3D product authenticity model for online retail: An invariance analysis

This study investigates the effects of different levels of invariance analysis on three dimensional (3D) product authenticity model (3DPAM) constructs in the e- retailing context. A hypothetical retailer Web site presents a variety of laptops using 3D product visualisations. The proposed conceptual model achieves acceptable fit and the hypothesised paths are all valid. We empirically investigate the invariance across the subgroups to validate the results of our 3DPAM. We concluded that the 3D product authenticity model construct was invariant for our sample across different gender, level of education and study backgrounds. These findings suggested that all our subgroups conceptualised the 3DPAM similarly. Also the results show some non-invariance results for the structural and latent mean models. The gender group posits a non-invariance latent mean model. Study backgrounds group reveals a non-invariance result for the structural model. These findings allowed us to understand the 3DPAMs validity in the e-retail context. Managerial implications are explained

Adapting tam and ECT: continuance intention of e-shopping in Saudi Arabia

The objective of this study is to clarify the theoretical problem and identify factors that could explain the level of continuance intention of e-shopping in context of Saudi Arabia. The study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure age differences with regard to continuance online shopping intentions. Structural equation model confirms model fit. The research findings confirm that Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance. The structural weights are mostly equivalent between the young and old groups, but the regression path from subjective norms to perceived usefulness is not invariant, with that relationship being stronger for the younger respondents. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The model explains 65% of the intention to continue shopping online. The research findings suggest that online strategies cannot ignore either the direct and indirect effects on continuance intentions

Understanding the factors that derive continuance intention of e-shopping in Saudi Arabia: Age group differences in behaviour

The objective of this study is to clarify the theoretical problem and identify factors that could explain the level of continuance intention of e-shopping in context of Saudi Arabia. The study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure age differences with regard to continuance online shopping intentions in Saudi Arabia. The sample (n=465) consists of 68.8% women and 31.4% men, 348 younger than 35 years old and 117 older than 35. A structural equation model confirms model fit. The research findings confirm that Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance in Saudi Arabia. The structural weights are mostly equivalent between the young and old groups, but the regression path from subjective norms to perceived usefulness is not invariant, with that relationship being stronger for the younger respondents. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The model explains 65% of the intention to continue shopping online. The research findings suggest that online strategies cannot ignore either the direct and indirect effects on continuance intentions in Saudi Arabia. The model can be generalized across the three main commercial regions of Saudi Arabia

Agent Behavior Prediction and Its Generalization Analysis

Machine learning algorithms have been applied to predict agent behaviors in real-world dynamic systems, such as advertiser behaviors in sponsored search and worker behaviors in crowdsourcing. The behavior data in these systems are generated by live agents: once the systems change due to the adoption of the prediction models learnt from the behavior data, agents will observe and respond to these changes by changing their own behaviors accordingly. As a result, the behavior data will evolve and will not be identically and independently distributed, posing great challenges to the theoretical analysis on the machine learning algorithms for behavior prediction. To tackle this challenge, in this paper, we propose to use Markov Chain in Random Environments (MCRE) to describe the behavior data, and perform generalization analysis of the machine learning algorithms on its basis. Since the one-step transition probability matrix of MCRE depends on both previous states and the random environment, conventional techniques for generalization analysis cannot be directly applied. To address this issue, we propose a novel technique that transforms the original MCRE into a higher-dimensional time-homogeneous Markov chain. The new Markov chain involves more variables but is more regular, and thus easier to deal with. We prove the convergence of the new Markov chain when time approaches infinity. Then we prove a generalization bound for the machine learning algorithms on the behavior data generated by the new Markov chain, which depends on both the Markovian parameters and the covering number of the function class compounded by the loss function for behavior prediction and the behavior prediction model. To the best of our knowledge, this is the first work that performs the generalization analysis on data generated by complex processes in real-world dynamic systems

Integrating information and knowledge for enterprise innovation

It has widely been accepted that enterprise integration, can be a source of socio-technical and cultural problems within organisations wishing to provide a focussed end-to-end business service. This can cause possible “straitjacketing” of business process architectures, thus suppressing responsive business re-engineering and competitive advantage for some companies. Accordingly, the current typology and emergent forms of Enterprise Resource Planning (ERP) and Enterprise Application Integration (EAI) technologies are set in the context of understanding information and knowledge integration philosophies. As such, key influences and trends in emerging IS integration choices, for end-to-end, cost-effective and flexible knowledge integration, are examined. As touch points across and outside organisations proliferate, via work-flow and relationship management-driven value innovation, aspects of knowledge refinement and knowledge integration pose challenges to maximising the potential of innovation and sustainable success, within enterprises. This is in terms of the increasing propensity for data fragmentation and the lack of effective information management, in the light of information overload. Furthermore, the nature of IS mediation which is inherent within decision making and workflow-based business processes, provides the basis for evaluation of the effects of information and knowledge integration. Hence, the authors propose a conceptual, holistic evaluation framework which encompasses these ideas. It is thus argued that such trends, and their implications regarding enterprise IS integration to engender sustainable competitive advantage, require fundamental re-thinking

Organising the knowledge space for software components

Software development has become a distributed, collaborative process based on the assembly of off-the-shelf and purpose-built components. The selection of software components from component repositories and the development of components for these repositories requires an accessible information infrastructure that allows the description and comparison of these components. General knowledge relating to software development is equally important in this context as knowledge concerning the application domain of the software. Both form two pillars on which the structural and behavioural properties of software components can be addressed. Form, effect, and intention are the essential aspects of process-based knowledge representation with behaviour as a primary property. We investigate how this information space for software components can be organised in order to facilitate the required taxonomy, thesaurus, conceptual model, and logical framework functions. Focal point is an axiomatised ontology that, in addition to the usual static view on knowledge, also intrinsically addresses the dynamics, i.e. the behaviour of software. Modal logics are central here – providing a bridge between classical (static) knowledge representation approaches and behaviour and process description and classification. We relate our discussion to the Web context, looking at Web services as components and the Semantic Web as the knowledge representation framewor

Simulation of complex environments:the Fuzzy Cognitive Agent

The world is becoming increasingly competitive by the action of liberalised national and global markets. In parallel these markets have become increasingly complex making it difficult for participants to optimise their trading actions. In response, many differing computer simulation techniques have been investigated to develop either a deeper understanding of these evolving markets or to create effective system support tools. In this paper we report our efforts to develop a novel simulation platform using fuzzy cognitive agents (FCA). Our approach encapsulates fuzzy cognitive maps (FCM) generated on the Matlab Simulink platform within commercially available agent software. We firstly present our implementation of Matlab Simulink FCMs and then show how such FCMs can be integrated within a conceptual FCA architecture. Finally we report on our efforts to realise an FCA by the integration of a Matlab Simulink based FCM with the Jack Intelligent Agent Toolkit

The MIXADAPT Scale: A Measure of Marketing Mix Adaptation to the Foreign Market

This study presents a four-dimensional multi-item scale for assessing the degree of marketing mix adaptation to the foreign market (the MIXADAPT scale). The scale shows evidence of reliability as well as convergent, discriminant and nomological validity in samples of Portuguese and British exporters. Additionally, the scale reveals factorial similarity and factorial equivalence across the two samples. The findings are used to generate managerial and theoretical implications as well as directions for future research.Cross-Country Study; Export Marketing Program; Measurement; MIXADAPT Scale