## 4 Results  
### Analysis of the Spread of IoT Tools and Solutions  
The survey looked at the prevalence of IoT tools and solutions among Hungarian companies, exploring their future plans and the factors which hinder them. The tools and solutions surveyed in the questionnaire included sensors, RFIDs, cloud storage, large data analytics, CPSs, CPPSs, robot arms, AGVs (Automatic Guided Vehicle) and other smart devices, as well as smart products. The first question was \"Please indicate whether your company is using the following tools and solutions?\" Table 2 shows that CPS is the most widely used tool (67.4%), especially in production (53.5%), and it can also build on data analysis (62.8%). In spite of the high rate of CPS use--and what is somewhat contradictory--the integration of sensors and RFIDs is relatively unusual. With these technologies, large companies are leading, with 18 of the 24 responding large companies using CPS, 15 using CPPS, and 15 using big data analyses. As far as industry sectors are concerned, CPS, CPPS, sensors, robotic arms and cloud storage are most common in the mechanical engineering industry, while in the rest of the industrial sector they occur on an ad hoc basis. This is also in line with international trends, where among the leading companies of the fourth industrial revolution, automotive industry companies are the most prominent. In the questionnaire, the following questions were raised in order to identify the benefits of introducing the tools listed in Question 1. Their utility was evaluated on a scale of 1 to 5. The questions were the following (numbered on the questionnaire from Q1 to Q7):  
1. The efficiency of the company's internal logistic processes (higher level of logistic service) (Q1). 2. The efficiency of processes with the ordering partner in the supply chain (Q2). 3. The efficiency of processes with the supplier partner in the supply chain (Q3). 4. Cooperation between certain functions of the company (e.g., marketing, finance, logistics) (Q4). 5. Market performance of the company (e.g., ensuring greater market share (Q5). 6. Financial performance of the company (Q6). 7. Competitiveness of the company (Q7). Essentially, sophisticated methods are needed to analyze the ways in which we can estimate the usefulness of IoT tools in terms of the increased logistics service level, the efficiency of the processes of \begin{table}
\begin{tabular}{c c c} \hline
**Tool** & **Prevalence in the Sample** & **Number of Observations** \\ \hline CPS & 67.4\% & 28 \\ Big data analytics & 62.8\% & 26 \\ CPPS & 53.5\% & 22 \\ Cloud & 32.6\% & 14 \\ Sensors & 30.2\% & 12 \\ Robot arms & 23.3\% & 10 \\ RFIDs & 14\% & 6 \\ Smart tools & 9.3\% & 4 \\ Smart products & 7\% & 3 \\ AGV & 2.3\% & 1 \\ \hline \end{tabular} Source: Authors’ own research, 2017.  
\end{table} 
Table 2: Prevalence of Internet of Things (IoT) devices and solutions (\(N=43\)). the business partners, cooperation among certain logistics functions, financial and market performance, and the competitiveness of firms. Therefore, independent sample \(t\)-tests are used to determine whether those companies applying one of the IoT tools tend to estimate their utility more highly than firms without them. Here, as the methodology is assumed, the utility responses are normalized. According to our results (Tables 3 and 4) a significant difference appeared between the two samples examined, in which those logistics companies applying IoT tools are proven to be more efficient and have better performance. In the case of CPS and CPPS, firms seemed to have a higher level of logistics service, more efficient processes with their partners, better cooperation among certain logistics functions, and higher financial and market performance and competitiveness. When using big data, we found a higher level of service, efficient logistics processes and greater competitiveness. In other cases, we found no substantial differences among the mean differences. Nevertheless, this study has its limitations which also need to be emphasized.