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Network Exchange: Power, Emotion, and Commitment Amy R. Baxter The University of Maryland – College Park. ABSTRACT
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Network Exchange: Power, Emotion, and Commitment Amy R. Baxter The University of Maryland – College Park ABSTRACT Network Exchange Theory is "a formal theory of power--- a structurally determined potential for obtaining relatively favorable resource levels in exchange networks” (Markovsky, Willer, and Patton 1988). Exchange networks are composed of lines of power advancing outward from each network position. INTRODUCTION The researchers are testing a conclusion that says when people are in an exchange network, the exchanges themselves produce positive emotion and commitment to the network. The researchers hypothesize that whether or not resources are distributed equitably effects the emotions and commitments of people in the network (Lawler and Yoon 1998). We think that when we control for earnings and frequency of exchange, someone being in a powerful position in the network will have the greatest effect on their commitment to the network and their emotions associated with the network. RESULTS (cont.) 2 line: A-B 3 line: A-B-C 4 line: A-B-C-D 5 line: A-B-C-D-E 6 line: A-B-C-D-E-F 7 box-tail: A ------ D-E-F-G \ / B-C 7 line: A-B-C-D-E-F-G COMMITMENT AND EMOTION (0.00676) (0.00717) (0.0101) (0.0107) _______________________________________________________________________________________ Commit Commit Posemot1 Posemot1 _______________________________________________________________________________________ MONEY 0.00872 0.00850 0.0248* 0.0265* LOW OR HIGH 0.488*** 0.482** 0.128 0.175 (0.129) (0.143) (0.193) (0.214) TIMES INCLUDED 0.000711 -0.00551 (0.00721) (0.0108) CONSTANT -0.829*** -0.853** -0.581** -0.398 (0.132) (0.273) (0.197) (0.409) ________________________________________________________________________________________ OBSERVATIONS 115 115 115 115 ADJUSTED r2 0.303 0.296 0.134 0.128 ________________________________________________________________________________________ Standard errors in parentheses * p<0.05, ** p<0.01, *** p<0.001 Figure 2 Figure 1 Models Ŷ (commitment)=βhat0+ βhat1(earnings)+ βhat2(power) Ŷ (commitment)=βhat0+ βhat1(earnings)+ βhat2(frqxchng)+ βhat3(power) Ŷ (positive emotion)=βhat0+ βhat1(earnings)+ βhat2(power) Ŷ (positive emotion)=βhat0+ βhat1(earnings)+ βhat2(frqxchng)+ βhat3(power) METHODS The data was gathered in an experimental setting that facilitated network exchange. I will analyze the data using regression analysis. Figure 4 • CONCLUSIONS • 11-cis Retinyl Ester Hydrolase (REH) activity is expressed in the membrane fraction of cultured human retinal pigment epithelial cells, ARPE 19; • Our data demonstrate that ARPE 19 has properties (i.e. 11-cis REH activity) similar to freshly isolated RPE cells; • Therefore, ARPE 19 has functional properties appropriate for in vitro studies of visual cycle physiology of the RPE. • 11-cis Retinyl Ester Hydrolase (REH) activity is expressed in the membrane fraction of cultured human retinal pigment epithelial cells, ARPE 19; • Our data demonstrate that ARPE 19 has properties (i.e. 11-cis REH activity) similar to freshly isolated RPE cells; • Therefore, ARPE 19 has functional properties appropriate for in vitro studies of visual cycle physiology of the RPE. HYPOTHESIS More powerful positions in the network will (a) have more positive emotion and (b) more commitment to network than less powerful positions in the network, controlling for earnings and frequency of exchange. DATA The data I am using is from an experimental study conducted to test aspects of network exchange on the emotions and commitments of individuals in the network. The individuals were placed in networks of exchange of between 2 and 7 people with either weak ,strong, high or low power. The number indicates the number of positions in the network and line or box indicates the type of network. When exchanging in a network, individuals must decide how to split up a floating pool of resources (in this case money). There is money inbetween each position in the network and if the participants cannot come to an agreement and make an exchange, the money is taken away. Each person can only exchange with one partner in each round. I'll use the example of a 5 line network. If person B decides to exchange with person C, person A loses out and is left with no money. We see then, that because person B will never be left out of an exchange, person B has much more power than person A and slightly more power than person C. Person C can exchange with person D if B exchanges with person A. Person C will be left with no money if person B exchanges with person A and person D exchanges with person E. Therefore, the most powerful positions in the network are position B and D, then C and lastly, A and E. n=233 Figure 3 REFERENCES Lucas, Jeffrew W., C. Wesley Younts, Michael J. Lovaglia, Barry Markovsky. 2001. "Lines of Power in Exchange Networks." Social Forces 80(1):185-214. Lawler, Edward J. and Jeongkoo Yoon. 1998. "Network Structure and Emotion in Exchange Relations." American Sociological Review 63:871-894. Special thanks to MMMM Laboratories
