Mohammad Sadeq Mohammadi; Behrooz Ghasemi; Soheil Sarmadsaeedi
Abstract
Purpose: The purpose of this research is to develop a model of export market orientation based on competitive intelligence in the era of the digital economy.
Method: This study employed a qualitative approach, utilizing grounded theory as the research method. Sampling was conducted purposefully and ...
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Purpose: The purpose of this research is to develop a model of export market orientation based on competitive intelligence in the era of the digital economy.
Method: This study employed a qualitative approach, utilizing grounded theory as the research method. Sampling was conducted purposefully and continued until theoretical saturation was achieved, involving a total of 15 managers and experts from selected exporting companies. The systematic research process comprised open coding, axial coding, and selective coding, facilitated by strategies such as analysis, questioning, comparison, reminders, schemas, and paradigms. During the coding process, revisions were made, and classifications were validated through feedback from the participants.
Findings: The findings revealed the paradigmatic pattern of export market orientation based on competitive intelligence in the era of digital economy including six main categories of causal conditions, context, phenomenon or central category, intervening conditions, strategies and the consequences. Causal conditions have three sub-categories of learning abilities promotion of customer-oriented culture, knowledge of export technology and R&D processes and identification of export market needs; background conditions include three sub-categories of competitive thinking, competitive export processes (technical evaluation) and competitive governance; intervening conditions include three sub-categories of market technical structure (new technologies), environmental uncertainty and global markets (export risks); the central phenomenon has three sub-categories of value chain (reward strategy), human resource empowerment and employee training (export intelligence); The strategies include three sub-categories of competitive value creation, development of export competitiveness and strategic evaluation of resources and competitive agility and strategic entrepreneurship; The results include three sub-categories of developing entrepreneurial activities, competitive advantage and promoting innovation and dynamic export capabilities.
Conclusion: Based on the results, successful implementation of the export market orientation model, grounded in competitive intelligence, requires managers of exporting companies to develop a deeper understanding of the export market. This can be achieved by allocating greater effort to market-oriented activities. Furthermore, by emphasizing competitive intelligence, these companies can improve the perception of their services and create a positive association with their brand in the minds of international customers.
Mohammad Satarifar; Mohammad Feghhi; Javid Bahrami; Morteza Borjloo
Abstract
Purpose: This research aimed to identify some of the existing financial frictions in the Iran's digital economy. In particular, based on cases taken from digital and knowledge-based companies, it empirically investigated the importance of the role of base volume in the liquidity of those companies' stocks ...
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Purpose: This research aimed to identify some of the existing financial frictions in the Iran's digital economy. In particular, based on cases taken from digital and knowledge-based companies, it empirically investigated the importance of the role of base volume in the liquidity of those companies' stocks in Tehran Stock Exchange.Method: To evaluate the empirical implications of applying the base volume in daily stock market practice, retrospectively a quantitative estimate of the base volume was implied by the economic model within the rules imposed by the market regulator via MATLAB software programming. Then, using the Generalized Method of Moments (GMM), the effects of the estimated base volume, percentage of free-floating share, securities turnover, and the ratio of transaction volume to base volume on Amihud index were econometrically studied for the selected companies during the period 2015-2020.Findings: The findings indicate that the applying base volume on the selected digital and knowledge-based companies has had a negative effect on the calculation of the final price and on the liquidity of studied knowledge-based companies. Also, the results of using the machine learning method (decision tree) showed a importance coefficient of 32.6% for the base volume on the Amihud index of the selected companies.Conclusion: Our results suggest that base volume as an idiosyncratic financial friction induced by Iranian stock market regulator has aggravated the illiquidity of studied digital and knowledge-based companies and thereby could have raised the financing costs for those companies. This would ultimately impede those companies’ growth prospect.
Kobra Bakhshizadeh Borj; Hamed Nasiri; Ali Akbari
Abstract
Mobile games are getting a lot of attention as a content-based sector of the digital economy. Especially considering "Free with In-App Purchase" as the mainstream business model of these games, designing the right economic structure to monetize the content of mobile games is crucial. However, there is ...
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Mobile games are getting a lot of attention as a content-based sector of the digital economy. Especially considering "Free with In-App Purchase" as the mainstream business model of these games, designing the right economic structure to monetize the content of mobile games is crucial. However, there is limited knowledge about the mechanisms of persuading users to pay for in-game content and most of the studies are merely focused on the revenue models. Due to this knowledge gap, this study attempts to aggregate the game monetization methods into a multi-level classification and focus on identifying the main content monetization mechanics of five genres: Arcade, Sport, Puzzle, Racing, and Platformer/ Runner. For this purpose, interviews were conducted by game design and economics experts about successful mobile games. As a result, a new multi-level classification for mobile games revenue models is proposed which includes monetization via selling core items, selling performance items, and providing supplementary services in addition to retailing and in-game advertising. It also became clear that monetization mechanics for each of these methods vary in different genres and change depending on the type of game. The results of this study can be useful for digital game researchers, designers, and marketeers to structure a better revenue stream.
