CHAPTER ONE

INTRODUCTION

Background of the study

The influence on the marketing business at the corporate level is usually measured by share price fluctuations and dividend payments to shareholders. However, due to the variability of a firm’s operations, performance analysis at the company level, whether for strategic or public policy goals, is frequently insufficient. A company’s strategic business units (SBUs) are frequently highly different. The profitability analysis that brings these businesses together provides little insight into strategic or public decision-making. Because of this heterogeneity, profitability analysis at the SBU level is frequently advised and carried out. The lack of a stock market at the SBU level necessitates the employment of a measurement tool other than a stock-based metric to analyze profitability.

For the advancement of research, strict promotion measures are necessary, especially when the variables of interest are complex or not observable. Surprisingly, strategic management has been chastised for not prioritizing this issue (Boyd, Gove & Hitt, 2005). Quantitative research suffers from a lack of precision in measurement, which obscures genuine relationships (Venkatraman and Grant, 1986).

This is especially important when it comes to the company’s success, which is one of the most important ideas in the area (Rumelt, Schendel, and Teece, 1994) and is frequently utilized as a final dependent variable (Richard, Devinney, Yip, and Johnson). 2009) in a variety of fields (Cho and Pucik 2005, Sila and Ebrahimpuor 2005, Wiklund and Shepherd 2003). Many studies use a single metric to assess a company’s success and portray the notion as one-dimensional, despite the fact that it is multidimensional (Glick, Washburn and Miller, 2005). If there are multiple dimensions, the researcher must choose the ones that are most relevant to his investigation and evaluate the outcomes of that decision (Richard et al., 2009). Ray, Barney, and Muhanna (2004) stress this point, pointing out the challenges in verifying the theory of resources using aggregate measures of performance and recommending the use of indicators specifically related to the resources under consideration. As a result, there is a clear need for a clearer conception of business performance, conversations about its aspects, and improved measuring efforts in the strategic management domain. In this article, we develop and test a multidimensional business performance model to help answer these issues. We based our model on stakeholder theory (Freeman, 1984) and carefully selected a set of indicators to indicate company success. We created the measuring model with the goal of allowing medium-term comparisons between organizations, and we evaluated it with a group of top executives and board members from Brazilian companies. Subjective measures are used, but not for the sake of convenience.

 Problem statement

Because there are few alternatives, a reporting unit’s performance is virtually usually dependent on accounting data. Accounting measurement, in particular, the return on investment (ROI), is widely regarded as the most important indicator and last test of a company’s “final outcome” (James Reese and William Cool, 1978). It’s utilized as a managerial goal as well as a dependent variable or criterion for assessing the impact of various factors on performance. Despite its widespread use, the return on investment (ROI) has been frequently challenged as an insufficient indication of economic rate of return (G. C. Harcourt 1965, Ezra Solomon 1971, Franklin Fisher and John McGowan 1983). The return on investment, which is commonly defined as net income divided by total assets, is not accurate in linking the flow of benefits to the investment that generated them. The numerator of results is a product of past investment decisions, but we may predict that the asset’s denominator has had an impact not only on past and current results, but also on future results. The return on investment has been chastised for its fundamental defect, which bears little or no similarity to the key idea of internal or economic rate of return, as a result of this inability to construct accurate maps. The return on investment would be so inadequate that its cross-sectional variability could be fully explained.

Purpose of the study

The goal of this research is to look at Return on Investment as a tool for assessing an organization’s marketing impact. The study’s objectives were as follows:

1 to see if ROI is utilized as a metric for measuring business growth.

2 find out what pros think about using ROI as a marketing effect metric.

3 to investigate ROI’s applicability as a performance indicator

Significance of the study

The findings of this study can be used by policymakers, company administrators, and instructors in the education sector to develop strategies for implementing marketing plans that support corporate growth. The study can also help the legal or legislative framework by giving businesses the information they need about the rules and regulations. The findings may also contribute to the global discussion on profitability indexes and their control, as well as provide ideas for future research on the causes, effects, and interactions of with other elements.

Study hypothesis

The following is the study hypothesis:

HO1: Return on investment (ROI) is not a meaningful performance indicator.

H11: Return on investment (ROI) is an important performance indicator.

H02: Return on investment (ROI) does not reflect the size of a company’s expansion.

H12: ROI shows extent of business growth

Scope and Limitations of the Study

The study’s scope is confined to looking into Return on Investment as a measure for measuring an organization’s marketing impact. The research was hampered by a lack of time and financial resources.

Organization of study

The research is divided into five sections. This is the opening chapter, and it provides an overview of the research. The second chapter is devoted to a review of the relevant literature. The research methodology is presented in Chapter 3; the data analysis, as well as the interpretation and discussion of the results, are presented in Chapter 4. The findings and recommendations are summarized in Chapter 5.

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