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Team teaching in higher education requires a great deal of coordination and commitment from both the professors teaching together, as well as administrators coordinating courses. Given the difficulties in logistics, it is not surprising that many teams give up on team teaching after only one or two semesters. The literature and lived experience by the authors verify the benefits that come from team teaching: multiple perspectives on the course material, more than one-course delivery method, greater attention from students used to just one instructor, and a greater level of energy in the room and on-line when more than one presenter shares the lecture time. Team teaching (or co-teaching as it is also referred to), in the Service Management Specialization at the Gustavson School of Business in Victoria, Canada, is sharing a cohort of students across three classes, and while each professor is responsible for separate course topics, each makes the time to integrate topics and share time in the classroom together multiple times during the semester.

The authors have been part of a team delivering curriculum this way for over 20 years, and this chapter examines how the material is organized and delivered to team teaching success. Critical elements include funding to support team teaching, commitment from professors to coordinate together, willingness to share materials, and building bridges from class to class to enable students to follow and integrate learnings. Team teaching has resulted in greater cohesiveness among faculty teaching in the program, higher teaching evaluations than professors experienced in solo teaching, and students who feel better prepared to tackle complex business problems that cross the interdisciplinary boundaries of marketing, operations, and talent management.

This paper focuses on the application of a robotic technique for modeling a three-wheeled mobile robot (WMR), considering it as a multibody polyarticulated system. Then the dynamic behavior of the developed model is verified using a physical model obtained by Simscape Multibody.

Firstly, a geometric model is developed using the modified Denavit–Hartenberg method. Then the dynamic model is derived using the algorithm of Newton–Euler. The developed model is performed for a three-wheeled differentially driven robot, which incorporates the slippage of wheels by including the Kiencke tire model to take into account the interaction of wheels with the ground. For the physical model, the mobile robot is designed using Solidworks. Then it is exported to Matlab using Simscape Multibody. The control of the WMR for both models is realized using Matlab/Simulink and aims to ensure efficient tracking of the desired trajectory.

Simulation results show a good similarity between the two models and verify both longitudinal and lateral behaviors of the WMR. This demonstrates the effectiveness of the developed model using the robotic approach and proves that it is sufficiently precise for the design of control schemes.

The motivation to adopt this robotic approach compared to conventional methods is the fact that it makes it possible to obtain models with a reduced number of operations. Furthermore, it allows the facility of implementation by numerical or symbolical programming. This work serves as a reference link for extending this methodology to other types of mobile robots.

This study aims to investigate the use of Artificial Intelligence (AI) applied to vertical farms to evaluate whether disrupting technology supports sustainability and increases strategic business model choices in the agricultural sector. The study responds through empirical analysis to the gap on the subject of AI-driven business models present in the growing sector literature.

The paper analyzes the case of “ZERO”, a company linked to the strategy innovation ecosystem of the Ca’ Foscari University of Venice, Italy. The empirical data were collected through a semi-structured questionnaire, interviews and the analysis of public news on the business model available in the analyzed case study. The research is empirical and uses exploratory, descriptive analysis to interpret the findings. The article focuses on the evaluation of AI impact on the agricultural sector and its potential to create new business models.

The study identified how AI can support the decision-making process leading to an increase in productivity, efficiency, product quality and cost reduction. AI helps increase these parameters through a continuous learning process and local production, and the possible decrease in prices directed toward the goal of zero km food with fresh products. AI is a winning technology to support the key elements of the vertical farm business model. However, it must be coupled with other devices, such as robots, sensors and drones, to collect enough data to enable continuous learning and improvement.

The research supports new research trends in AI applied to agriculture. The major implication is the construction of ecosystems between farms, technology providers, policymakers, universities, research centers and local consumer communities.

The ZERO case study underlines the potential of AI as a destructive technology that, especially in vertical farms, eliminates external conditions by increasing productivity, reducing costs and responding to production needs with adequate consumption of raw materials, boosting both environmental and social sustainability.

The study is original, as the current literature presents few empirical case studies on AI-supporting business models in agriculture. The study also favors valuable strategic implications for the policies to be adopted in favor of new business models in agriculture.

The primary objective of this study is to analyze the performance and risk characteristics of portfolios composed of Spanish family businesses (FBs) when sustainability and quality factors are taken into account. By comparing different portfolio compositions against a benchmark, the study aims to provide insights into the impact of these factors on portfolio performance.

This study employs an empirical approach to evaluate the performance and risk of portfolios consisting of Spanish family businesses (FBs) by incorporating sustainability and quality factors. It compares the results of various portfolios against a benchmark, utilizing GARCH models and the extended six-factor model of Fama and French for the period 2018–2023.

The findings reveal that investing in Spanish family businesses (FBs) yields higher returns compared to the index, with portfolios incorporating quality factors demonstrating superior performance. However, the inclusion of sustainability factors negatively affects portfolio performance. These results highlight the significance of considering sustainability and quality factors in portfolio construction and investment decisions.

This study contributes to the existing literature by examining the performance and risk implications of incorporating sustainability and quality factors into portfolios of family businesses. The findings offer valuable insights for investors and managers interested in constructing portfolios or developing financial products that balance risk and return effectively.

For decades, the construction industry has not significantly changed the way it operates, despite its economic and ecological importance worldwide. Hilti’s ambition is to change that and create a better future for its customers. This chapter highlights which trade-offs Hilti faces in their innovation journey towards solutions, while transforming the organisation: speed versus involvement, agility versus perfection and relationship versus competencies. Visible leadership and the preservation of the unique Hilti culture has been critical to deal with those dualities. To create tangible results, it has proven essential to evolve structures and processes for the ‘new solution’ businesses, while changing the way of hiring people and the types of people required for those new units. Innovating the ‘Hilti way’ summarises key learnings for other organisations.

This paper aims to study the role of ethics in the social innovation process and its effect on entrepreneurial passion. It explores the factors that encourage social entrepreneurs to innovate by examining the concepts of harmonious and obsessive passion and ethics.

The database consists of 97 entrepreneurs who benefited from the services offered by the support organizations for social entrepreneurs. The data are analyzed using the partial least squares structural equation modeling.

The results show that Islamic ethics has a positive effect on social innovation. This effect can be further amplified by harmonious passion (HP). Such passion certainly strengthens social entrepreneurs throughout the innovation process and consolidates the implementation phase of their projects.

This study highlights the importance of ethics in the process of social innovation. Ethics acts directly or through HP to stimulate social innovation. This passion enables taking actions and favors the creation of innovative social projects.

These findings add value to the previous literature by introducing ethics into the entrepreneurial passion theory and exploring new factors that promote social innovation.

Scholars note there are limited studies analyzing ticket price determinants. Using the common seat approach, the authors sought to advance this line of research by analyzing determinants of National Basketball Association (NBA) ticket prices in the secondary ticket market. The authors’ research seeks to ask two questions. The first is how ticket prices in the secondary market are associated with common determinants of consumer demand. The second question is what impact the COVID-19 pandemic has on ticket prices in the secondary market.

Ticket prices of NBA regular season games in the 2021–2022 season were collected a week before the game day from Ticketmaster.com. A regression model was estimated with a group of independent variables: income, population, consumer preference, quality of viewing, quality of contest and pandemic (the number of COVID-19 cases).

Results indicate income, population, consumer preferences (e.g. team quality and star players) and quality of viewing (e.g. arena age and weekend) impact prices. Further, the number of COVID-19 cases did reduce the ticket price.

The present study illuminates the theoretical significance of analyzing ticket prices as a proxy of demand in professional sport, while providing practical implications regarding the potential opportunity to increase revenue.

Nicolas Dupont, the owner of Chateau de Montana, a struggling (and old) boutique hotel in Crans-Montana Ski Resort, Switzerland, wished to renovate and reposition his family-owned hotel to target higher room rates. Dupont commissioned Olga Mitireva and Yulia Belopilskaya as consultants to assess the proposition. The consultants had to extract cues for the room rate of the repositioned hotel from comparable hotels. However, the room rates varied significantly across similar hotels due to their differing characteristics and locations. It was a cognitive challenge to read the patterns from a few comparable hotels. They collected the data of 200 hotels from similar locations and simulated room prices using hedonic regression models.