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Even though service marketers are interested in influencing customer choice at the service provider level (i.e. the service brand level), the decision to patronize a particular service firm seldom occurs until after the customer decides to use a service provider in the first place. Ultimately, this initial “make‐or‐buy” purchase decision – the decision to use a service category – restrains customer decisions at the service provider (brand) level. To enhance our understanding of customers’ service category decisions, a double cross‐validation approach was employed to investigate the applicability of a service category choice model which we adapted from Howard’s work on consumer decision making. Our model, which was tested with two different service categories, was supported.

To propose a categorisation of customer loyalty types to further increase our understanding of the nature of loyalty.

By segmenting customers who are both loyal in attitude and behaviour to a brand, a model is proposed that differentiates between customers whose loyalty is inertial, and those whose loyalty is positive.

Four categories of loyal customer are proposed: captive, convenience‐seekers, contented and committed. The behaviours and attitudes that can be expected of customers in these different categories are discussed. It is also suggested that customers in different categories will respond in different ways to triggers to switching. Further research that investigates customers' reasons for loyalty behaviour in relation to a portfolio of brands is recommended to validate the model and to enhance understanding and predictability of customer loyalty propensities.

There is agreement that loyals are important for the future of the business, and that this category is deserving of special attention. Since loyalty is key in customer development and profitability, it is important to understand the loyalty condition in more detail, and to use this understanding to develop further the relationship with customers in the loyal category. The model proposed here subdivides loyals in Dick and Basu's categorisation based on behaviour and attitudes. Four categories of loyalty are proposed: captive, contented, convenience‐seeker and committed. Each is described and discussed, and their management implications and research agendas identified. It is noted that any one individual is likely to exhibit the characteristics of each of these categories in relation to different products, services, outlets, and their associated brands. This is a speculative model at this stage of development, which is intended to provoke further thought about the nature of loyalty.

Preface The functions of business divide into several areas and the general focus of this book is on one of the most important although least understood of these—DISTRIBUTION. The particular focus is on reviewing current practice in distribution costing and on attempting to push the frontiers back a little by suggesting some new approaches to overcome previously defined shortcomings.

The term ‘strategy’ is one of the most frequently used terms in business, and its application in marketing is particularly common. Company strategy, market strategy, marketing strategy, sales strategy, promotion strategy, distribution strategy, low pricing strategy – it would take a long time to list all of them. Although this term is so commonly in use, its definition is not as straightforward and it can be interpreted in different ways. In comparison with tactical decisions, strategy is much more significant for an organisation as it brings long-lasting consequences. It is implemented by higher level managers on a regular basis, and it is based on external, often subjective information, so decisions – especially at the time they are made – are difficult to evaluate.

Taking into consideration the fact that strategy refers to a long-term rather than a short-term period, strategic decisions serve as the basis for undertaking operational activities. However, marketing refers to the market and the competition. It is possible to claim that marketing strategy is trying to find an answer to the question to which path an organisation should follow in order to achieve its goals and objectives. If, for example, a company has a goal to generate a profit of PLN 1 million by selling 100,000 pieces of a product, the market strategy should answer at least the following two questions:

1. Who will be our target group, for example, who will purchase the 100,000 pieces of the product?

2. Why is it us from whom a potential buyer should purchase the product?

Who will be our target group, for example, who will purchase the 100,000 pieces of the product?

Why is it us from whom a potential buyer should purchase the product?

The target market will be defined if a reply to the first question is provided. The second question identifies the foundations of competitive advantage. These two issues, that is, target market and competitive advantage are the strategic marketing issues. You cannot change your target group unexpectedly while competitive advantage is the basis for changing decisions regarding prices, promotions and sales.

This chapter describes the measures of marketing activities which refer to strategic aspects and testify a company’s market position – the measures of the performance of target groups and competitive advantage. Readers’ attention should be also focused on the indices that are less popular in Poland and, therefore, may be underestimated. It seems that some of them, for example, the index of marketing resources allocation and the marketing risk index, provide a lot of valuable information and, at the same time, make it possible to show the value of marketing investments. Their wider use in the near future is only a matter of time.

The purpose of this paper is to study Bayesian dependency modelling (BDM) to validate the model of educational experiences and the student-customer orientation questionnaire (SCOQ), and to identify the categories of educatonal experience in which students expect a higher educational institutions (HEI) to be student-customer oriented.

This paper employs a cross-sectional quantitative survey study, mixed methods research, exploratory factor analysis and BDM.

The validated model of educational experiences and the SCOQ; results indicate that students expect to be treated as customers in some, but not all categories of educational experience.

The authors contribute to existing literature on two fronts: the validated model of educational experiences and the categories of educational experience in which students expect to be treated as customers.

The validated SCOQ presented in the paper may be used by other HEIs to assess the degree to which students expect a particular HEI to be customer oriented. Also, HEIs should assess students’ expectations concerning student-customer orientation before employing such an approach.

The paper presents a validated model of educational experiences and a SCOQ. Additionally, the study does not investigate whether students expect a HEI as such to be student-customer oriented (as most studies have done so far); instead, the aim is to find out whether, in which categories of educational experience and to what extent students expect a HEI to be student-customer oriented. Thus, the study explores the phenomenon of student-customer orientation at a deeper level, i.e. separately at the level of educational experiences.

Seeks to revisit the theoretical basis for the concept of loyalty through a consideration of the state of “no loyalty”, which we term “disloyalty”. This category is present in the model proposed by Dick and Basu, but is seen to be of less interest than other categories. Here we argue that a more analytical approach to this category might provide a unique insight into loyalty behaviours, but specifically might aid an understanding of the nature of the challenge associated with widening the loyal customer base. We propose the following categories of disloyals: disturbed, disenchanted, disengaged and disruptive. These four categories can be mapped onto a grid with attitudinal and behavioural dimensions. The characteristics of each of these groups are outlined. Segmentation on the basis of these different types of disloyalty could have implications for marketing strategies. The relationships between the different categories of disloyals and Dick and Basu’s categories of loyals may be important in mapping the development of customer relationships. Finally, proposals are made for further research.

The purpose of this paper is to set out to explore how cancer patients and their carers perceive and evaluate the healthcare experience in order to develop and validate a classification framework for experience quality in healthcare.

The empirical work is centred on the systematic analysis of 200 cancer patient stories published on an independent healthcare feedback web site. Using the critical incident method, the authors captured 1,351 experience quality data items. Three judges independently sorted and classified these data items.

The authors identify and describe 22 main categories and 51 sub-categories that underlie the experience quality concept in healthcare and present them in a classification framework. The framework is informed through the categorisation of direct, indirect, and independent interactions. It also suggests a relationship between experience quality and satisfaction and loyalty behaviours.

This study provides researchers with a foundation for the further development and validation of a measurement scale for experience quality in healthcare.

The framework assists managers and healthcare professionals with the definition, evaluation, and improvement of the quality of the experience of patients and their carers.

The main contributions of this study lie in: first, a comprehensive classification framework for experience quality in healthcare; second, dimensions that extend existing health service quality models; third, dimensions that contextualise the generic concept of customer experience quality to healthcare.

This paper aims to examine the impact of the customer’s previous transaction behaviour (represented by loyalty and general cross-buying) on his/her choice of specific services offered by the same financial services provider.

This study uses a set of logistic regression models by incorporating panel data from a large bank. The database consists of 2,187 randomly selected customers, and it includes features related to individual loyalty and cross-buying behaviours, as well as demographic indicators, i.e. individual measures related to each customer and each service.

From the results obtained, a large variation in customer choice behaviour with regard to the studied banking services was observed. These results reveal which customer transactional behaviours drive cross-category financial services purchases.

In academic literature, little progress has been made in the study of individual and behavioural factors that affect customer choices by service category, especially within the banking sector. By understanding customer choices, the company will be able to meet customer needs in a more appropriate way, thereby increasing its competitiveness. Hence, the results from this study have both managerial and research implications, improving the strategy formulation of financial services companies.

The purpose of this paper is an exploratory study of customers’ “lived” experiences of commercial recommendation services to better understand customer expectations for personalization with recommendation agents. Recommendation agents programmed to “learn” customer preferences and make personalized recommendations of products and services are considered a useful tool for targeting customers individually. Some leading service firms have developed proprietary recommender systems in the hope that personalized recommendations could engage customers, increase satisfaction and sharpen their competitive edge. However, personalized recommendations do not always deliver customer satisfaction. More often, they lead to dissatisfaction, annoyance or irritation.

The critical incident technique is used to analyze customer satisfactory or dissatisfactory incidents collected from online group discussion participants and bloggers to develop a classification scheme.

A classification scheme with 15 categories is developed, each illustrated with satisfactory incidents and dissatisfactory incidents, defined in terms of an underlying customer expectation, typical instances of satisfaction and dissatisfaction and, when possible, conditions under which customers are likely to have such an expectation. Three pairs of themes emerged from the classification scheme. Six tentative research propositions were introduced.

Findings from this exploratory research should be regarded as preliminary. Besides, content validity of the categories and generalizability of the findings should be subject to future research.

Research findings have implications for identifying priorities in developing algorithms and for managing personalization more strategically.

This research explores response to personalization from a customer’s perspective.

Online customer reviews could shed light into their experience, opinions, feelings, and concerns. To gain valuable knowledge about customers, it becomes increasingly important for businesses to collect, monitor, analyze, summarize, and visualize online customer reviews posted on social media platforms such as online forums. However, analyzing social media data is challenging due to the vast increase of social media data. The purpose of this paper is to present an approach of using natural language preprocessing, text mining and sentiment analysis techniques to analyze online customer reviews related to various hotels through a case study.

This paper presents a tested approach of using natural language preprocessing, text mining, and sentiment analysis techniques to analyze online textual content. The value of the proposed approach was demonstrated through a case study using online hotel reviews.

The study found that the overall review star rating correlates pretty well with the sentiment scores for both the title and the full content of the online customer review. The case study also revealed that both extremely satisfied and extremely dissatisfied hotel customers share a common interest in the five categories: food, location, rooms, service, and staff.

This study analyzed the online reviews from English-speaking hotel customers in China to understand their preferred hotel attributes, main concerns or demands. This study also provides a feasible approach and a case study as an example to help enterprises more effectively apply social media analytics in practice.