طراحی و اعتبارسنجی الگوی رفتار مصرف کننده مبتنی بر محتوای کاربر ساخته در صنعت بانکداری (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
هدف پژوهش حاضر طراحی و اعتبارسنجی الگوی رفتار مصرف کننده مبتنی بر محتوای کاربر ساخته (UGC) در صنعت بانکداری می باشد. روش پژوهش با توجه به هدف آن، کاربردی و از حیث شیوه اجرا، آمیخته (کیفی-کمی) و از نظر استراتژی اجرای پژوهش توصیفی- اکتشافی می باشد. جامعه آماری در بخش کیفی شامل 15 نفر از خبرگان نظام بانکداری و دانشگاهی فعال در حوزه بازاریابی محتوایی و به روش نمونه گیری هدفمند قضاوتی و جامعه آماری در بخش کمی شامل 384 نفر از کلیه مشتریان بانک سپه شهر تهران که با استفاده از فرمول کوکران به عنوان نمونه و به روش نمونه گیری در دسترس انتخاب شدند. ابزارهای جمع آوری داده شامل محتوای کاربرساخته در شبکه های اجتماعی و پرسشنامه خبره مبنا برای مدلسازی و پرسشنامه با طیف لیکرت پنج تایی برای اعتبارسنجی بودند. در تجزیه وتحلیل داده های بخش کیفی با استفاده از تحلیل مضمون و از نرم افزار MICMAC و در بخش کمی از نرم افزارSPSS و PLS استفاده شد. ترکیب نتایج تحلیل مضمون و مدلسازی ساختاری- تفسیری، منتج به ارائه الگوی رفتار مصرف کننده برمبنای محتوای کاربر ساخته گردید. مضامین اصلی الگو شامل محتوای کاربر ساخته، احساسات و نگرش مشتریان، انتظارات مشتریان، کنش های مشتریان نسبت به محتواهای کاربرساخته و توسعه برند بر مبنای محتوای کاربرساخته است. نتایج تحلیل مضمون و مدلسازی ساختاری-تفسیری، به تأیید اعتبار الگو و تأیید تمامی فرضیه ها (به غیر از اثر تعدیل گری انتظارات مشتریان مبتنی بر محتوای کاربرساخته) منجر شده است.Design and validation of consumer behavior model based on user-generated content in the banking industry
The aim of the current research is to design and validate the consumer behavior model based on user-generated content (UGC) in the banking industry. According to its purpose, the research method is practical, and in terms of implementation method, it is mixed (qualitative-quantitative), and descriptive-exploratory in terms of the implementation strategy of research. The statistical population in the qualitative part includes 15 people from the experts of the banking and academic system active in the field of content marketing,selected by the method of judgmental purposeful sampling; and the statistical population in the quantitative part includes 384 people from all the customers of Sepah Bank in Tehran, selected using Cochran's formula as a sample, by available sampling method. Data collection tools included user-generated content in social networks and expert-based questionnaires for modeling and questionnaires with a five-point Likert scale for validation. MICMAC software was used in qualitative part data analysis and SPSS and PLS software was used in quantitative part. The combination of thematic analysis and structural-interpretive modeling resulted in the presentation of consumer behavior patterns based on user content. The main themes of the model include user-generated content, customer sentiments and attitudes, customer expectations, customer actions towards user-generated content, and brand development based on user-generated content. The results of theme analysis and structural-interpretive modeling have led to the validation of the model and the verification of all hypotheses (except for the moderating effect of customer expectations based on user-generated content).
Extended
Introduction
Engaging the audience in marketing activities has become one of the most important concerns of marketers, and in this regard, the use of user-generated content has received more attention than in the past (Liu et al, 2019).
User-generated content became popular as a new concept following the growth of Web 2 technology, and it also attracted the attention of marketing experts during this period. User-generated content refers to those contents published by users using various online social platforms (Naeem, 2019). In fact, any form of content, which is produced outside of professional structures, is called user-generated content, usually disseminated in social platforms and technologies including social networks, social computing, web 2, collective action tools, social web, read/write web, Customer-generated networks, virtual communities, computer-mediated communication, socio-technical systems (Koivisto & Mattila, 2018).
Today, knowing that the content produced by users have much deeper effects on consumer behavior, in order to achieve more profit, business owners use different tricks to set up various campaigns with user content (Liu, 2020). On the other hand, in various situations, user-made content campaigns with humanitarian, anti-war, cooperation with minorities, etc., have been held all over the world and have had many effects on consumer behavior (Colicev et al, 2019). Searching for different aspects of user-generated content on social networks has been able to increase interactive communication, word-of-mouth advertising, brand stories, and brand reviews among customers of service providers; so that the discussion regarding the importance of social enthusiasm for the brand and the influence of the produced content has been increasingly noticed among marketing experts, business leaders, marketing managers, and researchers (Naeem, 2019). Therefore, the research begins with the question: what is the pattern of consumer behavior based on user-generated content in social networks?
Theoretical Framework
Consumer behavior
Research has shown that having a correct analysis of consumer behavior can be considered as a critical factor in the success of companies' marketing programs (Taghikhah et al, 2020). In fact, in order for marketing strategies to have the ability to persuade customers to buy a product or service, a correct understanding of consumer behavior must first be created. Therefore, in recent years, marketing experts have emphasized the cognitive theory of emotions in order to describe consumer behavior (Sohrabi & Aghighi, 2018), because with a better insight into understanding consumer needs, better quality services and products can be provided to them, and created sustainable relationships between customers and the company (Bahreinizadeh & Hosseini, 2018).
User-generated content
User-generated content refers to those contents published by users using various online social platforms (Naeem, 2019). In fact, any form of content, which is produced outside of professional structures, is called user-generated content, usually in published in social platforms and technologies including social networks, social computing, web 2, collective action tools, social web, read/write web, Customer-generated networks, virtual communities, computer-mediated communication, and socio-technical systems (Koivisto, Mattila, 2018).
Sadeqi-Arani et al, (2023) investigated the development of the technology acceptance model: investigating the impact of consumption experience, inertia and the culture of the consumer on the acceptance of open banking. The results showed that the new investigated variables, i.e. consumer inertia, uncertainty avoidance, perceived risk, and previous consumption experience have a positive and significant effect on the willingness to accept open banking.
Mandi Habibabadi & Samadi (2023) investigated the effect of user-generated brand content on customers' behavioral responses. The results and data analysis showed that the brand-based content created by the user has an effect on the emotional response, the brand-based content created by the user has an effect on the cognitive response, the emotional response has an effect on the immediate behavioral responses, the emotional response has an effect on the next behavioral response, cognitive response has an effect on immediate behavioral responses, and cognitive response has an effect on subsequent behavioral responses.
Research methodology
According to its purpose, the research method is practical, and in terms of implementation method, it is mixed (qualitative-quantitative), and descriptive-exploratory in terms of the implementation strategy of research. The statistical population in the qualitative part includes 15 people from the experts of the banking and academic system active in the field of content marketing,selected by the method of judgmental purposeful sampling; and the statistical population in the quantitative part includes 384 people from all the customers of Sepah Bank in Tehran, selected using Cochran's formula as a sample, by available sampling method. Data collection tools included user-generated content in social networks and expert-based questionnaires for modeling and questionnaires with a five-point Likert scale for validation.
Research findings
MICMAC software was used in qualitative part data analysis and MICMAC software was used in qualitative part data analysis and SPSS and PLS software was used in quantitative part. The combination of thematic analysis and structural-interpretive modeling resulted in the presentation of consumer behavior patterns based on user content. The main themes of the model include user-generated content, customer sentiments and attitudes, customer expectations, customer actions towards user-generated content, and brand development based on user-generated content. The results of theme analysis and structural-interpretive modeling have led to the validation of the model and the verification of all hypotheses (except for the moderating effect of customer expectations based on user-generated content).
Conclusion
The current research has been conducted with the aim of designing and validating a consumer behavior model based on user-generated content (UGC) in the banking industry. The results of this research are in agreement with the results of Sadeqi-Arani et al, (2023), Mandi Habibabadi & Samadi (2023), javaherizade et al, (2020), Li et al, (2020), Liu (2020), Abrishmi et al, (2020), Colicev et al, (2019), Taghdimi et al, (2019), and Do Paco (2019). Mandi Habibabadi & Samadi (2023) showed that brand-based content created by the user has an effect on emotional response, brand-based content created by the user has an effect on cognitive response, emotional response has an effect on immediate behavioral responses, emotional response has an effect on subsequent behavioral responses, cognitive response has an effect on immediate behavioral responses, and cognitive response has an effect on subsequent behavioral responses.
According to the results of this research, the following suggestions are presented:
It is necessary to provide the requirements of user-generated content production by the bank for the users. In this regard, it is suggested to improve the social media literacy of customers to produce user-generated content, train and develop skilled and expert human resources in the field of information technology in the bank to analyze data, increase the level of security and privacy of customers, bank investment to develop social platforms and technologies, create trust among customers to produce user-generated content, create the ability of customers to access user-generated content platforms.
Bank officials use different tools to produce user-generated content by customers. In this regard, it is suggested to receive customers' criticisms and feedbacks from the services received online, narrating the experiences of customers from the services received on the web platform 2 and 3, receiving online suggestions and recommendations from customers with chatbots, creating user-made content campaigns with philanthropic; benevolent; environmental purposes; and etc., producing video and image advertisements of bank services, exchanging information related to the bank brand among customers, holding a brand story contest and bank brand reviews among customers, describing bank brand services, etc.
تبلیغات
