Customer Complaints Analysis Using Text Mining and Outcome-Driven Innovation Method for Market-Oriented Product Development

A Systematic Procedure for Utilization of Product Usage Information in Product Development

Product design is crucial for product success. Many approaches can improve product design quality, such as concurrent engineering and design for X. This study focuses on applying product usage information (PUI) during product development. As emerging technologies become widespread, an enormous amount of product-related information is available in the middle of a product’s life, such as customer reviews, condition monitoring, and maintenance data. In recent years, the literature describes the application of data analytics technologies such as machine learning to promote the integration of PUI during product development. However, as of today, PUI is not efficiently exploited in product development. One of the critical issues to achieve this is identifying and integrating task-relevant PUI fit for purposes of different product development tasks. Nevertheless, preparing task-relevant PUI that fits different product development tasks is often ignored. This study addresses this research gap in preparing task-relevant PUI and rectifies the related shortcomings and challenges. By considering the context in which PUI is utilized, this paper presents a systematic procedure to help identify and specify developers’ information needs and propose relevant PUI fitting the actual information needs of their current product development task. We capitalize on an application scenario to demonstrate the applicability of the proposed approach.

Cross-Societal Analysis of Climate Change Awareness and Its Relation to SDG 13: A Knowledge Synthesis from Text Mining

The awareness and the engagement of various stakeholders play a crucial role in the successful implementation of climate policy and Sustainable Development Goals (SDGs). SDG 13, which refers to climate action, has three targets for combating climate change and its impact. Among the three targets, SDG 13.3 aims to “improve education, awareness-raising and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning”. This target should be implemented based on the understanding of climate change awareness among various groups of societies. Furthermore, the indicator related to awareness-raising is absent in SDG 13.3. Hence, this study aims to explore the differences in climate change awareness among various social groups within a country from a text mining technique. By collecting and analyzing a large volume of text data from various sources, climate change awareness was investigated from a multilateral perspective. Two text analyses were utilized for this purpose: Latent Dirichlet Allocation (LDA) topic modeling and term co-occurrence network analysis. In order to integrate and comparatively analyze the awareness differences among diverse groups, extracted topics were compared by classifying them into four indicators derived from the detailed targets in SDG 13.3: mitigation, adaptation, impact reduction, and early warning. The results show that the Korean public exhibited a relatively high awareness of early warning compared to the other four groups, and the media dealt with climate change issues with the widest perspective. The Korean government and academia notably had a high awareness of both climate change mitigation and adaptation. In addition, corporations based in Korea were observed to have substantially focused awareness on climate change mitigation for greenhouse gas reduction. This research successfully explored the disproportion and lack of climate change awareness formed in different societies of public, social, government, industry, and academic groups. Consequently, these results could be utilized as a decision criterion for society-tailored policy formulation and promoting climate action. Our results suggest that this methodology could be utilized as a new SDG indicator and to measure the differences in awareness.

A Novel Framework for Identifying Customers’ Unmet Needs on Online Social Media Using Context Tree

Customer needs and user contexts play an important role in generating ideas for new products or new functions. This study proposes a novel framework for identifying customers’ unmet needs on online social media using the Context Tree through the Hierarchical Search of Concept Spaces (HSCS) algorithm. The Context Tree represents the hierarchical structure of nodes associated with related keywords and corresponding concept spaces. Unlike other methods, the Context Tree focuses on finding the unmet needs of customers from online social media. The proposed framework is applied to extract customer needs for home appliances. Identified customer needs are used to make user scenarios, which are used to develop new functions of home appliances.

Investigating the Role of Customer Co-Creation Behavior on Social Media Platforms in Rendering Innovative Services

The emergence of social media platforms as the main representatives of Web 3.0 applications significantly impacts the co-creation activities among enterprises, customers, and other stakeholders, and has enabled firms to benefit from creativity and ideas of their users and customers for developing and rendering innovative services. This study aims to investigate how the co-creation activities of users on social media platforms have an effect on the enterprises’ innovative services. For this purpose, the authors surveyed customers of innovative services who used social media platforms to meet their needs from the enterprises that innovatively offer such services. An online questionnaire was designed and distributed among the sample of customers, and 505 completed questionnaires were analyzed following the PLS-SEM approach. The findings revealed that customer citizenship behavior and customer participation behavior on social media platforms positively affect the rendering of innovative services. Findings also highlighted that an increase in social co-creation activities, as moderator, positively affects customer citizenship behavior on service innovativeness, and negatively affects customer participation behavior on service innovativeness. The findings of this research could be useful for entrepreneurs and managers of the enterprises that offer innovative services to efficiently use social media tools to benefit from the customers’ co-creation activities and to perform more competitively and sustainably in a hostile business environment.