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This paper aims to illustrate the extensive benefits of qualitative data analysis as a rarely undertaken process in post-occupancy evaluation surveys. As a result, there is limited evidence of what occupants say about their buildings, especially for operational parameters, as opposed to how they rate them. While quantitative analyses provide useful information on how workers feel about workplace operational factors, qualitative analyses provide richer information on what aspects of the workplace workers identify as influential to their comfort, well-being and productivity.

The authors analysed 6,938 comments from office buildings worldwide on workers’ perception of workplace operational factors: design, storage, needs, space at desks and storage in their work environments. These factors were analysed based on the buildings’ design intent and use, and the associated comments were coded into positive, negative and balanced comments. The authors used a combination of coding, descriptive analysis, content analysis and word cloud to dissect the comments.

The findings showed that whereas workers rated these operational factors favourably, there were significantly more negative comments about each factor. Also, the Chi-square test showed a significant association (p < 0.01) between the satisfaction scale and the type of comments received for all the operational factors. This means that when a factor is rated high in the satisfaction score (5–7), there were fewer negative and more positive comments and vice versa. The word cloud analysis highlighted vital aspects of the office environment the workers mostly commented on, such as open plan design, natural lighting, space and windows, toilets, facilities, kitchens, meeting room booking systems, storage and furniture.

This study highlights the importance of dissecting building occupants’ comments as integral to building performance monitoring and measurement. These emphasise the richness and value of respondents’ comments and the importance of critically analysing them. A limitation is that only 6,938 comments were viable for analysis because most comments were either incomplete with no meaning or were not provided. This underlines the importance of encouraging respondents to comment and express their feelings in questionnaire surveys. Also, the building use studies questionnaire data set presents extensive opportunities for further analyses of interrelationships between demographics, building characteristics and environmental and operational factors.

The findings from this study can be applied to future projects and facility management to maintain and improve office buildings throughout their life cycle. Also, these findings are essential in predicting the requirements of future workplaces for robust workplace designs and management.

The authors identified specific comments on the performance of workplaces across the globe, showing similarities and differences between sustainable, conventional, commercial and institutional buildings. Specifically, the analysis showed that office workers’ comments do not always corroborate the ratings they give their buildings. There was a significantly higher percentage of negative comments than positive comments despite the high satisfaction scores of the operational factors.

There are two theoretical concepts that can be taught in this case.The new approach to teaching entrepreneurship is termed “lean start-up” and “hypothesis-driven entrepreneurship.” The business model canvas is a core tool of this approach. This framework defines nine key components of a successful business strategy. These components include defining value propositions; identifying customer segments; identifying channels; maintaining customer relationships; defining key activities, key resources and key partners; understanding the revenue model of the business; and the organization’s cost structure. This is considered to be a rigorous approach to learning about and developing a new venture.The other theoretical approach that can be discussed through this case is the link between uncertainty and entrepreneurial growth. These theories associate the willingness of entrepreneurs to bear the perceived uncertainty associated with entrepreneurial acts as representative of the belief-desire model. There is a need for entrepreneurs to experiment and search for alternative paths forward in order to counter this uncertainty. Systematic search processes to discover relevant information will strengthen this process.

This case is based on primary data collected through interviews with company personnel. The company consented freely to the use of their data in the case. The authors have no connection with the company. The four student coauthors had previously pursued an internship with the company and had worked on the machine learning analysis part.The two faculty coauthors in the case contacted the company after the internship and discussed the opportunity to write the case on the company. One of the faculty then interviewed key personnel in the company, including one of the co-founders.

Xoxoday is a technology company that provides employee rewards and corporate gifting to its customers. The company was started by Sumit Khandelwal, Manoj Agarwal, Abhishek Kumar and Kushal Agarwal. In 2018, the company reinvented itself as an experiential gifting company.The company faced some challenges during the lockdowns imposed due to COVID-19. Khandelwal knew that they had to try something new to achieve higher growth in the future. He wondered if higher usage of technology was the solution. It was necessary for them to carve a new path in these times.

This case study can be used at the undergraduate level in courses relating to entrepreneurship strategy and business models for entrepreneurs.The case can be used to highlight the dilemmas faced by entrepreneurs due to unforeseen crises. This case is relevant for classes that will discuss growth crises and out-of-the-box solutions for unprecedented crisis situations.

Changes in the educational environment regarding the teaching–learning process are required as a result of social, economic, and cultural transitions. In light of this, this chapter will discuss and examine the flipped classroom method’s qualities as well as potential applications for individualized higher education. A bibliometric review of the Scopus database would be done in order to fulfil the suggested goal, and a report on a flipped classroom’s implementation at a Brazilian university was also provided. It was discovered that the traits are pre-class activities, actions done in preparation for class, and postclass activities. This instructional approach can be utilized to motivate pupils in individualized instruction.

The purpose of this study was to examine consumer data acquired by branded prescription drug websites and the ethics of privacy related to the interconnected web of personal information accessed, packaged and resold by tracker technologies.

The research used the DMI Tracker Tool to collect data on the top 17 branded prescription drug websites, with a specific interest in the tracker technologies embedded in those websites. That data was analyzed using Gephi, an open-source data visualization tool, to map the network of trackers embedded in those branded prescription drug websites.

Findings visualize the interconnections between tracker technologies and prescription drug websites that undergird a system of personal data acquisition and programmatic advertising vehicles that serve the interests of prescription drug marketers and Big Tech. Based on the theory of platform ethics, the study demonstrated the presence of a technostructural ecosystem dominated by Big Tech, a system that goes unseen by consumers and serves the interests of advertisers and resellers of consumer data.

The 17 websites used in this study were limited to the top-selling prescription drugs or those with the highest ad expenditures. As such this study is not based on a random sampling of branded prescription drug websites. The popularity of these prescription drugs or the expanse of advertising associated with the drugs makes them appropriate to study the presence of tracking devices that collect data from consumers and serve advertising to them. It is also noted that websites are dynamic spaces, and some trackers within their infrastructures are apt to change over time.

Branded prescription drug information has over the past three decades become part of consumers’ routine search for information regarding what ails them. As drug promotion moved from print to TV and the Web, searching for drug information has become a part of everyday life. The implications of embedded trackers on branded prescription drug websites are the subject of this research.

This study has significant social implications as consumers who are searching for information regarding prescription medications may not want drug companies tracking them in a way that many perceive to be an invasion of privacy. Yet, as the Web is dominated by Big Tech, web developers have little choice but to remain a part of this technostructural ecosystem.

This study sheds light on branded prescription drug websites, exploring the imbalance between the websites under study, Big Tech and consumers who lack awareness of the system that operates backstage.

This study aims to present a comprehensive knowledge mapping and an in-depth analysis of plastic and sustainability research to understand better global trends and directions in this field that emerged between 1995 and 2022.

This study presents a visual analysis of 1933 research articles listed in the Web of Science (WoS) databases between the years 1995 and 2022 related to plastic and sustainability. The knowledge mapping based on CiteSpace and VOSviewer presents the current research status, which contains the analysis of the collaboration network, co-citation network, references with citation bursts and keyword analysis.

The results reveal that China and the USA are the most prominent countries in exploring the notion of sustainability and plastic. The Chinese Academy of Science is the most prominent institution. Chai Qiang, Friedrich Daniel, Sahajwalla Veena and Ok Yong Sik are the most prolific authors in this field. Furthermore, circular economy, bioplastic, sustainable development, polyester and bioplastics are the highly discussed issues in recent years. Not surprisingly, COVID-19 is the latest topic of discussion started in 2021 due to its negative impact on plastic pollution and the challenges it posed to sustainability.

This study is among the pioneers to shed light on the current research status of plastic and sustainability using the bibliometric method and the newest data. This study also suggests that collaborations between scholars and institutions require to be enhanced for better management of plastic pollution and to contribute to sustainable development.

The research aims to provide a longitudinal case study to understand how digital transformation can be embedded in municipal reporting frameworks. The central role of such technology becomes increasingly evident as citizens demand greater transparency and engagement between them and governing institutions.

Utilising a longitudinal case study methodology, the research focusses on Turin’s Integrated Popular Financial Report (IPFR) as a lens through which to evaluate the broader implications of digital transformation on governmental transparency and operational efficiency.

Digital tools, notably sentiment analysis, offer promising avenues for enhancing governmental efficacy and citizenry participation. However, persistent challenges highlight the inadequacy of traditional, inflexible reporting structures to cater to dynamic informational demands.

Embracing digital tools is an imperative for contemporary public administrators, promoting streamlined communication and dismantling bureaucratic obstructions, all while catering to the evolving demands of an informed citizenry.

Different from previous studies that primarily emphasised technology’s role within budgeting, this research uniquely positions itself by spotlighting the transformative implications of digital tools during the reporting phase. It champions the profound value of fostering bottom-up dialogues, heralding a paradigmatic shift towards co-creative public management dynamics.

In post-normal times, when surprises and conflicts rule and the concept of normal is increasingly useless (Dufva & Rowley, 2022), leaders in organisations are faced with new and never-before-faced problems. That’s why it becomes crucial to focus on innovation leadership and its components. This chapter introduces Design2Be, a new methodology developed by Evidentia, a consulting firm, that changes the paradigm of leadership development. The very structure of Design2Be guides participants into an innovative experience of learning, no longer linear and sequential but circular and holistic, in which the goal is the development of an innovative self and team leadership mindset, by discovering and acting out a personal growth towards self-expression and fulfilment. We reflect on the development and application of this new approach, through a case story in a large Italian company with a group of (future) leaders testing and applying the new methodology. The chapter uses Paton’s (2001) reflective model to reflect on our roles as consultants, co-creating the approach with our client.

The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.