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The authors seek to understand the process of digital servitization as a shift of manufacturing companies from the provision of standard products and services to smart solutions. Specifically, the authors focus on changes in the business model (i.e. the value proposition, the value delivery system and the value capture mechanism) for digital servitization.

The authors examine a Chinese air conditioner manufacturer, Gree, who became the global leader with their smart solutions. These solutions included performance-based contracts underpinned by artificial intelligence (AI)-powered air conditioners that automatically adjust to environmental changes and are capable of remote monitoring and servicing thanks to its Internet of things (IoT) technology.

To successfully offer smart solution value propositions, a manufacturer needs an ecosystem value delivery system composed of suppliers, distributors, partners and customers. Once the ecosystem relationships are well aligned, the manufacturer gains value with multiple value capture mechanisms (i.e. efficiency, accountability, shared customer value and novelty). To arrive at this point, a manufacturer has to pass through different stages that are characterized by both discontinuous and continuous interplay between business models and digital technologies. At the beginning of each stage, new value propositions and value delivery systems are first discontinuously created and then enabled with digital technology. As a result, new value capture mechanisms are activated. Meanwhile, the elements of the existing business model are continuously improved.

By combining process-perspective and business-model lenses, the authors offer nuanced insights into how digital servitization unfolds.

Executives can obtain insights into the business model elements, they need to change over the course of digital servitization and how to manage the process.

A longitudinal case study of a traditional manufacturer that has achieved stellar success through digital servitization business models development.

Value creation based on artificial intelligence (AI) can significantly change global healthcare. Diagnostics, therapy and drug discovery start-ups are some key forces behind this change. This article aims to study the process of start-ups' value creation within healthcare.

A multiple case study method and a business model design approach were used to study nine European start-ups developing AI healthcare solutions. Obtained information was performed using within and cross-case analysis.

Three unique design elements were established, with 16 unique frames and three unifying design themes based on business models for AI healthcare start-ups.

Our in-depth framework focuses on the features of AI start-up business models in the healthcare industry. We contribute to the business model and business model innovation by systematically analyzing value creation, how it is delivered to customers, and communication with market participants, as well as design themes that combine start-ups and categorize them by specialization.

The objective of this paper is to study the role of artificial intelligence (AI) in supporting the supplier scouting process, considering the information and the capabilities required to do so.

Twelve cases of IT and information providers offering AI-based scouting solutions were studied. The unit of analysis was the AI-based scouting solution, specifically the relationship between the provider and the buyer. Information processing theory (IPT) was adopted to address information processing needs (IPNs) and capabilities (IPCs).

Among buyers, IPNs in supplier scouting are high. IT and information providers can meet the needs of buyers through IPCs enabled by AI-based solutions. In this way, the fit between needs and capabilities can be reached.

The investigation of the role of AI in supplier scouting is original. The application of IPT to study the impact of AI in business processes is also novel. This paper contributes by investigating a phenomenon that is still unexplored and unconsolidated in a business context.

The purpose of this study was to create an air movement operations planning model to rapidly generate air mission request (AMR) assignment and routing courses of action (COA) in order to minimize unsupported AMRs, aircraft utilization and routing cost.

In this paper, the US Army Aviation air movement operations planning problem is modeled as a mixed integer linear program (MILP) as an extension of the dial-a-ride problem (DARP). The paper also introduces a heuristic as an extension of a single-vehicle DARP demand insertion algorithm to generate feasible solutions in a tactically useful time period.

The MILP model generates optimal solutions for small problems (low numbers of AMRs and small helicopter fleets). The heuristic generates near-optimal feasible solutions for problems of various sizes (up to 100 AMRs and 10 helicopter team fleet size) in near real time.

Due to the inability of the MILP to produce optimal solutions for mid- and large-sized problems, this research is limited in commenting on the heuristic solution quality beyond the numerical experimentation. Additionally, the authors make several simplifying assumptions to generalize the average performance and capabilities of aircraft throughout a flight.

This research is the first to solve the US Army Aviation air movement operations planning problem via a single formulation that incorporates multiple refuel nodes, minimization of unsupported demand by priority level, demand time windows, aircraft team utilization penalties, aircraft team time windows and maximum duration and passenger ride time limits.

The reduced problem of the Navier–Stokes and the continuity equations, in two-dimensional Cartesian coordinates with Eulerian description, for incompressible non-Newtonian fluids, is considered. The Ladyzhenskaya model, with a non-linear velocity dependent stress tensor is adopted, and leads to the governing equation of interest. The reduction is based on a self-similar transformation as demonstrated in existing literature, for two spatial variables and one time variable, resulting in an ODE defined on a semi-infinite domain. In our search for classical solutions, existence and uniqueness will be determined depending on the signs of two parameters with physical interpretation in the equation. Illustrations are included to highlight some of the main results.

This paper aims to provide a discussion on the interface and interactions between data, analytical techniques and impactful research in humanitarian health supply chains. New techniques for data capturing, processing and analytics, such as big data, blockchain technology and artificial intelligence, are increasingly put forward as potential “game changers” in the humanitarian field. Yet while they have potential to improve data analytics in the future, larger data sets and quantification per se are no “silver bullet” for complex and wicked problems in humanitarian health settings. Humanitarian health supply chains provide health care and medical aid to the most vulnerable in development and disaster relief settings alike. Unlike commercial supply chains, they often lack resources and long-term collaborations to enable learning from the past and to improve further.

Based on a combination of the authors’ research experience, interactions with practitioners throughout projects and academic literature, the authors consider the interface between data and analytical techniques and highlight some of the challenges inherent to humanitarian health settings. The authors apply a systems approach to represent the multiple factors and interactions between data, analytical techniques and collaboration in impactful research.

Based on this representation, the authors discuss relevant debates and suggest directions for future research to increase the impact of data analytics and collaborations in fostering sustainable solutions.

This study distinguishes itself and contributes by bringing the interface and interactions between data, analytical techniques and impactful research together in a systems approach, emphasizing the interconnectedness.

The purpose of this paper is to investigate the economic feasibility of a three-echelon Halal Meat Supply Chain (HMSC) network that is monitored by a proposed radio frequency identification (RFID)-based management system for enhancing the integrity traceability of Halal meat products and to maximize the average integrity number of Halal meat products, maximize the return of investment (ROI), maximize the capacity utilization of facilities and minimize the total investment cost of the proposed RFID-monitoring system. The location-allocation problem of facilities needs also to be resolved in conjunction with the quantity flow of Halal meat products from farms to abattoirs and from abattoirs to retailers.

First, a deterministic multi-objective mixed integer linear programming model was developed and used for optimizing the proposed RFID-based HMSC network toward a comprised solution based on four conflicting objectives as described above. Second, a stochastic programming model was developed and used for examining the impact on the number of Halal meat products by altering the value of integrity percentage. The ε-constraint approach and the modified weighted sum approach were proposed for acquisition of non-inferior solutions obtained from the developed models. Furthermore, the Max-Min approach was used for selecting the best solution among them.

The research outcome shows the applicability of the developed models using a real case study. Based on the computational results, a reasonable ROI can be achievable by implementing RFID into the HMSC network.

This work addresses interesting avenues for further research on exploring the HMSC network design under different types of uncertainties and transportation means. Also, environmentalism has been becoming increasingly a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function.

The model can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management.

Although there were a few studies focusing on the configuration of a number of HMSC networks, this area is overlooked by researchers. The study shows the developed methodology can be a useful tool for designers to determine a cost-effective design of food supply chain networks.

This paper describes and discusses company spin-ins and spin-outs as a means to understand company growth in a dynamic context. The following question is asked: How can growth be understood in spin-ins and spin-outs of innovative firms? The paper suggests return on capabilities as a measure to understand growth in an open innovation context.

The empirical part of the paper consists of a single case study. Data was captured through interviews and secondary data sources.

The paper points to that resources alone do not explain strategic decisions by a company and how spin-ins and spin-outs result from the need for capabilities, changes in business foci and temporary solutions to deal with overcapacities or lack of alternatives.

The paper contributes to research by discussing contemporary issues in strategy and innovation and relating them to the resource-based view and the growth of the firm. Spin-outs, and acquisitions and divestitures as interlinked events have rarely been focused on in the literature, while they remain frequent phenomena in practice.

The purpose of this paper is to describe how emerging open standards are replacing traditional industrial networks. Current industrial Ethernet networks are not interoperable; thus, limiting the potential capabilities for the Industrial Internet of Things (IIoT). There is no forthcoming new generation fieldbus standard to integrate into the IIoT and Industry 4.0 revolution. The open platform communications unified architecture (OPC UA) time-sensitive networking (TSN) is a potential vendor-independent successor technology for the factory network. The OPC UA is a data exchange standard for industrial communication, and TSN is an Institute of Electrical and Electronics Engineers standard for Ethernet that supports real-time behaviour. The merging of these open standard solutions can facilitate cross-vendor interoperability for Industry 4.0 and IIoT products.

A brief review of the history of the fieldbus standards is presented, which highlights the shortcomings for current industrial systems in meeting converged traffic solutions. An experimental system for the OPC UA TSN is described to demonstrate an approach to developing a three-layer factory network system with an emphasis on the field layer.

From the multitude of existing industrial network schemes, there is a convergence pathway in solutions based on TSN Ethernet and OPC UA. At the field level, basic timing measurements in this paper show that the OPC UA TSN can meet the basic critical timing requirements for a fieldbus network.

This paper uniquely focuses on the specific fieldbus standards elements of industrial networks evolution and traces the developments from the early history to the current developing integration in IIoT context.

This paper proposes a holistic, proactive and adaptive approach to cybersecurity from a service lens, given the continuously evolving cyber-attack techniques, threat and vulnerability landscape that often overshadow existing cybersecurity approaches.

Through an extensive literature review of relevant concepts and analysis of existing cybersecurity frameworks, standards and best practices, a logical argument is made to produce a dynamic end-to-end cybersecurity service system model.

Cyberspace has provided great value for businesses and individuals. The COVID-19 pandemic has significantly motivated the move to cyberspace by organizations. However, the extension to cyberspace comes with additional risks as traditional protection techniques are insufficient and isolated, generally focused on an organization's perimeter with little attention to what is out there. More so, cyberattacks continue to grow in complexity creating overwhelming consequences. Existing cybersecurity approaches and best practices are limited in scope, and implementation strategies, differing in strength and focus, at different levels of granularity. Nevertheless, the need for a proactive, adaptive and responsive cybersecurity solution is recognized.

This paper presents a model that promises proactive, adaptive and responsive end-to-end cybersecurity. The proposed cybersecurity continuity and management model premised on a service system, leveraging on lessons learned from existing solutions, takes a holistic analytical view of service activities from source (service provider) to destination (Customer) to ensure end-to-end security, whether internally (within an organization) or externally.