Strategic consistency and performance: an analysis of real estate developers.

The past three years have seen the remarkable growth of publicly held real estate companies called Real Estate Investment Trusts (REIT). The industry is still dominated by small, privately held firms but REITs and other large companies are emerging as major players. Organization strategy and

The issue of organizational domain has received much attention in the strategic management literature (e.g., Subramanian et al., 1993; Kruger, 1989; Miles and Snow, 1978). This involves the key decision of determining the business or the portfolio of businesses the organization should be in. This domain choice requires the decision-maker's selection of the combination of the organization's specific product(s) and its target market(s). This strategic choice of product market domain is key because it creates the need for a particular organizational structure and supporting organizational processes to implement the strategy. Consistency between the chosen product market strategy and the supporting structure is a very important ingredient for success. Amburgey and Dacin (1994) report the existence of a hierarachial relationship between strategy and structure -- strategy being a more important determinant of structure than structure of strategy.

A strategy issue currently facing real estate development firms is how to structure or restructure their organizations in order to improve performance. In a major review of the management literature, in search of lessons for development firms, Bhambri et al. (1991) note that real estate development firms take on various organizational structures -- smaller firms tend to be project oriented, large firms are either project or functionally oriented, or a mix of the two. Large firms may be groups of partnerships that are highly decentralized or the firms may be integrated with staff in functional areas and therefore more centralized. The question that these authors raise is: What are the advantages and disadvantages of these alternative organizational structures? As real estate developers begin to restructure and reorganize and add functions such as property management and brokerage, the issue of the appropriate structure becomes very important. This is especially so since a Laventhol and Horwath (1989) survey of over 1,000 real estate firms found that most firms tended to operate on a short-term planning horizon, and while 81% of the firms had operating plans that were updated annually, only 59% had long-term (3-5 year) strategic plans. However, the survey indicates, real estate companies are now becoming more interested in developing business strategies.

Other studies of the real estate industry (e.g., Sriram and Anikeeff, 1991) have reported that none of the intended product market domain strategies is either more popular or leads to better performance among development companies. However, the issue of the consistent implementation of the chosen strategy was not investigated.

Thus, this paper seeks to form a bridge between the strategic management and the real estate literature by extending Sriram and Anikeeff's (1991) findings by investigating the relationship between the consistency of implementation of strategy and performance. Therefore, the primary purpose of this paper is to see if consistent implementation of strategy -- the matching of the appropriate organizational structure to the strategy -- results in superior performance. The secondary purpose of this study is to investigate whether this consistency is associated with the age of the organization and its size. While previous research has found mixed evidence for the relationship between age and strategic choice and size and strategic choice, there has been no research which has studied the association of these two variables (age and size) with the consistent implementation of the chosen strategy.

LITERATURE REVIEW

Strategic Group Analysis

Empirical studies have reported on conceptual typologies that are effective in identifying different types of group strategies and organizational structures that are found within an industry (Chrisman et al., 1988; Doty and Glick, 1994; Galbraith and Nathanson, 1978; Hofer, 1973; McKelvey, 1975; Miller, 1988; Porter, 1980, 1985; Richins et al., 1987). Studies of firms have found that those competing in the same industry often use different types of strategies and organizational structures (Suchman et al., 1987), but the number of different successful types are limited.

Strategic groups provide a useful intermediate frame of reference between seeing the industry as a whole and seeing each firm separately. The strategic group concept provides a framework for empirical evidence to show that among successful firms a limited number of patterns of strategic behavior exist.

One can see examples of different strategy/structure types in different real estate firms. In some firms, the solution is to design diversification strategies and develop approaches for managing the firm as a portfolio of diversified businesses in diversified markets (e.g., the Grubb and Ellis organization). Other firms do not choose to minimize risk through geographic diversification, preferring instead to dominate their local market place (e.g., the Charles E. Smith company in the Washington, D.C. area). Still others prefer one product and diversified markets (e.g., Melvin Simon, a firm which focuses on developing shopping centers in different geographic areas).

Organizational structure, as Bhambri et al. define it, refers to consistent relationships among positions within the organization. They suggest that the best way to structure an organization is a function of firm size, location, product emphasis, and whether the firm intends to handle various activities in-house or use outside consultants.

In the management literature, one model in particular directly addresses the question put forth by Bhambri et al. -- the Miles and Snow (1978) typology. This typology deals with a firm's product market domain selection strategies and its organizational structure. In this widely tested typology (e.g., Namiki, 1989; Snow and Hrebiniak, 1980) the ideal firm types are classified by the strategic choices made by the firm's decision makers as they adapt the firm's strategy, organizational structure, and administrative processes to the changing economic environment. The underlying assumption is that the firm must adapt if it is to continue to perform and, in the long run, survive.

Miles and Snow (1978) argue that determining the business or the portfolio of businesses of the organization is the key strategic choice. The strategic process of adapting the firm to the economic environment requires the firm solve three interrelated problems (discussed next). Their model also suggests that the adaptation occurs in one of three ways.

Miles and Snow (1978) believe that the first step in adaptation is the selection by the firm's decision makers of an intended product market domain, which they call the "entrepreneurial problem." The solution of the entrepreneurial problem is followed by the solution of the "engineering problem" -- the creation of a system which can implement the product market or entrepreneurial solution using appropriate technology and management information and control systems. The final step is the solution of the "administrative problem" -- the creation of the organizational structure and process that allow for the rationalization and stabilization of activities which solve the other two problems.

There are three adaptation strategies, each with its own solution to the entrepreneurial problem, based on the selection of a product market domain. Defenders select a narrow domain with a narrowly defined product and a narrowly defined market. The Prospector prefers a broadly defined domain with a broad product and a broad market. Analyzers prefer an intermediate strategy with a portion of the firm having a narrow product market domain and the other portion providing multiple products and/or serving broad markets. Miles and Snow emphasize that it is the consistent use of a particular strategy and the selection of the appropriate implementation system, organizational structure, and administrative processes that is important for high performance. None of the strategies are inherently superior. Miles and Snow (1978) define firms that are inconsistent as Reactors. These are the firms where the product market domain is not consistent with the appropriate technology, organization and/or administrative structure. Reactors are generally poor performers.

There have been many empirical studies which have found support for Miles and Snow's contention that none of the strategy types, with the exception of Reactors, is inherently superior in terms of performance (e.g., Namiki, 1989; Snow and Hrebiniak, 1980). However, Hambrick (1983) found that Defenders generally outperformed Prospectors in terms of cash flow and profitability, whereas Prospectors performed better in terms of market share.

Returning to our original question: What are the advantages and disadvantages of alternative organizational structures? According to the Miles and Snow model, the answer is contingent upon the organizational structure relationship to a particular strategy.

Product Market Matrix

Several authors have investigated the issue of product market strategies (e.g., Leinberger, 1993; Subramanian et al., 1993; Sriram and Anikeeff, 1991). Gutman (1964) found that 98% of the companies he studied chose the sale of existing products in existing markets as the best strategy for growth. Hofer (1973) suggests that the current product-existing market strategy is a good strategy if the market is growing, but the new product-existing market is a good strategy when technological innovations require new product introductions. Rumelt (1974) found companies that diversified into related businesses were on the average more profitable than other firms.

The Miles and Snow typology provides real estate developers with three stable strategy choices -- Defender, Analyzer, Prospector -- which yield four product market domain alternatives: (1) sell a narrow range of products in a narrowly defined market (Defender), (2) provide a narrow range of products to a broad market (Analyzer Type A), (3) offer a broad spectrum of products to a narrow market (Analyzer Type B), or (4) provide a broad range of products to a broad spectrum of markets (Prospector).

A previous study (Sriram and Anikeeff, 1991) of the Miles and Snow framework of strategic group analysis found the typology applicable to the real estate development industry. This study also found that there was no significant difference in the frequency with which the four product market matrix variations were found among single-family residential, multi-family residential, and commercial developers. By finding no significant difference in average performance (as measured by sales per employee) among the four intended product market strategy categories, the Sriram and Anikeeff (1991) study supports Miles and Snow. This lack of difference in performance was found even when controlling for builder type (multi-family residential, single family residential, commercial).

This earlier study demonstrated that various strategies exist among development firms and that no strategy in and of itself could bring about superior performance. However, there was a great deal of variance within each of the categories. The Miles and Snow model would suggest that this is due to differences in the implementation of the selected strategy. According to the model, certain strategies call for certain organizational and administrative processes. Failure to implement these consistently with the chosen strategy will yield poor performance.

Strategic Consistency

Miles and Snow emphasize that whereas none their stable strategic types is inherently superior in terms of performance, it is the consistent use of a particular strategy, coupled with the appropriate implementation system, organizational structure, and administrative processes, which is important for high performance. They label firms that are inconsistent as Reactors. These are the firms where the product market domain is not consistent with the appropriate technology, organization, and/or administrative structure. Reactors are generally poor performers.

While other studies have alerted managers to the importance of the issue of strategic consistency (e.g., Nath and Sudharshan, 1994; Parry and Parry, 1992), the issue of strategy in general, and consistent implementation in particular, has received little attention in the real estate literature. This study attempts to close that gap.

This study investigates the benefits of consistency in the implementation of two of the three stable types of strategies -- the Defender, with a narrow product market and the Prospector with the broad product market orientation. Ignoring the intermediate Analyzer category allows for sharper differentiation in the classification and greater face validity in the operationalization of the variables. Also, methodologically it is hard to define and classify a "consistent" Analyzer. This type does not have unique characteristics but rather is a hybrid which has characteristics of both Defenders and Prospectors. This approach of studying only the Defenders and Prospectors in order to test tendencies of extreme strategies is consistent with that followed by Hambrick (1983).

The Defender's problem is to seal off a portion of the total market to create a stable set of products and customers. This is done by aggressively defending a narrow domain and narrow product offering. Technologically, the problem for management is the efficient production of a product. This is accomplished by concentrating on creating a cost-efficient system with a tendency toward vertical integration.

In contrast, the Prospector's strategy is to locate and exploit new product and market opportunities. It does this by avoiding long-term commitments to a single technological process. It has a low degree of routine, it is flexible and gives up efficiency in its production system. The administration problem is how to facilitate and coordinate numerous and diverse operations. There is a tendency toward a product structure with low division of labor and low degree of formalization.

RESEARCH OBJECTIVES

Based on the characteristics of Defenders and Prospectors discussed above, for real estate developers the key determinant of consistency between strategy, structure, and the administrative process is the relationship between the firm and its construction function. Peiser and Schwanke (1992) believe that for real estate developers the two most important decisions are the purchase of the land and the commencement of construction. The work of the construction team represents the bulk of the project's total cost, and effectively managing their contributions is critical to the success of the development project. McMahan (1989) suggests that the development firm may undertake construction in a variety of ways -- in-house, on a contract basis with a general contractor, or as a joint-venture partner with a general contractor.

In the real estate industry, a consistent Defender would integrate the construction activity by doing it either in-house or with an affiliated firm in order to maintain control of the organization's core technology and maximize cost efficiency. (This broader definition of integration to include activities performed by close affiliates is consistent with that proposed by Williamson (1975) and has been employed by other researchers in strategic management). On the other hand, a consistent Prospector would outsource its construction activity to maintain flexibility in its ability to obtain multiple technologies. While other studies (e.g., Namiki, 1989; Snow and Hrebiniak, 1980) have confirmed that no one strategy is inherently superior, the empirical evidence on the benefits (if any) of strategic consistency is lacking. Our contention is that real estate developers who employ a means of performing their construction activity which is consistent with their chosen strategy (Defenders who are vertically integrated for their construction and Prospectors who subcontract it) will outperform ones which are inconsistent (Defenders who subcontract it and Prospectors who are integrated). Therefore, our first research statement (RS) is,

RS 1: There will be a positive association between

performance and strategic consistency.

The secondary objective of this study is to investigate whether consistency is a function of the age of the firm or of its size. While some authors have suggested that a firm's strategy and structure change as it progresses through its "life cycle" and that its strategy is influenced by its stage in this cycle (e.g., Hardy, 1986), others believe that strategy is not evolutionary (e.g., Miles and Snow, 1978). In addition, empirical studies (e.g., Sriram and Anikeeff, 1991) of real estate developers have shown that whether firms choose to be Defenders or Prospectors is not associated with their age. It is therefore likely that consistency of strategy and structure is not systematically related to age either. Therefore,

RS 2: There will be no association between firm

age and strategic consistency.

The evidence on the relationship between strategic choice and size is somewhat mixed. The Defender's strategy of focusing on cost-efficient technologies and a tendency toward vertical integration is more appropriate for larger firms since size is necessary to vertically integrate efficiently and to enjoy the economies of scale which in turn drive down costs. On the other hand, Prospectors are smaller and less bureaucratic in order to better respond to market opportunities. There is, however, no reason to believe that size has any relationship with the ability to consistently apply the selected strategy. Therefore,

RS 3: There will be no association between

firm size and strategic consistency.

METHODOLOGY

Sample

A sample of the largest real estate developers was generated from lists published by Professional Builder (1987) and Building Design and Construction (1988). The person named on these lists (i.e., the chief executive officer or the vice president/director of construction/real estate operation) for each of the companies was sent a mail questionnaire with a cover letter explaining the academic aims of the study and requesting them to respond. The survey included 391 of the 400 largest homebuilders, the 30 largest retail developers, the 50 largest industrial developers, and 40 largest hotel/motel/restaurant builders. A total of 80 responses were received from the 511 that were mailed, yielding a response rate of 16 percent. While this response rate is not very high, it is not markedly different from that found in other similar studies. In addition, a visual comparison between respondents and nonrespondents did not reveal any systematic differences between the two groups in terms of geographic location and sales volume. The responding firms varied in terms of age (median 20, range 3 to 78), size (median 65, range 5 to 5,300 employees), and type of product built. The respondents were distributed among those that received the majority of their sales from single-family residential (n = 31), multi-family residential (n = 17), and commercial (n = 11) development. The remaining firms either could not be classified because of missing data (n = 10) or received their revenue from a mix of product types (n = 11) without a predominant category (i.e., no one product accounted for over 50% of their sales).

Constructs and Measures

Where possible, constructs were operationalized using measurement items generated from existing scales (Miles and Snow, 1978), and others were developed specifically for this study. The questionnaire was pilot tested for its clarity, readability, and to ensure that the theory based items addressed issues of concern to real estate decision makers.

A firm's product market domain was used to determine whether it was a Defender or a Prospector. To measure this product market domain strategy, two sets of questionnaire items were developed: one set to determine the product domain and the other set to determine market domain. Each item was measured on a 5-point Likert-type scale anchored by "strongly agree" (1) and "strongly disagree" (5). Principal component factor analysis was used to determine the underlying concept (product domain or market domain) measured by the set of survey question items. The results provide internal level indices which are used to define the concepts.

Product domain was measured by those items in the questionnaire relating to whether the firm sought new product lines or was limited to existing lines; whether or not it would consider product line expansion in the face of uncertain profit; whether it diversified to balance risks; and whether or not it concentrated on well understood products. Market domain was measured by those items in the questionnaire which dealt with whether or not the firm planned to expand into new geographic areas even if profit levels were uncertain, whether or not it diversified geographically to balance its risks, whether it concentrated on well understood markets, and whether it would rather concentrate on new product lines in current markets or enter new markets.

A firm's age was measured by the number of years it had been in development. Size was measured by the number of employees in the firm. Performance was measured by sales per nonclerical employee. The total sales of the firm, as reported in the publication from which the firm was identified, was divided by the number of nonclerical employees as reported in the survey. This measure, rather than sales per employee, was used because in small firms, of which there are many in the real estate development industry, sales per nonclerical employee is a better measure of efficiency. Since all firms need a certain minimum number of clerical employees in order to function effectively and these employees are typically added on less than proportionately to sales increases, they account for a disproportionately high percentage of the total workforce in small firms. Their inclusion would therefore result in a misleadingly low sales per employee figure for smaller firms.

Scale Development

In order to assess the construct validity and unidimensionality of product domain and the market domain constructs discussed above, the multiple questionnaire items used to measure each were subjected to principal component factor analysis, with varimax rotation. Items loading on a factor at a level of 0.4 or higher were included in the scale for that construct. These items were then summed to yield a total score measure for each construct. These multiple item scales were subsequently assessed for reliability using Cronbach's alpha. Both the product domain and the market domain scales were above the recommended minimum (0.6) reliability. Table 1 shows the items used (those with loadings above 0.4) to form each scale, their factor loadings, and the reliability measure for each.

Table 1
Constructs and Measures

Variable   Items

PRODUCT    Seek new lines
           Limited product line
           Will expand product lines even if
           profit levels uncertain

DOMAIN     Diversify products
           Concentrate on a few, well
           understood products

MARKET     Look for geographic expansion
           Will expand geographically even if
           profit levels uncertain
           Diversify geographic scope

DOMAIN     Focus on new product lines rather
           than new markets
           Concentrate on a few, well
           understood markets

           Factor
Variable   Loadings   Reliability

PRODUCT    .6731
           .7085

           .7193

DOMAIN     .5383

           .6610
                      .7927
MARKET     .8263

           .8107
           .6291

DOMAIN
           .6170

           .4751
                      .7669

The individual firm's product market domain classification was determined next. The sample firms were divided into groups based on the breadth/narrowness of their product market domains. In the absence of any universally accepted yardstick for determining broad or narrow domains, the relative summed score for each firm on product domain and market domain was used as the basis for categorization. These scores were arrayed in hierarchical order for each of the two constructs. The firms with less than the mean score were identified as having a narrow focus, whereas those that had a higher than mean score were identified as having a broad focus. Thus, four categories of firms emerged as a result of this classification scheme: 1) Defenders, those with narrow product and narrow market domains, 2) Prospectors, with broad product and broad market domains, 3) Analyzers (Type A), with narrow product domain and broad market domain, and 4) Analyzers (Type B) with broad product and narrow market domain. Defenders had a mean product scope of 12.7 and market scope of 12.3. Prospectors averaged 19.3 and 20.9, respectively on these measures. (As can be seen from Table 1, the product and market scope measures each consisted of 5 items, with each item scaled 1-5.) In the study reported here, however, only the Defender and Prospector categories were investigated.

In order to determine which firms were consistent, an analysis of their construction activity was conducted (construction was selected rather than building design or property management, for instance, since construction is a function all developers require). According to Miles and Snow (1978), Defenders would vertically integrate and Prospectors would outsource. In the context of real estate development this would imply that consistent Defenders would use in-house or affiliated companies to undertake their construction activity whereas consistent Prospectors would either negotiate contracts or solicit open bids from outside firms in order to complete this activity. By extension, Defenders who outsourced their construction or Prospectors who had either an in-house or affiliated construction firm would be inconsistent. Thus, Defenders who did 75% or more of their construction in-house (or with an affiliated company) and Prospectors who outsourced 75% or more of their construction were deemed consistent. The rest were categorized as inconsistent.

Analytical Technique

In order to test for differences in age, size, and performance between consistent and inconsistent firms, one-way analysis of variance using the F-statistic was conducted. To measure the strength of the association between these variables and performance, the correlation coefficients were computed. For the purposes of hypothesis testing, p [is less than] .05 was taken as the measure of significance of the results.

ANALYSIS AND RESULTS

Consistency of Strategy

As indicated by the results presented in Table 2, consistent firms, with average sales per employee of $1,434.58, are almost twice as productive as the inconsistent ones ($753.66). These performance differences are statistically significant, with an F-statistic of 4.96 (p [is less than] .03). These results lend support to RS 1, indicating that consistency of strategy is associated with higher performance.

Table 2
ANOVA Results: Consistency and Performance

                                  Std.
Type            N       Mean      Dev.      F-Value   P

Inconsistent    15       753.66    509.90

Consistent      14      1434.58   1061.31     4.96    .03

Table 3 presents the results of the ANOVA conducted to test for differences in age between consistent and inconsistent firms. The consistent firms were on average 23.14 years old and the inconsistent ones had an average age of 22.24 years. The F-value of .03 (p [is less than] .86) indicates that there is no significant age difference between consistent and inconsistent firms. These findings are consistent with RS 2.

Table 3
ANOVA Results: Consistency and Performance

                             Std.
Type            N    Mean    Dev.    F-Value   P

Inconsistent    17   22.24   10.22

Consistent      14   23.14   18.21   .03       .86

Table 4 presents the ANOVA results for the test for size differences between consistent and inconsistent firms. Consistent firms are on average larger (379.14 employees) than inconsistent ones (187.93 employees) but these differences are not statistically significant (F =.38, p [is less than] .54), thus providing support for RS 3.

Table 4
ANOVA Results: Consistency and Size

                              Std.
Type           N    Mean      Dev.     F-Value   P

Inconsistent   15   187.93    151.43

Consistent     14   379.14   1188.44     .38     .54

Strength of Association

While the results presented in Table 2 suggest the existence of a statistically significant association between consistency of strategy and performance, they do not provide a measure of the strength of this association. To assess this, various measures of association were computed as can be seen in Table 5. High performers were those firms with sales/employee above the average for the sample and low performers were those firms with below average performance. AS can be seen from the chi-square statistic (6.81, p [is less than] .009), consistency and performance are not independent. The contingency coefficient (0.436, p [is less than] .009, for a two-by-two table, this coefficient's range is 0 to .707) indicates the existence of a positive, moderately strong association between consistency and performance. This conclusion is strengthened by the gamma coefficient (.867) which indicates a strong ability to predict performance based on consistency of strategy.

Table 5
Strength of Association: Consistency and Performance

                Performance

                Low      High

Inconsistent    n = 14   n = 1

Consistent      n = 7    n = 7

Chi-square Value: 6.81
Degrees of Freedom: 1
Significance: .009

Contingency Coefficient: 0.436
Significance: .009

Pearson's R: 0.484
Significance: .008

Gamma: 0.867

DISCUSSION AND CONCLUSION

The results of this study should be of interest to real estate developers. In an industry characterized by a great deal of volatility, the development of longterm strategic plans which incorporate clear product and market domain choices represents one way to buffer the organization from the severe cycles which often occur. However, as these findings suggest, it is the consistent implementation of the chosen strategy which is critical to success. As real estate developers increasingly incorporate strategic management thinking into the organization, they must ensure that their structure is appropriate to their product market strategy.

The results of this study indicate that consistent application of a chosen strategy results in higher performance than if the implementation of strategy were inconsistent. A key finding is the evidence of a moderately strong association between consistency and performance. As Table 5 shows, among inconsistent firms, the frequency of low performance is much higher than that of high performance. This suggests inconsistency is almost certain to be associated with a relatively lower performance. In short, consistency is necessary but not sufficient for high performance.

This study also found that age and size are not associated with consistency. This is of particular significance in the real estate development industry since many of the firms in it are small and young. Thus, as long as these firms select a strategy and organize their construction activity appropriately, they are likely to perform well regardless of how large they are or how long they have been in the industry. This points to the importance of an early choice of competitive strategy and the setting up of an administrative structure to go along with it. These findings provide further support to the argument that none of Miles and Snow's stable strategies is inherently superior, provided sufficient care is taken to ensure consistent implementation. While the findings of this study are interesting, the small sample size may make the statistical results somewhat unstable and the results, while revealing, should be interpreted cautiously. In order to enable stronger conclusions regarding the benefits of strategic consistency, other studies will need to replicate these findings using larger samples and add to their generalizability by investigating other industries. Extending these results will be of particular value to firms in other fragmented industries (e.g., services, retailing, distribution) which, like the real estate industry, consist of many small and young firms which could benefit from the application of business strategies. In addition, longitudinal studies will permit greater confidence in the stability of the results. Future studies of real estate developers also need to use multiple indicators of consistency (in addition to using degree of integration of construction activity) and assess performance using additional measures in order to validate the findings reported here. The availability of more conventional measures of performance (e.g., ROI, ROE, ROA, etc.) becomes easier as future studies focus on REITs in addition to small, privately held firms. Since REITs are publically held, more accurate and verifiable performance data have become available.

Traditionally, many academic researchers have examined large, well capitalized firms. This study shows that many of the basic findings of the strategic management literature are equally applicable to smaller firms in a fragmented industry. Further examination of small firms across various issues germane to strategy formulation and execution is necessary in order to identify the areas where the lessons learned from large firms can be utilized and those where small firms require separate analysis.

Since 1987/88 the real estate industry has gone through a fairly substantial restructuring as some firms have left the industry and many of the others have reorganized. The reorganized ones have become real estate companies and are not merely developers as in the past. As they have added additional functions (e.g, property management, brokerage) they are having to redefine their organizational strategy. The findings of this study can help these owners/managers to properly structure their organizations in order to ensure that this structure is consistent with their chosen strategy. As these results suggest, strategy selection by itself is not a determinant of performance, it is its consistent application which is associated with higher performance.

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