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The following is an introductory profile of the fastest growing firms over the three-year period of the study listed by corporate reputation ranking order. The business activities in which the firms are engaged are outlined to provide background information for the reader.

With the advance of the Silk Road Initiative proposed by China, it has been a focus of China government to develop strategic emerging industries. The development of strategic emerging industries needs the support of competitive intelligence on many aspects such as strategical planning, policy making, industrial structure adjustment, and technology innovation. However, so far there are few studies toward the competitive intelligence systems for strategic emerging industries. In this article, we focus on a number of issues related to the competitive intelligence for strategic emerging industries in China. First, we conduct a strengths, weaknesses, opportunities, and threats analysis on the situations of strategic emerging industries in China, based on which the necessity of building a competitive intelligence (CI) service system for strategic emerging industries is discussed. Next, the authors present a framework of a CI service system for strategic emerging industries in China. The principles, components, working process, and product forms are deeply described. The CI service system proposed in this article consists of a cooperation network platform, three layered organizations, and three systems, which integrates organizations, information, people, network, and service platforms into an ecosystem to offer competitive intelligence supports for government, industry, and enterprises. Finally, the authors discuss a case study of the proposed CI service system for the new energy automobile industry.

Because of the COVID-19, the digital transformation of global hospitality and tourism speeds up. This paper aims to provide comprehensive frame of the digital transformation for further hospitality and tourism research.

Through conducting a critical review of the impact of COVID-19, the current situation about the application of digital technology and digital transformation in hospitality and travel, this study used a qualitative approach to present the viewpoints.

This research presents a theoretical research framework for the hospitality and tourism about digital transformation, including possible directions, contexts and methods. It highlights the importance of digital transformation, and further proposing specific research topics.

This research brings valuable implications and guidance for future research from the aspects of key research streams, research context and methodological approaches in hospitality and tourism about digital transformation.

This paper supplies existing critical reviewed research through paying attention to the digital transformation approach in hospitality and tourism, providing research guidance technically to the industry of hotels and travel.

The information technology industries (computer software, telecommunications, data processing services, and information services) are among America's strongest service industries. These are industries in which Japanese policy makers and businesses are striving to gain competitive advantages (Congress of the United States, 1987), as Japanese information technology firms have not been considered very competitive in the international marketplace (Enderwick, 1990; Porter, 1990).

IT is accorded a central role in Malaysian Industrial Master Plan 2 (IMP2), not only as the foundation for the future development of the manufacturing sector, but also, as the engine of development and growth of other sectors of the economy. To fulfill this central role, what should be the value of IT Products and IT Services? We have computed the necessary capital stock of IT Products at RM21.556 billion in 1978 prices, each unit of which is to produce five times its value in output in the year 2005, for a start. The targeted output of IT Services would be another RM 21.556 billion in 1978 prices, for a total of RM43.112 billion for IT industry in 2005. Bill Gates, Chairman and CEO of Microsoft Corporation, holds that Broadband Network Technology (BNT) indispensable to implement the Information Highway would not be available to most US homes for at least a decade. No matter when BNT arrives, an overriding question is: what will be the UTILIZATION of the exploding multimedia content of the Information Superskyway. How will people USE 1,000 times the current content, arriving 1,000 times as fast? The raison d'etre of the Information Superskyway is the Matrix of Learning, with Content as the rows, Context as the columns, and Learning as the Cells. The user has to identify his (her) context of use (entertain‐ment, education, enlightenment, edification). Investment in input (con‐tent) will depend on the answer to the question: By how much will the context be impaired by delay or deficiency of the content (data)? As the capacity of chips increases exponentially, the price drops dramatically — already it is down to $0.14 per megabyte! In the future, a holographic memory of the size of one's fists could hold the contents of the entire Library of Congress. With fast and furious developments in transfer and transformation of multi‐media content, how should one go about investing in IT to reap the bounty of BNT? We have no guarantee of success; we can increase the probability of success in the long‐run using seven IT investment Considerations/Criteria: (1) Choose the “Long‐run” that is realistic: Consider the odds against surviving one year, let alone 10 years; and choose wisely. (2) Choose Your Segment of the IT Industry: Are you most competent in: communications, computers, or content industries? What is your primary product: information, education, enlightenment, shopping, or e‐mail? (3) Choose Your CONCOL competitor/collaborator in the IT Industry: No matter how powerful you are in your chosen segment of the industry, it is almost mandatory that you collaborate with some other(s) in your own industry, and/or in another of the C3 industries. Bill Gates says: “companies must be able to partner on some projects and compete vigorously in others. Few companies in the computer and communications industries are purely friends or purely foes.” (4) Choose the Technology/Territory Area for CONCOL: How will the CONCOLs be formed and dissolved‐in: (1) Technology, (2) Territory? The choice of future technology would depend on the territory: How long would it take for the particular technology to develop a mass market? In IT parlance, should we back advances in: (I) transfer of data, or (2) transformation of data? (5) Choose the Technology Transformation Profile: Visualizing technology say, five generations ahead would indeed be quite hard and hazardous. But we would choose linear extensions of performance characteristics over Quantum jumps. However, PC industry experience suggests that each successive computer generation tended to provide Quantum jumps, little of the earlier models being useable with the new generation. (6) Choose the Technology Transfer Sequence: By establishing a relationship with the techtransferor over the long‐term, and scrupulously observing the mutually‐agreed conditions of techtransfer, the transferee can steadily increase its technical competence. (7) Fiercely Focus on the UTILIZATION of the Exploding Multime‐dia Content: To make IT win in the marketplace, the mere increase in the volume of content or the mere increase in the speed of its transmission is quite inadequate. What will make the difference is the learning that is made possible by the multimedia content and communication.

Develops an original 12‐step management of technology protocol and applies it to 51 applications which range from Du Pont’s failure in Nylon to the Single Online Trade Exchange for Auto Parts procurement by GM, Ford, Daimler‐Chrysler and Renault‐Nissan. Provides many case studies with regards to the adoption of technology and describes seven chief technology officer characteristics. Discusses common errors when companies invest in technology and considers the probabilities of success. Provides 175 questions and answers to reinforce the concepts introduced. States that this substantial journal is aimed primarily at the present and potential chief technology officer to assist their survival and success in national and international markets.

Federal attempts to stimulate technological innovation have been unsuccessful because of the application of an inappropriate policy framework that lacks conceptual and empirical knowledge of the process of technological innovation and fails to acknowledge the relationship between knowledge production, transfer, and use as equally important components of the process of knowledge diffusion. This article argues that the potential contributions of high‐speed computing and networking systems will be diminished unless empirically derived knowledge about the information‐seeking behavior of the members of the social system is incorporated into a new policy framework. Findings from the NASA/DoD Aerospace Knowledge Diffusion Research Project are presented in support of this assertion.

Universities have a long history of training students to work in industry, and in recent years the number and percentage of students, especially those trained in science and engineering, who go to work in industry has grown. Today, three-eights of all PhDs with a degree in science and engineering (S&E) work in the private sector. These placements provide a major means for universities to participate in technology transfer. Students are not only up-to-date in terms of codified knowledge; they also possess tacit knowledge that can only be transferred by face-to-face interaction. They may also have participated as research assistants or as postdocs in the development of a technology that has been licensed by the firm where they are employed. Despite the important role that alumni play in technology transfer, universities rarely track the placements of graduate students in industry. Universities do not also systematically keep information on the contributions that alums make to innovations after graduating. Moreover, few programs socialize students to think of careers in the private sector as a top choice. Instead, many programs, especially in the biomedical sciences, socialize students to aspire to research careers in academe, with industry seen as a distinct second choice. Indeed, many PhDs only take jobs in industry after failing to find an academic position after serving as a postdoc for four or five years.

This paper examines recent placements of doctoral students in industry, using the verbatim records from the Survey of Earned Doctorates (SED) for 1997–2002. An advantage of this data is that we know the name of the firm (and the location of the firm) where the individual plans to work. This permits an exploration of several interesting dimensions regarding technology transfer not explored elsewhere, such as (1) sources (in terms of universities) educating students going to industry; (2) the R&D intensity of the firms where newly trained PhDs go to work and the industrial classification of the firms; (3) the role that proximity plays in facilitating these knowledge spillovers; and (4) the degree to which universities make placements with firms licensing their technologies.

The paper also examines the amount of information that universities provide regarding the placements of their PhDs. We find that although students are ready and willing to provide information regarding work plans after graduation, universities seldom provide information on placements. We conclude with a suggestion regarding the procedures universities could follow to create and make placement data available.

The purpose of this paper is to find the specific competitive industries in emerging industries of strategic importance of each province in China in order to provide references for industrial cultivation and development.

This paper uses quantitative analysis methods on RCA and R&D efficiency.

Different provinces have specific competitive emerging industries of strategic importance. Taking biotechnology, equipment manufacturing, and new generation of information technology industry as examples, this paper finds: for the advanced equipment manufacturing industry, Shaanxi, Sichuan, Guizhou, Tianjin, Liaoning, Heilongjiang and Jiangxi provinces have obvious characteristics and relatively high R&D efficiency; for bio‐technology, Jiangsu, Henan, Jiangxi, Hunan, Zhejiang and Shandong provinces have obvious characteristics and relatively high R&D efficiency; and for the next generation of the information technology industry, Jiangsu, Guangdong, Fujian, Beijing, Tianjin and Shanghai provinces have obvious characteristics and relatively high R&D efficiency.

This study is limited by lack of industrial comprehensiveness so that more statistical data about emerging industry of strategic importance is needed for more in‐depth analysis.

The identification of specific competitive emerging industry of strategic importance of each province will give managers and policy makers train of thought for the cultivation and development of strategic emerging industry and make future policies more targeted.

The paper contributes to the research on the differentiated cultivation and development tactics of strategic emerging industry by, respectively, finding out the specific competitive emerging industries of each province in China.

A study of Korean service firms found that the level of information technology use is significantly related to the performance of the marketing function. Support was lacking only for the categories of “use of outside database” and “networking between mainframe computer and PCs.” In addition, the form of information technology use is significant in its contribution to the performance of the marketing function. This study supports the argument that benefits of information technology investment can be identified. Furthermore, there is evidence of a time lag in the payoffs from information technology, because the benefits of connectivity have not yet been realized.