Driving Agricultural Transformation: Unraveling Key Factors Shaping IoT Adoption in Smart Farming with Empirical Insights
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6.1. Key Findings
Analysis of the research hypotheses indicated that IoT adoption in agricultural industries was affected by relative advantages, compatibility, technological competencies, and costs from the technological dimension, technical knowledge, top management support, organizational preparedness from the organizational dimension, and competitive pressures and governmental support from the environmental dimension. Nevertheless, the size of the organization, complexity, and information intensity had no impact on IoT adoption. The following points can be discussed according to the research results. First, the adoption of IoT is positively affected by relative advantages, as shown in a considerable number of prior studies [30,68,75]. Accordingly, IoT advantages contribute significantly to deciding on the adoption of this novel production approach. Considering IoT, innovation is seen as bringing relative advantages from the perspective of automation, effectiveness, immediate data availability, and saving costs [80].
Furthermore, the present study showed significant effects of compatibility on the adoption of IoT, which is consistent with the findings obtained in the relevant literature, confirming that perceived compatibility of innovations affects their adoption positively [36,81]. Thus, IoT is regarded in line with the current values, demands, and previous experiences of the probable adopters. Overall, the application of a form of IT is usually more convenient if higher degrees of technological compatibility are offered. As the empirical results show, technological competencies affected the adoption of IoT positively. Technological resources have been systematically regarded as a significant contributing factor in the success of adopting information systems [82]. As Jaafar et al. [83] have stated, higher rates of managerial as well as technical skills will lead to higher effectiveness in technological preparedness and support. Meantime, Lin and Lee [84] have pointed out that organizations having staff with the required skills and technical knowledge will potentially have more successful development of e-business applications. Moreover, [85] indicated that technological competencies have significant contributions in e-business applications. Consequently, the implementation of IoT applications needs novel IT skills and components, along with adaptation of the available information systems. Therefore, it is argued that higher levels of technological competencies lead to more favorable conditions for the adoption of IoT, while a lack of these competencies is supposed to prevent IoT adoption.
According to the results, costs had negative effects on the adoption of IoT in the agricultural sector. Perceived costs refer to all kinds of expenses that organizations need to pay to adopt novel technologies, including hardware, software, and system integration [86]. Prior research has considered this factor and concluded that it is one of the primary drivers that influence organizational willingness toward IoT adoption [26,87,88].
Based on the findings, technological knowledge affected the adoption of IoT significantly. This finding is consistent with the results of Shi and Yan [31] according to whom technical knowledge affects the adoption of RFID positively in the distribution industries related to agricultural products. As Cicibas and Yildirim [89] have stated, technical knowledge is important for the decision-makers in the adoption processes. Kleinveld and Janssen [90] also indicated that technical knowledge relevant to business fields and performance contributes significantly to the IT departments and is considered one of the central capabilities in the coordination of sourced IT functions. In addition, Priyadarshinee et al. [91] mentioned that organizations that have been previously successful in the implementation of information technologies will benefit from better technical knowledge, fostering skills to implement novel IT solutions and developing a more in-depth perception of the economy as well as organizational effects of the novel IT. Consequently, the present paper assumes that technical knowledge planning is necessary for the adoption of IoT so that the risks of adopting innovations are decreased and special production systems can be operated at competitive levels, which will in turn lead to the improvement of operational capabilities.
This paper indicated that top management support and adoption of IoT were positively associated. This result is consistent with [73,81]. In addition, Reyes et al. [56] also referred to the fact that higher levels of managerial support result in higher levels of RFID adoption. Thus, this factor contributed critically to the adoption of IoT because it can affect the integration of services, resource sharing, and re-engineering procedures [92]. Besides, as Wang and Wang [93] stated, with no support and assistance from the executive managers, the organization would show more resistance against the adoption of IoT. In this regard, top management support can ensure the appropriate allocation of the necessary financial resources to implement the recent technologies successfully across organizations.
Organizational preparedness affected the adoption of IoT significantly. This is in line with previous studies on the implementation of IT innovations [44,94,95]. Accordingly, the establishment of appropriate organizational preparedness seems necessary in the process of recent programs, methods, or policy implementation across the organization. Moreover, Iacovou et al. [96] found that organizations that are more ready to adopt electronic data interchange face a higher possibility of adoption and would benefit more than those that are less ready. As a result, with no appropriate technological as well as financial resources, organizations are not capable of adopting IoT.
Competitive pressures affected the adoption of IoT positively and significantly. This is in line with the findings of previous literature relevant to innovative technologies’ adoption [31,73,93]. According to the results obtained in this paper, competitive pressures imposed by competitors and other industries result in organizational innovation. As was found in the study, intense competitive conditions lead organizations toward technology adoption to remain competitive, since they think that IoT adoption helps in these competitions.
The present paper also indicated that governmental support and adoption of IoT were positively associated. This is both reasonable and in line with the previous studies [97,98]. The government contributes significantly to the support for organizations to adopt new technologies regarding regulations as well as initiatives in technologically developing countries [97]. Besides, the government’s understanding and planning may have direct or indirect impacts on the expansion of IT/IS and accelerate technology adoption [99].
Surprisingly, the technological dimension’s complexity did not have significant effects on the adoption of IoT in an agricultural context. The complexity of IoT adoption is associated with immature IoT technologies, lack of common standards, and difficult integration of this technology with the current organizational information systems as well as business processes. Based on Zhong et al. [100], the broad scope of IoT devices makes the technology more complex across the selection of the product and planning. Thus, complex IoT implementation contributes as a significant inhibitor of its adoption.
As indicated, information intensity was not a significant predicting factor in the adoption of IoT. This finding is consistent with the findings of Wang et al. [36], according to whom information intensity inhibited the adoption of RFID. Yap [101] stated that organizations with higher levels of information intensity will face a higher possibility of new IT adoption compared to organizations with lower levels of information intensity. Based on Lim Junn [102], businesses in different areas typically indicate a variety of information processing requirements, while higher levels of information intensity result in a higher possibility of IoT adoption compared to businesses with lower levels of information intensity. In other words, agricultural organizations in Malaysia need higher levels of information to adopt IoT and enhance their information processing capabilities, supporting the information processing perspective.
Eventually, it was found that the size of the organization does not affect its decision toward the adoption of IoT significantly or directly. This is in line with the results of Arnold and Voigt [30], who investigated the determining factors of IoT adoption in Germany’s manufacturing industries and concluded that organizational size was not a significant predicting element in the adoption of IoT. However, it is interesting to note that in prior research on technology adoption, this factor had been regarded as a significant determinant [63,103].
6.2. Theoretical Implications
IoT represents an era of disruptive technologies that offer both advantages and disadvantages to organizations. However, its adoption has not been widespread across organizations, necessitating a deeper understanding, particularly in the agricultural sector [23]. Hence, comprehending the determining factors of IoT adoption in these industries is essential. The “Technology-Organization-Environment” (TOE) framework has been utilized in previous research to identify technology adoption in various contexts. However, IoT adoption in the agricultural industries of Malaysia has not been explored using this framework. Thus, the present study undertook the development and validation of a research model, applying the TOE framework, to investigate the impacts of nine contextual constructs on IoT adoption in agricultural industries. This research contributes to the relevant literature in the following ways:
This paper presents significant results and insights into the factors affecting IoT adoption in an agricultural context. Technological, organizational, and environmental conditions determine whether organizations employ IoT in the agricultural field. Nine factors, namely relative advantages, compatibility, technological competencies, costs, technical knowledge, top management support, organizational preparedness, competitive pressures, and governmental support, were found to be significant in influencing IoT adoption. Governmental support emerged as the most significant factor in the adoption of IoT technology in Malaysian agricultural industries, followed by compatibility as the second influencing factor.
Moreover, this paper provides empirical validation affirming the feasibility and effectiveness of TOE frameworks in understanding IoT adoption within an organizational context. IoT adoption decisions are influenced by technological dimensions on the one hand and organizational and environmental factors on the other. The paper also investigates two significant predictive factors, governmental support, and compatibility, which have rarely been examined in prior research on IoT adoption.
6.3. Practical Implications
The integration of Internet of Things (IoT) technology in agriculture holds immense potential to transform farming practices, promoting sustainability, diversification, and high yields while minimizing environmental impact. IoT sensors and devices enable precision agriculture, allowing farmers to monitor crop health and conditions in real time. This data-driven approach optimizes resource use, such as water or fertilizer, minimizing waste and reducing costs. By tailoring practices to specific crop varieties, climates, and soil conditions, IoT fosters diversification, promoting biodiversity and making agricultural systems more resilient. Furthermore, IoT-enabled supply chains increase efficiency, match diverse crop distribution with consumer demand, and reduce food waste. This combination of data-driven decision-making, resource efficiency, and optimized production ensures high agricultural yields without compromising long-term sustainability, making IoT a key tool for resilient and adaptable farming in the face of global challenges.
This paper offers vendors and managers a reference framework to analyze organizational conditions before embarking on IoT adoption, considering key factors affecting adoption and assimilation. The suggested model can be adopted in developing strategies aimed at improving an organization’s readiness to use innovations, with a focus on overall organizational outcomes. Strategies can be devised to support the successful adoption of innovations in agricultural organizations concerning IoT.
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