Table of Contents 

Table of Contents

Chapter one – Introduction. 8

1.1 Introduction. 9

1.2 Background of the study….. 10

1.3 Rationale of the research study. 11

1.4 Development of research idea, question, objectives and hypothesis. 11

1.5 Research Access, Limitations & Resources. 13

1.6 Outline of the research. 13

Chapter two – Literature Review.. 15

2.1 Introduction. 15

2.2 Review on customer relationship management 16

2.3 Defining customer relationship management (CRM) 16

2.4 Goals of customer relationship management 18

2.5 Types of customer relationship management 19

2.5.1. Proactive and reactive customer relationship management 19

2.5.2 Operational CRM… 20

2.5.3 Collaborative CRM… 20

2.5.4 Analytical CRM… 20

2.6 Definition of productivity. 21

2.7 Significance of productivity. 21

2.8 Single productivity concepts. 22

2.9 Typical Calculations of Productivity. 22

2.9.1 Physical Productivity. 22

2.9.2 Functional Productivity. 22

2.9.3 Economic Productivity. 23

2.10 Business value impact of customer relationship management on productivity. 23

2.11 Summary. 25

Chapter three – Research Methodology. 26

3.1. Introduction. 27

3.2 Defining research philosophy and the selection of research philosophy. 29

3.3 Defining research approach and the selection of research approach. 29

3.4 Defining research design and the selection of research design. 29

3.5 Preferred research Strategies. 30

3.6 Time Horizon. 30

3.7 Research Instruments. 31

3.7.1. Sampling framework. 31

3.7.2. Data Collection mechanism.. 31

3.7.3. Data analysis tools. 32

3.8 Applicability of research validity and reliability. 33

3.9 Ethical considerations. 33

3.10 Summary. 33

Chapter 4 – Findings and Analysis. 34

4.1 Introduction. 35

4.2 Findings from the descriptive study. 37

4.3 Hypothesis testing. 45

4.4 Finding from the regression study. 46

4.5 Conclusion. 48

Chapter 5 – Discussion. 49

5.1. Introduction. 50

5.2. Comparing the first finding with literature. 50

5.3. Comparing the second finding with literature. 51

5.4. Rationale for research gaps. 51

5.5. Chapter Summary. 52

Chapter Six – Conclusions and Recommendations. 53

6.1 Introduction. 54

6.2 Summary of the major findings. 54

6.3 Covering of the aims and objectives. 54

6.4 Recommendations for improvement 55

6.5 Recommendations for further research. 55

6.6. Chapter Summary. 56

Appendix. 57

Reference. 61

List of figures

Figure 1 Types of CRM mapped against degree of personalization. 19

Figure 2 Research onion model 28

List of tables

Table 1: Concurrent corporate social responsibility dynamics…………………………………………….. 36

Table 2: Demography of respondents………………………………………………………………………………. 38

Table 3 Process of data coding………………………………………………………………………………………… 42

Table 4: Descriptive statistics results……………………………………………………………………………….. 44

Table 5: Hypothesis testing results………………………………………………………………………………….. 46

Table 6 unit root test……………………………………………………………………………………………………… 47

Table 7: Autocorrelation test…………………………………………………………………………………………… 47

 Chapter 1 – Introduction

1. Introduction

The high rate of growth in the business sector over the past few decades has increased the level of competition between the players. One aspect of this increased competition that has become significant and remained so in a sustained manner is the customer. Bose (2002) reiterates the concept of a good understanding of the importance of the customer in all business growth and productivity endeavors as key. Coupled with economic uncertainty, tough competition has continued to drive the strategy of many business organizations as they seek not only to remain afloat in these tough economic times, but also to grow in a sustainable manner. 

All successful business enterprises have come to acknowledge the importance of a satisfied customer as one of the prime ingredients of growth and productivity. On the other hand, dissatisfied customers are sure to affect the sales performance due to a spread in the bad buying and business experience (Chou et al, 2002). Consequently, these two factors, business growth and reputational factors have both come to rely on a relatively new aspect of the business’s promotional and marketing practice – customer relations management.

The need and importance of the customers’ feedback cannot be ignored in any discussion or even mention of marketing and promotional activity as they relate to the business organization. Chen and Popvich, 2003) state the importance of this crucial aspect of the business’s endeavor to improve its customer experience. As part of the interdepartmental approach to the business organization’s customer relations management, customer feedback and related aspects contribute a great deal to the organization’s awareness of the performance of its services and goods with regards to the customer’s satisfaction. Therefore, customer relations management is a combination of customer relations management tools and information management instruments, all combined to create an increased organizational productivity through customer satisfaction (Chou et al, 2002). Peelan (2003) also reiterates the same point by stating how customer relations management is a specialized information technology that fosters customer segments, organizes customer satisfaction variables, and enables processes, which cater to customer satisfaction all in a bid to optimize revenue growth within the organization.

Chou et al (2002) categorize Syngenta AG as a leading specialized chemicals firm that originated from Switzerland and majors in agricultural seeds and pesticides. In addition, the company also deals with biotechnology and genomic research in many European countries such as the UK, all centered around improving on the seeds and their disease-resistance, or productivity properties. From a commercial perspective, Syngenta AG takes the third place globally in terms of total volumes of seeds sold and marketed (Chen and Popvich, 2003). Bose (2002) states that Syngenta AG employs more than 3000 workers globally who assist the company’s operations in more than 90 countries rake in gross annual revenues in excess of 12 Billion US Dollars. Therefore, these facts place Syngenta AG in the top tier globally in terms of performance among its industry competitors.

Recently, Chen and Popvich (2003) reported how top management at Syngenta AG noticed the need to optimize their customer relations management practice by improving its information technology aspects. Subsequently, this research will try to establish if there exists any relationship between the performance attributes of Syngenta AG and its customer relations management practices.

1. Background to the Study

All business firms that understand the importance of productivity optimization rely on a wide variety of tools and techniques to improve it. Chou et al. (2003), attaches Syngenta AG to this fact by recognizing its modernized approach to customer relations management as part of the wider endeavor to optimize revenues through customer satisfaction. However, the firm’s management has noticed some slight deficiencies in the CRM aspects of the company in the currently dynamic competitive business environment. According to Chen and Popvich (2003), these deficiencies affected the company’s utilization of resources thus affecting work flow by incurring more-than-optimal resources such as time and funds. Ideas were suggested to the effect that information technology was one of the avenues through which the organization would improve its customer relations management practice. However, these suggestions faced the immensely crucial problem of probability of success. Thus, Syngenta AG’s management faced a huge dilemma concerning the existence of the relationship between improved performance and customer relations management. The company needed to ascertain the extent of the relationship between productivity and customer relations management and identify the resultant collaborative and operational customer relations management strategies would assist the organization boost its performance in terms of corporate productivity (Bose, 2002).

1. Rationale of the Study

As the global business and corporate scene faces a recessionary wave, many business organizations face stiff business conditions that continue to affect their sales revenue and profit margins. Syngenta AG is no exception. As Chen and Popvich (2003) point out, the global agricultural inputs magnate also faces periods of hardship that the management thinks can be reversed through an age-old, proven, productivity-based strategy. According to the strategists, the currently unfavorable business indicators can be driven back to favorable levels through the productivity-based strategies redeeming performance and reputational losses the company has been incurring alongside other international companies in the current economic downshift. 

Scholars and industry heavy weights have identified the effects blends of customer relations management and customer feedback through optimized information technology has on the firm’s performance. Therefore, customer feedback could be essential as part of Syngenta AG’s endeavor to return profitability levels back to the desired levels through satisfying customers in a more pronounced manner (Chou et al, 2002). 

A major determinant of productivity is customer relationship management whose efficient process will increase the overall organization’s productivity in multiple views (Bose, 2002). In academic perspectives, this study will add huge valued towards Syngenta AG’s concerns and towards aspects of customer relationship management by figuring out the level of association between corporate productivity terms and customer relationship management in a material business sense.

1. Development of the research idea, question, objectives, and hypothesis

Research aim: The concerned research endeavor aims at identifying the extent to which customer relations management is related to corporate productivity as a means to optimizing sales revenues.

Research objectives:

• Obtain a relevant definition of the term and concept of productivity through Syngenta AG’s perspective.
• Identify the extent of the relationship between organizational productivity and customer relations management.
• Establish the extent of the present rate of success in Syngenta AG’s customer relations management.
• Identify the presence of deficiencies in Syngenta AG’s customer relations management.

       Research questions:

• How is the term and concept of productivity defined from Syngenta AG’s perspective?
• How are concepts of customer relations management and organizational productivity related?
• Identify the present status of Syngenta AG’s customer relations management.
• What deficiencies exist in Syngnenta AG’s customer relations management?

      Hypothesis:

Null hypothesis 1: There is no relationship between customer relationship management and organizational productivity.

Alternative hypothesis 1: There is relationship between customer relationship management and organizational productivity. 

Null hypothesis 2: There is no relationship between operational customer relationship management program and organizational productivity.

Alternative hypothesis 2: There is relationship between operational customer relationship management program and organizational productivity.

Null hypothesis 3: There is no relationship between collaborative customer relationship management program and organizational productivity.

Alternative hypothesis 3: There is relationship between collaborative customer relationship management program and organizational productivity.

Null hypothesis 4: There is no relationship between analytical customer relationship management program and organizational productivity.

Alternative hypothesis 4: There is relationship between analytical customer relationship management program and organizational productivity.

1. Research Access, Limitations, and Resources

Due to the status of authorization attached to this research endeavor, based solely on the university’s permission to proceed, the opportunities to collect relevant information from various sources among other data collection efforts presented no problems. In addition, due to the applicability of the research endeavor and any accurate findings on an international agricultural company, the issues of research material applicability would be met. So much, the researcher anticipated her research findings to find use in other similar industrial and corporate scenarios.

The fundamental limitations of this research endeavor would revolve around the limited sample size and resource pool. Additionally, some degree of bias was expected from the respondent resulting in both systematic and non-systematic disorders in the research findings.

Finally, the researcher should be noted to be fully competent and a holder of all pertinent skills, conceptual and analytical, required in executing such business-oriented research.

1. Research outline

In the dissertation, the researcher is going to discuss about the definition of customer relationship management, the definition of productivity, the ways productivity can be measured using tools and techniques for efficient customer relationship management using tools and techniques. 

Furthermore, in the research methodology part of the study, the research philosophy, research designs, research approaches, data collection techniques, sampling framework and the ways to cover ethical aspects of this business research are explained. 

Within the discussion and analysis portion of the business research, the researcher has delineated the statistical tools and techniques, which had been used to depict the different layers of relationship that exist between customer relationship management and productivity. The researcher compared research outcomes with the academic findings and tried to explain the gaps among the literatures. Finally, the conclusion portion of the study depicted with a set of actionable recommendations to improve the present condition of the organizational productivity. 

                                                Chapter 2 – Literature Review

2.1 Introduction

This part of the research is primarily concerned with identifying the series if academic evidence relating to the researcher’s area of research. As such, the section will present a discussion that forwards the pertinent issues, supporting views, as well as any conflicting perspectives the academic community related to this research area has identified and put on record. Therefore, the various definitions of customer relations management, productivity concepts, and goals as well as objectives of customer relations management will be discussed. In addition, the significance and measurement procedures of the value of customer relations management on the business’s value will be investigated from the literature available.

2.2 Reviews on customer relations management

Both scholars and industry players have identified the importance of investigating the relationship between the customer’s satisfaction and their organization’s productivity as a subject of great interest. According to Baird and Parasnis (2011), the idea of CRM is new and with the concurrent advancement of information and enterprise software, it has adopted a great importance in real life business practices. The idea of customer relationship management has evolved from the relationship marketing techniques with the core objective of CRM being to promote a long-term profitable relationship with customers’ thorough improved productivity and customer service in organizations. CRM practices have been augmented in practical organizations because of the diverse customer base with differentiated preferences and buying behavior (Baran et al, 2008).

The currently competitive nature of business operations, especially in a global perspective, has forced the business community to embrace CRM practices in order to increase their customer’s portfolio value as one of the marketing and promotional methods of increasing profitability through tailored offerings (Buttle, 2008). In addition, Buttle (2012) points out how the customer relationship management efforts encompass a coordinated effort of all the departments in an organization. The application of CRM is a complicated process, which includes mining of all the customers’ data in order to obtain a good overall view of all the customers’ organized information for enabling firms to provide much efficient services (Chaturvedi, 2009). CRM helps a firm to focus effectively on the exact type of customers and market segments for sustainable future profitability and corporate growth (Coltman, 2007).

Consequently, the idea of CRM has been identified as one of the most crucial tactics that business organizations can manipulate as part of the larger marketing and promotional business practice to achieve two core goals – satisfy the customer better, and achieve increased profitability.

2.3 Defining customer relations management (CRM)

Customer relationship management has been defined as the core concept surrounding the business strategy and information technology concepts, integration of which helps an organization improve their efficient service criteria and promote productivity while catering to customers’ demands. Ernst et al (2011) define CRM as a collection of strategies that the organizations use to augment business value and create increased productivity through more customer-focused offerings.

Additionally, Homburg and Seiben (2008) add value to the process of creating an all-inclusive definition of CRM by stating that it is a collection of all business practices surrounding marketing, sales, and customer relations that aim at creating more productive business relationships between the customer and business organization. CRM adds extra advantage to the cost reduction, increase interaction values that ensure high sales revenue with the same resources. The theory of total quality management, backed by technological advances, has a severe impact over the development and shaping up of the modern customer relationship management, at least in recent times (Huang, 2007).

Although there is confusions around different definitions of customer relationship management by different authors in their researches but the core ideas evolve around customer relations and management, customer retention, personalization and marketing strategies (Huang, 2007). Some firms in technology intensive industries consider CRM as the ultimate technological solution to the customer management and tools for sales force automation, which integrates marketing and sales activities too (Iriana and Buttle, 2007). According to Keramati et al (2010), CRM is a function of sales and marketing departments wholly concentrated on individual customer communication management functions. On the other hand, King and Burgess (2008) argued that CRM has its major focus on two-way communication between customers and suppliers to build profitable long run relationship over time with the help of information technology strategies and resources.

From an information technology perspective, CRM entails an organization-wide integration of all the data warehouse, internet, intranet, extranet, phone, production, marketing and sales technologies. As per Knox et al (2012), CRM must use information technology to amass data for developing organized information to build up much personal interaction with customers to ensure a higher lifetime value to the firm. According to Krasnikov et al (2009), customer relationship management, if implemented successfully, enables businesses to maintain a customer driver, cross-functional and technology oriented business process strategies for maximizing relationship benefits. Krasnikov et al (2009) also argued CRM as not a mere technology application but rather a systematic combination of sales, marketing and service activities.

2.4 Objectives of CRM

From an industrial and practical perspective, Kumar (2010) stated that the goals of CRM surround two major issues: developing promotional processes efficiency and augmentation of process organizational efficiency. The ultimate goal of any business-focused firms’ investment in customer relationship management activities is to reduce operational costs and augment profitability (Kumar, 2010). Such objectives can better be achieved thorough activating sales and customer centric CRM activities from all aspects. As per Lin et al (2010), increased customer contentment and building customer loyalty should be the major CRM objectives for a business organization. Any organization can achieve business goals such as efficient sales management, simplified marketing and sales process, gathering new customer and retaining the old ones through improved customer service with an improved focus on customer relationship management (Berry and Linoff, 2011). Such activities will also provide room for more sales revenue and long run profit potentials.

Hence, any CRM practice needs to be at the intersection of customer processes augmentation, and an enhancement of organizational processes aimed at boosting both organizational performance and customer satisfaction.

2.5 The types of CRM

There are five broad categorizations of CRM. The most basic is between reactive and proactive CRM practices. The next include analytical, operational, and collaborative.

2.5.1 Operational CRM

Within the realm of operational CRM, customers can interact with a company through a number of approaches. The organization itself and its employees facilitate the direct connection with customers with several junctions called as touch points (Ngai et al, 2009). Customer relationship management aspects that are enabled with sale transactions, due payments, seeking information, suggestions, queries and complaints through operational touch points are called operational CRM or front office customer relationship management. Such CRM practices affect the promotional and marketing aspects of the organization quite severely if not well addressed.

2.5.2 Collaborative CRM

Osarenkhoe and Bennani (2007), outline the specific functions of a corporation, which facilitate any two-way communication among companies and its customers via number of channels for enabling and improving customer interaction quality, are defined as collaborative CRM. Collaborative CRM concentrates on establishing a cooperative effort with the business partners of a business organization. These partners can be business agents, distribution channels and/or other stakeholders (Raab et al, 2008). Interestingly, collaborative CRM does not encounter direct customers for the purpose of increasing productivity. Rather, such CRM’s idea is to maintain a well performing relationship with partners for better business coordination.

2.5.3. Proactive and reactive customer relationship management

Mendoza et al, (2007) state that proactive CRM comes into being while a company forecasts the market movements and responds to customers’ trending needs by itself with innovative strategies. Conversely, when a company adapts to the suggestions, requests, recommendations and complaints of customers, suppliers and other parties, the activities are defined as reactive customer relationship management (Nambisan and Baron, 2007). Proactive business firms concentrate on analyzing the customers changing demands and market movements to be prepared for future product and service needs and offer superior values through such actions at the evolution of customers’ need. Firms practicing proactive customer relationship management focus more on the personalization needs and individual marketing efforts. 

Figure 1 Types of CRM mapped against degree of personalization

Source: Baird, C. H. and Parasnis, G. (2011) ‘From social media to social customer relationship management’ Strategy & Leadership, Vol. 39, No. 5

2.5.4 Analytical CRM

Analytical customer relationship management, otherwise called strategic CRM, sits at the top tier of CRM types in terms of importance from a business productivity perspective. Business analysts are the key persons with responsibilities such as sort of customer relationship management (Reimann et al, 2010). Such analysts facilitate the major objective of analytical CRM by sorting out various preferences, tastes and activities of customers for offering custom-made solutions of their needs. Such analytical CRM works with capturing data from numerous touch points and subsequently analyzing them to find generalized consumer behavior. In addition, they develop solutions according to the findings of their analysis (Richards and Jones, 2008). Analytical CRM requires widespread use of management information system and information technology.

Seemingly, the principal focus of any organization is naturally remains over the operational items. Nevertheless, being proactive in CRM tactics and attending these policies from the analytical point of view will help to cater a better level of results in business indicators.

2.6 Definition of productivity

Sharma et al, (2008), describe productivity as the relationship between one or more related resources consumed, and the output produced in the process of business-oriented processes of production. The choice of a suitable concept of productivity relies on the objectives of measurement, data availability, and a research preference. A measure of productivity is considered a ratio of outputs produced to that of inputs used. Besides, Sinisalo et al (2007) discuss the need for the observer to contemplate over different choices regarding the nature and scope of both the resources and outputs considered. For instance, outputs may be measured for delivered product while resources may be measured for cost or effort. Numbers of productivity may be used in many various means, e.g., for the estimation of project and the evaluation of process. A measure of productivity assists an organization in making effective decisions about investments in methods, tools, processes, and outsourcing (Tamošiūniene and Jasilioniene, 2007). In addition to the wide area of inputs and outputs to be measured, other factors such as changes in requirements and quality of service delivery may influence the interpretation of the outcome of productivity measure.

2.7 Importance of Productivity

The significance of productivity revolves around what can be measured to determine growth rate or level. A high level of productivity or high growth rates point out a forceful and growing economy or prospective industry. Therefore, to keep alive in the competitive marketplace, a nation or her discrete industry will try to make efforts to develop her growth of productivity (Urbanskienė et al, 2008). 

Commonly, productivity can be used at four levels: project/site, organization/firm, individual industry and entire economy. As measures of productivity, prevail largely to be compared, it is better to use measures of production as performance indices (Venkatesan et al, 2007). By means of empirical production functions, when inputs and outputs have been calculated in constant prices, ratios of real outputs to individual real inputs can be measured to determine single productivity measures; and ratios of real outputs to all related real inputs can be measured to determine a MFP or TFP (Buttle, 2008). Single productivity measures reveal both productive efficiency changes and factor substitutions resulting from relative factor prices changes. Conversely, MFP or TFP has widely been recognized as a better sign of efficiency of productivity than conventional partial productivity for the measurement of effective resources utilization.

2.8 Single productivity concepts

The first measure of productivity, Labor productivity (Q/L), is a ratio measure of outputs produced to labor inputs used (Chaturvedi, 2009). Since labor is the only one of the factor of inputs, changes in productivity of labor are influenced by changes in factor substitution and by changes in factor substitution as calculated by multi-factor or total factor productivity (Coltman, 2007). 

Other concepts of single productivity are intermediate productivity and capital productivity, which measure the relationship between output and intermediate input and the relationship between output and capital input, respectively. The most commonly used measure is labor productivity among the three concepts of single productivity.

2.9 Typical Calculations of Productivity

Interestingly, and from a perspective of unitary productivity measurement, measures of size and resources may be integrated in many various manners. The three common approaches to outlining productivity are referred to as physical, functional, and economic productivity. 

2.9.1 Physical Productivity

Herein, the ratio of the amount of products to the resources used (usually effort) is calculated. Ernst et al, (2011) identify how products may be calculated with respect to screens, classes, code, or any other unit of product. Normally, effort is calculated with respect to staff hours, days, months, or years.

2.9.2 Functional Productivity

Here, the ratio of the amount of the functionality delivered to the resources used (usually effort) is calculated. The functionality may be determined with respect to requirements, use cases, features, or function points as suitable for the type of the software and the method of development. Usually, and as pointed out by Homburg and Sieben, (2008), effort is determined with respect to staff hours, days, months, or years.

2.9.3 Economic Productivity

In this ratio, the amount of product produced to the cost of the resources consumed to produce it is calculated (Homburg and Sieben, 2008) as part of a larger economic productivity identification endevor. Economic productivity assists in assessing the efficiency of an organization’s economy. For the calculation of economic productivity, we have to use the following equation:

ECONOMIC PRODUCTIVITY = VALUE/COST

The cost is easier to determine, whereas, the value is recognized as an integration of functionality and price. More functionality reflects higher prices. The amount, which the customers are willing to pay, denotes its value. Regrettably, the value of revenue may be calculated when the product has completed its worthwhile life (Mendoza et al, 2007). Therefore, the value must be calculated to determine economic productivity, considering all the factors that affect the decision-making of customer to purchase. Accordingly,

VALUE = f (PRICE, TIME, QUALITY, FUNCTIONALITY)

Poor quality may results in liability and guarantee costs that offset revenue, either planned or actual. Likewise, time must be taken into consideration while determining a product’s economic value. Thus, the quantity of revenue paid back by it will be unfavorably affected. As a result, in case of calculating the value for economic productivity, we must take account of quality and price, as well as timeliness and functionality (King and Burgess, 2008).

2.10 The business value impact of CRM on productivity

Compared to old-fashioned network technologies, the latest CRM applications are able to arrange and coordinate customer data with a lot less cost implications (Coltman, 2007). CRM system manages the data accumulation, storing, maintenance and distribution of customer knowledge throughout the organization (Knox et al, 2012). (Ngai et al, 2009) explained that CRM provide added advantages in product and service innovation, tailored product, consolidated customer view and customers’ lifetime value calculation; if effective information management is enabled. Customers’ profitability and loyalty can be evaluated with the assistance of CRM systems as it examines the customers’ repeat purchase history, longevity and amount spent on different items (Sinisalo et al, 2007). Because there has been so many technology solutions prevail in organization, some views consider CRM a part of pure technology misleadingly. 

Recently, as more firms has found the strategic significance of CRM in building better customer relationship and increasing their organizational productivity, CRM should be considered as a business value endeavor instead of just some technology-centric activities related to business intelligence or promotional activity (Coltman, 2007). Accordingly, if CRM strategies can be properly backed by information technology, it could leverage the major customer interaction points to maximize profitability. Keramati et al (2010) explains that the core drivers behind increased importance of CRM in modern businesses are skyrocketing competition, product and service innovations, technological advancements, increased internet accessibility. These factors inspired firms to allocate their resources to CRM activities more in customer access points for high profitability. Customers get the most out of business’s CRM activities in the form of tailored products and services, process simplicity and transaction convenience as the interaction channels are more proactive (Knox et al, 2012).) viewed CRM as enabling firms to get a competitive edge over the rivals with sustainable growth opportunity. Liu (2007) supports the view by acknowledging the ever-changing pattern of competition in international business where firms are unable to grab customers through easily imitable strategies. In such case, CRM helps firms to build long lasting profitable relationship by which firms can benefit in real terms. Successful businesses are those, which can deliver customers’ value as wanted by them with a perfect blend of relationship acknowledgement Buttle (2012).

According to Lin et al (2010), customer relationship management practices help find customers that are abandoned by other companies for their unprofitable propositions (Mendoza et al, 2007). The mentioned view is totally supported by many scholars and industry players as they explain that CRM provide ways to recognize worthy new customers, profitable customers to retain and untapped areas of market. Potential customers with strategic benefits are pointed out and so does the sectors of customer whom should be curtailed. As per Lin et al (2010), CRM improves a customer’s total lifetime value, which provides great benefit in increasing the real economic value of a business.

Successful customer relationship management strategies inspire customers for being engaged in buying, staying loyal and having effective communication with a particular firm. With perfect resource allocation in right time and right place, CRM helps to build customer satisfaction to a new height 

2.11 Summary

After the thorough analysis of the existing literature, it is evident that customer relationship management has a wider grip on different aspect of marketing, selling concepts, customer behaviour analysis and so on. On the other hand, productivity concepts evolved from the firms’ concern for offering quality products with least costly processes and efficient resource consumption (Linoff and Berry, 2011). However, there had been very many researches on diverse aspects of customer relationship management and productivity concepts on a standalone basis, there had not been any noteworthy study on how customer relationship management influences the productivity dimensions (Maklan et al, 2008). Therefore, this significant research gap will be concentrated throughout this research for better process outcome for Syngenta AG. 

                                                            Chapter 3 – Methodology

3.1. Introduction 

Syngenta AG’s senior management is concerned with the present productivity dimensions and wants to find out the drawbacks in the present CRM practices. In addition, the management also tried to acquire a thorough understanding of the nature of the relationship that exists between customer relationship management and organizational productivity. Therefore, it is obvious that there had been an evident and specific research problem needing urgent notice. 

Business-oriented research does not fall into the category of routine jobs in business organization (Cohen, Manion & Morrison, 2000). Such researches are carried out for some special intention to resolve a problem, finding alternative courses of action, listing ways for better resource management or focusing on any particular flank of business activities etc. To conduct a research in a coherent and systemic fashion, researcher needs a proper guideline and such guidelines are delineated accurately in a research proposal.

Researchers in a business-oriented environment such as this have to focus on covering different significant areas of the research matter to be handled (Patton, 2002). The major parts highlighted should be the research design, research approaches, philosophy of research, research strategies, data collection methods, proper framework for sampling and ethical issue compliance related with the particular research. After these related issues are taken care of, the researched will step forward for data collection through survey instruments. Usually, as pointed out by Silverman, (2005), sampling mechanisms are followed to gather the required data. Once data collection processes are completed, the researcher goes through diverse analytical tools to check hypotheses and find solutions to mentioned research problem (Creswell, 1994). 

Figure 2 Research onion model

Source: Kumar, R. (2005) Research Methodology: A step-by-step guide for beginners. Second Edition. London, SAGE.

Consequently, this business research demonstrated how the researcher followed all the mentioned proceedings for a professional business research environment assuring all stakeholders that this business research had been conducted with a systematic procedure. 

3.2 Defining research philosophy and the selection of research philosophy 

Within the realms of business research, there are two types of research philosophies commonly utilized. One is the very popular phenomenology and the other is positivism. Concerning phenomenology and positivism, phenomenology is measured a ballpark echo of actual situation (Cohen, Manion & Morrison, 2000). For steering this professional study on compensation package, the researcher is ardent to practice phenomenology as the definitive exploration philosophy. Phenomenology takes a supplementary advantage above positivism as it deliberates diverse socio-cultural issues while accompanying the research in material sense. The overall assessment about respondent’s choices is that they may make irrational decision on every occasion and recons systematic favoritisms. Thus, bearing in mind all these matters, phenomenology will act as the superior choice as it considers societal and behavioral configuration of respondents (Patton, 2002). 

3.3 Defining research approach and the selection of research approach 

Research approaches are the systems in which the whole research work will be accomplished. There are two major approaches for business research namely deduction and induction research approaches. In the case of deduction approach of research, null hypothesis is formed and then, based on gathered data, these null hypotheses are tested. In such process, academic theories help the researcher to recognize the researcher’s area of interest in a better way. However, the deductive approach’s main objective is not to develop theory formulation. In another sense, while the researcher takes into account the induction techniques, they opt for generalizing patterns and end up with new theories in the respective business research (Silverman, 2005). That is how the formulation of theories is considered as the lone objective of induction research approach. 

In this business research, the researcher has followed the deductive approach to business-oriented research as some null hypotheses are established and these hypotheses should be tested on the grounds of academic theories. 

3.4 Defining research design and the selection of research design 

There are three basic types of research designs: qualitative, quantitative, and mixed design processes. Among the three basic research designs, our particular business research will be based on a mixed design process. In a qualitative research design, researchers use numerical data and research outcome is identified in a numerical form in most cases as outlined by Amber and Putoni, (2004). In a qualitative research design, testing null hypothesis is much easier and researcher can easily judge the extent of reliability and validity of research. However, as data is collected through sampling mechanisms, the data authenticity and reliability may be in question at times (Johnson, 2007). On the other hand, the qualitative research design deals with different data set and variables, which are hard to put into the form of numerical. Focus group discussion has proven as a good source of collecting qualitative data from a population and the researcher present findings in qualitative form (Johnson, 2007). Testing research validity and reliability are often much difficult is this research design. Again, the researcher will not be able to test any null hypotheses in this research design as that will need some quantitative treatment. Finally, for this very business research, the researcher opts for going with the mixed research design that includes the benefits of both the qualitative and quantitative research designs. Mixed research design also ignores the pitfalls of both aforementioned designs (Narver and Slater, 1990). The research topic in consideration needs solely the analysis of quantitative data to bring outcome from the hypotheses. Therefore, this research endeavor has prompted the researcher to follow the quantitative method of data collection as research area is numerical data-dependent making it will be easier to handle this sort of data with a quantitative research design (Creswell, 1994). 

3.5 Preferred research Strategies

Research strategy is the mechanism through which collection of data and the sampling procedure is conducted. Examples of major forms of research strategies are experiments, grounded research, survey, case studies etc. In this professional business research, the researcher wants to have a survey technique as a research strategy. The scarcity of information with much ensured quality was prevalent at the time when the researcher started research process. Another view was the longitudinal timing orientation, which matches perfectly with the research design. Marshall and Rossman (2006) state the mentioned the constrains associated with insufficient data as why the researcher preferred survey technique to conduct this professional research. 

3.6 Time Horizon

During the conduction of business-oriented research, the duration and frequency of time are two core decisions needed while the exercise commences. For the cause of shortages in resource, the research needs a longitudinal timing approach very essentially as the researcher is concerned with specific time frame and assured robustness, which may not be possible in a cross sectional analysis (Creswell, 1994). 

3.7 Research Instruments

As an integral part of research methodology, this part will cover the different instruments used in the research process such as the sampling framework, mechanism for data collection and tools and techniques for data analysis.

3.7.1. Sampling framework

If consideration goes to the shortage of resources, and some other practical constraints, such as inaccessibility of all the population, the researcher has to go for sampling techniques instead of census method as stipulated by Saunders, et al, (2003). The management level employees in different branches of Syngenta AG will be the part of population taken as sample. Among various methods of acquiring sample from population, the simple random sampling method is most suited for this research, as every single element of population will then have the same chance to be included in the sample (Mikkelsen, 2005). Because of shortages in resource, the population could not be divided into homogenous segments and that is why the stratified random sampling is not used here, even though it could do a better job. 

3.7.2. Data Collection mechanism

To collect information, several data collection techniques are available such as questionnaire, focus group discussion and interviewing techniques. In questionnaire-based techniques, it is much easier to spread out the data collection materials over a large horizon (Cooper & Schindler, 2009). Even though, the reliability concern for the responses against questionnaire will be a big issue for the researcher(Creswell, 1994). To be very precise and effective in such data collection, having a self-filled up questionnaire or collecting data with face-to-face interview will ensure a high level of data accuracy (Klenke, 2008). The important fact is to ensure a very high rate of response and data authenticity. Focus group discussion will ensure an open and free discussion in the researcher’s area of interest and very significant data can be attained in this process. Thus for collecting the primary data, the researcher opts for primary data collection mechanism based on questionnaire. The questionnaire include systematically related, simple and easily understandable questions for accurate data collection (Nykiel, 2007). The questionnaire was sent to 42 sample respondents out of them 30 respondents provided with necessary information. Therefore, there was a 70 per cent response rate with full answers to the queries so made.

The researcher needs secondary information for conducting this research. The corporate website of Syngenta AG provided a good amount of necessary information. In addition, the various academic journals and industry reports were used in precious information collection relating the research objectives. Some textbooks materials helped to find useful information about the research questions (Ragin, 1994). While collecting the secondary information the researcher ensured the timeliness and relevant criteria properly. 

3.7.3. Data analysis tools

To analyze the information, the researcher has used various sorts of data analysis tools and techniques. The data and secondary information was condensed from a huge pile with special reference to accuracy and relevance (Johnson, and Duberley, 2000). We had used regression techniques, descriptive statistics and testing of hypothesis for analyzing the information. Regression serves to express the linear or multiple functionality among variables and the researcher tested some multiple regressions throughout the research. Hypothesis testing examines the genuineness of any research problem statement and for testing hypothesis; the researcher has enabled t-test based on one sample (Munhall & Chenail, 2008). The one sample t-test serves as the barometer to check if there is any difference between sample statistics and population parameter and whether the difference is significant or not. Mean and standard deviation measures are included in the descriptive statistics segment where mean served as a central tendency measure and standard deviation measures the implied difference of average data set from mean (Johnson, et al. 2007). Two of the famous statistics software namely E-views and SPSS are used to analyze such data set and statistical measurement. 

3.8 Applicability of research validity and reliability

The research is a valid based on several considerations, most of which rely on the researcher being able to attain all mentioned research objectives. As by changing the research methodology part to a little extent and shifting the data set will enable the researcher to achieve similar sort of research outcome, the research is sure to be considered as a reliable research (Creswell, 1994). 

3.9 Ethical considerations

Ethical consideration is a key fact for any quality research work. In this business research, ethical practices will be upheld in all the process of data collection and processing. All the research objectives will be made clear to respondents before gathering any data and voluntary participation will be ensured (Munhall & Chenail, 2008). Data so collected by surveys will be maintained and preserved properly with due diligence. 

3.10 Summary 

The research methodology fragment of this very research elucidates and delivers a clear knowledge about controlled and organized manner has actually directed through a systematic progression. However, to be very specific, the actuality were a little dissimilar from the predictable courses of actions and made to have evidence of overlapping steps in research process at times. The unpredicted hardships in attainment of data, resource restrictions and other issues intersecting at research process made the research endeavor encounter issues that promoted the process of hypothesis emanating into reality (Kumar, 2005).

                                               Chapter 4 – Results and Analysis

4.1 Introduction 

The basis of this research is the comprehensive questionnaire due to its ability to get useful insights about the CRM processes and its relationship with the productivity issues with a core focus to the case of Syngenta AG. The researcher was dependent on the responses from the sample respondents in line with the questionnaire specially prepared and disseminated among them. 

This research endeavor’s introductory chapter delineated the researcher’s core area of interest Therefore, this analysis segment of the research will involve the researcher’s use of an extended variety of analytical tools based on the gathered data to cover the all four key objectives of the research.

• The definition of the term productivity that is prevalent in the perspective of Syngenta AG Corporation. With information from different secondary sources of data about Syngenta AG such as the website of the company, financial records published, articles, newspaper citations and so on, the researcher gathered the essential information. The questionnaire also provided much of the knowledge about such a fact. 
• The accurate extent of relationship between customer relationship management and organizational productivity had been comprehensively assessed based on the survey results from the questionnaire through regression based study. 
• The actual status of customer relationship management in Syngenta AG had been comprehensively assessed based on the survey results from the questionnaire.
• The loopholes prevailing in the existing customer relationship management programs in Syngenta AG were duly identified thorough the data obtained from the questionnaire.

However, before embarking on a thorough analysis with different statistical tools, the researcher tried to present a summarized view of the concurrent CRM practices so prevailing in Syngenta AG for achieving business productivity.

4.2 Findings from the descriptive study

This section entails a thorough idea about the analysis covering the descriptive statistics concentrating on the impact of CRM on the productivity dimensions at Syngenta AG. Many insights had been revealed about the prevailing CRM practices and issues about CRM needing emergent focus were pinpointed here. However, the researcher would try to delineate a comprehensive discussion over the respondents’ demography before starting the analysis from descriptive statistics. 

Table 1: Demography of respondents

Data collected with the sampling device, in this case the questionnaire, was mostly categorical in every respect, and due to this reason; the responses from the sample were converted to quantifiable and numeric codes for making them eligible for subsequent analysis. The following table explained the researcher’s method of codifying in line with the questions used precisely to collect data from sample respondents. The researcher clarified the numeric codes behind each options used in the mentioned questions. 

Table 2 Process of data Coding

At this stage, the descriptive statistics will be encoded as outlined in the following table:

Table 3: Descriptive statistics results

All insights resulting from the descriptive statistics offer a greater understanding of the shared view among the sample respondents about diverse aspects of productivity at Syngenta AG and the impact of CRM over the same issue. As evidenced in the table above, the mean values provide knowledge about average opinion over the given facts and the standard deviation shows the scattered nature of the opinions among respondents. The results provide evidence that the concurrent status of productivity is at a moderate level and Syngenta AG’s prevailing business proposition is moderately effective when thought from the productivity dimensions. The concept of productivity is defined as having a reduced level of costs in the overall business processes of Syngenta AG. From the top level management, the extent of emphasize over the productivity concern of Syngenta AG is found at moderate level. Syngenta AG follows the functional practice for calculating the productivity measures that focus particularly over the organizational functions.

Syngenta AG’s core impact of CRM over business value so identified is the result of an optimized and increasingly effective management of data. Apart from this, the results provide evidence that the concurrent status of CRM is at a moderate level and Syngenta AG’s prevailing customer relationship practices is moderately effective when thought from the productivity dimensions. The core strength of Syngenta AG’s customer relationship management is identified as having exclusive customization opportunities. Poor involvement of the end users with the CRM processes is found as the most miserable aspect of Syngenta AG’s customer relationship management. The respondents highlight the lack of adequate training on the CRM practices and the ineffectiveness of concurrent CRM practices in offering provisions for measuring, monitoring and tracking progress made in productivity. As per the respondents’ answers, there lies a reduced level of participation on all round participation from customers. Last but not the least; the respondents favoured the fact that the all sorts of CRM practices have a relationship with Syngenta AG’s productivity level. 

4.3 Hypothesis testing 

This research paper’s hypothesis-testing part would enumerate testing the pre-mentioned hypotheses with a 5% level of significance. The so formed hypotheses were:

Null hypothesis 1: There is no relationship between customer relationship management and organizational productivity.

Alternative hypothesis 1: There is relationship between customer relationship management and organizational productivity. 

Null hypothesis 2: There is no relationship between operational customer relationship management program and organizational productivity.

Alternative hypothesis 2: There is relationship between operational customer relationship management program and organizational productivity.

Null hypothesis 3: There is no relationship between collaborative customer relationship management program and organizational productivity.

Alternative hypothesis 3: There is relationship between collaborative customer relationship management program and organizational productivity.

Null hypothesis 4: There is no relationship between analytical customer relationship management program and organizational productivity.

Alternative hypothesis 4: There is relationship between analytical customer relationship management program and organizational productivity.

Table 4: Hypothesis testing results

Evidently, with 29 degrees of freedom and a 5% significance level, all of the pre-mentioned null hypotheses were rejected. Consequently, in accordance with the respondents’ responses to the questionnaire, Syngenta AG’s productivity is related to the customer relationship management program, operational customer relationship management program, collaborative customer relationship management program and finally with analytical customer relationship management program.

4.4 Finding from the regression study 

This segment of the analysis has the researcher trying to examine the extent of relationship between the CRM practices and the productivity dimensions of Syngenta AG. The exercise’s fundamental objective is to establish whether emphasizing more on the effectiveness of CRM would yield a better productivity for Syngenta AG or not. However, before going to carry out the regression analysis, the researcher would like to check the data set and variables whether they meet the requirements of an ordinary least squares or not. The feasibility of the dataset was ensured through the auto-correlation and unit root test results.

Table 5 unit root test 

Table 6: Autocorrelation test

Regression between effectiveness of customer relationship management and organizational productivity:

During this regression analysis, organizational productivity (measured from composite indexes obtained in the questionnaire) was the independent variable and the effectiveness of customer relationship management (measured from composite indexes obtained from the questionnaire) was the dependent variable. The following tables presents the results of the multiple regression analysis. 

Table 8: Regression analysis output

• Thus the regression equation was formed as the following one: 

ORGANIZATIONAL PRODUCTIVITY = 4.603 + 0.657 EFFECTIVENESS OF CUSTOMER RELATIONSHIP MANAGEMENT + ERROR

The regression equation above provides a lot of evidence that there remained a positive relationship between the organizational productivity and the effectiveness of customer relationship management. Evidently, as the regression co-efficient of one unit changes, the effectiveness of customer relationship management will cause a positive change of 0.657 to organizational productivity. In addition, it also depicted that without any sort of effectiveness of customer relationship management, the organizational productivity will remain constant in the value of 4.603, given there is zero effect in the error term. 

• z- value = 6.51 and p-value = 0.0997

The relatively high p-value (.0997) and a relatively low z-value (6.51) provide evidence that the independent variable is much significant to the determination of the dependent variable. 

4.5 Conclusion

Perhaps the most important facts revealed by the previous analysis were concurrent dependencies between the productivity as well as the CRM programs at Syngenta AG, at quite an appreciable level. In addition, a good level of association was found among the CRM programs and the productivity aspects of Syngenta AG. However, the concern for management was not found much aligned with the industry standards. 

                                                            Chapter 5 – Discussion

5.1. Introduction

By applying the use of different statistical analysis instruments, the researcher has demonstrated a command over the research objectives. Therefore, this segment will offer a comprehensive discussion over these outcomes discovered and provide a comparative analysis with the established academic literature, thereafter, offering logical and rational conclusions. Before going to the main discussion, the researcher would try to explain the findings in a brief form.

• The researcher discovered outcomes which offer a lot evidence that Syngenta AG’s productivity is related to her CRM program, specifically, operational customer relationship management program, collaborative customer relationship management program and finally with analytical customer relationship management program.
• In addition, the research found outcomes offering more evidence that there remained a positive relationship between the organizational productivity and the effectiveness of customer relationship management.

5.2. Comparison of the first finding with literature 

Through a comprehensive analysis, the researcher sought to test whether; there remains any relationship between the overall CRM programs and the organizational productivity. However, the researcher had also enumerated a much deeper analysis while segregating the overall CRM practice and concept into three different segments namely: the operational CRM, collaborative CRM, and the analytical CRM. However, the researcher found that all of the customer relationship criteria either as a whole or in segregation had a statistically significant relationship with the organizational productivity. 

Earlier research endeavors facilitated on the manufacturing industry by Bose (2002), with a sample size of 530 employees investigated the operational CRM aspects. The research concluded in a positive tone with the relationship of operational CRM and the productivity of the manufacturing firms. However, the relationship was not much high in the research outcome rather provided a low-level positive relationship between the concerned variables. In another research by Jill Dyche (2002) on the 53 retailing firms and with 748 sample respondents, the researcher found a greater level of association with the collaborative CRM and the organizational productivity. Furthermore, another rigorous research by Chen and Popovich, (2003) supported the research outcome by Jill Dyche (2002) by establishing a greater level of association over the concerned variables of collaborative CRM and the organizational productivity. With a 5% level of significance, another research by (Bacuvier et al. 2001) offered much evidence that there is relationship between the analytical CRM and the productivity. 

Although this research did not provide any absolute relationship between the variables, the regression outcome offered a much significant proof about their relationship in a relative manner. Similar sort of outcome was also derived from a research by Zineldin (2000) where the hypotheses testing provided evidence regarding the impact of CRM over the productivity concepts. 

5.3. Comparing the second finding with literature

Evidence surfaced during the researcher’s processes suggesting the fact that organizational productivity can be augmented with effective customer relationship management. The regression outcome offered a highly positive association between the concerned variables with a 5% level of significance. A rigorous research by Zoltner & Sinha (2001) over 41 service firms and 247 sample respondents, the researcher found a greater level of association with the concerned variable. Furthermore, Mukerjee (2007) supported the research outcome by Zoltner & Sinha (2001) through establishing a greater level of association among effectiveness of customer relationship management and productivity. With a 5% level of significance, other two researches by Renolds (2002) and Wilson and McDonalds (2002) offered more evidence that there is relationship between the organizational productivity and customer relationship management with the aim of improving organizational performance from a promotional perspective. 

5.4. Rationale for research gaps

Several research constraints offered most of the differences among the established literature and the specific outcome of this research. Most of the above-mentioned research endeavors aimed at large samples and a greater industry coverage in terms of cross-border and cross-industry situations. This research had a relatively small sample size and covered the cases of Syngenta AG only with a concentration on the UK. Therefore, it is safe to assume that this research had been on a longitudinal period, whereas the other literatures were established over a cross-sectional base. 

5.5. Chapter Summary

Based on the views expressed after a thorough literature review earlier in the course of this research endeavor in conjunction with the current findings emanating from the methodology, there seems to be a significant correlation between literature reviewed and our analytical results. If we compared the absolute results of diverse statistical tools, the differences found could be attributed to differences in the sample sizes, industry specification, country focus, and differences in periods covered. 

Chapter 6 – Conclusions and Recommendations

6.1 Introduction 

The researcher’s hypothetical statements that formed the impetus and basis for this research have truly been fulfilled if the research results are anything to go by. Hence, the researcher wishes to conclude that all of the expected results matched with the outcomes as expected by her on an approximation basis earlier on in the process of hypothesis forming. Some arguments can be there for the research outcome but such differences are highly attributed to the business reality of Syngenta AG. 

Syngenta AG belongs to group of organizations that operate at the intersection of tough business competition and scientific research making productivity a key component of their strategy. The company’s dynamic business environment and a number of variables have influenced its operations as evidenced in the research outcome. In addition, the researcher would like to brief her audience on her major findings, cover the research objectives, finally, offer some constructive recommendations.

6.2 Summary of the major findings

This research endeavor and the resultant outcomes offer a lot of evidence that Syngenta AG’s productivity is related to the customer relationship management program, operational customer relationship management program, collaborative customer relationship management program and finally with analytical customer relationship management program. In addition, the researcher found research outcomes offer a lot of evidence that there remained a positive relationship between the organizational productivity and the effectiveness of customer relationship management. Hence, from the outcomes of the aforementioned research endeavor, the relationship between Syngenta AG’s productivity and CRM practices exists and does so in an optimized manner.

6.3 Covering of the aims and objectives 

The researcher endeavored at finding out the exact level to which the subject organization’s productivity dimensions are augmented by customer relationship management processes. The research findings offer the exact level of productivity augmentation reasoned by CRM practices. In this way, the core research objective was satisfied. 

Objectively, the definition of the term productivity that is prevalent in the perspective of Syngenta AG became synonymous with organizational strife to boost operational success. With information from different secondary sources of data about Syngenta AG such as the website of the company, financial records published, articles, newspaper citations and so on, the researcher gathered the essential information. The questionnaire also provided much of the knowledge about such facts. 

The accurate extent of the relationship between CRM and organizational productivity had been comprehensively assessed through regression-based study and hypotheses testing. The actual status of CRM practices at Syngenta AG has been found on the descriptive statistics based on the survey results from the questionnaire. The loopholes prevailing in the existing CRM programs in Syngenta AG were duly identified on the descriptive statistics thorough the data obtained from the questionnaire.

6.4 Recommendations for improvement 

• Productivity as a concept is defined as having a reduced level of costs in the overall business processes of Syngenta AG. This focus should be on the greater level of customer satisfaction and top-level management should have much emphasize over the CRM programs. Syngenta AG should calculate the productivity measures from the economic perspectives.
• The organization studied, Syngenta AG, should try to focus on the better criteria for  customer relationship building while designing strategic programs. It should enumerate much incorporation from the end users in the CRM process. 
• Finally, the proper training and progress measurement methods should be present in the organization for addressing measurement of the effectiveness of any CRM programs. A more augmented level of participation should be established with a concentration on the customers as      a way of optimizing the organization’s CRM programs.

6.5 Recommendations for further research

As a fundamental concentration of this research, the effectiveness of CRM in the chemical and agri-business industry was put to the test with a focus on Syngenta AG. Researchers can enable similar types of research in other industries too such as the retailing industry, financial service industry, grocery industry and so on. A simplistic change in the research methodology would enumerate a much comprehensive research in this regard. The end-result of such strategic activity across the entire customer-based sector of the global economic environment would improve the current performance of the mentioned sectors once more returning the power to influence economic performance through productivity to a major stakeholder – the customer.

6.6. Chapter Summary

Although the prevailing CRM practices are not up to the industry standard, there exists a lot of potential in the current business environment to address these deficiencies. As a representative of the currently dynamic global business environment, Syngenta AG should incorporate the customers more in the all CRM practices and concentrate more on their expectations from the organization. On the other hand, organizational top-level management should be more focused on the CRM designing and optimization strategies in place such as those suggested through this research endeavor. Additionally, these organizational heads should incorporate sustainable company goals with their organizational CRM practices. 

APPENDIX

Questionnaire

The following questionnaire intends to conduct a sample survey for a research endeavor of an academic nature. I humbly solicit for your kind participation emphasizing that is entirely based on voluntary participation. Any personal details provided in the questionnaire will be kept anonymous strictly. In addition, this material shall be preserved in accordance with international standards on anonymity during academic research procedures. 

Note: Please have a tick sign to the related circle

Respondent’s Demography

Age: _______ Year

Gender:                   Male           Female

Income level (annual in GBP):     Less than 50000 GBP         More than 50000 GBP     

Job experiences:  Less than 4 year’s     4 – 8 years  More than 8 years

1. What is Syngenta AG’s present status in terms of organizational productivity?

O Excellent 

O Very Good

O Moderate

O Low 

1. How is the concept of productivity defined from the perspective of Syngenta AG? 

O More output

O Higher sales growth 

O Greater level of customer satisfaction

O Reduced extent of costs

1. How effective is Syngenta AG’s concurrent business proposition with regards to the dimensions of productivity?

O Extremely effective

O Very effective

O Moderately effective

O Slightly effective

O Not at all effective

4. What is the emphasis of the significance of productivity with regards to Syngenta AG?

O Extreme emphasize

O Much emphasize

O Moderate emphasize

O Low emphasize

5. In which way was productivity measure calculated at Syngenta AG?

O Physical Productivity

O Functional Productivity

O Economic Productivity

6. How has CRM impacted the business value of Syngenta AG?

O Reducing costs

O Process automation

O Effective management of data

O Loyal and profitable customers

O Better customer relationship

O Increased competitive edge

7. What is the present status of Syngenta in terms of customer relationship management?

O Excellent 

O Very Good

O Moderate

O Low 

1. How effective is Syngenta’s customer relationship practices in terms of augmenting organizational productivity?

O Extremely effective

O Very effective

O Moderately effective

O Slightly effective

O Not at all effective

1. Which one do you think is in most severe condition in aspects of Syngenta AG’s CRM?

O Immeasurable business goals

O Alignment of Information Technology and business.

O Upfront executive support

O Involvement of end user

1. Is there an adequate measure of training on customer relationship management in Syngenta AG? 

O Yes 

O No

1. Do the concurrent CRM practices offer provisions for measuring, monitoring and tracking progress made in productivity at Syngenta AG?

O Yes

O No

1. Do the prevailing CRM processes at Syngenta AG ensure all-round participation from customers? 

O Yes 

O No

1. Do you think there is relationship between customer relationship management and organizational productivity?

O Yes 

O No

1. Do you think there is relationship between operational customer relationship management program and organizational productivity?

O Yes 

O No

1. Do you think there is relationship between collaborative customer relationship management and organizational productivity?

O Yes 

O No

1. Do you think there is relationship between analytical customer relationship management and organizational productivity?

O Yes 

O No

1. What is the core strength of Syngenta’s CRM process?

O Functional business goals

O Experienced and trained consultants

O Exclusive customization opportunities

O Customer focused processes

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