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Article
Publication date: 21 May 2024

Shuaiqi Roger Shen, Jaydeep Balakrishnan and Chun Hung Cheng

The home page design of a digital news website is a key factor in determining its attractiveness to readers. This study aims to propose an approach to manage the frequent…

Abstract

Purpose

The home page design of a digital news website is a key factor in determining its attractiveness to readers. This study aims to propose an approach to manage the frequent adjustment of the dynamic layout of the news content on the website home page in a real-time environment to increase its attractiveness to readers.

Design/methodology/approach

This paper shows that this news website layout design problem can be modeled as an optimization problem based on the information of news contents that change within a multiple-period planning horizon similar to the dynamic facility layout problem. A hybrid genetic algorithm-based approach integrated with local search heuristic methods is also proposed to improve the solution.

Findings

This paper finds that the DPLP model is effective in modeling the changing layout of a digital news website. The problem can solved in a timely manner using the proposed hybrid genetic algorithm.

Research limitations/implications

This paper was based on hypothetical data and on the assumption of equal section size. Actual data would help fine-tune the application of the dynamic facility layout model. As well the algorithm could be enhanced for unequal size sections.

Practical implications

The model should help online newspapers apply sophisticated algorithms to optimize the layout of news websites dynamically in a timely manner.

Social implications

News websites are increasingly the desired medium to consume news. So it has an important role in educating society. Thus optimizing and improving the process will help in this regard.

Originality/value

To the best of the authors’ knowledge, this paper is the first one to apply the DPLP model to the digital newspaper website dynamic design problem.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

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