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Article

Boosting Customers’ Co-Creation in Open-Source Software Environments: The Role of Innovativeness and a Sense of Community

by
Antonio Rebelo
,
Concepción Varela-Neira
* and
Emilio Ruzo-Sanmartín
Department of Business and Marketing, University of Santiago de Compostela, 15782 Galicia, Spain
*
Author to whom correspondence should be addressed.
J. Theor. Appl. Electron. Commer. Res. 2024, 19(3), 2476-2496; https://doi.org/10.3390/jtaer19030119
Submission received: 27 February 2024 / Revised: 9 September 2024 / Accepted: 12 September 2024 / Published: 20 September 2024
(This article belongs to the Topic Consumer Psychology and Business Applications)

Abstract

:
The increasing need for continuous innovation has given rise to a substantial increase in co-creation initiatives. Since the co-creation of value involves customers participating in the creation of product offerings voluntarily and actively, this investigation tries to understand what drives customers to participate in these co-creation initiatives. To do so, this study employs a probabilistic sample of 683 users enrolled in Linux forums for open-source software distributions. The path analysis and bootstrap samples revealed that customers who exhibit a high innate innovativeness and feel that they belong in the online community show a greater motivation towards platform exploration and participation in co-creation. Moreover, the effect of this synergic interaction on their co-creation participation was partially mediated by the normative dimension of their intrinsic motivation, while the hedonic dimension was not a strong predictor of co-creation contributions. This study fills the voids in the existing literature by showcasing the relevance of personal characteristics, beyond individual motivation, in co-creation behavior.

1. Introduction

In today’s ever-evolving environment, maintaining a continuous stream of innovation is crucial for cultivating the dynamic capabilities required for competitiveness and survival [1]. In order to attain their innovation objectives, firms must not only consider internal knowledge reservoirs; establishing partnerships with external entities and embracing open sourcing has turned out to be essential [2]. Simultaneously, technological progress fosters increased engagement between firms and customers [3,4]. Consequently, this growing popularity of information and communication technologies has enabled firms to appoint consumers as co-creators in the social marketing process [5]. As a result, in this environment, co-creation has gained popularity [6], becoming integral to innovation [7] and enhancing firm performance, brand value, and customer relations [8,9].
Consequently, there have been multiple approaches to co-creation research [10,11]. Prior systematic reviews show that co-creation has been studied within the political science, logistics, services sciences, consumer research, innovation, technology management, business, and marketing disciplines [12,13], with studies mainly using S-D logic, practice theory, social exchange theory, and stakeholder theory as their theoretical perspectives [11]. This work can be framed within the field of marketing, building upon the theoretical foundation of interactive marketing, which is defined as “the bi-directional value creation and mutual-influence marketing process through active customer connection, engagement, participation and interaction” [14]. Interactive marketing is among the most rapidly expanding fields in today’s business landscape [15]. Furthermore, this research adopts an innovative theoretical perspective by using psychological theories, such as trait theory, with support from SDT and need-to-belong theory. This approach sets it apart from most prior co-creation studies and contributes to the academic literature by using these theories as foundational mechanisms to enlighten emerging themes derived from real-world marketing phenomena [15].
Various conceptualizations of co-creation exist. Sugathan and colleagues [16] perceive it as customers actively engaging in the production and utilization processes through operant resources. Ranjan and Read [17] view it as consumers actively creating value with the firm. France et al. [18] identify behaviors like customers’ direct brand development participation as indicators of co-creation. Simultaneously, service-dominant logic views individual customers as contributors of skills and knowledge, resulting in co-creation [19]. The generation of knowledge takes place through interactions, which involve collaboration between firms and customers [20]. All of these conceptualizations, as well as the prior definition of interactive marketing, acknowledge the critical role of individuals in co-creation [21], emphasizing customers’ proactive behaviors and participation as key [14]. Thus, customers must actively participate in activities for free to co-create value, rendering co-creation vulnerable to self-selection [22] and contingent upon the varied objectives of a diverse customer base with dynamic demands [8].
Conversely, the academic literature has neglected to study the impact of the customer on co-creation. A significant portion of the research has delved into subjects such as the favorable impacts of collaborative creation for businesses (e.g., [23,24,25]), successful co-creation case studies (e.g., [26]), and managerial approaches and practices for conducting co-creation activities (e.g., [4,27,28]). Thus, the limited empirical investigations into individual characteristics have prompted appeals for additional studies on the co-creation behaviors of customers in particular to better understand their participation [29].
Covering this gap is important, especially in the context of the Internet, given that the rise of ICT-based platforms has resulted in a shift from person-to-person to platform-orchestrated multi-sided network interactions that facilitate large-scale co-creation activities [14]. Since participation in online communities is voluntary, achieving sustained engagement is an important challenge [30]. Researchers have emphasized the need to explore customers’ behaviors and interactivities in electronic platforms [4] in particular to understand the factors driving customer participation in online communities for effective knowledge integration into organizations [29]. Thus, businesses seeking to promote customer co-creation need a thorough understanding of customer motivations [31]. However, research into the motivations of voluntary customer participation in co-creation remains limited [32,33]. Recognizing co-creation tasks as a source of ‘intrinsic’ rewards [34] highlights the need to delve into customers’ intrinsic motivation.
Online communities are Internet-mediated platforms fostering interactions [35]. They engage consumers by connecting them around common goals through virtual contacts [36,37]. Given that participants in virtual co-creation groups experience advantages through their interaction with similarly inclined individuals and receive reciprocal support from fellow group members, collaborative engagements contribute to the enhancement of communal bonds and the cultivation of a sense of community amid participants. Therefore, a thorough examination of customers’ incentives to contribute to online communities and engage in co-creation necessitates a focus on their sense of belongingness within the community, as highlighted by Zhang et al. [38]. This has led to a growing call for research on the interplay between a sense of community, motivations, and contributions, particularly within the context of online communities [30]. Consequently, this investigation also examines how a consumer’s sense of community influences his/her co-creation behavior.
Furthermore, to explore customer characteristics in co-creation research, incorporating personality traits is deemed essential [39], due to their relative stability compared to transient characteristics like moods and attitudes [40]. Hence, recent co-creation studies explore individual differences using a personality foundation (e.g., [34,41]). These studies investigate the big five personality traits [42] to identify customers receptive to co-creation. Nevertheless, the ambiguous findings regarding the correlation between the big five personality traits and co-creation necessitate an exploration of the comprehensive set of connections that governs customers’ co-creation behavior. This study aims to reveal consumer profiles that exhibit a greater inclination toward co-creation, investigating pertinent characteristics and the psychological mechanisms involved, as proposed by Vermehren et al. [39]. Current studies in social psychology advocate for a hierarchical organization of personality, as exemplified by Mowen [43], who suggests a four-level order where narrower traits are posited to predict behavior more accurately than broader ones. Additionally, Oertzen et al. [41] suggest that co-creation behavior may arise from a personality hierarchy, with factors like creativity influencing behavior. Simultaneously, the adoption of innovative products is often linked to consumer innovativeness [44,45]. Thus, this study focuses on a more specific trait, innate innovativeness, which is closely tied to co-creation [39], as a kind of customer readiness [46], rather than relying on the broad big-five model, examining its relationship with customer co-creation.
Finally, there are different types of online communities. Sponsored co-creation communities are communities where individuals engage in activities at the behest of a firm [47] and co-creation occurs in various forms, including the development of software in the open-source domain [48]. While crowdsourcing and innovation contests have received considerable attention in e-commerce and information systems studies (e.g., [49]), other variations of sponsored co-creation, each possessing unique characteristics, have been overlooked [50]. At the same time, while empirical studies exist on company-sponsored co-creation communities, research into individual characteristics that lead to participation in them is lacking [51].
Centering on the previously identified research requirements, the objective of this study is to investigate how a consumer’s innate innovativeness and sense of community impact his/her intrinsic motivation for co-creation and subsequent participation in open-source software (OSS) development. Furthermore, within co-creation settings, the characteristics of consumers might serve as significant moderators influencing their relationships. Thus, this study also analyzes the interactions between innovativeness, a sense of community, and intrinsic motivation.
Hence, this investigation offers various valuable contributions to the co-creation literature. Firstly, amid the growing significance of co-creation, recent reviews have emphasized a predominance of qualitative studies, emphasizing the need for quantitative investigations into co-creation antecedents [8,11]; thus, our study bridges this gap by quantitatively exploring the drivers of actual co-creation behavior, and specifically participation. Secondly, it builds on existing investigations that link personality traits to co-creation behavior, thereby contributing to the limited research in this domain [39]. Thirdly, by acknowledging intrinsic innovativeness and a sense of community as antecedents, this study responds to the demand for investigation into the precursors of individuals’ motivation to engage in co-creation [52]. Fourthly, our study breaks new ground by examining the moderating role of personal characteristics, a theoretical approach not extensively explored in prior research, in co-creation participation determinants [8]. Finally, amid the industry-centric focus on co-creation, this investigation addresses calls for exploration across diverse industries [11], such as OSS, providing insights into how personal characteristics and intrinsic motivation influence co-creation participation in this environment.

2. Literature Review and Hypotheses

2.1. Open-Source Software

The past decade has seen a remarkable surge in the success of open-source software (OSS) platforms [53]. The use of open-source models in businesses is actually on the rise. Red Hat’s 2022 report ‘The State of Enterprise Open Source’ [54] suggests that 80% of IT leaders expect to increase their use of enterprises’ open-source software and 89% believe open source is as or more secure than its alternative. OSS is a software characterized by freely available source code, allowing for its reuse, enhancement, and distribution [55]. OSS development views software as a shared resource developed by a volunteer community, fostering collaboration and emphasizing transparency [56,57]. It has emerged as an alternative software development approach that exemplifies the community-based model [58]. It involves loosely organized global communities of geographically and temporally distributed participants who collaborate over the Internet to contribute code voluntarily [59]. These contributors range from professional developers to volunteers from diverse backgrounds, effectively working together in a decentralized manner [60,61].
Co-creation in open-source software refers to a collaborative process where a community of contributors collectively develops and maintains software [62]. This approach enables anyone to participate by contributing code, testing the software, documenting it, and providing other resources. User feedback and input play a crucial role in improving the software’s performance and usability [63]. The success of OSS communities lies in participants’ collaboration contributing to high-quality software tailored to diverse user needs [48]. The personalization of services and user involvement are key aspects of OSS, allowing users to express opinions and suggestions for software improvement [64]. Hence, OSS communities serve as a prime example of how co-creation principles operate within technology-related communities [65].
The collaborative relationships among developers form a “complex network” that is both random and structured, evolving over time [58]. Despite lacking the hierarchical structure typical of commercial organizations, OSS communities establish and enforce clear contribution policies [66]. In particular, the development process in OSS communities is characterized by a collaborative, community-driven ideology with shared norms, beliefs, and values [67,68]. These include principles of openness, collaboration, transparency, meritocracy, community orientation, sharing, free and open distribution, and flexibility. Norms also discourage project bifurcation, emphasizing the preservation of a project’s history and credit being given to contributors.
The studies that have focused on OSS often examine the development process, the source code and its evolution, and various aspects related to contributors [69]. In particular, most investigations dealing with contributors address the classification and definition of roles for individuals involved in OSS communities, the developer’s life cycle, or the pathways and activities that lead to participants becoming core members or long-term contributors [70,71].
One of the most remarkable aspects of OSS development is that most participants contribute without being employed, paid, or recruited by any organization [59]. Consequently, many OSS projects’ failures are attributed to problems within the development team [72]. Marsan et al. [73] reported that contributor loss is a significant issue. High turnover disrupts communities, reduces productivity [74], and degrades product quality [75,76]. Therefore, it is crucial to maintain a stable project workforce and retain core developers and their expertise.
Since individuals contribute to OSS without being directly remunerated, which contrasts sharply with the economic principle of homo oeconomicus, some previous research has tried to explain this behavior [77]. Thus, prior investigations have often seen the OSS community as a gift culture, where acts of altruism and reciprocity result in psychological benefits like satisfaction, enjoyment, and moral fulfillment which replace tangible rewards [59]. However, some economists argue that intrinsic rewards alone cannot account for the extensive contributions observed in OSS, as similar patterns are not seen in other economic sectors [78]. Other important motivations found in prior research include adapting software to personal needs and community-related factors like reciprocity and ideology. In this line, the Floss Survey 2003 [79] highlighted additional motivators, including community involvement, promoting open sources, and having fun, but recognized the need for further research to fully understand these motivations. Moreover, there is a lack of research focused on OSS that examines which personal characteristics make some individuals feel motivated to participate while others do not.

2.2. Customer Participation and Customer Characteristics

Current research distinguishes between innate innovativeness, consumer innovativeness, and domain-specific innovativeness, drawing distinctions based on the degree of abstraction [39]. Innate innovativeness reflects a person’s innovative character [80,81]; it also signifies a willingness to explore, experiment, learn, take risks, and adapt. Individuals with high innate innovativeness seek novelty [82] and prefer unique, personalized offerings [83]. These individuals are more inclined to seek out information, explore new ideas, and take risks by trying things related to uncertainty, danger, and risk; therefore, they are more receptive to adopting innovative advancements [46].
Defined as a trait reflecting an individual’s inherently innovative predisposition [81], innate innovativeness remains relatively stable across situations [84]. This elevated degree of abstraction corresponds to investigations that define innovativeness as a broad personality trait, such as a proclivity for change or a disposition toward seeking novelty. We argue that innate innovativeness, a general unobservable trait reflecting a person’s general disposition for the new and unusual [80,81], is the most suitable predictor of co-creation since the latter’s focus goes beyond adoption and consumption [85].
Psychological investigations have affirmed that personality traits markedly influence individual behavior (e.g., [86]). Individuals with high innate innovativeness show not just a willingness to explore uncharted territories, embrace calculated risks, and employ inventive strategies to foster innovation, but also display an openness to learning and adaptability, nurturing inventive actions that navigate a range of challenges. Considering that co-creation is inherently interactive and innovative, it is logical to expect that consumers who possess an open-minded attitude toward the new would naturally gravitate towards co-creation. At the same time, innovative individuals with a proclivity for novelty and uniqueness [44,82] are likely to view customization options within co-creation as advantageous [87]. In this line, previous studies suggest that innovativeness, in its different forms, positively relates to a willingness to contribute to co-creation (e.g., [39,88]). Thus:
H1: 
Innate innovativeness is positively related to customer participation in OSS environments.
A second crucial personal construct within co-creation arises from its relational and interactive nature. Virtual communities, characterized by intricate networks and collaborative efforts, involve meaningful relationships and goal-oriented collaboration [89,90]. Thus, a sense of community can serve as a catalyst for members’ actions and provide a guiding force [91]. It plays a pivotal role in social interactions, fostering information sharing, understanding, and a sense of mutual concern among community members [92]. This, in turn, has implications for co-creation, a collaborative process where individuals or groups contribute to creating, devising, or developing a good, service, or experience.
Drawing from the need-to-belong theory, when customers identify with a community, they share a connectedness to common interests and goals, fostering communication and collaboration among individuals, particularly towards the co-creation of ideas. Previous studies consistently highlight the significant influence of users’ sense of community and emotional connections on their behavior in co-creation environments [93,94,95]. Similarly, the depth of emotional connection has been correlated with the degree of involvement in group activities [96]. Also, prior research has found that community identification and community commitment are key drivers of helping behavior [97] and consumer citizenship behaviors, both in-role and extra-role [5]. Consequently, a strong sense of community naturally boosts participation, as engaged customers show a greater willingness to contribute [30]. In other words, their sense of belonging triggers commitment [36], fostering contributions, collaborative efforts, and altruistic acts [59]. Thus:
H2: 
A sense of community is positively related to customer participation in OSS environments.

2.3. The Mediating Role of Customers’ Intrinsic Motivation

Motivation is a key force driving individuals to action [98]. As per Self-determination theory (SDT, [99]), motivation serves to invigorate individuals, propelling them to invest effort and promoting persistence, thereby positively influencing behavioral outcomes [100]. Motivation acts as a driving force, mobilizing and energizing an individual’s endeavors and perseverance in the execution of a relevant task [101]. To be motivated implies being spurred to action, whereas “amotivation” characterizes a state where a person lacks the intent or purpose to act, perhaps due to feeling incapable of the activity, perceiving it as unimportant, or doubting its alignment with relevant objectives [102].
SDT classifies motivations into extrinsic and intrinsic according to their underlying reasons or aims. Extrinsic motivation relies on external incentives, such as career advancement, prestige, or monetary rewards [100]. Intrinsic motivation is self-driven and maintains behavior by deriving spontaneous satisfaction from effective voluntary actions [100,103]. It involves engaging in activities for enjoyment, exploration, learning, and self-actualization, independent of external rewards [104].
SDT conceptualizes intrinsic motivation as comprising two dimensions: intrinsic hedonic and normative motivation. Intrinsic hedonic motivation is rooted in the satisfaction with individual requirements for competence and autonomy [105]. Competence represents the desire for personal success achieved through personal efforts and responsibility, while autonomy is the longing to be self-determining [100]. Additionally, SDT introduces the third basic need of relatedness, emphasizing the need for social connection [100]. The satisfaction of this need leads to intrinsic normative motivation, which directs individuals toward behaviors that conform with norms and values and tasks benefiting the organization [106,107]. Hence, this comprehensive view of intrinsic motivation recognizes both task-related enjoyment (intrinsic hedonic motivation) and social value (intrinsic normative motivation) as its integral components.
Previous research has shown the important impact of intrinsic motivations on brand advocacy in the online brand community environment [108]. SDT also emphasizes the importance of intrinsic motivation in complex and innovative tasks like OSS contributions [109,110]. In OSS, the perceived value of participation can be multifaceted, encompassing psychological aspects like enjoyment [111]. Participation motives in the open-source movement arise from an inherent interest in the activity itself [32]. Additionally, it may involve self-efficacy, where engaging in such activities fosters a sense of competence, especially in crafting or problem-solving endeavors [112]. The complex nature of OSS, offering a spectrum of features for exploration, poses cognitive challenges to users, and consequently, contributing to OSS demands significant cognitive efforts. The social context, key in an online community, also plays a role in influencing intrinsic motivation, as posited by cognitive evaluation theory [99]. Therefore, this study concentrates on the intrinsic motivation of users within the realm of OSS.
Intrinsic motivation often demonstrates a favorable impact on engaging in intricate, inventive, and extra-role undertakings [101]. Individuals exhibiting intrinsic hedonic motivation are driven by wonder and a keen interest in understanding the traits of OSS and willingly explore them and embrace their challenges and risks [105]. Their intensive efforts in acquiring information and experimenting with innovative OSS features contribute to broader and more impactful engagement. At the same time, intrinsically hedonically motivated users absorbed in exploring OSS features are psychologically engaged, providing them energy for sustained effort and persistence in complex tasks. On the other hand, intrinsic normative motivation prompts users to exert intensive effort in exploring a variety of OSS features, evaluating their benefits for customers, groups, and firms. Simultaneously, intrinsic normative motivation allows individuals to align their behavior of investigating OSS traits with the scheme of their personal values, as users consistently perform actions supported by their values [100]. Consequently, we anticipate that high levels of intrinsic motivation, whether hedonic or normative, will drive individuals to invest intensive and sustained efforts in investigating OSS traits, positively affecting their participation in enhancing OSS. In this line of thinking, previous research underscores the significance of individuals’ intrinsic motivation in clarifying their contribution, effort, and commitment to sponsored online co-creation [113].
The association between intrinsic motivation and innovativeness is understudied [50], but positive correlations between innovativeness and cognitive absorption suggest a potential connection [114]. Moreover, recent psychological research suggests that broad personality traits impact situational traits affecting behavior [115,116], indicating a relationship between innate innovativeness, intrinsic motivation, and co-creation behaviors. Hence, innate innovativeness is expected to impact customers’ motivation towards co-creation endeavors.
Simultaneously, since this trait encompasses a willingness to explore, experiment, take risks, learn, and remain adaptable [81], we expect this personality trait to have a greater effect on the dimension of intrinsic motivation which arises from task-related enjoyment and the objective of participating in behavior that is self-determining and enhances one’s competence (i.e., hedonic motivation) than on the dimension of intrinsic motivation that relates to the desire to establish connections with others and to be proficient in navigating the social realm (i.e., normative motivation). Thus:
H3: 
Intrinsic hedonic motivation mediates the relationship between innate innovativeness and customer participation in OSS environments to a greater extent than intrinsic normative motivation.
The sense of being heard and valued in a community increases enjoyment and motivation for active participation in that community’s co-creation activities [63,117]. Additionally, since a sense of community involves a feeling of fitting into and being accepted by a group, and a willingness to lose for the collective [118], it motivates individuals to contribute to the collective well-being and benefit of the group and try to attain collective objectives. Conversely, if community members do not experience belonging and recognition in their relationship with other members, their motivation for engaging in co-creation initiatives within the community might diminish [119]. In conclusion, the sense of community plays a crucial role in co-creation, influencing individual motivations and contributing to the success of virtual communities.
Nevertheless, we expect sense of community to have a greater influence on the normative, i.e., compliance with norms and values and the desire to establish connections with others and to be proficient in navigating the social realm, component of intrinsic motivation than on the task-linked, enjoyment-founded hedonic component. In virtual communities, individuals are united by common objectives often defined and shaped by the community itself that enhance and address the needs and problems of the community [36,89]. Thus, responsible behavior is expected from users who act as resource integrators [120]. Socialization within the community leads members to recognize the value of tasks aligned with community values and norms, impacting the normative component driven by compliance with norms and values. Furthermore, a sense of community fosters a feeling of purpose and meaning in individuals’ lives. Members of a community know the importance that each one has in the community and understand the roles that everyone has to play [121,122]. This understanding of roles and significance can foster an increased sense of accountability and dedication to the community’s objectives, including co-creation activities. Thus:
H4: 
Intrinsic normative motivation mediates the relationship between a sense of community and customer participation in OSS environments to a greater extent than intrinsic hedonic motivation.

2.4. The Moderating Role of Customer Characteristics

Prior research suggests a person–motivation interaction, proposing that behavior may be contingent on both motives and an individual’s characteristics [123]. In the realm of co-creation initiatives, studies have also emphasized the dual role of an individual’s inherent innovativeness: as a factor shaping the trajectory and as a feature enhancing outcomes [124]. At the same time, according to goal-setting theory, behavior reflects conscious purposes and intentions, where efforts and enactment align with self-assigned goals [125,126]. Similarly, SDT and self-regulatory focus theory underscore that motivation is an inner resource for behavioral self-regulation and alignment with goals and standards [127].
Hence, while our previous hypotheses suggest a connection between innate innovativeness and co-creation behavior and between intrinsic motivation and participation in OSS, we also posit that there is a synergy when individuals exhibit a predisposition toward innovation and a strong motivation to contribute to co-creation, as motivation encompasses their energy, direction, and persistence in activating the behavior in question. Intrinsic motivation creates a context where innate innovativeness can be activated, allowing individuals to express personal inclinations and enhancing their disposition to participate in co-creation behaviors (trait activation theory, [128]). The positive impact of innate innovativeness on promoting a person’s contributions to co-creation may be dormant without intrinsic motivation, as innovativeness may be irrelevant in the absence of motivation for the task. Consequently, we suggest that intrinsic motivation acts as a catalyst and that the connection between innate innovativeness and co-creation participation could either be heightened or diminished based on an individual’s motivation level toward the task. This is in line with previous research [129] that showed that innovativeness positively interacts with intrinsic motivation in an organizational context.
At the same time, SDT also emphasizes “the social and environmental factors that can facilitate or undermine intrinsic motivation” ([130], p. 58). Similarly, trait theory argues that fundamental tendencies evolve into motivational concepts, behavioral intentions, and realized behavior within a dynamic personality system [131]. Thus, basic tendencies’ expressions may voluntarily change or adapt due to external circumstances [132]. Therefore, a critical aspect deserving thorough consideration is the central role played by a robust sense of community in reinforcing users’ innate innovativeness.
We argue that the depth of the association between the level of innate innovativeness exhibited by individuals and their motivation to participate in co-creation is subject to variation based on their sense of community [133]. Concurrently, the sense of community provides a nurturing space where such individuals can freely express and exchange their innovative thoughts, creating an environment conducive to the co-creation process. This strong sense of community not only fosters a collaborative atmosphere but also serves as a supportive backdrop for the exploration and experimentation of innovative concepts [134]. In this encouraging environment, individuals find their innovative capacities sparked and encouraged, leading to greater motivation to experiment and engage in problem-solving. Consequently, the harmonious synergy between innovativeness and a strong sense of community results in increased motivation to contribute to collaborative endeavors. Conversely, in situations where the spark of innovativeness is faint or the sense of community lacks vitality, the incentive to participate in co-creation activities may waver. Thus:
H5: 
Innate innovativeness interacts with (a) intrinsic hedonic and normative motivation to positively impact customer participation in OSS environments and with (b) the sense of community to positively impact intrinsic hedonic and normative motivation; namely, the greater the customer’s innate innovativeness, the greater the indirect relationship between their sense of community and participation in OSS environments through intrinsic motivation.

3. Research Methodology

3.1. Sample and Data Collection

Data were gathered in 2018, using a questionnaire developed by researchers. Respondents were required to be users enrolled in Linux forums for OSS distributions (commercial and non-commercial). The paid distributions included Red Hat, IPBrick, and SUSE, whereas the free distributions included Fedora, Debian, and Ubuntu. The respondents were randomly selected using a quota based on the number of posts that each user had published. This meant that the following percentages of users were selected for the study: 20% passive users (users without contributions), 60% ordinary/undifferentiated users (users with at least one contribution), and 20% platform programmers/dedicated support technicians (usually users with a high number of posts because they give feedback to suggestions/requests for help and contribute new ideas). In each community, the user selection process adhered to the percentage that was initially set for each group. Within each group, all users had an equal chance of being selected. Each user was assigned a sequential number. The selection was made using an algorithm that randomly selected numbers in each group up to the defined limit. A total number of 1662 users were selected. The questionnaire was disseminated, and data were collected directly from the official forums of each distribution.
Our sample encompasses the 683 respondents who fully answered the questionnaire (a response rate of 41.1%). The respondents mainly consisted of users of free distributions (73.6%) rather than users of paid distributions (26.4%). In terms of their profile, 52.6% of participants were men, their ages mostly ranged from 46 to 65 years old (45.8%), the majority have a university degree (89.2%), and most are currently employed (83.8%) in the private sector (52.9%).
The potential for non-response bias was assessed following Armstrong and Overton’s [135] guidelines, comparing early and late respondents. Early responses constituted the first 75% of returned questionnaires, while the last 25% represented late responses, intended to be reflective of users who did not participate in the survey [136]. A battery of tests was carried out on these two groups, examining various key respondent characteristics, such as years of collaboration (p = 0.342), number of contributions (p = 0.136), gender (p = 0.708), age (p = 0.498), level of study/graduation (p = 0.687), work status (p = 0.913), work type (p = 0.533), and migrant status (p = 0.999). The results indicated no significant differences, suggesting that non-response bias was not a concern.
Finally, the presence of common-method bias was tested for using two distinct methods to assess the extent of its variance. The Harman one-factor test [137] revealed that a single general factor did not account for the majority of the variance in an Exploratory Factor Analysis (28.2%), indicating that significant common-method variance was unlikely. Additionally, Jarvis et al.’s [138] approach involved re-estimating a new model with all observed variables loading on one factor. The results of this model were deemed unacceptable (Chi-square = 3043.42; df = 252; RMSEA = 0.127), further affirming that common-method bias was not a notable issue in this study.

3.2. Measurement Scales

The measurement items considered for each construct (see Appendix A) were adapted from previously validated scales to the platform context and were measured on a seven-point Likert-type scale ranging from 1 (strongly disagree) to 7 (strongly agree). Thus, intrinsic hedonic motivation (IHM) and intrinsic normative motivation (INM) were measured using 4 items each collected from Ke et al. [139]; a sense of community (SC) was measured using the 5 items employed by Gebauer et al. [140]; innate innovativeness (IN) was measured using the 11 items utilized by Im et al. [141]; and finally, customer participation (CP) was measured with the following question: Please indicate how many contributions have you made when participating in the development of the platform (number of code modifications and/or other proposals). The customer’s gender and age (as a natural logarithm) were included in the model as control variables.

4. Results

4.1. Psychographic Properties of the Scales

To ensure the accurate application of the scales, adhering to the recommendations of Gerbing and Anderson [142], Hair et al. [143], and Hu and Bentler [144], we performed a Confirmatory Factor Analysis (CFA). The findings of the CFA show a chi-square of 245.497 with 246 degrees of freedom. Also, we assessed the following goodness-of-fit indices: the comparative fit index (CFI = 0.999), incremental fit index (IFI = 0.999), the normed fit index (NFI = 0.976), and root mean square error of approximation (RMSEA = 0.015). Following the recommended approach of considering a combination of key indices, the fit indices were within the recommended thresholds, and the estimated CFA model was considered acceptable [143,145]. Regarding reliability, the results exceeded the recommended threshold values for the Cronbach’s alpha coefficient (CA > 0.70), composite reliability (CR > 0.60), and average variance extracted (AVE > 0.50) for all the constructs considered, thus showing acceptable levels of reliability [146]. In terms of convergent validity, all items were related to their specified constructs, and the individual loadings displayed were significant and above the recommended threshold of 0.5 (see Appendix A), thus indicating convergent validity [147]. Finally, to assess discriminant validity (see Appendix B), we observed the average variance explained and squared inter-construct correlations, and the explained variance per construct was higher than the inter-construct correlations; hence, discriminant the scales’ validity was also adequate [148].

4.2. Method

To evaluate the proposed moderated mediation process, we conducted a path analysis using Stata. Path analysis allows for the modeling of relationships among multiple independent and dependent variables simultaneously, providing a more comprehensive view of the entire model [149]. This method avoids the complexity of using latent variables in a large model like ours. Therefore, we replaced the constructs with the average scores of their indicators, consolidating them into single measures. Additionally, to prevent interpretation issues with some coefficients due to the scales of certain variables (which do not include zero), we centered the variables on their means. Furthermore, to establish moderated mediation, the strength of the mediation must vary across different levels of the moderator. Consequently, as recommended by Preacher et al. [150], we used 5000 bootstrap samples to create 95% bias-corrected confidence intervals for conditional indirect effects. These effects are considered statistically significant if zero is not within the 95% bias-corrected bootstrap confidence intervals at various levels of the moderator variable (1 SD below the mean, mean, and 1 SD above the mean).

4.3. Hypotheses Testing

The findings shown in Table 1 reveal that innate innovation and a sense of community have a positive effect on co-creation participation, supporting hypotheses 1 and 2, respectively. The results also reveal that innate innovativeness has a greater positive impact on intrinsic hedonic motivation but a smaller positive influence on intrinsic normative motivation than a sense of community. On the subject of the impact of intrinsic motivation, the findings show that its normative dimension has a positive impact on co-creation participation, whereas its hedonic dimension shows a non-significant effect.
Additionally, the results reveal a significant positive interaction effect between innate innovativeness and a sense of community on both dimensions of intrinsic motivation, together with a significant positive interactive effect between innate innovativeness and intrinsic motivation on co-creation participation. Consequently, higher levels of a sense of community will boost the positive impact of innate innovativeness on intrinsic motivation, especially on its normative dimension. At the same time, the greater the customers’ innate innovativeness and intrinsic motivation, the greater their contributions in the OSS environment.
Regarding conditional indirect effects, the significance of the indirect relationship between customers’ characteristics and participation via intrinsic motivation was calculated for customers with low/moderate/high innate innovativeness and a sense of community (see Table 2). The results reveal that none of the customer characteristics are related to participation through intrinsic hedonic motivation; thus hypotheses 3 is not supported. Regarding intrinsic normative motivation, our findings show that a sense of community is positively and indirectly related to participation via this motivation dimension only when a customer’s innate innovativeness is moderate (b = 2.716, p < 0.10) or high (b = 6.239, p < 0.01) and not when it is low (b = 0.636, p > 0.10). Moreover, the results also reveal that the positive indirect relationship between a sense of community and participation via intrinsic normative motivation is greater for customers with high innate innovativeness rather than moderate. Finally, the indirect relationship between innate innovativeness and customer participation through intrinsic normative motivation is significant when their sense of community is moderate or high, but not when it is low. Furthermore, the findings also show that the positive indirect relationship between innovativeness and participation via this motivation dimension is greater the greater the customer’s innate innovativeness and sense of community, reaching its peak when both customer characteristics are high. These results support hypotheses 4 and 5.

5. Discussion

This investigation was designed to examine co-creation from the viewpoint of the individual. In particular, this study tried to comprehend which personal characteristics relate to co-creation participation in an OSS context. Since incorporating customer knowledge into product development is essential to achieving innovation goals [32] and this customer participation is voluntary [30], understanding which individuals are more willing to contribute is essential for companies to target them appropriately. At the same time, since previous co-creation research primarily revolves around customers’ willingness or retrospective evaluations of their co-creation experiences [151], this investigation contributes to this field by examining actual behavior. Finally, this research responds to recent calls to use a different theoretical approach to study co-creation and move away from S-D logic, practice theory, social exchange theory, and stakeholder theory [11]; so, by building upon the theoretical foundation of psychological theories like trait theory and also drawing support from SDT and need-to-belong theory, this investigation contributes to the co-creation literature.
The results of our empirical analyses support the proposed model and have relevant implications for theory. First, since personality is a vital agent in elucidating individual attitudes and behavior [152], particularly within the domain of consumer behavior [153], this study contributes to the still limited literature that investigates the association between personality traits and co-creation [39]. Innate innovativeness emerged as the most relevant antecedent to an individual’s contribution to co-creation in an OSS environment, as it had the greatest impact. This finding is in line with previous research on innovation [45] and it emphasizes the special nature of OSS development communities, where innovation is the end outcome and depends on collaboration among all participants. Moreover, innate innovativeness is also the main predictor of intrinsic hedonic motivation, but second to a sense of community for intrinsic normative motivation, as proposed in the development of our hypothesis. This highlights the relationship between this personality trait and obtaining enjoyment from innovation, which activates the motivation to explore and contribute to the platform, but mainly through its hedonic dimension. Nevertheless, innate innovativeness also leads to intrinsic normative motivation, probably because people high on innate innovativeness tend to feel that they have original ideas and novel perspectives [141], which would make them feel capable and compelled to contribute to an OSS development community, where collaboration for innovation is the norm. Since little is known about the relationship between innovativeness and intrinsic motivation [50], these findings clarify this association and help us understand the impact of innovativeness on the different dimensions of motivation. Finally, these results highlight not just that personality determines which individuals are more willing to co-create, in line with prior investigations (e.g., [39,88]), but also that research should focus on those personality traits that best fit the subject under study, instead of using broad personality frameworks (e.g., [34,41]).
Second, the sense of community also plays a key part in co-creation, as it is the second greatest influence on co-creation participation and the main determinant of intrinsic normative motivation, consistent with previous research (e.g., [95]). The relational and interactive nature of online communities, and in particular OSS development communities, can give rise to feelings of belonging and a sense of community among their members [154]. These feelings give rise to obligations towards other members and the problems and needs of the group, which leads to normative motivation toward platform exploration and participation. When people feel like they are part of a community, they have greater intrinsic motivation to contribute to the community’s goals due to the promotion of values such as collaboration, mutual trust, and effective communication. At the same time, a sense of community creates a conducive environment for individuals with a greater disposition toward innovation, resulting in a synergic effect on intrinsic motivation, especially on normative motivation. This furthers the argument that a sense of community’s impact is mainly on the normative dimension of intrinsic motivation, even if it also inspires individuals to explore the platform and contribute to it by making the experience more enjoyable. Although these results are in line with prior investigations that relate a sense of community with co-creation participation intentions (e.g., [155]) and motivations (e.g., [32]), by differentiating between the different dimensions of motivation, they shed light on why the latter association happens. Simultaneously, by analyzing its synergic effect with innovativeness, they contribute to the literature by helping us understand when the impact of a sense of community is stronger or weaker.
Finally, these findings indicate that intrinsic normative motivation is also a substantial antecedent of co-creation participation, even if its impact is lesser than that of the individual’s personal characteristics, and acts as a partial mediator for these variables. On the other hand, intrinsic hedonic motivation does not affect this behavior independently. The statistical insignificance of the hedonic dimension aligns with similar research that has also found no significant impact of hedonic motivation on behavior [156]. The connection between hedonic motivation and behavior seems to vary depending on the specific context being studied. In an OSS environment, contributions are more dependent on the community members’ felt obligations than on how enjoyable the task may be. This aligns with previous studies on OSS participants’ motivations, which found that altruism is weakly correlated with effort [157], while social recognition is a significant incentive [158]. Members of the OSS community primarily aim to enhance a software’s performance and usability [63], which may not be perceived as inherently enjoyable or entertaining. Therefore, the degree of enjoyment and happiness obtained from contributing to OSS is not a sufficient determinant for individuals in deciding whether to engage with the community. This result is in line with Tamilmani et al. [159], who observed that investigations reporting a non-significant impact of hedonic value were centered on utilitarian value. These findings contribute to the literature by differentiating between the various dimensions of intrinsic motivation, addressing the gap that resulted in previous co-creation research often exaggerating the effect of hedonic intrinsic rewards and overlooking the normative dimension in recommendations to managers. Nevertheless, these findings also reveal that intrinsic motivation, whether normative or hedonic, is a catalyst for a person’s innate predisposition, supporting the person–motivation interaction proposed by prior research [123]. Highly innovative people have an openness to learning and exploring uncharted territories that is essential in an OSS context, and when this disposition is supported by motivation as a force that impels them to action, contributions increase substantially.

5.1. Managerial Implications

Looking at this from a managerial standpoint, our research carries various implications for managers. Enhancing customer involvement in co-creation contributes to the expansion of the firm’s knowledge base, ultimately bolstering the firm’s innovativeness and competitiveness in the long term [32]. Consequently, organizations aiming to leverage customer resources for innovation should carefully assess the kind of individuals they intend to engage when devising their communication strategies, as some are easier to attract than others. These findings emphasize the significance of accounting for the inherent innovativeness trait to facilitate the harnessing of customer resources. In order to achieve this, in line with recent developments in personality psychology, businesses could use customers’ digital footprints to predict this personality trait automatically. This could involve analyzing various aspects such as the content they engage with [160], the verbal communication utilized on social media platforms [161], or their personal expenditure habits [162]. On the other hand, the results also highlight the importance of presenting co-creation initiatives to communities where members show a high level of belonging, as well as the importance of trying to heighten the sense of community in the online communities managers participate in. Previous research can give us clues about how to identify these communities or achieve the latter. For example, in accordance with Koh et al. [163], the leader’s passion, shared interests among members, and entertainment value would reinforce a sense of virtual community. Likewise, Nohutlu et al. [154] identified five catalysts that enhance the sense of belonging among online community members: shared experiences, exclusive selection for the project, mutual interest in a specific topic, the alignment of ideas, and the discussion of common subjects.

5.2. Limitations and Future Research

To conclude, it is imperative to outline the constraints inherent in these empirical findings. This study is mainly constrained by its cross-sectional design, as the data were gathered at a specific point in time. Consequently, our ability to draw causal relationships from these data is limited, emphasizing the necessity for a longitudinal study to substantiate causal links. Moreover, since the data were collected in 2018, prior to the COVID-19 pandemic and the development of AI-based technologies, this could have affected the results. However, open-source development reports show no significant differences in trends regarding participants’ motivations to participate in OSS, which is the focus of this investigation. Digital Ocean’s 2018 report indicates that improving coding skills, being part of a community, learning new technologies, or advancing a career are the main motivators of participation, whereas it 2022 report lists enhanced skills, feeling purposeful or part of a wider community, networking opportunities, and job opportunities [164,165]. Furthermore, the 2023 Open-Source Congress report [166] highlights that open AI systems need different definitions, protocols, and development methods than the ones employed in open-source software, mainly due to the lack of transparency in AI systems. In fact, according to the World Economic Forum [167], the main way to achieve responsible AI development is for the industry to foster open-source development. However, since generative AI could boost productivity in software development [168], a significant challenge for OSS development is determining if the code produced by AI models is proprietary, open-source, or subject to another type of licensing [166].
Moving forward, researchers have a range of avenues for future investigations. Firstly, subsequent studies could replicate the proposed model within a co-creation context with a more pronounced hedonic focus. Secondly, the exploration of other personality traits as precursors to co-creation behavior could contribute valuable insights. Thirdly, investigations may delve into the conditions under which the various dimensions of intrinsic motivation correlate with co-creation behavior. Lastly, examining the impacts of innovativeness and a sense of community in a cross-cultural context could shed light on how associated behaviors vary across different cultures, aligning with the perspectives presented by Ng [169].

6. Conclusions

This investigation aimed to explore co-creation from the perspective of the individual, particularly focusing on the personal characteristics that influence participation in an open-source software (OSS) context. Given the voluntary nature of customer participation and the critical role of incorporating customer knowledge for innovation, understanding the traits that make individuals more likely to engage in co-creation is crucial for companies to target and leverage these contributors effectively.
This study’s empirical analyses supported the proposed model, revealing significant theoretical and practical implications. Notably, innate innovativeness was identified as the most influential factor driving individual contributions to OSS co-creation, aligning with previous research on innovation. A sense of community emerged as another key determinant that directly, and together with innate innovativeness, boosts individuals’ intrinsic motivation and participation. Also, the findings underscored that while hedonic motivation alone was not a strong predictor of co-creation contributions, intrinsic normative motivation played a substantial role as a mediator between personal characteristics and participation.
Despite these insights, this research has limitations due to its cross-sectional design and the evolution of the OSS context that may have occurred since the data’s collection. However, overall, this investigation enriches the co-creation literature by using psychological theories and providing a nuanced understanding of the individual characteristics and motivations that drive co-creation in OSS environments. These findings offer valuable guidance for companies aiming to harness customer innovation, emphasizing the importance of targeting individuals with high innate innovativeness and fostering a strong sense of community to enhance co-creation efforts.

Author Contributions

Writing—original draft, A.R.; Writing—original draft, C.V.-N.; Writing—original draft, E.R.-S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Xunta de Galicia, grant number ED431B 2022/32.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to privacy reasons.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Measurement scales used and their properties.
Table A1. Measurement scales used and their properties.
ItemsStandard Loading (λ)
Innate innovativeness (CA = 0.936; CR = 0.936; AVE = 0.573)
1. I often risk doing things differently. 0.743
2. I have original ideas. 0.756
3. I cope with several ideas at the same time. 0.764
4. I proliferate ideas. 0.761
5. I have fresh perspectives on old problems. 0.761
6. I am stimulating. 0.779
7. I will always think of something when stuck. 0.753
8. I can stand out in disagreement against a group. 0.772
9. I would sooner create than improve. 0.760
10. I like to vary set routines at a moment’s notice. 0.751
11. I need the stimulation of frequent change. (reversed) 0.722
Intrinsic hedonic motivation (CA = 0.883; CR = 0.883; AVE = 0.655)
1. I enjoy tackling platform problems that are completely new to me. 0.810
2. I enjoy trying to solve complex platform problems. 0.814
3. What matters most to me about platform exploration is enjoying what I do. 0.798
4. It is important that platform feature exploration provides me with an outlet for self-expression. 0.814
Intrinsic normative motivation (CA = 0.881; CR = 0.881; AVE = 0.650)
1. Exploring platform features and applications is consistent with the way I think business should be conducted. 0.816
2. Exploring platform features and applications fits the way I view our firms’ platform investment. 0.790
3. I feel that it is important to explore platform features and applications because of the support I received from our firm. 0.815
4. The support I get from our firm makes me feel obligated to explore platform features and applications. 0.803
Sense of community (CA = 0.885; CR = 0.885; AVE = 0.605)
1. I consider myself a member of this Community. 0.771
2. I think this Community platform is a good place to spend my spare time. 0.787
3. I feel closely connected to other participants of this Community. 0.777
4. I feel a sense of kinship with other Community members. 0.771
5. I have a strong desire to further interact with participants of this Community. 0.784
Note: chi-square = 245.497 (D.F. = 246); CFI: 0.999; IFI: 0.999; NFI: 0.976; RMSEA: 0.015.

Appendix B

Table A2. Discriminant validity.
Table A2. Discriminant validity.
1234
1. Innate innovativeness 0.757
2. Intrinsic hedonic motivation 0.7510.809
3. Intrinsic normative motivation 0.5120.6260.806
4. Sense of community 0.4640.5030.5240.778
Note: values on the diagonal represent the square root of the AVE. Correlations are shown.

References

  1. Teece, D.J. Business models, business strategy and innovation. Long. Range Plan. 2010, 43, 172–194. [Google Scholar] [CrossRef]
  2. Chesbrough, H.W. Open Innovation: The New Imperative for Creating and Profiting from Technology; Harvard Business Review: Boston, MA, USA, 2003. [Google Scholar]
  3. Huang, M.H.; Rust, R.T. Technology-driven service strategy. J. Acad. Mark. Sci. 2017, 45, 906–924. [Google Scholar] [CrossRef]
  4. Gao, L.; Li, G.; Tsai, F.; Gao, C.; Zhu, M.; Qu, X. The impact of artificial intelligence stimuli on customer engagement and value co-creation: The moderating role of customer ability readiness. J. Res. Interact. Mark. 2023, 17, 317–333. [Google Scholar] [CrossRef]
  5. Deng, N.; Jiang, X.; Fan, X. How social media’s cause-related marketing activity enhances consumer citizenship behavior: The mediating role of community identification. J. Res. Interact. Mark. 2023, 17, 38–60. [Google Scholar] [CrossRef]
  6. Ramaswamy, V.; Ozcan, K. What is co-creation? An interactional creation framework and its implications for value creation. J. Bus. Res. 2018, 84, 196–205. [Google Scholar] [CrossRef]
  7. Perks, H.; Gruber, T.; Edvardsson, B. Co-creation in radical service innovation: A systematic analysis of microlevel processes. J. Prod. Innov. Manag. 2012, 29, 935–951. [Google Scholar] [CrossRef]
  8. Ranjan, K.R.; Read, S. An ecosystem perspective synthesis of co-creation research. Ind. Mark. Manag. 2021, 99, 79–96. [Google Scholar] [CrossRef]
  9. Tran, T.; Taylor, D.G.; Wen, C. Value co-creation through branded apps: Enhancing perceived quality and brand loyalty. J. Res. Interact. Mark. 2023, 17, 562–580. [Google Scholar] [CrossRef]
  10. Alves, H.; Fernandes, C.; Raposo, M. Value co-creation: Concept and contexts of application and study. J. Bus. Res. 2016, 69, 1626–1633. [Google Scholar] [CrossRef]
  11. Saha, V.; Goyal, P.; Jebarajakirthy, C. Value co-creation: A review of literature and future research agenda. J. Bus. Ind. Mark. 2022, 37, 612–628. [Google Scholar] [CrossRef]
  12. Galvagno, M.; Dalli, D. Theory of value co-creation: A systematic literature review. Manag. Serv. Qual. 2014, 24, 643–683. [Google Scholar] [CrossRef]
  13. Leclercq, T.; Hammedi, W.; Poncin, I. Ten years of value cocreation: An integrative review. Rech. Appl. Mark. 2016, 31, 26–60. [Google Scholar] [CrossRef]
  14. Wang, C.L. New frontiers and future directions in interactive marketing: Inaugural Editorial. J. Res. Interact. Mark. 2021, 15, 1–9. [Google Scholar] [CrossRef]
  15. Wang, C.L. Editorial—What is an interactive marketing perspective and what are emerging research areas? J. Res. Interact. Mark. 2024, 18, 161–165. [Google Scholar] [CrossRef]
  16. Sugathan, P.; Ranjan, K.R.; Mulky, A.G. Atypical shifts post-failure: Influence of co-creation on attribution and future motivation to co-create. J. Interact. Mark. 2017, 38, 64–81. [Google Scholar] [CrossRef]
  17. Ranjan, K.R.; Read, S. Value co-creation: Concept and measurement. J. Acad. Mark. Sci. 2016, 44, 290–315. [Google Scholar] [CrossRef]
  18. France, C.; Grace, D.; Merrilees, B.; Miller, D. Customer brand co-creation behavior: Conceptualization and empirical validation. Mark. Intell. Plan. 2018, 36, 334–348. [Google Scholar] [CrossRef]
  19. Vargo, S.L.; Lusch, R.F. Evolving to a new dominant logic for marketing. J. Mark. 2004, 68, 1–17. [Google Scholar] [CrossRef]
  20. Blazevic, V.; Lievens, A. Managing innovation through customer coproduced knowledge in electronic services: An exploratory study. J. Acad. Mark. Sci. 2008, 36, 138–151. [Google Scholar] [CrossRef]
  21. Trischler, J.; Pervan Simon, J.; Scott, D.R. Exploring the “black box” of customer co-creation processes. J. Serv. Mark. 2017, 31, 265–280. [Google Scholar] [CrossRef]
  22. Mandolfo, M.; Chen, S.; Noci, G. Co-creation in new product development: Which drivers of consumer participation? Int. J. Eng. Bus. Manag. 2020, 12, 1–14. [Google Scholar] [CrossRef]
  23. Zaborek, P.; Mazur, J. Enabling value co-creation with consumers as a driver of business performance: A dual perspective of Polish manufacturing and service SMEs. J. Bus. Res. 2019, 104, 541–551. [Google Scholar] [CrossRef]
  24. Zhang, H.; Ma, Z. Is my design better? A co-creation perspective for online fashion design. J. Res. Interact. Mark. 2022, 16, 384–402. [Google Scholar] [CrossRef]
  25. Zhang, J.; Zhang, L.; Ma, B. Ride-sharing platforms: The effects of online social interactions on loyalty, mediated by perceived benefits. J. Res. Interact. Mark. 2023, 17, 698–713. [Google Scholar] [CrossRef]
  26. Bettiga, D.; Ciccullo, F. Co-creation with customers and suppliers: An exploratory study. Bus. Process Manag. J. 2019, 25, 250–270. [Google Scholar] [CrossRef]
  27. Zare, S.; Bettiga, D.; Lamberti, L. Does one design fit them all? Study of drivers of co-creation interest along different consumer segments. J. Strateg. Mark. 2019, 27, 630–650. [Google Scholar] [CrossRef]
  28. Nangpiire, C.; Silva, J.; Alves, H. Customer engagement and value co-creation/destruction: The internal fostering and hindering factors and actors in the tourist/hotel experience. J. Res. Interact. Mark. 2022, 16, 173–188. [Google Scholar] [CrossRef]
  29. Nohutlu, Z.D.; Englis, B.G.; Groen, A.J.; Constantinides, E. Innovating with the customer: Co-creation motives in online communities. Int. J. Electron. Commer. 2023, 27, 523–557. [Google Scholar] [CrossRef]
  30. Priharsari, D.; Abedin, B.; Mastio, E. Value co-creation in firm sponsored online communities: What enables, constrains, and shapes value. Internet Res. 2020, 30, 763–788. [Google Scholar] [CrossRef]
  31. Constantinides, E.; Brünink, L.A.; Lorenzo–Romero, C. Customer motives and benefits for participating in online co–creation activities. Int. J. Internet Mark. Advert. 2015, 9, 21–48. [Google Scholar] [CrossRef]
  32. Palma, F.C.; Trimi, S.; Hong, S. Motivation triggers for customer participation in value co-creation. Serv. Bus. 2019, 13, 557–580. [Google Scholar] [CrossRef]
  33. Zadeh, A.H.; Farhang, M.; Zolfagharian, M.; Hofacker, C.F. Predicting value cocreation behavior in social media via integrating uses and gratifications paradigm and theory of planned behavior. J. Res. Interact. Mark. 2023, 17, 195–214. [Google Scholar] [CrossRef]
  34. Ranjan, K.R.; Read, S. Bringing the individual into the co-creation of value. J. Serv. Mark. 2019, 33, 904–920. [Google Scholar] [CrossRef]
  35. Za, S.; Pallud, J.; Agrifoglio, R.; Metallo, C. Value Co-creation in online communities: A preliminary literature analysis. In Exploring Digital Ecosystems; Springer: Berlin/Heidelberg, Germany, 2020; pp. 33–46. [Google Scholar]
  36. Fernandes, T.; Remelhe, P. How to engage customers in co-creation: Customers’ motivations for collaborative innovation. J. Strateg. Mark. 2016, 24, 311–326. [Google Scholar] [CrossRef]
  37. Sawhney, M.; Verona, G.; Prandelli, E. Collaborating to create: The Internet as a platform for customer engagement in product innovation. J. Interact. Mark. 2005, 19, 4–17. [Google Scholar] [CrossRef]
  38. Zhang, T.C.; Kandampully, J.; Bilgihan, A. Motivations for customer engagement in online co-innovation communities (OCCs). J. Hosp. Tour. Technol. 2015, 6, 311. [Google Scholar]
  39. Vermehren, P.D.; Burmeister-Lamp, K.; Heidenreich, S. I am. Therefore, I will? Predicting customers’ willingness to co-create using five-factor theory. J. Serv. Manag. 2023, 34, 341–367. [Google Scholar] [CrossRef]
  40. Camoiras-Rodríguez, Z.; Varela, C. The influence of consumer personality traits on mobile shopping intention. Span. J. Mark. ESIC 2020, 24, 331–353. [Google Scholar] [CrossRef]
  41. Oertzen, A.S.; Odekerken-Schröder, G.; Mager, B. Driving users’ behaviours and engagement in co-creating services. J. Serv. Mark. 2020, 34, 549–573. [Google Scholar] [CrossRef]
  42. McCrae, R.R.; John, O.P. An introduction to the five-factor model and its applications. J. Personal. 1992, 60, 175–215. [Google Scholar] [CrossRef]
  43. Mowen, J.C. The 3M Model of Motivation and Personality: Theory and Empirical Applications to Consumer Behavior; Springer Science and Business Media: Berlin, Germany, 2000. [Google Scholar]
  44. Hirschman, E.C. Innovativeness, novelty seeking and consumer creativity. J. Consum. Res. 1980, 7, 289–295. [Google Scholar] [CrossRef]
  45. Rogers, E.M. Diffusion of Innovations; Free Press: New York, NY, USA, 1995. [Google Scholar]
  46. Lin, M.Y.; Do, B.; Nguyen, T.T.; Cheng, J.M. Effects of personal innovativeness and perceived value of disclosure on privacy concerns in proximity marketing: Self-control as a moderator. J. Res. Interact. Mark. 2022, 16, 310–327. [Google Scholar] [CrossRef]
  47. Chen, L.; Marsden, J.R.; Zhang, Z. Theory and analysis of company-sponsored value co-creation. J. Manag. Inf. Syst. 2012, 29, 141–172. [Google Scholar] [CrossRef]
  48. Zwass, V. Co-creation: Toward a taxonomy and an integrated research perspective. Int. J. Electron. Commer. 2010, 15, 11–48. [Google Scholar] [CrossRef]
  49. Ma, Z. Early backers’ social and geographic influences on the success of crowdfunding. J. Res. Interact. Mark. 2023, 17, 510–526. [Google Scholar] [CrossRef]
  50. Baswani, S.; Townsend, A.M.; Luse, A. Company-sponsored online co-creation and financial incentives: The impact of intrinsic motivation on participation intention. Int. J. Electron. Commer. 2021, 25, 394–415. [Google Scholar] [CrossRef]
  51. Ind, I.; Coates, N.; Lerman, K. The gift of co-creation: What motivates customers to participate. J. Brand Manag. 2020, 27, 181–194. [Google Scholar] [CrossRef]
  52. Neghina, C.; Bloemer, J.; van Birgelen, M.; Caniëls, M.C. Consumer motives and willingness to co-create in professional and generic services. J. Serv. Manag. 2017, 28, 157–181. [Google Scholar] [CrossRef]
  53. Yang, W.; Pan, M.; Zhou, Y.; Huang, Z. Developer portraying: A quick approach to understanding developers on OSS platforms. Inf. Softw. Technol. 2020, 125, 106336. [Google Scholar] [CrossRef]
  54. Cormier, P. The State of Enterprise Open Source: A Red Hat Report. 2022. Available online: https://www.redhat.com/en/resources/state-of-enterprise-open-source-report-2022 (accessed on 9 September 2024).
  55. Kumar Jha, S.; Dwivedi, A.K.D.; Tiwari, A. Reliability models and open source software: An empirical study. In Proceedings of the International Conference on Computational Intelligence and Computing Research, Coimbatore, India, 28–29 December 2010; pp. 1–5. [Google Scholar]
  56. Hemetsberger, A.; Reinhardt, C. Collective development in open-source communities: An activity theoretical perspective on successful online collaboration. Organ. Stud. 2009, 30, 987–1008. [Google Scholar] [CrossRef]
  57. Hemetsberger, A.; Reinhardt, C. Learning and knowledge-building in open-source communities. Manag. Learn. 2016, 37, 187–214. [Google Scholar] [CrossRef]
  58. Ngamkajornwiwat, K.; Zhang, D.; Güneş Koru, A.; Zhou, L.; Nolker, R. An Exploratory Study on the Evolution of OSS Developer Communities. In Proceedings of the 41st Hawaii International Conference on System Sciences, Waikoloa, HI, USA, 7–10 January 2008. [Google Scholar]
  59. Wu, C.G.; Gerlach, J.H.; Young, C.E. An empirical analysis of open source software developers’ motivations and continuance intentions. Inf. Manag. 2007, 44, 253–262. [Google Scholar] [CrossRef]
  60. German, D.M. The GNOME project: A case study of open source, global software development. Softw. Process Improv. Pr. 2003, 8, 201–215. [Google Scholar] [CrossRef]
  61. Crowston, K.; Wei, K.; Howison, J.; Wiggins, A. Free/libre open-source software development: What we know and what we do not know. ACM Comput. Surv. 2012, 44, 7. [Google Scholar] [CrossRef]
  62. Peters, I.; Hofer, M.; Gloss, T.M.; Stark, R. Success factors for company-community-collaboration in open-source hardware development facilitated by Makerspaces. In Proceedings of the 2022 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), Marrakech, Morocco, 23–25 November 2022. [Google Scholar]
  63. Füller, J.; Hutter, K.; Faullant, R. Why co-creation experience matters? Creative experience and its impact on the quantity and quality of creative contributions. RD Manag. 2011, 41, 259–273. [Google Scholar] [CrossRef]
  64. Nagle, F. Open source Software and firm productivity. Manag. Sci. 2018, 65, 1191–1215. [Google Scholar] [CrossRef]
  65. Gustafsson, A.; Kristensson, P.; Witell, L. Customer co-creation in service innovation: A matter of communication? J. Serv. Manag. 2012, 23, 311–327. [Google Scholar] [CrossRef]
  66. Gharehyazie, M.; Posnett, D.; Vasilescu, B.; Filkov, V. Developer initiation and social interactions in OSS: A case study of the Apache Software Foundation. Empir. Softw. Eng. 2015, 20, 1318–1353. [Google Scholar] [CrossRef]
  67. Li, R.; Pandurangan, P.; Frluckaj, H.; Dabbish, L. Code of conduct conversations in open source software projects on github. In Proceedings of the ACM on Human-Computer Interaction; ACM: New York, NY, USA, 2021; Volume 5, pp. 1–31. [Google Scholar]
  68. Stewart, K.J.; Gosain, S. The impact of ideology on effectiveness in open source software development teams. MIS Q. 2006, 30, 291–314. [Google Scholar] [CrossRef]
  69. Di Bella, E.; Sillitti, A.; Succi, G. A multivariate classification of open source developers. Inf. Sci. 2013, 221, 72–83. [Google Scholar] [CrossRef]
  70. Calefato, F.; Gerosa, M.A.; Iaffaldano, G.; Lanubile, F.; Steinmacher, I. Will you come back to contribute? Investigating the inactivity of OSS core developers in GitHub. Empir. Softw. Eng. 2022, 27, 76. [Google Scholar] [CrossRef]
  71. Iaffaldano, G.; Steinmacher, I.; Calefato, F.; Gerosa, M.; Lanubile, F. Why do developers take breaks from contributing to OSS projects? A preliminary analysis. In Proceedings of the International Workshop on Software Health (SoHeal ‘19), Montreal, QC, Canada, 28 May 2019; pp. 9–16. [Google Scholar]
  72. Coelho, J.; Valente, M.T. Why modern open source projects fail. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, Paderborn, Germany, 4–8 September 2017; pp. 186–196. [Google Scholar]
  73. Marsan, J.; Templier, M.; Marois, P.; Adams, B.; Carillo, K.; Mopenza, G.L. Toward solving social and technical problems in open source software ecosystems: Using cause-and-effect analysis to disentangle the causes of complex problems. IEEE Softw. 2018, 36, 34–41. [Google Scholar] [CrossRef]
  74. Mockus, A. Organizational volatility and its effects on software defects. In Proceedings of the Eighteenth ACM SIGSOFT Int’l Symposium on Foundations of Software Engineering, Santa Fe, NM, USA, 7–11 November 2010; ACM: New York, NY, USA, 2010; pp. 117–126. [Google Scholar]
  75. Foucault, M.; Palyart, M.; Blanc, X.; Murphy, G.C.; Falleri, J.R. Impact of developer turnover on quality in open-source software. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, Bergamo, Italy, 31 August–4 September 2015; ACM: New York, NY, USA, 2015; pp. 829–841. [Google Scholar]
  76. Schilling, A. What do we know about floss developers’ attraction, retention, and commitment? A literature review. In Proceedings of the 2014 47th Hawaii Int’l Conference On System Sciences, Waikoloa, HI, USA, 6–9 January 2014; IEEE: Piscataway, NJ, USA, 2014; pp. 4003–4012. [Google Scholar]
  77. Henkel, J. Champions of revealing—The role of open source developers in commercial firms. Ind. Corp. Chang. 2009, 18, 435–471. [Google Scholar] [CrossRef]
  78. Schmidt, K.M.; Schnitzer, M. Public subsidies for open source? Some economic policy issue of the software market. Harv. J. Law Technol. 2003, 16, 473–506. [Google Scholar] [CrossRef]
  79. David, P.A.; Waterman, A.; Arora, S. FLOSS-US the Free/Libre/Open Source Software Survey for 2003. Unpublished (Online). 2003. Available online: https://es.scribd.com/document/264266339/FLOSS-US-Report-pdf (accessed on 9 September 2024).
  80. Goldsmith, R.E.; Foxall, G.R. The measurement of innovativeness. In The International Handbook on Innovation; Shavinina, L.V., Ed.; Elsevier: Oxford, UK, 2003; pp. 321–330. [Google Scholar]
  81. Im, S.; Bayus, B.L.; Mason, C.H. An empirical study of innate consumer innovativeness, personal characteristics, and new-product adoption behavior. J. Acad. Mark. Sci. 2003, 31, 61–73. [Google Scholar] [CrossRef]
  82. Manning, K.C.; Bearden, W.O.; Madden, T.J. Consumer innovativeness and the adoption process. J. Consum. Psychol. 1995, 4, 329–345. [Google Scholar] [CrossRef]
  83. Roehrich, G. Consumer innovativeness—Concepts and measurements. J. Bus. Res. 2004, 57, 671–677. [Google Scholar] [CrossRef]
  84. Agarwal, R.; Prasad, J. A conceptual and operational definition of Personal Innovativeness in the Domain of Information Technology. Inf. Syst. Res. 1998, 9, 204–215. [Google Scholar] [CrossRef]
  85. Vargo, S.L.; Lusch, R.F. Institutions and axioms: An extension and update of service-dominant logic. J. Acad. Mark. Sci. 2016, 44, 5–23. [Google Scholar] [CrossRef]
  86. Woods, S.; Mustafa, M.; Anderson, N.R.; Sayer, B. Innovative work behavior and personality traits: Examining the moderating effects of organizational tenure. J. Manag. Psychol. 2018, 33, 29–42. [Google Scholar] [CrossRef]
  87. Handrich, M.; Heidenreich, S. The willingness of a customer to co-create innovative, technology-based services: Conceptualisation and measurement. Int. J. Innov. Manag. 2013, 17, 61–97. [Google Scholar] [CrossRef]
  88. Sarmah, B.; Kamboj, S.; Rahman, Z. Co-creation in hotel service innovation using smart phone apps: An empirical study. Int. J. Contemp. Hosp. Manag. 2017, 29, 2647–2667. [Google Scholar] [CrossRef]
  89. Baruah, T.D. Effectiveness of Social Media as a tool of communication and its potential for technology enabled connections: A micro-level study. Int. J. Sci. Res. Publ. 2012, 2, 1–10. [Google Scholar]
  90. Porter, C.E. A typology of virtual communities: A multi-disciplinary foundation for future research. J. Comput. Mediat. Commun. 2006, 10, JCMC1011. [Google Scholar] [CrossRef]
  91. Nambisan, S.; Baron, R.A. Virtual customer environments: Testing a model of voluntary participation in value co-creation activities. J. Prod. Innov. Manag. 2009, 26, 388–406. [Google Scholar] [CrossRef]
  92. Boyd, N.; Nowell, B.; Yang, Z.; Hano, M.C. Sense of community, sense of community responsibility, and public service motivation as predictors of employee well-being and engagement in public service organizations. Am. Rev. Public Adm. 2017, 48, 428–443. [Google Scholar] [CrossRef]
  93. Black, I.; Veloutsou, C. Working consumers: Co-creation of brand identity, consumer identity and brand community identity. J. Bus. Res. 2017, 70, 416–429. [Google Scholar] [CrossRef]
  94. Muniz, A.M.; O’guinn, T.C. Brand community. J. Consum. Res. 2001, 27, 412–432. [Google Scholar] [CrossRef]
  95. Rodríguez-López, N. Understanding value co-creation in virtual communities: The key role of complementarities and trade-offs. Inf. Manag. 2021, 58, 103487. [Google Scholar] [CrossRef]
  96. White, M.; Legg, E.; Foroughi, B.; Rose, J. Constructing past, present, and future communities: Exploring the experiences of community among last-dollar scholarship students. J. Community Psychol. 2019, 47, 805–818. [Google Scholar] [CrossRef]
  97. Liao, J.; Wang, W.; Du, P.; Filieri, R. Impact of brand community supportive climates on consumer-to-consumer helping behavior. J. Res. Interact. Mark. 2023, 17, 434–452. [Google Scholar] [CrossRef]
  98. Schiffman, L.; Kanuk, L. Consumer Behavior; Prentice Hall: Upper Saddle River, NJ, USA, 2007. [Google Scholar]
  99. Deci, E.L.; Ryan, R.M. Intrinsic Motivation and Self Determination in Human Behavior; Plenum Press: New York, NY, USA, 1985. [Google Scholar]
  100. Deci, E.L.; Ryan, R.M. The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior. Psychol. Inq. 2000, 11, 227–268. [Google Scholar] [CrossRef]
  101. Amabile, T.M.; Hill, K.G.; Hennessey, B.A.; Tighe, E.M. The work preference inventory—Assessing intrinsic and extrinsic motivational orientations. J. Personal. Soc. Psychol. 1994, 66, 950–967. [Google Scholar] [CrossRef] [PubMed]
  102. Ryan, R.M.; Deci, E.L. Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemp. Educ. Psychol. 2000, 25, 54–67. [Google Scholar] [CrossRef] [PubMed]
  103. Deci, E.L. The effects of contingent and non contingent rewards and controls on intrinsic motivation. Organ. Behav. Hum. Perform. 1972, 8, 217–229. [Google Scholar] [CrossRef]
  104. Coon, D.; Mitterer, J.O. Psychology: A Journey; Cengage Learning: Boston, MA, USA, 2010. [Google Scholar]
  105. Gagné, M.; Deci, E.L. Self-determination theory and work motivation. J. Organ. Behav. 2005, 26, 331–362. [Google Scholar] [CrossRef]
  106. Bagozzi, R.P.; Lee, K.H. Multiple routes for social influence: The role of compliance, internalization, and social identity. Soc. Psychol. Q. 2002, 65, 226–247. [Google Scholar] [CrossRef]
  107. Gottschalg, O.; Zollo, M. Interest alignment and competitive advantage. Acad. Manag. Rev. 2007, 32, 418–437. [Google Scholar] [CrossRef]
  108. Bilro, R.G.; Loureiro, S.M.C. I am feeling so good! Motivations for interacting in online brand communities. J. Res. Interact. Mark. 2023, 17, 61–77. [Google Scholar] [CrossRef]
  109. Jasperson, J.S.; Carter, P.E.; Zmud, R.W. A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Q. 2005, 29, 525–557. [Google Scholar] [CrossRef]
  110. Ko, D.G.; Krisch, L.J.; King, W.R. Antecedents of knowledge transfer from consultants to clients in enterprise system implementations. MIS Q. 2005, 29, 59–85. [Google Scholar] [CrossRef]
  111. Hoyer, W.D.; Chandy, R.; Dorotic, M.; Krafft, M.; Singh, S.S. Consumer cocreation in new product development. J. Serv. Res. 2010, 13, 283–296. [Google Scholar] [CrossRef]
  112. Mochon, D.; Norton, M.I.; Ariely, D. Bolstering and restoring feelings of competence via the IKEA effect. Int. J. Res. Mark. 2012, 29, 363–369. [Google Scholar] [CrossRef]
  113. Liang, H.; Wang, M.-M.; Wang, J.J.; Xue, Y. How intrinsic motivation and extrinsic incentives affect task effort in crowdsourcing contests: A mediated moderation model. Comput. Hum. Behav. 2018, 81, 168–176. [Google Scholar] [CrossRef]
  114. Agarwal, R.; Karahanna, E. Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Q. 2000, 24, 665–694. [Google Scholar] [CrossRef]
  115. Fleeson, W. Toward a structure- and process-integrated view of personality: Traits as density distributions of states. J. Personal. Soc. Psychol. 2001, 80, 1011–1027. [Google Scholar] [CrossRef]
  116. Respondek, L.; Seufert, T.; Nett, U.E. Adding previous experiences to the person-situation debate of achievement emotions. Contemp. Educ. Psychol. 2019, 58, 19–32. [Google Scholar] [CrossRef]
  117. Füller, J. Refining virtual co-creation from a consumer perspective. Calif. Manag. Rev. 2010, 5, 98–122. [Google Scholar] [CrossRef]
  118. McMillan, D.W.; Chavis, D.M. Sense of community: A definition and theory. J. Community Psychol. 1986, 14, 6–23. [Google Scholar] [CrossRef]
  119. O’Brien, L.T.; Bart, H.L.; Garcia, D.M. Why are there so few ethnic minorities in ecology and evolutionary biology? Challenges to inclusion and the role of sense of belonging. Soc. Psychol. Educ. 2020, 1–29. [Google Scholar] [CrossRef]
  120. Constantinides, E.; Romero, C.L.; Boria, M.A.G. Social media: A new frontier for retailers? In European Retail Research; Swoboda, B., Morschett, D., Rudolph, T., Schnedlitz, P., Schramm-Klein, H., Eds.; Springer: Berlin/Heidelberg, Germany, 2008; Volume 22, pp. 1–28. [Google Scholar]
  121. Brodie, R.J.; Ilic, A.; Juric, B.; Hollebeek, L. Consumer engagement in a virtual brand community: An exploratory analysis. J. Bus. Res. 2013, 66, 105–114. [Google Scholar] [CrossRef]
  122. Dholakia, U.M.; Bagozzi, R.P.; Pearo, L.K. A social influence model of consumer participation in network- and small-group-based virtual communities. Int. J. Res. Mark. 2004, 21, 241–263. [Google Scholar] [CrossRef]
  123. Augustine, A.A.; Hemenover, S.H.; Larsen, R.J.; Shulman, T.E. Composition and consistency of the desired affective state: The role of personality and motivation. Motiv. Emot. 2010, 34, 133–143. [Google Scholar] [CrossRef] [PubMed]
  124. Kim, E.; Tang, L.; Bosselman, R. Customer perceptions of innovativeness: An accelerator for value co-creation. J. Hosp. Tour. Res. 2019, 43, 807–838. [Google Scholar] [CrossRef]
  125. Locke, E.A.; Latham, G.P. A Theory of Goal Setting and Task Performance; Prentice-Hall: Englewood Cliffs, NJ, USA, 1990. [Google Scholar]
  126. Locke, E.A.; Latham, G.P. Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. Am. Psychol. 2002, 57, 705–717. [Google Scholar] [CrossRef]
  127. Kark, R.; van Dijk, D. Motivation to lead, motivation to follow: The role of the self-regulatory focus in leadership processes. Acad. Manag. Rev. 2007, 32, 500–528. [Google Scholar] [CrossRef]
  128. Tett, R.P.; Burnett, D.D. A personality trait-based interactionist model of job performance. J. Appl. Psychol. 2003, 88, 500–517. [Google Scholar] [CrossRef]
  129. Li, X.; Hsieh, J.J.P.A.; Rai, A. Motivational differences across post-acceptance information system usage behaviors: An investigation in the business intelligence systems context. Inf. Syst. Res. 2013, 24, 659–682. [Google Scholar] [CrossRef]
  130. Ryan, R.M.; Deci, E.L. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am. Psychol. 2000, 55, 68–78. [Google Scholar] [CrossRef]
  131. McCrae, R.R.; Sutin, A.R. A five-factor theory perspective on causal analysis. Eur. J. Personal. 2018, 32, 151–166. [Google Scholar] [CrossRef]
  132. Bleidorn, W.; Kandler, C.; Hülsheger, U.R.; Riemann, R.; Angleitner, A.; Spinath, F.M. Nature and nurture of the interplay between personality traits and major life goals. J. Personal. Soc. Psychol. 2010, 99, 366–379. [Google Scholar] [CrossRef] [PubMed]
  133. Söderlund, J.; Bredin, K. Participants in the process of knowledge integration. In Knowledge Integration and Innovation: Critical Challenges Facing International Technology-Based Firms; Berggren, C., Bergek, A., Bengtsson, L., Hobday, M., Söderlund, J., Eds.; Oxford University Press: Oxford, UK, 2011; pp. 96–121. [Google Scholar]
  134. Jiménez, A.; Zheng, Y. Unpacking the multiple spaces of innovation hubs. Inf. Soc. 2021, 37, 163–176. [Google Scholar] [CrossRef]
  135. Armstrong, J.S.; Overton, T.S. Estimating nonresponse bias in mail surveys. J. Mark. Res. 1977, 14, 396–402. [Google Scholar] [CrossRef]
  136. Weiss, A.M.; Heide, J.B. The nature of organizational search in high technology markets. J. Mark. Res. 1993, 30, 220–233. [Google Scholar] [CrossRef]
  137. Podsakoff, P.M.; Organ, D.W. Self-reports in organizational research: Problems and prospects. J. Manag. 1986, 12, 531–544. [Google Scholar] [CrossRef]
  138. Jarvis, C.B.; Mackenzie, S.B.; Podsakoff, P.M. A critical review of construct indicators and measurement model misspecification in marketing and consumer research. J. Consum. Res. 2003, 30, 199–218. [Google Scholar] [CrossRef]
  139. Ke, W.; Tan, C.H.; Sia, C.L.; Wei, K.K. Inducing intrinsic motivation to explore the enterprise system: The supremacy of organizational levers. J. Manag. Inf. Syst. 2012, 29, 257–290. [Google Scholar] [CrossRef]
  140. Gebauer, J.; Füller, J.; Pezzei, R. The dark and the bright side of co-creation: Triggers of member behavior in online innovation communities. J. Bus. Res. 2013, 66, 1516–1527. [Google Scholar] [CrossRef]
  141. Im, S.; Mason, C.H.; Houston, M.B. Does innate consumer innovativeness relate to new product/service adoption behavior? The intervening role of social learning via vicarious innovativeness. J. Acad. Mark. Sci. 2007, 35, 63–75. [Google Scholar] [CrossRef]
  142. Gerbing, D.W.; Anderson, J.C. An updated paradigm for scale development incorporating unidimensionality and its assessment. J. Mark. Res. 1988, 25, 186–192. [Google Scholar] [CrossRef]
  143. Hair, J.F.; Black, W.C.; Babin, B.J.; Anderson, R.E. Multivariate Data Analysis, 8th ed.; Cengage Learning, EMEA: Hampshire, UK, 2019. [Google Scholar]
  144. Hu, L.; Bentler, P.M. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equ. Model. A Multidiscip. J. 1999, 6, 1–55. [Google Scholar] [CrossRef]
  145. Byrne, B.M. Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming, 3rd ed.; Routledge: New York, NY, USA, 2016; Volume 460. [Google Scholar]
  146. Bagozzi, R.P.; Yi, Y. On the evaluation of structural equation models. J. Acad. Mark. Sci. 1988, 16, 74–94. [Google Scholar] [CrossRef]
  147. Anderson, J.C.; Gerbing, D.W. Structural equation modeling in practice: A review and recommended two-step approach. Psychol. Bull. 1988, 103, 411–423. [Google Scholar] [CrossRef]
  148. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. J. Mark. Res. 1981, 18, 39–50. [Google Scholar] [CrossRef]
  149. Bullock, H.E.; Harlow, L.L.; Mulaik, S. Causation issues in structural modeling research. Struct. Equ. Model. J. 1994, 1, 253–267. [Google Scholar] [CrossRef]
  150. Preacher, K.J.; Rucker, D.D.; Hayes, A.F. Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivar. Behav. Res. 2007, 42, 185–227. [Google Scholar] [CrossRef]
  151. Guzel, M.; Sezen, B.; Alniacik, U. Drivers and consequences of customer participation into value co-creation: A field experiment. J. Prod. Brand Manag. 2021, 30, 1047–1061. [Google Scholar] [CrossRef]
  152. Hirsh, J.B.; Dolderman, D. Personality predictors of consumerism and environmentalism: A preliminary study. Personal. Individ. Differ. 2007, 43, 1583–1593. [Google Scholar] [CrossRef]
  153. Bosnjak, M.; Bratko, D.; Galesic, M.; Tuten, T. Consumer personality and individual differences: Revitalizing a temporarily abandoned field. J. Bus. Res. 2007, 60, 587–589. [Google Scholar] [CrossRef]
  154. Nohutlu, Z.D.; Englis, B.G.; Groen, A.J.; Constantinides, E. Customer cocreation experience in online communities: Antecedents and outcomes. Eur. J. Innov. Manag. 2022, 25, 630–659. [Google Scholar] [CrossRef]
  155. Talò, C.; Mannarini, T.; Rochira, A. Sense of Community and Community Participation: A Meta-Analytic Review. Soc. Indic. Res. 2014, 117, 1–28. [Google Scholar] [CrossRef]
  156. Hilal, A.; Varela-Neira, C. Understanding consumer adoption of mobile banking: Extending the UTAUT2 model with proactive personality. Sustainability 2022, 14, 14708. [Google Scholar] [CrossRef]
  157. Hars, A.; Ou, S. Working for free?—Motivations of participating in open source projects. Int. J. Electron. Commer. 2002, 6, 25–39. [Google Scholar]
  158. Ye, Y.; Kishida, K. Toward an understanding of the motivation of open source software developers. In Proceedings of the 25th International Conference on Software Engineering, ICSE, Portland, OR, USA, 3–10 May 2003; pp. 419–429. [Google Scholar]
  159. Tamilmani, K.; Rana, N.P.; Dwivedi, Y.K. Consumer acceptance and use of information technology: A meta-analytic evaluation of UTAUT2. Inf. Syst. Front. 2021, 23, 987–1005. [Google Scholar] [CrossRef]
  160. Nave, G.; Minxha, J.; Greenberg, D.M.; Kosinski, M.; Stillwell, D.; Rentfrow, J. Musical preferences predict personality: Evidence from active listening and Facebook likes. Psychol. Sci. 2018, 29, 1145–1158. [Google Scholar] [CrossRef] [PubMed]
  161. Park, G.; Schwartz, H.A.; Eichstaedt, J.C.; Kern, M.L.; Kosinski, M.; Stillwell, D.J.; Ungar, L.H.; Seligman, M.E. Automatic personality assessment through social media language. J. Personal. Soc. Psychol. 2015, 108, 934–952. [Google Scholar] [CrossRef] [PubMed]
  162. Gladstone, J.J.; Matz, S.C.; Lemaire, A. Can psychological traits be inferred from spending? Evidence from transaction data. Psychol. Sci. 2019, 30, 1087–1096. [Google Scholar] [CrossRef]
  163. Koh, J.; Kim, Y.; Kim, Y. Sense of virtual community: A conceptual framework and empirical validation. Int. J. Electron. Commer. 2003, 8, 75–94. [Google Scholar] [CrossRef]
  164. DigitalOcean Currents. A Seasonal Report on Developer Trends in the Cloud: Open Source Edition. 2018. Available online: https://currents.nyc3.cdn.digitaloceanspaces.com/DigitalOcean-Currents-Q3-2018.pdf (accessed on 24 June 2024).
  165. DigitalOcean Currents. The 2022 Report on Open Source and Developer Trends. 2022. Available online: https://anchor.digitalocean.com/rs/113-DTN-266/images/DigitalOcean-Currents_June-2022.pdf (accessed on 24 June 2024).
  166. Williams, A. Standing Together on Shared Challenges. Report on the 2023 Open Source Congress. 2023. Available online: https://www.linuxfoundation.org/hubfs/LF%20Research/Standing%20Together%20on%20Shared%20Challenges%20Report%20on%20the%202023%20Open%20Source%20Congress.pdf?hsLang=en (accessed on 9 September 2024).
  167. Roy-Chowdhury, R. Why Open-Source Is Crucial for Responsible AI Development. 2023. Available online: https://www.weforum.org/agenda/2023/12/ai-regulation-open-source/ (accessed on 9 September 2024).
  168. Mckinsey. The Economic Potential of Generative AI: The Next Productivity Frontier. 2023. Available online: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-AI-the-next-productivity-frontier#/ (accessed on 9 September 2024).
  169. Ng, C.S.P. Intention to purchase on social commerce websites across cultures: A crossregional study. Inf. Manag. 2013, 50, 609–620. [Google Scholar] [CrossRef]
Table 1. Path model summary: direct effects.
Table 1. Path model summary: direct effects.
Exogenous VariablesCo-Creation ParticipationIntrinsic Hedonic MotivationIntrinsic Normative Motivation
Ln_age5.0520.276 *0.061
Gender−2.246−0.046−0.030
Innate innovativeness (IN)14.912 **0.746 **0.371 **
Sense of community (SC)10.361 **0.254 **0.485 **
IN × SC 0.090 **0.223 **
Intrinsic hedonic motivation (IHM)1.205
Intrinsic normative motivation (INM)5.601 **
IHM × IN3.346 *
INM × IN2.418 **
R-squared0.3500.5130.396
** p < 0.01; * p < 0.05.
Table 2. Bootstrap analysis: conditional indirect effects.
Table 2. Bootstrap analysis: conditional indirect effects.
RelationshipsINSCEffectSELLCIULCI
SC → IHM → CPLow −0.4010.299−1.0570.141
SC → IHM → CPModerate 0.3070.450−0.6071.186
SC → IHM → CPHigh 1.8200.991−0.0233.884
SC → INM → CPLow 0.6360.525−0.2251.895
SC→ INM→ CPModerate 2.7160.8281.1244.374
SC→ INM→ CPHigh 6.2391.8532.6659.937
IN → IHM → CPLowLow−1.6891.241−4.1530.722
IN → IHM → CPModerateLow−1.9891.474−4.8970.847
IN → IHM → CPHighLow−2.2891.710−5.6830.973
IN → IHM → CPLowModerate0.7631.105−1.3873.001
IN → IHM → CPModerateModerate0.8991.293−1.6403.485
IN → IHM → CPHighModerate1.0341.483−1.9183.936
IN → IHM → CPLowHigh3.2151.749−0.1816.792
IN → IHM → CPModerateHigh3.7862.052−0.2427.886
IN → IHM → CPHighHigh4.3582.363−0.3078.981
IN → INM → CPLowLow0.2570.263−0.0541.054
IN → INM → CPModerateLow1.0390.755−0.5602.486
IN → INM → CPHighLow1.8201.297−0.9864.210
IN→ INM→ CPLowModerate0.5130.3430.0051.388
IN→ INM→ CPModerateModerate2.0760.6690.8613.518
IN→ INM→ CPHighModerate3.6391.1081.4845.900
IN→ INM→ CPLowHigh0.7700.5090.0212.082
IN→ INM→ CPModerateHigh3.1141.0431.2375.283
IN→ INM→ CPHighHigh5.4571.7572.1238.961
Note: rows in italics indicate statistically significant relationships.
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Rebelo, A.; Varela-Neira, C.; Ruzo-Sanmartín, E. Boosting Customers’ Co-Creation in Open-Source Software Environments: The Role of Innovativeness and a Sense of Community. J. Theor. Appl. Electron. Commer. Res. 2024, 19, 2476-2496. https://doi.org/10.3390/jtaer19030119

AMA Style

Rebelo A, Varela-Neira C, Ruzo-Sanmartín E. Boosting Customers’ Co-Creation in Open-Source Software Environments: The Role of Innovativeness and a Sense of Community. Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(3):2476-2496. https://doi.org/10.3390/jtaer19030119

Chicago/Turabian Style

Rebelo, Antonio, Concepción Varela-Neira, and Emilio Ruzo-Sanmartín. 2024. "Boosting Customers’ Co-Creation in Open-Source Software Environments: The Role of Innovativeness and a Sense of Community" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 3: 2476-2496. https://doi.org/10.3390/jtaer19030119

APA Style

Rebelo, A., Varela-Neira, C., & Ruzo-Sanmartín, E. (2024). Boosting Customers’ Co-Creation in Open-Source Software Environments: The Role of Innovativeness and a Sense of Community. Journal of Theoretical and Applied Electronic Commerce Research, 19(3), 2476-2496. https://doi.org/10.3390/jtaer19030119

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