INVESTIGATING THE FACTORS AFFECTING ORGANIZATIONAL PERFORMANCE IN THE REAL ESTATE INDUSTRY
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Acknowledgement
I would like to acknowledge my supervisor Dr. Kevin Lu for the support he showed throughout the study process. I would also like to extend my gratitude to my family members for the mental and financial support they provided throughout the study period. Further, I would like to thank my friends and course mates for their contributions and availability whenever I needed them.
Table of Contents
1.3 Purpose and Significance of the Study 12
1.4 Research Aim and Objectives 13
Chapter 2: Literature Review 16
2.2.2 Types of rewards and significance (Intrinsic and Extrinsic) 17
2.2.3 Rewards and Governmental Policy 19
2.3 Organizational Performance 20
2.3.2. Performance measurement 21
2.4 Theories Explaining Reward Systems 23
2.4.1 Herzberg’s Two Factor Theory 23
2.5 Reward Systems and Organizational Performance 23
2.5.1 Effects of intrinsic rewards on organizational performance 23
2.5.2 Effects of extrinsic rewards on organizational performance 24
2.6 Organizational Goal Setting 25
2.6.1 Organizational goal types 25
2.6.2 Complexity of organizational goals 26
2.7 The McKinsey’s Seven “S”s Model 28
2.10 Hypothesis Development 32
Chapter 3: Research Methodology 35
3.4 Population and Sampling procedures 36
3.5 Data Collection procedures 37
3.7 Considerations of the Ethical requirements 40
Chapter 4: Analysis Results and Discussions 42
4.1 Introduction to the analysis 42
4.2 Analysis of Demographic Data 42
Chapter 5: Conclusions and Study Recommendations 56
List of Figures
Fig 1.1.1: Aspects of business management
Fig 2.7.1: The McKinsey 7s model
Fig 2.9.1: Mind Map diagram
Fig 3.8.1: The Gantt Charts
Fig 4.2.1: Histogram chart for the age data
Fig 4.3.1: Frequency histogram for the organizational performance
List of tables
Table 4.2.1: Gender Distribution results
Table 4.2.2: Job Position Distribution Results
Table 4.2.3: Region Distribution Results
Table 4.3.1: Descriptive Statistics Results
Table 4.3.2: Results for the level of performance
Table 4.4.1: Correlations analysis results
Table 4.4.2: Regression Results
Table 4.4.3: Analysis results of the variances
Table 4.4.4: Coefficients analysis results
Table 4.5.1: Opinion about the most important element among the seven “S”s in the McKinsey model
Table 4.5.2: ANOVA results
Table 4.5.3: The most common uses of the model
Table 5.2.1: Hypothesis summary Chart
Abstract
The performance in the real estate industry is still low with significant reasons for the need for improvement. The major focus area by many stakeholders and researchers has been on the management activities. Management in the real estate industry allows for full and proper screening or testing of an individual’s credit, rental history, criminal history and ability to pay. Previous research shows that management activities also ensure that there are thorough remediation and mitigation regarding maintenance issues within the budget, with a prior consent via relevant authorities. However, there has been insufficient knowledge on the effect of the management activities on the performance of the real estate organizations. The purpose of this study is to evaluate the management styles that are effective in real estate management and other industries to ensuring the success of the organization in achieving their set goals. The study aimed at assessing the effect of real estate management activities on the performance by focusing on the most common management techniques including setting targets, measuring results and rewarding performance. Evidence exists that many stakeholders in the organizations are very concerned about the setting of goals that are vital to the success of the company. The study adopted a quantitative research approach together with a descriptive design. The study targeted the population of all managers and employees in the decision making positions from companies dealing with real estate management or property management. A conclusion was made that management activities in the real estate companies contributed to the organizational performance positively. The study suggested that setting targets, measuring results and rewarding performance influenced 90.3% of the variations in the organizational performance.
Key Words: Organizational performance, Targets, Results, Rewards, Seven S Model.
Chapter 1: Introduction
1.1 Background Information
The management of the real estate is the control, operation and oversight of real estate. Conversely, management shows a need to care for, accountability and monitoring given for a condition and useful life. Studies done in the past showed that a positive relationship exists between levels of management and performance particular in the real estate business. According to Johnson Brown (2015), management allows for proper and full screening or assessing of an individual’s credit, rental history, criminal history and ability to pay. The endeavor also allows for the lease contracting or acceptance of rent using legal documents approved for the area I which the property is located. Management activities also ensure that there are thorough remediation and mitigation regarding maintenance issues within the budget, with a prior consent via relevant authorities (Wright, Mukherji & Kroll, 2011). This study aimed at assessing the impact of real estate management activities on the performance by focusing on the most common management techniques including setting targets, measuring results and rewarding performance. Many people in the organizations are very concerned about the setting of goals that are vital to the success of the company. In fact, all individuals set specific goals in their lives for the things that they want to achieve. One of the most common things is the fact that goal setting requires goals action that is defined in the activities involved. Real estate managers are nowadays aware of the significance of this and therefore, the reason they have adopted goal setting measures. A competent real estate firm must ensure that all the real estate features are well addressed. The management should engage the four main aspects of business management which include people management skills, financial management skills, planning and organizational skills, and sales and marketing skills as shown in the figure 1.1.1 below.
Fig 1.1.1: Aspects of business management
Another aspect that is prevalent in the organizations nowadays is the rewarding of the employees. Rewarding of the employees is a very common practice in today’s businesses since it is associated with the employee motivation and hence, the organizational workforce that leads to better performance (Zan, 2015). Since earlier developments and business practices that ensured better performance, there was a mix of rewarding tools that challenge the organization to adopt various measures to achieve. Many researchers have since, developed different systems that are geared towards rewarding the employees in the firm in a profitable way. Many people see this as a paramount activity in case the organization intends to engage the employees in a healthy manner and is, therefore, the key to the organizational performance. Reward systems have, therefore, become a significant part of the researcher’s interest as they seek to establish the best management practices that have a very crucial role in organizational success (Whitley, 2014). In fact, it is called for all the managers to think and re-think their decisions towards the activities that contribute to the success of the firm. Although there is a financial crisis in most of the firms nowadays, it is paramount to have a workforce that is determined and motivated to ensure productivity of the company. Also, rewards are seen as important aspects of preventing possible crises in the firm (Ajila & Abiola, 2014). However, for this to be achieved, numerous considerations ought to be made and implemented through a professional research.
1.2 Problem Statement
Performance measurement in a firm is an imperative aspect in both the practical and the theoretical spheres. Although many researchers have set their determination in the evaluation of organizational performance, there is still a gap that exists between the research conducted and the appropriate measures that should be undertaken (Vitale & Mavrinac, 2015). Numerous researchers in the management and accounting, as well as other fields, have set their sight on the effectiveness of the management practices that are conducted in numerous areas. However, none of the researchers has established methods of management that are crucial for all or most of the industries concerning measuring the performance of the firm. It is evident that all managers are concerned with growth and development of the firm while still undergoing minimal costs (Adams, Orvill & Hicks, 2010). However, some of the actions that ought to be undertaken by the management require financial support. Moreover, all organizations are concerned with the effectiveness of human capital in production so as to enhance their productivity (Venkatraman & Ramanujam, 2016). Employees are considered to be technically the human resources that are prevalent in the modern organizations and are thereby, considered very important aspects of organizational performance. Use of rewards has now become a crucial aspect of motivating employees so as to enhance performance with the fulfilling demands of the organization still being achieved. It was noted that the employees prefer the intrinsic rewards such as praise and recognition while other employees are happier with the extrinsic rewards such as salary increases, bonuses, and other incentives. However, there is need to establish a model concerning the correlation of the reward system and other aspects of organizational performance and success of the firm.
1.3 Purpose and Significance of the Study
The purpose of this study is to evaluate the management styles that are effective in real estate management and other industries to ensuring the success of the organization in achieving their set goals. It was noted that developing countries have considered numerous methods in their growing firms to make sure that there are success and development of their industrial sectors. One of the methods that is common in all these firms is the reward system. Countries such as China, Thailand, and India have embraced the reward system in most of their organizations with the aim of improving the performance of the firm through employee motivation (Tushman & Romanelli, 2015). Such managers noted that for a firm to realize its set goals, there is a need to have dedicated employees. One of the methods that they realized as effective is the recognition and appreciation of the employees and other forms of rewarding the employees. Also, the aspect of goal setting has proven paramount in every individual’s daily lives. Its importance is noted in the organizational success since firms have to develop and set objectives that are defined in their vision and mission statement. In this regard, it is important to come up with professional recommendations that are essential for the organizational management to put in practice to realize their firm’s goals. Also, the research will provide criteria for possible goal setting and provide actions that are more effective in the real estate management across the globe.
1.4 Research Aim and Objectives
The study’s aim was to investigate the impact of real management activities on performance. The study measured the management activities using three most common management techniques namely setting targets, measuring results and rewarding performance. Hence the study used the following specific objectives.
- To assess the effect of setting targets on organizational performance
- To investigate the effect of measuring results on organizational performance and
- To find out the effect of rewarding performance on organizational performance
- To understand the consumers’ perception of the most important element among seven “S”s in the model of real estate organizations
1.5 Research Questions
- What is the impact of setting goals on organizational performance?
- To what extent does measuring of results in a company impact on the organizational performance?
- How does rewarding of the employees impact on the organizational performance?
- What is consumers’ perception of the most important element among seven “S”s in the model of real estate organizations?
1.6 Research Justification
In the view of the study aims and research questions, it is evident that the findings of the study will have some practical relevance in the real estate management across the globe. One of the aspects that are important in firms although many employers do not fully comprehend is the aspect of reward system. Understanding the reward system and its significance in firms is paramount for the management as it will help them set out appropriate reward systems that have significance to the specific setting (Simons, 2010). It was noted that not all practices that are successful in one industry are successful in the other. This implies that the management should be aware of the appropriate methods that they should deploy. Also, the results of the findings in this study will have a vital impact on the planners for the human resource management in the real estates. Managers are bound to understand the rewarding systems that are appropriate for this type of industry so that they do not end up losing finances. The recommendations of the study will, therefore, prove vital to the success of many firms globally.
1.7 Research Theory
The key research theory employed was the 7-s Model by McKinsey. The theory suggests the application of an analyses tool to assess the organizational design of a firm by looking at 7 key internal elements which included structure, strategy, shared values, systems, style skills and staffs. The aim of the analysis is to identify if the elements are aligned in such a way that the organization is able to achieve its objectives. Research by Sim and Killough (2014) noted that reward management is a process that involves designing and implementing strategies that help the organizations to achieve their organizational objectives. In his study, he emphasizes the importance of setting goals and achieving them. However, although many firms, especially in real estate, have set goals and objectives, very few business owners and managers are aware of the best organizational practices to achieve their goals. It should be noted that mismanagement of the rewards just like any other forms of mismanagement can have detrimental effects on the organization. Sometimes, the rewards are susceptible to abuse thereby, destroying the intrinsic motivation (Simons, 2007). It is, therefore, important to come up with a research-based justification for the significance of the reward schemes. Managers need to be aware of the means of attracting, retaining, and engaging the employees with the best practices. The recommendations from this study will be essential for these managers to be aware of the measures that they can undertake to ensure employees are motivated. Also, it has become a difficult concept for the managers to ensure employee engagement in the right manner. This study, therefore, brings a common place among many practitioners to show a discretionary effort for real estate manager’s best management practices.
1.8 Conclusions
There is a need for the managers to recognize the needs of the employees and implement strategies that will ensure better performance and a successful team. As seen in the research problem, many firm managers, especially in the real estate, are not aware of the specific requirements in the firm’s management so as to ensure the success of the enterprise. Most of the managers reward the employees without a set goal or a financial analysis of the same. This implies that the company is likely to undergo mismanaged financial crises. This chapter also presented the research objectives that are vital to the study. One of the primary concern is the fact that for the creation of a competitive environment, there is need to have a reward system for the employees (Simons, 2015). However, managers do not have empirical evidence regarding the importance of reward systems to the organizational performance. Also, many firms set goals without consideration of the implication of the same towards the success of the company. It is evident that very few managers can relate the significance of setting goals to the success of the enterprise. This is because there is little evidence of the existing research concerning the correlation. However, this study seeks to reveal important recommendations for the managers particularly for the real estate management for the actions that they can take to facilitate better organizational performance and achievement of firm’s goals.
Chapter 2: Literature Review
2.1 Introduction
Organizational effectiveness is one of the most extensively researched issues since the early developments of the research theories. Despite the agreements by numerous researchers on the issue, there is still a common disagreement on the operationalization of the issues in all the organizations. New researchers have also focused more on the existing literature meaning that they hardly develop new results. However, Shenhav, Shrum and Alon (2014) noted that there is a need for the researchers in the field of management to have complementary streams with the specific evolution of the different areas of research as reconciled by the divergences and the convergences. Other researchers have narrowed down to the organizational theory and performance evaluation in a more theoretical manner. However, some of the aspects of corporate management are only practical and rewarding in a particular industry and might not be valid in another industry. To develop a framework that enables managers from different industries to use in their management, Scott (2017) developed a system of analytics that sort to relate the general firm’s perspective performance with the decisions taken. Also, the aspects of development that occur primarily on the mainstream of functional research paradigm have been investigated by numerous researchers. However, many researchers have paid their interest mainly on the management control systems forgetting the other vital aspect of employee best management practices. Despite this fallacy, all scientists agree that there is the need for the future researchers to focus on the employee satisfaction as an important aspect of organizational success.
2.2 Employee Rewards
2.2.1 Reward definition
According to Schiff and Hoffman (2016), rewards are the compensation benefits that a worker gets from a firm in exchange for the outstanding performance achieved by the employee in the working process. Rewards can also be seen as the assembly of the brain structures that regulator and also control the behaviors through induction of pleasure. It is very essential to pay the human resource in a business using different reward systems and techniques depending on the significance and importance. Rojas (2010) points out that management should develop an effective reward system that has a positive effect on the organizational performance. Many researchers and firm managers have shown a relationship between the reward systems deployed and the performance of the organizations. In this regard, organizations through their management teams must adopt policies and procedures that formulate the reward system in a way that increases the motivation of the employees (Foddy, 2014). One of the most crucial aspects of reward systems is its significance in employee motivation while the productivity of the firm is imperative. Roberts (2010) suggests that payment behaviors by the company are directly related to the firm’s productivity. Also, he argued that the reward system that a business develops depends on the size of the business. Moreover, the type of industry is paramount when designing any of the reward systems in the organization. Rewards are, therefore, considered imperative in any management that intends to achieve organizational goals and move a notch higher among its competitors in attracting and retaining more customers.
2.2.2 Types of rewards and significance (Intrinsic and Extrinsic)
According to Robbins (2013), rewards in the organization can be classified as either intrinsic or extrinsic. Intrinsic reward systems in the firm are the ones that individuals enjoy as a result of successfully completing the duties and achieving the goals. On the other hand, extrinsic rewards are the external rewards that include work conditions, pay, security, and fridge benefits among others. Also, Quinn and Rohrbaugh (2013) included the salaries, incentives, contract of service, bonuses, work environment, and job security as fundamental extrinsic rewards. However, researchers have indicated that every employee is attracted to different rewards as motivation. Despite this, it is agreed that employees are motivated by the rewards to work harder and improve their efforts to achieve the organizational goals. Also, such employees may set their targets which are higher than the goals of the organization. This implies that the company is likely to achieve higher goals that the set objectives are improving the organizational performance and ensuring competitiveness in the industry. According to Perera, Harrison and Poole (2007), rewards are important for the firm’s success since they have a psychological effect on the human resource. Considering that employees are the most important human resource in the organization, then intrinsic rewards are vital as they concern the psychological development of the employees that make them give free rewards. Research has shown that some of the intangible benefits such as feedback, participation and autonomy in decision making have a vital role in the success of the firm. This is because such employees will participate and are dedicated to achieving the organizational set goals as they were part of their initiation.
According to Ouchi (2009), intrinsic rewards that have proven successful in real estate management are mainly created to appreciate the employees in the form of self- esteem and other factors that are related to the emotional feeling of achievement and growth of the firm. When such an achievement is done, the employees are satisfied when they help in accomplishing tasks in work and that are orally appreciated in the organization. Norreklit (2010) also noted that the rewards shield the basic needs for the revenue to survive. Also, they help to create a sense of stability and recognition in the workplace. However, the researcher argued that there should always be an alternative topology that relates the two aspects of reward systems. Nowadays, many firms are using a mixture of both the extrinsic and intrinsic reward approaches to achieve employee motivation. However, Nevis, Dibella and Gould (2015) noted that although many employees appreciate cash reward system, managers should be discouraged not to extensively use this method when they seek to improve the performance levels of the organization. There is a likelihood that the need of the reward can be forgotten thereby, implicating negative organizational performance. Researchers warn the managers against using on- rewards thinking that they are motivational rewards since they have a negative impact on the organization (Neely, Gregory & Platts, 2015). Although they could be useful at times, they should be sparingly used since they are submissive and do not actually lead to optimistic organizational behaviors.
2.2.3 Rewards and Governmental Policy
Governments across the globe are nowadays increasingly adopting measures to ensure employee motivation through reward systems in the public sector. Some of the methods that are commonly adopted by the governments include the pays and incentives with the aim of improving the organizational performance (Neely, 2015). Researchers have indicated that the macroeconomic reforms should take note of the employees since they are vital human resources in the success of the organization. Nanni, Dixon and Vollmann (2012) also pointed out that governmental policies mainly emphasize on the payments as the integral components of the organizational performance. It was noted that many of the challenges that are prevalent especially in the public organizations relate to the lack of an appropriate compensation structure as well as weakness in the payment system. Researchers have argued that even though the governments take on salaries and incentives play a crucial role in organizational success, there are problems associated with the same that require organizations to look beyond the wages (Grandey, 2013). Some of them must include recognition, appreciation, promotion, working environment and bonuses. In this regard, it is important for the governmental organizations to advocate for the rewarding system that takes into account both the intrinsic and extrinsic reward components. Mitchell, Agle and Wood (2017) emphasized this in his research where he evaluated the organization ability to cope with the employee’s needs. It was evident from the research that meeting the needs of the employees is an indispensable ingredient for the performance of the organization. This implies that as managers seek to improve their organizational success, numerous factors need to be considered especially in public organizations.
2.3 Organizational Performance
2.3.1 Definition
According to Mia and Clarke (2012), corporate performance is the real output or organizational results that are measured against the intended outputs. According to the research, organizational performance also encompasses the three primary aspects of product market performance, financial performance, and shareholder return. Many researchers take organizational performance as the ultimate independent variable especially in quantitative studies as a variable for interest in any area of management Meyer and Gupta (2012). The broad construct that allows the researchers to focus on the employees is paramount as an aspect of consideration by the managers for the success of the organization. It was noted that for the firm to succeed in achieving the organizational goals, various measures must be taken concerning the employees. In this regard, the organizational performance is one of the most crucial criteria that is used by the firms to evaluate the organization, actions, and environment towards better performance. March and Sutton (2007) argued that it is imperative for any company to know how they are performing and this cannot be achieved without a clear goal and system of evaluation. This makes organizational performance a vital step in the organization. Many managers, therefore, deploy numerous methods of performance measurement that exist as developed by researchers.
2.3.2. Performance measurement
Numerous methods have been put forward for the analysis of the organizational performance at the organizational and the employee level. Some of the methods take into account the traditional methods while others are based on the assumptions where the performance is measured as the quantifiable units. According to Lipe and Salterio (2010), there are important financial measures of organizational performance that must be evaluated by any firm such as the income or the sales from operations, residual income, and the return on investment. Although these accounting and financial measures are paramount due to their importance, Levinthal and March (2011) noted that they are backward looking and cost based on little motivation. However, there are very few metrics that measure the performance of the organization as adopted by the financial specialists. One of the methods that are widely used is the balanced scorecard that is a set of different performance measures for the company. This method includes the performance measurement for the innovation, customer services, and the internal processes. One of the fundamental aspects in measuring performance is an evaluation of the different key players who have a vital role to this performance. For example, some people take into account the aspects of complaints, repeated customers, efficiency, and quality delivery of the services (Langfield-Smith, 2014). While the working and organizational environment are rapidly changing, there is a need for the improvement of the skills. However, all these are irrelevant if the employees are not inspired to work hard and realize the organizational goals. In this regard, performance measurement takes into account the different elements that lead or contribute to the success of the organization.
Another research by Kren (2014) revealed that performance appraisals could be used by the researchers in the quest for conducting management performance evaluation. The study also noted that the fulfillment of a firm could be measured regarding output such as the quantity and the quality of jobs. In fact, Kloot (2011) argued that job performance should be designed in a way that achieves the organizational objectives. One thing that is evident in all the pieces of research is the fact that specific conditions ought to be set so that the specific organizational goals can be achieved. Some of the measures that are vital for any management is the implementation of an efficient reward system. Kaplan (2010) noted that reward systems are crucial since they motivate the employees to work harder and hence, increase their performance. Other aspects of organizational performance that are vital include speed, accuracy, and also the number of transactions that are done in a particular time. The overall performance of the organization regarding sales volume and productivity are also impacted by the systems that are implemented. However, the research noted that organizational performance measurement is a hard task for most companies. It is important to have a system that works to relate and measure performance so that the management can realize the effectiveness of the strategies undertaken. Nevertheless, measuring performance must be done in all aspects even with scanty of models and measurement techniques especially in real estate management (Ittner & Larcker, 2010).
2.4 Theories Explaining Reward Systems
2.4.1 Herzberg’s Two Factor Theory
Numerous theories are adopted to explain the existing link and relationship between levels of the employee reward approaches and the performance of the firm. However, Herzberg’s two-factor theory is the commonest in this perspective of management (Huber, 2011). This theory suggests that people have sets of needs such as the need to grow psychologically and the need to avoid pain. Through the survey that Herzberg conducted on the issue, he found that the responses are entirely different when people feel good or bad about their job. He found that intrinsic factors such as work, achievement, and responsibility played a vital role towards job satisfaction (Hoque, Mia & Alam, 2011). Pieces of research have related this aspect with the employees in the job performance since many of them tend to associate these factors with their feelings. On the other hand, the employees who are not motivated tend to quote the extrinsic aspects like the supervision, payments and policies within the company, and attribute them to their feelings. Two factor theories are paramount in this study since they mention the factors that influence work performance. Issues such as salary and promotion are vital in the employment; hence, rewarding employers are likely to have a better environment for their employees (Hopper & Powell, 2015). Also, better work performance is realized when the employees are all geared towards the achievement of the set goals. This implies that they all have to show aggregated and collective efforts towards the performance.
2.5 Reward Systems and Organizational Performance
2.5.1 Effects of intrinsic rewards on organizational performance
Numerous researchers attribute intrinsic rewards to both individual and corporate performance. Hage (2010) noted that the employees in an organization are in the esteemed stage of development. Researchers have noted that these type of rewards enhance the employer and employee relationship as well as the ability to challenge the new tasks together accomplishment of new tasks. Such people can easily work in one accord and harmony. For an organization to realize organizational success, it is paramount to consider some of the aspects of corporate operations that seek to energize the employees (Gosselin, 2011). Employees who are intrinsically motivated are likely to become the marketers, informal recruiters in the organization through recommendation to their friends for the business products and services. However, employees who are not motivated intrinsically do not recommend potential customers to the services of the company. In fact, Goodman, Pennings and Associates (2017) indicated that intrinsic rewards create a win- win situation for the employees and the organization. When the employees are motivated, they feel happy and satisfied and are, therefore, in a better position to offer their best. The feelings of self- worth create job satisfaction and then it translates to the improvement of the work performance. On the other hand, the organization is likely to increase their sales volume and profit maximization. Also, there is a likelihood of greater levels of satisfaction and competency for the employees who are intrinsically motivated. Such employees work with more confidence thereby, enhancing organizational performance (Flamholtz & Tsui, 2015).
2.5.2 Effects of extrinsic rewards on organizational performance
According to a study by Cameron (2014), extrinsic rewards are vital since they cover all the important and basic needs of income to survive. It should be noted that all employees work so that they can meet a living. In this regard, salary is a vital motivation to every employee. Issues of stability and consistence, as well as recognition, are fundamental for all the employees. Some of the attributes that are discussed include salary, fridge benefits, and job security that can be compared to the context of Herzberg which he referred to as hygiene. A study by Burns (2012) indicated that social recognition rewards and financial rewards have a positive impact on the performance of employees. He argued that if the management ought to make the employees show their creativity, they have to use the extrinsic rewards. Also, other pieces of research have shown that extrinsic rewards help in enhancing individual’s creative performance who then turns to ultimately contributing to the performance of the organization. However, Yasmeen, Farooq and Asghar (2013) noted that it is not clear how the reward system impacts on the group effectiveness. While the rewards will impact on an individual positively, they must not be geared towards the achievement of the same goals. However, it is evident that such a reward system impacts positively on the employee performance that translates to organizational performance. This implies that workers compensation package ought to be taken with a lot of concern by the employers due to their significance in employee motivation and organizational performance.
2.6 Organizational Goal Setting
2.6.1 Organizational goal types
Organizational theories are crucial in the evaluation of various aspects of organizational performance. They are defined with the organizational goals that indicate the corporate level. Wood (2014) noted that the issue of organizational goal has evolved with time although the theoretical discussions for the organizational goal setting emphasize on the evaluative and normative functions. Researchers show that for an organization to succeed, they must work towards a particular direction through the set goals and objectives (Hackman & Oldham, 2016). Many people work with a specific idea and target that they need to achieve. Organizational goals are, therefore, the essence for benchmarks so as to ascertain whether the organizational behaviors are geared towards achieving profit maximization. Any manager in an organization intends to see his/ her organization in succeeding in attracting more customers and retaining quite a number so as to realize the best of profits (Williamson, Burnett & Bartol, (2009). Competition has grown to very high levels in all industries that require members of the party to ensure that they adopt the measures that are effective in ensuring organizational success. It was noted that organizational goal types must show a balance of the conflicting interests with the organizational behaviors in the forefront of organizational performance (Vance, 2012). Several actions ought to be undertaken so as to ensure that the goals set by the organization have a positive impact towards the organization. Also, it is vital for the steps taken to ensure the increase of sales and to improve profits in the firm.
2.6.2 Complexity of organizational goals
One theory that focuses on the challenges of organizational goals achievement is the complexity theory. Many researchers base their evaluation of organizational goal setting to the complexity theory so as to analyze various models and strategies that can be effective to the management (Tosti & Herbst, 2009). Some of the complexity that is witnessed in an organization is as a result of the interacting parts and personnel within the human resources. However, one complexity that is of particular interest to the researchers is the issue of organizational performance and complexity in achieving the same (Henderson, 2016). While many researchers argue that a company can overcome obstacles if they set goals, the petite evidence is given to show the correlation. However, many researchers have argued that the relationship must be positive since when an organization sets goals, they deploy the methods of achieving these goals (Schwartz, 2016). Another aspect that entails complex decision making is the complex environment that is prevalent nowadays. Researchers have shown that effective responses in the organization can be obtained when there is sustainability. Applying complexity in study goals is apparent so as to create the doubt that arises from single criterion. Scott (2010) noted that different goals that are set in the organization serve for different purposes towards the success of the firm. Managers who want to achieve specific and difficult tasks must be able to develop a particular interest in developing working goals. Despite the complexity, measures can be taken if the goals are set, and efforts are made towards achieving them.
According to Pulakos and O’Leary (2011), the complexity of setting goals in an organization is shown in the number of interdependence for the organizational goal types that are applied in an organization. The number of the target types that are emphasized by the group define the success of the firm. Researchers have shown that multiple goals are vital to the success of the organization and avoidance of the complexity. However, such goals are important to the organization since they provide the organization with a broader representation of the environment. This is vital for the relationship within the organization. Also, Nielsen and Therkildsen (2015) discussed that there is a balancing of conflicts when the organization sets achievable goals. However, this cannot be done without a proper mechanism that ensures that the stakeholders receive all the activities. Developing many goals in the organization ensure that the organization has multiple objectives and market possibilities. Such enables exploration of ideas and professions that see the exploitation of all the available materials and opportunities for the success of the firm. One particular aspect that is important in organizational success is the issue of goal type variability. According to Nawab, Ahmad and Shafi (2011), it refers to the prioritization among the set goals so as to ensure diversity. When this is done, it is possible to ensure that interests are achieved and set depending on necessity. There is a clear priority when it comes to organizational goal types and decision making which is vital for goal attainment.
According to Mikander (2010), the particular level of goal type complexity ensures the ability of the firm to exploit the environmental resources so as to attain their goals. When an organization creates a larger number of goal types, it implies that the enterprise is able and willing to balance the prevalent conflict of interests of the many stakeholders. Also, they do so to maintain the alertness of the indirect and the direct environmental factors. Research showed that for them to exploit the industrial munificence, companies must demonstrate the alertness in facing the problems that arise directly and using the best methods to resolve them (Lin, 2007). It was noted that environmental factors play a vital role for the organization to achieve their set goals. When an organization has a clearer vision, then they can ensure complete search for the opportunities within the industry. Many business managers have realized that it is important to go an extra mile and set multiple and conflicting goals so as they can evaluate the possibilities in many dimensions. Also, the organizations can set the required objectives for the present and the future of the organization. Goals must, therefore, be established with the aim of improving the performance of the firm (Lawler, 2015). Some studies have shown that well- set goals are pivotal for all the performing companies. This is because they can detect the opportunities that are scarce and ensure most appropriate measures to reap maximum benefits. In this regard, organizations can ensure growth and development if they adopt specific goals and deploy appropriate measures to achieve them.
2.7 The McKinsey’s Seven “S”s Model
The McKinsey’s 7s model, developed by Robert Waterman and Tom Peters (1980s), is a powerful tool used to assess and analyze the changes in the organization’s internal situation. The model is based on 7 key elements which help in determining the success of an organization. The elements are interdependent and aligned in such a way to allow for production of synergistic outcomes. The McKinsey 7s model represents the seven primary integrated or interrelated elements of an organization which appear in two broad categories namely hard and soft elements. The elements in the hard category are those that are within the direct control of the management. The elements include strategy, structure and systems. The strategy defines the action plan or the roadmap which the organization uses to gain a competitive advantage over the others. The structure, on the other hand, refers to the reporting pattern of an organization. Finally, the systems are defined as the daily activities involved by the staff members to ensure the completion of their assigned tasks. Conversely, the elements in the soft category are those that are tangible and difficult to be defined or identified. Such elements are more governed by the culture. However, the proponents of the McKinsey 7s model points out that the elements in the soft category are equally important as the elements in the hard category. The elements classified as soft elements include shared values, style, staff and skills. The shared values define the superordinate objectives which the codes of ethics or the organizational culture reflects upon. The style is an element used to lay emphasis on the style of leadership and the impact it has on the strategic decisions, organizational performance and people motivation. The staff, on the other hand, represents the general capabilities of the workers. Finally, the element of skills represents the core competencies of the workers and the role they play in defining the success of an organization. The seven ‘S’s and their respective categories are as described in the figure below.
Fig 2.7.1: The McKinsey 7s model
According to the figure above, the shared values are positioned at the center of the model implying that they influence the rest of the elements in the model which are interrelated and interconnected. The existence of the organization provides the origin of other elements since it is the vision set by those who create the organizational values. Hence, a change in the values results in an equal change from other parameters.
2.8 Consumers’ perception of the most important element among seven “S”s in the model of real estate organizations
Previous studies have pointed out that the Seven S Model is very useful in identifying the inconsistencies or gaps available between elements. Further, previous research revealed that the model provides a strategic action plan that enables the management to reach the desired organizational state. Checking of the alignment between each element is done by paying attention to three major steps namely, assessing the shared values, assessing the soft elements and the hard elements for alignment and interdependence and making adjustments or changes as well as conducting an analysis to investigate whether the elements function in alignment or otherwise.
Contradicting results have been presented by different researchers about consumers’ perception of the most important element among the seven “S” s in the McKinsey 7s model. According to Nawab, Ahmad and Shafi (2011), consumers feel that the seven “S”s in the model are not very important since they ignore the importance of the external environment while depicting only the crucial elements in the model to explain the interdependence of the primary factors and processes within the organization. To the contrary, Tosti and Herbst (2009) claimed that consumers perceive that elements in the hard category are more important than the elements in the soft category. The reason given by the researcher is that the hard elements are more applicable when analyzing and evaluating the impacts of futuristic adjustments on the organization. Further, the researchers pointed that the hard elements were more useful when the providing a recommendation framework for the implementation of a strategic action plan.
2.9 Conclusion
Literature from the research shows that organizations need to ensure engagement with the employees so that they can succeed in achieving their objectives. This chapter summarized the important aspects of organizational performance and enhanced the organizational goals that they seek to achieve. Many researchers focus on the employee engagement and other things that they can undertake so as to achieve the best (Lawler, 2008). It was also noted that employees are the most valuable human resources that are available for the organization. Some of the important aspects of the study that every firm must emphasize are the issue of reward systems. Although many researchers agree that the different types of rewards and reward systems have a specific role in organizational performance, it is not clear how they impact on the same. Also, managers are not aware of the actions that they should undertake so as to facilitate growth. Best performing companies, however, have developed systems for measuring performance in the already existing methods such as financial management and output means (Jibowo, 2017). However, there is the need for further research to show the correlation between the aspects of organizational performance and output. Goal setting is also a fundamental aspect that the firms ought to undertake so as to ensure that there are a clear path and activities that facilitate achievement of the organizational success.
2.10 Hypothesis Development
The available literature showed that the number of the target types that are emphasized by the group define the success of the firm. Also, setting of goals affects the organizational performance positively (Lawler, 2015). The particular level of goal type complexity ensures the ability of the firm to exploit the environmental resources so as to attain their goals (Henderson, 2016). Additionally, there was evidence of significant impact of measuring results on the performance of the firms. Further, the available information in the literature revealed that rewarding of the employees significantly impacts on the organizational performance (Jibowo, 2017). Above all, different researchers have presented differing results concerning the consumers’ perceptions of the most important element among seven “S”s in the model of real estate organizations. Conversely, other researchers claimed that consumers feel that the seven “S”s in the model are not very important since they ignore the importance of the external environment while depicting only the crucial elements in the model to explain the interdependence of the primary factors and processes within the organization. Following the information available in the literature, the study developed three sets of hypotheses as shown below.
Hypotheses set 1
H0: The impact of setting goals on organizational performance was not significant
H1: The impact of setting goals on organizational performance was significant
Hypotheses set 2
H0: Measuring of results in a company dos not impact on the organizational performance
H1: Measuring of results in a company significantly impacts on the organizational performance
Hypotheses set 3
H0: Rewarding of the employees does not impact on the organizational performance
H1: Rewarding of the employees significantly impacts on the organizational performance
Hypothesis set 4
H0: The consumers’ perception of the most important element among seven “S”s in the model of real estate organizations was the same
H1: The consumers’ perception of the most important element among seven “S”s in the model of real estate organizations was different
2.11 Conceptual framework
The conceptual framework was described using the mind map diagram as shown below.
Fig 2.9.1: Mind Map diagram
Chapter 3: Research Methodology
3.1 Introduction
The third chapter in this dissertation provides the description of the research methods adopted by the researcher. The chapter went further to give justifications of why the selected techniques were chosen by comparing their advantages over the alternative approaches. The chapter was, hence, presented through some sub-sections for the description of the research methods, design, target population and the selected sample, data collection procedures, data analysis and ethical considerations.
3.2 Method
The study adopted a quantitative approach. However, there are two alternative research methods which could have been adopted by the study. The alternative methods included qualitative research or mixed research techniques. The quantitative research approach involves the gathering of information in the form of numbers and statistics, often arranged in charts, tables, figures or other forms of non-textual data. The data is then analyzed using mathematical techniques to yield results and the conclusions made based on the analysis results. Conversely, qualitative research methods involve the collection of qualitative data regarding thoughts and opinions to uncover trends and dive deeper into the problem. Ideally, qualitative research utilizes the technique of inquiry which seeks to gather an in-depth knowledge of individuals’ behavior and the reasons that govern such kinds of behavior. To the contrary, some studies opt to combine aspects of both qualitative and quantitative methods in a single study. When this happens, it is said that the study adopts a mixed research method.
The researcher of the current study compared the merits and demerits of the possible research approaches, and the analysis led to the justification of the choice of quantitative research approach. In additional to the ability to use questionnaires and computer software to collect and analyze data, quantitative research approach allows for wider generalization of concepts, prediction of future results and investigation of a causal relationship. The current study aimed at investigating the relationship between real estate management and the organizational performance. Therefore, adoption of quantitative research method was paramount to achieve the desired results. Conversely, the alternative research methods faced a great disadvantage in that the researcher bias would be built in and unavoidable.
3.3 Design
The study design for this research was a descriptive design involving the analysis was done through quantitative research methods. The design is in many research cases used as a pre-cursor to the quantitative approaches since its general outline provides some important pointers to the variables that are worth testing using quantitative techniques. The major advantage which led to the adoption of the descriptive design is that the design offers an opportunity for the participants to be involved in a completely unchanged and natural setting.
3.4 Population and Sampling procedures
The study targeted the population of all managers and employees in the decision making positions from companies dealing with real estate management or property management. It was believed that this population was well familiar with the management activities implemented in their respective organizations and the levels of adoption made by the management. Also, the same population was in a position to confirm the organization performance retrieved from the various secondary sources concerning the organizations. However, collecting data from the entire population was a major challenge since the process would consume a lot of time and other resources. Also, the level of supervision would be small, and hence, the quality and integrity of the data would be poor leading to a lack of credibility and reliability of the study findings. Therefore, the study opted for a sample survey.
The research was based on purposive sampling method. This is a non-probability sampling technique where the sample is selected depending on the population’s characteristics and the objective of the research. For this particular study, the individuals were selected by connection, knowledge, and judgments of the researcher in the management activities implemented in one’s organization and the levels of adoption made by the management. The alternative use of probability sampling was not considered because of limited time and resources. The members of data collection team made contact with potential respondents via the email although phone calls were made when applicable. The informed consent form was first sent to the potential participant. The form was accompanied by a letter clarifying the purpose of the study and the time range they were supposed to get involved in the survey. The participants were requested to sign the form to show their interest in taking part in the study. Any respondent who signed the informed consent form received an email containing the survey questionnaire. The process continued until the researcher had a total of 80 participants who were willing and ready to participate in the study.
3.5 Data Collection procedures
The data was collected using a close-ended questionnaire. Although open-ended questions allow the researcher to realize the responses that participants provide spontaneously and also avoids the biases that could be introduced by the suggestion of responses, these type of questionnaires have great disadvantages. A significant advantage of the close-ended questions over the open-ended questions is the need for an extensive coding as well as the larger item non-response.
The questionnaires aimed at gathering data which was categorized into three broad categories namely the demographic data, explanatory factors and response factors. The demographic data included the respondents’ age, gender, job position and the region from which his organization is based. The explanatory factors were set to develop the independent variables in the study. The factors under the explanatory category included the level of target setting adopted, the level of measuring results adopted and the level of rewarding performance adopted. Lastly, the questionnaire gathered data on the response factor which was set to produce the dependent variable in the study. This variable included the organizational performance.
Both primary and secondary sources of data were used. The primary sources included the respondents who helped with the demographic data and the explanatory of the independent data. Conversely, the response variable which included the organizational performance was sourced from the organizational annual report. Hence, the data for the response variable was sourced from the secondary sources. However, the respondents were requested to confirm whether the value of the organizational performance recorded was correct or not.
The measurement of the data was done differently for the various variables. The age variable was measured on a continuous scale where each respondent was supposed to state his/her age in years. The gender variable was measured using a categorical scale with two classes labeled 1 and 2 for males and females respectively. The job position variable was also measured using a categorical scale with four classes labeled 1, 2, 3 and 4 for the manager, head of the department, customer service agent and others respectively. The region variable was measured using six categories representing the six regions of the world namely Western Europe, Central and Eastern Europe, Africa, Asia, the Middle East and Mediterranean, and the Americas. For the explanatory or independent variables, the study used a Likert scale ranging from 1-10 with 1 showing little implementation levels and 10 showing high implementation levels. The performance was measured using a standard scale for all organizations and presented as a percentage of the organizations’ total input.
3.6 Analysis Procedures
The study used SPSS software or the analysis process. The software, known by the name IBM SPSS Statistics, is an integrated family of statistical products that offers help to data analysis to address the whole analytical process ranging from data planning and collection to analysis and lastly to reporting and deployment. The analysis process was split into three sub-sections. The first section aimed at describing the demographic background of the sample. In this section, the study utilized the frequency histograms and the frequency distribution tables. The second analysis section involved the descriptive analysis. The section aimed at revealing the measures of central tendency, distribution, and dispersion of both the explanatory and response variables. In this section, the study utilized the descriptive analysis technique where statistics such as mean, median and coefficients of skewness and kurtosis. The third analysis section involved the inferential analysis procedures. Under this section, the study aimed at revealing the impact of various management activities adopted by the real estate companies on the organizational performance. The inferential analysis procedures utilized the linear regression model where the setting of targets, measuring results and rewarding of performance were set as the explanatory factors and the organizational performance set as the response factor. The following linear model was adopted.
y=b0+b1x1+b2x2+b3x3+ijkl
In the above model, the term y represented the organizational performance while the terms x1, x2, and x3 represented the setting of targets, measuring results and rewarding of performance respectively. The model was used to reveal the common effect of the explanatory or explanatory variables on the organizational performance. The individual impact of each of the independent variables was assessed using the T-test technique. The test statistic was calculated using the following formula.
Where x1 is the mean of a particular variable and x2 the hypothesized mean. The term s1 and s2 represents the sample’s standard deviation and the hypothesized standard deviation respectively.
3.7 Considerations of the Ethical requirements
All management research projects call for the researcher to explicitly understand the values, have increasing capacity to anticipate and reflex for various ethical dilemmas that are necessary for research endeavors. The researcher designed the current study in such a way that the processes ensured quality, integrity, and transparency. Also, the participants were fully informed about the aim, approaches and the intended uses of the research findings, what the respondents’ participation entails and what risks or benefits they were likely to encounter. Further, the confidentiality and anonymity of the information given by the participants were respected, and no information that allow for the identification of the participant was published in the public domain. The study ensured that the participants took part in the study voluntarily and free from coercion. The voluntary participation was ensured through the signing of the informed consent form. The study made sure that there was an apparent independence of the research and any conflicts of interest from the participants was avoided.
3.8 schedule
A Gantt chart was employed by the study as the project’s schedule control tool. The projected was projected to take duration of 9 weeks as described by the Gant chart below.
Fig 3.8.1: The Gantt Charts
| Activity | Wk1 | Wk2 | Wk3 | Wk4 | Wk5 | Wk6 | Wk7 | Wk8 | Wk9 |
| Preliminary investigations | |||||||||
| Writing the proposal | |||||||||
| Submitting the proposal for approval | |||||||||
| Gathering of the study data | |||||||||
| Analyzing the data | |||||||||
| Writing the report draft | |||||||||
| Submitting the report draft for corrections | |||||||||
| Writing and submitting the final report |
Chapter 4: Analysis Results and Discussions
4.1 Introduction to the analysis
The fourth chapter in the report helped to present the research findings by setting out the results of the study’s questionnaire data for various analysis sections. The chapter started by presenting and discussing the results of the demographic characteristics and then made a discussion of descriptive and inferential analysis results.
4.2 Analysis of Demographic Data
The analysis of the demographic data showed considerable variations in the assessed variables. According to the study, the age varied significantly from a minimum value of 25 to a maximum value of 54 years. The graphical representation of the age data, as presented by the frequency histogram, showed that the data was normally distributed with an average value of 42.03 and a standard deviation of 7.642. However, the histogram had a longer tail to the left side than to the right. Hence, the age data was negatively skewed implying that a majority of the people in the Real estate companies at a management or decision making position were older than the average age of the workers in the real estate industry.
Fig 4.2.1: Histogram chart for the age data
The study showed that many of the participants were females with a frequency of 44 (55.0%). The proportion of male respondents was represented by a frequency of 36 (45.0%). The results indicated that individuals in the real estate industry who worked in the management or other decision-making positions with interests in management research were females. The conclusion was made because the participation was free from coercion and, hence, only those employees with interest in the topic showed interest in participating in the study.
The analysis showed that a majority of the respondents were in the management and other job positions with frequencies equal to 24 (30.0%) and 25 (31.3%) respectively. The proportions of respondents in the head of departments and customer service agent positions were represented by frequencies equal to 12 (15.0%) and 19 (23.8%) respectively. The results implied that managers were more interested in understanding the impacts of real estate management activities on the organization performance and, hence, their desire and willingness to participate in the study was higher that workers in the head of departments and customer service agent.
| Table 4.2.2: Job Position Distribution Results | |||||
| Frequencies | Percentages | Valid Percentages | Cumulative Percentages | ||
| Valid | Manager | 24 | 30.0 | 30.0 | 30.0 |
| Head of department | 12 | 15.0 | 15.0 | 45.0 | |
| Customer service agent | 19 | 23.8 | 23.8 | 68.8 | |
| Others | 25 | 31.3 | 31.3 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
A majority of the participants were from the America, Asia, Western Europe and Central and Eastern Europe with frequencies equal to 18 (22.5%), 16 (20.0%), 14 (17.5%) and 13 (16.3%) respectively. The proportion of respondents from Africa and Mediterranean and the Middle East regions were presented by frequencies equal to 11 (13.8%) and 8 (10.0%) respectively.
| Table 4.2.3: Region Distribution Results | |||||
| Frequencies | Percentages | Valid Percentages | Cumulative Percentages | ||
| Western Europe | 14 | 17.5 | 17.5 | 17.5 | |
| Central and Eastern Europe | 13 | 16.3 | 16.3 | 33.8 | |
| Asia | 16 | 20.0 | 20.0 | 53.8 | |
| Africa | 11 | 13.8 | 13.8 | 67.5 | |
| Mediterranean and the Middle East | 8 | 10.0 | 10.0 | 77.5 | |
| Americas | 18 | 22.5 | 22.5 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
4.3 Descriptive results
The descriptive analysis was performed for independent and dependent variables separately. The analysis of the independent variables showed that the three factors averaged at 5.1125, 5.1500 and 5.2500 for the setting targets, measuring results and rewarding performance respectively. The analysis further revealed that the three factors varied at a standard deviation of 2.78329, 2.74254 and 2.58281 for the targets, measuring results and rewarding performance respectively. The minimum and maximum values for the level of targets, measuring results and rewarding performance set by the real estate companies were 1 and 10 respectively.
| Table 4.3.1: Descriptive Statistics Results | |||||||||
| N | Minm | Maxm | Mean | Std. Dev. | Skewedness | Kurtosis | |||
| Value | Value | Value | Value | Value | Value | Std. E | Value | Std. E. | |
| Setting targets | 80 | 1.00 | 10.00 | 5.1125 | 2.78329 | .282 | .269 | -.975 | .532 |
| Measuring results | 80 | 1.00 | 10.00 | 5.1500 | 2.74254 | .035 | .269 | -1.066 | .532 |
| Rewarding performance | 80 | 1.00 | 10.00 | 5.2500 | 2.58281 | .128 | .269 | -.912 | .532 |
| Valid N | 80 | ||||||||
The descriptive statistics for the models independent variable showed that on average, the organizations in the real estate industry showed a performance level of 42.38% when assessed on a standard scale. The median score was 42.5% with a mode of 35%. The standard deviation for the organization performance was 22.42. The value indicated that there was a great variation in the organization performance across different companies in the real estate industry. Another important statistic was the coefficient of skewedness. The value was equal to 0.138. Clearly, the value was greater than zero, indicating that the performance data was positively skewed. The results implied that a majority of the organizations in the real estate industry performed better than the expected performance level.
| Table 4.3.2: Results for the level of performance | ||
| Organizational performance | ||
| N(Total) | Valid | 80 |
| Missing values | 0 | |
| Mean/average | 42.3875 | |
| Median score | 42.5000 | |
| Mode | 35.00 | |
| Standard Dev. | 22.41637 | |
| Skewedness | .138 | |
| Std. Error of Skewedness | .269 | |
| Kurtosis | -1.104 | |
| Min value | 6.00 | |
| Max value | 85.00 | |
The frequency histogram for the organizational performance data showed that the variable was normally distributed with a mean of 42.39 and a standard deviation equal to 22.416. Also, the frequency histogram revealed that the data was continuous ranging from 6 to 85 for the minimum and maximum values respectively.
Fig 4.3.1: Frequency histogram for the organizational performance
The results described by the frequency histogram for the organizational performance showed that all the necessary assumptions for a linear regression model were met. The first assumption was that the dependent variable should be normally distributed with a given mean and standard deviation as the model parameters. The second and very necessary assumption was that the dependent variable was continuous in nature within a given range. After verifying the assumptions for the linear regression model, the study continued with the inferential analysis where a linear regression model was adopted.
4.4 Inferential analysis
The first type of inferential analysis conducted by the study involved the correlational analysis. The study computed the correlation coefficients for the pairwise correlation between organizational performance and each of the three independent variables, setting targets, measuring results and rewarding performance. The coefficient of correlation between organizational performance and setting targets was 0.906 with a probability value of 0.000. The coefficient implied that there was a strong, relationship between performance and setting of targets. Also, the probability value was less than 0.05. Hence, the nullifying hypothesis, which stated that the two variables were not significantly correlated, was rejected. The coefficient of correlation between organizational performance and measuring results was 0.896 with a probability value of 0.000. The coefficient implied that there was a strong, positive correlation between performance and measuring results. Also, the probability value was less than 0.05, the alpha level of significance. Hence, the nullifying hypothesis, which stated that the two variables were not significantly correlated, was rejected. Further, the coefficient of correlation between organizational performance and rewarding performance was 0.909 with a probability value of 0.000. The coefficient implied that there was a strong, positive relationship between performance and rewarding performance. Also, the probability value was less than 0.05. Hence, the nullifying hypothesis, which stated that the two variables were not significantly correlated, was rejected. The analysis also showed a positive correlation between the independent variables. What this meant is that the organizations which set high levels of targets were also having elevated levels of results measuring and further provided better rewards for performance.
| Table 4.4.1: Correlations analysis results | |||||
| Organizational performance | Setting targets | Measuring results | Rewarding performance | ||
| Organizational performance | Pearson’s Correlation | 1 | .906** | .896** | .909** |
| Significance value | .000 | .000 | .000 | ||
| N | 80 | 80 | 80 | 80 | |
| Setting targets | Pearson’s Correlation | .906** | 1 | .867** | .861** |
| Significance value. | .000 | .000 | .000 | ||
| N | 80 | 80 | 80 | 80 | |
| Measuring results | Pearson’s Correlation | .896 | .867 | 1 | .843 |
| Significance value | .00 | .00 | .00 | ||
| N | 80 | 80 | 80 | 80 | |
| Rewarding performance | Correlation | .909 | .861 | .843 | 1 |
| Significance value | .000 | .000 | .000 | ||
| N | 80 | 80 | 80 | 80 | |
A further assessment was done by fitting a linear regression model to the data with variables setting targets, measuring results and rewarding performance as the independent or explanatory factors and organizational performance as the dependent or response factor. The analysis results showing the model summary revealed that the model fit was good. The conclusion made following the observation that the computed for R-value and R-squared were 0.950 and 0.903 respectively. The R-value represented the correlation coefficient, and it implied that the model’s independent variables were highly correlated with the dependent variable. The value of R-square represented the coefficient of determination, and it suggested that setting targets, measuring results and rewarding performance influenced 90.3% of the variations in the organizational performance.
| Table 4.4.2: Regression Results | ||||
| Regression Model | R-value | R-Squared | Adj. R Squared | Standard. E. |
| 1 | .950a | .903 | .899 | 7.10776 |
| a. Predictors: (Constant), Rewarding performance, Measuring results, Setting targets | ||||
The study performed an analysis of variance test to assess the impact of the model. The results produced sums of squares equal to 35857.449 and 3839.538 for the model and error respectively. The mean sums of squares were equal to 11952.483 and 50.52 for the regression and residual respectively. The values yielded a computed F-value of 236.588 with a probability of 0. Hence, the model was statistically significant.
| Table 4.4.3: Analysis results of the variances | ||||||
| Model | S of Squares | D f | Mean S of Square | F-stat | Sign. | |
| 1 | Regression | 35857.449 | 3 | 11952.483 | 236.588 | .000b |
| Residual | 3839.538 | 76 | 50.520 | |||
| Total | 39696.988 | 79 | ||||
| a. Dependent Variable: Organizational performance | ||||||
| b. Predictors: (Constant), Rewarding performance, Measuring results, Setting targets | ||||||
The results of the model coefficients produced values equal to -0.731, 2.542, 2.399 and 3.385 for the model constant, setting targets, measuring results and rewarding performance respectively. The values implied that all the three independent factors influenced the performance levels positively. The analysis revealed that the performance was expected to increase by 2.542 levels for a one level change in the target level holding the measuring of results and rewarding of performance factors constant. Also, the analysis revealed that the performance was expected to increase by 2.399 levels for a one level change in the measurement of results holding target level rewarding of performance factors constant. Further, the analysis revealed that the performance was expected to increase by 3.385 levels for a one level change in the reward for performance holding the level of target setting and measuring of results constant.
| Table 4.4.4: Coefficients analysis results | ||||||
| Model | Un-std. Coefficients | Std. Coefficients | t-stat | Sign. | ||
| B (parameters) | Standard. E. | Beta values | ||||
| 1 | (Constant) | -.731 | 1.826 | -.400 | .690 | |
| Setting targets | 2.542 | .658 | .316 | 3.863 | .000 | |
| Measuring results | 2.399 | .633 | .293 | 3.788 | .000 | |
| Rewarding performance | 3.385 | .658 | .390 | 5.140 | .000 | |
| a. Dependent Variable: Organizational performance | ||||||
The level of target setting produced a computed T-value of 3.863 with a probability value equal to 0. The probability value was less than the set alpha level indicating that the nullifying hypothesis, stating that setting of targets never influenced performance, was rejected. Hence a conclusion was made that target setting statistically influenced the organizational performance. The level of results measuring produced a computed T-value of 3.788 with a probability value equal to 0.000. Hence a conclusion was made that measuring results statistically influenced the organizational performance. The rewarding of performance produced a computed T-value of 5.140 with a probability value of 0.000. The probability value was less than the set alpha level implying that the nullifying hypothesis, stating that rewarding of performance never influenced performance, was rejected. Hence a conclusion was made that rewarding performance statistically affected the organizational performance.
4.5 The consumers’ perception of the most important element among seven “S”s in the model of real estate organizations
The study found out that the consumers felt that the elements in the hard category were more important than those in the soft category. However, shared values, an element in the soft category received the highest frequency of 22 (27.5%). The hard elements had frequencies equal to 18 (22.5%), 14 (17.5%) and 10 (12.5%) for the strategy, structure and systems respectively. Conversely, other soft elements in the model produced frequencies equal to 9 (11.3%), 2 (2.5%) and 5 (6.3%) for the style, staff and skills respectively.
| Table 4.5.1: In your opinion, which is the most important element among the seven “S”s in the McKinsey model? | |||||
| Frequencies | Percentages | Valid Percentages | Cumulative Percentages | ||
| Strategy | 18 | 22.5 | 22.5 | 22.5 | |
| Structure | 14 | 17.5 | 17.5 | 40.0 | |
| Systems | 10 | 12.5 | 12.5 | 52.5 | |
| Shared values | 22 | 27.5 | 27.5 | 80.0 | |
| Style | 9 | 11.3 | 11.3 | 91.3 | |
| Staff | 2 | 2.5 | 2.5 | 93.8 | |
| Skills | 5 | 6.3 | 6.3 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
The mean comparison for the 7S’s in the model produced a computed F-statistic equal to F(6, 73)=3.344 with a probability value equal to p=0.006. Clearly, the nul hypothesis was rejected and conclusion made that the consumers’ perception of the most important element among seven “S”s in the model of real estate organizations was different.
| Table 4.5.2: ANOVA results | |||||
| Organizational performance | |||||
| SS | D f | MS | F-value | Significance. | |
| Between Groups | 8559.362 | 6 | 1426.560 | 3.344 | .006 |
| Within Groups | 31137.626 | 73 | 426.543 | ||
| Total | 39696.987 | 79 | |||
The study revealed that the model could be applied to many situations. Additionally, the study showed that the model was a valuable tool for organizational design. According to the analysis, the most common use of the framework included facilitating the organizational change with a frequency of 29 (36.3%) followed by helping in the implementation of new strategies and facilitating the merger of organizations with equal frequencies of 18 (22.5%). Further, the study revealed that the model was useful in identifying how each area could change in future.
| Table 4.5.3: The most common uses of the model | |||||
| Frequencies | Percentages | Valid Percentages | Cumulative Percentages | ||
| To facilitate organizational change | 29 | 36.3 | 36.3 | 36.3 | |
| To help in the implementation of new strategy | 18 | 22.5 | 22.5 | 58.8 | |
| To identify how each area may change in future | 15 | 18.8 | 18.8 | 77.5 | |
| To facilitate the merger of organizations | 18 | 22.5 | 22.5 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
Chapter 5: Conclusions and Study Recommendations
5.1 Introduction
The fifth chapter in the report helped in describing the conclusions reached by the study and comparing the findings with those from the previous research. The chapter highlighted the levels of agreement and disagreement between the current study and the previous studies. Further, the study used the conclusions to set the most appropriate recommendations for the various stakeholders and future scientists.
5.2 Conclusions
The current study concluded that management activities in the real estate companies contributed to the organizational performance positively. The results were in full agreement with those by Johnson Brown (2015). In his report, Johnson Brown revealed that there is a positive relationship between levels of management and performance particular in the real estate business. He further suggested that management allows for full and proper screening or testing of an individual’s credit, rental history, criminal history and ability to pay. Another research by Wright, Mukherji, and Kroll (2011) pointed out that management activities allow for the lease contracting or acceptance of rent using legal documents approved for the area I which the property is located.
The study revealed that there were considerable variations in demographic characteristics of the workers in the real estate industry. The study revealed that the age data was normally distributed with a mean of 42.03 and a standard deviation of 7.642 ranging from a minimum value of 25 to a maximum value of 54 years. The study also concluded that individuals in the real estate industry who worked in the management or other decision-making positions with interests in management research were females. This was because more females were captured in the survey than males and the participation in the study was free from coercion. Also, a majority of the respondents were in the management and other job positions. The results implied that managers were more interested in understanding the impacts of real estate management activities on the organization performance and, hence, their desire and willingness to participate in the study was higher that workers in the head of departments and customer service agent. Further, A majority of the participants were from the America, Asia, Western Europe and Central and Eastern Europe. Only small proportions were from Africa and Mediterranean and the Middle East regions.
The analysis of the independent variables showed that the three factors averaged at moderate values of 5.1125, 5.1500 and 5.2500 for the targets setting, results measuring and rewarding of performance respectively. The descriptive statistics for the models independent variable showed that on average, the organizations in the real estate industry showed a performance level of 42.38%. The organizational performance data was normally distributed with a mean of 42.39 and a standard deviation equal to 22.416.
According to the results of the pairwise correlation, there was a strong, positive relationship between performance and the three independent factors. Also, the study concluded that a positive relationship existed between the independent variables. What this meant is that the organizations which set high levels of targets were also having elevated levels of results measuring and further provided better rewards for performance.
The study, through the regression analysis technique, suggested that setting targets, measuring results and rewarding performance influenced 90.3% of the variations in the organizational performance. The study revealed that the performance was expected to increase by 2.542 levels for a one level change in the target level holding the measuring of results and rewarding of performance factors constant. Also, the study revealed that the performance was expected to increase by 2.399 levels for a one level change in the measurement of results holding target level rewarding of performance factors constant. Further, the study revealed that the performance was expected to increase by 3.385 levels for a one level change in the reward for performance holding the level of target setting and measuring of results constant.
The study concluded that the consumers felt that the elements in the hard category were more important than those in the soft category. However, ‘shared values’ was found to be the most important element of the McKinsey’s 7S model, despite it being among the soft elements. The study revealed that the model could be applied to many situations. Additionally, the study showed that the model was a valuable tool for organizational design. The most common use of the framework included facilitating the organizational change. Other important uses of the model included helping in the implementation of new strategies, facilitating the merger of organizations and identifying how each area could change in future.
Table 5.2.1: Hypothesis summary Chart
| Hypothesis | Null statement | Statistic | P-value | Decision |
| 1 | The impact of setting goals on organizational performance was not significant | T=3.863 | 0.000 | Rejected |
| 2 | Measuring of results in a company dos not impact on the organizational performance | T=3.788 | 0.000 | Rejected |
| 3 | Rewarding of the employees does not impact on the organizational performance | T=5.140 | 0.000 | Rejected |
| 4 | The consumers’ perception of the most important element among seven “S”s in the model of real estate organizations was the same | F(6,73)=3.344 | P=0.06 | Rejected |
5.3 Study Recommendations
A recommendation was made to the stakeholders in the real estate industry to implement all the necessary management activities to improve performance. The managers and workers at decision making positions within the organizations should set targets, measure results and reward performance. Also, managers should try innovations which ensure that the management activities are maintained at high levels always.
The study recommended that governments should set rules and regulations which allow for the implementation of high levels of management activities such as setting targets, measuring results and rewarding performance. The government should strengthen the workers’ unions to allow the easy call for rewards whenever an employee performed extemporarily. Also, the governments, through the ministry of education, should ensure that pupils and students are shown the importance of management activities, especially regarding the organizational performance. This will help in developing better entrepreneurs in future.
The future scientists should conduct a broader research which shows other important gains of management activities to the organizations apart from improved performance. Also, the future research should consider increasing the number of independent variables in the study to cater for more management activities.
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Appendices
Appendix 1
Questionnaire
- What is your age?
…………………………………………………………………………………….
- What is your gender?
| Gender | |
| Female | |
| Male |
- What is your job position?
| Job Position | |
| Manager | |
| Head of department | |
| Customer service agent | |
| Others |
- What is your region?
| Regions | |
| Western Europe | |
| Central and Eastern Europe | |
| Europe | |
| Asia | |
| Africa | |
| Mediterranean and the middle East | |
| Americans |
- Does your organization set targets?
| Answer | |
| Yes | |
| No |
- If your answer in question 5 above is ‘yes’, in your opinion, at what level does your organization set targets?
| Level | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
- Does your organization measure results?
| Answer | |
| Yes | |
| No |
- If your answer in question 7 above is ‘yes’, in your opinion, at what level does your organization measure results?
| Level | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
- Does your organization reward performance?
| Answer | |
| Yes | |
| No |
- If your answer in question 9 above is ‘yes’, in your opinion, at what level does your organization reward performance?
| Level | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 |
- What is the performance of your organization expressed as a percentage profit?
………………………………………………………………………………………………
- In your opinion, which is the most important element among the seven “S”s in the McKinsey model?
| Strategy | |
| Structure | |
| Systems | |
| Shared values | |
| Style | |
| Staff | |
| Skills |
- Which is the most common uses of the McKinsey model?
| To facilitate organizational change | |
| To help in the implementation of new strategy | |
| To identify how each area may change in future | |
| To facilitate the merger of organizations |
Appendix 2
Results of the Questionnaire
FREQUENCIES VARIABLES=VAR00001
/HISTOGRAM NORMAL
/ORDER=ANALYSIS.
Frequencies
| Notes | ||
| Output Created | 24-APR-2017 16:08:02 | |
| Comments | ||
| Input | Active Dataset | DataSet0 |
| Filter | <none> | |
| Weight | <none> | |
| Split File | <none> | |
| N of Rows in Working Data File | 80 | |
| Missing Value Handling | Definition of Missing | User-defined missing values are treated as missing. |
| Cases Used | Statistics are based on all cases with valid data. | |
| Syntax | FREQUENCIES VARIABLES=VAR00001
/HISTOGRAM NORMAL /ORDER=ANALYSIS. |
|
| Resources | Processor Time | 00:00:00.33 |
| Elapsed Time | 00:00:00.43 | |
[DataSet0]
| Statistics | ||
| Age | ||
| N | Valid | 80 |
| Missing | 0 | |
| Age | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | 25.00 | 1 | 1.3 | 1.3 | 1.3 |
| 26.00 | 2 | 2.5 | 2.5 | 3.8 | |
| 29.00 | 1 | 1.3 | 1.3 | 5.0 | |
| 30.00 | 1 | 1.3 | 1.3 | 6.3 | |
| 31.00 | 5 | 6.3 | 6.3 | 12.5 | |
| 32.00 | 3 | 3.8 | 3.8 | 16.3 | |
| 33.00 | 1 | 1.3 | 1.3 | 17.5 | |
| 34.00 | 2 | 2.5 | 2.5 | 20.0 | |
| 35.00 | 5 | 6.3 | 6.3 | 26.3 | |
| 36.00 | 2 | 2.5 | 2.5 | 28.8 | |
| 37.00 | 1 | 1.3 | 1.3 | 30.0 | |
| 38.00 | 4 | 5.0 | 5.0 | 35.0 | |
| 42.00 | 8 | 10.0 | 10.0 | 45.0 | |
| 43.00 | 3 | 3.8 | 3.8 | 48.8 | |
| 44.00 | 7 | 8.8 | 8.8 | 57.5 | |
| 45.00 | 6 | 7.5 | 7.5 | 65.0 | |
| 46.00 | 6 | 7.5 | 7.5 | 72.5 | |
| 47.00 | 1 | 1.3 | 1.3 | 73.8 | |
| 48.00 | 1 | 1.3 | 1.3 | 75.0 | |
| 49.00 | 4 | 5.0 | 5.0 | 80.0 | |
| 50.00 | 3 | 3.8 | 3.8 | 83.8 | |
| 51.00 | 3 | 3.8 | 3.8 | 87.5 | |
| 52.00 | 6 | 7.5 | 7.5 | 95.0 | |
| 53.00 | 3 | 3.8 | 3.8 | 98.8 | |
| 54.00 | 1 | 1.3 | 1.3 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
FREQUENCIES VARIABLES=VAR00002 VAR00003 VAR00004
/PIECHART FREQ
/ORDER=ANALYSIS.
Frequencies
| Notes | ||
| Output Created | 24-APR-2017 16:09:36 | |
| Comments | ||
| Input | Active Dataset | DataSet0 |
| Filter | <none> | |
| Weight | <none> | |
| Split File | <none> | |
| N of Rows in Working Data File | 80 | |
| Missing Value Handling | Definition of Missing | User-defined missing values are treated as missing. |
| Cases Used | Statistics are based on all cases with valid data. | |
| Syntax | FREQUENCIES VARIABLES=VAR00002 VAR00003 VAR00004
/PIECHART FREQ /ORDER=ANALYSIS. |
|
| Resources | Processor Time | 00:00:00.77 |
| Elapsed Time | 00:00:00.77 | |
[DataSet0]
| Statistics | ||||
| Gender | Job Position | Region | ||
| N | Valid | 80 | 80 | 80 |
| Missing | 0 | 0 | 0 | |
Frequency Table
| Gender | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Males | 36 | 45.0 | 45.0 | 45.0 |
| Females | 44 | 55.0 | 55.0 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
| Job Position | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Manager | 24 | 30.0 | 30.0 | 30.0 |
| Head of department | 12 | 15.0 | 15.0 | 45.0 | |
| Customer service agent | 19 | 23.8 | 23.8 | 68.8 | |
| Others | 25 | 31.3 | 31.3 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
| Region | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | Western Europe | 14 | 17.5 | 17.5 | 17.5 |
| Central and Eastern Europe | 13 | 16.3 | 16.3 | 33.8 | |
| Asia | 16 | 20.0 | 20.0 | 53.8 | |
| Africa | 11 | 13.8 | 13.8 | 67.5 | |
| Mediterranean and the Middle East | 8 | 10.0 | 10.0 | 77.5 | |
| Americas | 18 | 22.5 | 22.5 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
Pie Chart
DESCRIPTIVES VARIABLES=VAR00005 VAR00006 VAR00007
/STATISTICS=MEAN STDDEV MIN MAX KURTOSIS SKEWNESS.
Descriptives
| Notes | ||
| Output Created | 24-APR-2017 16:10:59 | |
| Comments | ||
| Input | Active Dataset | DataSet0 |
| Filter | <none> | |
| Weight | <none> | |
| Split File | <none> | |
| N of Rows in Working Data File | 80 | |
| Missing Value Handling | Definition of Missing | User defined missing values are treated as missing. |
| Cases Used | All non-missing data are used. | |
| Syntax | DESCRIPTIVES VARIABLES=VAR00005 VAR00006 VAR00007
/STATISTICS=MEAN STDDEV MIN MAX KURTOSIS SKEWNESS. |
|
| Resources | Processor Time | 00:00:00.02 |
| Elapsed Time | 00:00:00.01 | |
[DataSet0]
| Descriptive Statistics | |||||||||
| N | Minimum | Maximum | Mean | Std. Deviation | Skewness | Kurtosis | |||
| Statistic | Statistic | Statistic | Statistic | Statistic | Statistic | Std. Error | Statistic | Std. Error | |
| Setting targets | 80 | 1.00 | 10.00 | 5.1125 | 2.78329 | .282 | .269 | -.975 | .532 |
| Measuring results | 80 | 1.00 | 10.00 | 5.1500 | 2.74254 | .035 | .269 | -1.066 | .532 |
| Rewarding performance | 80 | 1.00 | 10.00 | 5.2500 | 2.58281 | .128 | .269 | -.912 | .532 |
| Valid N (listwise) | 80 | ||||||||
DESCRIPTIVES VARIABLES=VAR00008
/STATISTICS=MEAN STDDEV MIN MAX KURTOSIS SKEWNESS.
Descriptives
| Notes | ||
| Output Created | 24-APR-2017 16:13:15 | |
| Comments | ||
| Input | Active Dataset | DataSet0 |
| Filter | <none> | |
| Weight | <none> | |
| Split File | <none> | |
| N of Rows in Working Data File | 80 | |
| Missing Value Handling | Definition of Missing | User defined missing values are treated as missing. |
| Cases Used | All non-missing data are used. | |
| Syntax | DESCRIPTIVES VARIABLES=VAR00008
/STATISTICS=MEAN STDDEV MIN MAX KURTOSIS SKEWNESS. |
|
| Resources | Processor Time | 00:00:00.00 |
| Elapsed Time | 00:00:00.01 | |
[DataSet0]
| Descriptive Statistics | |||||||||
| N | Minimum | Maximum | Mean | Std. Deviation | Skewness | Kurtosis | |||
| Statistic | Statistic | Statistic | Statistic | Statistic | Statistic | Std. Error | Statistic | Std. Error | |
| Organizational performance | 80 | 6.00 | 85.00 | 42.3875 | 22.41637 | .138 | .269 | -1.104 | .532 |
| Valid N (listwise) | 80 | ||||||||
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/STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIAN MODE SKEWNESS SESKEW KURTOSIS SEKURT
/PIECHART FREQ
/ORDER=ANALYSIS
Frequencies
| Notes | ||
| Output Created | 24-APR-2017 16:14:29 | |
| Comments | ||
| Input | Active Dataset | DataSet0 |
| Filter | <none> | |
| Weight | <none> | |
| Split File | <none> | |
| N of Rows in Working Data File | 80 | |
| Missing Value Handling | Definition of Missing | User-defined missing values are treated as missing. |
| Cases Used | Statistics are based on all cases with valid data. | |
| Syntax | FREQUENCIES VARIABLES=VAR00008
/STATISTICS=STDDEV MINIMUM MAXIMUM MEAN MEDIAN MODE SKEWNESS SESKEW KURTOSIS SEKURT /HISTOGRAM NORMAL /ORDER=ANALYSIS. |
|
| Resources | Processor Time | 00:00:00.27 |
| Elapsed Time | 00:00:00.27 | |
[DataSet0]
| Statistics | ||
| Organizational performance | ||
| N | Valid | 80 |
| Missing | 0 | |
| Mean | 42.3875 | |
| Median | 42.5000 | |
| Mode | 35.00 | |
| Std. Deviation | 22.41637 | |
| Skewness | .138 | |
| Std. Error of Skewness | .269 | |
| Kurtosis | -1.104 | |
| Std. Error of Kurtosis | .532 | |
| Minimum | 6.00 | |
| Maximum | 85.00 | |
| Organizational performance | |||||
| Frequency | Percent | Valid Percent | Cumulative Percent | ||
| Valid | 6.00 | 2 | 2.5 | 2.5 | 2.5 |
| 7.00 | 1 | 1.3 | 1.3 | 3.8 | |
| 8.00 | 2 | 2.5 | 2.5 | 6.3 | |
| 9.00 | 2 | 2.5 | 2.5 | 8.8 | |
| 13.00 | 1 | 1.3 | 1.3 | 10.0 | |
| 14.00 | 2 | 2.5 | 2.5 | 12.5 | |
| 17.00 | 2 | 2.5 | 2.5 | 15.0 | |
| 18.00 | 1 | 1.3 | 1.3 | 16.3 | |
| 19.00 | 2 | 2.5 | 2.5 | 18.8 | |
| 21.00 | 3 | 3.8 | 3.8 | 22.5 | |
| 23.00 | 3 | 3.8 | 3.8 | 26.3 | |
| 24.00 | 1 | 1.3 | 1.3 | 27.5 | |
| 25.00 | 3 | 3.8 | 3.8 | 31.3 | |
| 29.00 | 2 | 2.5 | 2.5 | 33.8 | |
| 30.00 | 3 | 3.8 | 3.8 | 37.5 | |
| 33.00 | 1 | 1.3 | 1.3 | 38.8 | |
| 35.00 | 4 | 5.0 | 5.0 | 43.8 | |
| 36.00 | 1 | 1.3 | 1.3 | 45.0 | |
| 37.00 | 1 | 1.3 | 1.3 | 46.3 | |
| 41.00 | 1 | 1.3 | 1.3 | 47.5 | |
| 42.00 | 2 | 2.5 | 2.5 | 50.0 | |
| 43.00 | 2 | 2.5 | 2.5 | 52.5 | |
| 44.00 | 1 | 1.3 | 1.3 | 53.8 | |
| 45.00 | 2 | 2.5 | 2.5 | 56.3 | |
| 46.00 | 1 | 1.3 | 1.3 | 57.5 | |
| 48.00 | 2 | 2.5 | 2.5 | 60.0 | |
| 49.00 | 1 | 1.3 | 1.3 | 61.3 | |
| 50.00 | 1 | 1.3 | 1.3 | 62.5 | |
| 51.00 | 2 | 2.5 | 2.5 | 65.0 | |
| 52.00 | 3 | 3.8 | 3.8 | 68.8 | |
| 54.00 | 2 | 2.5 | 2.5 | 71.3 | |
| 57.00 | 1 | 1.3 | 1.3 | 72.5 | |
| 59.00 | 1 | 1.3 | 1.3 | 73.8 | |
| 60.00 | 1 | 1.3 | 1.3 | 75.0 | |
| 61.00 | 1 | 1.3 | 1.3 | 76.3 | |
| 64.00 | 1 | 1.3 | 1.3 | 77.5 | |
| 67.00 | 2 | 2.5 | 2.5 | 80.0 | |
| 69.00 | 3 | 3.8 | 3.8 | 83.8 | |
| 70.00 | 1 | 1.3 | 1.3 | 85.0 | |
| 71.00 | 2 | 2.5 | 2.5 | 87.5 | |
| 72.00 | 2 | 2.5 | 2.5 | 90.0 | |
| 74.00 | 1 | 1.3 | 1.3 | 91.3 | |
| 75.00 | 1 | 1.3 | 1.3 | 92.5 | |
| 78.00 | 2 | 2.5 | 2.5 | 95.0 | |
| 80.00 | 2 | 2.5 | 2.5 | 97.5 | |
| 82.00 | 1 | 1.3 | 1.3 | 98.8 | |
| 85.00 | 1 | 1.3 | 1.3 | 100.0 | |
| Total | 80 | 100.0 | 100.0 | ||
REGRESSION
/MISSING LISTWISE
/STATISTICS COEFF OUTS R ANOVA
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT VAR00008
/METHOD=ENTER VAR00005 VAR00006 VAR00007.
Regression
| Notes | ||
| Output Created | 24-APR-2017 16:15:31 | |
| Comments | ||
| Input | Active Dataset | DataSet0 |
| Filter | <none> | |
| Weight | <none> | |
| Split File | <none> | |
| N of Rows in Working Data File | 80 | |
| Missing Value Handling | Definition of Missing | User-defined missing values are treated as missing. |
| Cases Used | Statistics are based on cases with no missing values for any variable used. | |
| Syntax | REGRESSION
/MISSING LISTWISE /STATISTICS COEFF OUTS R ANOVA /CRITERIA=PIN(.05) POUT(.10) /NOORIGIN /DEPENDENT VAR00008 /METHOD=ENTER VAR00005 VAR00006 VAR00007. |
|
| Resources | Processor Time | 00:00:00.00 |
| Elapsed Time | 00:00:00.08 | |
| Memory Required | 2028 bytes | |
| Additional Memory Required for Residual Plots | 0 bytes | |
[DataSet0]
| Variables Entered/Removeda | |||
| Model | Variables Entered | Variables Removed | Method |
| 1 | Rewarding performance, Measuring results, Setting targetsb | . | Enter |
| a. Dependent Variable: Organizational performance | |||
| b. All requested variables entered. | |||
| Model Summary | ||||
| Model | R | R Square | Adjusted R Square | Std. Error of the Estimate |
| 1 | .950a | .903 | .899 | 7.10776 |
| a. Predictors: (Constant), Rewarding performance, Measuring results, Setting targets | ||||
| ANOVAa | ||||||
| Model | Sum of Squares | df | Mean Square | F | Sig. | |
| 1 | Regression | 35857.449 | 3 | 11952.483 | 236.588 | .000b |
| Residual | 3839.538 | 76 | 50.520 | |||
| Total | 39696.988 | 79 | ||||
| a. Dependent Variable: Organizational performance | ||||||
| b. Predictors: (Constant), Rewarding performance, Measuring results, Setting targets | ||||||
| Coefficientsa | ||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | ||
| B | Std. Error | Beta | ||||
| 1 | (Constant) | -.731 | 1.826 | -.400 | .690 | |
| Setting targets | 2.542 | .658 | .316 | 3.863 | .000 | |
| Measuring results | 2.399 | .633 | .293 | 3.788 | .000 | |
| Rewarding performance | 3.385 | .658 | .390 | 5.140 | .000 | |
| a. Dependent Variable: Organizational performance | ||||||
CORRELATIONS
/VARIABLES=VAR00008 VAR00005 VAR00006 VAR00007
/PRINT=TWOTAIL NOSIG
/MISSING=PAIRWISE.
Correlations
| Notes | ||
| Output Created | 24-APR-2017 16:16:13 | |
| Comments | ||
| Input | Active Dataset | DataSet0 |
| Filter | <none> | |
| Weight | <none> | |
| Split File | <none> | |
| N of Rows in Working Data File | 80 | |
| Missing Value Handling | Definition of Missing | User-defined missing values are treated as missing. |
| Cases Used | Statistics for each pair of variables are based on all the cases with valid data for that pair. | |
| Syntax | CORRELATIONS
/VARIABLES=VAR00008 VAR00005 VAR00006 VAR00007 /PRINT=TWOTAIL NOSIG /MISSING=PAIRWISE. |
|
| Resources | Processor Time | 00:00:00.00 |
| Elapsed Time | 00:00:00.01 | |
[DataSet0]
| Correlations | |||||
| Organizational performance | Setting targets | Measuring results | Rewarding performance | ||
| Organizational performance | Pearson Correlation | 1 | .906** | .896** | .909** |
| Sig. (2-tailed) | .000 | .000 | .000 | ||
| N | 80 | 80 | 80 | 80 | |
| Setting targets | Pearson Correlation | .906** | 1 | .867** | .861** |
| Sig. (2-tailed) | .000 | .000 | .000 | ||
| N | 80 | 80 | 80 | 80 | |
| Measuring results | Pearson Correlation | .896** | .867** | 1 | .843** |
| Sig. (2-tailed) | .000 | .000 | .000 | ||
| N | 80 | 80 | 80 | 80 | |
| Rewarding performance | Pearson Correlation | .909** | .861** | .843** | 1 |
| Sig. (2-tailed) | .000 | .000 | .000 | ||
| N | 80 | 80 | 80 | 80 | |
| **. Correlation is significant at the 0.01 level (2-tailed). | |||||
DATASET ACTIVATE DataSet0.
DATASET ACTIVATE DataSet0.
SAVE OUTFILE=’C:\Users\James\Documents\Real estate data.sav’
/COMPRESSED.
