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Abstract

Thanks to the rapid progress in the field of artificial intelligence algorithms are able to accomplish an increasingly comprehensive list of tasks, and often they achieve better results than human experts. Nevertheless, many consumers have ambivalent feelings towards algorithms and tend to trust humans more than they trust machines. Especially when tasks are perceived as subjective, consumers often assume that algorithms will be less effective, even if this belief is getting more and more inaccurate.

To encourage algorithm adoption, managers should provide empirical evidence of the algorithm’s superior performance relative to humans. Given that consumers trust in the cognitive capabilities of algorithms, another way to increase trust is to demonstrate that these capabilities are relevant for the task in question. Further, explaining that algorithms can detect and understand human emotions can enhance adoption of algorithms for subjective tasks.

Abstract

Whatever your perception of AI is, the machine age of marketing has arrived. To fully grasp how AI is changing every fabric of both our professional and private lives, we need to abstract beyond the presence of autonomous cars, digital voice assistants, or using machines to translate some text for us. AI is creating new forms of competition, value chains, and novel ways of orchestrating economies around the world. AI is more than just technology, it’s creating a new economy. The fuel that runs this economy is the combination of computational processing power, data, and the algorithms that process this data.

AI has the potential to make our life easier, but this convenience might come at a price which we have to pay such as biases directly built-in to the algorithms we use, data privacy issues or failed AI projects in business practice. But without testing, failing, and learning from our failures, there

Abstract

This paper examines the return and volatility spillovers of different sectoral stock prices in Nigeria using monthly data from January 2007 to December 2016. We employ the Diebold and Yilmaz (2012) spillover approach and rolling sample analysis to capture the inherent secular and cyclical movements in the sector stocks market.We show that there is substantial difference between the behaviour of the sectoral stock return and volatility spillover indices over time. We find evidence of interdependence among sector stocks given the spillover indices. While the return spillover index reveals increased integration among the sectoral stocks, the volatility spillover index experiences significant bursts during major market crises. Interestingly, return and volatility spillovers exhibit both trends and bursts respectively.

Abstract

The aim of this paper is to analyse the effect of the mobile phone penetration rate on inequality in Western Balkan countries and to provide empirical evidence. We explore the question of whether cell phone diffusion helps to decrease inequality and whether it has a positive income equality effect. In the developed conceptual framework, we consider that people with access to mobile telephony also have access to Wi-Fi and GPS and that individuals can perform different activities, such as engaging in e-commerce, e-governance, health, and education; paying bills; saving money; and transferring money to other persons. This represents a good foundation for poor persons exit the cycle of deprivation and leads to the development of equal opportunities. We analyse the impact of mobile phone penetration on inequality in Western Balkan countries by using ordinary least squares and two-stage least squares models (Asongu, 2015). Our results confirm the income-redistributive effect of mobile phone penetration.

Abstract

While many customers are still reluctant to entrust themselves to Alexa, Cortona or Siri in their homes, they seem to be less worried about controlling their TV sets via voice control. Comcast started offering a voice-based remote control in 2015 and has extended this service continuously. In the vast world of home entertainment, it seems that voice has come just in time to help consumers navigate and control their ever-increasing home entertainment options. Jan Neumann explains how Comcast enables its customers to comfortably boil down a huge entertainment portfolio to personally relevant content on the TV screen, and how the company remains successful in the highly competitive home entertainment market.

Abstract

This study examines the role of information and communication technology (ICT), access to electricity and transport infrastructure in reducing poverty and promoting inclusive growth in Nigeria for the period 1980-2014 using the error correction modeling approach (ECM). The results indicate that access to electricity and transport infrastructure is negative and statistically significant in both the incidence and the depth of poverty reduction and therefore conclude that this lead to inclusive growth. In particular, we show that access to ICT negatively influences the incidence of poverty, but the relationship is not robust when the measure of poverty is the poverty gap.

Abstract

The algorithms that control AVs will need to embed moral principles guiding their decisions in situations of unavoidable harm. Manufacturers and regulators are confronted with three potentially incompatible objectives: being consistent, not causing public outrage, and not discouraging buyers. The presented moral machine study is a step towards solving this problem as it tries to learn how people all over the world feel about the alternative decisions the AI of self-driving vehicles might have to make. The global study displayed broad agreement across regions regarding how to handle unavoidable accidents. To master the moral challenges, all stakeholders should embrace the topic of machine ethics: this is a unique opportunity to decide as a community what we believe to be right or wrong, and to make sure that machines, unlike humans, unerringly follow the agreed-upon moral preferences. The integration of autonomous cars will require a new social contract that provides clear guidelines about who is responsible for different kinds of accidents, how monitoring and enforcement will be performed, and how trust among all stakeholders can be engendered.

Abstract

Consumers produce enormous amounts of textual data of product reviews online. Artificial intelligence (AI) can help analyze this data and generate insights about consumer preferences and decision-making. A GfK research project tested how we can use AI to learn consumer preferences and predict choices from publicly available social media and review data. The common AI tool “Word Embeddings” was used and has shown to be a powerful way to analyze the words people use. It helped reveal consumers’ preferred brands, favorite features and main benefits. Language biases uncovered by the analysis can indicate preferences. Compared to actual sales data from GfK panels, they fit reasonably within various categories. Especially when data volumes were large, the method produced very accurate results. By using free, widespread online data it is completely passive, without affecting respondents or leading them into ranking or answering questions they would otherwise not even have thought of. The analysis is fast to run and no fancy processing power is needed.

Abstract

Powered by better hardware and software, and fueled by the emergence of computational social science, digital traces of human activity can be used to make highly personal inferences about their owner’s preferences, habits and psychological characteristics. The gained insights allow the application of psychological targeting and make it possible to influence the behavior of large groups of people by tailoring persuasive appeals to the psychological needs of the target audiences. On the one hand, this method holds potential benefits for helping individuals make better decisions and lead healthier and happier lives. On the other hand, there are also several potential pitfalls related to manipulation, data protection and privacy violations. Even the most progressive data protection regulations of today might not adequately address the potential abuse of online information in the context of psychological targeting, highlighting the need for further policy interventions and regulations.