Trust and Experience in Online Auctions

This paper aims to shed light on the complexities and difficulties in predicting the effects of trust and the experience of online auction participants on bid levels in online auctions. To provide some insights into learning by bidders, a field study was conducted first to examine auction and bidder characteristics from eBay auctions of rare coins. We proposed that such learning is partly because of institutional-based trust. Data were then gathered from 453 participants in an online experiment and survey, and a structural equation model was used to analyze the results. This paper reveals that experience has a nonmonotonic effect on the levels of online auction bids. Contrary to previous research on traditional auctions, as online auction bidders gain more experience, their level of institutional-based trust increases and leads to higher bid levels. Data also show that both a bidder’s selling and bidding experiences increase bid levels, with the selling experience having a somewhat stronger effect. This paper offers an in-depth study that examines the effects of experience and learning and bid levels in online auctions. We postulate this learning is because of institutional-based trust. Although personal trust in sellers has received a significant amount of research attention, this paper addresses an important gap in the literature by focusing on institutional-based trust

The assessment of usability of electronic shopping: A heuristic evaluation

Today there are thousands of electronic shops accessible via the Web. Some provide user-friendly features whilst others seem not to consider usability factors at all. Yet, it is critical that the electronic shopping interface is user-friendly so as to help users to obtain their desired results. This study applied heuristic evaluation to examine the usability of current electronic shopping. In particular, it focused on four UK-based supermarkets offering electronic services: including ASDA, Iceland, Sainsbury, and Tesco. The evaluation consists of two stages: a free-flow inspection and a task-based inspection. The results indicate that the most significant and common usability problems have been found to lie within the areas of ‘User Control and Freedom’ and ‘Help and Documentation’. The findings of this study are applied to develop a set of usability guidelines to support the future design of effective interfaces for electronic shopping

e-Consumer Behaviour

Purpose – The primary purpose of this article is to bring together apparently disparate and yet interconnected strands of research and present an integrated model of e-consumer behaviour. It has a secondary objective of stimulating more research in areas identified as still being underexplored. Design/methodology/approach – The paper is discursive, based on analysis and synthesis of econsumer literature. Findings – Despite a broad spectrum of disciplines that investigate e-consumer behaviour and despite this special issue in the area of marketing, there are still areas open for research into econsumer behaviour in marketing, for example the role of image, trust and e-interactivity. The paper develops a model to explain e-consumer behaviour. Research limitations/implications – As a conceptual paper, this study is limited to literature and prior empirical research. It offers the benefit of new research directions for e-retailers in understanding and satisfying e-consumers. The paper provides researchers with a proposed integrated model of e-consumer behaviour. Originality/value – The value of the paper lies in linking a significant body of literature within a unifying theoretical framework and the identification of under-researched areas of e-consumer behaviour in a marketing context

Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research

This paper reviews the published articles on eTourism in the past 20 years. Using a wide variety of sources, mainly in the tourism literature, this paper comprehensively reviews and analyzes prior studies in the context of Internet applications to Tourism. The paper also projects future developments in eTourism and demonstrates critical changes that will influence the tourism industry structure. A major contribution of this paper is its overview of the research and development efforts that have been endeavoured in the field, and the challenges that tourism researchers are, and will be, facing

Fire in the Records: The Dark Side of Knowledge Management

This paper discusses the implications of buyers and sellers being influenced by the information they receive and how that impacts their decision-making process in the context of a high-value low-frequency transaction (HVLFT). Using an exploratory case study, we explore a dark dimension of knowledge where tacit or explicit knowledge has been lost, distorted, suppressed, misrepresented, or misappropriated resulting in ambiguity and increased risk in decision making. The case study focuses on the decision-making process and the information flow seen from the perspective of different stakeholders involved in a HVLFT. Based on this case study we propose, articulate, and apply a model that explicitly acknowledges the dark side of knowledge. Our findings suggest the need for the application of convergent technologies to ameliorate the risk and asymmetricity caused by the dark side of knowledge and enhance governance particularly in the context of HVLFT

An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection

The biological immune system (BIS) is characterized by networks of cells, tissues, and organs communicating and working in synchronization. It also has the ability to learn, recognize, and remember, thus providing the solid foundation for the development of Artificial Immune System (AIS). Since the emergence of AIS, it has proved itself as an area of computational intelligence. Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. The V-Detectors algorithm depends greatly on the random detectors generated in monitoring the status of a system. These randomly generated detectors suffer from not been able to adequately cover the non-self space, which diminishes the detection performance of the V-Detectors algorithm. This research therefore proposed CSDE-V-Detectors which entail the use of the hybridization of Cuckoo Search (CS) and Differential Evolution (DE) in optimizing the random detectors of the V-Detectors. The DE is integrated with CS at the population initialization by distributing the population linearly. This linear distribution gives the population a unique, stable, and progressive distribution process. Thus, each individual detector is characteristically different from the other detectors. CSDE capabilities of global search, and use of L´evy flight facilitates the effectiveness of the detector set in the search space. In comparison with V-Detectors, cuckoo search, differential evolution, support vector machine, artificial neural network, na¨ıve bayes, and k-NN, experimental results demonstrates that CSDE-V-Detectors outperforms other algorithms with an average detection rate of 95:30% on all the datasets. This signifies that CSDE-V-Detectors can efficiently attain highest detection rates and lowest false alarm rates for anomaly detection. Thus, the optimization of the randomly detectors of V-Detectors algorithm with CSDE is proficient and suitable for anomaly detection tasks

An Information Systems Design Theory for Digital Broker Platforms

Authors accepted manuscriptService platforms are becoming dominant drivers of daily business operations in a digitalized environment. Research focuses on technological and network effects of such platforms, while socio-technical opportunities remain limited. Guidance support in selecting appropriate digital services on a multisided market platform may help companies with low domain knowledge as it increases their benefits by reducing existing barriers in adopting emerging technologies. We adapt the concept of a broker to a digital platform, which instantiates guidance support on multisided markets as core platform element. Further, we abstract the concept of a digital broker platform as an Information Systems (IS) design theory. By providing the necessary components of an IS design theory, we offer the possibility to derive digital broker platform artifacts, which are theoretically and conceptually grounded. We provide design principles for the method artifact and describe their applicability in an exemplary instantiation of the design theory in the domain of cloud computing. Lastly, we present the artifact’s mutability as well as its testable propositions.An Information Systems Design Theory for Digital Broker PlatformsacceptedVersio

Towards reputation-as-a-service

Reputation is used to regulate relationships of trust in online communities. When deploying a reputation system, it needs to accommodate the requirements and constrains of the specific community in order to assist the community to reach their goals. This paper identifies that there is a need for a framework to define a configurable reputation system with the ability to accommodate the requirements of a variety of online communities. Such a reputation system can be defined as a service on the Cloud, to be composed with the application environment of the online community. This paper introduces the concept of RaaS (Reputation-as-a-Service) and discusses a potential framework for creating a RaaS. In order to achieve such a framework, research is conducted into features of SaaS (Software-as-a-Service) components, user requirements for trust and reputation, and features of current reputation frameworks that can be configured in order to support a reputation service on the Cloud