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The research purpose is to investigate the mediating and moderating relationships between smartphone addiction and well-being (i.e. health-related quality of life).

A survey of 236 smartphone users was used to test the research model.

The structural equation modeling analysis results show that smartphone addiction negatively impacts well-being by draining a key personal resource, energy, thus creating strain. The adverse effect of smartphone addiction on users' well-being is found to be more intense when smartphones are used for hedonic purposes.

Through the conservation of resources theory lens, this study increases our understanding of the role of strain in mediating the negative effect of smartphone addiction on well-being. This study also has practical implications. By exploring the mediating and moderating mechanisms underlying when and how smartphone addiction can be detrimental to well-being, interventions can be carried out to mitigate the adverse effects on well-being.

Past research has focused on the antecedents and consequences of smartphone addiction while ignoring the contextual factors of smartphone addiction effects as well as the intervening mechanism through which smartphone addiction impacts well-being. Through the lens of the conservation of resources theory, we close this gap in the literature by providing a better understanding of the mechanism by which smartphone addiction reduces well-being and identifying a relevant contextual factor (i.e. hedonic use) that can worsen the impact of smartphone addiction on well-being.

The need for accelerating innovation is exacerbated as organizations struggle to either adapt or perish in this unforgiving condition due to the COVID-19 disruption. To address this issue, many organizations have embraced employee-driven participatory innovation to survive and thrive albeit the uncertainties. This study aims to investigate the role of enterprise social media (ESM) in supporting and facilitating these efforts.

This study first identified the underlying mechanisms that allow ESM use to foster and maintain participatory innovation and then reexamined how these mechanisms played out during the COVID-19 lockdown restrictions. The data was collected through a questionnaire in two phases, before and during work-from-home mandates, and the results were analyzed and compared to capture similarities and differences.

The results revealed that innovation culture and management support mediated the effects of ESM use on three measures of innovation productivity in both conditions. Interestingly, the effect of ESM use was more prominent in driving innovation in the work-from-home condition. This effect was not limited to the direct effect of ESM use on innovation productivity but on innovation culture and management support as well.

The results suggest that ESM offer a potentially useful path to support and enable employees to participate in the innovation processes, especially when they work remotely or in a distributed team. More generally, this paper should be of interest to researchers and practitioners interested in understanding, implementing and evaluating enterprise social software applications and encouraging employee-driven participatory innovation.

With the emergence of the sharing economy paradigm, the process of innovation is no longer unidirectional, but cyclical. This paradigm shift requires a better understanding of social actors to fully leverage the promise of co-innovation in the sharing economy. To this end, the purpose of this paper is to develop a classification model to profile social actors based on their motivation to participate in different co-innovation activities.

A preliminary case study was first conducted to identify actors’ motivations to continuously participate in co-innovation activities. Next, a survey was administrated to validate the measurement model and then a discriminant analysis was run on a sample of 244 actors to classify actors based on their willingness to participate in three forms of co-innovation activities. Lastly, the resultant classifiers were cross-validated.

The results indicate that financial gains, entrepreneurship and learning are significant predictors of ideation (sharing new ideas). Enjoyment and learning are strong indicators of collaboration (sharing knowledge or experience), whereas networking, enjoyment, and altruism are most strongly related to socialization (sharing network and connections). These findings highlight three classes of social actors – ideators, collaborators and networkers – based on motivational differences.

Co-innovation among individual inventors is an understudied aspect of the sharing economy. This study provides a theoretically parsimonious classification model to profile social actors, predict the sharing activities in co-innovation networks, and highlight the importance of platform design to appeal to different classes of potential contributors in collaborative innovation.

Enterprise social media (ESM) applications offer new opportunities for organizations to mobilize employees for open innovation, by promoting innovation beyond traditional R&D functions. Despite the popularity and success of these applications, current research has yet to fully explore the potential of ESM applications as a driver of employee-driven innovation, specifically through advancements in innovation culture. To fill this gap, this study proposes a theoretical framework that explains the role of ESM applications in facilitating employee innovation.

The authors administered a cross-sectional survey to collect data from professionals who use ESM applications regularly at work. Following a pilot study and instrument refinement, the authors conducted a field study to test measurement and the structural model by using the partial least square-structural equation modeling (PLS-SEM) method.

The findings of this study support the validity of the proposed theoretical model. First, the results confirmed the three antecedents of ESM use for innovation: perceived innovation possibilities enabled by ESM technology, the expected value of ESM use for innovation and organizational support for using ESM applications for innovation. Next, the results confirmed the importance of ESM use in encouraging individual innovation productivity in terms of product/service innovation, process innovation and social innovation. Finally, the results corroborated the mediating role of risk-taking and knowledge-sharing culture in the use of ESM to increase innovation productivity.

The findings presented here have implications for theory and practices that would concern fostering a supportive environment and building an organizational culture that promotes employees' innovation behavior (internal open innovation) by using social technologies.

This paper aims to analyze the moderating effect of knowledge leakage on the relationship between absorptive capacity and co-innovation, which implies collaborative work and knowledge exchange with external actors on virtual innovation platforms.

The research model was tested in a sample of companies through the use of structural equations by the partial least squares method.

The results confirm that absorptive capacity is a prior condition for co-innovation. However, the most interesting and surprising result has to do with knowledge leakage, which actually has a negative moderating effect, but whose size is modest, which dismisses the great damages that such leakage could generate.

This study is pioneering in analyzing knowledge leakage in the context of virtual innovation platforms, which occurs in a different manner as compared to leakage in the context of collaborative research and development, widely analyzed in the literature. However, the main contribution of the paper lies in the fact that the results evidence the existence of an intermediate position between the traditional approach that insists on demonstrating the devastating consequences of the leakage and the emerging approach that dismisses these negative repercussions and conceives leakage as a positive organizational phenomenon, natural and inherent to the interaction of the firm with the environment. The results also contradict recent empirical evidence that completely dismisses the negative repercussions of knowledge leakage in contexts where incremental innovations prevail.

Recent advancements in Artificial Intelligence (AI) and, at its core, Machine Learning (ML) offer opportunities for organizations to develop new or enhance existing capabilities. Despite the endless possibilities, organizations face operational challenges in harvesting the value of ML-based capabilities (MLbC), and current research has yet to explicate these challenges and theorize their remedies. To bridge the gap, this study explored the current practices to propose a systematic way of orchestrating MLbC development, which is an extension of ongoing digitalization of organizations.

Data were collected from Finland's Artificial Intelligence Accelerator (FAIA) and complemented by follow-up interviews with experts outside FAIA in Europe, China and the United States over four years. Data were analyzed through open coding, thematic analysis and cross-comparison to develop a comprehensive understanding of the MLbC development process.

The analysis identified the main components of MLbC development, its three phases (development, release and operation) and two major MLbC development challenges: Temporal Complexity and Context Sensitivity. The study then introduced Fostering Temporal Congruence and Cultivating Organizational Meta-learning as strategic practices addressing these challenges.

This study offers a better theoretical explanation for the MLbC development process beyond MLOps (Machine Learning Operations) and its hindrances. It also proposes a practical way to align ML-based applications with business needs while accounting for their structural limitations. Beyond the MLbC context, this study offers a strategic framework that can be adapted for different cases of digital transformation that include automation and augmentation of work.

The current study aims to advance the research on the extra-industry network, innovativeness and performance of small and medium enterprises (SMEs) by examining the mediation role of proactiveness. The study also aims to examine the mediating role innovativeness between extra-industry network and performance.

This study used the proportionate stratified random sampling method to select the study sample and the questionnaire survey approach to 580 SMEs. A total of 150 completed questionnaires were returned. Partial least squares structural equation modeling was administered to analyze data via Smart PLS 3.0 software.

The results reflect that proactiveness is mediated by the relationship between the extra-industry network and the performance of Iranian SMEs. In addition, the results illustrated that proactiveness is mediated by the relationship between innovativeness and the performance. The findings also address the limitation of previous studies on Iranian SMEs through the independent examination of the mediating role of innovativeness between firm extra-industry network and performance.

This article is one of few attempts that have addressed the significance of proactiveness as the key mechanism to transform the advantages of extra-industry network and innovativeness relationships to enhance performance.

Co-innovation networks face the important challenge of cultivating collective innovation outcomes while also preserving the interests of individual contributors. Addressing this challenge requires first understanding and then managing individuals’ perception of co-innovation risks. The purpose of this paper is to provide a meaningful approach to addressing co-innovation risks using a valid and reliable model to assess actors’ perception of risk and examine its effect on actor co-innovation behavior.

The construct of co-innovation risk from the actor’s perspective was conceptualized based on a case study of a co-innovation network. The measurement items underwent a pilot study and a field study to establish the necessary reliability and validity. This paper also empirically assesses a nomological network that illustrates the effect of risk on co-innovation behavior with a moderating effect of prior experience.

Co-innovation actors perceived four different individual risks: time, social, intellectual property right, and financial. The empirical results from the field study demonstrate a high degree of confidence in both translation validity and criterion-related validity. Negative effects of perceived co-innovation risk on actors’ continuous intention to ideate, collaborate, and communicate in co-innovation were evident, but prior experience moderated these relationships.

Drawing from co-innovation and individual risk literature, this study develops and validates a general instrument to measure co-innovation risk from the actors’ perspective. The result is a reliable and parsimonious instrument with 15 items, which contributes significantly to future empirical investigations of co-innovation behavior on virtual platforms.

The proliferation of non-fungible token (NFT)-based crypto-art platforms has transformed how creators manage, own and earn money through the creation, assets and identity of their digital works. Despite this, no studies have examined the drivers of continuous content contribution behavior (CCCB) toward NFTs. Hence, this study draws on the theory of relational bonds to examine how various relational bonds affect feelings of psychological ownership, which, in turn, affects CCCB on metaverse platforms.

Using structural equation modeling and importance-performance matrix analysis, an online survey of 434 content creators from prominent NFT platforms empirically validated the research hypotheses.

Financial, structural, and social bonds positively affect psychological ownership, which in turn encourages CCCBs. The results of the importance-performance matrix analysis reveal that male content creators prioritized virtual reputation and social enhancement, whereas female content creators prioritized personalization and monetary gains.

We examine Web 3.0 and the NFT creators’ network that characterizes the governance practices of the metaverse. Consequently, the findings facilitate a better understanding of creator economy and meta-verse commerce.

The discussion on co-innovation inhibitors usually focuses on external actors’ opportunism, related to the loss of intellectual property. However, from the organizational Machiavellianism perspective, inhibitors are not external as the company itself is a source of constraints. Unfortunately, there is a lack of research studies examining the possible negative impact of organizational Machiavellian behavior such as amorality or distrust and desire for control, which could destroy external partners’ trust and commitment. This paper aims to analyze the effect of organizational Machiavellianism on the relationship between co-innovation and innovation performance (product and process innovation).

Structural equations were used to test the research model using survey data from a sample of companies located in an emerging country with a high risk of corruption.

Surprisingly, distrust and desire for control do not moderate the relationship between co-innovation and innovation performance, but do have a positive and direct effect on innovation performance. Conversely, amorality has a negative moderating effect on this relationship.

The study reveals that amorality is an evident constraint of the positive impact of co-innovation, as it diminishes the amount and quality of external actors’ contributions in terms of new ideas and knowledge. In contrast, distrust and desire for control alert the firm about opportunistic behavior by external partners such as technology providers, who may induce the firm to adopt an inadequate technological standard in line with their commercial interests.