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Compare and contrast the various versions of ANOVA

Compare and contrast the various versions of ANOVA

In this assignment, you will compare and contrast the various versions of ANOVA.
Part 1
Using the week’s resources as well as those you locate yourself, define and describe the following variance analysis tools:
one-way ANOVA,
ANCOVA,

MANOVA, and
MANCOVA.
Part 2
Find two research studies (peer-reviewed journal articles) that each used one of these tools (e.g., one article about one-way ANOVA and another about MANOVA). Very briefly summarize each study. Then compare and contrast the two articles identifying, specifically, the type of hypothesis(es) the tools were used to investigate, etc.
COMPETITIVE ADVANTAGE THROUGH OPERATIONS SYSTEM AND SUPPLIER
NETWORK RESPONSIVENESS
Ashish Thatte, Gonzaga University, USA
thatte@gonzaga.edu
Parag Dhumal, University Of Wisconsin – Parkside, USA
dhumal@uwp.edu
Vikas Agrawal, Jacksonville University, USA
vagrawa@ju.edu
ABSTRACT
This study extends Thatte and Agrawal’s (2017) research which found positive effects of
operations system responsiveness (OSR) and supplier network responsiveness (SNR) on
competitive advantage (CA), and Thatte, Rao, and Ragu-Nathan’s (2013) research which found
positive relationships between supply chain management (SCM) practices, supply chain
responsiveness (SCR), and CA. As such, by utilizing MANOVA, this study analyses how CA is
effected by high and low levels of OSR and SNR. The study finds that high levels of OSR create
high levels of CA for a firm collectively and individually on price, delivery dependability, product
innovation, and time to market. The study also finds that high levels of SNR create high levels of
CA for a firm collectively and individually on price and delivery dependability. Useful
implications of the findings are drawn and discussed.
INTRODUCTION
Firms are finding it useful to aptly respond to changing customer needs (Huber, 1984; Ward,
McCreery, Ritzman, & Sharma, 1998) and supply disruptions (Christopher & Peck, 2004; Lee,
2004) in today’s global supply chains. Consistent with Thatte and Agrawal (2017) and Thatte,
Rao, and Ragu-Nathan (2013), this research studies the SCR construct from the customer demand
perspective, rather than a supply disruption perspective.
Thatte and Agrawal (2017) found OSR and SNR to positively impact CA. Thatte et al. (2013) dealt
with large scale instrument validation and hypotheses testing between SCR and CA using
structural equation modeling and found positive relationship between SCR and CA, SCM practices
and SCR, and SCM practices and CA. This study extends Thatte and Agrawal’s (2017) and Thatte
et al.’s (2013) studies by examining how CA responds to high and low levels of OSR and SNR, in
order to draw implications. Such a dimension level analysis between SCR and CA is lacking in
Volume 13, Number 1, May 2018

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