Providing a Sustainable Marketing Model in the Insurance Industry with a Focus on Artificial Intelligence
الموضوعات :
Elnaz Allaf Jafari
1
,
Alireza Rousta
2
,
Farzad Asayesh
3
,
Mahmoud Ahmadi Sharif
4
1 - Department of Business Administration, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
2 - Associate Professor, Department of Business Administration, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
3 - Associate Professor, Department of Business Administration, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
4 - Associate Professor, Department of Business Administration, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
الکلمات المفتاحية: sustainable marketing, artificial intelligence, insurance industry, grounded theory,
ملخص المقالة :
The current research was conducted with the aim of providing a sustainable marketing model in the insurance industry with a focus on artificial intelligence. According to the type of data, the research method is mixed (qualitative-quantitative) of exploratory nature. In the statistical population, 12 people were selected from among the experts until the theoretical saturation was reached. The experts included professors of the faculty of business management and senior managers of Alborz insurance company, who were selected by non-probability, targeted and chain sampling. Quantitative part of 400 managers were insurance industry experts, using Cochran's formula, 196 people were selected by stratified random method. To collect data, semi-structured interviews and researcher-made questionnaires were used. The analysis method has been carried out in several consecutive steps. In the first stage, to identify the components of the model, the qualitative method and semi-structured interviews using the grounded theory have been used. In the next section, using interpretative structural modeling, the identified indicators were leveled. Finally, in order to fit the designed model in the qualitative part, a quantitative method with structural equation modeling approach was used with PLS4 software. The findings showed that 6 components were identified and there is a significant relationship between all components and sustainable marketing and the designed model has an acceptable fit. It can be concluded that AI can be incorporated as an essential component of a sustainable marketing strategy, enabling marketing professionals and businesses to make positive changes while increasing their brand reputation and profitability.
Acheampong, S., Pimonenko, T., & Lyulyov, O. (2023). Sustainable Marketing Performance of Banks in the Digital Economy: The Role of Customer Relationship Management. Virtual Economics, 6(1), 19-37.
Adeoye, O. B., Okoye, C. C., Ofodile, O. C., Odeyemi, O., Addy, W. A., & Ajayi-Nifise, A. O. (2024). Integrating artificial intelligence in personalized insurance products: a pathway to enhanced customer engagement. International Journal of Management & Entrepreneurship Research, 6(3), 502-511.
Ahmadi, S. (2024). A Comprehensive Study on Integration of Big Data and AI in Financial Industry and its Effect on Present and Future Opportunities. International Journal of Current Science Research and Review, 7(01), 66-74.
Al Adwan, A., & Altrjman, G. (2024). The role of social media marketing and marketing management promoting and developing brand sustainability strategy. Available at SSRN 4436265.
Alshadadi, M. A., & Deshmukh, P. (2024). Sustainability and Practices of Insurance Companies: Literature Review. Studies in Economics and Business Relations, 5(1), 66-75.
Amui, L. B. L., Jabbour, C. J. C., de Sousa Jabbour, A. B. L., & Kannan, D. (2017). Sustainability as a dynamic organizational capability: a systematic review and a future agenda toward a sustainable transition. Journal of Cleaner Production, 142, 308-322.
Bebbington, J., & Unerman, J. (2020). Advancing research into accounting and the UN sustainable development goals. Accounting, Auditing & Accountability Journal, 33(7), 1657-1670.
Bolton, R. N. (2022). The convergence of sustainability and marketing: Transforming marketing to respond to a new world. Australasian Marketing Journal, 30(2), 107-112.
Casidy, R., & Yan, L. (2022). The effects of supplier B2B sustainability positioning on buyer performance: The role of trust. Industrial Marketing Management, 102, 311-323.
Dhatterwal, J. S., Kaswan, K. S., Preety, D., & Balusamy, B. (2022). Emerging technologies in the insurance market. Big Data Analytics in the Insurance Market, 275-286.
Do, J., Uusitalo, O., Skippari, M., & Salimi, M. (2023). Artificial intelligence-assisted sustainable marketing: Contribution and agenda for research. Proceedings of the European Marketing Academy,
Effatpanah, A., Bodaghi Khajeh Noubar, H., Alavimatin, Y., & Farahmand, F.-h. (2023). A model of sustainable consumer behavior in the insurance industry (Case study: Insurance Company Asia). International Journal of Nonlinear Analysis and Applications, 14(2), 341-358.
Ghezelbash, A. (2021). Investigating the effect of sustainable marketing activities, brand image on customer loyalty with the mediating role of customer satisfaction and trust (Central Insurance Organization). Journal of Accounting and Management Vision, 4(50), 42-49.
Gong, Y., Xiao, J., Tang, X., & Li, J. (2023). How sustainable marketing influences the customer engagement and sustainable purchase intention? The moderating role of corporate social responsibility. Frontiers in Psychology, 14, 1128686.
Jia, T., Iqbal, S., Ayub, A., Fatima, T., & Rasool, Z. (2023). Promoting responsible sustainable consumer behavior through sustainability marketing: the boundary effects of corporate social responsibility and brand image. Sustainability, 15(7), 6092.
Jin, K., Zhong, Z. Z., & Zhao, E. Y. (2024). Sustainable digital marketing under big data: an AI random forest model approach. IEEE Transactions on Engineering Management.
Kamboj, S., & Rahman, Z. (2017). Market orientation, marketing capabilities and sustainable innovation: The mediating role of sustainable consumption and competitive advantage. Management Research Review, 40(6), 698-724.
Kushwah, S. V., & Mathur, G. (2022). Practices in sustainable finance: A neoliberal marketing model in insurance sector. Academy of Marketing Studies Journal, 26(1), 1-11.
Monfared, A. R. K., Mansouri, A., & Hosseini, E. (2023). Do environmental factors affect the market atmosphere, amount of purchases and customer attitude? International Journal of Business and Emerging Markets, 15(2), 194-217.
Nath, P., & Siepong, A. (2022). Green marketing capability: A configuration approach towards sustainable development. Journal of Cleaner Production, 354, 131727.
Nicholson, J. E. (2019). Challenges for the Insurance Industry in the Future. Journal of Insurance Regulation, 38(6).
Pranugrahaning, A., Donovan, J. D., Topple, C., & Masli, E. K. (2023). Exploring Corporate Sustainability in the Insurance Sector: A Case Study of a Multinational Enterprise Engaging with UN SDGs in Malaysia. Sustainability, 15(11), 8609.
Rajabi Farjad, H., & Toranian, N. (2024). Identifying Factors Affecting the Performance of Sustainable Human Resources in the Insurance Industry. Dynamic Management and Business Analysis, 2(4), 33-52.
Rashid, A., Baloch, N., Rasheed, R., & Ngah, A. H. (2024). Big data analytics-artificial intelligence and sustainable performance through green supply chain practices in manufacturing firms of a developing country. Journal of Science and Technology Policy Management.
Ronaghi, M. H. (2023). The influence of artificial intelligence adoption on circular economy practices in manufacturing industries. Environment, Development and Sustainability, 25(12), 14355-14380.
Sharma, S., Gahlawat, V. K., Rahul, K., Mor, R. S., & Malik, M. (2021). Sustainable innovations in the food industry through artificial intelligence and big data analytics. Logistics, 5(4), 66.
Sheth, J. N., & Parvatiyar, A. (2021). Sustainable marketing: Market-driving, not market-driven. Journal of Macromarketing, 41(1), 150-165.
Shaw, S., Rowland, Z., & Machova, V. (2021). Internet of Things smart devices, sustainable industrial big data, and artificial intelligence-based decision-making algorithms in cyber-physical system-based manufacturing. Economics, Management and Financial Markets, 16(2), 106-116.
Shibli, R., Saifan, S., Ab Yajid, M. S., & Khatibi, A. (2021). Mediating role of entrepreneurial marketing between green marketing and green management in predicting sustainable performance in Malaysia's organic agriculture sector. AgBioForum, 23(2), 37-49.
Wilkinson, D., Christie, A., Tarr, A. A., & Tarr, J.-A. (2024). Big Data, Artificial Intelligence and Insurance. In The Global Insurance Market and Change (pp. 22-46). Informa Law from Routledge.
Yadav, A., & Sondhi, H. (2023). Systematic Literature Review on Sustainable Marketing and Artificial Intelligence. 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom),
Zhang, H., Wang, Y., & Song, M. (2019). Does competitive intensity moderate the relationships between sustainable capabilities and sustainable organizational performance in new ventures? Sustainability, 12(1), 253.
Received: 10/07/2024 Accepted: 12/09/2024 |
Journal of System Management (JSM)Online ISSN: 2538-1571, Print ISSN: 2322-2301
10(4), 2024, pp. 135-149
DOI: 10.30495/SJSM.2024.1126217
RESEARCH ARTICLE Open Access
Providing a Sustainable Marketing Model in the Insurance Industry with a Focus on Artificial Intelligence
Elnaz Allafjafari 1 , Alireza Rousta 2* , Farzad Asayesh 3 , Mahmood Ahmadi Sharif 4
Abstract
The current research was conducted with the aim of providing a sustainable marketing model in the insurance industry with a focus on artificial intelligence. According to the type of data, the research method is mixed (qualitative-quantitative) of exploratory nature. In the statistical population, 12 people were selected from among the experts until the theoretical saturation was reached. The experts included professors of the faculty of business management and senior managers of Alborz insurance company, who were selected by non-probability, targeted and chain sampling. Quantitative part of 400 managers were insurance industry experts, using Cochran's formula, 196 people were selected by stratified random method. To collect data, semi-structured interviews and researcher-made questionnaires were used. The analysis method has been carried out in several consecutive steps. In the first stage, to identify the components of the model, the qualitative method and semi-structured interviews using the grounded theory have been used. In the next section, using interpretative structural modeling, the identified indicators were leveled. Finally, in order to fit the designed model in the qualitative part, a quantitative method with structural equation modeling approach was used with PLS4 software. The findings showed that 6 components were identified and there is a significant relationship between all components and sustainable marketing and the designed model has an acceptable fit. It can be concluded that AI can be incorporated as an essential component of a sustainable marketing strategy, enabling marketing professionals and businesses to make positive changes while increasing their brand reputation and profitability.
Keywords: Sustainable Marketing, Artificial Intelligence, Insurance Industry, Grounded Theory
[1] 1.Department of Business Management, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
2*. Department of Business Management, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran (Corresponding Author :alirezarousta@yahoo.com )
3, 4. Department of Business Management, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran
Introduction
In today's societies, the term sustainability has become very popular, the daily activities and marketing of many organizations deal with sustainability and environmental goals and initiatives (Saulick et al., 2023). Sustainable marketing in the insurance industry refers to the practice of promoting insurance products and services in a way that not only promotes business growth, but also contributes to environmental and social sustainability. This approach includes the incorporation of sustainable practices in all aspects of marketing, from product development and distribution to communication and customer interaction (Effatpanah et al., 2023). Insurance companies are increasingly recognizing the importance of sustainability in their marketing efforts as consumers become more aware of the environmental and social impacts of their purchasing decisions. By aligning their marketing strategies with sustainable values, insurance companies can attract and retain customers who seek environmentally and socially responsible products and services. (Ghezelbash, 2021) Because, with the evolution of the marketing perspective for companies that want to differentiate themselves in the market, it is necessary to engage in corporate social responsibility strategies as a way to respond to this demand from consumers. Social responsibility in sustainable marketing involves taking actions that benefit society, such as supporting community initiatives, promoting diversity and inclusion, and advocating social justice. Insurance companies can demonstrate their commitment to social responsibility through their marketing campaigns, highlighting their efforts to give back to society and support causes that align with their values. By showing a strong sense of social responsibility, insurance companies can create a positive image of their brand and strengthen customer loyalty (Kushwah & Mathur, 2022).
Sustainable performance, on the other hand, focuses on the environmental impact of insurance products and services. Insurance companies can promote sustainable performance by offering products that support environmental protection, such as green insurance policies that encourage policyholders to adopt environmentally friendly practices. By highlighting their commitment to sustainable performance in their marketing efforts, insurance companies can attract environmentally conscious consumers and position themselves as leaders in the transition to a more sustainable economy (Rajabi Farjad & Toranian, 2024).
Also, the insurance industry is undergoing a significant transformation under the influence of technological advances and changing consumer expectations. In this era of digitization and sustainability, insurance companies are increasingly turning to artificial intelligence (AI) to transform their marketing strategies and drive sustainable performance. AI capabilities give insurers the opportunity to analyze vast amounts of data, personalize marketing campaigns and optimize operations, ultimately enabling them to effectively promote sustainable products and practices(Adeoye et al., 2024). One of the ways that AI can support sustainable marketing in the insurance industry is through data analysis. AI algorithms can analyze customer data to identify patterns and preferences, allowing insurance companies to tailor their marketing messages to specific customer segments. This personalized approach can help promote sustainable insurance products to customers who are likely to be interested in them, increase the effectiveness of marketing campaigns and reduce waste (Ahmadi, 2024).
Examining the determinants of sustainable marketing in the insurance industry is critical because it allows insurance companies to gain a deeper understanding of consumer preferences, market trends, and industry best practices, which are effective for developing sustainable marketing strategies (Alshadadi & Deshmukh, 2024). By investing in this area, insurance companies can make informed decisions, identify growth opportunities, and stay ahead of competitors in a rapidly developing market (Nicholson, 2019). It also helps insurance companies learn about industry trends and emerging technologies that can support sustainable marketing efforts. By staying up-to-date on the latest industry developments, companies can identify new opportunities for innovation, participation and market positioning (Dhatterwal et al., 2022). Research can also help companies benchmark their performance against competitors and track the effectiveness of their sustainable marketing initiatives over time.
One of the potential research gaps in the field of sustainable marketing in the insurance industry can be the lack of studies focusing on the specific impact of artificial intelligence capabilities on sustainable marketing strategies in insurance companies. While there is existing research on the use of artificial intelligence in marketing practices and sustainability in various industries (Rashid et al., 2024; Ronaghi, 2023; Sharma et al., 2021), but research aimed at understanding how intelligence technologies Artificial can be used specifically to promote sustainable insurance products and practices in Iran, not found. By addressing this research gap, researchers and industry practitioners can gain valuable insights into the role of AI in guiding sustainability efforts in the insurance industry and ultimately help develop more effective and impactful sustainable marketing strategies that align with consumer preferences. And industry best practices are aligned to help.
Theoretical Foundations and Research Background
In the last half century, sustainability has become an essential macro marketing perspective (Sheth & Parvatiyar, 2021). Based on this, the marketing focus should change from paying attention to the demands and requirements of customers to actively promoting the sale of environmentally friendly goods and services. This shows that marketing managers should be involved in developing a sustainability plan that fits the company's macro goals (Al Adwan & Altrjman, 2024). Some companies are responsible for environmental damage due to the consumption of large amounts of natural resources. Hence, there is a need to demonstrate how companies, despite investing in environmental sustainability strategies, achieve positive brand image and higher market performance through environmental sustainability (Cassidy & Yan, 2022). Market performance can be influenced by a company's commitment to environmental sustainability. This means that green marketing is a factor in the decision making process of marketing managers. There is a lot of research on how to advance the field of marketing and contribute to the United Nations Sustainable Development Goals (Bebbington & Unerman, 2020). (Bolton, 2022) in his research, he examines the current state of sustainability, the history of marketing, and the information gap between sustainable development goals and the expertise of marketers in achieving those goals. in creating a sustainable strategy. Taking a more active role in promoting sustainability is one of the strategies proposed in the literature as a means by which marketing managers may change the culture of their organizations to make them more sustainable (Sheth & Parvatiyar, 2021). On the other hand, the marketing industry is changing drastically with the advancement of technology. When working to create a more sustainable business culture, marketing managers must consider how new technologies will affect their field of work (Al Adwan & Altrjman, 2024).
Among the ongoing technological advancements, the transformative potential of big data and artificial intelligence is redefining conventional paradigms and impacting various industries. The use of big data and artificial intelligence technology has increased the efficiency of transactions, significantly shortening the gap between demand and supply, creating an increased mutual understanding between companies and consumers, thus enabling customers to (Shaw et al., 2021) Manufacturers, retailers, and Internet developers alike are benefiting from this paradigm shift significantly. As online commerce expands and the age of artificial intelligence emerges, accurate marketing decisions are increasingly focused on insights from big data analytics. Companies will restructure their operations based on data-driven optimization (Jin et al., 2024).
Artificial intelligence (AI) in the insurance sector has ushered in a new era of insurance products that increase customer engagement and satisfaction. AI-based algorithms and machine learning techniques enable insurers to analyze vast amounts of data with unprecedented speed and accuracy, facilitating the customization of insurance products to meet customer needs. By leveraging data from various sources such as IoT devices, social media, and historical claims data, insurers can gain deeper insights into customer behavior, preferences, and risk profiles (Adeoye et al., 2024). By simplifying communication channels and providing seamless interactions, AI technologies strengthen the bond between insurers and customers, fostering long-term relationships based on trust and transparency. The integration of artificial intelligence into personal insurance products represents a transformative path towards increased customer engagement. Using the power of AI-based analytics and automation, insurers can provide customized solutions that resonate with individual customers and drive higher levels of satisfaction, loyalty, and ultimately business growth (Wilkinson et al., 2024). Also, there is clear evidence of sustainability implementation by companies. In particular, insurance companies with global assets of more than $30 trillion are expected to strengthen the sustainability agenda through their key roles as risk managers, underwriters and investors. In this context, insurance companies are gradually investigating how to best coordinate their actions with international obligations to be more environmentally conscious and have a more positive impact on society (Pranugrahaning et al., 2023).
Research Methodology
The aim of this research is to provide a sustainable marketing model in the insurance industry with a focus on artificial intelligence. This research is a basic research from the point of view of the goal and from the point of view of the method of data collection, it is a non-experimental (descriptive) research of cross-sectional survey type. From the point of view of the nature of the data, it is a mixed research (qualitative-quantitative).
The statistical population in the qualitative section consists of scientific experts who are familiar with the concepts of sustainable marketing and artificial intelligence and had research experience in this field, and executive experts who have at least 5 years of management experience in Al-Bima. Also, non-probability and purposeful methods were used for sampling the qualitative part, theoretical saturation was achieved with 12 interviews. The statistical population of the research in the quantitative part is 400 managers and experts of Alborz insurance. Using Cochran's formula, the sample size is 196 people. Stratified random method was used for sampling.
The research data collection tool was semi-structured interview in the qualitative part, and in the quantitative part, test-retest reliability was used for qualitative reliability. After distributing the questionnaire in the selected sample, the validity of the questionnaire was checked with three methods of construct validity (external model), convergent validity (AVE) and divergent validity. AVE value for all variables should be greater than 0.5. In order to calculate the reliability, composite reliability (CR) and Cronbach's alpha coefficient of each factor were calculated. The combined reliability and Cronbach's alpha of all dimensions should be greater than 0.7 (Hensler et al., 2015). The results related to each of these indicators are presented in the external fit of the model. Grounded theory method was used to analyze the data in the qualitative part. For the analysis of the quantitative part, it was done to validate the model with partial least squares method and Smart PLS 4 software.
Research Findings
In the qualitative part, the views of 12 managers with experience in the central offices of the furniture industry in Tehran were used. In terms of gender, 8 people (67%) are men and 4 people (33%) are women. In terms of education, 6 (50%) of the experts have a master's degree and 6 (50%) have a doctorate. Finally, 9 people (75%) have less than 20 years of work experience and 3 people (25%) have more than 20 years of work experience.
In the quantitative section, the views of 350 furniture industry experts were used. In terms of gender, 120 people (61.2%) are men and 76 people (38.8%) are women. In terms of education, 69 people (35.2%) have a bachelor's degree, 105 people (53.6%) have a master's degree, and 22 people (11.2%) have a doctorate. Finally, in terms of work experience, 28 people (14.3%) have less than 10 years, 154 people (78.6%) have between 10 and 20 years, and 14 people (7.1%) have more than 20 years of work experience.
The research method was qualitative data-based theory that inductively uses a series of systematic procedures to create a theory about the phenomenon under study. The reason for using this strategy was to achieve a deep description of the attitudes and perceptions of experts about sustainable marketing. Based on the systematic design of the data base theory, the participants' perception about the process, content, strategies, context, and consequences of the research findings and the relationships between them were sought through a semi-structured interview. For data analysis, primary coding and central coding methods were used (category statistics and identifying the relationship between categories and determining the central phenomenon, describing cause conditions, Interferering condition, Strategies, Underlying conditions, Consequences) (Table 1).
Table 1.
Categories, components, indicators, selected code
selected code | indicators | components | Category |
|---|---|---|---|
artificial intelligence competency | Artificial intelligence capabilities | cause condition | |
Use of new technologies | |||
Coordination with the speed of competitors in the use of technology | |||
Increasing the reliability of using artificial intelligence | artificial intelligence service quality | ||
Ability of customer service team | |||
Collect information about customers and competitors | marketing information management | Marketing capabilities | |
Using information about customers and competitors | |||
Analyzing information about customers and competitors | |||
Marketing planning skills and processes | marketing planning | ||
Ability to effectively segment and target market | |||
Developing sustainable creative marketing strategies | |||
Development of the national economy | economic responsibility | Social responsibility | |
Attention to economic marketing activities | |||
Sharing of economic benefits | |||
Increase economic support | |||
Responsible and voluntary participation | social responsibility | ||
Support sports and cultural events | |||
Support social goals | |||
Development and use of environmentally friendly products | environmental responsibility | ||
Participation in environmental campaigns | |||
Using energy and resources efficiently | |||
Take advantage of new opportunities | entrepreneurial competence | Organizational capabilities | Strategies |
Encourage innovative ideas and behaviors | |||
Encourage new approaches | |||
Support the essential functions of the organization | strategic competence | ||
Create a clear vision of business value | |||
Integration of strategic business planning | |||
team management | Management capabilities
| ||
Managing tensions | |||
Motivate team members | |||
apportion duties | |||
Budget management ability | financial management | ||
Improve financial performance | |||
Correct allocation of resources | |||
Ability to identify risks | risk management | ||
Effective prediction of risks | |||
Reduce future damage | |||
Ability to recognize the need for changes in the organization | change management | ||
Developing appropriate strategies to implement change | |||
Reducing the production of toxic/harmful/dangerous/flammable substances | environmental performance | Sustainable performance
| Consequences |
Improved compliance with environmental standards | |||
Improve work safety | |||
Improve market share | economic performance | ||
Improving the company's position in the market | |||
Increased profitability growth | |||
Improving the quality of life of the surrounding community | social performance | ||
Strengthening the positive attitude of customers towards products and services | |||
Influencing customers' behavioral intentions |
Figure 1 is the conceptual model of the research. In this section, the main goal of the sustainable marketing model in the insurance industry is presented with a focus on artificial intelligence
Figure 1. Conceptual model of research
Partial least squares (PLS) method with Smart PLS4 software was used to validate the model. The results of the sustainable marketing model in the insurance industry with a focus on artificial intelligence are shown in Figure 2.
Figure 2. Model in path coefficient mode
In order to ensure the accuracy and correctness of the research results, the technical characteristics of the questionnaire were evaluated in the quantitative part, in two parts of validity and reliability using different criteria. The validity of the questionnaire has been evaluated and confirmed through content and construct validity. To measure the content validity of the tool, the opinions of professors and experts have been used, and to measure the construct validity, the model of structural equations of convergent and divergent validity has been used. In order to determine the convergent validity, the extracted average standard deviation index (AVE) was used, and for the divergent measurement, the extracted root mean variance index was used.
The average standard deviation extracted for the variables in this change is higher than 0.5 and indicates its high validity. Also, the reliability of the questionnaire tool was measured using Cronbach's alpha coefficient and composite reliability. Also, considering that the Cronbach's alpha of all variables was higher than 0.70 and the overall alpha of the questionnaire was calculated as 0.828, so it can be concluded that the research tool used has a good level of reliability. Also, coefficient of determination index (R2) and Stone-Geisser index (Q2) are used to measure the predictive power of the model. These values are calculated for endogenous variables. The higher these values are, the higher the prediction power of the model. (Table2).
Table 2.
Composite reliability and convergent validity of the model
R2 | Q2 | Average variance extracted (AVE) | Composite reliability | Cronbach's alpha |
|
|---|---|---|---|---|---|
|
| 0.474 | 0.782 | 0.830 | Artificial intelligence capabilities |
|
| 0.517 | 0.810 | 0.888 | Management capabilities |
|
| 0.557 | 0.790 | 0.802 | Marketing capabilities |
|
| 0.536 | 0.776 | 0.769 | Organizational capabilities |
|
| 0.505 | 0.803 | 0.874 | Social responsibility |
|
| 0.492 | 0.795 | 0.856 | sustanable performannce |
0.578 | 0.293 | 0.531 | 0.772 | 0.756 | Sustainable marketing |
Likewise, Table 3 shows that the average root mean square root value of the extracted variance is more than the acceptable minimum of 0.5; Therefore, research variables have divergent validity. Also, due to the fact that the root mean value of the extracted variance is greater than the correlation of the variable in question with other variables, divergent validity is acceptable if the numbers in the main diameter are greater than their underlying values (Manfard et al., 2023). It can be said that the variables have validity and their divergent validity is also confirmed.
Table 3.
Fornell Locker
sustanable performannce | Sustainable marketing | Social responsibility | Organizational capabilities | Marketing capabilities | Management capabilities | Artificial intelligence capabilities |
|
|---|---|---|---|---|---|---|---|
|
|
|
|
|
| 0.698 | Artificial intelligence capabilities |
|
|
|
|
| 0.719 | 0.668 | Management capabilities |
|
|
|
| 0.746 | 0.623 | 0.635 | Marketing capabilities |
|
|
| 0.732 | 0.608 | 0.597 | 0.619 | Organizational capabilities |
|
| 0.711 | 0.578 | 0.619 | 0.635 | 0.668 | Social responsibility |
| 0.728 | 0.614 | 0.630 | 0.612 | 0.653 | 0.640 | Sustainable marketing |
0.701 | 0.643 | 0.625 | 0.655 | 0.615 | 0.664 | 0.692 | sustanable performannce |
Finally, in order to check the assumed relationships between the variables, the t-statistic has been used, which can be seen in Figure 3.
Figure 3. Model in t-statistic mode
Structural fit using t coefficients is such that these coefficients must be greater than 1.96 in order to confirm their significance at the 0.95 confidence level. Of course, it should be noted that the t numbers only show the validity of the relationships and the intensity of the relationship between the structures cannot be measured with them, and the path coefficients also show the positive or negative effect of one variable on the other variable. is another (Table 4).
Table 4.
The results of the hypothesis test
نتایج | P values | T statistics | Original sample |
|
|---|---|---|---|---|
تایید | 0.040 | 2.056 | 0.126 | Artificial intelligence capabilities -> Sustainable marketing |
تایید | 0.000 | 4.082 | 0.206 | Management capabilities -> Sustainable marketing |
تایید | 0.013 | 2.484 | 0.125 | Marketing capabilities -> Sustainable marketing |
تایید | 0.000 | 3.916 | 0.189 | Organizational capabilities -> Sustainable marketing |
تایید | 0.014 | 2.450 | 0.125 | Social responsibility -> Sustainable marketing |
تایید | 0.012 | 2.499 | 0.140 | sustanable performannce -> Sustainable marketing |
Discussion
Considering that the purpose of this research is to provide a sustainable marketing model in the insurance industry with a focus on artificial intelligence. Qualitative research has been conducted through interviews with 13 experts in this field. The results have led to the identification of 6 components, 16 indicators and 48 selected codes.
In this research, the components of artificial intelligence capabilities and marketing capabilities have been identified in the causal conditions, which include artificial intelligence competence and artificial intelligence service quality. Also, marketing capabilities include marketing information management, marketing planning. It was also shown in the quantitative section that artificial intelligence capabilities and marketing capabilities have a positive and significant impact on sustainable marketing. This was also achieved in the results of the study (Kamboj & Rahman, 2017; Nath & Siepong, 2022) and it is consistent with the results of the present study. Because in today's dynamic and competitive business environment, organizations are continuously looking for ways to improve their marketing capabilities so that they can effectively reach their target customers. Marketing capability refers to the organization's ability to provide effective and efficient marketing activities and achieve desired results. It includes the knowledge, skills, processes and resources necessary to create, communicate and deliver value to customers. On the other hand, sustainable marketing is a concept that focuses on creating long-term value for customers and society, while also ensuring the preservation of natural resources and the well-being of future generations. By integrating sustainability principles into their marketing strategies, organizations can not only enhance their brand reputation and competitiveness, but also contribute to the greater good of society. Additionally, sustainable marketing can help build trust with customers, who are increasingly concerned about the ethical and environmental practices of the companies they choose to support. In order to successfully implement sustainable marketing practices, organizations must develop a strong marketing capability that enables them to effectively align their marketing planning with sustainability goals. This includes having a deep understanding of customer needs and expectations, the ability to develop and communicate values that resonate with consumers, along with marketing information management, the capacity to adapt to changing market conditions and stakeholder expectations. Ultimately, organizations that invest in building marketing capabilities and integrating sustainability principles into their marketing strategies are better positioned to create long-term value for all stakeholders while also delivering positive social and environmental impacts.
The findings are in line with the research results of (Do et al., 2023; Yadav & Sondhi, 2023) and state that the integration of artificial intelligence in marketing goes beyond technology. It is a commitment to environmentally friendly strategies for a healthier planet. In other words, integrating artificial intelligence into sustainable marketing is more than a technological advance. It is this commitment to a more sustainable future that provides synergy as a unique opportunity for businesses to lead the way in environmental responsibility. As AI continues to evolve, its role in driving sustainable practices will become more prominent, providing a path for companies to align their growth with environmental and social values.
In the intervening conditions, the component of social responsibility has been identified, which includes economic responsibility, social responsibility, and environmental responsibility. It was also shown in the quantitative section that social responsibility has a positive and significant effect on sustainable marketing. The results of the studies (Gong et al., 2023; Jia et al., 2023) are also consistent with the results of the present study. Because social responsibility is the commitment of businesses to act ethically and help improve society and the environment. This is not just a moral obligation, but a strategic imperative in today's competitive market. Social responsibility is a means to achieve sustainability. Adopting key principles of social responsibility, such as accountability and transparency, can help ensure the long-term viability and success of any organization or system. Social responsibility plays an important role in shaping sustainable marketing strategies and initiatives. This is because consumers are becoming increasingly aware of the ethical and environmental values of the brands they support. Brands that demonstrate a strong commitment to social responsibility are not only better perceived by consumers, but also more likely to attract and retain loyal customers. By integrating social responsibility into their marketing efforts, companies can not only enhance their reputation and credibility, but also contribute positively to society and the environment. Sustainable marketing, which focuses on long-term environmental and social impact rather than short-term profit, is well aligned with the principles of social responsibility. Through sustainable marketing practices such as using environmentally friendly materials, supporting fair labor practices, and contributing to communities, companies can build trust and loyalty with consumers while making a positive impact on the world. As a result, social responsibility and sustainable marketing are tightly intertwined, with companies that embrace both principles reaping the rewards of increased brand awareness, customer loyalty, and a more sustainable future for all.
In this research, in contextual conditions, the component of management capability has been identified, which includes team management, financial management, risk management, and change management. It was also shown in the quantitative section that managerial ability has a positive and significant effect on sustainable marketing. . This importance has been confirmed in the results of the study (Kamboj & Rahman, 2017; Nath & Siepong, 2022). Sustainable management capabilities refer to an organization's ability to effectively manage its resources, operations, and stakeholders while incorporating sustainability principles into its decision-making processes. This includes setting clear sustainability goals, monitoring and measuring performance against these goals, and continuously improving sustainability practices in all aspects of the business. Companies with strong sustainability management capabilities are better positioned to mitigate risks, seize opportunities, and create long-term value. Overall, organizations that prioritize sustainable marketing and management capabilities will not only survive, but thrive in today's dynamic business landscape. It encompasses a set of skills and competencies that enable leaders to effectively lead their teams toward achieving organizational goals. Team management involves the ability to motivate, inspire and coordinate people to achieve a common goal. Financial management requires a deep understanding of financial principles and the ability to effectively allocate resources to maximize profits. Risk management includes identifying potential risks, assessing their impact and implementing strategies to reduce it. Change management is critical in today's rapidly evolving business environment, requiring leaders to move and adapt to change to stay competitive. Overall, a strong management capability is essential to ensure the sustainability and long-term success of an organization.
In this research, for strategies, the component of organizational capability has been identified, which includes entrepreneurial competence, strategy competence. It was also shown in the quantitative section that organizational capability has a positive and significant effect on sustainable marketing. which is in line with the research results of (Amui et al., 2017; Zhang et al., 2019). Because organizational capabilities can be defined as a combination of skills, resources and processes that enable the organization to achieve its strategic goals and objectives effectively. These capabilities are critical in creating innovation, competition and growth in a company. When combined with strategic thinking and entrepreneurship, organizational capabilities play an important role in developing sustainable competitive advantage. Strategic thinking involves aligning an organization's resources and capabilities with its long-term goals and objectives, while entrepreneurship involves taking calculated risks and seizing opportunities to create value. By integrating these elements, organizations can create a dynamic and adaptive environment that is able to respond to changes in the market landscape and drive sustainable growth. On the other hand, sustainable marketing focuses on promoting products and services in a way that minimizes negative impact on the environment and society while maximizing long-term value for stakeholders. By leveraging organizational capabilities with strategy and entrepreneurship, companies can develop innovative marketing strategies that not only increase profitability, but also contribute to a more sustainable future.
And finally, for the consequences, the component of sustainable performance has been identified, which includes environmental performance, economic performance, and social performance. It was also shown in the quantitative section that sustainable performance has a positive and significant impact on sustainable marketing. . This importance has been confirmed in the results of the study (Acheampong et al., 2023; Shibli et al., 2021). Sustainable sourcing and sustainable performance have become increasingly important considerations for businesses in today's global marketplace. Companies recognize the need to shift to more environmentally and socially responsible practices to meet the demands of consumers who are increasingly aware of the impact their purchasing decisions have on the planet. Sustainable marketing involves developing and promoting products and services that have the least impact on the environment and society, while sustainable performance refers to a company's ability to maintain profitability and growth over the long term while acting in a socially responsible manner. And it works ecologically. By aligning their marketing strategies with sustainable practices, businesses can not only attract a growing segment of conscientious consumers, but also create a positive brand image that can lead to long-term success. In order to achieve sustainable performance, companies must not only focus on their financial income, but also consider their impact on the environment, employees and communities in which they operate. By implementing sustainable marketing practices and aligning them with sustainable performance goals, companies can make a positive impact on society while driving business growth and profitability in a responsible manner.
References
Acheampong, S., Pimonenko, T., & Lyulyov, O. (2023). Sustainable Marketing Performance of Banks in the Digital Economy: The Role of Customer Relationship Management. Virtual Economics, 6(1), 19-37.
Adeoye, O. B., Okoye, C. C., Ofodile, O. C., Odeyemi, O., Addy, W. A., & Ajayi-Nifise, A. O. (2024). Integrating artificial intelligence in personalized insurance products: a pathway to enhanced customer engagement. International Journal of Management & Entrepreneurship Research, 6(3), 502-511.
Ahmadi, S. (2024). A Comprehensive Study on Integration of Big Data and AI in Financial Industry and its Effect on Present and Future Opportunities. International Journal of Current Science Research and Review, 7(01), 66-74.
Al Adwan, A., & Altrjman, G. (2024). The role of social media marketing and marketing management promoting and developing brand sustainability strategy. Available at SSRN 4436265.
Alshadadi, M. A., & Deshmukh, P. (2024). Sustainability and Practices of Insurance Companies: Literature Review. Studies in Economics and Business Relations, 5(1), 66-75.
Amui, L. B. L., Jabbour, C. J. C., de Sousa Jabbour, A. B. L., & Kannan, D. (2017). Sustainability as a dynamic organizational capability: a systematic review and a future agenda toward a sustainable transition. Journal of Cleaner Production, 142, 308-322.
Bebbington, J., & Unerman, J. (2020). Advancing research into accounting and the UN sustainable development goals. Accounting, Auditing & Accountability Journal, 33(7), 1657-1670.
Bolton, R. N. (2022). The convergence of sustainability and marketing: Transforming marketing to respond to a new world. Australasian Marketing Journal, 30(2), 107-112.
Casidy, R., & Yan, L. (2022). The effects of supplier B2B sustainability positioning on buyer performance: The role of trust. Industrial Marketing Management, 102, 311-323.
Dhatterwal, J. S., Kaswan, K. S., Preety, D., & Balusamy, B. (2022). Emerging technologies in the insurance market. Big Data Analytics in the Insurance Market, 275-286.
Do, J., Uusitalo, O., Skippari, M., & Salimi, M. (2023). Artificial intelligence-assisted sustainable marketing: Contribution and agenda for research. Proceedings of the European Marketing Academy,
Effatpanah, A., Bodaghi Khajeh Noubar, H., Alavimatin, Y., & Farahmand, F.-h. (2023). A model of sustainable consumer behavior in the insurance industry (Case study: Insurance Company Asia). International Journal of Nonlinear Analysis and Applications, 14(2), 341-358.
Ghezelbash, A. (2021). Investigating the effect of sustainable marketing activities, brand image on customer loyalty with the mediating role of customer satisfaction and trust (Central Insurance Organization). Journal of Accounting and Management Vision, 4(50), 42-49.
Gong, Y., Xiao, J., Tang, X., & Li, J. (2023). How sustainable marketing influences the customer engagement and sustainable purchase intention? The moderating role of corporate social responsibility. Frontiers in Psychology, 14, 1128686.
Jia, T., Iqbal, S., Ayub, A., Fatima, T., & Rasool, Z. (2023). Promoting responsible sustainable consumer behavior through sustainability marketing: the boundary effects of corporate social responsibility and brand image. Sustainability, 15(7), 6092.
Jin, K., Zhong, Z. Z., & Zhao, E. Y. (2024). Sustainable digital marketing under big data: an AI random forest model approach. IEEE Transactions on Engineering Management.
Kamboj, S., & Rahman, Z. (2017). Market orientation, marketing capabilities and sustainable innovation: The mediating role of sustainable consumption and competitive advantage. Management Research Review, 40(6), 698-724.
Kushwah, S. V., & Mathur, G. (2022). Practices in sustainable finance: A neoliberal marketing model in insurance sector. Academy of Marketing Studies Journal, 26(1), 1-11.
Monfared, A. R. K., Mansouri, A., & Hosseini, E. (2023). Do environmental factors affect the market atmosphere, amount of purchases and customer attitude? International Journal of Business and Emerging Markets, 15(2), 194-217.
Nath, P., & Siepong, A. (2022). Green marketing capability: A configuration approach towards sustainable development. Journal of Cleaner Production, 354, 131727.
Nicholson, J. E. (2019). Challenges for the Insurance Industry in the Future. Journal of Insurance Regulation, 38(6).
Pranugrahaning, A., Donovan, J. D., Topple, C., & Masli, E. K. (2023). Exploring Corporate Sustainability in the Insurance Sector: A Case Study of a Multinational Enterprise Engaging with UN SDGs in Malaysia. Sustainability, 15(11), 8609.
Rajabi Farjad, H., & Toranian, N. (2024). Identifying Factors Affecting the Performance of Sustainable Human Resources in the Insurance Industry. Dynamic Management and Business Analysis, 2(4), 33-52.
Rashid, A., Baloch, N., Rasheed, R., & Ngah, A. H. (2024). Big data analytics-artificial intelligence and sustainable performance through green supply chain practices in manufacturing firms of a developing country. Journal of Science and Technology Policy Management.
Ronaghi, M. H. (2023). The influence of artificial intelligence adoption on circular economy practices in manufacturing industries. Environment, Development and Sustainability, 25(12), 14355-14380.
Sharma, S., Gahlawat, V. K., Rahul, K., Mor, R. S., & Malik, M. (2021). Sustainable innovations in the food industry through artificial intelligence and big data analytics. Logistics, 5(4), 66.
Sheth, J. N., & Parvatiyar, A. (2021). Sustainable marketing: Market-driving, not market-driven. Journal of Macromarketing, 41(1), 150-165.
Shaw, S., Rowland, Z., & Machova, V. (2021). Internet of Things smart devices, sustainable industrial big data, and artificial intelligence-based decision-making algorithms in cyber-physical system-based manufacturing. Economics, Management and Financial Markets, 16(2), 106-116.
Shibli, R., Saifan, S., Ab Yajid, M. S., & Khatibi, A. (2021). Mediating role of entrepreneurial marketing between green marketing and green management in predicting sustainable performance in Malaysia's organic agriculture sector. AgBioForum, 23(2), 37-49.
Wilkinson, D., Christie, A., Tarr, A. A., & Tarr, J.-A. (2024). Big Data, Artificial Intelligence and Insurance. In The Global Insurance Market and Change (pp. 22-46). Informa Law from Routledge.
Yadav, A., & Sondhi, H. (2023). Systematic Literature Review on Sustainable Marketing and Artificial Intelligence. 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom),
Zhang, H., Wang, Y., & Song, M. (2019). Does competitive intensity moderate the relationships between sustainable capabilities and sustainable organizational performance in new ventures? Sustainability, 12(1), 253.
