Restructuring scope, performance and R&D intensity: do all restructuring activities...

ABSTRACT

One of the most prominent aspects of corporate behavior during the 1980s was corporate restructuring--changes of business portfolios through a high level of acquisitions and divestitures. However, little attention has focused on the consequences of restructuring activities. This

paper investigated the impact of corporate restructuring activities on a firm's financial performance and long-term competitiveness during 1980s. In comparing a sample of nonrestructured firms, this study found that there are no significant performance differences between restructured and nonrestructured firms and the impacts of corporate restructuring vary depending on restructuring scope. Additionally, there exists a partial substitution relationship between restructuring scope and R&D intensity.

INTRODUCTION

The corporate restructuring phenomenon marked a drastic difference from the predominantly acquisitive period in the 1960s & 1970s (Singh 1993). On the one hand, a growing number of companies that once thought diversification and expansion were vital, are abruptly changing course. Many conglomerates have restructured their diversified businesses through divestitures and acquisitions. They are slimming down and narrowing their focus, lopping off divisions, and selling assets and product lines. They are not only jettisoning bad acquisitions of the early 1970s, but also making moves to spin off and scale down healthy businesses to concentrate on what they do best. Overall they reduce their degree of diversification. For example, Porter (1987) reported that half of the unrelated acquisitions made by conglomerates during the 1960s and 1970s have been reversed through divestitures. Similarly, Ravenscraft and Scherer (1987) estimated one-third of all (including related) acquisitions made in the 1960s and 1970s were later divested. Ollinger's (1994) research of the oil industry indicates that by 1990 many oil companies (e.g., EXXON, AMOCO, Mobil) had sold most of their unrelated businesses. Discarding all of their completely unrelated businesses such as retailing, electronics and electric motors, oil companies retained some units that were natural extensions of, or only distantly related to their existing businesses, such as mining.

On the other hand, the corporate refocusing movement does not mean that all diversified firms have terminated their diversification strategy all together. In fact, some researchers have observed that a significant number of firms are still diversifying their businesses, which defies the gospel of 1980s: focus on a few core businesses. Continuous expansion is still a popular measure of success in growth-oriented Corporate America. Many substantially diversified firms--Westinghouse, Berkshire Hathaway, Philip Morris, Hanson Trust, Teledyne, 3M etc. seem not to have followed the bandwagon of "downscoping." Statistics and empirical studies also indicate that the trend of diversifying continues, despite the business rhetoric of refocusing on firms' core businesses. For example, Davies, Diekmann and Tinsley (1994) found that 30 percent of largest firms still operated in three or more 2-digit industries in 1990 and shown sign of reversion. Markides' (1994) empirical study of Fortune 500 companies suggested that there exists an optimal level of diversification. From a random sample of the diversified firms, some might have over-diversified (above the optimal level), while others might be below their optimal diversification levels. Assuming profit-maximizing behavior of these firms, he found that the "under-diversified" firms would increase the degree of their business diversity, while the "over-diversified" firms would decrease the degree of their business diversity. He further found that the aggregate diversification level has not changed in the 1980s, which he attributed to the above-mentioned counterbalance movements of refocusing and diversifying. In a similar vein, Hoskisson and Johnson's (1992) empirical study also suggested that the widely diversified firms were not the prime target for corporate restructuring and restructuring may not always result in a reduction in the degree of business diversity. In fact, they found that due to inconsistent control systems (i.e., financial control vs strategic control), more firms were moving away from the intermediate strategy (i.e., related-linked) type and becoming distinctively related (reduction in diversification) or unrelated firms (increase in diversification). Although, to some extent, their conclusions are contradictory to Markides' (I 994) finding of optimal diversification levels, both studies suggested the juxtaposed diversifying and refocusing activities in the 1980s in Corporate America.

The swath of corporate restructuring activities poses questions to strategy researchers: why have firms changed their business portfolio so radically within such a short period of time? What are the consequences of firms' restructuring activities. Do restructuring activities always create value? Are there significant performance differences between restructured firms and non-restructured firms? Are certain types of restructuring activities associated with high levels of corporate performance? Are other types of restructuring strategies associated with lower levels of corporate performance? Despite wide attention from disciplines such as financial economics, business policy and strategy, and organization management, surprisingly little effort has been directed to examine these questions.

This paper is organized as follows. Attention is first devoted to a review of current literature on corporate restructuring. It is followed by hypothesis development regarding the influence of corporate restructuring activities on accounting performance and long-term competitiveness. Research design, data analysis and results are discussed next. Finally, this paper concludes with contributions and future research directions.

THEORETICAL BACKGROUND

Literature review suggests that: 1) corporate restructuring activities have been attributed to both macro, environmental, and micro, organizational factors; 2) scant research has been devoted to investigating the consequences of corporate restructuring. Among the few studies, their findings remain controversial and inconsistent.

Antecedents of Corporate Restructuring

Macro, Environmental Explanations. Environmental explanations contend that recent restructuring activities fit into a broad pattern of historical episodes, and are a function of organizational adaptation to major changes in the regulatory and competitive environments (Bhide, 1990; Bowman & Singh, 1990; Shleifer & Vishny, 1990; Bethel & Liebeskind, 1993). First, the relaxed enforcement of the Cellar-Kefauver Act makes it easier for firms to grow through acquisitions in their own basic industry with less fear of governmental challenge. Because horizontal expansion allows firms to exploit core capabilities better than diversifying expansion, firms may have shed diversified businesses and focused corporate resources on horizontal expansion when the opportunity arises (Shleifer & Vishny, 1990). Second, increasing global competition, deregulation of several key industries in the United States (Weston & Chung, 1990), turbulence due to technological innovations and demand change (Quinn, Doorley & Paquette, 1990) have ushered in an era of intensive rivalry (D'Aveni & Illinitch, 1992). Firms may have to reexamine their business concepts and reconsider capabilities and restructure their business portfolio in order to survive (Bowman & Singh, 1990). Third, in financial economic circles, many view corporate restructuring as transactions in a market for corporate control, where alternative management teams compete for the right to control the undervalued assets (Jensen, 1986). It is a mechanism that disciplines management teams that fail to realize a firm's potential value, and prompts managers to initiate defensive measures in order to thwart such bids through restructuring. The notion that the external capital market harmonizes agency conflicts through the threat of transfer of corporate control was suggested by Manne (1965) and refined by Fama (1980) and Fama and Jensen (1983a; 1983b). In this view, firms that are poorly managed and unprofitable become takeover targets. Outsiders attempt to displace incumbent managers in order to shift strategy, make efficient use of financial slack, and reap the gains stemming from increased profitability. These threats of displacement may help to discipline management by compelling it to expend more effort in pursuit of shareholder wealth maximization. Failure to improve firm performance, whether due to excessive consumption of corporate perquisites or due to low managerial abilities may ultimately lead to a transfer of corporate control.

While the environmental explanations focus on the issue of why corporate restructuring happened in 1980s, rather than in 1960s or 1970s where conglomerate diversification became dominant (Bethel & Liebeskind, 1993), the micro level research mainly deals with the issue of why some firms restructured and others did not in the 1980s, given the same operating environments.

Micro level, Organizational Explanations. A widely used framework to the analysis of corporate behavior has been agency theory, or the idea that managers pursue their own objectives that need not serve the interest of shareholders. Jensen (1986) and other agency theorists interpreted the restructuring wave in the 1980s mainly as an attempt to control nonvalue maximizing behavior of corporate managers and correct for inefficient over-expansion and over-diversification during 1960s and 1970s, when managers increased the size and scope of firms without increasing their value (Jenson, 1986, 1991). One of the factors noted by agency theorists has been the changes in the firms' governance structure during the 1980s, which constrained managers' opportunistic behavior and pressured them to divest or sell offthese diversified businesses. For example, it has been observed that the proportion of shares of large public U.S. corporations managed by institutions rose dramatically during the late 1970s and 1980s. Chaganti and Damapour (1991) reported that the percentage of U.S. corporate equities managed by institutions rose from 9 percent in 1970 to 23 percent in 1988. By 1991, 40 percent of the equity of U.S. large businesses is managed by institutions. Pound (1992) argued that these institutions have the incentive and the power to monitor and change firm policy.

The Consequences of Corporate Restructuring

The few studies that investigated the consequences of corporate restructuring have yielded inconsistent findings. For example, Grant and Soenen's (1994) study of restructuring activities in the oil industry found that the performance changes over the ten-year period 1979-1988 are instructive, even though the extent of environmental turbulence (volatility of oil price in particular) makes it difficult to separate the effects of environmental changes from those restructuring activities. In particular, they noted that the oil companies which engaged in the most radical shifts in strategy and pursued the most drastic restructuring, namely Exxon and Arco, were the companies which experienced the best profitability during 1986-1988 relative to the period 1980-1983. In their study, Grant and Soenen broadly referred restructuring as including both asset restructuring and internal management changes.

Viewing restructuring as the process in which firms reduced their diversification by refocusing on their core businesses, Markides's investigation of the 50 most aggressive U.S. restructurers over the period of 1980-1989 identified by the Mergerstat Review found that refocusing is positively associated with performance improvements (Markides, 1994). Empirical study by Brumagim and Klavans (1994) suggests that some conglomerates benefited from becoming more focused. Corporate performance, both in terms of return on equity and profit margin, nearly doubled within two years after the completion of conglomerate focusing actions In their study, they only examine one type of restructuring, the divestiture of one or more major segments. Zantout (1994) suggested that the sample aggressive restructurers were generally performing poorly during the early 1980s, supporting the argument that voluntary corporate restructuring has been a pre-emptive measure against the external capital market intervention. A survey conducted by Strategic Planning Association indicated that nearly half of large U.S. corporations restructured in the 1980s, among which more than 50 percent failed in their restructuring effort (Lewis, 1990).

The inclusive findings in the value of corporate restructuring activities warrant further research. Although theories generally hold that restructuring should lead to performance improvement, normative assertion should not substitute for empirical testing.

HYPOTHESES DEVELOPMENT

Some theorists have noted that not all restructuring programs are successful and performance of restructured firms is unitary (i.e., Lewis, 1990). Firms' restructuring activities differ in terms of the restructuring scope or propensity. Here, restructuring scope refers to the degree to which firms change their business diversity. The use of restructuring scope (or propensity, direction) to assess firms' restructuring activities is consistent to what strategy theorists argued the "content" dimension of strategic change (i.e., Ginsberg, 1988; Johnson, 1988) or changes in pattern, such as from related to unrelated diversification (Galbraith & Schendel, 1983), or from unrelated diversification to related diversification (Markides, 1992). Consequently, a company often faces two broad choices regarding how to restructure or configure its business portfolio: refocusing to increase business relatedness (putting all eggs in one basket, while benefiting from synergies) versus diversifying to increase business diversity (risk reduction is traded off synergies among businesses).

Restructured Firms versus Non-restructured Firms

One of the major reasons that there is little systematic empirical investigation of the restructuring/performance relationships is that the post-restructuring performance improvement has been normatively asserted. That is, the direct links between corporate restructuring and performance are assumed in research. Specifically, if firm can achieve the goal of optimizing resources allocation, reducing risks and selecting munificent operating environments through a series of acquisitions and divestitures, improved performance should result. For example, from the perspective of agency theory, corporate restructuring is a mechanism through which agency problems are corrected and the alignment of managerial interest and stockholders' wealth is reached. Consequently, firms should expect a significant improvement in post-restructuring performance. In the view of market for corporate control, supposedly inefficient and undervalued firms are targeted by corporate raiders, thus the primary purpose of the market for corporate control is to create efficiency in the operations of the firm. One should therefore expect an active market for corporate control to significantly increase average firm performance over time. Similarly, in the logic of diversification theorists, corporate restructuring is a process through which firms optimize their degree of diversification. Either a correction of over-diversification in the 1960s and 1970s by over-diversified firms or a movement toward diversification by under-diversified firms represents a rational action taken by top management to explore the economies of scale and scope, and the synergies among diversified businesses, while minimizing the side-effects such as bureaucratic costs.

Additionally, from the standpoint of resource-based theory, corporate restructuring activities represent a firm's effort to rebuild and optimize a firm's input-based competencies. They contribute to sustained competitive advantages through facilitating the development of the physical resources, organizational capital resources, human resources, knowledge, skills and capabilities that enable a firm's transformation process to create and deliver products and services that are valued by customers and superior to competitors (Lado, et al., 1992; Lado & Wilson, 1994). Therefore, it is expected that R&D intensity of restructured firms is greater than that of nonrestructured firms.

Based on the above discussion, the following hypotheses were proposed:

H1a: On average, the post-restructuring profitability of restructured firms is greater than that of nonrestructured firms, or:

RO[A.sub.restructured] > RO[A.sub.non-restructured]

H1b: On average, the performance improvement of restructured firms is greater than that of nonrestructured firms, or:

[DELTA]RO[A.sub.restructured] > [DELTA]RO[A.sub.non-restructured]

H1c: On average, the R&D intensity of restructured firms is greater than that of nonrestructured firms, or:

R&[D.sub.restructured] > R&[A.sub.restructured]

H1d: On average, the increase of R&D intensity of restructured firms is greater than that of nonrestructured firms, or:

[DELTA]R&[D.sub.restructured] > [DELTA]R&[D.sub.non-restructured]

Refocusers and Diversifiers

Researchers in strategy management have asserted that change in diversity is negatively related to firms' performance, especially when most of the restructured firms are over-diversified. Specifically, an increase in firms' diversity may result in a decline in firms' performance. Hitt and Hansen (1991) and other theorists (i.e., Hoskisson & Hitt, 1994; Markides, 1992) have speculated several reasons. First, when diversification is driven by managerial self-interest of increasing personal compensation and employment security, the risk avoidance motive for diversification has little to do with the efficiency of resource allocation. Second, an increased debt level, which most likely leads to a subsequent cut in R&D expenditures, usually accompanies an increase in business diversity. Therefore a reduction in innovation may depress performance. Third, diversification means increasing bureaucratic costs. Fourth, diversification may divert management's attention away from a firm's' core business and loss of strategic control.

On the other hand, Markides (1994) suggested that a significant number of restructured firms have decreased their business diversity because: 1) they were over-diversified after the 1960s and 1970s acquisition wave; 2) even if they were optimally diversified decades ago, they have now become over-diversified. This is due to the fact that the increased environmental uncertainty and volatility, increasing globalization have significantly increased the cost of diversification, subsequently decreased the optimal level of diversification. A reduction in a firm's business diversity may lead to performance improvement, because of the following reasons.

First, if many refocusers previously engaged in unprofitable diversification, as Jensen (1986, 1988) suggested, the divestitures of non-value-adding diversified assets means to stop financial loss and should improve performance. There is evidence that divested businesses in the 1980s performed poorly, which suggests that divestitures might lead to an improvement in firms' performance. It is also noted that divisions of diversified firms do not perform as well as similar businesses that stand alone or are a part of undiversified firms (Lichtenberg, 1990). This evidence suggests that the return to specialization might improve efficiency. The empirical study by Brumagim & Klavans (1994) found that some conglomerates benefited from becoming more focused. Corporate performance (on average), both in terms of return on equity and profit margin, experienced significant improvement within two years after the conglomerate's refocusing actions. The performance differences between "holders" and "focusers" where significant, after controlling for the industry profitability.

Second, a reduction in business diversity may improve firms' performance by creating narrow lines of businesses that will utilize related firm resources. Hite, Owen and Rogers (1987) noted in their research that managers cited poor performance, lack of fit, and need for capital to expand existing lines of business as reasons for sell-offs. For example, in 1983, seeking to concentrate its management skills on its publishing and video businesses, Time Inc. spun off its forest products operations. These operations had accounted for 17 percent of Time's profit and 33 percent of revenue. Initial results are encouraging: Time's publishing return on assets increased by 28 percentage points in 1984, while the post spin-off return on assets of the new forest-product company, Temple-Inland, reached its highest level in more than six years. These rationales imply that the divested resources siphoned attention and resources away from core businesses. Duhaime and Grant (1984) and Montgomery and her colleagues (1984) also found that if a divestiture strategy leads to a more focused company, such a strategy would produce higher gains.

Third, a reduction in diversification scope would reduce information-process demand on top management and provide the firm with the opportunity to reconfigure the governance structure, thereby allowing them to devote more time to increasing the efficiency of the assets that remain (Hill & Hoskisson, 1987). Thus, it enhances the prospects for improved long-term performance through increased focus on core businesses and improved corporate governance. Research by Hite, Owers and Rogers (1987), Sicherman & Pettway (1987), and Jain (1985) all document increases in firm value following divestiture, offering support for this perspective.

Based on the above discussion, the following hypotheses were proposed:

H2: Increasing restructuring scope or business diversity is negatively associated with firms' profitability.

H2a: On average, The profitability of refocusers is greater than that of diversifiers, or RO[A.sub.refocusers] > RO[A.sub.diversifiers]

H2b: On average, The performance improvement of refocusers is greater than that of diversifiers, or [DELTA]RO[A.sub.refocusers] > [DELTA]RO[A.sub.diversifiers]

Theorists in strategy and economics areas have noted that the impact of corporate restructuring on R&D intensity may vary depending on a firm's restructuring scope--changes in a firm's business diversity (i.e., diversifying or refocusing). For example, empirical study by Hill and Hansen (1991) in the pharmaceutical industry confirmed the negative relationship between R&D intensity and changes in diversity. They concluded that pharmaceutical firms partly finance diversification through reduction in R&D expenditures. Similarly, Hall's (1990) findings suggested a substitution relationship between acquisitions and R&D intensity, however she indicated that this relationship is due primarily to the debt incurred to finance such acquisitions and therefore has a negative effect on R&D expenditures. Baysinger and Hoskisson (1989) found that highly diversified firms have, on average, invested less in innovation than less diversified firms. Hoskisson and Hitt (1994) also contended that managers often prefer making acquisitions to the riskier option of investing in R&D since they are often tempted to act in their own self-interest, particularly when actions, such as innovation, carriers a high degree of uncertainty. Additionally, they reason that corporate executives increasingly emphasize financial controls (e.g., ROI goals) over strategic controls (evaluation of strategic actions which have long-run influence on performance, such as R&D investment) as firms are further diversified. Therefore the use of short-run performance control may lead to a reduction in R&D expenditures. These arguments suggest that diversification strategy, or an increase in the level of a firm's business diversity may most likely lead to a reduction in its investment in R&D.

On the other hand, firms which are refocusing on their core businesses and therefore are reducing the level of their business diversity may realize an increase in their investment on R&D. For example, Hoskisson & Johnson (1992) argued that a reduced business diversity and thus a reduced span of control may assure corporate executives a better strategic understanding of divisional operations and markets. Top management therefore may reassert strategic control and increase managerial commitment to innovation. This commitment can be subsequently observed in an increased level of investment in R&D (in the core businesses) and in championing new product ideas. Additionally, since refocusing strategy is usually accomplished through divestitures of unrelated business, resources from the sales of units may generate resources for reducing debt levels and decrease or even free management from debtors' pressures. Management may therefore refocus more on the firms' long-run competitiveness (i.e., R&D) than short-run financial returns. These arguments suggest that a refocusing strategy, or a reduction in the degree of a firm's diversity may most likely result in an increase of R&D expenditures.

Based on the above discussion, the following hypotheses were proposed:

H3: Increasing restructuring scope is negatively associated with R&D intensity.

H3a: On average, the R&D intensity of refocusers is greater than that of diversifiers, or R&[D.sub.refocusers] > R&[D.sub.diversifiers]

H3b: On average, the increase of R&D intensity of refocusers is greater than that of diversifiers, or [DELTA]R&[D.sub.refocusers] > [DELTA]R&[D.sub.diversifiers]

RESEARCH DESIGN

Sampling Procedures

Firms that divested and acquired two or more businesses, and signified major strategic change (i.e., more than 10 percent change in the business diversification index) were classified as restructuring. A number of studies in the restructuring area have used these criteria (i.e., Hoskisson & Johnson, 1992; Johnson et al., 1993; Simmonds, 1990). Since formal announcements of corporate restructuring can be rarely found in public sources such as the Wall Street Journal, BusinessWeek, Journal of Mergers and Acquisitions etc., I constructed the sample of restructured firms using the following procedures. First, 350 firms in the manufacturing industries (SIC 2000-3999) were randomly selected from Compustat PC Plus, with the condition that no leverage-buyouts occurred during the 1981-1990 period. Secondly, all mergers and divestitures for the sample firms were compiled from the Transaction Rosters in MergerStat Review and Journal of Mergers and Acquisitions, eliminating those firms with less than two transactions and those whose transactions appeared to be sporadic. For example, a company that made acquisitions in 1981 and 1985, and divested a business segment in 1990 was dropped from the sample since these transactions could not be conceived to have a pattern of restructuring activities. Therefore, only firms which had a series of acquisitions and divestitures with no more than two years interval between each transaction were retained in the sample. Specifically, a firm's restructuring period was determined by the year in which the first transaction started and the year in which the last transaction ended. Third business segment information for the sample firms during the restructuring period was collected from corporate annual reports as well as from Moody's Industrial Manual, depending on the information availability. The business diversification index was calculated using the entropy measure (Palepu, 1985). Only firms with more than 10 percent change in the business diversification index were included in the sample. Due to the data availability of other variables, the final sample of restructured firms was reduced to 106 manufacturing firms.

The sample of nonrestructured firms was constructed by the following steps. First, a reduced sample was constructed by eliminating the 106 restructured firms from the sample. Second, the reduced sample firms were verified by two criteria: 1) no significant change of the SIC four-digit industry between 1981 and 1990 (Hoskisson & Johnson, 1993; Markides, 1992, 1993, 1995; Brumagim & Klavans, 1994; Williams, Paez & Sanders, 1988); 2) the changes of their diversification index were less than 10 percent during the period. The final nonrestructured sample was reduced to 41. In testing the performance differences between restructured and nonrestructured firms, data for return-on-asset, R&D intensity, size, financial leverage was collected. Chi-square tests of sample distribution by size, industry classification and sale revenues between restructured and nonrestructured samples were not statistically significant.

Variable Operationalization and Data Sources

Post-restructuring Performance. A review of the strategic management literature reveals a number of studies using accounting returns, however, more recently, market-based performance measures have been adopted (Chatterjee, 1986; Dubofsky & Varadarajan, 1987; Hitt & Ireland, 1986; Lubatkin, 1987). Although accounting measures have been the subject of much debate, they are still commonly used and have been defended (Bromiley, 1986; Jacobson, 1987; Long & Ravenscraft, 1984). It has been suggested that it should not matter whether market-based or accounting-based measures of performance are used, because the positive or negative impact of diversification should be visible in both (Dubofsy & Varadarajan, 1987).

In this study, an efficiency view of performance was adopted and operationalized as return on total asset (ROA). ROA is earnings (excluding any extraordinary items) after deducting interest, tax, and any preferred dividend, expressed as a percentage of total assets. ROA is a widely used measure of business performance, and is strongly correlated with other relevant performance measures such as return on sales (ROS) and return on equity (ROE). Consistent with Hoskisson & Johnson (1992), Hitt, Hoskisson, Johnson and Moesel (1994) Brumagim and Klavans (1994), we averaged the post-restructuring, two-year ROA, which was aimed to minimize the effect of fluctuation. To control for the profitability of different industries, we adjusted ROA for both restructured and nonrestructured firms by deducting weighted industry ROA for the ending year of each firm's restructuring period, [summation of]([M.sub.ij4.sup.*]RO[A.sub.j])/[summation of][M.sub.ij4], where RO[A.sub.j] associated with 4 digit industry j, [M.sub.ij4] is the percentage of firm i's total sales that are in industry j. Change in performance was measured by the difference of ROA in the restructuring period. Firms' ROA data were available from Compustat PC Plus, and business segment information were constructed from sources such as Moody's Industrial Manual, Corporate Annual report and 10-K reports. Finally, industry profitability data were collected from Annual Industrial Norms and Business Ratios complied by Duns & Bradstreet.

R&D Intensity. R&D intensity is measured by the R&D expenditure divided by the total sales. This construct is well established and has been widely used by researchers, such as Hoskisson and Johnson (1992), Hill and Hansen (1991), Hoskisson, Johnson and Moesel (1994). Information for this dependent variable was obtained in the following two steps. First, similar to ROA, I averaged the post-restructuring, two-year R&D intensity for the consideration of fluctuation. The data was constructed from Compustat PC Plus. Second, to partial out the influence of the industry on the level of R&D intensity, I subtracted the industry average R&D intensity from the averaged two-year R&D intensity. Research and Development in Industry published annually by the National Science Foundation provides information of manufacturing company (except federal) R&D funds as a percentage of net sales by three-digit industry code. In this case, I used SIC of the dominant business segment within each firm (one with the largest sales contribution) obtained from Compustat PC Plus to make such adjustment for both restructured and nonrestructured samples. Change of R&D intensity was measured by the difference of two-year averaged R&D intensity during the restructuring period.

Restructuring Scope. Restructuring scope, or changes in business diversity is measured by the changes in a firm's business diversity. The level of firm diversification was calculated using the entropy measure (Jacquemin & Berry, 1979; Palepu, 1985). It was specified by Davis and Duhaime (1992) using the following formula, DT=[summation of][P.sub.j.sup.*]In(1/[P.sub.j]), Where [P.sub.j] is defined as the percentage of firm sales in segment j and In(1/[P.sub.j]) is the weight for each segment j. This measure, therefore, takes into account the number of segments in which the firm operates and the relative importance of each segment in sales (Palepu, 1985). This continuous measure of diversification has been found to have good construct validity relatively to other diversification measures (Chatterjee & Blocher, 1992; Hoskisson et al., 1993). Therefore, restructuring scope for a restructured firm is the difference of the diversification index between the starting year and the ending year of its restructuring period, or [DELTA]DT=D[T.sub.ending] - D[T.sub.starting]. where DT refers to the total diversification index. The business segment data for the sample firms were obtained from Moody's Industrial Manual and company annual report.

Model Testing

The hypotheses are tested using ANCOVA with orthogonal comparisons. Covariates included firm size, financial leverage and prior performance, since they were likely the confounding factors when performance (ROA) and R&D intensity were compared across restructured and nonrestructured groups. ANCOVA plus a priori orthogonal comparisons rather than post hoc multiple comparisons were employed based on the following. First, there are only as many of them as there are degrees of freedom in orthogonal comparison, so the temptation to over-spending degrees of freedom is avoided. Second, orthogonal comparisons analyze nonoverlapping variance. If one of them is significant, it has no bearing on the significance of another of them. Third, because they are independent, if all k-1 orthogonal comparisons are performed, the sum of the sum of squares for the comparisons is the same as the sum of squares for the IV in omnibus ANCOVA. That is, the sum of squares for the effect has been broken down into the k-1 orthogonal comparisons that comprise it. The idea behind the test was that the sum of weighted means is equal to zero when the null hypothesis is true. The more the sum diverges from zero, the greater the confidence with which the null hypothesis is to be rejected. Table 1 reports the weighting coefficients for orthogonal comparisons and their theoretical justification.

RESULTS

Table 2 and Table 3 provide a summary of results from analysis of covariance with adjusted performance and change in performance as the dependent variable respectively, size, financial restructuring and prior performance as the covariates, and group as the categorical variable. In both situations, I found that the effect of group was significant (F=2.78, p<0.1 for adjusted performance; F=3.99, p<0.05 for change in performance), suggesting the existence of significant differences in performance and performance change among the groups. Planned orthogonal comparisons provided information of the sources of between-cell mean differences. Comparison 1, which is related to hypothesis 1a and hypothesis 1b, predicting that the performance and performance improvement between restructured and non-restructured firms are not significantly different from zero, was not supported (t = 1.2799, p>0.1 for adjusted performance; t =1.4568, p>0.1 for change in performance). Comparison 2 was statistically significant (t = 1.8146, p<0.1 for adjusted performance; t = -2.2339, p<0.05 for change performance), suggesting that the existence of significant differences in performance and performance improvement within restructured group, between refocused and diversified group. On further examination, the means of performance and improvement in performance for the refocused firms and diversified firms demonstrated that refocused firms outperformed diversified and also experienced greater performance improvement than nonrestructured firms. Therefore, hypotheses 2a and hypothesis 2b were confirmed. Covariates including size, prior performance and financial restructuring were all statistically significant, providing further evidence of the need for controlling these factors.

As Table 4 indicates, comparison 1 was not statistically significant (t = - 0.7035, p>0.1), suggesting that there is no significant R&D intensity difference between restructured and nonrestructured firms. Therefore, hypothesis 1c, stating that R&D intensity is greater for restructured firms than nonrestructured firms, was not confirmed. However, comparison 2 was statistically significant (t = 1.8088, p<0.1), suggesting the existence of significant R&D intensity differences within the restructured group. Further examination of the means of the refocused and diversified firms indicated that R&D intensity is greater for the refocused firms than that for diversified firms, therefore confirming hypothesis 3a. The tests of changes in R&D intensity between restructured group and nonrestructured group, within restructured group between refocused and diversified firms are illustrated in Table 5. The omnibus test indicated that the effect of group on change in R&D intensity was statistically significant, suggesting the existence of mean differences between groups. Orthogonal comparison provided information regarding where the mean differences were stemmed from. Hypothesis 1d, which is consistent with comparison 1, was not confirmed, suggesting that the change in R&D intensity between restructured and nonrestructured firms is statistically insignificant (t = 1.0506, p>0.1). Comparison 2 was statistically significant (t = - 1.8282, p<0.1), confirming hypothesis 3b, stating that change in R&D intensity is greater for refocused firms than that of diversified firms.

In all four ANCOVA models, univariate homogeneity of variance tests, using Cochrans C and Barlett-Box F, was statistically insignificant, therefore suggesting that the assumptions of analysis of covariance were met.

DISCUSSION

Many writers have postulated a relationship between the degree of diversification and business performance (Gort, 1962; Carter, 1977; Amit & Livnat, 1988) and R&D intensity (Hitt & Snell, 1987; Hoskisson et al., 1993), and between the types of diversification (related vs unrelated) and performance (Rumelt, 1974; Christensen & Montgomery, 1979; Bettis, 1981; Grant, Jammine & Thomas, 1988). However, there is little empirical evidence to suggest how change in business diversity--corporate restructuring activities may directly influence a firm s performance and long-term competitiveness (proxy by R&D intensity) (Hoskisson & Johnson, 1988, Markides, 1995). The results of this study are generally consistent with the predictions of over-diversification hypothesis in general and more detailed hypotheses developed here.

This study demonstrated that there are no significant differences in performance and R&D intensity between restructured and nonrestructured firms. The insignificant findings can be primarily explained by the counter moves of the refocused firms and diversified firms within the restructured sample. As the orthogonal comparisons suggested, performance and R&D intensity for refocused firms were significantly greater than those for diversified firms. Not surprisingly, at the aggregate level, the differences between restructured and nonrestructured firms across the two consequence measures cannot be detected. Nevertheless, the findings, consistent with Markidess (1995) and Brumagim and Klavans (1994), challenge the normative assertion that corporate restructuring is positively associated with performance. It further suggests that the consequences of corporate restructuring are not unitary, and depends on the nature of corporate restructuring activities--restructuring scope.

First, restructuring scope, or an increase in business diversity, was negatively associated with post-restructuring performance utter controlling for size, capital structure, industry structure and firms' prior performance. More specifically, post-restructuring performances were significant higher in refocused firms than in diversified firms. This finding is consistent with the argument of diversity-performance relationships in the diversification research area. For example, Amit and Livnat (1988) found that diversification is negatively related to profitability in their randomly selected firms from Compustat. Similarly, in their investigation of 48 U.K. companies, Grinyer, Yasai-Ardekani and Albazzaz (1980) suggested that a negative relationship is generally observed between diversity and performance measured by return-on-investment (ROI). In particular, the reported findings supported the notion of an optimal level of diversification, beyond which firm's performance suffers (Markides, 1992, 1995). Since most conglomerates have been over-diversified, refocusing or a reduction in business diversity should be associated with performance improvement (Comment & Jarrel, 1991), while further diversification may result in decreased performance. Additionally, the results also lend support to the propositions of transaction cost economists (i.e., Montgomery & Wernefelt, 1988), who argue that the relationship between diversification and its marginal benefits is a decreasing function, and the benefits to be gained from over diversification are greatly outweighed by the inefficiencies incurred (Reed & Sharp, 1987). As firms diversify away from their core, increasing governance costs (Bhide, 1989), weakened or even loss of control (Hoskisson & Turk, 1990) and underutilized capacity (Casson, 1984), may marginalize the advantages gained from diversification.

Second, I found that a negative relationship between restructuring scope and change in R&D intensity and that refocusers experienced substantially greater increase in R&D intensity than that of diversifiers. However, such relationship is asymmetric, which is only partially consistent with previous studies which have shown the existence of a substitution relationship between diversification and a firm's expenditure on research and development (Baysingers & Hoskisson, 1989; Hoskisson & Johnson, 1992). On the one hand, refocusing may lead to an increase in R&D intensity. Resources from sell-offs may redirect to invest on research and development. A reduction of diversified scope may reassure management's strategic control, which emphasizes firm's long-term competitiveness (i.e., R&D) rather than short-term financial return. On the other hand, this study also demonstrated that an increase in diversification may not necessarily lead to reduction in R&D expenditure. Further T-statistics indicated that the change in R&D intensity for the diversifers is not significantly different from zero (p=0.05 level), suggesting that R&D intensity for the diversifiers almost remains unchanged during the restructuring period. It therefore implies that as firms further increase their diversified scope and a firm's size their R&D expenditure increases rather than decreases almost in proportion to the size increase. This interesting finding is contradictory to the substitution hypothesis which predicts that firms partly finance diversification through reduction in R&D expenditure. Several possible reasons may explain such an asymmetric relationship. First, innovations in takeover financing during the 1980s enable companies to complete the takeover using little of their own financial resource (Lipton & Steinberger, 1988), which may otherwise have to curtail resources on research and development. Second, the business operating environment during the 1980s is characterized by turbulence in which technological innovations and demands change quickly (D'Aveni & Illinitch, 1992; Quinn, Doorley & Paquette, 1990), and by radical increases in the number of international competitors who emphasize on R&D capability and organizational flexibility (Jarillo, 1988). Corporate America were therefore forced to increase R&D expenditures in order to stay competitive and maintain existing market share (Richeto, 1988). Third, increased diversification scope and firm size reduced top management employment risk, which may subsequently increase the managerial capacity of absorbing riskier decisions such as investments in R&D. Fourth, not all corporate restructuring is resorted to external acquisitions and divestitures. Diversification through internal ventures usually relies on innovations. Given the above-mentioned rationales and the negative relationship between restructuring scope and R&D intensity, I would expect at least unchanged R&D intensity for diversified firms and therefore a partial substitution between diversification and R&D intensity.

In summary, this study found that corporate restructuring activities are the major predictors of both short-term accounting performance as well as long-term competitiveness (R&D intensity). Nevertheless, the directions of influence depend on the different restructuring strategies adopted by the firm.

CONCLUSIONS AND FUTURE RESEARCH DIRECTIONS

Compared to other restructuring research, the current research is unique and contributes to the extant strategy research in the following aspects.

First, although a number of studies have identified the factors that prompted the corporate restructuring wave in the 1980s, the consequences of corporate restructuring, both firms' short-run accounting performance and long-term competitiveness, are under-explored. By focusing on post-restructuring consequences, this study carries significant theoretical significance and managerial importance. The importance of business performance in strategy management has been argued along three dimensions--namely theoretical, empirical, and managerial (Cameron & Whetten, 1983). Theoretically, the concept of post-restructuring performance is at the center of restructuring research. Most strategic management theories either implicitly or explicitly underscore performance implications (Hoskisson & Turk, 1990). Empirically, strategy research studies can employ the construct of post-restructuring consequences to examine a variety of restructuring strategies and restructuring process issues. The managerial importance of post-restructuring consequences is also highlighted in the many prescriptions offered for performance improvements (e.g., Nash, 1983). The current result-centered research is consistent with Bowman & Singh's (1993) definition of researching meaningful strategic questions.

Second, this research focuses on changes in business portfolio rather than individual acquisitions or divestitures. More specifically, this study is only concerned with the set of divestitures and acquisitions carried out in the context of portfolio restructuring, rather than individual divestment or acquisition events. Therefore, the current corporate-level study is different from conventional business-level research of acquisitions and divestitures, and other restructuring research which only focuses on "de-diversification" (i.e., Markides, 1992, 1994; Hoskisson et al., 1994).

Our findings stand in sharp contrast to the extant literature and general assertion that restructuring is always good. The finding of no significant difference between restructured and nonrestructured firms, and the significant negative relations between restructuring scope, performance and R&D intensity highlights the importance of the adoption of appropriate restructuring strategy.

This research also raises a number of interesting issues that should be addressed with continuing research efforts from both theoretical and methodological standpoints. The first is to develop a measurement model for several important constructs. For example, post-restructuring performance may be better gauged by both accounting-based performance ratios as well as market-based performance ratios. Accounting data, once universally used to gauge performance, are now recognized to have limitations arising from accounting rules and conventions, making inter-firm comparisons difficult. By contrast, market-based measures also have shortcomings due to their reliance on expectational equilibrium and questions relating to the adequacy of the capital asset pricing model or the statistical market model of firm performance. Some theorists have suggested that a more appropriate policy may be to pursue multiple measures of performance to foster accumulation of knowledge (i.e., Amit & Livnat, 1988).

Second, it would be fruitful to examine how the different diversity measures affect the results reported here. This study adopted the entropy measure of business diversity as validated by Palepu (1985). However, there are diverse ways of measuring business diversity, such as Rumelt's (1974) strategic categories and the traditional way of counting the number of businesses a firm operates. The inconsistency in the measure of business diversity across diversity studies makes the comparisons of findings extremely difficult, if not impossible. Therefore it is worthwhile to test the sensitivity of the analysis--to what extent the proposed relationships and the reported findings are affected by the different business diversification measures.

TABLE 1
Weighting Coefficients for Orthogonal Comparisons

Groups         Refocused   Nonrestructured   Diversified

Comparison 1   1           -2                1

Comparison 2   -1          0                 1

Groups         Theoretical Justifications

Comparison 1   Comparison between nonrestructured
               firms and restructured firms which
               comprise refocused and diversified
               firms.

Comparison 2   Comparison within restructured
               firms, between refocused and
               diversified firms.

TABLE 2
A Summary of ANCOVA with Orthogonal Comparisons: Post-Restructuring
Performance (1)

Sources of    Sum of Square       Degrees of   Means       F
Variation                         Freedom      Square

Within+       6087.52             138          44.11
  Residual
Regression    1355.09             3            451.70      10.24 ***
Groups        244.92              2            122.46      2.78 *
(Model) (2)   1743.69             5            348.74      7.91 ***
(Total)       7831.21             143          54.76

              Parameter           Coeffi-      Std. Err.   t-value
                                  cients (3)

Orthogonal    Comparison 1        3.2348       2.5274      1.2799
Comparisons   Comparison 2        2.4578       1.3545      1.8146 *

Covariates    Financial           -0.1885      0.030       -2.426 **
                Restructuring
              Size                0.1650       0.323       2.114 **
              Prior Performance   0.3416       0.133       4.300 ***

*** p < 0.01

** p < 0.05

* p < 0.1

(1) univariate Homogeneity of variance tests:
Cochran's C(47,3) = 0.38875 (p = 0.484),
Bartlett-Box F(2, 42215) = 0.92524 (p = 0.397).

(2) The sums of square (Model and Total) have been adjusted for
unequal sizes of the cells.

(3) Coefficients for covariates are standardized beta weights.

TABLE 3
A Summary of ANCOVA with Orthogonal Comparisons: Change in
Performance (1)

Sources of    Sum of Square       Degrees of   Means       F
Variation                         Freedom      Square

Within+       6157.28             138          44.62
  Residual
Regression    776.34              3            258.78      5.80 ***
Groups        356.32              2            178.16      3.99 **
(Model) (2)   1017.47             5            214.29      4.80 ***
(Total)       7228.75             143          50.55

              Parameter           Coeffi-      Std. Err.   t-value
                                  cients (3)

Orthogonal    Comparison 1        3.7031       2.5418      1.4568
Comparisons   Comparison 2        -3.0431      1.3622      -2.2339 **

Covariates    Financial           -0.2208      0.030       -2.714 ***
                Restructuring
              Size                0.1715       0.325       2.098 **
              Prior Performance   -0.2211      0.134       -2.659 ***

*** p<0.01

** p<0.05

* p<0.1

(1) Univariate Homogeneity of variance tests:
Cochran's C(47, 3) = 0.3803 (p = 0.598),
Bartlett-Box F(2, 42215) = 0.9293 (p = 0.395).

(2) The sums of square (Model and Total) have been adjusted for
unequal sizes of the cells.

(3) Coefficients for covariates are standardized beta weights.

TABLE 4
A Summary of ANCOVA with Orthogonal Comparisons: R&D Intensity (1)

Sources of    Sum of Square       df                 Means    F
Variation                                            Square

Within+       1319.96             136                9.71
  Residual
Regression    64.25               3                  21.42    2.21 *
Groups        33.83               2                  16.91    1.74
(Model) (2)   126.52              5                  25.30    2.61 **
(Total)       1446.48             141                10.26

              Parameter           Coefficients (3)   Std.     t-value
                                                     Err.

Orthogonal    Comparison 1        -0.8613            1.2243   -0.7035
Comparisons
              Comparison 2        1.1552             0.6389   1.8088 *
Covariates    Financial           -0.1574            0.014    -1.859 *
                Restructuring
              Size                0.1165             0.155    1.372
              Prior Performance   0.1106             0.071    1.259

*** p<0.01

** p<0.05

* p<0.1

(1) Univariate Homogeneity of variance tests:
Cochran's C(47, 3) = 0.4342 (p = 0.124),
Bartlett-Box F(2, 40513) = 1.4779 (p = 0.2280).

(2) The sums of square (Model and Total) have been adjusted for
unequal sizes of the cells.

(3) Coefficients for covariates are standardized beta weights.

TABLE 5
A Summary of ANCOVA with Orthogonal Comparisons: Change in R&D
Intensity (1)

Sources of    Sum of Square       df           Means       F
Variation                                      Square

Within+       626.17              136          4.60
  Residual
Regression    69.57               3            23.19       5.04 ***
Groups        23.30               2            11.65       2.53 **
(Model) (2)   104.38              5            20.88       4.53 ***
(Total)       730.55              141          5.18

              Parameter           Coeffi-      Std. Err.   t-value
                                  cients (3)

Orthogonal    Comparison 1        0.8859       0.8432      1.0506
Comparisons   Comparison 2        -0.8042      0.4399      -1.8282 *

Covariates    Financial           -0.1837      0.010       -2.236 **
                restructuring
              Size                0.0801       0.107       0.974
              Prior Performance   0.2623       0.049       3.079 ***

*** p<0.01

** p<0.05

* p<0.1

(1) Univariate Homogeneity of variance tests:
Cochran's C(46, 3) = 0.4058 (p = 0.309),
Bartlett-Box F(2, 40513) = 1.3263 (p = 0.266).

(2) The sums of square (Model and Total) have been adjusted for
unequal sizes of the cells.

(3) Coefficients for covariates are standardized beta weights.

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Jianwen Liao is currently on the faculty of Department of Management and Marketing in School of Business and Management at Northeastern Illinois University. He has also had academic appointments from DePaul University, Hong Kong University of Science and Technology (HKUST), China Europe International Business School (CEIBS). Dr. Liao's research expertise and teaching interests are in the areas of strategic formulation and implementation, management of technological innovation, venture creation process, and entrepreneurial growth strategies as well. His research work has been published in academic journals such as Family Business Review, Journal of High Tech Management Research, Frontier of Entrepreneurship Research, International Journal of Management and Computing. He has also presented more than 40 papers in regional, national and international conferences. Additionally, he also serves as a consultant for major multinational companies as well as high tech startups. He received his doctorate in strategic management from Southern Illinois University at Carbondale.