Multilevel Research

1. Multilevel Research 黃品全講授 本講義為 Mark Gavin 所撰

2. Bringing Attention to Multilevel Research • Calls for increased development and testing of multilevel theory (e.g., Hackman, 2003; House, Rousseau, & Thomas-Hunt, 1995; Klein, Dansereau, & Hall, 1994; Klein & Kozlowski, 2000a, 2000b; Rousseau, 1985) • Progress has been stunted by lack of tight theorizing and methodological and analytical problems

3. Overview of Workshop • Theoretical Issues • Methodological Issues • Analytical Issues

4. Theoretical Issues • Typology of multiple level models • Typology of higher-level constructs • The need for multilevel research (preliminary statistical issues)

5. Hierarchical Data Structures Hierarchical nature of organizations • Individuals nested in work groups • Work groups nested in departments • Departments nested in organizations • Organizations nested in industries/environments

6. Hierarchical Data Structures Constructs at different levels • Individuals • Work groups • Departments • Organizations • Industries/Environments

7. Caveat Workshop terminology usage: Discussion based on context of individuals nested within groups Terms used generically Individual = lower-level unit Group = higher-level unit

8. Two types of Multiple Level Models Borrowing from Rousseau’s (1985) typology • Composition model • Cross-level models

9. Single-level Model X Y Concerns the relationship between two constructs residing at the same level

10. Examples of Single-level Models • Individual attitudes influencing job performance • Group cohesion influencing group performance • Organizational structure characteristics influencing organizational performance

11. Composition Model X2 X1 Concerns the relationship between two (presumably) similar constructs residing at different levels where X2 is derived from X1 *Subscripts denote levels where 1 = individual level and 2= group level

12. Composition Model • Provides mechanism linking lower-level and higher-level constructs Examples of linking mechanisms*: • Leadership theories • Social information processing • Attraction-selection-attrition • Considers the form of the relationship • Isomorphism • Partial functional identity or fuzzy composition *These play a role beyond composition models by helping us understand why we observe similarity within groups

13. Isomorphism vs. Fuzzy Composition • Isomorphism (e.g., Rousseau, 1985) Specifies that the lower-level variable and its aggregate are conceptually and functionally identical • Partial functional identity (e.g., Rousseau, 1985) or fuzzy composition models (Bliese, 2000) • Specifies that the aggregate captures something conceptually and functionally different than its lower-level counterpart, even if we call them by the same name, largely because they pick up and carry contextual influences

14. Examples of Composition Models • Individual mood and group affective tone (George, 1990) • Psychological/Organizational climate (James, 1982; James, James & Ashe, 1990) • Individual/Organizational learning We’ll come back to composition models shortly

15. G G or X Y X Y Cross-level Models Cross-level main effect Cross-level moderation Concerns the influence of a higher-level variable on 1) a lower-level outcome or 2) the relationship between two lower-level variables *X and Y are individual-level variables and G is a group-level variable

16. Examples of Cross-level Models • Cross-level Main Effect • Climate research where organizational characteristics influence individual (shared) perceptions (and subsequently behavior) • Cross-level Moderation • Leadership climate moderates the relationship between task significance and hostility incidents (Gavin and Hofmann, 2002) • Cohesion moderates the relationship between satisfaction and OCBs (Kidwell, Mossholder & Bennett, 1997)

17. Types of Group-level Constructs • Global • Selected score • Additive • Direct consensus • Referent-shift consensus • Dispersion

18. Global constructs • These belong to the group and have no lower-level counterparts • They are NOT derived by aggregating individual variables/responses • Examples: group size, group structure

19. Selected Score Constructs • These originate with the individual and emerge to characterize the group • Relevant where, typically, members at the extreme place constraints on the group • The relevant individual’s score then represents the group • Examples: individual ability in certain task environments, individual personality in certain work settings, CEO tenure

20. Additive Constructs • These originate with the individual group members and emerge to characterize the group • They are derived by aggregating individual scores • The aggregate carries no particular meaning beyond a simple statistical summation of individual characteristics • Examples: unit sales as derived by summing individual sales, group expertise as a summing of individual member tenure

21. Direct Consensus Constructs • These originate with individual group members and emerge to characterize the group • They are derived by aggregating individual scores • They take on meaning when members share their individual characteristics or perceptions • Examples: group affective tone (George, 1990), psychological climate (James, 1982)

22. Referent-shift Consensus Constructs • These originate with the group (though they typically have meaningful individual-level counterparts) but emerge within the group setting • They are derived by aggregating individual scores • They take on meaning when members share in their perceptions of the group characteristic • Examples: collective efficacy, team empowerment

23. Dispersion Constructs • These originate with the individual group members and emerge to characterize the group • At the group level, these index variability or distributional properties of individual characteristics or scores within the group • They do NOT require similarity among group members – rather they often stress dissimilarity • Examples: demographic diversity, climate strength

24. Issues with Construct Types • Only theory can determine which type a given construct fits • Depending on the theory, the same variable could fit into different types (e.g., group ability could be defined by a select score model, an additive model, a dispersion model, or …)