Chapter Three: Methodology
The research methodology refers to the structured set of guidelines and activities undertaken by the researcher in order to report valid and reliable findings (Babbie 2010). The research methodology mainly depends on the nature of the present study as well as the research questions. This chapter describes the steps taken by the researcher in gathering the data required to answer the study questions and meet the objectives of the work. The research methodology was based on the steps outlined in the research onion documented by Saunders, Lewis, and Thornhill (2007), which describes the six steps to be made in the research methodology. These comprise of the research philosophy, methodological choice (research design), approach, strategy, time horizon, as well as procedures and techniques. The first step in the work onion is the research philosophy, which refers to the views and opinions of the researcher including his or her worldview. The research philosophy determines the strategy used in the study, which refers to the plan or method used by the scholar. It also influences all the other remaining aspects of the methodology. The research approach refers to the method used by the researcher to bring up new knowledge regarding the issue at hand; whereas the research strategy defines the action plan for guiding the research in terms of which he or she will conduct the research. This chapter discusses all the aspects outlined in the paper with respect to the present study. Moreover, the validity and reliability, ethical considerations, and study limitations are also included.
3.2 Research Philosophies
The researcher’s perception concerning the world, his or her assumptions about human knowledge and the nature of reality are important factors that determine how research questions and design are framed. Fisher (2007) points out that the research philosophy refers to the views of the researcher concerning what constitutes an acceptable knowledge as well as the process used in the development of the knowledge. For example, researchers who investigate observable phenomena tend to have a completely different point of view than those placing emphasis on having an in-depth understanding and subjective meanings of phenomena with respect to the way in which the research study should be conducted, the research design, research strategies, and the kind of data considered as pertinent (Cozby 2012; Daymon & Holloway 2010). According to Saunders, Lewis, and Thornhill (2007), it is imperative for the researchers to determine their worldview, which in turn aids in selecting the most appropriate research philosophy to lead the research. When determining it, Saunders, Lewis, and Thornhill (2007) outline three issues to be considered – ontology, epistemology, and methodology. Ontology is the researcher’s views concerning the nature of reality. Epistemology is the view of the researcher with respect to the attributes of acceptable human knowledge. The methodology represents the procedures and techniques that the researcher uses to collect the data needed to answer the study questions and meet the objectives of the study (Saunders, Lewis & Thornhill 2007).
The interpretivism beliefs are suitable for research studies seeking to gather rich insights associated with the subjective meanings rather than making generalizations (Creswell 2011). The epistemology of interpretivism is characterized by an emphasis on situational details. Ontologically, interpretivism advocates for the social construction of human knowledge (Ramsey et al. 2009). Methodologically, interpretivism entails using qualitative methods typified by in-depth investigations rather emphasizing the generalizations of the study findings (Gulati 2009). Its core element is the social construction of reality. According to this philosophy, it is assumed that reality is a constant process developed by the interpretation and re-interpretation of the behaviors of people. The ultimate objective of the interpretivism philosophy is to provide detailed insights relating to the meanings that people attach to the situations under investigation based on the worldview of the people found within those situations (Daymon & Holloway 2010). This means that the researcher plan an active role in the research by interpreting the happenings and trying to understand the processes used by people to construct the meanings (Snieder & Larner 2009). The researchers also try to establish the meanings that people associate with particular events in their situations.
Apart from the social construction of knowledge, interpretivism stresses an important role that the researcher plays with respect to determining the subjective realities and meanings which have an influence on the actions and behaviors of people (Vogt, Gardner & Lynne 2012). Therefore, the knowledge produced in interpretivistic research is attributed to the researcher’s understanding and comprehension of the views and opinions of people (Babbie 2010). The interpretivism philosophy was considered as a potential choice for this research; however, it was ruled out, primarily due to the delimitations of the study. In this paper, the researcher sought to generalize the findings of the study to a large population rather than developing a detailed analysis of the issue under investigation. Interpretivism does not have a provision to generalize the findings of the study.
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Pragmatism research philosophy places emphasis on the practical applications of the findings reported in the study, which means this philosophy focusing on addressing the practical problems that people encounter, the study questions posed, and outcomes of the study (Daymon & Holloway 2010). This theory does not advocate for any specific method. In fact, the core assumption of pragmatism is that no single method can guarantee comprehensive findings; as a result, the research is allowed to make use of diverse techniques and methods when gathering and analyzing data (Daymon & Holloway 2010). It is also crucial to note that pragmatism is sensitive to the social, historical and political context that spurs the inquiry process and considers issues associated with social justice, morality, and ethics as being crucial aspects of the research process. Mitchell and Janina (2009) state that pragmatism is all about using methods considered constructive in particular contexts in order to provide solutions to practical problems instead of engaging in debates as to which is the most suitable approach for conducting the study.
Pragmatism is distinguished from realism and positivism, which are based on the assumption that objective reality is possible and it is devoid of subjective biases (Cozby 2012). For pragmatic researchers, the debates regarding the subjectivity or objectivity of reality are not relevant to addressing the problems facing mankind. The ultimate goal of pragmatic researchers is to contribute to the world’s knowledge and make it a better place (Snieder & Larner 2009). In this respect, science should be of service to humanity, chiefly thanks to providing solutions to problems that mankind faces. Saunders, Lewis, and Thornhill (2007) point out that pragmatic research tends to be more problem-oriented and not curiosity-driven. In sum, the analysis of the study findings under pragmatism draws upon the social, moral and practical consequences of the inquiry with respect to improving the human condition. The problem under investigation is more significant than engaging in philosophical debates regarding the appropriateness of the methods.
Ontologically, pragmatic research assumes that reality represents the practical effects associated with ideas (Fisher 2007). Epistemologically, realism advocates for the use of any method provided it yields pragmatic solutions to the problem at hand. Methodologically, pragmatic research entails the use of mixed methods research, action research, and design-based studies (Sherri 2011). In this study, pragmatism philosophy was considered but disregarded on the grounds that it was inappropriate given the nature of the present research. Pragmatic research requires the use of an intervention, performing the empirical study in a natural setting, a collaboration between the practitioners and researchers, and the development of design principles and theory, which were not crucial components of this research. Moreover, this research did not involve the development of an intervention to be tested.
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Realism research philosophy assumes that the mind and the reality are not related. Moreover, this philosophy presupposes that trust is what is sensed by the researchers regardless of the fact that worldviews and experiences influenced researchers (Leedy & Ormrod 2010). According to realists, the existence of entities is independent of what is being perceived, or theories regarding them. Realists also argue for an external reality, which comprises of abstract things attributed to the minds of people although they are unrelated to any single person. Instead, this external reality is predominantly autonomous and created by “us” rather than a single individual (Walliman 2009). From an ontological perspective, realism philosophy assumes that reality is real although it is only probabilistically and imperfectly apprehensible; therefore, there is a need to triangulate data from diverse sources in order to know the truth. Epistemologically, the realism philosophy assumes that the researcher is value-aware and requires the researcher to triangulate any perceptions gathered (Babbie 2010; Neuman & Kreuger 2006; Vogt, Gardner & Lynne 2012). Methodologically, realism emphasizes the use of qualitative methods like convergent interviews and case studies.
The positivism research philosophy is considered most suitable for guiding studies that focus on observing and predicting outcomes that are based on law-like generalizations (Creswell 2011). Positivism is the most commonly adopted philosophy in business research. Its key assumption is that one can measure reality through value-free observation. As a result, the researcher has a limited role in the work, with his role being constrained to collecting data and analyzing the data through an objective lens (Ruane 2005; Singh & Bajpai 2008). It is also important to note that the finding of positivist research is often quantifiable and observable. Similarly to the research philosophy, positivism is consistency with the empiricist perspective that knowledge is attributed to the human experience. Positivism research is characterized by the ontological and atomistic view that the world constitutes of observable and discrete events and elements interacting in a regular, determined and observable way. Furthermore, positivism assumes that the research and the study are unrelated entities; as a result, positivist research does not take into consideration human interests. Fisher (2007) adds that as a general rule of thumb, positivist often uses inductive approaches.
In addition, positivism is consistent with the view that the researcher is supposed to emphasize facts. Ontologically, positivism assumes that an objective reality exists and that it can be understood using the laws governing the reality (Cozby 2012). Epistemologically, positivism research adopts a scientific approach. Methodologically speaking, positivism research advocates for the use of quantitative studies involving deduction. In this study, the positivist philosophy was deemed the most appropriate (Snieder & Larner 2009). Fisher (2007) points out that the positivism philosophy is appropriate for research studies that tend to be highly structured and lacking the influence of the researcher, which is the case with this research. In this study, the research problem is clearly defined and structured, and that the scholar distanced himself from the research. The choice of positivism research philosophy also stems from its dominance in management and business research types. Fisher (2007) cautions that, if a researcher assumes the positivism philosophy to guide the research, he or she must be convinced that he or she is independent of the research and that the research is purely objective. Logically then, it is the researcher’s conviction that he was independent of the research, which was achieved through minimal interaction with the participants in the course of the research. Moreover, since the study was clearly structured, data was gathered using questionnaires to facilitate minimal interaction with participants. The objectivity of the study was guaranteed through the use of statistical techniques when analyzing the data collected.
3.3 Research Approach
Two approaches can be used when performing any type of scientific inquiry, which is deduction and induction. The research method refers to the route undertaken by the researcher in the development of knowledge and theories (Snieder & Larner 2009; Vogt, Gardner & Lynne 2012). The reasoning approaches that can employ in any research are deductive or inductive approaches. The difference between these two approaches comes from the link between the actual study and the hypothesis. The deductive approach is akin to the evaluation of a theoretical suggestion, which commences from the formulation of hypotheses based on existing theories and literature and developing a research strategy in order to test the provisions of the study hypothesis (Snieder & Larner 2009). As a result, the deductive method often makes use of a top-down approach, typified by inferring conclusions that draw upon the collected data. It accentuates on the development of a set of hypotheses based on current theories followed by the designing the research strategy to assist in collecting information to either reject or confirm the hypotheses (Ramsey et al. 2009; Vogt, Gardner & Lynne 2012). Simply stated, the deductive approach usually commences with stating the anticipated relationships and patterns that are likely to exist between the variables, and then relying on observations when testing the outlined hypotheses. The deductive research approach employees specific-to-general reasoning.
The inductive research approach is often used in theory development rather than theory testing. It is usually guided by the use of research questions rather than testing hypotheses (Monette, Sullivan & DeJong 2005). The author considered using an inductive approach but decided not to because of the nature of the scientific inquiry used in this research. This research study employed a deductive approach, which can be attributed to the underlying research’s nature. The rationale for the use of a deductive approach in this study is because the research is confirmatory in nature (Snieder & Larner 2009). The paper starts with a review of existing literature, development of hypotheses based on it, and is followed by the empirical evaluation of this literature. The choice for the deductive approach to guide the study can also be attributed to the quantitative nature of the research. Fisher (2007) shows that quantitative studies inherently use deductive reasoning (Ruane 2005). It was possible to quantify and measure the business phenomena under investigation. In this respect, strategic purchasing, supplier relations, and operational performance will be expressed numerically, after which relationships between them will be analyzed using statistical techniques.
3.4 Research Design
The research design is an important methodological consideration in any study. Saunders, Lewis, and Thornhill (2007) point out that the choice of a suitable research design is determined by the appropriateness of the design in addressing the research questions. With regard to the research design, researchers have the option of using a single data collection technique coupled with a single analysis technique, which can be either a mono method quantitative or a mono-method qualitative design. Alternatively, researchers can employ multiple research designs, which can be either multi-method quantitative or multi-method qualitative design (Saunders, Lewis & Thornhill 2007). Moreover, a mixed methods approach involving the use of both qualitative and quantitative designs can be used. This study utilizes a quantitative design, which is the most suitable for descriptive and confirmatory research studies (Creswell 2011). Descriptive studies are used when trying to classify and identify participant’s characteristics and ascertain the nature of the relationships between variables. Confirmatory studies are used in the evaluation of a priori hypotheses. This research is descriptive since it will explore the characteristics of supply chain professionals in Nigerian oil and gas firms with respect to their use of strategic purchasing (Vogt, Gardner & Lynne 2012). Moreover, the study seeks to explore the relationship between strategic purchasing, buyer-supplier relationships, and operational performance supply chains. The study is considered confirmatory because it evaluates a number of hypotheses outlined in the first chapter. The quantitative research design is the most appropriate for this study because the emphasis is on exploring how the aforementioned variables relate to one another.
The qualitative research design focuses on the discovery of novel information and the relationship between the researcher and the topic under study. The quantitative research design is contrasted with the qualitative research design since its focus is on analyzing and measuring causal relationships between the variables under investigation (Vogt, Gardner & Lynne 2012). Therefore, a quantitative research design is characterized by measuring and counting things while the qualitative research design entails describing things. Another fundamental difference between qualitative and quantitative research design stems from the degree of the flexibility of the research design (Snieder & Larner 2009), the type of data that the researcher collects (Walliman 2009), the methods used in collecting the data, and the nature of the research questions (Sherri 2011). In particular, the qualitative research design employs an interpretive approach that seeks to offer in-depth understandings and insights regarding the meanings associated with a particular phenomenon (Creswell 2011). Such attributes contribute to the uniqueness of the qualitative research design, which turn to produce a comprehensive understanding of the context being investigated. By contrast, the quantitative research design has the primary objective of assessing a prearranged set of hypotheses by using extremely rigid and structured data collection methods (Daymon & Holloway 2010). The qualitative research design entails the use of open and flexible data collection methods.
It starts with a list of pre-set variables obtained from a conceptual framework or the literature review, which is congruent with the attributes of this research study since the variables incorporated into the hypotheses have been derived from the review of the literature (Snieder & Larner 2009; Singh & Bajpai 2008). In addition, the quantitative research design is the most preferred approach when tackling a structure, or some clear problems. This is not the case with qualitative research recommended for addressing unclear, unstructured research problems. Since the present study is confirmatory and descriptive, it can be implied that the research problem is clear and structured because the research hypotheses have incorporated precise variables to be investigated (Vogt, Gardner & Lynne 2012; Saunders, Lewis & Thornhill 2007). As a result, the variables of interest guided the entire research process, which is an indication that the research problem was both structured and precise. This posed the need to employ structured quantitative methods rather than relying on open-ended qualitative approaches.
Another justification for the use of the quantitative research design stems from the need to generalize the results of the study (Cozby 2012). Quantitative research designs are executed by carrying out a statistical analysis of the numerical data in order to make conclusions that can be inferred to the study population (Johnson & Christensen 2010). To this end, the research sought to explain the phenomenon under study using numerical data analysis with the aim of exploring the relationships between variables. As a result, the variables will be operationalized and quantified, after which the statistical analysis will be used for ascertaining the significance of the relationships.
The research design adopted for a job is also a crucial cornerstone of the research methodology. The research design is defined as a systematic plan that the researcher uses when investigating the study problem (Neuman & Kreuger 2006). As a result, the research design has an influence on the fundamental strategies employed by the researcher when collecting data. Moreover, the research design influences the processes used in selecting participants in the research (Mitchell & Janina 2009). In this study, the comparative design was used, which is often used when comparing various groups of participants to discover something or differences between the groups (Monette, Sullivan & DeJong 2005). In this regard, the specific comparative design used in this paper entailed comparing supply chain professionals who use strategic purchasing and those who do not in order to see if there are any differences concerning the buyer-supplier relationship. The objective was to determine the impact of strategic purchasing on buyer-supplier relationships. The independent variable is strategic purchasing while the dependent variables consist of buyer-supplier relationship and operational performance of the supply chain.
3.5 Research Strategies
The research strategy formulates the actions performed by the scholar in an attempt to answer the research questions and achieve the objectives of the study. It is important to ensure that congruency exists between the research strategy and the nature of the work (Maxwell 2005). From the research onion, numerous research strategies exist, including an experiment, survey, a case study, action research, a grounded theory, ethnography, and an archival strategy. The survey research strategy was adopted for this paper. It entails administering questions to people. Fisher (2007) shows that survey research is commonly utilized when assessing the thoughts, feelings, and opinions of people. The goals of the survey strategy can be diverse, have specific and limited goals, or targeting more widespread, global ones. The rationale underpinning the selection of the survey research strategy stems from its proven effectiveness in collecting diverse views and opinions concerning issues (Ness 2010). Moreover, the nature of the study ruled out other potential tactics. For instance, an experiment could not be conducted in such a situation at all. Similarly, other strategies like ethnography were dismissed because they are not suited for quantitative research strategies.
Fisher (2007) points out that the survey research strategy is common in business research because it is low cost and facilitates easy access to information. The first vital step in the survey research strategy entails determining the study aims, which have been outlined in Chapter 1. The next important step entails determining the sample group, which is discussed in the following section 3.6. Another decisive consideration in the survey research strategy is the choice of data collection techniques. These include interviews, observations, and questionnaires among others. The representativeness of the survey research is also another justification for its use in the present research (McBurney & White 2009). With the appropriate sampling approach, the survey research helps to produce results that can be generalized to the wider population. Through the basic principles of probability theory, researchers have been able to devise some efficient strategies that can be used in obtaining representative samples to help in generalizing the findings to the larger study population.
The specific survey strategy that was adopted for this study is a cross-sectional survey, which entails collecting data during a single point in time. The cross-sectional aspect of the survey also indicates the time horizon used in this research. According to Saunders, Lewis, and Thornhill (2007), the time horizons that a researcher can adopt include the cross-sectional and longitudinal survey. The cross-sectional design requires collecting data from at least one source at a specific point in time so as to collect quantitative data that can then be used to ascertain how variables relate. The cross-sectional survey was the appropriate time horizon because the survey is not progressive. The longitudinal survey is conducted over a prolonged period of time in order to consider potential changes that may be observed in the data (Sherri 2011). Fisher (2007) states that cross-sectional surveys provide an ideal opportunity for the researcher to evaluate relationships between variables as well as differences between subgroups within a population. Cross-sectional surveys are also significant in testing causal hypotheses in diverse ways (Cozby 2012). In this way, cross-sectional surveys were helped in estimating the impact of strategic purchasing on the relationship between the buyer and the supplier.
3.6 Sample Selection and Population Sampling Techniques
The population for this research comprises of supply chain professionals working for oil and gas companies in Nigeria. Before commencing the study, the researcher sought the permission of these professionals through informed consent. The next that followed the selection of the survey design was the choice of the sampling method. There are numerous sampling techniques that the researcher can adopt. In order to facilitate the generalization of the findings reported in this research, a probabilistic sampling approach was used. Probability sampling refers to the general approach to sampling whereby element in the study population is selected randomly, which means that each individual unit in the study population has an equal chance of being selected to participate in the research (Johnson & Christensen 2010). Probability sampling brings about two important benefits to the paper1. The first is that the researcher can confidently state that the sample is representative of the study population from which the sample was drawn. When elements have been chosen through non-probabilistic methods or when some quotas of the population have no chance of participation, it is impossible to ascertain the representativeness of the sample (Ramsey et al. 2009). Generalizations that exceed particular elements in the study sample can only be made when the researcher uses probability sampling. The second advantage associated with probability sampling is that it allows the scholar to accurately estimate the level of variance in the data set attributed to the sampling error. This means that researchers are capable of computing the degree to which random differences between the study population and the sample are likely to affect the precision of the reported results (Daymon & Holloway 2010). Through the use of probability sampling, researchers are able to define confidence intervals for their findings.
The specific probability sampling technique adopted for this study is simple random sampling. In this approach, the elements are selected from the population on a random basis, which means that all elements in the study population have an equal probability of being selected to participate in the research (Cozby 2012). The rationale underpinning the selection of such sampling method lies in the fact that there is a need to generalize the findings of the research. The sample size for the study comprised of 100 supply chain professionals drawn from the oil and gas companies operating in Nigeria.
3.7 Sources and Methods of Data Collection Techniques
Collection of data is a crucial prerequisite for any form of research because it influences the success of the work with respect to making inferences and conclusions from the collected data. Owing to the fact that business research significantly depends on data to explain various phenomena, it is important to devise appropriate data collection techniques and instruments to be able to report valid and reliable findings (Daymon & Holloway 2010). Two forms of data exist – primary and secondary one. Primary data refers to what is gathered by the researcher first-hand, whereas secondary includes information and data that has been collected and documented by other scholars. Primary data is gathered using data collection instruments such as questionnaires and interviews. Fisher (2007) points out that using primary data is a very effective approach of executing research since the information collected is often raw and devoid of manipulations by other researchers, which subsequently contributes to the validity of the research. Moreover, primary information can be collected and later triangulated against secondary sources to check for accuracy (Singh & Bajpai 2008). Owing to the fact that the current research uses the survey strategy, primary data will be gathered in the form of questionnaires.
A questionnaire a self-administered tool for eliciting responses from participants. They have been reported to be effective when gathering huge amounts of data within relatively short timeframes (Saunders, Lewis & Thornhill 2007). Moreover, questionnaires tend to be more cost-effective relative to other data collection instruments such as face-to-face interviews, especially for research studies involving large samples. Moreover, the effectiveness of the written questionnaire increases with the increase in the number of questionnaires. Another reason why the questionnaire was selected as the data collection instrument stems from the fact that their analysis is easy (Daymon & Holloway 2010). Data tabulation and entry from all surveys can be performed with the help of statistical software packages. Another advantage associated with the questionnaire is that it lessens bias in the data. Because of the standardized question, the middle man bias is reduced. The opinion of the research will not have any influence whatsoever on the responses provided by the participant, which is an important aspect of this positivist research undertaking. Fisher (2007) points out that questionnaires lack visual or verbal clues that can be used in influencing the participant. Another crucial advantage that provoked the use of the questionnaire lies in the fact that they are less intrusive when compared to interviews. When a respondent gets a questionnaire in the form of mail or email, he or she can fill it at a time of his or her convenience (Cozby 2012). Relative to other data collection instruments, the respondent faces minimal interruption when the questionnaire is used as the data collection instrument (Walliman 2009).
The questionnaire captured a number of aspects relating to the measures of strategic purchasing, buyer-supplier relationships, and the operational performance of the supply chain. These are based on the descriptions of this constructs in the literature review. Strategic purchasing was quantified by the self-reported measures of supplier integration, supply base flexibility, and the formal socialization process in the supply chain. Supply base flexibility refers to the number of suppliers that a firm has (B?nte 2008). It is akin to the concept of lean supply, whereby a firm maintains few suppliers in order to facilitate collaborative working and reduce supply chain costs. Supplier flexibility will be measured using a five-point Likert scale (5 – very many, 4 – many, 3 – moderate, 2 – few, 1 – very few).
Supplier integration is yet another aspect of strategic purchasing that will be assessed through self-reported perceptions of participants. It is defined as the extent to which suppliers are incorporated into the product development process including at the operational level (Cani?ls & Gelderman 2007). Supplier integration will also be measured using a five-point Likert scale (5 – very high, 4 – high, 3 – moderate, 2 – low, 5 – very low).
Another strategic purchasing element that was captured in the questionnaire is the formal socialization process, which is defined as a degree of interaction and communication between the firms in the supply chain (Cani?ls & Gelderman 2007). Participants were asked to rate the level formal socialization process using a five-point Likert scale (5 – very high, 4 – high, 3 – moderate, 2 – low, 1 – very low).
In addition, strategic purchasing measures, the questionnaire also captured constructs associated with the buyer-supplier relationship, which included cooperation, communication, trust, interpersonal relationship, and power dependence (Dyer & Chu 2011). Cooperation is the extent to which firms in the supply chain work jointly to achieve their mutual and individual business objectives. Communication in buyer-supplier relationships can be described as the formal and informal means used to share meaningful and timely information between partnering companies. Trust refers to the credibility of the partnering organization, which in this case denotes the supplier. An interpersonal relationship is also another cornerstone of buyer-supplier relationship defined as the extent to which personal relations influence the business relationship, that is, the degree to which personal connections comes to play with respect to buyer-supplier relations. Power dependence is defined as the ability of a business partner to influence the decisions made by their partner (Dyer & Chu 2011). All these dimensions of buyer-supplier relationships will be self-reported by participants on a five-point Likert scale. Moreover, participants will also self-report on the operational performance of their supply chain using the same scaling method.
Apart from the measures of strategic purchasing, buyer-supplier relations, and operational performance of the supply chain, the questionnaires also captured other aspects including a description of the constructs, the purpose of the research, and demographic factors of the participants, which include age, gender, and experience among others.
3.8 Data Analysis
Data analysis involves examining, converting and modeling the collected data in order to point out any meaningful information to help in inferring conclusions (Babbie 2010). In this study, the analysis of data focused on answering the research questions and testing the hypotheses. The research utilized both descriptive and inferential statistics. Descriptive statistics were used to summarize and describe data using statistical variables such as mean and percentages. It was also used for describing the variables. Inferential statistics were utilized to determine the nature of the relationships between the variables. Various forms of descriptive statistics were applied including the one-way ANOVA and correlation analysis. The one-way ANOVA was used to determine whether significant differences existed in the measures of buyer-supplier relationships when participants are grouped in accordance with the level of strategic purchasing. A one-way ANOVA analysis was performed for each construct. Correlation analysis was also performed so as to explore the relationships between variables using the Pearson correlation coefficient. Significant correlations were highlighted as well as the magnitude and their nature (negative or positive). The Statistical Package for Social Sciences (SPSS) was used for analysis.
3.8 Validity and Reliability
Ascertaining the validity and reliability of data is crucial before inferring conclusions. The reliability of the data was confirmed using Cronbach’s alpha coefficient, which is used in determining the internal consistency of a data collection tool. It ranges from 0 to 1, with 1 indicating higher reliability and 0 indicating lower reliability (Ruane 2005). One thing that is worth mentioning is that the validity of the study was guaranteed with the large sample size of 100, which is sufficiently large to yield significant results.
3.9 Ethical Considerations
Any research should take into consideration the diverse ethical issues that are inherent when performing an investigation. Saunders, Lewis, and Thornhill (2007) outlined numerous rights that participants enjoy, including the right not to take part in the study; the right to not be subjected to any harassments; the privilege not be offered any inducements that are beyond the scope of participation; the right to be contacted at times deemed reasonable; and the right to right to determine the time they will be involved in the data collection process. Participants also expect the researcher to obey and comply with the consent offered. Saunders, Lewis, and Thornhill (2007) further maintain that they cannot be forced to answer any question they do not want and that they should be subjected to a position that results in stress or discomfort. People are chosen for the study also expect the scholar to comply with the agreed anonymity and confidentiality requirement in the discussion of the results and when reporting the study findings. Based on these rights, the researcher must take into consideration various ethical issues.
The first ethical issue relates to voluntary participation. This principle demands that no one can be coerced into participating in the research. Achieving this requirement entails providing participants with informed consent (Saunders, Lewis & Thornhill 2007). This information consists of the study purpose, benefits of participation, and information detailing how the study findings will be utilized. The second principle relates to preserving the anonymity and confidentiality of participants. In this respect, no participant information that could aid in their identification was revealed in the findings and discussion. Moreover, the researcher refrained from gathering personal information such as names, telephone numbers and home address (Vogt, Gardner & Lynne 2012). Instead, identified information was used as a reference for participants in order to ensure that they even remained anonymous to the researcher. The third ethical requirement entails ensuring no harm resulting from participation in the research. It is imperative to note that this study is a low risk one, with no discomfort expected when participating. The only likely discomfort emanates from answering the online questionnaire when staring at the computer screen (B?nte 2008). The researcher complied with the rights of participants and offered them a detailed consent developed based on table 3.9 below
Lack of consent
Participant does not have any knowledge regarding the study
The participant lacks a full understanding of his or her rights.
The researcher provides the participant with informed consent containing full information regarding the study and outlines the rights of participants and how the findings will be used
The researcher employs deception when gathering data
The researcher implies consent on the use of the gathered data based on the fact that he or she was able to access the data.
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3.10 Limitations of the Study
This study is not without limitations. The first one is inherent to the quantitative design choice. In this respect, the focus on theory testing and hypothesis may result in the researcher missing the actual phenomena (Sherri 2011). Another limitation relates to the use of questionnaires, which increases the likelihood of collecting incomplete and inaccurate self-reported data (Cozby 2012). In order to address this limitation, the confidentiality anonymity of participants was guaranteed so as to encourage honesty.
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