BUSINESS REPUTATION SYSTEMS BASED ON BLOCKCHAIN TECHNOLOGY—A RISKY ADVANCE

Reputation is indispensable for online business since it supports customers in their buying decisions and allows sellers to justify premium prices. While IS research has investigated reputation systems mainly as review systems on online platforms for business-to-consumer (B2C) transactions, no proper solutions have been developed for business-to-business (B2B) transactions yet. We use blockchain technology to propose a new class of reputation systems that apply ratings as voluntary bonus payments: Before a transaction is performed, customers commit to pay a bonus that is granted if a service provider has performed a service properly. As opposed to rival reputation systems that build on cumulated ratings or reviews, our system enables monetized reputation mechanisms that are inextricably linked with online transactions. We expect this system class to provide more trustworthy ratings, which might reduce agency costs and serve quality providers to establish a reputation towards new customers, building on second-order trust

Trusted operational scenarios - Trust building mechanisms and strategies for electronic marketplaces.

This document presents and describes the trusted operational scenarios, resulting from the research and work carried out in Seamless project. The report presents identified collaboration habits of small and medium enterprises with low e-skills, trust building mechanisms and issues as main enablers of online business relationships on the electronic marketplace, a questionnaire analysis of the level of trust acceptance and necessity of trust building mechanisms, a proposal for the development of different strategies for the different types of trust mechanisms and recommended actions for the SEAMLESS project or other B2B marketplaces.trust building mechanisms, trust, B2B networks, e-marketplaces

Community and Thread Methods for Identifying Best Answers in Online Question Answering Communities

Much research has recently investigated the measurement of quality answers in Question Answering (Q&A) communities in the form of automatic best answer identification. Previous approaches have focused on manual user annotations and diverse features based on intuition for identifying best answers and proved relatively successful despite considering best answer identification as a general classification problem. Best answer modelling is generally distanced from community studies about what users regard as important for identifying quality content. In particular, previous research tends to only focus on the automatic aspects of best answers identification model by applying generic learning algorithms. This thesis introduces the concepts of qualitative and structural design in order to investigate if features derived from community questionnaires can enrich the understanding of best answer identification in Q&A communities and if the thread-like structure of Q&A communities can be exploited for better results. Two different approaches for exploiting the thread structure of Q&A communities are proposed and two new, previously unstudied, features are introduced. First, a measure of question complexity is introduced as a proxy measure of answerer knowledge. Second, different models of contribution effort are proposed for representing the answering reactivity of contributors. The experiments are systematically conducted on datasets issued from three different communities that vary in size, content and structure. The results show that the newly proposed features allow for better understanding of what constitute best answers. The findings also reveal that the thread-wise algorithms and optimisation techniques created from the structural design methodology correlate with best answers. In general both structural and qualitative design appear to improve best answer identification meaning that structural and qualitative methods may improve unrelated classification tasks

Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions

Purpose-Although the value of AI has been acknowledged by companies, the literature shows challenges concerning AI-enabled B2B marketing innovation, as well as the diversity of roles AI can play in this regard. Accordingly, this study investigates the approaches that AI can be used for enabling B2B marketing innovation. Design/methodology/approach-Applying a bibliometric research method, this study systematically investigates the literature regarding AI-enabled B2B marketing. It synthesises state-of-the-art knowledge from 221 journal articles published between 1990 and 2021. Findings-Apart from offering specific information regarding the most influential authors and most frequently cited articles, the study further categorises the use of AI for innovation in B2B marketing into five domains, identified the main trends in the literature, and suggest directions for future research. Practical implications-Through our identified five domains, practitioners can assess their current use of AI ability in terms of their conceptualisation capability, technological applications, and identify their future needs in the relevant domains in order to make appropriate decisions on whether to invest in AI. Thus, the research outcomes can help companies to realise their digital marketing innovation strategy through AI. Originality/value-While more and more studies acknowledge the potential value of AI in B2B marketing, few attempts have been made to synthesise the literature. The results from the study can contribute by 1) obtaining and comparing the most influential works based on a series of analyses; 2) identifying five domains of research into how AI can be used for facilitating B2B marketing innovation; and 3) classifying relevant articles into five different time periods in order to identify both past trends and future directions in this specific field

Risk and trust management for online distributed system

This thesis investigated the problem of strategic manipulation of feedback attacks and proposed an approach that makes trust management systems sufficiently robust against feedback manipulation attacks. The new trust management system enables potential service consumers to determine the risk level of a service before committing to proceed with the transaction

Impact of Business-to-Consumer Electronic Commerce Factors on Firm Performance in Taiwan\u27s E-Brokerage Sector

The new economy influences the entire economy, from corporations and governments to society. Business-to-consumer (B2C) electronic commerce (EC) continues to grow despite the burst of the 2000 e-bubble. Dramatic changes in EC and the significance of EC\u27s impact on firm performance are important practical issues. Variations in firm performance (outcome variable) are attributed to organization effect and to industry effect. Thus, a theoretical framework that combines a strategic typology with a resource-based view of the dynamic capabilities perspective can explain the industry and organization effect on firm performance. This non-experimental, correlational (explanatory) and causal-comparative (exploratory) survey and secondary data research design is the first to investigate the relationships among organizational characteristics (firm size and web age), CEO commitment to EC, strategy types, website design, and IT system integration capabilities on the performance of Taiwan\u27s e-brokerage firms. In this study, integrating factors of strategic types as an industry effect, CEO commitment to EC as a firm resource and website design and IT system integration as EC capabilities provided a better explanation of the performance of Taiwan\u27s e-brokerage firms. Findings indicated that strategy types showed no significant differences on the level of firm performance (online sales and market share). Another finding suggested that website design of catalog application and web age were significant contributors the to the online annual sales growth rate. In addition, CEO commitment to EC, website design of catalog application, IT system integration capabilities, and web age were significant explanatory factors of the online annual market share growth rate. Top managers of e-brokers in Taiwan must have the ability to do all things well in order to succeed in the rapidly-changing EC environment. EC firms can no longer benefit from first-mover advantage which contributes negatively to firm performance. At the same time, they need to emphasize and invest firm resources into EC and bundle and leverage EC (website design capabilities) as a way to create value for customers, build a sustainable competitive advantage, and gain superior performance over competitors

Trusted operational scenarios - Trust building mechanisms and strategies for electronic marketplaces.

This document presents and describes the trusted operational scenarios, resulting from the research and work carried out in Seamless project. The report presents identified collaboration habits of small and medium enterprises with low e-skills, trust building mechanisms and issues as main enablers of online business relationships on the electronic marketplace, a questionnaire analysis of the level of trust acceptance and necessity of trust building mechanisms, a proposal for the development of different strategies for the different types of trust mechanisms and recommended actions for the SEAMLESS project or other B2B marketplaces