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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 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.

This study aims to investigate the factors influencing the adoption of data analytics in performance management. By examining the role of organizational and environmental contexts, this study contributes to the existing literature by proposing a novel and detailed technology-organization-environment (TOE) model for the complex interplay between firm characteristics and the adoption of data analytics. The results offer valuable insights and practical implications for organizations seeking to leverage data analytics for effective performance management.

The research draws upon a data set encompassing over 21,869 companies operating across all European Union member states. A multilevel logistic regression model was developed to evaluate the influence of organizational and environmental factors on the likelihood of adopting performance analytics in organizations.

The findings indicate that the lack of awareness of the benefits of data analytics and its practical application to address specific business challenges is a significant barrier to its adoption. Organizational contexts, such as variable-pay systems, employee training, hierarchical structures and frequency of monetary rewards, also influence the adoption of data analytics.

The study informs managers about the strategic role of data analytics capabilities in performance management for improved business intelligence and driving data culture.

The study helps managers understand the strategic role of data analytics capabilities in performance management, leading to improved business intelligence and fostering a data-driven culture in five key areas: structural alignment, strategic decision-making, resource allocation, performance improvement and change management.

The study advances the TOE theory, making it a more detailed and complete framework, particularly applicable to the adoption of performance analytics. It identifies the main factors of adoption that play a crucial role in this process.

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.

This study aims to investigate the factors influencing the adoption intention of artificial intelligence (AI) by micro, small and medium enterprises (MSMEs) in Jordan.

The study adopts the technology–organization–environment (TOE) model. It examines the moderating effects of innovation culture, employee digital skill level and market competition on the relationships between the independent and dependent variables. A survey was utilized to collect data from 537 MSME owners or managers in Jordan and employed partial least squares structural equation modeling to test the hypotheses.

The results of the study support seven out of eight hypotheses. Business innovativeness, management support, perceived benefits and technological infrastructure have positive and significant effects on AI adoption intention, while perceived costs have no significant effect. However, the innovation culture, employee digital skill level and market competition were found to moderate the relationships between some of the independent variables and dependent variables.

The study provides valuable insights and recommendations for MSME owners, managers, employees, policymakers, educators and researchers interested in promoting and facilitating AI adoption by MSMEs in Jordan.

The current attempt extends the TOE framework by adding significant constructs representing the three contexts. Moreover, it is one of the few studies that analyzed the factors influencing the adoption intention of AI by MSMEs in Jordan, which are significant to the Jordanian economy and represent 99.5% of enterprises.

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.

Cyber security has never been more important than it is today in an ever more connected and pervasive digital world. However, frequently reported shortages of suitably skilled and trained information system (IS)/cyber security professionals elevate the importance of delivering effective Security Education,Training and Awareness (SETA) programmes within organisations. Therefore, the purpose of this study is the questionable effectiveness of SETA programmes at changing employee behaviour and an absence of empirical studies on the critical success factors (CSFs) for SETA programme effectiveness.

This exploratory study follows a three-stage research design to give voice to practitioners with SETA programme expertise. Data is gathered in Stage 1 using semi-structured interviews with 20 key informants (the emergence of the CSFs), in Stage 2 from 65 respondents to a short online survey (the ranking of the CSFs) and in Stage 3 using semi-structured interviews with nine IS/cyber security practitioners (the emergence of the guiding principles). Using a multi-stage research design allows the authors to propose and evaluate the 11 CSFs for SETA programme effectiveness.

This study conducted a mean score analysis to evaluate the level of importance of each CSF within two independent groups of IS/cyber security professionals. This multi-stage analysis produces a ranked list of 11 CSFs for SETA programme effectiveness, while the difference in the rankings leads to the emergence of five CSF-specific guiding principles (to increase the likelihood of delivering an effective SETA programme within an organisational context). This analysis also reveals that most of the contradictions/differences in CSF rankings between IS/cyber security practitioners are linked to the design phase of the SETA programme life cycle. While two CSFs, “maintain quarterly evaluation of employee performance” (CSF-DS6) and “build security awareness campaigns” (CSF-EV1), represent the most significant contradiction in this study.

The 11 CSFs for SETA programme effectiveness, along with the five CSF-specific guiding principles, provide a greater depth of knowledge contributing to both theory and practice and lays the foundation for future studies. Therefore, the outputs of this study provide valuable insights on the areas that practice needs to get right to deliver effective SETA programmes.

Hoping to increase the productivity of their employees, firms provide and expect their employees to use approved mobile apps. However, despite an intuitive appeal, the relationship between information technology usage and productivity is still seen as paradoxical. This study examines the relationship between employees' experience and engagement with business mobile apps provided by employers and its effects on employee work productivity.

Data from respondents who use employer-provided business apps were used to test the hypotheses. Measurement-corrected latent scores extracted from the PLS measurement evaluation were used in regression-centric assessment using PROCESS.

Results indicate that employee-users’ experience-based attributions of the business app, i.e. customization, performance quality and compatibility, have positive effects on productivity mediated by participation intensity. Further, work type (retail vs non-retail) and the depth of the employee user’s experience moderate experience-based attributions' indirect effects on productivity.

Unlike previous studies delving into this topic, this study focuses solely on the mediation and moderation effects for hypothesis testing. Specifically, this study investigates effects conditional on work type (retail vs non-retail), which the authors believe has significant implications for retailing. These findings have interesting implications for both future research and managers.

The purpose of this paper is to examine whether employee outcomes of employee performance and job satisfaction mediate and enhance the effect of e-HRM usage on organizational performance.

Data were collected through a survey involving 35 organizations using e-HRM systems. A partially mixed sequential dominant status explanatory design was used for the study. A stratified convenience sampling technique was used for the quantitative phase of the study. A purposive sampling technique was employed for the qualitative phase. A structural equation modelling technique with the use of the process macro approach was used to analyse collected data.

There is a positive relationship between e-HRM usage and employee outcomes. Employee performance and job satisfaction mediate the effect of e-HRM usage on organizational performance. Employee performance and job satisfaction are contextual variables that characterize effective e-HRM configurations.

Organizations should invest in employee outcomes in order to maximize the potential of e-HRM. The e-HRM configurations characterized by a multiplicity of dimensions are more likely to add to organizational value creation. The deployment of e-HRM systems should be preceded by high levels of employee performance and job satisfaction, for organizational success.

The study contributes to a growing body of knowledge on dimensions, which characterize effective e-HRM configurations, yielding organizational success. Employee performance and job satisfaction should be added to the characteristics of effective e-HRM configurations.

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.