Akbar Zahediyan Nezhad; Mashallah Valikhani; Alireza Shirvani Jouzdani
Abstract
Purpose: The purpose of this research is to design a model for evaluating digital innovation and transformation in startup business models.Method: The methodology of this reseatch is descriptive-exploratory and employs a qualitative approach. The thematic analysis was employed to study digital innovation ...
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Purpose: The purpose of this research is to design a model for evaluating digital innovation and transformation in startup business models.Method: The methodology of this reseatch is descriptive-exploratory and employs a qualitative approach. The thematic analysis was employed to study digital innovation and transformation in startup business models. The participants in this research were academic and industrial experts with a background in research and executive work in lean startups. Initially, a purposive sampling method was used to select the samples, and this was later extended using the snowball method. Ultimately, the researcher conducted 14 expert interviews to collect data. The data obtained from the interviews were reviewed and analyzed using coding based on theme analysis. Initially, codes were extracted from the text of the interviews. These codes were aggregated into more general codes, which were further studied and integrated into components. From these components, relevant dimensions were proposed, leading to the presentation of a model based on these dimensions and extracted components.Findings: The results indicate that the digital Innovation and transformation evaluation model for startup business models includes six main dimensions and 19 sub-themes. The proposed model consists of the following dimensions: "monitoring and analysis of market needs" with three components, "evaluation of product development costs" with three components, "digital innovation and transformation in the business model" with four components, "coordination and integration inside and outside the organization" with two components, "evaluation of learning ability and absorption of organizational knowledge" with three components, and "organizational resources and capacities" with four components.Conclusion: Based on the research findings, it is suggested that managers in the technology field understand the importance of lean startups. The indicators in the proposed model may be considered to help prepare and empower startups to improve their products and services. Each proposed dimension can be seen as a management skill necessary for the success of lean startups. Managers may create the appropriate conditions to integrate all of company capabilities.
Soraya Lashgari; sadegh abedi; Reza Radfar; Javad Iranban
Abstract
Automotive industry particularly, commercial automotive industry, ranks as a key industry in the economic growth. The necessity of investigating the research & development(R & D) activities of digital marketing and innovation in the form of a dynamic system in automotive industry based on the ...
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Automotive industry particularly, commercial automotive industry, ranks as a key industry in the economic growth. The necessity of investigating the research & development(R & D) activities of digital marketing and innovation in the form of a dynamic system in automotive industry based on the 3 variables: empowerment of supply network, of product innovation, and of digital marketing is quite undisputed. The present research has been done with a view to identifying and evaluating the cause-and-effect interdependent relations governing the variables of R & D of digital marketing and innovation in commercial automotive industry. The research is typically applied, and has been done using the descriptive-survey method. The research community consisted of 50 experts; all with acceptable academic backgrounds and years of experience as executive managers and marketeers in the R & D of automotive industry. To analyze the data, the views of some elected experts on automotive industry, along with Delphi fuzzy and Dematel method were applied. Our findings showed that the variable “Intensity of R & D of digital marketing and innovation” has the most effect on the other variables. The variable “Empowerment of supply network” with the score of 3,25 has the largest amount of interaction with the other variables. Also, the variable “ Empowerment of R & D in digital marketing and innovation” with the score of 1,08 has the smallest amount of interaction with the other variables.
