# Determinants to Adopt Industrial Internet of Things in Small and Medium-Sized Enterprises
## 1 Introduction  
Recent advancements in communication and reduced costs of IoT technologies have enhanced the adoption of IoT applications in diverse fields. Thus, manufacturing, healthcare, agriculture, and retail SMEs have considered these solutions. Small and medium-sized factories can use these technologies to enhance production quality and operational efficiency and reduce costs. A McKinsey and Company survey of over a thousand companies indicates a growing trend toward investing in digital technology: 51% expressed willingness to invest in technologies such as the IoT to gain a competitive edge, while 28% aimed to stay relevant with their industry practices [1]. Despite these benefits, approximately 58% of IoT projects in industrial settings fail, with only 12% succeeding, as reported by Software AG [2]. This high failure rate presents significant challenges for SMEs planning to adopt IIoT solutions. Identifying these challenges and emphasizing the short-term benefits and organizational changes brought by IIoT implementation is crucial, particularly in industrial settings. This study highlights factors beyond technical issues, revealing the value of implementing the IIoT. To address these challenges and factors, we conducted an evidence assessment of the related literature using keywords such as IIoT, IIoT factors, IoT determines, IoT security challenges, and IoT adoption in SME manufacturing. The collected research articles are limited to peer-reviewed published articles between 2015 and 2024. This evidence assessment helped us curate and design open-ended interview questions. The following section discusses the papers collected in this rapid literature review. SMEs encounter several significant constraints when implementing the IIoT, such as more human resources and financial limitations. SMEs' production lines often rely on reliable legacy machinery and systems. Thus, integrating the IIoT into these systems necessitates extensive modifications and retrofitting. This requires a deep understandingof the legacy machinery and systems and how to modernize them with new IoT devices and sensors. Thus, SMEs must implement the IIoT while considering how this can enhance customer production. Therefore, a customer-centric approach to adopting the IIoT can benefit the SME stakeholders in promoting long-term success for this implementation [3]. Integrating the IIoT into SMEs necessitates considering costs, seamless usage, and the need for skilled personnel. Many SMEs require support to discover suitable equipment and training for their human resources. Additionally, the technological complexity of adoption leads some SMEs to outsource and employ off-the-shelf solutions. This can be counterproductive, expensive, and limiting [4]. Moreover, the complexity of technology and the rapid and evolving landscape requires highly skilled workers, which requires collaboration between industry, academia, and government to develop education programs, equipping them with the essential knowledge and skills to use IoT systems [5; 6]. Furthermore, cybersecurity remains a critical issue that hinders SMEs' efforts to use the IIoT. Threats include data breaches or operational sabotage, which can affect productivity. To mitigate this, well-developed and robust security protocols and teams are essential for ensuring data confidentiality and system integrity for IoT systems [7]. The rise of IoT applications presents significant challenges to the 5 Vs owing to their strong connection with big data. Both small- and large-scale applications of the IoT have these issues [8]. However, in practical applications for IIoT in SMEs, these issues must be investigated when designing the IIoT application. Therefore, it is essential to address the 5 Vs of big data when adopting IIoT solutions in SMEs. Additionally, the connectivity among IoT devices is overlooked. Therefore, addressing these issues regarding connectivity from the hardware and software aspects is another factor that must be considered.