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Predicting customer demand for remanufactured products: A data-mining approach
16 references·16 citing·49 second hopsampled
Predicting customer demand for remanufactured products: A data-mining approach (2019)Predicting customer demand for remanufact…A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)A new hybrid classification a…Big data analytics in supply chain management: A state-of-the-art literature review (2017)Big data analytics in supply …Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500 (2016)Deep neural networks, gradien…Consumer product knowledge and intention to purchase remanufactured products (2015)Consumer product knowledge an…The Effect of Online Consumer Reviews on New Product Sales (2012)The Effect of Online Consumer…What Signal Are You Sending? How Website Quality Influences Perceptions of Product Quality and Purchase Intentions1 (2011)What Signal Are You Sending? …New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)New insights into churn predi…Deriving the Pricing Power of Product Features by Mining Consumer Reviews (2011)Deriving the Pricing Power of…Influence: science and practice (2008)Influence: science and practi…Heuristics made easy: An effort-reduction framework. (2008)Heuristics made easy: An effo…eWOM overload and its effect on consumer behavioral intention depending on consumer involvement (2008)eWOM overload and its effect …The Effect of Word of Mouth on Sales: Online Book Reviews (2006)The Effect of Word of Mouth o…A Consumer-Side Experimental Examination of Signaling Theory: Do Consumers Perceive Warranties as Signals of Quality? (1993)A Consumer-Side Experimental …Influence : science and practice (1985)Influence : science and pract…A Theory of Auctions and Competitive Bidding (1982)A Theory of Auctions and Comp…The Market for "Lemons": Quality Uncertainty and the Market Mechanism (1970)The Market for "Lemons": Qual…Demand Forecasting in Supply Chain Using Uni-Regression Deep Approximate Forecasting Model (2024)Demand Forecasting in Supply …Applications of artificial intelligence in closed-loop supply chains: Systematic literature review and future research agenda (2024)Applications of artificial in…Application of artificial intelligence in reverse logistics: A bibliometric and network analysis (2024)Application of artificial int…The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland (2023)The Role of Artificial Intell…Spatiotemporal analysis of bike-share demand using DTW-based clustering and predictive analytics (2023)Spatiotemporal analysis of bi…Exploiting time-varying RFM measures for customer churn prediction with deep neural networks (2023)Exploiting time-varying RFM m…The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods (2022)The derived demand for advert…A sustainable step forward: Understanding factors affecting customers’ behaviour to purchase remanufactured products (2022)A sustainable step forward: U…Promoting consumer's attitude toward refurbished mobile phones: A social media analytics approach (2021)Promoting consumer's attitude…On a Certain Research Gap in Big Data Mining for Customer Insights (2021)On a Certain Research Gap in …Marketing strategies for refurbished products: Survey-based insights for probabilistic selling and technology level (2021)Marketing strategies for refu…Customer purchase forecasting for online tourism: A data-driven method with multiplex behavior data (2021)Customer purchase forecasting…Correlation mechanism between smart technology and smart supply chain innovation performance: A multi-case study from China's companies with Physical Internet (2021)Correlation mechanism between…A Review on the Lifecycle Strategies Enhancing Remanufacturing (2021)A Review on the Lifecycle Str…Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming (2020)Optimal selection of heteroge…Business analytics: Defining the field and identifying a research agenda (2019)Business analytics: Defining …COUNTERSPECULATION, AUCTIONS, AND COMPETITIVE SEALED TENDERS (1961)Good News and Bad News: Representation Theorems and Applications (1981)Optimal Auction Design (1981)The Theory of Incentives: The Principal-Agent Model (2001)Field Experiments (2004)Statistical principles in experimental design. 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(1967)Word-of-Mouth Communication and Social Learning (1995)Trust among strangers in internet transactions: Empirical analysis of eBay' s reputation system (2004)Customer Engagement Behavior: Theoretical Foundations and Research Directions (2010)Consumer engagement in a virtual brand community: An exploratory analysis (2011)What Makes Online Content Viral? (2011)Evaluating Structural Equation Models with Unobservable Variables and Measurement Error (1981)Common method biases in behavioral research: A critical review of the literature and recommended remedies. (2003)The impact of user interactions in social media on brand awareness and purchase intention: the case of MINI on Facebook (2013)Assessing the effects of consumers’ product evaluations and trust on repurchase intention in e-commerce environments (2017)How do product recommendations affect impulse buying? 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References

  • 1970The Market for "Lemons": Quality Uncertainty and the Market Mechanism22,977 cited
  • 2006The Effect of Word of Mouth on Sales: Online Book Reviews5,993 cited
  • 1982A Theory of Auctions and Competitive Bidding3,770 cited
  • 1985Influence : science and practice3,573 cited
  • 2008Heuristics made easy: An effort-reduction framework.1,033 cited
  • 2008Influence: science and practice1,019 cited
  • 1993A Consumer-Side Experimental Examination of Signaling Theory: Do Consumers Perceive Warranties as Signals of Quality?1,017 cited
  • 2011Deriving the Pricing Power of Product Features by Mining Consumer Reviews1,011 cited
  • 2011What Signal Are You Sending? How Website Quality Influences Perceptions of Product Quality and Purchase Intentions1761 cited
  • 2016Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500749 cited
  • 2008eWOM overload and its effect on consumer behavioral intention depending on consumer involvement647 cited
  • 2012The Effect of Online Consumer Reviews on New Product Sales621 cited
  • 2017Big data analytics in supply chain management: A state-of-the-art literature review567 cited
  • 2018A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees529 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2011New insights into churn prediction in the telecommunication sector: A profit driven data mining approach460 cited
  • 2015Consumer product knowledge and intention to purchase remanufactured products442 cited
  • Cited by

    • 2024Applications of artificial intelligence in closed-loop supply chains: Systematic literature review and future research agenda112 cited
    • 2022A sustainable step forward: Understanding factors affecting customers’ behaviour to purchase remanufactured products93 cited
    • 2021Promoting consumer's attitude toward refurbished mobile phones: A social media analytics approach80 cited
    • 2019Business analytics: Defining the field and identifying a research agenda69 cited
    • 2023The Role of Artificial Intelligence within Circular Economy Activities—A View from Ireland69 cited
    • 2022The derived demand for advertising expenses and implications on sustainability: a comparative study using deep learning and traditional machine learning methods68 cited
    • 2020Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming67 cited
    • 2021A Review on the Lifecycle Strategies Enhancing Remanufacturing66 cited
    • 2021Customer purchase forecasting for online tourism: A data-driven method with multiplex behavior data66 cited
    • 2023Exploiting time-varying RFM measures for customer churn prediction with deep neural networks58 cited
    • 2024Demand Forecasting in Supply Chain Using Uni-Regression Deep Approximate Forecasting Model48 cited
    • 2021Marketing strategies for refurbished products: Survey-based insights for probabilistic selling and technology level43 cited
    • 2021Correlation mechanism between smart technology and smart supply chain innovation performance: A multi-case study from China's companies with Physical Internet40 cited
    • 2024Application of artificial intelligence in reverse logistics: A bibliometric and network analysis40 cited
    • 2023Spatiotemporal analysis of bike-share demand using DTW-based clustering and predictive analytics36 cited
    • 2021On a Certain Research Gap in Big Data Mining for Customer Insights34 cited