Modeling the key attributes for improving customer repurchase rates through mobile advertisements using a Fuzzy mixed approach

Abstract

Purpose Due to the high use of mobile devices, the market share of mobile advertisements (Ads) is significantly growing. Although mobile Ads can contact potential customers at any time and in any location depending on their unique demands, one of the biggest problems for advertisers is how to improve customer repurchases with their Ads. The development and empirical support of customer repurchase through mobile Ads context have not been addressed. Therefore, the purpose of this paper is to define and identify the key attributes of customer repurchase in a mobile Ads context. Design/methodology/approach In this research, the set of attributes was derived from a systematic literature review and finalized by applying the Fuzzy Delphi method. To develop a hierarchical model and classify the cause/effect groups among identified key attributes, the Fuzzy mixed approach uses a combination of Fuzzy interpretive structural modeling-decision-making trial and evaluation laboratory. Findings The findings suggest that language, type of website and social media are classified to as essential attributes for improving customer repurchase through mobile Ads. Research limitations/implications The focus of the current research is limited to identify and develop the hierarchical interrelationships between customer repurchase attributes that are unique to the mobile Ads business context. Additional research may be conducted for various media contexts and other products/services categories. Originality/value This study illustrated how multicriteria decision-making techniques could be used effectively using Fuzzy theory to explore the research area of customer repurchase in mobile Ads concept.

Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering

“…Tushar et al [30] presented a case study on the application of a MICMAC analysis to assess the factors influencing the adoption of green building technologies in the construction industry, facilitating informed decision-making for sustainable construction practices. Nalluri et al [31] used a MICMAC analysis to understand the dynamics of the factors affecting the consumer adoption of electric vehicles, providing insights for policymakers and industry stakeholders to promote sustainable mobility solutions.…”

“…Fuzzy-Delphi analysis combines the principles of the Delphi method with fuzzy sets to address the uncertainty and ambiguity in decision-making processes. Originating from the Delphi method as indicated in the flow diagram shown in Figure 2, it gathers expert opinions through iterative rounds of feedback, fuzzy-Delphi extends this approach by incorporating fuzzy sets into the method to quantify subjective judgments and handle imprecision [31,32,50]. By integrating these methodologies, fuzzy-Delphi analysis provides a systematic framework for eliciting and aggregating expert opinions in situations where traditional Delphi methods may encounter challenges due to vagueness or uncertainty.…”

“…Following the flow diagram in Figure 2, next method is ISM, which is used to analyze and understand the complex interrelationships among factors or variables within a system. Originating from operations research and systems theory, ISM provides a structured approach to model and visualize the hierarchical relationships among factors, allowing decision-makers to gain insights into the system's structure, dynamics, and key drivers [28,[30][31][32]. By identifying and interpreting hierarchical relationships, ISM enables effective decision-making, strategic planning, and problem-solving in diverse domains such as engineering, management, and policy analysis.…”