E-commerce Case Research Articles

Research on the Mode of E-Commerce Assisting Agricultural Innovation and Entrepreneurship under the Background of Platform Economy—A Case Study of E-Commerce Assisting Farmers in Wenchuan County

This paper takes the case of e-commerce aiding agriculture in Wenchuan County as an example to analyze the specific practices and economic benefits of e-commerce aiding agriculture in Wenchuan County. It is discovered that there exist problems such as backward infrastructure construction, shortage of skilled talents, and insufficient market credibility in e-commerce aiding agriculture in Wenchuan County. According to the innovation theory and in combination with the background of platform economy, this paper puts forward strategies and suggestions such as innovating the supply of industrial space, strengthening the introduction and cultivation of talents, and guaranteeing the quality and safety of agricultural products, with the aim of providing references for the development of rural e-commerce.

Infinite Potential of AI Chatbots: Enhancing User Experiences and Driving Business Transformation in E-commerce: Case of Palestinian E-Commerce

In the much-evolving digital age landscape, it is difficult to overlook artificial intelligence's enormous role in people. This study entails an empirical examination of the impact of AI-powered chatbots on improving customer experience, customer satisfaction, and potential benefits in the digital era. This study was handled by the use of quantitative data collection methods through an online survey from 221 online users of AI-powered chatbots in Palestine. The collected data was then analyzed using descriptive statistics and structural equation modeling techniques. According to the results, it was shown that service quality significantly influenced the intention to use chatbots by customers or users thus indirectly influencing the net benefits enjoyed by users in the digital era. Similarly, the service quality provided by AI-powered chatbots was found to significantly influence the intention to use them, thus indirectly influencing the net benefits of AI-powered chatbots. Additionally, service quality was found to influence user satisfaction with chatbots, which indirectly influenced the net benefits enjoyed by users/customers in the digital era. On the other hand, user satisfaction significantly and directly influenced the net benefits of AI-powered chatbots in the digital era. In this regard, this study significantly contributed to the AI-powered chatbot's body of knowledge in the Palestinian digital context by identifying the factors that influence the use of chatbots in the digital era from the users’ point of view with the capacity to help transform the Palestinian business landscape

Determinants of Customer Loyalty (Shopee E-Commerce Case Study)

Determinants of Customer Loyalty (Shopee E-Commerce Case Study)

Mengoptimalkan Penjualan Online Melalui Teknik Data Mining (Studi Kasus E-Commerce)

The aim of this research is to optimize online sales through data mining techniques (e-commerce case study). This type of research is a literature review. Data collection with documentation. Data analysis with SLR. Research result. Research results The use of data mining techniques in optimizing online sales, especially in the context of e-commerce, can provide significant benefits for companies. By analyzing purchasing patterns and consumer behavior using data mining algorithms, companies can identify customer trends and preferences, improve promotional targeting, and optimize marketing strategies. This not only improves operational efficiency, but also results in a significant increase in sales. Thus, the integration of data mining techniques becomes a necessity for e-commerce companies that want to remain competitive and successful in an increasingly competitive market

Identify Location Characteristics of Tourism Accommodation that are Influenced by e-Commerce Case Study: Lembang Tourism Area, Kab. West Bandung

The presence of the Industrial Revolution 4.0, which is marked by the rapid development of the internet, has fundamentally changed the way humans live, work, and communicate with each other. This development has also influenced the development of the business of providing accommodation in tourist areas. The ease of obtaining information via an internet network that is connected to regional areas opens up opportunities for the public to market tourist accommodation through e-commerce accommodation. The Lembang tourist area is an area with high potential for the development of e-commerce accommodation, covering 25.64% of tourist attractions in West Bandung Regency. This research aims to determine trends and developments in the characteristics of business locations providing accommodation in the Lembang tourist area based on observations via digital platforms. Data was obtained using a spatial analysis method with two different functions. The classification function is used to review location characteristics in businesses providing accommodation based on road class. The neighborhood function is used to review location characteristics based on proximity to tourist centers. The data was then analyzed descriptively and qualitatively. The results of the research show that the development trend of e-commerce accommodation in accommodation provision businesses continues to grow from year to year. Observation results via digital platforms show that as many as 136 accommodation business units were incorporated into e-commerce accommodation in 2019 in the Lembang tourist area. The location characteristics of the business providing accommodation tend to be concentrated around tourist areas with a radius of 1 km from the tourist center. Judging from the characteristics of business locations providing accommodation on roads, it is known that 59% of business units are predominantly located on neighborhood roads, while 41% are on main roads. The ease of access offered by this digital platform influences the development of business providing accommodation and location on the road class but does not significantly affect the distance to tourist centers.

Warehouse Location Optimization with Clustering Analysis to Minimize Shipping Costs in Indonesia’s E-Commerce Case

Due to the growth of the Internet economy, the popularity of online shopping has escalated in recent years. One of the largest e-commerce enterprises in Indonesia, PT. S, is the subject of the research in this article. Instead of typical e-commerce, where anybody may start a store, PT. S is concentrating on social commerce, which makes use of several resellers to offer hand-picked SME brand partners. PT. S must expand the market for inter-island or non-java-to-non-java transactions to fulfill its vision. However, PT. S will have logistical difficulty completing this job. The business used performance indicators to keep track of the logistics process’ vision and mission. Gross merchandise value, pickup time service level, and shipping time service level are a few of the performance indicators that pertain to logistics. The process of managing the supply chain will become more complex as a result of the opening of the new warehouse, and the business will need to maximize its use of various selling channels, logistical services, and supply chain management. With the aid of clustering analysis, which assesses demand similarity and proximity, the enterprise can locate a new warehouse. Durairaj and Kasinathan developed the framework template for this study in 2015. Based on the case study, literature review, and clustering method framework, the framework will be modified in several ways, particularly clustering analysis. The alteration concerns framework-integrated theories as an input and as a data source. According to the simulation’s findings, shipping costs per kilogram decreased by about 35% for five clusters. But if the corporation does not have a problem with the number of warehouses, according to the simulation’s findings, because the cost of transportation will go down as the number of clusters increases, the number of warehouses can be expanded to more than five.

Geographical relevance-based multi-period optimization for e-commerce supply chain resilience strategies under disruption risks

With the fierce competition in e-commerce, e-tailers are required to rapid responses to a variety of customised orders with multiple frequencies and strict delivery times. The delay or insufficient supply caused by disruptions might result in lost sales during long-term processes. To address this problem, a two-stage stochastic programming model considering profits, consumer service level (CSL) as well as market priorities is developed to manage long-term disruptions. We analyse multi-period consumer transaction data and formulate geographical relevance (GR) to link each marketplace with historical data in related regions and then prioritise market segments. A GR-based two-stage stochastic programming with multi-period is proposed, which (1) considers both proactive mitigation decisions before disruption and reactive recovery plans after disruption; (2) collaborates three resilience strategies; (3) optimises the e-tailer's profits considering market priorities during long-term disruptions. Using a real case of Chinese e-commerce under the COVID-19 pandemic, it is illustrated (1) the applicability and performance of the proposed GR-based model for multi-period resilience optimisation improving both the CSL and the total profit; (2) the efficiency and robustness of the developed sequential particle swarm optimisation with social structures algorithm. The proposed method could optimise e-tailers' response strategies for managing long-term disruptions in practice.

Boundary resource management in innovation ecosystems: The case of e-commerce

Major challenges in contemporary information systems development demand new development approaches, such as innovation ecosystems, consisting of a focal innovation platform surrounded by independent developers. The attraction of third-party developers and the amplification of generativity in extension development call for sophisticated boundary resources. As demarcation points between an innovation platform and external developers, boundary resources entail a strategic value and need to be managed carefully. However, existing research does not provide an approach for the holistic management of boundary resources from design to retirement. We apply a design science research approach consisting of two design cycles involving a literature review identifying 26 application lifecycles and the analysis of eight innovation platforms in e-commerce. We evaluated the model for boundary resource management in interviews with nine domain experts. We develop an integrated boundary resource management lifecycle as a specialization of application lifecycle management for the holistic management of boundary resources in innovation ecosystems addressing third-party developers. The boundary resource management lifecycle consists of four layers: boundary resource governance, continuous communication, technical boundary resources, and supplementary boundary resources. It decouples technical and supplementary boundary resources while emphasizing their intertwined nature for ecosystem participants. Owners of innovation platforms can instantiate the reference procedure model for attracting developers.

Performance measurement of e-commerce supply chains using BWM and fuzzy TOPSIS

PurposeThe purpose of this paper is to persuade a hybrid framework, which can be used to assess the performance of various supply chains and can be further used to segregate supply chains concerning critical KPMs. The KPMs have been selected in the COVID-19 pandemic condition.Design/methodology/approachA real case of e-commerce is presented to illustrate the working of the proposed framework comprising a hybrid methodology of BWM and Fuzzy TOPSIS to measure the performance of the e-commerce supply chains by identifying the critical key performance metrics (KPMs) and measuring the performance of the considered supply chains against these.FindingsThe proposed framework is illustrated using real-time data from experts, collected through interviews and discussions. It is found that rate of return on investment (SCPM 27), flexibility of service systems to meet particular customer needs (SCPM 23) and supplier lead time against industry norm (SCPM 33) are significantly weighed in assessing performance of the selected supply chains, with weights 0.07764, 0.06863 and 0.0547, respectively. Amazon and Flipkart are seen to stand out among the other supply chains taken for the present study with closeness coefficients as 0.945 and 0.516, respectively.Originality/valueThe contemporary world has seen the drastic attack of COVID-19 on many firms worldwide, and hence measuring the performance of the supply chains has become necessary so as to understand the critical factors affecting performance, their relative importance and the firm's relative standings. There have been studies in the recent past where researchers worked on similar motives to generate a framework to measure performance of supply chains, but it is seen that the methodologies lack flexibility with respect to effectively handling large data, uncertainty in human emotions, consistency, etc. This is where the current study stands out in effectively measuring the performance of supply chains so as to aid many firms affected by the pandemic.

Machine learning models to predict the engagement level of Twitter posts: Indonesian e-commerce case study

The growing utilization of social media platforms enables direct interaction between companies and consumers. However, the expanding range of interactions and real-world data complexities necessitate the development of more sophisticated decision models. To address this, the current research focuses on constructing machine learning models, namely multinomial logistic regression, decision tree, k-nearest neighbor, and random forest, to forecast the engagement level of Twitter posts from three prominent e-commerce platforms in Indonesia: Bukalapak, Blibli, and Tokopedia. The analysis comprises a dataset of 12,786 unique tweets, accumulating 11,870,254 favorites and 2,735,886 retweets over a seven-month period from February 1 to August 31, 2021. The prediction models are built upon three theoretical constructs with seven features, encompassing interactivity (e.g., links, hashtags), vividness (e.g., images, short videos, long videos), and temporal factors (e.g., day of post, last post time). Factors such as post frequency, interactive posting elements, and static visual elements emerge as significant features for predicting the engagement level of Twitter posts. Results demonstrate that the random forest model outperforms singular classifier models, including multinomial logistic regression, decision tree, and k-nearest neighbor models, in terms of precision, recall, and F1 score.

Information Society and Taxation: The Case of E-Commerce

Information Society and Taxation: The Case of E-Commerce

Blockchain-Based Smart Contract: Advancing Digital Consumer Protection and Preventing Private International Law E-Commerce Cases

<em>Blockchain has functioned as a ledger that decentralizes controls with immutable and irreversible character and have the potential to overcome the deficiency of traditional contracts, especially in today’s digital era such as the e-commerce industry. Unfortunately, although famous to be used for blockchain and smart contracts have not been applied widely in Indonesia and there is no regulation that specifically regulates the use of blockchain technology and smart contracts. This article will analyze the application of smart contracts to escalate consumer rights in e-commerce services. This research showed that the self-executory characteristic of smart contracts helps the consumer to have an equal bargaining position with businesses actors in determining the contents of the contract. In response to those curative efforts, the smart contract will be advantageous as a preventive scheme for PIL cases. The self-executory character of the smart contract will prevent many PIL cases which are potentially occurred. The immutable nature of blockchain records will also be helpful for any dispute settlement scheme. This might be led to the tendency that international e-commerce cases should not be litigated or to be set for an arbitration tribunal. Those international e-commerce cases might not require settlement of judicative branch and may be settled at the administrative level. Consequently, this would create a more effective and efficient settlement, both in time and money. Those advantages have made blockchain-based smart contracts will be prospective in Indonesia, in the upcoming future</em>

Comparative Carbon Footprint Assessment of Cross-Border E-Commerce Shipping Options

In the bid to stay competitive, online shopping platforms often offer a variety of shipping options to meet the preferences of consumers. While faster delivery might be desirable for consumers, this may be detrimental to the environment. Limited studies have evaluated the comparative environmental impact of different shipping options offered by e-commerce platforms. To fill this gap, this study aims to conduct a comparative carbon footprint assessment of the shipping options available in Taobao, a highly popular Chinese online shopping website. The case of cross-border e-commerce is evaluated, where goods are ordered from China to Singapore as the shipment destination. Thereafter, a shipping choice preference survey is conducted to evaluate the impact of carbon labelling on consumers’ shipping preferences. From the perspective of the consumer, when offered a variety of shipping options to choose from, there is always a trade-off between the cost and the speed of delivery. Additional information on the carbon impact of different options could influence consumers’ decision-making. The shipping options from Taobao are referenced to determine the cost, speed, and carbon emission values for the scenarios presented in the survey. Out of 188 survey respondents, slightly more than half (55%) were found to be willing to compromise the speed of delivery for a less carbon-intensive alternative. Given this finding, the study advocates for carbon labelling to be introduced for e-commerce shipping options.

An Advanced LSTM Model for Optimal Scheduling in Smart Logistic Environment: E-Commerce Case

At present, most logistics systems, especially those dedicated to e-commerce, are based on artificial intelligence techniques to offer better services and increase outcomes. However, the variety and complexity of resource allocation, as well as task scheduling, denote that dynamic environments have still great challenges to overcome. So advanced models based on strong algorithms are required. Introducing advanced models into scheduling solutions is a promising way to enhance logistics efficiency. As a result, managing system resources remain essential to optimize task scheduling respecting the interactive impacts, and logistics systems requirements. In response to these challenges, in this paper, a powerful solution based on a Long short-term memory (LSTM) model is proposed to optimize resource allocation and to enhance task scheduling in a smart logistics framework. This paper explores some of the most important scheduling techniques and hypothesizes that deep learning techniques might be able to afford accurate approaches. The proposed smart logistics model lays on strong techniques, for that, experimental simulations were conducted using various project instances. The validation tests demonstrated competitive results with important performance rates i.e.: accuracy of 92,44% with a precision of 93,83, a recall of 95.18%, F1-score of 94,92%, and an AUC of 88,17%. These results reveal the proof-of-principle for using LSTM models for effective and truthful logistics operations.

The Influence of Service Quality of E-Commerce on Consumer Satisfaction Degree and Repurchase Intention: The Case of Leisure Food E-Commerce in China

In recent years, the proportion of leisure food in E-commerce platforms has kept increasing year by year for its attribute characteristics and the rapid development of E-commerce platforms, but some problems have also emerged. This paper aims at studying the influence of service quality on customer satisfaction and repurchase intention by means of specific division of service quality of E-commerce with leisure food E-commerce being an example. In this paper, the collected data is analyzed in terms of reliability and validity, factor analysis and construction of equation models in the form of questionnaires with software SPSS and AMOS. The conclusions obtained from analysis include: 1. Customers’ expectation before purchasing has a significant positive impact on consumer satisfaction. 2. The assumption that E-commerce web design has a significant positive impact on consumer satisfaction is false. 3. E-commerce logistics has a significant positive impact on consumer satisfaction. 4. The quality of e-commerce products has a significant positive impact on consumers. 5. E-commerce after-sales service has a significant positive impact on consumer satisfaction. 6. Consumer satisfaction has a significant positive impact on repurchase intention.

The Effect of Trust and Satisfaction on Customer Loyalty in Online Shop: Case of C2C E-Commerce in Indonesia

The purpose of this study is to identify user interface quality, information quality, perceived security, perceived privacy, and online customer review as a factor affecting customer trust and customer satisfaction in online business, especially in C2C e-commerce platform in Indonesia. This study also analyzes the effect of customer trust and customer satisfaction as key factors influencing customer loyalty. A quantitative approach has been employed. The data collection using online questionnaire in 206 respondents and measurement using Likert scale. For the purpose of data analysis, Partial Square Structural Equation Modeling (PLS-SEM) has been adopted. This study found that user interface quality and information quality have positive effect on customer trust and customer satisfaction. This study also found that customer satisfaction influencing customer loyalty significantly in Shopee. This study suggests that Shopee as an e-commerce in Indonesia must focus on their customer trust and customer satisfaction strategies by increasing the quality of user interface quality and information quality to maintain the loyalty of their customers.

Cybersecurity and Custom Regulations as Trade Barriers in ASEAN e-Commerce: Case of Indonesian e-Commerce

ASEAN countries show tremendous potential for e-commerce growth. Boasting its 650 million population and massive internet users, ASEAN proves to be a significant market for e-commerce and digital economy in general. Nonetheless, there are still some significant barriers in e-commerce trade, both traditional and non-traditional barriers of trade. Those barriers include a lack of harmonized regulations between the ASEAN Member States, high tariff duties on imported goods, and weak consumer protections (and overall cybersecurity) in the region. This study explores these barriers, which hinder ASEAN's goal to achieve more robust growth in the digital economy, particularly in terms of the legal framework (custom harmonization) and cybersecurity. In order to delve more deeply into these impediments of e-commerce trade, this article also attempts to present a study case of Indonesia's e-commerce as the most prominent and most promising player in ASEAN. Keywords: ASEAN, e-commerce, digital trade, digital economy Negara-negara ASEAN menunjukkan potensi luar biasa bagi pertumbuhan e-commerce. Dengan jumlah penduduk 650 juta dan banyaknya pengguna internet, ASEAN terbukti menjadi pasar yang signifikan bagi e-commerce dan ekonomi digital secara umum. Meskipun demikian, masih terdapat beberapa hambatan signifikan dalam perdagangan e-commerce, baik hambatan perdagangan tradisional maupun non-tradisional. Hambatan-hambatan itu termasuk kurangnya regulasi yang harmonis antara negara-negara anggota ASEAN, bea masuk yang tinggi untuk barang-barang impor, dan lemahnya perlindungan konsumen (serta keamanan cyber secara keseluruhan) di dalam kawasan. Penelitian ini mengeksplorasi hambatan-hambatan yang menghambat tujuan ASEAN untuk mencapai pertumbuhan yang lebih kuat dalam ekonomi digital, terutama dalam hal kerangka hukum (harmonisasi aturan) dan keamanan cyber. Untuk menggali lebih dalam hambatan-hambatan perdagangan e-commerce ini, tulisan ini juga mencoba untuk menyajikan studi kasus e-commerce Indonesia sebagai pemain terbesar dan paling menjanjikan di ASEAN. Kata-kata kunci: ASEAN, e-commerce, perdagangan digital, ekonomi digital

Factors affecting online purchase intention: the case of e-commerce on lazada

This study aims to explore the scale and measure of the impact of factors affecting theonline shopping intention of the consumer on the Lazada e-commerce website in Ho Chi Minh City. The study confirms the theoretical analysis of consumer behavior (Theory of Reasoned Action - TRA), (Theory of Planned Behavior – TPB), as well as compares the research articles related to online shopping intention of domestic and foreign authors. From the survey results from 300 customers, the author pointed out that six factors positively affecting online purchase intention include usefulness - convenience, trust, behavior control awareness, business competency, and reference group opinion. The other factor is the perceived risk that has negative affect customers' online shopping intentions. Since then, the research offers the causes, solutions, implications to help traders on e-commerce sites capture the needs and psychology of customers and help them partially improve their ability to attract customers online shopping in Ho Chi Minh City.

Thailand’s E-Commerce Ecosystem: Understanding Business Formalization Within the Framework of Tax and Consumer Protection Regulations

Thailand’s e-commerce industry is growing fast and evolving rapidly. Currently, the majority of e-commerce SME sales occur on a handful of foreign-headquartered platforms: Lazada, Shopee, Facebook, Instagram and LINE. Meanwhile, business formalization amongst e-commerce SMEs is low. A minority of e-commerce SMEs are tax compliant, and e-commerce cases make up a disproportionate number of all consumer protection cases. Using interviews with industry participants and a literature review, this study outlines Thailand’s e-commerce ecosystem and its emerging regulatory framework. It analyses how e-commerce SMEs operate with regard to tax and consumer protection regulations. Using these insights, the study offers policy recommendations for the regulatory framework. The analysis points to emerging structural weaknesses in the regulatory framework, exacerbated by simultaneous trends of globalisation and localisation. Four main issues are identified. First, e-commerce is changing rapidly and forcing regulators across the world to catch-up. Second, regulators in emerging markets cannot simply import regulation from technologically-advanced countries, as the industry is developing simultaneously in countries across the world. Third, localized use of global platforms is creating regulatory fracture, where gaps are opening up in regulation, creating opportunities for businesses to undertake regulatory arbitrage. Fourth, as e-commerce networks have ‘winner takes all’ characteristics, regulatory decisions made now are critical, as they will affect the industry in the future. At a national level, Thailand’s regulators need to find strategic, regulatory coherence to streamline the plethora of regulations that apply to e-commerce and regulate effectively. Regulators need to understand the feedback loops in the industry, across regulators, businesses and consumers. Regulatory policies need to support the e-commerce ecosystem, ensuring that opportunities for regulatory arbitrage are rare and unprofitable. Three policy recommendations are offered, in particular: increasing regulatory coherence to make it easier for businesses to comply; reducing regulatory arbitrage at international and national levels; and promoting competition in ‘winner takes all’ markets.

Design of E-Commerce Gift Shop Case Study MR. Kuta Bali

E-commerce is an alternative which promising enough applied to companies at this time, because of e-commerce provide facilities for both sides, which is between merchant and customer. Although which transactions are conducted of being in two different though the continent, any transaction not there should have been negotiation stage and one of with poor this is a company gift shop. All this in MR.KUTA BALI, the transaction was done by using konvesional namely where clients visit directly to that place to choose and purchase products gift shop. The purpose of research is of designing and constructing system gift shop e-commerce case studies MR.KUTA BALI. Data collection is done by interviews to assistant general manager of the company gift shop mr.kuta bali by mrs. Umi Nur Aini. System building design was conducted using modeling DFD and the ERD to contrive in terms of relationships between table necessary. E-commerce system gift shop this they use of PHP language and in testing stage system done by using the method blackbox testing. The result has been testing the system in accordance with needs functionality designed.