Growing inequalities and illness among citizens call for innovative methods for developing resilient societies. This paper highlights the importance of urban design, which includes aspects of interactive communities, using participatory approaches such as co-design early in the process. To exemplify the method of co-design, this paper uses one case study from northern Sweden with two growing local initiatives, one focused on common cultivation, and another connected to youth activities for sustainability and recycling. Using design methods such as braindrawing and the Who, What, Where, When, Why, and How [WWWWH] enables people to stay in the conceptual stages, develop it and understand it further. Ideas that emerge from local initiatives can expand beyond the group itself, fostering more interactions and places for people to gather. Supporting these projects can significantly impact local communities by improving social and cultural sustainability, making it essential to promote community-led initiatives in urban design to enhance human wellbeing. The findings show the importance of embedding relational infrastructuring participatory approaches early in the process for designers and planners to identify local drivers for change that is aligned with community values, as well as fostering wellbeing through meaningful long-term involvement. Design can serve as an enabling practice contributing to ecological, social, and cultural sustainability.

This paper investigates employer attributes and perceptions of industry reputation and industry attractiveness, and their impact on employees’ intention to stay in tourism and hospitality. Results show that desired reputation, training, and development value, and prosocial value significantly influence perceptions of industry reputation. Desired diversity and prosocial value have a positive relation to industry attractiveness, while training and development value is negatively related. Perceptions of the industry attractiveness are a major contributor to the intention to remain within the sector. This paper seeks to further the discourse concerning employer branding by introducing an employment value proposition perspective applicable across industries.

Marketers play an integral part in the strategic planning process of a firm, both concerning the role of marketing in the strategic discourse, as well as the marketers’ interaction between various levels of hierarchy within an organization. The top management team (TMT) formulates strategic decision and influences the implementation of tactical approaches. Organizations often also mirror their TMT. Organizational strategy plays a critical role in the marketing capability of an organization, as activities are decided based on strategy and organizational goals. A TMT needs to be structurally composed in such a way that the firm is functionally positioned to respond and adapt to challenges in the marketplace continuously. With this in mind, the paper develops a conceptual representation of the interface between marketing organization, strategic decision-making, functional TMTs, and organizational structure. We conceptually assess the impact of functional TMT composition on marketing organization and corporate-level strategy alignment. Our research question focuses on how functional TMT composition and decision-making impacts marketing organization and overall market orientation. At the crossroads between strategic organizational decision-making and leadership, the upper echelon theory and contingency theory serves as the theoretical foundations from which conceptual propositions are developed in the context of marketing organization and market orientation.

Large language models (LLMs) not only mimic human language generally but are also showing the ability to exhibit nuanced, idiosyncratic human behavior. This could lead to the expanded use of LLMs in research and a diminution of the influence of humans. It also has implications for AI alignment and the role of the technology in society.

Online rating systems are central to how firms monitor performance and make decisions. Yet as ratings increasingly cluster at the top end, their ability to distinguish actual differences in quality declines – a phenomenon known as information compression. This paper examines when such compression distorts managerial insight and when it simplifies decision-making. We identify three categories of boundary conditions – evaluation system design, evaluator dynamics, and contextual factors – that determine whether compressed ratings hinder or help managerial interpretation. The proposed COMP-ACT (Compression–Action) framework links these diagnostic conditions to four actionable strategies: act diagnostically, triangulate, steward trust, or embrace compression. These strategies guide how managers interpret and manage online evaluations, depending on decision importance and the level of evaluator interaction. The framework further helps managers restore insight where ratings mislead and leverage convergence where it signals stability, offering practical tools for navigating compressed evaluative data in increasingly data-saturated markets.

In a complex business environment, the quest for intelligent solutions has placed artificial intelligence (AI) at the center of many operational business decisions, particularly within the retail sector. As retailers’ investment in AI disrupts value chains, they must adapt to organizational changes, yet limited research exists on how to address organizational challenges when integrating AI into the retail value chain. Using 23 expert interviews with retail executives and AI vendors, this study investigates the socio-technical challenges retailers encounter when integrating AI into their value chain and offers strategies to address these organizational hurdles. We identify micro-, meso-, and macro-level factors impacting AI implementation in retail and propose an AI Implementation Compass to address the change management process. This framework serves as a guide to navigate the complex landscape of AI adoption, emphasizing a holistic approach that considers not only internal organizational dynamics, but also external market forces.

The advent of personalized medicine, or precision medicine, promises a revolution in healthcare, offering treatments tailor-made to the genetic makeup and lifestyle choices of individuals. Despite the significant potential, its integration into mainstream healthcare is hindered by several challenges, including data silos, privacy concerns, and a lack of coordinated efforts across the healthcare ecosystem. This paper examines the role of Blockchain technology as a solution to these obstacles. By leveraging the unique attributes of Blockchain we propose a model for a healthcare system that aligns with the ideals of personalized medicine. Through conceptual analysis and discussing initiatives like the 100,000 Genomes Project, we illustrate the synergy between Blockchain and personalized medicine. The paper concludes by envisioning an integrated healthcare delivery model that not only advances drug research and treatments but also significantly improves patient outcomes through personalized care approaches.

Airports are essential to the global economy, providing significant revenue and driving regional growth. In order to remain competitive and achieve sustainable development, airports must continuously monitor and improve service quality. To this end, understanding traveller perceptions of their experiences is important. While traditional survey-based methods are beneficial, managers are increasingly looking for alternative ways of collecting feedback, such as online reviews. Automated text analysis provides a cost- and time-effective technique with which to analyse large datasets of unsolicited online reviews, providing managers with strategic insights to enhance service quality. This study explores the potential of supplementing traditional airport service quality monitoring methods with automated text analyses to better understand traveller feedback and improve service quality. The results provide new methods to measure airport service quality, offering a fresh perspective on customers’ satisfaction with service quality experiences, and highlighting key strategic implications that can help organisations gain a competitive advantage.

The democratization of powerful artificial intelligence (AI) tools, including ChatGPT, has sparked the interest of business practitioners given their ability to fundamentally change the way we work. While AI tools are positioned to augment human capabilities, their effective implementation requires the skill to understand where, when and how to best utilize them efficiently. Furthermore, meaningful engagement with the content produced by generative AI (GenAI) necessitates the intricacy of appropriate prompt engineering to optimize the learning process. As the field of GenAI continues to advance, the art of developing impactful prompts has become a necessary skill for harnessing its full potential. This research develops an AI prompting protocol through a constructivist theory lens. Based on the principles of constructivism, where individuals assimilate new knowledge by bridging it with their existing understanding, this research suggests an active engagement process in the human-AI co-construction of knowledge through GenAI. The goal is to empower business managers and their teams to construct effective AI prompts and validate responses, thereby enhancing user interaction, optimizing workflows, and maximizing the potential outcomes of AI chatbots.