Evaluating the Impact of Customer Relationship Management (CRM) Strategies on Customer Retention (A Study of Fast Food Chains in Pakistan)

Anees, Rao Tahir; Nordin, Nordiana Ahmad; Anjum, Temoor; Cavaliere, Luigi Pio Leonardo; Heidler, Petra

doi:10.5296/bms.v11i2.17934

Cited by 7 publications

(6 citation statements)

References 28 publications

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“…Composite reliability (CR) scores have been performed in this evaluation. The findings show that all constructs' CR scores exceeded the 0.7 threshold criterion, demonstrating high internal consistency of the scales used in this study (Anees, Nordin, Anjum, Cavaliere, & Heidler, 2020;Anees, Raju, & Anjum, 2020).…”

Section: Data Analysis and Resultssupporting

confidence: 51%

Untitled

2022

IJO-BS

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Employee engagement can be boosted by good HR practices. Complementary action can be gained by an organisation that provides training, compensation, career development, and equal and fair policies that meet the needs of its employees. Employees become more engaged. To address consumer needs, many service firms rely on information sharing techniques to enhance staff creativity. This study was carried out in Yemen's banking sector to see if an information sharing system that recorded workers' creative work improved the quality of their work, workplace engagement, and career development. This study underpinning theory, social exchange theory was used. Smart-PLS was used to evaluate the hypothesis using structural equation modelling using partial least squares. A five-point Likert scale was employed in the questionnaire to quantify all variables for data collection, and the structured questionnaire was utilised to measure the variables.

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Section: Data Analysis and Resultssupporting

confidence: 51%

Untitled

2022

IJO-BS

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“…PLS-SEM is a two-step process that involves evaluation measurement and structural models [81], [82]. The model of measurement is part of the entire model in which latent constructs are prescribed.…”

Section: Resultsmentioning

confidence: 99%

Brain Drain in Higher Education. The Impact of Job Stress and Workload on Turnover Intention and the Mediating Role of Job Satisfaction at Universities

Anees

Heidler

Cavaliere

et al. 2021

EJBMR

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This study seeks to determine the impact of job stress and workload on turnover intention along with the mediation role of job satisfaction. A total of 140 academics and management personnel participated in this study’s survey. A partial least square structural equation modeling was used for data analysis. The results show that job stress and workload have a positive effect on turnover intention, while job satisfaction mediates the relationship between job stress, workload, and turnover intention. Future research could adapt and adopt the herein used methodology and research topic to other countries or in other industries.

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“…This is particularly important given that retaining existing customers is significantly more valuable than acquiring new customers, as more resources are needed for new customer acquisition. It follows, therefore, that customer retention is one of the key priorities of the CRM strategy [32]. The ability to harness ML to significantly improve customer churn rates is of particular importance.…”

Section: Customer Churn Prediction Model For Telecom Industrymentioning

confidence: 99%

Prediction of Customer Churn Behavior in the Telecommunication Industry Using Machine Learning Models

Chang,

Hall,

et al. 2024

Algorithms

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Customer churn is a significant concern, and the telecommunications industry has the largest annual churn rate of any major industry at over 30%. This study examines the use of ensemble learning models to analyze and forecast customer churn in the telecommunications business. Accurate churn forecasting is essential for successful client retention initiatives to combat regular customer churn. We used innovative and improved machine learning methods, including Decision Trees, Boosted Trees, and Random Forests, to enhance model interpretability and prediction accuracy. The models were trained and evaluated systematically by using a large dataset. The Random Forest model performed best, with 91.66% predictive accuracy, 82.2% precision, and 81.8% recall. Our results highlight how well the model can identify possible churners with the help of explainable AI (XAI) techniques, allowing for focused and timely intervention strategies. To improve the transparency of the decisions made by the classifier, this study also employs explainable artificial intelligence methods such as LIME and SHAP to illustrate the results of the customer churn prediction model. Our results demonstrate how crucial it is for customer relationship managers to implement strong analytical tools to reduce attrition and promote long-term economic viability in fiercely competitive marketplaces. This study indicates that ensemble learning models have strategic implications for improving consumer loyalty and organizational profitability in addition to confirming their performance.

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Evaluating the Impact of Customer Relationship Management (CRM) Strategies on Customer Retention (A Study of Fast Food Chains in Pakistan)

Cited by 7 publications

References 28 publications

Untitled

Untitled

Brain Drain in Higher Education. The Impact of Job Stress and Workload on Turnover Intention and the Mediating Role of Job Satisfaction at Universities

Prediction of Customer Churn Behavior in the Telecommunication Industry Using Machine Learning Models

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