Product Price Research Articles

Consumer Purchase Decision and Brand Image Analysis Through Product Quality and Price: Study Case Frozen Pastry in Jakarta - Indonesia

The study investigates the effects of product quality and price on the purchasing decisions of Bonpatis Danish pastry sheets, with brand image acting as a mediator. Indonesia's food and beverage industry, mainly retail, is experiencing significant growth as modern retailers like Hypermart introduce competitive products. A quantitative approach was used, applying Structural Equation Modeling (SEM) with Partial Least Squares (PLS) to data collected from 83 respondents, mainly Hypermart bakery employees in DKI Jakarta. Results indicate that product quality and price positively influence brand image and purchasing decisions. Specifically, product quality boosts brand image and directly affects purchase decisions, whereas price influences purchase decisions directly but not via brand image. The study emphasizes the role of product appearance and packaging in shaping brand perceptions and suggests improving these elements to attract more consumers. Due to a limited sample size, the study recommends future research to explore broader aspects like customer satisfaction and loyalty. Keywords: Danish pastry sheet, product quality, price, brand image, purchase decision.

Do Product Quality and Price Affect Word of Mouth and Purchase Decisions for Sharia Property?

The research examines how quality products and price influence the decisions to purchase Sharia property, with word of mouth as a mediator. It employed descriptive quantitative methods to analyze responses from a sample of 71 consumers who purchase Sharia property. For the sampling process, we utilized the purposive sampling method. To collect data, we used questionnaires and conducted interviews. Partial Square analysis - Structural Equation Modelling (PLS-SEM) was used to analyze the data. Based on the data analysis, product quality significantly and positively impacts Sharia property purchase decisions. The price of Sharia property positively influences the decision to purchase. Additionally, word-of-mouth recommendations are significantly impacted by the quality of the product, while price also has a positive effect on word-of-mouth recommendations. Product quality positively and significantly influences Sharia property purchase decisions mediated by word of mouth. The findings indicate that word of mouth positively and significantly influences purchasing Sharia property. Keywords: price, purchase decisions, product quality, word of mouth

The Effect Of Product Quality And Price On Coal Purchase Interest Through Sales Based On Non-Kai Logistics At Pt Bukit Asam, Tbk

This study aims to analyze the effect of product quality and price on coal purchase interest through non-KAI-based logistics sales at PT Bukit Asam, Tbk. The background of this research is driven by the challenges faced by the company in increasing purchase interest through more flexible distribution strategies and reducing reliance on railway transportation. The research method used is quantitative, with data collected through surveys of 150 respondents, consisting of customers and brokers. Data analysis was conducted using multiple linear regression. The results show that product quality and price positively and significantly impact coal purchase interest. High product quality has been proven to enhance customer satisfaction, while competitive pricing is crucial in attracting consumer interest. In conclusion, PT Bukit Asam, Tbk, should continue to improve service quality and offer more competitive prices to expand its market and increase sales through the non-KAI logistics system.

Exploring Green Consumerism: The Impact of Environmental Knowledge, Social Influence, and Attitudes on Millennials' Purchase Intentions

Indonesia is experiencing a demographic bonus, where millennials make up a significant portion of the productive age population. This demographic shift presents challenges in meeting labour market demands, as well as consumption patterns, particularly concerning sustainable consumption. Simultaneously, environmental issues such as climate change and unsustainable resource usage have become pressing global concerns. Millennials have a crucial role in addressing these challenges by adopting environmentally friendly behaviours, including green product consumption. However, the factors that drive millennials' green purchase intentions, particularly in Indonesia, remain understudied. This study aims to investigate the influence of environmental knowledge, environmental concern, social influence, and attitude on the green purchase intentions of Indonesian millennials. The research employs a quantitative descriptive approach, using purposive sampling to collect data from 150 millennials in Banjarmasin. Data were analyzed using Structural Equation Modeling (SEM) through the Partial Least Squares (PLS) method. The findings reveal that environmental concern indirectly affects green purchase intention through the mediating role of attitude. Additionally, social influence and environmental knowledge have significant positive impacts on both attitude and green purchase intention. The study highlights the importance of enhancing environmental knowledge and leveraging social influence to encourage sustainable purchasing behaviour among millennials. Marketers can use these insights to design effective strategies that promote eco-friendly products to this demographic. Future research could explore other factors, such as perceived product quality and price sensitivity, to gain a more comprehensive understanding of green consumer behaviour.

Research Progress on the Quality, Extraction Technology, Food Application, and Physiological Function of Rice Bran Oil.

Rice bran oil is recommended by the World Health Organization as one of the three major healthy edible oils (along with corn and sesame oils), owing to its unique fatty acid composition and functional components. This study screened, organized, and analyzed a large number of studies retrieved through keyword searches, and investigated the nutritional value and safety of rice bran oil. It reviews the stability of raw rice bran materials and the extraction and refining process of rice bran oil and discusses food applications and sub-health regulations. Research has found that a delayed stabilization treatment of rice bran seriously affects the overall quality of rice bran oil. Compared with traditional solvent extraction, the new extraction technologies have improved the yield and nutritional value of rice bran oil, but most of them are still in the research stage. Owing to the lack of economical and applicable supporting production equipment, extraction is difficult to industrialize, which is a challenging research area for the future. Rice bran oil has stronger antioxidant stability than other edible oils and is more beneficial to human health; however, its application scope and consumption are limited owing to the product price and lack of understanding. Rice bran oil has significant antioxidant, anti-inflammatory, anti-cancer, hypoglycemic, lipid-lowering, and neuroprotective effects. Further exploratory research on other unknown functions is required to lay a scientific basis for the application and development of rice bran oil.

A new method for growing epitaxial films on foreign substrates − Bent epitaxy

In recent years, to mitigate the effects of climate change, countries’ transition to the green economy has accelerated, and thereby, the demand of semiconductor industry for wide-gap semiconductors such as SiC and GaN has increased dramatically. These semiconductors are expensive. To reduce the price of the final product, industrial production of thin epitaxial films of sought-after semiconductors on accessible and cheap substrates, such as Si and sapphire, is being developed. When growing epitaxial films on foreign substrates, the resulting heterostructure bends, becomes concave or convex, due to a mismatch between the coefficients of thermal expansion (CTE) of the substrate and the epitaxial film. As a result, the quality of the epitaxial film deteriorates and further processing of the resulting heterostructures in production lines becomes difficult or even impossible. The essence of the proposed new method is that the epitaxial film is grown not on a flat, but on a pre-curved substrate with the expectation that after cooling the fabricated heterostructure to room temperature, the heterostructure will take a flat shape due to the difference in the CTE of the epitaxial film and the substrate. A round bimetallic plate, located under the substrate, bends the substrate in the required direction to the desired value at the growth temperature, and gradually reduces the bend of the fabricated heterostructure during cooling, in proportion to the thermal contraction of the epitaxial film. This allows obtaining qualitative and flat epitaxial films, regardless of the material of the substrate or epitaxial film and the diameter of the substrate or thickness of the epitaxial film, without any buffer layers or carrying out any additional operations and costs.

Pengaruh Kualitas Produk dan Harga terhadap Minat Beli Ulang Produk Blush On Wardah di Kota Cimahi

This study tries to investigate the influence between product quality and price on the desire to repurchase Wardah blush products in Cimahi city. This study applied a questionnaire in its research technique and involved 90 people who had used Wardah blush products in Cimahi. Purposive sampling is a nonprobability sampling approach. Validity and reliability tests, as well as traditional assumption tests and multiple regression, were used in the analysis. Each of the three research hypotheses proposed was supported by empirical evidence. As an outcome of increasing quality of the assessed object's quality and assisting the assessed parties in their business growth, this study is meant to be useful to future comparable studies and the assessed parties.

Pengaruh Kualitas Produk, Harga, Kesadaran Merek dan Citra Merek terhadap Keputusan Pembelian (Studi pada pembeli Honda Beat di Purwokerto)

The purpose of this study was to test and determine the effect of product quality, price, brand awareness, as well as brand image on purchasing decisions for Honda Beat motorbikes in Purwokerto. In this study, the population was people who bought Honda Beat motorbikes in Purwokerto with a total of 100 respondents as samples. The data used is primary data, the sample is taken with the implementation of non-probability sampling with purposive sampling as the sample type, then the data is collected using a questionnaire. Quantitative research was applied in this study as a data analysis method using multiple linear regression with the use of the SPSS version 24 programme. The findings of this study reveal that simultaneously product quality, price, brand awerness and brand image have a positive and significant influence on purchasing decisions for Honda Beat motorbikes in Purwokerto city. While partially product quality, brand awareness and brand image have a positive and significant influence on purchasing decisions. But price has no influence on purchasing decisions for Honda Beat motorbikes in Purwokerto city.

Predicting smartphone prices using machine learning algorithms

This study investigates the prediction of smartphone prices using machine learning algorithms, motivated by the increasing demand for accurate pricing information in the highly competitive and rapidly evolving mobile phone market. With the proliferation of smartphones and the constant introduction of new models with varying specifications, it is crucial for consumers, retailers, and manufacturers to have a reliable method for estimating prices based on technical features. Accurate price prediction can assist consumers in making informed purchasing decisions, retailers in setting competitive prices, and manufacturers in optimizing production costs and pricing strategies. Utilizing Decision Tree Regression, Support Vector Regression (SVR), Random Forest Regression and Convolution Neural Network (CNN), the research investigates the efficacy of these methods in estimating prices accurately. Principal Component Analysis (PCA) is applied to reduce dimensionality and enhance model performance. Through rigorous experimentation and hyperparameter tuning, Random Forest Regression emerges as the most effective method, achieving the lowest Mean Squared Error (MSE) and the highest R-squared (R) score. The findings highlight the potential of ensemble learning techniques in addressing complex prediction tasks.

Impulsive Buying Behavior Towards Livestream Shopping through S-O-R Framework: An Islamic Economic Perspective (Case Study of the Central Java Muslim Community)

This study aims to analyze the factors that cause impulsive buying behavior towards livestream shopping through the Stimulus-Organism-Response (S-O-R) framework. Methods of data collection are done through a questionnaire. The research population includes the Muslim community of Central Java who have purchased products in livestream shopping with a sample of 220 respondents. The analysis tool used is SmartPLS 3.2.9 using the Structural Equation Modeling – Partial Least Squares (SEM-PLS) analysis method. The results of the analysis show that the stimulus factors which include interpersonal interaction, discount vouchers, and flash sales have a positive and significant effect on the perceived enjoyment of livestream shopping in the Muslim community of Central Java. In addition, the stimulus factors in the form of purchase convenience, product usefulness, and product price also positively and significantly affect the perceived usefulness of livestream shopping in the Muslim community of Central Java. As for the variables which are organisms, including the perceived enjoyment of livestream shopping and the perceived usefulness of livestream shopping, both have a positive and significant effect on the impulsive buying behavior of the Muslim community in Central Java which is the response in this study.

Integrated Pricing and Inventory Decisions for Product Quality-Driven Extended Warranty Services

Extended warranty services have become increasingly important for both manufacturers and retailers, offering avenues for new profit sources and growth opportunities. Focusing on the multiple effects of product quality, this study develops a two-period supply chain decision model to analyze the effects of product quality, pricing, and inventory management in the context of extended warranty services. Using a Stackelberg dynamic game model, this study examines the interaction between a manufacturer and a dominant retailer who provides extended warranties. The results indicate significant differences in optimal decisions between centralized and decentralized supply chains, especially concerning pricing and inventory control. Introducing a “quality cost-sharing” contract enhances product quality and improves coordination, leading to increased profits for both the manufacturer and the retailer. Numerical simulations confirm that the cost-sharing contract effectively balances product quality improvements with supply chain profitability.

Implementation of E-Commerce for Andika Jeans with PHP, MySQL, and SDLC for Web-based Applications

The website has information about the product's name, price, and specifications, which aims to make it easier for customers to choose the product they want to buy. This website is exclusively for men's jeans. This men's jeans E-Commerce Website contains information about products for men's needs. Andika Jeans previously used conventional methods, where customers had to come to the store to see the product. With these problems, the Andika Jeans website was created. The method used in this writing is SWLDC, which has several stages: analysis, design, implementation, and trial. The conclusion that can be drawn from this website is that it aims to get information about the available products so that visitors can easily choose products that meet their needs. This website has been hosted so that customers can access it and can also place and confirm orders. This website has been tested in several browsers and devices, and the results of this website function very well; this website can be accessed via http://widi-system.co/andikajeans/.

New control variates for pricing basket options

Abstract Accepted by: Giorgio Consigli Accurate pricing of basket options, which are financial derivatives on multiple underlying assets, is a challenging and practically important task for financial institutions. We propose several new control variates for accurate, fast and efficient pricing of basket options. The first approach to deriving new control variates is the use of Hermite polynomial approximation of appropriate function of the underlying asset prices, which leads to a Black–Scholes-like analytic solution. This approach is new in the option pricing context and opens up new possibilities in derivative pricing. Further control variates are analytically derived using Jensen’s inequality in one case, and distributional properties of multivariate Wiener processes in other cases. All the newly proposed control variates are shown to lead to excellent variance reduction in numerical experiments based on realistic data. The proposed methods are novel, computationally simple and have a strong potential to replace more conventional methods, such as the geometric lower bound in simulation-based pricing of basket options and similar products used in financial risk management.

A netnographic analysıs of tourists’ memorable tourısm experıences: the case of historical Egyptian (Spice) Bazaar ın Istanbul

Purpose To provide visitors with a variety of experiences, tourism is a collection of activities that might leave a lasting impact on them. Anticipating and understanding what makes visitors memorable can give destinations and tourism marketers a competitive advantage. Regarding this, the purpose of this study is to investigate the memorable tourism experiences of international tourists who have visited the Egyptian (Spice) Bazaar in Istanbul. Design/methodology/approach The comments made by travelers from abroad on TripAdvisor following their experiences were examined using a netnographic analysis methodology. The data were collected from the most recent to the oldest comments posted on tourist experiences about historical Egyptian (spice) bazaar (n: 825). Findings In line with the findings obtained from the reviews examined, six components were determined that make the tourists’ experiences memorable: ambience (1), novelty (2), hedonism (3), local culture (4), knowledge (5) and price (6). Originality/value The memorable Egyptian (Spice) Bazaar experiences of international tourists analyzed within the scope of the research were in line with the dimensions of novelty, hedonism, knowledge and local culture of the study conducted by (Kim & Ritchie, 2014); ambience and product price were found to be the two different dimensions. It can be stated that results of the study can help to develop effective strategies to improve the competitiveness of the destination.

Motor Insurance Claim Frequency Prediction Using XGBoost

Insurance claim frequency modelling is an important task for non-life insurers, this together with other variables forms an important part of product pricing and risk management. The traditional frequency models such as Poisson, Negative Binomial and Zero Inflated models have several weakness such as scalibility issues, overdispersion and independence assumptions for large datasets and therefore not ideal to use when dealing with complex and unstructured data. Extreme gradient Boosting Algorithm (XGBoost) is an ensemble learning which has the capacity to effectively handle big complex and unstructured insurance data. XGBoost creates tree-based models by iteratively fitting decision trees to the residuals of the previous predictions, effectively reducing the error in each iteration. This research utilized and explored the XGBoost algorithm to process motor insurance claims large dataset in-order to predict the frequencies of insurance claims, that is 0,1,2,and 3. Using this algorithm we aim to enhance the accuracy of predictions that will yield better estimates for improved risk assessment and pricing of insurance products. Cross validation was performed to assess the true performance of our model. Cross validation results showed that XGBoost models for the claim frequency had a RMSE estimate of 0.949, MAE of 0.7741 and RSQ 0.781. This demonstrated a strong predictive performance, with an RMSE of 0.949 and an MAE of 0.7741, indicating a low average error in the predictions.The RSQ of 0.781 suggests further that the model explained a significant proportion of variability of the insurance data. Our model was evaluated with a confusion matrix. The results of the confusion matrix showed that for the frequency 0 99.59% of cases were correctly predicted, frequency 1 94.01% were correctly predicted and frequency 2 84.80% and finally frequency 3 only 40.96% of the observations were correctly predicted.These results highlights the potential of XGBoost as a robust modeling technique for handling big data and accurately predicting insurance claim frequency. The results corroborate with other studies that XGBoost is an invaluable tool for insurance companies.

Prefer cheap or expensive products? Shopping stage matters.

E-commerce platforms generally provide consumers with the function of virtual shopping carts to help them store interested products. Although about 80% of online consumers intends to purchase after adding products to their shopping cart, the abandonment rate of cart products has been up to 70%. It is important to understand how to improve consumer attitude toward product both before and after cart use. Building on the relevant literature and the consumer shopping goal stages theory, this study aims to examine the effects of product price, as one of the most indispensable and important information in online shopping, on consumer attitudes toward product at different decision-making stages in online shopping (i.e., add-to-cart stage and place-an-order stage), and the mediating roles of perceived product quality and monetary sacrifice. The findings from behavioral experiment suggest that high price leads to a more positive attitude toward product at add-to-cart stage by strengthened perception of high product quality, while results in a less positive product attitude at place-an-order stage because of the enhanced perception of monetary sacrifice. Both theoretical contributions and practical implications are discussed.

Predicting e-commerce product prices through the integration of variational mode decomposition and deep neural networks

Product prices frequently manifest nonlinear and nonstationary time-series attributes, indicating potential variations in their behavioral patterns over time. Conventional linear models may fall short in adequately capturing these intricate properties. In addressing this, the present study leverages the adaptive and non-recursive attributes of the Variational Mode Decomposition (VMD) methodology. It employs VMD to dissect the intricate time series into multiple Intrinsic Mode Functions (IMF). Subsequently, a method rooted in the minimum fuzzy entropy criterion is introduced for determining the optimal modal number (K) in the VMD decomposition process. This method effectively mitigates issues related to modal confusion and endpoint effects, thereby enhancing the decomposition efficacy of VMD. In the subsequent phase, deep neural networks (DNN) are harnessed to forecast the identified modes, with the cumulative modal predictions yielding the ultimate e-commerce product price prognostications. The predictive efficacy of the proposed Variational Mode Decomposition-deep neural network (VMD-DNN) decomposition model is assessed on three public datasets, wherein the mean absolute percentage error (MAPE) on the E-commerce Price Prediction Dataset and Online Retail Dataset is notably low at 0.6578 and 0.5414, respectively. This corresponds to a remarkable error reduction rate of 66.5% and 70.4%. Moreover, the VMD-DNN decomposition model excels in predicting e-commerce product prices through DNN, thereby amplifying the VMD decomposition capability by 4%. The VMD-DNN model attains superior results in terms of directional symmetry, boasting the highest Directional Symmetry (DS) score of 86.25. Notably, the forecasted trends across diverse price ranges closely mirror the actual trends.

Deriving Priorities: Analytical Hierarchy Process (AHP) Approach (Case Study Of Traditional Gedogan Weaving Craft Products, Ranggo Village, Dompu, West Nusa Tenggara)

The objective of this study is to use the Analytical Hierarchy Process (AHP) method to prioritize alternative marketing strategies for traditional weaving handicrafts in Ranggo Village, Dompu, West Nusa Tenggara. The data for this study came from the questionnaire that traditional weaving craft business owners received. AHP ranks five criteria according to their weight: product, price, promotion, market segmentation, and market position. The study's findings show that the product has the most weight (1.98), followed by the price (1.49), market segmentation (0.99), promotion (0.71), and market position (0.41). In general, the research indicates that the marketing strategy of Gedogan's traditional weaving craft products is characterized by the following priority orders and critical components: product quality, price, market segmentation, promotion, and market position.

Farmers’ Perception and Financial Profitability of Mustard Production in Bangladesh

The study was undertaken to assess farmers’ perception and explore the factors affecting farmers’ decision to adopt mustard production along with estimate financial profitability and identify potentials and problems of mustard production. Based on stratified random sampling, 120 farmers were interviewed using a structured questionnaire to collect primary data from different villages of Ullahpara upazila under Sirajganj district of Bangladesh. A combination of descriptive statistics, mathematical and statistical technique was used to analyze the data and to achieve the objectives. The study depicts that the highest number of the respondents (35%) belong to the 31-45 age group. Seventy two percent respondents were small farmers having land less than 1.0 hectare and they allocated 34% of their farm area for mustard production. Financial profitability analysis shows that mustard production was profitable on both variable cost and total cost basis and its benefit cost ratio (BCR) was more than one. In case of farmers perception, it was revealed that short duration crop, consumers’ preferences, product price, extension services and sharing of work among household members were the main driving factors for mustard production. Applying dichotomous logistic regression model, four factors namely, farmers’ age, number of family members, experience and farm size were found as significant determinants of adoption of mustard production. Large domestic market, limited use of high-yielding varieties, growing demand for mustard oil and attack of pests and diseases were found as important strength, weakness, opportunities and threats of mustard production, respectively. Finally, the study recommends that there are ample opportunities to enhance mustard production by ensuring access to quality seeds, adopting new technologies, securing fair prices, providing input subsidies, and improving institutional credit facilities with favorable terms and conditions. Bangladesh J. Nuclear Agric, 38(1): 65-80, 2024

Retailer-manufacturer partnerships in E-commerce: Dual product strategy and market share dynamics

A new practice among online retail platforms, e.g., Amazon and Wayfair, is to offer their own private label product and a substitutable exclusive manufacturer product. We employ a game theoretic approach to examine conditions under which a retailer and a manufacturer find it optimal to enter into such a partnership. Our analysis reveals that a retailer finds it profitable to partner with a manufacturer with one of two profiles. The first is a manufacturer with low unit production and holding costs and large capacity, and the retailer gives the manufacturer most of the market share. In this case, the retailer uses a low private product price and marketing effort to pressure the manufacturer to set a low exclusive product price, which increases the manufacturer's revenue and the retailer's fees. The second is a manufacturer with a large consumer base, high unit production and holding costs, and small capacity. For this profile, the retailer takes most of the market share by offering a low private product price, and the manufacturer is unable to counteract the retailer's low private product price and marketing effort. The partnership results in a lower price when the marketing effort is costly and the retailer relies on private product price, intensifying price competition. Under some conditions, the retailer's profit may decrease in his share of the manufacturer's revenue. Also, the retailer may increase the marketing effort and decrease the private product price, not to take market share, but to pressure the manufacturer to decrease price.