Search Results (59)

Enterprise Resource Planning (ERP) projects have been the focus of extensive research in recent years. To overcome the challenges associated with these types of projects, one emerging and relatively unexplored stream of research has examined the application of agile project management (APM) in ERP implementation contexts. Despite its growing popularity, APM adoption remains complex, risky, and not yet fully understood. This study focuses on the critical role played by the customer in such projects, as it can either foster or hinder agility. A lack of customer collaboration can often be linked to the customer’s organizational culture (OC). Thus, this study aims to investigate the specific relationship between the customer’s OC and project agility in ERP implementation projects within small- and medium-sized enterprises (SMEs). To conceptualize OC, we adopted the Competing Values Framework (CVF), which distinguishes four cultural types: Clan, adhocracy, hierarchy, and market. Data were collected through an online questionnaire administered to 172 ERP end-users from Canadian SMEs who had participated in their organizations’ ERP implementation projects. The analysis was performed using SmartPLS version 4.1.0.9. The results confirm that customers characterized by a clan, adhocracy, or market culture positively influence project agility, while there was no significant effect of hierarchy culture on project agility. This study addresses several gaps in the literature and offers practical implications. The findings support the idea that vendors should better frame and justify introducing APM in ways that align with each customer’s cultural characteristics within ERP vendor–customer relationships. Full article

The proliferation of big data applications across various industries has led to a paradigm shift in data architecture, with traditional approaches giving way to more agile and scalable frameworks. The evolution of big data architecture began with the emergence of the Hadoop-based data stack, leveraging technologies like Hadoop Distributed File System (HDFS) and Apache Spark for efficient data processing. However, recent years have seen a shift towards modern data stacks, offering flexibility and diverse toolsets tailored to specific use cases. Concurrently, cloud computing has revolutionized big data management, providing unparalleled scalability and integration capabilities. Despite their benefits, navigating these data stack paradigms can be challenging. While existing literature offers valuable insights into individual data stack paradigms, there remains a dearth of studies that offer practical, in-depth comparisons of these paradigms across the entire big data value chain. To address this gap in the field, this paper examines three main big data stack paradigms: the Hadoop data stack, modern data stack, and cloud-based data stack. Indeed, we conduct in this study an exhaustive architectural comparison of these stacks covering the entire big data value chain from data acquisition to exposition. Moreover, this study extends beyond architectural considerations to include end-to-end use case implementations for a comprehensive evaluation of each stack. Using a large dataset of Amazon reviews, different data stack scenarios are implemented and compared. Furthermore, the paper explores critical factors such as data integration, implementation costs, and ease of deployment to provide researchers and practitioners with a relevant and up-to-date reference for navigating the complex landscape of big data technologies and making informed decisions about data strategies. Full article

This retrospective, non-interventional study investigated the impact of a forced training interruption, such as the COVID-19 nationwide lockdown, on the physical efficiency, performance, and technical-agility skills of prepubertal soccer players by comparing pre- and post-interruption cohorts within the same youth academy and at the same chronological age. Anonymised data collected across multiple competitive seasons included anthropometric measures and motor performance tests: Standing Long Jump, Shuttle Run, Shuttle Dribble, and Mini Cooper. Between-group differences were analysed using Mann–Whitney U tests, with p < 0.05 as the level of significance. The post-training interruption cohort showed significantly higher values in the Standing Long Jump (+11.2%, p < 0.001) and the Shuttle Run (+8.0%, p = 0.011), indicating improved explosive power and agility-speed. Conversely, performance on the Shuttle Dribble test declined by 13.4% (p < 0.001), while Mini Cooper results and BMI did not differ significantly. These findings suggest that modifications to compulsory training and children’s natural adaptability may have enhanced physical abilities, whereas the lack of contextual and interactive practice negatively affected technical-agility skills. Coaches should incorporate alternative workouts to maintain motor performance and emphasise ball-related and decision-making drills within ecological and dynamic environments to maximise developmental outcomes. This study offers new insights into the adaptive responses of young athletes and provides practical lessons for future youth soccer development, particularly during periods of forced training interruption. Full article

Organizations increasingly rely on Agile software development to navigate the complexities of digital transformation. Agile emphasizes flexibility, empowerment, and emergent design, yet large-scale initiatives often extend beyond single teams to include multiple subsidiaries, business units, and regulatory stakeholders. In such contexts, team-level mechanisms such as retrospectives, backlog refinement, and planning events may prove insufficient to achieve alignment across diverse perspectives, organizational boundaries, and compliance requirements. To address this limitation, this paper introduces a complementary framework and a supporting software tool that enable systematic cross-stakeholder alignment. Rather than replacing Agile practices, the framework enhances them by capturing heterogeneous stakeholder views, surfacing tacit knowledge, and systematically reconciling differences into a shared alignment artifact. The methodology combines individual Functional Resonance Analysis Method (FRAM)-based process modeling, iterative harmonization, and an evidence-supported selection mechanism driven by quantifiable performance indicators, all operationalized through a prototype tool. The approach was evaluated in a real industrial case study within the regulated gaming sector, involving practitioners from both a parent company and a subsidiary. The results show that the methodology effectively revealed misalignments among stakeholders’ respective views of the development process, supported structured negotiation to reconcile these differences, and produced a consolidated process model that improved transparency and alignment across organizational boundaries. The study demonstrates the practical viability of the methodology and its value as a complementary mechanism that strengthens Agile ways of working in complex, multi-stakeholder environments. Full article

The pursuit of continuous improvement is a defining feature of agile software development, yet its success depends on the systematic collection and interpretation of team members’ feedback. Conventional mechanisms, such as retrospectives and surveys, provide valuable insights but are often constrained by their episodic nature and susceptibility to subjective interpretation. This study examines the potential of Artificial Intelligence (AI), and in particular sentiment analysis, to complement feedback-driven practices and strengthen continuous improvement in agile contexts. Two literature reviews were conducted: one on applications of AI across software engineering domains and another focusing specifically on sentiment analysis in agile environments. Based on these insights, a prototype tool was developed to integrate sentiment analysis into task management workflows, enabling the structured collection and analysis of developers’ perceptions of task descriptions. Semi-structured interviews with experienced project managers confirmed the relevance of this approach, highlighting its capacity to improve task clarity and foster more transparent and inclusive feedback processes. Participants emphasized the value of the proposed approach in generating rapid, automated insights, while also identifying potential limitations related to response fatigue and the reliability of AI-generated outcomes. The findings suggest that incorporating sentiment analysis into agile practices is both feasible and advantageous, providing a pathway to align technical objectives with developer experiences while enhancing motivation, collaboration, and operational efficiency. Full article

The rapid integration of emerging technologies into organizational processes has fundamentally redefined the role of strategic human resource management (SHRM). This paper explores how digital innovations—such as artificial intelligence (AI), robotic process automation (RPA), blockchain, and immersive technologies—are reshaping the workforce and transforming the way organizations attract, develop, and retain talent. In the context of the digital era, human capital is no longer a passive input but a strategic enabler of sustainable competitive advantage. The purpose of the study is to analyze how SHRM practices must evolve to align with technology-driven organizational models, combining insights from a systematic literature review, institutional reports, and illustrative corporate cases. Findings indicate that agility, continuous reskilling, ethical AI governance, and employee well-being are critical levers for sustainable advantage. Comparative tables highlight differences between traditional HRM and SHRM in the digital era, while case studies (IBM, Walmart, Unilever, and UiPath) demonstrate the strategic value of predictive analytics, diversity and inclusion programs, virtual training, and people analytics. By proposing a conceptual model that links emerging technologies, SHRM, and competitiveness, the paper contributes to current debates on the transformation of work and organizational resilience. The study offers practical implications for HR leaders, policymakers, and academics navigating digital transformation while reinforcing human-centric performance and sustainability. Full article

The purpose of this study is to examine project performance through the sequential mediation of value co-creation and stakeholder satisfaction, as well as the moderate mediation of stakeholder management in construction companies. The data were collected from project-based organizations using a non-probabilistic, convenience sampling technique. The data were analyzed using structural equation modeling in Smart PLS V. 4. The results suggest that there is a positive and significant association between agile leadership and project performance. Value co-creation and stakeholder satisfaction both separately and sequentially mediate the association between agile leadership and project performance. It was also revealed that stakeholder management moderates this mediation, such that the relationship between agile leadership and project performance is stronger when stakeholder management is high. The implications for theoretical body of knowledge and practices are aligned with stakeholder theory. Full article

This study investigates how Development and Operations (DevOps) practices impact Project Management Office (PMO) governance within the technology sector of the United Arab Emirates (UAE). It addresses the need for agile-aligned governance frameworks by exploring how DevOps principles affect traditional PMO structures. A quantitative cross-sectional survey was conducted, and data was collected from 321 DevOps and PMO professionals in UAE organizations. The analysis, using Partial Least Squares Structural Equation Modelling (PLS-SEM), revealed a moderate positive correlation between specific DevOps practices—such as microservices, Minimum Viable Experience (MVE) culture, continuous value streams, automated configuration, and continuous delivery—and effective PMO governance. The study’s novel theoretical contribution is the integration of the Dynamic Capabilities Framework (DCF) with the Agile DevOps Reference Model (ADRM) to examine this alignment, bridging strategic agility and operational execution. This research offers actionable insights for UAE organizations and policymakers seeking to enhance governance and digital maturity. Full article

Co-creation emphasizes the active involvement of stakeholders in the design and delivery of public services. Despite its potential benefits, many public organizations struggle to implement co-creation because they are unclear about their readiness. To address this gap, this study develops a decision support system (DSS) to assess an organization’s readiness for co-creation in public administration. This study applies a design science research methodology to develop a structured assessment model. Through an in-depth content analysis of academic papers, 81 criteria were identified that represent drivers and barriers to co-creation. These criteria were hierarchically organized into categories, subcategories and aggregated attributes to create a decision model using the Decision EXpert (DEX) multi-criteria decision method. The resulting DSS allows decision makers to assess readiness based on binary inputs (“No”/“Yes”) at the basic level, which are then aggregated by utility functions to obtain the final readiness score. By providing a transparent, evidence-based and replicable approach, this model contributes to both theory and practice: it consolidates the fragmented readiness factors into a structured framework and supports agile governance by guiding strategic planning and the allocation of organizational resources to co-creation initiatives. This model was validated against synthetic test cases to demonstrate its applicability and potential value for public organizations seeking to better understand and improve their readiness and resilience for effective co-creation. Full article

In the context of accelerating digital transformation and growing sustainability imperatives, entrepreneurial ecosystems increasingly rely on open innovation and strategic collaboration to foster resilient, knowledge-driven growth. This study aims to examine how leadership behaviors and strategic alliances interact as enablers of sustainable innovation across macro (systemic), meso (organizational), and micro (individual) levels. To achieve this, this study employs a literature review, supported by bibliometric analysis, as its core methodological approach. Drawing on 86 influential publications from 1992 to 2024, two major thematic streams emerge: leadership dynamics in entrepreneurial settings and the formation and governance of strategic alliances as vehicles for innovation. The findings underscore the pivotal role of transformational and ethical leadership in cultivating trust-based inter-organizational relationships, facilitating digital knowledge sharing, and catalyzing sustainable value creation. Simultaneously, strategic alliances enhance organizational agility and innovation capacity through co-creation mechanisms, digital platforms, and crowdsourcing, especially in small and medium-sized enterprises (SMEs). This paper highlights a mutually reinforcing relationship: effective leadership strategies empower alliances, while alliance participation enhances leadership capabilities through experiential learning in diverse, digitalized environments. By bridging leadership theory, open innovation practices, and digital transformation, this study offers critical insights for entrepreneurs, managers, and policymakers seeking to drive inclusive and sustainable innovation within interconnected global markets. Therefore, this study provides practical guidance for business leaders aiming to strengthen alliance performance through adaptive leadership and for policymakers seeking to foster innovation ecosystems through supportive regulatory and institutional frameworks. Full article

This study explores how digital technologies (DTs) drive business model innovation (BMI) in the traditional manufacturing sector of an emerging economy, focusing on the mediating roles of firm agility (FA), absorptive capacity (AC), and the moderating role of market turbulence (MT). Drawing on organizational adaptation theory and the dynamic capability view, the study develops a conceptual model tested through a survey of 479 senior managers from small and medium-sized manufacturing enterprises (SMEs) in three major industrial cities in Turkey. The results confirm that DTs have a significant positive effect on BMI, with both FA and AC partially mediating this relationship. Additionally, MT strengthens the impact of DTs on FA but does not significantly moderate its effect on AC or BMI. These findings reveal that the effectiveness of digital transformation depends not only on technological investments but also on internal organizational capabilities and external environmental conditions. The study contributes to the digital transformation literature by offering empirical evidence from an underexplored emerging market context and by demonstrating the conditional pathways through which DTs influence innovation. Practical implications highlight the importance of enhancing agility and knowledge integration to translate digital investments into strategic value under turbulent market conditions. Full article

This article examines the challenges very small entities (VSEs) face as defined by the ISO/IEC 29110 standard, particularly their reliance on individual expertise and insufficient adherence to established software engineering practices and international standards, which can lead to increased rework. The article proposes a guide that harmonizes the Scrum and DevOps frameworks to address these challenges and facilitate their adoption in software development processes. An evaluation of the guide by experts indicates significant progress in integrating agile practices within VSEs. The methodology involved understanding both frameworks, modeling a harmonized development process, and creating a characterization tool to assess the current state of VSEs concerning best practices. Also, the guide includes an evaluation instrument to measure the adoption of its suggestions before and after implementation. While expert evaluations confirm the guide’s clarity and practical value, they suggest minor navigation and content clarity improvements. Ultimately, the guide aims to enhance VSEs’ development efficiency and improve software quality. Full article

To enhance the efficiency and accuracy of detecting insulation faults such as discharge carbon traces in large oil-immersed transformers, this study employs an inspection micro-robot to replace manual inspection for image acquisition and fault identification. While the micro-robot exhibits compactness and agility, its limited battery capacity necessitates the critical optimization of its 3D inspection path within the transformer. To address this challenge, we propose a hybrid algorithmic framework. First, the task of visiting inspection points is formulated as a Constrained Traveling Salesman Problem (CTSP) and solved using the Ant Colony Optimization (ACO) algorithm to generate an initial sequence of inspection nodes. Once the optimal node sequence is determined, detailed path planning between adjacent points is executed through a synergistic combination of the A algorithm*, Rapidly exploring Random Tree (RRT), and Particle Swarm Optimization (PSO). This integrated strategy ensures robust circumvention of complex 3D obstacles while maintaining path efficiency. Simulation results demonstrate that the hybrid algorithm achieves a 52.6% reduction in path length compared to the unoptimized A* algorithm, with the A*-ACO combination exhibiting exceptional stability. Additionally, post-processing via B-spline interpolation yields smooth trajectories, limiting path curvature and torsion to <0.033 and <0.026, respectively. These advancements not only enhance planning efficiency but also provide substantial practical value and robust theoretical support for advancing key technologies in micro-robot inspection systems for oil-immersed transformer maintenance. Full article

Background: Regression testing is critical in agile software development, as it ensures that frequent changes do not introduce defects into previously working functionalities. While agile methodologies emphasize rapid iterations and value delivery, regression testing research has predominantly focused on optimizing technical efficiency rather than aligning with agile principles. Aim: This study aims to systematically map research trends and gaps in regression testing within agile environments, identifying areas that require further exploration to enhance alignment with agile practices and value-driven outcomes. Method: A systematic mapping study analyzed 35 primary studies. The research categorized studies based on their focus areas, evaluation metrics, agile frameworks, and methodologies, providing a comprehensive overview of the field. Results: The findings strongly emphasize test prioritization and selection, reflecting the need for optimized fault detection and execution efficiency in agile workflows. However, areas such as test generation, test minimization, and cost analysis are under-explored. Current evaluation metrics primarily address technical outcomes, neglecting agile-specific aspects like defect severity’s business impact and iterative workflows. Additionally, the research highlights the dominance of continuous integration frameworks, with limited attention to other agile practices like Scrum and a lack of datasets capturing agile-specific attributes such as testing costs and user story importance. Conclusions: This study underscores the need for research to expand beyond existing focus areas, exploring diverse testing techniques and developing agile-centric metrics and datasets. By addressing these gaps, future work can enhance the applicability of regression testing strategies and align them more closely with agile development principles. Full article

Background: Physical activity (PA) plays a crucial role in improving the quality of life (QoL) in older people, particularly by enhancing their balance and movement coordination. Objective: This study aimed to assess the effects of sensorimotor training intervention in older adults. Methods: A total of 90 participants, divided into a Control Group (n = 44) and Experimental Group (n = 46) were involved in a 24-week sensorimotor training program. The physical capacities of the participants were assessed both before and after the intervention program. Strength and flexibility were measured using the “Rikli and Jones” protocol (1999), while agility and speed were assessed through “Timed-up-and-go” tests. Taking into account the participants’ gender, a descriptive analysis of the sample was conducted to describe the data using the mean and standard deviation. Student’s T test was performed to compare the differences between the groups according to the first and second data collection moments (before and after the intervention). Jamovi software (v. 2.5.2.0) was used to develop the statistical analysis, using a p-value of less than 0.05 to assess the statistical significance. Results: The Experimental Group showed significant improvements across all the analyzed variables following the intervention (p < 0.005), indicating substantial gains in physical capacities. In contrast, the Control Group in the “sitting and reaching” test did not show a significant difference between the groups highlighting the lack of improvement without intervention. According to the effect size of the sample, it was observed that the parameters “reach behind your back (right)” and “reach behind your back (left)” showed the highest effect size comparing the Control Group and Experimental Group (ES: 0.60, 0.71). Conclusions: The findings highlight the practical clinical impact of implementing tailored physical activity programs for older adults. Such interventions are critical for enhancing QoL, reducing the risk of falls, injuries, and chronic illnesses, and promoting overall health, independence, and well-being. Integrating sensorimotor training into the routine care for older people can support healthy aging and functional independence. Full article