Designing and developing the application model of IoT for export businesses

Introduction: The Internet of Things (IoT) has only recently found applications in export businesses; hence, there is still a lack of a comprehensive and elaborate view to propose with integration and cohesion on various applications of the IoT technology in export businesses. The present study aims to use grounded theory to investigate the adoption of IoT in export businesses. In the qualitative section of the research, the strategy involves grounded theory and the data gathered from research experts. The qualitative part includes interviews with experts. The corresponding statistical population consists of experts with knowledge of the research subject. In this part, sampling is conducted through the snowball technique, and interviews are continued until theoretical saturation is ensured. All the managers and experts of agricultural machinery export companies in Tehran, Iran, comprise the statistical population of the quantitative part of the research, where the Cochran formula is applied to calculate the sample size. The study uses structural equation modeling and the Smart PLS Software to test the model. The results of the grounded theory-assisted analysis show that some indicators can best be selected to design a model for the application of IoT in export businesses. They include technical infrastructure and the company's environment as categories of context, capabilities & costs as categories of causal conditions, decision-making & planning and process facilitation & acceleration as the core phenomenon categories, learning & training and marketing as categories of actions/interaction strategies, international customer inclusion as categories of intervening conditions, and performance in export businesses as categories of consequences.
Methodology: The study takes a mixed explanatory approach. In the qualitative part of the research, hermeneutic phenomenology is applied to explore the participants' lived experiences. To conduct in-depth interviews, a total number of twelve individuals were selected using the snowball sampling technique. The data analysis was performed through coding using the MAXQDA software. The descriptive-survey method is used in the quantitative part of the research. The study uses structural equation modeling and the Smart PLS Software to test the model.
Findings: As the results of the secondary coding imply, the indicators selected in designing a model for the application of IoT in export businesses include technical infrastructure and the company's environment as categories of context, capabilities & costs as categories of causal conditions, decision-making & planning and process facilitation & acceleration as the core phenomenon categories, learning & training and marketing as categories of actions/interaction strategies, international customer inclusion as categories of intervening conditions, and performance in export businesses as categories of consequences. The computations in the inter-operative structural modeling suggest that technical infrastructure and the company's environment are exogenous independent variables unaffected by any other variable in the model. The endogenous independent variable is the process facilitation and acceleration, and "international customer inclusion" and "performance" are the dependent variables. Furthermore, learning & training, and marketing are the variables that play a mediating role. The findings also demonstrate that, in agricultural machinery export companies, the desirable components are technical infrastructure, the company's environment, capabilities & costs, process facilitation and acceleration, decision-making & planning, learning & training, marketing, performance, and international customer inclusion.
Conclusion: According to the results, the indicators selected in designing a model for the application of IoT in export businesses are technical infrastructure and the company's environment as categories of context, capabilities & costs as categories of causal conditions, decision-making & planning and process facilitation & acceleration as the core phenomenon categories, learning & training and marketing as categories of actions/interaction strategies, international customer inclusion as categories of intervening conditions, and performance in export businesses as categories of consequences. The subject of capabilities & costs precisely refers to the degree of efficiency in the application of IoT in export businesses; that is, how much it costs to gain what extent of capabilities. In the case of indicators such as decision-making & planning and process facilitation and acceleration, the latter being a management indicator, if applied properly, IoT can essentially facilitate the processes, provided that careful planning is carried out and the right decisions are made regarding its adoption. Learning & training are the indicators with a potentially significant role in improved efficiency and the achievement of IoT capabilities. The proper training of managers and employers can be crucial in the technology's acceptance and operation. In this process, marketing such a technology can inspire a different feeling in customers, leading to a host of advantages in a practical sense. International customer inclusion refers to handling and facilitating customer affairs via new technologies such as IoT. Performance can undoubtedly be enhanced if all the indicators are aptly accomplished. The computations in the inter-operative structural modeling indicate that technical infrastructure and the company's environment are exogenous independent variables unaffected by any other variable in the model. The endogenous independent variable is the process facilitation and acceleration, and "international customer inclusion" and "performance" are the dependent variables. Furthermore, learning & training, and marketing are the variables that play a mediating role.