Implementation effects in the relationship between CRM and its performance

Pozza, Ilaria Dalla; Goetz, Oliver; Sahut, Jean Michel

doi:10.1016/j.jbusres.2018.02.004

Cited by 60 publications

(25 citation statements)

References 69 publications

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“…Similarly, successful CRM contributes to revenues positively due to cross-selling activities, increased customers penetration rates (Hennig-Thurau et al, 2002). Companies use CRM tools for various reasons such as growth stimulation for their revenues and customers or improvement in customer loyalty and acquisition (Dalla Pozza, Goetz, & Sahut, 2018). An empirical study by Li, Huang, and Song (2019) show that CRM has significant operational benefits that improve customer satisfaction and leads to higher profitability.…”

Section: Conceptualising Customer Lifetime Value (Clv)mentioning

confidence: 99%

An empirical investigation of the factors affecting customer lifetime value

Dandis

Eid

Robin

et al. 2021

IJQRM

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PurposeThe main objective of this paper is to investigate the factors affecting customer lifetime value (CLV) for Internet service providers in Jordan, namely, technical quality, functional quality, brand credibility, confidence benefits, special treatment benefits, customer satisfaction and commitment.Design/methodology/approachAn online survey was conducted involving a sample of 481 respondents. SPSS was used to analyse the data and test the proposed relationships, while SmartPLS was used to examine the robustness of our results.FindingsResults showed that confidence benefits, special treatment benefits and brand credibility had a significant and positive impact on customer satisfaction and commitment, with brand credibility appearing as the most influential factor leading to customer satisfaction and commitment, and ultimately CLV. Furthermore, research reveals an insignificant relationship between functional quality, technical quality and customer satisfaction.Practical implicationsServices' providers seeking to increase CLV need to build strong and sustainable relationships with their customers.Originality/valueThis study incorporates a set of crucial customer relationship management strategies that could be universally applied to enhance customers benefits and business performance. This is also the first study of its kind conducted in the Middle East, particularly in Jordan.

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Section: Conceptualising Customer Lifetime Value (Clv)mentioning

confidence: 99%

An empirical investigation of the factors affecting customer lifetime value

Dandis

Eid

Robin

et al. 2021

IJQRM

View full text Add to dashboard Cite

show abstract

“…Neural network was a better approach for analysing customer loyalty, satisfaction and perceived value. Dalla Pozza et al (2018) CRM implementations have equally affected customer acquisition, loyalty and growth. The success of CRM implementations depends on company objectives and the geographical dimensions.…”

Section: Classification By Country-wise (Where the Research Was Done)mentioning

confidence: 99%

Customer Relationship Management Research from 2000 to 2020: An Academic Literature Review and Classification

Meena

Sahu

2021

Vision

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This article aims to review the literature on customer relationship management (CRM) research. This review article analyses the trends in CRM research, popular research topics and tools used in studies. This study presents how CRM research developed over 21 years in terms of critical areas, type of studies, sources of papers, the origin of articles (country-wise distribution), type of data used, under-researched areas and popular researched areas. The study provides a broad classification and summarizes the last 21 years of CRM research in an organized way. For this review article, research papers were taken from January 2000 to June 2020, that is, 21 years. A total of 104 papers were selected from different journals and conferences. Findings show that most of the articles were published in the year 2009. A total of 95% of articles were published in journals, and 5% were conference papers—most of the CRM research done in the USA and the United Kingdom. Empirical papers were maximum in number, whereas case studies were least. Primary studies were more than secondary studies. In review papers, the maximum times CRM and electronic customer relationship management (E-CRM) were taken as a basis for reviewing. The further article has classifications within primary studies and review papers. It also presents the most frequently used keywords and variables in literature. The study will be useful for researchers, practitioners and academicians for further CRM research. This study also provides the classification within primary studies based on data collection tools used, sampling technique used, sampling country, industry, statistical tests and methods and software used, also it gives a brief view of keywords and variables used in a total of 104 papers. This article provides the first such review on keywords and variables, thus presenting the classification on a different basis, which none of the published research has presented.

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“…Para este autor, para alcanzarlo es imprescindible conocer tanto las fortalezas y debilidades de uno mismo, así como las del enemigo, ya que el desconocimiento de estas puede llevar a la derrota (Ahumada-Tello y Perusquia, 2016). Lo mismo ocurre en las organizaciones y en el ambiente empresarial, en donde los retos y las ventajas competitivas que se pueden lograr para alcanzar el éxito y la sostenibilidad en el mercado dependen en gran medida de obtener información significativa de los datos, diferenciando patrones y tendencias que permitan tomar decisiones más precisas (Dalla et al, 2018;Pozzaab et al, 2018).…”

Section: Inteligencia De Negocios Conceptosunclassified

Mejora de la toma de decisiones en ciclo de ventas del subsistema comercial de servicios en una empresa de IT

2020

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El alto volumen de datos, el tiempo de procesamiento y la visualización de información, son problemas que hoy en día debe enfrentar las organizaciones en el sector de tecnología, en particular el subsistema comercial. En esta investigación se desarrolló un modelo para la toma de decisiones basado en la interacción de los criterios y las etapas del ciclo de ventas. Se usó una herramienta especializada en inteligencia de negocios que facilitó el manejo de grandes volúmenes de datos, su procesamiento y la visualización de la información. Dentro de los resultados obtenidos se encontró una significativa reducción en el tiempo de obtención de la información, pasando de horas a minutos.

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Implementation effects in the relationship between CRM and its performance

Cited by 60 publications

References 69 publications

An empirical investigation of the factors affecting customer lifetime value

An empirical investigation of the factors affecting customer lifetime value

Customer Relationship Management Research from 2000 to 2020: An Academic Literature Review and Classification

Mejora de la toma de decisiones en ciclo de ventas del subsistema comercial de servicios en una empresa de IT

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