• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.190-198
• /
• 2023

To enhance customer satisfaction for higher profits, an e-commerce sector can establish a continuous relationship and acquire new customers. Utilize machine-learning models to analyse their customer's behavioural evidence to produce their competitive advantage to the e-commerce platform by helping to improve overall satisfaction. These models will forecast customers who will churn and churn causes. Forecasts are used to build unique business strategies and services offers. This work is intended to develop a machine-learning model that can accurately forecast retainable customers of the entire e-commerce customer data. Developing predictive models classifying different imbalanced data effectively is a major challenge in collected data and machine learning algorithms. Build a machine learning model for solving class imbalance and forecast customers. The satisfaction accuracy is used for this research as evaluation metrics. This paper aims to enable to evaluate the use of different machine learning models utilized to forecast satisfaction. For this research paper are selected three analytical methods come from various classifications of learning. Classifier Selection, the efficiency of various classifiers like Random Forest, Logistic Regression, SVM, and Gradient Boosting Algorithm. Models have been used for a dataset of 8000 records of e-commerce websites and apps. Results indicate the best accuracy in determining satisfaction class with both gradient-boosting algorithm classifications. The results showed maximum accuracy compared to other algorithms, including Gradient Boosting Algorithm, Support Vector Machine Algorithm, Random Forest Algorithm, and logistic regression Algorithm. The best model developed for this paper to forecast satisfaction customers and accuracy achieve 88 %.

• The Journal of Economics, Marketing and Management
• /
• v.11 no.4
• /
• pp.1-10
• /
• 2023

Purpose: This study investigated the relationship between product characteristics and customer purchase intention in live-streaming commerce. Research design, data and methodology: Six independent factors namely, scarcity, customization, discount, experimentalism, novelty, and informativeness were identified to analyze their effects on customer purchase intention in live-streaming commerce. The perceived value was accepted as a mediator between independent and dependent variables. Data were gathered from 643 respondents who experienced purchases in live-streaming commerce in China. Results: The results show that product characteristics strongly affect customer purchase intention, and perceived value plays an important mediating role in live-streaming commerce. Therefore, when developing a sales strategy in live-streaming commerce, product characteristics. Such as customization, discount, experimentalism, novelty, and information must be considered. Conclusions: The majority of live-streaming commerce research has focused on platform interactions and consumers. This study is meaningful in that it dealt with product characteristics and confirmed the mediating roles of perceived value in live-streaming commerce. The findings of this study have significant implications and offer valuable insights and practical guidance for both the academic community and practitioners engaged in the field of live-streaming commerce.

• Journal of Distribution Science
• /
• v.22 no.1
• /
• pp.79-94
• /
• 2024

Purpose: The popularity of social media has altered how customers interact with businesses, and an increasing number of customers prefer to voice their complaints on social media. Bystanders can observe the customer complaint process on social media, but the impact of transparency on bystanders remains uncertain. Therefore, this study established and verified a model for defining the effect of transparency and service recovery types on bystanders. Research Design and Methodology: In this study, we used the internet survey platform "So Jump" to collect data. And we validated three studies with SPSS 26.0 and Smart PLS 4.0. Result: First, we showed that the transparency process (vs. result) is more likely to increase customer forgiveness and E-loyalty and reduce E-NWOM intention among bystanders. Second, customer forgiveness also plays a complementary mediating role between transparency and E-loyalty, as well as between transparency and E-NWOM intention. Finally, we found a modest interaction effect between transparency (process vs. result) and service recovery types (psychological vs. tangible vs. hybrid) on bystanders' customer forgiveness and E-loyalty. Conclusions: This study provides actionable recommendations for how service managers can effectively employ social media as a means for distributing feedback information to manage service recovery in the future.

• Knowledge Management Research
• /
• v.24 no.4
• /
• pp.153-176
• /
• 2023

Generative AI, especially conversational AI like ChatGPT, has recently gained traction as a technological alternative for automating customer service. However, there is still a lack of research on whether current generative AI technologies can effectively replace traditional human managers in customer service automation, and whether they are advantageous in some situations and disadvantageous in others, depending on the conditions and environment. To answer the question, "Can generative AI replace human managers in customer service activities?", this study conducted experiments and surveys on customer online reviews of a food delivery platform. We applied the perspective of the elaboration likelihood model to generate hypotheses about whether there is a difference between positive and negative online reviews, and analyzed whether the hypotheses were supported. The analysis results indicate that for positive reviews, generative AI can effectively replace human managers. However, for negative reviews, complete replacement is challenging, and human managerial intervention is considered more desirable. The results of this study can provide valuable practical insights for organizations looking to automate customer service using generative AI.

• The Journal of the Korea Contents Association
• /
• v.14 no.12
• /
• pp.924-934
• /
• 2014

In the last 10 years the digital music contents market has grown rapidly. However digital music contents product and services are not managed with product planning and price policy considered customer attitude and digital music contents values. This study is to define the value properties of digital music contents services based on streaming and download as genre, price, sound quality, and usage appliance, and suggest the strategic market price and service composition of digital music contents service by customer attitudes about the value properties. The research used the conjoint analysis methodology based on the hedonic price model and collected 405 questionaries by users of Korean digital music contents services to the analysis. Hence 'sound quality' in download platform, and 'appliance' in streaming platform were the elements to evaluate the customer attitude. The results present the music contents productions and companies have to provide the differentiated services and price by the value properties of user preference in the market.

• Journal of Intelligence and Information Systems
• /
• v.17 no.4
• /
• pp.1-17
• /
• 2011

In order to maintain customer satisfaction and to remain productive and efficient in today's global competition, mass customization is adopted in many leading companies. Mass customization through product family and product platform enables companies to develop new products with flexibility, efficiency and quick responsiveness. Thus, product family strategy based on product platform is well suited to realize the mass customization. Product family is defined as a group of related products that share common features, components, and subsystems; and satisfy a variety of market niches. The objective is to propose a product family design strategy that provides priority weights among product components by satisfying customer requirements. The decision making process for a new product development requires a multiple criteria decision making technique with feedback. An analytical network process is adopted for the decision making modeling and procedure. For the implementation, a netbook product known as a small PC which is appropriate for the product family model is adopted. According to the proposed architecture, the priority weight of each component for each product family is derived. The relationship between the customer requirement and product component is analyzed and evaluated using QFD model.

• Information Systems Review
• /
• v.24 no.3
• /
• pp.1-21
• /
• 2022

This research investigates how a service provider's response(s) to negative customer reviews influences the success of accommodation services in the context of online accommodation reservation platforms. Specifically, we attempt to comprehend the important role of attentive and instant responses to users' negative review comments in fostering future success by analyzing panel data on 856 motels registered in the largest accommodation reservation platform in Korea. The results present that response volume (Attentiveness) and faster responses (Timeliness) are positively associated with success. We further find that the two review-response strategies have a positive interaction effect on success. Moreover, we show that the effect of review responses is strengthened when the reputation of motels drops. The key findings of this research offer a set of practical guidelines for accommodation owners to achieve business success by effectively managing customer reviews and claims

• The Journal of Information Systems
• /
• v.24 no.3
• /
• pp.47-74
• /
• 2015

Purpose By participating in the business ecosystems, customers make both positive and negative impacts in the ecosystem. In particular, users of platform businesses participate in the business ecosystem as partial employees who voluntarily create and manage content. According to the organizational behavior literature, employees' psychological ownership toward the organization has an influence on the organizational competitiveness. Thus, with an assumption that customers gain psychological ownership toward the business that they participate in, it is important to analyze the process and the factors that influence their psychological ownership. This study proposes a research model that describes the process: customers undertake customer socialization, which then lead them to participate in the business-level and the business ecosystem-level activities. Through the participation, customers gain psychological ownership toward the business. Design/methodology/approach Based on a structural equation model, this study analyzes the data regarding the factors in the research model. Data was collected by surveying college students who represent themselves as Facebook and DaumKakao users. By analyzing the collected data, the relationships are validated between customer socialization and customer participations (i.e., both business-level and business ecosystem-level participation), and between the participations and customers' psychological ownership. Findings Based on the validation, this study confirms the importance of managing customers' psychological ownership and offers customers' participation by their socialization as a solution for increasing customers' psychological ownership. Also, this study proposes the business ecosystem research model as the general research framework for future research and expands the scope of strategic management from the individual level strategy to the business ecosystem wide perspective.

• Asia pacific journal of information systems
• /
• v.22 no.4
• /
• pp.51-73
• /
• 2012

Social network services based on openness, connectedness, and mass participation are reshaping many aspects of how companies conduct business and create value for their customers. For instance, Facebook and Twitter are expected to play a pivotal role as a new communication channel through which companies-forge close relationships with their customers for co-creation of value for mutual benefits. Given the potential of social network services, it is not surprising that many companies have strategically invested in social network services to reach out to customers. Despite the growing interest in social network services as a platform to connect companies and their customers, few guidelines exist about how managers can effectively utilize social network services in forging relationships with their customers. As such, scholars should pay greater attention to how firms can successfully develop relationships with their customers on social network services. In particular, this study employs the S-O-R (stimulus-organism-response) framework as a theoretical lens to develop a research model that explains customers' participation in the value co-creation platform that companies opened on Twitter. According to the S-O-R framework, certain types of individuals' behaviors can be best understood based on a causal link from environmental stimulus to organism, and response. We apply the S-O-R framework to understand how ubiquitous connectivity (stimuli) can influence customers' experience (organism) with companies on Twitter, which in turn influence their participation behavior (response). Two steps have been undertaken to empirically test the research model. First, we conducted a content analysis of tweets written by customers who follow companies on Twitter. As a result, we found event/promotion participation, company support, and giving feedback as three specific types of customer participation behavior. Second, we conducted a web-based survey to test research hypotheses in the research model. Participations in the survey were solicited to customers who followed companies on Twitter. As a result, a total of 115 respondents have completed the survey. Data were analyzed using the partial least square (PLS) technique. The results of data analysis suggest that ubiquitous connectivity (stimuli) had strong positive effects on perceive usefulness, perceived enjoyment, and perceived intimacy (organism). Perceived intimacy showed positive effects on customer participation behavior (response), such as event participation, company support, and giving feedback. Perceived enjoyment was found to have strong positive effects on company support and giving feedback. On the other hand, perceived usefulness did not have significant impacts on the three types of customer participation behavior.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.3
• /
• pp.95-104
• /
• 2012

The companies have employed SNS for marketing, promotion, and customer relationship management. The SNS is a good tool to collect customers' opinions and to collaborate with internal and external employees, however, the function of SNS are limited in implementing a co-creation. Therefore, the purpose of this research is to suggest a SNS platform for co-creation that creates a corporate's values with customers. For this purpose, the limitations of SNS are defined and the new platform of the SNS is suggested. The proposed platform has 3 modules including integration of applications, cloud services, and integration to applications operated by companies. With a scenario method the suggested platform was validated. This is one of pioneer studies in co-creation.