Electronic Marketplace Research Articles

Examining Farmers’ Usage Behavior on Agricultural E-Markets: Integrating UTUAT2 and Swift Guanxi Factors

The agricultural sector recognizes the potential of electronic marketplaces (e-markets) in enhancing efficiency, market access, and pricing over traditional markets. Despite this acknowledgment, farmers’ adoption of these platforms in developing countries remains limited. This study examines the determinants of farmers’ usage behavior on agricultural e-market platforms by integrating the UTUAT2 and swift guanxi factors. The study employed a self-administered questionnaire to gather data from 330 farmers in India who had exposure to agricultural e-markets and utilized PLS-SEM to analyze the data collected through purposive sampling. The study found that UTAUT2 and swift guanxi factors significantly influence farmers’ intentions to adopt agricultural e-markets, with the exception of effort expectancy. The outcomes of the multigroup analyses indicate that both educational qualifications and crop type significantly influence farmers’ usage behavior. This study contributes to practical applications and academic literature by integrating the UTAUT2 framework and swift guanxi concepts in the context of the agricultural e-market. Notably, while all dimensions prove significant, the negative impact of effort expectancy on usage intention stands out, a departure from previous e-commerce studies. This study enriches the technology adoption literature by uncovering the pivotal factors shaping farmers’ adoption of e-market platforms in agriculture.

Online Purchasing Decisions Affected by Social Factors and Functionality

Online shopping has been experiencing continuous growth over the past few decades, a trend that was further accelerated by the COVID-19 pandemic. There is no expectation that this trend will slow down in the near future. The goal of this paper is to investigate specific factors, which could affect purchasing decisions on the Internet. We created two models, tested and compared them applying logistic regression on the sample of 1318 adults. Model 1 was designed to test the importance of other customers’ reviews by purchasing decisions. Model 2 tested the financial/non-financial benefits of online shopping. In model 1, we identified these statistically significant predictors related to social characteristics 1. Gender, 2. Study at university, 3. Identification with statement, 4. Purchase on electronic marketplaces, and with functionality: 5. The most trust-inspiring e-shop function, 6. Comparison of similar products from different sellers before purchasing. These factors explain, according to Nagelkerke R, 0.196 variability. In the second model for the social characteristics were: 1. Type of settlement, and for functionality: 2. Preferred payment option, and they explain 0.0341 variability of the dependent variable.

Economic role of online review filtering systems in the electronic marketplaces

Economic role of online review filtering systems in the electronic marketplaces

Dynamic effects of parallel selling channels on the electronic marketplace reputation and performance

Dynamic effects of parallel selling channels on the electronic marketplace reputation and performance

A Study Over Constructive Role of Delivery Services in Intensifying Customer Loyalty in E-Commerce Business: An Empirical Study in Delhi

The internet has evolved into a trustworthy community for the transaction of items and services. Because online purchases do not include face-to-face interaction, a variety of factors may impact on purchasers' purchasing intentions. Aside from appearance and usefulness, trust is an important factor that determines customers' decisions about an online business. Online retailers must devise tactics to keep loyal and trustworthy clients. This paper investigates the development and/or enhancement of customer loyalty in online retail. The COVID-19 epidemic has accelerated global market e-commerce growth and strengthened ties amongst online merchants. Businesses look for more sophisticated online shopping dimensions models. It can be used to customize services for customers. With the introduction of electronic commerce and online consumer buying patterns, theorists and practitioners of marketing have begun to understand the importance of developing and sustaining e-loyalty in electronic marketplaces. Managing client trust, happiness, and loyalty sentiments when using the services of e-commerce is critical for longterm business success. It becomes more crucial for online shopping as e-commerce competition heats up. sample of 320 respondents from e-commerce business has been considered in the study to know the role and impact of delivery services in intensifying customer loyalty in e-commerce business and the study concludes that there is significant impact of delivery services in intensifying customer loyalty in e-commerce business.

Моделирование процессов сбыта в системе «производитель – маркетплейс»

Introduction. E-commerce is becoming one of the priority channels for the distribution of goods. Marketplaces with their large segments of the target audience and a wide range of logistics, marketing, information, and other services are the most extensively growing e-platforms. It seems relevant to use mathematical tools to describe various schemes of interaction between manufacturers and marketplaces since by now scientific papers consider only theoretical issues of cooperation between manufacturers and marketplaces and do not outline the elements of this system. Purpose. The study investigates the basic schemes of interaction between manufacturers and marketplaces and develops a universally applicable economic and mathematical model of interaction between manufacturers and marketplaces. Materials and Methods. The article examines theoretical and methodological approaches to the organization of cooperation between manufacturers and electronic marketplaces to identify the cooperation models relevant for the Russian marketplaces, their features, advantages and disadvantages. Results. The authors developed a fulfillment-based economic and mathematical model of the organization of the manufacturer’s sales system provided the goods are safely stored in the warehouse of the marketplace. The model defines the functions of the manufacturer’s revenue as the volume of sales on the online platform and the costs of warehousing, transportation, marketing promotion, commission fee and other related costs to maximize the manufacturer’s profit, determines restrictions on the number of goods sold, stored and manufactured, the volume of goods in stock and the seller’s rating on the marketplace. Conclusion. The paper describes a universally applicable model for manufacturers using the first-level sales channel as a marketplace with no distributors, wholesalers, and retailers, and marketplaces providing a range of logistics services, including warehousing, sorting, and delivery of goods to customers. Further research suggests developing a model for manufacturers’ interaction with marketplaces to explore possible channels for the distribution of products in case goods are stored in their own warehouses and retail chains’ warehouses.

Intention to Sell on E-Marketplace: Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Price Value

The rapid growth of electronic marketplaces in Indonesia, coupled with government encouragement for businesses, necessitates a thorough understanding of sellers' adoption factors. This study investigates the influences on e-marketplace application adoption among active Indonesian sellers, incorporating gender, age, and experience as moderating variables. Employing SMARTPLS4 and PLS SEM analysis, the research identifies significant impacts of effort expectancy, performance expectancy, and price value on e-marketplace selling behavior. Contrarily, facilitating conditions and social influence show no effect. Age moderation significantly influences effort expectancy and price value, emphasizing the importance of tailored strategies for different age groups. Gender and experience, however, do not significantly moderate the results. Sellers' expectations emphasize the need for stakeholders to ensure fairness in online transactions, urging the government to establish appropriate e-marketplace regulations, aligning with sellers' needs for a thriving digital marketplace ecosystem.

E-customer preferences on sustainable last mile deliveries in the e-commerce market: A cross-generational perspective

Research background: In the last few years, e-commerce market has increased in population shares, but the situation has changed dramatically since the Covid-19 pandemic. Electronic marketplaces have changed due to rapid digitalization and shopping. Online services offer the possibility to choose a different delivery method such as home delivery or out-of-home delivery. This aspect of the e-commerce market faces an increased interest among practitioners and academia in the field of sustainable last mile deliveries. Interestingly, the subject literature consists of papers analyzing the e-commerce impact on the last-mile delivery. However, the identification of factors for choosing a delivery method and factors that motivate e-customers to choose an eco-friendly delivery method is still an unrecognized field of research. Purpose of the article: The authors of the paper focused on the e-customer perspective on sustainable deliveries in cities. Thus, the main purpose of the paper is to compare factors among the generations that motivate e-customers for choosing a delivery method. Methods: The research was conducted among 1.110 e-customers in Poland in 2021. The paper aims to answer the following research question: what factors motivate each generation for choosing a delivery method? To answer the above-mentioned question, the correspondence analysis (MCA) is prepared that help to identify and compare factors in each generation. Findings & value added: The original research procedure focused on the use of multivariate statistical methods in the study of e-customers’ preferences. The analysis revealed three clusters of e-customers in terms of pro-sustainable factors: (a) aged 65+ without pro-sustainable tendency, (b) aged 18–64 with pro-sustainable attitudes, and (c) mixed with no identified delivery preferences. As a result of the research, it can be concluded that the parcel price and the possibility of free return are still the most important factors in choosing the delivery method. From a business/practical perspective, the research results can be used by companies that are the main stakeholders in last mile deliveries, including mainly forwarders and transport companies.

Investigating the role of utilitarian and hedonic goals in characterizing customer loyalty in E-marketplaces

Despite significant growth in sales in recent years, retaining customers remains a major challenge for the electronic marketplace (e-marketplace) industry worldwide, including Indonesia. The small basket size of Indonesian customers has created a highly price-sensitive market, making it difficult to nurture customer loyalty. This study investigates the factors affecting consumer behavior and loyalty in Indonesian e-marketplaces by employing a newly proposed E-Marketplace Customer Loyalty Model. Since customers' expectations have extended from mostly utilitarian-oriented goals to incorporate hedonic goals, the proposed model includes both utilitarian and hedonic-based constructs by integrating the Expectation-Confirmation Theory, e-service quality, and the Hedonic Information Systems Model. The proposed model was tested using a comparative approach of machine learning classification algorithms and partial least square, aiming to create a more robust model. The PLS analytical results of ECLM hiearchical component model from 678 customers show that the fulfillment of hedonic values via perceived enjoyment has a greater impact on customer satisfaction than utilitarian values of perceived service quality. Perceived enjoyment, personalization, and customer satisfaction positively affect customer loyalty. The classification results provide further evidence for all hypothesized relationships of the ECLM. The Sequential Minimal Optimization (SMO) algorithm has demonstrated superior performance compared with other classifiers in predicting the dependent variable in most cases. Based on findings, this study offers theoretical and practical implications, and recommendations for sustainable loyalty programs in e-marketplaces.

Perceptions of Shopee and Tokopedia: UMSIDA Management Students' Comparative Analysis

This qualitative research with a qualitative descriptive approach aims to explore the views of Management Study Program students at UMSIDA university regarding the ease and benefits of Shopee and Tokopedia e-commerce platforms. Through interviews with 100 students, including 7 informants who were users of both platforms, the research findings indicate that both Shopee and Tokopedia are highly regarded as online shopping sites. Students, being millennials, prioritize convenience and value the extensive product range offered by these platforms. However, the preference of UMSIDA Management Study Program students leans towards Shopee due to perceived affordability and a wider product selection. The implications of this study highlight the significance of user-friendly e-commerce platforms that cater to the needs and preferences of students, thus enabling easy access to online shopping anytime and anywhere.
 Highlights:
 
 
 Ease and benefits of Shopee and Tokopedia: The research explores the views of Management Study Program students at UMSIDA regarding the convenience and advantages offered by both Shopee and Tokopedia e-commerce platforms.
 
 
 Comparative analysis: The study provides a comparative analysis of Shopee and Tokopedia, highlighting the preferences and opinions of UMSIDA students. It sheds light on factors such as product availability, pricing, and overall user experience.
 
 
 Implications for students and e-commerce platforms: The findings have implications for both students and e-commerce platforms. Students' preferences for Shopee over Tokopedia due to perceived affordability and a wider product range reflect the importance of catering to user needs. E-commerce platforms can use this information to enhance their offerings and improve user satisfaction.
 
 
 Keywords: Shopee, Tokopedia, E-commerce, Management Study Program, UMSIDA

Effects of electronic markets on prices, spikes in prices, and price dispersion: A case study of the tea market in India

AbstractBuyers and sellers in developing countries are often restricted from accessing distant markets by asymmetric price information and costly searches. Electronic marketplaces can reduce transaction costs and improve market performance. This study uses monthly panel data from 2000 to 2017 and applies a fixed effects approach using Driscoll and Kraay standard errors to address spatial and temporal correlations to provide empirical evidence on the effects of electronic markets on prices, spikes in prices, and price dispersion of an agro‐based commodity in India. The findings indicate that, between 2000 and 2017, the introduction of electronic markets reduced prices and short‐term variability in tea prices by nearly 2%. Moreover, electronic markets initially increased price dispersion between markets by 11%–14%; however, with further reduction in market friction over time, price dispersion reduced by 16%. [EconLit Citations: Q11, Q13].

Emotion detection of social data: APIs comparative study

The development of emotion detection technology has emerged as an efficient possibility in the corporate sector due to the nearly limitless uses of this new discipline, particularly with the unceasing propagation of social data. In recent years, the electronic marketplace has witnessed the establishment of various start-up businesses with an almost sole focus on building new commercial and open-source tools and APIs for emotion detection and recognition. Yet, these tools and APIs must be continuously reviewed and evaluated, and their performances should be reported and discussed. There is a lack of research to empirically compare current emotion detection technologies in terms of the results obtained from each model using the same textual dataset. Also, there is a lack of comparative studies that apply benchmark comparisons to social data. This study compares eight technologies: IBM Watson Natural Language Understanding, ParallelDots, Symanto – Ekman, Crystalfeel, Text to Emotion, Senpy, Textprobe, and Natural Language Processing Cloud. The comparison was undertaken using two different datasets. The emotions from the chosen datasets were then derived using the incorporated APIs. The performance of these APIs was assessed using the aggregated scores they delivered and the theoretically proven evaluation metrics such as the micro-average of accuracy, classification error, precision, recall, and f1-score. Lastly, the assessment of these APIs incorporating the evaluation measures is reported and discussed.

Demand-Response Control in Smart Grids

In the smart grid, electricity price is a key element for all participants in the electric power industry. To meet the smart grid’s various goals, Demand-Response (DR) control aims to change the electricity consumption behavior of consumers based on dynamic pricing or financial benefits. DR methods are divided into centralized and distributed control based on the communication model. In centralized control, consumers communicate directly with the power company, without communicating among themselves. In distributed control, consumer interactions offer data to the power utility about overall consumption. Online auctions are distributed systems with several software agents working on behalf of human buyers and sellers. The coordination model chosen can have a substantial impact on the performance of these software agents. Based on the fair energy scheduling method, we examined Vickrey and Dutch auctions and coordination models in an electronic marketplace both analytically and empirically. The number of software agents and the number of messages exchanged between these agents were all essential indicators. For the simulation, GridSim was used, as it is an open-source software platform that includes capabilities for application composition, resource discovery information services, and interfaces for assigning applications to resources. We concluded that Dutch auctions are better than Vickrey auctions in a supply-driven world where there is an abundance of power. In terms of equity, Dutch auctions are more equitable than Vickrey auctions. This is because Dutch auctions allow all bidders to compete on an equal footing, with each bidder having the same opportunity to win the item at the lowest possible price. In contrast, Vickrey auctions can lead to outcomes that favor certain bidders over others, as bidders may submit bids that are higher than necessary to increase their chances of winning.

Inventory competition on electronic marketplaces – A competitive newsvendor problem with a unilateral sales commission fee

We present a competitive newsvendor problem with a sales commission paid by one newsvendor to another newsvendor when selling a product. Customer demand is stochastic, and customers individually decide with given probabilities from which newsvendor they want to order or whether they do not want to order at all. These probabilities can vary depending on which newsvendor is out of stock. The problem described arises when marketplace operators offer the same or substitutable products as third-party vendors and therefore directly compete with third-party vendors on their platform. Our research is motivated by practical cases such as the Amazon marketplace, where Amazon is the marketplace operator that sets the sales commission and, simultaneously, directly competes with third-party vendors. Both the marketplace operator and a competing third-party vendor should ideally account for the other party's behavior when deciding their order quantity. We calculate the noncooperative Nash equilibrium and the optimal cooperative order quantities (centralized solution). Additionally, we emphasize analyzing the effect of the sales commission on the optimal order quantities and the gross profits of the two parties.

User switching intention from E-marketplace to E-pharmacy: The Influence of push, pull, and mooring factors

The COVID-19 pandemic triggered a shift in medicine purchasing behaviors worldwide, including in Indonesia, from physical pharmacies to online platforms such as electronic marketplaces (e-marketplaces) and electronic pharmacies (e-pharmacies). However, shopping for drugs through e-marketplaces does not always guarantee quality and safety, especially since drugs are high-risk products. Considering this issue, the present study was conducted to determine the factors that can motivate Indonesian people to switch to e-pharmacies, which are directly managed by the pharmacies themselves and thus offer safe processes and products. The push–pull–mooring theory and the DeLone and McLean information system success model were used in the study. Questionnaire data were collected from 778 respondents, and 30 respondents were in-depth interviewed. Partial least square structural equation modeling was conducted to process the quantitative data obtained, and a content analysis was used for the qualitative data. The research findings showed that push, pull, and mooring factors influence the intention to switch to an e-pharmacy, in turn affecting actual switching behaviors. The results provide valuable insights into how e-marketplaces can deliver the quality and security expected by their users, with regulators to provide strict regulations, and how e-pharmacies can strengthen their features for added value over e-marketplaces.

ML in the Electronics Manufacturing Industry

The manufacturing of electronics is renowned for emphasizing efficiency and precision. A single error can result in a defective unit, and a defective unit is a loss. The electronic marketplace is arguably the business that has risen to the top the quickest. Particularly in the electronics manufacturing industry, AI and ML have a wide range of uses, from waste reduction to improved forecasts and quality control. Manufacturers may lower expenses, cut down on mistakes, streamline supply chains, and boost productivity across the board with machine learning. At its core, ML uses statistical and probabilistic methods to draw insights from data and make predictions. Manufacturers face some difficulties as a result of the widespread use of electronic devices and systems and the complexity of their production. AI and ML have swiftly established themselves as indispensable instruments for streamlining the production process. It can be helpful to observe how AI and ML are being used in an actual manufacturing setting to fully grasp their potential. The application of Machine Learning in the electronics industry is a revolutionary development that has opened up a world of possibilities. It has enabled manufacturers to improve productivity, reduce costs, and create products that are more tailored to consumer needs. With its ability to provide a more efficient way of analyzing data and making decisions, Machine Learning can help electronics companies to better understand consumer behaviour and develop products that are better suited to customer preferences.

IoT Changing the Electronics Manufacturing Industry

Manufacturing companies supply goods and services to larger businesses, which makes them an essential part of the global value chain. The electronics industry is undergoing a rapid transformation due to the Internet of Things (IoT). The company that has probably risen to the top the fastest is the electronic marketplace. IoT is the ability to efficiently gather and distribute data when all physical objects have connections to the internet. By attaching sensors to these devices, digital intelligence is created, enabling real-time data communication without the need for human intervention. The introduction of IoT in the electronic manufacturing sector aims to further transform the sector's operating and managing practices by reevaluating the basic working process. Moreover, utilising IoT in the electronics sector will assist in overcoming the obstacles that the pandemic has brought about. IoT technology has changed the way manufacturers interact with their customers, allowing them to quickly respond to customer needs and demands. With the use of IoT sensors, manufacturers can monitor and control the quality of their products, ensuring that they meet customer expectations. Additionally, IoT technology has allowed manufacturers to quickly and accurately track inventory levels, allowing them to better manage their resources and reduce waste.

ОСОБЕННОСТИ СОВРЕМЕННОГО РАЗВИТИЯ МАРКЕПЛЕЙСОВ

The article points to the relevance of the study of electronic marketplace sites both in Russia and abroad, which is of particular importance during the intensification of digital transformation of trade, identifies key features of the modern development of marketplaces, presents the results of the survey of consumers of marketplaces carried out by the authors, formed conclusions on the development of marketplaces with taking in to account the results obtained.

Анализ рынка маркетплейсов в России и перспективы его развития для финансовой стабилизации экономики

The challenges of Russian economy require entrepreneurial activity increase and technologies extension to develop entrepreneurship. Online trading on electronic marketplaces platforms is one of such factors of successful business development at the startup stage and its promotion. At present, the marketplaces leaders are already successfully operating in the Russian markets. Such marketplaces as Wildberries, Ozon, AliExpress, SberMegaMarket, Yandex Market are among them. The marketplace market is developing. Competent analytics is needed for its effective functioning. Digital marketplace market analytics services are being created in the country, which allow obtaining the necessary data to assess the business functioning and its development prospects. Problems and opportunities, trends and prospects of marketplaces development for financial stability of the country determine the study relevance. The purpose of the article is to review the features of Russian marketplaces functioning, to study the specifics of the marketplaces analysis and to present its analytics, to identify prospects and forecasts of e-commerce market development. Digital analytics, comparative evaluation, and review of information services, research portals and organizations (Data Insight, IContext Group, INFOline, etc.) were used in the article. As a result of the conducted research, the following results were obtained: literary review was conducted to understand the essence of e-commerce, and its advantages and prospects. The largest marketplaces were compared on the sales volume, commission amount and the number of audience to reveal marketplaces leaders. External and internal indicators of the marketplace market were summarized, including financial performance indicators. An overview of analytics services about marketplace markets to obtain data for analysis is given. Trends in the development of e-commerce market were identified.

The effects of technology, organisation and environmental factors on small firm entry to electronic marketplace: a developing country perspective

The effects of technology, organisation and environmental factors on small firm entry to electronic marketplace: a developing country perspective