SENTIMENTALNA ANALIZA SADRŽAJA DRUŠTVENIH MEDIJA HRVATSKE HOTELSKE INDUSTRIJE

While social media have become a daily routine in modern society, brand communication and engagement with customers have become essential elements of marketing strategy and success in the tourism and hotel industry. This revolution of social media, in tourism and hospitality marketing, contributed to the rise of a novel sentiment analysis from a machine learning and natural language processing point of view. The purpose of the study is: to provide a general descriptive overview of comments posted by Facebook page followers; to identify specific textual attributes of hotel brand posts on social media and to apply the sentiment analysis to Facebook comments from four- and five-star hotel brands in Croatia to identify and compare customers\u27 feelings and attitudes towards the staff, services and products that hotel brands promote by posting messages on Facebook pages. To analyse hotel brand sentiments, the authors collected a total of 4,248 comments and 2,373 postings in English, German and Italian. The results showed that the comments on four- and five-star hotel brands expressed predominantly positive sentiments. Despite the positively oriented sentiments in the comments, Facebook page followers are predominantly passive users and do not tend to comment actively. The results can be used by marketers in the tourism and hospitality industry to plan their future social media communication strategies.Iako su društveni mediji postali svakodnevica u modernom društvu, brend komuniciranje i uključenost potrošača postali su ključni elementi marketinške strategije i uspjeha u sektoru turizma i ugostiteljstva. Revolucija društvenih medija, u marketingu, turizmu i ugostiteljstvu, pridonijela je razvoju sentimentalne analize sa stajališta strojnog učenja i obrade prirodnog jezika. Svrha ovog rada je: pružiti opći deskriptivni pregled komentara objavljenih od strane pratitelja Facebook stranice; identificirati specifične tekstualne karatkeristike objava hotelskih brendova na Facebook društvenoj mreži i primijeniti sentimentalnu analizu nad Facebook komentarima hotelskih brendova s četiri i pet zvjezdica u Hrvatskoj kako bi se identificirali i usporedili osjećaji, mišljenja i stavovi kupaca prema osoblju, uslugama i proizvodima koje hotelski brendovi promoviraju objavljivanjem poruka na Facebook stranicama. Da bi se analizirali sentimenti komentara pratitelja hotelskih brendova na Facebook društvenoj mreži, autori su prikupili ukupno 4.248 komentara i 2.373 objave na engleskom, njemačkom i talijanskom jeziku. Rezultati su pokazali da su komentari na stranicama hotelskih brendova imali pretežno pozitivan sentiment. Unatoč pozitivno orijentiranim osjećajima u komentarima, pratitelji Facebook stranica su uglavnom pasivni korisnici i ne sudjeluju aktivno u komentiraju objava. Rezultati mogu koristiti marketinškim stručnjacima u turizmu i ugostiteljstvu za planiranje budućih strategija komunikacije putem društvenih media

Harnessing big data to inform tourism destination management organizations

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceIn the last few years, Portugal has been witnessing a rapid growth of tourism, which reflects positively in many aspects, especially in what regards economic factors. Although, it also leads to a number of challenges, all of them difficult to quantify: tourist congestions, loss of city identity, degradation of patrimony, etc. It is important to ensure that the required foundations and tools to understand and efficiently manage tourism flows exist, both in the city-level and country-level. This thesis studies the potential of Big data to inform destination management organizations. To do so, three sources of Big data are discussed: Telecom, Social media and Airbnb data. This is done through the demonstration and analysis of a set of visualizations and tools, as well as a discussion of applications and recommendations for challenges that have been identified in the market. The study begins with a background information section, where both global and local trends in tourism will be analyzed, as well as the factors that affect tourism and consequences of the latter. As a way to analyze the growth of tourism in Portugal and provide prototypes of important tools for the development of data driven tourism policy making, Airbnb and telecom data are analyzed using a network science approach to visualize country-wide tourist circulation and presents a model to retrieve and analyze social media. In order to compare the results from the Airbnb analysis, data regarding the Portuguese hotel industry is used as control data

Sentiment analysis in online customer reviews: the Feels Like Home case

Portugal has been, for many years, an attractive destination for tourists from all over the world. This continuous flow of people opens opportunities for companies to explore and for some new other companies to emerge. All the data generated from the interaction of these companies with tourists can be submitted to data mining techniques to extract useful information and, therefore, create knowledge.Thiscasestudy uses those data mining techniques to try to explain the polarity of sentiments found in the online reviews of the properties that Feels Like Home, a local accommodation rental platform, manages. Out of the Feels Like Home’s portfolio, information regarding negative and positive mentions for each house (monthly) was retrieved from ReviewPro’s API, allowing for the final data set to have 1131 entries containing important information to be targeted bydata mining.Through the usage of descriptive analysis and predictive models (CART decision trees), the relationship between the properties and reservations’ characteristics and the sentiment polarity found in the reviews is described, as well as the main factors that can help predict those sentiments are revealed. Additionally, the relationship between the monthly occupancy rates and the sentiments’ polarity is also described.This way, this study generates useful knowledge for Feels Like Home and possibly for the rest of the industry to use and adapt to their business needsPortugal tem sido, por muitos anos, um destino atraente para turistas vindos de todo o mundo. Este fluxo contínuo de pessoas abre oportunidades para empresas explorarem e para novas empresas surgirem. Toda a informação gerada a partir das interações entre estas empresas com turistas pode ser submetida a técnicas de data mining para poder extrair informação útil e, assim, gerar conhecimento.Este estudo de caso usa essas técnicas de data mining para tentar explicar a polaridade de sentimentos encontrada nos comentários online das propriedades que a Feels Like Home, uma plataforma de aluguer de alojamento local, gere. De todo o portfólio daFeels Like Home, informação acerca de menções negativas e positivas para cada casa (mensalmente) foi retirada da API daReviewPro, permitindo que a amostra final tivesse 1131 entradas contendo informação importante para ser alvo de data mining.Através do uso de análise descritiva e de modelos preditivos (árvores de decisão CART), a relação entre as características das propriedades e reservas e a polaridade dos sentimentos encontrada nos comentários é descrita, assim como os principais fatores que podem ajudar a prever esses sentimentos são revelados. Adicionalmente, a relação entre as taxas de ocupação mensais e a polaridade dos sentimentos é também descrita.Desta forma, este estudo gera conhecimento útil para a Feels Like Home e possivelmente para o resto da indústria poderem usar e adaptar às suas necessidades de negócio

How crowdsourcing impacts prices and customer satisfaction: the Airbnb case

The travel accommodation industry has changed drastically due to the sharing economy. This sharing economy depends significantly on crowdsourcing in the form of quantitative and qualitative reviews. In this thesis, we study the impact of expressed sentiments in the text reviews on listing prices; we explore differences in the factors that lead to satisfaction according to customer origin and the effects of external shocks on Airbnb´s prices. We employ NLP to extract the sentiment and emotion scores to be modeled as a function of different characteristics and geophysical information. Our study provides an important contribute to the research on pricing and customer satisfaction in the sharing economy by finding a significant effect of the expression of positive sentiments on prices, describing the differences in the factors that lead to satisfaction according to customer origin, and revealing that guests moved away from main municipalities and valued listings with more bedrooms during the Covid-19 pandemic

Research in multi-cultural relationship building

This study aims to explore the ‘missing gap' between the values of an Accounting firm and the preference shown by Maaori on how they would like to be approached when wanting to build a trusted relationship within a business sense. This study makes use of qualitative approaches in which data is collected primarily through interviews and analysed to produce results and recommendations. The study found that Maaori would like to be approached in a way that makes sense to them and also identifies with their cultural proceedings. It also provides insight into how important trust is when establishing a relationship with Maaori. The study recommends that further studies conducted should interview a wider variety of focus groups to add different elements to this research and that FIRM A's small business department's offerings do not align with what Maaori want so need to be rethought to adapt to Maaor expectations

Expanding the education role to narrow the audit expectation gap: exploring the expectation gap’s existence among accounting students

Society perceives and expects more from auditor’s than what auditors can actually achieve. Society has been found to misperceive the role of an auditor, in particular, in regards to fraud, internal controls and going concern issues. Society’s differing perceptions and expectations of the auditing profession is known as the audit expectation gap. This study aims to explore the audit expectation gap’s existence among Wintec accounting students and the effect that education has on the audit expectation gap. This research intends to answer two research questions. First, does an audit expectation gap exist among Wintec accounting students? Second, what is the effect of education on the audit expectation gap? To answer these research questions, 20 Wintec accounting students have been interviewed. Ten students who have received an audit education, and ten students who have not received audit education. Qualitative data was collected from these interviews and analysed using a mixed methods approach. This study found that an audit education exists among Wintec accounting students. This study also found that education reduced the audit expectation gap, in particular, the deficient performance gap and the communication gap. However, while education did reduce the audit expectations gap, it was not eliminated. This study recommends that Wintec provides a more basic auditing education during introductory accounting papers, educating students on the role of an auditor. This study also recommends that education focuses on the practical use of an audit report, to increase student’s understandings of the information in the audit report, and how this information is communicated. Thus, the researcher believes that these recommendations will help to further reduce the audit expectation

Analysis and optimization of distribution logistics for Just Water Company

This report details the various factors that affect the operational efficiency of distribution logistics. The research aimed at studying the existing components involved in the distribution logistics of Just Water. Distribution logistics begins at the end of the production line where the finished product is emerged until it reaches the customers. The literature review explains the key components of distribution logistics in an organisation. This research analyses the existing components of the distribution logistics of Just Water and discusses possible improvements that can be adapted to increase the overall efficiency of the distribution logistics operation. The background of the research is that Just Water faces difficulty with delivering its products on time during peak seasons. The research tries to unveil the reason for this delay and finds that the demands for extra water-out deliveries are interfering with the normal runs of the trucks, therein delaying their regular schedule. One another cause was found to be the shortage of supplies due to slow or less return logistics. The research suggests a change in the existing drop shipping distribution model and recommends the adaptation of intermediary or multi-stage distribution networks, possibly the ‘Last Mile Delivery’ configuration in order to reduce delivery lead-time, reduce transportation costs and improve customer satisfaction

Co-creating a smart tourism local service system in rural areas: a case study from south

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementThe most recent trends show an increase in the urbanization of cities, and, consequently, inner territories become more depopulated, business activities get closed, services get reduced and the overall services become poor and not able to offer quality offers to visitors (Bolay, 2020). According to (United Nations, 2019), by 2050 more than three out of four people will be living in urban areas. Nowadays, many studies have addressed the evolution and features of Smart Cities (Van Dijk & Teuben, 2015) and tourism is also one of those spheres that got digitally transformed by Smart Cities (Khan, Woo, Nam, & Chathoth, 2017). One of the features of smart applications is the possibility to let the user be a driver of value in creating and sharing contents (Kontogianni & Alepis, 2020). However, the explosion of smart solutions enabled by the latest technological innovations has been mostly contextualized in urban environments while fewer solutions have been developed in less urbanized rural areas (Steyn & Johanson, 2010). The methodology used employs the merging of two of the core contemporary service research approaches: Service Science and Service-Dominant logic; the first offers an organizational framework to generate and integrate value co-creation in terms of a smart service systems (Polese, Botti, Grimaldi, Monta & Vesci, 2018). For the same purpose, but differently, the second proposes a different layout called service ecosystems (Vargo & Lusch, 2016). This combination of approaches overcomes individual model limitations by setting an integrated model that can be employed to hypercompetitive and experience-based sectors (Polese, Botti, Grimaldi, Monta & Vesci, 2018), and that was adopted by using a case study methodology, relying on semi-structured interviews