The existing body of research on dynamic customer segmentation has primarily focused on segment-level customer purchasing behavior (CPB) analysis to tailor marketing strategies for distinct customer groups. However, these approaches often lack the granularity required for personalized marketing at the individual level. Moreover, the analysis of customer transitions between different groups has largely been overlooked. This study addresses these gaps by developing an efficient framework that enables businesses to forecast customer behavior, assess the impact of various strategies on each customer separately, and analyze customer transition between segments. This can facilitate providing personalized marketing strategies, fostering a gradual transition toward a desired customer status, and enhancing the overall marketing precision. In this study, we employ time series feature vectors encompassing recency, frequency, monetary value, and lifespan, applying the K-means algorithm with a range of distance metrics for customer segmentation along with classification algorithms to predict customer behavior. Leveraging counterfactual analysis, we establish a solution for analyzing customer transitions between groups and evaluating personalized marketing strategies. Our findings underscore the superior performance of the Euclidean distance metric, closely followed by the Manhattan distance, in distinguishing the patterns in time series customer behavior, with logistic regression excelling in predicting customer status. This study enables decision-makers to forecast the impact of diverse marketing strategies on customer behavior which facilitates customer retention and engagement through well-informed decisions.
{"title":"Analyzing the Dynamics of Customer Behavior: A New Perspective on Personalized Marketing through Counterfactual Analysis","authors":"Mona Ebadi Jalal, Adel Elmaghraby","doi":"10.3390/jtaer19030081","DOIUrl":"https://doi.org/10.3390/jtaer19030081","url":null,"abstract":"The existing body of research on dynamic customer segmentation has primarily focused on segment-level customer purchasing behavior (CPB) analysis to tailor marketing strategies for distinct customer groups. However, these approaches often lack the granularity required for personalized marketing at the individual level. Moreover, the analysis of customer transitions between different groups has largely been overlooked. This study addresses these gaps by developing an efficient framework that enables businesses to forecast customer behavior, assess the impact of various strategies on each customer separately, and analyze customer transition between segments. This can facilitate providing personalized marketing strategies, fostering a gradual transition toward a desired customer status, and enhancing the overall marketing precision. In this study, we employ time series feature vectors encompassing recency, frequency, monetary value, and lifespan, applying the K-means algorithm with a range of distance metrics for customer segmentation along with classification algorithms to predict customer behavior. Leveraging counterfactual analysis, we establish a solution for analyzing customer transitions between groups and evaluating personalized marketing strategies. Our findings underscore the superior performance of the Euclidean distance metric, closely followed by the Manhattan distance, in distinguishing the patterns in time series customer behavior, with logistic regression excelling in predicting customer status. This study enables decision-makers to forecast the impact of diverse marketing strategies on customer behavior which facilitates customer retention and engagement through well-informed decisions.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141523116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AI is considered a key driver of industrial transformation and a strategic technology that will shape future development. With AI services continuing to permeate various sectors, concerns have emerged about the ethics of AI. This study investigates the effects of different types of AI services (mechanical, thinking, and affective AI services) on consumers’ attitudes through offline and online AI service experiments. We also construct a model to explore the mediating roles of identity threat and perceived control. The findings reveal that mechanical AI services negatively affect consumers’ attitudes while thinking and affective AI services have a positive effect. Additionally, we explore how consumers’ attitudes vary across different service scenarios and ethical judgments (utilitarianism and deontology). Our findings could offer practical guidance for enterprises providing AI services.
{"title":"Is Smarter Better? A Moral Judgment Perspective on Consumer Attitudes about Different Types of AI Services","authors":"Qingji Fan, Yan Dai, Xue Wen","doi":"10.3390/jtaer19030080","DOIUrl":"https://doi.org/10.3390/jtaer19030080","url":null,"abstract":"AI is considered a key driver of industrial transformation and a strategic technology that will shape future development. With AI services continuing to permeate various sectors, concerns have emerged about the ethics of AI. This study investigates the effects of different types of AI services (mechanical, thinking, and affective AI services) on consumers’ attitudes through offline and online AI service experiments. We also construct a model to explore the mediating roles of identity threat and perceived control. The findings reveal that mechanical AI services negatively affect consumers’ attitudes while thinking and affective AI services have a positive effect. Additionally, we explore how consumers’ attitudes vary across different service scenarios and ethical judgments (utilitarianism and deontology). Our findings could offer practical guidance for enterprises providing AI services.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Blockchain technology enables innovative financing models in supply-chain finance. This research constructs a tripartite evolutionary game model that includes core enterprises as employers, small- and medium-sized enterprises (SMEs) as contractors, and banks as financial institutions, where they have been simulated for their impact on blockchain technology, especially on the strategic choices of supply-chain financing behavior and the system’s evolutionary path under core enterprises’ guarantee mechanism. The findings show the application of blockchain technology can effectively reduce the regulatory and review costs for financial institutions, thereby enhancing the efficiency of supply-chain financing. Particularly, blockchain technology provides a more reliable credit endorsement platform for SMEs in reducing their tendency to default. The guarantee mechanism of core enterprises is more effective with the support of blockchain technology, which helps to build more solid supply-chain financial cooperation relationships. The research contributes to the theoretical research on the integration of blockchain technology into supply-chain finance, especially for improving the operational efficiency of financial services. It also highlights the need for blockchain-backed guarantees from core enterprises in optimizing supply-chain financial services.
{"title":"Blockchain and Supply-Chain Financing: An Evolutionary Game Approach with Guarantee Considerations","authors":"Jizhou Zhan, Gewei Zhang, Heap-Yih Chong, Xiangfeng Chen","doi":"10.3390/jtaer19020079","DOIUrl":"https://doi.org/10.3390/jtaer19020079","url":null,"abstract":"Blockchain technology enables innovative financing models in supply-chain finance. This research constructs a tripartite evolutionary game model that includes core enterprises as employers, small- and medium-sized enterprises (SMEs) as contractors, and banks as financial institutions, where they have been simulated for their impact on blockchain technology, especially on the strategic choices of supply-chain financing behavior and the system’s evolutionary path under core enterprises’ guarantee mechanism. The findings show the application of blockchain technology can effectively reduce the regulatory and review costs for financial institutions, thereby enhancing the efficiency of supply-chain financing. Particularly, blockchain technology provides a more reliable credit endorsement platform for SMEs in reducing their tendency to default. The guarantee mechanism of core enterprises is more effective with the support of blockchain technology, which helps to build more solid supply-chain financial cooperation relationships. The research contributes to the theoretical research on the integration of blockchain technology into supply-chain finance, especially for improving the operational efficiency of financial services. It also highlights the need for blockchain-backed guarantees from core enterprises in optimizing supply-chain financial services.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mariia Bordian, María Fuentes-Blasco, Irene Gil-Saura, Beatriz Moliner-Velázquez
The study intends to identify and analyze different consumer segments. For this purpose, we examine why customers turn to electronic word-of-mouth (eWOM) before making a purchase and how they perceive a hotel’s information and communication technology (ICT) and relational innovation after making a purchase. The objective was empirically tested with data from a panel of consumers who stayed at hotels during the post-pandemic recovery period in Spain. In total, 393 valid questionnaires were obtained. The estimation of a finite mix model was applied to identify guest profiles. Estimation identified three guest profiles where the perceptions of the hotel’s relational innovation and ICT present a high discriminant power in the first two segments. Moreover, compared to the second segment, the first group is characterized by the low impact level of these variables. On the other hand, the motivation to consult eWOM in the prebooking stage significantly influences all three groups; however, the guests of the third segment present less motivation than the rest. Hotel managers may consider ICT, relational innovation, and eWOM factors when segmenting consumers. Understanding this would enhance the company’s service delivery and the hotel’s competitiveness. The contribution of this study lies in considering ICT, relational innovation, and eWOM as novel factors that help identify different guest profiles.
{"title":"Technology and Innovation: Analyzing the Heterogeneity of the Hotel Guests’ Behavior","authors":"Mariia Bordian, María Fuentes-Blasco, Irene Gil-Saura, Beatriz Moliner-Velázquez","doi":"10.3390/jtaer19020078","DOIUrl":"https://doi.org/10.3390/jtaer19020078","url":null,"abstract":"The study intends to identify and analyze different consumer segments. For this purpose, we examine why customers turn to electronic word-of-mouth (eWOM) before making a purchase and how they perceive a hotel’s information and communication technology (ICT) and relational innovation after making a purchase. The objective was empirically tested with data from a panel of consumers who stayed at hotels during the post-pandemic recovery period in Spain. In total, 393 valid questionnaires were obtained. The estimation of a finite mix model was applied to identify guest profiles. Estimation identified three guest profiles where the perceptions of the hotel’s relational innovation and ICT present a high discriminant power in the first two segments. Moreover, compared to the second segment, the first group is characterized by the low impact level of these variables. On the other hand, the motivation to consult eWOM in the prebooking stage significantly influences all three groups; however, the guests of the third segment present less motivation than the rest. Hotel managers may consider ICT, relational innovation, and eWOM factors when segmenting consumers. Understanding this would enhance the company’s service delivery and the hotel’s competitiveness. The contribution of this study lies in considering ICT, relational innovation, and eWOM as novel factors that help identify different guest profiles.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Syed Abdullah Ashraf, Aariz Faizan Javed, Sreevatsa Bellary, Pradip Kumar Bala, Prabin Kumar Panigrahi
Driven by motives of profit and competition, fake reviews are increasingly used to manipulate product ratings. This trend has caught the attention of academic researchers and international regulatory bodies. Current methods for spotting fake reviews suffer from scalability and interpretability issues. This study focuses on identifying suspected fake reviews in the hospitality sector using a review aggregator platform. By combining features and leveraging various classifiers through a stacking architecture, we improve training outcomes. User-centric traits emerge as crucial in spotting fake reviews. Incorporating SHAP (Shapley Additive Explanations) enhances model interpretability. Our model consistently outperforms existing methods across diverse dataset sizes, proving its adaptable, explainable, and scalable nature. These findings hold implications for review platforms, decision-makers, and users, promoting transparency and reliability in reviews and decisions.
{"title":"Leveraging Stacking Framework for Fake Review Detection in the Hospitality Sector","authors":"Syed Abdullah Ashraf, Aariz Faizan Javed, Sreevatsa Bellary, Pradip Kumar Bala, Prabin Kumar Panigrahi","doi":"10.3390/jtaer19020075","DOIUrl":"https://doi.org/10.3390/jtaer19020075","url":null,"abstract":"Driven by motives of profit and competition, fake reviews are increasingly used to manipulate product ratings. This trend has caught the attention of academic researchers and international regulatory bodies. Current methods for spotting fake reviews suffer from scalability and interpretability issues. This study focuses on identifying suspected fake reviews in the hospitality sector using a review aggregator platform. By combining features and leveraging various classifiers through a stacking architecture, we improve training outcomes. User-centric traits emerge as crucial in spotting fake reviews. Incorporating SHAP (Shapley Additive Explanations) enhances model interpretability. Our model consistently outperforms existing methods across diverse dataset sizes, proving its adaptable, explainable, and scalable nature. These findings hold implications for review platforms, decision-makers, and users, promoting transparency and reliability in reviews and decisions.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Claudimar Pereira da Veiga, Cássia Rita Pereira da Veiga, Júlia de Souza Silva Michel, Leandro Ferreira Di Iorio, Zhaohui Su
This article delves into Brazil’s rapidly expanding e-commerce sector, emphasizing its significant growth and evolving dynamics. Employing a meta-narrative review and a convergence-coding matrix, this research systematically analyzes and integrates findings from the existing literature to reveal critical industry patterns. The analysis identifies four pivotal clusters: consumer behavior, e-commerce structure, product distribution, and environmental sustainability. These elements collectively offer a comprehensive view of Brazil’s present and future e-commerce directions. This study underscores the imperative for strategies responsive to changing consumer behaviors, technological advancements, and environmental concerns. It also furnishes practical insights for enhancing online retail consumer engagement, logistical efficiency, and sustainability. Furthermore, this research advocates for e-commerce as a vehicle for digital inclusion, calling for policies that promote equitable access to online markets. This underscores its broader socio-economic importance, suggesting a path forward for stakeholders in shaping a more inclusive and sustainable e-commerce ecosystem.
{"title":"E-Commerce in Brazil: An In-Depth Analysis of Digital Growth and Strategic Approaches for Online Retail","authors":"Claudimar Pereira da Veiga, Cássia Rita Pereira da Veiga, Júlia de Souza Silva Michel, Leandro Ferreira Di Iorio, Zhaohui Su","doi":"10.3390/jtaer19020076","DOIUrl":"https://doi.org/10.3390/jtaer19020076","url":null,"abstract":"This article delves into Brazil’s rapidly expanding e-commerce sector, emphasizing its significant growth and evolving dynamics. Employing a meta-narrative review and a convergence-coding matrix, this research systematically analyzes and integrates findings from the existing literature to reveal critical industry patterns. The analysis identifies four pivotal clusters: consumer behavior, e-commerce structure, product distribution, and environmental sustainability. These elements collectively offer a comprehensive view of Brazil’s present and future e-commerce directions. This study underscores the imperative for strategies responsive to changing consumer behaviors, technological advancements, and environmental concerns. It also furnishes practical insights for enhancing online retail consumer engagement, logistical efficiency, and sustainability. Furthermore, this research advocates for e-commerce as a vehicle for digital inclusion, calling for policies that promote equitable access to online markets. This underscores its broader socio-economic importance, suggesting a path forward for stakeholders in shaping a more inclusive and sustainable e-commerce ecosystem.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Catarina Almeida, Cecilia Castro, Víctor Leiva, Ana Cristina Braga, Ana Freitas
Sentiment analysis is a cornerstone of natural language processing. However, it presents formidable challenges due to the intricacies of lexical diversity, complex linguistic structures, and the subtleties of context dependence. This study introduces a bespoke and integrated approach to analyzing customer sentiment, with a particular emphasis on a case study in the Portuguese retail market. Capitalizing on the strengths of SentiLex-PT, a sentiment lexicon curated for the Portuguese language, and an array of sophisticated machine learning algorithms, this research constructs advanced models that encapsulate both lexical features and the subtleties of linguistic composition. A meticulous comparative analysis singles out multinomial logistic regression as the pre-eminent model for its applicability and accuracy within our case study. The findings of this analysis highlight the pivotal role that sentiment data play in strategic decision-making processes such as reputation management, strategic planning, and forecasting market trends within the retail sector. To the extent of our knowledge, this work is pioneering in its provision of a holistic sentiment analysis framework tailored to the Portuguese retail context, marking an advancement for both the academic field and industry application.
{"title":"Optimizing Sentiment Analysis Models for Customer Support: Methodology and Case Study in the Portuguese Retail Sector","authors":"Catarina Almeida, Cecilia Castro, Víctor Leiva, Ana Cristina Braga, Ana Freitas","doi":"10.3390/jtaer19020074","DOIUrl":"https://doi.org/10.3390/jtaer19020074","url":null,"abstract":"Sentiment analysis is a cornerstone of natural language processing. However, it presents formidable challenges due to the intricacies of lexical diversity, complex linguistic structures, and the subtleties of context dependence. This study introduces a bespoke and integrated approach to analyzing customer sentiment, with a particular emphasis on a case study in the Portuguese retail market. Capitalizing on the strengths of SentiLex-PT, a sentiment lexicon curated for the Portuguese language, and an array of sophisticated machine learning algorithms, this research constructs advanced models that encapsulate both lexical features and the subtleties of linguistic composition. A meticulous comparative analysis singles out multinomial logistic regression as the pre-eminent model for its applicability and accuracy within our case study. The findings of this analysis highlight the pivotal role that sentiment data play in strategic decision-making processes such as reputation management, strategic planning, and forecasting market trends within the retail sector. To the extent of our knowledge, this work is pioneering in its provision of a holistic sentiment analysis framework tailored to the Portuguese retail context, marking an advancement for both the academic field and industry application.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141361134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As a result of globalization and other factors, periodic shocks to economic activity have become more frequent in recent years. How these periods of economic uncertainty affect different business sectors and industries has become an important emerging area of research activity. Sensory experiences are increasingly recognized as an important aspect of the customer experience. Likewise, online reviews and the usefulness rating given by review consumers are important factors in the consumers’ purchasing decision-making process. How these factors are affected by periods of crisis is an underexplored area of research that this study addresses through the exploration and comparison of the perceived helpfulness of sensory experience online reviews, specifically in the hotel industry, before and since the COVID-19 pandemic. Primary data were harvested from the Booking.com website before and during the pandemic; 143,739 online reviews were analyzed using a keyword search based on six dimensions of hotel services to identify those reviews with sensory experience content. The analysis applied Herzberg’s two-factor theory, where each service attribute was examined as both positive (satisfier) and negative (dissatisfier). Empirical analytical methods were applied to produce compelling findings. The findings indicate that the reviews of multisensory experiences affect the perceived value of a post both negatively and positively, respectively, and that the pandemic did not affect the relationship between reviews and the perceived helpfulness of the reviews. This study has both theoretical and practical implications for researchers and practitioners by applying and building on Herzberg’s two-factor theory of online reviews in the hospitality sector during a period of crisis, as well as addressing a gap in the existing literature on how the pandemic affected the relationships between the online reviews of sensory experiences and their perceived usefulness. Practitioners may find the results useful in how they allocate their resources and focus during such periods to optimize their competitiveness.
{"title":"Usefulness of Online Reviews of Sensory Experiences: Pre- vs. Post-Pandemic","authors":"Jong Min Kim, K. Park, R. Marjerison","doi":"10.3390/jtaer19020073","DOIUrl":"https://doi.org/10.3390/jtaer19020073","url":null,"abstract":"As a result of globalization and other factors, periodic shocks to economic activity have become more frequent in recent years. How these periods of economic uncertainty affect different business sectors and industries has become an important emerging area of research activity. Sensory experiences are increasingly recognized as an important aspect of the customer experience. Likewise, online reviews and the usefulness rating given by review consumers are important factors in the consumers’ purchasing decision-making process. How these factors are affected by periods of crisis is an underexplored area of research that this study addresses through the exploration and comparison of the perceived helpfulness of sensory experience online reviews, specifically in the hotel industry, before and since the COVID-19 pandemic. Primary data were harvested from the Booking.com website before and during the pandemic; 143,739 online reviews were analyzed using a keyword search based on six dimensions of hotel services to identify those reviews with sensory experience content. The analysis applied Herzberg’s two-factor theory, where each service attribute was examined as both positive (satisfier) and negative (dissatisfier). Empirical analytical methods were applied to produce compelling findings. The findings indicate that the reviews of multisensory experiences affect the perceived value of a post both negatively and positively, respectively, and that the pandemic did not affect the relationship between reviews and the perceived helpfulness of the reviews. This study has both theoretical and practical implications for researchers and practitioners by applying and building on Herzberg’s two-factor theory of online reviews in the hospitality sector during a period of crisis, as well as addressing a gap in the existing literature on how the pandemic affected the relationships between the online reviews of sensory experiences and their perceived usefulness. Practitioners may find the results useful in how they allocate their resources and focus during such periods to optimize their competitiveness.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141369676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jocelyn Tapia, Paula Fariña, Ignacio Urbina, Diego Dujovne
This study aims to provide valuable insights into consumer preferences for delivery services in online shopping in Chile. The COVID-19 pandemic has accelerated the evolution of delivery and logistics services, leading to increased competition among online stores. Chile, with its highly digitally enabled population and a competitive landscape of online retailers, serves as an ideal reference case for Latin America. By analyzing key delivery attributes such as delivery time, order arrival time range, compensation policies for delivery delays, and delivery prices, we offer valuable insights into consumer behavior. These insights will, in turn, inform the formulation of effective strategies within the online shopping industry. We examine the following aspects: (a) The willingness of consumers to pay for the service attributes; (b) The relative importance assigned to these attributes by consumers; and (c) The relationship between consumer preferences and socioeconomic characteristics. Using Multinomial Logit Models and a database from a Discrete Choice Experiment, we have discovered that the most significant attributes of delivery service are the time until product arrival and the existence of compensation in case of delivery delays. Additionally, we found that consumers are willing to pay more for the same delivery service if the product is large, as large products generally have higher prices. Furthermore, we observed that delivery time preferences vary by gender and for small products, and price sensitivity varies according to educational level, household size, and socioeconomic status. To the best of our knowledge, no previous research of this kind has been conducted for Chile.
{"title":"Examining the Retail Delivery Choice Behavior in a Technology-Aware Market","authors":"Jocelyn Tapia, Paula Fariña, Ignacio Urbina, Diego Dujovne","doi":"10.3390/jtaer19020070","DOIUrl":"https://doi.org/10.3390/jtaer19020070","url":null,"abstract":"This study aims to provide valuable insights into consumer preferences for delivery services in online shopping in Chile. The COVID-19 pandemic has accelerated the evolution of delivery and logistics services, leading to increased competition among online stores. Chile, with its highly digitally enabled population and a competitive landscape of online retailers, serves as an ideal reference case for Latin America. By analyzing key delivery attributes such as delivery time, order arrival time range, compensation policies for delivery delays, and delivery prices, we offer valuable insights into consumer behavior. These insights will, in turn, inform the formulation of effective strategies within the online shopping industry. We examine the following aspects: (a) The willingness of consumers to pay for the service attributes; (b) The relative importance assigned to these attributes by consumers; and (c) The relationship between consumer preferences and socioeconomic characteristics. Using Multinomial Logit Models and a database from a Discrete Choice Experiment, we have discovered that the most significant attributes of delivery service are the time until product arrival and the existence of compensation in case of delivery delays. Additionally, we found that consumers are willing to pay more for the same delivery service if the product is large, as large products generally have higher prices. Furthermore, we observed that delivery time preferences vary by gender and for small products, and price sensitivity varies according to educational level, household size, and socioeconomic status. To the best of our knowledge, no previous research of this kind has been conducted for Chile.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141258719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Romania, the pandemic and post-pandemic effects, coupled with the nearly 80% increase in internet service penetration, have led to an extraordinary acceleration of e-commerce activity. Rising rents and operational costs, heightened financial challenges, and the improved quality and accessibility of internet connectivity have prompted some Romanian SMEs to sell their products and services online or through other online communication networks. In this context, it becomes essential to conduct marketing research to identify factors that could stimulate business performance. The purpose of this study is to assess the impact of e-marketing orientation, sustainability orientation, and technology orientation on the performance of online SMEs in Romania. Hypothesis testing and validation of the proposed construct model were conducted using structural equation modeling with partial least squares (SEM-PLS) and multi-group analysis (PLS-MGA). The research results have indicated that all three independent variables have positive and significant effects on online SMEs’ business performance. Finally, the study suggests that SME managers should focus on integrating these three variables and on selling products and services both nationally and internationally through the internet if they aim for long-term business performance growth.
{"title":"Driving Success: Unveiling the Synergy of E-Marketing, Sustainability, and Technology Orientation in Online SME","authors":"Mirela Cătălina Türkeș","doi":"10.3390/jtaer19020071","DOIUrl":"https://doi.org/10.3390/jtaer19020071","url":null,"abstract":"In Romania, the pandemic and post-pandemic effects, coupled with the nearly 80% increase in internet service penetration, have led to an extraordinary acceleration of e-commerce activity. Rising rents and operational costs, heightened financial challenges, and the improved quality and accessibility of internet connectivity have prompted some Romanian SMEs to sell their products and services online or through other online communication networks. In this context, it becomes essential to conduct marketing research to identify factors that could stimulate business performance. The purpose of this study is to assess the impact of e-marketing orientation, sustainability orientation, and technology orientation on the performance of online SMEs in Romania. Hypothesis testing and validation of the proposed construct model were conducted using structural equation modeling with partial least squares (SEM-PLS) and multi-group analysis (PLS-MGA). The research results have indicated that all three independent variables have positive and significant effects on online SMEs’ business performance. Finally, the study suggests that SME managers should focus on integrating these three variables and on selling products and services both nationally and internationally through the internet if they aim for long-term business performance growth.","PeriodicalId":46198,"journal":{"name":"Journal of Theoretical and Applied Electronic Commerce Research","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141258730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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