Trust in “Trust-free” Digital Networks: How Inter-firm Algorithmic Relationships Embed the Cardinal Principles of Value Co-creation

In this exploratory research, I develop new knowledge on trust in inter-firm cooperation that leverages recent technologies such as blockchain and the Internet of things in a digital platform ecosystem. In a digital network, advanced algorithms govern and shape inter-firm business processes. While such algorithms introduce efficiency in inter-firm business processes, their limitations, especially their apparent lack of transparency, may affect the key trust dimensions (i.e., reliability, fairness, and goodwill) in the relationships among the participating firms. I introduce algorithmic relationship, a label that embeds the concepts of smart contracts in inter-firm cooperation. Algorithmic relationships involve autonomous and semi-autonomous implementations of smart contracts in all lifecycle stages of inter-firm cooperation. By analyzing extant literature on trust, inter-firm cooperation, business model innovation, and digital platforms, I demonstrate how various factors influence whether firms adopt smart contracts: perceptions about other participants’ trustworthiness, participants’ own propensity to trust, participants’ shared goals and resource embeddedness in the network, perceived risks in inter-firm interactions, and complexity and time criticality of inter-firm interactions. Taking a temporal perspective, I also recognize the present lacunae with smart contracts from various perspectives (algorithm development, algorithm implementation, algorithm governance, and the availability of appropriate legal resources in the event that disputes occur) and demonstrate how these drawbacks impede shared value creation

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Trust and Reputation Management for Blockchain-enabled IoT

In recent years, there has been an increasing interest in incorporating blockchain for the Internet of Things (IoT) to address the inherent issues of IoT, such as single point of failure and data silos. However, blockchain alone cannot ascertain the authenticity and veracity of the data coming from IoT devices. The append-only nature of blockchain exacerbates this issue, as it would not be possible to alter the data once recorded on-chain. Trust and Reputation Management (TRM) is an effective approach to overcome the aforementioned trust issues. However, designing TRM frameworks for blockchain-enabled IoT applications is a non-trivial task, as each application has its unique trust challenges with their unique features and requirements. In this paper, we present our experiences in designing TRM framework for various blockchain-enabled IoT applications to provide insights and highlight open research challenges for future opportunities.Comment: COMSNETS 2023 Invited Pape

Designing a Blockchain-Based Digital Twin for Cyber-Physical Production Systems

Trust in all processes on the shopfloor is crucial for the success of a production process, especially in cross company scenarios such as shared manufacturing, in which independent parties interact with each other. A cyber-physical production system (CPPS) contributes to the vision of a decentralized, self-configuring and flexible production. Digital twins (DTs) can visualize the material, information and financial flows in real time and improve the process transparency of such production systems. The efficiency of digital twins depends on the integrity of the provided data, especially if data is shared across company borders. Due to its characteristics such as immutability and transparency, blockchain technology (BCT) provides a basis for establishing the desired trust in the systems on the shopfloor. This paper proposes the design of a BCT-based DT in CPPS. The design is demonstrated by a prototype including smart contracts attached to a CPPS simulation model visualizing the information and material flow. Tasks are decentrally allocated, deployed and safely documented via blockchain. The demonstrator is revealing supplementary benefits in terms of transparency provided by the BCT. This paper further examines whether BCT can enrich existing solutions and provide a reliable information basis for profound data and process analysis

The Semantic Grid: A future e-Science infrastructure

e-Science offers a promising vision of how computer and communication technology can support and enhance the scientific process. It does this by enabling scientists to generate, analyse, share and discuss their insights, experiments and results in an effective manner. The underlying computer infrastructure that provides these facilities is commonly referred to as the Grid. At this time, there are a number of grid applications being developed and there is a whole raft of computer technologies that provide fragments of the necessary functionality. However there is currently a major gap between these endeavours and the vision of e-Science in which there is a high degree of easy-to-use and seamless automation and in which there are flexible collaborations and computations on a global scale. To bridge this practice–aspiration divide, this paper presents a research agenda whose aim is to move from the current state of the art in e-Science infrastructure, to the future infrastructure that is needed to support the full richness of the e-Science vision. Here the future e-Science research infrastructure is termed the Semantic Grid (Semantic Grid to Grid is meant to connote a similar relationship to the one that exists between the Semantic Web and the Web). In particular, we present a conceptual architecture for the Semantic Grid. This architecture adopts a service-oriented perspective in which distinct stakeholders in the scientific process, represented as software agents, provide services to one another, under various service level agreements, in various forms of marketplace. We then focus predominantly on the issues concerned with the way that knowledge is acquired and used in such environments since we believe this is the key differentiator between current grid endeavours and those envisioned for the Semantic Grid

The Internet of Everything:Smart things and their impact on business models

The internet of everything (IoE), connecting people, organizations and smart things, promises to fundamentally change how we live, work and interact, and it may redefine a wide range of industry sectors. This conceptual paper aims to develop a vision of how the IoE may alter business models and the ways in which individuals and organizations create value. We review literature on networked business models and service ecosystems, and show that a clearer understanding is needed of how the IoE will impact on the ways that organizations go about their business at the micro, meso and macro levels. Combining this with an inductive, vignette-based approach, we present a new taxonomy of smart things based on their capabilities and their connectivity. We derive their implications for business models and conclude the paper with propositions that form a research agenda for business researchers