1,721,007 research outputs found
Investigating companies journey toward business model innovation through case studies research
No full textThis case study presents an overview of the main steps and challenges encountered in a qualitative, longitudinal investigation of how companies reconfigure and innovate their business models. A business model describes how a company is concretely realizing its long-term strategy, describing the choices for creating, delivering, and capturing value. The fast-changing nature and the increasing complexity of current competitive environments require companies to spend considerable effort into developing new solutions—and therefore innovating their business models—to remain competitive and succeed in the creation of added value. The methods case highlights the importance and the issues in the choice of approaches in qualitative research involving a multiple case study and a longitudinal perspective. We describe the decisions, steps, problems, and lessons learned throughout the phases of (1) research setting and selection of cases, (2) data collection, and (3) data analysis. The case allows us to shed light on the practical challenges that researchers have to face when analyzing the process of business model innovation, such as choosing proper cases; collecting and analyzing rich, temporal, and unstructured data from different companies; and drawing valuable insights from their analysis
An evaluation of agile Ontology Engineering Methodologies for the digital transformation of companies
No full textOntologies are increasingly recognised among the key enablers of the digital transformation of knowledge management processes, but still with a low level of adoption in manufacturing companies. Because ontologies and underlying technologies are complex, Ontology Engineering Methodologies (OEMs) provide a set of guidelines to move from an informal to a formal representation of the company's knowledge base. This study evaluates three agile OEMs, i.e. UPONLite, SAMOD and RapidOWL, in terms of their process and outcome features, i.e. the OEM steps and the expected quality of the ontological models produced. The assessment is performed from the viewpoint of developers of ontology-based technologies in real industrial use cases. Results show that the three agile OEMs reflect different features to effectively support the digital transformation of companies' knowledge management; thus, they cannot be interchangeable. UPONLite is more effective in contexts where there is a lack of skills in OE, with the need for a structured approach in involving domain experts and generating documentation. SAMOD requires a more extended development period, but with several cycles that allow to map different types of knowledge and enable a “try-and-learn” approach. Conversely, RapidOWL lacks a structured sequence of modelling activities and encourages developers to be creative, but at the same time requires higher expertise in OE. Thus, companies and personnel dedicated to OE should choose the methodology according to the main aims guiding their digitalisation process, the current development status, and the level of expertise
Collaborative Ontology Engineering Methodologies for the Development of Decision Support Systems: Case Studies in the Healthcare Domain
Full text linkNew models and technological advances are driving the digital transformation of healthcare systems. Ontologies and Semantic Web have been recognized among the most valuable solutions to manage the massive, various, and complex healthcare data deriving from different sources, thus acting as backbones for ontology-based Decision Support Systems (DSSs). Several contributions in the literature propose Ontology engineering methodologies (OEMs) to assist the formalization and development of ontologies, by providing guidelines on tasks, activities, and stakeholders' participation. Nevertheless, existing OEMs differ widely according to their approach, and often lack of sufficient details to support ontology engineers. This paper performs a meta-review of the main criteria adopted for assessing OEMs, and major issues and shortcomings identified in existing methodologies. The key issues requiring specific attention (i.e., the delivery of a feasibility study, the introduction of project management processes, the support for reuse, and the involvement of stakeholders) are then explored into three use cases of semantic-based DSS in health-related fields. Results contribute to the literature on OEMs by providing insights on specific tools and approaches to be used when tackling these issues in the development of collaborative OEMs supporting DSS
Investigating organisational learning to master project complexity: An embedded case study
No full textUnderstanding and properly facing the increasing complexity of projects is a key determinant for success, especially in project-based organisations (PBOs), where projects are the primary unit for innovation. This paper aims to provide new insights into the interplay between project complexity and organisational learning, by exploring the dimensions of complexity identified in literature (i.e. diversity, interdependence, dynamicity, uncertainty) and the patterns and mechanisms of organisational learning (i.e. experience-based knowledge acquisition, knowledge creation, and knowledge capture and codification) within projects embedded in a common organisational context. An embedded case study research was conducted in a leading company of the shipbuilding industry. Results show that different dimensions of complexity require project teams and PBOs to activate (or experience the emergence of) different organisational learning processes. The complexity issues fostering specific behaviours and approaches for organisational learning, and related implications for the overall PBO encompassing project management practices and routines, are discussed
Natural resources in health tourism: A systematic literature review
Full text linkNatural resources are recognized among the key determinants for the improvement of wellness, and thus the development and sustainability of health tourism destinations. This study applied a systematic review to investigate the contributions mapping and analyzing under different perspectives the value of the natural resources of a destination and related activities for health tourism. The main research topics identified from a review of 52 papers include the analysis and exploitation of natural resources in health tourism, the nature-based factors considered in clustering of tourists and their motivations, the development of value offer and marketing, as well as the cultural issues. Research gaps and future directions are summarized in a research agenda laying the foundations for the development of a multidisciplinary research stream focused on nature-based health tourism. Results also represent a key reference for managers and policy makers to identify key issues, areas of intervention and practices for industry development in the health tourism destinations through an effective and sustainable exploitation of natural resources
Unboxing the hyper-connected supply chain: a case study in the furniture industry
No full textThis work aims to investigate the role of digital technologies, specifically enhanced interconnectivity, in supply chains (SC)s and their management. With a case study of an international company leading the home furniture industry and its suppliers, we explore the development of (new and integrated) practices and routines in operational processes for heading to a hyper-connected SC. The study builds on the notion of absorptive capacity to frame the SC transformation brought by the assimilation of specific digital technologies (i.e. Internet of Things, Cloud-based platforms, Augmented and Virtual Reality, and Artificial Intelligence). We analyze how SC actors combine these technologies to develop their SC processes and routines in terms of real-time data exchange and end-to-end visibility between globally distributed companies, devices, products, and people. Key theoretical implications rely on identifying interconnection levels across SC processes that allow incorporating technological knowledge at the SC level, building on trustful collaboration and secure and reliable communications beyond the boundaries of every single factory. Results also provide practitioners with a set of collaborative practices and related challenges to integrate digital technologies at different (and complementary) levels as guidelines for a transformation towards SC hyper-connectivity aimed at improving the overall SC performance
To be or not to be... digital! How supply chain partners can support the adoption of digital technologies
No full textThis research examines the adoption of Artificial Intelligence, blockchain, and drones in the pharmaceutical supply chain, with a focus on the role of collaboration among supply chain partners. Using a mixed-methods approach, the findings indicate a higher adoption rate of AI compared to blockchain and drones. Technology providers are leading the way in supporting organizations on their digital transformation journey, often through partnerships with complementary service providers. The study also underscores the importance of multi-stakeholder collaboration in overcoming barriers to digital technology integration and standardization within the PSC
A survey on the role of pharmaceutical supply chain actors in digital innovation
No full textThe pharmaceutical supply chain is crucial for ensuring timely access to medications and patient care. To address challenges and improve efficiency, organizations are increasingly investing in digital technologies such as blockchain, drones, and artificial intelligence. However, the integration of these technologies faces challenges, particularly related to resource scarcity for digitalization, cultural resistance within organizations, skill gaps, and data security concerns. Collaborative approaches among pharmaceutical supply chain partners can help overcome these challenges and accelerate digital transformation. Despite the strategic importance of digital technology adoption, research has primarily focused on understanding relationship dynamics rather than collaborative initiatives among pharmaceutical supply chain partners to enhance digital technology adoption. An exploratory survey was conducted in this study to assess the degree of digital innovation adoption within pharmaceutical supply chain operations and provide insights into the specific contributions of four key pharmaceutical supply chain actors in the adoption of artificial intelligence, drones, and blockchain. The findings indicate a greater adoption of artificial intelligence compared to drones and blockchain. Technology providers play a central role in facilitating digital technology adoption. This study identifies key supportive initiatives such as unified data exchange platforms, pilot tests, synergies with complementary technologies, and identification of trusted technology providers. The regression analysis suggests a positive correlation between the adoption of artificial intelligence, blockchain, and drones, with research centers emerging as key supporting actors of technological advancement within the pharmaceutical supply chain. Overall, results highlight the importance of understanding barriers and supportive actions across the PSC and offer practical guidance for managers navigating the digitalization process, emphasizing the adoption of impactful yet challenging technologies, i.e. artificial intelligence, blockchain, and drones
A novel agile ontology engineering methodology for supporting organizations in collaborative ontology development
Full text linkOntologies can represent technological enablers for knowledge elicitation and management in different kinds of organizations, especially with the exponential growth of sources and types of data fostered by digital transformation. However, their adoption in business applications is still limited, with existing Ontology Engineering Methodologies (OEMs) lacking adequate support during knowledge elicitation, authoring and reuse phases. This paper introduces a novel agile ontology engineering methodology (AgiSCOnt) to support ontologists (especially novice ones) in ontology development workflow, fostering collaboration with domain experts in an iterative, flexible and customizable approach. AgiSCOnt combines macro-level instructions with micro-level guidance, leveraging existing techniques and a management framework to help novice ontologists throughout the whole ontology engineering process. The methodology is compared to existing OEMs and assessed with three other agile methodologies (UPONLite, SAMOD, and RapidOWL). The evaluation is conducted with a sample of novice ontologists in a learning environment on Industry 4.0 technologies. Both the development process with a methodology from a user perspective and the quality of the developed ontologies were considered in the evaluation. Preliminary results show that AgiSCOnt effectively supports authoring and reuse, with developed ontologies of good quality. It is perceived as clear and simple, while being flexible and adaptable enough, thus supporting knowledge management and sharing in industrial organizations through the documentation of the ontologies
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