Numbers Can Restrict Results?: Qualitative Research Methods as Information and Knowledge Management Support in Supply Chain and Logistics Sectors

Numbers Can Restrict Results?: Qualitative Research Methods as Information and Knowledge Management Support in Supply Chain and Logistics Sectors

George Leal Jamil (InescTec, Portugal)
DOI: 10.4018/978-1-5225-0973-8.ch001
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Abstract

This chapter intends to evaluate how mixed researches are significant knowledge producers for business management. A discussion is conducted about the trade-off around the success and restrictions offered by the dominance of quantitative methods, especially when there is interest to study supply management and logistics. Quantitative methods are essential for any kind of management, but, as more dynamics in market competition produces more complex scenarios, qualitative answers are needed, along its approaches to formulate new questions that will help organizational decision-makers to apply knowledge for their planning activities. This chapter will explore three main points: 1) how the excessive concentration on quantitative methods can restrict managerial views; 2) how any organization can apply qualitative methods to enrich results observed from quantitative, resulting in better, more sustainable decisions; and 3) how qualitative and quantitative methods, associated, can implement this approach in real cases, with an overview of mixed scientific research methodologies.
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Introduction

The main theme of this book produces a rich context for this study: Supply chain, Logistics and information management are, as a matter of fact, cooperative contexts where information and knowledge emerge every second. Facts as the massive production of data in every transaction, entrepreneurial chains being formed dynamically and the intensive application of information technology resources, frequently impact business operations. This way, old, established research and managerial methods must be continuously reviewed and a new scenario descriptions produced, allowing new fronts of knowledge application for understanding, comprehension and problem-solving. It is possible to consider that production, operations and innovation management are among different and relevant paths where this intensively generated data, information and knowledge can produce immediate results that, unavoidably, will potentially lead to another level of organizational maturity (Bowersox, Closs & Cooper, 2002; Akbar, 2003).

Supporting such initial attractiveness for continuous learning, business-oriented scientific methodologies are the real pillars where such valuable contents can always be supplied. But, with a worrying frequency, these methods are neglected, mostly due to the fast market dynamics, where produced results should be immediately applied, without the needed reflection or scientific criteria. This sense of instantaneous need for decisions, along with precarious level for decisions implementations, are the main motivations to propose this study. In this chapter, our main objective is to observe how some of information and knowledge management practices can be applied with a better combination of quantitative and qualitative research methods, observing specially the context of supply chain and logistics operations (Babbie, 1990; Bowersox, Closs & Cooper, 2002; Chen, Long & Yan, 2004; Creswell, 2013).

It is opportune to select the area or service of supply chain and logistics because, firstly, it is, remarkable, complex, fast-moving and competitive sector which, at a first glance, potentially produces immense volumes of numeric, quantitative results (Bowersox, Closs & Cooper, 2002; Ballou, 2003). It also unfolds in managerial cultural aspects, as executives are trained to work mainly applying numbers in typical decisions, and, because of this fact, dedicate also more attention to processes and methods which focuses the generation, analysis and reports of quantitative results. Some of these results are, nowadays, considered classical methods, topics, themes and services that constitute “a must” for software projects and products, consulting services and almost all knowledge production for these sectors, leading to a situation where it is regarded to be as the only source of structured knowledge (Leidner & Elam, 1995; Bowersox, Closs & Cooper, 2002; Golicic & Davis, 2012; Jamil et al, 2012, Bazeley, 2015).

Key Terms in this Chapter

Quantitative Methods: Set of research methods techniques which mainly collect and process numeric values, resulting in precise, objective, quantitative results.

Supply Chain: Set of activities which implements logistics specifications, goals and definitions, using calculation methods and technological resources, as information technology, for example.

Information Management: A process focused on information production, generation, collection, sharing and application towards knowledge production.

Logistics: Set of activities related to top-level management decisions regarding strategic planning of supply chain issues, defining its strategic effective positioning.

Knowledge Management: A process designed to produce and apply knowledge in one organization, involving activities such as creation, collection, sharing, valuation, strategic application, among others.

Research Methodologies: Set of techniques applied to conduct researches, which may result in answers to a proposed research topic. It encompasses methodological techniques and tools, which guide practical specifications of questionnaires, investigations, interviews, observational exams and other application issues.

Qualitative Methods: Set of research methods techniques which are applied in order to generate textual, symbolic, parametric and several other non-numerical answers, encompassing interviews, opinions, group focus activities, etc.

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