How to Choose a Laptop?

Summary

This article examines the factors and criteria that should be evaluated when selecting a laptop for various user needs. It reviews technical specifications (processor, memory, storage), screen features, battery life, ergonomics, connectivity options, and aspects of pricing and warranty service. A systematic model is presented to help link these criteria with specific user profiles and make informed decisions. Environmental and supply chain aspects are also discussed. It is shown that a thorough evaluation of multiple criteria significantly reduces the risk of purchasing a device that does not meet expectations and allows for optimal investment based on needs and budget.

Introduction

Laptops are one of the most important tools in modern daily life and work, widely used in business, studies, creativity, or entertainment. The rapid technology cycle and wide range of devices available in Lithuania complicate the selection process: a poor model can lead to lower performance, short battery life, an uncomfortable keyboard, or limited connectivity in daily work and gaming.
The main goal of this article is to provide a clear, evidence-based decision-making model that helps analytically evaluate laptop characteristics and make optimal choices. Two issues are analyzed: (1) what technical and usability criteria to evaluate, and (2) how to weigh them consistently according to individual user needs (work, study, creativity, gaming, or mobility).

Literature Review

Importance of Technical Parameters

Research emphasizes that the architecture of the processor (CPU), the number of cores, and dynamic frequency directly affect the performance of complex tasks (video editing, 3D, data analysis). It is important to consider newer mobile platforms (e.g., modern „Intel Core”/”Core Ultra”, „AMD Ryzen” mobile processors, or the „Apple M” series). The amount and type of RAM (DDR4, DDR5) determine multitasking capabilities and system smoothness.

Storage Solutions

SSDs, compared to HDDs, provide significantly faster system boot times and file processing; NVMe SSDs are generally faster than SATA SSDs, making them suitable for larger projects, photo and video materials, and data analysis tasks.

Importance of Screen and Graphics

Screen quality directly affects comfort and productivity. Higher resolutions (FHD, 2.8K, 3K, 4K), appropriate brightness, contrast, and color space coverage (sRGB – internet standard, DCI-P3 – widely used in cinema and modern screens, „Adobe RGB” – more relevant for photographers/printing) enhance the experience and reduce eye strain. Dedicated graphics (e.g., „NVIDIA GeForce” or „AMD Radeon”) are essential for gaming, 3D, and GPU-accelerated tasks, while integrated graphics are suitable for everyday tasks.

Battery Life Studies

Practice shows that actual battery life often differs from claims – it is influenced by workload, screen brightness, background processes, and network modules. It is recommended to analyze independent tests and choose models with confirmed real working durations of at least 8–10 hours, and for cases where mobility is crucial, 12–20+ hours.

Ergonomics and Design

Ergonomics includes keyboard quality, touchpad accuracy, chassis durability, cooling, weight, and dimensions. A comfortable keyboard, stable palm rest, and unobtrusive fan noise are particularly important for long working sessions.

Methodology

3.1 Selection of Decision-Making Framework

A multi-criteria decision analysis (MCDA) model has been chosen, allowing for the simultaneous evaluation of multiple, competing criteria. The Analytic Hierarchy Process (AHP) is used for weighting criteria through pairwise comparisons. The TOPSIS method is employed for ranking alternatives, assessing the distance to ideal and anti-ideal solution sets.

3.2 Data Collection and Criteria Identification

Criteria were established based on literature analysis and expert insights, encompassing technical, ergonomic, financial, and environmental indicators. Twelve main groups were identified: CPU performance, RAM amount and type, storage, screen features, battery life, weight, connectivity, price, warranty/service, software ecosystem compatibility, cooling acoustics, and environmental indicators.

3.3 Criteria Weighting

In the AHP phase, experts compared criteria pairwise (1–9 scale), calculated weights, and checked the consistency of matrices according to the consistency ratio (CR), ensuring acceptable deviation.

3.4 Alternative Evaluation

TOPSIS involves normalizing the decision matrix, applying weights, determining ideal and anti-ideal sets, and calculating distances to these sets. Alternatives are ranked based on proximity to the ideal solution, providing a clear basis for choice.

Criteria Analysis

4.1 Technical Performance

Processor architecture, core count, and energy efficiency determine performance in complex applications. RAM capacity and type (e.g., DDR5) are important for smooth multitasking. SSDs (especially NVMe) have significantly higher read/write speeds than SATA SSDs or HDDs – speeding up boot times, file transfers, and data processing.

4.2 Screen and Graphics

Resolution (FHD, 2.8K, 3K, 4K), panel type (IPS, OLED), brightness (cd/m²), refresh rate (60–240 Hz), and color spaces (sRGB, DCI-P3, „Adobe RGB”) determine quality and eye comfort. For creativity, accurate color representation and higher brightness are needed; for gaming, a higher refresh rate and dedicated GPU are important.

4.3 Battery Life and Mobility

Independent tests (e.g., MobileMark, practical editorial tests) show that modern ARM/”Apple M” platforms can achieve double-digit (12–20+ hours) durations, while traditional x86 mobile CPUs achieve ~8–12 hours, depending on scenarios. When choosing for mobility, it is advisable to apply the „at least 8–10 hours” rule and check real reviews.

4.4 Ergonomics and Design

Keyboard travel, key stability, touchpad accuracy, hinge strength, cooling acoustics, and chassis materials directly affect comfort. Lightweight (<1.5 kg) and thin (<18 mm) models are particularly suitable for mobile environments.

4.5 Connectivity and Expandability

For daily use, USB-A and USB-C, headphone jacks, HDMI, or DP via USB-C/”Alt Mode” are important. For professionals, „Thunderbolt 4″/USB4 (data, displays, charging), SD card readers, and 2.5GbE/USB-Ethernet adapters are useful. In wireless connectivity, look for Wi-Fi 6/6E or Wi-Fi 7 and „Bluetooth 5.2/5.3”. Check for RAM/SSD upgradeability and the presence of an additional SSD slot.

4.6 Price and Warranty Conditions

Price is important, but consumer rights and warranty service should also be considered. The EU and Lithuania apply a 2-year statutory warranty (seller’s responsibility), while commercial (manufacturer/seller) warranties may be longer. Before purchasing, it is worth evaluating service availability in Lithuania, spare parts prices, and extended warranty conditions.

4.7 Environmental and Supply Chain Aspects

Life cycle assessments (LCA) indicate the largest CO₂ footprint occurs during the production phase (especially in screens and electronics). EPEAT/ENERGY STAR certifications help evaluate efficiency, recyclability, and materials. Refurbished models often reduce the GHG footprint, and prioritizing repairability and parts availability is a sustainable choice.

Discussion

5.1 Practical Application of the Model

The integrated AHP–TOPSIS method provides a transparent platform to compare models based on needs (business, students, creativity, gaming, mobile work) and budget.

5.2 Adaptation of User Profiles

Different profiles weigh criteria differently: for business – security, battery, and external displays; for creators – color accuracy, powerful CPU/GPU, and RAM; for travelers – weight, Wi-Fi 6E/7, USB-C charging.

5.3 Limitations of the Study and Future Research

The model is based on expert evaluations and literature; further research should aim to expand real user data, include TCO (total cost of ownership) analysis, and monitor dynamic changes in criteria (e.g., Wi-Fi 7/USB4/”Thunderbolt” evolution).

Conclusions

Consistent multi-criteria evaluation allows for informed decisions when choosing a laptop. AHP provides objective criteria weighting, while TOPSIS offers a clear ranking of alternatives. By incorporating technical, ergonomic, financial, and environmental aspects, as well as the Lithuanian legal context (statutory 2-year warranty), the risk of unexpected disappointments is reduced, and investments are optimized according to individual usage scenarios.

Case Study

To practically evaluate the AHP–TOPSIS model, a comparison of three popular alternatives was conducted:

• Model A – business-class ultrabook (Intel Core i7 / „Core Ultra”, 16 GB DDR5, 512 GB NVMe SSD, 14″ FHD/2.8K IPS, Wi-Fi 6E).
• Model B – gaming laptop (AMD Ryzen 7, 32 GB DDR5, 1 TB NVMe SSD, 15.6″ 144 Hz FHD IPS, „NVIDIA RTX 3060/4060”).
• Model C – 2-in-1 convertible ultrabook (Intel Core i5, 8–16 GB DDR5, 256–512 GB NVMe SSD, 13.3″ 2.8K/4K OLED, stylus support).

7.1 Data Input and Normalization

Data for each model were collected based on 12 criteria: CPU, RAM, SSD, screen resolution and color space, battery, keyboard ergonomics, weight, connectivity, price, warranty duration/service, cooling acoustics, and environmental labels. Quantitative data were normalized (0–1), while qualitative data (e.g., EPEAT level) were converted into numerical values.

7.2 Results and Interpretation

AHP weights (example): processor (0.18), screen quality (0.15), battery (0.13), price (0.12), storage (0.10), connectivity (0.08), ergonomics (0.07), warranty (0.06), environment (0.06), others (0.05). TOPSIS indicated the proximity to the ideal solution in the following order: Model A (balance between performance, mobility, and price), Model C (versatility and OLED advantages), Model B (high performance, but shorter battery life and higher weight/price – less attractive for non-gamer profiles).

Decision Support System Development

Based on the model results, an online application was created that allows users to:

• Configure a needs profile (weights according to criteria).
• Select models from the database or enter them manually.
• Automatically generate a compatibility table and TOPSIS ranking.
• Visualize criteria weights and proximity to the ideal solution.
• Export results in PDF or spreadsheet format.

The application also offers interactive recommendations (e.g., alternatives with better screens, Wi-Fi 6E/7, or longer battery life), allowing flexible adjustments of weights and immediate visibility of result changes.

Future Research Directions

• Dynamic criteria fluctuations – investigate how importance changes over time due to advancements in technology (Wi-Fi 7, USB4/”Thunderbolt”, OLED, new mobile platforms).
• Integration of machine learning – use user feedback and real sales data to automatically refine weights/rankings.
• Preference heterogeneity – examine the influence of cultural and demographic factors in Lithuania.
• Deepening environmental indicators – more detailed LCA by components (screen, battery, motherboard) and supply chain transparency.

System Validation and User Evaluation

11.1 Usability Study

In a user study (30 respondents), using the System Usability Scale (SUS), an average score of 78.3 (Cronbach α = 0.91) was obtained, corresponding to the „good” usability category.

11.2 Quantitative Evaluation According to ISO 9241-11

The ISO 9241-11:2018 methodology showed that the average task completion time decreased by ~25%, and the error rate fell below 5%, confirming the system’s effectiveness.

11.3 Qualitative Feedback

Interviews and observations revealed that users positively evaluate weight visualizations and clear explanations but desire more detailed guidelines on interpreting criteria weighting for different profiles.

Appendix A: AHP Pairwise Comparison Matrix

Appendix B: TOPSIS Calculation Overview

Normalization: each performance score x_ij is normalized according to the formula r_ij=x_ij/√∑_i=1^mx_ij².
Applying Weights: normalized scores are multiplied by the corresponding criteria weights w_j.
Ideal and Anti-Ideal Solution Sets: A⁺={max v_ij} and A^–={min v_ij} for benefit criteria and inversely for cost-type criteria.
Distance Measurements: S_i⁺=√∑_j=1ⁿ(v_ij–A_j⁺)², S_i^–=√∑_j=1ⁿ(v_ij–A_j^–)².
Relative Proximity: C_i*=S_i^–/(S_i⁺+S_i^–); alternatives are ranked in descending order according to C_i*.

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