Rater Model: An Assessment Among Health Insurance Patients

Kp, Krishna Priya; Bhoomadevi, A.

doi:10.34218/ijm.11.12.2020.231

Cited by 2 publications

(2 citation statements)

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“…"Lead" pertains to an intentional or unintentional recorded indication of interest in a company's goods or services, whether from a new potential or an existing customer (Monat, 2011;Jabbouri, 2023). Lead is generated when a potential contact satisfies the company-predetermined lead criterion, usually forming interest documentation (Espadinha-Cruz et al, 2021); transformed to cold lead once minimal lead information is collected (Monat, 2011;Priya V, L. 2020). For a lead to be classified as a "marketing qualified lead" (MQL) or "hot lead," it must undergo a lead funnel conversion process: lead generation, lead nurturing, and lead qualification (Espadinha-Cruz et al, 2021).…”

Section: Conversion Targetingmentioning

confidence: 99%

Enhancing Conversions and Lead Scoring in Online Professional Education

Yim,

Khaw,

Lim

et al. 2024

IJOMFA

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This study seeks to enhance lead conversion for online professional education providers by using supervised machine learning algorithms for lead conversion targeting and lead scoring, including Logistic Regression, K-Nearest Neighbors, Support Vector Machines, Naïve Bayes, Random Forst, Bagging, Boosting, and Stacking. A lead dataset was used to train and test the machine-learning models. The Recursive Feature Elimination (RFE) is used to establish a precise lead profile. The performance of the trained lead conversion models was evaluated and compared using the 10-Folds cross-validation method based on accuracy, precision, recall, and F1-score. The results show that Stacking is the best model with an accuracy of 0.9233, precision of 0.9391, and F1-score of 0.8939. Meanwhile, the Logistic Regression-based lead scoring model demonstrated promising potential for automating lead scoring. The results of the Logistic Regression-based lead scoring model achieved an accuracy of 0.9019, recall of 0.9019, precision of 0.9015, and F1-score of 0.9014. The optimal lead scoring threshold is 0.20, which stroked the optimal trade-off balance between accuracy, sensitivity, and specificity.

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Section: Conversion Targetingmentioning

confidence: 99%

Enhancing Conversions and Lead Scoring in Online Professional Education

Yim,

Khaw,

Lim

et al. 2024

IJOMFA

View full text Add to dashboard Cite

show abstract

“…In marketing, research studies that apply design science have been published recently (e.g., Barati et al, 2021;Priya, 2020;, with publications encouraging further development. This research method is an answer to the permanent demand of marketing managers to increase the practical usefulness of marketing research (e.g.…”

Section: The Design Science Research Landscape: a Bibliographic Analysismentioning

confidence: 99%

Essays on Design Science in Management and Marketing

Micu

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This thesis explores design science in management and marketing, with a focus on how to expand the research approach from the field of management to that of marketing specifically. Design science is a pragmatic problem-solving approach that provides the researcher with the means to develop artifacts that improve future outcomes. This cross-disciplinary study scopes the allied field of management and proceeds to answer the research question: How can marketing use design science? The thesis employs a systematic literature review, a bibliometric co-citation analysis and conceptual development. Key findings: 1. Purpose of design science: A systematic literature review reveals that design science is presently used in empirical articles to support researchers to evidence the development of an artifact, often related to technology. 2. Norms: The study explores how design science is used by researchers in empirical articles, in the allied field of management. Our findings indicate that design science can be used as a research method, employing a well-known theoretical process or framework, or alternatively as a paradigm on its own. 3. Mapping: Examining the progress over time, a visualization of the various streams of research in design science is presented, by employing a bibliometric co-citation analysis. Findings suggest that the design science literature is segmented, however still concentrated around Information Systems authors. 4. Positioning: This thesis assesses the positioning of design science and suggests some options that may prove useful for marketing. First, critical realism philosophy of science aligns well with the pragmatism of design science; a second direction is seeing design science as a new paradigm, a new lens to understand the world. 5. Exemplifying: Using a conceptual paper as an example, this PhD thesis explores how marketing can use design science. As a paradigm, a new lens, design science can help advance research in problematic areas, such as conceptualizing value creation in digital platforms. Implications for future research and marketing: This PhD thesis not only contributes to the management and the emerging stream of design research in the field of marketing by exploring how this approach is presently used, but also provides guidelines, propositions, and research agendas to guide future research. Such avenues include the exploration of using design science in essential areas of marketing such as consumer research and developing marketing-led conceptual works for design science, design artifact or operationalization of kernel theory. Conclusion: In conclusion, this study underlines the importance of having a problem-solving approach to research when dealing with today’s challenges for marketing, design science being ideally positioned to increase collaborations and drive innovation. By developing design science grounding, this PhD thesis offers valuable guidance for future research seeking to find solutions to the increased demands of marketing practitioners, policymakers, and society at large.

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Rater Model: An Assessment Among Health Insurance Patients

Cited by 2 publications

References 0 publications

Enhancing Conversions and Lead Scoring in Online Professional Education

Enhancing Conversions and Lead Scoring in Online Professional Education

Essays on Design Science in Management and Marketing

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