International Journal of Electronic Business (17 papers in press)
Predicting P2P Lenders Decisions: The Prospect Theory Approach
by Yong Lu, Zhexiang Sheng, Kaidong Zhang, Qiang Duan
Abstract: This study investigates the importance predictors for lenders decisions on peer-to-peer lending based on prospect theory. We apply two machine learning algorithms (decision trees and random forest) to identifying the important measures. We found that borrowers default history is the most important variable, followed by the default ratio of the borrowers other type of friend and borrowers credit score as lender. These results prove that lenders play safety rule in the highly risky P2P lending business. Maximum entropy algorithm verifies these results and proves the robustness of our model.
Keywords: Prospect Theory; Machine Learning; P2P Lending.
Antecedents of the intention to use electronic payment: evidence from individual and household retailers in Vietnam
by Thi Minh Ngoc Luu, Phuong Mai Nguyen
Abstract: In recent years, electronic payment is becoming more popular in businesses worldwide. The purpose of this study is to analyze the factors affecting the intention to use the electronic payment of individual and household retailers in Vietnam by using an extended technology acceptance model adopted from the study of (Venkatesh and Davis, 2000). We collected data from 773 individual and household retailers through an online self-administered questionnaire survey in the three largest cities of Vietnam, including Hanoi, Ho Chi Minh City, and Da Nang. Structural equation modelling (SEM) analysis was used to test the research hypotheses. Research findings prove that perceived ease of use, perceived usefulness, security, cost, and effort expectancy positively influence the intention to use the electronic payment of individuals and household retailers. However, there is not enough statistical evidence to conclude about the relationship between social influence and the intention to use electronic payment.
Keywords: electronic payment; technological acceptance model; retail industry; Vietnam.
DISTRACTED DRIVER RECOGNITION SYSTEM USING DEEP FOREST
by Moolchand Sharma, Ananya Bansal, Utkarsh Agrawal, Pramod Goyal
Abstract: This paper looks at various images of distracted drivers taken from people performing different actions, some of which can be deemed as distracting while behind the wheel of a car. Developing a real-time system, which takes in a live video feed from the dashcam as the input. Distracted driving is an ongoing problem that seems only to be getting worse with the dependence on technology. A Convolutional Neural Network has already been used to predict what activity a driver is being distracted by. We have used deep forest, which isrna recently researched algorithm, developed as an alternative to deep learning models based on neural networks, by developing deep learning models based on non-differentiable modules like decision trees. Our focus is on implementing deep forest for classification and comparing the results with other techniques. It is an ensemble-based decision tree approach that emphasizes on building deep models using modules which are non-differentiable. The use of deep forest models to classify ten types of distracted drivers led to an increase in the accuracy of the prediction of the distracted drivers when compared with neural network models. The recognition of the driver as inattentive can be further used to trigger an alert or some cautionary actions. The success of the models will, hopefully, one day, aid combat the ongoing and increasing issue of distracted drivers on the roads.
Keywords: Convolution neural network; deep forest; decision trees; ensemble-based; non-differentiable,rndeep learning.
Factors Influencing Trust in Social Commerce: The Case of Qatar
by Hamad Al Kubaisi, Emad Abu-Shanab
Abstract: The global spread of social media platforms, along with the technology acceptance, has contributed significantly in accelerating the birth of social commerce, which is one of the most prominent advancements of e-commerce. To keep up with the trend, online vendors or social vendors need to improve customers' trust towards social commerce to enhance customer engagement and to leverage the potential power of social networking. This research aims at studying the factors influencing trust in Social commerce in the context of Qatar. The proposed research model adopted seven different factors that are assumed to influence trust in social commerce in Qatar. These factors include Platform Involvement (PI), Information Quality (IQ), Perceived Privacy Protection (PPP), Trust Disposition (TD), Informational Support (IS), Social Commerce Constructs (SCCs), and Reputation of Online Vendors (REP). A sample of 320 valid responses was collected using a snowball sampling technique. Different statistical methods were performed, including multiple regression for hypotheses testing. Four variables out of seven were found statistically significant in predicting the trust in social commerce, namely, the Reputation of online vendors, Information Quality, Platform Involvement, and Social Commerce Constructs. Based on the research findings, research and managerial implications, limitations, and future work were presented and discussed.
Keywords: Social Commerce; Trust; Qatar; Platform Involvement; Information Quality; Reputation of Online Vendors; Social Commerce Constructs; Trust Disposition; Informational Support; Perceived Privacy Protection.
Analysing Online Reviews of Restaurants in Malaysia: A Novel Approach to Descriptive and Predictive Analytics
by Kok Wei Khong, Shasha Teng, Mohammad Mohsin Butt, Babajide AbuBakr Muritala
Abstract: This paper aims to develop a model of restaurant products and services quality based on consumer sentiments shared on social networks. We applied Term Frequency-Inverse Document Frequency (TF-IDF) weighted algorithm to generate empirical entities. These entities were incorporated into hypothetically defined constructs which reflect their thematic and sentimental nature, to test our predictive model using variance-based structural equation modelling. The results suggest that consumers have a positive attitude toward Malaysian restaurants regarding price, hospitality, location, waiting time, food variety and restaurant atmosphere. Restaurant managers are advised to prioritize their restaurant attributes and manage key attributes to sustain and attract customers. By understanding the relative importance of restaurant reviews, restaurant managers are able to create and maintain competitive advantages in the restaurant industry, ultimately achieving customer loyalty and positive brand image.
Keywords: Online Reviews; Text Mining; Unstructured Data; Clustering; Bayesian Structural Equation Modelling.
The impact of payment methods and payment-related marketing communications on e-commerce retailer trust An empirical consumer analysis of Indonesian e-commerce start-ups
by Farrah Almira Lakeman, Nadine Walter, Thomas Cleff
Abstract: The purpose of this paper is to investigate preferences of online payment methods of consumers using e-commerce websites of start-up companies in Indonesia. A quantitative online survey was used and 215 valid responses from e-commerce consumers in Indonesia were generated. The study confirms the positive impact of trust on the online purchase decision. It also reveals that convenience of online payment methods positively influences the level of trust in e-commerce start-ups. This was confirmed for access and transaction convenience. Payment-related marketing communication also proves to generate trust information dissemination about payment methods throughout the customer journey (before the check-out) and the usage of assurance seals are particularly important.
Keywords: Payment methods; e-commerce; convenience; availability; trust; communication; assurance seals; online retailer; start-up; Indonesia.
Preliminary insight into electronic commerce adoption in a developing country: Evidence from Ghana
by Frederick Pobee
Abstract: Despite the barriers that have slowed electronic commerce adoption in developing countries, evidence suggests a recent surge in its adoption. This research explores the factors that influence the adoption of electronic commerce among Ghanaians. This research integrates the protection motivation theory (PMT) and the theory of planned behavior (TPB) to propose a conceptual model. Data was collected from 920 Ghanaian university students to validate the conceptual model. Structural Equation Modelling (SEM) was employed to evaluate the suggested hypotheses. The findings indicate that self-efficacy, response-efficacy, attitude, subjective norms, perceived behavioral control significantly affect the behavioral intention to adopt e-commerce. Whereas perceived vulnerability, perceived severity, and response cost have an insignificant effect on the behavioral intention. This study presents us with the enablers of e-commerce adoption in a developing country. Online vendors are expected to provide customers with trustworthy information on their websites and a secure payment mode. As the findings revealed, these influence consumers behavioral intention to adopt e-commerce. The study presents a conceptual research model that serves as a theoretical lens for investigating e-commerce adoption. The model includes behavioral and security/risk facilitators of e-commerce adoption. The model enriches our understanding of behavioral and the perception of risk that influence consumer e-commerce adoption behavior in a developing countrys context. As a practical implication, e-vendors and website business designers should build online shopping websites that are easy to navigate, requiring less mental and physical stress from consumers.
Keywords: e-commerce; self-efficacy; subjective norm; adoption; behavioral intention; perceived vulnerability; response cost; self-efficacy.
ANTECEDENT AND CONSEQUENCES OF CONSUMERS SATISFACTION IN ONLINE GROCERY SHOPPING
by Adinda Citra Kusuma, Mukhamad Najib, Irman Hermadi
Abstract: The rapid development of the Internet and changes in consumption patterns in Indonesia encourage consumers to shop for various products online including shopping for daily necessities such as groceries. This study aims to analyze the effect of online grocery shopping experience factors on satisfaction and the effect of consumer satisfaction on trust and loyalty. Data collection was carried out utilizing online survey of 169 respondents who had shopped online for groceries. The data were analyzed using the Structural Equation Model (SEM) Method using SmartPLS software. The analysis shows that the online shopping experience has a significant and positive influence on consumer satisfaction except variable customization and ease of return. Furthermore, consumer satisfaction has a significant and positive effect on trust and loyalty. The experience of consumers in shopping online can be used as a reference to increase satisfaction so that consumers become trustworthy and loyal.
Keywords: Consumer Satisfaction; Trust; Loyalty; Online Shopping Experience; Online Grocery Shopping.
Promoting Trust through Linguistic Features of Provider Profiles in the Sharing Economy
by Maarten Ter Huurne, Jonas Moons, Amber Ronteltap, Rense Corten, Vincent Buskens
Abstract: Trust between providers and consumers in the sharing economy is crucial to complete transactions successfully. From a consumer
Keywords: sharing economy; trust; perceived trustworthiness; LIWC; linguistic features; C2C.
Special Issue on: Intelligent Security using Blockchain for Internet of Things
Security Framework for IoT and Deep Belief Network based Healthcare System using Blockchain Technology
by Senthil Murugan Nagarajan, Prathik Anandhan, Muthukumaran V, Uma K, Kumaran U
Abstract: Nowadays, the computerization and information systems need a very fast, easier and secure data analysis models. So, Blockchain technology and Deep learning concepts plays an important role for data security and analysis in field of healthcare applications. Blockchain technology has optimal reliability in various sectors like healthcare, security, information management, smart home etc. In this paper, Blockchain technology is used for healthcare system to provide a secure and reliability of data transmission. Furthermore, IoT based wearable devices are used to collect the data from the patients. Moreover, Deep Belief Network (DBN) is proposed to classify the obtained data in order to predict the type of disease or problems for patients. The experimental results shows that the proposed framework and classification model abruptly outperforms when compared with other existing techniques. The efficiency of the proposed framework is analysed based on the performance metrics like throughput and latency. The loss ratio for the proposed model seems obtain very less of 0.0126 when compared with other existing techniques like MLP, SVM, ANN, and CNN. The accuracy obtained for the proposed DBN classifier is above 95% for the increase in the number of patients.
Keywords: Blockchain Technology; Healthcare System; Internet of Things (IoT); Deep Belief Network (DBN); Security.
RPL enhancement with mobility aware two stage objective function for improving network lifetime in IoT
by Robin Cyriac, Saleem Durai MA
Abstract: The routing protocol for low power and lossy network (RPL) has tremendous scope in IoT, due to the fact that it can be customized as per networks domain requirement by altering Objective Function (OF). Many studies have proven that the careful crafting of OF with different metrics improve the quality of route identified by RPL. As the complexity of OF increases due to different metric combinations, the performance of RPL will start to deteriorate. We divide OF into a two stage process to solve this problem. In the first stage we keep a simple OF that considers ETX and path delay and rank parents as per RPL specification. A fixed number of best ranked parents from the first stage OF are considered for further processing in the second stage OF. Fuzzy based second stage OF considers mobility history, queue availability and remaining energy of the parents to select the preferred route. Second stage OF is run only on limited number of parents which improves performance of RPL. Performance evaluation shows that our Two Stage Objective Function (TS-OF) reduces packet loss by 28% and energy consumption by 34% compared to the state of the art RPL objective function. \r\n
Keywords: IObjective Function; RSSI; Energy consumption; Parent selection mechanism; RPL; IoT
A Markov Decision Process based Secure Consensus Framework for Leveraging Blockchain Technology in IoT Applications
by Nonita Sharma, Monika Mangla, Sachi Nandan Mohanty
Abstract: In this manuscript, we propose a secure consensus framework that implements Markov Decision Process (MDP) for blockchain technology in IoT applications. The proposed framework presents projection for the sojourn time and stationary efficiency measures for any transaction or block. Implementing MDPs provides a group of states and a collection of actions to choose from. MDP also offers instantaneous reward purpose and a probabilistic transition matrix. The proposed framework that suggest implementation of MDP in blockchain technology further escalates the security of the network. The paper demonstrates the architecture of the proposed framework.
Keywords: blockchain; bitcoin; byzantine faults; consensus; distributed ledger; smart contract; markov decision process.
Blockchain-based consensus algorithm for solving security issues in distributed internet of things
by Bhabendu Kumar Mohanta, Kalpana Samal, Debashish Jena, Somula Ramasubbareddy, Marimuthu Karuppiah
Abstract: In the last decade internet of things (IoT) emerged as one of the most promising fields of research. The services provided by the IoT have come as a big relief to human life due to the smartness and real-time monitoring without human intervention. IoT applications are widely used as it provides a high level of comfort, automation of the system, and efficiency. To make successful use of ever-growing IoT applications requires addressing the security, privacy, and trust to protect IoT devices and user privacy from attackers. In this paper, initially different security and privacy challenges are identified in an IoT application. Secondly, analysis regarding blockchain technology is done which gives the idea to solve some of the IoT security challenges. Blockchain-based consensus algorithm PBFT is used to perform secure computation in a smart transportation system. Security analysis shows
that the proposed protocol worked correctly in presence of malicious or faulty nodes.
Keywords: internet of things; IoT; security; privacy; blockchain; consensus algorithms; distributed system; trust management.
Special Issue on: GLRC-2020 Digital Transformation and Disruptive Innovation Drivers for Future Business Growth
The Antecedents and Consequences of Brand Experience and Purchase Intention.
by Mahima Shukla, Ashok Sharma, Richa Misra, Vinamra Jain
Abstract: The way a brand communicates with its consumers has changed significantly during the last decade. The advertisement methods have evolved from mass media to personalised advertising. The advent of social media has made personalised marketing a very effective tool. Facebook has emerged as one of the most popular social media site with users logging in large numbers. Proper utilisation of available information (demography, location, and profile) enables businesses to create relevant and appropriate advertisements for the consumers, resulting in satisfying experiences and loyalty in the long run. Personalised advertising leads to better customer experience as it is customized as per their requirement based on their social media and browsing history. The present study has developed an inclusive model to test the relationship between brand experience formed by the affective and cognitive stimulus as a result of personalised advertisements. Further, the influence of brand experience on brand Image and Perceived Value is also being hypothesised. The relationship between brand image and its impact on perceived value and purchase Intention is also tested. The study becomes relevant in the Indian context since India has the highest young population, who spent a significant amount of time on Facebook. The platform provides small businesses with the cheapest and most targeted form of advertising. The model proposed in the study will be helpful in designing an appropriate communication strategy particularly for small businesses with pressing budget and resource constraints.
Keywords: Facebook advertising; Personalisation; Brand Experience; Affective; Cognitive; Social Media; Brand image; Perceived Value; Purchase Intention;.
Mobile Shopping Apps Adoption: A Systematic Literature Review
by Rajat Gera, Priyanka Chadha, Vandana Ahuja
Abstract: The study aims to contribute by evaluating and synthesizing the findings across various strata of populations in developed and developing countries and by unifying the diverse streams of research into a more coherent and cohesive knowledge entity. The theoretical models and determinants of M-Shopping apps adoption intentions and behaviors from selected papers in literature are reviewed to synthesize the findings and identify the gaps and contradictions. Recommendations for future research are made as regards theoretical approaches, research methodology, anchor constructs, consumer profiles to be researched, and technological and marketing perspectives to be explored. The research findings in literature are limited by exclusive focus on smartphones, selective geographical regions, theoretical models, consume profiles and methodological approaches and hence not generalizable.
Keywords: M commerce; UTAUT; UTAUT 2; TAM; TPB; Repurchase Intention; Re- patronage Intention.
THE EFFECTS OF CULTURAL DIMENSIONS ON MOBILE COMMERCE ACCEPTANCE OF VIETNAMESE CONSUMERS
by Mai Ngoc Tran
Abstract: The acceptance of mobile commerce (m-commerce) is different among countries, a principal cause of which is national culture. This study evaluates whether cultural aspects affect the m-commerce acceptance in Vietnam context. Hofstedes cultural dimensions (PDI, IDV, MAS, UAI, LTO) were adopted as influence factors to Perceived Usefulness, Perceived Ease of Use and Social Influence which has been known as the constructs of the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT). Research conducted on 315 respondents. The questionnaire used in this study was developed based on previous studies that had proven validity. The structural equation model (SEM) was tested using SPSS and Amos 22. Lastly, a result comparision with a similar study carried out in the context of Indonesia was provided in order to draw implications about the validity and generality of the research model. Based on the findings, the paper offers some recommendations for businesses, telecom service providers, and m-commerce providers to attract more users.
Keywords: mobile commerce; m-commerce; national culture; technology acceptance; Vietnam; cultural dimensions; Hofstede.
Digital innovation for strengthening seed market and augmenting targeted business in agriculture
by Swati Nayak, Ritesh Dwivedi, Anjani Kumar Singh
Abstract: Access to quality seeds of right varieties remains a prerequisite for higher farm production. In India, there are several private and public seed agencies who deals with multiple products (varieties). Public and small firms working closely with high volume crops and small farmers, are not equipped with robust market demand estimation processes or demand driven distribution systems. SeedCast is one such digital application which has been developed and piloted in the region with an objective to measure the existing demand-supply gaps accurately, to estimate geography wise and product wise demand and act as business decision support tool. Piloting and execution of this application for the state of Odisha indicated several gaps in demand and supply for diverse products, potential demand for new products, a scope of product diversification and the size / volume of market (product wise) for the leading public seed corporation in focus as future business opportunity.
Keywords: Seed; Agriculture; Products; Varieties; Market; SeedCast; Digital; Demand.