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The relationship marketing literature largely overlooks the most common type of loyal consumer, one who feels no personal attachment to a firm (Guo et al., Journal of the Academy of Marketing Science,45(3), 357–376, 2017). To explain why so many consumers engage in this pragmatic form of loyalty, we bridge the loyalty and relationship marketing literature to reconsider the conceptualization and measurement of loyalty propensity. In particular, the present research provides evidence of loyalty propensity as a multi-dimensional relational schema that draws from consumers' self-identity as a moral actor and less altruistic traits (e.g., deal proneness). As per these theoretical foundations, we develop a two-dimensional scale for loyalty propensity and assess it across four studies. The results indicate that loyalty propensity predicts loyalty outcomes (e.g., loyalty and economic exchange), whereas relational constructs (i.e., preference for closeness) predict relational outcomes (e.g., attachment and social exchange). A field study shows that loyalty propensity strongly predicts consumer responsiveness to a firm's loyalty investments (e.g., sales agents' customer orientation). Overall, the present research provides a way to expand the view of consumers as either relational or transactional. [ABSTRACT FROM AUTHOR]

Model transformation (MT) contributes a major role in the model-driven engineering (MDE), which are used to transfer the models among various languages to refactor and simulate the models or to obtain the useful codes from the models. Thus, the need for MT in MDE is very important, but the practical methods are not suitable for the detection of errors in transformations. This paper proposes an advanced algorithm, called fractional whale optimization integrated adaptive dragonfly (F-WOADF) algorithm to perform the MT from the class diagram (CLD) to relational schema (RS) model. The proposed algorithm modifies the adaptive dragonfly (ADF) algorithm with the concept of whale optimization algorithm (WOA) using the fractional theory. The UML CLD is transformed into the RS model using the optimal blocks that are selected with the use of the proposed algorithm. The performance of the F-WOADF method is evaluated using automatic correctness (AC), and fitness measure. The proposed method produces the maximum AC of 0.8583 and the maximum fitness measure of 0.8984 that indicates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Serving as mental models, psychological contracts guide consumers' service interactions with their service providers. This study incorporates a psychological contract perspective into the relationship marketing literature, exploring service customers' beliefs about the terms and conditions of the resource exchange process and the types of relationships they form with service providers. It provides new insights that explain why and how some customers respond favorably to a company's relationship overtures and investments while others do not. A latent class analysis on a sample of 700 consumers across three different service industries reveals that consumers form four distinct types of psychological contracts: relational, standard, transitional, and captive. To further validate the differences between the contract types, open-ended responses from the respondents were sorted by each class. The distinctive themes that emerged provide a richer understanding of the characteristics of each class beyond those inferred from the quantitative results. Each contract type is also profiled against its underlying level of trust, satisfaction, and commitment to understand the relationship between the contract types and these traditional relationship marketing variables. Marketers can differentiate their relationship marketing strategies and allocate their resource investments more effectively by segmenting consumers according to their psychological contract type. [ABSTRACT FROM AUTHOR]

Storing XML documents in relational databases has drawn much attention in recent years because it can leverage existing investments in relational database technologies. Different algorithms have been proposed to map XML DTD/Schema to relational schema in order to store XML data in relational databases. However, most work defines mapping rules based on heuristics without considering application characteristics, hence fails to produce efficient relational schema for various applications. In this paper, we propose a workload-aware approach to generate relational schema from XML data and user specified workload. Our approach adopts the genetic algorithm to find optimal mappings. An elegant encoding method and related operations are proposed to manipulate mappings using bit strings. Various techniques for optimization can be applied to the XML to relational mapping problem based on this representation. We implemented the proposed algorithm and our experiment results showed that our algorithm was more robust and produced better mappings than existing work. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new relational schema (R-schema) to XML schema translation algorithm, VQT, which analyzes the value cardinality and user query patterns and extracts the implicit referential integrities by using the cardinality property of foreign key constraints between columns and the equi-join characteristic in user queries. The VQT algorithm can apply the extracted implied referential integrity relation information to the R-schema and create an XML schema as the final result. Therefore, the VQT algorithm prevents the R-schema from being incorrectly converted into the XML schema, and it richly and powerfully represents all the information in the R-schema by creating an XML schema as the translation result on behalf of the XML DTD. [ABSTRACT FROM AUTHOR]