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The purpose of this paper is to propose a novel Unmanned Combat Air Vehicle (UCAV) flight controller parameters identification method, which is based on predator-prey Biogeography-Based Optimization (PPBBO) algorithm, with the objective of optimizing the whole UCAV system design process.

The hybrid model of predator-prey theory and biogeography-based optimization (BBO) algorithm is established for parameters identification of UCAV. This proposed method identifies controller parameters and reduces the computational complexity.

The basic BBO is improved by modifying the search strategy and adding some limits, so that it can be better applied to the parameters identification problem. Comparative experimental results demonstrated the feasibility and effectiveness of the proposed method: it can guarantee finding the optimal controller parameters, with the rapid convergence.

The proposed PPBBO algorithm can be easily applied to practice and can help the design of the UCAV flight control system, which will considerably increase the autonomy of the UCAV.

A hybrid model of predator-prey theory and BBO algorithm is proposed for parameters identification of UCAV, and a PPBBO-based software platform for UCAV controller design is also developed.

Asteroids have the characteristics of noncooperative, irregular gravity and complex terrain on the surface, which cause difficulties in successful landing for conventional landers. The purpose of this paper is to study the trajectory tracking problem of a multi-node flexible lander with unknown flexible coefficient and space disturbance.

To facilitate the stability analysis, this paper constructs a simplified dynamic model of the multi-node flexible lander. By introducing the nonlinear transformation, a concurrent learning-based adaptive trajectory tracking guidance law is designed to ensure tracking performance, which uses both real-time information and historical data to estimate the parameters without persistent excitation (PE) conditions. A data selection algorithm is developed to enhance the richness of historical data, which can improve the convergence rate of the parameter estimation and the guidance performance.

Finally, Lyapunov stability theory is used to prove that the unknown parameters can converge to their actual value and, meanwhile, the closed-loop system is stable. The effectiveness of the proposed algorithm is further verified through simulations.

This paper provides a new design idea for future asteroid landers, and a trajectory tracking controller based on concurrent learning and preset performance is first proposed.

The case is primarily based on publicly available data, which includes the company website, industry reports and articles published in various media sources, as well as video-recorded interviews with the company representatives. Some factual data is fetched from or triangulated with public and licensed databases such as Statista, Crunchbase and PitchBook.

In November 2021, six years after its establishment, a Finnish food delivery platform startup, Wolt Enterprise Oy, was acquired by San Francisco-based technology company Doordash, Inc., in a staggering all-stock transaction of approximately US$8.1bn (EUR 7bn). This case invites students to analyze the international growth of a startup from its establishment toward becoming a unicorn amidst an ongoing pandemic and further toward a top-level exit deal and continuation as a subsidiary of a publicly listed multinational company. The case provides an overview of the food delivery industry and its key players and examines the challenges and opportunities faced by Wolt as it expanded to different regions, including Europe, Asia and the Middle East. The case provides a comprehensive and nuanced perspective on the strategic decisions and trade-offs that entrepreneurs face in the rapidly evolving food delivery market. By the end of this case study, students will learn about internationalization challenges and opportunities in the food delivery industry, how to navigate external shocks like COVID-19, analyze the competitiveness of a born-global startup in a competitive delivery business and evaluate the pros and cons of an acquisition deal for future international growth.

The case is designed for use in graduate courses in international business and entrepreneurship, such as internationalization of the firm and global marketing, strategies of business growth and international business strategy. A more diverse student body will be beneficial in uncovering different views on country differences, including various competitive, technological and regulative landscapes.

It provides insights into the challenges digital platforms like Wolt face when expanding globally. Students can apply theories such as the Uppsala model and platform economics while exploring how network effects and first-mover advantages influence Wolt’s competitive edge. The case also highlights localization strategies for global marketing and serves as a basis for examining valuation and integration in mergers and acquisitions. Overall, it helps students understand the unique dynamics and growth strategies in digital platform businesses worldwide. This case was classroom tested in the Internationalization of Firm and Global Marketing course for first-year master’s students of the International Business and Entrepreneurship program of LUT University Business School, Finland, during the years 2020–2023. Prior to this course, the students completed the Global Business Environment course, where they learned how to analyze forces in the external environment for further development of firm-level internationalization strategies.