Using humanness and design aesthetics to choose the “best” type of trust: a study of mobile banking in France

PurposeThe research aims to addresses the limitations of previous literature regarding choosing the appropriate conceptualization of trust (i.e. interpersonal trust or system trust) and the role of design aesthetics in generating system trust and intention to adopt mobile banking.Design/methodology/approachThe research conducts two studies. Study 1 determines the degree of humanness in a mobile banking application. Study 2 tests the research model. A total of 261 respondents participate in Study 1 and 491 in Study 2. Statistical Package for the Social Sciences (SPSS) (study 1) and SmartPLS (PLS software) (study 2) are used to test the hypotheses.FindingsStudy 1 establishes that the mobile banking application is perceived to have low humanness. Thus, it is expected that system trust is more appropriate to use than interpersonal trust. Study 2 demonstrates that (i) system trust is more useful than interpersonal trust in the mobile banking context and (ii) design aesthetics positively influences consumer system trust and intention to adopt.Originality/valueTo the best of the authors' knowledge, the current research is the first to distinguish empirically between system trust and interpersonal trust and identify the best choice of mobile banking trust type. Specifically, the study determined the choice of system trust for mobile banking through a priori humanness measures and validated this choice by measuring both system trust and interpersonal trust, which has not been done before. In addition, retail banking should consider the influence of design aesthetics on consumer trust and incorporate elements that enhance consumers' opinions about the mobile banking application's functionality, reliability and helpfulness.

Education loan delivery by banks in India: A qualitative enquiry

Education financing is a key retail banking product for most commercial banks and a lifeline for large numbers of students seeking professional courses. This study aimed to identify the impediments in the successful delivery of this loan product in India, where it is marketed majorly by public sector banks under a common scheme devised by the government. The study adopted a qualitative approach to probe behavioral issues related to the credit appraisal process, which is the most suitable approach for unstructured exploratory design. Since credit managers in banks work with applicants for education loans, their insight becomes essential to understanding the issues plaguing with the smooth implementation and delivery of this scheme. Thus, ten public sector bank managers working in different geographical locations were selected using a homogeneity purposive sampling technique. The study collected 41 responses, which were then divided into 4 major categories. The responses were simultaneously transcribed manually to ensure that data remained close to the original verbatim of the participant. All transcribed interviews were imported into ATLAS.ti 8 Software for analysis. The 4 observational categories lead to a broad understanding that product accessibility, operational hurdles, scheme features and limitations in bad loan recovery are key bottlenecks in managing education loans. These responses had over 80% commonality on key issues of product feature and cost. It was concluded that education financing can perform better by improving access, rationalizing interest rates and liberalizing repayment terms. These findings can be used as input for tweaking the product for better performance.

The impact of hedonic and utilitarian dimension in mobile service banking quality towards relationship quality

<p>Service quality is vital for retail banking institutions nowadays to have a competitive advantage against their competitors. One of the ways was developing a mobile banking application. By relying on the mobile banking application, the banking institutions would serve their existing customers better and attract new potential customers. The purpose of this research was to investigate the effect of mobile banking service quality empirically in terms of the utilitarian and hedonic dimensions on the relationship quality variables, namely commitment, trust, and satisfaction. The research focused on 220 respondents from university students in Indonesia who are at least 17 years old and using a mobile banking application on their smartphones. The method for collecting data is based on convenience sampling. The Structural Modelling Equation was also used to analyze the data result. The findings show that trust significantly and positively influences commitment/satisfaction. Furthermore, the dimensions of mobile 'banking. Service quality (Security/ Privacy, Practicality, Design/Aesthetics, and Enjoyment) has a low-moderate effect on relationship qualitative variables (Trust, Satisfaction, and Commitment). The dimensions of mobile banking service quality positively influence the relationship quality, except PPracticalitydoes not affect Commitment, Design/Aesthetics does not influence trust, and enjoyment does not influence commitment.</p>

Exploration of the investment patterns of potential retail banking customers using two-stage cluster analysis

Identifying investment patterns as part of customer segmentation is one of the most important tasks in retail banking. Clustering customers effectively is an important element of improving marketing policy and strategic planning. There are several methods for identifying similar groups of customers and describing their characteristics to offer them appropriate products. However, using machine learning methods is rare, and the application is limited for certain types of data. The aim of this study is to investigate the benefits of using a two-stage clustering method using neural-network-based Kohonen self-organizing maps followed by hierarchical clustering for identifying the investment patterns of potential retail banking customers. The unique benefit of this method is the ability to use both categorical and numerical variables at the same time. This research examined 1,542 responses received for an online investment survey, focusing on the questions that are related to the respondents’ investment preferences and their current financial assets. The research utilizes descriptive statistics and multiple correspondence analysis (MCA) to understand the variables and Kohonen self-organizing maps (SOMs), in combination with hierarchical clustering, to identify customer groups and describe the characteristics of these clusters. The analysis was able to identify clusters of potential customers with similar preferences and gained insights into their investment patterns related to their investment portfolio and investment behavior, including their savings profile, attitude to risk-taking, and preferences for investment advice. These findings were supported by additional insights through the application of multiple correspondence analysis (MCA) describing patterns of financial instruments and portfolios. The main contribution of the research is the combined application of the machine learning methods Kohonen SOM, hierarchical clustering, and MCA for investment pattern analysis in the retail banking business.

Key Trends and Regulations of the Development of Digital business Models of banking services in Industry 4.0

The subject of the research is trends in the implementation of digital technologies in the banking sector. The relevance of the paper is due to the objective processes of global digital intervention of technologies in all spheres of human life and society. The research aims to identify, systematize and generalize key trends and regulations in the development of digital business models of banking services in Industry 4.0. For the first time, the authors identified and systematized modern trends and regulations in the development of digital business models of banking services in Industry 4.0, offered their own conceptual vision of the concept of “digital business model of banking services”. The authors apply general scientific, philosophical, analytical, statistical, problem chronological and historical-genetic methods, as well as methods of expert assessments. The article summarizes the main stages of the evolution of business models of the banking sector, reveals substantive and methodological differences between traditional remote banking services and digital banking, highlights the main business models for organizing digital banking; provides up-to-date data on the level of development of digital banking in the main geographic zones of the world; shows the dynamics and key areas of investment in the fintech industry in 2014–2019 and provides a critical analysis of their conditions; identifies problematic aspects of the development of digital business models of banking; describes the functionality of the main digital business models of Russian banks with the author’s assessment of their capabilities and examples of their use in Russian practice. The authors conclude that the main drivers of digitalization of the banking sector are stable growth of non-cash payments in the world and in Russia; stable growth of the global digital banking market; the impact of the COVID-19 pandemic on the active demand of consumers of remote financial services; increased competition in the retail banking market; and a significant decrease in margins for traditional banking products. Identification and systematization of trends and regulations in the implementation of digital business models of banking services can form the basis for further analysis of the specifics of digitalization and personalization of digital banking in Industry 4.0 for the sustainable socio-economic development of the country in terms of possible advantages and threats to the security of financial resources and personal data of customers.

The role of switching cost in the e-service recovery framework among banking customers

Purpose The emergence of tech-driven initiatives in retail banking has created a vast spectrum of system-related service failures; hence, e-service recovery quality is of prime importance to banks to ensure e-service recovery satisfaction. However, e-service satisfaction is dependent on the ease of moving from one service provider to the other; thus, switching costs assume great significance. This study aims to probe the moderating role of switching cost on e-service recovery satisfaction by exploring e-service recovery quality antecedents. Design/methodology/approach A measurement model is suggested in the contextual settings of the Indian banking scenario and is estimated using structural equation modeling. Responses from 399 e-banking customers, who had experienced a service failure, were sought using a five-point Likert scale. Findings The result affirms that “recovery expectation” is the most significant predictor of e-service recovery satisfaction, and that switching cost moderates the relation between e-service recovery quality and e-service recovery satisfaction. Practical implications The study highlights the high relevance of switching costs in the e-banking context and emphasizes investment in marketing strategies and campaigns to do away with switching intentions. It also highlights the relevance of recovery expectations as an antecedent of e-service recovery quality and thus stresses the need to satisfactorily address the same in the e-service recovery process. Originality/value This study contributes to the e-service recovery satisfaction literature in the banking context by empirically validating the moderating role of switching cost. It also identifies the critical antecedents of banking e-service recovery quality.

Antecedent of Organizational Change and Its' Consequnce towards Organizational Performance

Even very successful organizations need to constantly change (evolve) due to very dynamic business environment conditions (Pangarkar, 2015). An organization needs to adapt to any changes in technology, economy, demographics, regulations, competition, and consumer preferences that change rapidly (Anyieni, 2016). Dynamic changes also constantly occur in the banking industry in Indonesia. As the central institution in driving economic growth, the bank needs to be more adaptive to changes in the business environment driven by customer expectations, technological capabilities, policies, demographics, and macroeconomic conditions. Over the last ten years, competitive pressures in the industry have put pressure on the level of banking profitability and efficiency issues (Source: SPI 2019, www.ojk.go.id). Barquin et al. (2018) also mentioned that technology development had brought a new competitive landscape in the banking industry. Technology has provided more convenience in terms of access to the financial services that also raise concern on the relevance of old-style banking services with high reliance on the conventional branch as access. As an impact of technology development change in financial services, increasing financial technology (fintech) services have emerged another competition platform in the banking industries in recent years. Digital technology will change the competition platform in the financial services industry. If banks are not ready to adapt to the change will be exposed to the shrinking market share (www. Economy.okezone.com, 2019). Fintech is expected to put more pressure on banking lending products, particularly within the retail banking segment, potentially will exist in 2025, as explained by McKinsey (www.keuangan.kontan.co.id, 2018). The commercial lending segment will expose to the competition due to technical support in terms of ease of access. Strong investor support to develop their market in Indonesia is expected to accelerate the change of competition landscape in the small-medium enterprise business (www.money.kompas.com, 2019). Keywords: Change, Leader, Organizational Commitment, Organizational Change, Organizational Learning, Organizational Performance.

Validating brand identification and personality scale within the South African retail-banking context

While marketing experts agree that brand personality is important for brand identification, there is no evidence of a validated brand-identification-and-personality scale in the context of retail banking in South Africa. To address this literature gap, this study’s purpose was to explain the process used to validate brand identification and personality within the retail-banking context of South Africa. A convenience sample of Generation Y banking consumers was selected, and a descriptive and single cross-sectional research design was followed. Self-administered questionnaires were used as a data collection tool and a sample size was chosen (N = 235). Data analysis entailed descriptive and confirmatory factor analysis. The confirmatory factor analysis results validated brand identification and brand personality in retail banking as a five-factor structure that includes bank identification and brand personality dimensions such as successfulness, sophistication, sincerity and ruggedness. Furthermore, the results of the study indicate the internal consistency and composite reliability of the measurement model, as well as construct, convergent, discriminant and nomological validity. In addition, the measurement model revealed no signs of multicollinearity between the factors, and the model fit index values of IFI, TLI, CFI, SRMR and RMSEA showed a good fitting model. This study concluded that this five-factor model is a reliable and valid instrument of brand identification and personality in retail banking and is the first validated brand-identification-and-personality scale within the retail-banking context of South Africa.