درخت حوزه‌های تخصصی

The objective of this study is to understand the customer journey in technology product adoption by exploring the experiences and perspectives of individuals who have recently adopted new technology products. This research aims to identify key themes and factors influencing the customer journey from initial awareness to ongoing engagement and retention, providing insights to enhance customer experiences and inform marketing strategies. This qualitative study employed semi-structured interviews with 20 participants selected through purposive sampling to ensure diverse representation. Participants included individuals who had recently adopted technology products within the past six months. Data collection continued until theoretical saturation was reached. The interview transcripts were analyzed using NVivo software, following an inductive approach to identify patterns and themes. The analysis revealed three main themes: Awareness and Decision-Making, First-Time Use and Learning, and Ongoing Engagement and Retention. Initial awareness was driven by advertising, social media, and word-of-mouth, while decision-making was influenced by peer recommendations, brand reputation, and price sensitivity. The first-time use phase highlighted the importance of intuitive design and support resources. Regular updates, community engagement, and product reliability emerged as critical factors in ongoing engagement and retention. Participants valued seamless omnichannel experiences, personalized marketing efforts, and robust support systems. The study underscores the significance of personalized, seamless customer journeys in technology product adoption. Businesses should focus on integrating physical and digital touchpoints, leveraging AI for personalized experiences, and maintaining active user communities to enhance customer satisfaction and loyalty. Addressing cultural nuances in global markets and managing digital signals effectively can further optimize the customer journey. These insights provide valuable guidance for businesses aiming to improve customer experiences and foster long-term engagement in the competitive technology market.

This study examines the relationship between stock liquidity and return predicta-bility of 116 publicly-traded firms in Tehran Stock Exchange (TSE). To this end, we constructed a dated-regular frequency of time series with total 40128 stock-firm observations. After calculating daily bid-ask spreads and stock returns, the observations were classified based on liquidity into three classes and the return predictability was investigated across different classes using a set of parametric tests. The results exhibit signs of return autocorrelation and non-independence over three liquidity groups. Our findings didn’t show a connection between stock liquidity and market efficiency. The Hurst exponent also revealed mean reversion of returns series across different liquidity classes. We conclude that stock liquidity doesn’t play a significant role in market efficiency and return predictability of stocks in TSE. In case of TSE as other emerging markets, due to the small num-ber of traders (the need for more trading activity) and low market making activi-ties, both the cost of trading increases and the reaction to stock price information is delayed, resulting in predictability of price /return.