## 2 Proposed Benchmarking Method and Objectives of the Paper  
Therefore, the agriculture domain has been identified as a paradigmatic field where the application of structured methods might benefit innovation. In this regard, the previous section has highlighted the importance of benchmarking requirements to steer new product development initiatives, their correct formulation, and the avoidance of redundant indications. The present paper primarily deals with these design-related challenges and presents a benchmarking procedure that is deemed beneficial when the designers/users are largely unaware of or lack considerable expertise in the topic they are going to tackle. Because of this \"unawareness\" condition, which mirrors authors' expertise at the beginning of the presented work, the procedure starts from an information gathering process. From a methodological viewpoint, the procedure swivels on _value curves_. Value curves (or _strategy canvas_) proposed within the blue ocean strategy (BOS) [35] are a valuable tool to visualize the main competing factors for a given industry and their level of fulfilment for each alternative proposition. Among other potential advantages, the chance of displaying competing factors and performances in a diagram supposedly help individuate redundancies; at least, it undoubtedly urges designers to limit the set of illustrated requirements to essential ones. This graphical representation has proven to be successful for diagnosing companies' current strengths and weaknesses in value delivery (e.g., in [36]). Value curves are a valuable support both a) when firms are aware of their competitive status and are willing to project their strategic moves, and b) when such awareness is not present, and the competition has to be analyzed [37]. Applications of the value curves include critical situations for requirements' elicitation, such as cases in which multiple stakeholders are involved [38] and user-centered design is adopted [39; 40]. Their use has recently surfaced in the agricultural domain too [41; 42], but the whole benchmarking procedure has not been described and the specific category of agricultural systems leveraged here (see Section 3) has not been involved. Figure 1 shows an illustrative example of value curves in which it is possible to notice:  
* _N (competing) systems_ comprehensively representing the existing solutions (or families/categories of solutions) pertaining to the domain of interest, such as an industry (e.g., kitchen furniture), a branch of services (e.g., healthcare), or an overall goal (e.g., travelling);
* _M competing factors_ being representative of the advantages/benefits that the use (or in some cases the ownership) of a technical system may engender, which are shown in succession on the horizontal axis; and
* The _level of performances_ that each competing technical system satisfies for each competing factor, shown on the vertical axis. Each system/existing solution corresponds to a single curve in the diagram; the ordinates feature the level of fulfillment of each system with respect to competing factors on abscissas. Nevertheless, supposedly because of the unsystematic methods shown in the BOS [43], the use of value curves has not made inroads in the design domain despite their possible support to benchmark requirements after those are elicited. In addition, value curves are predominantly used to show preconeceived descriptions of current competitive environments to justify strategic moves. In other words, the employment of value curves seldom follows the structured analysis of current products in terms of requirements and the level of fulfilment thereof. In this respect, the attribution of a performance level to a competing factor mirrors the formal definition of an operational design requirement according to [18; 44]. In compliance with this notice and in light of the non-shared terminology in the literature of this field, the terms that follow will be used hereinafter. Figure 1: Illustrative example of value curves.