The Business Review, Cambridge

The Business Review Journal

Vol. 30 * Number 1 * Summer 2023

The Library of Congress, Washington, DC   *   ISSN 1553 - 5827

Online Computer Library Center   *   OCLC: 920449522

National Library of Australia   *   NLA: 55269788

The Cambridge Social Science Citation Index, CSSCI,

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The primary goal of the journal will be to provide opportunities for business related academicians and professionals from various business related fields in a global realm to publish their paper in one source. The Journal will bring together academicians and professionals from all areas related business fields and related fields to interact with members inside and outside their own particular disciplines. The journal will provide opportunities for publishing researcher's paper as well as providing opportunities to view other's work.  All submissions are subject to a double blind peer review process. The journal is a refereed academic journal which  publishes the  scientific research findings in its field with the ISSN 1553-5827 issued by the Library of Congress, Washington, DC.  No Manuscript Will Be Accepted Without the Required Format.  All Manuscripts Should Be Professionally Proofread Before the Submission.  You can use for professional proofreading / editing etc...The journal will meet the quality and integrity requirements of applicable accreditation agencies (AACSB, regional) and journal evaluation organizations to insure our publications provide our authors publication venues that are recognized by their institutions for academic advancement and academically qualified statue.  The journal submission guideline can be seen at: submission guideline

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Entrepreneur: The Positive Side of Failing – Learning

Dr. George Vukotich, Northeastern Illinois University, Chicago, IL

Marko Lavrencic, Editor-in-Chief,, Slovenia



According to a study conducted by the consulting firm Cap Gemini about 52 percent of the companies on the Fortune Global 500 list in the year 2000 are no longer on the list as of 2020. These are the largest revenue generating companies in the world. In researching this article, the authors wondered why and if these large organizations had such a challenge what could startups and the entrepreneurs that build them learn from it.  One of the main reasons than large successful firms often fail is that they worry more about failure than trying to innovate to continue to succeed. Too often they are not aware of what their competitors are doing, not seeing changing customer preferences, missing overall economic changes, and ignoring technological advancements that could help them change to continue to be successful (Schumpeter, 2017). Doing what made them successful in the past and maintaining the status quo are the reasons these powerful organizations fail (McGrath, 2019). The question is why not innovate (Tushman & O’Reilly, 2017)?  The challenge is a fear of failure. The image of a successful firm having a failure paints a negative picture of not only the company but the leadership and individuals that work there (McGrath, 2011). Often not doing anything or holding back on potential innovations is done since the odds of success are not always well known. There are a number of reasons for this: the risk of the company’s stock price falling, the reputation of the CEO being tarnished along with it their compensation package being reduced, and the overall negative impact of the morale of the employee population that bought into the success of the organization they joined (Rauch, Wiklund, Lumpkin, & Frese, 2009).  But what exactly constitutes failure? And what counts as success? The answers might not be as straightforward as you might think.  Entrepreneurs face uncertainty. But what have they learned through the accumulation of their expertise in this unique environment that can be taught and learned.  While everyone wants to be successful at all they do the entrepreneur learns as they go along. There are generally no well laid out paths to success. Coming up with a new product, service, or business model often requires trial and error. The ideas are a dime a dozen. And it is wise to remember that there is no such thing as a “good” idea up front – there are only ideas we implement and ones we don’t.  According to a recent article on Forbes (https :// approach/ ?sh=6faa37cb2e20) , the minimum viable product approach is gaining popularity among entrepreneurs. The concept of a minimum viable product (MVP) is usually the starting point not the end as in many corporate environments. Once an entrepreneur has their idea and shapes their MVP, they can test it and ask stakeholders what they think. The potential customers, investors, and collaborators can give feedback on what might work and what might not. And not pursuing the original idea has proven to be the right thing to do for many entrepreneurs!  The Startup Genome Project, a Berkley research project, shows that entrepreneurs not only change the idea they started with, but that this change is also positively associated with financial success. Herrman and Marmer who founded the Startup Genome report have also created a business accelerator called Blackbox which leverages the data they collected which showed that startups that pivot once or twice raise 2.5 times more money, have 3.6 times better user growth and are 52% less likely to scale prematurely than startups that pivot more than two times or not at all.  Lean is a common term in the startup environment. It is focused on speed and efficiency. Eric Ries, a Silicon Valley entrepreneur pioneered the concept and wrote the book “The Lean Startup” to focus on a product with minimal features. The idea is that rather than spend a lot of time and money to bring a fully functioning product to market, it is better to bring a simple version known as the minimum viable product to market and evaluate customer feedback related to it. It is an iterative process of improvement where a continuous cycle of feedback and improvement take place (Blank, 2013).  The Lean Startup model is based on five principles.


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Impact of Covid on Consumer Behavioral Habits

Dr. Nasim Z. Hosein, Norwich University, Northfield, VT



This research incorporates two attitude-measuring models, observable and abstract, to compare the attributes that impacted consumer behavior due to Covid.  To analyze the data SEM techniques were used and the findings indicate that the respondents are influenced by factors associated closely to the program's observable and abstract attributes. These discoveries should assist in the understanding of how Covid procedures and practices influenced consumers in their behavior and how marketers can incorporate these changes with their future strategies. In the past recent years, the impact of Covid on consumers has changed the way consumers search, choose and purchase products. As a result, marketers need to adjust their strategy to accommodate this new wave of consumer thinking relevant to purchasing products.  With the availability of the Internet and online shopping, customers are exposed to a great deal of consumer flexibility about products. E-tailers are known to add a tremendous amount of service and product content purposefully to tempt buyers to make purchases at their websites. Additional insight into consumers’ purchasing intentions can help support and enhance the strategic positioning of products and services.  Online shopping is experienced by consumers in many different ways depending on factors such as processes relating to consumer decision-making and interactivity; as well as their experience. Thus, the significance of this paper is to focus on whether Covid has impacted the consumer decision-making process. This literature review outlines the consumer decision-making models that are central in the virtual environment of online shopping. Used are numerous search databases to generalize sources that are relevant to e-tailing, retail, and online access; interaction between retailer and consumer. This review starts with the consumer decision-making models that exist and then goes into consumer behavior- which pertains to online shopping behavior. Lamb, Hair, and McDaniel (2020) devoted a chapter in their book that outlined the needs and wants of consumers through sequential steps in this model. This model purport to capture the essence of consumer thinking- called the consumer decision-making process model. This particular model has five elements that explain sequential steps as a consumer decides. However, it is important to note, each decision-making segment stems from consumers' cultural, social, individual, and psychological factors (p. 90). These factors weigh heavily in one's thought process either indirectly or directly, in both online and in-store purchasing.  However, in this particular study, the ability of consumers to make decisions on purchases online during Covid is what this research attempts to discover.   “Attitude toward a behavior is defined as a person's general feeling of favorableness or unfavorableness for that behavior" (Ajzen and Fishbein, 1980). “Subjective Norm is defined as a person's perception that most people who are important to him think he should or should not perform the behavior in question" (Ajzen and Fishbein, 1980). “Therefore, attitude toward a behavior is a function of the product of one's salient belief (B) that performing the behavior will generate certain outcomes and will lead to an evaluation of those outcomes (E), i.e., rating of the desirability of the outcome.” (Ajzen and Fishbein, 1980). TRA was developed by Ajzen and Fishbein (1980) to guide research concerning consciously intended behaviors. According to TRA, the performance of a specified behavior is determined by the individual’s intention to perform that behavior, which, in turn, is determined by the individual’s attitude towards the behavior and his or her perceptions of social pressures (i.e. subjective norm) for performing (or not performing) the behavior in question (Ajzen, 1988). TRA has received considerable empirical support (Sheppard et al, 1988) and provides a suitable model for this research because trusting behaviors involve an individual’s intention to trust in each situation. Figure 2, from a theoretical framework perspective, indicates that the first realization is Visakhapatnam, Visakhapatnam, in measuring consumers' ability to be comfortable with using technology (intention), the impact(attitude), and their views on the rules and procedures for Covid (subjective norms). before they think about future actions (behavior). Individual behavior is proposed to be the outcome of careful reflection - a cognitive process of evaluating what acts are suitable in specific situations. Identifying that behavior is the target for measuring the impact is the first inference in using the theoretical framework. Several factors are involved in the definition of behavior; the target (online purchasing), the action (concerns/procedures/compliance), and the context (future course of action).


Full Paper


Best Practices and Bank Efficiency in MDIs: Evidence from Black-Owned Banks in the USA

Dr. Michael Porter, Alabama A&M University, AL

Dr. Qian Shen, Alabama A&M University, AL

Dr. Augustine Dike, Alabama A&M University. AL



In an environment marked by inflation, rising interest rates, bank runs, and historic failures of a few large banks, calls by mid-sized banks for the FDIC to insure depositors’ funds regardless of amount has thrusted the stability of the entire banking industry into the spotlight. The emerging regulatory landscape of the banking industry along with extant macroenvironmental factors point to a greater need to understand the potential impact these changing conditions may have on competition, firm performance and efficiency in smaller minority depository institutions, particularly Black banks. This paper examines the relationship between competition and efficiency in Black banks in the USA. Using Data Envelopment Analysis (DEA) to measure and analyze the relative technical efficiency of 19 Black Minority Depository institutions, the authors construct an empirical measure of technical efficiency in these institutions. The results of this study show that Black MDIs, despite high-risk failure rates, have relatively high efficiency rates. Over the period investigated in this study, 2017-2022, 52.6% of banks operated at the 96-100%. The best practices of the most efficient banks are examined and reasons for inefficiencies along with perceived main weaknesses were identified for the least efficient banks. The paper concludes that the vast majority of Black banks are efficient with modest input targets required to improve efficiency in less efficient banks.  The efficient use of resources is deemed advantageous across all industries, including the financial and banking industry, more so following the fiscal crisis of 2007-2008 and the recession shadows of 2022-23. It is widely accepted that an efficient banking industry is a pillar of economic growth and development. The efficiency ratio is one important way to measure productivity of institutions in the banking industry and to examine the kinds of decisions, around the mobilization of resources, that managers should take to attain optimal efficiency.  All banks, regardless of size and missional focus, have a pivotal role in sustaining and driving economic growth in a nation. The current macroenvironment and regulatory landscape leading to rising interest rates, bank runs, and historic bank failures have turned the spotlight on the banking industry. The potential impact of these changing economic conditions on the performance of smaller banks, in particular Black-owned banks, needs to be better understood. At the end of the 1969, there were 22 Black owned or controlled banks in the U.S. The Minority Bank Deposit Program (MBDP), created in 1970, acted as a catalyst for expanding the number of minority banks nationwide. State charters and chartered financial institutions also contributed toward the rapid expansion of Black banks (Brimmer, 1971). In 1971, Black banks accounted for 80% of total minority banks, but 9 years later and at the start of the 80s decade, this declined to less than 50%. Congress then passed the Financial Institution Reform, Recovery, and Enforcement Act of 1989 (FIRREA) to support and preserve minority banks. At the end of 2022, there were 22 Black-owned banks nationwide. The subject of performance differences across minority banks has been underexplored by researchers (Fairchild and Juelfs, 2020), while for black banks it is non-existent (Gardner, 1982). This subject is still relatively underexplored with respect to empirical studies on Black banks. Moreover, there has been no empirically undertaken study that examines efficiency in Black banks, in the United States, using data envelopment analysis (DEA). The purpose of this study is to examine the technical efficiency of Black banks by applying the data envelopment analysis and determining targets that would optimize efficiency levels for these financial institutions. Reasons for inefficiencies are identified, targets are ascertained, and best practices are advanced. This study adopts the use of data envelopment analysis (DEA) which has gained much popularity in assessing the performances of DMUs because of its capacity to readily establish benchmarks for multiple inputs and outputs, while having fewer assumptions, compared to the kinds of assumptions required for linear and nonlinear models used in regressions. The paper contributes toward the recent research paradigm that utilizes quantitative models to evaluate relative efficiency in minority depository institutions, with a special emphasis on Black banks.  Banks have been designed as financial intermediaries to mobilize and distribute financial resources to and across various institutions and agents. In the course of their operations, banks like many other firms operating in various industries, achieve greater competitive advantage and profit growth when they are more efficient, thereby making efficiency a staple focus for banks. Several types of efficiencies exist including technical, pure technical, scale, cost, and allocative efficiencies. Many disciplines are concerned with the measurement of efficiency and the search for ways to improve efficiency levels across various organizational units. There are several techniques for measuring technical efficiency including DEA, Stochastic Frontier Analysis (SFA), regression analysis (Tobit) and other liner programming (Kozubíková et al., 2017). The DEA approach has become immensely popular in empirical (Shahooth, et., al, 2006) on efficiencies across various institutions, particularly in studies that focus on bank efficiency.  


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Copyright: All rights reserved. No part of the material protected by this copyright notice may be reproduced or utilized in any form or by any means, including photocopying and recording, or by any information storage and retrieval system, without the written permission of the journal.  You are hereby notified that any disclosure, copying, distribution or use of any information (text; pictures; tables. etc..) from this web site or any other linked web pages is strictly prohibited. Request permission / Purchase this article:

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Index: The Library of Congress, Washington, DC:    ISSN: 1540 – 7780

Index: Online Computer Library Center, OH:   OCLC: 805078765 

Index: National Library of Australia: NLA: 42709473

Index: Cambridge Social Science Citation Index, CSSCI.

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