Search Results (224)

With the rapid growth of LLM-based chatbots and their applications in fields such as health, education, and entertainment, there is a growing interest in developing systems capable of mimicking human behavior through conversation and natural language interaction. These chatbots are available in several languages, such as English, French, and Spanish. Unfortunately, Arabic chatbots—especially those that understand Arabic dialects—are still very limited. In this paper, we develop a chatbot for the Moroccan Arabic dialect, specifically designed for the public sector, such as the fiscal domain and government administration. These institutions require tools to reduce communication loads, limit human assistance, and minimize the time needed to find documents or complete payment procedures. Our optimized chatbot combines recent technologies like LLMs and semantic similarity. It supports Moroccan citizens by providing responses in the Moroccan dialect (Darija), both in text and speech, without requiring extensive resources. It also supports other citizens in French, Spanish, and English. Our chatbot was tested in a real use case in the tax domain, and the results were satisfactory, especially considering the general complexity of the Arabic language and the particular challenges of the Moroccan dialect. Full article

Materialism is recognized as an important determinant of consumer behavior. However, studies exploring how materialism influences impulsive buying through the Diderot effect in digital contexts remain scarce. This study analyzes data from 416 adult consumers in Türkiye using Structural Equation Modeling (SEM). Four hypotheses were tested: (i) materialism increases the Diderot effect, (ii) the Diderot effect strengthens impulsive buying, (iii) materialism directly influences impulsive buying, and (iv) materialism indirectly affects impulsive buying through the Diderot effect. The findings support all four hypotheses. Materialism significantly increases both the Diderot effect and impulsive buying in online environments. The Diderot effect partially mediates this relationship and acts as an independent predictor of impulsive tendencies. The study also points out that digital stimuli such as recommendation systems, fast payment options, and social proof may reinforce this mechanism, highlighting the importance of understanding consumer behavior in digital settings. Overall, the results underline that materialistic desires, when combined with the completion motive of the Diderot effect, strongly shape impulsive tendencies. Beyond advancing theory, the study emphasizes that marketing strategies should go beyond promoting higher consumption and instead foster conscious and sustainable shopping practices. This approach not only supports consumer well-being, but also contributes to building ethical and sustainable markets. Full article

The aim of this study was to analyze international differences in online consumer behavior. The analysis was carried out on a sample of 763 participants from the countries of Spain, France, Poland and Russia. Online consumer behavior was examined from the perspective of seven dimensions: shipping-related concerns and preferences, price sensitivity and perceived cost advantage, quality perception, security concerns, time-related benefits, availability and quality of information, and shopping service satisfaction. Data were verified using Average inter-item correlation, the Shapiro–Wilk test and Levene Statistic. Subsequently, Welch’s ANOVA and one-way ANOVA and the Games–Howell and Tukey HSD post hoc tests were applied. Statistically significant differences were fully identified in all examined dimensions. The largest differences were recorded in price sensitivity, shipping-related concerns and security concerns. The effect measurements, in addition to ANOVA and post hoc tests, confirm the significance of these differences. National context, shaped by culture, institutional trust and digital infrastructure, continues to influence online consumer behavior. The strategies that the businesses should adopt should focus on approaches that are tailor-made for a specific market. This means that adapting pricing models, strengthening trust (e.g., through secure payments and strengthening safe return policies), and adapting delivery options to local preferences can lead to improved customer satisfaction in cross-border e-commerce. Full article

Although technological innovations are often intended to improve quality and efficiency, they can exacerbate systemic challenges when not aligned with the principles of value-based care. As a result, healthcare systems in many countries face persistent inefficiencies stemming from the overuse, underuse, misuse, and waste associated with the adoption of health technology. This narrative review examines the dual impact of healthcare technology and evaluates how contract mechanisms can serve as strategic tools for promoting cost-effective, outcome-oriented integration. Drawing from healthcare management, and supply chain literature, this paper analyzes various payment and contract models, including performance-based, bundled, cost-sharing, and revenue-sharing agreements, through the lens of stakeholder alignment. It explores how these mechanisms influence provider behavior, patient access, and system sustainability. The study contends that well-designed contract mechanisms can align stakeholder incentives, reduce inefficiencies, and support the delivery of high-value care across diverse healthcare settings. We provide concrete examples to illustrate how various contract mechanisms impact the integration of health technologies in practice. Full article

Among searchable encryption techniques, multi-user dynamic searchable encryption (MUDSE) schemes are an important research direction. After the data owner transfers data to the cloud, it may be necessary to authorize different users to access some or all of the data while allowing for dynamic updates. Enabling dynamic data sharing in cloud storage while preserving users’ ability to search the data is crucial for promoting data flow and maximizing its value. This approach is particularly significant in addressing the data silo problem. However, existing security mechanisms remain imperfect, and most current scenarios assume that cloud servers are merely “curious but honest”. In reality, cloud servers may exhibit malicious behavior, such as returning incorrect or incomplete search results. Similarly, malicious users might falsify search results—for example, to avoid payment—or collude with cloud servers to steal other users’ search privacy. To address these challenges, this paper proposes an updatable multi-user dynamic searchable encryption scheme with bidirectional verification. The scheme enables secure dynamic data sharing in multi-user scenarios by constructing an index structure using homomorphic message authentication codes and bitmaps. This ensures secure updates to encrypted data without revealing the relationship between files and keyword search keys while providing forward and backward security. Regarding privilege management, the scheme employs updatable keys, ensuring that users can only generate valid search commands if they possess the latest encryption key. Additionally, blockchain technology is introduced to assist in verifying user honesty. Through actual testing and security analysis, the proposed solution demonstrates improved search speed over traditional methods while maintaining security. It also exhibits high adaptability for handling frequently changing cloud data. Full article

Mobile payment technology (MPT) has emerged as a tool with the potential to advance financial inclusion and sustainable development. However, the existing literature inadequately explains how sustainability factors influence user behavior toward MPT adoption and how this behavior translates into financial inclusion especially under the influence of mobile transaction tax policies in African countries. This study addresses this gap by examining the antecedents of sustainable usage behaviors of MPT and their implications for digital financial inclusion in Ghana. Specifically, it integrates the triple bottom line (TBL) dimensions (economic, social, and environmental impact) with constructs from the theory of planned behavior (TPB) (attitude, perceived behavioral control, and subjective norms) into a unified sustainability-TPB framework. This study further investigates the moderating role of a mobile transaction tax policy (MTTP) on the relationship between sustainable usage behaviors and financial inclusion. The PLS-SEM method was utilized to analyze the theoretical model using the cross-sectional data of 320 respondents. The findings of this study supported that all TBL dimensions and TPB constructs influence behavioral intention and adoption through the usage of mobile payment technology and consequently financial inclusion. Notably, the mobile transaction tax policy negatively impacts the adoption of sustainable behaviors and financial inclusion. This study contributes to the current theoretical discourse on sustainable consumer behaviors and positions it on the broader sustainable development framework through financial inclusion by providing a shred of empirical evidence in the Ghanaian mobile payment industry perspective. The practical and policy implications are also suggested. Full article

The mobile gaming industry has undergone remarkable expansion alongside advancements in mobile and information technologies. Facing intensified market competition due to user number saturation and product homogeneity, industry practitioners require actionable insights into design features that drive user engagement and in-game payments. This study employs a qualitative research approach based on grounded theory, focusing on role-playing mobile games as the research subject. Primary data were collected through in-depth interviews and focus groups with gaming industry professionals and users, supplemented by online textual data collection. Utilizing the three-stage coding paradigm of grounded theory and drawing upon emotional design theory, this study constructs a dimensional model of mobile game design features comprising 4 major categories, 16 primary design characteristics, and 41 specific design elements. The findings provide theoretical support for understanding how mobile game design features influence user behaviors while offering practical insights for optimizing mobile game products. This research contributes to both academic discourse and industrial practice by systematically identifying and categorizing critical design elements that affect user engagement in mobile games. Full article

Mangrove ecosystems are vital for coastal protection, fisheries, biodiversity, and local livelihoods, yet they are increasingly threatened by land-use changes, climate impacts, and limited conservation funding. This study investigates how much local communities are willing to pay (WTP) to conserve the Chwaka Bay mangrove forest in Zanzibar. Using the Contingent Valuation Method (CVM) with a payment card approach, we conducted a structured household survey to assess both monetary contributions and the psychological and socioeconomic factors influencing them. This study is guided by Ajzen’s Theory of Planned Behavior (TPB), incorporating attitudes, subjective norms, perceived behavioral control, and mangrove knowledge. The results show that 68.2% of respondents are willing to pay for mangrove conservation, while 24.2% are not—mainly due to financial constraints or skepticism about fund use. Key drivers of WTP include perceived ecological and livelihood benefits, environmental awareness, and prior conservation involvement. Statistical validation using the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity confirmed the reliability of the model. The findings demonstrate the value of combining behavioral theory with economic valuation to better understand and support community-based conservation strategies. This approach can inform policymakers in designing targeted, transparent, and inclusive mangrove protection programs. Full article

As consumer behavior increasingly shifts toward hyperlocal, digitally mediated retail journeys, community unmanned stores have emerged as a transformative model that integrates smart technologies with community proximity services. These fully automated stores offer convenient, contactless shopping and hybrid digital–physical interactions, playing an increasingly important role within broader omnichannel digital retail ecosystems. However, there remains a lack of validated instruments to assess customer experience in such autonomous and locally embedded retail formats. This study develops and validates an ECUS-scale (an experience in community unmanned store scale), a multidimensional measurement tool grounded in qualitative research and refined through exploratory and confirmatory factor analysis. The scale identifies nine key dimensions—convenient service, smooth transaction, preferential price, good quality, safe environment, secure payment, comfortable space, comfortable interaction, and friendly image—across 36 items. These dimensions reflect the technological, spatial, and emotional–social aspects of customer experience in unmanned retail settings. The findings demonstrate that the ECUS-scale offers a robust framework for evaluating consumer experience in low-staffed, tech-enabled community stores, with strong relevance to omnichannel digital retail strategies. Theoretically, it advances the literature on smart retail experience by capturing underexplored dimensions such as emotional engagement with technology and perceptions of safety in staff-free environments. Practically, it serves as a diagnostic tool for businesses to enhance experience design and optimize customer engagement across digital and physical touchpoints. Full article

Willingness to pay (WTP) measurements often contain a hypothetical bias (HB) when participants’ responses result from ‘fictitious’ survey scenarios rather than actual purchasing behavior or field studies. This discrepancy usually leads to inaccurate WTP values, which affect pricing strategies. Our quantitative online survey with German consumers (N = 215) examines the HB of WTP for different mobile phone plans as an example of a widespread consumer good. The aim is to focus on the correlation between hypothetical and actual WTP and the influence of socio-demographic factors on the HB. We used the Certainty Approach to correct hypothetical WTP data to reflect actual payment behavior. The findings show that hypothetical WTP values are generally higher than current expenditure, which demonstrates that HB significantly affects WTP measurements in the context of mobile communications products. The applied Certainty Approach successfully reduced this discrepancy. We found a moderate negative correlation between actual WTP and the extent of the HB, indicating that higher actual WTP is associated with lower bias. Moreover, socio-demographic factors such as age and income do not significantly influence the HB. This study suggests pricing strategies should consider HB-adjusted WTP values to avoid management decisions based on inflated hypothetical data. Full article

In the increasingly competitive mobile ecosystem, understanding user behavior is essential to improve targeted sales and the effectiveness of advertising. With the widespread adoption of smartphones and the increasing variety of mobile applications, predicting user behavior has become more complex. This study presents a comprehensive framework for predicting mobile payment behavior by integrating demographic, situational, and behavioral factors, focusing on patterns in mobile application usage. To address the complexity of the data, we use a combination of machine-learning models, including extreme gradient boosting, light gradient boosting machine, and CatBoost, along with Shapley additive explanations (SHAP) to improve interpretability. An analysis of extensive panel data from Korean Android users reveals that incorporating application usage behavior in such models considerably improves the accuracy of mobile payment predictions. The study identifies key predictors of payment behavior, indicated by high Shapley values, such as using social networking services (e.g., KakaoTalk and Instagram), media applications (e.g., YouTube), and financial and membership applications (e.g., Toss and OK Cashbag). Moreover, the results of the SHAP force analysis reveal the individual session-level drivers of mobile purchases. These findings advance the literature on mobile payment prediction and offer practical insights for improving targeted marketing strategies by identifying key behavioral drivers of mobile transactions. Full article

The large-scale integration of renewable energy sources (RESs) has raised concerns regarding grid congestion in Japan. Battery energy storage systems (BESSs) can mitigate congestion by adjusting charging schedules; however, BESS owners basically prioritize market arbitrage, which may not be aligned with congestion mitigation. This paper proposes a charging incentive design to guide arbitrage-oriented BESS charging toward time periods that are effective for grid congestion mitigation. The system operator predicts congested hours and ensures that BESS owners can purchase electricity at the lowest daily market price. This design intends to shift the BESS charging time towards congestion periods. Because market prices tend to decline during congestion periods, the proposed method reduces the operator’s financial burden while encouraging congestion-mitigating charging behavior. Numerical simulations using a simplified Japanese east-side power system model demonstrate that the proposed method reduced the congestion mitigation costs by 3.86% and curtailed the RES output by 3.89%, compared to using no incentive method (current operation in Japan). Furthermore, additional payments to BESS owners accounted for only around 7% of the resulting cost savings, indicating that the proposed method achieved lower overall system operating costs. Full article

Considering the rapid increase in mobile payment usage, numerous big tech companies have added mobile payment to the primary services that their platforms offer. However, extant research predominantly treats this added service as a standalone offering and investigates user adoption and behavior for this service independent of the primary services. Recognizing this gap in the literature, this study considers the added service as part of an extended ecosystem and examines different motivations for using the primary service. Therefore, this study examines how different motivations for using social networking services (SNSs) shape trust in the extended payment service and ultimately influence behavioral intentions. Drawing on the schema congruity theory, we conceptualize trust as a multidimensional construct—distinguished between cognitive and emotional trust—and explore the impact of trust in the primary service on the use of an added service. Specifically, we analyze survey data of 478 users of South Korea’s leading SNS. The results reveal that both hedonic and utilitarian motivations positively influence emotional and cognitive trust, which, in turn, drive behavioral intention. However, hedonic (utilitarian) motivation exerts a stronger effect on emotional (cognitive) trust. Overall, the findings enhance the knowledge regarding trust formation in extended service ecosystems and offer insights for tech firms integrating financial services into their platforms. Full article

This study explores how system-based and cognitive-based factors affect platform trust and its role in the actual use of PayLater services (buy now, pay later or BNPL) in Indonesia and Malaysia. PayLater, a fintech innovation, provides fast and convenient payment options through online platforms. By incorporating platform trust into the technology acceptance model (TAM), the research investigates whether borrowing intention acts as a mediator between platform trust and actual usage. Utilizing a quantitative approach with purposive sampling, data were gathered from 106 respondents in Indonesia and 169 in Malaysia, with 62 and 85 respondents meeting the criteria, respectively. Partial least squares (PLS) analysis indicates notable differences in how Indonesian and Malaysian users perceive platform trust, while the effect of platform trust on borrowing intention remains consistent across both nations. Borrowing intention emerges as a crucial factor influencing the actual use of PayLater services. The results offer important insights into the adoption of fintech services in emerging markets, highlighting the significance of platform trust in shaping user behavior. This research provides practical suggestions for fintech providers to improve platform trust and user engagement in cross-country scenarios. Full article

Despite the rapid advancements in payment technologies, cash continues to play a significant role in modern society. This phenomenon presents a unique area of analysis, particularly within metropolitan societies such as those in the Jakarta metropolitan area in Indonesia. The present study aimed to investigate cash usage in the Jakarta metropolitan area by analyzing two cases: (1) cash usage in physical stores, and (2) intention to continue to use cash in daily activities. To this end, two analytical techniques were employed: logistic regression and structural equation modeling (PLS-SEM). These techniques were implemented using data from 400 respondents residing in the Jakarta metropolitan area. The results of the study indicate a preference for cash over digital payments in transactions among a significant proportion of the respondents. The determinant analysis further identified several factors influencing cash usage in physical stores, including education, employment status, and the number of bank accounts. Furthermore, this study identified attitudes toward behavior, subjective norms, and satisfaction as variables affecting the intention to continue using cash in Indonesian society. Full article