Customer Relationship Management and the Social and Semantic Web

2012 ◽  
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
The Social

Customer Relationship Management in Social and Semantic Web Environments

2010 ◽  
Vol 1 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
Juan Miguel Gómez-Berbís ◽  
Fernando Paniagua Martín
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Paradigm Shift ◽  
Dynamic Environment ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Web 3.0 ◽  
Web Technologies ◽  
The Social

The growing influence of the Internet in current 21st-century everyday life has implied a paradigm shift in terms of relationships between customers and companies. New interaction means in the Web 1.0 have undergone a dramatic change in quantity and quality with the advent of the so-called Web 2.0, the Social Web. The upcoming Web 3.0, the Semantic Web will also impact tremendously in how companies understand Customer Relationship Management (CRM). In this dynamic environment, the present work presents a combination of both Social and Semantic Web Technologies and their application in the particular field of CRM. Tool and technology analysis both prove the challenging opportunities for these cutting-edge innovation trends in the CRM domain.

Customer Relationship Management in Social and Semantic Web Environments

2012 ◽  
pp. 83-92
Author(s):  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
Juan Miguel Gómez-Berbís ◽  
Fernando Paniagua Martín
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Dynamic Environment ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Web 3.0 ◽  
Web Technologies ◽  
The Social ◽  
The Web

The growing influence of the Internet in current 21st-century everyday life has implied a paradigm shift in terms of relationships between customers and companies. New interaction means in the Web 1.0 have undergone a dramatic change in quantity and quality with the advent of the so-called Web 2.0, the Social Web. The upcoming Web 3.0, the Semantic Web will also impact tremendously in how companies understand Customer Relationship Management (CRM). In this dynamic environment, the present work presents a combination of both Social and Semantic Web Technologies and their application in the particular field of CRM. Tool and technology analysis both prove the challenging opportunities for these cutting-edge innovation trends in the CRM domain.

Customer Relationship Management as an Imperative for Academic Libraries

2015 ◽  
pp. 44-77
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Academic Libraries ◽  
Linked Data ◽  
Trust Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Customer Group

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

Customer Relationship Management as an Imperative for Academic Libraries

2016 ◽  
pp. 1641-1674
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Academic Libraries ◽  
Linked Data ◽  
Trust Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Customer Group

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

Customer Relationship Management as an Imperative for Academic Libraries

2016 ◽  
pp. 395-428
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Academic Libraries ◽  
Linked Data ◽  
Trust Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Customer Group

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

scholarly journals Investigating the effect of the social customer relationship management (CRM) on customers and financial performance

2021 ◽  
Vol 10 (1) ◽  
pp. 235-245
Author(s):  
Ali B Abduljabar Al mashahedi ◽  
Jing Zhang ◽  
Sinan Harjan
Keyword(s):  
Financial Performance ◽  
Customer Relationship Management ◽  
Structural Equation ◽  
High Performance ◽  
Relationship Management ◽  
Research Data ◽  
Customer Relationship ◽  
Equation Modeling ◽  
Innovation Activities ◽  
The Social

This research aims to investigate the effect of the social customer relationship management (CRM) process on achieving superior levels of costumers and financial performance. The object of this research is the Iraqi firms at the Iraqi environment market, while the subject is more than 200 respondents. Six variables from the research data were gathered through an instrument model invalid form that structured to be measured through reliable questionnaires. Statistical Analysis of the research data used partial least squares structural equation modeling with the significance in accordance with the output of SPSS 22.0. The findings indicate that the social CRM technologies of the firms improve the innovation activities on Both (services and products). This has a positive effect on the ability to achieve high performance through building customer-linking capabilities by adopting innovations, resulting in higher levels of efficiency. In exchange, higher levels of consumer contribution lead to having positive levels of customer and financial performance.

Formal modeling and verification of a service composition approach in the social customer relationship management system

2019 ◽  
Vol 32 (6) ◽  
pp. 1591-1607 ◽  
Author(s):  
Alireza Souri ◽  
Amir Masoud Rahmani ◽  
Nima Jafari Navimipour ◽  
Reza Rezaei
Keyword(s):  
Model Checking ◽  
Customer Relationship Management ◽  
Service Composition ◽  
Relationship Management ◽  
Customer Relationship ◽  
Content Type ◽  
Behavioral Interactions ◽  
Verification Method ◽  
Social Crm ◽  
The Social

Purpose The purpose of this paper is to present a formal verification method to prove the correctness of social customer relationship management (CRM)-based service composition approach. The correctness of the proposed approach is analyzed to evaluate the customer behavioral interactions for discovering, selecting and composing social CRM-based services. In addition, a Kripke structure-based verification method is presented for verifying the behavioral models of the proposed approach. Design/methodology/approach Evaluating the customer behavioral interactions using the social CRM-based service composition approach is an important issue. In addition, formal verification has an important role in assessing the social CRM-based service composition. However, model checking can be efficient as a verification method to evaluate the functional properties of the social CRM-based service composition approach. Findings The results of model checking satisfied the logical problems in the proposed behavior model analysis. In the statistical testing, the proposed URM mechanism supported the four knowledge creation process conditions. It was also shown that the percentage of state reachability in the URM with KCP conditions is higher than the URM mechanism without supporting KCP conditions. Originality/value The comparison of time and memory consumption of the model checking method shows that the social CRM-based service composition approach covers knowledge process features, which makes it an efficient method.

scholarly journals The role of social customer relations management in achieving outstanding performance / a survey of the views of a sample of managers and executives in a number of small service projects in the city of Duhok

2021 ◽  
Vol 10 (2) ◽  
pp. 240-266
Author(s):  
HILOVAN HUSNI OTHMAN ◽  
Ferhad Abbas Abdulaziz
Keyword(s):  
Customer Relationship Management ◽  
Relationship Management ◽  
Main Tool ◽  
Research Problem ◽  
Customer Relationship ◽  
Aggregate Level ◽  
Important Indicator ◽  
The Social ◽  
Independent Variable

This aims of research is to identify the role of social customer relationship management in achieving outstanding performance.  The research problem represents that the idea of social customer relationship management and the lack of understanding of its significance in achieving outstanding results are not completely perceived. Researchers have relied on the social customer relationship management as an independent variable and outstanding performance as a dependent variable. For research, a number of hypotheses have been formulated, the most important of which are: -1- There is direct correlations between the social customer relationship management as the independent variable level and the distinct performance as dependent variable at aggregate level, and a number of partial hypotheses are subdivide at the two dimensional level.2- There is a significant impact of the social customer relationship management as the independent variable on the distinct performance as dependent variable at aggregate level. The research depends on the questionnaire as a main tool for collecting field data, and using a number of statistical methods in analyzing the data. The most substantial results that research accomplished is there   understanding of the sample examined to both the concept of social customer relationship management and outstanding performance, however there were lack awareness of concepts, and it follows from statistical analysis that there is a strong correlation and impact between social customer relationship management and outstanding performance. In the light of these conclusions, the study has made numbers of suggestion that serve the field sought from, perhaps the most important embodied the need to increase the concentrate by the departments of small projects on the philosophy of social customer relationship management, because of its emergence as a variable affecting all the research hypotheses, and this is an important indicator in the awareness of senior  

I Earn It, But They Just Get It: Loyalty Program Customer Reactions to Unearned Preferential Treatment in the Social Servicescape

2019 ◽  
Vol 61 (1) ◽  
pp. 84-97 ◽  
Author(s):  
Youngsun Sean Kim ◽  
Melissa A. Baker
Keyword(s):  
Customer Relationship Management ◽  
Social Presence ◽  
Management Strategies ◽  
Relationship Management ◽  
Customer Relationship ◽  
Preferential Treatment ◽  
Loyalty Program ◽  
Perceived Trust ◽  
The Social ◽  
Customer Delight

Hospitality and tourism firms use two different strategies in customer relationship management: rewarding loyalty program customers with earned rewards (earned preferential treatment) and delighting the nonprogram customers with surprise rewards (unearned preferential treatment). However, research overlooks the key impact of how these two customer relationship management strategies may negatively affect the observing loyalty program customers. To address these gaps, Study 1 finds that providing a nonprogram customer with a high-value unearned treatment significantly decreases perceptions of distributive justice, status, and loyalty among the observing loyalty program customers. No significant interaction effects of a firm’s explanation were found, suggesting that the practice of unearned preferential treatment cannot be justified simply by presenting a reason for the practice. Study 2 finds that compensating the affected program customers with tangible compensation is the only significant factor that enhances the observing loyalty program customers’ perceived trust, suggesting rebuilding customers’ trust as the key element in recovery. This research is grounded in social comparison and justice theory and builds upon the loyalty, social servicescape, and customer delight literature to explicitly examine the reward comparison stemming from the social presence of other customers.

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