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The purpose of this paper is to measure students’ satisfaction with the didactics in a large Italian university, that of Padua, giving special attention to its evolution over time in consecutive academic years. The overall level of the quality of the didactics is examined and its change over time is modeled. Moreover, the effect of courses’ and teachers’ variables on it is estimated.

Latent cluster class models and mixture latent class Markov models are estimated in order to identify groups of courses that are homogeneous for the level of the quality of the didactics. Evolution over the three academic years of satisfaction is monitored. The effect on the clustering and its dynamics of potential covariates is also examined.

Results of model estimation reveal some interesting evidences that are important indications for the university management to define targeted strategies to elevate teaching quality.

The paper gives its original contribution both on the side of methods applied to analyze data collected with students evaluation of teaching and on the evidences obtained for a large university.

Microfinance has become an important way to alleviate poverty. Though four decades have passed since its introduction, its impact is still not entirely clear. What makes it difficult to ascertain its efficacy is the existence of diverse types of microfinance organizations and client profiles. Microfinance institutions must primarily pay more attention to the client, and to the mechanism through which financial services are delivered. The purpose of this paper is to identify the profiles of microfinance customers and the features of their operations.

In this paper, multilevel latent class models were estimated to reveal clusters of operations and classes of clients.

The results show that there are six clusters of operations and four classes of clients in the market, each with distinct profiles and needs. Different strategies are recommended for each cluster and class.

Numerous studies have focused on the importance of getting to know the clients of microfinance programs, but none as yet have used market segmentation as a way to do so. The goal is to generate better strategies to help clients improve their business results. Applying market segmentation to the microfinance market may point to different products for different groups of clients, taking the real needs of each of them into account.

The purpose of the paper is the analysis of the evolution of students’ satisfaction over time in a large Italian university and the effects on it because of some characteristics of the teachers: didactic practices, beliefs and needs with regard to teaching and learning.

The first step of the analysis identifies a latent construct, measured with items composing the questionnaire, and proposes a reduced set of indicators to measure satisfaction and to model its evolution over time (information collected in three consecutive academic years is available). A second step clusters teachers in homogenous groups with reference to their opinions, beliefs and needs, collected with a new survey conducted at the University of Padova, with the aim of developing strategies to support academic teachers. Then, a mixture conditional latent growth model is estimated with covariates affecting the latent parameters and class membership.

Model estimation identifies a large group of university courses with a high level of satisfaction, which stays constant over time, and a small group of problematic courses with low satisfaction, moreover, that decreases over the three considered academic years. Interesting significant effects of covariates related to both the teacher and the didactic activity are estimated.

Statistical analyses show that the implementation of innovative didactic practices and commitment to quality of teaching are important factors to be encouraged by the university management. On the contrary, the traditionalist way of teaching and a low passion for teaching do not improve students’ satisfaction.

Students’ evaluation of teaching quality plays a major role in higher education. Satisfaction is not directly observable, nevertheless it can be measured through multi-item measurement scales. These instruments are extremely useful and their importance requires accurate development and validation procedures. The purpose of this paper is to show how latent class (LC) analysis can improve the procedures for developing and validating a multi-item measurement scale for measuring students’ evaluation of teaching and, at the same time, provide a deeper insight in the phenomenon under investigation.

The traditional literature highlights specific protocols along with the statistical instruments to be used for achieving this goal. However, these tools are suited for metric variables but they are adopted even when the nature of the observed variables is different, as it often occurs, since in many cases the items are ordinal. LC analysis takes explicitly into account the ordinal nature of the variables and also the fact that the object of interest is unobservable.

The data refer to the questionnaire to evaluate didactics to the students of the University of Padua. Within LC analysis allows an insight of scale properties, such as dimensionality, validity and reliability. Moreover, the results provide a deeper view in the way students use the scale to report satisfaction suggesting to revise the instrument according to the suggestion by the National Agency for University Evaluation.

The paper gives an original contribution on two sides. On the side of methods, it introduces a more accurate methodology for evaluating scales to measure the students’ satisfaction. On the side of applications, it provides important suggestions to the university management to improve the process of quality of the didactics evaluation.

Dynamic market segmentation is a very important topic in many businesses where it is interesting to gain knowledge on the reference market and on its evolution over time. Various papers in the reference literature are devoted to the topic and different statistical models are proposed. The purpose of this paper is to compare two statistical approaches to model categorical longitudinal data to perform dynamic market segmentation.

The latent class Markov model identifies a latent variable whose states represent market segments at an initial point in time, customers can switch to one segment to another between consecutive measurement occasions and a regression structure models the effects of covariates, describing customers’ characteristics, on segments belonging and transition probabilities. The latent class growth approach models individual trajectories, describing a behaviour over time. Customers’ characteristics may be inserted in the model to affect trajectories that may vary across latent groups, in the author’s case, market segments.

The two approaches revealed both suitable for dynamic market segmentation. The advice to marketer analysts is to explore both solutions to dynamically segment the reference market. The best approach will be then judged in terms of fit, substantial results and assumptions on the reference market.

The proposed statistical models are new in the field of financial markets.

Specifically, this study aims to examine residents’ perceptions regarding the following: the sociocultural, environmental and economic impacts generated by the presence of Airbnb and the irritability caused by the presence of Airbnb based on Doxey’s Doxey (1975) irritation index (i.e. index).

Twenty-one semistructured in-depth interviews were conducted between February and March 2021 with residents of three condominiums in the Huancaro residential complex. Data were analyzed using the qualitative data analysis software ATLAS.ti 8.

Results showed that participants perceived negative economic impacts regarding investments, jobs, real estate prices and overall cost of living; negative sociocultural impacts regarding criminality, social conflicts and cultural exchange; and negative environmental impacts regarding sanitation in the context of the pandemic and the state of the Airbnb apartments. Further, it was found that participants related to the following three of the four stages of irritability: euphoria, apathy and annoyance.

It is necessary to complement the information with the perceptions of the residents about the city’s authorities and managers in the hotel business before the stage of the COVID-19 pandemic and the current stage.

The study identifies improve Airbnb operations like establishing health paraments and defining cohabitation rules at the condominiums.

The residents consider that visitors’ returns produce positive and negative impacts on the quality of life being important for understanding their perceptions.

Short-term rental companies, such as Airbnb, generate a range of impacts on urban residents, particularly when travelers encroach on areas of the city beyond the traditional “tourist bubbles.” This study explored the perceptions of Airbnb’s impacts on activities among residents of Huancaro, a residential section of Cusco-Peru, in the context of tourism reopening after a year of an almost complete halt in tourism activities because of the COVID-19 pandemic. The study also highlighted the heterogenetic responses to Airbnb within the community.

COVID-19 has dramatically changed how people live, socialise and think about their future. The disruptive shock that hit societies all over the world had a significantly negative impact on businesses, creating not only economic discontinuity but also uncertainty and disorientation. This special issue on COVID-19 aims to phrase the pandemic crisis and its impact on how to do business.

The authors follow MacInnis’s (2011) suggestion that a conceptual article sees what others have identified in a new or revised way.

The authors develop the crisis management framework. The authors acknowledge that disruptive events may be repeated, and their consequences will have long-term and permanent impacts. These aspects highlight the need for a systemic approach in which the focus is not limited to an analysis of the cause of the crisis and ways of solving it but includes the paths through which the business, economic and social systems evolve because of the crisis.

Managerial policies, business models and practices that have been effective up to now will probably no longer work. Beyond this backdrop, the articles compiled in this special issue aim to help set the agenda for post-COVID business research

The authors identify four primary themes captured by these articles: strategies, capabilities, organisational transformations and value processes. In their entirety, they represent pieces of a conceptual puzzle that do not provide knowledge of “hard facts” but rather a “soft interpretation of how to approach the “new normal”, i.e. a new social and business context.

The purpose of this paper is to explain the different stages of business sustainability through a visual metaphor. This metaphor compares the interaction between the different variables of sustainability to the interaction between the colour wheels in the Interconnected Spinning colour wheel. As a result of this comparison, we propose the different stages of business sustainability.

Domains-interaction model approach is used to develop the metaphor.

The four stages of the business sustainability system resulting from this metaphor are: designable, feasible, endurable and responsible.

We recognize that a visual metaphor provides only a limited insight, which is a general drawback of a metaphor.

This visual metaphor as a tool will help practitioners, students and academics to easily understand the concept of business sustainability and the various stages of the system. This new perspective can support the practitioners in making effective decisions for sustainability.

This paper contributes in the field of corporate sustainability through the novel visual metaphor proposed. This metaphor can enhance the theoretical development in this field by approaching the concept of corporate sustainability from a different perspective.