International Journal of Product Development (11 papers in press)

Regular Issues

• A Precision Marketing Method for Digital Product Big Data Based on User Generated Content  
  by Jing Liu, Yiwen Ruan, Jia Lin 
  Abstract: In order to improve the marketing accuracy and user satisfaction of digital product big data, a precision marketing method based on user generated content for digital product big data is proposed. Firstly, vectorise the user generated evaluation text, digital product category text and image information of digital product descriptions. Secondly, convolutional fusion is performed on the text comprehensive features and image features of digital products. Finally, construct a digital product user interest model based on the level of user interest. Using tag weights to construct a precise marketing function for digital product big data. The experimental results show that compared with existing marketing methods, this paper method can improve the marketing accuracy of digital product big data, while also enhancing user satisfaction.
  Keywords: User generated content; Digital products; Big data precision marketing; User interest model.
  DOI: 10.1504/IJPD.2024.10067928
   
  
• Product Image Modelling Optimisation Design Method Based on Improved Support Vector Machine  
  by Hua Song 
  Abstract: In order to make the image modelling of the product more in line with the design goals, this paper proposes an optimized design method for product image modelling based on improved support vector machines. Firstly, construct the ontology triplet of product image modelling and extract the lexical features of image modelling. Secondly, using chaos algorithm and particle swarm optimisation algorithm to improve support vector machine to more accurately capture product appearance features. Finally, based on the extraction results of product appearance features, simulated annealing algorithm was introduced as an optimisation tool to solve the optimisation design problem of product image modelling, achieving efficient optimisation of product image modelling. The experimental results show that for the four door sedan, the target vocabulary scores of the image modelling method in this article all exceed 0.9, and the highest aesthetic score of the image modelling design reaches 96.67 points.
  Keywords: Improving support vector machines; Product image modeling; Optimize design; Simulated annealing algorithm.
  DOI: 10.1504/IJPD.2024.10067937
   
  
• Fuzzy Decision Tree Based Online Precision Marketing Method for Brand Products on the Internet  
  by Chunyan Liu 
  Abstract: To solve the problems of poor user satisfaction, low user purchase rate, and low recommendation accuracy in current brand product marketing methods, this paper proposes an online precision marketing method for brand products based on fuzzy decision trees.Firstly, collect and obtain user characteristics of brand products driven by internet data; Secondly, construct a user influence relationship model and a user preference and interest model for the product; Again, classify brand product data features based on fuzzy decision trees; Finally, precise online marketing of brand product users is achieved through cosine similarity calculation. The experimental outcomes demonstrate that the marketing satisfaction achieved by the approach introduced in this article consistently exceeds 92%,reaching a peak user purchase rate of 52.18% and attaining a maximum accuracy of 95.08% in product recommendations. The approach outlined in this article can significantly enhance the efficacy of data-driven online precision marketing strategies for brand products.
  Keywords: Fuzzy decision tree; Online marketing; User characteristics; Interest model; Precision marketing.
  DOI: 10.1504/IJPD.2024.10067938
   
  
• Colour Matching Design Method in Product Visual Communication based on Grey Relational Analysis  
  by Fan Wu, Huaxi Chen 
  Abstract: Colour matching in product visual communication results in high colour differences due to insufficient consideration of the degree of correlation between colours. Therefore, a colour matching design method in product visual communication based on grey relational analysis is studied.Firstly,201 colours were selected as initial samples, and fuzzy processing techniques were used to combine colour merging and noise removal to screen colours. Then, it introduces the expected value of colour imagery, adjust weights, and the initial colour scheme is design. Finally, the grey correlation analysis improved by the tomographic analysis method is used to determine the weighted grey correlation of colours and optimize the initial colour scheme. The colour matching of this method meets the requirements with the highest product colour difference value of 1.63 and a consensus degree of 0.85 according to the experiment. It improves the colour coordination of the product and conforms to user image preferences.
  Keywords: Product colour matching; Visual communication; Colour scheme design; Colour screening; Grey correlation analysis; Weighted grayscale correlation.
  DOI: 10.1504/IJPD.2024.10067940
   
  
• Optimal Styling Method of Product Appearance Considering Users' Emotional Preferences  
  by Yonghua Li 
  Abstract: To improve user satisfaction with product styling, this paper proposes a product styling optimization design method that takes into account user emotional preferences. Firstly, obtain a dataset of target product shape image samples and classify the product shape image samples; Secondly, based on the Apriori algorithm, obtain the frequent itemsets of the target product's shape image samples for users, and mine their perceptual preference features; Once again, set the preference feature attribute content of the styling image samples, and classify the user's perceptual preference feature attributes based on naive Bayes; Finally, the fitness of each design scheme is calculated using the differential bee colony algorithm, and the product shape optimisation design is achieved through iterative optimisation. The experimental results show that using the proposed method, the user satisfaction rate is over 87%, and the user's product purchase intention score remains above 7 points. The application effect is good.
  Keywords: Emotional preferences; product appearance; Apriori algorithm; Naive Bayes Differential bee colony algorithm.
  DOI: 10.1504/IJPD.2024.10067942
   
  
• The Application of AI Technology to Upgrade Retailers' Traditional Marketing Means  
  by Lu Zhang, Ruixue Dong 
  Abstract: In order to improve the conversion rate of users' purchase and the personalization of marketing push, the application of AI technology in upgrading traditional marketing methods of retailers was studied. Firstly, it analyses the limitations of traditional retailers' marketing methods. Secondly, aiming at the existing limitations, AI technology is introduced to upgrade marketing means, big data analysis technology is used to mine user behaviour data, collaborative filtering algorithm in machine learning algorithm is used to recommend products individually, and natural language processing technology is used to evaluate user satisfaction. Finally, the application effect of this method is evaluated through a case study. The results show that the conversion rate of this method is high, with the highest value of 48.3% and the highest score of personalization degree of 1.0, which shows that it can predict users' purchasing behaviour more accurately and provide more personalised recommendation results.
  Keywords: AI technology; Retailer; Marketing means; User behavior data; Collaborative filtering algorithm; Satisfaction evaluation.
  DOI: 10.1504/IJPD.2024.10067943
   
  
• Study on Strategies for Enhancing Enterprise Management Decision-Making Ability Facing Market Demand  
  by Yang Yang 
  Abstract: In order to help enterprises achieve strategic goals, meet customer demands, and adapt to market changes, this article conducted a strategies for enhancing enterprise management decision-making ability facing market demand. It analyses the relationship between market demand and enterprise management decision-making, elaborating on the importance and necessity of enhancing enterprise management decision-making abilities from multiple perspectives. The article also identifies existing issues in enterprise management decision-making, and proposes targeted strategies such as strengthening market research and analysis capabilities, enhancing information and data management capabilities, simplifying decision-making processes, improving the decision-making abilities of management teams, fostering a culture of cross-departmental teamwork, and establishing a learning organisation to enhance enterprise management decision-making abilities. The analysis results show that the maximum recall rate of the proposed method is 98.3%, the average management decision time is 39.2 days, and the average management decision fit is 0.96.
  Keywords: Market demand; Enterprises; Management decision-making ability; Strategies for enhancing; Decision-making process; Culture of cross-departmental teamwork; Learning organization.
  DOI: 10.1504/IJPD.2024.10067944
   
  
• Personalised Push Method for Sports Goods Purchase Information in the Context of Marketing  
  by Ziya Wang, Fei Gao 
  Abstract: To solve the issues of low satisfaction and low UV click rate in the existing personalised push methods of commodity purchase information, this paper proposes a personalized push method for sports goods purchase information in the context of marketing. By utilising crawler technology, an online shopping platform users' behaviour dataset for purchasing sporting goods is established. A generalised hierarchical tree of user portrait attribute tags is constructed, and the browsing time of sporting goods containing a certain tag is calculated to allocate the membership degree of sporting goods and mine user interest preferences. The Pearson similarity algorithm is applied to construct the similarity matrix for personalised push, enabling personalised push of sporting goods purchase information. Experiments demonstrate that the user satisfaction rate using this method consistently remains above 88%. Furthermore, the highest UV click rate achieved is 7.56%, indicating a successful push effect.
  Keywords: Sports goods; User portrait; Generalised hierarchical tree; Membership degree; Pearson similarity.
  DOI: 10.1504/IJPD.2024.10067945
   
  
• Research on Image Detail Enhancement of Cultural and Creative Product Packaging Design based on Improved Guided Filtering  
  by Jin Yan 
  Abstract: In order to avoid image distortion caused by excessive processing during image detail enhancement, an image detail enhancement method for cultural and creative product packaging design based on improved guided filtering was proposed. Obtain the packaging design image of cultural and creative products, use the improved non local mean filtering algorithm to denoise the image, and repair the bad points in the image to protect important details; The multi-scale guidance filter is introduced to improve the guidance filter, and the multi-scale guidance filter is used to enhance the details of the modified image. The experimental results show that the minimum peak signal-to-noise ratio of the image enhanced by this method can reach 53.2db, the entropy value is 0.94, and the minimum average contrast of the image can reach 0.85, indicating that the image processed by this method has high quality and high detail retention rate.
  Keywords: Cultural and creative product packaging; Design image; Detail enhancement; Improved guided filtering; Lifting wavelet.
  DOI: 10.1504/IJPD.2024.10067947
   
  
• Fuzzy Comprehensive Evaluation of Product Marketing Management Performance under the Background of Data Driven  
  by Ming Yang 
  Abstract: In order to overcome the problems of low weight and score values, large fluctuations in indicator membership, and low credibility in traditional methods, this paper designs a new fuzzy comprehensive evaluation method of product marketing management performance under the background of data driven. Determine financial performance indicators, innovation performance indicators, and market competition performance indicators. Utilizing data driven technology to mine and clean performance indicators for product marketing management, combined with dimensionless evaluation indicators and consistency calculation to complete indicator data preprocessing. Build a fuzzy comprehensive evaluation model for product marketing management performance, input preprocessed indicator data into the model, and obtain evaluation results. The test results show that the weight and score values of this method are high, the fluctuation of the membership degree of the evaluation index is low, and the credibility of the comment results is high.
  Keywords: Data driven; Product marketing; Management performance; Fuzzy comprehensive evaluation; Dimensionless; Data driven technology.
  DOI: 10.1504/IJPD.2024.10067948
   
  
• Speech Recognition Interaction Control Method for Smart Home Based on Natural Language Processing  
  by Shuqing Wu 
  Abstract: In order to solve the problems of high speech recognition error rate, low success rate, and high latency in traditional methods, a new speech recognition interaction control method for smart home based on natural language processing is proposed. A first-order FIR high-pass digital filter is used for pre-emphasis of smart home voice, signal framing is achieved by adding a Hamming window, and smart home voice signal enhancement is achieved by combining a linear filter. An improved DTW algorithm is used to recognise the smart home voice. Based on the smart home voice recognition result and natural language processing technology, interactive control instructions are determined and input into a fuzzy self-tuning PID controller to achieve smart home voice recognition and control. Experimental results show that the mean recognition error rate of this method is 5.36%, the mean success rate is 97.52%, and the delay is below 0.6s.
  Keywords: Natural language processing; Smart home; Speech recognition; Interactive control; Linear filter; Improved DTW algorithm.
  DOI: 10.1504/IJPD.2024.10067949