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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 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.

Although it is commonly agreed that prescriptive analytics can benefit organizations by enabling better decision-making, the deployment of prescriptive analytics tools can be challenging. Previous studies have primarily focused on methodological issues rather than the organizational deployment of analytics. However, successful deployment is key to achieving the intended benefits of prescriptive analytics tools. Therefore, this study aims to identify the enablers of successful deployment of prescriptive analytics.

The authors examine the enablers for the successful deployment of prescriptive analytics through five organizational case studies. To provide a comprehensive view of the deployment process, each case includes interviews with users, managers and top management.

The findings suggest the key enablers for successful analytics deployment are strong leadership and management support, sufficient resources, user participation in development and a common dialogue between users, managers and top management. However, contrary to the existing literature, the authors found little evidence of external pressures to develop and deploy analytics. Importantly, the success of deployment in each case was related to the similarity with which different actors within the organization viewed the deployment process. Furthermore, end users tended to highlight user participation, skills and training, whereas managers and top management placed greater emphasis on the importance of organizational changes.

The results will help practitioners ensure that key enablers are in place to increase the likelihood of the successful deployment of prescriptive analytics.

In recent years, the emergence of Industry 4.0 technologies as a way of increasing productivity has attracted the attention of the manufacturing industry. This study aims to investigate the relationship between Industry 4.0 technologies and lean tools (LTs) by measuring how the internalisation of LTs influences the adoption of Industry 4.0 technologies and how the synergy between them helps improve productivity in European manufacturing firms.

Results from 1,298 responses were used to analyse linear regression and study the correlation between the use of LTs and Industry 4.0 technologies.

Results show that the companies analysed tend to implement more Industry 4.0 technologies when their level of lean internalisation is high.

This study provides useful information for managers of manufacturing firms by showing the correlation between LT internalisation and Industry 4.0 technologies, corroborating that optimal implementation of these technologies is preceded by a high level of LT internalisation. Furthermore, although there are studies showing the relationship between LTs and Industry 4.0 technologies, none consider the intensity of their implementation.

The purpose of this paper is to present a conceptual model that defines the essential components shaping the new Digital Supply Chains (DSCs) through the implementation and acceleration of Industry 4.0.

The scope of the present work exposes a conceptual approach and review of the key literature from 1989 to 2019, concerning the evolution and transformation of the actors and constructs in logistics and Supply Chain Management (SCM) by means of examining different conceptual models and a state-of-the-art review of Industry 4.0’s concepts and elements, with a focus on digitization in supply chain (SC) processes. A detailed study of the constructs and components of SCM, as defined by their authors, resulted in the development of a referential and systematic model that fuses the inherent concepts and roles of SCM, with the new technological trends directed toward digitization, automation, and the increasing use of information and communication technologies across logistics global value chains.

Having achieved an exploration of the different conceptual frameworks, there is no compelling evidence of the existence of a conceptual SCM that incorporates the basic theoretical constructs and the new roles and elements of Industry 4.0. Therefore, the main components of Industry 4.0 and their impact on DSC Management are described, driving the proposal for a new conceptual model which addresses and accelerates a vision of the future of the interconnectivity between different DSCs, grouped in clusters in order to add value, through new forms of cooperation and digital integration.

This research explores the gap in the current SCM models leading into Industry 4.0. The proposed model provides a novel and comprehensive overview of the new concepts and components driving the nascent and current DSCs. This conceptual framework will further aid researchers in the exploration of knowledge regarding the variables and components presented, as well as the verification of the newly revealed roles and constructs to understand the new forms of cooperation and implementation of Industry 4.0 in digitalized SCs.

The purpose of this article is to develop a configurational approach based on the TOE framework (technology, organization and environment) to understand the degree of implementation of I4.0 technologies in manufacturing small- and medium-sized enterprises (SMEs). Specifically, the study considers technological infrastructure and competence, I4.0 integration capabilities, organizational agility and strategic flexibility, environmental dynamism and industry-specific forces as simultaneous pre-conditions for achieving an effective implementation of I4.0 technologies.

This study uses the fuzzy-set qualitative comparative analysis (fsQCA) methodology as it allows for asymmetric and configurational-focused testing of proposition and sound theoretical development. In total, 305 responses were collected through a survey administered to SME managers in Europe and the United Kingdom (UK).

The study examines the influence of technology, organizational and environmental aspects on I4.0 technologies implementation in SMEs. High I4.0 degree of implementation is structured around 5 configurations, while other 4 configurations are related to low levels of I4.0 implementation.

This study proposes a configurational approach for SMEs to become I4.0 ready and how they may successfully implement I4.0 technologies. Such findings represent an original and novel contribution to existing research, offering a broad view on the I4.0 implementation by manufacturing SMEs.

Drawing on the theoretical concept of organisational fit, this paper questions the relevance of employees' participation in the link between continuous improvement (CI) and operational performance. The literature has long emphasised that to be successful, CI implementation needs to rely on employees' involvement as soon as its inception. This paper argues that this approach is not generalisable.

Based on a database of 330 firms across 15 countries, regression analyses were used to hypothesise that the fit between CI and employee participation is positively associated with operational performance, and that the fit between CI and centralisation of authority is negatively associated with operational performance. The authors also ran a robustness check with polynomial regression analyses and the response surface methodology.

CI–employee participation fit is positively associated with operational performance, suggesting that there is less need for employees to be involved when a firm has scarcely developed CI. Employee participation becomes gradually more relevant as CI progresses. Moreover, the results demonstrate that the CI–centralisation of authority fit is negatively associated with operational performance, suggesting that a top-down management approach with centralised authority is preferable when CI is low, whereas a bottom-up management approach is helpful when a firm has extensively developed CI.

This research draws on the concept of organisational fit to explore the relationships between internal practices in the operations management literature. The authors suggest that managers should dynamically balance the practices of employee participation and centralisation of authority as CI improves. This study highlights that CI has different evolutionary levels that require different managerial approaches and practices.

The purpose of this paper is to investigate KM practices that may be in place in the higher education institutions (HEIs) and whether the KM practices are made known to the employees for improving the teaching and learning environment provided at the Malaysian higher education institutions.

Data were collected using a personal administrated method made available to private higher education institutions academic members in five states with 30 or more employees. A total of 1,100 survey questionnaires were handed out, out of which 273 were collected and were usable (24.8 per cent response rate). The sample was checked for response and non-response bias. Results were tested using SPSS application and questionnaire tools.

It was essential to establish the knowledge management (KM) capacity in key areas such as the ability to recognise experts within the institution, leadership’s innovation, knowledge sharing and knowledge acquiring work culture, and technology usage. KM tools and techniques would help the institutions to meet their competitive goals; therefore, it is vital for HEIs to create KM awareness among the employees.

Similar to most studies, it is anticipated that the participants’ awareness of KM practices at their HEIs is very high. The samples were collected to evaluate the general view of KM awareness and how participants perceived KM practices. The total samples received for this study were expected; however, they were sufficient to study the impact.

This paper provides support for the importance of KM practices and employees awareness at HEIs to enhance innovation and performance teaching and learning environment.

This paper is one of the first papers to find empirical support for the role of KM practices at HEIs. Further, the positioning of KM practices as a competitive tool can be considered as an influential factor to competitive advantage.

The information systems (IS) literature has indicated the importance of data analytics capabilities (DAC) in improving business performance in organizations. The literature has also highlighted the roles of organizations’ data-related resources in developing their DAC and enhancing their business performance. However, little research has taken resource quality into account when studying DAC for business performance enhancement. Therefore, the purpose of this paper is to understand the impact of resource quality on DAC development for business performance enhancement.

We studied DAC development using the resource-based view and the IS success model based on empirical data collected via 19 semi-structured interviews.

Our findings show that data-related resource (including data, data systems, and data services) quality is vital to the development of DAC and the enhancement of organizations’ business performance. The study uncovers the factors that make up each quality dimension, which is required for developing DAC for business performance enhancement.

Using the resource quality view, this study contributes to the literature by exploring the role of data-related resource quality in DAC development and business performance enhancement.

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.