Strategic Determinants of Executive Compensation in Small Publicly Traded Firms
1997; Wiley; Volume: 35; Issue: 2 Linguagem: Inglês
ISSN
0047-2778
Autores Tópico(s)Corporate Finance and Governance
ResumoAn important assumption of strategic human resource management is that managing a firm's human resources well is vital to gaining competitive success. It is often stated that the design and implementation of an appropriate organizational reward system is a critical dimension of managing human resources in all organizations (Milkovich and Newman 1996). Moreover, the agency literature (Pratt and Zeckhauser 1985; Fama 1980) suggests that top managers, like other employees, need to be motivated to achieve specific organizational performance objectives. Thus, given this kind of theoretical interest and the close scrutiny that the popular press focuses on the issue of compensation to chief executive officers (CEOs), it is not surprising that so much intellectual effort is expended in the academic literature identifying the key control variables of executive compensation. The issue of performance-contingent pay has been examined from a wide variety of perspectives and across many disciplines (Miller 1995; Veliyath, Ferris, and Ramaswamy 1994; Hill and Phan 1991; Gerhart and Milkovich 1990; Ehrenberg 1990; Gibbons and Murphy 1990; Leonard 1990; Abowd 1990; Deckop 1988; Gomez-Mejia, Tosi, and Hinkin 1987; Deckop and Mahoney 1982; Loomis 1982; Ciscel and Carroll 1980; Foster 1980; Lewellen and Huntsman 1970; Baumol 1959; and others). Empirical research on CEO pay has provided mixed results. For example, some authors state that the nexus between pay and performance at the executive level is either nonexistent or very weak. Compensation is often declared excessively high (Crystal 1991; Loomis 1982; Redling 1981; and Yarrow 1972); unrelated to the firm's performance (Crystal 1991; Redling 1981); or, if related, only to short-term performance (Rappaport 1978). Other studies claim that CEO compensation is more closely related to firm size (measured by sales or assets) than to profit. That is, sales have been found to be a stronger predictor of salary and bonus than profit (Roberts 1959; McGuire, Chiu, and Elbing 1962; Ciscel and Carroll 1980). Research in this area by Gibbons and Murphy (1990) suggests that changes in CEO compensation should be related to corporate performance relative to some comparison group, rather than to absolute corporate performance. However, the majority of the studies in the area of executive compensation focus on large organizations and use the data for Fortune 500 firms. It is not at all clear whether or not the few variables that do appear to be statistically significant in explaining how compensation is determined in large firms are also important determinants of executive compensation in small firms. Small firms often operate in highly competitive environments, with two major objectives: growth (Rue and Byars 1989) and survival, especially in the face of global competition (Holt 1993). Consequently, this study concentrates on small, publicly traded firms in order to broaden our understanding of the relationship between pay and performance for CEOs of small firms. In addition to the conventional performance variables such as return on equity (ROE), sales, and growth in sales, this study also examines in detail the role of insiders on the of directors, how much of the firm is owned by the members (referred to here as board ownership), and the firm's risk. Given the unique circumstances of small firms, there could be significant differences between the coefficients of explanatory variables for large and small firms. It is doubtful that one could use a sample consisting of both large and small firms and efficiently capture the firm size effect by merely introducing a dummy variable in the regression equation. Indeed, the results of this study indicate that the differences in the organizational structure, the relationship between the CEO and the board, and the role of insiders on the cannot possibly be captured by placing a single dummy variable in the regression equation. …
Referência(s)