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’.     

Innovation Contests: A Review,Classification and Outlook

Innovation contests as a means to realize innovative product or service solutions are growing in popularity among practitioners and researchers. An increasing number of organizations worldwide have adopted innovation contests, not only for innovation purposes, but also for other reasons such as promoting sustainability. At the same time, innovation contests represent a growing research field to scholars from different backgrounds, e.g., economics or information systems. In this article, first, the growing body of literature on innovation contests is reviewed and classified into five research categories: economic perspective, management perspective, education focus, innovation focus and sustainability focus. Second, some design elements of innovation contests that are central for the understanding, design and management of innovation contests are presented based on the current body of literature. Finally, current research gaps are presented and some of the research questions are developed that could be explored to contribute to the body of literature.     

A User Community‐Based Approach to Leveraging Technological Competences: An Exploratory Case Study of a Technology Start‐Up from MIT

Many studies highlight the impact of technology commercialization on innovation and wealth creation. However, this impact could be far greater, especially as many technologies developed with high costs and effort remain vastly underutilized. One important reason for this problem can be found at the front end of the technological competence leveraging process: searching for market opportunities for a technology is a formidable challenge. In many cases, alternative fields of application (or even a single viable market opportunity) for a given technology are simply unknown to the entity in charge of commercialization. Based on an extensive literature review, we identify two major shortcomings at the front end of the technological competence leveraging process which contribute to the underutilization problem: (1) the local search behaviour of the commercializing entity and (2) the use of solution‐based instead of problem‐based search specifications. On the basis of these insights, we discuss the potential role of user communities in the search for (additional) market opportunities for a given technology, a process usually referred to as technological competence leveraging. We then empirically explore a user community‐based approach in an illustrative case study with a start‐up from MIT. Our findings show that when users were included in the search process, the number of potential markets in which the technology could be applied was five times higher, and more far‐distant application areas as well as application areas previously unknown to the technology holder were reached. In addition, we discover design principles for a user community‐based search process, providing practitioners with a hands‐on guideline for employing a user community‐based approach to technological competence leveraging.     

基于成图与建模创新大赛的思考

为进一步推动高等院校工程图学教学方法改革,论文在介绍成图与建模创 新大赛的基础上,探讨了全国大学生成图与建模创新大赛的意义,分析了竞赛中发现的问题, 阐述了工程图学课程教学中理论知识与实践能力同步发展的重要性,提出了全国大学生成图 竞赛引导建立新的教学理念、教学内容和教学考核方式的设想,以适应卓越工程师培养和工 程教育改革的趋势,促使学校在学生整体工程实践能力培养方面更上一层楼。     

Reducing the Health and Digital Divides: A Model for Using Community‐Based Participatory Research Approach to E‐Health Interventions in Low‐Income Hispanic Communities

Low‐income Hispanics are the most digitally underserved population in the U.S. This article examines the potential of community‐based participatory research approach to e‐health to decrease the disparities in access to technology and health information in low‐income Hispanic communities. To demonstrate this framework, we describe the process of designing a community‐based e‐health intervention to increase knowledge and parental self‐efficacy in coping with young children's mental health problems including mental health service utilization. Our model incorporates utilizing promotoras de salud (lay community health educators) and community media principles to create the content of e‐health interventions and train community members in using the technology. This case study illustrates the processes involved in using this approach, barriers for participatory e‐health interventions in bridging the Digital Divide, and lessons learned.     

Performance Analysis of The Auxiliary‐Model‐Based Multi‐Innovation Stochastic Newton Recursive Algorithm for Dual‐Rate Systems

The stochastic Newton recursive algorithm is studied for dual‐rate system identification. Owing to a lack of intersample measurements, the single‐rate model cannot be identified directly. The auxiliary model technique is adopted to provide the intersample estimations to guarantee the recursion process continues. Intersample estimations have a great influence on the convergence of parameter estimations, and one‐step innovation may lead to a large fluctuation or even divergence during the recursion. In the meantime, the sample covariance matrix may appear singular. The recursive process would cease for these reasons. In order to guarantee the recursion process and to also improve estimation accuracy, multi‐innovation is utilized for correcting the parameter estimations. Combining the auxiliary model and multi‐innovation theory, the auxiliary‐model‐based multi‐innovation stochastic Newton recursive algorithm is proposed for time‐invariant dual‐rate systems. The consistency of this algorithm is analyzed in detail. The final simulations confirm the effectiveness of the proposed algorithm.     

Innovation and Competition: Survival Skills Through Stress Reduction

As the world economy begins to shift from the industrial states of the past toward marketable service orientations, the need for those adults under highly stressful circumstances to reduce their stress levels becomes imperative. The peak performer, whether in business and industry, education and teaching or any other field, should regard, accept and anticipate stress indicators by using appropriate methods to alleviate that stress before it becomes highly detrimental to employment and personal performance. The utilization of those activities we played as children can become modified tools and techniques for the stressed personality.     

Sketch‐to‐Design: Context‐Based Part Assembly

Designing 3D objects from scratch is difficult, especially when the user intent is fuzzy and lacks a clear target form. We facilitate design by providing reference and inspiration from existing model contexts. We rethink model design as navigating through different possible combinations of part assemblies based on a large collection of pre‐segmented 3D models. We propose an interactive sketch‐to‐design system, where the user sketches prominent features of parts to combine. The sketched strokes are analysed individually, and more importantly, in context with the other parts to generate relevant shape suggestions via adesign galleryinterface. As a modelling session progresses and more parts get selected, contextual cues become increasingly dominant, and the model quickly converges to a final form. As a key enabler, we use pre‐learned part‐based contextual information to allow the user to quickly explore different combinations of parts. Our experiments demonstrate the effectiveness of our approach for efficiently designing new variations from existing shape collections.     

Continuous Action Generation of Q‐Learning in Multi‐Agent Cooperation

Conventional Q‐learning requires pre‐defined quantized state space and action space. It is not practical for real robot applications since discrete and finite numbers of action sets cannot precisely identify the variances in the different positions on the same state element on which the robot is located. In this paper, a Q‐Learning composed continuous action generator, called the fuzzy cerebellar model articulation controller (FCMAC) method, is presented to solve the problem. The FCMAC displays continuous action generation by linear combination of the weighting distribution of the state space where the optimal policy of each state is derived from Q‐learning. This provides better resolution of the weighting distribution for the state space where the robot is located. The algorithm not only solves the single‐agent problem but also solves the multi‐agent problem by extension. An experiment is implemented in a task where two robots are taking action independently and both are connected with a straight bar. Their goal is to cooperate with each other to pass through a gate in the middle of a grid environment.     

基于校企合作的软件工程课程体系创新模式(英文)

Through the cooperation of College of Software and IBM Corporation,new technologies and methods are introduced into classroom successively to carry on the innovation of industrialized software education curriculum system.Take the new "data structure and modeling" course for example.This innovation model develops teaching materials and laboratory manuals.It improves students' hands-on ability through business cases training and preferably enhances students' ability to solve problems in the process of analyzing practical situations.This model cultivates students to meet actual demands of enterprises.Besides,supported by Co-Lab,student clubs and innovation units can be set up to compete,practice,and complete final design,achieving "pre-employment" in the training base.The practices of this model have already brought up a plenty of engineering-type,innovation-type and utility-type talents,bringing the continuous rise in the students' employment rate and employment quality.     

Cooperation and Competition in ALIAS: A Logic Framework for Agents that Negotiate

This paper presents ALIAS, an agent architecture based on intelligent logic agents, where the main form of agent reasoning is abduction. The system is particularly suited for solving problems where knowledge is incomplete, where agents may need to make reasonable hypotheses about the problem domain and other agents, and where the raised hypotheses have to be consistent for the overall set of agents. ALIAS agents are pro-active, exhibiting a goal-directed behavior, and autonomous, since each one can solve problems using its own private knowledge base. ALIAS agents are also social, because they are able to interact with other agents, in order to cooperatively solve problems. The coordination mechanisms are modeled by means of LAILA, a logic-based language which allows to express intra-agent reasoning and inter-agent coordination. As an application, we show how LAILA can be used to implement inter-agent dialogues, e.g., for negotiation. In particular, LAILA is well-suited to coordinate the process of negotiation aimed at exchanging resources between agents, thus allowing them to execute the plans to achieve their goals.     

Folksonomy‐Based Recommender Systems: A State‐of‐the‐Art Review

Collaborative tagging systems, also known as folksonomies, have grown in popularity over the Web on account of their simplicity to organize several types of content (e.g., Web pages, pictures, and video) using open‐ended tags. The rapid adoption of these systems has led to an increasing amount of users providing information about themselves and, at the same time, a growing and rich corpus of social knowledge that can be exploited by recommendation technologies. In this context, tripartite relationships between users, resources, and tags contained in folksonomies set new challenges for knowledge discovery approaches to be applied for the purposes of assisting users through recommendation systems. This review aims at providing a comprehensive overview of the literature in the field of folksonomy‐based recommender systems. Current recommendation approaches stemming from fields such as user modeling, collaborative filtering, content, and link‐analysis are reviewed and discussed to provide a starting point for researchers in the field as well as explore future research lines.     

A Human–Computer Cooperation Fuzzy c‐Means Clustering with Interval‐Valued Weights

In this paper, a fuzzy c‐means clustering algorithm based on interval‐valued weights is proposed for improving clustering performance. In the proposed algorithm, the interval‐valued weights are first constructed by synergy of the ReliefF algorithm and the analytic hierarchy process (AHP) method, and then they are transformed into a constraint condition associating with each weight variable in the weighted clustering objective function. In the sequence, the weighted clustering objective function is solved by combining the Lagrange multiplier method with the gradient‐based iteration computation. In the whole process of algorithm iteration, a compulsion strategy with human–computer cooperation is adopted to ensure each weight variable satisfies interval constraint itself. Three well‐known data set are used to perform profound experiments. Experimental results clearly show that the proposed algorithm has better clustering performance than other the weighted fuzzy c‐means clustering algorithm.     

Organizing Pharmaceutical Innovation: From Science‐based Knowledge Creators to Drug‐oriented Knowledge Brokers

The pharmaceutical industry is exposed to severe conditions: while a typical R&D process lasts up to 13 years, only one out of 10,000 substances becomes a marketable product. In addition, markets for pharmaceutical products tend to become more fragmented, leading to an increased risk of market failure. At the same time, R&D productivity has been deteriorating for several years. The number of new drug approvals is constantly declining, while R&D expenditures are escalating as a result of high investments in new drug discovery technologies and more complex clinical studies. As a response, pharmaceutical firms have started to focus on balancing the right size and structure of their R&D activities. This leads to several organizational trends: (1) novel management of technologies; (2) R&D internationalization; and (3) open innovation modes.     

Attribute‐Domain Matrix: A Reverse Engineering Method for Innovation

An innovative idea is a beautiful thing, but most innovative ideas do not become successful new products. For products that are successful, there is a variety of examples over more than 150 years of situations where customers used them in ways never planned by the designer. Only few companies are systematically exploiting non‐conventional use as a method to generate ideas for new product outcomes and problem solutions. TRIZ awareness of analogies systematizes the search for available alternate situations: the attribute‐domain matrix actively transfers product attributes to unexpected application domains, breaks the functional fixedness pattern and helps make aware the resources that are available in any product or system.     

Shading‐Based Surface Recovery Using Subdivision‐Based Representation

This paper presents subdivision‐based representations for both lighting and geometry in shape‐from‐shading. A very recent shading‐based method introduced a per‐vertex overall illumination model for surface reconstruction, which has advantage of conveniently handling complicated lighting condition and avoiding explicit estimation of visibility and varied albedo. However, due to its discrete nature, the per‐vertex overall illumination requires a large amount of memory and lacks intrinsic coherence. To overcome these problems, in this paper we propose to use classic subdivision to define the basic smooth lighting function and surface, and introduce additional independent variables into the subdivision to adaptively model sharp changes of illumination and geometry. Compared to previous works, the new model not only preserves the merits of the per‐vertex illumination model, but also greatly reduces the number of variables required in surface recovery and intrinsically regularizes the illumination vectors and the surface. These features make the new model very suitable for multi‐view stereo surface reconstruction under general, unknown illumination condition. Particularly, a variational surface reconstruction method built upon the subdivision representations for lighting and geometry is developed. The experiments on both synthetic and real‐world data sets have demonstrated that the proposed method can achieve memory efficiency and improve surface detail recovery.     

Radical Innovation with Limited Resources in High‐Turbulent Markets: The Role of Lean Innovation Capability

How do firms radically innovate with limited resources in high‐turbulent environments? We examine this question via in‐depth comparative case studies of ten start‐up firms in diverse high‐turbulent markets. Evidence shows that the perceived value of resources depends on two contextual factors: market type and business model type. More interestingly, firms that see resource limitation as an enabler rather than an inhibitor seem to have a distinct capability that we call lean innovation capability. It is defined as a distinct capability that reflects a firm's ability to experiment with ideas that meet core customer needs by constantly iterating the initial offering with the purpose of validating the learning through continuous market feedback to achieve sustainable performance. The three main qualities of these companies are (1) adopting abductive reasoning, (2) embracing a validity‐driven approach, and (3) operating in the overlapping spaces of fundamental customer needs, business viability and technological feasibility. Lean firms adopt design‐thinking methodology and act like bricoleurs, such as make‐do by applying combinations of the available resources through rapid prototyping to new problems and opportunities in an experimental way. Briefly, lean innovation capability enables firms to manage limited resources by reconfiguring and reallocating existing resources, and, thereby, helps empower resource‐limited radical innovation.     

Toolkit‐Based Modelling and Serious Play as Means to Foster Creativity in Innovation Processes

In this article we describe and discuss means that foster the emergence of innovation through representational methods which interrelate manual modeling with playfulness. Based on the observation that demands to innovation processes have changed significantly in recent years due to changed collaboration forms, like co‐configuration or open innovation, we look for a methodological approach able to deal with such collaboration forms. We describe and discuss a methodological approach on how innovation processes in heterogeneous – interdisciplinary, cross‐functional and interorganizational – groups can be kicked off to bring about collectively shared understanding, as well as the ability to develop creative ideas. The approach relies on a playful modeling methodology, which is based on the hands‐on creation of visualizations and physical models in connection with their verbal explanation and narration. With reference to two case studies we report and discuss experiences of applying the methodology.