Managerial decisions on the nature and scale of corporate activity diversification in the construction sector

Ansoff ’s four corporate growth strategies can be divided into two groups (Pierscionek, 1966):

expansion strategies (market penetration, development and product improvement);

The choice of one of the two options must be based on the analysis of internal and external business conditions because namely this analysis determines corporate growth prospects. The above-mentioned strategies reveal long-term sale forecasts based on the trends in national economic policies, international indicators, business specifics, competition, cost fluctuations and so forth. If it turns out that expansion strategies do not provide any opportunities to develop the current business and thus increase the volume of products or services, or if there is a risk of a decline in a company’s market share, then the company should further grow through diversification.

As already mentioned before, Ansoff ’s concept of a strategy choice is based on the analysis of internal and external business environment (Ansoff, 1957) (Fig. 2).

Fig. 2

On the other hand, it is widely acknowledged that diversification, as a corporate growth strategy, plays an increasingly important role in business management, and a growing number of international corporations rely on in their activities. For instance, in recent years, it has been implemented by more than 94 per cent of the world’s top 500 corporations (Li et al., 2013). The importance of diversification has grown significantly in the context of business internationalisation, which is particularly noticeable in developing economies (Chen et al., 2014).

Many previous studies address the impact of diversification on different corporate activity aspects: reinvestment strategies (Mackey & Barney, 2013), capital costs and structure (Hann et al., 2013), the effects of banking activity diversification on stock markets (Sawada, 2013), company’s value (Kuppuswamy et al., 2014; Hyland, 2003; Jara-Bertin et al., 2015; Nazarova, 2015), the profitability of business operations (Zahavi & Lavie, 2013; Becerra & Santaló, 2006; Santarelli & Tran, 2016; Knapková et al., 2019; Bilan et al. 2019), and the need of technologies for the implementation of the diversification process (Li et al., 2013; Wang et al., 2014). Many studies focus on the impact of corporate ownership on the processes of diversification (Chung, 2013; Hernández-Trasobares & Galve-Górriz, 2016; Schmid et al., 2015; Sanchez-Bueno & Usero, 2014). Geographical diversification of business companies (Chonghui et al., 2013; Thoumrungroje & Tansuhaj, 2005; Gaur & Delios, 2015; Qian et al., 2013; Yahaya et al., 2009; Mauer et al., 2015), diversification risks (Busse et al., 2014; Yücel & Önal, 2015), the processes of diversification in business networks (Kim et al., 2014; Chen & Jaw, 2014) are areas of continuous interest among researchers.

Internal environment assessment is based on the SWOT analysis, i.e. identification of a company’s strengths, weaknesses, opportunities and threats, while the main purpose of external environment assessment is to identify what opportunities a company has to capture new markets. In the context of increasing complexity and dynamics of national and global economic systems, the analysis of enterprise’s environment requires application of sophisticated methods grounded in the foresight logic (Nazarko et al., 2007a; Nazarko et al., 2007b; Ejdys et al., 2019). Such analyses are relevant to all economic sectors (Nazarko et al., 2015), including construction. The analysis should also comprise assessment of the potential of a new business, the synergies expected from capturing new markets, etc. (Ginevičius, 1998).

The problem of the scale and nature of diversification covers several aspects: first, identification of the scale or, in other words, the number of simultaneous activities; second, the technological relation among the conducted activities.

The basis for tactical actions while implementing a particular diversification strategy is the so-called corporate core skill (Wrigley, 1970). This concept refers to the general ability of a company to accurately and effectively accumulate the knowledge of markets and technologies for profit, growth, and thus external adaptation. Basically, the core skill reflects a company’s professionalism and its strategic potential. It determines how many and what types of activities a company can conduct considering the situation in the market.

The scale of diversification, or the number of simultaneous activities, reflects the quantitative nature of the diversification process, while the technological relation among the conducted activities is linked to the technological similarity of these activities. In this sense, a distinction is made between related and unrelated diversification. Related diversification refers to the expansion of the new products manufactured or sold within the corporate core skill. Unrelated diversification, on the contrary, refers to the inclusion of such products that require the skills outside the corporate core skill. The latter type virtually reflects the qualitative side of diversification.

All aspects of the scale and nature of diversification are closely linked together (Fig. 3).

Fig. 3

Figure 3 proposes that both quantitative and qualitative parameters of the process of corporate activity diversification depend on the market situation. A market can be growing, shrinking or steady. When the market is growing, the demand for current products is so high that a company can profitably raise its production volumes without high risks. In this situation, there is no point in raising the number of unrelated activities. Previous research also confirmed that the degree of corporate activity diversification is declining in growing markets (Ginevičius, 2008a).

In shrinking markets, companies find themselves in the opposite situation because the demand for current products is significantly declining. Companies can only survive by entering new, less crisis-affected markets with their new products. Thus, when markets shrink, the importance of corporate production diversification grows.

Stable markets combine the features of both growing and shrinking markets. Entering new markets is always associated with various extra costs, which means a higher risk not to achieve a desired economic result. On the other hand, an excessive narrowing of the production program may also have a negative effect because a company becomes too sensitive to demand fluctuations.

An economically reasonable number of simultaneous activities can be estimated by employing a correlation-regression analysis, the basic model of which is written as follows: y = f(x). Here y represents the results of commercial-economic activities (operational efficiency) in diversified companies, e.g. profit; x marks the number of activities. The research in the construction sector allowed to assess the impact of the scale of diversification on operational efficiency (Fig. 4) (Ginevičius, 2005).

Fig. 4

Figure 4 indicates that the companies which have not changed the profile of their activities as well as the ones that unreasonably expanded this profile record lowest operational efficiency, which was confirmed by the results of the research in the construction sector. The general trends of the diversification process also show that the highest operational efficiency is achieved by concentrating corporate activities in the areas not too remote from the corporate core skill.

Previous research indicates that before the global financial crisis of 2008–2009, when the construction sector was growing steadily, companies had started narrowing their profiles because they had been making large profits from their core activities and therefore did not see any need to expand their activities to other, unrelated markets. But when the sector began to shrink, companies started expanding their profiles to have independent sources of revenue and thus offset their losses in the core market.

As can be seen in Figure 4, when the market in the EU’s developing states is steady, the rational number of corporate activities in the construction sector amounts to 2–4. There is a trend that this number grows over time, which means that the quality of management in diversified construction companies is also rising. In any case, the number of simultaneous activities is significantly affected by the size of a company. These are “the two sides of a coin”: when the size of a company grows, the degree of corporate activity diversification also increases, and vice versa – a rising degree of corporate activity diversification leads to the growth in the size of a company.

There exists a close relationship between the number of activities and the nature of diversification, i.e. between quantitative and qualitative sides of diversification: when the number of activities grows, companies move away from their core skills, which means an increase in the scale of unrelated diversification.

A generalized picture of the corporate activity diversification process depending on a market situation is presented in Figure 5.

Fig. 3

Figure 5 indicates that a project of corporate activity diversification will be successful, if a company is able to develop an appropriate strategy and assess the whole set of conflicting conditions and, most importantly, to anticipate the changes in the market.

Organisational management conditions for the success of diversification projects should also be considered. The experience of diversified companies confirms the fact that diversification is a complex and controversial phenomenon since a large number of diversification projects fail, especially in the early stages of their implementation. The main cause of this failure is that a corporate organisational management structure does not correspond to the philosophy of diversification as the development strategy. Until the stormy development of the diversification processes between 1950 and 1970, corporate management had been dominated by an exclusively functional structure where particular management units used to specialize in the performance of well-defined functions only. Such structures were reasonable when a company focused on the release of one or several closely-related products, i.e. when a company was specialized. However, because diversification processes were developing faster than the restructuring of corporate organisational management systems, the management of diversified companies became inefficient, which led to low operational efficiency and even bankruptcies. It was later realized that the release of new products refers to different material-technical resources, especially in terms of technologies, i.e. it refers to new knowledge that is different from the core skill knowledge. This perception, in turn, led to the transition from a functional organisational management structure to a divisional one, i.e. formation of autonomous management units based on the released products. The main feature of this structure was the focus on different product markets.

Some scientific studies propose that the strategy of diversification seems controversial in terms of a modern organisation. It is considered that modern organisations must focus on the use of knowledge and thus develop the level of professionalism which ensures a successful competition. The development of professionalism, in turn, can only be ensured by an appropriate degree of specialization. This contradiction is fully resolved by employing a divisional organisational management structure since divisions specialize in the release of a particular product only.

The divisional organisational management structure allows a diversified company to significantly reduce its management costs by taking advantage of synergies (Hitt et al., 2001). Today, the commercial and economic performance of diversified companies, especially large ones, depends exclusively on the quality of their management.

Measuring the level of diversification is a fundamental problem in the diversification process that is far from being fully resolved. The theory of diversification has expanded the extent of both unrelated and related diversification. This issue earns special attention in scientific studies. In order to manage the diversification process, it is necessary to quantify its level at a certain point of time. Methods for measuring unrelated diversification are most developed. They are all based either on the number of activities or estimation of the variation between the number of activities and the volumes of work. The first approach is based on the diversification index system proposed by M. Gort (Gort, 1962; Bühner, 1985; Wolf, 1995a, 1995b), while in the second case, the diversification index is estimated by the following principal expression (Wolf, 1995a, 1995b): (1)Dj=∑i=1nωiPi,{D_j} = \sum\limits_{i = 1}^n {{\omega _i}{P_i}} , here Dj – diversification index; Pi – the relative size of activity i; ωi – the significance of activity i; n – the number of activities.

By equating the significance of a particular activity to its relative size (ωi = Pi), the Herfindahl concentration index is obtained: (2)DH=∑i=1nPiPi=∑i=1nPi2{D_H} = \sum\limits_{i = 1}^n {{P_i}{P_i} = \sum\limits_{i = 1}^n {P_i^2} }

Since production concentration is the opposite of production diversification, the Herfindahl index is transformed to obtain Berry diversification index (Berry, 1971): (3)DB=1−DH=1−∑i=1nPi2{D_B} = 1 - {D_H} = 1 - \sum\limits_{i = 1}^n {P_i^2}

For measuring unrelated diversification, the entropy and Uton indices are also used (Jackuemin et al., 1979; Palepu, 1985; Uton, 1977). (4)ED=∑i=1nPiln1Pi{E_D} = \sum\limits_{i = 1}^n {{P_i}\ln \frac{1}{{{P_i}}}} (5)Wu=2∑i=1niPi−1{W_u} = 2\sum\limits_{i = 1}^n {i{P_i} - 1} here: Ed – diversification entropy index; Wu – Uton diversification index.

The main shortcoming of the above-discussed methods applied for measuring diversification is insufficient methodological substantiation. Gort indices are imperfect because they are linked to limited classification systems, i.e. they do not cover all areas of corporate activities and do not estimate the variation among them.

The value of the most common Berry index is directly affected by the variation in the volumes of work, thus this index does not consider the number of activities, though namely the latter determines the changes in the organisational management structure in a diversified company.

For improvement of the Berry index, the following diversification measure is proposed (Ginevičius, 2009): (6)DG=1−1∑i=1n1−Pmax1−Pi{D_G} = 1 - \frac{1}{{\sum\limits_{i = 1}^n {\frac{{1 - {P_{\max }}}}{{1 - {P_i}}}} }} here: DG – unrelated diversification index; Pmax – the relative size of the largest activity by volume.

In order to illustrate the situations in Figure 5 with a real example, a typical period of 2005–2019, which incorporates all three market stages (periods 2005–2007–2008–2009 and 2010–2019, respectively), will be considered.

Period 2005–2007 represents a growing market characterised by the tendency that Lithuanian construction companies, which generate a substantial share of the country’s GDP, were granted major restriction-free bank loans on exceptionally good terms, which led to a disproportional expansion of the construction sector and a “price bubble” formation. Construction companies did not need to expand their business profiles as they earned steady revenues from their core activities, which is evidenced by the low values of diversification indicators (see Table 1).

The small effect of diversification on corporate commercial performance is also confirmed by the results of the correlation-regression analysis (see Table 2).

As can be seen in Table 2, over the period 2005–2007, the effect of diversification on corporate commercial profitability was weak.

Period 2008–2009 represents the global financial crisis characterised by the burst of the “price bubble”, i.e. the construction sector shrank significantly, corporate revenues fell, and corporations had no reserves to repay bank loans. The situation resulted in the bankruptcies of a significant number of construction, retail and wholesale companies which possessed no independent sources of revenue, i.e. they had failed to expand their business profile on time. On the other hand, the other part of business companies were aware of the impending danger and prepared for it accordingly: they diversified their activities to introduce new products to the markets less affected by the crisis, which is evidenced by the higher values of diversification indicators (see Table 1) as well as the results of the correlation-regression analysis disclosing the links between corporate commercial performance and the degree of diversification (see Table 2).

The third period (2010–2019) is characterised by a well-established market. In this situation, companies achieve their best commercial results when they, on one hand, do not unreasonably narrow their business profiles, on the other hand, do not develop new products unreasonably remote from the core product, and can therefore exploit the same technologies and knowledge without any need to change their organisational management structures, etc. This is evidenced by the values of the diversification indicator as well as the results of the correlation-regression analysis (see Tables 1 and 2).

Estimation of the scale of unrelated diversification is based on the presumption that corporate activities are not related either technologically or in any other way. But the reality is usually different, so the actual picture of diversification is distorted. Thus, to further improve the quantitative estimation of the scale of diversification, new methods need to be developed.

The methods applied for qualitative estimation of the scale of related diversification are even less developed, though this aspect of diversification is extremely important considering the fact that different corporate activities are technologically or in any other way related to the core activity. Probably due to the difficulty to quantitatively estimate these relations, the scale of related diversification is commonly measured by employing the discrete-categorical measure (Wrigley, 1970). The essence of this method is that all companies are divided into four categories: single product, dominant product, related product and unrelated product. Practical application of this concept revealed a number of shortcomings, which led to its subsequent refinement by Rumelt (Rumelt, 1974). Nevertheless, even this methodology does not provide a reliable basis for measuring related diversification. The latest methods for measuring this type of diversification include Varadarajan and Ramanajan’s (Varadarajan & Ramanujan, 1987) suggestions which, however, are highly subjective.

The main drawback of the above-discussed methods developed for measuring the scale of related diversification is that they do not consider quantitative estimation, which is considered in the following index (Ginevičius, 2012): (7)Ds=1−∑i=1nWiPmaxPi1−Pmax{D_s} = 1 - \frac{{\sum\limits_{i = 1}^n {\frac{{{W_i}}}{{{P_{\max }}}}{P_i}} }}{{1 - {P_{\max }}}} here: Ds – index of the related corporate activity diversification; Wi – aggregate strength of the relationship between the ith product-market combination and the core product-market combination; Wmax – the largest possible value of the relationship between the ith product-market combination and the core product-market combination.

Formula (7) indicates that the related diversification measurement is based on the quantitatively expressed strength of the relationship between all product-market combinations and the core product-market combination.

Average values of the indicator of related diversification estimated for construction companies in different periods of the term under consideration are presented in Table 3.

The low value of unrelated diversification (see Table 1) and the high value of related diversification (see Table 3) indicate that when the number of simultaneous activities is decreasing, companies are moving closer to their core products, i.e. they exploit the same production technologies. All this is typical of a growing market.

When the degree of unrelated diversification increases, the degree of related diversification decreases (see Tables 1 and 3), which means that when the number of simultaneous activities declines, companies move away from their core production technologies and start applying new ones that differ from the former. At the same time, the opportunities to sell new products in new markets appear.

In a well-established market, the degree of unrelated diversification decreases, which prompts companies to move closer to their core products, thus the degree of related diversification increases accordingly (see Tables 1 and 3).

Summarising, the following generalized picture of the interrelations between unrelated and related diversification depending on the market situation emerges (see Fig. 6).

Fig. 6

Nevertheless, this method for measuring the scale of corporate activity diversification does not resolve the problem of how the measure of related diversification can be integrated into the measure of unrelated diversification, which is important because only by integrating these two measures, a complex estimation of the scale of diversification can be conducted. The above-discussed issues of corporate activity diversification require further research.