O impacto da inteligência artificial no negócio eletrónico

Pela importância que a Inteligência Artificial exibe na atualidade, revela-se de grande interesse verificar até que ponto ela está a transformar o Negócio Eletrónico. Para esse efeito, delineou-se uma revisão sistemática com o objetivo de avaliar os impactos da proliferação destes instrumentos. A investigação empreendida pretendeu identificar artigos científicos que, através de pesquisas realizadas a Fontes de Dados Eletrónicas, pudessem responder às questões de investigação implementadas: a) que tipo de soluções, baseadas na Inteligência Artificial (IA), têm sido usadas para melhorar o Negócio Eletrónico (NE); b) em que domínios do NE a IA foi aplicada; c) qual a taxa de sucesso ou fracasso do projeto. Simultaneamente, tiveram de respeitar critérios de seleção, nomeadamente, estar escritos em inglês, encontrarem-se no intervalo temporal 2015/2021 e tratar-se de estudos empíricos, suportados em dados reais. Após uma avaliação de qualidade final, procedeu-se à extração dos dados pertinentes para a investigação, para formulários criados em MS Excel. Estes dados estiveram na base da análise quantitativa e qualitativa que evidenciaram as descobertas feitas e sobre os quais se procedeu, posteriormente, à sua discussão. A dissertação termina com as conclusão e discussão de trabalhos futuros.Due to the importance that Artificial Intelligence exhibits today, it is of great interest to see to what extent it is transforming the Electronic Business. To this end, a systematic review was designed to evaluate the impacts of the proliferation of these instruments. The research aimed to identify scientific articles that, through research carried out on Electronic Data Sources, could answer the research questions implemented: a) what kind of solutions, based on Artificial Intelligence, have been used to improve the Electronic Business; b) in which areas of the Electronic Business Artificial Intelligence has been applied; c) what the success rate or failure of the project is. At the same time, they must comply with selection criteria, to be written in English, to be found in the 2015/2021-time interval and to be empirical studies supported by actual data. After a final quality evaluation, the relevant data for the investigation were extracted for forms created in MS Excel. These data were the basis of the quantitative and qualitative analysis that evidenced the findings found and on which they were subsequently discussed. The dissertation ends with the conclusion and discussion of future works

Electronic word of mouth in online social networks: strategies for coping with opportunities and challenges

In today's world, the widespread success of the Internet, social media, and online social networks (OSN) provide the basis for electronic word of mouth (EWOM). EWOM can be seen as a digital enhancement of traditional word of mouth that makes communication more efficient and involves less effort by its users. The resulting speed of diffusion and information transparency have caused transformative changes in consumer behaviour in all types of markets, which requires the development of new business strategies for adequately dealing with the new circumstances. This doctoral dissertation is divided into three overall subject areas that concern the investigation of capable strategies for coping with the emerged opportunities and challenges of EWOM in OSN. The first subject area concerns negative electronic word of mouth in OSN and investigates capable countermeasure strategies for firms to adequately address claims of unsatisfied customers. For this, three simulation studies are conducted in which the propagation of a negative message and its countering by a positive message published by the firm are numerically analysed. The results reveal that, in general, the persuasiveness of a firm's response is more important than a quick response with a less persuasive counter-message. To some extent, this also holds if the number of OSN members who initially disseminate the counter-message on behalf of the firm is increased. In the second subject area, an optimisation model for individualised pricing is developed for an online store whose customers are interconnected in an OSN and can share price information via EWOM. The model is solved numerically by artificial intelligence solution methods. The results indicate that personalised prices can be financially worthwhile even under price transparency. The third subject area investigates market entry strategies for social media apps and services that are advertised in an OSN for acquiring new users and examines the role of EWOM in this context. A diffusion model is developed and analysed numerically by simulation. Three different targeting approaches are compared to each other regarding their ability to reach a high share of active users in the OSN: (1) a random marketing strategy, where randomly chosen members in the OSN are presented the advertisement, (2) cluster marketing, where whole clusters of members who are densely connected to each other are simultaneously shown the advertisement, and (3) influencer marketing, where the most influential users in the OSN are selected to share sponsored posts about the app in the OSN. The results suggest that EWOM can have detrimental effects if OSN members are too early informed about the app or service. If the information about the app reaches clusters in the OSN prematurely where a sufficient level of activity is not present yet, it can deplete the excitement of the users. The lack of excitement, in turn, can significantly reduce the effect of subsequent marketing campaigns. However, if applied appropriately, a higher level of EWOM about the app or service can increase the performance of the random marketing strategy to the extent that it outperforms cluster and influencer marketing