Ieva Meidutė-Kavaliauskienė

Integrating Metacognitive and Psychometric Decision-Making Approaches for Bank Customer Loyalty Measurement

Greater competition and the aftermath of the financial crisis have meant that banks are increasingly focused on improving service quality and achieving higher levels of customer loyalty. Doing so requires being able to identify, understand and measure the determinants of such loyalty, however; and given the variety of multi-faceted factors involved, and the interrelationships among them, this is a complex undertaking. This paper proposes and tests an integrated application of cognitive mapping and multiple criteria decision analysis (MCDA), thus combining metacognitive and psychometric decision-making approaches, to create a framework for the assessment of bank customer loyalty, which identifies its determinants and allows the trade-offs among them to be calculated. Practical advantages and limitations of our proposal are also discussed.

A metacognitive decision making based-framework for bank customer loyalty measurement and management

AbstractBank customer loyalty is becoming a priority concern for banking institutions, as a means of gradually increasing complementary margins and eliminating the lack of liquidity caused by the current economic climate. Following a top down process, this focus culminates at the branch level, where banks’ front office employees are seen as a driving-force for building customer loyalty. At the same time, however, the difficulty in identifying and operationalizing the factors or determinants that most contribute to creating and maintaining bank customer loyalty has long been recognized. In this sense, based on the integrated use of cognitive maps and measuring attractiveness by a categorical based evaluation technique (MACBETH), this study proposes a multiple criteria framework for bank customer loyalty measurement and management. The results show that our framework allows bank customers with higher rates of customer loyalty to be identified and, from a benchmarking perspective, indicates what best practic...

Setting rents in residential real estate: a methodological proposal using multiple criteria decision analysis

The real estate sector has been negatively affected by the recent economic recession, which has forced structural changes that impact property value and price. Recent pressures have also motivated reduced liquidity and access to credit, causing a drop in property sales and, thus, boosting the rental housing market. It is worth noting, however, that the rental housing segment is not with-out difficulties and complexity, namely in terms of legislation and rental value revaluation. In light of this reasoning, this study aims to develop a multiple criteria decision support system for calculation of residential rents. By integrating cognitive maps and the measuring attractiveness by a categorical based evaluation technique (MACBETH), we also aim to introduce simplicity and transparency in the decision making framework. The practical implications, advantages and shortfalls of our proposal are also analyzed.

An idiosyncratic decision support system for credit risk analysis of small and medium-sized enterprises

AbstractSmall and medium-sized enterprises (SMEs) are currently considered an important driving force of economic growth. Several studies have been developed to analyse this issue and, in particular, to assess the credit risk of SMEs. Most of these applications, however, share the same methodological limitations, such as the manner by which criteria are selected, or the methods used for calculating the weights between them. Based on the integrated use of cognitive mapping techniques and the Interactive Multiple Criteria Decision Making (TODIM) approach, this study aims to create an idiosyncratic decision support system for the identification of multiple criteria and the calculation of their respective weights (i.e. the trade-offs) in the evaluation of SME credit risk. The results show that the model created in this study allows for simple and straightforward credit concession decisions, facilitating the evaluation of SME credit applications through more informed and transparent risk assessments. Practical...

A fuzzy knowledge-based framework for risk assessment of residential real estate investments

AbstractRisk analysis of residential real estate investments requires careful analysis of certain variables (or determinants). Because real estate is a key sector for economic and social development, this risk analysis is seen as critical in supporting decision processes relating to buying or selling residential properties, partly due to the pressures caused by the current economic environment. This study aims to develop a conceptual reference model for risk assessment of residential real estate using fuzzy cognitive mapping. This fuzzy model allows cause-and-effect relationships between determinants to be identified and better understood, which in turn allows for better informed investment decisions. The results show that the use of cognitive maps reduces the number of omitted criteria and favors learning with regard to how the criteria relate to each other, holding great potential and versatility in structuring complex decision problems. Practical implications, strengths and weaknesses of our proposal a...

Enhancing knowledge and strategic planning of bank customer loyalty using fuzzy cognitive maps

AbstractUnderstanding customer loyalty has been a growing concern for the services industry. In a context of increasing competitive pressures, such loyalty is seen as a key element in service companies’ success. Maintaining customer loyalty and identifying its underlying factors, however, are recognizably difficult to do. Grounded on the use of cognitive mapping techniques, this paper proposes a knowledge-based framework for the identification of the key determinants of customer loyalty, and the relationships among them. A step-by-step guide to the development of such a framework is presented, and illustrated through a practical application in the banking context. The resulting findings are supportive of the applicability of such methods for understanding customer loyalty, and the improvement of long-term relationships with customers. They are furthermore indicative of new ways in which knowledge can be incorporated into management activities to improve service outcomes. Some managerial implications of ou...

Perceived key determinants of payment instrument usage: a fuzzy cognitive mapping-based approach

The recent economic climate has had direct repercussions on people’s daily lives. This has occurred not only in how they use payment instruments, but is also evinced in new concerns adjacent to technological advances, people’s safety and the credibility of financial institutions. In this regard, the banking sector has had a crucial role in countries’ economic development, making it increasingly important to understand how the banking system operates and what payment instruments are available to users. Relying on specialized literature and the application of fuzzy cognitive mapping, this study aims to understand the cause-and-effect relationships between customers’ preference factors in using payment instruments. The results show that usability aspects and safety concerns constitute the factors which users pay more attention to. Strengths and limitations of our proposal are also discussed.