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Purpose – This paper focuses on a unique historical case study of industry evolution in order to develop a road map where historical and strategic research could develop a common ground for trans-disciplinary inquiry.

Design/methodology/approach – The industry I explore is the Universal Credit Card Industry since its inception with the Diners Club in 1949 until its maturity in late 1990s. My empirical objective here is to develop a historically detailed and theoretically rich case study in which evolutionary processes are discovered as a result of the historical narrative.

Findings – The historical account of the industry demonstrates how the evolution of alternative business models as organizing forms has led to the establishment of interorganizational platforms with unique ecosystems. These alternative business models, through various experimentations, have ultimately produced two critical interorganizational organizations, one based on an open-loop system represented by Visa and MasterCard, and the other based on a closed-loop system represented by Diners Club and the American Express. The historical account also shows that in a given industry competition is not only among specific firms in the industry but also among the business models and the platforms created by these models.

Originality/value – I conclude that historical analyses reveal the nature of competition not only among firms but also among alternative business models where traditional strategy research rarely covers.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

This study investigates the relationship between financial inclusion (FI) and banks’ performance in the economy of Jordan using annual data of 13 commercial banks from 2009 to 2014. Performance is measured by gross income and return on assets (ROA) of these banks. To ensure the robustness of our results, we used six different measures of FI. These include credits for small and medium enterprises (SMEs), deposits for SMEs, number of ATMs, number of ATM services, number of credit cards, and new services. We found a significant impact of FI on ‘ performance when measured by gross income, and ROA, although our study displays different results when considering the effect of FI variables separately. Thus, FI contributes to enhance the banks’ performance. Therefore, the banks should devote more resources to increase FI as it benefits their profitability.

Purpose: This chapter aims to examine machine learning (ML) models for predicting credit card fraud (CCF).

Need for the study: With the advance of technology, the world is increasingly relying on credit cards rather than cash in daily life. This creates a slew of new opportunities for fraudulent individuals to abuse these cards. As of December 2020, global card losses reached $28.65billion, up 2.9% from $27.85 billion in 2018, according to the Nilson 2019 research. To safeguard the safety of credit card users, the credit card issuer should include a service that protects customers from potential risks. CCF has become a severe threat as internet buying has grown. To this goal, various studies in the field of automatic and real-time fraud detection are required. Due to their advantageous properties, the most recent ones employ a variety of ML algorithms and techniques to construct a well-fitting model to detect fraudulent transactions. When it comes to recognising credit card risk is huge and high-dimensional data, feature selection (FS) is critical for improving classification accuracy and fraud detection.

Methodology/design/approach: The objectives of this chapter are to construct a new model for credit card fraud detection (CCFD) based on principal component analysis (PCA) for FS and using supervised ML techniques such as K-nearest neighbour (KNN), ridge classifier, gradient boosting, quadratic discriminant analysis, AdaBoost, and random forest for classification of fraudulent and legitimate transactions. When compared to earlier experiments, the suggested approach demonstrates a high capacity for detecting fraudulent transactions. To be more precise, our model’s resilience is constructed by integrating the power of PCA for determining the most useful predictive features. The experimental analysis was performed on German credit card and Taiwan credit card data sets.

Findings: The experimental findings revealed that the KNN achieved an accuracy of 96.29%, recall of 100%, and precision of 96.29%, which is the best performing model on the German data set. While the ridge classifier was the best performing model on Taiwan Credit data with an accuracy of 81.75%, recall of 34.89, and precision of 66.61%.

Practical implications: The poor performance of the models on the Taiwan data revealed that it is an imbalanced credit card data set. The comparison of our proposed models with state-of-the-art credit card ML models showed that our results were competitive.

After more than three decades of research and legal cases pursued by the European Commission (EC) and national regulators, interchange fees for four-party consumer card transactions are capped on December 9, 2015 across the European Union (EU). Since then, the development of card scheme fees has been a raising concern for merchants. Due to their nature, these fees have not been dealt with in research or covered by the Interchange Fee Regulation (IFR). This chapter aims to assess the recent development of card scheme fees within four-party card payment networks by relying on survey data obtained from 104 merchants across the EU. Findings show that for half of the merchant population card scheme fees have increased since the regulation. Further concerns related to transparency of fees, pass-through of savings to retailers and subsequently consumers, and the development of commercial cards are discussed. In light of the EC's scheduled review of the impacts of the policy intervention in 2019 (Article 17 of the IFR), this chapter evaluates alternative arrangements for the setting of card scheme fees with a focus on the legal basis for a potential regulation. Findings shall provide a ground for further interaction between academics, practitioners, and policymakers.

Internal control mechanisms are fundamental to organizational governance; particularly, to the agency relationship associated with decentralization of decision rights. Management accounting and organizational literatures provide conflicting predictions on the association between decentralization and internal controls, with some research arguing that internal controls be tightened to mitigate the risks associated with greater decentralization of decision rights while other work avers that tighter internal controls defeat the purposes of decentralization. In this chapter, we argue that managers choose these two organizational design variables jointly. Capitalizing on a unique database of control practices in the purchasing and payment process within the procurement function, this chapter examines the relationship between control tightness – a critical characteristic of internal controls – and decentralization. Using a simultaneous equation model, the study finds that decentralization and internal control design are endogenously determined. Tight control is negatively associated with the level of decentralization, while decentralization has a positive effect on the tightness of control. These results reconcile the apparently contradictory results relating these two variables. The chapter also finds that decentralization and tight control mechanisms operate both independently and synergistically to improve performance.

The chapter is prepared on the basis of previous scientific developments of the author, as well as the current legislation of the United States of America. The following laws were studied: Truth in Lending Act; Electronic Fund Transfers Act; Fair Credit Reporting Act; Consumer Leasing Act; Consumer Protection Act; Equal Credit Opportunity Act; Fair Debt Collection Practices Act; Real Estate Settlement Procedures Act; Privacy of Consumer Financial Information Act; Home Mortgage Disclosure Act; Alternative Mortgage Parity Act; Code of Arbitration Procedure for Customer Conflicts – Customer Code; and Code of Arbitration Procedure for Industry Conflicts. One of the new US laws was analyzed – Arbitration Fairness Act, 2017. Data was also used from the Final Report to Congress on the use of pre-dispute arbitration clauses in consumer financial services contracts, 2015, and information resources available on the websites of financial regulators: the Federal Reserve, the Federal Deposit Insurance Corporation, the Office of the Currency Comptroller, the National Administration of Credit Unions, the Securities and Exchange Commission, the Commodity Futures Trading Commission, the Federal Agency for Housing Finance, the Financial Bureau Consumer Protection, Financial Industry Regulatory Authority, and American Arbitration Association.

Methodologically, the research is based on the author's materialistic worldview, which is implemented meaningfully in a positivist approach to the scientific article. In preparing the chapter, general scientific methods were applied: formal logic, system-functional, historical, analysis and synthesis, induction and deduction; special methods: mathematical, and statistical. Also the author applied private scientific methods of jurisprudence: normative-dogmatic, method of legal and technical design, interpretation of law, and others.

In this chapter customer opinion and perception towards e-payment system is disclosed with the help of descriptive analysis of the responses collected from the respondents using questionnaire.

To examine bad credit experiences in the context of identity to understand the entanglement between bad credit and the deformation of identity.

A qualitative method using depth interviews and hermeneutical analysis.

Bad credit is a major life event and plays a critical role in identity. By restricting or eliminating identity construction and maintenance through consumption, identities are deformed. Consumer identities are deformed as they are consumed by the identity deformation process as normal patterns of consumption that have built and supported their identities are disrupted and demolished. Bad credit is overwhelmingly consumptive of consumers – it consumes their time, energy, patience, lifestyle, relationships, social connections, and perhaps most importantly, it consumes their identity as it deforms who they are.

Researchers need to examine more closely not just the creation and maintenance of identity, but also how identity is deformed and deconstructed through consumption experiences that can no longer be enjoyed.

Government agencies may want to reexamine policies toward the granting of credit to reduce the incidence of loading up consumers with credit they are not able to pay for. The deformation of identity may result in anti-social behavior, although our study does not address this directly.

This study is different from previous work in several ways. We focus on identity deformation due to bad credit. By analyzing a crisis response that transcends the specific impetus of bad credit, we extend identity theory by developing an insight into “identities-in-crisis.” We also provide a theoretical framework and explore how consumers’ identities are deformed and renegotiated.