A Reliable Transaction Processing Framework for Digital Business Ecosystems

Improving the rural economic climate to narrow the rural-urban economic gap is necessary in order to address the problematic urbanization phenomenon in many developing countries. To this end, the participation of rural communities in the digital business ecosystem is being viewed as a promising approach. However, there are high barriers that hinder rural communities from participating in the digital business ecosystem. The barriers are mainly due to the low digital readiness of the rural communities, the limited government capability, and the limited third-party involvement. With an aim to lower these barriers, our paper proposes the architectural specification of a digital platform based on a service-oriented architecture, where the provisioning of digital business services for rural communities is realized through a collaboration between the government and third-party service providers. The proposed architecture has been instantiated by means of a prototype and validated by a panel of experts from the rural areas of West Java, Indonesia.

During the almost 27 years of its existence, the business ecosystem research has developed a substantial level of ambiguity and multifacetedness. Because to the technological advancements that promote interconnectedness and value co-creation, the field has consequently spun off into more domain-specific branches, such as the arena of digital business ecosystems that are driven by Internet of Things (IoT). Nonetheless, despite the efforts to mend the theoretical foundations and to close the gap between academia and empirical practice, the absolute majority of IoT-driven digital business ecosystem literature follows the trend of conceptual randomness while expanding the volume of publications exponentially. Therefore, in order to address this unfavourable increase in random adoption of distinct concepts that ultimately refer to the same subject matter, the author encourages other scholars involved in the research field of IoT-driven digital business ecosystems to make extended efforts and support the external validity of their research (as well as the relevance of the research stream as a whole) by bounding the IoT-driven digital business ecosystems on a rigorous basis through deploying the extant theory in a careful and appropriate manner. Via a thorough examination of the theoretical fundaments that underpin the concept of IoT-driven digital business ecosystem, and based on a concise thematic review of corresponding literature published until September 2020, this article articulates logic for viewing the conceptual hierarchy within the business ecosystem research and proposes six literature-based recommendations for developing further IoT-driven digital business ecosystem (DBE) research in a rigorous way.

This research investigates how the dimensions of the Technology, Organization, and Environment (TOE) framework influence the digital business ecosystem (DBE) and, in turn, how this ecosystem impacts the adoption of Islamic Mobile Banking (IMB). It addresses a gap in existing literature by adopting a customer-centric perspective, highlighting how DBE affects IMB adoption, a departure from previous studies that primarily focused on internal organizational factors. To achieve its objectives, the study employs a quantitative approach using Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data from 985 IMB users in Indonesia. The findings reveal that DBE significantly influences IMB adoption, particularly when moderated by customer behavior as an environmental factor. Factors such as perceived usefulness and ease of use within the technological domain, firm reputation and innovation within the organizational domain, and perceived risk and sharia compliance as environmental factors all positively and significantly impact DBE. Additionally, perceived security has a significant effect on DBE, especially when mediated by perceived ease of use. Furthermore, DBE serves as a crucial mediator between all dimensions of the TOE framework and IMB adoption. This research offers a theoretical contribution by examining the TOE framework dimensions from a customer's perspective, revealing their impact on DBE and IMB adoption. From a managerial perspective, the study provides valuable insights for banks on how to effectively manage technological, environmental, and organizational dimensions to strengthen DBE and promote IMB adoption.

This paper is an introduction to Business Ecosystems and its improvements as represented in Digital Business Ecosystem. In traditional non-digital economic ecosystems, the hubs, once established are static. It is difficult to create new hubs and as such these established hubs enjoy considerable power in the marketplace. Indeed, in many instances, these hubs become the main impediments for the growth of smaller nodes. In other instances, they try to misuse their powers by creating monopolies or oligopolies. In contrast, it is hoped that Digital Business Ecosystems, by virtue of their loosely-coupled and self-organizing properties, will help Small and Medium Enterprises to create a fully distributed network, sidestepping the above mentioned problems of dominance of the large hubs in the market. The authors try to provide a brief introduction to Business Ecosystems and focus on the reasons and advantages of such a move/transition towards Digital Business Ecosystems.

In this paper, which is only an opening exploration, we are imagining a multi-vendor component-based robotic software system as a digital business ecosystem. We have explored implementing model-based electronic institutions, “SmartIN” on RobMoSys (EU H2020 project) compliant SmartMDSD toolchain. This extension to SmartMDSD lets software components spontaneously remodel their service behaviour according to the institution they conform to. Electronic institutions in “SmartIN” are envisioned as models that collect several services and encapsulate patterns of their related behaviour in a rule-based multi-agent organisation. The presented idea and associated tooling are functionally adequate as a vessel. The authors lack inputs from multi-disciplinary experts for an accurate and deep understanding of possible models and mechanisms that should be incorporated to make the presented vessel truly beneficial. Hence parts of the work and tools are being shared with the community at an early stage.KeywordsModel-Driven Engineering (MDE)Component-Based Software Development (CBSD)Service-Oriented Architecture (SOA)Service-Oriented Business Ecosystem (SOBE)Electronic Institutions (EI)Digital Business Ecosystems (DBE)Electronic contractsCoalition formation

The system described herein represents the first example of a recommender system in digital ecosystems where agents negotiate services on behalf of small companies. The small companies compete not only with price or quality but also with a wider service-by-service composition by subcontracting with other companies. The final result of these offerings depends on negotiations at the scale of millions of small companies. This scale requires new platforms for supporting digital business ecosystems (DBEs), as well as related services like open-id, trust management, monitors, and recommenders. This is done in the Open Negotiation Environment (ONE), which is an open-source platform that allows agents, on behalf of small companies, to negotiate and use the ecosystem services, and enables the development of new agent technologies. The methods and tools of cyber engineering are necessary to build up ONEs that are stable, a basic condition for predictable and reliable business environments. Aiming to build stable DBEs by means of improved collective intelligence, we introduce a model of negotiation-style dynamics from the point of view of computational ecology. This model inspires an ecosystem monitor and a novel negotiation-style recommender (NSR). The ecosystem monitor provides hints to the NSR to achieve greater stability of ONE in a DBE. The greater stability provides the small companies with higher predictability and, therefore, better business results. The NSR is implemented with a simulated-annealing algorithm at a constant temperature, and its impact is shown by applying it to a real case of ONE populated by Italian companies.

We investigate an abstract conceptualisation of Digital Ecosystems from a computer science perspective. We then provide a conceptual framework for the cross pollination of ideas, concepts and understanding between different classes of ecosystems through the universally applicable principles of Complex Adaptive System (CAS) modelling. A framework to assist the cross-disciplinary collaboration of research into Digital Ecosystems, including Digital Business Ecosystems (DBEs) and Digital Knowledge Ecosystems (DKEs). So, we have defined the key steps towards a theoretical framework for Digital the Ecosystems, that is compatible with the diverse theoretical views prevalent. Therefore, a theoretical edifice that can unify the diverse efforts within Digital Ecosystems research.

In contrast to traditional business models, digital business ecosystems (DBEs) have several distinctive features—heterogeneity of involved actors, symbiosis in the exchange of resources, co-evolution of their interactions, and self-organisation. Designing DBEs is a task demanding a well-defined DBE’s scope, roles and responsibilities of the actors, their interactions and dependencies, as well as versatile technologies and data. The study focuses on two DBEs—Marispace-X and Skippo in the maritime domain to capture the tenets of the blue economy with dataspaces. Because the design approaches to DBE are scarce due to the paradigm’s novelty, the study aims to evaluate a model-based design method, DBEmap. The evaluation results concerning practitioners’ perceived usefulness of the DBEmap and its support for integrating DBE-related perspectives and benchmarking DBE resilience are presented. Reflections on the applicability of DBEmap and its implications for organisational support, highlighting the systematic guidance and actionable outcomes observed in the two case workshops, are discussed alongside the study’s limitations and directions for future research.

This study examines the roles of collaboration and innovation in developing digital business ecosystems. It employs a narrative literature review of core scholarship on business ecosystems, digital platforms, and collaboration–innovation practices in both global and Indonesian contexts. The synthesis indicates that digital business ecosystems constitute multilateral interdependence structures that require alignment of roles and activities across actors to realize a shared value proposition. Collaboration therefore becomes a structural necessity, as ecosystem innovation is modular and complementary, and value emerges only when contributions from diverse parties are coherently integrated. Digital platforms accelerate ecosystem growth through generativity and network effects, yet they also demand collaborative governance to keep collective innovation coordinated and goal-oriented. Empirical evidence further shows that collaboration facilitated by platforms, hubs, or intermediaries speeds up the exchange of data, knowledge, and resources, triggering technological, service, governance, and business-model innovations that enhance ecosystem performance and sustainability. However, many ecosystems still face limitations in the depth of collaboration—often not progressing to co-production or joint R&D—resulting in suboptimal collective innovation. This study enriches digital ecosystem theory and offers practical implications for orchestrating collaboration and sustaining innovation in digital business ecosystems.

In this paper the authors describe the implementation of an ecologically inspired Digital Business Ecosystem (DBE) to promote and improve business collaboration by allowing Small and Medium sized Enterprises (SMEs) to find partners for interaction. Building on the analysis of how biologically-inspired computing is useful to represent business interactions and how small firms can benefit from this, the authors employ a methodology for defining ecological interactions among agents (SMEs) in a multi-agent system for the implementation of MADBE, an open-source Multi-Agent DBE. With MADBE, SMEs are able to publish their characteristics, services and needs and the system, using an intelligent protocol of interaction, simulates business interactions and suggests the optimal collaborative links between the participant firms that ultimately can derive in new joint ventures.

The concept of digital health innovation ecosystems is an emerging body of literature which suggests that components of digital health, innovation and digital ecosystems are important in the administration and delivery of healthcare services. The current literature indicates which components of digital health, innovation and digital ecosystems constitute a digital health innovation ecosystem, but it is less clear as to which components of digital health, innovation and digital ecosystems are relevant to the development of such an ecosystem for the Namibian context. The purpose of this paper was to identify the components of digital health, innovation and digital ecosystems relevant to the development of a digital health innovation ecosystem for the Namibian context. Therefore, the Delphi method was adopted in which 22 knowledgeable professionals from within the Namibian context were purposively selected to take part. The findings revealed essential components of digital health, innovation and digital ecosystems which are considered relevant to the development of a digital health innovation ecosystem for the Namibian context. Additionally, there are differences noted between the components of digital health, innovation and digital ecosystems essential for the Namibian context and the components of digital health, innovation and digital ecosystems identified in literature. The essential components identified will inform decision makers in the Namibian healthcare sector on the implementation of a digital health innovation ecosystem for Namibia.

The digital business ecosystem (DBE) project experimented with new ways of bringing small and medium-sized enterprises (SMEs) into a major R&D project. Such involvement is an important factor in projects where the R&D performers are not the exploiters. The project utilised the social capital of regional actors, and conceptualised a certain kind of SME, known as driver SMEs. The strategy adopted has worked for this project and has provided a basis for self-sustained post-project expansion. In doing so it has created a model that could easily be adopted by other projects, both in Digital Ecosystems and beyond.

Digital platforms bring together organizations from different market segments. Consequently, digital business ecosystems orient themselves gradually according to the constraints imposed by different organizations although they are under the same segments. This phenomenon of influence also considerably enriches the data corpus. It has seldom been observed that the existing data features are always dynamic in nature. The context has become more challenging as many companies are often reluctant to share their information probably due to its confidentiality. Hence, with this paradigm of several variations, conventional matching to search a particular enterprise from the largest data corpus fails to deliver optimal matching prediction with respect to the different roles of the enterprises. This article presents an analytical and practical case study deploying a hybrid machine learning algorithm. The proposed methods depict the background of the digital business ecosystem, missing data imputation, and supervised machine learning approaches towards developing such models.

Following September 11 2001, company ABC zeroed in on a home-grown fat client system, System E, as the enterprise data warehouse for risk management. It became mission critical for System E to remove key person dependencies and migrate from C++, a niche technology, to a more accessible platform. Under the leadership of a new hire, System E adopted an Service Oriented Architecture (SOA) approach to re-architecture. As company ABC’s IT unit is under a flat headcount constraint, an incremental SOA approach was the only way to get upper management approval. A pilot is well underway and scheduled to complete in December 2005. This paper presents the current/target architectures of System E, a theoretical framework for SOA, the Unified Modeling Language class diagram for SOA Model at ABC, and concludes with lessons learned from the pilot to date. Key contributions of the paper include SOA Model at ABC, and lessons learned regarding enterprise architecture initiatives.

The paper aims to analyze the possibilities of increasing the reliability level of software applications based on a Service Oriented Architecture (SOA) by the means of Design by Contract principles and explicit manipulation of business rules. Two architectural approaches have been taken into consideration: process centric SOA and information centric SOA. Also, a comparative analysis regarding the use of process diagrams versus use cases in SOA modeling is presented.