Printer Friendly

Conformity behavior during a fire disaster.

Fires are one of the leading causes of unintentional injury (Keane, Drury, Karau, Hessburg, & Reynolds, 2010), and a number of major fire disasters have occurred. For example, 119 people died in the Jilin poultry plant fire in China on June 3, 2013, and 50 more were injured (Lu, 2013), and the Kiss nightclub fire in Brazil on January 27, 2013, resulted in the deaths of 234 people (Dal Ponte, Dornelles, Arquilla, Bloem, & Roblin, 2015).

An important consequence of people's exposure to disastrous fires may be changes to their decision-making functions and their behavior (Wilson, Winter, Maguire, & Ascher, 2011). The relationships among a fire situation, emotion, and conformity behavior have yet to be clearly established. Conformity has been defined as a specific category of social influence in which an individual changes his/her behavior to align with the behavior of others (Cialdini & Goldstein, 2004), and previous researchers have examined this type of behavior in the context of particular situations or events. For example, Murray and Schaller (2012) suggested that infectious diseases exert a significant influence on conformist attitudes and behavior. Further, Rosander and Eriksson (2012), who examined conformity behavior in the context of computer-mediated communication, found that, when answering questions, people are more likely to conform on the Internet than they are during face-to-face meetings.

Although there is relatively little extant research on conformity behavior in emergency situations, scholars have recently started to pay attention to the relationship between conformity behavior and specific emotions. Their research has laid the groundwork for the current study while, at the same time, exposing some inconsistencies in previous conclusions. For example, Tong, Tan, Latheef, Selamat, and Tan (2008) postulated that a positive mood enhances conformity behavior and negative mood reduces it; however, Brown and Schaefer (2010) claimed that people are more likely to conform when encountering situations that generate neutral emotions compared to those that generate positive or negative emotions. Therefore, in this study we explored the differences in emotion and conformity behavior between a fire emergency and a nonemergency situation.

Literature Review and Hypotheses Development

We developed and tested a model of conformity behavior during a fire emergency (see Figure 1). A fire situation involves three key properties: a) a high level of fear activation induced by a perception of danger, b) uncertainty about decision-making performance when making an escape decision, and c) having a number of available options to choose from when making an escape decision. Therefore, in this research we have assumed that each of these properties would influence conformity behavior during a fire situation.

[FIGURE 1 OMITTED]

Several sociologists (e.g., Zvolensky et al., 2009) have suggested that the degree of conformity behavior practiced by those exposed to a particular situation (e.g., an emergency) is closely related to their level of anxiety and fear. Jetten and Hornsey (2012) developed a further prediction about conformity behavior with regard to the increased desire to escape from an emergency situation. However, their prediction not only lacks practical and experimental support, but also cannot fully explain the causal and logical relationships among fear, escape decision making, and conformity behavior in an emergency situation. We surmised that dangerous or disturbing situations that were different (nonemergency vs. emergency) would have different impacts on an individual's level of fear activation, and that the level of fear activation would affect that individual's tendency to conform and decision-making behavior. Specifically, we formed the following hypotheses:

Hypothesis 1: A fire emergency will result in significantly greater likelihood of conformity behavior than will a disturbing but nonemergency situation.

Hypothesis 2: A fire emergency will result in significantly better escape decisions than will a disturbing but nonemergency situation.

Hypothesis 3: A fire emergency will result in a significantly higher level of fear activation than will a disturbing but nonemergency situation.

Fear has been found to be associated with appraisals of danger or threat, low certainty, and a sense of lack of control (Cauberghe, De Pelsmacker, & Janssens, 2009; Shah, 2013). Once generated by an emotion-inducing event, fear then goes on to influence decision outcomes (Lerner & Tiedens, 2006; Mitchell, 2011). As is the case with emotional activation in general (Russell, 1980), fear activation refers to the intensity of fear emotion that is experienced. Previous researchers have explored situations that generate fear and addressed the influence of these situations on fear emotion (e.g., Barker & Galea, 2010). However, there has been little research on the causal relationships among fear, behavior representing decision making, and conformity behavior. We believed that dangerous or disturbing situations that were different (nonemergency vs. emergency) would evoke different levels of fear activation that would have different influences on an individual's conformity behavior and decision-making performance (i.e., right or wrong decision; see Measures subsection below). Therefore, we proposed the following hypotheses:

Hypothesis 4: Level of fear activation will be positively related to conformity behavior in a fire situation.

Hypothesis 5: Level of fear activation will be negatively related to decisionmaking performance in a fire situation.

Greater uncertainty has been found to be associated with less accuracy in situational evaluation (Nja & Rake, 2009), and fire-emergency situations are usually accompanied by a high level of uncertainty (see e.g., Thompson & Calkin, 2011). Cao, Yu, and Geng (2014) found that people exposed to a fire emergency paid a great deal of attention to uncertainty related to decision-making performance in order to ensure that their escape decision was correct. This aspect of fire emergencies is addressed in the following hypothesis:

Hypothesis 6: Decision-making performance will be negatively related to conformity behavior in a fire situation.

Finally, we examined uncertainty associated with the number of decision alternatives (Rosenthal, Charles, & Hart, 1989). This type of uncertainty usually results in people in an emergency situation needing to solve problems based on unclear, unreliable, or unavailable information (Peerbolte & Collins, 2013). For example, people may not know how many exits there are from a building that is on fire or which exit is the best one to use to escape the fire. We explored uncertainty in a fire situation by providing individuals with a number of different decision options for escaping and proposed the following hypotheses in relation to this variable:

Hypothesis 7: The number of alternative choices for a decision about escaping will be negatively related to conformity behavior in a fire situation.

Hypothesis 8: The number of alternative choices for a decision about escaping will be negatively related to decision-making performance in a fire situation.

In summary, our aim was to establish the roles of the type of situation, level of fear activation, decision-making performance, and the number of alternative choices for a decision about escaping, as factors that may affect conformity behavior in a fire-emergency situation. Our intention was to extend conformity theory and fire-situation literature by examining the relationship among some of the factors that influence conformity behavior.

Method

Participants

We posted a notice on a bulletin board and an electronic bulletin board system, both of which were accessible to all students of Shanghai Jiao Tong University. Volunteer participants were required to list, in descending order, the three things that they feared the most. Those who listed insects as the thing they feared the most were screened out and did not participate in the study in order to avoid inflicting psychological damage on those people. Eventually, 114 undergraduate students (63 women, [M.sub.age] = 22.10 years, SD = 1.24, range = 19-26 years) were selected to participate in exchange for RMB100 (approximately US$14.50). They were randomly assigned to one of two groups, each of which had 57 members. All decisions presented to the first group (29 women) had two response options whereas those presented to the second group (34 women) had four response options.

Procedure

Participants logged on to a computer system and provided basic demographic information about gender and age. They were then asked to immerse themselves in the story presented on screen, and imagine that they were the main character. After watching each scenario, participants were given a description of the situation they were in and answered a related question with either two or four response options. The Asch (1955) paradigm was used to test for conformity behavior; after making an initial decision (see Measures below), participants then had the option of changing their original choice. When the video was over, participants rated their level of fear activation for the eight scenarios (see Measures below).

The video that the participants watched was about an undergraduate who reluctantly accepted an invitation to visit an exhibition of insects held at the famous Pearl Tower in City A. The undergraduate viewed each of the various exhibits in turn. Suddenly a fire broke out and the undergraduate had to try his/her best to quickly decide about the best way to escape. The disturbing nonemergency situation used as a baseline was the same insect exhibition and consisted of four scenarios (spiders, caterpillars, cockroaches, and wasps) taken from the documentary film Animal World (China Network Television, 2014). The fire emergency situations consisted of four scenarios taken from the English version of the film Das Inferno-Flammen uber Berlin (Matsutani, 2007). The two situation types (nonemergency and fire emergency) were edited into a complete and reasonable video involving eight scenarios by rewriting the dialogue and dubbing it in Chinese. The dubbing was performed by undergraduates from Shanghai Film Art Academy and the translation-back-translation procedure (Brislin, 1970) was followed to ensure accuracy of content.

Experimental tasks. Participants were asked to perform eight decision-making tasks, wherein each scenario shown in the video was followed by a statement describing the situation at that moment followed by a question requiring the participants to make a decision. All questions involved decision making during the fire situation and were taken from the brochure Prevention or Escape? Fire Safety (DUWO, 2009).

Number of alternative choices for a decision about escaping. In this experiment, each situation had either two or four response options. For example: "You hear a fire alarm activate. What will you do?" In the two-option version, the choices were as follows: a) look for an elevator and b) look for an exit. In the four-option version, the choices were as follows: a) look for an elevator, b) look for an exit, c) look for shelter, and d) stay where you are.

Measures

Level of fear activation. We used a self-report measure of the level of fear activation that participants experienced while watching the video, based on the circumplex model of emotion (e.g., Russell, 1980). Participants rated their level of fear activation on a 6-point intensity scale (0 = high fear deactivation, 5 = high fear activation). Four items were used to measure fear activation in the disturbing nonemergency situation, and the other four were used to measure fear activation in the fire emergency situation (e.g., "When you saw flames in the corridor, how did you feel?"; 0 = high fear deactivation, 5 = high fear activation). The Cronbach's alpha coefficient for the scale as a whole was .79 and reliabilities ranged between .71 and .84 for individual items.

Decision-making performance. In order to measure performance on the initial decision-making response to each situation, the answer was assessed using the fire safety brochure (DUWO, 2009). This assessment was performed for the initial decision-making response, before the participant had the opportunity to change his or her choice of option to match the majority. Decision-making performance was marked as a Boolean value.

Conformity behavior. In order to identify instances when a participant was susceptible to making a change to his/her initial decision to align with the majority's decision, the Asch (1955) paradigm of bogus information was employed. After the participants had chosen an initial response to a situation, the system was programmed to provide bogus information. For example: "The option you chose has been selected by zero other participants and the option you did not choose has been selected by five other participants." The system was also programmed to then ask whether or not the participant wanted to change his or her response. If the participant decided to change his/her response this was considered as conformity; if the decision was not to change, this was considered as nonconformity. Conformity and nonconformity were marked as Boolean values.

Data Analysis

All statistical analyses were conducted using SPSS version 18.0. Linear regression was performed to examine the effect of the fire situation, as compared to the disturbing nonemergency situation, on the level of fear activation. Binary logistic regression was employed to examine the effect of fear activation and the number of alternative choices for a decision about escaping on decision-making performance and conformity behavior. Statistical significance was set at p < .05.

Results

Results of a binary logistic analysis indicated that the prevalence of conformity behavior in the fire situation (11.40%) was significantly higher than that in the nonemergency situation (7.24%), B = 0.501, SE = 0.233, p = .032, which supports Hypothesis 1. Results of a second binary logistic analysis showed that the fire situation had a significant effect on decision-making performance, B = -0.563, SE = 0.136, p < .001, which supports Hypothesis 2. Regression analysis results indicated that the fire situation induced a higher level of fear activation (score range: 1-5) than the nonfire situation did (score range: 0-3), B = 2.086, SE = 0.033, p < .001, which supports Hypothesis 3. Table 1 shows the means, standard deviations, and correlations among the independent variable and the dependent variables.

Supporting Hypothesis 4, the effect of level of fear activation on conformity behavior was positive and significant, B = 0.809, SE = 0.119, p < .001. Further, as predicted in Hypothesis 5, the effect of level of fear activation on decision-making performance was negative and significant (B = -0.385, SE = 0.061, p < .001).

Results of a binary logistic analysis confirmed that decisions with two possible choices led to more conformity behavior than decisions with four choices did, which supports Hypothesis 8, B = -0.362, SE = 0.120, p = .002. Likewise, the effect of number of choices for an escape strategy on decision-making performance was negative and significant (B = -0.309, SE = 0.068, p < .001), which supports Hypothesis 7. Figure 2 shows the effect of decision-making performance on conformity behavior in the two types of situations for (a) two-choice and (b) four-choice responses. Compared to the nonfire situation, the fire situation led to inferior decision-making performance and more conformity behavior, regardless of the number of choices presented. Results of a further binary logistic analysis showed that decision-making performance had a negative and significant effect on conformity behavior, B = -1.595, SE = 0.261, p < .001, which supports Hypothesis 6.

[FIGURE 2 OMITTED]

According to the hypothesized model (Figure 1), decision-making performance played an instrumental role in mediating the association between level of fear activation and conformity behavior. Following the method used by previous researchers (Kenny, Kashy, & Bolger, 1998), we used four criteria to assess this mediation. The unstandardized logistic regression coefficients of the mediation model can be seen in Figure 3, and show that the four criteria were met, such that decision-making performance was negatively associated with the level of fear activation and with conformity behavior. This implies that decision-making performance is a partial intermediary variable affecting the level of fear activation and conformity behavior.

Using the same method of analysis, we found that decision-making performance also significantly satisfied the four conditions as a mediator between number of alternative choices for a decision about escaping and conformity behavior (see Figure 3). This suggests that the effect of number of alternative choices for a decision about escaping on conformity behavior is, in part, realized through decision-making performance in the given situation.

[FIGURE 3 OMITTED]

Discussion

In our study the aim was to establish whether or not, and how, people will engage in conformity behavior when faced with a fire emergency. The results suggest that people are more likely to conform in a fire situation than they are in nonemergency situations, which is in agreement with our initial hypothesis.

In a situation of conflict between one's own decision and that of a group, individuals try to evaluate the conflict. After this assessment, if individuals believe that the group decision is better than their own (e.g., Deuker et al., 2013), their brain will send a negative signal to their underlying social-learning cognitive mechanism that leads to the individual adjusting his/her decision, resulting in conformity behavior. Conversely, if the individual judges that his/her decision is better than that of the group, his/her brain signals to the social-learning cognitive mechanism that there is no need to change that decision. In either case, this experience will generate new knowledge as a result of social learning. On one hand, the fear that most individuals feel in the face of fire is greater than their general fear of insects. This is probably because fire is perceived as being capable of causing greater harm to people than are insects On the other hand, most individuals have less experience with fire disasters than with encountering insects in everyday life, and people's decision-making capacity during a fire emergency depends on how much relevant information and previous experience they have (Jones, Ribbe, Cunningham, Weddle, & Langley, 2002).

Previous explanations of conformity behavior have been based in neuroscience and information influence. Information influence means that the group is seen as a valid source of information, such that an individual believes that his/her decision can be altered and the group decision is internalized (Zaki, Schirmer, & Mitchell, 2011). Survival instinct causes individuals to desire more information to ensure the maximum probability of survival during a fire emergency, and they may believe that the majority possesses a greater amount of valid information than they do themselves. Therefore, during an emergency, individuals have a greater tendency to imitate majority behaviors, even when this means changing their own original decision, in order to achieve the maximum probability of survival. Consequently, conformity behavior as a result of information influence is more evident in a fire situation than it is in everyday situations.

Furthermore, in our study the participants' conformity behavior decreased along with the increase in the number of options offered for a decision about escaping and of available information. This suggests that, for some individuals, their dependence on others may reduce because they have more information when there are more alternative options offered than is the case when they have fewer options; thus, in the situation of having more options, they rely on their own instinct and risk preference to make decisions, and they are less likely to choose conformity behavior.

http://dx.doi.org/10.2224/sbp.2016.44.2.313

Qi Duo and Huizhang Shen

Shanghai Jiao Tong University

Jidi Zhao

East China Normal University

Xiaomin Gong

Shanghai Jiao Tong University

Qi Duo and Huizhang Shen, Department of Management Information Systems, Shanghai Jiao Tong University; Jidi Zhao, School of Public Administration, East China Normal University; Xiaomin Gong, Department of Management Information Systems, Shanghai Jiao Tong University. This study was supported by the Major Program of China National Social Science Fund (Grants 11 & ZD174).

Correspondence concerning this article should be addressed to: Huizhang Shen, Department of Management Information Systems, Antai College of Economics and Management, Shanghai Jiao Tong University, No. 1954 Huashan Road, Xuhui, Shanghai 200030, People's Republic of China. Email: hzshen@sjtu.edu.cn

References

Asch, S. E. (1955). Opinions and social pressures. Scientific American, 193, 31-35. http://doi.org/ bpgsrx

Barker, J. M., & Galea, L. A. (2010). Males show stronger contextual fear conditioning than females after context pre-exposure. Physiology & Behavior, 99, 82-90. http://doi.org/dnjmz8

Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1, 185-216. http://doi.org/b99wbg

Brown, C., & Schaefer, A. (2010). The effects of conformity on recognition judgments for emotional stimuli. Acta Psychologica, 133, 38-44. http://doi.org/bqksxv

Cao, L. J., Yu, X. M., & Geng, D. Y. (2014). Subway station group decision and evaluation of fire emergency. Applied Mechanics and Materials, 580, 1408-1411. http://doi.org/7wx

Cauberghe, V., De Pelsmacker, P., & Janssens, W. (2009). The role of fear, threat and efficacy in threat appeals: Putting fear back in the danger control response. In P. De Pelsmacker, & N. Dens (Eds.), Advertising research: Message, medium and context (pp. 123-132). Antwerp, Belgium: Garant.

China Network Television. (2014). The insect world: The warehouse of the secret weapon. Retrieved from http://tv.cntv.cn/video/C12278/2be7d38551fc43ffaa5455aabd3d15f6

Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591-621. http://doi.org/ctvwr4

Dal Ponte, S. T., Dornelles, C. F., Arquilla, B., Bloem, C., & Roblin, P. (2015). Mass-casualty response to the Kiss Nightclub in Santa Maria, Brazil. Prehospital and Disaster Medicine, 30, 93-96. http://doi.org/7wz

Deuker, L., Muller, A., Montag, C., Markett, S., Reuter, M., Fell, J., ... Axmacher, N. (2013). Playing nice: A multi-methodological study on the effects of social conformity on memory. Frontiers in Human Neuroscience, 7, 79-89. http://doi.org/7w2

DUWO. (2009). Prevention or escape? Fire safety. Retrieved from https://www.duwo.nl/

Jetten, J., & Hornsey, M. J. (Eds.). (2012). Beyond conformity. Rebels in groups: Dissent, deviance, difference and defiance. Chichester, UK: Wiley-Blackwell.

Jones, R. T., Ribbe, D. P., Cunningham, P. B., Weddle, J. D., & Langley, A. K. (2002). Psychological impact of fire disaster on children and their parents. Behavior Modification, 26, 163-186. http:// doi.org/b2s529

Keane, R. E., Drury, S. A., Karau, E. C., Hessburg, P. F., & Reynolds, K. M. (2010). A method for mapping fire hazard and risk across multiple scales and its application in fire management. Ecological Modelling, 221, 2-18. http://doi.org/ck3974

Kenny, D. A., Kashy, D. A., & Bolger, N. (1998). Data analysis in social psychology. In D. Gilbert, S. Fiske, & G. Lindzey (Eds.), Handbook of social psychology (Vol. 1, pp. 233-265). Boston, MA: McGraw-Hill.

Lerner, J. S., & Tiedens, L. Z. (2006). Portrait of the angry decision maker: How appraisal tendencies shape anger's influence on cognition. Journal of Behavioral Decision-Making, 19, 115-137. http://doi.org/cz8b2t

Lu, H. (2013). 119 dead in Jinlin poultry plant fire. Retrieved from http://bit.ly/1VlbsAe

Matsutani, R. (Director). (2007). Das inferno--Flammen uber Berlin [Raging inferno] [Motion picture!. Medienfonds GFP Germany. Retrieved from http://v.youku.com/v show/id XNDg1NzI1NDIw.html?from=s1.8-1-1.1

Mitchell, D. G. (2011). The nexus between decision making and emotion regulation: A review of convergent neurocognitive substrates. Behavioural Brain Research, 217, 215-231. http:// doi.org/bpbtkp

Murray, D. R., & Schaller, M. (2012). Threat(s) and conformity deconstructed: Perceived threat of infectious disease and its implications for conformist attitudes and behavior. European Journal of Social Psychology, 42, 180-188. http://doi.org/drdgb7

Nja, O., & Rake, E. (2009). A discussion of decision making applied in incident command. International Journal of Emergency Management, 6, 55-72. http://doi.org/bkqcdd

Peerbolte, S. L., & Collins, M. L. (2013). Disaster management and the critical thinking skills of local emergency managers: Correlations with age, gender, education, and years in occupation. Disasters, 37, 48-60. http://doi.org/7w3

Rosander, M., & Eriksson, O. (2012). Conformity on the Internet--The role of task difficulty and gender differences. Computers in Human Behavior, 28, 1587-1595. http://doi.org/f24xb5

Rosenthal, U., Charles, M., & Hart, P. (Eds.). (1989). Coping with crises: The management of disasters, riots and terrorism. Springfield, IL: Charles C. Thomas.

Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39, 1161-1178. http://doi.org/fc6rg5

Shah, T. M. (2013). Chaos and fear: Creativity and hope in an uncertain world. International Sociology, 28, 513-517. http://doi.org/7w4

Thompson, M. P., & Calkin, D. E. (2011). Uncertainty and risk in wildland fire management: A review. Journal of Environmental Management, 92, 1895-1909. http://doi.org/bc6hdd

Tong, E., Tan, C., Latheef, N., Selamat, M., & Tan, D. (2008). Conformity: Moods matter. European Journal of Social Psychology, 38, 601-611. http://doi.org/bsk4qs

Wilson, R., Winter, P., Maguire, L., & Ascher, T. (2011). Managing wildfire events: Risk-based decision making among a group of federal fire managers. Risk Analysis, 31, 805-818. http:// doi.org/fnmswj

Zaki, J., Schirmer, J., & Mitchell, J. P. (2011). Social influence modulates the neural computation of value. Psychological Science, 22, 894-900. http://doi.org/cmtq7z

Zvolensky, M. J., Marshall, E. C., Johnson, K., Hogan, J., Bernstein, A., & Bonn-Miller, M. O. (2009). Relations between anxiety sensitivity, distress tolerance, and fear reactivity to bodily sensations to coping and conformity marijuana use motives among young adult marijuana users. Experimental and Clinical Psychopharmacology, 17, 31-42. http://doi.org/c26cgv
Table 1. Means, Standard Deviations, and Correlations
Among Study Variables

Variable                M      SD    1      2       3       4

1. Gender             0.45    0.50   --   .11 **   .00   -.09 **

2. Age (years)        22.11   1.33           --    .00   -.01

3. Fire situation     0.50    0.50                 --     .00

4. Number of
   alternative
   choices for
   decision about
   escaping           3.00    1.00                         --

5. Level of fear      2.02    1.16
   activation

6. Decision-making    0.58    0.49
   performance

7. Conformity         0.09    0.29
   behavior

Variable                 5         6         7

1. Gender             -.04       .08 *    -.03

2. Age (years)         .01 *     .03       .03

3. Fire situation      .90 **   -.14 **    .07 *

4. Number of
   alternative
   choices for
   decision about
   escaping           -.05      -.15 **   -.10 **

5. Level of fear        --      -.21 **    .24 **
   activation

6. Decision-making                --      -.22 **
   performance

7. Conformity                               --
   behavior

Note. Gender: male = 1, female = 0; * p < .05, ** p < .01.
Fire situation: 0 = nonfire situation, 1 = fire situation.
COPYRIGHT 2016 Scientific Journal Publishers, Ltd.
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2016 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Duo, Qi; Shen, Huizhang; Zhao, Jidi; Gong, Xiaomin
Publication:Social Behavior and Personality: An International Journal
Article Type:Report
Date:Mar 1, 2016
Words:4216
Previous Article:Effects of individuals' motivations on communications in online health forums.
Next Article:Love for one's country or oneself: a brand-choice framework in emerging markets.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |