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This paper aims to present a novel framework for an artificial intelligence (AI)-powered Employee Experience Management (EXM) platform that addresses strategic HR concerns such as employee engagement, personal and professional development and job satisfaction.

This paper conducted a comprehensive study of the applications of AI technology in HR management and workforce development between 2020 and 2023. The study results were then contextualized in the context of EXM to identify an innovative employee-centered framework.

This paper presents a novel framework comprising three essential elements: advanced sentiment analytics, context-sensitive career crafting and augmented mentorship. These elements are introduced with the purpose of enhancing the employee experience by leveraging AI technology to provide personalized support.

This paper presents possibilities and priorities in designing the next generation of EXM platforms. Furthermore, this paper offers criteria for evaluating and selecting emerging EXM technologies to guide organizations in adopting future EXM platforms.

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 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.

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.

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.

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 importance of co-innovation platforms has been well established, but a valid and reliable instrument to measure the affordances of these platforms for co-innovation behavior has not yet been reported in the literature. A robust, validated instrument to measure co-innovation platform affordances (PAs) will facilitate the conduct of studies across different platforms and contribute to enhanced understanding of co-innovation behaviors, outcomes, and platform design. The purpose of this paper is to conceptualize co-innovation PAs, develop a reliable measurement instrument capturing critical facets of co-innovation, namely ideation, collaboration, and communication, and validate the instrument.

The construct of PAs was conceptualized based on the findings from two case studies of co-innovation networks and the key characteristics of social mediating technology affordances. The measurement items newly developed via a case study underwent a two-round exploratory analysis to ensure face validity and content validity. The resulting instrument was subjected to a pilot study and a field study to establish the necessary reliability and validity.

The findings of the study reveal that co-innovation PAs have three distinctive components, namely ideation, collaboration, and communication. Furthermore, the results of the study suggest that PAs are most appropriately operationalized as a second-order construct comprising all three components. The empirical results from the field study show a high degree of confidence in both translation validity and criterion-related validity.

Drawing from co-innovation and affordances literature, this study develops and validates a general instrument to measure co-innovation PAs. The result is a reliable and parsimonious instrument with 12 items. The authors believe that the instrument can contribute significantly to future empirical investigations of co-innovation behavior on virtual platforms.

This chapter focuses upon high school preparation and transition planning activities as they apply to students with disabilities. The reader will find a review of needs for reform of high school standards-based curricula, the development of inclusive general education curriculum content, and strategies for integrating functional and daily living skill training and meaningful transition planning activities, which include collaboration with adult agencies. The authors further present a number of evidence-based practices to address these needs and make recommendations for moving forward in ways to improve post-school outcomes for youth with disabilities.