Identification of Lead User Characteristics Driving the Quality of Service Innovation Ideas

Research indicates that creative ideas provide the seed for successful service innovations. However, little attention has been paid to understanding idea creation, especially for service innovations. Lead user analysis has been shown to provide the highest potential to create attractive innovation ideas. But which characteristics in lead users are important in this regard is still under‐researched. In the realm of an idea contest, we examine the impact of specific lead user characteristics in driving the quality of service innovation ideas. Our study broadens the understanding of which customers are suitable and should be activated for service innovation idea contests. Using the data of 120 ideas resulting from an idea contest for new online services of soccer clubs, our findings demonstrate that specific lead user characteristics affect the quality of service ideas generated. We find that dissatisfaction with existing services has the highest impact on idea quality. Thus, companies should make use of their complaint management database to invite dissatisfied users to participate in idea contests. The results also show that highly experienced users provide ideas of higher quality. Our findings imply that companies should design closed‐membership idea contests so that only people who show specific characteristics can be admitted.     

User idea implementation in open innovation communities: Evidence from a new product development crowdsourcing community

In collaborative crowdsourcing communities for open innovation, users generate and submit ideas as idea co‐creators. Firms then select and implement valuable ideas for new product development. Despite the popularity and success of these open innovation communities, relatively little is known about the factors that determine the implementation of the user‐generated ideas. Based on research on individual creativity, we propose a conceptual model integrating users' previous experience, idea presentation characteristics and feedback valence to explain the likelihood of idea implementation. We validate our research model with a panel data analysis of 43 550 ideas submitted by 16 360 users in the MIUI new product development community hosted by Xiaomi, a large electronics manufacturing company in China. We find an inverted U‐shaped relationship between users' past successful experience and idea implementation. Furthermore, the length of ideas is positively associated with the likelihood of idea implementation. There is also an inverted U‐shaped relationship between supporting evidence and idea implementation. Finally, we demonstrate the negative effect of positive feedback and the positive effect of negative feedback on idea implementation. These findings offer rich insights to understand the phenomenon of open innovation better. Theoretical and practical implications are discussed.     

BFF: A tool for eliciting tie strength and user communities in social networking services

The use of social networking services (SNSs) such as Facebook has explosively grown in the last few years. Users see these SNSs as useful tools to find friends and interact with them. Moreover, SNSs allow their users to share photos, videos, and express their thoughts and feelings. However, users are usually concerned about their privacy when using SNSs. This is because the public image of a subject can be affected by photos or comments posted on a social network. In this way, recent studies demonstrate that users are demanding better mechanisms to protect their privacy. An appropriate approximation to solve this could be a privacy assistant software agent that automatically suggests a privacy policy for any item to be shared on a SNS. The first step for developing such an agent is to be able to elicit meaningful information that can lead to accurate privacy policy predictions. In particular, the information needed is user communities and the strength of users’ relationships, which, as suggested by recent empirical evidence, are the most important factors that drive disclosure in SNSs. Given the number of friends that users can have and the number of communities they may be involved on, it is infeasible that users are able to provide this information without the whole eliciting process becoming confusing and time consuming. In this work, we present a tool called Best Friend Forever (BFF) that automatically classifies the friends of a user in communities and assigns a value to the strength of the relationship ties to each one. We also present an experimental evaluation involving 38 subjects that showed that BFF can significantly alleviate the burden of eliciting communities and relationship strength.     

In Search of New Product Ideas: Identifying Ideas in Online Communities by Machine Learning and Text Mining

Online communities are attractive sources of ideas relevant for new product development and innovation. However, making sense of the ‘big data’ in these communities is a complex analytical task. A systematic way of dealing with these data is needed to exploit their potential for boosting companies' innovation performance. We propose a method for analysing online community data with a special focus on identifying ideas. We employ a research design where two human raters classified 3,000 texts extracted from an online community, according to whether the text contained an idea. Among the 3,000, 137 idea texts and 2,666 non‐idea texts were identified. The human raters could not agree on the remaining 197 texts. These texts were omitted from the analysis. The remaining 2,803 texts were processed by using text mining techniques and used to train a classification model. We describe how to tune the model and which text mining steps to perform. We conclude that machine learning and text mining can be useful for detecting ideas in online communities. The method can help researchers and firms identify ideas hidden in large amounts of texts. Also, it is interesting in its own right that machine learning can be used to detect ideas.     

Virtual Communities for Innovation: Influence Factors and Impact on Company Innovation

An extensive body of literature indicates the growing influence of virtual communities not only on social interaction, spending free time and working, but also on the interaction of companies with their customers to exchange information on products and to develop innovative ideas. However, engaging in virtual communities poses certain challenges to companies which more often than not results in failure to establish a successful collaboration with customers. This leads to the following questions: What are virtual communities and how can companies establish successful interaction? Why and how can interaction with a community lead to an improvement of the innovation process? This article develops a comprehensive concept of the collaboration between companies and virtual communities called community–company interaction quality (CCIQ). Based on insights from academic literature, this paper reviews factors influencing the quality of community–company interaction, suggesting an integrative framework. After developing a working definition for virtual communities in innovation, a summary of findings regarding interaction quality in context of human–technology interaction and behaviour related to innovation is proposed.     

Mapping an inland wetland complex using hyperspectral imagery

The goal is to determine the extent to which heterogeneous inland wetland vegetation communities and their dominant species, as well as adjacent upland vegetation types, can be mapped using 4‐m hyperspectral Compact Airborne Spectrographic Imager (CASI) data. Two classification algorithms, the maximum‐likelihood classifier (MLC) and the spectral angle mapper (SAM), are applied to CASI data acquired over an inland wetland complex located in southern Ontario, Canada. Application of the MLC algorithm to all bands of the CASI data produced better classification results than use of the SAM. Using the MLC, 10 classes were identified with an overall accuracy of 92%. This approach permitted differentiation between areas of shrub‐dominated vegetation communities, floating aquatic communities, emergent aquatics and shallow open water. In the SAM classification, 11 image‐derived spectral endmembers were generated. Wetland classes identified were shrub‐dominated wetlands, floating aquatic vegetation communities, shallow open water and moderately turbid shallow open water. Upland vegetation types were accurately mapped with both algorithms. Reasons why the SAM did not perform as well as the MLC in this complex environment are suggested. It is concluded that high‐resolution hyperspectral data can provide information needed by wetland managers about inland wetland plant communities and their dominant species.     

Communitition: The Tension between Competition and Collaboration in Community‐Based Design Contests

Following the concepts of crowdsourcing, co‐creation or open innovation, companies are increasingly using contests to foster the generation of creative solutions. Currently, online idea and design contests are enjoying a resurgence through the usage of new information and communication technologies. These virtual platforms allow users both to competitively disclose their creative ideas to corporations and also to interact and collaborate with like‐minded peers, communicating, discussing and sharing their insights and experiences, building social networks and establishing a sense of community. Little research has considered that contest communities both promote and benefit from simultaneous co‐operation and competition and that both types of relationships need to be emphasized at the same time. In this article, it is argued that the firm‐level concept of co‐opetition might also be relevant for an innovation's success on the individual level within contest communities. Our concept of ‘communitition’ should include the elements of competitive participation without disabling the climate for co‐operation, as numerous user discussions and comments improve the quality of submitted ideas and allow the future potential of an idea to shine through the so‐called ‘wisdom of the crowd’.     

Ethical implications of social stratification in information systems research

When investigating the use of information systems within organizations, researchers inevitably make decisions relating to the classification, or ‘stratification’, of information technology users. Most commonly, users are stratified along functional boundaries or by their membership in various communities of practice. It is important to note, however, that any such method of social stratification necessarily focuses the attention of a researcher on certain issues while unavoidably downplaying or neglecting other concerns. Individuals whose interests, values or identification align with these neglected issues may be inadvertently marginalized by the research approach. This observation suggests a range of ethical concerns related to the methods of social stratification used by researchers. In this paper, we argue that the method by which information systems researchers stratify organizational actors in their research has significant ethical implications. We propose a framework that maps stratification strategies that researchers bring to their analyses using Weber's theory of stratification and the dimensions of class, status and party, in conjunction with his distinction between heterogeneous and homogenous forms of work. We offer illustrative theoretical lenses for each category in the framework and demonstrate how each lens favours certain issues and potentially neglects others.     

Interactive tree comparison for co-located collaborative information visualization

In many domains increased collaboration has lead to more innovation by fostering the sharing of knowledge, skills, and ideas. Shared analysis of information visualizations does not only lead to increased information processing power, but team members can also share, negotiate, and discuss their views and interpretations on a dataset and contribute unique perspectives on a given problem. Designing technologies to support collaboration around information visualizations poses special challenges and relatively few systems have been designed. We focus on supporting small groups collaborating around information visualizations in a co-located setting, using a shared interactive tabletop display. We introduce an analysis of challenges and requirements for the design of co-located collaborative information visualization systems. We then present a new system that facilitates hierarchical data comparison tasks for this type of collaborative work. Our system supports multi-user input, shared and individual views on the hierarchical data visualization, flexible use of representations, and flexible workspace organization to facilitate group work around visualizations.     

Copyright liability for users and distributors of content sharing and communication technologies: a crossroads between past and present

In the last decade or so, society has seen the beginnings of a digital revolution where innovation and technological advancement met and changed the way in which people use digital technology. This has only increased the ambit of confusion between the law and technology innovation. This is evident with the creation and distribution of content sharing and communication technologies such as peer-to-peer, network distributive systems, file sharing software and other technology enabling software where users are able to share and access information. The recurring issues that appear throughout case precedent have reinforced the uncertainty and confusion over the interpretation of authorisation. This paper will explore the concept of authorisation and evaluate the courts' interpretation of what constitutes an authorisation of infringement with respect to technology innovators of communication technologies. This will be achieved through a discussion of the cases that explored ‘authorisation’ through the genealogy of authorisation. It is important to discuss the history of authorisation first, and then evaluate how the courts have interpreted ‘authorisation’. This paper will demonstrate how the interpretation of authorisation has created ambiguity and uncertainty for technology innovators and developers.     

增强用户体验的人机交互技术教学模式探索

尝试人机交互技术教学互动的实践模式,探索学生以用户身份参与的学习模式。让学生主动探索开放的个性化模式,改变传统被动的课堂组织形式。学生在学习理论课程的同时也在体验和创造课程。两主一辅的教学模式和特性化分类教学使教师和学生都参与到设计的过程中,增强的用户体验让学生成为真正的主体、设计者、创新者。     

How good are ideas identified by an automatic idea detection system?

Online communities can be an attractive source of ideas for product and process innovations. However, innovative user‐contributed ideas may be few. From a perspective of harnessing “big data” for inbound open innovation, the detection of good ideas in online communities is a problem of detecting rare events. Recent advances in text analytics and machine learning have made it possible to screen vast amounts of online information and automatically detect user‐contributed ideas. However, it is still uncertain whether the ideas identified by such systems will also be regarded as sufficiently novel, feasible and valuable by firms who might decide to develop them further. A validation study is reported in which 200 posts from an online home brewing community were extracted by an automatic idea detection system. Two professionals from a brewing company evaluated the posts in terms of idea content, idea novelty, idea feasibility and idea value. The results suggest that the automatic idea detection system is sufficiently valid to be deployed for the harvesting and initial screening of ideas, and that the profile of the identified ideas (in terms of novelty, feasibility and value) follows the same pattern identified in studies of user ideation in general.     

Towards a Comprehensive Understanding of Lead Userness: The Search for Individual Creativity

In innovation research the identification of lead users has attracted considerable research effort. While lead user research has made important advances, there is still a significant lack in terms of understanding antecedents to lead userness. Therefore the aim of this paper is to offer a framework which is rooted in creativity psychology in order to provide a more comprehensive understanding of who leading‐edge users are. It will allow for a systematic investigation and detection of innovative users. We conducted an empirical study in the field of small kitchen appliances in co‐operation with Philips Consumer Lifestyle, a field which lacks some of the typical characteristics that have been emphasized in markets traditionally studied in lead user research. With our research we show that (1) lead userness is fundamentally linked to individual creativity; (2) particularly creativity‐ and domain‐relevant skills (cognitive style, product knowledge and use experience) are related to lead userness; (3) creativity‐relevant skills can be explained by personal characteristics, such as education, gender and openness to experience.     

“互联网+”背景下档案信息资源开发创新研究

"互联网+"的提出给档案信息资源开发带来新的思路,通过"互联网+"的思维指导和技术支持,档案信息资源开发可以重新焕发活力,并向协作整合、创新驱动、开放生态等方向转变;同时,档案信息资源开发应形成"互联网+"的新模式,在生态化开发方面进行创新,使档案信息资源得到充分利用,满足用户的需求,激活档案的价值。本文从档案信息资源与档案信息资源服务入手,探讨"互联网+"背景下档案信息资源开发创新的价值,分析当前档案信息资源开发过程中存在的问题,并提出改进措施,旨在为推动档案信息资源开发提供参考。     

基于Ontology的P2P社区组织

如何将大量的电子信息以一种有效的方式组织、管理并能将信息尽可能准确、快速的提供给用户是P2P系统中一个需要解决的关键问题。采用Ontology作为一种能在知识和语义层次上描述信息的概念建模工具,提出社区组织算法,能够动态形成社区,形成共享概念模型,使用户得到满意的结果。     

Tuning Users' Innovativeness During Ideation

Although there is increasing acknowledgement that consumers can contribute useful ideas during the development of innovative services, there has been little empirical examination of how such users can best be managed in order to contribute their ideas to the ‘fuzzy front end’ of new service development. The present study examines the relationship between the nature of user‐created ideas regarding new technology‐based services and the characteristics of the users supplying the ideas. In particular, the study investigates whether users' ideas become more incremental or more radical depending on the users' awareness of technological restrictions and their utilization of use experience. The results show that idea creators with high use experience who are unaware of any technological restrictions tend to produce service ideas that are more radical in nature, whereas idea creators with high use experience who are aware of technological restrictions tend to produce service ideas that are more incremental in nature. The study provides empirical support that, in order to provide innovative ideas, ordinary users involved in ideation must both have a contextual use experience and not be restricted in their ideation by ‘too much’ technology information and restrictions on potential feasibility.     

Caught between the users and the firm: How does identity conflict affect employees' innovative behavior

Absorbing external knowledge is crucial for innovation within the organization. One way of tapping external knowledge sources is to rely on employees who reach out across the firm's boundary to external stakeholders and address knowledge sets located beyond the organizational boundary. However, such employees are likely to identify with the stakeholders they reach out to which exposes them to potentially conflicting demands—with positive or negative effects for their employing organization. We investigate whether and how their dual identification with the organization and with users, and the potential identity conflicts this engenders, affects their job satisfaction and innovativeness. We study a sample of 243 employees in two industries, revealing that perceived conflict between organizational identification and user identification detracts from job satisfaction if and only if employees are strongly identified with both targets. We find also that identity conflict is indirectly and negatively related to innovative work behavior through job satisfaction. Our paper contributes to the literature on the benefits and risks of employee ties to external stakeholders. We contribute also to research on embedded users by elucidating under what conditions they are most valuable to their employing organizations.     

A multi-user perspective for personalized email communities

Email classification and prioritization expert systems have the potential to automatically group emails and users as communities based on their communication patterns, which is one of the most tedious tasks. The exchange of emails among users along with the time and content information determine the pattern of communication. The intelligent systems extract these patterns from an email corpus of single or all users and are limited to statistical analysis. However, the email information revealed in those methods is either constricted or widespread, i.e. single or all users respectively, which limits the usability of the resultant communities. In contrast to extreme views of the email information, we relax the aforementioned restrictions by considering a subset of all users as multi-user information in an incremental way to extend the personalization concept. Accordingly, we propose a multi-user personalized email community detection method to discover the groupings of email users based on their structural and semantic intimacy. We construct a social graph using multi-user personalized emails. Subsequently, the social graph is uniquely leveraged with expedient attributes, such as semantics, to identify user communities through collaborative similarity measure. The multi-user personalized communities, which are evaluated through different quality measures, enable the email systems to filter spam or malicious emails and suggest contacts while composing emails. The experimental results over two randomly selected users from email network, as constrained information, unveil partial interaction among 80% email users with 14% search space reduction where we notice 25% improvement in the clustering coefficient.