ABSTRACT
The fast-changing scenario related to the COVID-19 pandemic calls for firms to rapidly redefine and innovate their strategies to sustain their businesses, with research emphasizing the key roles of digital technologies and servitization. We aim to enrich the theoretical debate on this matter by assessing how small and medium-sized enterprises (SMEs) achieve product innovation under time constraints by leveraging two specific technology groups (information and communication technologies [ICT] and Industry 4.0 data-processing technologies) and servitization. The research is based on a mixed-method approach consisting of an original survey completed by 257 Italian SMEs (grounded on a previous qualitative study about such SMEs' behaviors during the first Italian lockdown), followed by in-depth interviews with the owners and/or managers of the eight SMEs that participated in the survey. The results show a positive relationship between the increased use of digital technologies (ICT and Industry 4.0 data-processing technologies) during the pandemic with servitization and, in turn, with product innovation. Specifically, the increased use of ICT during the pandemic had a direct positive effect on product innovation, while Industry 4.0 data-processing technologies affected product innovation only through the full mediation of servitization. The qualitative study allowed us to highlight how the different kinds of digital technologies supported SMEs' innovation (servitization and product innovation) during the pandemic. The theoretical and practical contributions of this study are discussed.
ABSTRACT
INTRODUCTION: Before the approval of any Intensity Modulated Radiation Therapy or Volumetric Modulated Arc Therapy treatment plan, quality assurance (QA) tests are needed to reveal potential errors such as an inaccurate calculation of the dose distribution, the failure of the record-and-verify system, or the delivery system of the linear accelerator. Currently, the method adopted to compare the measured dose distribution with the treatment planning system TPS calculated dose distribution is gamma analysis. However, gamma analysis has been shown to be ineffective for the clinical evaluation of treatment plans. We proposed and tested a new method (the isodose structures method) alternative to gamma analysis. METHOD: Different errors were introduced in 33 error-free Head and Neck plans. The modified plans were recalculated using TPS software and the dose distributions obtained were compared to those of the original (error-free) plans. The comparison was performed using gamma analysis and the new method. The target was to calculate overall and organ-specific gamma passing rates as well as the overlapping ratio (OR) and volume ratio (VR) factors of the isodose structures method for each error-included plan. RESULTS: Eight of the 33 plans passed both the gamma analysis and the isodose structures (IS) analysis, ten plans did not pass either of them, while 13 plans which did not pass the IS analysis, passed the gamma analysis. Two plans which did not pass gamma, passed IS analysis. Furthermore, Dose Volume Histogram (DVH) metrics could not detect the low agreement between the dose distributions of two error-free plans and the respective modified plans. In this case, the IS analysis also allowed us to detect clinically meaningful differences between measured and TPS dose distributions. CONCLUSIONS: The IS method analysis clearly showed a high efficiency in detecting clinically relevant differences between TPS and measured dose distributions not seen in gamma analysis and in DVH-based metrics. Therefore, IS analysis proved to be a valid tool, alternative to gamma analysis for dose comparison in patient-specific QA test.
