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30 August 2010, Volume 42 Issue 08 Previous Issue    Next Issue

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Integrative Model or the Priority Heuristic? A Test from the Point of View of the Equate-to-Differentiate Model WANG Zuo-Jun,OU Chuang-Wei,LI Shu 2010, 42 (08):  821-833.  Abstract ( 1822 )   Theories intended to describe decision making under risk and uncertainty can be classified as two families according to their theoretical basis: the integrative model and heuristic model. The integrative model postulates that the decision maker is both willing and able to combine information from different dimensions through two fundamental processes: weighting and summing. The heuristic model assumes that people do not integrate these kinds of information but rely on a repertoire of simple decision strategies—called heuristics—to make inferences, choices, estimations, and other decisions. A total of four experiments were conducted to compare these two sets of competing models from the view of the equate-to-differentiate model (Li, 1994, 2004a, 2004b) by using a response time approach. Experiment 1 re-examined the priority heuristic by using the decision questions employed by Brandstatter, Gigerenzer and Hertwig (2006), but failed to duplicate their results. The priority heuristic predicted that the increase of reasons (steps) required would be associated with the increase of time for making a choice. Experiment 2 tested the priority heuristic by manipulating the number of reasons (steps) assumed by the priority heuristic and the difference between two options on the best-outcome/worst-outcome dimension assumed by the equate-to- differentiate model. It was revealed that the decision time did not increase with the increasing number of reasons (steps) assumed by the priority heuristic but decreased with the increased difference between two options on the best-outcome/worst-outcome dimension. These results obtained in Experiments 1 and 2 were not friendly to the priority heuristic model. Experiments 3 and 4 were designed to test the integrative model. Experiment 3 tested the integrative model by comparing the decision time under risk and under ambiguity. Interestingly, the average decision time under risk was much longer than that under ambiguity. This was contrary to the implications of the integrative model because integrating an ambiguous probability with a given outcome will take longer time than integrating an exact probability with a given outcome to give an overall value or utility. Experiment 4 tested the integrative model by manipulating the difference between CPT (Cumulative Prospect Theory) values and the difference between two options on the best-outcome/worst-outcome dimension. The results showed that the decision time did not decrease with the increased difference between the CPT values but decreased with the increased difference between two options on the best-outcome/worst-outcome dimension, which were not consistent with integrative model but consistent with the equate-to-differentiate model. In sum, neither integrative model nor priority heuristic could help account for the data on choice process that we observed. Future work may focus on testing these two sets of models by employing methods which can provide a much richer description of the decision process than the response time approach employed in the present paper. Related Articles | Metrics

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The Role of Causal Models in Analogical Inference WANG Ting-Ting,MO Lei 2010, 42 (08):  834-844.  Abstract ( 1099 )   Analogical inference is important for academic tasks and daily life. There are two kinds of extant models, computational models and causal models, trying to explain the analogy process in different ways. Computational models of analogy assume that the strength of an inductive inference about the target is based directly on similarity of the analogs. In contrast, causal models suggest that analogical inference is also guided by causal models of the source and target. Lee and Holyoak (2008) reported that analogical inference appeared to be mediated by building and running a causal model. However, the causal model adopted in their materials was common-effect model, which was merely one kind of causal models. Causal models include cause-effect and effect-cause in the reasoning directions; unique cause-effect model, common-effect model, common-cause model, and multiple cause-effect model in the feature dimensions. More importantly, the common-effect model is significantly different from the common-cause model both in reasoning direction and reasoning difficulty. Then whether the results of Lee and Holyoak (2008) can represent all kinds of causal models? To answer this question, this research focused on the possibility that people make analogical inference by running causal models in cause-effect and effect-cause order, under the conditions of common-effect and common-cause feature structure. Two experiments were performed to investigate the possibility that people make analogical inference by running causal models. About fifty undergraduates were randomly selected to participate in each experiment. Participants were asked to read a description of imaginary animals in a booklet, and then evaluate the inductive strength of analogical inference. In experiment 1, participants were asked to make analogical inference in a cause-effect order under the conditions of common-effect and common-cause feature structure. In experiment 2, participants were asked to make analogical inference in an effect-cause order under the conditions of common-effect and common-cause feature structure. The results of experiment 1 showed that in cause-effect direction, participants used causal models to make analogy in common-effect feature structure, but used both causal models and computational models in common-cause feature structure. The results of experiment 2 showed that in effect-cause direction, participants used causal models to make analogy in both common-effect and common-cause feature structure. The present findings indicated that people could build and run causal models in both cause-effect order and effect-cause order to make analogical inference. When computational models and causal models competed with each other, people tended to use causal models in analogical inference; but if the two models didn’t compete, people tended to use both. Future work should be focused on building a more perfect model to explain the cognitive process of analogical inference. Related Articles | Metrics

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The Promoting Effect of Different Encoding Mode on Chinese Character Graphic Memory of Children with Spelling Difficulties YANG Shuang,NING Ning,PAN Yi-Zhong,SHI Wei-Xia 2010, 42 (08):  845-852.  Abstract ( 1329 )   Spelling difficulty (SD) is a kind of learning disorders. Children with SD have deficits in graphic memory. Because of the complexity in graphic representation, Chinese characters are difficult to be memorized only by visual encoding. Other encoding ways are needed to improve graphic memory. The aim of the present study is to investigate the influence of motor encoding and visual encoding to the graphic memory of children with SD. In the first experiment, effects of visual encoding and visual-motor encoding on graphic memory of children with SD and children without spelling difficulties (CNSD) were compared. First, participants were asked to learn a series of simple psudo-characters either in visual condition (only seeing the characters) or in visual-motor condition (tracing the character with finger while seeing the character). After a mental arithmetic task, their performances were tested by using a free recalling task. As a follow-up experiment, in experiment 2 we are going to investigate whether stroke phonetic encoding could help improve the effect of visual-motor encoding on graphic memory of children with SD. The procedure was the same as in Experiment 1, except that visual condition was changed into visual-motor-phoneme condition. In the new condition, participants were asked to learn the psudo-character together through seeing the character, tracing with finger and speaking out the pronunciation of every stroke. In experiment 1, 1) main effect of encoding mode and group were significant. Psudo-character memory performance of all participants under visual-motor condition was higher than under visual condition; and global performance of children with SD was poorer than children without SD. 2) Interaction between encoding mode and group was prominent. Visual-motor encoding can significantly improve recalling performance of children with SD, but have no significant effect for children without SD. In experiment 2, 1) main effect of group was not significant, and that of encoding mode was only marginal significant. The correct rate of graphic recalling under visual-motor-phoneme condition was slightly higher than under visual-motor condition. 2) Interaction between encoding mode and group was significant. Pronouncing the strokes didn’t significantly facilitate graphic recalling performance of children with SD, but prominently improved the performance of children without SD. In experiment 1, visual-motor encoding could improve the graphic recalling performance of children with SD. Motor tracing might induce children with SD to elaborately encode each character’s grapheme. Children without SD have intact visual encoding abilities; they could directly encode the subtle properties of grapheme, and form graphic representation of high quality. Hence, motor tracing had no significant facilitating effect for them. In experiment 2, phonological encoding of strokes can improve the graphic recalling performance of children without SD, but have no significant effect on that of children with SD. There might be three possible reasons. First, visual-motor-phoneme encoding task required participants to simultaneously encode the graphic and phonetic properties of strokes. However, the poor graphic-phonetic connections of children with SD blocked the facilitating effect of phonetic process on graphic process. Second, when participants were enforced to encode the graphic and phonetic characteristics simultaneously, children with SD would tend to ignore and inhibit the phonetic characteristics. This process needs mental resource, and may in turn interrupt graphic encoding process. Lastly, according to the phonological deficit hypothesis of spelling difficulties, children with SD may have deficit in phonological processing. Related Articles | Metrics

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The Association Between Rs1824024 Polymorphism in the CHRM2 Gene and Early Adolescents’ Depression WANG Mei-Ping,ZHANG Wen-Xin 2010, 42 (08):  853-861.  Abstract ( 1526 )   Depression is among the top five leading causes of disability and disease burden throughout the world. It is well established that depression often has its origins in childhood, and early adolescence is associated with a sharp increase in the prevalence. The mechanism underlying depression has been studied intensively during the last few decades. With the advancement of molecular genetics, a number of studies have been conducted in recent years to identify the candidate genes and investigate the gene-environment interactions related to depression. However, the extant research has mainly focused on serotoninergic and dopaminergic systems, muscarinic–cholinergic pathways have scarcely been investigated. Although several recent studies have investigated the association between the polymorphisms in the CHRM2 gene and depression, the findings have not been always consistent. Meanwhile, no research on the effect of interaction between CHRM2 polymorphism and environment was reported. Besides, whether there is a moderating effect of age on the association between CHRM2 polymorphism and depression remains to be examined. The present study aimed to examine the association between rs1824024 polymorphism in the CHRM2 gene and depression among Chinese early adolescents, with particular focus on the moderating effect of negative life events, gender and grade on the association. The subjects of this study were 127 grade 7-9 adolescents (male = 65, female = 62) of high depression group (n= 59) and lower depression group (n= 68). The subjects’ status of depression were identified via adolescent’s self-rating on the depression questionnaire (CES-D, a = 0.87) and further validated via teacher assessment. DNA was extracted from saliva, and genotype at rs1824024 was performed for each participant in real time with MassARRAY RT software version 3.0.0.4 and analyzed using the MassARRAY Typer software version 3.4 (Sequenom). Data analysis was performed using the Statistical Package for Social Sciences 17.0 (SPSS 17.0), and chi-square and logistic regression analyses were conducted to depression distributions. A marginal moderating effect of gender on the association between depression and rs1824024 polymorphism was observed, such that female adolescents with T alleles possessed a decreased risk of depression, but no significant association was found among males. A marginal moderating effect of negative life events on the association between rs1824024 polymorphism and depression was also found. Compared with adolescents carrying GG genotype, adolescents carrying T allele had a decreased risk of depression, but this difference only existed among adolescents reporting low level of negative life events. No moderating effect of grade on the association between rs1824024 polymorphism and depression was found. The present study lends further support for the theory that acetylcholine may play an important role in depression, and thereby contributes to CHRM2 gene-depression literature by elaborating the moderating effect of negative life events and gender among healthy early adolescents. Related Articles | Metrics

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Cognitive Representations, Behavioral Routines and Dynamic Capabilities in Collective Problem Solving WANG Jian-An,ZHANG Gang 2010, 42 (08):  862-874.  Abstract ( 1185 )   Since the concept of dynamic capabilities was first introduced by Teece and his collaborators (1997) many studies have been conducted to further clarify the concept and its underpinnings. Zollo and Winter (2002) defined a dynamic capability as “a learned and stable pattern of collective activity through which the organization systematically generates and modifies its operating routines in pursuit of improved effectiveness”. This definition distinguishes dynamic capabilities from operational capabilities, but suggests that, like operational capabilities, dynamic capabilities consist of patterned organizational behaviors, i.e. organizational behavioral routines. The question is that if so what the difference between them is. The present paper proposed that the stable pattern in and the determinant of dynamic capabilities were not behavioral routines but cognitive representations. Specifically speaking, on the one hand proper cognitive representations contributed to the improvement of dynamic capabilities; on the other hand behavioral routines without proper cognitive representations impeded the development of dynamic capabilities. In order to test the propositions a game called “Transform The Target” with 9 cards for 3 players (the original game) and its variant (the variant game) were introduced as experimental tasks. An experimental design with 2 (with or without cognitive representations) × 2 (original game or variant game) between-subject factors was adopted. A total of 240 students participated in the experiment, every 3 students formed a team to play two rounds of the game, each of which consisted of 20 hands and must be completed within 25 minutes. According to whether they were informed of the problem space or not and whether they were asked to play the original or variant game in the first round, the 80 teams were divided into 4 blocks and were asked to play their respective games. In the second round all teams were asked to play the variant game. The average move time per hand and the strategy or path in the problem space they took were used as the indicators to measure behavioral routines. The rate of transfer from the capabilities learned from the original game in the first round to the variant game in the second round was used as the indicator to measure dynamic capabilities. The analyses of the whole processes of some typical hands of the games played by some typical teams were also used to gather the detailed information of behavioral routines. The numerical data were analyzed by the use of repeated measures of ANOVA. The results showed that while proper cognitive representations contributed to the improvement of dynamic capabilities, behavioral routines without proper cognitive representations impeded the development of dynamic capabilities. To put it briefly, the determinant of dynamic capabilities was cognitive representations but not behavioral routines. These results marked a breakthrough in the study of dynamic capabilities, wherein the orthodox view was that the stable pattern in and the determinant of dynamic capabilities were behavioral routines. This breakthrough opened up new areas for the academic studies of dynamic capabilities, for example, the studies of the nature, function, structure and measurement of dynamic capabilities. And it also provided new thinking for the firms and other organizations in the real world to develop their dynamic capabilities. Related Articles | Metrics

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Risk Considerations and Delegation Behavior: The Role of Leader-Member Exchange and Centralization YANG Ying,LONG Li-Rong,CHOU Li-Fang 2010, 42 (08):  875-885.  Abstract ( 1355 )   Delegation can effectively improve work performance and organizational interests, but it is still not a common phenomenon that managers willing to delegate. Furthermore, most of the past studies on delegation concentrated on delegation’s positive outcome; however, little attention was paid to delegation obstacles. The purpose of this study is to explore the no-delegation phenomenon from the supervisor’s risk considerations for delegation, as well as to probe how Leader-Member Exchange (LMX) and organizational centralization moderate the relationship between delegation risk and delegation behavior based on interactive and structure perspectives. The sample consisted of 157 supervisors and 471 subordinates in 17 enterprises from different industries throughout Mainland China, and supervisors and subordinates were matched in accordance with the ratio of 1:3. HLM method was used for testing hypothesis and results showed that (1) The supervisors delegated less when perceived more delegation risks on task performance and organization benefit. (2) There were significant moderations of LMX on the relationships between supervisor’s delegation behavior and task performance risk, organizational benefit consideration. When Leader-Member Exchange was high, delegation risk about task performance and organization benefit exerted less negative impact on supervisor’s delegation behavior. Namely, the impact of delegation risk about task performance and organization benefit was strong in low LMX. (3) Organizational centralization had negative main and moderating effects on delegation behavior significantly. In higher degree of organizational centralization, the delegation risk consideration on power-status and organizational benefit had more strong negative influences on supervisor delegation; on the contrary, delegation risk consideration on power-status and organizational benefit positively or irrelevantly related with delegation behavior in lower organizational centralization. This study contributed to understand the supervisor delegation behavior through supervisor’s psychological mechanism and clear the critical role of LMX and organizational centralization on the supervisor’s mental-behavior linkage. In addition, our finding offers to a great extent explanation on why no-delegation is prevailing in Chinese organizations. Finally, implications for supervisor delegation study, future research, and practice are discussed. Related Articles | Metrics