The most valued social media attributes of Portuguese consumers

The exponential growth of the entertainment and media industry has revolutionized the social media landscape. Increasingly more people use social media platforms in their daily lives for different reasons. The goal of this research is, in particular, to determine what are the attributes of Facebook Instagram and Tik Tok they value the most, as well as having an overview on how Portuguese consumers perceive such platformsandwhat influences its engagement. To reach such goals,reasons why people use social media were identified,aperceptual map with two dimensions was plotted, and a conjoint analysis was performed. On the associations found to be linked with social media, all three social media platforms do not need to readjust their positioning strategy to occupy a specific position in the market, but there is still room for attributes improvement, to engage with potential Portuguese valuable consumers, considering the different needs, preferences, and behaviors. The most important feature and counterpart for the usage of social media is linked with privacy concerns

What influences the engagement on Facebook, Instagram and Tiktok

The exponential growth of the entertainment and media industry has revolutionized the social media landscape. Increasingly more people use social media platforms in their daily lives for different reasons. The goal of this research is what influences its engagement, closer insight on the reasons why people use social media, perceptual map’s associations with two dimensions, and on a conjoint analysis’s preferences. Althoughall three social media platforms do not need to readjust their positioning strategy to occupy a specific position in the market, there is still room for attributes improvement, to engage with potential Portuguese valuable consumers, considering the different needs, preferences, and behaviors. The most important feature and counterpart for the usage of social media is linked with privacy concerns

Can Upward Brand Extensions be an Opportunity for Marketing Managers During the Covid-19 Pandemic and Beyond?

Early COVID-19 research has guided current managerial practice by introducing more products across different product categories as consumers tried to avoid perceived health risks from food shortages, i.e. horizontal brand extensions. For example, Leon, a fast-food restaurant in the UK, introduced a new range of ready meal products. However, when the food supply stabilised, availability may no longer be a concern for consumers. Instead, job losses could be a driver of higher perceived financial risks. Meanwhile, it remains unknown whether the perceived health or financial risks play a more significant role on consumers’ consumptions. Our preliminary survey shows perceived health risks outperform perceived financial risks to positively influence purchase intention during COVID-19. We suggest such a result indicates an opportunity for marketers to consider introducing premium priced products, i.e. upward brand extensions. The risk-as�feelings and signalling theories were used to explain consumer choice under risk may adopt affective heuristic processing, using minimal cognitive efforts to evaluate products. Based on this, consumers are likely to be affected by the salient high-quality and reliable product cue of upward extension signalled by its premium price level, which may attract consumers to purchase when they have high perceived health risks associated with COVID-19. Addressing this, a series of experimental studies confirm that upward brand extensions (versus normal new product introductions) can positively moderate the positive effect between perceived health risks associated with COVID-19 and purchase intention. Such an effect can be mediated by affective heuristic information processing. The results contribute to emergent COVID-19 literature and managerial practice during the pandemic but could also inform post-pandemic thinking around vertical brand extensions

Human behaviour and ecosystem services in sustainable farming landscapes : an agent-based model of socio-ecological systems

Agricultural areas represent around 40% of the earth surface and provide a variety of products and services essential to human societies. However, with policy reforms, market liberalisation and climate change issues, continuous land use and cover change (LUCC) brings uncertainty in the quantity and quality of ecosystem services supplied for the future generations. The processes of LUCC have been explored using top-down approaches at global and regional level but more recent methods have focused on agents’ interactions at smaller scale. This approach is better suited to understanding and modelling complex socio-ecological systems, which emerge from individual actions, and therefore for developing tools which improve policy effectiveness. In recent years, there has also been increasing interest in gaining more detailed understanding of the impacts of LUCC on the range of ecosystem services associated with different landscapes and farming practices. The objectives of this thesis are: 1/ to understand and model the internal processes of LUCC at local scale, i.e. farmer behaviour, 2/ to explore heterogeneous farmer decision making and the impacts it has on LUCC and on ecosystem services and 3/ to inform policy makers for improving the effectiveness of land-related policies. This thesis presents an agent-based modelling framework which integrates psycho-social models of heterogeneous farmer decisions and an ecological model of skylark breeding population. The model is applied to the Lunan, a small Scottish arable catchment, and is empirically-grounded using social surveys, i.e. phone interviews and choice-based conjoint experiments. Based on ecological attitudes and farming goals, three main types of farmer agents were generated: profit-oriented, multifunctionalist, traditionalist. The proportion of farmer types found within the survey was used to scale-up respondent results to the agent population, spatially distributed within a GIS-based representation of the catchment. Under three socio-economic scenarios, based on the IPCC-SRES framework, the three types of farmers maximise an utility function, which is disaggregated into economic, environmental and social preferences, and apply the farm strategy (i.e. land uses, management style, agri-environmental measures) that best satisfies them. Each type of agents demonstrates different reactions to market and policy pressures though farmers seem to be constrained by lack of financial opportunities and are therefore unable to fully comply with environmental and social goals. At the landscape level, the impacts on ecosystem services, in particular the skylark local population, depend strongly on policy objectives, which can be antagonist and create trade-offs in the provision of different services, and on farmer socio-environmental values. A set of policy recommendations is offered that encompasses the heterogeneity of farmer decision-making with the aim of meeting sustainable targets. Finally, further improvements of the conceptual and methodological framework are discussed

Understanding the destination choice: a study of the Chinese long-haul outbound tourists

Among tourism decision making studies, choice heuristics are barely explored. Choice heuristics are a set of rules decision makers use to process information about their choice criteria. The types of rules applied in the process can make a substantial difference to eventual outcomes, which for tourists includes not only the final choice of the tour package but also the choice process (Sen, 1997). Therefore, in order to better understand tourists' decision making behaviour, choice heuristics deserve greater attention. However, whilst compensatory choice heuristics are commonly applied in consumer focused tourism research, and conjoint analysis is often used for modelling compensatory heuristics, mirroring the predominant approach in consumer research, less attention has been afforded to non-compensatory heuristics. Recently, a greedoid method was introduced by Kohli and Jedidi (2007) and Yee et al. (2007) independently to that contributed to methodology for estimating non-compensatory heuristics. The aim of this study was to provide a greater understanding of consumer decision-making processes, based on the exploration of different choice heuristics used by the Chinese long-haul outbound tourists. This thesis makes theoretical contribution by providing insights on (1) how the concept of choice heuristics can be used to better understand the process of decision making and (2) how choice heuristics are used for the selection of complicated intangible services, tourism destinations in this case. The study also sheds light on the possible measurements for evaluating the fit of different choice heuristic models. In addition, the information found regarding the destination preference of Chinese long-haul outbound tourist is of great use for marketers and suppliers to improve their destination products as well as their advertisement campaigns

Understanding the destination choice: a study of the Chinese long-haul outbound tourists

Among tourism decision making studies, choice heuristics are barely explored. Choice heuristics are a set of rules decision makers use to process information about their choice criteria. The types of rules applied in the process can make a substantial difference to eventual outcomes, which for tourists includes not only the final choice of the tour package but also the choice process (Sen, 1997). Therefore, in order to better understand tourists' decision making behaviour, choice heuristics deserve greater attention. However, whilst compensatory choice heuristics are commonly applied in consumer focused tourism research, and conjoint analysis is often used for modelling compensatory heuristics, mirroring the predominant approach in consumer research, less attention has been afforded to non-compensatory heuristics. Recently, a greedoid method was introduced by Kohli and Jedidi (2007) and Yee et al. (2007) independently to that contributed to methodology for estimating non-compensatory heuristics. The aim of this study was to provide a greater understanding of consumer decision-making processes, based on the exploration of different choice heuristics used by the Chinese long-haul outbound tourists. This thesis makes theoretical contribution by providing insights on (1) how the concept of choice heuristics can be used to better understand the process of decision making and (2) how choice heuristics are used for the selection of complicated intangible services, tourism destinations in this case. The study also sheds light on the possible measurements for evaluating the fit of different choice heuristic models. In addition, the information found regarding the destination preference of Chinese long-haul outbound tourist is of great use for marketers and suppliers to improve their destination products as well as their advertisement campaigns

The Users' Perspective on Autonomous Driving: A Comparative Analysis of Partworth Utilities

Digitisation has brought a major upheaval to the mobility sector, and in the future, self-driving cars will probably be one of the transport modes. This study extends transport and user acceptance research by analysing in greater depth how the new modes of autonomous private cars, autonomous carsharing and autonomous taxis fit into the existing traffic mix from today's perspective. It focuses on accounting for relative added value. For this purpose, user preference theory was used as a base for an online survey (n=172) on the relative added value of the new autonomous traffic modes. Results show that users see advantages in the autonomous modes for driving comfort and time utilization whereas, in comparison to conventional cars, in many other areas – especially in terms of driving pleasure and control – they see no advantages or even relative disadvantages. Compared to public transport, the autonomous modes offer added values in almost all characteristics. This analysis at the partwor th level provides a more detailed explanation for user acceptance of automated driving