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The object of this paper is to help to understand what it is all about in question when talking about personalization.

A conceptual framework of personalization is presented, based on the literature.

Marketers are looking increasingly at personalization to help them improve the performance of their efforts. However, personalization seems to be hard to apply. Some of these problems are caused by the fact that personalization means something different to each business and to the different actors in the value chain. This lack of agreement regarding the meaning of personalization limits successful communication between the different actors who produce or buy services and products that are connection with personalized marketing. This hinders co‐operation between service providers and marketers who are willing to apply personalization.

It is hoped that the framework is useful when discussing and developing the idea of personalization further.

The purpose of this paper is to explore the importance of personalisation in the relationship between the architectural design of homes and inhabitants’ psychological well-being.

This interdisciplinary mixed-method study first investigates the existence of a link between personalisation and users’ association with home through a quantitative study (n = 101) and then explores the nature of this relationship through qualitative interviews (n = 13) in a sequential explanatory approach.

The main findings of the study highlight the significance of personalisation in relation to the way people perceive home. A direct link was established between participants’ involvement in the transformation of the home and their satisfaction with the residence, as well as satisfaction with life in general. Further thematic analysis of the qualitative study revealed further conceptualisations of personalisation, which together form an umbrella concept called transformability.

The findings underscore the need for embedding flexibility as an architectural concept in the design of residential buildings for improving the well-being of occupants.

The design of homes has a great impact on inhabitants’ psychological well-being. This is becoming of greater importance in light of the global COVID-19 pandemic that has led to an increase in the amount of time spent in homes. This research contributes to this debate by proposing concepts for a deeper understanding of architectural influences on the psychology of the home.

This study aims to examine the influence of reward personalization on financing outcomes in the Industry 5.0 era, where reward-based crowdfunding meets the personalized needs of individuals.

The study utilizes a corpus of 218,822 crowdfunding projects and 1,276,786 reward options on Kickstarter to investigate the effect of reward personalization on investors’ willingness to participate in crowdfunding. The research draws on expectancy theory and employs quantitative and qualitative approaches to measure reward personalization. Quantitatively, the number of reward options is calculated by frequency; whereas text-mining techniques are implemented qualitatively to extract novelty, which serves as a proxy for innovation.

Findings indicate that reward personalization has an inverted U-shaped effect on investors’ willingness to participate, with investors in life-related projects having a stronger need for reward personalization than those interested in art-related projects. The pledge goal and reward text readability have an inverted U-shaped moderating effect on reward personalization from the perspective of reward expectations and reward instrumentality.

This study refines the application of expectancy theory to online financing, providing theoretical insight and practical guidance for crowdfunding platforms and financiers seeking to promote sustainable development through personalized innovation.

As educators seek ways to enhance student motivation and improve achievement, promising advances are being made in adaptive approaches to instruction. Learning technologies are emerging that promote a high level of personalization of the learning experience. One type of personalization is context personalization, in which instruction is presented in the context of learners’ individual interests in areas like sports, music, and video games. Personalized contexts may elicit situational interest, which can in turn spur motivational and metacognitive states like positive affect and focused attention. Personalized contexts may also allow for concepts to become grounded in prior knowledge by fostering connections to everyday activity. In this Chapter, we discuss the theoretical, design, and implementation issues to consider when creating interventions that utilize context personalization to enhance motivation.

First, we provide an overview of context personalization as an instructional principle and outline the emerging evidence that personalization can enhance motivation and improve achievement. We then discuss the theory hypothesized to account for the effectiveness of context personalization and discuss the approaches to personalization interventions. We close by discussing some of the practical issues to consider when bridging the design and implementation of personalization interventions. Throughout the paper, we anchor our discussion to our own research which focuses on the use of context personalization in middle and high school mathematics.

The theoretical mechanisms through which context personalization enhances learning may include (1) eliciting positive affective reactions to the instruction, (2) fostering feelings of value for the instructional content through connections to valued personal interests, or (3) drawing upon prior funds of knowledge of the topic. We provide hypotheses for the relatedness of context personalization to triggering and maintaining situational interest, and explore potential drawbacks of personalization, considering research on seductive details, desirable difficulties, and authenticity of connections to prior knowledge. We further examine four approaches to personalized learning – “fill-in-the-blank” personalization, matching instruction to individual topic interests, group-level personalization, and utility-value interventions. These approaches vary in terms of the depth of the personalization – whether simple, shallow connections are made to interest topics, or deep, meaningful connections are made to learners’ actual experiences. The consideration of depth also interacts with grain size – whether content is personalized based on the broader interests of a group, or the individual experiences of a particular learner. And finally, personalization interventions can have different levels of ownership – an instructor can generate the personalized connections, the connections can be made by the curriculum designers, or learners can take an active role in personalizing their own learning. Finally, we discuss the practical implementation issues when bringing context personalization interventions into K-12 classrooms. Personalization can be logistically difficult to implement, given that learners hold a diverse array of interests, and may experience each of those interests differently. In addition, particular types of instructional content may show greater sensitivity when personalization is implemented, and personalization may be most helpful for learners with certain background characteristics.

Realizing the promise of personalized learning is an unsolved problem in education whose solution becomes ever more critical as we confront a new digital age. Context personalization has the potential to bring together several well-established strands of research on improving student learning – research on the development of interest, funds of knowledge, and utility value – into one powerful intervention.

This chapter reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy and review the methodological approaches available for personalization. We discuss scalability, generalizability, and counterfactual validity issues and briefly touch upon advanced methods for online/interactive/dynamic settings. We then summarize the three evaluation approaches for static policies – the Direct method, the Inverse Propensity Score (IPS) estimator, and the Doubly Robust (DR) method. Next, we present a summary of the evaluation approaches for special cases such as continuous actions and dynamic settings. We then summarize the findings on the returns to personalization across various domains, including content recommendation, advertising, and promotions. Next, we discuss the work on the intersection between personalization and welfare. We focus on four of these welfare notions that have been studied in the literature: (1) search costs, (2) privacy, (3) fairness, and (4) polarization. We conclude with a discussion of the remaining challenges and some directions for future research.

Scholars and practitioners alike wish to understand what makes workplace conflict beneficial or injurious to, for example, performance and satisfaction. The authors focus on parties’ personal experience of the conflict, which is complementary to studying conflict issues (i.e. task- or relationship-related conflict). Although many authors discuss the personal experience of conflict, which the authors will refer to as conflict personalization, different definitions are used, leading to conceptual vagueness. Therefore, the purpose of this paper is to develop an integrative definition of the concept of conflict personalization.

The authors conducted a systematic literature review to collect definitions and conceptualizations from 41 publications. The subsequent thematic analysis revealed four building blocks that were used to develop an integrative definition of conflict personalization.

The authors developed the following definition: Conflict personalization is the negative affective as well as cognitive reaction to the self being threatened and/or in danger as a result of a social interaction about perceived incompatibilities.

The integrative definition of this study enables the development of a measurement instrument to assess personalization during workplace conflict, paving the way for developing effective research-based interventions.

Conceptual vagueness hampers theoretical development, empirical research and the development of effective interventions. Although the importance of conflict personalization is mentioned within the field of workplace conflict, it has not been empirically studied yet. This paper can serve as the basis for future research in which conflict issue and personal experience are separated.

Customer service conversations are becoming increasingly digital and automated, leaving service encounters impersonal. The purpose of this paper is to identify how customer service agents and conversational artificial intelligence (AI) applications can provide a personal touch and improve the customer experience in customer service. The authors offer a conceptual framework delineating how text-based customer service communication should be designed to increase relational personalization.

This paper presents a systematic literature review on conversation styles of conversational AI and integrates the extant research to inform the development of the proposed conceptual framework. Using social information processing theory as a theoretical lens, the authors extend the concept of relational personalization for text-based customer service communication.

The conceptual framework identifies conversation styles, whose degree of expression needs to be personalized to provide a personal touch and improve the customer experience in service. The personalization of these conversation styles depends on available psychological and individual customer knowledge, contextual factors such as the interaction and service type, as well as the freedom of communication the conversational AI or customer service agent has.

The article is the first to conduct a systematic literature review on conversation styles of conversational AI in customer service and to conceptualize critical elements of text-based customer service communication required to provide a personal touch with conversational AI. Furthermore, the authors provide managerial implications to advance customer service conversations with three types of conversational AI applications used in collaboration with customer service agents, namely conversational analytics, conversational coaching and chatbots.

This paper aims to explore the realm of literature about personalization of digital library services. This paper focuses on users’ unique needs and will identify different types of personalized services. Therefore, this study has identified different types of services personalization in the context of digital academic libraries.

In this research, the systematic review method has been used to obtain the relevant indicators of different types of personalization in the context of libraries. To explain basic indicators, a Delphi method has been used. The Delphi panel’s members consisted of 15 experts (faculty members, researchers, professional users and software designers). A purposeful sampling and the Delphi fulfillment process were performed in three rounds. After collecting data, descriptive statistics (mean and standard deviation), inferential statistics (binomial distribution test) and the Kendall coordination coefficient were used to determine the consensus rate among experts.

A total of 103 indicators were extracted for different types of personalization through a systematic literature review. Of these, 90 indicators were considered significant in the experts’ view. Generally, content personalization, interactive personalization, collaborative personalization and information retrieval personalization are the main components of personalization types, each of which has its own indicators.

This study has dealt with the issue of what is personalized in the context of digital academic library. The findings should be helpful and effective in the development of a holistic view on personalization of services in digital libraries.