The influence of national culture on the attitude towards mobile recommender systems

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This study aimed to identify factors that influence user attitudes towards mobile recommender systems and to examine how these factors interact with cultural values to affect attitudes towards this technology. Based on the theory of reasoned action, belief factors for mobile recommender systems are identified in three dimensions: functional, contextual, and social. Hypotheses explaining different impacts of cultural values on the factors affecting attitudes were also proposed. The research model was tested based on data collected in China, South Korea, and the United Kingdom. Findings indicate that functional and social factors have significant impacts on user attitudes towards mobile recommender systems. The relationships between belief factors and attitudes are moderated by two cultural values: collectivism and uncertainty avoidance. The theoretical and practical implications of applying theory of reasoned action and innovation diffusion theory to explain the adoption of new technologies in societies with different cultures are also discussed.National Research Foundation of Korea Grant funded by the Korean governmen

INDIVIDUALITY OR CONFORMITY: RECOMMENDATION EXPLOITING COMMUNITY-LEVEL SOCIAL INFLUENCE

With the increasing prevalence of online businesses and social networking services, a huge volume of data about transaction records and social connections between users is accumulated at an unprecedented speed, which enables us to take advantage of electronic word-of-mouth effect embedded in social networks for precision marketing and social recommendations. Different from existing works on social recommendations, our research focuses on discriminating the community-level social influence of different friend groups to enhance the quality of recommendation. To this end, we propose a novel probabilistic topic model integrating community detection with topic discovery to model user behaviors. Based on this model, a recommendation method taking both individual interests and conformity influence into consideration is developed. To evaluate the performance of the proposed model and method, experiments are conducted on two real recommendation applications, and the results demonstrate that the proposed recommendation method exhibits superior performance compared with the state-of-art recommendation methods, and the proposed topic model exhibits good explainablibity of topic semantics and community interests. Furthermore, as some people are more individual interest oriented and some are more conformity oriented demonstrated by the experiments, we explore factors that influence each individual’s conformity tendency, and obtain some meaningful findings

The adoption intention of travel-related app: a framework integrating perceived characteristics of innovation and software quality

This thesis aims to analyze the views of customers who have great appetite for tourism on the tourism application. According to the perception characteristics of technology acceptance model, innovation diffusion theory and software quality model, the thesis sets up the research model and puts forward the corresponding research hypothesis on the combination of current research results. In the manner of questionnaire design and collection and data processing, data analysis and hypothesis verification will be conducted by the use of structural equation model. The research result implies that application design attributes and application performance features are key to promote the adoption of mobile travel application. In addition, this research broadens our horizons on the accidental impact of application attributes on adoption behavior through adding user gender as a variable to the model, and increases an awesome theoretical basis for future research in this field.Esta tese tem como objetivo analisar as visões de potenciais turistas com grande interesse por aplicações turísticas. De acordo com as características de percepção do modelo de aceitação de tecnologia, teoria da difusão da inovação e modelo de qualidade de software, a tese estabelece o modelo de investigação e propõe hipóteses de investigação correspondentes, sobre a combinação de resultados da pesquisa atual. Uma vez realizado o desenho do questionário e feita a recolha e processamento de dados, a análise de dados e a verificação de hipóteses foram conduzidas pelo uso do modelo de equações estruturais. O resultado da pesquisa implica que os atributos de design do aplicativo e os recursos de desempenho do aplicativo são fundamentais para promover a adoção do aplicativo móvel de viagem. Além disso, esta pesquisa amplia os horizontes sobre o impacto acidental de atributos de aplicação no comportamento de adoção, adicionando o gênero do usuário como uma variável ao modelo, e aumenta uma importante base teórica para pesquisas futuras neste campo

Regulating Habit-Forming Technology

Tech developers, like slot machine designers, strive to maximize the user’s “time on device.” They do so by designing habit-forming products— products that draw consciously on the same behavioral design strategies that the casino industry pioneered. The predictable result is that most tech users spend more time on device than they would like, about five hours of phone time a day, while a substantial minority develop life-changing behavioral problems similar to problem gambling. Other countries have begun to regulate habit-forming tech, and American jurisdictions may soon follow suit. Several state legislatures today are considering bills to regulate “loot boxes,” a highly addictive slot-machine- like mechanic that is common in online video games. The Federal Trade Commission has also announced an investigation into the practice. As public concern mounts, it is surprisingly easy to envision consumer regulation extending beyond video games to other types of apps. Just as tobacco regulations might prohibit brightly colored packaging and fruity flavors, a social media regulation might limit the use of red notification badges or “streaks” that reward users for daily use. It is unclear how much of this regulation could survive First Amendment scrutiny; software, unlike other consumer products, is widely understood as a form of protected “expression.” But it is also unclear whether well-drawn laws to combat compulsive technology use would seriously threaten First Amendment values. At a very low cost to the expressive interests of tech companies, these laws may well enhance the quality and efficacy of online speech by mitigating distraction and promoting deliberation

Using Active Privacy Transparency to Mitigate the Tension Between Data Access and Consumer Privacy

Recently, news exposure about privacy practices has brought substantial negative effects on companies’ reputation and trust, which, in essence, reflects the escalating tension between data access and privacy protection that companies are currently facing. Accordingly, we design an active privacy transparency measure and implement it on our self-developed app. Through a two-task experiment, we simultaneously explore the profound and immediate effects of privacy transparency on firms and the underlying mechanisms. Results from our analyses show that active privacy transparency significantly mitigates users perceived psychological contract violations, which in turn helps companies prevent negative word-of-mouth and loss of trust. Moreover, it also ensures companies’ immediate access to user data, and the moderating role of privacy literacy provides an explanation for this insignificant effect and previous inconsistent findings. More interestingly, we find that active privacy transparency might better elicit users’ actual privacy preferences and help companies identify their targeted users