Indifference Curves Research Articles

Children's Preference Patterns and Opportunities for Sensory‐Led Reformulation of Chocolate Chip Cookies

ABSTRACTIn the context of the rising prevalence childhood obesity, this study investigated children's preferences for chocolate chip cookies, a high impact food category. The objective was to explore drivers of preferences and to identify potential pathways for reformulation. A home use test was conducted in four cities in France with 151 school‐aged children on eight commercial chocolate chips cookies. An external preference mapping analysis was performed using descriptive analysis data from a trained sensory panel and analyses of cookies' composition and physicochemical properties. Texture emerged as a critical driver of preference, with a majority of children favoring softer textures. Preferences were not particularly driven by sweetness, challenging the assumption that children always prefer the sweetest products. Cluster analysis revealed distinct preference patterns that were linked to children's BMI and demographic factors. Notably, children with higher BMIs showed preferences for sweeter cookies and higher sugar content.

User Preference Maps: Quantifying the Built Environment

The built environment in which we live holds the potential to provide life experiences that allow pedestrians to observe, feel, learn, and grow through their surroundings in everyday urban spaces. If a city offers opportunities for careful observation and exploration according to users’ preferences, it will become more appealing to many people. This study selected Midtown, New York, as the research site and collected a total of seven datasets based on 30 intersections in the area. The data, categorized into three main areas—activity, comfort, and natural elements—were evaluated, visualized, and restructured using a path exploration algorithm to produce a final user-based map. For this, 3D modeling software Rhino version 7, visual programming tool Grasshopper, and Grasshopper verion 2023 plugin programs were used. The final result included 3D route information, quantitative measurement data, and multidimensional visual materials. This approach presents an alternative to traditional route navigation based on uniform criteria and, through data-driven design, is believed to ultimately enhance walkability, activate urban spaces, and contribute to the development of sustainable cities. The scope of related research can further expand as the targets, duration, and methods of data collection continue to evolve and as case studies in various cities increase.

Political Preferences Of Young Generation (Gen Y And Gen Z) Ahead Of The Contestation Of The 2024 West Java Governor And Vice Governor Elections

Gen Y (millennials) and Z are predicted to have a vital role in the conduct of General Elections, this cannot be separated from quantitative data-based considerations, specifically their very large proportion of the total number of Voters. Within the context of the 2024 West Java Governor and Vice Governor Elections, such figure is realized to reach 54 percent. Given such background, it is not surprising that all components of interest, in this case the electoral committees, electoral candidates, and including academics are competing in making a more detailed map of the political preferences and voting behavior of gen Y and Z. This study uses a qualitative method and critical discourse analysis approach. This study seeks to show a number of factors in relation to the political preferences of gen Y and Z in the implementation of democratic mechanisms, specifically General Elections. These political preferences of gen Y and Z are mapped out through survey data, those survey data are analyzed in depth through the theory of voting behavior. This study is expected to be a reference for electoral committees and electoral candidates in the formulation of strategic policies to improve gen Y and Z's participation and involvement in electoral politics.

OligoFormer: an accurate and robust prediction method for siRNA design.

RNA interference (RNAi) has become a widely used experimental approach for post-transcriptional regulation and is increasingly showing its potential as future targeted drugs. However, the prediction of highly efficient siRNAs (small interfering RNAs) is still hindered by dataset biases, the inadequacy of prediction methods, and the presence of off-target effects. To overcome these limitations, we propose an accurate and robust prediction method, OligoFormer, for siRNA design. OligoFormer comprises three different modules including thermodynamic calculation, RNA-FM module, and Oligo encoder. Oligo encoder is the core module based on the transformer encoder. Taking siRNA and mRNA sequences as input, OligoFormer can obtain thermodynamic parameters, RNA-FM embedding, and Oligo embedding through these three modules, respectively. We carefully benchmarked OligoFormer against six comparable methods on siRNA efficacy datasets. OligoFormer outperforms all the other methods, with an average improvement of 9% in AUC, 6.6% in PRC, 9.8% in F1 score, and 5.1% in PCC compared to the best method among them in our inter-dataset validation. We also provide a comprehensive pipeline with prediction of siRNA efficacy and off-target effects using PITA score and TargetScan score. The ablation study shows RNA-FM module and thermodynamic parameters improved the performance and accelerated convergence of OligoFormer. The saliency maps by gradient backpropagation and base preference maps show certain base preferences in initial and terminal region of siRNAs. The source code of OligoFormer is freely available on GitHub at: https://github.com/lulab/OligoFormer. Docker image of OligoFormer is freely available on the docker hub at https://hub.docker.com/r/yilanbai/oligoformer.

Liking and sensory determinants of perceived naturalness and healthiness. A study on pizzas with young adults in a natural eating environment

This study aims to determine the sensory drivers of liking, perceived naturalness, and healthiness of pizzas in an ecological setting. The approach consisted in evaluating beliefs, perceptions, and liking by consumers of a large range of 16 pizzas representative of the French commercial market and selected on environmental and nutritional criteria. Sixty-four pizza consumers were invited to take 16 different meals in real-setting conditions of consumption at a university restaurant with pizza as the main course. Pizzas were also characterized by a trained sensory panel. This study confirms a positive link between liking and healthiness and naturalness, even though individual differences were evident, with some consumers prioritizing naturalness while others favored healthiness. Frozen pizzas are perceived as highly processed but were well liked when evaluated in the dining condition. Overall, preferences were mainly driven by the presence of multiple pieces of vegetables, sauce, and color. Drivers of dislike were mostly related to texture (stickiness and difficulty to cut). Although preference, naturalness, and healthiness mappings are relatively similar, our models show a discrepancy in the way texture drives preferences and perceived healthiness. This suggests that texture may play a critical role in the trade-offs between liking and healthiness, and that there may be a fine line between what is considered a desirable texture and a healthy texture. Individual regressions provided insights into consumer diversity, while combining sensory profiling with consumer-based methods offered a comprehensive understanding of product perception.

Validation of Optimization Methods for Sensory Characteristics Using Rate-All-That-Apply and Intensity Scales: A Case Study of Apple Juice.

Preference mapping (PM), which integrates consumer and descriptive analysis (DA) data to identify attributes that drive consumer liking, is widely employed for product optimization. However, a limited group of trained panelists cannot fully represent the diverse consumer population or reliably predict market acceptance. Consequently, numerous studies have explored consumer-based methodologies as potential replacements for DA; however, their efficacy for product optimization remains limited. Therefore, this study was conducted to explore the potential of optimizing products using two consumer-based profiling techniques as alternatives to DA in external preference mapping (EPM). Overall, 8 trained panelists profiled 12 sensory attributes of 7 commercial apple juices, whereas 160 consumers assessed the same attributes using a 5-point rate-all-that-apply (RATA) scale and a 10 cm intensity scale (IS). Danzart's response surface ideal modeling was employed to identify optimal products using DA, RATA, and IS through barycenter calculations, focusing on three products from the original consumer test located around the group ideal point. Overall, the ideal products of the group and their sensory characteristics were successfully identified using DA, RATA, and IS. Regarding sensory intensities, high concordance was observed between DA and RATA (Rv = 0.92) and between DA and IS (Rv = 0.91). Overall liking and preference scores for products mixed at the optimal ratio for each method showed no significant differences in preference among the ideal products identified using DA, RATA, and IS. This study suggests that both RATA and IS are viable alternatives to DA in EPM for identifying ideal sensory profiles.

Innovation and Path to Inclusiveness in Developing Countries

This study examines the effect of innovation on inclusive growth in 63 developing countries and employs System Generalized Method of Moments (GMM) estimation techniques. The study used the global innovation index to measure innovation. In addition, we construct an index of inclusive growth. Further, due to the complex nature of inclusive growth, using a single index may not provide the full picture. So, for substantial empirical support, the study uses a set of dimensions of inclusive growth separately. The empirical results show a positive relationship between the measures of innovation with inclusive growth. Further, the study also constructs indifference curves for selected developing economies to measure the inclusiveness in growth. Finally, it is suggested that developing economies should put in policies to promote innovation activities that include poor segments of society to improve the impact of innovation on inclusive growth.

Milking the label: The impact of category labels on consumer liking and category fit of non-dairy milks

The influence of labels on expectation is well documented, but the effect of category labels on consumer perception is not well understood. The fast pace of emerging product categories highlights the importance of ensuring that category labels meet consumer expectations. To examine the impact of category expectations on liking, 384 consumers were assigned one of four conditions where they were told they were drinking either milk (broad condition), plant-based milk (intermediate condition), almond milk (specific condition), or given no information (control group). All groups were given six almond milks and asked to rate their liking on a 9-point hedonic scale. Consumers in the broad, intermediate, and specific conditions were also asked to rate category fit on a 9-point Likert scale. Category label had a significant impact on overall liking, with the specific condition having significantly higher liking than the control, as well as a significantly higher liking than the intermediate and control conditions. External preference mapping showed that the sensory drivers of liking were constant across the four conditions, but the sensory drivers of category fit changed depending on which category condition participants were part of. In the broad condition, sweetness and vanilla flavour contributed to category fit. Creaminess was more important for the intermediate condition, while nutty and roasted flavours determined category fit for the specific condition. Our results suggest that increased specificity in category labels can increase product liking, underscoring the importance of sensory evaluation for understanding the link between category labels and consumer perception.

Sensory Characterization of Conventional and Diets in Sugar Guava Sweet by Check-All- That-Apply and Emotion Measurement Methods

This study aimed to investigate the sensory characterization of commercial diets in commercial guava sugar samples by the Check-all-that-apply (CATA) and Emotion Measurement methods. The samples were evaluated by 120 consumers using the CATA method, (CATA) Ideal, Acceptance Test, Purchase Intention, Emotion Measure, and Ideal Test in relation to the sweetness and taste of guava, allowing the construction of two External Preference Maps aimed to associate the results from the overall impression with the terms from CATA and the emotional responses. The samples of conventional C1, C2, and C4 showed greater correlations with the descriptors terms and positive emotions, and the samples of diets D2 and D4 showed greater correlations with the descriptors terms and negative emotions, which was also observed in the acceptance and purchase intention tests, showing the consumers preference for the product with high caloric value.

Impact of adding papain to sous vide cooking on texture and sensorial traits of marinated semitendinosus beefsteaks.

Sous vide meat is an emerging food category, the consumption of which has increased owing to greater convenience, sensory traits, elderly consumers acceptance, and low-cost cuts use. However, required prolonged thermal treatment to achieve desired tenderness, impact energy-consumption besides triggering lipid oxidation, undesired off-flavors, and cooked meat profiles. Using a response surface methodology (RSM), this study evaluated the effects of the vegetal proteolytic papain (0 to 20 mg/kg) and low-temperature sous vide cooking (SVC) time (1 to 8 h at 65°C) in low-value marinated M. semitendinosus beefsteaks on technological characteristics associated with tenderness, and lipid oxidation. Additionally, the sensory profile traits of the pre-selected treatments were described using check-all-that-apply (CATA) and preference mapping. Shear force (WBsSF) was reduced with greater papain addition, whereas higher cooking losses (CL) were observed with longer SVC cooking times. Both the released total collagen and TBARS values increased with increasing papain concentrations and SVC times. Combining high levels of papain (>10 mg/kg) and SVC time (>6 h) resulted in lower WBsSF values (<20 N) but higher CL (>27%) and the CATA descriptors "aftertaste" and "mushy." The optimized conditions (14 mg/kg papain; 2 h SVC) also reduced WBsSF values (<26 N) with lower CL (<20%) and were most preferred and described as "juicy" and "tender" by consumers. Observed results suggest that combined mild SVC and papain may potentiate tenderness, conjointly favor juiciness and oxidation, further representing a promising tool for reducing SVC time without compromising valued sous vide sensory traits.

ANALISIS POSITIONING COFFEE SHOP LOKAL DI WILAYAH JABODETABEK

This research aims to examine the concept of coffee shop brand positioning in Indonesia, namely Kopi Janji Jiwa, Kopi Kenangan, Point Coffee, Kopi Lain Hati, and Kopi Kulo. The data collection method used was by distributing questionnaires online with samples taken using non-probability sampling techniques with purposive sampling to respondents who enjoy 5 coffee shop brands in Indonesia. Descriptive testing is used to analyze the influence of positioning on the coffee shop brand. The data used in this research is primary data obtained from distributing questionnaires to 41 respondents. This research uses cross sectional research, namely a research method carried out over a relatively short time and in a certain place. The data analysis method used in this research is to analyze the attributes owned using the attribute based approach. In this research, three outputs will be produced, namely canonical discriminant function, preference map, as well as market strategy and marketing mix.

Traditional preference mapping and computational machine learning techniques: A comparative study of approaches to guide product development

Preference mapping, a well-known set of multivariate statistical techniques, has become widely adopted due to its demonstrated effectiveness as a powerful tool in guiding the development of new products and enhancing existing ones. Recent advancements in open-source software and computational capabilities have introduced a new set of accessible tools with the potential to address limitations associated with traditional methods. This study introduces an alternative algorithm for building predictive models, employing regularized regression in combination with Multivariate Adaptive Regression Spline (MARS). These methods make fewer assumptions about the relationship between predictors and the target and can easily capture complex and non-linear relationships. Additionally, the study presents a robust and systematic alternative approach for calculating optimum profiles and performing simulations. The paper aims to compare this new set of tools, referred to as computational machine learning techniques, with a well-established and widely recognized method − PrefMap based on Partial Least Squares Regression. The primary intention of the comparison between computational machine learning and one example of a traditional approach is not to determine a winning methodology, but rather to enhance awareness and deepen the understanding of this emerging family of models and techniques now available to sensory and consumer scientists. Results are assessed side by side to reveal their similarities and differences in terms of predictive power, drivers of liking, and the optimal profile aspects, and a list of practical considerations is provided at the end, enabling a better understanding of the trade-offs between the two approaches presented here.

Two hours to the office, two minutes to the kitchen table: trends in local public-transportation expenditures from 2018 to 2021

The COVID-19 pandemic altered consumer spending on public transportation, including both intracity (mass transit, taxi, and limousine) and intercity (air, ship, bus, and train). According to the Consumer Expenditure Surveys, spending on public and other transportation fell 66.3 percent in 2020. With shifts toward virtual work and school attendance, many commuters’ 2 hours to the office became 2 minutes to the kitchen table. This article examines changes in dollars spent for public transportation, mainly intracity mass-transit spending from January 2018 to December 2021, among various unique demographic groups: urban and rural residency, occupation type, educational attainment, and selected metropolitan statistical areas. Essential workers generally were unable to telework. Simultaneously, private-transportation costs declined in 2020 for all, while affordability rose for many. Gasoline prices fell 46 cents (17 percent) per gallon in 2020, according to the Consumer Price Index. Furthermore, average annual income fell for certain occupational groups and rose for others (income rose 2 percent for all consumer units). A model of indifference curves and budget constraints is used to show which members of specific education groups are likely to substitute private for public transportation. Results in 2020 show that income growth and lower private-transportation costs compared with those of public transportation resulted in increased private-transportation spending of up to 5 percent, with accompanying public-transportation spending reductions of 40 to 50 percent. Although intracity mass-transit spending rebounded in 2021, it did not reach prepandemic levels.

Participatory mapping of tree equity, preferences, and environmental justice in Portland, Oregon

In this study, we examine community lived experiences, preferences, and narratives about tree equity in Portland, Oregon. Using an environmental justice framework combined with participatory mapping, focus group discussions, and semi-structured interviews, we examine values, perceptions of canopy cover, and everyday relationships with trees across different racial and socio-economic backgrounds. Results show that participants from neighborhoods with histories of investment and privilege had different lived experiences compared to those with histories of disinvestment and marginalization. While participants overall valued trees, concerns about tree-related risk and safety varied in ways that reflected racial and class identities. Furthermore, memories and historic knowledge shaped perceived tree equity but contemporary problems such as tree removal, maintenance policies, and gentrification were viewed as barriers to achieving more equitable outcomes. Our study underscores the importance of centering community experiences, values, and needs along with tree programs that can alleviate barriers to tree care and maintenance.

A model for the noninvasive, habitat-inclusive estimation of upper limit abundance for synanthropes, exemplified by M. fascicularis.

Accurately estimating population sizes for free-ranging animals through noninvasive methods, such as camera trap images, remains particularly limited by small datasets. To overcome this, we developed a flexible model for estimating upper limit populations and exemplified it by studying a group-living synanthrope, the long-tailed macaque (Macaca fascicularis). Habitat preference maps, based on environmental and GPS data, were generated with a maximum entropy model and combined with data obtained from camera traps, line transect distance sampling, and direct sightings to produce an expected number of individuals. The mapping between habitat preference and number of individuals was optimized through a tunable parameter ρ (inquisitiveness) that accounts for repeated observations of individuals. Benchmarking against published data highlights the high accuracy of the model. Overall, this approach combines citizen science with scientific observations and reveals the long-tailed macaque populations to be (up to 80%) smaller than expected. The model's flexibility makes it suitable for many species, providing a scalable, noninvasive tool for wildlife conservation.

Sensory profile and consumer perception of plant-based non-dairy milk jellies

This study focused on the organoleptic characteristics and consumers’ purchasing decision of milk jellies made with lactose-free cow milk and various plant-based non-dairy milk, including almond milk, coconut milk, oat milk and soymilk. All milk alternatives were measured for the CIE color system. The hedonic scale was used to evaluate product liking on appearance, color, taste, flavor, texture, and overall acceptability–still, the scaling test assigned for the purchasing intention. The results showed that milk alternatives' lightness, taste, and flavor preference affected consumers' liking and purchasing decisions for nondairy milk jellies. Preference mapping showed the relevance of the high lightness of milk alternatives and product acceptability. Coconut milk jelly was the most preferred, as did lactose-free milk jelly, while soymilk jelly was the least.

Price theory, loanable fund theory, and indifference curves: theorizing authority through misuse of mathematics, logic and improbable assumptions

Economist Adam Smith‘s study ( 1776 ) initially was ‘Political Economy ‘, then knowledge used for eradicating poverty, want, and unemployment and then to study inflation, stagnation, recession, etc. Thus it became the science of economics. Economist J.M. Keynes viewed ‘ Political Economy and added three definitions a) Wealth b) Welfare and c) Scarcity in the study. But Richardo shifted from production and distribution of wealth to “ The produce of earth - all that is derived from its surface by the united application of labor, machinery, and capital. Economist T.R. Malthus ( 1820 ) joined to add one more dimension of wealth “ material(productive ) wealth and immaterial ( unproductive ) wealth “. L. Robbins and others criticized the neglect of immaterial wealth and stressed the importance of services. Modern economists are of the view that immaterial wealth - services are essential to increase production, productivity, and good health. Economist Alfred Marshall stated, “ Political Economy or Economics is the study of mankind in the ordinary business of life; it examines that part of individual and social action which is most closely connected with the attainment and the use of the material requisites of well-being “. Robins ( 1931 ), defined economics based on i) Unlimited wants ii) Scarce means, and iii) Alternative uses of means. This is the historical background of definitions in Economics in general. With utopian and illogical assumptions, passing no mathematical rigor, ignoring very vital parameters, and free use of mathematical figures as ornaments the topics of a) price theory b) loanable fund theory, and c) indifference curves have no theories, no precision but are only verbose and literary...The author feels that these topics do not deserve a place in 21st-century Economics.

Physicochemical, colour, microbiology, sensory and mineral attributes of set-type yoghurt produced from Gundelia tournefortii L. and its gum

The present study aimed to investigate the production of yoghurt in which the parts of the Gundelia tournefortii L. and its gum were added to milk at levels of 3% (v/v), incubated until the pH value reached 4.7 at 42 °C and then stored at 4 °C for 21 days. The Ca, P, K, Na and Mg contents of the yoghurt sample containing Gundelia tournefortii L. proved to be higher than those found in the control sample. Acidity, acetaldehyde, viscosity, a* values of yoghurt samples increased during storage, while the volatile fatty acids, gel firmness, whey separation, water holding capacity, L* and the b* values were decreased. The lactic acid bacteria count on the 21st day was > 6 log CFU/g in all yoghurt samples. The total aerobic mesophilic bacteria decreased except for the yoghurt sample containing Gundelia tournefortii L. milk, while the yeast and mold increased. The preference map revealed that 60–80% of consumers were satisfied with the control sample and the Gundelia tournefortii L. gum sample. Gundelia tournefortii L. milk and Gundelia tournefortii L. leaves samples were also found to have acceptable scores. As a result, adding Gundelia tournefortii L. into the yoghurt turned out to have a positive impact on its sensory and functional properties and could lead to an innovative approach in the dairy product market.Graphical abstract

Constructing a MOEA approach for product form Kansei design based on text mining and BPNN

Kansei Engineering (KE) is a product design method that aims to develop products to meet users’ emotional preferences. However, traditional KE faces the problem that the acquisition of Kansei factors does not represent the real consumers demands based on manual and reports, and using traditional methods to calculate relationship between Kansei factors and specific design elements, which can lead to the omission of key information. To address these problems, this study adopts text mining and backward propagation neural networks (BPNN) to propose a product form design method from a multi-objective optimization perspective. Firstly, Term Frequency-Inverse Document Frequency (TF-IDF) and WordNet are used to extract key user Kansei requirements from online review texts to obtain more accurate Kansei knowledge. Secondly, the BPNN is used to establish the non-linear relationship between product Kansei factors and specific design elements, and a preference mapping prediction model is constructed. Finally, BPNN is transformed into an iterative prediction value of non-dominated sorting genetic algorithm-II (NSGA-II), and the model is solved through multi-objective evolutionary algorithm (MOEA) to obtain the Pareto optimal solution set that satisfies the user’s multiple emotional needs, and the fuzzy Delphi method is used to obtain the best product form design scheme that meets the user’s multiple emotional images. Using the example of electric bicycle form design could show that this proposed method can effectively complete multi-objective product solutions innovation design.

Ideal concentration of turmeric to be added to artisanal cassava flour according to consumer preference

In the artisanal manufacture of yellow cassava flour, in the North region of Brazil, it is common to add turmeric. However, there are no recommendations on this process considering the preference of consumers. The present study proposes to determine this ideal concentration of turmeric that should be added to cassava flour based on consumers’ preference. Samples were produced with 0, 0.05, 0.10, 0.15, and 0.20% concentrations of turmeric in the flour. The flours were evaluated for moisture, ash, ether extract, fiber, protein, acidity, pH, aw, and instrumental color. Sensory evaluation was analyzed in the cities of Rio Branco and Cruzeiro do Sul, state of Acre, Brazil. The addition of turmeric promoted an increase in acidity and a reduction in moisture and water activity of the flours. The intensity of the yellow color increased as higher concentrations of turmeric were added. Sensory tests using the hedonic, ideal, and purchase intention scales and internal preference mapping revealed differences between the two municipalities in terms of preference of consumers. In Rio Branco, there was a preference for flours with intermediate concentrations of turmeric, from 0.05 to 0.15%, while Cruzeiro do Sul recommended a concentration of 0.05% of turmeric.