A review of the research methodology of an academic article: Purchasing and Supply

A review of the research methodology of an academic article: Purchasing and Supply [informed by chatpdf.com]

Article name: "Customer attractiveness: A comparative analysis of startups versus incumbents in supplier choice " Journal of Purchasing and Supply Management.

My question 1: "What are the research objectives of the article?"

The reply: "The research objectives of the article are as follows:

1. To assess the impact of company type (startup versus incumbent) on customer attractiveness: This involves understanding how the classification of a company influences its attractiveness to suppliers .

2. To identify and compare factors that significantly influence customer attractiveness for startups and incumbents: This objective is aimed at uncovering which specific attractiveness factors are more impactful for startups as compared to established companies .

These objectives guide the research in analyzing the competitiveness of startups in attracting supplier resources and understanding the dynamics at play in supplier selection , ."

My question 2: "What are the research methods employed as reported in the article?"

The reply: "The research methods employed in the article include:

1. Discrete Choice Experiment (DCE): The study used this method to empirically assess supplier preferences and how they choose between startups and incumbents. DCE allows for exploring preferences in a controlled environment by offering participants hypothetical choices and estimating the utility of different attributes , .

2. Sample Selection: The research targeted American salespersons, utilizing an online recruitment platform, Amazon Mechanical Turk (MTurk). This approach provided access to a diverse participant pool while also emphasizing quality control measures . Various strategies were applied, such as demographic filtering to focus on U.S. salespeople and ensuring participant quality through specific criteria, including a minimum approval rate .

3. Data Quality Measures: To enhance the validity of the data collected, the researchers incorporated CloudResearch’s MTurk toolkit, conducted sample representativeness checks, and ensured fairness in participant compensation relative to typical hourly rates .

These methods collectively contributed to gathering insights on supplier perceptions of customer attractiveness across different company types."

My question 3: "What is the underlying research philosophy of the study as reported in the article?"

The reply: "The underlying research philosophy of the study is grounded in empirical and experimental research methodologies, particularly the use of the Discrete Choice Experiment (DCE). This approach is indicative of a positivist philosophy, which emphasizes observable phenomena and the collection of quantitative data to derive conclusions about supplier preferences in customer attractiveness.

The study aims to explore preferences through controlled experimental conditions rather than relying solely on traditional perceptual surveys, which may yield unreliable results due to limited experiences with certain types of customers (i.e., startups versus incumbents). The DCE methodology is designed to simulate real decision-making scenarios, allowing for the analysis of trade-offs suppliers consider when selecting customers , .

Thus, the research philosophy underscores a systematic and factual analysis, striving to produce generalizable insights based on empirical data regarding supplier behavior and preferences in the context of customer attractiveness."

My question 4: "Did the study employ the mono method, multi method or mixed method as its overall research approach?"

The reply: "The study employed a mono method approach as its overall research strategy. Specifically, it utilized the Discrete Choice Experiment (DCE) as the sole methodological framework to examine supplier preferences in selecting attractive customers. The study focused exclusively on this quantitative method to gather empirical data and assess the factors influencing customer attractiveness without integrating other qualitative or alternative quantitative methods alongside it , ."

My question 5: "Were the research method design informed by any academic theories?"

The reply: "Yes, the research method design was informed by academic theories, particularly the reverse marketing concept. This theoretical framework was utilized to evaluate supplier choices regarding customer attractiveness in the DCE. Additionally, the study drew upon the liabilities of newness as a theoretical lens when operationalizing firm newness, distinguishing between startups and well-established companies , . These theoretical underpinnings guided the operationalization of attributes and the design of choice sets within the experiment, enhancing the study's relevance and rigor within the context of customer attractiveness research."

My question 6: "Did the study employ the deductive, inductive or the abductive research approaches?"

The reply: "The study primarily employed a deductive research approach. This is evident from its formulation of specific research questions based on existing theories and prior research related to customer attractiveness and the liabilities of newness. The study aimed to test hypotheses regarding the impact of company type (startup versus incumbent) on customer attractiveness and the influence of various attractiveness factors. By gathering empirical data through the Discrete Choice Experiment (DCE) to validate or refute these hypotheses, the research aligned with a deductive framework, which typically involves testing theories through structured methodologies , , ."

My question 7: "Did the study employ the triangulation method?"

The reply: "The study did not explicitly mention employing the triangulation method in its methodology. Triangulation typically involves using multiple methods, data sources, or theoretical perspectives to enhance the credibility and validity of research findings.

While the study utilized a Discrete Choice Experiment (DCE) as its primary data collection method, it mainly focused on testing specific hypotheses related to customer attractiveness without integrating additional data sources or alternative methodological perspectives commonly associated with triangulation , . However, the study did integrate insights from prior qualitative and quantitative research when framing its hypotheses and discussing its findings, which could be considered a form of methodological robustness, but not strict triangulation as defined in qualitative research practices , ."

My question 8: "Does the research methodology design address the research objectives of the study?"

The reply: "Yes, the research methodology design effectively addresses the research objectives of the study. The study aimed to understand the factors that influence customer attractiveness from the perspective of suppliers, particularly in distinguishing between startups and incumbents. To achieve this, the methodology implemented a Discrete Choice Experiment (DCE), which allowed researchers to assess supplier preferences for different customer attributes in a controlled and empirical setting , .

The DCE method aligns with the research objectives by enabling a systematic evaluation of how suppliers prioritize various factors influencing customer attractiveness. By establishing a clear choice architecture and generating decision-making scenarios that replicate real-world conditions, the study effectively fulfills its goal of exploring supplier preferences and trade-offs between customer attributes , .

Furthermore, the use of appropriate sample size calculations, attribute levels, and the participant demographic analysis bolster the methodological design, reinforcing its ability to provide substantial insights into the research questions posed , . Overall, the choice of methodology is well-structured to meet the study's objectives and validate the formulated hypotheses regarding customer attractiveness."

My question 9: "What is the research method design quality of the study, in terms of the qualitative research method design quality criteria and quantitative research method design quality criteria?"

The reply: "The research method design quality of the study can be evaluated in terms of both qualitative and quantitative research method design quality criteria as follows:

Qualitative Research Method Design Quality Criteria

1. Credibility: While the study primarily utilizes a quantitative approach (DCE), it draws from previous literature and qualitative insights to frame its hypotheses. This enhances its credibility by building on established findings within the field .

2. Transferability: The study's findings may have limited transferability due to the focus on American salespeople and the absence of industry-specific factors. This raises concerns regarding the generalizability of results to different contexts or countries. However, it aims for a diverse sample of respondents, which partially mitigates this limitation , .

3. Dependability: The project followed systematic procedures in designing the questionnaire and collecting data, ensuring that the processes were well-documented. This contributes positively to dependability. However, it acknowledges potential limitations due to the use of hypothetical scenarios, suggesting a need for caution in interpretation , .

4. Confirmability: The study provides clear methodological documentation, including the rationale for using DCE, which allows for a level of transparency in the process. Yet, the reliance on hypothetical choices may introduce biases that affect confirmability .

Quantitative Research Method Design Quality Criteria

1. Validity: The DCE method is a well-established approach in marketing and purchasing research, suggesting high validity in measuring supplier preferences regarding customer attractiveness . The attributes and levels used in the study were thoughtfully chosen based on theoretical frameworks, enhancing content validity.

2. Reliability: The study's careful design, including attention checks and pre-testing of the questionnaire, supports the reliability of the data collected , . The sample size (129 usable responses) is deemed sufficient for carrying out statistical analyses.

3. Generalizability: As noted, the focus on American respondents and a specific sample of salespeople may limit generalizability. The study recognizes this as a limitation and suggests avenues for future research in different cultural and industry contexts , .

4. Statistical Power: The study employs a fractional factorial design for the DCE, which optimizes the data collection process and enhances the power of the analysis while reducing complexity for respondents .

Conclusion

Overall, the study demonstrates strengths in both qualitative and quantitative aspects but also faces challenges related to generalizability and the potential biases introduced by hypothetical scenarios. While it effectively employs established methodological frameworks, further research could enhance the robustness of its findings across diverse contexts."

Reference: a collection of blog notes on using chatgpt for research purpose.