Critical Analysis of Two Academic Journal Articles

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Critical Analysis of Two Academic Journal Articles

Introduction

Research in Human Resources (HR) relies on solid methodology and careful use of both primary and secondary data. Academic journals in this field often differ in how they design their studies, collect data, and interpret findings. This essay critically analyses two peer-reviewed journal articles that adopt different research approaches within HR. The analysis focuses on how each paper applies qualitative or quantitative methods, manages data collection (primary and secondary), and presents its findings. By comparing their sampling, analytical techniques, and data presentation, this paper highlights what makes research credible and practically useful in the HR profession.

The two selected articles are:

1. Guest, D. E. (2017). “Human resource management and employee well-being: Towards a new analytic framework.” Human Resource Management Journal, 27(1), 22–38.

2. Paillé, P., Chen, Y., Boiral, O. and Jin, J. (2014). “The impact of human resource management on environmental performance: An employee-level study.” Journal of Business Ethics, 121(3), 451–466.

These papers were chosen because they both address HR’s influence on employee outcomes, but use contrasting research designs , one primarily conceptual and qualitative, the other quantitative and data-driven.

Article 1: Guest (2017) – A qualitative and theoretical research approach

Guest (2017) adopts a conceptual and analytical approach rather than empirical field research. The paper develops a theoretical framework linking HR practices to employee well-being and organisational performance. This makes it a qualitative study rooted in secondary research. The author synthesises existing literature, evaluates theoretical assumptions, and constructs an integrative model to guide future empirical testing.

Research approach

The paper uses an inductive qualitative approach, drawing from multiple theoretical traditions in HR, psychology, and organisational behaviour. Rather than collecting new data, Guest analyses and integrates secondary sources such as peer-reviewed studies, meta-analyses, and policy documents. This method suits the aim of theory development rather than testing.

Guest’s use of literature is systematic and critical. The analysis identifies inconsistencies in prior research linking HR practices with well-being, noting that earlier studies often lacked consistent definitions of “well-being” or mixed causal directions. By constructing a new analytic model, Guest contributes to conceptual clarity in the field.

Data sampling and sources

Since the paper uses secondary data, there is no sampling of participants. Instead, Guest samples prior research based on relevance and academic credibility. The sources span psychological and HRM studies from Europe and North America, offering a broad academic foundation but limited empirical diversity.

Data analysis and presentation

Data analysis here takes the form of conceptual synthesis. Guest identifies recurring variables across prior research (such as job design, engagement, satisfaction, and performance) and maps their relationships within a theoretical framework. Results are presented narratively and diagrammatically, with clear models illustrating the proposed relationships.

This qualitative structure makes the paper highly readable and insightful, but its lack of primary data means findings are theoretical rather than tested. Nonetheless, Guest acknowledges this limitation, calling for future empirical validation.

Strengths and limitations

The strength of Guest’s approach lies in its depth of conceptual understanding. It integrates diverse strands of theory to produce a cohesive analytical tool for future research. However, the absence of primary data or measurable variables means practical HR implications remain untested. The study’s reliance on secondary literature also risks selection bias , what is included or excluded depends on the author’s perspective.

Article 2: Paillé et al. (2014) – A quantitative empirical research approach

In contrast, Paillé et al. (2014) conduct a quantitative empirical study investigating how HR practices influence employees’ environmental performance. Their research design is grounded in data collected from 320 employees across several Chinese manufacturing firms, using structured questionnaires.

Research approach

This study follows a deductive research model. The authors begin with hypotheses derived from social exchange theory and the resource-based view of the firm, predicting that HRM practices such as training, empowerment, and reward systems will positively influence pro-environmental behaviour.

The approach is positivist, focusing on measurable variables and statistical relationships. Unlike Guest’s theoretical framework, this paper tests pre-specified hypotheses using numerical data and statistical analysis.

Data collection and sampling

Paillé et al. collect primary data through self-administered surveys distributed to employees. The sample includes workers from multiple firms to improve generalisability. A stratified sampling technique ensures representation from different job levels and departments.

To complement primary data, the authors use secondary data such as company environmental policies and sustainability reports to contextualise their findings. This mix of data sources strengthens validity.

Data analysis and presentation

Quantitative data are analysed using structural equation modelling (SEM), a statistical technique that tests relationships between multiple variables simultaneously. Results are presented through tables, correlation matrices, and path diagrams. These allow readers to visually interpret causal relationships and significance levels.

The data presentation is transparent and technically rigorous, enabling replication. The use of statistical measures (e.g., Cronbach’s alpha for reliability, p-values for significance) enhances the paper’s credibility.

Strengths and limitations

The main strength lies in the precision and empirical grounding of results. The study confirms significant relationships between HRM practices and environmental performance, offering actionable insights for managers. However, its reliance on self-reported data introduces bias, as employees might overstate positive behaviours.

Moreover, the sample is limited to Chinese manufacturing firms, which restricts cross-cultural generalisation. While the paper includes secondary data for context, it is primarily quantitative, offering limited qualitative depth or insight into employee motivations.