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Over recent decades, talent agglomeration has emerged as a critical topic for scholars, businesses and government officers. Innovative ability is a core competition for high-tech talents. In China, low innovation is the bottleneck, as the high-tech industry usually cannot provide sufficient support for the continuous needs of innovative talents. To enhance the continuous support of talents, it is important to obtain the mechanisms of talent evaluation and flow in high-tech industry. Exploring the incentive factors influencing the scientific and technological personnel, adjust the layout of talents and promote the rational agglomeration. It’s significant to realize the regional economic development.

This study proposes an assessment model using the multi-criteria decision-making method of analytical hierarchy process (AHP) to determine the weights of incentive factors and a nonlinear programing model, from micro, meso and macro perspectives of individual, organizational and social incentives by adopting Maslow’s hierarchy of needs theory, Kurt Lewin’s field theory and Lee’s push-pull theory. After the literature review and interviews with 14 experts, this study produced a research framework and a pairwise comparison questionnaire. In addition, the relative quantitative weights of 3 main categories and 15 indicators are identified and ranked based on the AHP method.

The results demonstrate that the most important dimension is the individual, and the top three highest weighted factors are job satisfaction, sense of working accomplishment and interpersonal relationships. The discussion in this study showed that the proposed model is rational and acceptable to motivate high-tech innovation talent (HTIT) agglomeration for high-tech enterprises, universities, government and start-ups.

The pairwise comparison using the AHP method is limited to expert opinions, which are considered comparatively subjective. The number of incentive factors should be increased, as some indicators may have been omitted from the AHP model.

According to the results, some suggestions can be recommended to corporate executives, HR managers and government officers to attract and retain high-tech talents and further to improve industrial clusters and economic development.

This paper derives a relative ranking of importance based on the opinions of experienced HR specialists, high-tech talent, scholars and government official, and assesses the consistency of results. The ordering represents the importance of indicators and sub-indicators of two levels from respondents’ perspectives in an industry cluster background. The study, focusing on the high-tech industry in China (which is a developing country), offers a unique view, as earlier studies mainly collect data from developed countries.

An issue that is becoming yet more relevant to modern manufacturers is that of flexibility. As life cycles become shorter a manufacturing firm can easily be left with redundant stock and dated processes. In Taiwan this issue has been addressed at several levels, this case study describes one such project. A Taiwanese academic conducted a study, gaining business acceptance of a hierarchical set of theoretical flexibility factors, then rearranging these via pictorial representations of fuzzy logic-derived plane surfaces, and finally re-presenting them to business as a set of ordered propositions designed to identify the key factors contributing to flexibility. The learning points relate, first, to the empirical facts uncovered about the specific factors that have a major bearing on manufacturing flexibility. These factors are, of course, specific to Taiwan and the current environment there. Second, though, is the more enduring illustration of a mixed-method case approach; where interviews, fuzzy logic analytical methods, and pictorial representation of the fuzzy logic output all combine to give clear guidance to managers of an industrial sector under stress, and to the policy makers who exert significant control over their environment.

Establishing a performance‐oriented evaluation in public sectors is the key to successful administrations. However, because of lacking relative comparable measuring standards, it is difficult to measure the relative performance of one unit while comparing to other units with regard to the multiple criteria decision making (MCDM) of performance evaluation. This paper aims to focus on the performance ranking of research and development (R&D) projects in Taiwan's public sectors.

The algorithm in this paper is based on the concept of fuzzy set theory and the hierarchical structure analysis. The analyzing method adopts the methods of standard normal distribution, linear transformation, and fuzzy MCDM, carrying on the analysis of multiple criteria of the performance evaluation.

This paper constructs linguistic values to the subjective judgments and analyzes the ranking results of the performance evaluation with respect to 45 R&D projects of one of Taiwan's electric power companies. Thus, the paper demonstrates a successful way of evaluating R&D projects in the public sector.

In this paper, a decision algorithm based on the fuzzy set theory is proposed to solve the performance evaluation of R&D projects in public sectors. In order to solve the difficulties of measuring one unit of the relative performance of quantitative criteria comparing to the other units, the method of standard normal distribution is adopted while measuring the quantitative criteria. The concept of linguistic values and fuzzy numbers are used in this paper since they could easily be used to describe the subjective measurement of the appropriateness of alternatives and the importance weightings of criteria.

The essence of core competitiveness in an enterprise is the ability to embed knowledge into the routine work of the enterprise and to transform personal knowledge into corporate assets. The purpose of this paper is to explore this area.

This study reviews three interoperated variables of external knowledge acquisition, enterprise knowledge accumulation, and knowledge accumulation mechanism to construct a model of knowledge interoperability within firms.

This study finds that in the thin film transistor liquid crystal display (TFT‐LCD) industry, implicit knowledge collected through the interactive coordination mechanism has a significant impact on the knowledge accumulation of the enterprise, where knowledge is accumulated in real technology systems and employees’ skills. The more willing companies are to invest resources in the shaping of knowledge and the environment, the more successful they will be in transforming implicit knowledge into explicit knowledge.

This study points to a new direction of interchanging implicit and explicit knowledge within firms.

This study argues that an improved interoperability of firm‐level knowledge can mitigate problems of knowledge integration and sharing, leading to better decisions and greater partner synergies.

Knowledge transformation allows employees to share and transfer valuable experience and knowledge within the enterprise and forms a knowledge‐intensive corporate culture or work environment, creating so‐called learning‐ and innovation‐oriented enterprises.

This study provides the impetus of valuable experience and knowledge of employees to be fully shared and passed on, resulting in a corporate culture and working atmosphere that creates the so‐called learning‐oriented enterprise or innovative enterprise.

The purpose of this paper is to help interfirm-collaborating cluster (ICC) executives examine the relevance of alternative decision rules in practical business contexts. Multi-party-implemented strategies and establishing multi-lateral collaborations are necessary actions for achieving success in new product development by small and medium enterprises (SMEs). This study explores interfirm decision-making heuristics relating to industrial ICCs.

The study examines the relevancy to decision making in ICCs of heurstics such as “fast-and-frugal decision trees” (FFDTs) and “take-the-best” (TTB) to processing possibly influential decision-making cues. The study also examines simple heuristics versus the value of a “fully rational” approach to making decisions – calculating cue values, importance weights, multiplying values by weights, summing and selecting the option having the highest summed score. This study included interviewing executives of the pivotal firm in an ICC.

This study reveals a decision-making solution for shortening the time and processes required in seeking new business collaboration partners in an ICC. This study not only develops a FFDT for six decision-making modules to quickly identify potential collaboration partners, but it also constructs a decision systems analysis (DSA) flowchart to effectively shorten the decision-making process.

This study is in accordance with the general type of industrial interfirm collaboration in Taiwan. The industrial interfirm collaboration could be further divided into the types of formal, semi-formal and informal industrial interfirm collaborations.

This study argues that firms usually find it difficult to develop their own technology because of the high costs of research and development for SMEs. Therefore, firms need to collaborate with partners to maintain their competitive advantage. However, to collaborate, firms must learn to trust their collaboration partners, and the degree of collaboration also strongly depends on the degree to which they trust their collaboration partners.

This study provides the efficient models of FFDT and DSA to quickly identify potential collaboration partners and to effectively shorten decision-making processes.

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