Transaction Attributes Research Articles

From caretaking to transaction: Women politicians, motherhood, and political authority in Kenya

AbstractFeminist scholars have noted how motherhood opens avenues for women to access political authority. For African and Black women, scholars have noted how presenting themselves as mothers in the political sphere allows them to capitalize on an identity that traditionally allowed them access to power. However, these perspectives on motherhood and politics privilege a perspective on motherhood that deems the role as selfless and sacrificial. In this article, I propose moving beyond the caretaking dimensions of motherhood when analyzing how women politicians utilize motherhood. Drawing on evidence from research among Kenyan women politicians between 2017 and 2020, I argue that political motherhood often emerges as a transaction. Rather than interpreting the actions of women politicians as an extension of maternalistic impulses into the political realm, I illustrate how women politicians present the benefits of motherhood in exchange for citizens’ votes. By diversifying the meanings of political motherhood beyond caretaking and communal roles, this article counters perspectives that assume women politicians are less corrupt or are the victims of patriarchal politics. Instead, by foregrounding the transactional dimensions of political motherhood, this article illustrates how women politicians strategically use gendered identities to build political authority.

A systems approach to improving health consideration in UK urban development: a real estate perspective

ABSTRACT This research investigates how population health is considered in urban development decision-making by developing a causal loop diagram from 21 interviews with senior real estate actors. It classifies variables in the model in structural, attitudinal, and transactional dimensions, links them to relevant decision-making actors, and identifies key feedback loops. This enhances understanding of the system and informs intervention strategies for improving the consideration of health. Structural and attitudinal variables are powerful leverage points but are more challenging to influence directly and slower to change. Yet, when activated through a transactional variable, such as enhancing a data-led health metric to increase the ability of stakeholders to include health in planning, investment and development decisions, they generate virtuous feedback loops. These drive and sustain decision-making that shapes a healthier built environment.

Revisiting research on the governance of interorganizational relationships

This essay re-examines the literature on the governance of interorganizational relationships, focusing on the insights of alliance research using transaction cost economics. Despite substantial progress, challenges arise because research has not devoted attention to some mechanisms of governance (i.e., administrative controls and supporting legal institutions) compared with others (i.e., incentives). Parties can develop bespoke collaborative agreements that mix and match various mechanisms of governance along these dimensions, rather than accessing a typical bundle commonly associated with a discrete organizational form. This conclusion challenges the iconic governance continuum and surfaces new methodological opportunities for this research stream. The essay also challenges what we think we know by identifying a variety of omitted variable problems that often crop up in governance research (e.g., focusing on the cooperative context of collaboration while not attending to the competitive context, excluding critical administrative structures when studying the interplay between contracts and trust, assuming transactional attributes are exogenous rather than endogenous to a search process, failing to account for shifting institutional supports for collaboration, etc.). By clarifying what we know and do not know about alliance governance, the essay identifies some pathways for developing more reliable, cumulative knowledge on interorganizational relationships.

Network Based Feature Extraction Method for Fraud Detection Using Label Propagation

Abstract: Nowadays, judging the current transaction based on user history transactions is an important detection method. However, different users have different transaction behaviors, when all users use the same limit to judge whether the transaction is abnormal, it will result in higher misjudgment for some users. Aiming at the above problems, this paper proposes an individual behavior transaction detection method based on hypersphere model. In this model, considering multiple dimensions of normal historical transaction records, the characteristics of user’s transaction behavior is generated with the trend of transaction. Then, the user optimal risk threshold algorithm is proposed to determine the optimal risk threshold for each user. Finally combining the transaction behavior and the optimal risk threshold, the user behavior benchmark is formed, which is used to construct the multidimensional hypersphere model. On this basis, a mapping method for transforming transaction detection into midpoint in multidimensional space is proposed. The experiment proves that the proposed method is superior to other models, and it is found that the characterization effect of user behavior is related to the frequency of users’ transactions. Applied computing → Secure online transactions; Digital cash; Computing methodologies → Instance-based learning; Rule learning

Revealing governance forms: the case of French agrifood platforms

PurposeAgrifood platforms are now part of consumption habits. They have emerged in various forms, and we need to describe this diversity to understand better how platforms manage their relationships with farmers. We aim to understand the governance forms of agrifood platforms and consider whether they comply with the principles of transaction cost economics (TCE).Design/methodology/approachBased on a survey of 103 French platform managers, a two-step cluster analysis and ordered logit regressions were applied to test hypotheses derived from the theory.FindingsThe results enable us to propose a refined typology of eight governance forms for the farmer-platform relationship. These different forms can be classified according to a continuum ranging from “market to hierarchy”, conforming to TCE principles. We define a gradient describing how the platforms manage their relations with the farmers through contractual and relational control. We show that specific assets, behavioural uncertainty, and membership in a platform network are associated with more integrated governance forms.Practical implicationsThe article describes the different forms of platform governance and their relevance to market conditions. This clarification is necessary for farmers to elect the more suitable platform and for platform managers to create a new business or improve its efficiency.Originality/valueThis article is the first to offer a detailed typology of agrifood platform governance. It highlights these governance characteristics and their relationship with transaction attributes.

Enhancing Customer Analytics: A Comprehensive Framework for Effective Churn Prediction

This paper presents a comprehensive framework designed to forecast churn rates within organizations and provide visual representations for proactive and reactive analyses. Churning is the process of customer discontinuation from a product or service due to dissatisfaction or shifting needs of customers. Since keeping current clients comes with a considerably cheaper cost, acquiring new ones is no longer a smart business plan. By leveraging historical customer data encompassing demographic, behavioral, and transactional attributes, predictive models are developed and evaluated. Given that we already have all of the current customer's data, retention is far more affordable and successful. This paper aims at improving the accuracy and gives a churn prediction model which is suitable for all organizations. There are Five main components in this framework: Data preprocessing, pattern recognition, exploratory data analysis(EDA), Gradient Boost algorithm (ML algorithm to identify whether the customer is satisfied with the service or not) and Churn prediction. The churn prediction will give the results as reactive and proactive analysis. We have used the Gradient Boost algorithm ( ensemble learning technique) along with SMOTE-ENN in this paper which gives us an accuracy of 95%.This gradient boost algorithm gives the best accuracy when compared with other machine learning algorithms like, Logistic Regression, Random Forest Classifier and Decision Tree Classifier. Visualization of churned data and risk analysis is facilitated through Power BI.

Transações no SAG lácteo no Paraná: um estudo a partir dos custos de transação e de mensuração

Abstract: This article aimed to understand how governance structures and the search for value protection influence transaction costs in the relationship between dairy producers and processors in Paraná, Brazil. These aspects are treated by Transaction Cost Economics (TCE) and by Measurement Cost Economics (MCE). For data collection, 30 semi-structured interviews were conducted and Content Analysis was used for data treatment and results analysis. For the theory, the study contributed demonstrating that although the alignment between transaction attributes and governance structures contribute for value protection as proposed by TCE, in the absence of complete information, this alignment is still not enough to guarantee economic rights, as predicted by MCE. Empirically, it contributed suggesting the use of formal contracts and the importance of formal information available to milk producers and processors to improve their results in the activity. Thus, considering the governance structures in Paraná’s dairy AGS, it is predicted that even if the hybrid structure is adequate, under TCE view, due to its alignment with transaction attributes, MCE concepts help to explain why agents still need guarantee mechanisms. Those mechanisms, such as long-term relationships, normative instructions and informal agreements, attempt to protect value, given informational problems.

Detecting Fraud in Automated Teller Machine Transactions in the Nigerian Bank System Using Unsupervised Deep Learning

Automated Teller Machines (ATMs) are globally adopted for financial transactions. However, the exponential rise in ATM fraud poses a significant risk to Nigeria's digital payment and banking systems, with many banks failing to provide intelligent services to ATM customers. Moreover, existing research predominantly employed supervised learning on labelled data for ATM fraud detection, overlooking unlabelled customer-clustered transaction data. In this study, customer-clustered transaction attributes were employed with unsupervised autoencoder deep learning models to develop a fraud detection system. Three years of historical transaction data were obtained from a selected Nigerian bank's ATM transaction repository, consisting of 1.2 million transaction records from 10 bank customers. The transaction features considered in this work included CardNo, Amount, TransType, BranchCode, and TransDateTime. H2O autoencoder deep learning models, and anomaly detection algorithms were adopted to uncover underlying patterns in ATM transactions. The results indicated a remarkable overall system performance, with an average Mean Squared Error (MSE) of 0.0057, accuracy of 97.6%, precision of 94.8%, recall of 93.5%, and an F1-score of 94.0%. Individual model assessments revealed slightly lower performance for specific customer clusters. The study's findings emphasized the efficacy of unsupervised deep learning in combatting ATM fraud within the Nigerian banking system. Keywords: ATM, H2O.ai, Unsupervised Learning, Deep Learning, Autoencoder, Fraud detection CISDI Journal Reference Format Ojulari, H.O., Oke, A.O. & Arulogun, O.T. (2024): Detecting Fraud in Automated Teller Machine Transactions in the Nigerian Bank System Using Unsupervised Deep Learning. Computing, Information Systems, Development Informatics & Allied Research Journal. Vol 15 No 2, Pp 1-... dx.doi.org/10.22624/AIMS/CISDI/V15N2P1. Available online at www.isteams.net/cisdijournal

REPRESENTING FINE GRINED CO-OCCURANCES FOR BEHAVIOR BASED FRAUD DETECTION IN ONLINE SYSTEM

The vigorous development of e-commerce breeds cybercrime. Online payment fraud detection, a challenge faced by online service, plays an important role in rapidly evolving e-commerce. Behavior-based methods are recognized as a promising method for online payment fraud detection. However, it is a big challenge to build highresolution behavioral models by using low-quality behavioral data. In this work, we mainly address this problem from data enhancement for behavioral modeling. We extract fine-grained co-occurrence relationships of transactional attributes by using a knowledge graph. Furthermore, we adopt the heterogeneous network embedding to learn and improve representing comprehensive relationships. Particularly, we explore customized network embedding schemes for different types of behavioral models, such as the population-level models, individual-level models, and generalized-agentbased models. The performance gain of our method is validated by the experiments over the real dataset from a commercial bank. It can help representative behavioral models improve significantly the performance of online banking payment fraud detection. To the best of our knowledge, this is the first work to realize data enhancement for diversified behavior models by implementing network embedding algorithms on attribute-level co-occurrence relationships.

RESEARCH ON THE INCENTIVE PROBLEMS AND COUNTERMEASURES OF CORE STAFF IN JS BANK FROM THE PERSPECTIVE OF PSYCHOLOGICAL CONTRACT

As a regional joint-stock city commercial bank, JS Bank is faced with huge development problems such as weakening advantages of national and local support policies, weak core competitiveness and declining performance. JS Bank fully recognizes that talent is the source of power for banks to "produce" and "create" better products and services and to win market competition, and core employees who master core technology or have strong management ability are valuable human capital of banks. Through questionnaires and interviews, this research learned several incentive factors in which core employees are not very satisfied with the current incentive mechanism and very dissatisfied with the evaluation. From the perspective of psychological contract transactions, the problems include unreasonable salary structure. From the dimension of psychological contract relationship, the construction of organizational culture is insufficient. From the dimension of psychological contract development, the existing problems are that the promotion channels are not smooth. Based on three dimensions of psychological contract, this study proposes countermeasures to optimize the incentive mechanism. Moreover, from the transaction dimension, the countermeasures are to optimize the salary system. The countermeasures from the relationship dimension are to pay attention to the communication and feedback between superiors and subordinates. In addition, the countermeasures from the development dimension are to perfect the promotion system.

A study on the legal risk assessment of virtual currency transactions based on statistical analysis

Abstract This paper first analyzes the definition and characteristic attributes of virtual currency transactions, secondly constructs the legal risk indicator evaluation system, then pre-processes the evaluation data and assigns the indicators, and then constructs the legal risk evaluation model using TOPSIS-grey correlation. Finally, the quantitative data analysis was carried out by analyzing the indicator weights and evaluating indicators. The results show that the overall score of the trading platform is 73.86, with the evaluation scores of the first-level indicators being 24.56, 11.35, 16.23, 15.42, and 6.30, respectively. This study fully illustrates that the use of TOPSIS-grey correlation analysis can provide data support and a decision-making basis for legal risk assessment and prevention and new directions for reforming and developing the legal risks of virtual currency trading.

180° view on general practitioners’ leadership skills: practice-level comparisons of leader and staff assessments using data from the cluster-randomised controlled IMPROVEjob study

ObjectivesStrong primary care leaders are needed to assure high quality services for patient populations. This study analysed general practitioners’ (GP) leadership skills comparing practice-level self and staff assessments based on...

Developing Website for Belimbing Tourism Village, Tabanan, Bali

Purpose: The purpose of this research is to evaluate the Belimbing Village website in development efforts website by model information, communication, transaction, relationship and techical-merit (ICTRT) carried out to support the Belimbing Tourism Village produces dimensions of effectiveness website the maximum in helping the promotion of Belimbing Tabanan Tourism Village.
 Research methods: The data collection methods used were observation, interviews, questionnaires and interviews. In this study using qualitative and quantitative approaches or better known as mixed method research by using SWOT analysis techniques and Importance Performance Analysis.
 Findings: The results of the research using the interview method show that the application website in Belimbing Village is still very minimal because there are many features and items that need to be developed, one of which is the information dimension, transaction dimension and communication dimension. The results of the study using SWOT analysis showed that Belimbing Village has utilized ICT, but even though it has implemented ICT there are still many aspects that are lacking in website, so that more in-depth research is needed to assess its effectiveness in website Belimbing Village. Based on analysis Importance Performance Analysis produce effectiveness attributes. The researcher adopted the ICTRT model which consisted of 47 evaluation instruments which were divided into 5 evaluation dimensions.
 Implication: Site evaluation website expected to maximize promotion through website in Belimbing Village because website is an effective solution to introduce and market products/services by utilizing the internet as an information medium.

Applying neural networks analysis to assess digital government evolution

There are diverse measurement systems to assess the advance of digital government, but all are based on the evolutionary perspective. This view consists on a linear, progressive and add-on evolution of digital government, emphasizes the critical role of technology, and the learning sharing or imitation among governments. Official websites and portals have been subject of various studies using multiple metrics and indicators. The existing measurement approaches and traditional estimations present different limitations for assessing the complex characterization of digital government evolution overtime. Up-to-day there is no agreement of what constitute the proper approach to assess digital government evolution and more sophisticate techniques need to be developed to capture a more realistic metric of digital government advance. This article challenges the assumptions of the evolutionary perspective and argues in favor of the potential of the computational tools for the evaluation of these assessment tools of digital government performance. In particular, the technique of neural networks analysis and self-organized maps have the potential to describe the multi-parametric characterization of multiple metrics and indicators of this phenomenon and its evolution overtime. A database of a digital government ranking of Mexican states during the period 2009–2015 is used as a case study. This computational technique was useful data mining and visualization tool of patterns and profiles of digital government performance overtime. The procedure automatically arranges the available data into clusters of characteristics that subsequently are illustrated using visualizations through bi-dimensional maps to analyze the evolution of digital government advance. The results indicate that the evolutionary assumptions do not hold across states in Mexico and the dimensions of information, participation and transaction are relevant for improving digital government evolution overtime. Several theoretical and practical implications are discussed.

Homestay Innovation Capability in a Property Business Perspective

The rapid development of entrepreneurship-based tourism has encouraged households in tourist areas to try to take advantage of opportunities to do business through residential property to become homestays. Homestays are offered for tourists who want to spend the night naturally, enjoy daily life with the local culture of the destination visited with all the facilities which of course can meet the needs of traveling. Residential home owners try to become property entrepreneurs by understanding the management of the property business through innovation capabilities that transform residential homes into homestays. The needs of tourists in choosing homestay accommodation are different from hotels or villas or bungalows, preferring to enjoy a homely atmosphere by getting memories and local experiences in tourist destination areas. Residential homeowners will seek information regarding home repairs and the physical availability of residential homes, arrange schedules, and need to study property management in collaboration with residential developers. So this study aims to determine the innovation ability of homestay property developers who are considered influential in increasing business through the dimensions of technology development, operational capabilities, managerial routines and property transactions. This descriptive research with quantitative and qualitative approaches uses triangulation data collection techniques and is statistically analyzed using Partial Least Square. It is important for homestay business owners to find building developers who can repair or rearrange buildings who have the ability to innovate in the property business. The results of measurements from residential home owners and property developers in tourist destinations show that the dimensions of strong property innovation capabilities are innovation capabilities in management and routine operations, while the dimensions of innovation capabilities that still have weaknesses are innovation capabilities in technology development and transactions.
 
 Keywords: Innovation capability; homestays ; Property Business.

Geohash-Based Rapid Query Method of Regional Transactions in Blockchain for Internet of Vehicles.

Many researchers have introduced blockchain into the Internet of Vehicles (IoV) to support trading or other authentication applications between vehicles. However, the traditional blockchain cannot well support the query of transactions that occur in a specified area which is important for vehicle users since they are bound to the geolocations. Therefore, the querying efficiency of the geolocation attribute of transactions is vital for blockchain-based applications. Existing work does not well handle the geolocation of vehicles in the blockchain, and thus the querying efficiency is questionable. In this paper, we design a rapid query method of regional transactions in blockchain for IoV, including data structures and query algorithms. The main idea is to utilize the Geohash code to represent the area and serve as the key for transaction indexing and querying, and the geolocation is marked as one of the attributes of transactions in the blockchain. To further verify and evaluate the proposed design, on the basis of the implementation of Ethereum, which is a well-known blockchain, the results show that the proposed design achieves significantly better-querying speed than Ethereum.

Reshaping Internationalization Strategy and Control for Global E-Commerce and Digital Transactions: A Hayekian Perspective

As the sharing economy has grown rapidly and replaced the traditional businesses, new rules and norms for data and digital trade have emerged divergently in many countries. Such divergence in global e-commerce policies may be a major barrier to the internationalization of the sharing economy business. This paper aims to develop an internationalization theory that addresses how the sharing economy firms can internationalize under the condition of the divergence of global e-commerce policies. Drawing on Hayek’s knowledge economy approach, we build a new internationalization theory for the sharing economy firms that facilitate autonomously self-organized business ecosystems and adapt to the lack of harmonized rules and norms for the sharing economy. We first theorize on the attributes of the digital platform-based transactions for the internationalization of the sharing economy firms and then provide some insights into the current international debates of e-commerce policies. Our theory offers two main insights: (1) the competitive advantages of the sharing economy firms stem mainly from digital platform algorithms to catalyze digital platform-based transactions between autonomous actors; (2) the divergence of global e-commerce policies and different internet regimes in different countries may affect the internationalization of business models based on such digital platform-based transactions.

Customer experiences and situational vulnerability: An exploration of hotel services during a disaster

Hotels have gained greater attention in society for the ability to provide services to individuals during disasters and crises. With critical resources like food, shelter, and staff, a hotel can represent an ideal refuge for individuals in need. However, the extant research on disaster and hotels provides minimal insights into the experiences of customers and the specific areas where hotels may be helping or making matters worse. This study builds on the hotel service, disaster, and vulnerability literature to identify the central attributes and characteristics of service experienced by customers during a disaster. Using multiple text analysis methods including natural language processing, semantic theme analysis, and qualitative content analysis, we investigate customer experiences during situational vulnerability through public consumer review data. The findings reveal service attributes of care, provisions, and transactions influence the support or in some cases impair well-being of individuals utilizing hotel services during a disaster.

The territorial dimension of transactions in the Canary Islands’ grape market

The territorial dimension of transactions between grape growers and wine producers in the Canary Islands’ grape market is examined. This is a market fragmented into different wine-grape zones and institutionally organised through protected designations of origin (PDOs) which, except in the case of one that is regional in scope, restrict the spatial mobility of grapes. We use information from the harvest declarations submitted by grape growers, which indicate the location of the vineyard plots, and production declarations submitted by the wine producers, which indicate the grape grower who supplies grapes to their winery, as well as from harvest reports, which contain a record that facilitates the traceability of the grape's journey from the plot of origin to the winery of destination. The results obtained show that there are hardly any inter-island movements of grapes and that inter-zone transactions were selectively intensified between the wine-grape zones of the island of Tenerife following the creation of a regional PDO.

Detection System of Promotion Abuse Using Similarity and Risk Scoring Methods

Offering promotion coupons is one of the most popular strategies of online marketing to attract new customers and increase customer loyalty. However, this strategy opens chances for fraud risk as the coupons are being redeemed multiple times using fake accounts. This risk becomes a burden to marketing costs and leads to failure to accomplish the intended strategic value. Therefore, this research focuses on building an automatic detection system of online promotion abuse based on its risk level. The proposed system also must work on live stream and bulk data. Therefore, in live stream data, it could alert the administrator before the transaction finished or the next process started. After conducting an exploratory factor analysis of the 24 attributes collected from four tables of data transaction, there were seven attributes indicating promotion abuse. These attributes were the user IP address, shipping address, mobile number, member email, order email, payment ID, and product name. Then, supervised machine learning of similarity algorithms was used to build models and find the hidden correlation of attributes to indicate the promotion abuse. The result from comparing five similarity methods showed that based on the workflow and performance, the most suitable methods for this case were exact match and Levenshtein edit base. The automatic risk scoring feature of the proposed system used seven attributes of online transactions as their most prominent promotion abuse parameter based on its hidden correlation. From the system performance testing, the result values of precision, recall, and F-measure are 95%, 93%, and 0.94, respectively. These results indicate that the system performance is satisfactory.