App Market Research Articles

Developing a Mobile App to Prevent Suicide Based on a Software Development Life Cycle: Application of Ecological Momentary Assessment and Interventions.

To improve mental health, diverse mobile applications (apps) have been developed to target those who actively use smartphones and in-phone apps. In this vein, this study developed a mobile app, eRAPPORT, to prevent suicide using ecological momentary assessment and intervention. A brief literature review and mobile app market search were conducted to determine the app's content and modality. The design and contents of eRAPPORT were developed through consulting with contextual and methodological experts for end-users' need assessment and technician review. For implementation, an experienced mobile app developer collaborated with the research team to create the app, which includes a safety plan, a feature to track suicidal risk and mental health status, evidence-based information from international and national authorised organisations, an outreach service with online/offline counselling and pop-ups displaying emergency contacts. Twenty-five general adults participated in the feasibility study. After using eRAPPORT for a month, they completed a self-reported questionnaire, followed by an in-depth interview of functionality, acceptability and safety. Both quantitative and qualitative evaluations assured the moderate level of usability and acceptability due to some features that should be improved before applying those with a high risk of suicide. No critical adverse event was reported. Thus, this eRAPPORT feasibility study provides fundamental information to describe the patient-centred processes on how to develop a mobile app for suicide prevention. Further study will be conducted to test the app's effectiveness and determine the application in clinical practice for monitoring and preventing suicide risk by collecting real-time and longitudinal data.

The impact of security and privacy perceptions on cryptocurrency app evaluations by users: A text mining study

This study examines how perceived security and privacy influence user ratings of cryptocurrency applications, which are critical for adoption and satisfaction amid the growing popularity of blockchain technologies and rising concerns over information security in online platforms and mobile apps. The study focuses on mobile applications from the Android app market. It used text mining methods to investigate over 64 thousand text-based user reviews and star ratings of over 140 cryptocurrency-related mobile applications available in the Google Play store. Using a partially supervised machine learning approach, this study first identified reviewer sentiment related to privacy and security, then employed ordinal regression analysis to examine the data to reveal the relationship between perceived security threats, privacy concerns, and app ratings. This study found that crypto apps average 3.84 out of 55 stars, which is higher than Productivity apps (3.46) but lower than FinTech (4.29) and Banking (4.25) apps. Ordinal regression analysis revealed security and privacy threats negatively impact ratings, while robust security measures improve them, with a model Pseudo R² of 0.25. These results have implications for both cryptocurrency app developers and platform managers, offering insights for enhancing user experiences and informing future research endeavors in this domain. It contributes to the literature by integrating the Protection Motivation Theory with sentiment analysis and provides a structured framework for developing an understanding of user behavior in the context of cryptocurrency apps.

Indian Millennials’ continued usage intentions toward online dating apps: the interplay between trust and perceived autonomy

Purpose This study aims to empirically examine the role of privacy, security, trust and autonomy in Millennials’ continued use of online dating applications. Emerging markets have been famous for their rapid modernization, growth and cultural shifts. Yet, consumer worries about online dating consumption need to be addressed in the literature through a better understanding of their behavioural intentions. This study examines the interplay of the underlying variables by testing a conceptual framework grounded on the theory of reasoned action (TRA), the self-determination theory (SDT) and the information systems continuance theory (ISCT) with regard to an emerging market. Design/methodology/approach A cross-sectional and quantitative research design is adopted. Using a well-designed structured questionnaire adapted from established scales, data was collected through a survey featuring 332 substantive responses from actively involved Millennial users of online dating apps in India. The data was analysed using confirmatory factor analysis (CFA) and structural equation modelling (SEM) through IBM SPSS AMOS (Analysis of Moment Structures) 24.0 to provide evidence of the reliability and validity of constructs alongside testing the hypothesis in the proposed model. Furthermore, Preacher and Hayes’ (2004) approach is used to explore mediation effects. Findings The results show that autonomy and trust positively affect the continued use of online dating apps. The study further reveals that autonomous behaviour motivates Millennials to use online dating apps, overriding their concerns for privacy and security. Furthermore, the results indicate that trust fully mediates the relationship between concern for privacy, perceived security and continued usage intention. Therefore, trust affects users’ intentions to continue using online dating apps as it bridges the effect of users’ concern for privacy and the perceived security in the online dating platform, making these dimensions relevant as a whole. Research limitations/implications This study provides critical insights into the theory and practice. The findings demonstrate that autonomy is more significant in motivating Millennials to use online dating apps than concerns about privacy and perceptions of security. In addition, trust plays a crucial role in mediating the relationship between these variables. Therefore, app developers, app marketers and app stores can use the findings to motivate Millennials to continue using their platforms by encouraging a sense of freedom and a better inner self, fostering engagement and conveying user trust. Originality/value Several studies have investigated the pre-adoption behaviour of users of online dating apps, and little attention has been paid to continuance usage. This study provides a unique theoretical research model and perspective for online dating apps that uncovers the role of concern for privacy, perceived security and trust that affect post-adoption behaviour by integrating the TRA, SDT and ISCT. This integration offers a more futuristic and refined perspective on human behaviour by considering both cognitive and motivational aspects. The study establishes that autonomy outweighs concern for privacy and perceived security.

Exploring Perceived Value of Retail App Attributes (RAA) and Retail App Experience (RAE) Effects on Retail App Loyalty (RAL)

This research assesses how perceived value of Retail App Attributes (RAA) create Retail App loyalty (RAL) through retail app experience (RAE). Assessment of the integrated model depicts important aspects of RAA which triggers RAE and RAL. Findings (N = 604) show that innovative RAA features such as product recommendation and advanced technology (AR, VR and 3D) generate positive hedonic and personal experience, which yields RAL. Empirical evidence supports the three-staged integrated model, depicting the stepwise development of mobile retail app loyalty. The expanded three stage model has theoretical contribution, emphasizing the importance of personal dimension in RAE and of innovative feature in RAA. Overall, this study adds to the knowledge of mobile retail app loyalty and provides meaningful insights for designing and targeting effective mobile retail app marketing strategies.

The Impact of Teacher-generated Quizzes of Raz-Kids in Cultivating Primary School Students’ Reading Skills

Many schools integrate technology into their curriculum to reap the benefits incessantly. Thanks to unprecedented technological breakthroughs, the popularity of e-books has increased significantly. As a result, the market for e-book apps has expanded exponentially. Although multiple studies have been conducted on the widely used reading program Raz-Kids, there has been no study regarding teacher-generated quizzes on Raz-Kids in Iraq. With this fact in mind, this study explored the effects of teacher-created quizzes on improving the reading skills of third-grade students during the fall and spring semesters of the 2023-2024 academic year. Forty-four students from a private international primary school in Iraq were selected via convenience sampling to represent one of the groups. The control group engaged with the books and answered standard quiz questions via the Raz-kids app. On the other hand, the experimental group studied the books and completed teacher-generated quizzes. The data were collected via reading examinations and surveys to be analyzed by either SPSS 29 or MAXQDA. Exams and surveys were used to compare students’ reading performance and analyse their perceptions in-depth. Quantitative data showed that students in the experimental group efficiently utilized teacher-created quizzes, resulting in exceptional performance in reading assessments. Moreover, composing balanced, coherent, engaging questions influenced students’ written and spoken English proficiency. Thus, the findings of this study may guide stakeholders seeking to include e-book applications in English classes.

Factors influencing consumer satisfaction and behavioural loyalty in relation to online grocery shopping Apps

This article explores the factors that have an impact on consumers' satisfaction and behavioural loyalty in relation to ordering and delivery applications, focusing on the emerging trend of online grocery shopping. Considering the digital revolution in retail, it is critical to comprehend consumer behaviour in this space. This study offers insights from a sample of 445 respondents in South Africa. A quantitative descriptive research methodology and a non-probability convenience sampling method were employed for the study. Structural equation modelling was utilised to validate the research measurement model and to test the study’s hypotheses. The results highlight the critical roles of design aesthetics, usefulness and confirmation and show robust positive correlations that support the linkages that the study's model postulates. Notably, design aesthetics, satisfaction and usefulness are all positively influenced by confirmation, and these factors, in turn, improve consumer satisfaction and behavioural loyalty. This study stands out because it provides a fresh viewpoint on the factors that influence customer satisfaction and behavioural loyalty, particularly when it comes to grocery shopping Apps. The distinctiveness of this study resides in its thorough analysis of important concepts and how they interact with one another, all against the backdrop of an African consumer base. The results obtained have numerous applications in the real world. Prioritising the factors that influence customer satisfaction and behavioural loyalty will help marketers and companies to improve app design and marketing tactics, which will increase user satisfaction and behavioural loyalty. Such a strategy could help close the gap between the rather different literatures on consumer behaviour and digital retailing, while also increasing sales through grocery shopping applications. Through this approach, stakeholders can obtain practical insights aimed at augmenting user engagement and loyalty within the fiercely competitive online grocery sector. All things considered, this study not only clarifies the essential elements that influence consumer satisfaction and behavioural loyalty in the online grocery industry but also lays out a roadmap for future research in this quickly developing field.

Warm for fun, cool for work: the effect of color temperature on users’ attitudes and behaviors toward hedonic vs. utilitarian mobile apps

PurposeIn the competitive app store environment, understanding how various app store elements influence user preferences is crucial. While prior research has primarily focused on textual and numeric elements of app stores, the role of visual elements remains underexplored. This study addresses this gap by investigating how color temperature (warm vs. cool) in app screenshots can influence users’ intentions to download hedonic vs. utilitarian mobile apps.Design/methodology/approachMultiple online experiments were conducted, including two main experiments (N = 192) and two supplementary experiments (N = 157). The experiments manipulated the color temperature of screenshots for hedonic (e.g. gaming) and utilitarian (e.g. banking) apps and measured participants’ perceptions of color appropriateness, attitudinal responses, and download intentions.FindingsWarm colors were perceived as more appropriate for hedonic apps, while cool colors were perceived as more suitable for utilitarian apps. The congruence between color temperature and app value orientation significantly influenced users’ ad attitudes and app download intentions. Specifically, hedonic apps in warm colors and utilitarian apps in cool colors received more favorable responses, with perceived color appropriateness mediating this effect.Originality/valueThis research enhances the understanding of the impact of color on app users’ perceptions and behaviors and also offers valuable insights for app developers and marketers on effectively using color as a visual marketing tool in app store environments.

Mobile apps for diabetes self-management: An updated review of app features and effectiveness.

Self-management of diabetes is extremely challenging and non-adherence is common. Health consequences are significant for those unable to adhere to the complex treatment regimen, which includes regular oral medication and/or insulin use, frequent blood sugar checks, strict dietary management, and regular physical activity. Mobile applications (apps) present a tremendous opportunity to help patients improve adherence to these behaviors. The availability of commercial diabetes self-management apps is increasing exponentially, making it difficult for patients and providers to stay informed about app options and benefits. Previous reviews have described commercial diabetes apps and their features and usability for patients with diabetes. A smaller number have reviewed the effectiveness of these apps in improving blood glucose as well as other aspects of diabetes management. The aim of this article is to update our 2016 review, summarize the results of new reviews, review outcomes of diabetes apps described in the literature, and offer recommendations for app features, effectiveness research, and marketing in apps for diabetes self-management. Although higher-quality research is needed, current reviews suggest that many diabetes apps are effective in lowering HbA1c. Recommendations for future research include reporting critical details such as patient demographics and intervention elements and designing studies to identify the most effective components of diabetes management apps. Furthermore, clearly labeling apps that have data supporting clinical efficacy in app stores would allow both providers and patients to easily identify apps that might be most beneficial. Future research should explore the use of apps for the prevention of diabetes in individuals diagnosed with prediabetes.

Analyzing User Reviews on Digital Detox Apps: A Text Mining and Sentiment Analysis Approach

ABSTRACTDue to the growing concerns around problematic smartphone use and its negative impact, there is a rising interest in digital detox. While many digital detox apps have been developed in recent years, there is still limited understanding of the long‐term effectiveness of digital detox applications and the attitude of people towards these apps. This study fills this gap by identifying the topics that people post in their reviews on the Google Play Store about digital detox apps and the emotion‐based sentiment of those reviews. A total of 3500 reviews of 25 digital detox apps were collected from the Google Play Store using a scraping tool called “Parsehub.” Data was analyzed using R studio. Sentiment analysis results suggest that positive sentiments dominated the data frame. “Trust” and “anticipation” were the two most expressed emotions in the reviews. Regression analysis confirmed that sentiment scores could explain the ratings of the apps. Through LDA topic modeling four major topics of the reviews were identified and are discussed in detail in the later section of the research paper. The findings of this study may help app developers and marketers improve digital detox apps so that people can learn and practice mindful smartphone use with the help of these apps. This study fills a gap in digital detox research by adopting a new methodological approach and procedure since it combines text mining, sentiment analysis (NRC Lexicon using Syuzhet package), regression analysis, and LDA topic modeling. To the best of our knowledge, this is the first study which uses this research approach in the context of digital detox apps.

Native Enterprise Mobile App Development: Best Practices for Security, Performance, and Scalability

This article explores best practices for developing high-quality native enterprise mobile applications, addressing security, performance optimization, scalability, seamless enterprise integration, and automated testing and compliance. With the enterprise mobile app market projected to reach $430 billion by 2024, organizations must prioritize robust development strategies to enhance operational efficiency and data security. The article discusses key techniques such as implementing strong encryption, leveraging native SDKs, adopting modular architectures, utilizing well-designed APIs, and incorporating AI-driven testing tools. By adhering to these practices, enterprises can significantly reduce the risk of data breaches, improve app performance, ensure scalability for future growth, streamline integration with existing systems, and maintain compliance with industry regulations, ultimately positioning themselves for long-term success in an increasingly mobile-first business landscape.

Factors Influencing Consumers’ Resistance Towards Property Rental Payments In Proptech Apps

This study investigates the reasons behind resistance to using the payment functionalities of proptech apps among users who have adopted the search features but not the payment feature. To explore this, the study employs Innovation Resistance Theory (IRT), mixed with variables from UTAUT2. Previous research showed that various barriers can influence user resistance to app payments. A mixed-methods approach is used in this research, combining qualitative preliminary testing and quantitative main testing. The study adopts convenience sampling to gather data. Data were collected through questionnaire and analyzed using Multiple Linear Regression Analysis in SPSS 27.0. The findings reveal that three main barriers—Risk, Tradition, and Image—significantly influence users from making payments through proptech apps. The Risk Barrier pertains to concerns over security and privacy. The Tradition Barrier involves users' preference for conventional method ways over alternatives. The Image Barrier relates to the perception of the app's reputation and trustworthiness. Future research recommendation include conducting discriminant analysis to compare non-adopters of proptech app payments distinct groups, incorporate demographic elements such as age, income, and gender as moderating variables and including additional independent variables that can expand the research scope. This study contributes to the existing literature by addressing user resistance to increase the adoption of digital payment functionalities in proptech applications. The findings can help app developers and marketers design better strategies to overcome these barriers and promote wider acceptance of proptech app payments.

User Behavior Analysis and Optimization Countermeasures in Shopping APP Interface Design

In this study, the interface design and marketing strategy of shopping APP were deeply discussed, and a series of optimization countermeasures were put forward. The principles of interface design and user behavior are analyzed, and the design problems such as information overload, complicated navigation, low usage frequency and high user loss are pointed out. The countermeasures of interface design optimization, user behavior guidance and marketing strategy adjustment are put forward, including simplifying interface, optimizing navigation, personalized recommendation, incentive mechanism, brand building and marketing promotion. These measures are aimed at improving user experience, enhancing user stickiness and enhancing market competitiveness. Through this research, it provides theoretical basis and practical guidance for shopping APP interface design optimization and market strategy adjustment.

Assessment of Eye Care Apps for Children and Adolescents Based on the Mobile App Rating Scale: Content Analysis and Quality Assessment.

In China, the current situation of myopia among children and adolescents is very serious. Prevention and control of myopia are inhibited by the lack of medical resources and the low awareness about eye care. Nevertheless, mobile apps provide an effective means to solve these problems. Since the health app market in China is still immature, it has become particularly important to conduct a study to assess the quality of eye-care apps to facilitate the development of better eye-care service strategies. This study aimed to evaluate the quality, functionality, medical evidence, and professional background of eye-care apps targeting children and adolescents in the Chinese app stores. A systematic search on iOS and Android app stores was performed to identify eye-care apps for children and adolescents. The general characteristics, development context, and functional features of the apps were described. Quality assessment of the apps was completed by 2 independent researchers using the Mobile App Rating Scale. This study included 29 apps, of which 17 (59%) were developed by commercial organizations and 12 (41%) had a design with relevant scientific basis. The main built-in functions of these apps include self-testing (18/29, 62%), eye exercises (16/29, 55%), and eye-care education (16/29, 55%). The mean overall quality of eye-care apps was 3.49 (SD 0.33), with a score ranging from 2.89 to 4.39. The overall Mobile App Rating Scale score exhibited a significant positive correlation with the subscale scores (r=0.81-0.91; P<.001). In addition, although most apps provided basic eye-care features, there are some deficiencies. For example, only a few apps were developed with the participation of medical organizations or professional ophthalmologists, and most of the apps were updated infrequently, failing to provide the latest eye-care information and technology in a timely manner. In general, the quality of eye-care apps for children and teenagers in Chinese app stores is good. These apps fulfill users' needs for eye-care services to a certain extent, but they still suffer from insufficient medical background, low user engagement, and untimely updates. In order to further improve the effectiveness of eye-care apps, cooperation with medical institutions and professional ophthalmologists should be strengthened to enhance the scientific and authoritative nature of the apps. At the same time, interactive features and regular updates should be added to enhance user participation and the continuity of the apps. This study provides a reference for future development or improvement of eye-care apps, which can help promote myopia prevention and control.

Mobile Service Quality’s Impact on Customer Repurchase Intention in Food and Beverage Mobile Applications

This study aims to assess the impact of mobile service quality on customer repurchase intention in Indonesia’s food and beverage mobile applications. The research identifies key dimensions such as application design, ease of use, privacy, and customer support and evaluates their influence on customer e-satisfaction and repurchase behavior. A quantitative approach was employed, utilizing purposive sampling to gather data from 401 active users of these applications. The analysis, conducted using Structural Equation Modeling-Partial Least Squares (SEM-PLS), revealed that these dimensions significantly enhance overall mobile service quality, which in turn positively affects customer e-satisfaction and repurchase intention. The findings underscore the importance of a minimalist and user-friendly design, robust privacy measures, and responsive customer support—particularly for Gen-Z users in Indonesia, where privacy concerns are increasingly prominent. This study contributes to the existing literature by providing insights specific to the Indonesian market and offering practical recommendations for the food and beverage industry to improve mobile service quality, thereby fostering stronger customer loyalty and increasing repurchase rates. The novelty of this research lies in its focus on the rapidly growing mobile app market in Indonesia, addressing unique regional challenges and opportunities. Doi: 10.28991/HIJ-2024-05-03-011 Full Text: PDF

From trial to triumph! A longitudinal design eliciting social impact perspective for sustained usage of gamified fitness apps

PurposeAs fitness apps have integrated gamification elements into their design to transform exercise into a compelling and competitive experience, this study draws on the expectation confirmation model (ECM) and self-determination theory (SDT) to propose a comprehensive framework for sustained usage by satisfying the psychological needs of users.Design/methodology/approachA longitudinal study design is utilized where data from 598 fitness app users were gathered over two distinct phases separated by 24 weeks, where data were analyzed using structural equation modeling.FindingsThe findings until phase 1 depict that motivational affordances significantly affect mastery, autonomy and relatedness, which in turn exert a significant influence on flow. Identification and compliance have a more pronounced effect in phase 2 compared to stage 1 of the analysis.Research limitations/implicationsIndividuals are more prone to being swayed by fellow members of their social group who share an affiliation with fitness apps, leading them to sustain their usage of fitness apps. These insights can potentially guide app developers and marketers in formulating strategies based on modifiable factors to foster sustained growth for gamified fitness apps.Originality/valueThis study takes a novel stance by employing social impact theory (SIT) in a longitudinal setting to reveal how users react to identification and compliance effects during initial and post-adoption usage of gamified fitness apps.

Digital Product Differentiation and Firm Performance: Evidence from the Mobile App Market

Digital Product Differentiation and Firm Performance: Evidence from the Mobile App Market

A scoping review of studies on self-tracking for weight management: Social contexts and experiences of a practice

The market for self-tracking tools and apps for weight management has been growing over the last two decades. The aim of this scoping review is to identify social science studies that explicitly focus on the actual practices and experiences of users of these tools and the social contexts in which they take place. Searching four databases in April 2021, we identified 15 peer-reviewed articles published between 2010 and 2021 in Western countries. The review of the studies shows the ambivalences of the use of self-tracking tools for weight management and especially how the designs and features of the apps frame positive (e.g. through social networks) as well as negative experiences (e.g. through reminder features). It also reveals a lack of in-depth intersectional research with reference to gender, social stratification and country-specific body cultures as well as a need for research to question itself on its fatmisiac assumptions.

Why Do Small Restaurant Operators Intend to Terminate Their Relationship with Food Delivery Apps During Covid-19 Pandemic?

This study investigates the factors influencing restaurant operators’ intention to terminate their relationship with food delivery apps. This research develops a model with key variables based on the loyalty theory and adds variables reflecting the specific context of the food delivery app market. The face-to-face survey of 128 restaurant managers was conducted in South Korea from Oct 1st to Oct 30th, 2020, and the data obtained were analyzed by SEM. The results showed that distrust is a direct antecedent of their intention to terminate. However, there is no significant relationship between dissatisfaction and that intention. Revenue increase is negatively associated with dissatisfaction, whereas exposure opportunities are positively associated with dissatisfaction. The fee paid for food delivery apps, lack of control of delivery service, goal incongruity, and transparency are shown to be the important determinants of distrust. Our findings will enhance the understanding of the food delivery app market in South Korea and the relationship between the food delivery app and the small restaurant. Based on the results, recommendations for prospect research and theoretical and practical implications are presented.

The Role of Korean Food Delivery Apps as a Third-Party Logistics Provider: Focusing on Self-Determination Theory

Purpose: This study aim to examines the relationships between users' self-determination motivation, perceived utili-ty and hedonic values, attitudes, and intentions to reuse the app. Additionally, the moderating effect of information search effort was explored. Design/methodology/approach: Data were collected via online surveys targeting domestic consumers using K-FDA services. We used PLS-SEM for hypothesis testing. Findings: The results suggest that K-FDA users perceive more value as they use the app with greater voluntary motivation, leading to higher attitudes and intentions to reuse the services. Additionally, hedonic value interacted with information search effort level to significantly influence attitude, indicating the need to encourage users to use K-FDA services more proactively. Research limitations/implications: According to self-determination theory, an individual's autonomy can be dis-tinguished into various stages ranging. Differences in perceived value and behaviors during the K-FDA usage process may emerge according to these stages. Therefore, it is suggested that future research conduct studies comparing differences by refining the degree of self-determination. Originality/value: Despite the increasing distribution costs as Korean Food Delivery Apps (K -FDA) serve as third- party logistics providers, the number of K-FDA users is on the rise. In this context, there is a need to investigate users' motives and the values perceived during the use of the app to attract and retain users. Therefore, we adopted the Self-Determination Theory to examine the effects of intrinsic motivation on the perceived value (utilitarian and hedonic) during the app usage process and proposed the role of K-FDA in attracting users to the app and encouraging reuse in the fiercely competitive delivery app market.

Data Analysis and Prediction of Of Various app

Abstract – This study focuses on the exploratory data analysis (EDA) and prediction of ratings for various apps available on the Google Play Store. As the number of mobile applications continues to grow exponentially, understanding the factors that influence app ratings can provide valuable insights for developers and stakeholders. This research involves a detailed examination of a dataset containing information about numerous apps, including their categories, sizes, user ratings, number of installs, and more. The EDA process involves summarizing the main characteristics of the data, identifying patterns, and uncovering anomalies. Key techniques such as descriptive statistics, visualization, and correlation analysis are utilized to explore relationships between app ratings and various attributes. Insights gained from EDA include the distribution of app ratings, the influence of app category and size on ratings, and trends in user feedback over time. Following EDA, a predictive modeling approach is employed to forecast app ratings based on identified influential features. Various machine learning algorithms, such as linear regression, decision trees, and random forests, are applied and compared to determine the most effective model. Performance metrics like Mean Squared Error (MSE) and R-squared are used to evaluate and validate the models. The results of this study highlight significant predictors of app ratings, offering practical recommendations for app developers to enhance user satisfaction. Additionally, the predictive models provide a framework for anticipating app success in the market, enabling more informed decision-making. Overall, this research contributes to a deeper understanding of the app ecosystem on the Google Play Store and demonstrates the value of data-driven approaches in optimizing app development and marketing strategies. IndexTerms – Car price prediction, Machine learning, Regression analysis, Automobile market, Predictive modeling, Vehicle valuation, Data analysis, Price determinants, Automotive industry, Market efficiency