Purpose The purpose of this paper is to investigate the impact of knowledge-based dynamic process capabilities (KBDPCs) on innovation performance, considering the mediator role of innovation processes in the Iranian knowledge-based high-tech companies. Design/methodology/approach Based on an in-depth review of previous studies, the indicators pertaining to the research constructs were extracted. Then, exploratory and confirmatory factor analyses were applied to identify and confirm the research constructs. Partial least squares-based structural equation modeling was used to investigate the intended relationships. Findings The results of the direct effect showed that KBDPCs have a significant positive effect on innovation performance. Further, moderation analysis demonstrated that innovation processes are moderated by the relationship between KBDPCs and innovation performance. Accordingly, the findings revealed that KBDPCs affect product innovation performance and exploratory innovation and transitional innovation increase this effect. Also, the mediator role of exploitation innovation in the relationship between KBDPCs and process innovation performance was proved. Research limitations/implications As this research was performed in the Iranian context, caution should be taken regarding the generalizability of the findings. Practical implications This paper provides a roadmap based on existing scenarios to enhance innovation performance for the surveyed-companies, in particular, and other companies, in general. Social implications The social implication of this study is to respond to the challenge of the managers of Iranian knowledge-based high-tech companies to improve innovation performance through KBDPCs and innovation processes and to grow and develop a sustainable business. Originality/value Given rare studies that have so far been conducted on the research field, this study extends the theories of KBDPCs, innovation processes and innovation performance. The constructs of the research model and relationships intended among them are also significant.
Value-Originality. Startup companies look for solutions to remove useless issues and enhance the activities offering value adding over the product/service development stage in such a way that such companies will be able to provide great products and more probabilities for success with no need to employ considerable investments from external sources. Accordingly, innovation, business intelligence, and knowledge management will contribute to the positive findings of startup companies. Objectives. Hence, the purpose of the present study was to conduct an investigation on the impact of business intelligence over the performance of startup companies according to such mediators as innovation and knowledge management. Methods. The type of this study is correlation and is also an applied and descriptive-survey work regarding objective and data gathering. Our statistical population encompassed all related experts and managers in the following Iranian startups: Pinket, Alibaba, Snapp, Filimo, IDPay, PhonePay, TapSell, and Body Spinner. Our sample was composed of 108 experts and managers in mentioned companies, who were chosen based on the cluster sampling method. Structural equation modeling with partial least squares approach was used to analyze the gathered data. Findings. Our results reveal the effectiveness of business intelligence, innovation, and knowledge management on the performance of startups and that of business intelligence on innovation and knowledge management. Ultimately, innovation and knowledge management are mediators of the relationship between business intelligence and performance of startups. Conclusion. The startup companies’ managers are strongly recommended to take advantage of innovation and knowledge management in order to enhance the performance of their businesses.
Goal: International trade and success in this field is one of the most important goals based on the profitability and reputation among different companies and organizations, in which the most important tool is optimal global and international marketing; therefore, this research aims at drawing the model of structure by the components influencing optimal global marketing. Design / Methodology / Approach: To this end, 385 experts, professionals, and scholars in this field, whose number was determined by the Cochran formula, completed a researcher-made questionnaire. In this paper used the structural equation method. Results: The results show that the application of technology, product quality, price, variety and communication (brand) are the five affecting factors on optimal global marketing. In the meantime, the product quality has the greatest effect on optimal global marketing, and with exception of the diversity which is the indirect predictor of optimal global marketing, other variables directly predict this indicator, as well as the results of fitting the model showed that the created model is an efficient and reliable tool for investigating the components affecting the identification of global optimal marketing. Limitations of the investigations: This research has been done in Iran, Naturally, it has to be validated for use elsewhere in the world, it is possible that it may not be cited elsewhere or give different results. Practical implications: Results of this study can be use to increase sales and supply rates of products Because by knowing the best marketing agents can increased the rate of supply of goods and products. Originality / Value: It has not been studied so far and the results of this article can be used all over the world.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.