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.

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.

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.

The importance of play is well established in early childhood development; however the importance of play appears to diminish in more advanced levels of education. Despite this, the demand for experiential, engaging learning experiences that seek to differentiate graduate-level programs in a fiercely competitive market continues to increase. This research sought to explore the phenomenon of bringing play and playfulness to the graduate-level classroom as a means through which to enhance creativity, student engagement, and teamwork. The LEGO® Serious Play (LSP) activity was originally created to be used as a facilitation strategy for business executives seeking to enhance innovation and business performance. This research sought to develop a protocol to adapt the LSP activity for masters’ students completing a mandatory marketing course. The primary aim of the research considered whether LSP would provide a valuable learning activity for future graduate-level marketing classes. As such, feedback was collected on the activity from students following engagement with LSP. The results of the study provide guidelines for marketing educators to seamlessly incorporate novel activities, such as LSP, into their teaching practice.

The impact of COVID-19 on global human resource (HR) management has been swift, dramatic and has fundamentally changed HR processes. The prompt online migration of business has altered the skills required by employees to succeed in the workplace of the future. This research examines the hard and soft skill gaps that exist in the digital marketing and advertising industry. Through the use of two data collection points in 2019 and 2020, the research identified a renewed importance being placed on soft skills in the wake of the COVID-19 pandemic. Soft skills and the development thereof have become a key focal area of training for new employees as a result of remote working. The identified hard skill gaps are indicative of the future growth areas of the industry, focusing on data analytics, marketing automation and user experience. Future research should consider an expansion to other industry-specific skills and contrast country-level skill gaps.

Kindness can strengthen your employer brand. The business environment is changing, and the value of kindness in the corporate world is garnering increased attention. Paying it forward is a way to pass acts of kindness on to others. This allows employees and business partners to go above and beyond formal expectations that not only benefit the individuals involved but also the businesses they represent. Paying it forward can potentially create competitive advantage for firms from an employer branding perspective (to attract and retain talent) and in the broader market sense. This behavior can strengthen the employer brand in numerous and effective ways, and managers must understand, engage in, and encourage such conduct. In this article, we discuss different examples, benefits, and risks of paying kindness forward on a micro-, meso-, and macro-level. After providing this foundation, we introduce practical guidelines for managers on how to foster a paying-it-forward mindset among employees and the broader organization. The guidelines were created using insights from interviews we conducted with stakeholders in a business ecosystem in northern Sweden.

Consumers today are well accustomed to a digitized consumer journey, actively seeking social proof from online customer reviews to guide consumption decisions. These review platforms have been shown to be influential in guiding consumer behavior across many product and service categories. The language used to describe products on review platforms is of importance, given its potential to influence consumer perceptions and purchase intentions. Despite this, little attention is placed on the language used in reviews. In order to address this gap, this research sought to analyze and contrast the language used in online customer reviews within the wine category, by contrasting the lexical characteristics of reviews of white and red wine. The research made use of 2917 online wine reviews for four different varietals, two red wine (cabernet sauvignon and shiraz) and two white wine (chardonnay and sauvignon blanc) varietals. The Linguistic Inquiry and Word Count (LIWC) software was used to conduct a lexical analysis, with the results indicating both similarities and differences between the reviews of red and white wine varietals. The results provide insight into the lexical components of the wine reviews and the implications that these bear on the perceived usefulness of the review.

This study operationalizes the knowledge-based dynamic capabilities (KBDC) that act as drivers of innovation performance in an innovation ecosystem. Four constructs, knowledge creation, knowledge diffusion, knowledge absorption and knowledge impact, are comparatively analyzed to assess their impact on the innovation performance of developed, transition and developing market economies. Using the Global Innovation Index 2019 dataset, partial least squares path analysis is employed to identify which KBDC is the biggest driver of innovation performance across 129 countries at different stages of economic development. Across all four constructs, knowledge creation is the biggest driver of innovation performance. In developed and developing market economies, knowledge creation is the strongest predictor of innovation performance, while knowledge absorption is the strongest predictor of innovation performance in transition economies. An innovation ecosystem framework, centered around KBDC, is proposed to provide a point of reference for the innovation performance and competitive advantage inherent in each knowledge-related capability.