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Several different factors have an influence on the hotel sector in Jordan. Due to the different circumstances and the turbulence in this region, hotels face a competitive and dynamic economic environment, which causes these hotels to seek differentiation. Consequently, hotels need different strategies and support from information technology to achieve a competitive advantage. The purpose of this study is to investigate the extent to which enterprise resource planning ERP system usage affects service differentiation in the hotel sector in Jordan and examine the mediating effect of organizational agility on the aforementioned relationship.

Questionnaires were used to collect data from the hotel sector in Jordan. The response percentage was 75.41%.

The result showed that there is a significant effect of ERP system usage on service differentiation in Jordanian hotels, and this relationship was mediated by organizational agility. Organizational agility and its dimensions have a partial mediating role on the relationship between ERP system usage and service differentiation except for responsiveness which has a full mediating role. So, being an agile hotel will increase the ability to achieve service differentiation by using ERP systems.

This research focuses on investigating the mediating role of organizational agility in the relationship between ERP system usage and service differentiation within hotel sector in Jordan. Moreover, this research investigated the applicability of organizational agility on the hotel sector as it is mainly implemented in the manufacturing sector. The results show that organizational agility and its dimensions have a partial mediating role on the relationship between ERP system usage and service differentiation except responsiveness which has a full mediating role. So, being an agile hotel will increase the ability to achieve service differentiation by using ERP systems. Therefore, hotel practitioners in Jordan should focus on applying the required technologies and achieving organizational agility in order to achieve service differentiation. In addition, this study highlights that ERP usage has a positive impact on achieving organizational agility and service differentiation; hence, using these systems will help hotels in Jordan to implement agility capabilities which, in turn, help to achieve service differentiation. However, there are real challenges in hotel sector as implementation of ERP is expensive and time-consuming. The outcomes of this research can have additional reference that could benefit researchers in the future and bring attention of hotel managers in Jordan to the importance and advantages of this research.

A new model has been developed. An empirical investigation was performed on the hotel sector in Jordan to test the new model.

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 study explores the critical success factors (CSFs) for Security Education, Training and Awareness (SETA) program effectiveness. The questionable effectiveness of SETA programs at changing employee behavior and an absence of empirical studies on the CSFs for SETA program effectiveness is the key motivation for this study.

This exploratory study follows a systematic inductive approach to concept development. The methodology adopts the “key informant” approach to give voice to practitioners with SETA program expertise. Data are gathered using semi-structured interviews with 20 key informants from various geographic locations including the Gulf nations, Middle East, USA, UK and Ireland.

In this study, the analysis of these key informant interviews, following an inductive open, axial and selective coding approach, produces 11 CSFs for SETA program effectiveness. These CSFs are mapped along the phases of a SETA program lifecycle (design, development, implementation and evaluation) and nine relationships identified between the CSFs (within and across the lifecycle phases) are highlighted. The CSFs and CSFs' relationships are visualized in a Lifecycle Model of CSFs for SETA program effectiveness.

This research advances the first comprehensive conceptualization of the CSFs for SETA program effectiveness. The Lifecycle Model of CSFs for SETA program effectiveness provides valuable insights into the process of introducing and sustaining an effective SETA program in practice. The Lifecycle Model contributes to both theory and practice and lays the foundation for future studies.

This study focuses to develop a common humanitarian supply chain process model (HSCPM) that enables effective enterprise resource planning (ERP) systems for NGOs, and the study also investigates the role of modularity as a dynamic capability that supports creating such model.

A multifocus group study was performed as part of a larger project, the Frontline Humanitarian Logistics Initiative, aiming to establish a common data model that would serve as the backbone of humanitarian ERP systems. Fourteen international humanitarian organizations (IHOs) participated in the process, reaching a consensus on the structure of the process model.

An HSCPM was proposed based on the consensus reached across IHOs. Four degrees of customization differentiating between “generic,” “tailored,” “specific,” and “unique” processes are presented and discussed.

The findings show modularity applied to process as a mean to create dynamic efficiencies and position the modular process model within the dynamic capabilities framework, supporting supply chain responsiveness and expanding the literature on supply chain management (SCM), dynamic capabilities, and humanitarian logistics.

This research proposes a consensus-based data model, facilitating the advancement of ERP systems in the humanitarian context and lays a foundation for interoperability among ERP systems across diverse IHOs.

First attempt to elucidate the specific characteristics and unique processes defining an HSCPM, this study reached an unprecedented consensus for the humanitarian sector, setting the base toward an industry standard.

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.

The metaverse is a virtual world where users can communicate with each other in a computer-generated environment. The use of metaverse technology has the potential to revolutionize the way businesses operate, interact with customers, and collaborate with employees. However, several obstacles must be addressed and overcome to ensure the successful implementation of metaverse technology. This study aims to examine the implementation of metaverse technology in the management of an organization's supply chain, with a focus on predicting potential barriers to provide suitable strategies.

Covariance-based structural equation modeling (CB-SEM) was used to test the model. In addition, artificial neural network modeling (ANN) was also performed.

The CB-SEM results revealed that a firm's technological limitations are among the most significant barriers to implementing metaverse technology in the supply chain management (SCM). The ANN results further highlighted that the firm's technological limitations are the most crucial input factors, followed by a lack of governance and standardization, integration challenges, poor diffusion through the network, traditional organizational culture, lack of stakeholder commitment, lack of collaboration and low perception of value by customers.

Because metaverse technology has the potential to provide organizations with a competitive advantage, increase productivity, improve customer experience and stimulate creativity, it is crucial to discuss and develop solutions to implementation challenges in the business world. Companies can position themselves for success in this fascinating and quickly changing technological landscape by conquering these challenges.

This study provides insights to metaverse technology developers and supply chain practitioners for successful implementation in SCM, as well as theoretical contributions for supply chain managers aiming to implement such environments.

Digitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.

In this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.

The study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.

The implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

This article aims to understand where industry is in terms of digitalizing their operations, what features of this transformation are essential for practitioners, and what barriers they are facing during their journey. In addition, the authors aim to provide recommendations for organization to start their digital transformation.

Through literature review, the authors summarize the emerging tools and technologies in operations and supply chains to inform the practitioners. Then, the authors use surveys conducted on 183 operations and supply chain professionals, and use statistical tools to examine the association between variables of the data set. The authors present real-life case studies to explain important steps of a digital transformation project.

The survey results indicate that real-time monitoring and data analytics are viewed as the most important and needed tools for organizations. High cost, lack of stakeholder buy-in and lack of successful business use cases are major barriers for companies when starting a digital transformation.

The authors provide recommendations for practitioners based on the survey responses, and outline that starting small, focusing on stakeholder buy-in and implementation of software are the three key steps for a successful transformation journey.

Main contributions of this article are to understand practitioner perspectives in digitalization and provide guidelines for organizations to follow when transforming their operations. This research closes the gap between academic research and practice by collaborating with operations and supply chain professionals.

The purpose of this study is to demonstrate that Strategic Enterprise Management (SEM) and Business Intelligence (BI) have the potential to integrate management decisions vertically through an organization’s hierarchy. This study also aims to present a design theory framework and build a model dimension using eight principles serving as mid-range theories.

This study uses a design science perspective to posit how organizations can successfully implement SEMBI (a union of SEM and BI). This study then completes the design theory by building the method dimension using two principles. Finally, the study presents testable hypotheses for the theory and an evaluation using stakeholder attitudes and judgments as proxies for objective measures.

In the search for a prescription for SEMBI success, this study finds that the notion of the Capability Maturity Model (CMM) is a good artifact with which to organize the principles the authors are seeking. CMM has since been adapted to suit different contexts by incorporating relevant principles from those domains. Hereafter, this study refers to SEMBI–CMM as the adapted solution for SEMBI's success.

This study coins and uses the term SEMBI to represent the union of SEM and BI. This term retains its distinct identities and principles and forms a holistic and integrated view of SEM and BI implementation strategies. In an effort to advance this line of research, this study employs a design science perspective to address the question of how an organization can successfully implement SEMBI.

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.