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This study embraces the call for exploring the determinants of continuous intention in TikTok. Taking the perspective of social influence, this study not only tries to explore the contextual sources of two types of social influence but also aims to unveil the influence mechanism of how social influence affects TikTok viewers’ continuous intention.

This study empirically analyzes how TikToker attractiveness, co-viewer participation, platform reputation and content appeal affect informative and normative social influence and then lead to the continuous intention of TikTok. Based on 547 valid survey data, this study adopts a mixed analytical approach for data analysis by integrating structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA).

SEM results unveil that content appeal is the most critical antecedent of informational social influence, while the TikToker attractiveness and platform reputation have no effect on it. Differently, all four external sources positively lead to normative social influence. Among them, content appeal and co-viewer participation influence the most. The influences of both two types of social influence on continuous intention are demonstrated. FsQCA results reveal seven alternative configurations that are sufficient for influencing continuance intention and further complement and reinforce the SEM findings.

Addressing the critical contextual elements of TikTok, this study explores and confirms the sources which may engender social influence. The authors also demonstrate the critical role of social influence in affecting TikTok viewers’ continuous intentions by the hybrid analytical approach, which contributes to existing academic literature and practitioners.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

During the COVID-19 pandemic, public sector organisations produced thousands of social media messages weekly answering citizens questions and informing the public on safety related matters. The purpose of this study was to investigate how the pandemic shaped social media listening in Finland's public sector organisations and how these organisations aligned their listening and strategic communication to address emerging questions, news (real and fake) and rumours during the pandemic.

Building on a theoretical background from strategic communication, organisational listening, digital marketing and public sector communication, qualitative interview data included communicators (N = 14) from all central Finnish public sector organisations in charge of COVID-19 communication. Findings were themed and analysed qualitatively to understand the level of alignment of strategic communication on social media.

The findings revealed that the pandemic had strained public sector organisations' communication capabilities, forcing them to align their processes and resources reactively to enable useful content and limit false/misleading content. The results confirmed that organisational listening remained somewhat unaligned. A dual role of public sector communication as speakers but increasingly as listeners was highlighted.

The study’s findings point to organisational listening on social media being a central requisite for public sector organisations overcoming a crisis.

The purpose of this study is to explore the usefulness of popular reporting (PR) in an Italian city as a dialogic accounting tool for promoting citizens’ engagement with digital platforms. This study aims to contribute to the debate on democratic accounting technologies with a focus on PR and digital platforms, using the theoretical lens of dialogic accounting.

A longitudinal case study is used to analyse the implementation and evolution of PR in the city of Turin, Italy and explore how the city involved its citizens with digital platforms.

This study contributes to the debate on public accountability through dialogic accounting tools.

Multiple sources (surveys, interviews and interventionist workshops) are used to analyse Turin, Italy as a longitudinal case study.

This study offers practical reflections for legislators, politicians and public managers who need new knowledge and empirical analysis of the effective implementation of the PR as a tool for dialogue and empowering public accounting to hold continuous dialogue with the citizens.

PR can be considered a useful dialogic accounting tool for politicians, managers and government experts to encourage citizens’ engagement in a pluralistic society.

This study aims to provide more insight into how customer voice is captured and used in managerial decision-making at the marketing-finance interface. This study’s focus is on understanding how the customer voice, often communicated through online and social media platforms, is used in high-performing hotels.

This research is based on a case study of four high-performing Irish hotels. For each case, multiple informants, including marketing managers, general managers and finance managers, were interviewed and shadowed. Twenty seven decisions across the four cases were analysed to assess the use of customer voice in managerial decision-making.

Social media provides a stage that has empowered the customer voice because of the public nature of the interaction and the network effect. Customer voice is incorporated in managerial decision-making in three distinct ways – symbolically as part of an early warning system, for action-oriented operational decisions and to some extent in the knowledge-enhancing role for tactical decisions. While there is a greater appreciation among senior managers and the finance and accounting managers of the importance of customer voice, this study finds clear limits in its utilisation and more reliance on traditional finance and accounting data, especially in strategic decision-making.

The cases belong to a highly visible open environment of hotels in an industry where customer voice has immediate and strong effects. The findings may not directly apply to industries characterised by a relatively more closed context such as banking or insurance. Moreover, the findings reflect the practices of high-performing hotels and do not necessarily capture the practices used in less successfully operating hotels.

While marketers need to enhance their ability to create a narrative that links the customer voice to revenue generation, finance managers also need to develop a skillset and adopt a mindset that appropriately reflects the influential role for customer voice in managerial decision-making.

Despite the linkage of marketing performance to business performance, there is limited research on the impact of customer information on managerial decision-making. This research provides insight into how customer voice is considered at the critical marketing-finance interface.

The purpose of this research is to explore how an industry is represented in multimodal public media narratives and to explore how this representation subsequently affects the formation of public sense-giving space during a persisting crisis, such as a pandemic. The question asked is: how do the use of multimodality by public service media dynamically shape representations of industry identity during a persisting crisis?

This study made use of a multimodal approach. The verbal and visual media text on the restaurant industry during the COVID-19 pandemic that were published in Finland by the public service media distributor Yle were studied. Data published between March 2020 and March 2022 were analysed. The data consisted of 236 verbal texts, including 263 visuals.

Three narratives were identified– victim, servant and survivor – that construct power relations and depict the identity of the restaurant industry differently. It was argued that multimodal media narratives hold three meaning making functions: sentimentalizing, juxtaposing and nuancing industry characteristics. It was also argued that multimodal public service media narratives have wider implications in possibly shaping the future attractiveness of the industry and organizational members' understanding of their identity.

This research contributes to sensemaking literature in that it explores the role of power – explicitly or implicitly constructed through media narratives during crisis. Furthermore, this research contributes to sensemaking literature in that it shows how narratives take shape multimodally during a continuous crisis, and how this impacts the construction of industry identity.

The purpose of this study is to examine how sports marketing can attract audiences towards less popular sports.

A total of 22 interviews were conducted first to explore the opinions of sports professionals about how audiences can be attracted towards less popular sports. Then 479 responses to an online questionnaire were collected. The online questionnaire includes a pretest-posttest experiment in which each respondent has watched a video. Confirmatory factor analysis, reliability test and hierarchical regression analysis have been performed.

The elements of sports marketing that can help to attract audiences towards less popular sports are sports media, sports advertising, star athlete and sports sponsorship. The performance of national teams moderates the relationship between sports advertising and attraction towards less popular sports.

To the best of the authors’ knowledge, a definition of sustainable sports marketing is introduced for the first time. Sustainable sports marketing can be defined as the continuous implementation of marketing activities in the sports context to ensure the continuous existence of the sports themselves (all types of sports) and the prosperity of future generations. Elements that can attract audiences towards less popular sports have been examined for the first time.

The purpose of this paper is to analyse data literacy in the new Digital Competence Framework for Citizens (DigComp 2.2). Mid-2022 the Joint Research Centre of the European Commission published a new version of the DigComp (EC, 2022). This new version focusses more on the datafication of society and emerging technologies, such as artificial intelligence. This paper analyses how DigComp 2.2 defines data literacy and how the framework looks at this from a societal lens.

This study critically examines DigComp 2.2, using the data literacy competence model developed by the Knowledge Centre for Digital and Media Literacy Flanders-Belgium. The examples of knowledge, skills and attitudes focussing on data literacy (n = 84) are coded and mapped onto the data literacy competence model, which differentiates between using data and understanding data.

Data literacy is well-covered in the framework, but there is a stronger emphasis on understanding data rather than using data, for example, collecting data is only coded once. Thematically, DigComp 2.2 primarily focusses on security and privacy (31 codes), with less attention given to the societal impact of data, such as environmental impact or data fairness.

Given the datafication of society, data literacy has become increasingly important. DigComp is widely used across different disciplines and now integrates data literacy as a required competence for citizens. It is, thus, relevant to analyse its views on data literacy and emerging technologies, as it will have a strong impact on education in Europe.

Innovation dynamics have been the object of study of several researchers, focusing in particular on technological innovation and the emergence of a dominant design. However, these models have been challenged by how the pervasiveness of digital technologies is speeding up the pace at which innovation evolves. On the other hand, a growing body of literature in innovation management has started underlining the relevance of new product and service meanings as a source of innovation.

This research aims to study the different innovation dynamics within an industry, investigating not only how companies react to fast-changing functional advancements but rather how their behavior changes as shifts in meaning occur. To properly assess the phenomenon, this longitudinal study analyzes the social media industry, strongly subjected to continuous functional advancements, through a deep dive in the 160 innovations introduced between 2003 and 2017 by the eight leading players in the industry.

Our results illustrate the co-existence of different approaches to innovation within an industry and hint that consequent and fast cycles of innovation in both functionalities and meanings discourage the emergence of a dominant design.

Our results help managers and innovators acknowledge the possibility to leverage not just on the technological dimension of innovation but also the reason why people use a given product or service, innovating its meaning. Furthermore, our results recognize the co-existence of different innovation streams upon which innovators can act.

This research contributes to the extant literature in innovation management, extending the classical models of innovation dynamics by including the evolution of innovations of meaning in relation to technological innovation.

This study explores the pioneering approach of utilising machine learning (ML) models and integrating social media data for predicting tourist arrivals in Sri Lanka.

Two sets of experiments are performed in this research. First, the predictive accuracy of three ML models, support vector regression (SVR), random forest (RF) and artificial neural network (ANN), is compared against the seasonal autoregressive integrated moving average (SARIMA) model using historical tourist arrivals as features. Subsequently, the impact of incorporating social media data from TripAdvisor and Google Trends as additional features is investigated.

The findings reveal that the ML models generally outperform the SARIMA model, particularly from 2019 to 2021, when several unexpected events occurred in Sri Lanka. When integrating social media data, the RF model performs significantly better during most years, whereas the SVR model does not exhibit significant improvement. Although adding social media data to the ANN model does not yield superior forecasts, it exhibits proficiency in capturing data trends.

The findings offer substantial implications for the industry's growth and resilience, allowing stakeholders to make accurate data-driven decisions to navigate the unpredictable dynamics of Sri Lanka's tourism sector.

This study presents the first exploration of ML models and the integration of social media data for forecasting Sri Lankan tourist arrivals, contributing to the advancement of research in this domain.