User Decision Research Articles

The Role of Technical Car Features in Managing and Promoting New Peer-to-Peer Car-Sharing Systems: Insights from Potential Users and Strategic Implications for Service Providers

Peer-to-peer car-sharing systems are an evolving branch of urban mobility, aligning with global trends focused on sustainable development and reducing congestion in cities. A research gap has been identified concerning the specific vehicle attributes that would encourage the public to potentially use these services. Addressing this gap, and in the context of launching a new peer-to-peer car-sharing service in Katowice, Poland, this article investigates the technical features influencing the choice of vehicles in peer-to-peer car-sharing systems, particularly from the perspective of individuals who currently do not use such platforms. The study employs Social Network Analysis (SNA) to examine the interrelationships between vehicle attributes. The analysis reveals that key factors influencing users’ decisions include fuel/energy consumption, safety features, and technological advancement, with a particular emphasis on driver assistance systems, including autonomous driving capabilities. The network structure, characterized by a relatively low density (0.2536) and a short average path length (1.872), suggests that a few central vehicle features dominate user decisions, and improvements in these key areas can quickly propagate through the decision-making process, enhancing overall user satisfaction. To validate the findings, a Gradient Boosting Regression (GBR) analysis was conducted, confirming the significance of the key factors identified by the SNA, such as fuel efficiency, battery capacity, and safety systems, thus strengthening the reliability of the results. This study underscores the growing importance of sustainability and technological innovation in the automotive industry, particularly in the context of the sharing economy. It suggests that car-sharing platforms and vehicle manufacturers should prioritize these features to meet user expectations and preferences. These findings provide valuable insights for the strategic and operational management of peer-to-peer car-sharing services, emphasizing the importance of targeted vehicle selection and user-centered innovations to improve platform performance and scalability.

Tác động của ESG đối với niềm tin thương hiệu và sự gắn kết của khách hàng tại thành phố Hồ Chí Minh: Nghiên cứu điển hình trong ngành thực phẩm và đồ uống

As the world increasingly focuses its resources on sustainable business practices, Environmental, Social, and Governance (ESG) factors have become increasingly important to consumers in their brand selection and usage decisions. While there has been extensive research on the role of ESG in investment decisions, its impact on consumer behavior in Vietnam remains underexplored. This study aims to bridge this gap by examining the direct and indirect effects of ESG practices on Brand Trust and Customer Engagement in the Food and Beverage (F&B) industry. Using a mixed-methods approach combining qualitative and quantitative data, the research includes surveys of 385 consumers in Ho Chi Minh City conducted from March to May 2024. The findings confirm that ESG factors have both direct and indirect effects on Customer Engagement through Brand Trust within the F&B sector. The findings confirm that the Environmental factor has the strongest impact on Brand Trust and Customer Engagement, followed by the Social factor, while the Governance factor has the lowest direct influence.. The study highlights that effective ESG strategies not only enhance trust but also increase consumer attachment to F&B brands.

The Sharing Economy: A Systematic Literature Review and Research Agenda

ABSTRACTThe sharing economy has emerged as a transformative model in the digital age. However, existing reviews often focus on isolated aspects and provide limited insights into its complexity. This paper comprehensively reviews 92 studies through a dual‐framework approach, employing both the Antecedents–Decisions–Outcomes (ADO) and the Theories–Contexts–Methods (TCM) frameworks. The ADO framework reveals key factors influencing user decisions—including adoption, usage, booking, continued use, engagement, participation, purchase, and switching—that are shaped by economic, social, technological, trust‐related, environmental, and political antecedents. Meanwhile, the TCM framework structures an in‐depth examination of dominant theories (e.g., Technology Acceptance Model, Social Exchange Theory), diverse contexts (e.g., studies in China, the US), and methods (e.g., quantitative and qualitative) prevalent in the literature. Key findings emphasize the importance of regulatory dynamics and market shifts on user engagement and platform sustainability. Practical implications offer actionable guidance for platform managers to enhance user retention and to align strategies with evolving regulatory and market environments. The review also identifies future research directions to expand our understanding of global trends and challenges within the sharing economy.

Influence Factor Analysis of Consumer Decision in Using Special Tariff Policy on Regional Rail in Indonesia (Case Study : Sawunggalih Regional Train)

Indonesian railway transportation service companies are constantly striving to improve service and facility optimization while increasing train passenger numbers. The purpose of this study is to examine the impact of special fare tickets on train user decisions in order to boost passenger traffic and strengthen railways' role in the regional economy. This study examines price, time (length), and certainty opportunities as influences on the decision to acquire special fare tickets for public transportation trains. The study took a quantitative approach, with the questionnaire asking about Ability to Pay (ATP) and Willingness to Pay (WTP). Furthermore, the data was examined using multiple linear regressions to identify the impact of variables on consumer behavior. Overall, 54% of respondents can buy rail tickets at official pricing, including regular and special fares. 44% of respondents always purchase special price train tickets for long journeys and always take trains. Therefore, the resulting regression model is as follows: Y=3.115 - 0.49X1 + 0.042X2. The price variable shows a negative influence (-0.49), indicating that the greater the ticket price, the less likely someone will purchase a special fare train ticket. In contrast, the time variable has a positive effect, with a value of + 0.043, indicating that the longer the time given, the more likely someone will opt to buy.

Discount Vouchers and Perceived Benefits: Decision to Use Grabfood Online Food Ordering Application in Semarang City

This study examines the influence of discount vouchers and perceived benefits on consumer decisions to use the GrabFood online food ordering application in Semarang, Indonesia. The research seeks to analyze how these factors interact to shape user behavior, offering insights for optimizing marketing strategies in the competitive food delivery sector. Using a quantitative approach and Structural Equation Modeling Partial Least Squares (SEM-PLS) for data analysis, the study collected responses from 130 GrabFood users in Semarang. The findings indicate that both discount vouchers and perceived benefits significantly impact consumers’ decisions to adopt GrabFood. Discount vouchers not only directly enhance perceived financial savings but also strengthen users’ perceptions of the overall value of the service, thereby encouraging app usage. Additionally, perceived benefits, such as convenience and service quality, mediate the relationship between discount vouchers and user decisions. These results underscore the importance of strategic pricing and effective value communication in driving user engagement and retention within the food delivery industry

Demand for Payment Services and Consumer Welfare: The Introduction of a Central Bank Digital Currency

Abstract In this paper, we study how potential characteristics of the new payment instrument may affect consumer adoption and usage decisions at the point of sale. We do this by developing and estimating a structural model of payment choice, which accounts for rich heterogeneity in consumer preferences and distinguishes between adoption and usage decisions. In the model, consumers face uncertainty about acceptance decisions by merchants, who represent the opposite side of the market. We use parameter estimates to simulate introduction of a new payment instrument and to evaluate the effect of this introduction on the welfare of various demographic groups of consumers.

The Influence of MuseScore Software on Students' Creative Thinking in Music

ABSTRACTAs pedagogical training becomes more advanced and intensive, new methods of instruction that incorporate information technology are becoming increasingly important. The purpose of this article is to investigate how using the MuseScore scorewriter to teach solfeggio affects music students' ability to think creatively. The program designed for a quasi‐experimental study was implemented with two groups of students (N = 87) at the Conservatory of Music, Ningbo University. One group used the MuseScore scorewriter to practice solfeggio during weekly music lessons, while the other group used written notation. A mixed within/between‐subject ANOVA test was used to examine students' mean pre‐and post‐test scores. The analysis revealed significant differences in total scores between the mean pre‐and post‐test scores. The experimental group significantly improved their creative thinking scores due to the intervention, whereas the control group showed only minor changes. More research is required to gain a fuller picture of music students' interactions with music technology and how they view its use in the classroom. Future research should expand on these findings by delving deeper into the reasons and motivations behind musicians' technology usage decisions, as well as the innovative ways in which they incorporate technology into their teaching methods.

The Impact of Applying Total Quality in Improving the Decisions of Users of Financial Accounting Statements: An Analytical Study of Korek Telecom Company

The Impact of Applying Total Quality in Improving the Decisions of Users of Financial Accounting Statements: An Analytical Study of Korek Telecom Company

Live Streaming, Content Marketing, Flash Sale In Online Shopping Decisions For E-Commerce

This study underscores the pressing need to support the growth and success of e-commerce platforms in addressing the challenges and seizing the opportunities of today's digital commerce landscape. The primary objective of the research is to assess the impact of live streaming, content marketing, and flash sales on the online shopping decisions of users on Tokopedia. The study employs a descriptive statistical analysis, combining qualitative methods with quantitative elements. The research population consists of Tokopedia users in Medan City, with purposive sampling used to select participants. A convenience sampling technique determined the sample size, which included 260 respondents. The results of the study show that content marketing has a significant and notable effect on online shopping decisions, whereas flash sales and live streaming have smaller effects and are not statistically significant.

Conceptual Model of Innovation Decision Process and Hesitation to Adopt Augmented Reality in Tourism Industry

Augmented reality (AR) is gaining popularity in tourism by improving immersive experiences. Therefore, understanding the factors influencing perceptions and barriers is critical. This study examines visitors’ attitudes and decision making hesitation. The innovation decision process is a conceptual model for comprehending user decisions and analyzing AR features and visitor characteristics. The early majority of AR users completed 401 online questionnaires. The causal relationships were investigated using PLS-SEM and IPMA. PLS-SEM results discovered that visual appeal and environmental embedding influenced AR attitudes. This study found that low tourist memorability affected visitor resistance and AR attitudes. The dimensions of visitor perception show that novelty and enjoyment significantly influence AR attitudes. Additionally, we discovered that AR attitudes significantly affected hesitation to reuse AR, revisit and engage in EWOM. IPMA results indicate that the AR attitude is significantly effective and crucial in reducing tourism AR hesitation. Additionally, we present a novel framework that integrates the domains of policy, people and technology.

Technology and energy choices for fleet asset decarbonization under cost uncertainty

The road freight transportation sector faces significant challenges in reducing greenhouse gas emissions due to uncertainty in the costs and trajectories of low-emission technologies. This work introduces the Fleet Assets Decarbonization Problem (FADP) to guide and facilitate fleet owners’ investment decisions by providing cost-minimizing decarbonization pathways for ground fleets under decarbonization targets. It integrates strategic vehicle and infrastructure composition decisions with tactical fuel and energy usage decisions. We propose a stochastic programming formulation that incorporates cost uncertainty and optimizes the fleet decarbonization strategy over a range of scenarios. We provide a tailored rolling-horizon two-stage stochastic programming approximation solution approach and apply our formulation and solution approach to the heavy-duty truck fleet of a large U.S. consumer packaged goods company.

Pre-Service Teachers’ Perceptions and Utilisation of ChatGPT in Higher Institutions using UTAUT Theory: Evidence from an Emerging Economy

ChatGPT is a valuable tool for students, aiding in linguistic support, idea clarification, and quick material retrieval. However, issues like data security, privacy, and reliance on technology remain concerns. This study explored Nigerian pre-service teachers' perceptions and use of ChatGPT as it gains traction in education. Using a descriptive research method, data were collected via questionnaires from 450 pre-service teachers at two Nigerian colleges, selected through purposive sampling. Findings showed mixed feelings towards ChatGPT, with accessibility, response quality, and individual preferences as key factors shaping perception. Many pre-service teachers used ChatGPT as a supplementary study tool, though its reputation as a time-saver does not significantly influence their usage decisions. This study provided valuable insights for Nigerian educators and policymakers, underscoring the importance of personalised strategies to optimise ChatGPT’s benefits while addressing limitations. Enhancing digital literacy and providing support services are essential steps in bridging the digital divide and fostering effective technology integration in education.

The Influence of Perceived Ease of Use and Security on QRIS Usage Decisions Among the Community in Lampung Province

The Influence of Perceived Ease of Use and Security on QRIS Usage Decisions Among the Community in Lampung Province

The Effect of Viral Marketing and Bandwagon Effect on Decision to Use Social Media Threads in Bekasi

The purpose of this research was to analyze the effect of Viral Marketing, the Bandwagon Effect, on the Decision to Use Social Media Threads in the Bekasi Region. Data was collected by distributing questionnaires to 100 respondents who used Social Media Threads in the Bekasi area for at least 2 months. Sampling was carried out using non-probability sampling techniques and using purposive sampling. The analytical tool used is multiple linear regression; classical assumption tests (normality test, multicollinearity test, and heteroscedasticity test) are carried out as requirements that must be met in multiple linear regression analysis. Hypothesis testing simultaneously using the (F) test and partially using the (T) test. The results of this study indicate that viral marketing and bandwagon effect variables simultaneously affect customer satisfaction; this is evidenced by the F test with an Fhitung> Ftabel value (59.866> 3.09) and an amount of 0.552 (55.2%), viral marketing and bandwagon effect variables can be explained influenced by usage decisions while other variables outside this model influence the remaining 44.8%. While viral marketing partially / partially has an influence on usage decisions, this is proven by the T test with a value of Thitung> Ttabel of (5.423> 1.985) and has an influence of 0.231 (23.1%). And the bandwagon effect partially / partially has an influence on usage decisions; this is evidenced by the T-test with a Thitung> Ttable value of (9.859> 1.985) and has an influence of 0.498 (49.8%).

Research on the influence of perceived quality on users' continuance usage intention of online live streaming class platforms: the mediating role of flow experience and the moderating impact of perceived usefulness.

With the penetration of the "Internet+" into social life, the digitization of education has become a trend and national demand. Alongside the rise of the "Everyone Live Streaming" era, online live streaming class platforms have rapidly grown due to favorable user experiences. Grounded in the Expectation Confirmation Theory, this study employed questionnaire surveys to investigate the influence mechanism of perceived quality, flow experience, and perceived usefulness on individuals' continuance usage intention of online live streaming class platforms. Through the analysis of 773 survey responses, this study reveals several key findings. Firstly, perceived quality significantly and positively affects users' intention to continue using the online live streaming class platforms. Secondly, flow experience partially mediates the relationship between perceived quality and continuance usage intention, underscoring its significance in user decision-making. Additionally, Perceived usefulness negatively moderates the relationship between perceived quality and flow experience, demonstrating varied effects. On the one hand, online live streaming platforms should actively invest in improving the quality of user perception, as this can lead to a better user flow experience and continued willingness to use. On the other hand, they should also pay more attention to the user's flow experience, which has a direct impact on the user's propensity to continue to use. Besides, the perceived usefulness of the online live class by the user should also be taken seriously.

Keeping viewers hooked: Netflix’s innovative strategies for reducing churn

Netflix’s digital disruption in the entertainment industry has been significantly enhanced by digital nudging, which refers to using behavioural science techniques to subtly influence user decisions (Thaler and Sunstein, 2008). By leveraging data analytics, Netflix personalises the viewing experience, guiding users toward content they are likely to enjoy, which increases engagement and encourages binge-watching. The platform employs sophisticated algorithms to recommend titles, effectively nudging viewers to explore new genres or original content based on their viewing history (Lobato, 2019). This strategy has been pivotal in fostering a binge-watching culture, contrasting sharply with traditional broadcasting schedules offering weekly instalments. Netflix’s ability to analyse user data allows it to create content that aligns with viewer preferences, further enhancing its appeal. By understanding what resonates with audiences, Netflix can produce targeted original content that captures attention and retains subscribers. Digital nudging plays a crucial role in Netflix’s strategy, reinforcing its position as a leader in the streaming market while reshaping consumption habits across the industry. However, digital nudging presents both opportunities and challenges for customer churn management, raising critical ethical questions about autonomy and manipulation. Finding the right balance between effective customer retention strategies and ethical considerations will be vital for fostering trust and enhancing the overall user experience on the platform.

A Crowd-Intelligence-Driven, Multi-Attribute Decision-Making Approach for Product Form Design in the Cloud Environment

In the traditional decision-making process for product form design, designers and experts often prioritize schemes based on their own knowledge and experience. This approach can lead to an oversight of user preferences, ultimately affecting decision outcomes. In contrast, crowd-intelligence-driven, multi-attribute decision-making for product form design in the cloud environment builds upon traditional approaches by leveraging the vast and diverse expertise of individuals on cloud platforms, engaging participants from various fields and roles in the decision-making process to enhance comprehensiveness and accuracy. To address the issue of a single decision-maker and limited user participation in the decision-making process for product form design schemes in the cloud environment, a multi-attribute decision-making method integrating expert knowledge and user preferences is proposed. This method aims to select a product form design scheme that optimally balances expert and user satisfaction. Initially, the Pythagorean Hesitant Fuzzy Set (PHFS) is used to quantify qualitative product attributes and to establish a comprehensive multi-attribute evaluation system. In the aspect of expert decision-making, a gray correlation coefficient decision matrix based on expert knowledge is established and the overall score of the base alternative is calculated by the ViseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method and the Improved Osculating Value method. In terms of user decision-making, weights are determined by calculating the similarity between user evaluation matrices, and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to calculate scores for product form designs based on user preferences. Ultimately, optimal selection is achieved by aggregating the aforementioned expert evaluation values and user preference values. The method’s effectiveness and feasibility are confirmed through a case study of coffee machine product form design schemes.

Thinking or feeling? The effect of information diversity on consumption decisions based on the social support framework

PurposeInstrumental and emotional information influence paradoxically on people’s decision-making, and similar influences are more evident in e-commerce scenarios where physical information is limited. This study aims to construct a systematic explanatory framework for the influence of multidimensional recommendation information diversity (RID) on users' click and purchase decisions based on the social support theory (SST).Design/methodology/approachThis study analyses 453,176 data from 67,079 users of a Chinese e-commerce platform, applying lasso algorithmic techniques and cross-fit partialling-out (XPO) regression for empirical analysis.FindingsThe study finds that instrumental support information diversity (ISID) and emotional support information diversity (ESID) play divergent roles, and that the effects of both on user decision-making are inconsistent with mode-flip and marginal change. Differences in users' information craving and information overload processing mechanisms for instrumental and emotional information, leading to an inverted U-shaped effect of ISID on consumption decisions, while ESID has a U-shaped effect. Additionally, supplier certification eliminates the marginal change in ESID, and products with a high information standardisation degree eliminate the marginal change in ISID.Originality/valueResearch results reveal the opposing roles of the two types of RID and the application boundaries of their roles, providing empirical evidence for academic research.

Exploring impacts of electricity tariff on charging infrastructure planning: An activity-based approach

In the past decade, electric vehicles (EVs) have gained popularity for their efficiency and environmental benefits. Advances in battery technology and charging equipment have yielded long-range EVs and fast-charging. However, many major cities lack adequate charging infrastructure for daily EV use. This study addresses this gap by integrating activity-based modeling, charging behavior simulation, and charging infrastructure optimization. The research utilizes the POLARIS agent-based transportation model to accurately capture user activities, trip patterns, and traffic flows. Additionally, the study investigates the impact of fixed and spatiotemporal electricity rate distributions on optimal charging infrastructure deployment. The framework is applied to the Chicago regional area network and analyzed under various EV ownership scenarios. The results reveal significant impacts of the charging pricing strategy on user decision-making and charging demand distribution. There is also a need for consistent pricing policies in charging infrastructure planning and operational phases to avoid drops in service quality.

Impact of gist intervention on automated system interpretability and user decision making.

As they become more common, automated systems are also becoming increasingly opaque, challenging their users' abilities to explain and interpret their outputs. In this study, we test the predictions of fuzzy-trace theory-a leading theory of how people interpret quantitative information-on user decision making after interacting with an online decision aid. We recruited a sample of 205 online crowdworkers and asked them to use a system that was designed to detect URLs that were part of coordinated misinformation campaigns. We examined how user endorsements of system interpretability covaried with performance on this coordinated misinformation detection task and found that subjects who endorsed system interpretability displayed enhanced discernment. This interpretability was, in turn, associated with both objective mathematical ability and mathematical self-confidence. Beyond these individual differences, we evaluated the impact of a theoretically motivated intervention that was designed to promote sensemaking of system output. Participants provided with a "gist" version of system output, expressing the bottom-line meaning of that output, were better able to identify URLs that might have been part of a coordinated misinformation campaign, compared to users given the same information presented as verbatim quantitative metrics. This work highlights the importance of enabling users to grasp the essential, gist meaning of the information they receive from automated systems, which benefits users regardless of individual differences.