ABSTRACT
To compete with the speedy revolution of high technological innovation and restarted economy for the post-COVID-19 period in China, governments and organizations should be active in attracting high-tech talent to enhance independent and indigenous R&D capability. Talent agglomeration effectiveness is the strongest endogenous force pushing competitiveness for regional economy and industrial development. Due to the complexity of high-tech talent agglomeration, there are still considerable gaps to evaluate the incentive factors. This study evaluates the influential indicator system by using a hybrid fuzzy set theory extended Analytic Hierarchy Process (AHP) approach for proximity to reality from individual, organizational and environmental dimensions. The statistical analysis is adopted to verify the results of fuzzy AHP analysis. This research explores the founding that individual incentives are more important than environmental factors, and environmental incentives are more influential than organizational incentives. Job satisfaction, welfare system, and geographical location are the highest ranking factors. High-tech start-ups should give priority to combine geographical location with political support to reserve site selection or firm relocation for a great effectiveness of high-tech talent agglomeration. © 2022 Elsevier Ltd
ABSTRACT
Background: In the current era, innovation has become the basis for the success of all industries. In reality, fast innovation facilitated by rapidly changing technological discoveries is critical to global economic progress. Aim: The primary goal of this article is to examine the effect of knowledge exchange and development of supervisory support, trust, training, information technology, and industrial cluster resources on innovation capabilities in the dairy sector of Pakistan. Setting: From a total of 520 small and medium enterprise (SMEs) dairy farms, 227 owners and managers were carefully chosen to participate in the survey. Method: The current study's research framework was based on the resources and diffusion of innovation perspective theories. The data were gathered from dairy farm owners and managers in Punjab, Pakistan. SmartPLS-SEM was used to examine the multivariate connection among the variables. Results: The current research finds that training and development, supervisory assistance, and industrial cluster resources strongly influence knowledge sharing. Furthermore, trust has a favourable influence on innovative capabilities. However, the mediation effect of knowledge sharing (KS) did not support information technology (IT) training and development (T&D) and innovative capabilities (IC). Conclusion: According to findings in the study, T&D as a form of learning connect employees through the sharing of new ideas, allowing the business to improve and the concept to be modified. This study found that supervisory assistance significantly impacts innovative capabilities and knowledge sharing. © 2023. The Authors. Licensee: AOSIS.
ABSTRACT
The continuous transfer of knowledge within an industrial cluster is a key element for the cluster to maintain its long-term competitiveness. In recent years, various shocks have occurred frequently, and issues related to the resilience of regional economies and industrial clusters have attracted attention. These shocks may also hinder the transfer of knowledge within industrial clusters, thereby limiting the development of industrial clusters. However, most of the previous studies have focused on economic performance, and little attention has been paid to how knowledge exchanges within the firms in cluster are affected by shocks. Therefore, this study adopted a resilience perspective, examined the evolution of innovation modes and proximity within industrial clusters, and constructed a four-quadrant analytical framework consisting of two types of proximity and two types of innovation modes, respectively. We attempted to examine whether shocks cause the shift of innovation modes and proximity in the four-quadrant analytical framework to fill the aforementioned gap. In order to further explored its connotation and make future policy advice more valuable, this study used the concept of life cycle development of clusters to analyze evolution. We took the Hsinchu Science Park as the research object, and used the global financial crisis in 2008 and the Covid-19 in 2020 as the shocks to compare the change of innovation modes and proximity at different life cycle stage. © 2021, Chung Hua University. All rights reserved.
ABSTRACT
The innovation and development practices of the pharmaceutical industry are of great importance for the continual enhancement of public health. Industrial clusters are one of the important means by which the pharmaceutical industry can be transformed and developed, but there is a lack of research on the evolutionary path and development innovation of pharmaceutical industrial clusters. As a country with a major pharmaceutical industry, the transformation and development path of traditional pharmaceutical industrial clusters in China has important reference value for the sustainable development of the global pharmaceutical industry. Through an analysis of the evolution of traditional pharmaceutical industrial clusters in Shijiazhuang, this study explores the law of the dynamic evolution of pharmaceutical industrial clusters and the associated mechanisms. Specifically, we conclude that the evolutionary path of traditional pharmaceutical industrial clusters can be divided into the government-led pharmaceutical industrial cluster start-up stage, the government-guided pharmaceutical industrial cluster development stage, and the government-served pharmaceutical industrial cluster transformation stage. The operating mechanisms include a self-organization mechanism, an innovation-driven mechanism, and an outward associated mechanism, each of which plays different roles in the different stages of the dynamic evolution of the cluster, and the synergistic operation of the three mechanisms forms an important basis for the evolution of pharmaceutical industrial clusters. We found that the innovation development of traditional pharmaceutical industrial clusters is influenced by the synergy of the self-organization, innovation-driven, and outward associated mechanisms. The self-organization mechanism is a necessary condition for pharmaceutical industrial clusters to realize the transition from disorder to order. The innovation-driven mechanism is the core driving force for the innovative development of pharmaceutical industrial clusters. Finally, the outward associated mechanism is the main means by which pharmaceutical industrial clusters integrate into the global value chain.