Determinants and Process of the Choice of Goal Difficulty

Abstract

A laboratory study was designed to examine the impact of methods of payment (piece-rate vs. hourly flat-rate), choice of self-set goals (hard, easy, and free-choice), and self-esteem on the choice of goal difficulty. A significant (p = .01) two-way interaction between task-specific self-esteem and methods of payment was found to influence the choice of goal difficulty. High task-specific self-esteem subjects-as opposed to low task-specific self-esteem subjects-set significantly harder goals under the piece-rate plans than under the hourly flat-rate plans. In addition, a significant (p = .003) two-way interaction between choice of self-set goals and task-specific self-esteem was found to influence perceived total valences of job performance. Perceived total valences of job performance mediates the effects of task-specific self-esteem and choice of self-set goals on the choice of goal difficulty.

Determinants, Process, and Consequences of Personal Goals and Performance

“…Perceived goal valences are the anticipated satisfaction of attaining a specific level of performance/goals (Vroom, 1964). Several researchers (Campbell, 1982;Hollenbeck & Brief, 1987;Hollenbeck & Klein, 1987;Klein, 1991;Locke & Latham, 1990;Matsui et al 1981;Mento et al, 1992;Meyer & Gellatly, 1988;Moussa, 1996;Riedel et al, 1988;Tubbs, Boehne, & Dahi, 1993) have examined the relationship between goal setting and expectancy theory. For example, Klein (1991) and Riedel et al (1988) found that expectancy theory constructs influence personal goals.…”

“…Moreover, we expect the highest level of performance to be under the straight piece-rate, followed by the differential piece-rate with goal attainment step bonus, and hourly flat rate. The motivational influence of contingent rewards as compared to noncontingent rewards is well documented by research (see Jenkin et al, 1998;Lawler, 1987;Moussa, 1996;Scott, Farh, & Podsakoff, 1988;Wagner, Rubin, & Callahan, 1988). Based on these arguments, the following hypothesis is developed.…”

“…Ample research exists that strongly supports the positive relationship between goal difficulty and performance (e.g., Locke & Latham, 1990, Tubbs, 1986 as well as the effects of monetary incentives in increasing performance and modifying behavior (e.g., Jenkin, Gupta, Mitra, & Shaw, 1998;Lawler, 1987;Locke, Feren, McCaleb, Shaw, & Denny, 1980;Moussa, 1996Moussa, , 1990. Although researchers (e.g., Locke, 1968;Locke, Bryan, & Kendall, 1968;Locke & Latham, 1990) have emphasized the importance of connecting goals to incentives to enhance performance, Erez, Gopher, and Arzi (1990), Locke andLatham (1984, 1990), Mowen, Middlemist and Luther (1981), Wright (1989Wright ( , 1994, and Wright and Kacmar (1995) have shown that tying monetary incentives to goal attainment encourages individuals to perform poorly and to set lower goals.…”

Do versus Don’t: The Impact of Framing on Goal-Level Setting

“…Goal setting is instrumental not only to goal achievement, but also to higher-order needs such as self-completion (e.g., Higgins 1988;Gollwitzer, Wicklund & Hilton 1982). We therefore contribute to a larger stream of research focusing on the role of the self in motivated (consumer) behavior (Moussa 1996;Fishbach 2012, 2015). A feeling of failing to live up to important https://mc.manuscriptcentral.com/jconres standards is aversive and drives self-improvement motivations, even in the stage of the goal level decision and before any actual performance has taken place (see Duke and Amir 2019).…”

The Fit Between Purchase Situations and B2B E-Marketplaces and its Impact on Relationship Success

“…Since for the variance analysis the independent variables have to be nominal (Elsbach 1994, Moussa 1996, Backhaus et al 2000, the construct purchase situation and B2B E-marketplace have been grouped in three equal sized groups for classifying the extent of relationship support and requirement. The results are displayed in the following The res s of the 2-factor variance analysis support the res ult ults of the hierarchical regression nalysis.…”