Provision of a Scale for Assessing Product Search Channels Based on Hedonic and Utilitarian Shopping Attributes

With the proliferation of electronic commerce, examining the role of various information channels during the customer journey has become increasingly important. Online information channels, which conveniently provide a variety of relevant information, significantly influence purchase decisions. Given the complexities of customer journeys on the internet, identifying the mechanisms behind the choices and usage of information channels remains a challenge. These choices and usages depend on a range of retailer and product-category characteristics, as well as diverse consumer preferences. Additionally, the rapid expansion of online retailing has been driven by the global increase in Internet access. This trend has created a marketplace where consumers have access to a diverse array of supplier and product information, enabling them to compare products and services with those of competitors and achieve more favorable outcomes. In other words, the evolution of the Internet as a primary sales channel has prompted researchers to investigate the fundamental factors and motivations that drive online shopping. They aim to understand why consumers choose specific online channels based on various motivations, whether hedonic or utilitarian. According to studies, consumers choose online shopping based on hedonic or utilitarian motivations, both of which subsequently influence their online shopping experiences and purchase decisions. Consequently, the relative importance of channel features for consumers largely depends on their motivations. Understanding the different motivations that consumers have for utilizing various online communication channels offers valuable insights for improving the effectiveness of online marketing efforts, warranting further investigation. This study aims to validate a scale for assessing product search channels based on hedonic and utilitarian shopping characteristics, followed by an evaluation of the model's ability to predict the use of online channels.

The present study employed a mixed-methods approach, utilizing semi-structured interviews within a phenomenological framework with twenty-three participants during the qualitative phase. A questionnaire was developed based on the insights gathered from participants in this phase. Additionally, quantitative research was conducted to build upon the qualitative findings, aiming to develop and validate a scale that examines the model's capacity to predict online customers' search and purchasing behavior. The foundation of this research was grounded in quantitative analysis. Furthermore, questionnaires were administered to four hundred thirty-four online customers in Tehran, selected through non-probability and convenience sampling, and the data were analyzed using multivariate analysis techniques. This research was exploratory and applied in nature, evaluating the relationships between indices and sub-constructs, as well as between main and sub-constructs, through exploratory and confirmatory factor analysis and structural equation modeling within a positivist framework. Additionally, the validity of the constructs was established through convergent and discriminant validity indices, while the reliability of the constructs was confirmed using composite reliability and maximum reliability coefficients.

A total of fourteen components were identified based on the results of exploratory factor analysis conducted using SPSS. Additionally, confirmatory factor analysis performed with AMOS supported the reliability and validity of the measurement tool through various indices. Furthermore, evidence was assessed using structural equation modeling in AMOS to evaluate the model's ability to predict the use of online channels based on purchasing motivations. The results of the structural equation modeling indicated that customers with utilitarian shopping motivations significantly utilized search engines, product websites, third-party information, and visits to online retail websites. In contrast, customers with hedonic shopping motivations significantly engaged with social media and manufacturer websites.

The findings indicate that consumers with hedonic and utilitarian motivations utilize different online channels during the shopping process. There are distinct online platforms tailored to these varying motivations. Consequently, marketers should formulate their strategies based on product categorization to improve efficiency. Businesses must design their online stores to deliver optimal customer experiences, thereby encouraging increased online purchases. It is essential for organizations and businesses to recognize that customer experience is the most significant competitive advantage. Properly designing product search channels reduces costs and enhances customer engagement. This enables companies to better understand and identify different user segments and their needs, allowing them to select appropriate strategies for customers' journeys. This research not only provides practical recommendations for online stores but also assists future researchers in developing and exploring the research model with other effective variables across various contexts. In doing so, it bridges research gaps and serves both practical and theoretical purposes. The research findings have both theoretical and practical applications. The theoretical insights can enhance the scientific community and assist researchers by expanding the existing literature and directing future studies on the topic across various statistical populations. Additionally, they can aid in the development of the research model by incorporating other potential variables. On the practical side, the results can provide valuable guidance to managers of online stores.