An Overview of Blockchain Integration with Robotics and Artificial Intelligence

Blockchain technology is growing everyday at a fast-passed rhythm and it's possible to integrate it with many systems, namely Robotics with AI services. However, this is still a recent field and there isn't yet a clear understanding of what it could potentially become. In this paper, we conduct an overview of many different methods and platforms that try to leverage the power of blockchain into robotic systems, to improve AI services or to solve problems that are present in the major blockchains, which can lead to the ability of creating robotic systems with increased capabilities and security. We present an overview, discuss the methods and conclude the paper with our view on the future of the integration of these technologies.info:eu-repo/semantics/draf

Purchasing through Social Platforms with Buy Buttons: Academic and Practical Considerations

Social commerce sales are considerably increasing in recent years. Social platforms (e.g., Facebook, Instagram, and WeChat) play a strategic role in world economy. However, social platforms ran into several burning issues: low ad conversion rates, social platform users’ free-riding behaviors, etc. Although buy buttons, a clickable navigation element leading users from a social platform to an e-commerce platform, could be a solution for such issues, the outcomes of using buy buttons did not reach many professionals’ expectation. This thesis studied four issues related to social shopping with buy buttons. First, as it is undetermined whether a social platform should roll out the buy-button feature or not, it is necessary to study whether the presence of buy button is associated with better outcomes (e.g. users’ higher willingness to purchase through the social platform) or not. Second, as social commerce is a remote shopping mode in which buyers and sellers cannot have face-to-face interactions, high risk and low trust could be two crucial barriers of social commerce. Hence, it is needed to study how risk- and trust-related factors influence users’ direct purchasing behavior. Third, considering that social commerce could be risky, this thesis wants to examine whether the presence of safe shopping measures (vs. an unsafe shopping scenario) can improve the performance of social shopping or not. Finally, social commerce involves a purchase path from a social platform to an e-commerce platform. There are many pain points (e.g., re-entering billing and shipping information) in the purchase path. Meanwhile, as social shopping risks and pain points in the purchase path could be caused by a same factor, the silos between social platforms and e-commerce platforms. It is interesting to study how safe shopping measures and integrated path-to-purchase (users can complete a purchase without leaving the social platform; vs. separated path-to-purchase in which users have to leave the social platform and go to the e-commerce platform to complete a purchase) jointly influence users. In order to answer these questions, three essays have been included in this thesis. Several online surveys were conducted. The between-subjects experimental design and the Structural Equation Modeling (SEM) technique were used. The results showed that the presence of buy button was related to better outcomes. It found that risk- and trust-related factors significantly influenced users’ direct purchasing behavior. Both the safe shopping measures and the integrated path-to-purchase design can generate better outcomes of using a buy button in social shopping. In most circumstances, users showed more positive reactions when the safe shopping measures or the integrated path-to-purchase was present. However, no significant interaction effects between the safe shopping measures (vs. an unsafe shopping scenario) and the integrated path-to-purchase (vs. the separated path-to-purchase) were found. The theoretical contributions have been discussed in contrast to previous literature. This thesis has added academic value by offering new insights for previously established variable relationships in a different research context and studying variable relationships that have not been examined in previously relevant studies. From a practical viewpoint, as buy buttons inject e-commerce capabilities into social platforms, this thesis implies that socially focused platforms could reap benefits from social commerce by rolling out a buy-button feature. It is recommended that social platforms wanting to roll out buy buttons take safe shopping measures and create a seamless shopping experience for users.Tesis Univ. Granada.China Scholarship Council grant number: 201606170055National Natural Science Foundation of China grant number: 7170206

Classifying Web 2.0 Supported Applications By Pattern Of Usage: Functional & Technical ISSUES

The rapid evolution of Internet technologies have witnessed new Web elements, such as blogs, wikis, social networking, social bookmarking, and other related applications referred to as Web 2.0. Web 1.0 paradigm was related with passive, just receptive users, whereas Web 2.0 paradigm relies mainly on user participation and user-generated content. In Web 2.0 applications users are invited to comment, share, edit, classify, as well as remix data from multiple sources. Although there are several Web 2.0 applications in the market there is still lack of a profound approach guiding the analysis, design and development of such applications. This paper suggests classifying Web 2.0 tools by “Pattern of Usage” or in other words the functionalities that characterize their specific features. By reviewing several literatures we extracted multiple attributes related to functionalities of Web 2.0 tools. These have been crystallised into 7 patterns of usage that include; Inter-connectivity, Content authoring, Content tagging & rating, Content aggregation & syndication, Content remixing, Content streaming and File sharing. By interlinking functionality/ usage with underlying technologies, techniques and architecture we provided insight into design and technical requirements for Web 2.0 supported applications. Furthermore we broke down the patterns into basic, elementary to include Inter-connectivity, File sharing and Content remixing, and secondary, supportive to include the other four patterns. This would provide the technical core for any development methodology targeted at Web 2.0 applications

Understanding and Mitigating Product Uncertainty in Online Auction Marketplaces

The Internet interface poses a difficulty for buyers in evaluating products online, particularly physical experience and durable goods, such as used cars. This increases buyers' product uncertainty, defined as the buyer's perceived estimate of the variance in product quality based on subjective probabilities about the product's characteristics and whether the product will perform as expected. However, the literature has largely ignored product uncertainty and mostly focused on mitigating buyer's seller uncertainty. To address this void, this study aims to conceptualize the construct of product uncertainty and propose its antecedents and consequences in online auction marketplaces. First, drawing upon the theory of markets with asymmetric information, we propose product uncertainty to be distinct from, yet affected by, seller uncertainty. Second, based on auction pricing theory, we propose that product uncertainty and seller uncertainty negatively affect two key success outcomes of online marketplaces: price premium and transaction activity. Third, following information signaling theory, we propose a set of product information signals to mitigate product uncertainty: (1) online product descriptions (textual, visual, multimedia); (2) third-party product certifications (inspection, history report, warranty); (3) auction posted prices (reserve, starting, buy-it-now); and (4) intrinsic product characteristics (book value and usage). Finally, we propose that the effect of online product descriptions and intrinsic product characteristics on product uncertainty is moderated by seller uncertainty. The proposed model is supported by a unique dataset comprised of a combination of primary (survey) data drawn from 331 buyers who bid upon a used car on eBay Motors, matched with secondary transaction data from the corresponding online auctions. The results distinguish between product and seller uncertainty, show the stronger role of product uncertainty on price premiums and transaction activity compared to seller uncertainty, empirically identify the most influential product information signals, and support the mediating role of product uncertainty. This paper contributes to and has implications for better understanding the nature and role of product uncertainty, identifying mechanisms for mitigating product uncertainty, and demonstrating complementarities between product and seller information signals. The model's generalizability and implications are discussed

Conceptualizing the Electronic Word-of-Mouth Process: What We Know and Need to Know About eWOM Creation, Exposure, and Evaluation

Electronic word of mouth (eWOM) is a prevalent consumer practice that has undeniable effects on the company bottom line, yet it remains an over-labeled and under-theorized concept. Thus, marketers could benefit from a practical, science-based roadmap to maximize its business value. Building on the consumer motivation–opportunity–ability framework, this study conceptualizes three distinct stages in the eWOM process: eWOM creation, eWOM exposure, and eWOM evaluation. For each stage, we adopt a dual lens—from the perspective of the consumer (who sends and receives eWOM) and that of the marketer (who amplifies and manages eWOM for business results)—to synthesize key research insights and propose a research agenda based on a multidisciplinary systematic review of 1050 academic publications on eWOM published between 1996 and 2019. We conclude with a discussion of the future of eWOM research and practice

Bartering Books to Beers: a Recommender System for Exchange Platforms

Bartering is a timeless practice that is becoming increasingly popular on the Web. Recommending trades for an online bartering platform shares many similarities with traditional approaches to recommendation, in particular the need to model the preferences of users and the properties of the items they consume. However, there are several aspects that make bartering problems interesting and challenging, specifically the fact that users are both suppliers and consumers, and that the trading environment is highly dynamic. Thus, a successful model of bartering requires us to understand not just users’ preferences, but also the social dynamics of who trades with whom, and the temporal dynamics of when trades occur. We propose new models for bartering-based recommendation, for which we introduce three novel datasets from online bartering platforms. Surprisingly, we find that existing methods (based on matching algorithms) perform poorly on real-world platforms, as they rely on idealized assumptions that are not supported by real bartering data. We develop approaches based on Matrix Factorization in order to model the reciprocal interest between users and each other’s items. We also find that the social ties between members have a strong influence, as does the time at which they trade, therefore we extend our model to be socially- and temporally- aware. We evaluate our approach on trades covering books, video games, and beers, where we obtain promising empirical performance compared to existing techniques

An Empirical Study of Branding Strategy at Dealer point for Selling of Car-a qualitative & systematic Review of Literature

India is one of the world’s fastest growing automobile markets and is poised to become the third largest passenger’s car market by 2020 (Philip, L. 2016, Economic Times). The recorded sales growth of 4 wheelers like passenger car & utility vehicle has also risen up to 7.87 % and 6.25% respectively during April-March 2016 (SIAM, 2015-16). But what makes a car maker like Japan’s Maruti Suzuki and Korea’s Hyundai enjoys more than 67% of market share while others like US car makers Ford India and General Motors combined market share is just 4-5%(Philip,L.2016,The Economic Times). Sales in the North & East region have evidenced only 5%of changes in the FY16 which is comparatively lower than the west & south region (Khan,A.N,2016, The Economic Times). The Japanese car makers(Honda, Hyundai, Isuzu Motors, Nissan &Toyota) achieved an average of 48.01% of growth till July 2016 having a better stand from the Indian car makers (Hindustan Motors, M&M,M&S, Tata & Force motors) i.e. 6.74% (Autocar Pro News Desk, July 2016). In this study the researcher explored the factors affecting the satisfaction of prospective car buyers and existing car users at dealer point and facilitate dealer to create a brilliant “moment of truth” (Pioneered by JanCarlzon) when a customer encounter with company.(Madge, Davidson & Beaujean, 2006

DIGITAL WINE: HOW PLATFORMS AND ALGORITHMS WILL RESHAPE THE WINE INDUSTRY

La tesi si propone di analizzare come la digitalizzazione e gli approcci basati sui dati, in particolare quelli che sfruttano l'intelligenza artificiale, stiano impattando il settore vitivinicolo e facendo emergere modelli nuovi di business. Quest'ultimo aspetto sarà approfondito tramite due casi studio di piattaforme digitali che, attraverso approcci diversi, stanno contribuendo a generare un ecosistema digitale virtuoso, con potenziali benefici per tutta la catena del valore a livello di settore.The thesis aims to analyze how digitalization and data-driven approaches, in particular those that leverage artificial intelligence, are impacting the wine industry and generating new business models. The latter aspect will be explored through two case studies of digital platforms which, through different approaches, are helping to generate a virtuous digital ecosystem, with potential benefits for the entire value chain at the industry level

Startup dilemmas - Strategic problems of early-stage platforms on the internet

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