guiding research and organizing and making sense of research findings

guiding research and organizing and making sense of research findings
Question # 1
Theories play a vitally important role in guiding research and organizing and making sense of research findings. In spite of the great importance of theory-building and theory testing within your field of specialization, there is no generally accepted conception of what a theory is. Because your dissertation must contribute to theory, you must have a clear understanding of the variety of conceptions of theory, types of theories, and ways of contributing to theory and be able to justify how, exactly, your study contributes to theory.

Part 1
Using Gelso (2006), Harlow (2009), Stam, H. (2007, 2010), Wacker (1999), and five additional peer-reviewed articles from your specialization, discuss scholarly views on the nature and types of theory. Compare and contrast at least three views of what constitutes a theory, including the view you will use in Part 3 of this question. Be sure to distinguish theory from related concepts, such as hypothesis, paradigm, model, and concept.

Part 2
Using Ellis & Levy (2008), Harlow, E. (2009), and five additional peer-reviewed articles, review the scholarly literature on the relationship between theory and research and the ways research (quantitative and qualitative) can contribute to theory. Discuss at least three ways research can contribute to theory.

Part 3
Pick a theory (in one of the views of what constitutes a theory that you identified in Part 1) of current interest directly related to the topic area of your dissertation. A theory is currently of interest if there are articles published on it in the past five years. Using at least 10 published, peer-reviewed research articles:

1. Explain how the theory adds or may add to our understanding of your field and/or research topic.

2. Discuss and analyze the literature on two areas of controversy or unanswered questions related to the theory

Introduction
In this paper, the theoretical frameworks for reliability engineering research are discussed. In the paper the nature and types of theories as well as a comparison and contrasting views of what constitutes theory, including the views common in the field of reliability engineering, in introduced. The difference between theory and related concepts such as hypothesis, paradigm, model, and concepts are assessed. The conception of a theory and its relationship with research are also discussed. Quantitative and qualitative methods of research are explored, and their contributions to theory are assessed. The contributions, controversies, and gaps in the identified theory will also be analyzed .
Literature Review
According to Isac-Maniu (2010) reliability theory derived from the domain of demography and adapted the main idea used there, specifically the rate of mortality, which is the ratio between the number of deceased persons and the number of survivors at the same time. According to Isaic-Maniu (2010) in reliability concept when the death rate becomes the hazard or failure rate, where the persons (living beings) are replaced by objects such as components, subassemblies of a system. Reliability theory explains failure in three different regions, such as infant mortality, useful life, and wear out failures. These three regions define the bathtub curve of reliability. Roesch (2014) modeled bathtub curve to measure failures in each section.
Isaic-Maniu (2010) explained reliability as product failure due to a product, a process, and a service to experience undesired conditions when the intended function are not performed safely and cost effectively. However, reliability functions decrease over time due to wear out. According to Isaic-Maniu, reliability functions decrease so that the reliability of item will diminish overt time. In contrast, reliability can be explained as a means for improving the state-of-the-art in the field, having in mind that nothing is perfect, and that the difference between an unreliable product and a robust one is “merely” in the level of the never-zero probability of failure (Suhir, 2014)
Reliability is to ensure product performance for an intended period without failure. Thaduri, Verma, Gopika, Gopinath, and Kumar (2014) argued that traditional reliability with constant failure modes and process no longer provides accurate time to failure. The failure characteristics must consider the physics of failure. Thaduri et al. explained that the physics of failure characterizes the nature of the failure. Whereas Ma, He, and Wu (2014
) argued that the current reliability process is mainly focused on product design and does not have a good knowledge of reliability assurance in the manufacturing process, thus the reliability process must include manufacturing. Reliability deals with all aspects of the process of failure, trying to construct formulaic–mathematical models for this random phenomenon (Isaic-Maniu, 2010).
System reliability growth (improvement) prediction focuses on overall system reliability but lacks clear methodology to accurately estimate the warranty life of critical components. Vervenne and Deconinck (2011) proposed a new method of predicting system reliability beginning with the determination of the single point component(s) critical to system reliability. Whereas, Wei,Lin, Luo, Yang, and Konson (2014) developed a method to predict system reliability of multiple components and their interactions .
Discussion/Findings
Investigating various complex phenomena allows researchers to explain and predict events. This analysis will examine findings related to research and theory, research contributions to theory, and reliability theory.
What Constitutes Theory
A theory is a hypothesis developed to test the relationships among variables to provide logical explanations. A theory should explain why the variables or constructs are expected to relate to or influence one another (Gelso, 2006). According to Gelso (2006), some theories are never disproved nor fully confirmed. There is a misunderstanding about what constitutes a theory (Gelso, 2006), because the term theory has several meanings (Harlow, 2009). In essence, then, “a theory is a statement of the suspected relationship between and among variables” (Gelso, 2006, p. 2). Corley and Gioia (2011) described theory as a declaration of ideas showing interrelations between those ideas that provided the clarifications about how and why such a phenomenon occurred.
According to Corley and Gioia (2011) it becomes obvious that researcher should conduct a more open dialogue between practitioner and theoretical contributions that both derive from and inform practice. Whereas Stam (2010) noted that theory as a systematic representation of a valid problem expressed, mathematically, scientifically in logically manners. However, Geslo (2006) clarified how the terms theory and theoretical proposition may be distinguished from the term hypothesis. According to Gelso (2006) though there are no outright differences theories contain theoretical propositions, whereas hypotheses are derived from these propositions (Gelso, 2006). Hypotheses tend to be more specific than the propositions, directly tested in empirical research (Gelso, 2006). Wacker (1998) described theory as a combination of variables and predations.
According to Corley & Gioia (2011) theory is more pertinent to solving significant societal problems, contributing a theoretical contribution that is critical not only researcher to researcher communications but one with greater opportunity and prospect to influence current and future organizational practice. Harlow (2009) stated that case studies either test a particular theory, develop theory, or both and “developing theory inevitably involves an element of testing, and, therefore, the two are interlinked” (p. 237). It is by means of this process that a theoretical contribution might be made (Harlow, 2009).
A paradigm begins with a novel solution to an outstanding problem, or anomaly created but not resolved by the dominant normal scientific practice in a field up to that point (Doppelt, 2014). The solution is novel because it breaks with the concepts, ontology, methods and standards that have previously defined inquiry (Doppelt, 2014). The paradigm implicitly generates the norms a group uses to identify what counts as a legitimate or significant problem and an acceptable solution, based on the common way members of the group read the novel problem–solution, which they seek to replicate, extend, and articulate to solve similar problems (Doppelt, 20144 )
The Relationship between Research and Theory
Research depends on theory. Theory provides insight into why and how research needs to be conducted. According to Harlow (2009), research begins with a review of the relevant literature; through the literature the researcher will engage with the existing theoretical explanation of the topic in question. Theory needs to be tested for viability prior to exploration. With the exploration of the current strengths and limitations of explanations, the theoretical approach to be tested or developed can be identified (Harlow, 2009). According Harlow (2009) the theory and construct to be tested or developed will inform the choice of problem or problems to be studied, the data to be collected, the methods by which the research is designed to collect data, as well as the way the data will be analyzed and communicated. The research project will conclude by discussing the original research question in light of the theory and the empirical evidence gathered (Harlow, 2009).
Research approach must follow inductive or deductive reasoning. According to Harlow (2009), researchers must apply a process of deductive and inductive reasoning. Although often thought of as separate, it has been argued that, in case study research, the two processes are blurred and mutually beneficial (Harlow, 2009). Likewise, it has been argued that theory testing and theory development are inevitably associated and that the interplay of both is implicated (Harlow, 2009). Harlow stated that the reproduction process is a noble approach defining this relationship because it provides a means by which the researcher tests his or her theoretical ideas against the emerging data, reframes the ideas, and retests until the conclusions reached are deemed reliable .
A researcher must understand the nature of the research and the method to follow before conducting research. The theory provides the direction; the why and how research should be conducted. The research inquiry must begin with questions. According to Ellis and Levy (2008) the nature of research design and methodology applied must be correct for the type of the problem leading the research; thus, the methodology produces the results of the study, which in turn produces the evidences required to validate the conclusions recommended. According to Sharma (2014) a case study method of research using inductive or deductive methods of reasoning to test and formulate a theory
According to Wacker (1998), a theory is a set of conceptual relationships between ideas. However, Ellis and Levy (2008) viewed theory as structured idea that integrates a number of unique, but linked elements, including the research problem that leads the study, the purpose, and research questions, review of the literature, research design and mythology, findings, and conclusions. Qiu, Donaldson, and Luo (2014) argued theories come and go, but methodologies tend to remain constant, and only gradually evolve, such as the increase in sophistication of statistical methods over the last 4 decades, they may change more slowly than the beliefs of some researchers in fundamental theories.
Analyzing previous research contributes to theory. For example, Smith, Gonin, and Besharov (2014) conducted research on how institutional theory informs our understanding of public impacts on social-business tensions and their management by analyzing existing research on tensions in social enterprises. Theories recommend leads to the identification of important subject areas, which require further research. Avgerou (2013) argued that research tends to form explanations by refining concepts of the researchers’ chosen theories of action and empirically deriving insights that enrich and adjust the foundational concepts, but do not add new explanation propositions beyond those suggested by the concepts of the general theoretical framing of the research.
Research contributes to a theory by reviewing previous literatures. Research must involve a literature review before conducting research. For example, Alvesson and Sandberg (2011) indicated that high-quality, qualitative, inductive research must involve not only reviewing the literature to illustrate gaps in prior research, but also explaining why it is important to fill the gap. Qualitative and quantitative research is organized in a logical way, so their contribution to theory is clearly understood. For example Palmatier, Houston, Dant, and Grewal (2014) explained how theory of relationship dynamics contributed to the theory and practice of relationships in marketing through theoretical and empirical foundations to form a dynamic model.
Research contributes to theory if structured in logical methods. For example, Parris and Peachey (2014) explored research studies that have examined servant leadership theory in a given organizational setting and found they validated servant leadership as a viable and valuable theory, illustrating how servant leadership theory can be used to inform future empirical studies. According to Ellis and Levy (2008) an effective research must include a structure that incorporates a number of specific requirements such as the research questions lead the investigation , the purpose , previous work review, findings, and recommendation for future research.
Research is credible if it links the new theory to the old theory. Researchers readily find the new theory credible, because they are already intellectually committed to its core elements in the old context and simply shift their commitment to a new context (Qiu et al., 2014). While the new and old theories share the same core, they are different enough that paradigm extension involves more change than paradigm continuity or paradigm elaboration (Qiu et al., 2014). Quantitative and qualitative research can contribute to theory in different ways. Both research methodologies follow different structures and designs to inform new theory. The new theory is based on research findings. Results from research findings generate new constructs or theory for future exploration. According Hassard, Wolfram Cox and Rowlinson, (2014) the deterioration of one theoretical domain and rise of another can be linked in terms of the research program being followed, for the process of change may propose not necessarily the demise of one theory and dawn of another but more integration of the current idea .
Theory Adds to Understanding of Research
According to Ansari and Bell (2009), the activities of the researcher add to the body of existing theoretical understanding with observed results because the action researcher not only detects what is happening in the actual world, but also contributes in actions to achieve the anticipated objective. Product reliability and warranty are the two related variables. According to Chu and Chintagunta (2011), the key assumptions of signaling theory are information asymmetry in the sense that vendors have better knowledge about product reliability than consumers, warranties are costly to the vendor, and costs are systematically related to product reliability. This research topic is to examine the impact of reliability growth on warranty cost.
Reliability improvement (growth) and warranty are interrelated. Traditional system reliability growth prediction focuses on overall system reliability, but lacks clear methodology to accurately predict the reliability of critical components. Vervenne and Deconinck (2011) found that the current uses of prediction standards to determine the reliability of a system are not sufficient, particularly when key component reliability is measured. The lack of accurate failure prediction impacts warranty cost. Garg and Sharma (2014) argued that if a failure occurs frequently, then the manufacturer loses enormous capital due to an unreliable product.
Key components reliability improvement is measured before and after design improvement is implemented. According to Pavasson, Cronholm, Strand and Karlberg (2014) the likelihood of predicting the reliability of hardware for both components and systems is important in product development. The component importance measure concept has been extensively used in reliability engineering to quantify the criticality of a particular component within a system design (Zhang, Ramirez-Marquez & Sanseverino, 2011). Zhang et al. noted that using the component importance measure one can assess or prioritize system elements in order of their importance with respect to system reliability.
The key component failures provide insight into how the system performs in the field. According to Li and Kapur (2014), the reliability of a component degrades over time resulting in continuous stochastic performance degradation. Benkamra, Terbeche, and Tlemcani (2014) argued in reliability engineering two crucial objectives are considered to maximize the estimate of system reliability and minimize the variance of the reliability estimate. According to Oestreicher (2011), products supporting the status quo most may increasingly fail, because there are not sufficient new customer experiences. Therefore, successful new products may reduce corporate efficiency development, since effectiveness will require really new products even quicker (Oestreicher, 2011).
The traditional probabilistic reliability measurement found to be ineffective due to lack of accurate prediction reliability growth during warranty period. This research may add to reliability growth theory by investigating the relation between reliability growth and warranty. Integrating probabilistic reliability prediction and true field data can accurately predict the impact of reliability growth on warranty. Findings from this research will further expand reliability growth management theory and contribute to the research within the field of product reliability .
Unanswered Questions
There are some controversies and unanswered questions related to probabilistic reliability theory. Reliability theory using probabilistic measures may provide a sound theoretical basis for studying reliability growth. Zeng, Wen, Kang (2014), however, noted that traditional reliability metrics have limitations because of their probabilistic nature. In engineering practices, failure data are often so scarce that traditional metrics cannot be obtained and furthermore, in many applications, premises of applying these metrics are violated frequently (Zeng et al., 2014). However, Zhu and Kuo (2014) emphasized the importance of reliability based probabilistic measurement
According to Garg and Sharma (2014) estimating and predicting the likelihood of the failure and improving the operational management must be related with the provision of the failures related with maintaining strategies. If the failure occurs repeatedly, then the company loses revenue due to low production rates and product recall (Garg &Sharma, 2014). On the other hand, the occurrence of failure is expected, implying that the equipment will fail sooner or later (Garg &Sharma, 2012). Identifying product failure and implementing long-term solutions can improve reliability (reliability growth). The only way to avoid or minimize the inconvenient impact of unreliability is to increase both reliability and maintainability of the production system (Garg &Sharma, 2014). Unanswered questions related to the current reliability theory are how to effectively apply reliability growth to predict failure and warranty costs. According to Garg and Sharma (2014), there are unanswered questions related to the optimal value of various reliability initiatives, which provide optimum system performance, low manufacturing and repair costs.
These unanswered questions make it difficult to close the gap between reliability growth and warranty. These unanswered questions resulted inaccurate product life cycle cost predication during warranty period. The rapidly increasing pace and continuously evolving reliability requirements of new products have made life cycle reliability assessment of new products an imperative, yet difficult work (Peng, Huang, Li, Zuo, & Xie, 2013). Peng et al. (2013) argued that while much work has been done to separately estimate reliability of new products in specific stages, a gap exists in carrying out life cycle reliability assessment throughout all life cycle stages. The lack of accurate prediction of product life cycle cost during warranty period can lead to revenue loss to manufacture and high down time consumers.
Recommendation
The gap between reliability growth and product warranty prediction can increase the cost of ownership. It is essential to investigate the relationship between reliability growth and warranty. Reliability growth affects product life cycle costs during the warranty period. The challenges of reducing product cycle costs and failure rates are enormous to maintain profitability and higher customer satisfaction. Higher reliability designed into a product is perceived as a competitive advantage because reliability contributes to reduced product life cycle costs during the warranty period. Understanding the relationship between reliability growth will further expand to the reliability theory and can provide practical insights about warranty prediction.
Conclusion
Reliability growth is part of the product reliability assessment process, which focuses on the removal of product failures. Reliability improvement (growth) reduces warranty costs and product life cycle costs. The elimination of product failures during warranty provides guarantees to users. This research contributes to reliability theory in the field of reliability growth management by identifying the relationship between reliability growth management and warranty cost. Knowledge from this research may lead to the definition of reliability improvement projects aimed at reducing product life cycle costs during the warranty period.

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