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With the increasing popularity of online games like Pokémon Go, a new wave of crowdsourcing communities have emerged, allowing gamers to collaborate, communicate and share useful game-related information. This paper aims to examine the factors that influence gamers' crowdsourcing behaviour.

A conceptual framework is developed that combines the DeLone & McLean model, self-determination theory, and different levels of engagement behaviour. The online survey collected 371 responses that were analysed using Covariance Based Structural Equation Modelling (CB-SEM).

The results show that extrinsic and intrinsic motivation positively influenced gamers' crowdsourcing engagement intention. System quality and information quality were also confirmed to be positively associated with gamers' crowdsourcing engagement intention. Furthermore, crowdsourcing engagement intention was found to be positively associated with crowdsourcing content consumption, contribution, and creation.

The findings of this study are useful for the owners of Pokémon Go and other gaming-related crowdsourcing platforms in devising tailored strategies to increase the crowdsourcing engagement of gamers.

This study provides the first empirical evidence of factors motivating online gamers' crowdsourcing intention. This study also presents novel insight into online gamers' crowdsourcing intention by combining diverse theories which offer different perspectives and a more comprehensive understanding of the phenomenon. Contribution to the research on the intention-behaviour gap by modelling three behavioural outcomes (content creation, contribution, and consumption behaviour) of crowdsourcing engagement intention, is another important contribution of this study.

Limited by the types of sensors, the state information available for musculoskeletal robots with highly redundant, nonlinear muscles is often incomplete, which makes the control face a bottleneck problem. The aim of this paper is to design a method to improve the motion performance of musculoskeletal robots in partially observable scenarios, and to leverage the ontology knowledge to enhance the algorithm’s adaptability to musculoskeletal robots that have undergone changes.

A memory and attention-based reinforcement learning method is proposed for musculoskeletal robots with prior knowledge of muscle synergies. First, to deal with partially observed states available to musculoskeletal robots, a memory and attention-based network architecture is proposed for inferring more sufficient and intrinsic states. Second, inspired by muscle synergy hypothesis in neuroscience, prior knowledge of a musculoskeletal robot’s muscle synergies is embedded in network structure and reward shaping.

Based on systematic validation, it is found that the proposed method demonstrates superiority over the traditional twin delayed deep deterministic policy gradients (TD3) algorithm. A musculoskeletal robot with highly redundant, nonlinear muscles is adopted to implement goal-directed tasks. In the case of 21-dimensional states, the learning efficiency and accuracy are significantly improved compared with the traditional TD3 algorithm; in the case of 13-dimensional states without velocities and information from the end effector, the traditional TD3 is unable to complete the reaching tasks, while the proposed method breaks through this bottleneck problem.

In this paper, a novel memory and attention-based reinforcement learning method with prior knowledge of muscle synergies is proposed for musculoskeletal robots to deal with partially observable scenarios. Compared with the existing methods, the proposed method effectively improves the performance. Furthermore, this paper promotes the fusion of neuroscience and robotics.

Customer referral programs (CRPs) are popular; however, they often generate low referral rates. The authors propose that certain CRP referral tasks may hinder consumers’ referral likelihood. This study aims to explore the effects of referral tasks (communication content and approach) on customers’ referral likelihood on social platforms and the role of self-construal.

This study establishes a theoretical model based on online social platforms and conducts three scenario-based experiments. The authors obtain data from consumers on Sojump platform and test the hypotheses using analysis of variance (ANOVA) analysis and mediation analysis in SPSS. The valid sample sizes for these three experiments are 288, 203 and 214, respectively.

Three experimental studies indicate that communication content and approach have a significant effect on referral likelihood. Furthermore, the effect of communication content on referral likelihood depends on the communication approach. Self-construal plays a moderating role in the effect of communication content and approach on perceived social costs.

CRPs typically involve tasks and rewards; consumers are asked to complete a referral task and then receive a reward. Both tasks and rewards can affect an individual’s willingness to participate; however, existing studies on CRP focus primarily on the reward component. To the best of the authors’ knowledge, this is the first study to systematically investigate the role of referral tasks (communication content and approach) in CRPs. The authors extend the related research by examining the impact of referral tasks on consumers’ willingness to recommend. In addition, this study introduces self-construal into CRPs research.

Small and medium-sized enterprises (SMEs), typically with limited resources, strive hard to obtain the trust of ecosystem participants as an orchestrator. Accordingly, the firms do not have sufficient legitimacy to persuade other parties to join their networks. This study aims to investigate how an SME operating in the publishing industry orchestrates ecosystem participants. In particular, the study analyzes how the orchestrating firm stimulates interactions among ecosystem participants.

Case study research with a qualitative approach has been documented as a well-accepted method for investigating complex phenomena and for theory building. Collected data from various informants and different collection techniques are triangulated to ensure validity. Cross-case analysis to identify common patterns is undertaken as the basis for developing a sound conclusion.

The study demonstrated what orchestrating firms should do to foster innovations and how they benefit from other participants in the ecosystem. The analysis identified the orchestrator's four roles: entrepreneurship networks, knowledge activation, innovation intermediary and network leadership. Among the four roles, there are interrelationships, and to some degree, these overlap. The orchestrating firm must emerge into the ecosystem and work together with all members of the ecosystem. Managers of the orchestrating firm and network members should collaborate to find the most beneficial configuration for all ecosystem participants.

This research is limited to the knowledge-intensive publishing industry. The use of specific industries closely related to innovation provides an advantage in the way that enables researchers to conduct depth analysis, but at the expense of generalizability, and therefore, future research can analyze different industries.

This study focuses on networks as the unit of analysis. Previous studies assumed individual firms as the unit of analysis and ignored the fact that companies interact with other companies when pursuing open innovation. The study focuses on the interactions between actors as the unit of analysis and on the role of orchestrators undertaken by an SME.

Researchers continue to address the concept of self-disclosure because it is foundational for helping social networking sites (SNS) function and thrive. Nevertheless, the authors' literature review indicates that uncertainty remains around the underlying mechanisms and factors involved in the self-disclosure process. The purpose of this research is to better understand the self-disclosure process from the lens of dual-process theory (DPT). The authors consider both the controlled factors (i.e. self-presentation and reciprocity) and an automatic factor (i.e. social influence to use an SNS) involved in self-disclosure and broaden The authors proposed a model to include the interactive facets of enjoyment.

The proposed model was empirically validated by conducting a survey among users of WeChat Moments in China.

As hypothesized, this research confirms that enjoyment and automatic processing (i.e. social influence to use an SNS) are complementary in the SNS self-disclosure process and enjoyment negatively moderates the positive relationship between controlled factor (i.e. self-presentation) and self-disclosure.

Theoretically, this study offers a new perspective on explaining SNS self-disclosure by adopting DPT. Specifically, this study contributes to the extant SNS research by applying DPT to examine how the controlled factors and the automatic factor shape self-disclosure processes and how enjoyment influences vary across these processes – enriching knowledge about SNS self-disclosure behaviors. Practically, the authors provide important design guidelines to practitioners concerning devising mechanisms to foster more automatic-enjoyable value-added functions to improve SNS users' participation and engagement.

This study examines the level of awareness and usage of game elements among construction professionals with a view to promoting the usage of gamification tools for the effective and efficient delivery of construction projects.

Data were obtained from construction professionals including architects, builders, engineers and quantity surveyors. Retrieved data were analyzed using several statistical tools such as percentages, frequencies, mean item scores and exploratory factor analyses.

The analysis revealed that progress bars, certificates and bonuses are the significant game elements adopted by professionals, but there is a low awareness of elements such as avatars and badges.

There is a salient need for construction stakeholders' awareness of the importance of gamification and game elements as a key digital tool for the delivery of construction projects. The findings of this study make a case for stakeholders, professional bodies and government agencies to embrace and implement gamification practices in the construction sector.

This study is the first conducted in Nigeria to examine the level of awareness and usage of game elements among construction professionals. The findings of this study will provide a reference point for researchers who will undertake studies relating to the concept of gamification in the construction industry context.

The purpose of this study is to propose and test a model to explain users’ intention to adopt m-health devices and divide the importance of antecedents for users to adopt m-health devices based on the stimulus-organism-response (S-O-R) framework.

This research conducted an online survey with m-health app users and collected 562 valid responses. A hybrid SEM-ANN approach was employed to evaluate the research model and hypotheses.

The results show that motivation (M), opportunity (O), and ability (A) affect users’ flow experience and loyalty and further affect their adoption intention of m-health technology. Opportunity plays a more critical role in m-health adoption intention than ability.

This study comprehensively examined the factors that affect users’ deep engagement and m-health adoption from the perspective of MOA. It used the hybrid SEM-ANN method to divide the critical role of motivation, opportunity and ability, providing a new analysis approach for studying information technology (IT) behavior.

The paper aims to empirically test a framework to predict the desire and intention to engage with an elective health-care procedure and implement a methodology to test the anticipated positive and negative emotions in hedonic adaptation to an elective procedure.

Two studies in USA and Australia (N = 1,200) confirmed the psychometric properties of the key constructs under the chemical peel condition. Two further studies in the USA and Australia (N = 1,100) explored the research question and hypotheses in the adapted model of goal-directed behaviour under the Botox condition. A survey was self-administered to online panels who had previously engaged in such elective procedures.

The findings highlighted the pragmatic implications for communication and activation strategies to safeguard consumer interests and retain their loyalty.

From the authors’ best understanding, neither a methodology nor a theoretical framework exists to explore hedonic adaptation to recurring engagement with elective health care. A methodology and theoretical framework will highlight the mood states and factors that predict desire and intention to engage. This can advance the research on hedonic adaptation and decision-making and offer pragmatic suggestions for communication and activation strategies to safeguard consumer interests and retain their loyalty.

Marketing professionals are under pressure to implement methods and metrics that demonstrate the value of the function. This paper aims to propose a model to measure marketing performance, focusing on four categories of metrics and two types of factors that influence the effectiveness of the assessment process.

The paper is organized in three parts. The first part includes a synthesis of the theoretical background on the subject. Next, the rationale and architecture of the model are presented, together with an explanation of the elements that compose it. A reflection on the work developed is presented in the last section.

Benefits regarding how to best assess marketing practice are considerable, as organizations with effective performance measurement systems tend to show better results than others. In this context, the choice of metrics is important, but it is also necessary to understand the mechanisms through which the effectiveness of the measurement process can be improved.

Literature has mainly focused attention on the effect of individual programs on specific measures or on conceptual models that do not sufficiently address all major elements in the marketing assessment process. This work extends previous contributions on the subject, presenting a model that combines metrics with factors underlying the measurement process.

The purpose of the article is to examine the concepts of knowledge management strategies, innovation and service quality in information technology companies that have research and development (R&D) departments in the technoparks of research universities.

The research was carried out in information technology companies with R&D departments in the technoparks of universities. Due to the “innovation” focus of the research, 302 engineers were selected by random sampling from engineers working in information technology companies in technoparks, and the prepared scale was sent to them via e-mail. In total, 302 units of data were subjected to path analysis and mediation effect analysis using the SmartPLS program.

In the research, it is supported by hypotheses that both knowledge management strategies and organizational innovation have a positive effect on the success of service quality and product innovation in information technology companies with R&D departments. At the same time, it can be explained as a result of analysis that innovation capability has both an independent and an intermediary variable effect.

Considering the limitations of the research, it is not correct to generalize the results of the analysis because the research was conducted only in information technology companies located in technoparks, and the data were collected from engineers working in these companies. For this reason, it is recommended that similar studies that are planned to be conducted in the future should do their research by taking this situation into account. At the same time, it is recommended to carry out future studies in different sectors and to bring the results obtained to the literature by comparing them.

The importance of information is increasing in technology-oriented companies where competition is increasing. Companies that cannot go beyond imitation or offer similar products and/or services cannot compete with their competitors in a competitive environment. The fact that companies can be successful in a competitive environment is supported by hypotheses as a result of the analysis that they need to develop organizational innovation and knowledge, as well as develop innovation capability at the same time.

The research is an original study in terms of examining the R&D departments of information technology companies operating in the technoparks of universities. Innovation and knowledge management strategies are examined within the scope of the research model by collecting data from information technology companies with R&D departments.