Designing a Model of Fixed Internet Service Consumers’ Behavior and Customer-Centric Strategies: A Grounded Theory Study

In the contemporary digital landscape, fixed internet services represent one of the foundational pillars of national and global digital infrastructure. These services are not only essential for daily communication and access to information but also form the backbone of economic and social development, particularly in urban areas such as Tehran. However, despite their critical importance, the fixed internet service industry is increasingly facing significant challenges in understanding and managing consumer behavior. Rapid technological changes, market competition, and shifting consumer expectations have added new layers of complexity to the decision-making processes of internet service users. The present study seeks to address this gap by developing a comprehensive model of consumer behavior in the fixed internet service sector of Tehran. The necessity of this research lies in the fact that consumer behavior in this field is no longer linear or predictable; rather, it is shaped by a multitude of interrelated factors—economic, social, technological, and psychological. In this context, gaining an in-depth understanding of how and why consumers choose particular internet service providers (ISPs), how they evaluate service quality, and what influences their loyalty and advocacy behaviors becomes crucial for service providers aiming to achieve competitive advantage.

This study is particularly concerned with the role of customer service strategies—both proactive and reactive—in shaping and influencing consumer behavior. While previous studies have often treated customer service as a peripheral factor, this research places it at the center of behavioral modeling. It aims to provide a nuanced perspective by identifying the interactions between customer service strategies and broader contextual, causal, and intervening variables that affect consumer decision-making.

Research Objectives

The primary objective of this research is to design a consumer behavior model for fixed internet services in Tehran, with a special focus on the role of customer service. In order to fulfill this objective, the following secondary goals have been pursued:

1. Identifying the key factors that influence consumer behavior in the fixed internet service industry.

2. Explaining the stages of consumer decision-making, including pre-purchase, purchase, and post-purchase behavior.

3. Analyzing the role of customer service strategies in influencing consumer perceptions, satisfaction, and loyalty.

4. Presenting a holistic framework that integrates all relevant variables to understand behavioral outcomes such as brand loyalty, word-of-mouth advocacy, and customer retention.

Methodology

Given the exploratory nature of the research and the need for theory generation, a qualitative approach based on grounded theory methodology was adopted. Grounded theory is particularly suitable for understanding complex, context-bound social phenomena, and it allows researchers to build theoretical frameworks directly from empirical data.

Data collection was conducted through in-depth semi-structured interviews with 21 individuals who were selected from among the sales and customer service personnel of various fixed internet service providers in Tehran. The selection process followed the purposive sampling method, specifically employing the maximum variation strategy to ensure a wide range of perspectives and experiences were included.

Interviews continued until theoretical saturation was achieved—i.e., the point at which no new themes or concepts were emerging from the data. The data analysis process consisted of open coding, axial coding, and selective coding, carried out using MAXQDA software, a specialized tool for qualitative data analysis. During this process, data were continuously compared, categorized, and refined to construct a coherent and valid theoretical model.



Discussion and Results

During open coding, 148 unique concepts were labeled and categorized into 17 categories through comparison of differences and similarities. In axial coding, the categories were classified as follows: economic factors, individual factors, social factors, and marketing factors were classified as causal conditions; need recognition and information gathering, evaluation of options and selection, and post-purchase evaluation were classified as consumer behavior categories; proactive customer service and responsive customer service were classified as customer service strategy categories; technology and telecommunications infrastructure and similarity of products/services were classified as contextual conditions; brand reputation and consumer knowledge were classified as intervening conditions; and purchase intention, brand recommendation, active participation, and brand defense were classified as consumer behavior outcomes.



Conclusion

This study highlights the complex, multidimensional nature of consumer behavior in the fixed internet service sector. The findings reveal that while traditional factors such as pricing and marketing still play a role, the quality of customer service—especially in a market with homogenous products—is a critical determinant of consumer satisfaction and loyalty.

The consumer behavior model proposed in this research synthesizes a variety of influencing factors into a coherent framework that can be practically applied by service providers, marketers, and policymakers. By recognizing the importance of proactive and responsive customer service strategies, ISPs can design better engagement programs, personalize service delivery, and enhance consumer trust.

Moreover, the model provides a strategic roadmap for marketing managers to develop customer orientation loyalty programs and for service managers to design performance metrics aligned with consumer expectations. Policy-makers, too, can benefit from the insights of this study to create regulatory frameworks that ensure fairness, transparency, and consumer rights in the digital services ecosystem.

In conclusion, by offering a comprehensive behavioral model, this research not only fills existing gaps in the literature but also provides actionable insights for improving customer experience and sustaining competitive advantage in an increasingly saturated and commoditized market.