Purpose -The purpose of the paper is to distinguish features of m-commerce from those of e-commerce and identify factors to influence customer satisfaction (m-satisfaction) and loyalty (m-loyalty) in m-commerce by empirically-based case study. Design/methodology/approach -First, based on previous literature, the paper builds sets of customer satisfaction factors for both e-commerce and m-commerce. Second, features of m-commerce are identified by comparing it with current e-commerce through decision tree (DT). Third, with the derived factors from DT, significant factors and relationships among the factors, m-satisfaction and m-loyalty are examined by m-satisfaction model employing structural equation model. Findings -The paper finds that m-commerce is partially similar in factors like "transaction process" and "customization" which lead customer satisfaction after connecting an m-commerce site, but it has unique aspects of "content reliability", "availability", and "perceived price level of mobile Internet (m-Internet)" which build customer's intention to the m-commerce site. Through the m-satisfaction model, "content reliability", and "transaction process" are proven to be significantly influential factors to m-satisfaction and m-loyalty.Research implications/limitations -The paper can be a meaningful step to provide empirical analysis and evaluation based on questionnaire survey targeting actual users. The research is based on a case study on digital music transaction, which is indicative, rather than general. Practical implications -The paper meets the needs to focus on customer under the fiercer competition in Korean m-commerce market. It can guide those who want to initiate, move or broaden their business to m-commerce from e-commerce. Originality/value -The paper develops a revised ACSI model to identify individual critical factors and the degree of effect.

With the rapid change in markets and technologies, it is becoming essential for firms to develop new products constantly. This can most successfully be achieved by using technology roadmaps (TRMs), which are effective tools for connecting product and technology planning. However, TRMs generally tend to overstate the qualitative and expert-dependent knowledge rather than incorporating quantitative and objective information. This paper proposes a new approach where patent data are used in a quantitative methodology to support reliable decision-making in roadmapping processes. In this study, text-mining techniques were utilized to extract the relevant information on which portfolio, co-word, and network analyses were carried out. The results were three types of product-technology maps that can be applied to specific roadmapping steps. The suggested approach is expected to yield useful information about roadmapping, and help improve the overall effectiveness and quality of the technique.

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Since parts and systems are closely linked to each other in complex engineering products, a change in a single part or system causes changes in other parts or systems, which in turn propagate through a product. This paper proposes an analytic network process (ANP) approach to measuring the relative importance of parts and modules in a modular product in terms of design change impacts and propagation. Although the primary purpose of the ANP is selection and prioritisation of alternatives, this study applies the ANP to change propagation by exploiting its advantageous feature, taking indirect impacts among elements into account. To begin with, a design dependency network that represents design change relationships among parts and modules is constructed as a network model of the ANP. The ANP procedure is then carried out to derive the relative change impacts (RCIs) of parts and modules. The RCI values can be used for various works in engineering change management. A case study on an automobile system is presented to illustrate the proposed approach.

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