Document Type : Original Article (Qualitative)
Authors
1
Department of Business Administration, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran
2
Department of Business Management, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran,
3
Department of Business Management, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran.
Abstract
Abstract
The objective of this research is to design a grounded theory model for the social acceptance of smart home technology (SHT) among Iraqi consumers. This study was conducted based on an interpretive paradigm through a qualitative approach. The statistical population consists of 15 smart home technology experts and university professors specializing in marketing, selected through the snowball sampling method, and participated in semi-structured interviews. The data were analyzed by latent content analysis tactics in MAXQDA 2024 software through three stages: open, axial, and selective coding. The findings led to the conceptualization of several categories, including “acceptance of smart home technology,” “perceptions of trust and security,” “lifestyle integration behaviors,” “economic decision-making,” and “response to social influence,” with seven main and original hypotheses established among them. The results revealed that the core category, “Social Acceptance of Smart Home Technology,” encompasses a multi-faceted construct influenced by cognitive, social, and innovative dimensions.
Introduction
In recent years, Iraq has faced significant challenges in the energy sector due to international sanctions and the occurrence of multiple wars (Al‑Ghabera et al., 2024). Efficient energy consumption in this country has become highly important and has been introduced by the government as a national priority (Al‑Yozbaky et al., 2022). Smart home technology represents the convergence of the Internet of Things (IoT), artificial intelligence (AI), sensors, and automation systems to create intelligent and responsive living environments that enhance residents’ comfort, security, energy efficiency, and sustainability (Yeoh Lui et al., 2025). In Iraq, where persistent challenges such as frequent power outages, security concerns, water shortages, and rapid urbanization exist, smart home systems offer an appropriate solution for optimizing resource use and adapting to local lifestyles (Mustafa et al., 2025).
On the other hand, an examination of Iraq’s demographic composition indicates that the majority of the country’s population consists of young people, many of whom pay particular attention to innovation in their purchasing decisions and tend to prefer products that possess a superior mental image compared with competing alternatives (Ahmed et al., 2020). Furthermore, according to reports from Iraq’s National Housing Sector, approximately 75 percent of Iraqi households are interested in adopting modern and innovative architectural approaches in order to improve their quality of life (Al‑Khafaji & Kamaran, 2019).
A cultural analysis of Iraq based on Hofstede’s cultural dimensions shows that the country is characterized by high power distance, a collectivist culture, masculinity, and a high level of uncertainty avoidance (Sardar, 2015). Analytical studies indicate that societies with high power distance often demonstrate lower resistance to smart home technologies, as many households in such cultures are willing to adopt innovative architectural ideas to enhance comfort and welfare (Bao et al., 2014; Wang et al., 2024). Regarding collectivism, researchers argue that positive social attitudes toward smart home technology spread rapidly within society, and once the technology gains collective acceptance, resistance declines and consumers quickly move from early adoption to more rational and widespread use (Liu et al., 2021; Mouzaidis et al., 2023).
Analysis of the masculinity–femininity dimension suggests that in more feminine cultures there is a greater tendency to adopt practical and modern technologies such as remote-control systems, graphical user interfaces, and smart electricity technologies (Jeong et al., 2013). Finally, studies on uncertainty avoidance indicate that in such cultures consumers often view new technologies with caution and tend to accept smart home technologies only after they become widely adopted within society (Furszyfer Del Rio et al., 2021; Chang & Chiu, 2025). Accordingly, the present study seeks to answer the following main research question: What is the grounded theory model of social acceptance of smart home technology among Iraqi consumers?
Theoretical Framework
Social Acceptance of Smart Home Technology
Social acceptance refers to the processes through which individuals, groups, and societies approve, adopt, or integrate innovations, technologies, or social phenomena into their norms, behaviors, and institutional structures (Moeremans & Dooms, 2025; Shuhaiber & Mashal, 2019). The theory of social acceptance is not a single unified framework; rather, it is a multidimensional concept that has evolved across different disciplines, particularly in social psychology, energy transition studies, and innovation research. It encompasses psychological needs for belonging, the social validation of innovations, and the institutional transformations required for systemic change (Ji & Chan, 2020; Alshammari & Alkhwaldi, 2025).
Norouzzadeh et al. (2025) examined the role of the Internet of Things (IoT) in residential smart home technologies. Their findings indicated that social influence was not a significant factor in the adoption of IoT-based smart home technologies. They attributed this result to habit-related barriers and the level of effort required from users within the studied sample, suggesting that technology acceptance depends more on individual usability than on social norms.
Moghbal Naseri et al. (2023) investigated human behavior based on sleep–wake patterns using smart home sensors. In this study, smart home technologies were used to monitor the behavior of elderly individuals who faced physical or psychological challenges and lived independently or with pets. Using data collected from smart home sensors, the daily behaviors of individuals during waking and sleeping periods were predicted and analyzed through computational approaches. The researchers developed an algorithm capable of modeling sleep and wake behavior patterns and enabling behavioral prediction. By analyzing data from the CASAS smart home dataset, this approach was presented as an effective method for improving the ability of individuals with physical or mental limitations to live independently.
Research Methodology
This study was conducted based on the interpretive paradigm through a qualitative research approach. The statistical population consisted of 15 experts in smart home technology and university professors specializing in marketing. Participants were selected through the snowball sampling method and took part in responding to the interview questions. The data collection tool was semi‑structured interviews.
Research Findings
The collected data were analyzed by latent content analysis techniques in MAXQDA 2024 software through three stages: open coding, axial coding, and selective coding. The findings led to the identification and development of several key categories, including smart home technology acceptance, perceived trust and security, lifestyle integration behaviors, economic decision‑making, and responses to social influence. Seven main and novel hypotheses were established among these categories. The results indicated that the core category, “Social Acceptance of Smart Home Technology,” represents a multidimensional construct influenced by cognitive, social, and innovation‑related dimensions.
Conclusion
The present study aimed to design a grounded theory model for the social acceptance of smart home technology among Iraqi consumers. The findings of this research are consistent with previous studies conducted by Moghbal Naseri et al. (2023), Nakhalet al‑Jannah and Ghaffarian (2022), Abbasi (2022), Pirzada et al. (2022), Farah Hussin et al. (2022), Arar et al. (2021), Pal et al. (2021), Gross et al. (2020), Mashal et al. (2020), and Ko et al. (2020).
Pal et al. (2021) found that user characteristics, particularly user skills, have the greatest influence on privacy concerns, followed by legal and policy aspects and technological dimensions. In addition, physical and psychological privacy were considered more important than concerns related to informational privacy.
Based on the results of the study, the following recommendation is proposed. Managers and stakeholders should recognize the lack of a significant relationship between economic decision‑making and perceptions of trust and security. This insight should encourage them to separate financial incentives from security‑focused campaigns. Instead, they should develop independent educational initiatives that address cost–benefit analysis separately, ensuring that trust‑building efforts are not influenced by perceptions of economic trade‑offs.
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