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This paper aims to identify and discuss insights from the business model field on the creation and delivery of value to customers that provide new thinking in relation to the strategic management accounting field.

The customer emphases exhibited in parts of the extant strategic management accounting literature are highlighted and amplified using insights from the business model literature, including those relating to value propositions, customer value creation and delivery and meeting customers’ value expectations.

The paper demonstrates that in addition to providing valuable insights for accounting to management, an extended strategic management accounting concept enables accounting and reporting to customers, now identified as major stakeholders, in the context of integrated reporting.

Through its customer resonances, the paper affirms strategic management accounting’s practical utility for organisations seeking a strong position in highly competitive marketplaces, via the addition of a focus on accounting to customers.

The paper’s use of insights from the business model literature further reinforces the view that strategic management accounting potentially constitutes a pivotal development within both managerial and financial accounting and reporting.

This study aims to investigate the impact of organizational external environmental factors on strategic management accounting (SMA) usage in an emerging economy.

The study collected data from 79 public limited companies listed with the Dhaka Stock Exchange (Bangladesh) through a questionnaire survey. Multiple regression analysis is employed to test the impact of external environmental variables such as perceived environmental uncertainty and intensity of competition on SMA usage.

The study finds a significant positive impact of environmental uncertainty (fluctuation in the external environmental factors) and intensity of competition (domination by few companies) on SMA usage. However, the direction and magnitude of this impact vary considerably for specific groups of SMA practices such as costing, competitor accounting, customer accounting and planning and performance measurement techniques.

This study shows the impact of several facets of environmental uncertainty (i.e. unpredictability, fluctuation, ambiguity, lack of information and uncertainty of the outcome of decision) and intensity of competition (i.e. stressfulness and domination) in the empirical-based SMA research.

After the effective date of International Financial Reporting Standard (IFRS) 15, the accounting treatment of credit card rewards programmes (CCRPs) is no longer explicitly prescribed. Uncertainty regarding what constitutes faithful representation, and the inconsistent accounting practices observed, has created a need for guidance on the appropriate accounting treatment of CCRP transactions. Accounting theory has the potential to provide the foundation for this guidance. As a result, the objective of this study was to develop a theoretical model for the accounting treatment of CCRP transactions using accounting theory.

This non-empirical qualitative conceptual study utilised document analysis, focussing specifically on accounting theory, to construct an accounting treatment model.

Applying the relevant accounting theory (International Accounting Standards Board's (IASB's) Conceptual Framework), a theoretical model for the accounting treatment of CCRP transactions was developed, which emphasises the importance of understanding the economic phenomenon (the CCRP transaction) and determining how management views the transaction (in isolation as marketing or as an integral part of the credit card transaction).

Addressing the problem of accounting for CCRP transactions with reference to accounting theory (which is the main element of scholarly activity in accounting) distinguishes this study from previous research on the topic. The CCRP accounting treatment theoretical model could assist CCRP management in faithfully accounting for a CCRP transaction and reduce uncertainty and inconsistency in practice. Moreover, this study identified the procedures to be employed when using accounting theory to determine the appropriate accounting treatment of business transactions. These procedures could be employed by accountants when faced with other transactions not covered by specific accounting standards.

The purpose of this paper is to find out the role and factors that lead to efforts by banking institutions to deal with money laundering by using the principle of knowing your customer.

This research method uses a sociological juridical approach and descriptive analysis in analyzing the data.

The results of the study found that the implementation of the principle plays a role in identifying each transaction, and if there is a transaction that is considered suspicious, each bank is required to report the transaction to the center for reporting and analysis of financial transactions.

Banks must reduce the risk of being used as a means of money laundering by knowing customer identities, monitoring transactions, maintaining customer profiles and reporting suspicious transactions made by parties using bank services. The application of the know your customer principle (KYCP) is based on the consideration that KYCP is not only important in the context of eradicating money laundering but also in the context of implementing prudential banking to protect banks from various risks in dealing with customers.

To the best of the author’s knowledge, this is first empirical study of banking in Indonesia that conduct money laundering crimes through application of KYCPs.

This study aims to integrate research on customer success (CS) management with the service ecosystems perspective of selling to enhance the understanding of the CS management function and the outcomes selling firms should expect based on implementation of CS management.

The authors apply the service ecosystems perspective of selling to describe how CS management is manifested in practice by offering relevant insights and practical industry examples.

Study findings identify relevant ecosystem actors, acting on behalf of the customer, required for the delivery of desirable customer outcomes. Study findings also link the orchestration efforts of CS managers to theory-based tenets for explanation of how CS management facilitates the attainment of competitive advantages via the thickening and thinning of ecosystem crossing points.

Given that the research is conceptual, additional research that empirically examines this framework and the insights presented would lend further credence to the recommendations the authors suggest.

From a practical perspective, the authors present a “Customer Relationship and Solution Innovation Matrix” which integrates necessary value-creating activities that CS managers perform and the coordination with internal actors that CS managers rely on to create value.

Although the practice of CS management is becoming increasingly common, theoretical approaches capable of explaining the function have been lacking. Similarly, while the service ecosystems perspective redefines selling to encompass a broader set of actors than traditionally examined, practical examinations of the theory are limited. The authors address these issues, integrating both research streams for an enhanced understanding of the CS management function through the service ecosystems perspective theoretical lens.

The present work has proposed and employed an innovative hybrid method based on the combination of factor analysis and an artificial neural network (ANN) model to forecast customer satisfaction from the identified dimensions of service quality in India, a developing country.

The qualitative study is conducted with Internet banking users to understand e-banking clients' perceptions. The data is collected with the help of a questionnaire from randomly selected 208 customers in India. Firstly, factor analysis was performed to determine the influential factors of customer satisfaction, and four factors i.e. efficiency, reliability, security and privacy, and issue and problem handling were extracted accordingly. The neural network model is then applied to the factor scores to validate the key elements. Lastly, the comparative analysis of the actual ANN and the regression predicted result is done.

The success ability of the linear regression model is challenged when approximated to nonlinear problems such as customer satisfaction. It is concluded that the ANN model is a better fit than the linear regression model, and it can recognise the complex connections between the exogenous and endogenous variables. The results also show that reliability, security and privacy are the most influencing factors; however, problem handling and efficiency have the slightest effect on bank client satisfaction.

This research is conducted in India, and the sample is chosen from the urban area. The limitation of the purposeful sampling technique and the cross-sectional nature of the data may hamper the generalisation of the results.

The conclusions from the study will be helpful for policymakers, bankers and academicians. To our knowledge, few studies used ANN modelling to predict customer satisfaction in the service sector

In October 2016, Timothy Sloan, the newly appointed CEO of American banking giant Wells Fargo, faced a massive public-relations crisis. A few weeks earlier, a United States government agency had announced the results of its regulatory review of the bank and exposed a shocking practice common in the retail division, in which aggressive community bankers had created more than a million fraudulent accounts and credit card applications on behalf of unaware customers for the past several years. Over the next few weeks, the bank—and Sloan's predecessor, John Stumpf, in particular—suffered from harsh criticism from politicians, journalists, and former employees alike, ultimately forcing Stumpf's resignation. As Sloan sought to minimize the public-image backlash and restore general trust in Wells Fargo, he struggled to construct the best communication strategy for the bank's next chapter.

The purpose of this paper is to examine the contribution of big data in the transforming process of an IT firm to a learning organization.

The authors adopted a qualitative research approach to define and interpret the ideas and experiences of the IT firms’ employees and to present them to the readers directly. For this purpose, they followed a single-case study design. They researched on a small and medium enterprise operating in the IT sector in Düzce province, Turkey. This paper used a semi-structured interview and document analysis as data collecting methods. In all, eight interviews were conducted with employees. Brochures and website of the organization were used as data sources for the document analysis.

As a result of in-depth interviews and document analysis, the authors formed five main themes that describe perception of big data and learning organization concepts, methods and practices adopted in transforming process, usage areas of big data in organization and how the sample organization uses big data as a learning organization. The findings of this paper show that the sample organization is a learning IT firm that has used big data in transforming to learning organization and in maintaining the learning culture.

The findings contribute to literature as it is one of the first studies that examine the influence of big data on the transformation process of an IT firm to a learning organization. The findings reveal that IT firms benefit from the solutions of big data while learning. However, as the design of the research is single-case study, the findings may be specific to the sample organization. Future studies are required that examine the subject in different samples and by different research designs.

In literature, research on how IT firms’ managers and employees use big data in organizational learning process is limited. The authors expect that this paper will shed light on future research that examines the effect of big data on the learning process of the organization.

This paper examines the relationships between bank switching and both customer vulnerability and consumer-oriented policies (financial education and disclosure practices).

The analysis employs microdata from the Special Eurobarometer on Financial Products and Services, for 24 European nations. It carries out a probit estimation on the factors explaining propensity of bank switching, focusing on three characteristics associated with customer vulnerability: an advanced age, low educational attainment and residence in a rural or a relatively poor region.

The authors report that the probability of bank switching is significantly lower for three groups of vulnerable customers: the elderly, the less educated and those living in deprived regions. Further the authors identify that national financial education policies and disclosure practices have no significant effects on bank switching.

Based on these results, the authors propose more targeted policies recognising customers' heterogeneity are required to increase bank switching behaviour.

This paper exploits a unique source of information on bank switching behaviour and customer characteristics across European nations. These data are complemented with information about consumer financial education policies and disclosure practices from the World Bank and geographical, market and regulatory factors at the regional and national levels. The paper contributes to two academic areas. First, it presents further evidence on heterogeneity of bank customer switching behaviour, addressed at improving the understanding of customer vulnerability in banking services. Second, it examines the efficacy of consumer-oriented policies (financial literacy and disclosure practices) in encouraging bank switching.