to implement the blockchain-based systems or to have control over the third-party service providers during the adoption stage.

To the best of the authors' knowledge, no empirical studies have used a holistic organizational context to understand the factors influencing the adoption of blockchain technology from traditional to blockchain-based banking systems.

Megaproject knowledge innovation (MKI) is perceived as a critical strategy for engineering value co-creation and industrial chain upgrading. Ascertaining the impact mechanism of MKI is a crucial initial step towards improving management practices. Within the framework of complex systems in megaprojects, factors exhibit intricate interdependencies. However, the current domain of knowledge has either overlooked or oversimplified this relationship and therefore cannot propose pragmatic and efficacious strategies for enhancing MKI. To close this gap, this study develops a Bayesian network (BN) model aiming to investigate the interdependencies among MKI-related factors and their impact on MKI.

First, this study implements literature review, expert interview and field investigation to identify the influencing factor nodes for the network model development. Second, a Bayesian network was constructed by integrating the expert knowledge with Dempster-Shafer theory. Next, a MKI measurement model was established using 253 training samples. Finally, the factor significance and optimal MKI improvement strategies are identified from the sensitivity analysis and probabilistic reasoning within the BNs.

The results indicate that (1) the BN model exhibits significant reliability and holds promotion and application value in formulating MKI management strategies; (2) knowledge sharing, shared vision and leadership are the key influencing factors of MKI; and (3) simultaneously improving institutional pressure, leadership and knowledge sharing is the most optimal strategy to enhance MKI.

This study innovatively introduced the BN method into the domain of MKI management, providing an appropriate approach for modelling complex relationships among factors and investigate nonlinear influences. The developed model raises megaproject stakeholders’ awareness about factors influencing MKI and presents quantified strategies that increase the likelihood of maximising MKI levels. Its ease of generalisability positions it as a promising decision support tool, facilitating the implementation of sustainable MKI practices.

This study aims to examine the impact of client information technology (IT) capabilities on audit report lag and audit fees in Jordanian companies listed on the Amman Stock Exchange (ASE) during the COVID-19 pandemic.

This study analysed financial and non-financial data from 72 Jordanian public shareholding companies listed on the ASE between 2014 and 2021. Using fixed- and random-effects models, the authors examined the impact of client IT capabilities on audit report lag and audit fees. The authors also examined how the COVID-19 pandemic might affect audit report lag and audit fees. The analysis incorporated various control variables specific to the Jordanian context to ensure accuracy.

Empirical evidence indicates that client IT capabilities do not significantly impact audit report lag and audit fees. In contrast, the COVID-19 pandemic has positively impacted audit report lag and audit fees, leading to an increase in audit report lag of 60 to 67 days and an increase in audit fees of approximately 15%. It is worth noting that these effects are more pronounced when influenced by factors including return on assets, company losses and audits conducted by the Big 4 firms.

The scope of this study, which focuses on Jordanian firms, may limit the generalisability of the findings to other contexts. Reliance on aggregate IT infrastructure and software assets as proxies for IT capabilities might not fully capture their multifaceted nature, overlooking the qualitative aspects crucial for audit outcomes. Furthermore, excluding external factors such as governmental regulations underscores the need for future research to explore the nuanced interplay between IT capabilities, internal control systems and regulatory environments, enriching our understanding of audit practices.

This study contributes to auditing literature by examining the interplay between IT capabilities and audit processes during the COVID-19 pandemic in Jordan. This study highlights the unexpected finding that IT capabilities have minimal impact on audit report lags and fees, opening new avenues for research on how pandemics and similar crises can reshape auditing practices and influence regulatory policies in an evolving economic environment.