Search results

The reputation has a significant impact on business, and it influences by causing an exponential positive or negative effect. There are many different issues that affect the level of reputation, and they are independent from the sector of the activity. If we focus on museums, previous studies mainly highlight the different strategies in order to manage and to increase their reputation. However, each research points out a specific aspect linked to the engagement, the use of digital technologies, or social media platforms. Our research aims to deep investigate the governance and leadership drivers in order to increase positive feeling within stakeholders also by using social media instruments. This research has indeed an exploratory nature as, to the best of our knowledge, no previous research focused on a similar strategy that characterizes for a “stellar” manager applied to a small museum in a small city.

The research uses a case study by observing the effects of selecting a well-known manager of the top ranked museum in the world (Louvre) in order to boost the reputation of a “startup” museum barely known (Pistoia Museums). After having analyzed the main drivers of reputation of the case, the study uses interview with the scientific director of the small museum.

The results contribute to the discussion about the drivers and the different strategies to boost reputation by showing how the management and leadership issues are able to increase it rapidly. However, findings also point out the need to have a clear overview about the digital tools applied to an adequate communication. The results show how the flexibility of a small growing museum can positively affect and boost reputation. This strategy can be applied to other small museums that aim to affirm their identity.

Online reputation manager has become increasingly important in tourism industry. Managers, regardless of working for a hospitality structure or a tourism destination, are paying more and more attention in respect of the importance of reputational levels. Online reputation, in fact, originates in visitor's user-generated contents (UGCs) but reverberates on the whole web, on successive visitors' attitude and behavior, and on managed organization performances. How to manage online reputation in tourism and destination management anyway mostly stayed an anecdotal topic for many years. While best practices exist, indeed, literature has frequently neglected their systematization. Building on this need, this book will try to improve and organize the existing body of knowledge on this topic to help future hotel and destination managers to better deal with the mounting environmental complexity.

A destination's ability to attract tourists is associated with the visitor experience and, in recent years, visitors have increasingly used virtual environments and digital innovation, such as social media platforms, to communicate their experience of tourist destinations. A positive well-communicated tourist experience improves the reputation of the destination and has relevant consequences for both the destination's attractiveness and its competitive advantage. On the contrary, when the destination's reputation is negatively affected by visitors' experiences, comments and reviews, such destination might compromise its ability to attract new visitors. Studies in this field agree alike that the tourist experience is negatively affected by overcrowding and overflows phenomena occurring around the visited city attractions. The present research, merging the aforementioned observations, investigates whether visitor density affects the online reputation of the Uffizi Gallery, estimated by extracting visitors' opinions and feedbacks on the city's main attractions from TripAdvisor ratings and from Twitter posts, by applying sentiment analysis to evaluate whether the text is positive, negative, or neutral. The city of Florence is an ideal case study, as the city records almost 16 million tourist overnight stays per year hence highly exposed to the risk of tourist overcrowding and overflows. The research findings reveal that Uffizi Gallery experiences and mood are influenced by the number of visitors insisting and if tourists live a negative experience, this is further exacerbated by the growing density of visitors themselves. We find that, if tourists have a negative experience, this is exacerbated by the density of visitors to the Uffizi Gallery. The results reveal also that tourists' experiences are even more influenced by any general dissatisfaction they experience in the city of Florence in a broader way. Practical implications and theoretical contributions are discussed.

This research aims to provide evidence of the impacts of market orientation, customer value approach (through prestige, value for money and reputation for quality) and innovation on museum sustainability.

The model is analysed through partial least squares (PLS-SEM), using a sample of 549 European museums.

The results reveal that reputation for quality, prestige, innovation and value for money positively and significantly influence museum sustainability. Interestingly, the most meaningful linkage is between market orientation and innovation.

This research helps museums that need to increase their customer value and innovativeness so as to ensure museum sustainability. It proves that museum managers have to increase employees’ involvement in decision-making processes.

By using a wide sample of European museums, this study suggests that museum managers need to consider the impact of marketing strategies and customer value perceptions on the economic and social sustainability of museums.

Online forums help in stimulating debates and reflection on a wide range of cultural topics, as well as providing answers for museum professionals working in specialised areas. The main objective of this paper is to concentrate on the relevance of individuals interacting virtually within an informal knowledge setting, from which to judge the value of Web‐based discussion groups. However, little is known about how museum‐related forums target their audience and which subjects are of real interest to them. Arising from the statistical results of an international survey of users of online museum forums, the authors have investigated the users’ socio‐demographic profile, their content preference, and favourite Web‐based discussions (e.g. e‐mail lists, newsgroups, forums). The outcome of the collected data should be useful in further binding together the worldwide museum community, as there is great scope for enlivening interactions and empowering individual knowledge in various fields of expertise.

Grounded in destination web reputation, the purpose of this paper is to propose a methodological framework for the analysis of the destination image-building process, where the sentiment analysis (SA) is integrated with social network analysis (SNA) tools and social media analytics (SMA), making them accessible and functional for destination management choices. The outlined framework was successively tested through an empirical analysis carried out on the image and web reputation of Naples as a tourism destination.

Critical analysis of literature on web reputation has allowed the building of the conceptual framework applied to analyse the online reputation of the case study of the city destination of Naples. The empirical research was based on the use of a platform to listen to and analyse social media conversations that allowed one to collect the data on both the destination image and the online reputation of the city.

The paper conceptualises the theme of destination web reputation, proposing an online discourses classification, presenting and ranking destination dimensions, which might influence prospective tourist decision-making processes. Furthermore, this study can also be apt for all destination managers who need to monitor their destination online reputation and brand, and better manage their online presence.

From a theoretical perspective, through the integration of destination management principles with SA, SNA and SMA, this paper provides an original point of view for the analysis. The web reputation analysis of a destination is one of the instruments which – if systematically used – allows us to develop an effective policy to promote a destination in a tourist-centric way, in which the local offer system will be increasingly co-created and thus tailored to customers.

User-generated social media comments can be a useful source of information for understanding online corporate reputation. However, the manual classification of these comments is challenging due to their high volume and unstructured nature. The purpose of this paper is to develop a classification framework and machine learning model to overcome these limitations.

The authors create a multi-dimensional classification framework for the online corporate reputation that includes six main dimensions synthesized from prior literature: quality, reliability, responsibility, successfulness, pleasantness and innovativeness. To evaluate the classification framework’s performance on real data, the authors retrieve 19,991 social media comments about two Finnish banks and use a convolutional neural network (CNN) to classify automatically the comments based on manually annotated training data.

After parameter optimization, the neural network achieves an accuracy between 52.7 and 65.2 percent on real-world data, which is reasonable given the high number of classes. The findings also indicate that prior work has not captured all the facets of online corporate reputation.

For practical purposes, the authors provide a comprehensive classification framework for online corporate reputation, which companies and organizations operating in various domains can use. Moreover, the authors demonstrate that using a limited amount of training data can yield a satisfactory multiclass classifier when using CNN.

This is the first attempt at automatically classifying online corporate reputation using an online-specific classification framework.

This study aims to analyse the level of digitalization in the cultural industry. More in detail, it aims to examine the determinants and effects of the digitalization level of museum organizations and the role played by the COVID-19 pandemic in the adoption of digital technologies.

In order to answer the research questions, this study uses the multiple case study methodology. In particular, three different museum organizations operating in the Apulian context were examined.

The findings show that the adoption of digital technologies derives from the desire to attract more visitors, reduce costs, improve the visitor experience and adapt to competitors. On the contrary, they show that the lack of funding represents a drag on the adoption of digital tools. In relation to the effects, the findings show financial advantages connected to an increase in revenues and a reduction in costs and non-financial benefits connected to an improvement of the intangibles. Finally, the results show that the COVID-19 pandemic has accelerated the adoption of digital technologies.

This work enriches the current literature through the analysis of the drivers and effects of digitalization in the museum industry and through the focus on COVID-19. Furthermore, to the authors’ knowledge, this is the first study that examines the level of digitalization of museum organizations in the Apulian context.