Hanjun Lee

Who creates value in a user innovation community? A case study of MyStarbucksIdea.com

Purpose – Successful open innovation requires that many ideas be posted by a number of users and that the posted ideas be evaluated to find ideas of high quality. As such, successful open innovation community would have inherently information overload problem. The purpose of this paper is to mitigate the information problem by identifying potential idea launchers, so that they can pay attention to their ideas. Design/methodology/approach – This research chose MyStarbucksIdea.com as a target innovation community where users freely share their ideas and comments. We extracted basic features from idea, comment and user information and added further features obtained from sentiment analysis on ideas and comments. Those features are used to develop classification models to identify potential idea launchers, using data mining techniques such as artificial neural network, decision tree and Bayesian network. Findings – The results show that the number of ideas posted and the number of comments posted are the most...

The Influence of Negative Emotions in an Online Brand Community on Customer Innovation Activities

With Web 2.0 increased user participation in diverse e-communities results in prevalence of information, including emotional information. We examined the influence of negative emotion in an online brand community, MyStarbuckIdea.com developed to collect diverse customer ideas for firms innovation, with the purpose to investigate how such emotion affects customer innovation activities in the community. We first established several hypotheses on the relationships between discrete negative emotions and innovation activities. Then, having collected 84,918 customer ideas, we conducted POS tagging and term-based matching to calculate the inclusion and intensity of negative emotion, using negative emotion lexicon which we developed. As a result of testing hypotheses with regression models, we show that 1) negative emotion significantly affects innovation activities in the brand community and frustration is the most influential among the discrete negative emotions; 2) as the intensity level of negative emotions increases, so does their influence.

What Determines an Agreeable and Adoptable Idea? A Study of User Ideas on MyStarbucksIdea.com

Rising tide of crowdsourcing as a new method of innovation is surging across diverse industries. Considering that the goal of crowdsourcing is generating ideas which can be seeds of innovation, understanding the characteristics of user-agreeable and organization-adoptable ideas can enhance the effectiveness of idea generation. In our approach, we extract idea contents characteristics such as subjectivity, negativity, publicness, and depth of idea as well as user characteristics such as user experience and reputation to examine what are the factors that affect user-agreement and organizational adoption. An analysis of 71,134 ideas from MyStarbucksIdea.com shows that there are significant differences between user-agreeable and organization-adoptable ideas. Besides, moderating effect of user reputation is found. Managerial implications are discussed.

Recommending valuable ideas in an open innovation community: A text mining approach to information overload problem

Purpose Open innovation communities are a growing trend across diverse industries because they provide opportunities of collaborating with customers and exploiting their knowledge effectively. Although open innovation communities can be strategic assets that can help firms innovate, firms nonetheless face the challenge of information overload incurred due to the characteristic of the community. The purpose of this paper is to mitigate the problem of information overload in an open innovation environment. Design/methodology/approach This study chose MyStarbucksIdea.com (MSI) as a target open innovation community in which customers share their ideas. The authors analyzed a large data set collected from MSI utilizing text mining techniques including TF-IDF and sentiment analysis, while considering both term and non-term features of the data set. Those features were used to develop classification models to calculate the adoption probability of each idea. Findings The results showed that term and non-term features play important roles in predicting the adoptability of ideas and the best classification accuracy was achieved by the hybrid classification models. In most cases, the precisions of classification models decreased as the number of recommendations increased, while the models’ recalls and F1s increased. Originality/value This research dealt with the problem of information overload in an open innovation context. A large amount of customer opinions from an innovation community were examined and a recommendation system to mitigate the problem was proposed. Using the proposed system, the firm can get recommendations for ideas that could be valuable for its business innovation in the idea generation phase, thereby resolving the information overload and enhancing the effectiveness of open innovation.

An Analysis of Organizational-Adoptable and User-favorable Ideas in a Crowdsourcing Community : Focused on MyStarbucksIdea.com

Open innovation concept is advocating the importance of the customer roles in firm`s innovation. As a result, crowdsourcing community is drawing attention as a strategic asset for open innovation across diverse industries. Considering that the goal of crowdsourcing community is harnessing innovative ideas, understanding the characteristics of user-favorable and organization-adoptable ideas can enhance the effectiveness of idea crowdsourcing. In our approach, we extract idea content-based characteristics such as subjectivity, negativity, prosocialneess, and depth of idea to examine what are the factors that affect user preference and organizational adoption. An analysis of 71,134 ideas from MyStarbucksIdea.com shows that there are significant differences between user-favorable and organization-adoptable ideas in terms of idea characteristics. Lastly, both theoretical and managerial implications are discussed.

The Influence of Negative Emotions on Customer Innovation Activities: An Examination Using Sentiment Analysis

With the advent of Web 2.0, increased user participation in diverse e-communities resulted in an abundance of information, including emotional information. We examined the influence of negative emotion in an online brand community, MyStarbuckIdea.com, developed to collect diverse customer ideas for the firm?s innovation, with the purpose of investigating how such emotion affects customer activities for innovation in the community. We first established several hypotheses on the relationships between discrete negative emotions and innovation activities. Then, having collected 84,918 customer ideas, we conducted POS tagging and term-based matching to calculate the inclusion and intensity of negative emotion using the negative emotion lexicon which we developed. As a result of testing our hypotheses with regression models, we show that 1) negative emotion significantly affects innovation activities in the brand community, and frustration is the most influential among the discrete negative emotions; and 2) as the intensity level of negative emotions increases, so does their influence.

A Comparative Analysis between Organization-Adoptable and User-Favorable Ideas in a Crowdsourcing Community

Traditionally, organizations have innovated themselves with their internal resources. However, due to the rapid development of technology and the frequent changes in the business environment, organizations have begun to open their innovation process advocating the importance of the customer role. On...