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Electronic commerce or business is more than just another way to sustain or enhance existing business practices. Rather, e‐commerce is a paradigm shift. It is a “disruptive” innovation that is radically changing the traditional way of doing business. The industry is moving so fast because it operates under totally different principles and work rules in the digital economy. A general rule in e‐commerce is that there is no simple prescription and almost no such thing as an established business or revenue model for companies even within the same industry. Under such conditions, an analytical framework is needed to assist e‐commerce planners and strategic managers in assessing the critical success factors when formulating e‐commerce business models and strategies. This research develops an analytical framework based on the theories of transaction costs and switching costs. Both demand‐side and supply‐side economies of scale and scope are also applied to the development of this framework. In addition, e‐commerce revenue models and strategies are also discussed. Based on the analytical framework developed by this research, this paper discusses the five essential steps for e‐commerce success. They are: redefine the competitive advantage; rethink business strategy; re‐examine traditional business and revenue models, re‐engineer the corporation and Web site; and re‐invent customer service. E‐commerce planners and strategic managers will be able to use the framework to analyze and evaluate the critical successful factors for e‐commerce success.

Summarizes the flat panel display (FPD) industry outside of Japan, with a focus on advances in Korea and Taiwan. Discusses the major manufacturers in each country as well as their current status. Concludes with a brief discussion on the future outlook of the FPD market.

The purpose of this paper is to differentiate traditional industrial clusters from emerging consumption‐oriented and destination‐based regional service clusters (e.g. entertainment, service‐based tourism, and convention destination); to develop an analytical framework to examine the impacts of both cluster and network effects in service clusters; and to offer implications for managing service innovation to enhance regional development and global competitiveness.

By applying industrial cluster, strategic network, and value creation theories, this research develops a framework to study value creation in service clusters.

The research concludes that firms' decisions to enter or exit a service cluster depends on the net strategic effects, which is the sum of agglomeration economies (i.e. cluster effects) and the economies of network (i.e. network effects).

Further empirical research is needed to determine the significance of both cluster and network effects that determine firms' decisions to enter the service clusters.

First, firms need to incorporate cluster‐specific elements, such as experience economy, value networking, and service innovation to maximize the consumer's use value or perceived customer benefits. Second, in order to increase consumers' willingness to pay a higher price, firms located inside the service clusters need to adopt strategies, such as product or service differentiation, that increase the perceived benefits or use value of customers. Third, service cluster firms' other objectives should be to minimize location‐specific cost differentials by capitalizing on the positive effects of both agglomeration economies and economies of network. Fourth, public policy implications need to include laws and regulations that encourage and promote innovation and new ventures creation, competition in the marketplace, and capital investment to maximize value creation. Finally, policy makers need to promote high value‐added economic activities in the service clusters in order to maximize consumer welfare.

A growing number of policymakers and scholars have recognized the significant economic contributions from the consumption‐oriented regional clusters. This paper is the first effort to develop an analytical framework to study value creation in service clusters for effective managerial and policy decisions.

Presents the findings of a cross‐cultural analysis of perceived risks of environmental, technological, and societal problems. An international sample of 295 undergraduate and graduate students at three US universities and the National Taiwan University was surveyed. The study was designed to test two hypotheses: first, that today’s university students have grown numb to threat warnings and second, that differences in cultural and political contexts result in variation in the way societies perceive environmental issues and social concerns. Analysis of variance tests identified a number of significant differences in the way US and Asian university students perceive environmental risks, despite the many similarities in the university‐student cultures of both regions.

In‐depth tourism is a new traveling pattern, which combines thematic traveling experience and personal knowledge. This paper aims to analyze the industry characteristics and approaches to develop and promote in‐depth tourism from a service innovation perspective.

The paper introduces the concept of in‐depth tourism and presents two case studies depicting the practices of this new approach. The paper also includes training and exercises on in‐depth tourism's implementation.

A three‐dimensional framework consisting of customer value, regional resources and competences, and technology adoption (e.g. information and communication technologies) is developed to guide service innovations in the tourism industry.

The new theoretical framework and set of training exercises provide management with the tools to effectively create and promote service innovations through in‐depth tourism.

The paper introduces the concepts and practices of in‐depth tourism from a service innovation perspective. In addition, the research provides several managerial and policy implications to manage service innovations and to promote regional development through in‐depth tourism.

The purpose of this study is to use current literature in conjunction with the insights from a detailed analysis of current practice to clarify and extend the knowledge of networks of clusters.

This research is an exploratory study of cluster formation and global competitiveness. By applying cluster and network theory, this study examines critical elements of high‐technology networks and clusters. A case study of two clusters in Taiwan and two in China reveals both intra‐ and inter‐cluster network relationships.

This research concludes that networks of clusters do exist and they carry potential advantages for both firms' and clusters' competitive advantage and innovation. Close network relationships and interdependences of industrial clusters have contributed significantly to the competitiveness of high‐technology clusters in the Asia‐Pacific region.

Further research is needed to determine what conditions best promote inter‐cluster networks and when such networks are likely to generate the most value.

First, the relationship among firms in an industrial cluster may be viewed as not only extended supply chains but also as more complex network forms. Firms in a cluster may work together to co‐evolve for the purpose of enhancing competitiveness. This process is worthy of further attention from managers looking to more rapidly develop the competitiveness of their firms. Second, the industrial clusters offer a relatively favorable environment that allows the participating firms to more easily pool the resources, investments, and synergies necessary for them to become competitive in the global arena. Third, to the extent that specialization may increase comparative advantage, an industrial cluster can concentrate firms and industries in a region dedicated to a particular product or competence. Finally, once a cluster successfully pools the resources and develops the core products and competences, the phenomena of networks of clusters is likely to emerge for participating parties to share complementarities across both national and geographical boundaries.

Most studies on high‐technology clusters are focused on intra‐cluster interaction. This study broadens the scope of analysis to explore the inter‐cluster network structure that enhances global competitiveness of both firms and clusters in an effective and efficient manner. This study offers initial empirical evidences and a number of important insights to assist managers and policy makers in enhancing global competitive advantage.

The research of industrial clusters, trust, and learning can be traced back to early strategic management and organization theory. The purpose of this paper is to review past literature and offer a conceptual framework that is related to industrial clusters, trust and learning.

This study incorporates a literature review to filter key factors of industrial clusters, trust and learning by using a deductive approach to conclude a conceptual framework.

This study provides a conceptual framework which includes a firm's industrial cluster involvement, trust and learning. Based on the literature, inter‐organizational trust may be strengthened due to reduced proximity and better information flow within a cluster. Further, industrial clusters encourage co‐evolution and co‐adaptation that stimulates effective learning practices for clustering firms.

This study uses a literature review and offers a conceptual framework to examine a firm's involvement in industrial clusters with the possible influences of trust and organizational learning. There is a need for empirical as well as statistical analysis to validate the framework and to obtain more insight.

Industrial clusters are widely considered a network‐based industrial system, with the aim of adapting to fast‐changing markets and technologies as an organized whole. Firms within a cluster can work together to co‐evolve for the purpose of enhancing competitiveness and entering the world market through effective learning and inter‐firm trust. As the sum of the benefit of a cluster is of greater value than each individual company or institution, whether to be involved in an industrial cluster to sustain competitiveness and enhance learning is worthy of managers' consideration.

The major contribution of this work is that it is the first attempt to produce the measures for a firm's involvement in industrial clusters for empirical tests, which are generally considered insufficient in this area of research. Further, this study offers a conceptual framework which brings cluster, trust and learning together for future empirical study.

The purpose of this paper is to construct a process theory of cluster development, in order to complement the many studies focusing on the factors that determine successful clusters.

This theory‐building effort relies on event‐driven methodology, which triangulates narratives collected at different points in time with other documented materials, in order to trace cluster development over a six‐year period. The empirical data are analysed according to theoretical classes formed a priori and anchored in Aldrich's framework of emergence, events and consequences. The idea is to identify critical events that subsequently inform theory development.

The authors show that three critical processes drive sustainable cluster development: the exploitation of current opportunities, the exploration of future opportunities, and processes that facilitate the balancing of the two. Whereas the conceptual focus in the extant literature is on exploration and exploitation processes, the authors find that balancing processes are also critical.

The paper's findings are of practical relevance to private and public policy makers with regard to the management and financing of balancing mechanisms that help to secure sustainable development. The authors will continue to follow the development of this specific cluster in order to identify a wider range of sub‐processes that contribute to the long‐term viability of clusters in general.

This work is original in the sense that it extends March's exploration and exploitation theory, applies it to the inter‐organisational context of clusters, and links the two processes through a process of balancing. The empirical evidence and the methodological approach used contribute in terms of building a “real process theory”, according to Aldrich's specification of an event‐driven research approach.

The purpose of this paper is to study the specialization of regional clusters and their innovative behaviour, in a particular Portuguese region.

A regional case study (Region Centro of Portugal) is used, employing secondary and primary data in order to measure specialized critical mass of a region's clusters and analyze their innovative behavior following the European Cluster Observatory (ECO) methodology.

Combining the different nature of data (primary and secondary), this paper identifies the specialized critical mass of a region's cluster, makes statements about the role of clusters in a regional context, and demonstrates how a regional clustering approach is important to understanding the innovative process. Based on an empirical survey, three types of clusters were found: basic, intermediate and advanced.

Among the research limitations is the undersized sample of primary data which does not allow deep findings to be drawn about the innovative behavior of the clusters in a general way. Therefore, future research should focus on this area, extending the empirical analysis presented here to add qualitative indicators on innovative behaviour, to calculate the impact of absorptive capacity in the case of regional clusters.

This study provides a consistent methodology of cluster operation which could be useful for undertaking comparative work within regions' clusters across different sectors and countries, to reinforce the importance of the current discussion of policy clusters, and to identify specific requirements and needs of each cluster in order to improve the quality of decision making and to draw some policy implications.

This paper is the first to measure specialized critical mass of a region's clusters at the enterprise level and to explain cluster innovative behaviour, combining primary and secondary, based on ECO criteria. Furthermore, it provides initial empirical evidence and an amount of significant findings to support managers and policymakers in the understanding of regional and innovation clustering of small to medium‐sized enterprises.