نشریه مدیریت صنعتی
سال شانزدهم شماره 52 (بهار 1403)

The success rate of a type of technology is manifested in its adoption and continued use. In this sense, the condition development, user behavior, and the factors affecting it should be identified. However, this issue has been almost neglected and most of the studies only examined the factors influencing the adoption and use of technology at a particular time. Over the last two decades, scientific research has notably focused on the adoption of theories of emerging technologies within information and industrial systems. Innovation intermediaries are organizations or bodies that act as representatives or agents in every aspect of the innovation process between two parties and are recognized as important actors that can facilitate the innovation process. The combination of these two with the embargoes governing Iran’s industrial environment, imposed with different intentions, has led this research to investigate the effect of innovation Intermediaries on the adoption of emerging technologies in the automotive industry with the moderating role of embargo restrictions.
 
This research is applied in terms of purpose and descriptive survey in terms of method. Its statistical population includes senior managers (CEO, board members, research and development managers, sales managers, and quality control managers) of Iran’s automotive industry. This paper used the probability sampling method with the available population. Considering the statistical population, 130 people were selected as a sample using Cochran’s formula. The main instrument for gathering information was a questionnaire. The reliability and validity of the research instrument were measured using composite reliability tests, factor loadings, Cronbach's alpha, convergent, and divergent validity. The data were analyzed using SmartPLS 3 and SPSS 24. A key advantage of this approach is its ability to achieve reliable results with a smaller sample size compared to Lisrel modeling. Through SmartPLS modeling, standard regression coefficients can be obtained for paths, coefficients of determination for internal variables, and index sizes for the conceptual model. It is worth mentioning that to test the hypotheses, the t-test was used to determine the validity of the relationship between the constructs.
 
The hypotheses showed that the innovation intermediaries have a significant effect on understanding the ease of use of emerging technologies, perceived usefulness, willingness to adopt emerging technologies, legal support in the adoption of emerging technologies, security concerns in the adoption of emerging technologies, cost savings of emerging technologies in the automotive industry. The F2 test results revealed that sanction restrictions act as a moderating factor in the relationship between innovation intermediaries and the adoption of emerging technologies in Iran's automotive industry.
 
This study strongly showed that innovation intermediaries could provide an effective contribution to innovation processes and the adoption of emerging technologies in automotive companies. The present study has filled a research gap by empirically verifying the relationship between innovation intermediaries and the adoption of emerging technologies in the automotive industry. Innovation intermediaries play an important role in filling the gap between emerging technologies and their successful adoption by businesses and consumers. They act as catalysts, connecting different stakeholders, providing expertise, and fostering collaboration, which in turn paves the way for the adoption of emerging technologies.

In the innovation system, actors are involved in a complex situation of formal and informal networks, both within and among subgroups. The unsteady interactions between the actors make the role of intermediaries important. Intermediary organizations in the innovation system try to assume functions based on the deficiencies in the interactions. The functions of intermediary institutions have been examined from various aspects in various articles and studies. The diversity stems from communication gaps and inherent shortcomings among the interacting parties within the innovation system. Although studies provide a list of these functions, how to guide these intermediate actors of the innovation system and determine their appropriate functions in a reflection of the characteristics of the industry is still questioned by innovation policymakers. Especially, the nature of innovation and the technological regime of the industries have substantial differences. The current research aimed to provide a comprehensive definition of the current knowledge and the classification of intermediary institutions in industries by Poit (1984) based on the definitional functions of Howells (2006) and also to create an interpretation of the existing research gaps.
 
In this study, using the Systematic Literature Review (SLR) method, all related qualitative and quantitative studies, including articles published in journals and conferences until 2022, were examined, and finally 77 articles were found and analyzed in the field of innovative intermediary institutions. To determine the scope of the study, despite determining and identifying the search keywords and the appropriate database, the quality of the journals that include the articles was evaluated. Since the scope of this study includes the relationship between the functions of mediating institutions and innovation; the two concepts of "intermediary institutions" and "innovation" were defined as the main keywords, and a wide range of synonym keywords were used to collect studies and do a comprehensive search. In the subsequent phase, criteria were established to ensure the validity and quality of the articles and to mitigate the inclusion of irrelevant studies. These criteria included: (1) studies pertaining to mediating and innovative institutions (organizations), (2) articles published exclusively in English, (3) articles featuring at least one of the selected keywords in the title, abstract, or keywords, and (4) articles published in esteemed journals indexed as Q1 and Q2.
 
The results of the analysis showed four main themes: (1) the functions of intermediary organizations in convergence with the macro trends of changes and new technological developments; (2) their functions at various levels of innovation systems, (3) mediating organizations as actors for managing knowledge-based industries, and (4) their functions in different industries are presented.
 
This study highlights the importance of understanding the nature of innovation and the technological regime of industries to define the appropriate functions of these organizations.

Given the escalating complexity of various scientific fields and the competitive nature of markets, the focus on innovation has become crucial for the survival of businesses in the industry. Industries characterized by rapid new product development often undergo shorter cycles of innovation. Mining and mineral enterprises, recognized as long-wave innovators, must not only assimilate new knowledge and technologies but also effectively incorporate them within their organizational processes. The primary aim of this research is to propose a framework aimed at enhancing the technological capabilities of enterprises with long-wave innovation through the integration of novel technological insights.

The method of this research was based on a case study of successful projects in the mining and mineral industries (as an industry with similar characteristics to industries with long-wave innovation). In this study, the analysis focuses on latecomer firms in industries characterized by long-wave innovation, with the unit of analysis being successful projects involving the integration of new technological knowledge. Therefore, an exploratory single-case study method was used. The unit of analysis was selected based on specific criteria, and ultimately, four successful projects in the mining industries were selected and analyzed. For this analysis, 12 semi-structured interviews were conducted, implemented, and coded using the content analysis method.

The findings of this study include a set of activities and initiatives identified by latecomer firms in industries with long-wave innovation in organizational (functional and managerial) and technological (product-centric and process-centric) dimensions for success in technological knowledge integration. These activities and initiatives are introduced in three main stages of identification and transfer of new technological knowledge (including three sub-sections of identifying new technological knowledge, identifying suitable knowledge sources, and transferring new technological knowledge), combining new technological knowledge with the firm's knowledge base (including three sub-sections of external new technological knowledge interpretation, external new technological knowledge sharing, and external new technological knowledge consolidation), and exploitation of new technological knowledge (including two sub-sections of implementation and reconfiguration).

This study reveals that activities such as aligning new technology with operational functions, adopting new technology at the right time to match the firm's knowledge base, maintaining equipment, evaluating product compatibility with international standards, and implementing integrated technology information systems are crucial for firms to achieve greater success in knowledge integration. This study can create opportunities for further analysis and studies for future researchers. It can also serve as a foundation for ongoing research and further studies on technological knowledge integration.

Due to the importance of innovation ecosystems in the global economic circle, the absorptive capacity concept is important in Iran, too. Sharif University of Technology is important in establishing innovation clusters, because of its scientific status, access to knowledge resources, and being close to various industries and factories. It also provides a platform for the flow of knowledge between academic and business fields.

Sharif University of Technology is a pioneer in establishing a cluster platform for start-ups and accelerators. The growth of innovation clusters is a current policy focus in many countries. This article examines and analyzes the absorption capacity of the ecosystem. The primary variable is the measurement of knowledge flows within clusters, while the ability of units to utilize these knowledge flows is another crucial factor. Knowledge flow and the capacity to leverage it are vital inputs for fostering innovative approaches within the cluster. Although the analysis of absorptive capacity has traditionally focused on individual companies without considering the geographical context and external knowledge connections, this approach has often overlooked the external role of companies. Consequently, the effectiveness of knowledge within each organization has been neglected.

In this study, In this respect, the role of technology sectors of the Sharif University Innovation Ecosystem regarding knowledge communication and their cognitive position will be explored. The absorption capacity and models of knowledge connection between technology sectors in the innovation cluster are tested by identifying and extracting the role of each sector of the innovation cluster to use the Social Network Analysis (SNA) method. As the absorptive capacity of technological fields is conducive to their innovative performance, detecting and fostering the knowledge flow between such fields ways is essential to develop the innovative platform of innovation clusters, which, in turn, aims at investigating the current situation in terms of the dimensions of absorptive capacity, namely acquisition, adaptation, transfer, and exploitation in the innovation cluster's scope and its external environment. It picks out and exploits the cognitive stance of every field of technology based on the communication of knowledge. Thus, it will be spotting the input to everyone and the output from it, the types of communication, and the types of knowledge interactions with the outside entities. All these interactions result in roles such as technology gatekeepers, stars, and isolates.

The absorption capacity model has been identified by extracting the role of each technology field from within and outside the cluster utilizing the social network analysis method by computing the degree of knowledge input, output, and intermediateness. Through expert opinions and a literature review, the improvement solutions of the knowledge network have been identified and are presented as part of a transition mechanism to enhance the condition.

This study focuses on designing a digital transformation model for the offshore oil and gas industry in Iran to be utilized in the strategic planning and policy-making process in the industry. While applying digital achievements and novelties in the oil and gas industry is not new, employing digital transformation in this sector is relatively new. Digital transformation, when implemented in the Iranian offshore oil and gas industry, helps the sector become a world leader, therefore benefiting from all the benefits that come along with digital achievements.
 
This research adopts a qualitative approach and utilizes the grounded theory research strategy. The data gathered from interviews with industry experts and documentation and reports concerning digital transformation, especially in the oil and gas industry, helped the researchers construct a comprehensive model. Through the grounded theory approach, the study could design a model of digital transformation in the offshore oil and gas industry of Iran, including six main elements: phenomenon-centered, consequences, causal conditions, contextual conditions, intervening conditions, and strategies.
 
One of the most notable instances of phenomenon-based digital transformation in the offshore oil and gas industry involves using digital technology tools for data-driven decision-making, consistency in industry decisions, and improving operational efficiency and productivity of personnel and equipment. Furthermore, among the most effective strategies to achieve this goal at the organizational level, stand cooperation with various bodies such as reputable information technology and communications companies, universities, and active startups in the digital technology sector. Also, promoting an organizational culture based on the adoption of digital technologies at industry and national levels via establishing stringent environmental and safety regulations for personnel who work on offshore platforms and supporting investment in digital transformation in the oil and gas industry can help with reaching the set targets.
 
The key consequences of digital transformation in the offshore oil and gas industry at the organizational level include increased efficiency in organizations active in the offshore oil and gas industry, increased accuracy and speed in decision-making based on data analysis, and the possibility of proactive, targeted maintenance and cost-saving in organizations. Digital transformation in this industry can lead to consequences such as increased oil recovery factor from offshore oil reservoirs, reduced environmental risks in marine environments, and improved performance in the offshore oil and gas industry at the industry and national levels.

The current research was conducted to design and model digital transformation based on the fourth-generation industrial revolution in Iran Khodro Company. In this regard, the main question focuses on identifying the factors that impact the design and modeling of digital transformation, rooted in the fourth-generation industrial revolution, and exploring the pattern of causal relationships among these factors in Iran Khodro. 

This study adopts an applied-developmental approach in terms of its purpose, utilizes a descriptive survey method for data collection, and employs a mixed data analysis method. The community of participants in the qualitative section comprised of experts, policymakers, academics, managers of knowledge-based companies, and senior managers of Iran Khodro Company. Sampling was done in a targeted way and theoretical saturation was achieved with 15 people. The statistical population for the quantitative part comprised experts from Iran Khodro Company, estimated to be 172 individuals using Cochran's formula. The required sample volume was provided by a simple random sampling method. A semi-structured interview and a researcher-made questionnaire were used to collect data. The underlying categories of digital transformation in Iran Khodro Company were identified by the grounded theory method and the final model was validated by the partial least squares method. Qualitative data analysis was conducted using Maxqda software, while the quantitative analysis was performed using Smart PLS.

To explain the digital transformation model based on the fourth-generation industrial revolution in Iran Khodro company, semi-structured expert interviews were conducted with marketing professors and managers of Iran Khodro company. At this stage, before the start of the interview, six open questions were considered and during the interview process, new questions were also raised as expected. To get familiar with the depth and scope of the content of the data, repeated and active reading of the data (searching for meanings and patterns) were done. The results of the interviews were extracted using the grounded theory method based on the theory of Strauss and Corbin and by open, central, and selective coding. In the open coding stage, 256 codes were first identified, duplicate codes were removed and synonyms were combined, and finally 58 open codes were identified. During the central coding stage, the initial 58 codes were categorized into 10 classes, and in the selective coding stage, these 10 classes were further condensed into six main classes. In the process of theorizing the database, after collecting, analyzing, and interpreting the data, the next step is to present the model, draw conclusions, and summarize the research. By examining the current situation, the obtained data were classified into six main categories. Professors and experts contributed their perspectives, leading to the utilization of 58 indicators to elucidate the digital transformation model rooted in the fourth-generation industrial revolution at Iran Khodro Company, drawn from all indicators derived through qualitative analysis of interview content.

Based on the research paradigm model, it was determined that digital infrastructure, digital leadership, digital human resources, and digital marketing affect digital transformation in Iran Khodro Company. The fourth industrial revolution provides the necessary platform and the competitiveness of Iran Khodro plays an intervening role. Finally, the digital strategy of Iran Khodro Company leads to the financial and non-financial performance of the company.