Mobility, its current state and development perspectives in the future creates challenges with respect to sustainability, the first of which is the uncontrolled increase in greenhouse gas emissions in the last few decades, while road transport is one of the “sinners” creating long-term negative impact. The second is the dominance of car travel and car usage in the passenger transportation segment before the latest COVID-19 pandemic accelerated environmental problems. Although recent trends show new, greener patterns in consumption, there is still a relatively low share of consumers acknowledging the importance of sustainable and green preferences. This research study aims to investigate car sharing from users’ perspectives and to determine the most significant factors influencing their choice of sharing services to ensure upscaling of car sharing and, thus, contribute to urban sustainability. This research study contributes to the overall scientific discussion on car sharing and its role within urban sustainability, particularly with the following: (1) deeper investigation of car sharing and its users motivation perspectives in Latvia; (2) analyses of the most significant motivational factors for car-sharing users and aspects of sustainability; and (3) the insight into the generational differences triggering a number of car-sharing users. The existing and potential users of car sharing were surveyed in order to determine the motivational factors for its usage and attitudes towards it. Socio-demographic variables in statistical analysis were used to identify economic and environmental factors that meaningfully influence the choice of car-sharing services. The results of this study can support further development in new car-sharing business models and the value proposition for consumers in Latvia, as well as preparing policy recommendations on the promotion of sustainable transport. These findings are also useful to academics for the investigation of recent trends in car sharing during the COVID-19 pandemic.

Nowadays cities face numerous challenges amplified to build necessary urban municipal and community capacity to ensure sustainability transformation to respond to the local and global challenges of climate change, inequality, and access to resources. This research combines the study fields of sustainability, economic development, governance of sustainability transformation, providing the multidisciplinary approach as a systemic-oriented view encompassing the social, technological and ecological aspects of urban transformation. The purpose of the paper is to explore how the concept of urban transformation could be operationalized for research of economic development under the economic strain assuming the emergency of Covid-19 grand challenge. The research methods used are a systematic literature review and the content analysis. The paper provides a detailed characterization of the urban transformation exploring this concept from the structure and system perspectives for the economic exit from the crisis.

Digitisation of business processes has attracted practitioner attention across a wide range of industries as it enables enterprises to better manage their processes and improve results. The rate of digitisation has grown over the last decade and has become essential for enterprises to handle unforeseen disruptions and promote better management of resources. The COVID-19 pandemic is one example of a recent major disruption that caught enterprises off-guard and had a major impact on their value chains. The adoption of digitisation of business processes has significantly sped up to improve enterprise and their value chain resilience and enable enterprises to survive and potentially thrive in today’s uncertain environment. Through this movement, innovative companies have embraced idea management to develop new business models and achieve competitive advantage. One of the major digital tools that support enterprises in their idea management efforts is web-based idea management systems. This study aims to show how enterprises can manage the rewards of platforms, such as web-based idea management systems, to achieve a first-in-class quality and quantity of ideas sourced from the stakeholders involved in these platform-based ecosystems. To reach this aim, a global survey study was conducted involving over 400 responses from enterprises that use web-based idea management systems and consequent results were analysed. The impact of intrinsic and extrinsic rewards on the results of enterprises is a well-researched area. To further verify the results, the authors have conducted ten expert interviews and a qualitative analysis of a data set sourced from a database that contained 129 company entries that utilise web-based idea management systems and was available for this research that was conducted over a two-year period. Results strongly indicate that mixed and financial reward type tasks result in a higher quantity of ideas created, however, higher idea quality—i.e., ideas selected—is higher for financial reward tasks. The research highlights that there could be differences between different web-based idea management systems application groups.

The combination of Artificial Intelligence (AI) and unmanned aerial vehicles (UAVs), sometimes known as drones, has become a revolutionary approach in modern military and security operations. The purpose of this study is to explore and assess the efficiency of AI-enabled autonomous navigation and decision-making systems for drones in defense security applications. Through a comprehensive literature review, researchers analyze the various AI techniques and algorithms used in these systems, including machine learning, deep learning, and reinforcement learning. The study examines different aspects of autonomous drone navigation, such as sensors, decision-making modules, communication systems, and countermeasure systems. By reviewing scholarly articles and existing studies, researchers gain insights into the hardware and software components, including GPS modules, IMUs, cameras, and other sensors. This analysis provides a clear understanding of the current state of AI-enabled drone technology for defense security and identifies potential areas for future research and improvement. This research study discusses the working of AI-enabled drone autonomous navigation and decision-making systems designed primarily for defense security applications. The study starts by explaining the structure of drone navigation systems, which includes a wide range of hardware and software components. These comprise GPS modules for tracking location, inertial measurement units (IMUs) for estimating attitude, and cameras for seeing the environment. By incorporating these sensors into a sturdy structure, drones are able to detect their surroundings and man oeuvre independently in intricate situations. The effectiveness of AI-enabled drone navigation relies heavily on the application of sophisticated artificial intelligence techniques and algorithms. Machine learning algorithms, such as deep neural networks and reinforcement learning, are crucial in improving the decision-making abilities of drones. AI algorithms allow drones to dynamically adjust their navigation tactics, optimize flight trajectories, and intelligently respond to unforeseen obstacles or hazards by analyzing large volumes of sensor data in real-time. Furthermore, this research explores the datasets being employed in the training and evaluation of AI models for the purpose of drone navigation and decision-making. These datasets contain varied environmental conditions, topographical features, and security scenarios experienced in defensive operations.

The purpose of this paper is to create and test an idea management sequence framework to reinvent or redefine the value proposition. Idea management with sequencing activities must be considered as a systematic managerial process and should not be confused with the occasional result of an individual with a design thinking mindset. This paper suggests a new approach—a systematic, 4-step idea management sequence to redefine or reinvent value proposition in a business model, which was validated through an action-based research method involving 20 managers from practice by applying the proposed framework. Based on the idea management approach, authors describe the idea generation and evaluation processes and their possible moderation elements. This research contributes to previous studies of the design thinking and innovation by substantiating a concept of the idea management sequencing and proposing a new 4-step approach that can be applied by organisations to redefine or reinvent value proposition in their business models. Being influenced by pandemic restrictions and the full or partial remote workforce, the 4-step idea management approach is beneficial for virtual group sessions as it increases the quality of outcomes, engagement of individuals, collaborative openness, and confidence.

This literature review explores Green Human Resource Management (Green HRM) initiatives aimed at nurturing employees' commitment towards eco-friendly work output and environmental sustainability in organisations. Green HRM is a strategy that integrates an organisation's environmental values into its human resource strategy and practices. This review reflects on the interplay between Green HRM practices and employees' green commitment, that is, the degree to which they feel psychologically bonded to environmental goals and pursue them. Moreover, it focuses on how green commitment contributes to achieving specific organisational environmental sustainability outcomes, including waste reduction, energy saving, and improved corporate social responsibility. Drawing on empirical research, the review outlines specific mechanisms by which Green HRM practices (e.g., green training programs and green performance appraisal) influence employees' sustainability-related attitudes and behaviours. It also addresses barriers to adopting Green HRM and developing green dedication, such as inadequate resources, a lack of management interest, and resistance within the company. The review findings are concluded with suggestions for future research direction, requesting the need for cross-sector studies and the examination of the long-term implications of Green HRM implementations on environmental sustainability. Through qualitative methodology, the study establishes a link between the main variables involving environmental sustainability, employees' green behavior, and GHRM (Green HRM). Future research can examine more closely how industry-specific elements affect workers' green commitment and how digital technologies like artificial intelligence and big data might assist businesses in meeting their sustainability goals. Further investigation into the cultural factors that can account for variations in green commitment among various geographic areas will also yield a more comprehensive comprehension of this idea. The impact of employee green commitment on organizational sustainability performance requires longitudinal studies to understand organizational practice better. Finally, future research topics must look into the barriers to Green HRM practices to promote their successful impact.