Stripping customers' feedback on hotels evaluation through data mining

Com a constante evolução tecnológica e a consequente afluência de partilha de informação entre os consumidores, as plataformas online, como é o caso do TripAdvisor, começaram a ser usadas para análise, principalmente na indústria hoteleira. Estas plataformas permitem aos clientes a partilha de opiniões e a respectiva atribuição de uma avaliação quantitativa aos hotéis visitados. Os estudos publicados têm-se focado, fundamentalmente, na análise dos comentários; contudo, estudos relacionados com a avaliação quantitativa são mais escassos. Este estudo foi desenvolvido através de técnicas de data mining por forma a modelar a pontuação atribuída no TripAdvisor. Foram recolhidos dois comentários por cada mês do ano de 2015 referentes a 21 hotéis localizados na avenida mais emblemática de Las Vegas, a Strip, num total de 504 comentários. A localização foi seleccionada por ser um destino de elevado impato turístico já que a cidade persiste devido à hotelaria e aos casinos. Foram seleccionadas 19 variáveis que representam o utilizador, o hotel e as suas características para alimentarem uma máquina de vectores de suporte objectivando a modelação da avaliação quantitativa para extração de conhecimento. Os resultados atestaram a utilidade do modelo na sua capacidade preditiva. Após esta validação foi aplicada uma análise de sensibilidade ao modelo para compreender a relevância das variáveis. Os resultados revelaram que as variáveis diretamente relacionadas com o utilizador e a sua experiência na utilização do TripAdvisor têm maior influência na atribuição das pontuações, comparativamente com as variáveis relacionadas com o hotel.The emergence of online reviews’ platforms such as TripAdvisor provided tools for tourists to write their opinions and rate hotels with a quantitative score. While numerous studies are found based on textual comments of users, research on the score is rather scarce. This study presents a data mining approach for modeling TripAdvisor score using 504 reviews published in 2015 for the 21 hotels located in the Strip, Las Vegas. Nineteen features characterizing the reviews, hotels and the users were prepared and used for feeding a support vector machine for modeling the score. The results achieved reveal the model is a good approximation for predicting the score. Therefore, a sensitivity analysis was applied over the model for extracting useful knowledge translated into features’ relevance for the score. The findings unveiled user features related to TripAdvisor membership experience play a key role in influencing the scores granted, clearly surpassing hotel features

Developing a business strategy to increase customer loyalty for Q variety stores

Q Variety Stores started as a small $2 shop in 2012, and now it has expanded to eight branches and one franchise all over New Zealand. As the business grows, Q Variety Stores is also facing more increased competition from its peers in the industry. Recent research acknowledged customer loyalty as one of the most significant factors for the success of an organisation, because it can bring many benefits and retain existing customers. Therefore, this research aims to investigate strategies to improve customer loyalty for Q Variety Stores. The author conducted a questionnaire to customers in eight branches to get feedback and provided a specific loyalty programme in the survey for customers’ feedback. A key finding shows that Q Variety Stores already have had some loyal customers, but there is still room for improvement. The questionnaire also revealed that customers’ acceptance of the hypothetical loyalty programme is low, but most of them are fond of some other mature customer loyalty programmes with other suppliers. It is concluded that a loyalty programme that won’t cost customers a lot may work at Q Variety Stores, and it should provide customers with the benefits that actually meet their needs

Stripping customers' feedback on hotels through data mining: the case of Las Vegas Strip

This study presents a data mining approach for modeling TripAdvisor score using 504 reviews published in 2015 for the 21 hotels located in the Strip, Las Vegas. Nineteen quantitative features characterizing the reviews, hotels and the users were prepared and used for feeding a support vector machine for modeling the score. The results achieved reveal the model demonstrated adequate predictive performance. Therefore, a sensitivity analysis was applied over the model for extracting useful knowledge translated into features' relevance for the score. The findings unveiled user features related to TripAdvisor membership experience play a key role in influencing the scores granted, clearly surpassing hotel features. Also, both seasonality and the day of the week were found to influence scores. Such knowledge may be helpful in directing efforts to answer online reviews in alignment with hotel strategies, by profiling the reviews according to the member and review date.info:eu-repo/semantics/submittedVersio

Creating A Better Competitive Edge Through Environmental Sustainability: A Case Study of Panasonic

This paper investigates Panasonic's strategies for its better competitive edge through environmental sustainability. The study analyzed the data collected from the company's websites, customers' personal experiences, and questionnaires. The surveys on customers' feedback on Panasonic products and services were carried out. This study's literature contribution value lies in its investigation of how Panasonic's environmental sustainability has led the company to a competitive advantage. The findings of this paper have significant importance since people today are more concerned about environmental sustainability. Strategies and practices that create a sustainable world economy were discussed

Science 3.0: Corrections to the Science 2.0 paradigm

The concept of Science 2.0 was introduced almost a decade ago to describe the new generation of online-based tools for researchers allowing easier data sharing, collaboration and publishing. Although technically sound, the concept still does not work as expected. Here we provide a systematic line of arguments to modify the concept of Science 2.0, making it more consistent with the spirit and traditions of science and Internet. Our first correction to the Science 2.0 paradigm concerns the open-access publication models charging fees to the authors. As discussed elsewhere, we show that the monopoly of such publishing models increases biases and inequalities in the representation of scientific ideas based on the author's income. Our second correction concerns post-publication comments online, which are all essentially non-anonymous in the current Science 2.0 paradigm. We conclude that scientific post-publication discussions require special anonymization systems. We further analyze the reasons of the failure of the current post-publication peer-review models and suggest what needs to be changed in Science 3.0 to convert Internet into a large journal club.Comment: 7 figure

A New Model for Crowdsourcing Innovation

On paper, crowdsourced innovation makes a lot of sense: If two heads are better than one, why not 20,000? Surely, some of those outsiders will have fresh solutions to your problem. But in practice, such programs have often not worked out as well as hoped. More often than not, even the best crowdsourced ideas disappear in a Bermuda Triangle of logistical difficulties, internal politics, and professional insecurity. The International Committee of the Red Cross has developed a new collaborative approach to crowdsourcing ideas that limits the competition to teams. It designed its Enable Makeathon project not only to generate good ideas of products to help people with disabilities but also to make sure those ideas reach the market

MODELING INFORMATION SYSTEMS FOR EVENT MANAGEMENT

Website that could help event organizer to organize and manage Event wasn’t a new thing. But today most similar portal providing services only for top-level steering committee due to the cost is quite high. This is the background of the author to conduct this research. Using the techniques of data collection, analysis, and several stages of research, it can be concluded that people required the website that could help them not only for organizing the event but also commercializing and helping them reach the customer. This research resulted in the model of event management website that dedicated for event organizers of the event from low to the middle level, where in addition to providing services and sales promotion, the portal also provides services for the evaluation for the event management

Managing engagement behaviors in a network of customers and stakeholders: evidence from the nursing home sector

Firms striving for long-term profitability need to build stronger customer-firm relationships by getting their customers more engaged with the firm. One path to this end is introducing practices to manage different forms of customer engagement behaviors (CEBs). To develop more effective and efficient CEB management practices, this research proposes and empirically tests a theoretical model on managerial and psychological processes to encourage CEBs that are embedded in a broader network of customers and stakeholders. Based on qualitative and quantitative studies in nursing homes, we demonstrate that organizational support and overall service quality toward significant others influence some forms of CEBs—more particularly feedback and positive word of mouth (WOM) behaviors—through customer affect toward the organization. It is interesting to note that customer affect toward the organization encouragesWOMbehaviors, while it discourages feedback behaviors. Conversely, managerial processes that increase customer role readiness—such as organizational socialization and support from other customers—were found to have a positive impact on all forms of CEBs. This research helps managers of nursing homes and other services with a broad network of customers and stakeholders to improve existing CEB management practices and develop new CEB management practices that are beneficial for the firm and its stakeholders

Communication and Procedural Models of the E-commerce Systems

E-commerce systems became a standard interface between sellers (or suppliers) and customers. One of basic condition of an e-commerce system to be efficient is correct definitions and describes of the all internal and external processes. All is targeted the customers´ needs and requirements. The optimal and most exact way how to obtain and find optimal solution of e-commerce system and its processes structure in companies is the modeling and simulation. In this article author shows basic model of communication between customers and sellers in connection with the customer feedback and procedural models of e-commerce systems in terms of e-shops. Procedural model was made with the aid of definition of SOA.E-commerce, decision-making processes, customer requirements, customer feedback, e-commerce processes, CRM, models.

Water Accountability Model under Emergency Cases and for Areas Gained New Access to Water Services

We present a reference accountability model for water utilities that consists of five major components, namely organization, systems, data, communication, and quality management. The model has been discussed with water officials, experts, and stakeholders in order to build and customize the model for each utility through a pre-prepared questionnaire and focused groups. Results have shown that water utilities have different accountability systems with several drawbacks. There was a need for actions taken to secure regular customers’ data updates as well as activate e-services in order to access vital information during emergencies. It was therefore our strong recommendation to the water utilities to move forward with some measures to support and sustain their bi-directional communication with customers. Further recommendations encouraging water utilities to enhance the accountability mechanism such as the deployment of e- services complaints management and tracking, expanding the Enterprise Resources Planning system, improving staff communication skills, training staff on the procedures used in analyzing customers’ feedback, and moving to performance- based management system