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This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.

The adoption of social media has been extensively discussed. However, to explain the adoption of traditional social media, considering the benefits and risks accumulated from the experiences of social media use, the extent literature is limited. Thus, this paper investigated the act of traditional social media users’ switching behavior from a dynamic perspective and the level of information privacy concerns and social media privacy to measure the risks and benefit accumulated from this dynamic process.

This study of Facebook and Twitter users, who are regarded as representative of traditional social media, are selected as research targets surveyed and were required to answer a specially designed questionnaire in order to determine their general feeling on social media platforms they currently use. As a part of this process, quota sampling was used to collect different samples based on gender and age. In this paper, t-test, one-way ANOVA and multiple comparisons were used for the statistical analysis, conducted through SPSS.

Information privacy concerns and social media dependency affect the adoption of social media. Secondly, social media dependency is a more salient determinant for social media adoption. Therefore, social media firms should pay more attention to enhancing user dependency of social media by increasing user involvement of social media.

This study intends to conduct a research design that provides an overall and holistic understanding of user usage experience. To do this, it investigates the intensity of switching behavior through the level of dependency and the level of information privacy concern that users inevitably exhibit through the use of social media over long time.

This paper analyses how the purchase channel and customer complaint goals affect the sequential choice of post–purchase complaint channels when customers experience a service failure followed by a service recovery failure (double deviation).

An online survey involving a scenario manipulation was conducted with 577 apparel shoppers. The study employs multi-group latent class analysis to estimate latent customer segments within both online and offline groups of shoppers and compare latent classes between the two groups.

The results show that the purchase channel has a lock-in effect on the complaint channel, which is stronger for offline buyers. Moreover, there is evidence of channel synergy effects in the case of having to complain twice: shoppers who complain in store in the first attempt turn to online channels in the second complaint attempt, and vice versa. Complaint goals shape the choice of complaint channels and define different shopper segments.

The present study is the first to adopt a cross-stage approach that analyses the dependencies between the purchase channel and the complaint channel used on two subsequent occasions: the first complaint after a service failure and the second following a service recovery failure.

The chapter discusses the characteristics of audiovisual (AV) media sectors in the Baltic Sea region. Therein it focuses on the specifics of media industries in small countries in the region as they are challenged in ways notably different from large countries with large domestic markets for media content. It discusses the differences between the AV media industries in the Nordic and Baltic countries and suggests that while in the first case long-term welfare society policies and conscious policy-driven system building have conditioned growth and international success then also in the second case innovation policy rationales have facilitated recent growth and dynamics. It then discusses the specific challenges, especially platformisation to small media industries in contemporary globalising media markets, and suggests that opportunities to resist these challenges may be in local inter-sectoral cooperation, that is, in building cross-innovation systems.

In times of converging and diversifying audiovisual (AV) industries, digitising health sector and the increasing phenomenon of cross-sectoral innovation, the question arises about the state of affairs between the health and AV sectors. The chapter aims to explore what the main modes of cross-sectoral cooperation between the health and AV sectors are and what supports and hinders the emergence of a related cross-innovation system. The chapter introduces two case studies carried out in Estonia and the wider Aarhus region (Midtjylland) in Denmark. At each site representatives of the main stakeholders of both sectors were interviewed – policy makers, entrepreneurs, educators and professionals. The results demonstrate the crucial role of path-dependencies – in terms of both hindering and enabling cross-sectoral dialogues – and also the importance of effective coordination in supporting cross-innovation.

The purpose of this paper is to develop Delphi methodology toward a holistic method for forecasting market change. Delphi methodology experienced its culmination in marketing research during the 1970s–1980s, but still has much to offer to both marketing scholars and practitioners in contexts where future market changes are associated with ambiguity and uncertainty.

This study revives the Delphi methodology by exemplifying how a recently developed framework on market change can be combined with the Delphi technique for data collection to support forecasting activities and research. The authors demonstrate the benefits of the improved methodology in an empirical study on the impact of the fifth generation of wireless communications technologies (5G) on the Finnish media market.

The developed methodological approach aids marketing scholars in categorizing and analyzing the data collected for capturing market change; and better guiding experts/respondents to provide holistic projections of future market change. The authors show that using a predefined theoretical framework in combination with the Delphi method for data collection and analysis is beneficial for studying future market change.

This paper develops Delphi methodology and contributes with a novel methodological approach to assessing market change.

Like other European countries, Germany is facing regional physician shortages, which have several consequences on patient care. This study analyzes how hospitals perceive physician shortages and which strategies they adopt to address them. As a theoretical framework, the resource dependency theory is chosen.

The authors conducted 20 semi-structured expert interviews with human resource officers, human resource directors, and executive directors from hospitals in the northwest of Germany. Hospitals of different ownership types, of varying sizes and from rural and urban locations were included in the sample. The interviews were analyzed by using qualitative content analysis.

The interviewees reported that human resource departments in hospitals expand their recruiting activities and no longer rely on one single recruiting instrument. In addition, they try to adapt their retaining measures to physicians' needs and offer a broad range of employment benefits (e.g. childcare) to increase attractiveness. The study also reveals that interviewees from small and rural hospitals report more difficulties with attracting new staff and therefore focus on recruiting physicians from abroad.

Since the staffing situation in German hospitals will not change in the short term, the study provides suggestions for hospital managers and health policy decision-makers in dealing with physician shortages.

This study uses the resource dependency theory to explain hospitals' strategies for dealing with healthcare staff shortages for the first time.

Limited facilities operating and modernization budgets require organizations to carefully identify, prioritize and authorize projects to ensure allocated resources align with strategic objectives. Traditional facility prioritization methods using risk matrices can be improved to increase granularity in categorization and avoid mathematical error or human cognitive biases. These limitations restrict the utility of prioritizations and if erroneously used to select projects for funding, they can lead to wasted resources. This paper aims to propose a novel facility prioritization methodology that corrects these assessment design and implementation issues.

A Mamdani fuzzy logic inference system is coupled with a traditional, categorical risk assessment framework to understand a facilities’ consequence of failure and its effect on an organization’s strategic objectives. Model performance is evaluated using the US Air Force’s facility portfolio, which has been previously assessed, treating facility replicability and interruptability as minimization objectives. The fuzzy logic inference system is built to account for these objectives, but as proof of ease-of-adaptation, facility dependency is added as an additional risk assessment criterion.

Results of the fuzzy logic-based approach show a high degree of consistency with the traditional approach, though the value of the information provided by the framework developed here is considerably higher, as it creates a continuous set of facility prioritizations that are unbiased. The fuzzy logic framework is likely suitable for implementation by diverse, spatially distributed organizations in which decision-makers seek to balance risk assessment complexity with an output value.

This paper fills the identified need for portfolio management strategies that focus on prioritizing projects by risk to organizational operations or objectives.

Football exists and evolves in a dynamic ecosystem, displaying a massive and multidimensional influence on most contemporary societies, and football has grown into a significant industry with a plethora of stakeholders. This research is the first to comprehensively identify the key industry stakeholders and their distinct value, from the individual club perspective, and to conceptualise and test their interrelationship toward the development of a corresponding framework of club benefits.

The study applied a multilevel approach to collect and verify qualitative data. It initially developed a preliminary conceptual framework, which was first validated by an expert panel and was subsequently extensively tested in the Cyprus-specific context, which offered fertile ground for such a study. The empirical stage rested on 41 semi-structured, face-to-face interviews with very high-ranking individuals from the top nine football clubs, as well as with key industry stakeholders.

Though the examined industry is partly in line with international norms, it is also highly affected by unique characteristics that alter the various stakeholders' role, producing (even negative) value of varied typologies that is directly linked with the industry's financial, sporting, cultural and social conditions.

The research ultimately presents scholars, practitioners and policymakers with a systemic and comprehensive understanding of the individual club stakeholder value offerings, delivers a tested framework as a tool for social and business management and prescribes future avenues for research, governance and practice.

Extant studies on the subject are either partial or focus on individual stakeholders and evidently lack requisite scientific comprehensiveness. The current research bridges this significant gap in knowledge by exhaustively identifying the key industry stakeholders, explicating their relative social, economic or other value in the individual club perspective and developing a value-based stakeholder framework.