Transactional Behavior Research Articles

Combination Grouping Techniques and Association Rules For Marketing Analysis based Customer Segmentation

Changes in people's transaction behavior using the internet resulted in the exponential growth of e-commerce. With the growth of digital shopping transactions, it is difficult to predict customer segments and patterns using traditional mathematical models. Timely identification of emerging trends from large volumes of data plays a major role in business processes and decision making. This is different from previous research works that apply the RFM model based on K-Means Clustering to find potential customers as an ingredient in determining marketing targets. In this study, a clustering technique approach is proposed to classify customer data which is evaluated using the Davies Bouldin, Calinski Harabasz and Silhouette methods to determine the optimal number of clusters, then the results are used in the Apriori algorithm to find patterns of goods that are often purchased together. Based on the test results on the K-Means Clustering, Spectral Clustering, and Gaussian Mixture Model techniques produced 5 clusters with 76% more accurate the K-Means Clustering method than the other two methods so that it was determined as a method in the RMF model, then the results of customer grouping were used on the Apriori algorithm to find patterns of concurrent product purchases by customers that are expected to be useful in future marketing management.

Comparison of Apriori, Apriori-TID and FP-Growth Algorithms in Market Basket Analysis at Grocery Stores

Market Basket Analysis is an analysis of consumer behavior specifically from a certain group/group. Market Basket Analysis is generally used as a starting point for seeking knowledge from a data transaction when we do not know what specific pattern we are looking for. Market Basket Analysis in this study is applied to the search for patterns of purchasing groceries at grocery stores and then analyzed by season. This study aims to compare the Apriori, Apriori TID and FP-Growth methods in determining consumer transaction behavior and calculating the quantity of consumer transactions in several seasons based on data obtained from the Market Basket Analysis database. In the results of this study, it is known that FP-Growth has the best performance among the other two algorithms, but uses more memory than other algorithms. The Apriori-TID algorithm uses lighter and faster memory than the Apriori Algorithm

Generation X Consumption Behavior Model in Using Digital Transactions

Technology is a necessity that cannot be separated from today's life. Daily activities become easier, even ignoring distance, space, and time. This convenience provides cost savings, improves the use of time, and even changes business processes. This study aims to analyze the model of consumer behavior of generation X in the use of digital transactions. This research is quantitative research with 73 respondents who meet the qualifications. Data was collected using a questionnaire which was then tested for validity, reliability, and model fit using the WarpPLS 6.0 analysis tool. The results of data processing and testing are carried out; it can be concluded that first, cultural factors mediated by consumption behavior do not directly affect generation X in digital transactions. Second, psychological factors have a direct influence on generation X digital transactions. Consumption behavior as a mediating variable does not have an influence between psychological factors and digital transaction behavior for generation X. The limitation of this study is that the population only focuses on generation X.

Business Development Strategy of Instant Ginger Start-Up in The Covid-19 Pandemic

COVID-19 has changed people's lifestyles and transaction behavior. People switch to a healthier lifestyle and use digital marketing for daily transactions. Arvan Natural Group, a start-up company that produces ginger powder, must be able to optimize these opportunities. The increment of a competitor in the health drink sector has even tighter competition. In addition, this company faces several problems regarding raw materials (continuity and quality), product development, and limited channels. Therefore, this study aims to identify existing business models, develop alternative strategies, prioritize business strategies, and build a new business model. The data processing technique thoroughly analyzes BMC, SWOT, IFE/EFE, and QSPM. Experts working in biopharmaceutical research and business give the weights and ratings. IE matrix showed the company's position is in quadrant II (2.92, 3.02). It is categorized as grow and build strategy. Based on QSPM analysis, strategies classified as high urgency and plotting in the new business model are expanding channels (strategic location, reseller system), adding advertisement budget and joining promotion events, and applying for bonus promotion. Besides, there are differentiating products, creating an operational partnership system with farmers, improving marketing content (video), applying the functional structure of human resources, and creating product size variety. Keywords: BMC, digital marketing, lifestyle, QSPM, SWOT

CRIMINAL LAW ASPECT IN CASES OF VIOLATION OF CONSUMER RIGHTS IN ELECTRONIC TRANSACTIONS

The development of information technology currently affects people's behavior in transactions. The use of online transactions in Indonesia is growing rapidly. Without direct or face to face meeting in the transaction, the risk of crime in a transaction will increase. The transaction, which was originally a private legal activity, will intersect with the public aspect. Consumers who feel that their rights have been violated can take legal steps through criminal law instruments. As an effort to prevent the occurrence of criminal acts that harm consumers in online transactions, education is needed for the public regarding criminal law aspect in cases of violation of consumer rights. This article is the result of community service activities carried out using the public lecture method through virtual meeting or webinar. The result of this community service activity is an increase in public understanding of the various kinds of criminal acts that can occur in online transactions, the legal arrangements in the Indonesian legal system, and efforts can be made to prevent the emergence of consumer losses in online transactions.

FA-GNN: Filter and Augment Graph Neural Networks for Account Classification in Ethereum

As the first blockchain platform supporting smart contracts, Ethereum has become increasingly popular in recent years and generates a massive number of transaction records. Nowadays, millions of accounts in Ethereum have been reported to participate in a variety of businesses, and some of them have been found to be involved in illegal behaviors or even cyber-crimes by exploiting the pseudonymous nature of blockchain. Therefore, there is an urgent need for an effective method to conduct account classification and audit transaction behaviors of each account. In this paper, we model the Ethereum transaction records as a transaction network, and the account classification problem is converted to a node classification problem. Based on the Ethereum transaction network, we propose a novel framework named <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>F</u></b> ilter and <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>A</u></b> ugment <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>G</u></b> raph <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>N</u></b> eural <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><u>N</u></b> etwork (FA-GNN), which can retain the information of important neighbors and augment node features with high-order information. Experimental results demonstrate that our proposed FA-GNN outperforms state-of-the-art methods in Ethereum account classification.

English

While the current economic crisis clearly puts pressure on governments to cut spending and save money, and whilst the call for a more cohesive interface between the public and private sectors is currently resonating, public procurement has been marred by scandals, mismanagement, and possibly malpractices. According to the literature, corporate integrity drives transactional behaviors by acting as a hidden hand of social factors that are frequently beyond an individual&#39;s control. But scantly studied, as behavioral control mechanism in transaction costs. This paper studies the moderating effect of integrity on the relationship between transaction costs&rsquo; behavioral dimensions and competitive tendering in public procurement. Following a literature review, the paper takes a conceptual framework towards developing evidence of cascaded transaction costs&rsquo; behavioral dimensions, bounded rationality and opportunism. Formal research propositions amplify both concepts and its relationship with independent variable and dependent variables. The results are based on the empirical data collected from a self-administrative survey from public procurement practitioners in Tanzania. Descriptive and Hierarchical regression results reveals that public procurement practitioners&rsquo; perceived transaction costs to negatively when related with competitive tendering as moderated by integrity. This means, integrity can moderate the behaviors of public procurement practitioner which, in turn, accelerates efficiency of competitive tendering by reducing transaction costs. &nbsp; Key words:&nbsp;Transaction costs, competitive tendering, integrity, public procurement.

무인 스터디카페 거래 데이터 분석 및 머신러닝 분류 모델 기반 고객세분화

A study cafe is a new form of learning environment that combines a study room and a cafe. Regarding the COVID-19"s impact, the unmanned platform has become the new normal. The number of unmanned study cafes, launched by individuals, is rapidly increasing due to lower labor costs. Despite strong growth and promising market potential, little research on customer relationship management in unmanned study cafes has been conducted. Unlike franchises, the founder of an individual business must learn customers from the ground up. As a result, the purpose of this research is to provide a framework for individual founders to use in developing CRM strategies for their own unmanned study cafe. To accomplish this, analyze transaction data to better understand customers" untact transaction behavior and usage patterns, and also provide an example of customer segmentation approach using machine learning classification model so founders can plan practical CRM strategies based on the customer groups.

A novel deep learning based peer‐to‐peer transaction method for prosumers under two‐stage market environment

With the development of the electricity market, peer-to-peer (P2P) transaction plays an important role in promoting local consumption of renewable energy and arousing the enthusiasm of prosumers. However, due to the diversification of prosumers, the confidentiality of the information and the interaction between prosumers, there are increasing challenges for the traditional model-based optimisation methods in both P2P modelling and model solution accuracy. Therefore, this paper proposes a novel P2P transaction method based on deep learning under a two-stage market environment, which uses a data-driven approach to build a transaction behaviour model based on public information. The neural network model based on Long Short-Term Memory (LSTM) is utilised to characterise the behaviour of prosumers in P2P transactions effectively. Based on this model, the energy consumption plans and P2P bids of prosumers are optimised accordingly. Through the simulation test of an example system with six prosumers, the results show that the model established can well represent the P2P transaction behaviour of prosumers, and the proposed method can effectively improve the efficiency of P2P transactions and the economic benefits of prosumers, providing a reference for the decision-making of P2P transactions.

The Effect of Changes in the Value of Conventional Interbank Transfers and Digital Banks in Technological Development

The digital revolution in the last decade has drastically changed the transaction behavior of economic agents. Consumption patterns are shifting to shopping on digital platforms and demanding an all-in-one payment method. From 2014 to 2021, Bank Indonesia noted that Indonesia experienced an increase in income. Even during the COVID-19 pandemic, many startups in Indonesia played a role in helping Indonesia's economic activities and stabilizing people's incomes. In addition, Bank Indonesia also helps Conventional Banks to compete with Startups that have become Digital Banks by creating an Open-Banking-based BI-Fast program. This program also helps Retail UMKM make it easier for the community to make payments at a cost of IDR 2500.

Evolution of Transaction Pattern in Ethereum: A Temporal Graph Perspective

Ethereum is one of the most popular blockchain systems that support more than half a million transactions every day and foster miscellaneous decentralized applications with its Turing-complete smart contract machine. Whereas it remains mysterious what the transaction pattern of Ethereum is and how it evolves over time. In this article, we study the evolutionary behavior of Ethereum transactions from a temporal graph point of view. We first develop a data analytic platform to collect external transactions associated with users as well as internal transactions initiated by smart contracts. Three types of temporal graphs, user-to-user, contract-to-contract, and user-contract graphs, are constructed according to trading relationships and are segmented with an appropriate time window. We observe a strong correlation between the size of the user-to-user transaction graph and the average Ether price in a time window, while no evidence of such linkage is shown at the average degree, average edge weights, and average triplet closure duration. The macroscopic and microscopic burstiness of Ethereum transactions are validated. We analyze the Gini indexes of the transaction graphs and the user wealth in which Ethereum is found to be very unfair since the very beginning, in a sense, “the rich is already very rich.”

Simulation of the Bidding Behavior of Electricity Retailers Based on the Q -Learning Algorithm

At present, the reform of electricity marketization has become a new trend in the development of the world’s electric power industry and electricity retailers have a huge role in further activating power market competition. Simulation of the bidding behavior of electricity sales companies is helpful to analyze the rationality of the transaction behaviors of electricity sales companies and predict the potential risks of market operation. Considering the complex and diverse behaviors of electricity retailers and the immaturity of existing simulation technologies in the power sales market, this paper proposes a Q -learning algorithm-based simulation method for the bidding behavior of electricity retailers. Firstly, we analyze the factors influencing the bidding behavior of electricity retailers, then, we construct a simulation model of electricity retailers’ bidding behavior based on the Q -learning algorithm, and finally, we simulate the bidding process of medium- and long-term trading in provincial power markets by using simultaneous learning from both sides of the generation and consumption. The results show that the behavior of different types of electricity retailers meets the expected level of the model and the simulation method has generalization and extension significance. On this basis, this paper also proposes a bid simulation system architecture based on the bid line simulation model of electricity retailers, which provides a certain reference value for market operation agencies to carry out the corresponding deduction work.

Effect Of Perception Of Usability And Perception Of Ease Of Use Of Digital Payment On The Performance Of Cashless Society Programs In The Management Of State Finances

This study aims to understand the effect of perceptions of usability and perceptions of ease of use of digital payment on the performance of the Cashless Society program in the financial management of the transaction state as a new 4.0 business behavior that is supported by Cashless Society 5.0. Until now, digital competencies, demographics, and infrastructure in Indonesia in implementing cashless economies are not optimal. This study uses a descriptive-qualitative approach with the literature study method. The purpose of the study to determine the development of the Cashless Society transaction behavior in the management of state financial results stated that Cashless and Cardless Transaction behaviors have been running, it is a business behavior that can provide economic added value and become an alternative solution to economic problems in Indonesia. Indonesia's readiness to be cashless society still requires support from various parties to megoptalize financial and digital literacy.

Effect Of Perception Of Usability And Perception Of Ease Of Use Of Digital Payment On The Performance Of Cashless Society Programs In The Management Of State Finances

This study aims to understand the effect of perceptions of usability and perceptions of ease of use of digital payment on the performance of the Cashless Society program in the financial management of the transaction state as a new 4.0 business behavior that is supported by Cashless Society 5.0. Until now, digital competencies, demographics, and infrastructure in Indonesia in implementing cashless economies are not optimal. This study uses a descriptive-qualitative approach with the literature study method. The purpose of the study to determine the development of the Cashless Society transaction behavior in the management of state financial results stated that Cashless and Cardless Transaction behaviors have been running, it is a business behavior that can provide economic added value and become an alternative solution to economic problems in Indonesia. Indonesia's readiness to be cashless society still requires support from various parties to megoptalize financial and digital literacy.

Leadership Behaviour in Covid-19 Crisis Response: A Personal Strategy Proposition

This paper analyses the personal strategy driving COVID-19 crisis behaviours of 20 country leaders. It explains the concept of personal strategy and establishes its theoretical basis. It also reviews leaders’ COVID-19 action contexts, actions and associated dynamics to infer the personal strategy driving their behaviour. The article finds the best personal strategy for COVID-19 crisis management as ‘crisis resolution’ and its variants adopted by leaders with a track record in crisis management or facing serious political compulsions—the latter, with a ‘career turnaround’ motive, were focused on erasing unfavourable political image. Leaders following personal strategies of self or negative orientations were the least successful or most unpopular. The article categorizes personal strategies broadly as crisis-focused, negative-focused, ideology-focused and mixed-focused, and it shows that personal goals and personal strategies of country leaders could be interpreted with existing theories. Drawing from a previous study on the same 20 leaders, the article shows that personal strategy of ‘crisis-focus’ is associated with positive styles of crisis action and leader behaviour, ‘negative-focus’ is related to negative action and behavioural styles, and ‘mixed-focus’ is linked to ‘strategic’ actions and transactional behaviour. Except for ideology-focus, leaders’ choice of personal strategy is not found exclusively related to the developmental or geopolitical status of their countries, which proves that personal strategy is a leader phenomenon. Differences in personal strategy among leaders led to different results in different countries—positive orientation resulted in positive outcomes and negative focus caused negative outcomes. The article concludes that personal strategy as a medium of transmitting leader traits into leader behaviour through support of personal goal can fill the gap in the current literature in connecting personal traits to leader behaviour.

Effect of Perceived Usefulness, Perceived Ease of Use, Perceived Security, and Cashback Promotion on Behavioral Intention to the DANA E-Wallet

Changing patterns of behavior in public financial transactions during this pandemic has increased the use of e-wallet services. One of the Indonesian people's most widely used e-wallet services is DANA. This study aims to determine the effect of perceived usefulness, perceived ease of use, perceived security, and cashback promotion on behavioral intention to the DANA e-wallet (a survey of people in the Special Region of Yogyakarta). The sampling technique used is non-probability sampling with the purposive sampling method. The number of samples in this study was 100 respondents with the criteria of people who have a DANA account but have never used it for transactions. The analytical technique used is multiple linear regression analysis. Based on the results of this study, it was found that perceived usefulness, perceived ease of use, perceived security, and cashback promotion simultaneously or together had an effect on behavioral intention in DANA e-wallet with a significance value of 0.00 &lt; 0.05 and an Adjusted R-value by 55.1%. This shows that the variables perceived usefulness, perceived ease of use, perceived security, and cashback promotion can explain 55.1% of behavioral intention variables, and the remaining 44.9% is influenced by other variables outside of this study. In addition, this study also obtained results that perceived usefulness, perceived ease of use, perceived security, and cashback promotion partially or one by one affect behavioral intention.

Empirical Analysis of Machine Learning Algorithms on Detection of Fraudulent Electronic Fund Transfer Transactions

Online financial systems like electronic funds transfers (EFT) are heavily dependent on the public Internet. A diverse set of Internet traffic is generated from the use of different online financial platforms. The analysis of raw Internet traffic fails to identify any anomalous behavior in financial transactions. A similar result is obtained when we apply application layer anomaly detection in financial transactions. In this article, we propose a machine learning-based multi-layer framework which will detect and classify anomalous financial transactions. The proposed framework can help a financial service provider to avoid incidents like intrusions and online frauds. It also provides a secure mechanism to detect network anomalies in financial transactions to augment the credibility of such online financial platforms or gateways.

How transactional and transformational safety leadership behaviours are demonstrated within the construction industry

Transactional and transformational safety leadership have been repeatedly found to be important for safety. Yet how transactional and transformational leadership behaviours are most effectively demonstrated can be dependent on the context and industry. Using an ethnographic approach, supervisor safety leadership was explored across eleven construction sites in Australia. The findings revealed that, within the construction site context, contingent reward, idealised influence, and management-by-exception behaviours demonstrated by supervisors closely aligned with their definitions in Full-Range Leadership Theory (FRLT). These three types of leadership behaviour reflect observation of supervisors’ positive actions, which included: praising workers for good safety performance; proactively anticipating and attending to safety issues; and consistently leading-by-example with safety, even at times of significant production pressure. Other theoretically described dimensions of leadership behaviour, i.e. individual consideration, inspirational motivation, and intellectual stimulation, were not directly reflected in observed supervisors’ behaviour in the way they are conceptualised in FRLT. The existence of a good supervisor-worker relationship enabled workers to comfortably raise safety issues, think creatively about how to undertake work safely, and talk to their supervisor if they were experiencing personal problems. These are motivational, intellectual, and empathetic elements of leadership, which do not directly align with the way leadership behaviours are conceptualised in mainstream FRLT. The study suggests that, in the construction worksite context, leadership behaviours may take a form that differs from theoretical ideal types and that ethnographically attained insights into supervisors’ interactions with workers can contribute to understanding transformational and transactional leadership in practical terms.

Performance Evaluation of Data Transactions in Blockchain

Blockchain is an emerging technology, with a decentralized infrastructure avoiding third party dependency. Smartcontracts are one of the features of Ethereum blockchain, capable of running distributed applications in unreliableenvironments, enabling process automation and being one of the most sought technologies due to the highcustomization added to transactions. However, little is known about predicting the cost and execution time behavior of blockchain-based system transactions. This work aims to evaluate the performance of an Ethereum network through an application designed to analyze the cost and time of transactions that store characters in the blockchain. To meet the proposed objective, we designed an application for performing transactions with data inclusion and query on a blockchain, collecting time and cost data. As main conclusions of this work we have: the Ethereum platform proved to be inconstant in relation to the processing time of transactions on the blockchain and the application developed based on blockchain can provide a mechanism to evaluate text-type operations on Ethereum network.

ONLINE DIGITAL TRANSACTIONS AS A SOLUTION FOR NATIONAL ECONOMIC RECOVERY DURING THE COVID-19 PANDEMIC

The Covid-19 pandemic has impacted face-to-face restrictions, which from a financial perspective reduces cash transactions. Payment with a cashless payment method is currently the leading choice of the community. Digital transactions are one way to anticipate the spread of viruses. This article aims to find out the behavior of the public towards the Cashless Payment method in financial transactions. The study uses a qualitative phenomenological approach. Through qualitative approaches, it is found that people's behavior in digital transactions is more due to humanitarian reasons. The community considers that the Covid-19 pandemic is a shared responsibility for that there needs to be mutual care. New Normal in the view of society is a form of learning in the form of increasing concern for self, society, and God. The follow-up of the results of this study encourages authors to conduct further research using quantitative approaches through multiple regression analysis. Further investigation showed that the use of Cashless Payment affects increasing spending, where simultaneously the increase in expenditure is directly proportional to the rise in bills, consumerism of food via online, shopping for drugs and vitamins, and sharing behaviors (Jogo Tongo).