Different models have been proposed by scholars and practitioners for the formulation (or formation) of a technology strategy at the level of firm. But, companies may find it difficult to select and exploit the appropriate one which fits their context (internal and external) contexts. This paper reviews the most familiar models and frameworks for a technology strategy elaboratied by Porter, McKinsey, Little, Ford and Saren, Chiesa, Burgelman et al. and Hax and Majluf; their characteristics, limits and applicability are discussed in order to facilitate this choice. These models are evaluated using a process-based approach and according to De Wit and Meyer’s point of view, on the basis of the process of strategy formulation or formation they propose and their expected outputs. Finally, a taxonomy of reviewed models is presented according to the school of thought they follow (positioning vs. resource-based and rational vs. incremental) as well as their understanding of the technology strategy concept.

In order to achieve food security, timely, accurate and repeatable monitoring the cultivated areas is necessary. In this regard, the present research aimed to improving accuracy of separation the crops cultivated area in the northeastern region of Ahvaz. To achieve the research goal, based on the available data, three groups of time series combination were created. The first group includes the combination of Sentinel 1 and 2 time series along with the NDVI index for the entire period, the second group of Sentinel 1 and 2 time series combinations based on the peak greenness and the third group were single images of Sentinel 1 and 2 in the peak greenness period. Then, images were classified using ML and SVM algorithms. Finally, crops cultivated area maps were prepared. the accuracy of the obtained results was evaluated using overal accuracy indices and Kappa coefficient. Based on the obtained results, it was found that the combination of the time series of Sentinel 1 and 2 images along with the NDVI index for the entire period (Combination No. 3) using the SVM method to extract the cultivated areas of the study area has the highest overall accuracy and Kappa coefficient, which is 91.22 and 0.89 percent respectively. Also, the obtained results indicated that the SVM algorithm has the highest overall accuracy and kappa coefficient for time series combinations, and for single image methods, the ML algorithm has the highest overall accuracy and kappa coefficient. Based on the findings, it is concluded that the combination of the time series of Sentinel 2 images and the SVM template for extracting cultivated areas have high accuracy compared to the single image method, and combining the VH polarization of Sentinel 1 to the time series of Sentinel 2 improved the accuracy about 5%.

Objective: In recent years, industries worldwide have been striving to adopt a groundbreaking accomplishment of the fourth industrial revolution known as smart manufacturing. This advanced manufacturing system is based on Industry 4. 0 technologies to improve systems' reliability, efficiency, and productivity. To have the highest level of performance and success, organizations need to pay constant attention to some variables and conditions, which are called Critical Success Factors (CSFs). Critical Success Factors play a significant role in all projects. Implementing smart manufacturing requires the identification of Critical Success Factors to be implemented effectively. Managers need to know the relationship between components of technology and the critical success factors, as well as the stakeholders who are involved or exert influence over these components. Therefore, the purpose of this study is to collect the Critical Success Factors of smart manufacturing implementation and also to determine the Critical Success Factors' relationship with components of technology and stakeholders of organizations, based on the extant research. Methods: Collecting all the Critical Success Factors will be possible through a comprehensive and systematic literature review. In a systematic literature review, in addition to answering research questions, gaps in a field can be identified and introduced to researchers. To conduct a systematic literature review in this study, keywords were first selected based on the research objectives and questions. Then, articles were collected by searching selected databases. After collecting the articles, relevant articles were identified according to the selected criteria. Finally, the research questions were answered by using the selected related articles. In addition to answering the research questions, the citation analysis of the selected articles was also done. Results: In this study, 62 relevant research studies were identified. Through the examination of the selected research, 22 critical success factors were recognized. These factors were further classified into the domains of Technology-Organization Environment (TOE Model). By conducting a thorough analysis of the content in the selected studies, the interconnections between the critical success factors, stakeholders, and components of technology were thoroughly investigated. Conclusion: The findings of this study can provide valuable assistance to researchers in gaining insights into existing gaps and addressing them appropriately. Moreover, the research outcomes can prove beneficial to managers as they endeavor to implement intelligent production methods. By effectively harnessing the identified critical success factors, managers can ensure that their endeavors are impactful and successful. This study offers a comprehensive understanding of the crucial factors that contribute to success in the chosen domain. It serves as a guide for future research endeavors and provides actionable insights for practitioners aiming to optimize their strategies. The study underscores the importance of considering stakeholder engagement and technological aspects in conjunction with organizational structures