# What drives a salesperson’s goal achievement? An empirical examination

V. Kumar (Department of Marketing, Georgia State University, Atlanta, Georgia, USA)
Ashley Goreczny (Department of Marketing, Georgia State University, Atlanta, Georgia, USA)
Todd Maurer (Department of Managerial Sciences, Robinson College of Business, Georgia State University, Atlanta, Georgia, USA)

ISSN: 0885-8624

Publication date: 5 February 2018

## Abstract

### Purpose

The purpose of this study is to understand how a salesperson’s preset goals, customer satisfaction levels and past performance affect the extent of goal achievement, as well as how job-specific attitudes and emotions affect the relationship between preset goals and goal achievement.

### Design/methodology/approach

This study uses a modeling framework with both main, moderating and mediating effects, using transaction data and survey results from a telecommunications firm.

### Findings

The results indicate that preset goals and customer satisfaction, interestingly, have an inverted-U relationships with goal achievement. Further, attitudes and emotions regarding workplace conduciveness and workplace ethics and diversity, reduce the effect preset goals have on goal achievement. However, attitudes and emotions regarding workplace philosophy strengthens the effect preset goals have on goal achievement, whereas with disagreement, this relationship diminishes.

### Research limitations/implications

Two of the primary limitations of this study are: one, because of the cross-sectional nature of the study, there is limited opportunity to control for unobserved heterogeneity; and two, performance goal achievement, though is important for the firm, is one of many potential goals that affect a salesperson. For example, customer satisfaction goals or a one-time special event goals could play a role. Therefore, only using performance goal achievement could be a limitation of this study.

### Originality/value

This study contributes to academic literature in three ways. First, it demonstrates the diminishing effect of customer satisfaction on goal achievement. Second, it identifies an inverse U-shaped relationship between preset goals and goal achievement. Finally, it examines how attitudes and emotions regarding workplace culture (conduciveness, ethics and diversity and philosophy) affect the relationship between preset goals and goal achievement.

## Keywords

#### Citation

Kumar, V., Goreczny, A. and Maurer, T. (2018), "What drives a salesperson’s goal achievement? An empirical examination", Journal of Business & Industrial Marketing, Vol. 33 No. 1, pp. 3-18. https://doi.org/10.1108/JBIM-06-2017-0128

### Publisher

:

Emerald Publishing Limited

One of the most important concerns a manager has, is whether they are assisting their key employees to reach their highest potential. As reported in wsj.com, “Technical sales and sales-management positions play a critical role for USA businesses […]” (Weber, 2015). Without an effective salesforce closing sales, a company will be unable to consistently satisfy their stockholders. For example, this generation of employees are very different than their previous generation counterparts, as they are more confident in their abilities, more technologically sound, motivated by significant tasks and cautious to take on a fast-paced work environment such as sales (Myers and Sadaghiani, 2010; Chou, 2012; Weber, 2015). Also, it takes over a year for a company to gain the full capacity of a newly hired salesperson, as knowledge about the product and target market takes time to learn and adjust to. Therefore, strategically retaining a company’s present salesforce is a priority. To do this, supervisors must be able to effectively manage a salesforce with different skill levels, as there is a lot of variance in salesperson performance. For example, companies can have star performers, moderate performers and low performers (Kelley and Caplan, 1992). Though star performers achieve peak performance quality for the firm, low performers could contain an immense amount of talent that has not been discovered yet. With management that is informed about what motivates and drives their salesforce, the star performer’s category could grow and the low performers could become moderate performers or get efficiently weeded out. Proper salesforce management would minimize the millions of dollars companies spend because of salesforce turnover, in training, lost incentives, detriment to customer relationships, etc. (Bendapudi and Leone, 2002; Zoltners et al., 2008).

One of the drivers of salesforce motivation that managers must understand is optimal goal setting. Though goals keep employees motivated, satisfied and productive (Locke and Latham, 1990), optimal goal setting can be challenging for managers (Ordóñez et al., 2009). Previous literature finds that the type of goal, as well as goal difficulty increases performance (Kim, 1984; Latham and Baldes, 1975; Locke et al., 1970). To capture an understanding of optimal goal setting for their salesforce, open communication is a must (Kim and Hamner, 1976). However, this open communication might not capture the effect attitudes and emotions has on the extent to which a salesperson can achieve their goals. As stated by Locke (1996), “Human action cannot, in fact, be understood by looking at a man only from the outside or only at his internal physiology.” Therefore, managers could be overlooking one of the key ingredients of enhancing salesperson performance without further information.

Past research has conceptually studied the effects of goal setting on a salesperson’s performance and the direct effect of emotions on goal attainment (Locke et al., 1988; Seijts and Crim, 2006; Brockner and Higgins, 2001). However, there has been little research on how the relationship between a salesperson’s preset goals and the extent of their goal achievement varies by hihe/sher attitudes and emotions regarding workplace culture, such as environment, management, firm ethics and propensity to churn, among others. Yet, this effect cannot be studied independently to get a holistic understanding of what drives the extent of salesperson goal achievement. A salesperson who has been successful at selling (i.e. highly achieving their goals) might be affected by their attitudes and emotions regarding workplace culture differently than someone who has not been as successful. For the purpose of this study, attitudes are defined as evaluations that have a range from positive to negative and exist in a person’s memory (Olson and Zanna, 1993; Harmon-Jones et al., 2011). For example, stating that “people are having fun at this firm” is an item reflecting attitude. We define emotions as occurring timely to a stimulated event, regarding something important to the salesperson, causing a salesperson to focus everything on the stimulated event and reactive to changes in the environment, so though intense, having a short time period (Scherer, 2005). For example, joy or anger at the workplace can reflect emotions. This study captures the influence of both attitudes and emotions of salespeople on a variety of workplace specific topics. Therefore, using the goal-setting theory, as well as the identity theory, we propose the following research questions:

RQ1.

What role do preset goals, customer satisfaction levels and past performance levels play on a salesperson’s extent of goal achievement?

RQ2.

How do salesperson’s attitudes and emotions, regarding workplace culture, affect the relationship between preset goals and the extent of goal achievement?

RQ3.

Is the relationship between past performance and the extent of goal achievement mediated by preset goals?

RQ4.

Can managers enhance a salesperson’s extent of goal achievement based on the findings of this study?

The main goal of this research is to provide a theoretically and empirically robust framework to test these research questions. To do this, we develop hypotheses describing what drives levels of goal achievement using theories from the psychology, management and sales literature. As stated by the identity theory, a person’s future reactions are driven by their previous results (Stryker and Burke, 2000). Also, the goal-setting theory states that there is a relationship between performance and goal difficulty Miner (2005). Therefore, we use these principles as the overarching conceptual drivers in developing our proposed framework. These theories will be discussed in detail in the conceptual framework section. Next, we estimate a regression model that accounts for observed heterogeneity, using a salesperson-level cross-sectional dataset from a national telecommunications provider.

Our results indicate that preset goals and customer satisfaction, interestingly, have inverted U-shaped relationships with goal achievement, whereas past performance has a positive linear relationship with goal achievement. Further, attitudes and emotions regarding workplace conduciveness, as well as workplace ethics and diversity, weaken the inverted U-shaped relationship between preset goals and the extent of goal achievement. However, attitudes and emotions regarding the alignment between the manager’s guiding principles and the firm philosophy in the workplace creates a diverging relationship between preset goals and the extent of goal achievement. Specifically, at high levels of alignment, there is an inverted U-shaped relationship between preset goals and the extent of goal achievement. However, with low levels of alignment, the relationship becomes reversed (U-shaped). Therefore, as there is less alignment between the manager’s guiding principles in the workplace and the firm philosophy, low preset goals still elicits low levels of goal achievement; however, as preset goals become higher, there is an increasing effect on higher levels of goal achievement. This is the first study, to our knowledge, that examines:

• The inverted U-shaped relationship between preset goals and the extent of goal achievement;

• How customer satisfaction and previous performance, together, with preset goals drive the extent of goal achievement; and

• The effect attitudes and emotions of salespeople regarding workplace culture has on the “preset goal” to “goal achievement” relationship.

In the next sections, we discuss the motivation of this research, conceptual framework, methodology, results, discussion, limitations and future research.

## Research motivation

In this section, we highlight the need for studying the drivers of goal achievement from a managerial perspective and an academic perspective. We discuss the managerial perspective by using model-free evidence from our data, and the academic perspective through a review of the relevant literature.

### Managerial perspective

Model Free Evidence Our dataset consists of 1,399 salespeople from a national telecommunications firm during April 2011. Also, in the month of April 2011, a survey was conducted using a questionnaire regarding the attitudes and emotions salespeople have towards different aspects of workplace culture in the firm. Upon a review of the dataset, we found a clear discrepancy in the extent of goal achievement in our data. For example, two salespeople who started with a similar sales performance in the previous month, March 2011 (approximately $4,500 and$5,000 in sales revenue), did not have a similar performance in April 2011. We can see in Figure 1 that both salespeople had a goal of around $3,500 in April. Yet, while both salespeople decreased their total performance, Salesperson A’s performance level dropped by around$1,200, twice the amount of Salesperson B. Further, Salesperson B’s goal was met, but Salesperson A’s goal was not. Despite the lack of longitudinal data, we can observe the cross-sectional heterogeneity. This demonstrates that goal achievement is a phenomenon that managers need to better understand to anticipate when a certain salesperson will be unsuccessful/successful. This will aid in the development of salesforce strategies.

Salespeople could also be influenced in their extent of goal achieving ability, by their attitudes and emotions regarding the workplace culture of the firm. For example, if a salesperson strongly agreed that they would be happy to spend the rest of their career with this organization, they might push themselves to close one additional sale. Therefore, we examined Salesperson A’s and Salesperson B’s responses from 6th April 2011 survey, to see if their attitudes and emotions are different. As illustrated in Figure 2, survey responses regarding workplace conduciveness, as well as agreement in the workplace philosophy are opposite for the two salespeople, and Salesperson B more strongly disagreed that the firm has workplace ethics and diversity than Salesperson A. Overall, Salesperson B has stronger levels of agreement or disagreement than Salesperson A. These responses display the need to study the effect attitudes and emotions have on the relationship between preset goals and the extent of goal achievement.

The goal-setting theory posits that goals are a major part of increasing a firm’s bottom line (Latham and Seijts, 1999). The importance of effective goal setting has been studied from various perspectives (Locke et al., 1970; Miner, 2005; Latham and Baldes, 1975). For example, Bandura and Locke (2003) find that personal goals and self-efficacy enhance motivation and performance. However, our study is unique by proposing to test the relationship between preset goals, past performance and customer satisfaction on the extent of goal achievement.

Further, previous literature has examined goal achievement behavior from a variety of angles. It has been studied in numerous settings and across multiple countries (Locke and Latham, 1990; Mitchell and Daniels, 2003). For example, Gollwitzer and Sheeran (2006) used a meta-analysis to understand the relationship between implementation intentions, preset goals and goal attainment. Past literature has also used experiments to understand goal commitment and performance (money earned) by using need for achievement and self-efficacy, respectively (Latham and Seijts, 1999; Hollenbeck et al., 1989). Further, both Cron and Slocum (1986) and Locke et al. (1981) studied how to enhance salesperson performance, though Cron and Slocum (1986) took a survey-based approach to study how past performance and work environment attitudes affect performance, whereas Locke et al. (1981) summarized 48 studies and concluded that preset goals, need for achievement and self-efficacy are factors that need to be considered in attempting to improve performance. Figure 3 summarizes the literature overview.

The ability to set goals to achieve optimal performance is well understood. However, this relationship has been thought to be strictly positive and linear, unless goals are outside the capacity of the salesperson (Locke and Latham, 2002). Further, how emotions and attitudes affect this relationship is not well researched. For example, what is not known is how a salesperson feels about the ethics of the firm or feels the level of ethics their direct manager has. These feelings can change a salesperson’s ability to be motivated by their preset goals, thus changing the relationship between preset goals and the extent of goal achievement. Therefore, another unique aspect of this study is that we test the moderating effect of workplace culture specific attitudes and emotions between preset goals and the goal achievement behavior. Upon examination of past literature and popular press, we find that prevalent workplace culture attitudes and emotions are:

Further, how past performance and customer satisfaction affects the extent of goal achievement can also be very important for creating managerial strategies, yet has not been empirically tested. Therefore, an advancement to the academic literature is the inclusion of the proposed variables, as well as, in capturing the moderating effects of workplace culture attitudes and emotions on preset goals and the extent of goal achievement, and the mediating effects of preset goals on the relationship between past performance and goal achievement behavior.

## Conceptual framework

To understand what drives the extent of goal achievement, we study the influence of personal effects (customer satisfaction and performance levels) on the extent of goal achievement as well as the external effect of managerially set goals on the extent of goal achievement. The overall foundation for this framework has been developed from the identity theory and the goal-setting theory. Specifically, the identity theory helps us understand how a salesperson views himself/herself within the firm through hihe/sher past behavior using both cognitive and motivational processes (Stryker and Burke, 2000). If the salesperson is succeeding, they will feel motivated and will then, achieve more. For example, Zimmerman et al. (1992) shows students with high senses of focus and drive, or self-efficacy, regarding their education (typically because of previous academic achievement) have higher academic performance. When a salesperson’s confidence increases, their performance on all accounts will also increase, thereby creating higher firm performance levels (Gist, 1987). Further, a salesperson wants to maintain their performance consistency within the firm, and as they succeed at this, their self-efficacy will be elevated (Stets and Burke, 2000). Applying this concept in a salesforce setting, the identity theory predicts that past performance results influence self-efficacy and, therefore, will influence future performance behaviors.

In the goal-setting theory, it is shown that goals can change how an employee performs. As goal difficulty increases, performance increases, which can save a firm hundreds of dollars (Latham and Baldes, 1975). The goal-setting theory is based on an action caused by a purpose, or “final causality” as named by Aristotle (Locke, 1996; Latham and Locke, 1991). However, a significantly challenging goal that is seemingly unachievable can cause an employee to lose motivation. This high goal can also cause a salesperson to push their customers too hard for a sale, harm the customer’s perceptions of the firm, jeopardize future purchases and ultimately demotivate the employee (Ordóñez et al., 2009; Miner, 2005). However, if a salesperson’s performance goal is too easily obtainable, salespeople might not have enough motivation, resulting in lost sales for the firm. Further, specific goal type can also change the effect a goal has on a person (Elliot and Harackiewicz, 1994). For example, for a particular type of person, goals that are task-focused can motivate better than goals that are mastery-focused. That is, goals regarding the number of items to sell will motivate better than goals that are about becoming an expert in the service the firm offers, as the “expert” goal is not as tangible. Therefore, two people with the same goals can behave differently, depending on their personality and experience. An effective goal setting for each employee is a strategy that needs to be perfected in management. By using these theories, we propose our conceptual framework, as seen in Figure 4. We discuss the proposed main effects, the moderating effects and the mediating effects in detail in the following section.

### Past performance

Zimmerman et al. (1992) studied the role of how self-efficacy and preset goals affect the student’s final performance. The identity theory predicts that positive behaviors in the past enable the salesperson to enhance hihe/sher role within the organization, which improves self-efficacy (Stajkovic and Luthans, 1998). Based on self-efficacy theory, self-efficacy improves as past performance improves (Bandura, 1977). Then, as self-efficacy improves, future performance also improves (Gist, 1987). Therefore, as past performance increases, future performance will increase. Thus:

H1.

As a salesperson’s past performance increases, that salesperson’s extent of goal achievement increases.

### Customer satisfaction

Self-efficacy affects both a salesperson’s sales performance and their customer satisfaction performance. If a salesperson has the skills to make their customers happy, they will have an increased self-verification and, therefore, increased belief in their abilities. For example, to increase a customer’s perception of service quality, a salesperson must have high levels of self-efficacy (Hartline and Ferrell, 1996). This is further seen from George (1998), who finds that as salespeople become more positive in their work place, customers’ needs are met at a higher level. Not only does self-efficacy and positive attitudes elevate customer satisfaction scores, but as a result of increased satisfaction, sales performance increases because of customers’ needs being met (Saxe and Weitz, 1982). However, a satisfied customer can only increase a salesperson’s performance by the amount of the share of wallet that customer possesses. Therefore, the positive effect customer satisfaction has on the extent of goal achievement can only increase to a certain extent, after which the increasing effect will level off. Thus:

H2.

As a salesperson’s customer satisfaction increases, that salesperson’s extent of goal achievement increases at a diminishing rate.

### Preset goals

As mentioned in the introduction of this study, appropriate goal-setting has a huge effect on a company’s bottom line because an employee’s motivation and performance changes as goals change (Latham and Baldes, 1975; Locke and Latham, 1990). Following the goal setting theory, as goal difficulty increases, performance increases (Locke and Latham, 2002; Miner, 2005). However, if the goal is too difficult and/or seemingly unobtainable, motivation levels will decrease or unethical behavior will ensue (Schweitzer et al., 2004; Ordóñez et al., 2009). Further, if goals appear threatening to the salesperson, for example if they focus on the potential for failure, performance will reduce compared to salespeople who are not threatened by the goal (Locke and Latham, 2006). Essentially, if goals are too easy or too difficult, levels of goal achievement will be low, but within a “sweet spot” of preset goals, levels of goal achievement will be optimized. Thus:

H3.

Preset goal of the salesperson has an inverted U-shaped relationship with that salesperson’s extent of goal achievement.

### Moderating role of attitudes and emotions

As noted previously, following the goal setting theory, there is an ideal range for goals to be optimally motivational. However, we expect that this effect changes based on a salesperson’s attitudes and emotions, regarding workplace culture, for three reasons. First, there are numerous studies on how attitudes and emotions affect an employee’s performance (Cron and Slocum, 1986; Schat and Frone, 2011; Cropanzano et al., 2003). For example, the type of focus an employee has affects both their emotions and levels of goal achievement (Brockner and Higgins, 2001), and hihe/sher emotional exhaustion stemming from feelings of burnout or unfairness affects job performance (Cropanzano et al., 2003; Maslach and Jackson, 1981; Wright and Bonett, 1997). Further, as Bond and Bunce (2003) find, the attitude an employee has toward accepting their situation and environment changes their performance level. Therefore, it is evident that emotions and attitudes, whether strongly (by frustration) or slightly (by optimism) (McColl-Kennedy and Anderson, 2002), impact an employee’s performance results. The effect attitudes and emotions have on performance has also been studied in popular press. Specifically, Barsade and O’Neill (2016) state that research over the years has found that both positive and negative emotions affect employee performance.

Second, attitudes and emotions regarding workplace culture can further change a salesperson’s performance. Workplace culture can be considered a set of thoughts that are shared by the social unit, in the workplace (O’Reilly et al., 1991). O’Reilly et al. (1991) discuss that when a social unit shares values, their beliefs also become aligned, and their behavior follows. Examples of workplace culture are how well salespeople can function in the workplace, if the manager’s guiding principles align with the firm’s philosophy, and finally, the firm’s standard of diverse and ethical principles. Numerous studies, from popular press, management literature, as well as human resources literature, discuss how workplace culture affects employees (Holmes and Marra, 2002, Sheridan, 1992; Barsade and O’Neill, 2016). For example, Brightman and Sayeed (1990) found that senior employees more easily identified and dealt with culture gaps within the division of their organization. This ability causes the senior employees to be more versatile at work and, therefore, achieve more effective performance (Merrill and Reid, 1981). Thus, the study of whether the manager’s guiding principles align with the firm’s philosophy is a concern to managers. Further, how well salespeople can function in the workplace can cause a change in performance. For example, Huselid (1995) concluded that high performance work practices enhances employee productivity and overall firm performance. High performance work practices include enabling knowledgeable employees to improve how their jobs are performed, as well as incentivizing successful employees. This type of workplace culture will enhance all salespeople’s extent of goal achievement no matter their past performance, thereby suggesting that attitudes and emotions regarding workplace culture causes the relationship between past performance and the extent of goal achievement to weaken. Finally, organizations having a high standard of diversity and ethics will enhance their competitive advantage (Gilbert et al., 1999). This advantage stems from less employee turnover, more collaboration in the workplace and more creativity, to name a few.

Third, as the attitudes and emotions of our study relies on extrinsic motivation, we use the expectancy theory to understand if attitudes and emotions drive a salesperson’s extent of goal achievement. This theory states that employees who are extrinsically motivated will perform better (Kumar et al., 2014; Walker et al., 1977). An example of extrinsic motivation in the marketing literature is employee engagement. This literature has found that the more an employee is engaged with the firm, the more emotionally connected they are to the firm, leading to reduced costs, enhanced customer satisfaction and increased customer perceptions on quality (Seijts and Crim, 2006; Kumar and Pansari, 2017). This engagement is partially driven by managers. Thus, as workplace functionality, alignment of the principle-to-firm philosophy and the standard of diversity and ethics increases, performance and, in turn, the extent of goal achievement increases for all salespeople, no matter their past performance level. Therefore:

H4.

As a salesperson perceives an increase in the alignment between the manager’s guiding principles and the firm philosophy, the inverted U-shaped relationship between preset goals and a salesperson’s extent of goal achievement weakens.

H5.

As a salesperson’s perceived functionality in the workplace increases, the inverted U-shaped relationship between preset goals and a salesperson’s extent of goal achievement weakens.

H6.

As a salesperson perceives an increase in the standard of diversity and ethics, the inverted U- shaped relationship between preset goals and a salesperson’s extent of goal achievement weakens.

### Mediating role of preset goals

A question arises based on how past performance influences the extent of goal achievement, “Are there mediation effects at play here?” (Hayes, 2012; Baron and Kenny, 1986). A series of qualitative surveys were conducted to understand how managers determined how to set salesperson goals. They stated that a salesperson’s performance, in part, affects their goals. Goals are also set based on the market conditions, the manager’s belief in the salesperson’s ability, the salesperson’s work schedule, among other influences. If the salesperson improves in their selling ability, goals will increase to keep the salesperson motivated. So, as a salesperson becomes better at their job, management will reexamine goals to achieve peak motivation and performance from their salespeople. Therefore:

H7.

Preset goals mediate the relationship between past performance and the extent of goal achievement.

## Methodology

### Data

The data come from a Fortune 500 company that sells telecommunications services to consumers, in the USA. The data consist of 1,399 salespeople, from 727 stores, in April 2011. Further, the firm conducted a survey, via a questionnaire, in April 2011, regarding salespeople’s opinions on topics such as work environment, company characteristics and the diversity and ethics of management.

To capture the questions of our study, we focus on salesperson performance, where goals are preset by the managers of the organization. To take into account the potential for observed heterogeneity, we include salesperson identifying variables, such as age, tenure at the firm and store location. Store location is measured by the region of the salesperson’s assigned store. Further, because of the store size influencing the potential for higher levels of goal achievement, we also include the square footage of the store the salesperson is based out of as a control variable. We present the operationalization, where the variable was adapted from, and the expected effects for the variables used in this study in Table I.

A salesperson can generate revenue in six ways: handset sales, upgrades in service plans or cell phones, recurring revenue from contract, line activations, accessory sales and warranties. Therefore, the past performance variable is the summation of the revenue the salesperson achieved from all of these revenue products and services in March 2011. However, because of the repercussions of breaking a contract, it is assumed that once a contract is initiated from items such as line activations and warranties, it will not be broken. Therefore, though there will be recurring revenue in the future from a salesperson’s initial performance, there will not be future goals associated with these contracts. In turn, the preset goals variable is operationalized by the summation of revenue goals for handset sales, upgrades in service plans or cell phones, line activations, accessory sales and warranties. The dependent variable of interest is a salesperson’s extent of goal achievement, which is measured as the difference between the salesperson’s monthly revenue performance and their preset goals. The goal achievement variable ranges from −$10,345 to$6,199 with a mean of −77. To capture customer satisfaction, customers responded to a survey regarding their satisfaction of their experience with the salesperson and the store. The firm tested this survey method with a multi-item scale; however, it was found that they could capture the customer’s opinions with a single-item scale. Specifically, customers were asked, “On a scale from 1 to 5, overall, how satisfied were you with your experience in the [Brand] Store that you visited?” Customer ratings below five are considered poor performance; therefore, customer satisfactions scores are the percentage of fives the salesperson achieved of all customer satisfaction surveys completed in April 2011. Table II presents the basic summary statistics. ### Factor analysis To test our hypotheses concerning attitudes and emotions regarding workplace culture, we focus on the domain of the construct, item generation and item purification. The initial scale items consist of three forms of questions: Q1. Existing scales refined from the literature (Hackman and Oldham, 1974; Busch, 1980; Allen and Meyer, 1990). Q2. Measures based on popular press (Barsade and O’Neill, 2016). Q3. Measures based on manager interviews. This scale was then administered to the salesforce by the firm in April 2011. The scale is measured on a five-point Likert scale, which ranges from “Strongly Disagree” to “Strongly Agree”. To refine our scales, an exploratory factor analysis (EFA) was conducted. We used the varimax rotation, as our factors are considered orthogonal and independent of each other. After the EFA, we removed 41 out of 76 items based on the items cross loading among the factors or the item’s factor loadings were less than 0.7, as suggested by Nunnally (1978). In other words, there were many items that appeared to be redundant. Upon examining the results where an eigenvalue was greater than one (Hair, 2010; Kumar et al., 2015), we have three factors. The Cronbach’s alpha for all the factors are higher than 0.95, and the Eigen value explained by each factor are: Factor 1 is 11.4, Factor 2 is 8.15 and Factor 3 is 7.98. This results in the three factors explaining 78 per cent of the variance in the scale items. The outcomes of the exploratory factor analysis are provided in Tables III and IV. The first factor consists of statements such as, “At this firm, we have the resources and authority to get the job done”, “At this firm, we expect and accept nothing less than excellent results” and “At this firm, we consider the customer in every decision”. Basically, this factor represents that the salesperson considers the firm a great place to work, feels they have a clear contribution to the firm and there is a clear philosophy followed by the firm. Thus, high values of this factor means there is an alignment between the manager’s guiding principles and the firm philosophy in the workplace. The second factor has statements such as, “I am treated with respect when I am at work”, “My organization’s top leaders act in ways consistent with what they say” and “My organization promotes our own employees whenever possible”. Overall, this factor represents that the workplace has good communication, promotes internally, has a respectful environment, accepts trial and error, is customer focused and encourages timely decision-making. Therefore, high values of Factor 2 means there is a higher level of perceived functionality in the workplace. Finally, the third factor includes statements such as, “Unethical behavior is not tolerated in my department”, “Senior leaders at my company are honest and possess integrity” and “Achieving diversity (in markets, in hiring, in thought and ideas) is part of my company/org.’s strategy”. It represents that there is a high level of ethics and diversity at all levels, reporting unethical behavior is encouraged, unethical behavior is quickly responded to and employees feel they can find another job easily. Consequently, high values of workplace diversity and ethics means there is a high standard of diversity and ethics in the workplace. Therefore, we label the three factors as Workplace Philosophy (F1), Workplace Conduciveness (F2) and Workplace Diversity and Ethics (F3). ### Model We use a multiple regression model to explain the extent of goal achievement behavior of salespeople [Equation (1)]. In our model specification, we are attempting to understand how attitudes and emotions influence the relationship between a salesperson’s preset goals and the extent of their goal achievement behavior. Further, we are attempting to understand the mediating role preset goals have on the relationship between past performance and the extent of goal achievement. As mentioned previously, for richer results, we control for observed heterogeneity using control variables[1]. Model Specification: (1)yi=β0+β1PastPerfi+β2CSATi+β3CSATSqri+β4PresetGoalsi+β5PresetGoalsSqri+β6F1i+β7F2i+β8F3i+β9F1PGi+β10F1PG2+β11F2PGi+β12F2PG2ii+β13F3PGi+β14F3PG2+β15Agei+β16Tenurei+β17Locationii+β18StoreSizei+εi Where: yi = The Level of Goal Achievement of Salesperson ‘i’; β = Parameters to be estimated; PastPerfi = Performance in the Previous Period of Salesperson ‘i’; CSATi = Customer Satisfaction Level of Salesperson “i”; CSATSqri = Quadratic Term Individual Salesperson Customer Satisfaction Level; PresetGoalsi = Individual Salesperson Performance Goal (inRevenue);

PresetGoalsSqri

= Quadratic Term Individual Salesperson Performance Goal (in Revenue); F1i = Workplace Philosophy Factor Scores; F2i = Workplace Conduciveness Factor Scores; F3i = Workplace Diversity and Ethics Factor Scores; F1PGi = Interaction between Workplace Philosophy and Individual Salesperson Performance Goal of Salesperson “i”; F2PGi = Interaction between Workplace Conduciveness and Individual Salesperson Performance Goal of Salesperson “i”; F3PGi = Interaction between Workplace Diversity and Ethics and Individual Salesperson Performance Goal of Salesperson “i”; F1PGi2 = Squared Interaction between Workplace Philosophy and Individual Salesperson Performance Goal of Salesperson “i”; F2PGi2 = Squared Interaction between Workplace Conduciveness and Individual Salesperson Performance Goal of Salesperson “i”; F3PGi2 = Squared Interaction between Workplace Diversity and Ethics and Individual Salesperson Performance Goal of Salesperson “i”; Agei = Age of Salesperson “i”; Tenurei = Tenure of Salesperson “i”; Locationi = Region of the ith Salesperson’s Assigned Store; StoreSizei = The Size of the ith Salesperson’s Assigned Store; εi = Error Term of Salesperson “i”; and i = Salesperson. ### Mediation analysis To assess if preset goals mediates the relationship between past performance and the extent of goal achievement, we conducted a mediation analysis based on Baron and Kenny (1986)[2]. To enhance the robustness of our analysis, we include age, tenure, location and store size as control variables. The first step in the Baron and Kenny (1986) mediation analysis is to test the path between past performance and goal achievement [Equation (2)]: (2)GoalAchi=α1+cPastPerfi+δControlsi+e1 Where: c = the parameter for the relationship between Past Performance and the extent of Goal Achievement; α1 = the intercept for this equation; Controlsi = the control variables of Salesperson “i”; δ = the parameter estimates for the control variables; e1 = the error term for this equation; and i = Salesperson. Then, the path between past performance and preset goals is tested [Equation (3)]: (3)PresetGoalsi=α2+aPastPerfi+δControlsi+e2 Where: a = the parameter for the relationship between Preset Goals and Past Performance; α2 = the intercept for this equation; Controlsi = the control variables of Salesperson “i”; δ = the parameter estimates for the control variables; e2 = the error term for this equation; and i = Salesperson. Finally, the paths between preset goals and the extent of goal achievement, as well as past performance and the extent of goal achievement are tested [Equation (4)]: (4)GoalAchi=α3+cPastPerfi+bPresetGoalsi+δControlsi+e3 Where: c = the parameter for the relationship between Past Performance and the extent of Goal Achievement; b = the parameter for the relationship between Preset Goals and the extent of Goal Achievement; α3 = the intercept for this equation; Controlsi = the control variables of Salesperson “i”; δ = the parameter estimates for the control variables; e3 = the error term for this equation; and i = Salesperson. Finally, as goal achievement is an objective measure and the independent variables (customer satisfaction, preset goals, past performance and the survey items) were all given by different sources, common method bias is not a problem in this study (See the variable source information provided in Table II) (Siemsen et al., 2010). The outcome of this analysis is discussed further in the next section. ## Results The summary of our results can be seen in Table V. Recall that our first hypothesis proposes that with an increase in a salesperson’s past performance, a salesperson’s extent of goal achievement will increase. We find the effect to be positive and significant (β1 = 0.251, p < 0.01), thus supporting H1. The second hypothesis theorizes that as a salesperson’s customer satisfaction increases, that salesperson’s extent of goal achievement increases with diminishing returns. From the estimation, we find that the linear effect is positive and significant (β2 = 26859.43, p < 0.01), but the squared term is negative and significant (β3 = −1947.74, p < 0.01). This supports H2, implying the diminishing return relationship between customer satisfaction and the extent of goal achievement. Another quadratic relationship we’re hypothesizing is hypothesis three, which proposes that there is an inverted U-shaped relationship between preset goals and the extent of goal achievement. We find the main effect to be positive and significant (β4 = 0.206, p < 0.05), whereas the squared term effect is negative and significant (β5 = −0.0001, p < 0.01), thus supporting H3. ### Moderating effects H4 posited that as a salesperson perceives an increase in the alignment between the manager’s guiding principles and the firm philosophy, the inverted U-shaped relationship between preset goals and a salesperson’s extent of goal achievement weakens. We find the linear effect to be positive and significant (β9 = 0.093, p < 0.01) and the quadratic effect to be negative and significant (β10 = −0.00003, p < 0.01). Using Dawson (2014)’s two-way interaction graphing techniques, we can visually see the moderated relationship. Attitudes and emotions regarding the alignment between the manager’s guiding principles in the workplace and the firm philosophy creates a diverging relationship between preset goals and the extent of goal achievement. At high levels of alignment, there is convex relationship with diminishing returns between preset goals and the extent of goal achievement. However, with low levels of alignment, the relationship becomes reversed. Therefore, as there is less alignment between the manager’s guiding principles in the workplace and the firm philosophy, low preset goals still elicits a low level of goal achievement; however, as preset goals become higher, there is an increasing effect on a higher level of goal achievement (Figure 5). The fifth hypothesis, which states that as a salesperson’s perceived functionality in the workplace increases, the inverted U-shaped relationship between preset goals and a salesperson’s extent of goal achievement weakens, is supported. The linear and quadratic effects are significant (β11 = −0.1755, p < 0.01 and β12 = 0.0001, p < 0.01, respectively). This can be seen in Figure 6, which shows that both high and low values in the agreement of the workplace philosophy have a weakened concave pattern. This phenomenon also occurs for the sixth hypothesis, which states that as a salesperson perceives an increase in the standard of diversity and ethics, the inverted U-shaped relationship between preset goals and a salesperson’s extent of goal achievement weakens. The linear effect is negative and significant (β13 = −0.1944, p < 0.01), whereas the quadratic effect is positive and significant (β14 = 0.0001, p < 0.01); thus, H6 is also supported (Figure 7). ### Mediating effects Finally, we looked at the results of our mediation analysis. As displayed in Figure 8, we find that the relationship between past performance and the extent of goal achievement without other variables, or the “c” path, is significant (c = 0.35, p < 0.01). Further, we find that past performance significant predicts preset goals, or path “a”, (a = 0.06, p < 0.01). Finally, to measure paths “c’” and “b”, we run a regression model with past performance and preset goals predicting the extent of goal achievement. We find that both c’ and b are significant. However, because of equation (5), we can see that we must compare the c path to the combination of the other paths (Hayes, 2012): (5)c1=c1+a1b1 The past performance coefficient, “c’”, only slightly reduces compared to the c path, rather than becoming zero, so we have partial mediation rather than full mediation[3]. Finally, to test the overall goodness of fit, the coefficient of determination, or the adjusted R-squared, is 0.571, showing a fair amount of variation of the extent of goal achievement explained by past performance, preset goals and customer satisfaction. In the next section, we discuss these results and their implications. Also, because the models use a multiple regression model, we can compare the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC) of our focal model to a reduced model that excludes the moderators and squared term for the extent of goal achievement, as these variables have never been tested before in literature. We find that the AIC of the focal model is 10,484.36 and of the reduced model is 10,525.81. Further, the BIC of the focal model is 10502.69 and of the reduced model is 10,534.98. These results demonstrate the superiority of our focal model, showing that it is critical to account for the quadratic relationship preset goals have on the extent of goal achievement, as well as the moderating effect attitudes and emotions have on this relationship. ## Discussion The implications of this study have both an academic and managerial impact. Our main questions of this research is to understand how much preset goals, customer satisfaction and past performance levels affect the extent of goal achievement, how a salesperson’s attitudes and emotions regarding workplace culture affect the relationship between preset goals and the extent of goal achievement, if there is a mediating effect between past performance and the extent of goal achievement via preset goals and finally, strategies managers can take to enhance the effect of goal achievement. To begin our discussion, though the role of past performance on the extent of goal achievement has been suggested before (Zimmerman et al., 1992; Bandura, 1977; Gist, 1987; Locke et al., 1970), the nonlinear roles of both customer satisfaction and preset goals on the extent of goal achievement are uniquely interesting. There is a logical link between an increase in customer satisfaction and a salesperson’s extent on goal achievement. However, this is a diminishing relationship. If there are new customers, a salesperson’s extent of goal achievement can still be affected, even though they have not previously interacted with the firm. Thus, our research first question regarding the role preset goals, customer satisfaction and past performance play on a salesperson’s extent of goal achievement has been addressed. Though goal setting has been discussed by physiology literature (Locke and Latham, 2002; Miner, 2005), an inverted U-shaped relationship between preset goals and the level of goal achievement has not been proven, to our knowledge[4]. However, our results indicate the existence of such a relationship, enhancing academic literature in this field. This means that managers must be conscious regarding their salesperson’s drivers. If the manager is too lax for a salesperson or too strict, they will not have optimal levels of goal achievement. Further, if the manager does not personalize goals for specific salespeople, they could be missing out on revenue. Discussing the next research question, our results indicate that certain attitudes and emotions regarding workplace culture affect the relationship between preset goals and the extent of goal achievement differently. First, attitudes and emotions regarding the alignment between the manager’s guiding principles in the workplace and the firm philosophy creates a diverging relationship between preset goals and levels of goal achievement. Specifically, at high levels of alignment, there is a concave-shaped relationship with diminishing returns between preset goals and the extent of goal achievement. However, with low levels of alignment, the relationship becomes reversed. Therefore, as there is less alignment between guiding principles in the workplace and firm philosophy, low preset goals still elicits low levels of goal achievement; however, as preset goals become higher, there is an increasing effect on higher levels of goal achievement. This could be driven from the salesperson’s need for direction in their workplace being fulfilled via their goals. However, attitudes and emotions regarding the standard of ethics and diversity in the workplace weaken the quadratic relationship between preset goals and the extent of goal achievement. This result could stem from the culture of equality. Salespeople will feel more influenced by their teammates and managers than by their personal goals. They will look to each other to uphold a high standard of ethics, and work together to build solutions to increase diversity in their teams. For example, as agreement increases that people of all backgrounds can succeed in this company, the salesperson’s idea of what it takes for them to succeed does not change if their goals are difficult. The knowledge of how to be successful in the firm will be an integration of goals, customer satisfaction, team work, product knowledge and so on. Finally, attitudes and emotions regarding the perceived functionality in the workplace also weakens the quadratic relationship between preset goals and the extent of goal achievement. This supports engagement literature, which states that people who perceive a conducive workplace are self-motivating (Kumar and Pansari, 2017; Seijts and Crim, 2006). Taking an example from the survey results, as a salesperson perceives that employees are encouraged to find new ways of solving problems, they will not need guidance on how to approach a new solution. They will attempt to be creative and think outside the box; therefore, goals will be less influential. However, if creativity is seemingly discouraged in the work environment, salespeople, across the board, will become more influenced by their goals, as they will look for rules in the more structured culture. Thus, our research second question regarding how a salesperson’s attitudes and emotions, regarding workplace culture, affect the relationship between preset goals and the extent of goal achievement has been addressed. Our next research question, regarding the relationship between past performance, preset goals and the extent of goal achievement, is important for managers. At the focal firm, an increase in past performance increases preset goals. Then, this effect influences the levels of goal achievement. However, because this is a partial mediation, managers must pay attention to the direct effect past performance has on the extent of goal achievement as well as the influence of preset goals. Therefore, managers must balance how much they change preset goals based on past performance, keeping a salesperson’s self-efficacy in mind. If a manager sets goals too difficult for the new level of self-efficacy in the salesperson, they could be reducing the possibility for the salesperson to reach the highest level of goal achievement (Zimmerman et al., 1992). Thus, our third research question has been addressed. The implications these results have on managers are significant. The ability for a manager to understand a salesperson’s attitudes and emotions regarding workplace culture causes that manager to pay more attention to each salesperson individually. Thus, suggesting that the firm might need to increase the number of managers per store. Further, the firm must understand that there are times when goals are very important in their motivation strategy, but in other times, goals are only a part of what motivates a salesperson. Communication in the firm appears to be a key way to motivate salespeople without the pressure of optimal goals. Following strategies similar to our suggestions can help managers enhance the salesforce in increasing their levels of goal achievement thus addressing our fourth research question. The implications on academic research are taking the discovery of the preset goals inverted U-shaped relationship with a salesperson’s extent of goal achievement further by including moderators regarding attitudes and emotions. This can have an impact on fields beyond marketing, such as organizational behavior, management and psychology. One approach to reducing the effect of preset goals on the extent of goal achievement is by letting the salespeople be involved in their goal setting (Zimmerman et al., 1992). If supervisors elicit control of a salesperson’s goals, there could be negative consequences, as customer satisfaction as well as performance can be harmed (Challagalla and Shervani, 1996). ## Limitations and future research First, this being a cross-sectional dataset, we’re not able to account for unobserved heterogeneity. This is the first time that any study is showing these effects; therefore, there is opportunity for future researchers to test the effects across segments through latent class regression analysis. Second, because of the potential bias of social desirability or mood state bias, the salespeople could have answered the survey items in a more favorable way to please the firm or a different way as per their mood at the time. Therefore, future researchers can conduct experiments to tease out these potential effects. Another limitation is the possibility of omitted variable bias, or endogeneity. There is a possibility of the existence of a third variable influencing preset goals and past performance, such as sales team pressure or manager pressure. Further, more emotion-based questions rather than primarily attitudes about the firm would enhance our understanding of the effect that attitudes and emotions have on the preset goal-to-goal achievement relationship. Therefore, future research could examine the possibility of these influences. Finally, performance goal achievement, though is important for the firm, is one of many potential goals that affect a salesperson. For example, customer satisfaction goals, goals regarding team work, or even one-time, special event goals. Therefore, only using goal achievement is a limitation of this study. Further, as suggested by Brockner and Higgins (2001), different types of goals can be achieved from different types of attitudes and emotions. For example, the authors mention that a person who is promotion-focused will be more likely to succeed with goals that help them align their performance with their ability to get a raise, whereas someone prevention-focused will be more likely to have high levels of goal achievement when goals are linked to ensuring nonlosses. Therefore, there is an opportunity for future research in examining our conceptual framework with different types of goals. Further, as the field of engagement increases in importance (Kumar and Pansari, 2014; Pansari and Kumar, 2017), it would be interesting to test how attitudes and emotions change the relationship between preset goals and the extent of goal achievement as salespeople become more or less engaged with the firm. ## Figures #### Figure 1 Levels of goal achievement for April 2011 #### Figure 2 Attitudes and emotions of salesperson a and B #### Figure 3 Select literature overview #### Figure 4 Conceptual framework #### Figure 5 Effect of workplace philosophy*preset goals on goal achievement #### Figure 6 Effect of workplace conduciveness*preset goals on goal achievement #### Figure 7 Effect of workplace diversity and ethics*preset goals on goal achievement #### Figure 8 Mediation analysis ## Table I Variable operationalization Variable Operationalization Definition adapted from Variable source Expected effect Goal achievement The difference between the salesperson’s monthly revenue performance and their preset goals (inRevenue) Gollwitzer and Sheeran (2006) NA NA
Past performance A salesperson’s previous month’s (March 2011) performance (in $Revenue) Barrick et al. (1993) Objective Performance + Preset goals A salesperson’s performance goal (in$Revenue) Smith et al. (1990) Salesperson’s Managers
Customer Satisfaction (CSAT) Per cent of a salesperson’s customer satisfaction surveys with a rating of 5, answering the question “Overall, how satisfied were you with your experience in the [Firm Name] Store that you
visited (1 = very dissatisfied to 5 = very satisfied).”
Crosby and Stephens (1987), Garbarino and Johnson (1999),
Wiley (1991)
Salesperson’s Customers
Factor1 - Workplace philosophy Exploratory factor analysis from a firm initiated survey via questionnaire Moderating variables Self-Reported by Salesperson
Factor2 – Workplace conduciveness Exploratory factor analysis from a firm initiated survey via questionnaire Self-Reported by
Salesperson
Factor3 – Workplace ethics and diversity Exploratory factor analysis from a firm initiated survey via questionnaire Self- Reported by Salesperson
Location Region of store. Either West, Southwest, Midwest, Southeast or Northeast Control Variables NA NA
Store size The square foot of the store the salesperson works
Age The salesperson’s age
Tenure The number of days the salesperson has been employed with the focal firm

## Table II

Mean and standard deviation of variables

Variables Mean SD
Goal achievement −77.24 1214
Past performance 3514 1630
Preset goals 3121 804.74
CSAT 0.77 0.15
Factor1 0 1
Factor2 0 1
Factor3 0 1
Age 26.28 4.74933
Tenure 235.89 131.54
NE Region 0.16 0.36
SE Region 0.18 0.39
SW Region 0.24 0.43
W Region 0.21 0.41
Square footage 2571 1317

## Table III

Correlation matrix

Correlations
Goal Ach 1
Past Perf 0.47*** 1
Preset Goals −0.52*** 0.11*** 1
Preset Gls^2 −0.62*** −0.01 0.94*** 1
CSAT 0.014 0.05* −0.04 −0.03 1
CSAT^2 0.002 0.03 −0.05* −0.04 0.99*** 1
Factor1 0.02 −0.01 −0.03 −0.02 −0.02 −0.02 1
Factor2 −0.001 −0.04 −0.01 −0.03 0.04 0.04 0 1
Factor3 0.04 0.06** 0.004 −0.01 0.04* 0.05* 0 0 1
F1*GAch 0.05** −0.001 −0.05* −0.05* −0.03 −0.02 0.97*** −0.01 0.01 1
F2*GAch 0.06* −0.03 −0.07*** −0.09*** 0.05* 0.05** −0.01 0.96*** 0.01 0.01 1
F3*GAch 0.09*** 0.06** −0.04* −0.07*** 0.05* 0.06** 0.01 0.01 0.97*** 0.02 0.01 1
F1*GA^2 0.09*** −0.001 −0.09*** −0.105*** −0.02 −0.02 0.82*** 0.01 0.01 0.93*** 0.08*** 0.02 1
F2*GA^2 0.15*** −0.01 −0.15*** −0.20*** 0.05* 0.05* 0.01 0.74*** 0.01 0.07*** 0.89*** 0.01 0.22*** 1
F3*GA^2 0.17*** 0.07*** −0.15*** −0.21*** 0.06** 0.06** 0.01 0.01 0.82*** 0.02 0.01 0.92*** 0.04 −0.02 1
Age −0.01 −0.04 −0.01 −0.02 0.01 0.01 −0.004 −0.05* 0.02 −0.01 −0.04 0.01 −0.003 −0.02 0.01 1
Tenure 0.13*** 0.29*** −0.03 −0.003 −0.04 −0.04 −0.05 −13*** −0.03 −0.02 −0.12 −0.03 −0.01 −0.1*** −0.04 −1*** 1
NE Reg. 0.06** 0.03 −0.07** −0.06** 0.01 −0.004 0.02 −0.0002 −0.03 0.02 0.001 −0.03 0.02 0.01 −0.02 0.01 −0.001 1
SE Reg. 0.04* 0.02 −0.03 −0.01 −0.02 −0.002 0.05* 0.05** −0.03 0.04* 0.05* −0.02 0.04 0.04 −0.04 −0.004 0.03 −0.20*** 1
SW Reg. −0.02 −0.04 0.02 0.01 −0.03 −0.04 −0.03 −0.08*** −0.01 −0.01 −0.10** −0.01 0.004 −0.04 0.01 0.04 −0.06** −0.24*** −0.27*** 1
W Reg. −0.04 0.03 0.15*** 0.10*** 0.02 0.02 −0.11*** 0.01 0.01 −0.11*** 0.02 0.01 −0.08*** 0.03 0.001 −0.04 −0.01 −0.22*** −0.25*** −0.29*** 1
Store Size 0.01 0.03 0.08*** 0.06** −0.08*** −0.08*** −0.04 −0.01 −0.02 −0.03 −0.02 −0.03 −0.03 −0.01 −0.05* −0.05* 0.03 0.04 −0.07** 0.09*** 06** 1
Notes:

*p < 0.1;

**p < 0.05;

***p < 0.01

## Table IV

Items F1: Workplace philosophy F2: Workplace conduciveness F3: Workplace ethics & diversity
My organization promotes our own employees whenever possible 0.74578
I am treated with respect when I am at work 0.73861
People here are encouraged to find new ways of solving problems 0.79683
My organization accepts mistakes in the process of trying new things 0.75883
I see cooperation across different departments and groups 0.70212
I get good information quickly from people within my organization 0.80346
I understand how my organization plans to be successful in the future 0.80874
My organization adapts well to changes that affect how we operate 0.82843
My organization’s strategy matches what our customers want 0.78926
My organization’s top leaders make good decisions in a reasonable amount of time 0.81141
My organization’s top leaders act in ways consistent with what they say 0.79162
My job responsibilities are clear to me 0.79826
I understand how my work projects or assignments are connected to my company’s overall strategy 0.80598
I would be happy to spend the rest of my career with this organization 0.72275
I would recommend this company as a great place to work 0.83143
At this firm, we act with a sense of urgency 0.84731
At this firm, we have the resources and authority to get the job done 0.8157
At this firm, we take responsibility for results and how they are achieved 0.89686
At this firm, we consider the customer in every decision 0.85846
At this firm, we work across departments to get the job done 0.77663
At this firm, we expect and accept nothing less than excellent results 0.88836
At this firm, we take responsibility for our job and career development 0.897
At this firm, we actively work to simplify and improve the business 0.86297
At this firm, we are intolerant of unethical behavior 0.80297
At this firm, we have fun 0.85584
Achieving diversity (in markets, in hiring, in thought and ideas) is part of my company/org.’s strategy 0.92792
People of all backgrounds (cultural, gender, age, religion, etc.) can succeed in my company/org −0.92886
I can report unethical behavior or practices without fear of retaliation at my company 0.91062
My company responds quickly and consistently to verified or proven unethical behavior −0.90933
Unethical behavior is not tolerated in my department 0.91714
I feel pressured to compromise my company’s Code of Conduct, company policy, or the law in order to achieve business goals −0.75279
Senior leaders at my company are honest and possess integrity 0.92334
Ethical expectations have been clearly communicated to me by my company −0.92301
If I wanted to, I could easily find a job with another company 0.89956
I feel I have too few options to consider leaving this company −0.81714
Notes:

Cronbach Alpha: Factor 1: 0.96; Factor 2: 0.97; Factor 3: 0.97

## Table V

Regression model results

Variable Coefficient SE Hypothesis
Intercept −2047.676*** 826.443
Past Performance 0.252*** 0.0136 H1: Supported
CSAT 2859.433** 1107.9923 H2: Supported
CSAT^2 −1947.739** 755.5689
Preset Goals 0.206** 0.09092 H3: Supported
Preset Goals^2 −0.0001*** 0.00001
Factor1 × GoalAch 0.093*** 0.0292 H4: Not Supported
F1 × GoalAch^2 −0.00003*** 0.00001
Factor2 × GoalAch −0.1755*** 0.0229 H5: Supported
F2 × GoalAch^2 0.0001*** 0.00001
Factor3 × GoalAch −0.1944*** 0.0239 H6: Supported
F3 × GoalAch^2 0.0001*** 0.00001
Factor 1 −22.500 21.849 N/A
Factor 2 48.085** 21.730
Factor 3 −6.597 21.831
Age 0.238 4.635
Northeast region 173.470** 72.470
Southeast region 226.756*** 69.513
Southwest region 53.280 65.392 Control Variables
West region 51.565 67.473
Store size 0.035** 0.017
Tenure 1.309*** 0.208
Notes:

*p < 0.1;

**p < 0.05;

***p < 0.01

## Notes

1.

The correlations between preset goals and past performance is low at 0.11 (p < 0.01). Therefore, there is limited multicollinearity between these variables (Kumar, 2015).

2.

For robustness, we also conducted the PROCESS, as created by Hayes (2012).

3.

This result was verified using PROCESS, as suggested by Hayes (2012).

4.

A paper by Atkinson (1958), discusses that task difficulty, measured as the probability of success, has an effect on performance in a nonlinear, inverse functional form. However, when task performance goals were measured, the author’s results have not been successfully duplicated.

## References

Allen, N.J. and Meyer, J.P. (1990), “The measurement and antecedents of affective, continuance and normative commitment to the organization”, Journal of occupational Psychology, Vol. 63 No. 1, pp. 1-18.

Atkinson, J.W. (1958), “Towards experimental analysis of human motivation in terms of motives, expectancies, and incentives”, Motives in Fantasy, Action and Society, Van Nostrand, Princeton, New Jersey, pp. 288-305.

Bandura, A. (1977), “Self-efficacy: Toward a unifying theory of behavioral change”, Psychological Review, Vol. 84 No. 2, p. 191.

Bandura, A. and Locke, E.A. (2003), “Negative self-efficacy and goal effects revisited”, The Journal of Applied Psychology, Vol. 88 No. 1, p. 87.

Baron, R.M. and Kenny, D.A. (1986), “The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations”, Journal of Personality and Social Psychology, Vol. 51 No. 6, p. 1173.

Barrick, M.R., Mount, M.K. and Strauss, J.P. (1993), “Conscientiousness and performance of sales representatives: test of the mediating effects of goal setting”, Journal of Applied Psychology, Vol. 78 No. 5, p. 715.

Barsade, S. and O’Neill, O.A. (2016), “Manage your emotional culture”, (accessed 20 May 2016).

Bendapudi, N. and Leone, R.P. (2002), “Managing business-to-business customer relationships following key contact employee turnover in a vendor firm”, Journal of Marketing, Vol. 66 No. 2, pp. 83-101.

Bond, F.W. and Bunce, D. (2003), “The role of acceptance and job control in mental health, job satisfaction, and work performance”, The Journal of Applied Psychology, Vol. 88 No. 6, p. 1057.

Brightman, H.J. and Sayeed, L. (1990), “The pervasiveness of senior management’s view of the cultural gaps within a division”, Group & Organization Management, Vol. 15 No. 3, pp. 266-278.

Brockner, J. and Higgins, E.T. (2001), “Regulatory focus theory: Implications for the study of emotions at work”, Organizational Behavior and Human Decision Processes, Vol. 86 No. 1, pp. 35-66.

Busch, P. (1980), “The sales manager’s bases of social power and influence upon the sales force”, The Journal of Marketing, Vol. 44 No. 3, pp. 91-101.

Challagalla, G.N. and Shervani, T.A. (1996), “Dimensions and types of supervisory control: effects on salesperson performance and satisfaction”, The Journal of Marketing, Vol. 60 No. 1, pp. 89-105.

Chou, S.Y. (2012), “Millennials in the workplace: A conceptual analysis of millennials’ leadership and followership styles”, International Journal of Human Resource Studies, Vol. 2 No. 2, p. 71.

Cron, W.L. and Slocum, J.W. Jr. (1986), “The influence of career stages on salespeople’s job attitudes, work perceptions, and performance”, Journal of Marketing Research, Vol. 23 No. 2, pp. 119-129.

Cropanzano, R., Rupp, D.E. and Byrne, Z.S. (2003), “The relationship of emotional exhaustion to work attitudes, job performance, and organizational citizenship behaviors”, Journal of Applied Psychology, Vol. 88 No. 1, p. 160.

Crosby, L.A. and Stephens, N. (1987), “Effects of relationship marketing on satisfaction, retention, and prices in the life insurance industry”, Journal of Marketing Research, Vol. 24 No. 4, pp. 404-411.

Dawson, J. (2014), “Interpreting interaction effects”, available at: www.jeremydawson.com/slopes.htm (accessed 5 May 2016).

Elliot, A.J. and Harackiewicz, J.M. (1994), “Goal setting, achievement orientation, and intrinsic motivation: a mediational analysis”, Journal of Personality and Social Psychology, Vol. 66 No. 5, p. 968.

Garbarino, E. and Johnson, M.S. (1999), “The different roles of satisfaction, trust, and commitment in customer relationships”, The Journal of Marketing, Vol. 63 No. 2, pp. 70-87.

George, J.M. (1998), “Salesperson mood at work: Implications for helping customers”, Journal of Personal Selling & Sales Management, Vol. 18 No. 3, pp. 23-30.

Gilbert, J.A., Stead, B.A. and Ivancevich, J.M. (1999), “Diversity management: a new organizational paradigm”, Journal of business Ethics, Vol. 21 No. 1, pp. 61-76.

Gist, M.E. (1987), “Self-efficacy: implications for organizational behavior and human resource management”, Academy of Management Review, Vol. 12 No. 3, pp. 472-485.

Gollwitzer, P.M. and Sheeran, P. (2006), “Implementation intentions and goal achievement: a Meta‐ analysis of effects and processes”, Advances in Experimental Social Psychology, Vol. 38, pp. 69-119.

Hair, J.F., William, C.B., Barry, J.B., Rolph, E.A. and Tatham, R. (2010), “Multivariate data analysis”, Pearson Prentice Hall, Upper Saddle River, NJ.

Hackman, J.R. and Oldham, G.R. (1974), “The job diagnostic survey: an instrument for the diagnosis of jobs and the evaluation of job redesign projects”, JSAS Catalog of Selected Documents in Psychology, Vol. 810 No. 4, p. 148.

Harmon-Jones, E., Harmon-Jones, C., Amodio, D.M. and Gable, P.A. (2011), “Attitudes toward emotions”, Journal of Personality and Social Psychology, Vol. 101 No. 6, p. 1332.

Hartline, M.D. and Ferrell, O.C. (1996), “The management of customer-contact service employees: an empirical investigation”, The Journal of Marketing, Vol. 60 No. 4, pp. 52-70.

Hayes, A.F. (2012), “Process: a versatile computational tool for observed variable mediation, moderation, and conditional process modeling”, White paper, available at: www.afhayes.com/public/process2012.pdf

Hollenbeck, J.R., Williams, C.R. and Klein, H.J. (1989), “An empirical examination of the antecedents of commitment to difficult goals”, Journal of Applied Psychology, Vol. 74 No. 1, p. 18.

Holmes, J. and Marra, M. (2002), “Having a laugh at work: how humour contributes to workplace culture”, Journal of Pragmatics, Vol. 34 No. 12, pp. 1683-1710.

Huselid, M.A. (1995), “The impact of human resource management practices on turnover, productivity, and corporate financial performance”, Academy of Management Journal, Vol. 38 No. 3, pp. 635-672.

Kelley, R. and Caplan, J. (1992), “How bell labs creates star performers”, Harvard Business Review, Vol. 71 No. 4, pp. 128-139.

Kim, J.S. (1984), “Effect of behavior plus outcome goal setting and feedback on employee satisfaction and performance”, Academy of Management Journal, Vol. 27 No. 1, pp. 139-149.

Kim, J.S. and Hamner, W.C. (1976), “Effect of performance feedback and goal setting on productivity and satisfaction in an organizational setting”, Journal of Applied Psychology, Vol. 61 No. 1, p. 48.

Kumar, V. (2015), Global Marketing Research, Sage, New Delhi.

Kumar, V., Bhagwat, Y. and Zhang, X. (2015), “Regaining ‘Lost’ customers: the predictive power of first-lifetime behavior, the reason for defection, and the nature of the win-back offer”, Journal of Marketing, Vol. 79 No. 4, pp. 34-55.

Kumar, V. and Pansari, A. (2014), “The construct, measurement, and impact of employee engagement: a marketing perspective”, Customer Needs and Solutions, Vol. 1 No. 1, pp. 52-67.

Kumar, V. and Pansari, A. (2017), “Competitive advantage through engagement”, Journal of Marketing Research, Vol. 81 No. 4.

Kumar, V., Sunder, S. and Leone, R.P. (2014), “Measuring and managing a salesperson’s future value to the firm”, Journal of Marketing Research, Vol. 51 No. 5, pp. 591-608.

Latham, G.P. and Baldes, J.J. (1975), “The” practical significance” of Locke’s theory of goal setting”, Journal of Applied Psychology, Vol. 60 No. 1, p. 122.

Latham, G.P. and Locke, E.A. (1991), “Self-regulation through goal setting”, Organizational Behavior and Human Decision Processes, Vol. 50 No. 2, pp. 212-247.

Latham, G.P. and Seijts, G.H. (1999), “The effects of proximal and distal goals on performance on a moderately complex task”, Journal of Organizational Behavior, Vol. 20 No. 4, pp. 421-429.

Locke, E.A. (1996), “Motivation through conscious goal setting”, Applied and Preventive Psychology, Vol. 5 No. 2, pp. 117-124.

Locke, E.A., Cartledge, N. and Knerr, C.S. (1970), “Studies of the relationship between satisfaction, goal- setting, and performance”, Organizational Behavior and Human Performance, Vol. 5 No. 2, pp. 135-158.

Locke, E.A. and Latham, G.P. (1990), “Work motivation and satisfaction: Light at the end of the tunnel”, Psychological Science, Vol. 1 No. 4, pp. 240-246.

Locke, E.A. and Latham, G.P. (2002), “Building a practically useful theory of goal setting and task motivation: a 35-year odyssey”, American Psychologist, Vol. 57 No. 9, p. 705.

Locke, E.A. and Latham, G.P. (2006), “New directions in goal-setting theory”, Current Directions in Psychological Science, Vol. 15 No. 5, pp. 265-268.

Locke, E.A., Latham, G.P. and Erez, M. (1988), “The determinants of goal commitment”, Academy of Management Review, Vol. 13 No. 1, pp. 23-39.

Locke, E.A., Shaw, K.N., Saari, L.M. and Latham, G.P. (1981), “Goal setting and task performance: 1969– 1980”, Psychological Bulletin, Vol. 90 No. 1, p. 125.

McColl-Kennedy, J.R. and Anderson, R.D. (2002), “Impact of leadership style and emotions on subordinate performance”, The Leadership Quarterly, Vol. 13 No. 5, pp. 545-559.

Maslach, C. and Jackson, S.E. (1981), “The measurement of experienced burnout”, Journal of Organizational Behavior, Vol. 2 No. 2, pp. 99-113.

Merrill, D.W. and Reid, R.H. (1981), “Personal styles & effective performance”, in Mitchell, T.R. and Daniels, D. (Eds), Motivation. Handbook of Psychology, CRC Press, FL, Vol. 12, pp. 225-254.

Mitchell, T.R. and Daniels, D. (2003), “Motivation,”, Handbook of Psychology, (Industrial and Organizational Psychology), Vol. 12, pp. 225-254.

Miner, J.B. (2005), “Goal-setting theory”, Organizational Behavior 1: Essential Theories of Motivation and Leadership, Prentice-Hall, India, Chapter 10, pp. 159-183.

Myers, K.K. and Sadaghiani, K. (2010), “Millennials in the workplace: A communication perspective on millennials’ organizational relationships and performance”, Journal of Business and Psychology, Vol. 25 No. 2, pp. 225-238.

Nunnally, J. (1978), Psychometric Methods, McGraw-Hill, New York.

Olson, J.M. and Zanna, M.P. (1993), “Attitudes and attitude change”, Annual review of Psychology, Vol. 44 No. 1, pp. 117-154.

O’Reilly, C.A., Jennifer, C. and David, F.C. (1991), “People and organizational culture: A profile comparison approach to assessing person-organization fit”, Academy of management journal, Vol. 34 No. 3, pp. 487-516.

Ordóñez, L.D., Schweitzer, M.E., Galinsky, A.D. and Bazerman, M.H. (2009), “Goals gone wild: The systematic side effects of overprescribing goal setting”, The Academy of Management Perspectives, Vol. 23 No. 1, pp. 6-16.

Pansari, A. and Kumar, V. (2017), “Customer engagement: the construct, antecedents and consequences”, Journal of the Academy of Marketing Science, Vol. 45 No. 3.

Saxe, R. and Weitz, B.A. (1982), “The SOCO scale: a measure of the customer orientation of salespeople”, Journal of Marketing Research, Vol. 19, pp. 343-351.

Schat, A.C. and Frone, M.R. (2011), “Exposure to psychological aggression at work and job performance: the mediating role of job attitudes and personal health”, Work and Stress, Vol. 25 No. 1, pp. 23-40.

Scherer, K.R. (2005), “What are emotions? And how can they be measured?”, Social Science Information, Vol. 44 No. 4, pp. 695-729.

Schweitzer, M.E., Ordóñez, L. and Douma, B. (2004), “Goal setting as a motivator of unethical behavior”, Academy of Management Journal, Vol. 47 No. 3, pp. 422-432.

Seijts, G.H. and Crim, D. (2006), “What engages employees the most or, the ten C’s of employee engagement”, Ivey Business Journal, Vol. 70 No. 4, pp. 1-5.

Siemsen, E., Roth, A. and Oliveira, P. (2010), “Common method bias in regression models with linear, quadratic, and interaction effects”, Organizational Research Methods, Vol. 13 No. 3, pp. 456-476.

Sheridan, J.E. (1992), “Organizational culture and employee retention”, Academy of management Journal, Vol. 35 No. 5, pp. 1036-1056.

Smith, K.G., Locke, E.A. and Barry, D. (1990), “Goal setting, planning, and organizational performance: an experimental simulation”, Organizational Behavior and Human Decision Processes, Vol. 46 No. 1, pp. 118-134.

Stajkovic, A.D. and Luthans, F. (1998), “Self-efficacy and work-related performance: a Meta-analysis”, Psychological Bulletin, Vol. 124 No. 2, p. 240.

Stets, J.E. and Burke, P.J. (2000), “Identity theory and social identity theory”, Social psychology Quarterly, Vol. 63 No. 3, pp. 224-237.

Stryker, S. and Burke, P.J. (2000), “The past, present, and future of an identity theory”, Social Psychology Quarterly, Vol. 63 No. 4, pp. 284-297.

Walker, O.C., Jr., Churchill, G.A., Jr. and Ford, N.M. (1977), “Motivation and performance in industrial selling: present knowledge and needed research”, Journal of Marketing Research, Vol. 14 No. 2, pp. 156-168.

Weber, L. (2015), “Why it’s so hard to fill sales jobs”, (accessed 21 March 2016).

Wiley, J.W. (1991), “Customer satisfaction: a supportive work environment and its financial cost”, People and Strategy, Vol. 14 No. 2, p. 117.

Wright, T.A. and Bonett, D.G. (1997), “Research the contribution of burnout to note work performance”, Journal of Organizational Behavior, Vol. 18 No. 5, pp. 491-499.

Zimmerman, B.J., Bandura, A. and Martinez-Pons, M. (1992), “Self-motivation for academic attainment: the role of self-efficacy beliefs and personal goal setting”, American Educational Research Journal, Vol. 29 No. 3, pp. 663-676.

Zoltners, A.A., Sinha, P. and Lorimer, S.E. (2008), “Sales force effectiveness: a framework for researchers and practitioners”, Journal of Personal Selling & Sales Management, Vol. 28 No. 2, pp. 115-131.

#### Supplementary materials

9781787561168.pdf (15.9 MB)
JBIM_33_1.pdf (3.6 MB)

## Acknowledgements

We thank the editors of this special issue, Leila Borders and Elyria Kemp for their support of this article. We thank an anonymous firm for providing us with the data for this study. We thank Sarang Sunder and Kihyun (Hannah) Kim for their helpful comments on various drafts of this article. We thank Renu for copy editing the manuscript.

## Corresponding author

V. Kumar is the corresponding author and can be contacted at: vk@gsu.edu