Do Performance Goals and Development, Feedback and Recognition, and a Climate of Trust Improve Employee Engagement in Small Businesses in the United States?

Small businesses are the predominant contributors to the U.S. economy, yet they face many challenges to remain competitive and sustainable. There are several reasons a small business could fail, including a lack of human resources, limited financial resources, competition, technological advancements, disaster, and globalization. Improving employee performance by getting them engaged and productive in their work is an issue that cannot be overlooked for small businesses to function and remain competitive. There is limited empirical evidence that explains the dimensions of performance management and employee engagement in small businesses. However, how small businesses sustain their long-term performance remains uncertain. This study sought to bring together two previously distinct constructs: overall employee engagement and overall performance management, characterized by performance goals and development, a climate of trust, and feedback and recognition. The research was correlational in nature. A survey was conducted to generate and analyze data gathered from 121 employees of small businesses located in the United States. A series of Pearson correlation analyses confirmed the existence of statistically significant positive relationships between employee engagement and each variable of performance management, namely performance goals and development, feedback and recognition, and climate of trust. Notwithstanding these positive correlations, a multiple regression model with the three performance management variables as independent variables and employee engagement as the dependent variable suggested that there was a statistically significant regression model F(3, 117) = 32.34, p < .001, R = .453, explaining 45.3% of the variability in employee engagement. Nonetheless, this model confirmed that the variables performance goals and development and climate of trust were not statistically significant in the model (p > .05). In other words, only the feedback and recognition variable was statistically significant in the regression model, suggesting that it explained most of the variability in engagement, including that already explained by the other two variables. Overall, the outcome of this study suggests that small businesses implementing performance management processes have more engaged employees. The conclusions drawn from these findings suggest that overall performance management and overall employee engagement contribute to small business productivity and organizational success.


Introduction
Employee engagement remains a critical concern for organizations and small businesses (Kapoor & Meacham, 2012;Lartey & Randall, 2021;Mishra et al., 2014). Increasingly, employee engagement has become well-known in businesses. Kahn (1990) defined engagement as the harnessing or the personal attaching of employees' selves to the work they perform. In recent years, human resources (HR) professionals have generated significant interest in employee engagement (Albdour & Altarawneh, 2014). Many researchers claim engagement has a positive relationship with performance management, productivity, employee satisfaction, and organizational outcomes (Heger, 2007;Mone & London, 2009;Robertson & Cooper, 2009). Employee engagement has also been shown to be strongly related to employee performance (Heger, 2007), positive organizational outcomes (Robertson & Cooper, 2009), and a positive impact on employees' psychological well-being (May et al., 2004). Additionally, studies have linked employee engagement to organizational commitment. According to Ali et al. (2013), employee engagement is the employee's long-term commitment to the organization. Despite the contributions provided by many scholars, engaging employees is significant because a business cannot function without its employees.
Small businesses constitute a driving force for both job creation and economic growth. In the United States, most small businesses, those with 500 or fewer employees, fail within the initial five years of operation ( Small Business Administration, 2012). Generally, the number of new small business firms that start in any given year is approximately equal to the ones that closed due to failure in the same year (Brown, 2007). The Small Business Administration (SBA, 2014) reported 10-12% of small firms both open and close annually. In other words, as one small business opens, another one is closing. Approximately two-thirds of small businesses survive up to two years, and about half of these businesses survive five years (SBA, 2012). Further, in 2013, a total of 33,212 small business bankruptcies were reported (SBA, 2014). However, it remains uncertain how to sustain long-term performance.
As for small businesses, improving employee performance by getting employees engaged in their work to be more productive is an issue that cannot be overlooked, in order to function and remain competitive. Scholars and practitioners have found positive relationships between performance management and employee engagement in larger companies. Small businesses are the predominant contributors to the U.S. economy, yet they face many challenges to remain competitive and sustainable. Limited empirical evidence exists that explains the dimensions that make up performance management structures that engage employees in small businesses.
Empirical studies show that out of every 100 new small businesses, approximately 70 of them are less likely to be successful (Ucbasaran et al., 2010). There may be several factors as to why small firms fail; however, employee engagement is an important element that can promote organizational success. For example, many companies show low productivity, although management reports that their employees are satisfied . Individuals like their jobs for various reasons. Heger (2007) found that employees who feel satisfied with their jobs are not necessarily engaged. Employees may share differences regarding how they feel about their work. However, employers that seek to gain a better understanding of their employees, including their interests and values, may discover ways to address business concerns. Heger suggested that employee engagement is a good measure for understanding the association between employee attitudes, behaviors, and business results. For this reason, researchers are taking more interest in studies regarding employee engagement and the relationship it has with small businesses (Bakker et al., 2007;Macey & Scheneider, 2008). The current research addresses the knowledge gap regarding the relationship, if any, between overall performance management activities (involving performance goals and development, feedback and recognition, and a climate of trust) and overall employee engagement within small businesses in the United States.

Small Businesses in the United States
Small businesses account for a relatively large segment of the U.S. economy (Stewart, 2002;Kowalewski & Phillips, 2012;Yallapragada & Bhuiyan, 2011). The number of businesses that are being generated annually can present an understanding of the high percentage of small businesses and their importance. Small business employers comprise approximately 99% of the U.S. economy, and the largest share of small business employment derives from firms with less than 100 employees (Small Business Administration, 2019). Undeniably, small businesses can be vital to the U.S. workforce. In 2011, small businesses created over half the jobs in the U.S. private workforce (Small Business Administration, 2014). The Small Business Administration (2014) reported small businesses created 60% of the net new jobs. Small businesses are important to the U.S. because they employ a majority of the workforce, which can affect the economic effectiveness.
Small businesses have trouble succeeding in a highly competitive business environment dominated by large firms (Brinckmann et al., 2010). Additionally, engaging employees and boosting productivity becomes difficult when the competitive business climate repeatedly hits an organization for many reasons (Catteeuw et al., 2007). As previously mentioned, today's competitive economy continuously undergoes rapid changes as businesses face a multitude of challenges. Small businesses face several challenges, including financial, globalization, competition, technological advancements, and disaster (Mone & London, 1998;Scarborough & Zimmerer, 2003). Among these challenges, a lack of adequate finances seems to be the primary cause of failure, with human resources in second place (Brown, 2007). O'Connell (2004) listed ten top reasons why organizations or businesses fail and claimed that ineffective communication skills and practices are the leading causes of organizational failure. Failing to clarify directions or poor performance expectations ranked fourth. A lack of personal integrity and trust ranked eighth, and poor planning practices and reactionary behavior ranked tenth. All these actions link employee engagement to some performance-management-related activity, which raised interest in examining the relationship between the three variables in small businesses.
Similarly, Mone and London (2009) argued setting meaningful and effective goals, building a climate of trust, providing constructive feedback, and recognizing employees' performance are employee engagement exercises that can lead to improved performance and business success. For small businesses to remain successful, it is imperative for the small business firm to be aware of the necessary skills and to hire employees to compensate for the missing skills (Yallapragada & Bhuiyan, 2011). Small businesses are operating in a competitive environment, which entails continuous improvements. Therefore, businesses are seeking ways to drive their performance to remain competitive (Markos & Sridevi, 2010). Nevertheless, most of these issues may be effectively addressed by one critical endeavor: employee engagement.

Employee Engagement
Recently, in the realm of human resources development (HRD), academia, and practitioners, employee engagement has become and remains a hot topic (Albrecht, 2012;Fairlie, 2011;Lartey & Randall, 2021;Saks, 2006) and a critical concern for organizations (Kapoor & Meachem, 2012). Researchers are taking more interest in studies regarding employee engagement (Bakker et al., 2007;Macey & Schneider, 2008) and its relationship with small business success. Presently, there is no universal agreement on the phenomenon of employee engagement (Markos & Sridevi, 2010). Employee engagement has many wide accepted definitions by scholars in the academic realm. However, several definitions of employee engagement have been presented in literature over the last two decades (Ali, 2013;Bhattacharya & Mukherjee, 2009;Dash, 2013;Kahn, 1990;Mani, 2011). According to Dash (2013), these definitions measure the employees' emotional attachments to their jobs, which directly influence their anticipation toward learning and performing at work. For example, Kahn (1990) defined employee engagement in management literature as the personal attaching of employees' selves to the work they perform. Lartey (2021) defined employee engagement as: a two-way relationship between an organization and a worker, in which the organization provides the worker with the environment and conditions to be successful through good leadership and management, and the worker provides the organization with a positive and self-motivated performance leading to the achievement of the organizational mission, vision, purpose, and goals (p. 137).
Similarly, many other scholars defined employee engagement as an employee's commitment and involvement level toward an organization and its values (Ali, 2013;Bhattacharya & Mukherjee, 2009;Dash, 2013;Mani, 2011). Moreover, Schaufeli et al. (2006) characterized employee engagement in three dimensions: vigor, dedication, and absorption. The authors noted that (a) vigor was characterized by high levels of energy and mental resilience while working; (b) dedication was characterized as a sense of significance, enthusiasm, inspiration, pride, and challenge; and (c) absorption was characterized by being fully concentrated and happily engrossed in one's work.
Presently, the U.S. spends over $720 million toward employee engagement improvements (Gerst, 2013). Small businesses that consider the impact employee engagement has on the business and the benefits that come with the employees may gain a competitive advantage. Importantly, employees possess the required knowledge a business needs to function. According to Lorenzet et al. (2006), companies rely on the knowledge, competence, and capabilities of their human assets as a competitive advantage. In recent times, HR professionals have generated significant interest in employee engagement (Albdour & Altarawneh, 2014) as many researchers claim engagement has a positive relationship with performance management, productivity, employee satisfaction, and organizational outcomes (Heger, 2007;Mone et al., 2011;Mone & London, 2009;Robertson & Cooper, 2009). Performance management can engage employees. Further, studies found that performance management can drive employee engagement (Mone et al., 2011;Mone & London, 2009), especially in larger companies. Performance management is viewed as the key structure that can promote business success (Haines et al., 2004) and engage employees. There can be some challenges with employees and their work relationships. Significantly, in the modern age, the relationships that employees have with their work have been acknowledged, along with the challenges that may surface when the relationship takes an unexpected course (Maslach et al., 2001).
People have the option to get engaged in various functions at work (Saks, 2006). Although some research placed emphasis on the state of engagement (Bakker et al., 2007;Kahn, 1990;Macey & Schneider, 2008), it has been suggested that there might be some antecedents to engagement that could enhance and possibly help in the development of an engaged workforce (Saks, 2006). Employee engagement can be developed from an organizational, individual, or work level. However, regarding employee engagement, antecedents that develop engagement at the organizational level revolves around personnel and human needs (Sarwar & Abugre, 2013). According to Shuck et al. (2011), there is a need to both identify basic employee needs and create organizational conditions conducive to engagement.
Employee engagement can be an important element to business and organizational success. Several scholars and practitioners reported employee engagement as a key factor to organizational success (Albrecht, 2012;Catteeuw et al., 2007). Further, Simon (2011) confirmed organizations are focusing on ways to get employees more engaged. For example, Albrecht (2012) pointed out engaged employees contribute to performance and commitment. Moreover, Catteeuw et al. (2007) found engaging employees increased the employees' innovation, creativity, and focus on their work. Tate et al. (2019) established attentiveness, expressiveness, and motivation as significant predictors of engagement. Lartey (2021) identified career planning, employee autonomy, and manager recognition as drivers of engagement in small and medium size businesses. Handa and Gulati (2014) posited personality is a significant predictor of employee engagement. The authors noted by understanding the relationship between personality traits, the employee attitudes, and behaviors likely enables managers to accomplish a better fit between employees and their job. When considering increasing employee engagement or creating teleworking opportunities, Tate et al. (2019) suggested emotional analysis approaches to gain a profound understanding of the employee's motivation. In fact, Saks (2006) found that employees differ in their levels of job engagement and organization engagement, as well as the predictors and consequences of each kind of engagement.

Performance Management
Many scholars and practitioners have paid close attention to sources of firm performance (Rosli & Mohmood, 2013). For decades, performance management has been linked to a multitude of organizational capabilities and other disciplines: accounting and psychology, organizational performance, human resource management, and sustainability (Chenhall & Langfield-Smith, 2007;Delaney & Huselid, 1996;Lahteenmaki et al., 1998;Searcy, 2012). Regardless of the views, to increase performance, all the scholars and practitioners shared common processes and measurements. Therefore, the ultimate goal of performance management is to increase productivity in organizations.
There are models that explain performance and how it should be measured systematically. According to Searcy (2012), performance measurements provide insight into system development processes, indicator selection criteria, and the roles of these systems. Tangen (2005) described successful performance measurement systems as a group of performance measures that provide an organization with information that can be used to assist in managing, controlling, planning, and performing activities. Equally important, the performance measures design must reflect the most important factors influencing the productivity of the organization's different processes. For this reason, performance should be measured from multiple perspectives since high productivity is the outcome of many factors. (Pekuri et al., 2011).
Performance management can be viewed as the business foundation to long-term success. Increasingly, organizations view performance management as the primary structure that can promote business success (Haines et al., 2004). For instance, Brudan (2010) identified three traditional performance management levels in an organizational context as strategic, operational, and individual performance. On the other hand, Lutwama et al. (2013) claimed the three main functions of performance management are strategic, administrative, and developmental.
Despite the difference in functionality terminology, both the functions and the levels of performance management share similarities and have demonstrated engaging employees in a business. For example, Brudan (2010) argued the operational level of performance management aligns with corporate strategy and places more emphasis on the functional aspects of this role. This level focus is to achieve department objectives and is traditionally evaluated by the accounting function utilizing financial indicators in terms of effectively and efficiently. In contrast, Lutwama et al. (2013) pointed out the strategic function connects the employees' performance to the organization's overall strategy. Brudan (2010) emphasized the individual level of performance management mirrors the organization's maturity level, and human resource managers are the primary drivers at the individual performance management level.
A well-defined performance management process still lacks in many organizations (Goh & Anderson, 2007. To meet business goals and achieve organizational success, firms must have a robust performance management process in place (Wortzel-Hoffman & Boltizar, 2007). Performance management is a continuous process that renews itself as the performance unfolds (Mone & London, 2009). In other words, since there are no fixed processes, organizations must design performance management systems that best meet their business needs. Further, developing processes that link company objectives to operations and providing relevant business information help identify areas for improvements (Pekuri et al., 2011). Moreover, the process and the individual measurement indicators should be explained, known, and available to the employees (Lutwama et al., 2013).

Goal-Setting Theory
For nearly five decades, goal-setting theory has strongly influenced organizational behavior and practice (Bipp & Kleingeld, 2011;Locke, 1968;Locke & Latham, 2002;Medlin & Green, 2008). According to Van De Ven (1989), a good theory is practical precisely because it advances knowledge in a scientific discipline, guides research toward crucial questions, and enlightens the profession of management. Goal setting is a work motivation concept that provides a profound understanding of how setting goals is the primacy to performance. Pinder (1984) concluded that "goal-setting theory has demonstrated more scientific validity to date than any other theory or approach to work motivation" (p. 169). In the field of organizational behavior, Miner (2003) found goal-setting theory to be one of the most respected theories.
The emphasis of goal-setting theory is placed on the core properties of an effective goal (Locke & Latham, 2002). These properties include: Specificity and difficulty; goal effects at the individual, group, and organization levels; the proper use of learning versus performance goals; mediators of goal effects; the moderators of goal effects; the role of goals as mediators of other incentives; and the effect of goal source. (p. 714) Previous studies have shown a relationship between goal setting and performance. A goal is the object or aim of an action that an individual is trying to accomplish (Locke & Latham, 2002;Locke et al., 1981). Other frequently used concepts with meanings similar to that of a goal include the performance standard, quota, work norm, task, objective, deadline, and budget (Locke et al., 1981). According to Latham and Locke (2007), goal-setting theory declares a direct positive relationship exists between high specific goals and task performance. Goal-setting theory is "associated with the relationship between conscious goals or intentions and task performance" (Latham & Yukl, 1975;Locke, 1968, p. 291). The authors noted the basic premise of the goal-setting theory is that an individual's conscious thought or understanding regulates his actions. For instance, Locke (1968) concluded that goals and intentions are significant determinants of task performance. He found an indication that goals and intentions mediate the effects of incentives or behavior. The dimensions of interest were to the degree to which the various incentives suggested specific goals or intentions to the subjects. Based on his findings, the author noted that "an essential or necessary condition for incentives to affect behavior is that the individual recognizes and evaluated the incentive and develop goals, and/or intentions in response to this evaluation" (Locke, 1968, p. 184). The author identified five direct and indirect means of manipulating goals and intentions. These incentives included (1) instructions, (2) time limits, (3) knowledge of score, (4) competition, and (5) money, praise and reproof, and participation.
According to Locke (1968), the instructions and time limits were the most direct methods of manipulating goals and intentions. Regarding instructions and time limits, once an individual accepts the directions or time limit, and accepts it as a personal goal or intention in conjunction with the ability to follow the instructions dependent upon the employee's ability, knowledge, and the situation, then instructions and time limits can influence behavior. Knowledge of the score and providing competition are less direct means of manipulating goals since these incentives do not directly tell the employee what they are attempting to reach. However, they may suggest specific standards to the employee if provided in the right form (Locke, 1968). For example, providing an employee raw scores after each quarterly evaluation may suggest the goal of improvement (providing the evaluations are all the same so that the scores are comparable).
In contrast, money, praise and reproof, and participation were found to be indirect means of manipulating goals (Locke, 1968). These incentives do not precisely imply that an employee should attempt to reach a specific goal. However, the author noted, Offering an individual money for output may motivate him to set his goals higher than he would otherwise but this will depend entirely upon how much money he wishes to make and how much effort he wishes to expend to make it. (p. 185) Other indirect effects on goal setting are praise and reproof, which represents only appraisals of the employee's performance history. Neither praise nor reproof suggests future goals or expectations. Praise and reproof only acknowledge that the employee did something good or well. In other words, praise and reproof do not explicitly state what the employee should do in the future regarding goals. Locke (1968) pointed out a combination of these incentives are employed in real-life work settings. The author described these factors as ways to getting the employee to establish and accept work goals plus retain goal commitment while guaranteeing persistence during the process time period. These may be ways to motivate employees to get engaged.
The same as Locke, a study by Prichard and Curtis (1973) found that performance did not increase when offered small incentives in comparison to no incentive when goal level was held constant. However, large incentives resulted in higher performance than did small or no incentives when the goal level was held constant (as cited in Latham & Yukl, 1975), which was contrary to Locke. This means that, totally separate from goal level and commitment, incentives can affect performance, based on Prichard's and Curtis' (1973) findings.

Feedback
Goal setting and feedback have been proven to improve productivity (Locke & Latham, 2002). Locke (1968) stated employees are motivated by clear goals and feedback. Erez (1977) reported feedback is a necessary condition for goals to affect performance. Theoretically, performance appraisals are a way to provide feedback that determines salary enhancements, promotions, and termination (Appelbaum et al., 2011). Also, performance appraisals can help managers identify employees' strengths and weaknesses or areas for change. Based on these determinants, managers can identify development needs that support career planning.
Feedback is a tool managers and organizational leaders can use to motivate, direct, and instruct the performance of employees (Ashford, 1986). For example, research on goal setting has not measured perceptions of goal attributes nor similar moderators such as feedback and supervisory support (Lee et al., 1991). These attributes are essential because they expand the theoretical understanding of the goal-setting process and how it works (Lee et al., 1991). According to Locke et al. (1981), goal setting works best if employees receive feedback on their goal progress. The employees will not know if they are working hard enough or their task strategies are appropriate without feedback (Becker, 1978;Erez, 1977).
Similarly, if employees are aware and understand their respective targets, then they are motivated to exert more effort, which increases performance (Locke & Latham, 1990). Further, if employees are unaware of their status in reaching their goals, then it is hard for them to adjust their performance strategies to meet the goal requirements (Locke & Latham, 2002). Some individuals may be willing to adjust and increase their efforts once they learn they are below the target goal or attempt another strategy. Moreover, management must clearly communicate to the employee why the goals are set for them, clarify how the performance is being measured, and provide routine feedback indicating how they are performing (Lee et al., 1991).
Feedback is information available to individuals at work that denotes the employee's status on meeting various goals (Ashford & Cummings, 1983). Positive feedback may generate a positive affect; it enables individuals to experience satisfaction with goal attainment, thus motivating employees by indicating that continued performance will lead to further satisfaction (Bandura & Cervone, 1986). Together, goal setting and feedback may be the best way to improve performance. Becker (1978) concluded that the joint effect of feedback and goal setting resulted in improved performance. Further, summary feedback moderates goal effects, meaning goals and feedback together are more effective than goals alone (Becker, 1978;Erez, 1977).
The primary interest in feedback has been sustained because of its performance-enhancing effect (Ashford & Cummings, 1983). For instance, appropriately using performance appraisal review sessions can lead to performance improvements in conjunction with other critical outcomes such as perceptions of procedural fairness (Lee et al., 1991). There may be other associated factors that relate to feedback. Further, when an employee accomplishes assigned goals, offering tangible rewards such as recognition, time off, job security, and promotion opportunities can be used to increase both goal acceptance and motivation. Support systems can enhance employee efforts toward completing tasks. Lee et al. (1991) found some other support mechanisms may be necessary from both managers and the organization, such as providing adequate support and resources to complete the job. Moreover, the company policies should not intervene with goal attainment because strict rules may hinder action plans from being implemented (Lee et al., 1991). In other words, companies can create a feedback environment or culture to support the employee needs to reach both individual and organizational goals.

Theoretical Framework
The theoretical underpinnings for this study are primarily related to the goal-setting paradigm. The goal-setting theory provided strong theoretical connections between the use of performance management activities, performance goals and development, feedback and recognition, and the climate of trust that promoted employee engagement. Performance goals and development, feedback and recognition, and climate of trust were dimensions of performance management that directly or indirectly facilitate employee engagement in conjunction with performance outcomes in organizations (Mone & London, 2009). This quantitative, non-experimental correlation study aimed to examine the relationship between overall performance management (performance management and development; feedback and recognition, and climate of trust) and overall employee engagement in small businesses in the United States. In this study, there are no specific independent or dependent variables for the correlation analyses; this research focused on understanding the relationship among these variables. In the following section, Figure 1 illustrates this relationship.

Research Question
The following research questions must be answered to determine the relationship, if any, between performance management activities (performance goals and development; climate of trust; feedback and recognition) and employee engagement.
RQ: What is the relationship between the three performance management activities (performance goals and development, feedback and recognition, and climate of trust) and overall employee engagement within small businesses in the U.S.?

Sub-Questions
SQ 1: What is the correlation of performance goals and development with employee engagement in small businesses in the U.S.?
SQ 2: What is the correlation of feedback and recognition with employee engagement in small businesses in the U.S.?
SQ 3: What is the correlation between a climate of trust and employee engagement in small businesses in the U.S.?

Omnibus Hypotheses and Alternative
H 0 1: There is no statistically significant relationship between overall performance management activities (performance goals and development, feedback and recognition, climate of trust) and employee engagement within small businesses in the U.S.
H A 1: There is a statistically significant relationship between overall performance management activities (performance goals and development, feedback and recognition, climate of trust) and employee engagement within small businesses in the U.S.
Sub-hypotheses examined each of the independent variables.

Sub-Hypotheses
H 0 2: There is no statistically significant correlation of performance goals and development with employee engagement in small businesses in the United States.
H A 2: There is a statistically significant correlation of performance goals and development with employee engagement in small businesses in the United States.
H 0 3: There is no statistically significant correlation of feedback and recognition with employee engagement in small businesses in the United States.
H A 3: There is a statistically significant correlation of feedback and recognition with employee engagement in small businesses in the United States.
H 0 4: There is no statistically significant correlation between a climate of trust and employee engagement in small businesses in the United States.
H A 4: There is a statistically significant correlation between a climate of trust and employee engagement in small businesses within in United States.

Study Design
This study employed a quantitative, non-experimental correlation research design using two instruments to determine the relationships between overall performance management activities (independent variables) and overall employee engagement (dependent variable) within small businesses in the U.S. This study also used a quantitative, non-experimental correlational approach. The primary objective of the study was to determine the relationship between overall performance management activities such as performance goals and development, feedback and recognition, a climate of trust, and overall employee engagement in small businesses in the U.S. In contrast to experimental approaches, this study did not manipulate data to determine causal outcomes or give treatments (Patten, 2012).
The selection of the variables was derived from the work of Mone and London (2009). Several authors used similar variables in their studies (Kahn, 1990;Latham & Locke, 2007;Macey & Schneider, 2008). Mone et al. (2011) identified similar variables in a quantitative study to investigate the relationship between performance management and employee engagement. The authors examined the association of performance and development goals, providing ongoing feedback and recognition, managing employee development, conducting mid-year and year-end appraisals, and building a climate of trust and empowerment to employee engagement. Mani (2011) provided similar interpretation and classification of trust, rewards, and development as predictors of employee engagement.
The study administered the Pearson correlation coefficient as the model to analyze the data. This model was supported by the decision tree exhibited by Field (2013) and Tabachnick and Fidell (2013). Utilizing the decision tree, the model for the study was determined by examining the research question based on the following decision path.
This study had three independent variables of scale measurement level, which allowed the multiple regression and the Pearson correlation coefficient as appropriate models to answer the research questions. The independent variables (IV) were performance goals and development (GOALSDEV), feedback and recognition (FDBKREC), climate of trust (CLTRUST), and the dependent variable (DV) was employee engagement (ENGAGEMT). IBM: SPSS Statistical Software version 24 was used to analyze the data.

Measurement Instruments
The survey questionnaire included two instruments. Both instruments were selected based on their relevancy, reliability, and validity. The first instrument, a survey developed by Mone and London (2009) measured performance management with three sub-constructs (performance goals and development, feedback and recognition, and climate of trust). This scale was used in a large corporation study and other research finding performance management can increase employee engagement (Mone et al., 2011). Mone and London's (2009) survey contained a 28-item scale answered on a five-point Likert-type scale ranging from strongly disagree to strongly agree with a neutral midpoint with an interval level of measurement.
This survey was designed to measure five actions of performance management that can lead to employee engagement, which include setting performance and development goals, providing ongoing feedback and recognition, managing employee development, conducting mid-year and year-end appraisals, and building a climate of trust and empowerment with employees. Granted permission from Mone (Appendix B), the survey was modified from "XINC" to "My Company" to be more applicable to the small businesses managed in the U.S., which was significant to the proposed study. The 28 questions were a set of questions from Mone and London's (2009) original scale of over 100 questions. The 28 questions were the final questions determined by Mone and London (2009) to be the most relevant toward measuring performance management and employee engagement.
Performance goals and development was defined as seeking specific outcomes based on assigned tasks to increase employee productivity with an emphasis on performance outcomes (Seijts & Latham, 2005). Performance goals and development was measured by the participation in a task, then measuring the extent to which the participant felt engaged to the demand of the task. Each variable was addressed by specific questions in the survey. To address this variable, data was collected using Questions 2, 6, 7, 8, and 9 from Mone's and London's (2009) scale.
Feedback and recognition were combined into one variable. Feedback was defined as specific dialogue regarding the employee's performance and set standards to ensure the employee understands performance strengths and areas of development to increase performance (Saedon et al., 2012). Recognition is a form of feedback defined as the task of non-monetary or monetary rewards to an employee to reinforce the desired behaviors, after which the behavior has occurred (Long & Shields, 2010). Recognition is a form of feedback tied to employees' behaviors or the accomplishment of specific tasks or goals. The feedback and recognition variable was addressed by Questions 1, 3, 4, 5, 10, 11, 12 in the Mone's and London's (2009) scale. Lastly, climate of trust was defined as the willingness to risk one's vulnerability to someone else whose behavior is out of one's control (Zand, 1972). This variable was addressed by Questions 13, 14, 15, 16, and 17 in the Mone-London scale.
The second instrument, the Utrecht Work Engagement Scale (UWES-9), developed by Schaufeli et al. (2006), was used to measure the dimensions of employee engagement. It was selected because of its specificity and work-related characteristic measures for engagement, reliability, and validity. This scale was grouped in three subscales: dedication, vigor, and absorption, which reflected dimensions of engagement. The nine-item scale was scored on a seven-point Likert-type scale ranging from 0 (never) to 6 (always). Schaufeli et al. (2006) confirmed that the original 17-item Utrecht Work Engagement Scale could be shortened to nine items and concluded that the resulting scores contained acceptable psychometric properties and the scale was employable for positive organizational behavior studies (p. 701). Overall employee engagement was measured using all nine questions in the Schaufeli et al. scale.

Sampling Procedure
The population was comprised of employees employed by small businesses, those businesses with 500 or fewer employees in the U.S. The population size for this study was approximately 15,000 employees of small businesses in the U.S. A random sample was selected from the target population. The small business members of the Sample Panel in QuestionPro sought respondents in small businesses in the U.S. The demographics consisted of respondent ages and genders. Only employees employed by small businesses in the U.S. were considered for this study. Specifically, only employees who worked for those businesses with 500 or fewer employees in the U.S. federal, state, local government, municipalities, and non-profits were exempted from this study.
G*Power, a statistical power analysis and size calculating tool, was used to determine the sample size. Faul et al. (2009) presented the G*Power in the domain of correlation and regression analysis. According to Field (2013), using power to calculate the sample is useful (p. 70). To calculate the sample size, the level of significance, power of the test, and effect size must be specified. Sample size calculations are considered important for determining the right number of necessary subjects for the proposed study (Parker & Berman, 2003). More importantly, the sample, which determines the rigor of the study, defines the results to a degree that can be generalized beyond the study (Swanson & Holton, 2005). Further, to estimate the parameters of the population precisely, the sample must be large enough. Alternatively, a sample too small will not offer enough information to determine good results. In other words, it reduces the statistical power and increases the risk of failing to detect the actual relationship within the population (Vogt, 2007). Lenth (2001) added that the sample size must be adequate.
In terms of the level of significance, .05 is the alpha level or criterion for significance, to ensure the probability of rejecting the null hypothesis when it is true (Type I error) remains below 5% (Field, 2013). The statistical power gives the investigator the ability to reject a null hypothesis when it is utterly false (Swanson & Holton, 2005), which is a Type II error (Swanson & Holton, 2005;Vogt, 2007). Using a power value of .80 indicates that the probability of correctly rejecting a false null hypothesis is 80%. Calculating the ordinary least squares multiple regression, a medium effect size of .15, power of .80, and alpha of .05 resulted in a minimum sample size of 77.
Previous literature also supported the sample size. Saks (2006) used a sample of 102 to determine the antecedents and consequences of employee engagement using multiple regression. According to Parker and Berman (2003), the number of subjects being studied must be specified in any protocol involving human subjects. Based on this analysis and sample size based on previous empirical studies, a minimum sample size of 77 constitutes an acceptable sample size for this study. Since this study employed an ordinary least square multiple regression with three potential outcomes, a 1.5 multiplier was applied to the estimated minimum sample size of 77 (77 x 1.5 = 115.50). As a result, the overall minimum sample was rounded to 116 participants. For this reason, the estimated minimum sample size for this study was 116 participants. For this study, the actual sample size was 121 participants.

Sample Size and Power
Population and sample frame. The target population of this study consisted of workers in small businesses with 500 or fewer employees. The population included employees and workers residing within the United States of America. The small business members of the Sample Panel in Question Pro, Inc. sought respondents from the small business population.

Sampling Procedure
After building the survey questionnaire, the researcher tested it and confirmed its proper function. With this confirmation, the survey firm created a random sample of potential participants using its audience database. Emails were then sent to the selected audience, inviting them to participate in the study. Once the prospects clicked on the hyperlink to take the survey, they were directed to the informed consent form, which was the first question before starting the survey, and then the respondent could proceed with the survey.

Sample Size
After receiving the invite, 152 prospective participants viewed the informed consent. Of this number, 79% provided their informed consent and took the survey, representing 121 participants. All 121 participants provided answers to all the survey questions. The 121 responses obtained were analyzed, and none were removed from the final file; all 121 responses were valid.

Demographic Description of the Sample
The total sample of 121 participants who completed the survey was composed of 59 males and 62 females. As such, the proportion of males was 48.8%, while that of females was 51.2%. This demographic breakdown is like that of a recent study by Lartey et al. (2015) that had a sample with 44.2% of males and 55.8% of females, suggesting that the random sampling of this study produced the expected proportions of males and females. Table 1 represents the demographic breakdown of participants by gender. This survey also collected the age of the participants, another demographic variable. In the questionnaire, participants had four options for specifying their age bracket, namely: younger than 25; between 26 and 40; between 41 and 55; and 56 or older. Table 2 shows the breakdown of participants by age. Of course, participants younger than 18 were not allowed to participate in this study.  Table 2, participants were evenly distributed in the higher three brackets. The younger population had a low representation, just 6.6%. As such, to conduct proper analysis based on the age group, the first bracket considered was that of those aged 40 or younger. Table 3 reflects this new breakdown of the participants by age.

Data Analysis
The primary purpose of this quantitative, non-experimental correlation study was to determine whether there is a relationship between the independent variables: performance goals and development, feedback and recognition, and climate of trust representing performance management activities and the dependent or outcome variable, employee engagement. This purpose was explored using multiple regression statistical analysis. According to Lee (2003), Petrocelli (2003), and Rocconi (2013), multiple regression is a powerful set of methods for examining specific hypotheses and relationships among non-experimental data and used to analyze a dependent variable with a set of independent variables.
In the case of this study, the multiple regression model was deemed appropriate to identify the relationship between the independent variables: performance goals and development, feedback and recognition, and climate of trust, and the dependent variable employee engagement. For the other hypotheses deriving from the research sub-questions, the Pearson correlation was deemed adequate to analyze the data. This provided answers to whether any correlation existed between each independent variable and the continuous variable.
A multiple regression analysis was conducted on data collected from 121 participants working in small businesses in the United States. The research question of the study asked: What is the relationship between overall performance management activities (performance goals and development; climate of trust; feedback and recognition) and overall employee engagement within small businesses in the U.S.? Various assumptions of the multiple regression were tested and validated, and the final model was created.

Assumptions of the Multiple Regression Model
Tabachnick and Fidell (2013) identified the main assumptions to validate for the multiple regression model. These assumptions are summarized by Randal, Lartey, and Tate (2020) as: (1) ratio of cases to independent variables; (2) absence of outliers among the IVs and on the DV; (3) absence of multicollinearity; (4) normality, linearity, and homoscedasticity of residuals; and (5) independence of errors.

Ratio of Cases to Independent Variables
This study had 121 participants and four independent variables. As such, the number of cases is above the minimum requirement indicated of 103 + 4 = 107, as suggested by Tabachnick and Fidell (2013). Therefore, the sample was adequate for testing the variables using multiple regression. In addition, there were no missing values, thus confirming the adequacy of the sample.

Absence of Outliers
The computation of the z-score of all variables, both independent and dependent, showed that none of the values was outside the range of -3.29 to +3.29. This confirmed the absence of univariate outliers, as suggested by Tabachnick and Fidell (2013). Furthermore, the calculation of the Mahalanobis distance along with the probability from the chi-square distribution using 3 degrees of freedom (number of independent variables) confirmed the absence of multivariate outliers, as no resulting score was below .05, the alpha value used in this study.

Absence of Multicollinearity
The assumption of multicollinearity suggests that independent variables should not be highly correlated. This was tested using the variance inflation factor (VIF). All the VIF values between each pair of variables were well below 10, indicating that there was no major concern for multicollinearity, as explained by Field (2013). Hence, the assumption of an absence of multicollinearity was met for this study.

Normality, Linearity, and Homoscedasticity of Residuals
This assumption was validated through the analysis of the standardized predicted values and the standardized residuals on a graph. The resulting graph was not curved, showed a rectangular pattern, and no residual was outside the range -3.29 to +3.29. In addition, a review of the descriptive statistics of each variable showed skewness and kurtosis values between -1 and +1. These observations confirmed the assumption of normality, linearity, and homoscedasticity of residuals in the study.

Independence of Errors
The assumption of independence of errors was tested using the Durbin-Watson test, which detects autocorrelations in residuals. Based on the nature of this study, there were no correlations between residuals as the cases were independent of each other.

Assumptions of the Pearson Correlation Model
Three sub-questions were identified from the research question and were answered using Pearson correlation statistics. For that reason, the assumptions of Person's correlation model were validated on the sample. There were three primary assumptions to validate for the Pearson correlation model (Field, 2013;Tabachnick & Fidell, 2013). Those assumptions included (1) two or more variables being measured at the interval level (continuous variables); (2) normality: each pair was bivariately distributed normally, and (3) linearity at all levels of the other variables, which ensured the variables are linearly related. There were four variables being measured at the scale level, which confirmed the assumption of two or more continuous variables. Those variables were GOALSDEV, FDBKREC, CLTRUST, and ENGAGEMT. Normality was confirmed in the assumptions of multiple regression. For visual confirmation, linearity was tested using scatterplots to visually inspect the relationship between the variables. As a result, the assumptions of continuous variable, normality, and linearity were met for this study, and bootstrapping was not needed to use the Pearson correlation model in answering the sub-questions.

Results
The purpose of this study was to examine the nature of the relationship between three independent variables (i.e., performance goals and development, feedback and recognition, and climate of trust) and the dependent variable, employee engagement. The main research question asked: What is the relationship between overall performance management activities and employee engagement within small businesses in the U.S.? To answer this research question, a multiple regression model was created on data collected from 121 participants. The model created to answer this question used three predictors and one outcome variable, all continuous in nature. In addition to the main research question, three sub-questions (SQ1, SQ2, and SQ3) were generated. To answer these sub-questions, various correlation models were created using the collected data.
SQ1: What is the correlation of performance goals and development with employee engagement in small businesses in the U.S.?
H 0 2: There is no statistically significant correlation of performance goals and development with employee engagement in small businesses in the United States.
H A 2: There is a statistically significant correlation of performance goals and development with employee engagement in small businesses in the United States.
Hypotheses H 0 2 and H A 2 were tested using Pearson correlation coefficient, r, with independent variables GOALSDEV and ENGAGEMT. The output of the test is presented in Table 4. Based on this output, there was a statistically significant positive relationship between ENGAGEMT and GOALSDEV, r = .609, p < .001. As such, the null hypothesis of no relationship was rejected.  -tailed) .000 N 121 121 ** Correlation is significant at the 0.01 level (2-tailed). SQ2: What is the correlation of feedback and recognition with employee engagement in small businesses in the U.S.? H 0 3: There is no statistically significant correlation of feedback and recognition with employee engagement in small businesses in the United States.
H A 3: There is a statistically significant correlation of feedback and recognition with employee engagement in small businesses in the United States.
Hypotheses H 0 3 and H A 3 were tested using Pearson r correlation with independent variables FDBKREC and ENGAGEMT. The output of the test is presented in Table 5. This output indicates that there is a statistically significant positive relationship between ENGAGEMT and FDBKREC, r = .669, p < .001. As such, the null hypothesis of no relationship was rejected.  -tailed) .000 N 121 121 ** Correlation is significant at the 0.01 level (2-tailed). SQ3: What is the correlation between a climate of trust and employee engagement within small businesses in the U.S.? H 0 4: There is no statistically significant correlation between a climate of trust and employee engagement in small businesses within the United States. H A 4: There is a statistically significant correlation between a climate of trust and employee engagement in small businesses within the United States.
Hypotheses H 0 4 and H A 4 were tested using Pearson r correlation with independent variables CLTRUST and ENGAGEMT. The output of the test is presented in Table 12. This output indicates that there is a statistically significant positive relationship between ENGAGEMT and CLTRUST, r = .523, p < .001. As such, the null hypothesis of no relationship was rejected.  -tailed) .000 N 121 121 ** Correlation is significant at the 0.01 level (2-tailed).
All the above-mentioned correlations are represented in Table 7, representing the overall Pearson correlation table. RQ1: What is the relationship between overall performance management activities (represented by performance goals and development, climate of trust, and feedback and recognition) and overall employee engagement in small businesses in the U.S.?
H 0 1: There is no statistically significant relationship between overall performance management activities and overall employee engagement in small businesses in the U.S.
H A 1: There is a statistically significant relationship between overall performance management activities and overall employee engagement in small businesses in the U.S.
Hypotheses H 0 1 and H A 1 were tested using a multiple regression model with the three independent variables FDBKREC, GOALSDEV, and CLTRUST, and one dependent variable, ENGAGEMT. A summary of the model is presented in Table 8 and shows that the model explains 45.3% of the variability in the dependent variable. This finding suggests that other factors explain the remaining 54.7% of the variability in the dependent variable. To understand the contribution of each variable, the final model was used, as shown in Table 9. An analysis of this model suggested that the variables GOALSDEV (p = .437) and CLTRUST (p = .268) were not statistically significant (p > .05) in determining the criteria variable ENGAGEMT. Based on the results presented, correlation study, the null hypothesis of no relationship was rejected for each of the performance management activities and the following output indicated that there was a statistically significant positive relationship between (1) ENGAGEMT and GOALSDEV, r = .609, p < .001; (2) ENGAGEMT and FDBKREC, r = .669, p < .001; and (3) ENGAGEMT and CLTRUST, r = .523, p < .001. In fact, the results illustrate that feedback and recognition (FDBKREC ) had the largest correlation to engagement, followed by goals and development (GOALSDEV) and climate of trust (CLTRUST) with the least correlation.
From a multiple regression standpoint, this study confirmed that while there was a correlation between employee engagement and goals and development (GOALSDEV) as well as between employee engagement and climate of trust (CLTRUST), these two variables were not statistically significant in explaining employee engagement when teamed with feedback and recognition. The feedback and recognition (FDBKREC) variable was the only independent variable statistically significant in determining employee engagement. The resulting model can be represented visually as shown in Figure 2.

Discussion of the Results
This study was based on and evolved from previous performance management and employee engagement research. There is a gap in the research that examines the data being captured and how both practitioners and researchers can utilize the data to illustrate the correlational relationship. This research expanded the current organization and management literature by examining the strength of the association between performance management activities, namely performance goals and development, feedback and recognition, and climate of trust, and employee engagement in small businesses in the United States. To collect data, a quantitative survey incorporating both the Utrecht Work Engagement Scale and a survey to measure performance management activities in conjunction with demographic questions was administered (Mone & London, 2009;Schaufeli et al., 2006). The online survey firm QuestionPro randomly distributed the surveys to 152 employees in small businesses, meaning businesses with 500 or fewer employees working within the United States, resulting in the receipt of 121 surveys and an overall response rate of 79%. Demographic questions were presented to identify individual characteristics of the respondents. The majority of the respondents were females, 51.2% of the total sample, while the remaining proportion of males were 48.8%. Respondent aged ranged from 18 to 65 with the age groups 26-40 and 56+ evenly distributed at 32.2%. Respondents between the ages 41 and 55 were 28.9%. Comparably, the younger population had the least representation of 6.6%.
A Pearson correlation analysis was performed to test and determine the correlational relationship between overall performance management activities (performance goals and development, feedback and recognition, and climate of trust) and overall employee engagement in small businesses in the U.S. Before conducting the Pearson correlation analysis, various procedures were employed to evaluate both the data and assumptions associated with this model. There was no missing data. As for the multiple regression model, the assumptions of normality, linearity, homoscedasticity, independence of errors, and multicollinearity were met (Field, 2013;Tabachnick & Fidell, 2013). For the Pearson correlation model, the assumptions of normality, linearity, and two or more continuous variables were met. The assumption of normality was met by the central limit theorem. There were no outliers in the data examined. Scatterplots were used to visually inspect the relationship between the variables to confirm linearity. A statistically significant regression model F (3, 117) = 32.34, p < .001, R 2 = .453, was created, explaining 45.3% of the variability in the overall employee engagement. While performance goals and development along with a climate of trust were not statistically significant in the model (p > .05), feedback and recognition were statistically significant (p < .001). In other words, feedback and recognition was the main determinant of employee engagement in small businesses in the U.S., even though climate of trust and performance goals and development each had direct positive correlations with employee engagement.
This study supports the literature presented on goal-setting theory. According to the literature, employee engagement had no universal definition that can comply with all situations. Research showed that employee engagement can be modified in various ways depending on the context of the study. For this study, employee engagement, as a multi-faceted construct, was defined as the level of involvement and commitment an employee has toward the organization and its value (Ali, 2013;Bhattacharya & Mukherjee, 2009;Dash, 2013;Kahn, 1990;Mani, 2011). Dash (2013) admitted employee engagement measures employees' emotional attachment to their jobs that directly influences their anticipations of learning and performing at work to some extent. The engagement comes into play when the employee becomes involved in various processes such as communication, appraisal, coaching, and performance. Therefore, the literature supports employees who receive feedback regularly in small businesses tend to become more engaged and productive.
The Pearson correlation results presented a statistically significant positive relationship between ENGAGEMT and GOALSDEV, r = .609, p < .001; ENGAGEMT and FDBKREC, r = .669, p < .001; and ENGAGEMT and CLTRUST, r = .523, p < .001. In fact, the results illustrated that feedback and recognition had the strongest correlation with engagement, followed by goals and development and climate of trust with the least correlation. Therefore, small businesses that create a culture of feedback and recognition will have more engaged employees than those small businesses that do not have these performance management activities installed. Based on the findings from the multiple regression model, feedback and recognition is the most important of the three variables, as it was the only one that had a statistically significant relationship in determining employee engagement, suggesting that it accounted for the variability in engagement from a climate of trust and goal setting and development. In supervisor-employee relationships at work, trust is not necessarily mutual and is not reciprocal (Schoorman et al., 2007). A supervisor may trust the employee, but the employee may have no trust in the supervisor, or vice versa. Providing regular and objective feedback is key to inciting engagement in employees.

Implications of the Results
This study has examined the relationship between overall performance management activities, performance goals and development, feedback and recognition, climate of trust, and overall employee engagement in small businesses in the United States. This study has filled the gap that was absent in scholarly research. Filling this current gap provides insight into how companies and managers make decisions regarding organizational and employee performance through goal setting, feedback and recognition, and a climate of trust. In consideration of the study results, the implications are that the myriad of scholarly research into this general area can be supported.
This study supports Latham and Locke (2007) goal-setting theory and performance management research. Goal setting is a work motivation concept that provides a profound understanding of how setting goals is the primacy to performance. Goals are important in any business since they lay the blueprint on how the business is intended to function. Brudan (2010) pointed out performance is associated with two inseparable processes: performance management and performance measurement. The author described performance management as the overarching process that an organization has toward performance, such as planning and goal setting, strategy implementation, training, and measuring performance. Further, the author emphasized the performance measurement component of this process is associated with evaluating the results. Theoretically, performance appraisals are used to evaluate the results and determine salaries, promotions, terminations, layoffs, and training (Appelbaum et al., 2011). Performance appraisals help managers identify employee strengths and areas for improvement to determine development needs.
From the employee engagement perspective, Mone and London (2009) pointed out how feedback helps the employee understand how their work contributes to the team and the business. Conceptually, at the organizational level, cultural literature suggests that feedback provisions may drive potential conditions for engagement. It is extremely important for small businesses to provide incentives and rewards that are valuable to employees due to their scarce resources in conjunction with their dependency on highly motivated employees (Kowalewski & Phillips, 2012). Brun and Dugus (2008) argued it is necessary to consider the act of recognition from an interactional perspective that contains a reciprocity element while considering the bidirectional nature of human relationships. In terms of engagement, Bhattacharya and Mukherjee (2009) found employees expressed greater emphasis on non-financial rewards than financial rewards received. Additionally, the employees considered rewards important for keeping them engaged in their organization (p. 175). This supports the data analysis findings showing feedback and recognition having the largest correlation with employee engagement (ENGAGEMT and FDBKREC, p < .001).
This study provided information on the correlational strength between performance management activities and employee engagement to provide practitioners with information to better understand the impact of performance management and employee engagement in small businesses. More specifically, this study contributes significantly to the field of organization and management by affirming the broad understanding that Mone and London (2009) pointed out: the relationship between performance management and employee engagement. In other words, where there is performance management, there is employee engagement. Without performance management, employee engagement might not exist. The information in this study provides practitioners with information to help determine which specific performance management activity may have a stronger correlation with employee engagement in small businesses in the U.S. Human resources development (HRD) and organizations that foster and promote a climate of engagement could benefit by identifying and gaining a holistic understanding of chief factors of employee engagement.

Limitations of the Study
While this study made significant contributions to both academia and practice, it had its limitations that provide avenues for future research directions. The primary limitation was related to the data collection. The use of survey instruments to gather primary data has been widely accepted in organizational research for several years (Swanson & Holton, 2005). The design for this study was quantitative and correlational. The instruments used in this design to collect data were suitable for asking questions and acquiring specific responses for analyzing data to determine if a relationship exists between overall performance management and overall employee engagement. The questions were directed toward the individuals' experiences within small businesses in the U.S., and the participants' answers were on behalf of the whole organization. This study was limited to correlation data, and causality should not be assigned to the relationships found in the results.
Another limitation involved recruiting participants and the sampling strategy. A panel of qualified participants was acquired from QuestionPro. The participants were assumed to be randomly selected. The researcher had minimum control over the quality of the sample regarding participant qualification. Further, the researcher had minimum control over the random selection from the target population. Lastly, the sample was limited to employees in small businesses within the United States, meaning businesses with 500 or fewer employees. These respondents were assumed to represent their personal perspective from experience in their organization at a particular point in time and may not be generalizable to alternate settings and to other industries (Creswell, 2009;Swanson & Holton, 2005). Other industries were exempted from this study, such as federal, state, local government, municipalities, and non-profits. As a result of conducting this research study and analyzing the findings, several recommendations for future research have emerged.

Recommendations for Further Research
The results of this study indicate that when compared individually to employee engagement, performance goals and development, feedback and recognition, and climate of trust, each has a statistically significant positive correlation with employee engagement in small businesses in the United States. When used together, only feedback and recognition has a statistically significant relationship with employee engagement. This study only considered employees in small businesses within the United States. These findings offer the opportunity for future studies to investigate more intensely into other industries, companies, and countries. Future research can be done in areas that address all levels of the organization and depth of the subject, including managers, non-managers, CEOs, and business owners. Since there is no uniform process for performance management and no universal definition of employee engagement, the subject of overall performance management activities and its relationship with employee engagement is an area of study in need of continued analysis.
This study expanded on current performance management and employee engagement literature by examining the overall relationship between the two constructs. It illustrated the correlational relationship between overall performance management activities, performance goals and development, feedback and recognition, climate of trust, and overall employee engagement in small businesses in the U.S. Based on its findings, without performance management in small businesses, there is likely less employee engagement. This means, where performance management exists, there is employee engagement and productivity.
A qualitative analysis could evaluate more in-depth ways performance management activities, namely performance goals and development, feedback and recognition, and a climate of trust, can engage employees. Further, other performance management activities for employee engagement need to be identified and evaluated.
Interviews could investigate the employee's perceptions of the many facets and distinctions of the specific topic. A similar analysis could determine whether the same findings are applicable for other sectors or other countries.
Quantitative analysis in future research could delve more into the unfilled gaps on this topic. A quantitative method presenting predictive or explanatory analysis with other variables may be appropriate, regarding small businesses, organization size, and the number of years in business may be appropriate, more specifically, in small size businesses. As previously mentioned, the research could determine applicability to other countries, companies, and industries such as non-profits and local governments.

Conclusion
The purpose of this study was to examine the nature of the relationship between three independent variables (i.e., performance goals and development, feedback and recognition, and climate of trust) and the dependent variable, employee engagement. To achieve its goal, this study reviewed prior research related to performance management, employee engagement, and small businesses. Its execution was anchored around the following research question: What is the relationship between overall performance management activities (performance goals and development, feedback and recognition, and a climate of trust) and overall employee engagement within small businesses in the U.S.?
This research was grounded in existing performance management and employee engagement literature. It was conducted to gain a more profound understanding of the relationships that exist between the dependent variable characterized as the overall employee engagement and the overall performance management activities comprising performance goals and development, feedback and recognition, and climate of trust within small businesses. A quantitative, non-experimental correlational method was incorporated to measure and evaluate the relationship. An online questionnaire was used to collect the research data.
A series of Pearson correlation analyses indicated the existence of statistically significant positive relationships between overall employee engagement and each variable of performance management activities, namely performance goals and development, feedback and recognition, and climate of trust. Notwithstanding these positive correlations, a multiple regression model with the three performance management variables as independent variables and overall employee engagement as dependent variable suggested that there was a statistically significant regression model F (3, 117) = 32.34, p < .001, R 2 = .453, explaining 45.3% of the variability in the employee engagement. Nonetheless, this model confirmed that performance goals and development along with climate of trust were not statistically significant in the model (p > .05). In other words, only the feedback and recognition variable was statistically significant in the regression model, suggesting that it explained most of the variability in engagement, including that already explained by the other two variables.