Introduction

The open innovation approach underlines that firms increasingly use external knowledge and technology sources to accelerate their innovation processes (Chesbrough, 2003a, 2006). Openness builds upon the idea that a company cannot innovate in isolation, but should involve different actors to acquire resources and ideas from the external environment to keep up with the competition (Chesbrough, 2003b; Laursen & Salter, 2006). Building upon the triple helix innovation model proposed by Etzkowitz and Leydesdorff (2000), which relies on university-industry-government relations, Carayannis et al. (2012) have proposed the quadruple helix innovation model and have emphasized the importance of knowledge society for knowledge production and innovation. The fourth helix (i.e., civil society) considers the individuals as lead users, co-developers, and co-creators of innovative initiatives (Carayannis et al., 2020). From this perspective, external actors can leverage the firm’s investments in internal R&D and increase opportunities for previously disconnected knowledge and capabilities combinations (Fleming, 2001; Hargadon & Sutton, 1997; Schumpeter, 1942).

Previous literature has argued that open innovation can be explored at different levels of analysis such as firms, sectors, and individuals (West et al., 2006). In particular, open innovation platforms could be helpful for the company for the realization of a durable value-creation mechanism (De Falco et al., 2017; Hossain & Islam, 2015). Accordingly, Aquilani et al. (2016) have proposed that open innovation platforms may trigger co-creation procedures in the innovation network, by incorporating and integrating capabilities and knowledge to support innovation processes (Abbate et al., 2021).

From the customers’ perspective, the use of open innovation platforms, such as “knowledge- and value-accretive” websites based on highly interactive digital technologies and customization toolkits, increasingly allows users’ participation in the product definition. Over the past decade, indeed, many firms have involved their customers in the product development process in different ways, ranging from usability groups who test product prototypes to innovation contests (Chesbrough, 2003c; Terwiesch & Ulrich, 2009). In this regard, one of the most used applications is represented by co-creation toolkits for user-driven innovation and design (e.g., Dellaert & Stremersch, 2005; Thomke & von Hippel, 2002). A relevant stream of literature has focused on the methods and tools to support the interaction between firms and customers (e.g., Thomke & von Hippel, 2002; von Hippel, 2001) for the purposes of user design (Randall et al., 2005) or self-design (Franke et al., 2010) in the context of the most advanced customization approaches. In particular, co-creation toolkits allow users to design their products online by ensuring a trial-and-error process and by providing immediate feedback on the potential result until a satisfactory solution is found. At the end of that process, the design of the product can be transferred to the company’s production system and, subsequently, delivered to the customer. Depending on the application context and on the type of toolkit, the result can be a customized product (Dellaert & Stremersch, 2005) or a co-created innovation (Dahan & Hauser, 2002).

Firm-user interaction, such as the one achieved through co-creation toolkits, can be transformed into a source of new ideas for the company (Jeppesen, 2005). Particularly in the idea generation stage, open innovation contests have emerged as a commonly used innovation practice (e.g., Bullinger et al., 2010; Hofstetter et al., 2021). Firms are increasingly proposing open innovation contests that, while favoring engagement and attachment to the brand (Batra et al., 2012; Park et al., 2010), also permit to generate new ideas that can be used for commercial purposes (Schreier et al., 2012).

In open innovation contests, creativity is a desirable outcome for companies looking for “outside the box” thinking (Leung et al., 2012) and searching for useful suggestions to boost innovation development. Previous studies on creativity support the idea that open innovation contests may favor the creativity of ideas and outputs, especially under specific conditions. According to Shalley and Oldham (1997), individuals generate more creative ideas in competitive scenarios than in non-competitive scenarios, particularly when the informational aspect of the competition outweighs the controlling aspect. Similarly, Amabile (1996) has shown that a controlled environment is harmful to creativity, whereas an informational environment is conducive to more novel outcomes. The competitive setting of an open innovation contest (e.g., forms of incentives or constraints), then, could affect users’ creativity during co-creation procedures. Research on the impact of constraints on creativity revealed that individuals’ creative performance can actually benefit from time constraints (e.g., Hennessey & Amabile, 2010; West, 2002), showing that the presence of such constraints may lead to more creative outputs (e.g., Burroughs & Mick, 2004; Moreau & Dahl, 2005). Crossing the evidence on open innovation contests as a form of co-creation and the literature on creativity constraints, it appears relevant to identify the conditions which may boost creativity in open innovations contests. As a matter of fact, previous literature has emphasized how contests can be of different types and have different winning criteria (Bullinger et al., 2010), but has not examined the joint effect of types of open innovation contests and time constraints on product creativity.

The purpose of this article is to investigate the contingencies under which open innovation contests, hosted on platforms providing co-creation interfaces, stimulate product creativity. Specifically, this paper aims to analyze how different types of contests, involving customization toolkits, interact with time constraints in determining product creativity. Moreover, this research examines the underlying process through which different types of open innovation contests contribute to output creativity under specific time constraint conditions, suggesting that design variety explains the investigated effects. The presented study contributes to increasing the current knowledge about the opportunities and challenges of collaborative innovation between firms and external actors (i.e., consumers).

To achieve these goals, we conducted an experimental study in which we manipulated the type of open innovation contest (evaluative vs. luck based) and the time constraints (absent vs. present) and measured product creativity and design variety. The results showed that evaluative contests, based on external judgments (e.g., a jury), lead to more creative outputs compared to luck-based contests, based on random draws (e.g., sweepstakes), but only in the presence of time constraints. Overall, findings support the hypotheses that open innovation contests which involve simultaneously the evaluation of external actors and the presence of time constraints increase product creativity, and that this effect is driven by design variety.

The rest of this article is organized as follows. First, we present the theoretical background by discussing the literature on customization toolkits, open innovation contests, and time constraints, and develop our conceptual model. Next, we illustrate the experimental study conducted to test the hypotheses and present the related findings. Finally, we summarize the theoretical contribution and managerial implications for firms that use co-creation platforms to acquire and integrate knowledge from external sources.

Background and Hypotheses Development

Innovation Through Customization Toolkits

In recent decades, innovative processes of companies have evolved considerably. According to the traditional approach, companies invested in basic or scientific research and then aimed to develop commercial applications from such research. Over the years, a new paradigm has emerged, suggesting that innovation can be directly driven by potential users (O’Hern & Rindfleisch, 2010; Rayna & Striukova, 2021). The acquisition of reliable need-related information that permits product developers to design the products that consumers really want is a crucial aspect of conventional market research. According to von Hippel (1998), the adoption of “user toolkits for innovation” (i.e., product customization tools) allows bypassing information acquisition for product development by directly offering to the user the tools s/he needs to customize essential parts of the product (Thomke & von Hippel, 2002; von Hippel, 2005; von Hippel & Katz, 2002).

For some time, user toolkits have been proposed by leading firms to both professional users and consumers. Nestlé has provided chefs of Mexican food with ingredients toolkits to create personalized food solutions that can simply be conveyed back and reproduced in Nestlé’s factories (von Hippel, 2001). Companies such as Adidas, Nike, and M&M’s have proposed web toolkits that enable consumers to design key features of the product by themselves. Based on such applications, many firms have started to directly include customers in the product development process in different fashions, ranging from usability groups who test product prototypes to innovation contests (Chesbrough, 2003c; Terwiesch & Ulrich, 2009). Using toolkits implicates translating need-related product development tasks from producers to users, by equipping the users with tools to carry out those development tasks (von Hippel & Katz, 2002). Then, consumers may employ customized product applications without having any specific technical knowledge (Piller et al., 2004).

Over the years, the co-creation approach in value-creation activities has become highly appreciated by all kinds of firms in different industries, and virtual customer integration is now seen as an important and cost-efficient mechanism of customization and innovation management. According to Piller et al. (2004), two main strategies have emerged: (i) mass customization (e.g., Dellaert & Stremersch, 2005; Pine, 1999); and (ii) user-driven innovation (e.g., von Hippel, 1998). Based on mass customization, products and services are made with the aim to meet individual customers’ needs, still maintaining mass production efficiency. User-driven innovation concerns customer integration in the early value chain steps of product innovation and development. In other words, consumers create customized product variants in mass customization activities, while they participate in the innovation process through user-driven innovation activities, for example, by developing new product concepts by themselves or co-developing them with the firm. In this way, manufacturers can directly take advantage of the innovativeness, experience, and insightful knowledge of users (Piller et al., 2004). In their 7-year longitudinal research project with Adidas, Fredberg and Piller (2011) have provided a concrete example of how interactive customization toolkits can be used for open innovation purposes. Another example of co-creation activity conducted on open innovation platforms includes Nike basketball shoes joint developed by using customer-contributed designs (Füller et al., 2007).

In sum, the co-creation approach involves a joint value creation process (Prahalad & Ramaswamy, 2004) and allows the integration of customers in “user design” (e.g., Randall et al., 2007) and “self-design” (e.g., Franke et al., 2010) processes. The user plays a very active role in defining the product thanks to the use of interactive and engaging tools which, in turn, feed the perception to be the designer of her/his own product. The interaction between the firm and the user (e.g., Dellaert & Stremersch, 2005; Randall et al., 2005; Thomke & von Hippel, 2002) allows companies to efficiently and quickly communicate with users and to innovate successfully. In general, consumer involvement allows companies to co-create brand identity (Essamri et al., 2019). Forms of gamification, such as contests, represent tools to co-create the brand with its customers (Nobre & Ferreira, 2017). Therefore, the co-creation approach can evolve up to co-creating brands (Payne et al., 2009). Moreover, previous research has provided evidence of gender’s impact on co-creation activities. While females tend to co-create more with brands in hedonic activities, males co-create more with brands in activities considered to be socially important (Kennedy et al., 2022).

Open Innovation Contests

The digital environment evolution has multiplied the interactive forms of contacts between firms and customers to reinforce market relationships. Importantly these forms of interaction can be transformed into a source of new ideas for the company (Coviello & Joseph, 2012). Over the past decade, several firms involved consumers in the product development process by using innovation contests (Chesbrough, 2003c; Terwiesch & Ulrich, 2009) that solicit creative solutions from consumers in the idea generation stage (Brucks & Huang, 2016). In an innovation contest, many individuals or teams are invited to propose and submit plans or prototypes to an innovating company (Terwiesch & Xu, 2008). The character of openness of the innovation contest allows users to participate in a competition with other users, with all submissions being transparent and accessible to participants (Hofstetter et al., 2021). Open innovation platforms are the most common formats of creative crowdsourcing used in the business context (Eyeka, 2017) to receive ideas and projects at reduced costs. Recent examples of open innovation platforms hosting such contests are Hyvecrowd.com, OpenIdeo.com, Crowdspring.com, or 99designs.com.

From the firm perspective, open innovation contests are proposed to stimulate engagement and attachment to the brand (Park et al., 2010), to favor brand relationship development (Batra et al., 2012), as well as to generate new ideas that can be used for commercial purposes (Piller & Walcher, 2006). The company requires a solution for an undetermined task within a certain deadline (Piller et al., 2012). In the definition of the contests, companies specify that the property of the proposed ideas belongs to the company itself. For this reason, it is preferable to offer some form of reward in order to restore fairness in the relationship. Possible forms of rewards are monetary incentives, products, experiences in the company, or simply advertising the winner on the web pages of the company (Piller et al., 2012). Previous studies on incentives to creativity have provided evidence that extrinsic, monetary rewards lead the individual to focus on self-performance (Vohs et al., 2006). Monetary incentives, indeed, induce individuals to merely attend to the given assignment with the aim to complete the performance goal (Eisenberger & Aselage, 2009; Eysenck & Eysenck, 1982). Recent evidence has clarified that creativity-contingent, monetary rewards lead to a performance focus, whereas social-recognition rewards lead to a normative focus (Mehta et al., 2017). In addition to the forms of rewards, another relevant aspect of innovation contests concerns the method of awarding the contest prizes. The winner can be determined by external actors, such as a jury or a peer-review system (Bullinger et al., 2010), or through a random draw (e.g., sweepstakes) among all contest participants (Kalra & Shi, 2010). While the former can be defined as evaluative contests, the latter is purely based on luck.

Open innovation contests may contribute to the dynamic interaction and involvement of customers with the firm in every phase of the value-creation process (Vargo & Lusch, 2004). According to Hsieh and Chang (2016), a well-designed brand contest is an important tool able to enhance consumer engagement and, then, to turn engaged consumers into intangible assets for firm innovation. An interesting example of open innovation contest is the one proposed by Kicksguide.com, a platform dedicated to basketball shoes. Creative and passionate users of basketball shoes may submit, on a monthly basis, creative ideas to the design contest of Kicksguide.com. The winning designs of the contest participate at the “Artist Series Shoe Design of the Year” and, subsequently, the website sends the creation of the winner to several shoe producers.

The Role of Constraints on Creativity

Building upon the characteristics of co-creation toolkits and open innovation contests, firms could adopt various strategies to stimulate users’ creativity during the collaborative product design stage. Creativity concerns the generation of novel and useful outcomes (e.g., ideas, products, solutions, processes—Amabile & Pratt, 2016; van Knippenberg, 2017) and is a valuable feature of co-creation outputs. Several studies have examined how consumers process information during co-creation tasks to understand which elements are able to generate more creative outcomes (Moreau & Dahl, 2005). Accordingly, in several studies, creativity has assumed the role of the dependent variable, as researchers aim to identify the determinants of creative outputs (Miceli & Raimondo, 2020).

The effect of constraints on creativity and innovation has attracted substantial interest in different fields, such as strategic management, entrepreneurship, organizational behavior, and marketing (Acar et al., 2019; Brem & Wolfram, 2014). Constraints are defined as any externally imposed factor (e.g., deadlines, regulations and rules, requirements, and resource availability) that could affect creativity and innovation (Dahl & Moreau, 2007). In the marketing literature, several contributions have provided evidence that the presence of constraints (e.g., item or temporal constraints) leads to more creative outputs (e.g., Burroughs & Mick, 2004; Moreau & Dahl, 2005). By performing a 5-year panel study, Andrews and Farris (1972) have shown that there are positive and significant relations between time pressure and scientists’ creativity. According to Baer and Oldham (2006), instead, there is a curvilinear relationship between individual time pressure and creativity, with moderate time pressure levels maximizing creativity. Other evidences have shown that, although the effects of time pressure on creativity are generally negative, creativity might be enhanced by time pressure if individuals are protected from disruptions, or if they feel engaged like in a mission (Hennessey & Amabile, 2010). According to Ward (1994), if an individual is asked to complete a task without any kind of constraint, the individual will adopt a strategy called path of least resistance (POLR). Based on this strategy, individuals invoke the first solution that comes to their minds, typically related to some pre-existing paths, and then begin to recreate them. By using the POLR approach, individuals decrease their cognitive effort but, consequently, will often fail to develop a sufficiently creative solution to the task. On the contrary, if individuals fail to collect all elements and information to recreate such solutions, the problem is faced by posing maximum cognitive effort (Ward, 1994). Through a series of experimental studies, Moreau and Dahl (2005) have provided evidence that the implementation of a series of input and time constraints allows overcoming the POLR strategy, showing that the presence of input constraints (i.e., less available items to create a new product) increases the creativity of the output if time constraints are not present simultaneously. In the presence of both types of constraints (i.e., input and time constraints), individuals fail to generate a sufficiently creative solution. Previously, Burroughs and Mick (2004) have demonstrated the moderating role of time constraints on the effects of consumers’ locus of control and involvement on the creativity of solutions. In a problem-solving task with less available time, the positive effects of consumers’ locus of control and involvement on creative solutions increase. Moreover, input constraints (e.g., lower available quantity of a shoe cleaner) increase the creativity of solutions (Burroughs & Mick, 2004).

Research Hypotheses and Theoretical Framework

This paper focuses on the effects of different types of open innovation contests on output creativity and on the conditions that allow increasing creativity. Keeping constant the extrinsic motivation in participating in the contest (i.e., the prize or the award), the company can propose different evaluation modalities defining different types of open innovation contests (Bullinger et al., 2010). An open innovation contest may involve a competition based on either the evaluation of external actors (e.g., a jury) or a random draw (e.g., sweepstakes) among all participants to determine the winner. We refer to the former as evaluative contests and to the latter as luck-based contests.

One may expect that evaluative contests can stimulate more creative outputs because participants would be motivated to impress external judges and to invest more effort to find novel solutions. However, we maintain that such effect may not hold, in general, due to potential boundaries to creativity determined by familiar—therefore, less novel—product designs that participants keep in memory and that can hamper exploration of more original solutions. In other words, the motivating effect of an evaluative contest may be dampened by a free-from-constraint elaboration that can lead toward a POLR and therefore less creative outputs. We hypothesize that the effect of the type of contest (evaluative vs. luck based) on product creativity is moderated by time constraints. Specifically, in the presence of time constraints, evaluative contests (compared to luck-based contests) may determine more creative outputs because the need to impress the evaluator is salient and the presence of constraints may prevent participants to follow a POLR approach, thus producing a double boost toward creativity. On the contrary, in the absence of time constraints, participants will not be able to overcome the path of least resistance (Ward, 1994), jeopardizing the creativity potential determined by evaluative contests and therefore dampening the effect of the type of contest on creativity. Formally:

H1:

The effect of the type of contest (evaluative vs. luck based) on product creativity is moderated by time constraints. Specifically, (a) when time constraints are present, evaluative contests will lead to more creative products than luck-based contests; (b) when time constraints are absent, the same effect will disappear.

To explain this effect, we refer to a process based on design variety. Previous research demonstrated that elements of design variety, such as the number of colors, are positively correlated to creativity assessments (Amabile, 1982). We hypothesized that, in the presence of time constraints, evaluative contests will lead participants to generate designs with a higher number of variations to impress the jury compared to luck-based contests and without experiencing the POLR. Instead, the absence of time constraints leads participants to evaluative contests (vs. luck-based contests) to recreate already seen designs with fewer color variants, thus purging the effect. Formally:

H2:

The effect of the type of contest on product creativity, moderated by time constraints, is mediated by design variety.

Figure 1 presents the theoretical framework of this study.

Fig. 1
figure 1

Conceptual model

Full size image

Empirical Evidence

Design, Task Context, and Procedure

To test the research hypotheses, we conducted a 2 (type of contest: evaluative vs. luck based) × 2 (time constraints: absent vs. present) between-subjects experimental study. Participants were 99 undergraduate students (48.5% female, Mage = 22.76, SDage = 3.32), majoring at the Department of Business Administration of a large European University, who were randomly assigned to one of the four experimental conditions. We opted for an experimental study in order to obtain evidence with high internal validity on the investigated causal effects.

Participants were invited to participate in a contest with the chance to win a customized pair of sneakers. In detail, participants in the condition of the evaluative contest were told that a commission of judges would identify the winner. In the condition of the luck-based contest, the winner would have been identified by random extraction. In both conditions, we kept constant the possibility of winning exactly the shoes designed by the participant within the task. In this way, we kept constant the motivation in the task and the level of realism in the drawing constant. In the condition with time constraints, participants had 4 min to complete the task, while in the condition without time constraints they had 20 min to complete the task. These time levels were identified through a pre-test, which showed that 4 min was enough to complete the task, but required a lot of haste in the operation. Instead, 20 min represented a time level in which all the customization operations could be completed calmly and by double checking the choices several times.

To operationalize the customization task, we used a toolkit available on the market to increase the realism of the experiment and to allow high levels of interaction with the product, keeping the task simple to complete. In detail, we opted to use the customization toolkit proposed by Nike, “Nike iD,” which was the one that offered the greatest depth of customization and the lowest operational complexity. Furthermore, our sample of undergraduate students is in the target of this product, thus increasing the engagement toward the task. Participants were asked to customize the Air Max 90 shoe model, which is a unisex product and therefore suitable for our research setting. For this model, the toolkit allowed to customize 14 separate and independent modules, allowing to obtain millions of possible combinations. In detail, the shoes were customizable in the following elements: product base (22 options), external lining (17 options), mudguard (12 options), tongue (22 options), swoosh (17 options), internal lining (13 options), laces (14 options), eyelets (26 options), mudguard (13 colors), heel counter (13 options), midsole (18 options), wedge heel (10 options), sole (13 options), and iD on the heel counter (choice between Nike logo or inserting a custom text). These options concerned the colors of the modules, the material, or other specific design elements (e.g., inserting a spray or polka dot effect). In detail, participants began to work on a model in which all modules were positioned on the default option, which was white and without design elements (see Fig. 2). Then, for each of the 14 modules, it was possible to customize according to the available options. At any time, participants had the option to go back to the previous module, to skip a module they did not want to customize, and to preview the project in real time.

Fig. 2
figure 2

The customization toolkit used in the study

Full size image

The use of a real customization toolkit prompted us to apply a series of precautionary settings to the web browser. In particular, the ability to scroll the page of toolkit page was disabled as well as the arrows on the keyboard. In this way, participants were exposed to the toolkit in the same location, without the possibility to view other parts of the page. In addition, the timer was positioned to cover the price preview of the customized product. In this way, we pursued the dual goal of providing participants with the time still available to complete the task and to prevent any possible influence of price information (see Fig. 2).

Measures

After the completion of the task, participants notified the experimenter who took note of the time actually taken to customize the shoes. Subsequently, the experimenter took three screenshots of the design created (i.e., front, side, back). After the collection, the number of colors (Mcolors = 4.15, SDcolors = 1.22) present in each product was coded by a research assistant as a measure of design variety.

Finally, three independent judges (business administration students) evaluated the screenshots of the customized products using two 7-point Likert items on the level of novelty (1 = not new at all; 7 = very new) and creativity (1 = not creative at all; 7 = very creative) of the product. For all judges, data showed a high degree of reliability (α1 = 0.90, α2 = 0.83, α3 = 0.73). Joint reliability analysis on the six ratings showed a satisfactory reliability (αtotal = 0.88). For the subsequent analyses, therefore, we used a single product creativity measure computing the average of the six creativity judgments (Mcreativity = 3.97, SDcreativity = 1.28).

Results

In the condition without time constraints, participants completed the task on average in 10 min and 52 s, while in the condition with time constraints they used on average 3 min and 55 s (t(97) = 10.94, p < 0.001). In detail, in the condition without time constraints, 46 participants out of 49 took more than 4 min, while in the condition with time constraints 43 participants out of 50 completely used the 4 min available. These data indicate that the thresholds chosen actually represent a suitable time constraint upon completion of the task. Moreover, a two-way ANOVA on the time used in the task revealed a main effect of time constraints (F(1,95) = 121.42, p < 0.001), whereas the effect of type of contest (F(1,95) = 2.21, p = 0.14) and the interaction effect (F(1,95) = 1.86, p = 0.18) were both non-significant.

A two-way ANOVA on product creativity showed a non-significant effect of type of contest (Mluck-based = 3.86, SDluck-based = 1.30; Mevaluative = 4.08, SDevaluative = 1.26; F(1,95) = 0.74, p = 0.39) and a non-significant effect of time constraints (Mconstraints absent = 3.82, SDconstraints absent = 1.32; Mconstraints present = 4.13, SDconstraints present = 1.23; F(1,95) = 1.46, p = 0.23). More important, we found a significant type of contest × time constraints interaction (F(1, 95) = 6.20, p = 0.02). Planned comparisons revealed that, when time constraints were present, an evaluative contest led to more creative outputs than a luck-based contest (Mevaluative = 4.55, SDevaluative = 0.25; Mluck-based = 3.71, SDluck-based = 0.25; F(1,95) = 5.68, p = 0.02). When time constraints were absent, instead, evaluative contests led to a similar output, in terms of creativity, compared to luck-based contests (Mevaluative = 3.62, SDevaluative = 0.25; Mluck-based = 4.03, SDluck-based = 0.25; F(1, 95) = 1.311, p = 0.25). These results provide support to H1 and are represented in Fig. 3.

Fig. 3
figure 3

The moderating role of time constraints

Full size image

Finally, we tested H2 by means of a moderated mediation model in which time constraints (0 = absent, 1 = present) moderated the path from type of contest (0 = luck based, 1 = evaluative) to design variety, and in which design variety influenced product creativity. Results showed a just significant type of contest × time constraints interaction on design variety (b = 0.92, p = 0.05). The effects of type of contest (b = 0.08, p = 0.81) and time constraints were non-significant (b =  − 0.24, p = 0.48). Design variety was positively associated with product creativity (b = 0.55, p < 0.001), while the effect of type of contest on product creativity was non-significant (b =  − 0.08, p = 0.73). These results provided evidence that, without time constraints, the type of contest → design variety → product creativity indirect effect was not significantly different from zero (IE = 0.04, 95% bootstrap CI [− 0.31; 0.40]). Instead, with time constraints, the type of contest → design variety → product creativity indirect effect was positive and significantly different from zero (IE = 0.55, 95% bootstrap CI [0.19; 1.00]). The index of moderated mediation is positive and significantly different from zero (IE = 0.51, 95% bootstrap CI [0.01; 1.09]), suggesting that the investigated indirect effect is significantly different in the two constraint conditions. These results allow to support H2.

Discussion

The results of the experimental study provide support to our theoretical framework. First, we tested H1, which predicts the moderating effect of the level of time constraints (absent vs. present) on the relationship between contest type (evaluative vs. luck based) on product creativity. By means of a two-way ANOVA and planned comparisons, we have shown that evaluative contests lead to more creative outputs only in the presence of time constraints. Second, we tested H2, which proposes the mediating role of design variety, through a moderated mediation model. The results show that in the presence of time constraints, the evaluative contest leads participants to use more colors in the definition of their products, producing, in turn, higher creativity evaluations by the judges. Considering that firms can define the contests according to different criteria (Bullinger et al., 2010), our results allow identifying a preferable combination to obtain more creative projects from consumers. Furthermore, customization toolkits, such as the one employed in our study, have the benefit of not requiring particular user technical knowledge (Piller et al., 2004), thus increasing the number of potential participants in the competition. Finally, customization toolkits offer the further advantage of being easily modulated in terms of company needs, for example, by limiting changes only to specific product parts upon which new ideas are needed.

General Discussion

The goal of this research is to investigate open innovation contests based on the use of co-creation toolkits for the generation of new ideas and creative products, providing an example of civil society involvement in the innovation process (Carayannis et al., 2021). Results of an experimental study in which we manipulated the type of contest (evaluative vs. luck based) and the presence of time constraints (absent vs. present) confirm that the effect of type of contest on product creativity is moderated by time constraints. Whereas without time constraints there is no effect of type of contest on product creativity, the presence of time constraints leads evaluative contests to generate more creative products than luck-based competitions. Moreover, results of a moderated mediation analysis suggest that this effect is explained by design variety. This second analysis clarified that with evaluative contests (vs. luck-based) and in the presence of time constraints (vs. in absence), participants generated more varied designs in terms of colors, which were evaluated as more creative by the judges.

This research contributes to the literature in two main directions. The first contribution concerns the open innovation platform literature, with a specific focus on open innovation contests. Given that many companies use contests to get new ideas from consumers (Brucks & Huang, 2016), it is essential to understand which conditions allow obtaining optimal outputs. This study, indeed, compares two types of contests (evaluative based vs. luck based), underlining the preferential role of evaluative contests in the presence of time constraints.

The second area of contribution of this research regards the literature on the effects of time constraints on creativity. The marketing literature has long clarified the positive impact of time pressure on creativity outputs (e.g., Burroughs & Mick, 2004; Moreau & Dahl, 2005). Several studies in cognitive psychology (e.g., Costello & Keane, 2000; Stokes, 2001) also found that, when constraints are active, the outcomes obtained in conceptual combination in the production of art are considered more creative than when constraints are inactive. This research contributes to this line of work showing that, even through the use of particularly interactive and dynamic customization toolkits, it is possible to obtain more creative outputs in the presence of evaluative contests and time constraints.

This research also offers relevant implications for managers. Companies interested in proposing contests to obtain innovative ideas from consumers should opt for competitions that include the evaluation by external actors and the presence of well-defined deadlines, which are able to represent a time constraint for the participants. Luck-based contests can be valid alternatives for other purposes, such as the generation of leads (Schulten & Rauch, 2015), but they can be less optimal solutions when the goal of the company is to obtain new creative ideas. From the consumers’ viewpoints, the active participation in product customization activities, such as the possibility of actively contributing to the creation of new product ideas through open innovation contests, could be seen as an opening by the company to establish trust-based relationships with the consumers. With this in mind, open innovation contests constitute a winning strategy to increase the consumers’ involvement toward the company and, in turn, to enhance consumers’ brand engagement and brand loyalty.

This study suffers from a series of limitations that can be addressed by future research. The research hypotheses were tested using a single experimental study in a single context. Future research could analyze secondary data from open innovation contests to increase the external validity of our results. Although our experiment was conducted in a controlled context, to achieve high internal validity, the realistic customization toolkit that was used and the behavioral task conducted by participants make us confident about the external validity of our findings. Future research could analyze open innovation contests for products and contexts different from the one we have analyzed on a larger and heterogeneous sample. One limitation of our research is the use of a small sample composed of only university students. Despite we believe there is a good fit between our sample and the potential participants in a real open innovation contest based on sneakers, a future study could involve people of various age groups. Although shoes represent a common product in an important domain (fashion), it would be interesting to observe the effect of different types of contests and time constraints for more complex products, such as financial services.

In conclusion, co-creation toolkits are important means for companies aiming to pursue open innovation goals. These tools, combined with the logic of contests, allow companies to communicate directly with their customers, in a highly interactive, still easy to use, context.