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The purpose of this paper is to demonstrate how negatively worded innovative ideas can be rejected during a crowdsourcing event sponsored by a service firm via an online forum. The goal of an ideation forum is to collect user-generated content in the form of ideas for new products or services. An ideation forum attempts to clarify the “fuzziness” on the front-end of new product development.

A 2 × 2 (satisfied/dissatisfied customers and negatively/positively worded ideas) experiment replicates the effect of mood-incongruent interactions within ideation forums and measures the likelihood for an idea to be buried or selected on the basis of its merit rather than its negative/positive wording.

The results demonstrate that mood-incongruent interactions have different effects on different groups of participating customers. Negatively worded innovative ideas are rated lower by satisfied customers, despite their superior merit.

The nature of the experiment shows a high validity, but lacks in reliability. Thus, future research should attempt to replicate this experiment on a larger scale and across different industries.

In an open forum where thousands of customers can give a thumbs’ up or down to an idea, merit should prevail over mood-congruency. If the crowdsourcing mechanism cannot be trusted, it puts the burden back on the firm’s review team to promote or review any downgraded innovative idea, which ends up being counterproductive.

These findings shed light on the hidden aspect of crowdsourcing when the aim is to find unique, if not radical, ideas for services. Thus, hoteliers and other hospitality and tourism managers should use these findings to design better ideation forums.

Service innovation is a key source of competence for service enterprises. Along with the emergence of crowdsourcing platforms, consumers are frequently involved in the process of service innovation. In this paper, the authors describe the crowdsourcing ideation website—MyStarbucksIdea.com—and find the motivations of customer-involved service innovation.

Using a rich data set obtained from the website MyStarbucksIdea.com, a dynamic structural model is proposed to illuminate the learning process of consumers.

The results indicate that initially individuals tend to underestimate the costs of the firm for implementing their ideas but overestimate the value of their ideas. By observing peer votes and feedbacks, individuals gradually learn about the true value of ideas, as well as the cost structure of the firm. Overall, the authors find that the cumulative feedback rate and the average potential of ideas will first increase and then decline.

First, the previous researches concerning the crowdsourcing show that the creative implementation rate is low and the number of creative ideas decreases, and few scholars have studied the causes behind the problems. Second, the data used in this paper are true and valid, and it is difficult to obtain now. These data can provide strong empirical support for the model proposed in this paper. Third, it is relatively novel to combine the customer learning mechanism and heterogeneity theory to explain the phenomenon of reduced creativity and low implementation rate in crowdsourcing platform, and the research results can provide a reasonable reference for the construction of this industry.

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.

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.

The results show that the number of ideas posted and the number of comments posted are the most significant among the features. And most of comment-related sentiment features found to be meaningful, while most of idea-related sentiment features are not in the prediction of idea launchers. In addition, this study show classification rules for the identification of potential idea launchers.

This study dealt with information overload problem in an open innovation context. A large volume of textual customer contents from an innovation community were examined and classification models to mitigate the problem were proposed using sentiment analysis and data mining techniques. Experimental results show that the proposed classification models can help the firm identify potential idea launchers for its efficient business innovation.

The study aims to use netnography to investigate the role of customers' contributions in social networks for NSD purposes.

The study adopted an exploratory case study methodology to conduct a content analysis of customers' contributions in a social network, namely www.mystarbucksidea.com. Netnography was used for data analysis and interpretation.

The findings reveal that online customers' interactions and dialogues enable customers to share and understand the context of using services, which in turn triggers emotions and cognition that help customers to generate and further enhance ideas for new services. Thus, the variety of customers and the sharing of their diverse roles have a positive influence on enabling participants of online social networks to generate new service ideas.

The findings are applicable to the study's context, but future research should try to triangulate and enhance them by conducting studies in other contexts. The findings also provide ideas on how to further investigate the observational learning processes and behavioural impacts taking place amongst customers' interactions within online social networks.

The findings provide several implications showing firms why and how to nurture, develop and moderate online customer interactions to enhance the effectiveness of their NSD processes.

The paper examines the role and the management of customers' contributions in social networks for NSD purposes. The topic has received only limited attention in traditional and online settings. Several suggestions for further research are also provided.

The purpose of this paper is to analyze the extent to which the use of social media can support customer knowledge management (CKM) in organizations relying on a traditional bricks‐and‐mortar business model.

The paper uses a combination of qualitative case study and netnography on Starbucks, an international coffee house chain. Data retrieved from varied sources such as newspapers, newswires, magazines, scholarly publications, books, and social media services were textually analyzed.

Three major findings could be culled from the paper. First, Starbucks deploys a wide range of social media tools for CKM that serve as effective branding and marketing instruments for the organization. Second, Starbucks redefines the roles of its customers through the use of social media by transforming them from passive recipients of beverages to active contributors of innovation. Third, Starbucks uses effective strategies to alleviate customers' reluctance for voluntary knowledge sharing, thereby promoting engagement in social media.

The scope of the paper is limited by the window of the data collection period. Hence, the findings should be interpreted in the light of this constraint.

The lessons gleaned from the case study suggest that social media is not a tool exclusive to online businesses. It can be a potential game‐changer in supporting CKM efforts even for traditional businesses.

This paper represents one of the earliest works that analyzes the use of social media for CKM in an organization that relies on a traditional bricks‐and‐mortar business model.

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.

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.

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.

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.

This paper aims to propose an extended model to examine these motivations. As technology-led changes have revolutionized the marketplace, researchers and practitioners have grown keen to understand customers’ motivations for engaging in co-innovation in online communities.

The research model is based on a review of previous literature and relevant business practices.

The proposed conceptual model can be used to test empirically and explicate customers’ attitude towards engagement in co-innovation communities in the hospitality industry. Three major motivations drive customer engagement in online co-innovation communities (OCCs): brand equity, sense of community and monetary incentive. Customers’ prior experience with co-innovation projects also moderates the effects of the three motivations on customers’ attitude towards engagement in OCCs.

The proposed model highlights the importance of engaging customers through OCCs to create service innovations. These OCCs advance customers’ active participation in the firm’s co-creation and co-innovation process. Leading service firms already rely on online brand communities to stay on the cutting edge. Co-creation represents a unique, strategic partnership between the firm and the customer that can enhance both the customer experience and the firm’s innovativeness.

This study provides an initial exploration of the key components of the co-innovation of service through online communities in the hospitality industry.

In this interview with Prof. Venkat Ramaswamy, Strategy & Leadership reviews the way the concept of co-creation of value with customers is being implemented on its tenth anniversary. Prof. Ramaswamy explains the basic elements of the co-creation playbook.

Based on his research with companies pioneering innovation co-creation with customers, Prof. Ramaswamy offers insights for executives into what makes this perspective different and powerful.

Prof. Ramaswamy discusses the guiding principle underlying the transformation of enterprises towards co-creation: how to engage people to create valuable experiences together while enhancing network economics.

In designing and managing a co-creation platform, ask, how accessible is it to consumers or any other key stakeholders; how well does it facilitate dialogue among them; how transparent is this interaction to all, which helps to build trust and attract even more participants; and how well does it enable the reflexive leveraging of the innovation and learning generated to enhance the value of the platform?

Senior executives need to know how co-creation engagement platforms can also be used to generate ideas for continuously improving products and services through the lens of customer experiences.

This paper aims to explore the factors that influence Generation Y’s positive or negative electronic word-of-mouth (eWOM) behavior via social media and mobile technology in the foodservice sector. Three types of dining experiences were examined: positive and negative customer experiences and negative customer service followed by a satisfactory recovery package.

A survey was adopted to test the factors posited to influence Generation Y consumers in these service contexts. Participants were recruited through Amazon Mechanical Turk , and multi-group structural equation modeling was performed to analyze the data.

Active use of social media and peer influence had a sweeping influence on Generation Y’s intentions to engage in eWOM about their service experiences. Technological sophistication with mobile technology influenced Generation Y to spread positive or negative service experiences, rather than satisfactory recovery experiences. Family influence had a mixed influence on Generation Y subgroups (21-24 years old vs 25-35 years old) to engage in eWOM about their satisfactory or poor service experiences. In satisfactory recovery experiences, family influence showed no significant influence on Generation Y’s eWOM behaviors.

This study enriches online reviews and eWOM marketing theories, adds to service failure and recovery literature and enhances understanding of consumer behavior expressed by Generation Y through the empirical investigation of Generation Y consumers’ behavioral motivations to engage in eWOM through social media and mobile technology.

Engaging Generation Y consumers with social media campaigns and mobile technology development is not merely sufficient in eWOM marketing strategies. Instead, it is essential to create integrative peer communities to motivate Generation Y consumers to engage in eWOM marketing. Marketers need to pay attention to the mixed effects of family influences on the eWOM behaviors of subgroups of Generation Y in positive or negative service experiences.

Given the scarcity of consumer behavior research into Generation Y as an emerging market segment, this paper makes an incremental contribution by developing and validating a model of factors that influence Generation Y consumers’ eWOM intentions through social networking and mobile technologies in three major service contexts: positive, negative and recovery following a service failure.