Choice-based Conjoint Analysis Research Articles

Guideline Daily Amount (GDA) outperforms Nutri-Score in assessing healthiness. Case study with breakfast cereals

AbstractNutritional information on packaging is becoming increasingly important in the food industry. Currently, labels are seen not only on the back of the packaging but also on the front. As there are many versions of front-of-pack labels (FoPLs), the research aims to determine which helps consumers the most in making decisions about which food to include in a healthier lifestyle. Nutri-Score, Guideline Daily Amount (GDA) and Multiple Traffic Lights (MTL) FoPLs on cereals were compared using eye-tracking (ET) and choice-based conjoint analysis (CBCA). CBCA was used to assess consumer preferences and the labels and products were also ranked. Based on the results, GDA type FoPL proved to be the most useful based on conjoint analysis, ranking and the analysis of ET parameters. This label helped participants the most in choosing the product that best fits into a healthier lifestyle. The Nutri-Score label, which offers little information on a product's nutritional content, was not favourably received by the Hungarian sample, who preferred more detailed FoP labels.

Analysis of Price- and Services-Related Preferences for Nursing Homes in Japan Using a Nested Logit Model in Choice-Based Conjoint Analysis

Analysis of Price- and Services-Related Preferences for Nursing Homes in Japan Using a Nested Logit Model in Choice-Based Conjoint Analysis

Research on the Application of Conjoint Analysis in Carbon Tax Pricing for the Sustainable Development Process of China

This study aims to evaluate the preferences of Shanghai residents for four key attributes of carbon tax policies via the choice-based conjoint analysis method, with the goal of understanding the potential application of carbon tax policies in China. The findings indicate that the most critical concern for Shanghai residents is the annual cost of the ca trbonax (48.87%), followed by policy transparency (24.72%), revenue allocation (16.68%), and policy implementers (9.73%). The average willingness to pay is CNY 1435.28 annually, indicating a relatively high acceptance of carbon tax policies. Furthermore, increasing public awareness of carbon tax policies significantly enhances willingness to pay, which in turn helps increase tax revenue and promotes the development of low-carbon technologies. This study provides valuable insights for policymakers on carbon tax implementation, contributing to China’s transition to a low-carbon economy.

Gender differences in preferences for mental health apps in the general population – a choice-based conjoint analysis from Germany

BackgroundMen and women differ in the mental health issues they typically face. This study aims to describe gender differences in preferences for mental health treatment options and specifically tries to identify participants who prefer AI-based therapy over traditional face-to-face therapy.MethodA nationally representative sample of 2,108 participants (53% female) aged 18 to 74 years completed a choice-based conjoint analysis (CBCA). Within the CBCA, participants evaluated twenty choice sets, each describing three treatment variants in terms of provider, content, costs, and waiting time.ResultsCosts (relative importance [RI] = 55%) emerged as the most critical factor when choosing between treatment options, followed by provider (RI = 31%), content (RI = 10%), and waiting time (RI = 4%). Small yet statistically significant differences were observed between women and men. Women placed greater importance on the provider, while men placed greater importance on cost and waiting time. Age and previous experience with psychotherapy and with mental health apps were systematically related to individual preferences but did not alter gender effects. Only a minority (approximately 8%) of participants preferred AI-based treatment to traditional therapy.ConclusionsOverall, affordable mental health treatments performed by human therapists are consistently favored by both men and women. AI-driven mental health apps should align with user preferences to address psychologist shortages. However, it is uncertain whether they alone can meet the rising demand, highlighting the need for alternative solutions.

Unveiling risk factors influencing the selection of the Northern Sea Route: A conjoint analysis approach for Japanese shippers

This paper explores how Japanese corporations assess risks associated with using the Northern Sea Route (NSR) as a new maritime transport route in Asia and identifies measures to promote its usage. We address two key questions: (1) What risks influence shippers' route choices in maritime transport? (2) Does risk evaluation vary by cargo type and company size? Using choice-based conjoint analysis and a conditional logit model with online survey data, we identified five main risk factors influencing shippers: route unavailability rate, delay probability, piracy probability, transport costs, and war conditions, ranked in importance from highest to lowest as war conditions, delay probability, transport costs, route unavailability rate, and piracy probability. Additionally, the risk factors significantly influencing route selection were found to be robust, showing minimal variation across company size, type of trade (import/export), and the nature of the goods transported. Our findings suggest several policy implications. Diplomatic efforts are crucial for safe vessel navigation on the NSR. Government initiatives should focus on reducing transport delays through technology investments and implementing strategies to decrease NSR delay rates without increasing shippers' costs. Additionally, emphasizing the lower piracy risks on the NSR compared to Suez Canal Route could boost its attractiveness.

Lifetime deals: the role of software service offering in convincing consumers

Purpose This study aims to reveal consumer purchase intentions for Software-as-a-Service (SaaS) lifetime deals and the role of service offerings in shaping these intentions. Design/methodology/approach Lifetime deals − an aggressive market penetration strategy − have the potential to allow startups to gain market share, user base and the cash necessary for growth. However, startups need to mitigate consumer concerns for which service offering design plays a key role. Drawing on expectancy-value and signaling theories, this study developed a research model and then conducted empirical research on 2,173 consumers via choice-based conjoint analysis to reveal the critical service offering attributes for consumer utility in lifetime deals in the SaaS presentation tool market context. After using the hierarchical Bayes model to derive each respondent’s part-worth utilities for service offering attributes, the hypotheses were tested via the factor score regression method. Findings The results show that the service offering attributes of low price, refund option, human support and feature updates enhance consumer utility in SaaS lifetime deals. Three of these four attributes, namely, low price, refund option and feature updates, enhance consumers' purchase intentions by reducing their concerns about the service’s performance, seller and lifespan, respectively. Originality/value This study elucidates consumer purchase intentions for SaaS services in digital marketplaces. By investigating a widespread market entry strategy − lifetime deals − it shows consumer preferences and behavior for these deals in the fast-growing online tools market. This study also shows how startups can use lifetime deals through a well-designed service offering to mitigate various consumer concerns.

Which features of AI-based tools are important for students? A choice-based conjoint analysis

AI-based language tools such as ChatGPT have the potential to fundamentally change studying and teaching at universities. Since there have been few empirical studies on the use of AI systems by students, this article aims to analyze the use of AI in higher education. In particular, it focuses on identifying features that are important to students when using AI during their studies. For this purpose, a choice-based conjoint experiment was conducted through a survey involving over 6300 participants from German universities. The results show that students attach particular importance to the degree of scientific rigor. The optimal package for an AI-based tool for studying includes the citation of reliable or truthful sources, the detection and correction of errors in the input, a comprehensive and detailed formulation of the output, no AI-caused hallucinations and transparency of the database. These characteristics differ only slightly in group-specific analyses.

Writing restaurant menu descriptions: The influence of word choice on consumer behavior

This study examined the influence of words used in restaurant menu descriptions. Menu descriptions are typically short, communicating a great deal of information in a brief statement. Understanding the types of words that resonate most with consumers addresses a gap in menu research. Correspondingly, this study assessed how consumers process menu words to minimize ordering risk by applying a choice-based conjoint analysis approach utilizing word attributes and levels. 1500 participants were recruited to simultaneously evaluate multiple menu description variations. Findings noted that words can be classified as hedonic (emotional) or utilitarian (functional) and that utilitarian words can be further sub-categorized as experiential or descriptive. Findings support a hierarchy of word influence, and add to research literature, specifically menu design. The practical implications are that restaurateurs can improve their menu descriptions by utilizing words drawn from the most influential categories as a means of mitigating consumer anxiety.

Too much, too little? A CBC approach accounting for screening from both sides

Consumers are often assumed to use a two-stage decision process, screening out products in the first step and choosing among the remaining alternatives in the second step. When analyzing data from discrete choice studies, a compensatory decision strategy is usually presumed. Gilbride and Allenby (2004) introduced a method to model a decision process in a choice-based conjoint analysis combining the compensatory assumption with the two-stage decision process. Respondents first screen out alternatives that do not meet minimum requirements for attributes, followed by a choice between the remaining alternatives using the compensatory rule.In this paper, we extend their approach by considering not only screening with a minimum threshold but also with a maximum value for every attribute. We compare this extension to the original method by Gilbride and Allenby (2004) and a single-step compensatory model. We do so on the basis of one simulation scenario as well as three empirical conjoint datasets.The results indicate that two-sided screening is applied especially to prices. Both the original and extended models exhibit nearly identical performance. However, they outperform the one-step choice model that ignores screening in terms of fit and predictive validity.

Medial Patellofemoral Ligament Reconstruction in Adolescents: What Parents Care About.

Numerous techniques exist for pediatric medial patellofemoral ligament (MPFL) reconstruction (MPFL-R). Pediatric orthopaedic surgeons and patient families must navigate choices between allograft and autograft, incision type, and surgery cost. While previous research has found similar surgical outcomes among different MPFL-R techniques, minimal data exists on what patients and their families prefer. To engage in shared decision-making (SDM), pediatric orthopaedic surgeons must understand family preferences, including between incision type and cost. We conducted a study utilizing choice-based conjoint (CBC) analysis to explore these preferences. A survey was developed using Sawtooth Software (Lighthouse Studio version 9.2.0) to gather demographic information and preferences on surgical scenarios via CBC analysis. Anonymous participants, recruited via the Prolific crowdsourcing platform, qualified if they were US residents over 18 years of age with children aged 13 to 17. Data analysis involved the Hierarchical Bayes (HB) method to generate utility scores to determine the desirability of attributes. The study included 496 participants who prioritized surgical success (average importance 48.8%) followed by co-pay amount (21.5%), incision size (17.4%), and return to sport (12.3%). Participants earning over $200,000 annually prioritized incision size over cost (25.8% vs. 12.1%, P<0.0053). Those with incomes below $50,000 valued recovery time at a lesser extent than other income groups (10.4% than 12.3% overall importance P<0.0003). The sex of the child significantly influenced preferences: incision size was more important to parents of girls (21.1%) than boys (14.0%, P<.0001). The importance of surgery success and recovery time also differed by sex, being higher for boys (50.4%, 13.1%) than girls (47.0%, 11.7%; P=0.025, 0.026, respectively). This CBC analysis suggests parents of adolescent patients undergoing MPFL-R most value surgical success (avoiding revision surgery), followed by copay, incision size, and time to return to sport. Of note, parent income level and sex of the child significantly influenced parental preferences. We hope this information will assist orthopaedic surgeons in SDM in MPFL-R surgery. Level III.

Determining Consumer Preferences In Choosing Low Budget Accommodation Services In Medan City With Choice-Based Conjoint (CBC) Analysis

The hotel accommodation service industry in Medan City has witnessed significant growth following the pandemic, driven by increased business and tourism activities. With over 200 hotels in the city, there is a notable presence of middle-class hotels offering affordable prices. This study aims to determine consumer preferences in choosing low-budget accommodation services using Choice-Based Conjoint (CBC) analysis. The CBC method presents consumers with a series of menus featuring different hotel attributes, such as location, facilities, and price, to identify which attributes most influence their preferences. A sample of 40 respondents was analyzed to identify key factors influencing their hotel choices. The results revealed that consumers prioritize hotels located outside the central city area, with free internet service, basic room amenities, availability of a café or lounge, breakfast services, and non-smoking rooms. The study found that breakfast service is the most important attribute, followed by the availability of non-smoking rooms. These insights can help low budget hotel or managers in Medan City to modify their services to better meet consumer demands and improve market positioning.

Designing Package Labels for Upcycled Food Products in Japan: Case Study of Broccoli Stem Snack

ABSTRACT This study addresses the growing interest in upcycled foods as a solution to food loss by focusing on designing more appealing package labels in Japan. Through an online survey, we collected data on consumer attitudes and perceptions toward upcycled foods. We applied factor analysis to identify key factors and cluster analysis to segment consumers into distinct profiles. Using these insights, we conducted a choice-based conjoint analysis to extract the package design attributes most valued by consumers. Our results highlight key factors influencing purchase intentions, including food safety, innovation, and eco-friendliness. We identified two main consumer profiles: sustainability-focused and quality/safety-conscious, and innovative and socially engaged. Food safety emerged as the most crucial factor affecting purchase willingness, followed by product image and environmental considerations. The study emphasizes the importance of transparent, sustainable, and visually appealing package design in influencing consumer decisions and building long-term loyalty toward upcycled foods in Japan.

Gender Differences in Preferences for Meaning at Work

Scholars have examined whether preferences for job characteristics help explain why men and women sort into different occupations but have overlooked preferences for meaning at work. We first document gender differences in preferences for meaning in a large-scale survey covering individuals in 47 countries. We then conduct a choice-based conjoint analysis of a cohort of MBA students at a leading business school to study gender differences in preferences for meaning compared to other job attributes. We show that gender differences in preferences for meaning at work are widespread and partly explain gender differences in behavioral outcomes, including industry of work. (JEL D91, I23, J16, J24, J28)

Eliciting Customers’ Preferences in the Cooperative Insurance Industry: Evidence from the Saudi Motor Insurance Market

This research aimed to provide a better understanding and analysis of consumer patterns relative to behavioral preferences in the Saudi cooperative motor insurance market. This aim was motivated by the fact that customers’ preferences have been underexplored in this market. Thus, this paper applied a multi-attributes decision analysis methodology to analyze the decision process of purchasing or retaining cooperative motor insurance based on a discrete choice experiment and a choice-based conjoint analysis. The methodology was conducted via a designed questionnaire that asked 385 customers in the Eastern Region to choose between a finite set of decision purchase options that varied along three key attributes: type of coverage, availability of discount, and insurance premium. Sample results showed that the most important attributes were the insurance premium, followed by the type of coverage. The availability of a discount was the least important attribute; however, compared with men, women placed a higher importance on coverage and discounts. The findings can be valuable to policymakers and managers of insurance companies in designing new characteristics for cooperative motor insurance products in Saudi Arabia in line with Saudi Arabia’s Vision 2030. JEL Classification: C9, D7, C13, G22

Customer Preference Analysis on Attributes of Toyota’s EV Shuttles Using Conjoint Approach: A Business Case of the Stones Hotel Bali Collaboration Project

This study examines Indonesia’s efforts to achieve Net Zero Emissions (NZE) by 2060, with a specific focus on Bali’s pioneering initiatives to reach NZE by 2045. The research primarily investigates sustainable mobility solutions in the tourism sector as an approach to accomplish this goal. The study analyzes customer preferences for Toyota’s xEV (BEV/PHEV/HEV) shuttle services at The Stones Hotel Bali. The objective is to support the hotel in differentiating itself through sustainable practices and support Toyota Indonesia to develop xEV products that are suitable for the market. The study employs Choice-Based Conjoint (CBC) analysis to assess five key attributes: EV rent price, capacity, technology, CO2 emission reduction, and baggage capacity. The results indicate that the most significant attributes affecting customer choices are EV rent price (33.18%), capacity (24.97%), and CO2 emission reduction (18.84%) are the most influential factors in customer decision-making, followed by baggage capacity (15.63%) and EV technology (7.38%). These insights provide a foundation for developing targeted marketing programs and product offerings that align with customer preferences and Bali’s NZE goals, while supporting the broader transition to sustainable transportation in Indonesia’s tourism industry.

Deciphering the plot preferences of forest contractors when purchasing stumpage through conjoint analysis

In order to have sustainable wood value chains, it is essential to understand the factors that determine the incorporation of wood resources into them. Forest contractors are among the key players in this process. This study evaluates the preferences of forest contractors when purchasing forest parcels. The variables considered are: slope of the terrain, distance to the nearest road, parcel size, parcel shape, and the fragmentation of the surrounding land. The study area is Galicia, a region in northwestern Spain that is dominated by small-scale family forestry. An Attribute Levels Survey was designed to establish threshold values of the considered variables to afterwards perform a Choice Based Conjoint Analysis (CBCA). The CBCA allowed to analyze the preferences of forest contractors in relation to the values of these variables and their relative importance. Also, it allowed to generate a map of the level of preference for all the Galician forest parcels with individual, private ownership. The most noteworthy result of this survey was that size greatly impacts the preference of timber contractors, preceded by slope and followed by distance to roads. These results will aid in the design of landscape-scale policies in a geospatial dimension, like the promotion of forest associations, and will lead to an improvement in the sustainability of wood supply.

Optimizing Entrepreneurial Ecosystems: Insights from Choice-based Conjoint Analysis of Chinese Entrepreneurs

Entrepreneurship is pivotal for economic growth, and fostering urban entrepreneurship environments has gained significant attention from policymakers and scholars. This study investigates the importance of different attributes within Entrepreneurial Ecosystems (EE) and their impact on regional entrepreneurship. Using Choice-based Conjoint Analysis (CBCA), preferences of 550 Chinese entrepreneurs were examined. Results reveal that funding size, government size, and financial capital are critical attributes. Entrepreneurs with higher initial capital prioritize funding size over market potential. Moreover, entrepreneurs with lower initial capital demonstrate a significantly higher willingness to pay for relocating to regions with higher per capita deposits. These findings provide insights for local governments to tailor strategies for attracting entrepreneurs with diverse capital levels, emphasizing subsidies for large enterprises or improving local livelihoods to foster small and medium-sized enterprises.

Towards Sustainable Eating Habits of Generation Z: Perception of and Willingness to Pay for Plant-Based Meat Alternatives

Within the food sector, there is a growing embrace of meat substitutes as a more sustainable alternative to meat, driven by ethical, environmental, and health considerations. This study aims to explore consumer behavior and willingness to pay (WTP) for plant-based meat alternatives (PBMAs), illustrated by the example of vegan burger patties. The sample of the study (n = 433) consists of young consumers roughly below 30 years of age, known as Generation Z (Gen Z). The study aims to (1) assess of the importance of PBMA attributes to Gen Z, and (2) approximate Gen Z’s willingness to pay for specific PBMA attribute levels. A choice-based conjoint analysis was used to assess Gen Z’s preferences for meat substitutes. The findings indicate that the most crucial PBMA attribute is origin, followed by price and the primary vegan ingredient. Notably, Gen Z values domestic and EU-sourced products positively, contrasting with the negative perception of third-country imports. Organic production is associated with a positive part-worth utility, whereas the attribute fat content has almost no impact. Consequently, WTP is approximated to be the highest for products of domestic origin compared to the significant discount required for non-EU origin. All other attribute levels have a much lower impact. Despite sociodemographic variables, the respondents’ eating habits (vegan, vegetarian, etc.) most significantly influence the approximation of the importance of some of the PBMA attributes, in particular price and primary ingredient.

Assisting Healthier and More Sustainable Online Food Choices Through Digital Quality Signals: Exploring Preferences and Segments

The current paper contributes to signalling theory by demonstrating the importance of digital quality signals in influencing consumer preferences for sales and segmentation in the context of marketing fresh fish online. We conducted a choice-based conjoint analysis with a latent class segmentation to analyse the significance of digital quality signals compared to traditional attributes online. The analysis of 1,411 global consumers revealed that product rating was among the most important factors when purchasing fresh salmon fillets online. Latent class segmentation identified four distinct segments, the largest being ‘value for money’, where product rating and pricing were most important. The other segments were ‘environmentally friendly’, prioritising procurement methods and place of origin; ‘want it now’, where delivery was the most important factor; and ‘quality conscious’, which relied on three attributes – origin, delivery, and product rating. This study enhances understanding of the impact of socially mediated stimuli. It demonstrates the ability of digital quality signals to compensate for the absence of sensory evaluation in online store environments or deficiencies in knowledge or experience. The findings will benefit the food industry and online grocery retailers in promoting healthier and more sustainable products such as fish online.

New markets for local, renewable, or affordable energy? A segmentation analysis to identify consumer preferences for decentralized energy markets

Local Energy Markets (LEMs) allow direct citizen involvement in energy production and trading. A study surveyed 636 Swiss electricity consumers using choice-based conjoint analysis to explore preferences for various LEM characteristics. Three consumer segments emerged: 'Renewable energy enthusiasts' (42 %), interested in energy mix and community PV investment; 'Price sensitives' (30 %), driven mainly by costs; and 'Uninvolved' (28 %), focused on energy mix but hesitant about PV investment. Demographic and psychological variables helped characterize these segments, suggesting tailored communication strategies to boost participation in future energy markets. Communication strategies should focus on ‘Renewable energy enthusiasts’ segment and should emphasize environmental benefits and community engagement to leverage their high motivation for involvement.