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Part 1

  1. 1. Research Methods for Organizational Studies - 2ed, 2004 LIU YING copyrightⓒ 2013 All rights reserved by LIU YING 1
  2. 2. 1. Introduction • Research Activities • A Point of View • Objectives and Organization • Summary • For Review • Terms to Know copyrightⓒ 2013 All rights reserved by LIU YING 2
  3. 3. Consider these courses of action: • An elementary school principal establishes a set of difficult teacher goals to improve students' academic performance. • A medical director has staff members make suggestions anonymously to encourage participation. • A company president joins an alliance with other firms in the industry to improve returns from research and development expenditures. • Parents take their children to a concert to stimulate an interest in music. • A union leader calls for a strike vote to increase members' solidarity. • A basketball coach has team members take dancing lessons to improve agility. • A director of marketing recommends that a product be renamed, repackaged, and increased in price to attract more affluent customers. • A captain in the Salvation Army posts names of the bell ringers who obtain the greatest contributions each day to encourage bell ringer solicitations. • A human resource manager proposes a flexible benefit plan to reduce employee turnover. copyrightⓒ 2013 All rights reserved by LIU YING 3
  4. 4. • Each of the expected relationships is causal. In causal relationships one factor influences another. copyrightⓒ 2013 All rights reserved by LIU YING 4
  5. 5. • Empirical research can help obtain evidence on the veracity of expected causal relationships of the type described here. Empirical research addresses expected relationships through the systematic study of relationships between scores obtained from cases on measures. • Cases are the entities investigated in research. • Measures are instruments used to obtain scores on the cases studied. • scores (or data) represent information obtained from cases on the measures used. Typically, scores are recorded in numerical form. Researchers use these scores to identify whether relationships exist as expected. copyrightⓒ 2013 All rights reserved by LIU YING 5
  6. 6. copyrightⓒ 2013 All rights reserved by LIU YING 6
  7. 7. Research Activities • The scenario described indicates that empirical research involves three activities: measurement, design, and analysis. Measurement involves activities associated with measuring the factors that form the expected relationship. • Research design establishes procedures to obtain cases for study and to determine how scores will be obtained from those cases. • Empirical research also involves analyses of scores. Analyses are performed to describe scores on single measures and, especially, to identify relationships that may exist between scores across different measures. copyrightⓒ 2013 All rights reserved by LIU YING 7
  8. 8. Research Activities The lines linking the three research activities signal two things. • First, they signal that these research activities are related in practice. • Second, they signal that knowledge of any one research activity is helpful in learning about the other activities. copyrightⓒ 2013 All rights reserved by LIU YING 8
  9. 9. A Point of View • Research is sometimes described as a major tool of "the scientific method," and that method is described in terms so abstract as to be nearly incomprehensible. Research methods may then be seen as a mysterious set of practices that only a chosen few can accomplish, probably in cloistered laboratories. • This book is written with a less deferential view of research methods. Research methods are easily accessible. These methods do not differ qualitatively from our everyday practices of observing events and making sense of them. • This book takes the view that research methods have two advantages for obtaining knowledge and that these are only advantages when research is appropriately conducted and reported. • First, research methods properly conducted address questions systematically. • Second, research properly performed is a public process; it is transparent. • These are modest claims. Single research studies do not answer questions definitively. copyrightⓒ 2013 All rights reserved by LIU YING 9
  10. 10. Objectives and Organization • The book is written to help you acquire skills to conduct research with this view of research methods and outcomes in mind. The systematic nature of the research enterprise is emphasized. This applies to all three major research activities: measurement, design, and analysis. The book is organized into eight parts consistent with its viewpoint and objectives. • Part I includes this and the next chapter. Chapter 2 presents a model of the entire research enterprise. This model introduces research objectives and shows how measurement, design, and analysis contribute to knowledge generation. • Part II contains two chapters on measurement. These chapters describe measurement objectives and introduce criteria used to evaluate measures against these objectives. These chapters also describe measurement procedures commonly used in organizational studies. • Part III addresses research design. Chapter 5 identifies challenges for research design and identifies major decisions that researchers make when designing empirical research studies. The chapter also shows how these decisions affect conclusions that can appropriately be drawn from research studies. It concludes by introducing major types of designs that researchers use. Chapters 6 and 7 elaborate on these major design types. • Chapters in part IV focus on data analysis. Chapter 8 provides an overview of data analysis and introductory material on important characteristics of scores for analysis purposes. Chapter 9 describes methods for summarizing information about scores obtained from a single measure. These include statistics of central tendency, variability, and shape. Chapters 10 and 11 describe simple and multiple correlation and regression, respectively. These statistics provide useful ways to summarize relationships between scores from two or more measures. copyrightⓒ 2013 All rights reserved by LIU YING 10
  11. 11. Objectives and Organization • Part V has two chapters on the use of statistics and probability theory for drawing inferences that transcend the relations observed on scores. These statistical inferences are made to address causal relationships and to address whether a statistic observed on the group of cases studied likely applies in the broader population from which the sample group was drawn. Chapter 12 introduces the statistical inference process. Chapter 13 describes two methods for performing generalizations: hypothesis testing and confidence intervals. • Part VI has a chapter on other types of inferences researchers seek to make from their research. It discusses the important role of repeating research studies to obtain information on the likely generalizability of research findings. It also describes two methods that researchers use to make these sorts of generalizations: narrative reviews and meta-analysis. • Part VII contains a chapter on research report writing. Research reports have a special obligation to satisfy the second advantage of research mentioned earlier—namely, to provide a public record of the research for evaluation. Chapter 15 identifies the elements of research that should be included in a report to meet this obligation. • Part VIII contains six chapters that extend topics covered earlier in the book. The first three of these address incomplete data sets, a challenge facing nearly every empirical study; reliability, a challenge for nearly all measurement efforts; and mutlicollinearity, an analysis issue that typically confronts researchers in even moderately complex studies. Two chapters follow that draw on earlier chapters to show how researchers carry out research studies to address causal questions and the challenges they confront when doing so. Finally, the last chapter draws on all earlier chapters to suggest what makes for conducting a persuasive research study. This chapter also serves as a guide for evaluating whether research conducted by others is persuasive. copyrightⓒ 2013 All rights reserved by LIU YING 11
  12. 12. • Summary • For Review • Terms to Know copyrightⓒ 2013 All rights reserved by LIU YING 12
  13. 13. 2. A Model of Empirical Research • Research Variables – Conceptual and Operational Variables – Dependent and Independent Variables • The Model – Conceptual Relationships – Operational Relationships • Empirical Relationships • Causal Relationships at an Empirical Level – Conceptual to Operational Relationships • Generalizing from the Model – Statistical Generalization – External Generalization • Summary • For Review – Terms to Know – Things to Know – Issues to Discuss copyrightⓒ 2013 All rights reserved by LIU YING 13
  14. 14. Research Variables • Variables are characteristics of objects or events that can take on two or more values. Variables are central to research. Most research is concerned with relationships between variables. • Conceptual and Operational Variables – At this level of abstraction variables are called conceptual variables or constructs. Constructs are mental definitions of objects or events that can vary. – Empirical research activities are carried out at an operational level of abstraction. Empirical research obtains scores from cases on measures. These measures represent operational variables. • Dependent and Independent Variables – Dependent variables are outcomes or consequences; – Independent variables are those thought to influence or at least predict dependent variables. – Dependent variables typically are influenced by more than one independent variable. – Variables can be dependent in one context and independent in another. Researchers are usually interested in causation. In such research, the independent variable represents a cause; the dependent variable represents the consequence. However, independent and dependent variables are not necessarily causally linked. Independent variables may simply predict dependent variables without causal linkages. copyrightⓒ 2013 All rights reserved by LIU YING 14
  15. 15. The Model 1. Independent and dependent variables are identified by X and Y, respectively. 2. The symbol prime, ', is used to designate that a variable is specified at the conceptual level. 3. Arrows represent the direction of influence or cause. copyrightⓒ 2013 All rights reserved by LIU YING 15
  16. 16. The Model • Conceptual Relationships • Operational Relationships – Empirical Relationships – Causal Relationships at an Empirical Level • Conceptual to Operational Relationships copyrightⓒ 2013 All rights reserved by LIU YING 16
  17. 17. Conceptual Relationships • A causal conceptual relationship describes a situation in which an independent construct is thought to influence a dependent construct. • Researchers usually have an expectation about this relationship before conducting a study. In research, such expectations are called hypotheses, tentative beliefs about relationships between variables. Research is done to obtain information about whether the hypothesized relationship is valid. copyrightⓒ 2013 All rights reserved by LIU YING 17
  18. 18. Operational Relationships • Empirical Relationships An Empirical Relationship, represented by line (d), refers to the correspondence between scores on measures of X and Y. Line (d) is solid to signal that this relationship can actually be observed, typically by using some statistical procedure (see part IV). • Causal Relationships at an Empirical Level – Internal validity is present when variation in scores on a measure of an independent variable is responsible for variation in scores on a measure of a dependent variable. copyrightⓒ 2013 All rights reserved by LIU YING 18
  19. 19. Causal Relationships at an Empirical Level copyrightⓒ 2013 All rights reserved by LIU YING 19
  20. 20. Causal Relationships at an Empirical Level • Line (c), as (a), is broken, because internal validity cannot be established with certainty. Internal validation procedures (see part III) are used to infer internal validity indirectly. – The first criterion states that a relationship must be observed between scores on measures of X and Y. Although not sufficient, an empirical relationship is necessary for causation. – The second criterion follows from a linear time perspective. It is based on an assumption that things occurring later in time are not responsible for those occurring earlier. A causal (independent) variable occurs before a consequence (dependent) variable. – The third criterion has two parts. First, it requires that there is a reasonable conceptual explanation for why X causes Y. Researchers often use theory to help them in this process. A theory provides a tentative explanation for why a causal relationship(s) obtains (see Research Highlight 2.1). copyrightⓒ 2013 All rights reserved by LIU YING 20
  21. 21. Conceptual to Operational Relationships • Conceptual validity requires that activities conducted at the operational level be linked to the conceptual level. This link depends on relationships between measures and their respective constructs; these are represented by lines (b1) and (b2) in Exhibit 2.2. • The construct X' is measured by the set of operations X; the construct Y' is measured by the set of operations Y. Construct validity is present when there is a high correspondence between the scores obtained on a measure and the mental definition of the construct it is designed to represent. Lines (b1) and (b2) are also broken to show that construct validity is also tentative. copyrightⓒ 2013 All rights reserved by LIU YING 21
  22. 22. Construct validation • Construct validation (see part II) involves procedures researchers use to develop measures and to make inferences about a measure's construct validity. copyrightⓒ 2013 All rights reserved by LIU YING STEP 1 • Define the construct and develop conceptual meaning for it STEP 2 • Develop/choose a measure consi stent with the definition STEP 3 • Perform logical analyses and emp irical tests to determine if observat ions obtained on the measure co nform to the conceptual definition 22
  23. 23. Generalizing from the Model • Statistical Generalization • External Generalization copyrightⓒ 2013 All rights reserved by LIU YING 23
  24. 24. Statistical Generalization Researchers have two methods to obtain validity evidence about research generalization. One, statistical validation (see part V), uses probability theory to generalize a relationship observed on a sample of cases to the relationship that applies to the broader population from which the sample was drawn. Statistical generalization validity is obtained when the empirical relationship observed on a sample of cases validly estimates the relationship in the population of cases from which the sample was drawn. (Statistical validation relies on probability theory for both internal and statistical generalization validity.) copyrightⓒ 2013 All rights reserved by LIU YING 24
  25. 25. Statistical Generalization copyrightⓒ 2013 All rights reserved by LIU YING 25
  26. 26. External Generalization • External validation (see part VI) refers to procedures researchers use to investigate all other types of research generalization. External validity is present when generalizations of findings obtained in a research study, other than statistical generalization, are made appropriately. Exhibit 2.6 provides examples of external generalization. Substantial progress has been made in methods to address external generalization during the last three decades. This external validation technology usually goes by the name meta-analysis. Meta-analysis is a research procedure designed to provide quantitative estimates of the generalizability of relationships across studies. copyrightⓒ 2013 All rights reserved by LIU YING 26
  27. 27. • Summary • For Review – Terms to Know – Things to Know – Issues to Discuss copyrightⓒ 2013 All rights reserved by LIU YING 27

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