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All Journal Advances in Business & Industrial Marketing Research
Dzreke, Semefa Elikplim
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Economics, Econometrics & Finance

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The Symbiotic Dance – How Agile Supply Chains and Strategic Marketing Orchestrate Brand Responsiveness to Evolving Consumer Demands Dzreke, Simon; Dzreke, Semefa Elikplim
Advances in Business & Industrial Marketing Research Vol. 3 No. 3 (2025): June - September
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/abim.v3i3.624

Abstract

Purpose: This study aims to develop and validate the Adaptive Brand Ecosystem model, a new framework that integrates marketing intelligence with agile supply chain execution to enhance organizational responsiveness and competitiveness. It hypothesizes that tighter integration between marketing and operations leads to superior market performance and customer retention. Research Design and Methodology: The research employed a quantitative design using cross-sectional data from 214 companies across various global markets. Performance indicators such as response speed, inventory turnover, and customer retention were analyzed to measure the impact of marketing–supply chain integration. Additionally, case studies from Zara and Warby Parker were used to provide qualitative insights into real-world applications of adaptive capabilities. Findings and Discussion: The findings reveal that firms with strong marketing–operations integration respond 68% faster to market changes, achieve 28% higher inventory turnover, and retain 22% more customers than competitors. The analysis highlights how dynamic market-sensing capabilities restructure supply chains to translate consumer insights into operational advantages. Implications: The model provides executives with strategic guidance for building co-evolving marketing and supply chain systems and introduces tools such as the Demand Response Scorecard. For academics, theory advances by linking dynamic capabilities, market orientation, and operational flexibility, promoting a shift from market-responsiveness to market-propulsion.
The Credibility Gap: Why 68% of Marketers Reject Superior AI Reports (200-CMO Blind Test) Dzreke, Simon; Dzreke, Semefa Elikplim
Advances in Business & Industrial Marketing Research Vol. 3 No. 3 (2025): June - September
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/abim.v3i3.625

Abstract

Purpose: A significant paradox undercuts artificial intelligence's promise in strategic marketing: while 92% of organizations already use AI-generated insights, 74% of executives distrust them for crucial decisions. Research Design and Methodology: This study addresses the credibility dilemma by conducting a groundbreaking blind test with 200 Chief Marketing Officers from Fortune 500 companies, analyzing identical business challenges—half answered by premier AI platforms (GPT-4 and custom LLMs), and half by experienced human analysts. Findings and Discussion: The technique found an unexpected discrepancy: whereas NLP assessment indicated AI matched or exceeded human report quality in 82% of cases, displaying higher predictive accuracy (+14%) and data comprehensiveness, executives rejected 68% of algorithmically generated insights. A multivariate study identified explanatory inadequacies as the crucial factor: AI's inability to communicate why patterns mattered (causal reasoning), base discoveries in operational realities (contextual framing), and structure insights coherently (narrative flow) accounted for 53% of the trust gap. This "analytics without understanding" dilemma was evident when CMOs ignored an AI report accurately predicting telecom churn because it overlooked how back-to-school tuition payments stretched household budgets—the explanation that made the helpful finding. The study proposes a hybrid approach that adds human-authored "why explanations" (about 47 words) to AI outputs, increasing adoption intent by 40% while maintaining 60% efficiency improvements. Implications: These findings suggest viewing algorithm aversion as a fundamental epistemic reconciliation challenge—one where narrative intelligence links computational power and human judgment. As AI affects strategic decision-making, this study gives a trust calibration plan for maximizing its potential while maintaining interpretative depth.
Co-Authors Dzreke, Simon