How preference markets assist new product idea screening

2siPurpose - The purpose of this paper is to examine the different heuristics adopted by a crowd and a management committee to evaluate new product proposals, and whether, in assessing the value of proposals, they emphasize different features. Design/methodology/approach - The study takes a quantitative analysis approach to study an internal innovation contest held by the biotechnology company Novozymes. The contest generated 201 proposals that were evaluated by 109 research and development professionals by means of a virtual preference market, and by a management committee. Findings - The crowd and the committees' assessments of the value of the proposals were based on different features. The committee emphasized experience and inventors' seniority; the crowd set more store on informative idea descriptions but penalized overly complex and lengthy proposals. Research limitations/implications - The design of the innovation contest does not allow full comparison of the preference functions of crowd and committee. The findings from this case study cannot be generalized. The early stage of new product development seems fruitful for investigating crowdsourcing and knowledge management. Practical implications - Firms should consider adopting preference markets for idea screening and evaluation since they appraise ideas from different angles compared to managers. However, they complement, rather than substitute managerial evaluation, especially in the case of more detailed proposals. Originality/value - This is one of the first attempts to identify differences in the decision-making processes of crowds and committees. The paper identifies their strengths as evaluators of new product ideas and finds that the "wisdom of crowds" has some limitations in relation to the ability to process complex information.reservedmixedLauto, Giancarlo; Valentin, FinnLauto, Giancarlo; Valentin, Fin

Ideate. Collaborate. Repeat. A Research Agenda for Idea Generation, Collaboration and Evaluation in Open Innovation

Open innovation has been and remains to be a rapidly changing field of research in Information Systems and various other disciplines. With the rise of professional open innovation platforms and the emergence of crowdsourcing as well as employee-driven innovation, studies on the front-end of open innovation – namely idea generation, collaboration and evaluation – are facing new challenges. In this structured literature review, we analyze a large body of prior research in order to derive a framework, which is able to classify and reflect the lively debate on open innovation. In addition, we identify important implications for practitioners with advise on the design of open innovation systems. Moreover, our study identifies several promising areas for future research

A Framework for the Systematic Evaluation of Data and Analytics Use Cases at an Early Stage

Due to the immense growth of collected data and advancing big data technologies, there are countless potential use cases of data and analytics. But most data initiatives fail and do not bring the desired outcome. One essential reason for this situation is the lack of a systematic approach to evaluate and select promising analytics use cases. This study presents an evaluation framework that enables the systematic screening at an early stage by assessing nine criteria with the help of a scoring model. It also supports a prioritization among several use cases and facilitates the communication to decision makers. The action design research approach was followed to build, test, and evaluate the framework in three iterative design cycles. It was developed in close collaboration with Bundesdruckerei GmbH, an IT-security company owned by the German government that offers products and services for secure identities, data, and infrastructures

NOT ALL TASKS ARE ALIKE: EXPLORING THE EFFECT OF TASK REPRESENTATION ON USER ENGAGEMENT IN CROWD-BASED IDEA EVALUATION

Crowdsourcing has experienced increasing popularity in recent years. While performance-based issues, such as the quantity or quality of output produced by the crowd, have been in the focus of research, users’ experience, which unfolds through interaction with the crowdsourcing platform and ultimately creates engagement, has been largely neglected. However, user engagement does not only determine the scope of effort users put into the crowdsourcing task, but is considered a determinant for future participation. This paper focusses on the role of task representation–manifested in mechanisms for crowd-based idea evaluation–as potential stimuli for user engagement. Therefore, we conduct a web-based experiment with 198 participants to investigate how different task representations translate into differences in users’ experience and their engagement. In particular, we analyze two distinctive task representations: sequential judgement tasks in form of multi-criteria rating scales and simultaneous choice tasks in the form of enterprise crowdfunding. We find differences in task representation to influence user engagement while mediated by a user’s perceived cognitive load. Moreover, our findings indicate that user engagement is determined by a user’s perceived meaningfulness of a task. These results enhance our understanding of user engagement in crowdsourcing and contribute to theory building in this emerging field

The 2P-K Framework: A Personal Knowledge Measurement Framework for the Pharmaceutical Industry

Knowledge is a dynamic human process to justify our personal belief in pursuit of the truth. The intellectual output of any organisation is reliant upon the individual people within that organisation. Despite the eminent role of personal knowledge in organisations, personal knowledge management and measurement have received little attention, particularly in pharmaceutical manufacturing. The pharmaceutical industry is one of the pillars of the global economy and a knowledge-intensive sector where knowledge is described as the second product after medicines. The need of measurement to achieve effective management is not a new concept in management literature. This study offers an explanatory framework for personal knowledge, its underlying constructs and observed measures in the pharmaceutical manufacturing context. Following a sequential mixed method research (MMR) design, the researcher developed a measurement framework based on the thematic analysis of fifteen semi-structured interviews with industry experts and considering the extant academic and regulatory literature. A survey of 190 practitioners from the pharmaceutical manufacturing sector enabled quantitative testing and validation of the proposed models utilising confirmatory factor analysis. The pharmaceutical personal knowledge framework was the fruit of a comprehensive study to explain and measure the manifestations of personal knowledge in pharmaceutical organisations. The proposed framework identifies 41 personal knowledge measures reflecting six latent factors and the underlying personal knowledge. The hypothesised factors include: regulatory awareness, performance, wisdom, organisational understanding, mastership of product and process besides communication and networking skills. In order to enhance the applicability and flexibility of the measurement framework, an abbreviated 15-item form of the original framework was developed. The abbreviated pharmaceutical personal knowledge (2P-K) framework demonstrated superior model fit, better accuracy and reliability. The research results reveal that over 80% of the participant pharmaceutical organisations had a form of structured KM system. However, less than 30% integrated KM with corporate strategies suggesting that KM is still in the early stages of development in the pharmaceutical industry. Also, personal knowledge measurement is still a subjective practice and predominately an informal process. The 2P-K framework offers researchers and scholars a theoretically grounded original model for measuring personal knowledge. Also, it offers a basis for a personal knowledge measurement scale (2P-K-S) in the pharmaceutical manufacturing context. Finally, the study had some limitations. The framework survey relied on self-ratings. This might pose a risk of social desirability bias and Dunning–Kruger effect. Consequently, a 360- degree survey was suggested to achieve accurate assessments. Also, the model was developed and tested in an industry-specific context. A comparative study in similar manufacturing industries (e.g. chemical industries) is recommended to assess the validity of the current model or a modified version of it in other industries

The Gamification of Crowdsourcing Systems: Empirical Investigations and Design

Recent developments in modern information and communication technologies have spawned two rising phenomena, gamification and crowdsourcing, which are increasingly being combined into gamified crowdsourcing systems. While a growing number of organizations employ crowdsourcing as a way to outsource tasks related to the inventing, producing, funding, or distributing of their products and services to the crowd – a large group of people reachable via the internet – crowdsourcing initiatives become enriched with design features from games to motivate the crowd to participate in these efforts. From a practical perspective, this combination seems intuitively appealing, since using gamification in crowdsourcing systems promises to increase motivations, participation and output quality, as well as to replace traditionally used financial incentives. However, people in large groups all have individual interests and motivations, which makes it complex to design gamification approaches for crowds. Further, crowdsourcing systems exist in various forms and are used for various tasks and problems, thus requiring different incentive mechanisms for different crowdsourcing types. The lack of a coherent understanding of the different facets of gamified crowdsourcing systems and the lack of knowledge about the motivational and behavioral effects of applying various types of gamification features in different crowdsourcing systems inhibit us from designing solutions that harness gamification’s full potential. Further, previous research canonically uses competitive gamification, although crowdsourcing systems often strive to produce cooperative outcomes. However, the potentially relevant field of cooperative gamification has to date barely been explored. With a specific focus on these shortcomings, this dissertation presents several studies to advance the understanding of using gamification in crowdsourcing systems

Organizational Online Participation

As today’s employees demand higher degrees of involvement in terms of how, when, and where they work, open innovation and (internal) crowdsourcing are being widely adopted. Despite recent efforts by many organizations to implement such systems in order to increase the possibilities for organizational participation, studies have only narrowly explored how their design affects employee opinions and communication as well as how organizational culture influences usage and adoption. This thesis investigates the conditions, capabilities and components for the design of organizational online participation systems, applying a Design Science Research approach. Following a literature review on idea generation, collaboration and evaluation in open innovation processes, we outline success factors for open innovation systems. We validate our success factors in practice by conducting semi-structured interviews with 20 experts from mid- and large-cap private and public organizations in Germany. Moreover, we derive three key challenges that guide our subsequent studies. First, we investigate the “Bag of Lemons” approach, a novel rating technique, and compare it to the standard techniques Likert scales and up- and down-voting. Our study with 141 participants in an open innovation engagement at a public-private research organization finds that BOL is perceived as more frustrating than the other two rating techniques, which is partly mediated by the significantly increased information overload. Second, we turn to anonymity in two distinct studies. We analyze the effect of anonymity, as compared to identifiability of user profiles, on communication persuasiveness – operationalized as actual opinion change – in a two-staged online experimental survey with 377 participants. We find anonymity to be a double-edged sword as it decreases perceived social presence, which in turn affects both user involvement as well as perceived user credibility. Thereafter, we investigate the design of a feature for optional anonymous contributions and its effect on participation and the choice of language in an internal crowdsourcing platform. Our analysis of an implementation and five-month test at a public organization with more than 110 employees shows the effectiveness of our “opt-in anonymity” feature as we elicit participation from otherwise reticent employees and no disinhibited language. Third, we analyze the design of an internal crowdsourcing system at this public organization in more detail, focusing on the influence of its organizational culture on usage and acceptance. We assert an IT-culture-conflict, as the organizational values do not match the open and communal approach transposed by the crowdsourcing system. We suggest that organizational online participation is a promising tool to enhance employee involvement, driving innovations and enabling organizational transformation