Context Of Transactions Research Articles

Adoption of NFT transaction in metaverse platform: a trust transfer approach to leverage trust among users

Purpose Recent growth of metaverse adoption has impacted the adoption of nonfungible tokens (NFTs) which is becoming increasingly attractive. Recently, researchers have explored the adoption of NFTs in metaverse platform. However, considering the risk involved in the transaction, the need for trust on NFT transaction arises. Drawing on trust transfer theory, this study aims to fill this gap by investigating the trust transfer process from trust on metaverse platform and online payment. Moreover, the moderating effect of perceived effectiveness of dispute resolution (PEDR) between trust and adoption of NFT transaction in metaverse platform is explored. Design/methodology/approach This study adopts an empirical approach using a questionnaire survey in India based on simple random sampling technique and is analyzed using structural equation modeling through the Smart PLS software. Findings The findings reveal that users with a higher trust disposition will trust the metaverse platforms, online payments and NFT transactions in the metaverse. Also, the study reveals that trust transfers from the metaverse platform and online payments toward NFT transactions in the metaverse, which further leads to the adoption intent of NFT. The study provides information for platforms on how the trust transfer process occurs and how to manage conflict resolution to attract the trust of users to use NFTs in their transaction. Research limitations/implications The study makes a valuable contribution by identifying the significant impact of trust disposition and social influence in explaining user trust in NFT transactions within the metaverse. Also, the study explores how established trust in conventional online payment mechanisms translates and contributes to trust-building on NFTs and transactional contexts within virtual worlds. Practical implications This study implies that ensuring robust security measures for NFT transactions, such as two-factor authentication, blockchain verification and secure wallets, can reassure users with different levels of trust disposition. Social implications Metaverse platforms should focus on educating users about how trust operates within their environment by providing tutorials, FAQs and support channels to help users navigate the process confidently. Highlighting security measures, user rights and privacy protections can enhance trust toward NFT payment. Originality/value To the best of the authors’ knowledge, this study contributes to research as it is the first of its kind study to explore the factors affecting adoption intent of NFTs transaction in metaverse platform using trust transfer theory. Thereby, developing substantial theoretical and practical contributions by considering an emerging technology.

Distributor whistleblowing: The effects of manufacturer trustworthiness, opportunism, and transaction contexts

Distributor whistleblowing: The effects of manufacturer trustworthiness, opportunism, and transaction contexts

Income Shifting And Tax Avoidance: Evidence In Indonesia

Purpose: This study aims to examine the effect of income shifting instruments on tax avoidance efforts. The instruments focused on transfer pricing and intangible assets, and the role of multinationality in moderating both Methodology/approach: The sample selection used a purposive sampling method with a final sample of 110 observations. With secondary data from the company's annual report and financial statements, this study uses Panel Data Regressions and Moderated Regression Analysis (MRA) with Stata 15. Findings: The results show that transfer pricing has a positive effect and intangible assets have a negative effect on tax avoidance. Also, multinationality only moderates the relationship between transfer pricing and tax avoidance. Practical implications: This study contributes to helping companies evaluate performance by always complying with tax regulations. Nowadays, there are regulations governing transfer pricing mechanisms and ownership of intangible assets and this study can be an assessment of the regulations effectiveness. Lastly, this study offers empirical evidence to support the discourse of the two pillars of the international tax architecture agreement at the G20 event, where no studies have yet attempted to provide this information. Originality/value: This study uses multinationality as a moderating variable which in previous studies was widely used as an independent variable. This study also uses Internalization theory to explain tax avoidance in cross-border transaction context, especially related to transfer pricing and intangible assets

Time, ties, transactions: temporality and relational work in economic exchange

This paper explores the intersection of time and relational economic sociology. Building on Viviana Zelizer’s relational framework, I argue that analyzing the temporal dimensions of exchange provides insight into how social ties gain meaning through economic practices. The paper shows time’s dual role as both an organizing structure bounding action, and a dynamic element that actors leverage to shape transactional contexts. As structure, time offers culturally-available templates like schedules and rhythms that facilitate coordination and signify predictable social meanings befitting particular relational categories. Yet time also constitutes relational work itself; strategic timing, duration, pacing, and sequencing of interactions signal context, manage expectations, and sustain bonds amidst entanglements. Synchronization through temporal agency prevents mismatches between transactions and social contexts that could strain ties. This agency in time ranges from passive adherence to dominant structures to active assertions of power resistance, enabling both domination and defiance across economic contexts. Analyzing shared temporal infrastructure within circuits of commerce further illuminates how actors distinguish those spheres of exchange at various scale from the impersonal market. Ultimately, incorporating temporality strengthens relational economic sociology by identifying a key mechanism through which practices of exchange become relationally meaningful.

The perpetual twilight of records: consentful recordkeeping as moral defence

In this article, we examine the significance of establishing participatory and consentful recordkeeping practice in the face of ubiquitous use of records beyond their original intent. Among such secondary uses is the decontextualisation of data as part of the 'industrialisation' of access and use of ‘historical’ records within current transactional contexts, together with a wide range of data sharing practices arising from contemporary data science paradigms. To situate the call to action for consentful recordkeeping practice, we begin the article by exploring how human ability to navigate through the perpetual twilight of records becomes increasingly murky when a wholesale approach to data collection and governance is applied by machine learning practitioners. We then re-frame some classical archival principles to align them with participatory approaches; specifically, by expanding the scope of Jenkinsonian ‘moral defence’ as an imperative for proactive engagement with the Archival Multiverse. We then describe a case study of consentful recordkeeping in practice, using the example of the AiLECS Lab’s newly developed collection acquisition and management system. This principles-based framework informs our practices for collecting and curating datasets for machine learning research and development and aims to privilege the ongoing consent of those represented in records to their use. In the context of this work, our core premise is that technologies designed to prevent exploitation of children should aim to avoid underlying data practices that are themselves exploitative (of children or adults).

Dynamic Bi-layer Graph Learning for Context-aware Sequential Recommendation

Sequential recommendations have received great attention in recent years due to their wide application in e-commerce, trip planning, and online education. Contexts reveal the intention of a user in a transaction such as consuming or purchasing an item, and highly affect her behaviour. However, existing techniques cannot fully capture the context-sensitive and dynamic sequential user behaviours for effective and efficient sequential recommendation. To address this limitation, we propose a novel Dynamic Bi-layer Graph learning (DBIG)-based framework for sequential recommendation, which learns the sequence dynamics of user behaviours and contexts. Specifically, we first propose a context graph to identify the relevant contexts to a target user. Then, we propose a transaction context graph that predicts the probability of a transaction happening under certain contexts. In addition, we apply BERT (Bidirectional Encoder Representations from Transformers) to our graph embedding for understanding the user sequential behaviours in bidirectional ways and generating recommendations. Finally, we propose a cluster-structure-based algorithm, which incrementally maintains the DBIG model and BERT over dynamic transaction updates. We evaluate our DBIG-based framework by conducting extensive experiments over five public datasets. The quantitative results demonstrate the superiority of our approach in terms of effectiveness and efficiency.

Transparency and trust in cargo claims: microenterprises selling internationally on a peer-to-peer platform

PurposeThe purpose of this study is to determine the factors that impact the trust of microenterprises in online selling platforms and cargo carriers and examine the consequences of a lack of trust.Design/methodology/approachThis study adopts a qualitative exploratory approach and uses grounded theory to generate insights based on interviews with 27 microenterprise owners selling internationally on an online selling platform.FindingsThe results show that a lack of competence, an absence of an integrated claim system and a lack of transparency are the main factors affecting sellers’ trust in online selling platforms. The relationship between the sellers’ intention to continue to use the online selling platform and their trust in the platform was found to be moderated by switching costs.Research limitations/implicationsThis study is limited in that the results were mainly based on the sellers’ perspectives although the phenomenon of interest involves various actors. To mitigate this limitation and cross-check the data, the customer reviews and some of the sellers’ account statistics were also analyzed.Practical implicationsThis study introduces the sellers’ perspectives on the dynamics of supply chain management in international micro trade. These dynamics provide a guideline for how to build and manage an online selling platform targeting microenterprises.Originality/valueUnlike previous studies, this study examines online transaction behaviors from the standpoint of sellers, not buyers. Moreover, it is the first study examining the damaged or lost shipments within the context of online transactions in international micro trade.

Interaction Design and Research for User Interfaces of Central Bank Digital Currency: An Empirical Study

There is already a consensus among central banks to accelerate the development of Central Bank Digital Currencies (CBDC). To facilitate a smooth money transfer process, the interactive experience of the CBDC user interface design is very important. However, much of the current research has focused on the technical feasibility of the CBDCs, and no scientific research has yet attempted to design an effective CBDC user interface. In this study, a series of CBDC user interfaces were designed to help study the interaction process of CBDCs in a simulated payment transaction context with a focus on the user interface and interactive experience of the CBDCs. The experiment in this study was a 2 (graphical metaphor) × 3 (gesture type) × 2 (visual feedback) mixed factorial design in which a total of 12 CBDC prototypes were created and evaluated based on users’ task performance and a series of subjective evaluations. The results of our empirical study revealed that graphical metaphor user interface design can improve the interface usability and subjective evaluation of CBDCs, and may also trigger the user’s sense of experience with traditional banknotes. Specifically, the use of animated cues for currency movement on the CBDC user interface may help evoke the user’s experience of using cash. In addition, we found that the wave type gesture may cause users to spend more time completing the CBDC operational tasks. Moreover, the animated cue of money moving may have faster performance and a higher degree of rationality. The above-mentioned results may provide an important design reference for CBDC developers to create easy-to-use CBDC services.

Unraveling Abusive Supervision Climate in Aircrew Workplaces: The Roles of Temporary Organizational Features, Trust, and Gender Dynamics.

This study aims to advance the theoretical understanding of the contextual antecedents underlying abusive supervision. It provides a fresh perspective on how subordinates' perceptions of an abusive supervision climate are shaped in temporary work environments. By developing a robust model, this research examines the relationships between temporary organizational characteristics (i.e., temporariness and membership flexibility), trust in ad-hoc supervisors, and perceived abusive supervision climates. We tested the hypothesized model using data from 340 aircrew engaged in temporary and constantly shifting supervisor-subordinate relationships. The results revealed that: (a) temporariness has a direct negative relationship with trust in ad-hoc supervisors, whereas membership flexibility positively affects this trust; (b) the link between temporariness/membership flexibility and a perceived abusive supervision climate is mediated by trust in ad-hoc supervisors. Furthermore, this study highlights gender interactions in a transactional context, indicating that: (c) females perceive a stronger negative association between trust and abusive supervision climates compared to males; and (d) the relationship between temporariness/membership flexibility and trust in ad-hoc supervisors is significant for women and men, respectively. In conclusion, this study underscores the importance of considering the unique organizational characteristics of temporary work settings when examining abusive supervision. It also emphasizes the role of gender in shaping subordinates' perceptions of a workplace victimization climate, particularly in situations where leader-member exchanges are ephemeral and contractual.

Detection and Analysis of Ethereum Energy Smart Contracts

As blockchain technology advances, so has the deployment of smart contracts on blockchain platforms, making it exceedingly challenging for users to explicitly identify application services. Unlike traditional contracts, smart contracts are not written in a natural language, making it difficult to determine their provenance. Automatic classification of smart contracts offers blockchain users keyword-based contract queries and a streamlined effective management of smart contracts. In addition, the advancement in smart contracts is accompanied by security challenges, which are generally caused by domain-specific security breaches in smart contract implementation. The development of secure and reliable smart contracts can be extremely challenging due to domain-specific vulnerabilities and constraints associated with various business logics. Accordingly, contract classification based on the application domain and the transaction context offers greater insight into the syntactic and semantic properties of that class. However, despite initial attempts at classifying Ethereum smart contracts, there has been no research on the identification of smart contracts deployed in transactive energy systems for energy exchange purposes. In this article, in response to the widely recognized prospects of blockchain-enabled smart contracts towards an economical and transparent energy sector, we propose a methodology for the detection and analysis of energy smart contracts. First, smart contracts are parsed by transforming code elements into vectors that encapsulate the semantic and syntactic characteristics of each term. This generates a corpus of annotated text as a balanced, representative collection of terms in energy contracts. The use of a domain corpus builder as an embedding layer to annotate energy smart contracts in conjunction with machine learning models results in a classification accuracy of 98.34%. Subsequently, a source code analysis scheme is applied to identified energy contracts to uncover patterns in code segment distribution, predominant adoption of certain functions, and recurring contracts across the Ethereum network.

When Payments Go Social: The Use of Person-to-Person Payment Methods Attenuates the Endowment Effect

The authors examine how person-to-person (P2P) payment methods affect consumers’ participative pricing decisions. Participative pricing occurs when people choose how much to pay for a good or how much they will sell it for. This pricing mechanism is increasingly common, for example, on platforms like Craigslist, eBay, or Etsy. A successful transaction requires that consumers converge on a mutually acceptable price, yet decades of research on the endowment effect show that sellers often demand more for goods than buyers are willing to pay. The authors propose that compared with traditional payment methods, when consumers use P2P payments they make somewhat more cooperative pricing decisions: buyers are willing to pay a bit more and sellers are willing to accept a bit less. This attenuates the endowment effect and increases the odds of a successful trade. This occurs because even when the trade is with a stranger, P2P payments can subtly activate a social transaction context, cuing the social transaction pricing norm of making more cooperative pricing offers. The authors test these proposals in eight studies using consequential and hypothetical choices, moderation, and mediated moderation. A simulation indicates that compared with traditional payment methods, the use of P2P payments can increase successful transactions in a marketplace by nearly 10%.

To imitate or not to imitate? A note on control misalignment in supply chains

For supply chain partners to realize existing potentials, effective controls are necessary to serve as the underlying basis of relationship management. The design and use of controls are ideally based on the principle of matching, in line with the transaction context. Yet, misaligned control structures commonly exist in practice – and this is often associated with negative performance implications. Based on prior research findings, this article points to imitating behavior as a potential source of control misalignment in supply chains. To imitate appropriately and, hence, avoid situations of misalignment, firms should consider tailoring and adapting the control structure to meet specific relationship needs.

Fiduciary Duty in a Guanxi Society

China has imported the Anglo-American law of fiduciary duty into its corporate statute. I argue that fiduciary duty confronts a problem. Its transplantation is into the rich cultural soil of guanxi, a soil that is incompatible with the equally richly developed culture of fiduciary duty.This is the first paper to examine the relationship between fiduciary duty and guanxi. I conclude that, while fiduciary duty may take root in the limited (but important) context of self-dealing transactions, it is likely to fail in its essential function of guiding fiduciary behavior in the presence of a guanxi relationship.

Credit Card Fraud Detection project

Abstract: For some time, there has been a strong interest in the ethics of banking (Molyneaux, 2007; George, 1992), as well as the moral complexity of fraudulent behavior (Clarke, 1994). Fraud means obtaining services/goods and/or money by unethical means, and is a growing problem all over the world nowadays. Fraud deals with cases involving criminal purposes that, mostly, are difficult to identify. Credit cards are one of the most famous targets of fraud but not the only one; fraud can occur with any type of credit products, such as personal loans, home loans, and retail. Furthermore, the face of fraud has changed dramatically during the last few decades as technologies have changed and developed. A critical task to help businesses and financial institutions including banks is to take steps to prevent fraud and to deal with it efficiently and effectively, when it does happen (Anderson, 2007). Anderson (2007) has identified and explained the different types of fraud, which are as many and varied as the financial institution’s products and technologies, such as Transaction products: credit and debit cards and checks, Relationship to accounts first, second and third parties, Business processes: application and transaction, Manner and timing short versus long term, Identify misrepresentation: embellishment, theft and fabrication, Handling of transaction: lost or stolen, not received, skimming and at hand, Utilization counterfeit, not present, altered or unaltered, Technologies ATM and Internet. Solutions for integrating sequential information in the feature set exist in the literature. The predominant one consists in creating a set of features which are descriptive statistics obtained by aggregating the sequences of transactions of the cardholders (sum of amount, count of transactions, location from where the payment is being made etc..). We used this method as a benchmark feature engineering method for credit card fraud detection. However, this feature engineering strategy raised several research questions. First of all, we assumed that these descriptive statistics cannot fully describe the sequential properties of fraud and genuine patterns and that modelling the sequences of transactions could be beneficial for fraud detection. Moreover, the creation of these aggregated features is guided by expert knowledge whereas sequence modelling could be automated thanks to the class labels available for past transactions. Finally, the aggregated features are point estimates that may be complemented by a multi-perspective univariate description of the transaction context. We proposed a multi-perspective HMM-based automated feature engineering strategy in order to incorporate a broad spectrum of sequential information in the transactions feature sets. In fact, we model the genuine and fraudulent behaviors of the merchants and the card-holders according to two univariate features: the country from where the payment is being made and the amount of each of the transactions being made. Moreover, the HMMbased features are created in a supervised way and therefore lower the need of expert knowledge for the creation of the fraud detection system. In the end, our multiple perspectives HMM-based approach offers automated feature engineering to model temporal correlations so as to complement and possibly supplement the use of transaction aggregation strategies in order to improve the effectiveness of the classification task. Experiments conducted on a large real world credit card transaction dataset (46 million transactions from belgium card-holders between March and May 2015) have shown that the proposed HMMbased feature engineering allows for an increase in the detection of fraudulent transactions when combined with the state-ofthe-art expert-based feature engineering strategy for credit card fraud detection. To conclude, this work leads to a better understanding of what can be considered contextual knowledge for a credit card fraud detection task and how to include it in the classification task in order to get an increase in fraud detection. The method proposed can be extended to any supervised task with sequential datasets. The main aims are, firstly, to identify the different types of credit card fraud, and, secondly, to review alternative techniques that have been used in fraud detection. Indeed, transaction products, including credit cards, are the most vulnerable to fraud. On the other hand, other products such as personal loans and retail are also at risk, and have serious ethical conflicts. Keywords: Behavior and Location Analysis (BLA); Fraud Detection System (FDS); Automated Teller Machine (ATM); Credit Card Fraud Detection; DB: Database.

Comparing Requirements Analysis Techniques in Business Intelligence and Transactional Contexts

Requirements elicitation is a key concern in information technology (IT) projects. Busi-ness intelligence systems (BI) have emerged and are now used widely in organizations. These systems are designed to support manager's decision-making in their business performance moni-toring activities and their requirements are very different from those of transactional systems. But past research did not consider these differences. Therefore, this paper relies on a comparative approach to assess differences in the level of use and perceived effectiveness of requirements analysis techniques in both business intelligence and transactional contexts. An exploratory quali-tative study was conducted with two phases of semi-structured interviews with experienced practitioners. Our results show that 28% of the techniques differ in their level of use or perceived effectiveness, thus demonstrating the specificity of decision makers' needs. Our results reveal the importance of using techniques appropriate to the context to adequately define requirements and improve projects’ success.

Global Payment Systems: A Critical Review

The Banking system is known as the lifeblood and an important base of the economy. It plays a vital role in the economic development and GDP of the country. The Banking System across the globe has improved to a larger extent in the last two decades with the rapid digital wave, globalization, and privatization which encourages more competition resulting in a balanced ecosystem.The world of payments is going to be fundamentally transformed between now and then. It will be reshaped by technology and redefined by regulation, the emergence of new economic powers, and changes in the global currency landscape. Most importantly, payments will be refocused from a commoditized proposition to a strategic, value-adding solution; one that is offered with a greater focus on the broader commercial and transactional context within which payment (or a transfer of value) takes place. In all of this, commercial banks can remain key players, but only if they respond quickly enough and with compelling value propositions.

Material and accompanying logistics transactions: Collaboration and coordination issues

Governance mechanisms are examined within the context of material transaction (vendor-manufacturer governance form) and logistics transactions (vendor-third-party-logistician-manufacturer governance form). Using arguments from dynamic capability proponents, the effect of governance mechanisms (trust, commitment, and flexibility) on logistics capability is found to be contingent on the interactive governance forms. Sampling organizations from material and logistics transactions in a business-to-business setting, financial performance outcomes are a joint function of the governance mechanisms deployed in these transactions.

Household waste management in Shanghai and its implications for the second-tier cities in China

Seeing that Shanghai implemented mandatory household waste sorting system (referred as Shanghai Model) in 2019 and achieved remarkable improvements, the study focuses on how to localize it in second-tier cities. Specifically, by applying system dynamics method, a qualitative Basic Model and a quantitative Shanghai Model simulating residents’ waste related behavior are built. Combined Theory of Planned Behavior and the Split-Core Model are adopted. Data of Zhengzhou is inputted and simulated to representatively deliver policy implications to second-tier cities. The result shows that improving transactional context can lift the weight of willingness and depress the weight of opportunism in behavior decision makings. Shanghai Model significantly improves the legal transaction context of waste sorting which make residents actively sort the wastes under the promotion of willingness. For second-tier cities of China, improving transactional context to reduce opportunism and conquering the short board of willingness to promote active participation are indispensable. And, waste reducing measures like the unit pricing system are recommended to make up the shortage of the Shanghai Model. The study puts forward a synthetic analyzing framework of waste related behaviors and builds a portable policy analyzing system of waste management for both China and other developing countries.

What is the Added Value of Social Network Analysis when Developing and Evaluating Complex Interventions

IntroductionMost complex interventions target upon a network of multiple (health care) professionals. Social Network Analysis (SNA) is a powerful technique that aims to characterize and study how social relationships within a network establish and evolve. This study identified the added value of using SNA in the developing and evaluation of complex interventions.Theory/Methods A scoping review was conducted by identifying the research question, identifying relevant studies, selecting studies, charting the data; and collating, summarizing and reporting the results. EMBASE, PsycInfo, CINAHL and PubMed were searched with a timeframe of 15 years. Complex healthcare intervention studies using SNA were included. The study selection and data extraction were conducted by two researches independently. We identified the characteristics, the reported strengths and limitations and reported implications of SNA application in complex intervention studies.ResultsThe search identified, after removal of duplicates, 2466 studies. After abstract screening, 40 full text studies were assessed for eligibility resulting in 25 studies that were included. Fifteen studies used SNA to examine effectiveness, one study in examining acceptability, one in identifying interventionists, five in process evaluation studies, and three in implementation studies.Reported strengths of SNA application were that primary data can be collected through several methods, and the easy feasibility of data collection and visualization of results. A reported limitation in data analysis was the challenge for untrained researchers to use SNA programs.Reported implications of using SNA when developing complex interventions was identifying key individuals who can be harnessed for dissemination of innovations or selected as interventionists. When evaluating complex interventions, SNA can support the conclusions from traditional analysis and generated new information such as revealing important intervention dynamics that would not have been found with classical methods. SNA allows analysis of the network as whole system and on individual level. When implementing, SNA can provide understanding of the barriers and/or facilitators of the diffusion and implementation of the intervention which offers actionable insights. DiscussionThe application of SNA is wide but at the same time very underutilized in complex intervention research. The optimal use of SNA in developing and evaluating complex interventions is therefore currently underexposed.ConclusionSNA is a widely applicable method that can be used in different phases of complex intervention research. Studies reported more strengths than limitation in the application of SNA. The reported implications emphasized the diverse and added value of using SNA in the development and evaluation of complex interventions.Lessons learnedThe potential value of SNA in unravelling and characterizing networks in the development and evaluation of complex interventions needs more attention in health care research.LimitationThere is no sharp boundary between simple and complex health care interventions. Therefore, search terms that widely cover complex interventions in health care were used and a hand search of reviews was performed.Suggestion for future researchRoutine use of SNA in developing and evaluating complex interventions could gain actionable insights which are useful in a transactional context as in complex interventions.

13 City, State, and Market: Lessons from Mesoamerica

ABSTRACTIn evaluating the contributions to this issue, this chapter questions the predictable co‐occurrence of cities with markets and states, a long‐held position in western social theory. However, an extreme relativism is also flawed, and the projection of anti‐capitalist fantasies on past, other peoples have equally distorted interpretations of the archaeological record and blinded researchers to the reality of market economies in societies including the Maya. Ultimately, the power of the comparative method entails more than the identification of commonalities between different market traditions. It can also serve to illuminate how market economics were embedded in distinct cultural, ideological, and material worlds. Calculating self‐interest, supply‐and‐demand, and impersonal exchange do not operate according to a single behavioral logic but are shaped by ideologies of identity and desire specific to distinct regimes of value. Therefore, attention to the cultural and spatial context of economic transactions—in the original spirit of Polanyi—remains indispensable to interpreting how markets may have shaped historically particular constructions of personhood, community, inequality, place, and the ontological status of commodities. In the end, I argue that archaeologists also need to investigate the political affordances of markets as specific urban places and not simply as epiphenomena to a priori political or economic institutions.