Artificial Neural Networks and Structural Equation Modeling: Marketing and Consumer Research Applications

ISBN-13: 9789811965081 / Angielski / Twarda / 2022 / 341 str.

Alhamzah Alnoor; Khaw Khai Wah; Azizul Hassan

Opis

This book goes into a detailed investigation of adapting artificial neural network (ANN) and structural equation modeling (SEM) techniques in marketing and consumer research. The aim of using a dual-stage SEM and ANN approach is to obtain linear and non-compensated relationships because the ANN method captures non-compensated relationships based on the black box technology of artificial intelligence. Hence, the ANN approach validates the results of the SEM method. In addition, such the novel emerging approach increases the validity of the prediction by determining the importance of the variables. Consequently, the number of studies using SEM-ANN has increased, but the different types of study cases that show customization of different processes in ANNs method combination with SEM are still unknown, and this aspect will be affecting to the generation results. Thus, there is a need for further investigation in marketing and consumer research. This book bridges the significant gap in this research area. The adoption of SEM and ANN techniques in social commerce and consumer research is massive all over the world. Such an expansion has generated more need to learn how to capture linear and non-compensatory relationships in such area. This book would be a valuable reading companion mainly for business and management students in higher academic organizations, professionals, policy-makers, and planners in the field of marketing. This book would also be appreciated by researchers who are keenly interested in social commerce and consumer research.

Spis treści

Introduction

Alhamzah Alnoor

Part I Artificial Neural Network and Structural Equation Modeling Techniques: Social commerce 

Chapter 1. Artificial neural network and structural equation modeling techniques

The goal of using the SEM approach with ANN is to capture linear and non-compensated relationships. However, there are many shortcomings in understanding the mechanism of application of such techniques. Therefore, this chapter describes the concept of the SEM method and the concept of ANN. Hence, an insight into how to adopt the ANN method with SEM will be provided. Finally, the discussion and conclusion of this chapter will be addressed.

Chapter 2. Social commerce determinants 

There are many determinants of social commerce that have been touched upon in the literature. Thus, this chapter aims to shed light on the determinants of social trading, such as the theory of social presence, the theory of social support, the theory of innovation barriers, and the elaboration likelihood theory and commitment trust theory. This chapter describes several theories that strengthen consumers' intentions and confidence in online commerce channels. Finally, discussion and conclusion will be described. 

Chapter 3. Technology acceptance model in social commerce

Acceptance of technology is a vital issue that faces many resistances from consumers. Much of the literature adopted the UTAUT, the UTAUT2, and the TAM2 model. Scientists have expanded such models extensively. Describing the factors of technology acceptance models contributes to shedding light on the most important factors of customer resistance to adopting new payment methods or adopting new electronic channels. This chapter provides insight into the application of technology acceptance models in social commerce and consumer research.

Chapter 4. Mobile commerce and social commerce 

With the development of Web 2.0 technology, the trends towards mobile adoption in commerce increased. Describing the role of the new trend in commerce will assist many researchers to identify the gaps and challenges towards the use of such technology. However, there are many doubts about the adoption of mobile commerce by customers. Minimal trust in mobile commerce increases the possibility of failure of several businesses Therefore, this chapter describes the determines and benefits of using mobile commerce based on the SEM and ANN approach. 

Chapter 5. Electronic word of mouth and social commerce

Advances in Web 2.0 technologies have led to the wide adoption of electronic commerce platforms as an innovative shopping method to replace traditional shopping. However, due to pro-technology bias, scholars focus on technology adoption and slightly attention has been paid to the impact of electronic word of mouth (eWOM) on customers’ intention to use new online channels. This chapter addresses this gap by examining this intention through exploring the effect of eWOM on customers’ intention. In addition, this chapter will address the role of the positive and negative factors of eWOM such as affective, mishandling, and aesthetics factors in social commerce.

Chapter 6. Determinants of customer intentions to use social commerce 

Advances in Web 2.0 technologies have led to the wide adoption of electronic commerce platforms as an innovative shopping method to replace traditional shopping. However, due to pro-technology bias, scholars focus on technology adoption and slight attention has been paid to the impact of electronic word of mouth (eWOM) on customers’ intention to use new online channels. This study addresses this gap by examining this intention through exploring the effect of eWOM on male and female intentions and identifying the mediation of perceived crowding. This chapter contributes to shedding light on the determinants of customers' intentions towards social commerce channels based on SEM and ANN methods. 

Chapter 7. Barriers to using social commerce

Several barriers such as Usage barrier, value barriers, risk barrier, tradition barrier, and image barrier, perceived risk, and so on increase customer skepticism in social commerce. The SEM and ANN literature has attempted to investigate further barriers. Exploring and identifying barriers to social commerce adoption by customers provide practical and theoretical implications for practitioners and academics. This chapter attempts to focus on the barriers to social commerce adoption.

Chapter 8. The role of blockchain adoption and supply chain practices on social commerce 

Supply chains provide support for social commerce activities. However, the use of blockchain technology with supply chains increases competitive advantages such as quality, timeliness, reduced risk, and reliability. Social commerce transactions through Blockchains prevent fraud, increase security and are essential to supply chains. This chapter provides insight into the use of Blockchains with supply chains in social commerce activities. Hence, the most important challenges and issues related to the topic will be discussed.

Chapter 9. Social commerce of rural communities

Social commerce firms must improve design, arrangement, and level of security on online channels of rural communities. Potential customers adopt social commerce platforms that have positive information regarding the review of products or services by previous customers in rural communities. In addition, confidence in information is generated based on the security of social commerce platforms in rural communities. In-depth investigation into social commerce of rural communities will contribute to shedding light on the determinants of customers' intentions towards online commerce in such sector. Many challenges and limitations of social commerce of rural communities will be described in this chapter.

Part II Artificial Neural Network and Structural Equation Modeling Techniques: Technology of marketing 

Chapter 10. Determinants of wearable technology

Wearable devices are easy to use and can handle many transactions online such as watches, jewelry, clothes, and eyeglasses. Wearable devices can access the Internet. The use of wearable devices has spread to many countries. Highlighting the benefits of adopting such a technology increases the contributions that can be made to literature and practitioners. Therefore, this chapter describes determinants of wearable technology. In addition, discussing many factors that stimulate the adoption of such a technique.

Chapter 11. Mobile payment technology 

Using mobile payment technology improves many tasks. Mobile payment technology has a high value due to the perceived benefit of such a technology. Adopting mobile payment technology increases purchasing convenience, improves customer satisfaction, and increases efficiency at checkout. However, the SEM and ANN literature has explored many of the determinants of mobile payment technology adoption such as mobile usefulness, price savings, and referent network size. This chapter contributes to describing the determinants of mobile payment and provides practitioners with insight into how to motivate customers to adopt mobile payment technology.

Chapter 12. The role of Online advertising in the intentions of customers

Online advertising boosts content ratings and increases sales. Online advertising has grown across different product categories. Many social commerce companies allocate huge amounts to online advertising. For example, $2.9 billion is spent annually on advertising by Walmart. Trust in online advertising is a vital factor because the effectiveness of advertisements is affected in the case of low consumer confidence in advertisements. Developing consumer confidence in advertising is a complex process that requires an exploration of linear and nonlinear relationships. Thus, this chapter describes the role of online advertising in the intentions of customers.

Chapter 13. Intention to use social media technology amongst customers 

Intention to use social media technology amongst customers is important to understanding customers' perceptions of online commerce products and services. Social media technology includes entertainment, personalization, direction, interaction, and word of mouth. Customer interaction on social media platforms aims to facilitate communication and provide emotional and informational support. Nevertheless, this chapter attempts to provide more theoretical contributions that expand the literature on such a topic. Hence, at the end of the chapter, the discussion and conclusion are described.

Chapter 14. Barriers to using mobile payment technology 

Barriers to using mobile payment technology are a significant impediment to users adopting new technologies. Barriers can be defined as the consumer's opposition to any innovation. The barriers to using mobile payment technology will therefore be described in this chapter. Several theories that influence the adoption of mobile payment technology such as social bond theory and social network theory will be addressed.

Chapter 15. Revisiting technology acceptance model (TAM2) in behavioral targeting advertising

The technology acceptance model (TAM) consists of seven factors: subjective norms, output quality, voluntariness, job relevance, image, result demonstrability, and experience. However, the development of the technology acceptance model to become TAM2 increased the explanatory power of TAM2 to be 20% higher than that of the original TAM. Many industries such as electronic commerce have adopted such a model. Assigning and describing the role of the TAM2 model in social commerce is a vital issue addressed in this chapter.

Part III Artificial Neural Network and Structural Equation Modeling Techniques: Sustainability of marketing 

Chapter 16. Green practices in marketing

This chapter aims to describe the role of green communication, openness, and altruism on customers' intentions to purchase green products. The theory of planned behavior and value-attitude-behavior cognitive hierarchy will be described in this chapter. In addition, many challenges and issues associated with green practices in social commerce will be addressed.

Chapter 17. Social responsibility in marketing

Social trading companies must adhere to the concept of social responsibility by engaging in activities that provide benefits to society. Social responsibility in marketing is through providing products and services that help the community environmentally, socially, and economically. Several literatures have discussed the role of social responsibility in customer intentions towards social trading channels. Discussing and describing the role of social responsibility in marketing is an important issue that needs to be investigated. This chapter describes the role of social responsibility in marketing activities. Promotions that raise awareness of societal issues and problems, recyclable packaging, and direct portions of profits toward charitable efforts are critical factors that will be described in this chapter as well.

Part IV Artificial Neural Network and Structural Equation Modeling Techniques: Future Research Directions

Chapter 18. Artificial neural network and structural equation modeling in future 

According to the literature survey, 75 articles were identified that dealt with the application of the SEM with ANN method. Much of the literature has focused on marketing such as social commerce and customer intentions. However, there is a huge gap in the previous literature that needs to be addressed. In this context, this project will contribute to potential future work by extending the application of the mentioned techniques to more vital applied topics such as entrepreneurship, family business, organizational studies, and the health sector. Hence, this chapter will describe the potential future work of SEM and ANN by highlighting several issues that need to be explored on the basis of linear and nonlinear relationships.

Conclusion

O autorze

 Alhamzah Alnoor is a professional administrator with ten years of experience in organizational studies, social commerce, internship programs, multi-criteria decision analysis, leadership and innovation, strategic planning, and technology acceptance models. Successfully achieved several projects during my career with impactful business values. Creative, flexible, motivated with active optimism and belief in diversity and inclusion. He is a reviewer for many journals. He published many papers in different and high-impact journals. He is a senior lecturer at the Southern Technical University, Management Technical College. He received his M.B.A. from the University of Basrah, Iraq. He received his Ph.D. from the School of Management, Universiti Sains Malaysia, Malaysia.

Khaw Khai Wah is a senior lecturer in the School of Management, Universiti Sains Malaysia. He holds a Ph.D. in statistical quality control from Universiti Sains Malaysia. He is a coordinator of the Business Analytics Program in the School of Management, USM. His areas of research are in advanced analytics and statistical quality/process control. He has featured in prominent international publications. His efforts and excellence have been acknowledged and awarded at several dignified platforms. He is actively involved in conducting training in statistics and visualization. Prior to his academic career, he worked in a renowned US multinational company as a data analytics team leader.

Azizul Hassan is a member of the Tourism Consultants Network of the UK Tourism Society. Hassan’s areas of research interest are technology-supported marketing for tourism and hospitality, immersive technology application in the tourism and hospitality industry, and technology-influenced marketing suggestions for sustainable tourism and hospitality industry in developing countries. Hassan authored over 100 articles and book chapters in leading tourism outlets. He is also part of the editorial team of 20 book projects from Routledge, Springer, CAB International and Emerald Group Publishing Limited. Hassan is a regular reviewer of Tourism Management, Journal of Hospitality and Tourism Management, Tourism Analysis, the International Journal of Human Resource Management, Journal of Ecotourism, Journal of Business Research, eReview of Tourism Research (eRTR), International Interdisciplinary Business-Economics Advancement Journal, International Journal of Tourism Cities, Heliyon, Technology in Society, Anatolia, Journal of King Saud University - Computer and Information Sciences, and Tourism Recreation Research.