Corporate Reputation of Family-Owned Businesses: Parent Companies vs. Their Brands

Abstract

The reputation of companies is one of their key success factors. It is therefore necessary to value this intangible asset. In order to detect possible threats quickly, continuous monitoring of corporate reputation plays an important role in this valuation process. Family businesses are an ideal object for reputation management research, as through their brands they integrate tradition and addressability at the same time. The main aim of the paper is to discuss the issue of innovative approaches to the online reputation management. We performed an in-depth analysis of online reputation through an Advanced sentiment analysis on the significant sample of ten largest family-owned businesses in the world. Taking into account all relevant determinants of reputation such as Google as well as major social networks, namely Facebook, Twitter, YouTube, and LinkedIn. As there is a noticeable difference between the marketing communication of the parent company and the marketing communication of the brand owned by the company, the findings of the analyses will provide a better insight into the issue of sustainable brand development. By identify good practices, as well as highlighting weaknesses, our research has the ambition to contribute to the shift of knowledge in the field of reputation management.

1. Introduction

The issue of reputation is relatively complicated, as the very concept of reputation integrates in itself economic, managerial, philosophical, or even theological aspects. This multidisciplinary construct is gaining more prominence in business practice. From the point of view of organizations, the reputation acquires the nature of an intangible asset and it is therefore necessary to approach it as a means that can generate benefits for the company. Associated with this resource, we highlight the need to value this asset. As the reputation of the company often determines its success or failure in the competition of countless anonymous companies. Due to the nature of the market and the variability of the environment, our research focuses on corporate reputation in the Internet environment, as it is in this environment that reputation is most prone to damage. Building a reputation on the Internet requires, among other things, constant monitoring. In the event that the slightest threat is detected, the necessary procedures must be applied immediately to prevent possible damage and to seek remedial action. The speed at which a virtual environment can generate the variables necessary to be considered is unparalleled in the traditional world. At this point, we come to the need to identify appropriate methods and procedures for a comprehensive reputation analysis. One of the available methods applied to managerial practice is also sentiment analysis, in our case sentiment analysis in its advanced form. The method we have been developing for almost a decade allows monitor key variables and thus prevent losses or even contribute to building a positive reputation. For the purposes of this study, we are presenting the application of the mentioned method to a highly significant sample of companies. Specifically, to the 10 largest entities in the field of family businesses. We chose the area of family business given the nature of the entities, as we assume their higher addressability and corporate responsibility in their external market communication. Within the theoretical overview, we are elaborating the issue of family business from the point of view of its dominant specifics. At the same time, we are examining the current state of knowledge within the trends in the field of corporate reputation. The analyzed facts serve as a literary basis for subsequent study in the form of qualitative analysis. The identified findings and the resulting connections are interpreted and visualized. By comparing the findings with the reference studies, the identified facts creating examples of good practice. At the same time, we are pointing out to possible areas in which it is necessary to consider the introduction of correction mechanisms. Although the study focuses on a sample of multinational corporations, the findings and examples of good practice can also be applied to small and medium-sized enterprises, as the nature of the Internet in the form of real-time address communication greatly obscures differences in business size.

2. Theoretical Overview

As we mentioned in the introduction, in the theoretical overview we will focus primarily on the issue of family business and its specifics. Subsequently, we will examine current trends in terms of the development of corporate reputation.

2.1. The Issue of Family Businesses

It is difficult to define the term a family business (as business entity), as, according to Hudáková [1], differences of opinion and definition play an important role in defining the basic issues of family business (as form of business activity). As far as the family business itself is concerned, by this term we can understand such business units where family members participate in the business activity, functioning, building and development of business unit. The main specific and different factor from non-family business is the participation of family members in the management and control of the implementation of business activities [2]. With a relatively rough definition and essence of family business, we come to the definition of a family business. A family business is a business in which the family, represented either closer or more distant members, seeks to maintain, control and develop decisive power for the benefit of future generations [3]. Despite the fact that the literature offers us dozens of definitions, it is problematic to reduce relatively vague concepts to clear statements. However, according to Brad [4], all these concepts include to some extent three key aspects, namely:

• Aspect of ownership;
• Aspect of business/management;
• Aspect of personnel/people.

From the point of view of ownership, we encounter different data across countries from the point of view of the expected percentage of the family within the structure of owners. According to Family Capital [5] which (in cooperation with PWC) compiles a list of the 750 largest family businesses, we can state that if it is to be a family business, the family must have at least a 50% voting shares in the case of private companies. In the case of publicly listed companies, the family must have at least 32% of the voting rights, despite the fact that 30% of such rights are usually sufficient to dominate a general assembly.

Related to this is the management aspect, when the family should be involved in managing and deciding on key business issues. The last aspect is the personnel aspect. The family business usually employs individual family members. Involving them in the overall operation of the company is important for its maintenance and development.

From the point of view of family business models, in the fundamental starting points of the professional literature [6] we encounter three basic models of family businesses:

• F-PEC model;
• Three-Circle Model;
• Holacracy.

The first of the mentioned models, F-PEC model (Family influence through Power, Experience and Culture) was created to compare businesses based on how much the family affects business performance. By decomposing the name, we get to aspects such as strength and experience. Under the term strength we understand the economic indicators of the company such as capital and also the number of family members involved in the management of the company. Experience represents the know-how for the management of the company itself and its gradual transfer to successors [7,8,9].

The second of the models, called the Three-Circle Model, developed in the 1970s by Tagiuri and Davis [10], takes into account the three spheres that determine the ecosystem of the family business: ownership, the family and the business itself. The spheres take the form of interconnected circles, which form a total of seven interest groups. Each of these groups has its own legitimate perspective, goals and dynamics. This brings us back to the discussion of the vague definition of family business in terms of its key aspects, presented at the beginning of this chapter.

The last of the models, the Holocracy model, is a system that relies heavily on decentralization and the sharing of authority. This is a relatively interesting, albeit rather controversial, concept [11,12,13,14].

After defining the key starting points, we will move on to the topic in further detail. From the point of view of the market situation, it can be stated that both decades of the twenty-first century significantly contributed to the increase of market dynamics, especially in their ends. The first of the decades was marked by generational change, especially in Italy, which, as one of the oldest European markets, has a relatively large representation of family businesses in the national economy. This generational change proved to be the right one, and companies, especially in the field of fashion, began to prosper again. The post-communist countries of Central and Eastern Europe also faced the challenge of handing over succession [15]. The second decade of the twenty-first century was mainly marked by the uncertainty caused by both Brexit and the threat of an impending pandemic of the new coronavirus. Although we cannot assess the impact of these threats at the moment [16], it can certainly be stated that these are factors that significantly increase market dynamics and thus generate both threats and challenges for companies.

If we take into account the relatively complex structure of relationships and interests in the constructions, which we call family businesses, and expose it to their own market dynamics, we get an ideal object for the implementation of empirical research in management sciences. Before moving on to the research itself, we consider it important to point out current trends and challenges in the field of reputation management.

2.2. Issue of Reputation Management

When we talk about reputation, it is necessary to define at the outset the context in which we will perceive reputation. From the point of view of economics and management, reputation can be seen as an intangible asset [17]. At the same time, it is necessary to distinguish the basic concepts, which are:

• Image;
• Trust;
• Reputation.

From the nature of the word Image, we clearly deduce that it is almost literally an image of a given company in the eyes of its internal as well as external markets [18,19,20]. As for trust, it is perceived across the whole spectrum of sciences, especially its theological aspect is extremely appealing. In any case, this is a situation in which one entity relies on another on the basis of various, often irrational, assumptions. However much we see trust, the state is the basis of cooperation, a force that transforms anarchy into harmony [21,22]. So how is it possible to look at the concept of reputation? If we wanted to reduce the concept to a pure essence, then we could speak of reputation as an overall perceived quality that is attributed to the subject by its target audience [17]. Unlike Image, however, it is a complex multi-dimensional quantity. In the literature [23] we can find different levels of reputation, such as:

• Primary;
• Secondary;
• Cyclical.

These levels depend on the way in which the target audience becomes acquainted with the object whose reputation it subsequently forms. As for the starting points, which to a large extent help to build a reputation, we most often encounter in the literature concepts such as transparency, identity, consistency or clear targeting [24,25,26,27].

Current studies in which the issue of reputation is examined to a relatively wide extent across the economic and managerial sciences bring interesting findings and, last but not least, confirm the topicality of the chosen topic. After studying a wide range of available literature, it is possible to extract key aspects that need to be taken into account in the reputation building process. In a study on building trust mechanisms, Shao et al. [28] state that security is a key element in building the trust and reputation. Another study [29] on consumer interactions in the online environment states that digital content marketing is on the decline. It is not a particularly surprising finding, but an interesting fact is that the study points to a growing need to seek customer involvement in brand building process. It is this procedure that we increasingly encounter in business practice. Involving customers in communication activities or directly in the processes of building a brand is certainly one of the new challenges for reputation management. The most important consequences of brand-customer interaction include cognitive, emotional and behavioral engagement of consumers. Marketers encourage customers to identify with brands, thus creating a committed community of followers. Online platforms use the communication capability of the Internet in order to develop large networks in which perceived quality can be assessed and thus contribute to increasing trust and building the reputation of entities [30]. So far, this technology is well-known and used for building trust, especially in online marketplaces such as Amazon and eBay. However, the mechanisms and algorithms that allow these entities to work with data are ready for application to a wider range of uses. Decision-making support and the mechanisms recommended in complex specific scenarios can also be used in areas such as e-health and e-marketing. A transparent, digitized and interconnected environment is putting increasing pressure on companies to take social responsibility for their actions. Studies confirm that accepting social responsibility increases customer loyalty to the brand [31].

With regard to family businesses, due to the specific characteristics of these businesses, there is a strong identification of the owner with the organization. An important goal in business activities is to a large extent to create and maintain the good reputation of the organization. These are mainly non-financial objectives such as customer retention and social capital. The growth and reputation of family businesses has been the subject of many studies. Despite the growing intensity of research, a comprehensive overview of this topic is still lacking. The work of Segeder, Mitter, and Feldbauer-Durstmueller [32] synthesizes the ways in which the public perceives family businesses, then complements these ways with factors, procedures and impacts which it integrates within the proposed model. The importance of approaching the customer and taking into account the company’s non-financial indicators is also highlighted in a British study [33] in which the authors examine the extent to which retailers need to improve their reputation in order to subsequently optimize their returns. In a sample of 981 companies in five European cities, they found the fundamental importance of reputation in the brand building process. The market environment, influenced by digitization, which shifts the dominant level of interaction to the online world, is changing the practices used by businesses in the past [34]. The traditional media have lost their information monopoly.

The Internet environment brings to companies many changes and pitfalls. Market approaches used by them must be adapted to those changes in real time. The decentralized, anonymous or even dehumanized nature of the Internet contributes to the considerable uncertainty of organizations in managing their reputation. Threats can appear in almost any form in real time. Ongoing monitoring and analysis seem to be an important tool for reputation management. This is possible with the use of more or less autonomous solutions. The literature offers us a myriad of methods and procedures, and based on the accumulated knowledge [17,35] we select the following:

• Systems based on counting and averaging;
• ReGreT model;
• Sentiment analysis.

In the case of the first of the procedures, it is one of the simplest systems for monitoring reputation, as the essence of the system is the aggregation of ratings of the same polarity in a preset rating system. This system is especially preferred by digital marketplaces, as it integrates simplicity and efficiency. As for the ReGreT model, we are talking about a reputation analysis system that takes into account the three determinants of reputation, namely direct experience, third party information and social structures. The third procedure, sentiment analysis, is in its simplest form used to determination of the polarity of the written text relating to subject within the preferred information source. The analysis has several forms; its advanced form is described in the section presenting the methodology of our study.

3. Materials and Methods

The main aim of the paper is to discuss the issue of innovative approaches to the reputation management. In order to fulfill our goal, it is necessary to decompose it into research tasks. Decomposition occurs by linking the goal to the key starting points of the topic. These were identified on the basis of an in-depth analysis of the issue in the form of a literature search of the current state of knowledge. The key topics can be summarized as follows:

• The specific nature of family business requires more consistent approaches to brand development;
• Social networks create an environment for building customer tribes;
• The nature of the online environment puts pressure on the continuous analysis of variables affecting the company’s reputation.

It is known from business practice that building a brand is an extremely complex process. Taking into account the key topics, it is possible to proceed to the definition of research tasks, namely:

• Examine the overall level of online reputation of family businesses;
• Examine the overall level of online reputation of selected brands from the portfolio of these companies;
• Compare results and identify specifics.

At this point, it is possible to formulate a research question, namely:

Is there a difference between the parent company’s e-marketing communication and the brand’s e-marketing communication belonging to that company’s portfolio?

The object of the research is 750 large family companies operating on the global market. The research sample is made up of the ten largest companies in this group, as listed by Family Capital and PWC [5]. In order to answer the research question, one brand is always identified within the portfolio of companies from the research sample, which is communicated to the market within the company.

Among the main scientific methods used in research can be included mainly:

• Analysis;
• Synthesis;
• Methods of abstraction and subsequent induction.

From the point of view of specific procedures and methods used in the analysis, it is possible to mention in particular the Sentiment Analysis in its expanded form, which is the basis for calculating the Total Online Reputation of TOR. The description of the procedures is as follows:

• Identification of the object of research;
• Identification of determinants of reputation for given entities;
• Implementation of Sentiment Analysis in its expanded form;
• Implementation of Analysis for individual reputators;
• Calculation of the total value of the TOR reputation for each of the entities.

To clarify the procedures at this point, we will approach each of the methods used, starting with the Sentiment Analysis. The analysis is based on a method called Opinion mining, which is a linguistic method of natural language processing [36]. It can be automated, but data collection and assessment can also be personalized. The aim of the analysis is to identify and quantify the polarity of the text related to the object of research. Polarity usually takes on positive, negative, or neutral values. Based on our previous research [37], the process can be described as follows. The first step in this analysis is to define a set of objects that will be tested by this analysis. Subsequently, the choice of data source for the polarity analysis of the texts is important. In the case of the Sentiment Analysis, which is used in our research, the Google.com search engine is used as a data source. Subsequently, the polarity of the search results of its own name is assessed for each subject in the first ten places in the search result. For each of the positions and each of the assumed sentiments, the numerical value is clearly quantified according to the following

Table 1. Sentiment analysis [37].

Sentiment/Position of the Result	1	2	3	4	5	6	7	8	9	10
Positive sentiment	20	19	18	17	16	15	14	13	12	11
Website owned by an entity	10	9	8	7	6	5	4	3	2	1
Neutral sentiment	2	2	2	2	2	2	2	2	2	2
Negative sentiment	−20	−19	−18	−17	−16	−15	−14	−13	−12	−11

.

Numerical values of the subject’s sentiments at each of the search result positions are recorded and then calculated, the resulting value gives us the basic input variable for in-depth analysis. If the analysis remained only in its simplest form, we would proceed to the definition of a reference group of entities within which we would repeat the procedure from its first step. Subsequently, we would compare the resulting values of the entities and on the basis of them we could create an order that would have the nature of benchmarking our entity with respect to its reference groups/competitors.

Our preferred form of sentiment analysis has a more sophisticated form, we call it Advanced Sentiment Analysis (ASA), and it takes into account other variables in addition to the basic parameter 10 of the search results. Depending on the subject, we can define search results in the main tabs of the Google search engine, such as news, or add selected keywords to the subject’s own name in order to more accurately identify its online reputation. The resulting score is recalculated and expressed as a percentage according to the number of variables. The number of groups is not limited. However, the quantification is based on the assumption that the maximum score obtained when searching for one parameter (usually the subject’s own name) is 155 points according to the methodology we use. The value of one point converted to percentages is as follows: 1 point = 0.645%. With two parameters within our research (Google tab All and News), the maximum score is 310 points, where then 1 point represents 0.322%.

The second step in quantifying the overall level of reputation is to define other determinants of the entity’s reputation. We call these determinants reputators. These are determinants that can fundamentally affect a perceived online reputation of an entity. Due to the diverse nature of the entities, it is not possible to define a standard group of initial reputators. For each group of entities, it is necessary to focus on the most relevant determinants. By default, however, the reputator:

• Has the ability to significantly determine the online reputation of the entity;
• The determination value is quantifiable;
• The value can be quantified as a percentage.

If it is not possible to directly quantify the value of the reputator (it is mostly if quantification is based on the size of the user base/customer tribe in the social network environment), it is possible to proceed to quantification using a parameter called Competitive Score (CS), in which case define a set of reference entities/competitors on the basis of which we will make a comparison. The sum of the total number of user bases of all subjects of the sample gives us the size of the total customer base in the industry. This is then compared against the size of individual sub-bases/own tribes of the analyzed subjects. The share of the size of the subject’s tribe in the total size of the industry’s tribe gives us a competitive score of the subject with respect to the reference subjects. The CS parameter is calculated separately for each of the identified reputations. The reputators identified for our chosen research group are as follows:

• Facebook (total number of followers of the official and verified global profile, in the following tables referred to as FCS);
• Twitter (total number of followers of the official and verified global profile, in the following tables referred to as TCS);
• YouTube (total number of subscribers of the official global profile, in the following tables referred to as YCS);
• LinkedIn (total number of followers of the official global profile, in the following tables referred to as LCS).

The third step is the calculation of the Total value of the Online Reputation (TOR) for each of the analyzed entities. We perform the calculation on the basis of a simplified version of the formula, which does not take into account the weight of individual reputators. It is the following formula:

$$\mathrm{TOR}=\frac{{\mathrm{R}}_{\mathrm{ASA}}+{{\displaystyle \sum }}_{i=1}^n{\mathrm{R}}_{\mathrm{i}}}{\mathrm{n}+1}$$

(1)

where:

• TOR–total online reputation in %,
• R_i–reputator (% score based on a given i-th determinant of online reputation),
• R_ASA–reputator ASA (% score based on the advanced sentiment analysis),
• n–number of indicators.

In this case, the overall score is in the nature of the arithmetic mean of the individual determinants of reputation.

From the point of view of processing research results, basic statistical methods are used; research as such, despite a significant sample, is of a dominant qualitative nature. The analyzed connections are then visualized in order to illustrate the results.

With regard to data collection and processing, the research itself took place in the first half of 2020, and so the temporal informative value of the data reflects this period. Due to the nature of the research sample, we do not assume that seasonality will affect the data to a dominant extent.

4. Results

Based on an extensive empirical study, and with using the described methodology, we identified both partial and total online reputation values for our research sample, before moving on to the presentation of results through summary tables, we consider it necessary to describe the analyzed subjects.

The first entity we analyzed is the retail giant Walmart Inc., which operates a chain of Walmart hypermarkets, especially in North America. The company was founded by Sam Walton in the 1960s and is still run by the Walton family. From the company’s portfolio, we selected the Sam’s Choice brand for comparison in the analysis. Sam’s Choice is the company private brand used primarily for a selected group grocery for almost 30 years.

The second entity is the Volkswagen AG, which is one of the largest car manufacturers in the world. The company is owned by Austrian Porsche and Piëch families. We have chosen the Audi brand as one of the brands in company’s wide portfolio.

Third in line is Berkshire Hathaway Inc, owned by Warren Buffett. As we do not register other brands with which company presents itself, within the analysis the company represents both the parent company and the presented brand.

The fourth entity is the Italian company Exor NV, managed by the Agnelli family, which belongs to the thirty largest corporations according to Fortune magazine. We chose Fiat as the reference brand from Exor portfolio.

The fifth entity is the American giant Ford Motor Company, due to the same name of the parent company and the most important brand in its portfolio, we chose the Lincoln brand as an example for comparison.

The sixth entity is the German company Schwarz Gruppe, owned by Dieter Schwarz. We choose the Lidl brand from its portfolio.

The seventh entity is the German BMW AG, owned by the Quandt family. Similar to Ford, we chose a replacement for the brand that shares the name with its parent company, specifically we chose the Mini brand from our portfolio.

Eighth in line is the American company Cargill, Incorporated, which is currently the largest private company in the world. It is owned by the Cargill family. We chose Wilbur Chocolate from their brand portfolio.

The penultimate entity is the Indian giant Tata Sons Ltd., which is owned by Dorabji and Ratan Tata. We select the Jaguar brand from the brand portfolio.

The last of the entities is Koch Industries, Inc., which is the second largest private company in the United States. We select the Georgia-Pacific brand from its portfolio.

Each of the subjects was thoroughly tested, in the following

Table 2. Overall (Total) online reputation- Parent companies.

No. 1	Subject/Result Sentiment 2	ASA Score (%)	FC Score (%)	TC Score (%)	YC Score (%)	LC Score (%)	Number of Pages Indexed by Google	TOR Score (%)
1.	Walmart Inc.	43	32	27	15	25	282,000,000	28
2.	Volkswagen AG	70	33	3	1	8	64,800,000	23
3.	Berkshire Hathaway Inc.	21	0	0	0	1	41,900,000	5
4.	Exor NV	23	0	0	0	0	258,000	5
5.	Ford Motor Company	77	15	33	75	27	700,000,000	45
6.	Schwarz Gruppe	89	0	0	0	0	82,700,000	18
7.	BMW AG	57	19	16	1	16	89,900,000	22
8.	Cargill, Incorporated	29	0	1	0	13	2,360,000	9
9.	Tata Sons Ltd.	19	0	18	7	10	15,200,000	11
10.	Koch Industries, Inc.	62	0	1	0	1	11,300,000	13

¹ Sorted by order according to Family Capital ranking, based on 2017 revenues in USD; ² The results were rounded to the nearest whole number, therefore, the value of 0 does not necessarily indicate the absence of the subject’s profile on the social network, it may also indicate a very low representation from the point of view of the size of the tribe of followers with respect to competing entities.

and

Table 3. Overall (Total) online reputation- Brands.

No.	Subject/Result Sentiment	ASA Score (%)	FC Score (%)	TC Score (%)	YC Score (%)	LC Score (%)	Number of Pages Indexed by Google	TOR Score (%)
1.	Sam’s Choice	28	9	3	1	6	18,800,000	9
2.	Audi	70	2	52	7	34	1,400,000,000	33
3.	Berkshire Hathaway Inc.	21	0	0	0	2	41,900,000	5
4.	Fiat	−33	10	4	8	27	731,000,000	4
5.	Lincoln	30	3	3	29	0	665,000,000	13
6.	Lidl	46	0	0	1	1	108,000,000	10
7.	Mini	36	31	7	18	2	4,150,000,000	19
8.	Wilbur Chocolate	67	0	0	0	0	2,810,000	13
9.	Jaguar	55	45	31	36	22	610,000,000	38
10.	Georgia-Pacific	36	0	0	1	5	423,000,000	8

we present the partial as well as the total values achieved in our analyzes.

From the point of view of the presented findings, we can state that in the Advanced sentiment analysis (ASA) the parent companies reached maxims at the level of almost 90% of the possible reputation. In contrast, the lows were at a level of just under 20%. The average is around 49% of the potential. In terms of the overall level of reputation, (TOR) entities reach their maximums at 45%, the minimums are at 5%, with an average value of 18%. We will discuss the findings in more detail in the Discussion section. Regarding the data measured for selected brands of parent companies, the situation is as follows:

From the point of view of the presented findings, we can state that in the Advanced sentiment analysis (ASA) the brands owned by parent companies reached maxims at the level of almost 70% of the possible reputation. In contrast, the lows were at a level of just under zero, specifically −33% in case of Fiat. The average is around 36% of the potential. In terms of the overall level of reputation, (TOR) brands reach their maximums at 38%, the minimums are at 4%, with an average value of 15%. As with parent companies, we will discuss the findings in more detail in the Discussion section.

We will therefore proceed to the presentation of the results of the comparison of the parent companies against their brands. Using the following Figure 1, part (a) and part (b), we graphically interpret comparisons of the results of the Advanced sentiment analysis (ASA), as well as a comparison of results of the total level of online reputation (TOR) of the entities and their brands.

In the visualization (b) it is possible to identify significant differences in the total online reputation of entities and their brands, we considered it essential to decompose this shift into the visualization of Social media strength, which is presented through the following Scheme 1.

The analyzed data have been the subject of extensive discussion.

5. Discussion

The discussion is divided into two parts, in the first part we discuss in general the findings from an in-depth analysis of the reputation of the parent companies, then we will focus in more detail on the brands themselves owned by these companies.

5.1. Parent Companies

Firstly, we focused on analyzing the virtual reputation of the subjects using an Advanced Sentiment Analysis (ASA). With regard to each subject, we analyzed the first 10 results of the Google search. Searching by specifying the first parameter, the subject’s own name, we recorded the subjects’ own sites predominantly at the first positions in searching. This is not a surprising fact since the situation is almost the same for all sectors of business. It was expected that the following nine search results will be of a neutral character; however, this was not confirmed in any cases. Neutral search results are mostly various subpages of the homepage or various formal references found on pages related to the subject. Although they do not damage the reputation of the subject, they definitely do not add to its value with respect to the virtual attractiveness. Positive search results related to the searched subject are from the point of view of Internet users more interesting, especially if the users have no direct experience with any of those. The perception of the subject is thus established on very subjective–virtual experience. In this case, the positive sentiment regarding the studied subject was generally associated with the presence of the subject on Wikipedia, encyclopaedic dictionary or subject’s presence on social media. Then we repeated the measurements with one parameter in the Google News Table Based on the results, we can state that our tested subjects can be divided into two groups, those who already mastered they mass media communication, and those who for some reason leave this area outside the mainstream of their activities. From the first group we would like to highlight the Ford Motor Company and Schwarz Gruppe, which in the view of the media presentation leaves nothing to chance. They recorded (as only two subjects from sample) positive sentiment in all positions in Google tab News.

In the second step, we analyzed the reputation of the subjects calculating their competitive strength across all relevant social medias. In this step we found an interesting finding, namely that three out of ten entities do not have an authorized official profile on any of the dominant social networks (except for LinkedIn). One of them, Schwarz Gruppe does not even have such a profile on any virtual mainstream social network. The absence of such profiles of Schwarz Gruppe is well-supported by the well-managed online marketing communications of companies Lidl and Kaufland in its portfolio, however, such conduct is rather exceptional today. It is a compulsory round of any company operating in a turbulent market to create and maintain channels of communication at all levels of its business. The opposite action may give the impression of a negative nature associated with inadequacy, lack of transparency and mystery, all these sentiments are unacceptable to the modern company in 21st century.

In the third step of the analysis, we calculated the overall reputation. The clear winner in virtual world is the Ford Motor Company, the rating of which exceeded 45% of the total value of positive online reputation. The winner from brick world, Walmart Inc. was followed Ford by more than 28% of the total value of positive online reputation. Interestingly enough, that being in competition fight with the best, providing great work is not enough, you need to be just perfect.

5.2. Brands Owned by Parent Companies

In the first step, we focused on the results of an Advanced analysis of the sentiment of ten selected brands belonging to the portfolio of the largest family businesses in the world. The first brand in our order is Sam’s Choice, a brand from the portfolio of Walmart Inc. From the point of view of the brand’s virtual presence in the first 10 Google search results, the brand’s reputation is relatively vague compared to that of the parent organization. From the point of view of the second observation, the situation was even more embarrassing, all the references in the Google News tab were irrelevant, which in the end meant ten neutral sentiments. With the gain only a little more than ten percent of the total potential. Here, the betrayal of neutral sentiment is fully demonstrated, which, although it does not harm the brand, but can cause significant differences in rankings when compared within a larger sample of active subjects. The second analyzed subject was Audi from Volkswagen’s portfolio. Although it did not surpass its parent organization in the general search results category, it nonetheless gains the full number of points in the search results in the News Table As part of our observation, it is a demonstration of exceptional media work of the brand managers, which also helped the brand to be number one among entities in terms of reputation based on search results. Third in line was Warren Buffett’s company Berkshire Hathaway, this company was specific in our measurement as it does not directly have its own brands, so we left it as a reference in our table of results. The fourth in a row was the Fiat brand belonging to the portfolio of Exor NV. Here we can say that, in comparison with the competing brand Audi, in the first observation the Fiat brand achieved only slightly worse numbers, but in the second observation in the category of news, it was the exact opposite of the Audi brand. Fiat recorded negative sentiment in each of the 10 places in search. This earned Fiat the last place among the analyzed subjects within the given category. The fifth in a row was the Lincoln brand, which belongs to the Ford Group’s portfolio. Except for small differences, in the first observation it recorded the same values as its competitors. In the second observation, it completely copied situation of the Sam’s Choice brand from Walmart’s portfolio, where it recorded neutral sentiment in each position. At this point, a trend began to emerge, temporally called the black hole effect, when a strong parent company attracts all the attention with its gravity and makes it significantly impossible for the subsidiaries in the portfolio to grow on their own. Sixth was Lidl, which belongs to the Schwarz Gruppe portfolio. In the first observation, the brand reaches only a little more than 30% of the potential, in the second observation, the excellent result thwarted the occurrence of negative sentiment in the third position in the search results. Seventh in the ranking was the brand MINI belonging to the BMW portfolio. From all samples, MINI is one of two brands, that in the first of the observations scored more than 90 points, which is equivalent to 60% of the total possible online reputation. The chances of a good position were thwarted by the presence of negative sentiment in the third position in the News tab, which dealt with the closure of the local dealership, as well as the amount of irrelevant content probably caused by the general nature of the brand name. The eighth in the ranking was the Wilbur chocolate brand, which belongs to the Cargill portfolio. With a gain of more than 60% of the total potential, Wilbur ranked first in this round of observations. Also, in terms of the overall result within the ASA parameter, Wilbur significantly exceeded the reputation of its parent company Cargill. Here we began to record another of the trends, temporally called the celebrity effect, when a huge corporation focusing out of the mainstream complex (and thus) uninteresting media coverage is overshadowed by a relatively small brand with a solid tradition and a strong mainstream product. The ninth was the Jaguar brand, which belongs to the portfolio of the Indian company Tata. It was the first subject to record almost identical results in both observations. Once again, we are seeing the aforementioned celebrity effect, where the Jaguar brand, the winner of the overall standings, significantly exceeded the level of reputation of its parent company Tata. Our observations are closed by the Georgia-Pacific brand, which belongs to the Koch Industries portfolio. Based on the observations, it can be stated that the results of a predominantly organic nature did not show signs of significant reputational error. In any case, the organic nature of the results left the subject to chance, which was reflected in the negative sentiments recorded in the first, second and fourth place in the search category of the Google News Table This was also due to the fact that the brand only slightly exceeds the potential of the parent company. All relevant data is graphically processed in the Figure 1a.

In the second step, we focused on the point of view of comparing the size of the tribes of individual brands in the environment of virtual social networks. The situation was diverse. The brand with the largest tribe on the most popular virtual social network Facebook is Jaguar. In terms of the number of fans, it has almost half size of the total tribe compared to the sum of the sizes of the tribes of all other brands in our analysis. This finding is not surprising; in any case, it points to the celebrity effect already mentioned in our study, especially considering the fact, that parent company Tata jumped from the numbers on the level of statistical deviation through its Jaguar brand into the first place in our test sample. When it comes to the virtual social network/virtual social media Twitter, the market is dominated by the Audi brand followed by the Jaguar. YouTube once again shows the trend of a black hole effect, where the Ford dominated in the parent company environment with almost 75% of the market, the subsidiary Lincoln with a more modest 29% leaves the first place in the brand environment to the Jaguar. The professional social network LinkedIn is divided almost equally between three brands Audi, Fiat and Jaguar.

In the third step, we focused to the overall numbers. From the point of view of the overall results visualized in Figure 1b, it can be stated, that the overall level of reputation of parent companies is surpassed by only three entities, namely- Audi, Wilbur Chocolate and Jaguar. Jaguar, with a gain of almost 40% of the total possible reputation level, also becomes the number one in our comparison. In terms of the overall level of reputation of its parent company, it surpasses it more than threefold.

This led us to the point at which we can answer our research question.

Is there a difference between the parent company’s e-marketing communication and the brand’s e-marketing communication belonging to that company’s portfolio?

The answer is a strong Yes. Significant differences in the reputation of the parent company and the brand from its portfolio were recorded for selected entities within our sample. In three out of ten cases, namely Walmart, Ford and Tata, there were literary class differences.

6. Conclusions

From the point of view of summarizing the most important findings, we consider it necessary to comment on each of the defined research topics on the subsequently derived research tasks.

Based on our previous research [38,39,40,41] and the findings from our current analysis, we can state that regarding the specific nature of family businesses, given their approaches to branding, the businesses approach branding in a diverse way. It is obvious that in selected companies from the category of family businesses, specific brands literally fulfill the showcase of their business, they become ambassadors of perceived quality. Especially in the case of the Indian concern Tata and the jewel of their portfolio in the form of the British brand Jaguar. As for the traditional and long-established brands in the industry, in our case especially the car manufacturers BMW, Volkswagen and Ford, a consistent approach to building brands is obvious at first glance.

From the point of view of user group/tribes on social networks, we identified significant disproportions across the sample. Coherent access to all mainstream social media is the new norm. Allocating resources to preferred forms of communication is a logical step, but diversification across the market and the media is a necessary reality.

Regarding the issue of the open nature of the Internet and the need for constant monitoring, we have identified several pitfalls of the online market in our analyzes: whether it was a problematic media communication of the Exor concern in the case of its Fiat brand, or the Georgia-Pacific brand from Koch Industries, for which the dominant organic search results leave its reputation to chance. Compared to the positive examples of Audi and Wilbur, it is clear how close monitoring of the environment and optimal use of market opportunities can contribute to gaining a competitive advantage in the form of minimizing the market threat.

Based on the examination of the issue, the recommendations for the research file relevant to the research topics could be summarized as follows:

• Approach a more consistent paths to brand development within the portfolio;
• Build and maintain user tribes on all available communication platforms;
• Apply systems of continuous online reputation analysis in order to prevent reputational losses.

Regarding the research tasks, the online reputation of a highly relevant sample of family businesses was thoroughly examined in the analysis, the online reputation of selected brands from their portfolio was examined in parallel. The results were compared with each other and then the specifics were interpreted graphically and also discussed in an extensive discussion. Among the most interesting findings we could choose the following:

• Black hole effect, when a strong parent company attracts all the attention with its gravity and makes it significantly impossible for the subsidiaries in the portfolio to grow on their own;
• Celebrity effect, when a parent corporation focusing out of the mainstream complex (and thus) uninteresting media coverage is overshadowed by a relatively small brand with a solid tradition and a strong mainstream product;
• Risk of organic results, when predominantly organic nature of media communication results did not show signs of significant reputational error. Anyhow in any case, the organic nature of the results left the subject to chance regarding turbulent media market.

From the point of view of general findings, it is possible to direct the recommendations predominantly to the research group. Thus, based on the findings, postulate the results dominantly for globally known family businesses. In our research, when choosing the research set, we took into account the fact that family businesses, regardless of size and due to their specifics (in terms of ownership, management and human capital) show higher sensitivity when it comes to sustainable management of corporate reputation. As this was an assumption, and its confirmation will be the subject of further investigation, it is possible to approach the file as representatives of global corporations. We believe that the findings and identified practices are relevant to both family businesses and corporations with different ownership. Also, the phenomenon of the size of the subject is the subject of controversy. The nature of the Internet, as we presented in the theoretical study in the first part of our paper, largely eliminates differences between entities in terms of reputational risk. Of course, large entities are certainly more visible, but in terms of the open nature of the Internet and an infinite number of variables, the likelihood of reputational damage through an unsatisfied customer (but also user, disappointed fan, respondent, etc.) is as dangerous for a large corporation as for a small local enterprise. The online environment can multiply both positive and negative appeals, for all of which we can mention Jeff Jarvis and the Dell Hell affair. The conclusions of our qualitative research have the ambition to acquire a universal nature, at least in terms of defining the preconditions for further research.

7. Limitations

From the point of view of limitations, we consider it necessary to note that with regard to data collection and processing, the research itself took place in the first half of 2020, and so the temporal informative value of the data reflects this period. Due to the nature of the research sample, we do not assume that seasonality will affect the data to a dominant extent.

From the point of view of the selected research group and the subsequently selected sample, it is possible to mention the limitations from the point of view of the size and scope of the subjects we have selected. In our sample, global representatives from the family business environment are represented by corporations with billions in turnover. It can therefore be concluded that the market power of these entities can significantly affect the universality of the findings with respect to the whole research population. However, we believe that due to the nature of the environment and the factors of the Internet market, all subjects in the sample are subject to the same specifics in the form of uncertainty and immense variability of the environment as such.

Another possible limitation is the qualitative nature of one’s own research; nonetheless, due to the attractiveness of the topic and the dynamics of the industry, further research is necessary.

Last but not least, we consider it necessary to mention the overall uncertainty of the issue of family business as such. Due to the nature of the definitions, this is a relatively diverse topic, as the specifics determining the classification of a family business are inconsistent across countries. It is possible to start from some fundamentals, as far as the starting points are concerned. However, the absence of deeper and especially universal starting points greatly complicates applied research. Therefore, in our opinion, it is necessary to continue basic research and strive for a continuous shift in knowledge of the issue as well as produce empirical material suitable for application in business practice.