A study of managers’ perceptions

“Blue Chip” chararcteristics: A study of managers’ perceptions

Chye, Koh Hian

Introduction

The word “blue chip” originated from gambling, where it is used to refer to the highest value gambling chip (Pennant-Rea and Emmot, 1990). Today, the term has found common usage not only in the stock market, but among business administrators and academics as well. With the term being used in a variety of contexts, the fundamental perception is that it refers to companies that are, in some way, superior.

However, there is no precise definition in the literature nor among investment professionals as to what qualifies as a “blue chip” company, although the tag seems to be applied to the stock market’s larger, betterknown, and more established companies. As Pennant-Rea and Emmot (1990) aptly put it, “blueness is in the eyes of the beholder”.

The “blue chip” status seems to be a dynamic rather than static concept – a company considered to be a “blue chip” in the past may no longer be regarded as one today. However, banks and stock exchanges often continue to regard, rightly or wrongly, some companies as “blue chips” long after they have ceased to deserve the label. Rolls-Royce, for instance, still held “blue chip” status until shortly before its collapse in 1971. In the United States, Chrysler and Continental Illinois Bank are examples of “blue chip” companies getting into financial troubles. To cite a very recent example, the now-defunct Barings Bank was considered a “blue chip” until the Leeson debacle (Ladbury, 1995).

As existing businesses grow and new ones start up, there is an increasing need for classifying companies and for classification guidelines for the “blue chip” tag. For example, equity or debt providers may want to assess the quality of the company they are considering. Analysts and fund managers may require a standard guideline to classify companies as “blue chips” to minimise the risks of their portfolios and safeguard their investment decisions with proper justifications. Further, a company’s management may want to benchmark their company characteristics against “blue chip” criteria to formulate goals and identify shortcomings.

Interestingly, there exist accolades conferred upon companies for possessing “blue chip” characteristics. For instance, in the United States, annual awards are accorded to “blue chip” enterprises. For the Blue Chip Enterprise Initiative Award, small businesses are judged on their quality of management and their ability to overcome extraordinary challenges and become stronger, where strength is measured with reference to earnings and growth potential. In a similar vein, the Blue Chip Enterprise Award honours businesses that overcome adversity and become stronger. (See the three articles written by Nelton in 1994).

Literature Review

Several authors have mentioned certain criteria for a stock to qualify as a “blue chip” investment. The New Shorter Oxford Dictionary (Brown, 1993) defined “blue chip” stocks as common stocks of “well-known” companies with a history of profit growth and dividend payment as well as “quality management of products and services”. In the Dictionary of Finance and Investment Terms (Downes, 1985), a “blue chip” is a common stock of a nationally known company reputed for its quality management. In the International Dictionary of Securities Industries (Valentine, 1989), it is defined as “an equity share of a large, safe and prestigious company”. These dictionary definitions are somewhat consistent with Stafford (1987), who opined that “blue chips” are shares in “very sound, well-established and usually large companies”, citing Prudential, Unilever and ICI as examples.

In contrast to these somewhat qualitative definitions, Belsky (1993) gave a more quantitative interpretation by listing the following requisite characteristics of “blue chip” companies: (1) estimated revenues of at least US$300 million, (2) solid balance sheets with debt of no more than 40 per cent of total capital, (3) likely profit growth of at least 15 per cent, and (4) projected share price gains of 20 per cent or more. A fundamentally similar set of criteria was enunciated by Willis (1993), although the numerical conditions laid down were different. Essentially, Willis (1993) asserted that “blue chip” companies are companies that dominate niches in their markets and that are capable of solid long-term earnings growth potential. Both Belsky (1993) and Willis (1993) considered “high sales turnover”, “high profit growth” and “low debt-equity ratio” to be important characteristics of a “blue chip” company. The similarity of characteristics chosen is underscored by the general perception of “superiority” that these characteristics convey.

Consistent with both Belsky (1993) and Willis (1993),, Hardy (1987) concurred that the best stocks are those of companies that have little or no debt, inferring that a low debt-equity ratio may provide some evidence of a company’s “blue chip” status. However, he cautioned that this cannot be the sole criterion; lack of debt may not be a mark of quality if management is overly conservative and not willing to expand as rapidly as it could with borrowed funds. Smart managers “maintain a judicious balance between debt and equity capital”. Profitability and stability were also highlighted by Hardy (1987) as two key important criteria in determining which are the best stocks.

Bailey (1994) suggested that the two broad areas that are to be considered in picking a “quality stock” are income and growth. In addition to these two key areas, investors should also take into account the risks they are prepared to take. The lowest-risk shares can be found among those of the large, well-established companies (the “blue chips”) which make up the FIF-SE 100 index. Bailey (1994) further pointed out the importance of looking at the Price Earnings Ratio (PER). A high PER is more characteristic of a “blue chip” stock, as it indicates that “investors expect profits to grow in the long run”.

On the characteristic of “high share price growth”, some authors further suggest that a “blue chip” stock, whose price usually shows an upward trend, will also tend to remain stable in times of recession. Sivy (1994) in giving his analysis of the United States economy for the period winter 1994 to spring 1995 – a period in which inflation and interest rates were rising and the stock market was bearish – predicted that “blue chip” stocks would make little headway. He also made the point that “blue chip” companies are generally capable of weathering harsh economic conditions and remaining stable.

The literature also shows that not all authors are fundamentally congruent with one another with respect to the characteristics of a “blue chip”, some to the extent of holding opposite views. For instance, Holden (1988) considered the Nippon Telegraph and Telephone Corporation (NTT) the ultimate “blue chip” based on its hefty price of US$17,537 a share, thus inferring that share price is an important determinant of what constitutes a “blue chip” company. However, Weiss and Lowe (1988) contended that price has little to do with value, and even less to do with the definition of a “blue chip” stock. Price, they argued, is an important measure of “blue chip” quality only as it relates to dividends, earnings or book value. In their opinion, “blue chip” companies are those that are managed by experienced leaders. Also, their products and services are well-known and widely distributed, and are often sold in international markets, especially in the lesser-developed countries where growth potentials are still extraordinary. Weiss and Lowe (1988) also emphasised that “blue chip” companies, more often than not, have sophisticated research centres, elaborate advertising programmes, and a long history of profitable progress. They are also usually the first stocks to rise in the bull market and the last stocks to fall when the market declines.

A few authors were somewhat unclear in their definition of the “blue chip” concept. Schilit and Schilit (1992), for instance, did not elaborate on the “blue chip” concept in their book ironically entitled Blue Chips and Hot Tips. Other than stating that “blue chip” companies are “established companies” (citing Coca Cola, General Electric, Procter & Gamble, among others, as examples), the authors were silent on the explication of the “blue chip” concept. Rather, they focused on “red chips”, which they defined to be “hot emerging growth companies”, such as Compaq, Microsoft and LA Gear, which are companies that are generally higher in risk, but often higher in returns (relative to “blue chips”). Throughout the book, Schilit and Schilit (1992) seem to suggest that companies go through some form of evolution, in which “blue chip” status must be preceded by “red chip” status. The inference is that “blue chip” companies are companies that have stood the test of time in that they have proven their mettle. Lynch (1992) was likewise nebulous in his definition of the “blue chip” concept, contending that the characteristics of a “blue chip” really depend on the industry a company is in. He was sceptical of the view that stock price growth and stability (in times of recession) were conclusive “blue chip” characteristics, supporting his cynicism with the example of starkly contrasting stock price movements of two “blue chips” in the 1980s – Ford whose stock price fluctuated wildly and Bristol-Myer whose stock price remained stable during the same period.

In summary, there seems to be a general lack of congruent views in the literature on the characteristics of a “blue chip” company. In their attempts to provide guidelines to gauge “blue chip” characteristics, some authors even held fundamentally contrasting viewpoints.

Research Methodology

This study attempts to identify the characteristics of a “blue chip” company as perceived by managers. The research methodology employed is summarised below.

Description of Sample

The population under study comprises middle-level managers in Singapore. They can be deemed as persons who are aware of the “blue chip” concept as it applies to the stock market and who have some idea or opinion of a “blue chip” company. Ideally, the respondents should have some logical and explicable explanation of what they perceive a “blue chip” company to be. In this respect, they should be educated in business, business persons, business professionals or discerning investors.

MBA participants (both past graduates and present students) of the Nanyang Technological University (NTU) were chosen as the target group for this study. They represent an important section of middle-level managers in Singapore and form an informed group who is expected to be more aware of, if not more involved in, the stock market. The study involved administering a mail questionnaire survey to a random sample of the MBA participants.

Survey Questionnaire

The survey questionnaire comprises two major sections. The first section requires the respondent to rate, on a five-point scale (1 = Extremely Important to 5 = Not Important), 16 listed “blue chip” characteristics in terms of how important they are in defining a “blue chip” company. The list of “blue chip” characteristics included in the study was identified in the following manner.

As indicated in the literature review section, published literature does not provide an adequate definition of the specific characteristics of a “blue chip” company. However, several authors, within the context of their articles, have stated characteristics that they believe characterise “blue chip” companies (see, for example, Belsky, 1993 and Willis, 1993). In addition to these, a telephone interview was conducted to solicit perceptions of “blue chip” characteristics in the Singapore context. For this purpose, 35 MBA participants were randomly selected for the interview and were asked what characteristics they would associate with a “blue chip” company. Generally, local perceptions were consistent with the literature, but two characteristics not found in the latter were highlighted by the MBA participants, namely “close links with government” and “great degree of regionalisation”. Based on these findings and the information obtained from the literature, the following list of “blue chip” characteristics was drawn up:

(1) High sales turnover

(2) Low debt-equity ratio

(3) High stability of share price during recession

(4) High profit growth

(5) Close links with government

(6) Great degree of regionalisation

(7) High market capitalisation

(8) Long history of establishment

(9) High dividend yield

(10) Growing stage of industry life cycle

(11) High growth of share price

(12) Good reputation and quality of management

(13) Great emphasis on research and development

(14) High price-earnings ratio

(15) High regard of company in business circles, and

(16) Large market share.

The second section of the survey questionnaire requests demographic information about the respondent such as gender, age, marital status, educational background, functional area and income. This facilitates developing a profile of the respondents.

Research Hypotheses and Statistical Methods

To study the perceptions of “blue chip” characteristics, the following two null hypotheses are tested. The first null hypothesis (on absolute importance) can be stated as follows:

Ho,: The 16 listed characteristics are not important characteristics of a “blue chip” company.

This null hypothesis can be evaluated using the t-test of means to test if each mean importance rating is significantly less than 3 (Ha), where 3 = Important on a scale of I to 5 in decreasing order of importance. For each listed “blue chip” characteristic, rejection of Ho, indicates that the characteristic is an important “blue chip” characteristic.

The second null hypothesis (on relative importance), which is related to the first, can be stated as follows:

Ho 2: The 16 listed characteristics are equally important characteristics of a “blue chip ” company.

This null hypothesis can be evaluated using 1 -way analysis of variance (ANOVA) to test if the mean importance ratings of at least two of the 16 listed “blue chip” characteristics are significantly different from each other. Rejection of Ho 2 indicates that the importance of the listed characteristics differs significantly in terms of defining “blue chip” companies. To assess the differences further, multiple comparisons (Duncan multiple range test) is performed. In other words, the Duncan multiple range test is used to determine the relative importance of the 16 characteristics in defining a “blue chip” company. In the data analysis, the sample mean importance rating measures the mean importance of each characteristic in defining the term “blue chip”.

Results and Implications

A total of 350 survey questionnaires was administered to a random sample of MBA participants at the beginning of June 1995. At the end of June 1995, 110 usable questionnaires were returned via stamped, selfaddressed envelopes. This gives a response rate of 31.43 per cent.

Profile of Respondents

Descriptive statistics of the demographic variables are summarised in Table 1. As can be seen, 83 (75.5 per cent) of the respondents are male and 74 (67.3 per cent) are married. The majority (61 or 55.5 per cent) have annual income of at least S$55,000 and the average age is 33.03 years (standard deviation = 4.54 years). As for educational background, half of the respondents (55 or 50 per cent) have engineering background and 32 (29.1 per cent) have accounting and business background. Finally, most of the respondents are working in the functional areas of engineering/production (41 or 37.3 per cent), accounting/finance (24 or 21.8 per cent) and marketing (13 or 11. 8 per cent).

T-test Results

Respondents are requested to rate on a five-point scale (1 = Extremely Important to 5 = Not Important) 16 listed “blue chip” characteristics in terms of how important they are in defining a “blue chip” company. The correlation matrix of the importance scores of the 16 characteristics is summarised in Table 2. As can be seen, only low and moderate correlations are observed. This suggests that the respondents can and do differentiate among the 16 listed “blue chip” characteristics as well as their importance in defining a “blue chip” company.

To assess if the listed characteristics are significantly associated with the “blue chip” concept, the t-tests of means are performed. That is, the mean importance rating of each characteristics is tested against the benchmark of 3 (where 3 = Important). The alternate hypothesis is Ha: Mean

The t-test results are summarised in Table 3. At a 0.05 level of significance, the following characteristics are significantly associated with a “blue chip” company: high sales turnover, high stability of share price during recession, high profit growth, great degree of regionalisation, high market capitalisation, high dividend yield, high growth of share price, good reputation and quality of management, great emphasis on research and development, high regard of company in business circles and large market share. The following characteristics do not appear to be significantly associated with a “blue chip” company: low debt-equity ratio (p-value = 0.9999), close links with government (p-value = 0.9883), long history of establishment (p-value = 0. 1158), growing stage of industry life cycle (pvalue = 0.9981) and high price-earnings ratio (p-value = 0. 1798).

To investigate the relative importance of the 16 listed characteristics in defining a “blue chip” company, I-way ANOVA and Duncan procedures are performed. ANOVA and Duncan Results The 1-way ANOVA results are presented in Table 4. As shown, the model is significant at a 0.05 level of significance (p-value = 0.0001). In other words, there are significant differences in the importance of the 16 listed characteristics with regards to the “blue chip” concept. This finding is consistent with indications of the t-test results.

The Duncan multiple range test is performed to analyse the mean importance ratings further. In particular, the Duncan groupings provide further insight into the perceptions of the respondents by providing statistical evidence as to which mean importance ratings are significantly different from the others. That is, characteristics belonging to the same Duncan grouping have means (importance) that are not significantly different from each other. Conversely, characteristics belonging to two different Duncan groupings have means (importance) that are significantly different from each other, provided the characteristics do not belong to both the Duncan groupings simultaneously (for overlapping Duncan groupings).

The Duncan results are also summarised in Table 4. As can be seen, good reputation and quality of management is the single most important characteristic of “blue chip” companies (mean importance rating = 1.55). The next group of most important “blue chip” characteristics comprises high stability of share price during recession, high regard of company in business circles, high profit growth and large market share (with mean importance ratings of 1.97, 2.02, 2.04 and 2.17, respectively).

This is followed by high sales turnover, high market capitalisation and high dividend yield (with mean importance ratings of 2.30, 2.53 and 2.55, respectively) as the next group of important “blue chip” characteristics. At the other end of the importance scale, close links with government (mean = 3.25), growing stage of industry life cycle (mean = 3.30) and low debtequity ratio (mean = 3.51) appear to be unrelated to the concept of “blue chip”. The t-test results have also indicated that high price-earnings ratio (mean = 2.91) is not a “blue chip” characteristic.

Implications

The results suggest that good reputation and quality of management, high stability of share price during recession, high regard of company in business circles, high profit growth and large market share are the critical characteristics that determine whether a company is a “blue chip”. Interestingly, some of the most important “blue chip” characteristics are qualitative in nature (for example, good reputation and quality of management and high regard of company in business circles). It is noted that good reputation and quality of management is the most important “blue chip” characteristic; it is significantly more important than all the other listed characteristics (see also Brown, 1993; Downes, 1995; and Weiss and Lowe, 1988). This underlies the critical importance of management in making or breaking a company.

In addition to qualitative characteristics, high share price stability, high profit growth and large market share (which can be considered quantitative in nature) are also among the most important “blue chip” characteristics. This finding is consistent with the existing “blue chip” literature (for example, Belsky, 1993; Willis, 1993; and Sivy, 1994). Coupled with the previous finding, it can perhaps be assumed that with a good management, the other things (such as high profit growth, high share price, large market share… etc) will result.

At the other end of the importance scale, financial ratios such as high price-earnings ratio and low debt-equity ratio do not appear to be related to whether a company is a “blue chip”. This finding is contrary to the suggestions of some authors (for example, Belsky, 1993 and Bailey, 1994). It may be that the price of a share is influenced by market sentiment and other external and/or short-term factors and therefore does not necessarily reflect the fundamental value of the share. Further, the debt-equity ratio is derived primarily from historical figures which may not reflect the current situation and too low a debt-equity ratio may actually give negative signals (for example, the company is too conservative and not utilising its debt capacity). See also Hardy (1987).

Close links with government and growing stage of industry life cycle appear to be irrelevant in defining “blue chip” companies too. That is, good relationship with the government alone does not guarantee corporate success and “blue chip” companies can develop in various stages of the industry life cycle. Conclusion In interpreting the findings of the study, it is important to bear the following limitations in mind. First, the MBA population in the Nanyang Technological University was used to draw a sample from which the perceptions of the characteristics of “blue chip” companies were derived. The MBA sampling frame may not be representative of the population of middle-level managers in Singapore. Hence, the findings may be biased to the extent that perceptions of the MBA participants may differ from the target population of middle-level managers.

Second, the usual limitations of a self-report survey apply (that is, nonresponse bias and response bias). Non-response bias may come about when sampled subjects who are significantly different from the respondents do not respond. However, the usable response rate of 31.43 per cent can be considered acceptable. Response bias may be introduced when a respondent’s perceptions are biased by the background characteristics of the respondent or the study. This, however, is mitigated by the non-sensitive nature of the survey, provision of stamped self-addressed return envelopes, anonymity of the respondents, and promised confidentiality of the responses.

Third, the findings may lack generalisability (that is, external validity). In particular, they may not be applicable to a different population (for example, investors or stock brokers/dealers) or geographical region (for example, managers in Japan or Australia).

Finally, in this concluding section, it is appropriate to suggest directions for future research. In particular, future research can extend the study to other populations, geographical regions and contexts. Comparisons of such findings can be useful in understanding the “blue chip” concept better. Also, future studies can look at other “blue chip” characteristics that are not included in the current study (for example, well-diversified business portfolios, good management-employee relations, high level of corporate social responsibility … etc).

This study investigates “blue chip” characteristics from an empirical perspective. Current writings focus primarily on normative/theoretical considerations. It is hoped that in spite of the limitations highlighted earlier, the study can contribute to the existing “blue chip” literature.

References

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Koh Hian Chye

Associate Professor and Vice Dean

Nanyang Business School

Chan Seet Meng

Pranjal S Gupta

Sujata Ramakrishna

MBA Graduates

Nanyang Business School

Copyright Singapore Institute of Management 2000

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