Study on customer relationship management activities in Taiwan tourism factories

Chung, Yi‐Chan; Chen, Szu Ju

doi:10.1080/14783363.2015.1019341

Cited by 4 publications

(1 citation statement)

References 34 publications

(53 reference statements)

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“…In the 1990s, in the business domain the concept of customer relationship management (CRM) gradually emerged, which prevailed from its very first years, gaining prominence as a legitimate area of scholarly inquiry and stimulating the interest of the global business and research community (Soltani and Navimipour, 2016). CRM is the operational model by which enterprises understand and influence customer behavior via interaction in order to obtain new customers, keep old customers and increase customer loyalty and thereby improve profits (Chung and Chen, 2016). Faced with increasing complexity and competition, today’s firms need to develop innovative activities to understand customers’ needs and improve customer satisfaction and retention (Razieh et al , 2012).…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of different customer segmentation approaches based on RFM and demographics analysis

2016

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Purpose The purpose of this paper is to determine the best approach to customer segmentation and to extrapolate associated rules for this based on recency, frequency and monetary (RFM) considerations as well as demographic factors. In this study, the impacts of RFM and demographic attributes have been challenged in order to enrich factors that lend comprehension to customer segmentation. Different types of scenario were designed, performed and evaluated meticulously under uniform test conditions. The data for this study were extracted from the database of a global pizza restaurant chain in Turkey. This paper summarizes the findings of the study and also provides evidence of its empirical implications to improve the performance of customer segmentation as well as achieving extracted rule perfection via effective model factors and variations. Accordingly, marketing and service processes will work more effectively and efficiently for customers and society. The implication of this study is that it explains a clear concept for interaction between producers and consumers. Design/methodology/approach Customer relationship management, which aims to manage record and evaluate customer interactions, is generally regarded as a vital tool for companies that wish to be successful in the rapidly changing global market. The prediction of customer behaviors is a strategically important and difficult issue because of the high variance and wide range of customer orders and preferences. So to have an effective tool for extracting rules based on customer purchasing behavior, considering tangible and intangible criteria is highly important. To overcome the challenges imposed by the multifaceted nature of this problem, the authors utilized artificial intelligence methods, including k-means clustering, Apriori association rule mining (ARM) and neural networks. The main idea was that customer clusters are better enhanced when segmentation processes are based on RFM analysis accompanied by demographic data. Weighted RFM (WRFM) and unweighted RFM values/scores were applied with and without demographic factors and utilized to compose different types and numbers of clusters. The Apriori algorithm was used to extract rules of association. The performance analyses of scenarios have been conducted based on these extracted rules. The number of rules, elapsed time and prediction accuracy were used to evaluate the different scenarios. The results of evaluations were compared with the outputs of another available technique. Findings The results showed that having an appropriate segmentation approach is vital if there are to be strong association rules. Also, it has been determined from the results that the weights of RFM attributes affect rule association performance positively. Moreover, to capture more accurate customer segments, a combination of RFM and demographic attributes is recommended for clustering. The results’ analyses indicate the undeniable importance of demographic data merged with WRFM. Above all, this challenge introduced the...

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Section: Introductionmentioning

confidence: 99%

Performance evaluation of different customer segmentation approaches based on RFM and demographics analysis

2016

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Customer relationship management and its impact on entrepreneurial marketing: a literature review

et al. 2022

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Entrepreneurship is one of the business forces with the greatest power to transform today's society, due to its ability to discover and take advantage of new opportunities to satisfy customer new and changing needs and expectations. Customer relationship management (CRM) has proved to be both a highly influential business management strategy and a powerful business management technology solution, with a particularly relevant impact in the area of entrepreneurship. CRM has helped drive growth and future expectations and has had excellent results in terms of return on investment wherever it has been implemented. An exhaustive review of previously published findings in a specific subject area can uncover new lines of research. This paper uses semi-systematic review to the study of the reality of the link between CRM and entrepreneurial marketing in business. This approach is used to comprehensively describe the state of the art of the impact that CRM can have in the modern business environment, through the empowerment of entrepreneurial marketing. In a structured manner, the present paper reviews the 86 most relevant studies of how CRM affects entrepreneurial marketing policy development through its alignment with relationship marketing and customer-centric business models. The growing use of CRM in companies is one of the pillars of technological and social change in entrepreneurship, being a clear example of how big data can benefit society. The study focuses on the period from 2015 to 2019.

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Concept of Integration between Social Media and Customer Relationship Management: Impact on business performance and growth

Anwar,

Mohamed Shuhidan,

Masrek

2023

E-BPJ

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Companies that successfully integrate Social Media (SocMed) as a tool for their Customer Relationship Management (CRM) will create a synergy that will further enhance business performance and growth. Unfortunately, not many SMEs realize this potential and because of that Social Media adoption for CRM and other purposes among SMEs is still very low. This study aims to develop a research framework of Integration between Social Media utilizations and Customer Relationship Management practices on business performance and growth. The findings will help to formulate strategies on how to further enhance the use of SocMed and CRM to improve business performance and growth.

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Study on customer relationship management activities in Taiwan tourism factories

Cited by 4 publications

References 34 publications

Performance evaluation of different customer segmentation approaches based on RFM and demographics analysis

Performance evaluation of different customer segmentation approaches based on RFM and demographics analysis

Customer relationship management and its impact on entrepreneurial marketing: a literature review

Concept of Integration between Social Media and Customer Relationship Management: Impact on business performance and growth

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