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Uncertainty reduction theory
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The uncertainty reduction theory, also known as initial interaction theory, developed in 1975 by Charles Berger and Richard Calabrese, is a communication theory from the post-positivist tradition. It is one of the only communication theories that specifically looks into the initial interaction between people prior to the actual communication process.The theory asserts the notion that, when interacting, people need information about the other party in order to reduce their uncertainty. In gaining this information people are able to predict the other's behavior and resulting actions, all of which according to the theory is crucial in the development of any relationship.[1][2]
Charles Berger and Richard Calabrese explain the connection between their central concept of uncertainty and seven key variables of relationship development with a series of axioms, and deduce a series of theorems accordingly. Within the theory two types of uncertainty are identified; cognitive uncertainty and behavioral uncertainty. There are three interactive strategies which people may use to seek information about someone, these are passive, active, or interactive. Furthermore, the initial interaction of strangers can be broken down into individual stages—the entry stage, the personal stage, and the exit stage. According to the theory, people find uncertainty in interpersonal relationships unpleasant and are motivated to reduce it through interpersonal communication.
Contents
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1 Background
2 Assumptions
3 Types of uncertainty
3.1 Cognitive uncertainty
3.2 Behavioral uncertainty
4 Processes of uncertainty reduction
4.1 Proactive uncertainty reduction
4.2 Retroactive uncertainty reduction
5 Axioms and theorems
5.1 Axioms
5.2 Theorems
6 Stages of relational development
6.1 The entry stage
6.2 The personal stage
6.3 The exit stage
7 Incentives to reduce uncertainty
8 Uncertainty reduction strategies
9 Ethnicity and cultural differences
9.1 Korean-Americans and Americans
9.2 Japanese and Americans
9.3 Indian and Americans
10 Contemporary use
10.1 Job hiring process
10.1.1 Job hiring via extracted information
10.2 In-group identification
10.3 Computer-mediated communication
10.3.1 Online auctions
10.3.2 Online dating
10.3.3 Online surrogacy ads
11 Critique
11.1 The scope of the axioms and theorems
11.2 Uncertainty measurement
11.3 Beyond initial interaction
11.4 Motivation to reduce uncertainty
11.4.1 Motivation to reduce uncertainty (MRU) model
11.5 Anxiety/uncertainty management theory
11.5.1 Example: Online cancer research
11.6 Defense
12 See also
13 References
14 Further reading
15 External links
Background[edit]
In 1975, Charles Berger and Richard Calabrese created uncertainty reduction theory "to explain how communication is used to reduce uncertainties between strangers engaging in their first conversation together".[2] Previous researchers had approached interpersonal communication from empirical perspectives. Hypotheses had been derived from social psychological theories as well. However, the lack of focus on interpersonal communication process motivated Berger and Calabrese to form hypotheses that directly involve communication behavior.[1]
The foundation of the uncertainty reduction theory stems from the information theory, originated by Claude E. Shannon and Warren Weaver.[2] Shannon and Weaver suggests, when people interact initially, uncertainties exist especially when the probability for alternatives in a situation is high and the probability of them occurring is equally high.[3] They assume uncertainty is reduced when the amount of alternatives is limited and/or the alternatives chosen tend to be repetitive.
Assumptions[edit]
There are seven assumptions associated with the uncertainty reduction theory:[2]
People experience uncertainty in interpersonal settings.
Uncertainty is an aversive state, generating cognitive stress.
When strangers meet, their primary concern is to reduce their uncertainty or to increase predictability.
Interpersonal communication is a developmental process that occurs through stages.
Interpersonal communication is the primary means of uncertainty reduction.
The quantity and nature of information that people share change through time.
It is possible to predict people's behavior in a lawlike fashion.
Types of uncertainty[edit]
Cognitive uncertainty[edit]
Cognitive uncertainty pertains to the level of uncertainty associated with the cognition (beliefs and attitudes) of each other in the situation.[4] Uncertainty is high in initial interactions because individuals are not aware of the beliefs and attitude of the other party.[4]
Behavioral uncertainty[edit]
Behavioral uncertainty pertains to "the extent to which behavior is predictable in a given situation".[4] Uncertainty is one motivation behind adoption of norms in most societies in which people tend to abide by, and if in initial conversations one chooses to ignore such norms there are risks of increasing behavioral uncertainty and reducing the likelihood of having future interactions. A great example of ignoring societal norms is engaging in inappropriate self-disclosure.
Processes of uncertainty reduction[edit]
Proactive uncertainty reduction[edit]
Proactive uncertainty reduction, making predictions of the most likely alternative actions the other person might take, is strategic communication planning prior to interaction.[1] In initial meetings, people attempt to predict what the other may want to hear based on the meaning they acquired from previous statements, observations, or information ascertained.
Retroactive uncertainty reduction[edit]
Retroactive uncertainty reduction is the process of analyzing the situation post interaction, which refers to making explanations for the other person's behavior and interpreting the meaning of behavioral choices.[1][2]
Based on these two processes, Berger and Calabrese suggest that interpersonal communication behavior has at least two different roles to play within this framework. First, communication behavior itself is what we endeavor to predict and explain. Second, communication behavior is one vehicle that enables the formulation of predictions and explanations.[1]
Axioms and theorems[edit]
Berger and Calabrese propose a series of axioms drawn from previous research and common sense to explain the connection between their central concept of uncertainty and seven key variables of relationship development: verbal communication, nonverbal warmth, information seeking, self-disclosure, reciprocity, similarity, and liking.[5] The uncertainty reduction theory uses scientific methodology and deductive reasoning to reach conclusions.[6] This part of uncertainty reduction theory demonstrates the positivistic approach Berger and Calabrese took. The approach "advocates the methods of the natural sciences,with the goal of constructing general laws governing human interactions".[2]
Axioms[edit]
Axiom 1 – Verbal communication: Given the high level of uncertainty present at the onset of the entry phase, as the amount of verbal communication between strangers increases, the level of uncertainty for each interactant in the relationship will decrease. As uncertainty is further reduced, the amount of verbal communication will increase.[2] It is also important to consider more recently published work by Berger, in which, he states the importance of appropriate levels of verbal communication, where too much verbal communication may lead to information seeking by the other party.[2]
Axiom 2 – Non-verbal affiliative expressiveness/warmth: Non-verbal affiliative expressiveness includes eye contact, head nods, arm gestures and physical distance between the interactants(closeness). As non-verbal affiliate expressiveness increases, uncertainty levels will decrease in an initial interaction situation. In addition, decreases in uncertainty level will cause increases in non-verbal affiliative expressiveness[2]
Axiom 3 – Information seeking: In initial interactions, interactants are expected to engage in question asking, and the questions asked might only demand relatively short answers, for example: request for information of one's occupation, hometown, places of prior residence and so on.[1] High levels of uncertainty cause increases in information-seeking behavior. As uncertainty levels decline, information-seeking behavior declines[2]
Axiom 4 – Intimacy level of communication content: High levels of uncertainty in a relationship cause decreases in the intimacy level of communication content. Low levels of uncertainty produce high levels of intimacy[2] For example, during initial interaction, the communication content are expected to be of low intimacy level such as demographic information, rather than content of high intimacy level such as attitudes and opinions.[1]
Axiom 5 – Reciprocity : High levels of uncertainty produce high rates of reciprocity. Low levels of uncertainty produce low rates of reciprocity.[2] Berger and Calabrese assume that the easiest way to reduce mutual uncertainty would be to ask for and give the same kinds of information at the same rate of exchange and that as uncertainty is reduced, there is less need for symmetric exchanges of information at a rapid rate.[1]
Axiom 6 – Similarity : Similarities between persons reduce uncertainty, while dissimilarities produce increases in uncertainty[2] Dissimilarity between persons increased uncertainty because the number of alternative explanations for behavior also increases.[1]
Axiom 7 – Liking : Increases in uncertainty level produce decreases in liking; decreases in uncertainty produce increases in liking.[2] A number of theorists have presented supportive evidence that there is a positive relationship between similarity and liking. In the view of Axiom 6, the tendency that people seek out similar others in order to reduce uncertainty should tend to produce liking.[1]
Based on further research two additional axioms were added to the theory, the 8th axiom was add by Berger and Gudykunst (1991) and the 9th axiom was suggested by Neuliep and Grohskopf (2000):[2]
Axiom 8 – Shared Networks : Shared communication networks reduce uncertainty, while lack of shared networks increases uncertainty. This axiom is based on further research done by Berger and William B. Gudykunst (1991) which pertained to relationship beyond the entry stage.[2]
Axiom 9 – Communication satisfaction: There is an inverse relationship between uncertainty and communication satisfaction. Communication satisfaction is defined as "an affective response to the accomplishment of communication goals and expectations".[2] Suggested by James Neuliep and Erica Grohskopf (2000), this is an important axiom because it relates uncertainty to a specific communication outcome variable.[2]
Theorems[edit]
Berger and Calabrese formulated the following theorems deductively from their original seven axioms:[7]
Amount of verbal communication and nonverbal affiliative expressiveness are positively related.
Amount of verbal communication and intimacy level of communication are positively related.
Amount of verbal communication and information seeking behavior are inversely related.
Amount of verbal communication and reciprocity rate are inversely related
Amount of verbal communication and liking are positively related.
Amount of verbal communication and similarity are positively related.
Nonverbal affiliative expressiveness and intimacy level of communication content are positively related.
Nonverbal affiliative expressiveness and information seeking and information seeking are inversely related.
Nonverbal affiliative expressiveness and reciprocity rate are inversely related.
Nonverbal affiliative expressiveness and liking are positively related.
Nonverbal affiliative expressiveness and similarity are positively related.
Information seeking and reciprocity are positively related.
Information seeking and liking are negatively related.
Information seeking and similarity are negatively related.
Intimacy level and reciprocity are negatively related.
Intimacy level and similarity are positively related.
Intimacy level and liking are positively related.
Reciprocity rate and liking are negatively related.
Reciprocity rate and similarity are negatively related.
Similarity and liking are positively related
Viewed collectively, the theorems provide a framework for examining and predicting the process of getting to know someone.[1]
Table 1: Theorems of Uncertainty Reduction Theory
Verbal Communication Nonverbal Communication Information seeking Intimacy level Reciprocity Similarity Liking
Verbal Communication + - + - + +
Nonverbal Communication + - + - + +
Info seeking - - - + - -
Disclosure + + - - + +
Reciprocity - - + - - -
Similarity + + - + - +
Liking + + - + - +
*Table 1 summarizes the seven axioms and their relationships as theorems

Stages of relational development[edit]
Berger and Calabrese separate the initial interaction of strangers into three stages: the entry stage, the personal stage, and the exit stage. Each stage includes interactional behaviors that serve as indicators of liking and disliking.[1]
The entry stage[edit]
The entry stage of relational development is characterized by the use of behavioral norms. Meaning individuals begin interactions under the guidance of implicit and explicit rules and norms, such as pleasantly greeting someone or laughing at ones innocent jokes. The contents of the exchanges are often dependent on cultural norms. The level of involvement will increase as the strangers move into the second stage.[1]
The personal stage[edit]
The personal phase occurs when strangers begin to explore one another's attitudes and beliefs. Individuals typically enter this stage after they have had several entry stage interactions with a stranger. One will probe the other for indications of their values, morals and personal issues. Emotional involvement tends to increase as disclosure increases.[1]
The exit stage[edit]
In the exit phase, the former strangers decide whether they want to continue to develop a relationship. If there is no mutual liking, either can choose not to pursue a relationship.[1]
Understanding the cycle of relational development is key to studying how people seek to reduce uncertainty about others.
Incentives to reduce uncertainty[edit]
Berger suggests that an individual will tend to actively pursue the reduction of uncertainty in an interaction if any of the three conditions are verified:[8]
Anticipation of future interaction: A future meeting is a certainty.
Incentive value: They have or control something we want.
Deviance: They act in a manner that is departing from accepted standards
Example: For a couple of weeks there will be a new manager in your workplace, therefore future interactions with this person is a certainty. The manager is assigning projects to the people in your department, every project returns a different commission which will directly influence your income. Arguably, being assigned a higher paying project has a greater incentive value for anyone in the department. The manager has a sibling in your department, which could influence the manager's decision on project assignments.
According to the theory, any single aforementioned factor or all three of them combined can result in an increase in one's desire to reduce uncertainty in interpersonal interactions.[1]
Uncertainty reduction strategies[edit]
People engage in passive, active, or interactive strategies to reduce uncertainty with others. Strategies as seeking information, focusing on primary goals, contingency planning, plan adaptation, accretive planning, and framing are often utilized by human communicators.[9]
According to Berger, If a person were to observe another in their natural environment, intentionally unnoticeable, to gain information on another, would be categorized as using a passive tactic for reducing uncertainties.[9] For example, watching someone in class, cafeteria, or any common area without attracting attention.
An active strategist would result to means of reducing uncertainties without any personal direct contact.[9] For example, if one were to ask a friend about a particular person, or ask the particular person's friend for some information without actually confronting the person directly.
An interactive strategist would directly confront the individual and engage in some form of dialog to reduce the uncertainties between the two.[9]
These strategies are meaningful to communication studies in a way that people's "unique capacities for forethought and planning and their ability to monitor carefully ongoing communication episodes" is valued in communicative process.[9]
A new strategy for reducing uncertainty was suggested in 2002 by Ramirez, Walther, Burgoon, and Sunnafrank that complements computer mediated communication and the technological advancements. Given the vast amount of information one could find about an individual via online resources a fourth uncertainty reduction strategy that uses online mediums to obtain information was labeled as extractive information seeking.[10]
Ethnicity and cultural differences[edit]
Study has shown that intercultural communication apprehension—the fear or anxiety with intercultural communication is positively associated with uncertainty.[11] In addition to that, socio-communication orientation, which refers to people's ability to be a good speaker and good listener, is negatively associated with uncertainty in intercultural communication.[11] Measures of intercultural communication apprehension and ethnocentrism are significantly and negatively correlated with measures of uncertainty reduction and communication satisfaction according to James Neuliep's study in 2012.[12]
Studies have been conducted to determine the differences in the uses of uncertainty reduction strategies among various ethnicities. A study, conducted in the United States, suggests that significant differences are apparent. Self-disclosure has a pan-cultural effect on attributional confidence but other types of uncertainty reduction strategies appeared to be more culture-specific.[13] "A multiple comparisons analysis using a least significance difference criterion indicated that for both self- and other-disclosure, African-Americans used greater self-disclosure than Euro-Americans, Hispanic-Americans, and Asian-Americans and perceived greater other intraethnic disclosure. The only other significant differences found in the multiple comparisons test were between self- and other-disclosure levels for Hispanic-Americans and Asian-Americans, namely, the former perceived greater self- and other-disclosure levels than Asian-Americans."[13]
Results of study that compares verbal behaviors and perceptions in intracultural interactions and intercultural interactions during the initial communication suggest that "intercultural interactions may not be as dissimilar from intracultural interactions as has been traditionally assumed".[14] This result also proves that the sixth axiom of uncertainty reduction theory may be weak, which claims a positive relationship between similarity and uncertainty reduction.[14]
Korean-Americans and Americans[edit]
A study of intercultural communication between Korean-Americans and Americans conclude that Korean-Americans' uncertainty level toward Americans did not decrease as their amount of verbal communication increased.[15] However, as Korean-Americans' intimacy level of communication content increased, their uncertainty level toward Americans decreased. But these two tested axioms are only a partially useful formulation for understanding such intercultural communication.[15]
Japanese and Americans[edit]
Another study suggests that cultural similarities between strangers influence the selection of uncertainty reduction strategies by increasing the intent to interrogate, intent to self-disclose, and nonverbal affiliative expressiveness.[16] The study also expressed an individual's culture influences their selection of uncertainty reduction strategies.[16] For example, US students exhibit higher levels of interrogation and self-disclosure than in Japanese students.[16]
Indian and Americans[edit]
Study of mocking hiring interviews examines nonverbal behavior between Indian applicants and United States interviewers.[17] It shows that the effects of the similarity/dissimilarity of interviewers' and interviewees' nonverbal behaviors exhibited during an intercultural hiring interview have some effects on interviewers' perceptions of and hiring decisions about interviewees, but such effects are much less than Berger and Calabrese claim.[17]
Contemporary use[edit]
The uncertainty reduction theory has been applied to new relationships in recent years. Although it continues to be widely respected as a tool to explain and predict initial interaction events, it is now also employed to study intercultural interaction (Gudykunst et al., 1985), organizational socialization (Lester, 1986), and as a function of media (Katz & Blumer, 1974). Gudykunst argues it is important to test the theory in new paradigms, thus adding to its heuristic value (Gudykunst, 2004).
Job hiring process[edit]
See also: Matching theory
Scholarly studies have examined the practical application of uncertainty reduction theory in the context of job hiring by studying the communication process between interviewers and applicants prior and during an interview. Understanding the interview process as an interactive communication process aimed to reduce uncertainty is important to organizations, as it has been proven that the more positive and negative information about expectations and organizational norms are shared during the interview process, both by the applicant and interviewer, the greater the job satisfaction and the less turnover rates.[18] An applicant's interview satisfaction is measured in terms of the amount of information and time given to the applicant. Findings suggest that applicants prefer conversational questions that helps them reduce uncertainties about the job they are applying to.[19]
The interview is suggested to be the initial means of communication in which both participants thrive to reduce their uncertainties.[20] Both interviewees and interviewers engage in strategies to reduce uncertainty.[20]
Job hiring via extracted information[edit]
Research studies have applied uncertainty reduction theory to online information seeking utilized in the context of job hiring. Using uncertainty reduction strategies through online sources have proven to be good predictions and indicators of targeted individuals. However, findings have also concluded the negative effects on job applicants when negative information is obtained by employers via online sources that may conflict with the already developed perception of the job applicant obtained from normal means such as résumés and cover letters.[21]
Furthermore, online information's effect on job applicants has been widely discussed, as many guide books now suggest that applicants minimize what could be preserved by employers as negative presence in their online communities and strategically enhance any positive presence. As more organizations are including online information extract as part of their recruiting process, empirical results show that applicants with negative online presence are perceived as less qualified than those with a positive or neutral online presence.[22]
In-group identification[edit]
Empirical studies have examined the relationship between the effects of self-uncertainty and in-group entitativity. One important question that was investigated was; what motivates people to join or identify with groups and engage in specific forms of inter-group behavior? Based on the concept of uncertainty reduction theory, the hypothesis that people identify most strongly with groups if they felt self-conceptual uncertainty was tested. Results revealed that people who feel self-conceptual uncertainty are motivated to join groups in which they identify with as an efficient strategy and immediate way to reduce one's self-conceptual uncertainty.[23][24] Hogg bases his argument on the premise that subjective uncertainty, especially those about one's self and identity are unpleasant and that people strive to reduce uncertainties they feel about themselves.[25]
A person's self-categorization is affected by group identification including nationality, religion, gender, ethnicity and many other associated groups. Thus people continue to try to reduce the uncertainties they feel about themselves by identifying with even more specific groups. There is also evidence that people who are highly uncertain about themselves are more likely to identify with more homogeneous groups to reduce their uncertainty of self and reach a more definite state.[26] Generally, people will be able to reduce their self-uncertainty either significantly or to a low degree, depending on the type of group they join and to what extent one can relate to his or herself within a group.[27]
Computer-mediated communication[edit]
Given that uncertainty reduction theory was primarily developed for face-to-face interactions, critics have questioned the theory's applicability to computer-mediated communication (CMC). Pratt, Wiseman, Cody and Wendt argue that the theory is only partially effective in asynchronous, computer-mediated environments.[28] Although many computer mediated communications limit the possibility of utilizing many traditional social cues theories, such as social information processing and the hyperpersonal model, suggest individuals are quite capable of reducing uncertainties and developing intimate relationships.[29]
Antheunis, Marjolijn L., et al. investigated whether language-based strategies, employed by computer-mediated communication users, would aid in reducing uncertainties despite the absence of nonverbal cues.[30] Examining three interactive uncertainty reduction strategies (i.e., self-disclosure, question asking, and question/disclosure intimacy) in computer mediated communications, the study questioned the use of language-based strategies to three communication options: face-to-face, visual CMC supported by a webcam, or text-only CMC.[30] It finds that "text-only CMC interactants made a greater proportion of affection statements than face-to-face interactants. Proportions of question asking and question/disclosure intimacy were higher in both CMC conditions than in the face-to-face condition, but only question asking mediated the relationship between CMC and verbal statements of affection."[30]
In addition, a study was conducted on 704 members of a social networking site to see what reduction theory strategies they used while gaining information on people they had recently met in person. All respondents used passive, active and interactive strategies, but the most common and beneficial strategy was the interactive strategy through which people show a perceived similarity and increasing social attraction.[31]
Online auctions[edit]
In an online consumer-to-consumer (C2C) e-commerce context, transactions usually happen directly between individuals with a third party involved acting as an intermediary or a communication platform, but not guaranteeing that the transaction happens. Therefore, C2C e-commerce platforms constantly involve initial interaction between strangers that is motivated by the desire to exchange a product for money. Such environments are a significant risk for both the seller and the buyer, given the financial and psychological cost of a transaction failing because of a lack of information.[32]
Online auction platforms such as eBay are considered to be risky and uncertain environments for exchange, especially from the standpoint of the bidder, as there is limited information available regarding both the merchandise and the seller.[33]
Using uncertainty reduction theory and predicted outcome value theory, a study of 6477 randomly selected data sets of auctions conducted on eBay.com indicated that the more detailed information about a certain product was available as part of the product description the more bids there were and the higher the final bid was. In addition, a higher seller's reputation resulted in more bids and a higher selling price.[34] One means to reduce the uncertainty of a product's worth is having extensive descriptions and pictures of the item available and more positive feedback from previous users.[35]
Findings from the study illustrate that uncertainty reduction theory provides an insightful framework in which individuals' initial interactions in the context of online auctions can be understood. The study also provides evidence that strategies for reducing uncertainty in online initial interaction are similar to those used in face-to-face transactions.[36] Although online auction users seem to favor passive strategies, including viewing product information and seller reputation, there are more active strategies in use: a user may look up the seller in other online platforms to gather relevant information or may use an interactive strategy, sending a private message to the seller asking for more information.[37]
Online dating[edit]
Online dating sites typically bring together individuals who have no prior contact with one another and no shared physical space where nonverbal cues can be communicated through gestures, facial expression and physical distance. This limited access to nonverbal cues produces a different set of concerns for individuals, as well as a different set of tools for reducing uncertainty. Gibbs, Ellison and Lai report that individuals on online dating websites attempt to reduce uncertainty at three levels: personal security, misrepresentation, and recognition. The asynchronous nature of the communications and the added privacy concerns may make people want to engage in interactive behaviors and seek confirmatory information sooner than those who engage in offline dating.[29]
Online dating mainly supports passive strategies for reducing uncertainties. The option to view profiles online without needing to directly contact an individual is the main premise of passively reducing uncertainties. Gibbs, et al. found that "participants who used uncertainty reduction strategies tended to disclose more personal information in terms of revealing private thoughts and feelings, suggesting a process whereby online dating participants proactively engage in uncertainty reduction activities to confirm the private information of others, which then prompts their own disclosure."[29]
Online surrogacy ads[edit]
Parents and surrogate mothers have great incentive for reducing uncertainty, taking optimal control, and finding a suitable third party for their pregnancy process. May and Tenzek assert that three themes emerged from their study of online ads from surrogate mothers: idealism, logistics, and personal information. Idealism refers to surrogates' decision to share details regarding their lifestyle and health. Logistics refers to the surrogates' requested financial needs and services. Personal information refers to the disclosure of details that would typically take several interactions before occurring, but has the benefit of adding a degree of tangible humanness to the surrogate (e.g. the disclosure of family photos). Idealism, logistics and personal information all function to reduce potential parents' uncertainty about a surrogate mother.[38]
Critique[edit]
The scope of the axioms and theorems[edit]
Due to the law-like framework to explain and predict other's behavior, if a particular theorem is disproved, it destroys the axiological base upon which it rests. Through their studies with 1,159 students from 10 universities in the United States, Kathy Kellerman and Rodney Reynolds conclude that "no need exists to integrate concern for uncertainty reduction into the axiomatic framework" (1990). They also provide evidence with their studies that there is no association between information seeking and level of uncertainty, which disprove axiom 3 developed by Berger and Calabrese.
Uncertainty measurement[edit]
In addition, the subjectivity of people's self-assessment render the premise of uncertainty reduction problematic. The generation of uncertainty comes from people's lack of knowledge about themselves, information and environment. However, it is primarily people's self-perception about one's own cognitions and ability that cause uncertainty, and this self-perception itself is hard to measure.[39] In Brashers' study on uncertainty management's application to health communication, he explains the uncertainty of self-perception that people's feeling of uncertain is not necessarily correspond to its self-assessment of available knowledge.[39]
Beyond initial interaction[edit]
Uncertainty reduction theory has been cast doubt on its association with communication beyond initial interaction. Planalp & Honeycutt suggest that people's potential changes, lack of understanding each other, or impetuous behavior will increase uncertainty in communication outside initial interaction.[40] Their study questions the assumption that increased knowledge of other people and relationships will help social actors to function effectively in the social world.[40] However, their findings provide supportive evidence that uncertainty (in long-term relationships) usually impacts negatively on the relationship.[40]
Motivation to reduce uncertainty[edit]
Uncertainty reduction theory has sparked much discussion in the discipline of communication. Critics have argued that reducing uncertainty is not the driving force of interaction. Michael Sunnafrank's predicted outcome value theory (1986) indicated that the actual motivation for interaction is a desire for positive relational experiences. In other words, individuals engaging in initial interactions are motivated by rewards opposed to reducing uncertainties. According to Sunnafrank, when we communicate we are attempting to predict certain outcome to maximize the relational outcomes. Kellerman and Reynolds (1990) pointed out that sometimes there are high level of uncertainty in interaction that no one wants to reduce.[6] Their study find that the central determinant of both information seeking (axiom 3) and liking (axiom 4) is the predicted outcome values rather than reducing uncertainty.[41]
Motivation to reduce uncertainty (MRU) model[edit]
The uncertainty reduction theory also lead to the formation of a model originated by Michael W. Kramer. Kramer presents some major tenets and criticisms of the uncertainty reduction theory and then propose a Motivation to Reduce Uncertainty (MRU) model.[42]
MRU suggests that different levels of motivation to reduce uncertainty can lead to certain communication behaviors depending on competing goals.[42]
MRU suggests at least four different reasons for low motivation to seek information:[42]
People do not experience uncertainty in every event or encounter. Predictable or easily understood situations will not result in significant levels of uncertainty.[42]
Individuals have different levels of tolerance for uncertainty. The more one tolerates uncertainty the less information one seeks.[42]
Because communication always has social or effort costs,[43] minimizing those costs with limited effort may be preferable to information seeking.[42]
Individuals may also create certainty with minimal information seeking and without overt communication. For example, classification systems, such as stereotyping, create certainty out of uncertain situations.[42]
Research demonstrates that MRU could be used to examine how employees manage uncertainty during adjustment processes. MRU uses theoretical explanations for examining the approaches to understanding group decision making. "When groups are highly motivated to reduce the uncertainty surrounding a decision and there are no competing motives such as time or cost limitations, highly rational behaviors lead to information seeking to reduce uncertainty to optimize decisions."[42] MRU could be used at the organizational level to examine communication related to organizational strategy.[42]
Anxiety/uncertainty management theory[edit]
Inspired by Berger's theory, the late California State, Fullerton, communication professor William Gudykunst began to apply some of the axioms and theorems of uncertainty reduction theory to intercultural settings. Despite their common axiomatic format and parallel focus on the meeting of strangers, this theory contrasts uncertainty reduction theory by identifying reduction as only one of the many actions that people take when uncertainty arises.[44]
Gudykunst's anxiety/uncertainty management theory (AUM) also differs from Berger's uncertainty reduction theory in several significant ways. First, AUM asserts that people do not always try to reduce uncertainty. When uncertainty allows people to maintain positive predicted outcome values, they may choose to manage their information intake such that they balance their level of uncertainty. Second, AUM claims that people experience uncertainty differently in different situations. People must evaluate whether a particular instance of uncertainty is stressful, and if so, what resources are available.[45]
Gudykunst also points out that uncertainty reduction theory was formulated to describe the actions and behaviors of middle-class, white strangers in the United States. This is the demographic in the studies Berger and Calabrese used to develop the theory.[46]
Example: Online cancer research[edit]
Hurley, Kosenko and Brashers argue that 65% of internet-based cancer news is associated with the increase of uncertainty. In order of their degree of magnitude, information regarding treatment, prevention, detection, survivorship, and end-of-life issues yielded the most uncertainty. Given the inverse relationship between information-seeking behavior and uncertainty reduction, Hurley, Kosenko and Brashers assert that Uncertainty Management Theory may be more accurate and effective than uncertainty reduction theory. More research is needed to determine what computer-mediated communications exacerbate and help individuals manage their uncertainty regarding their health.[47]
Defense[edit]
Eleven years after uncertainty reduction theory was introduced, Berger published Uncertain Outcome Values in Predicted Relationships: Uncertainty Reduction Theory Then and Now. His aim was to defend his theory in new contexts and modify it, as necessary. Berger later proposed three types of information seeking behavior: passive (watching the interactant for clues in reactions to stimuli), active (posing questions to other individuals about the interactant), and interactive ( posing direct questions to the interactant).[6] Later research by Berger and Bradac (1982) indicated that disclosures by interactants may lead them to be judged as more or less attractive.[4] The judgment will determine whether the judge will continue to reduce their uncertainties or end the relationship. Berger also acknowledges the works of Gudykunst, et al. (1985) and Parks & Adelman (1983) to extend uncertainty reduction theory to the realm of more established relationships.[48]
See also[edit]
List of basic communication topics
References[edit]
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Jump up ^ Carr, C. T., & Walther, J. B. (2014). Increasing attributional certainty via social media: Learning about others one bit at a time. Journal of Computer‐Mediated Communication
^ Jump up to: a b Ryan, D., & Neuliep, J. (1998). "The influence of intercultural communication apprehension and socio-communicative orientation on uncertainty reduction during initial cross-cultural interaction". Communication Quarterly, 46(1), 88.
Jump up ^ Neuliep, J. (2012). "The relationship among intercultural communication apprehension, ethnocentrism, uncertainty reduction, and communication satisfaction during initial intercultural interaction: An extension of anxiety and uncertainty management (AUM) theory". Journal of Intercultural Communication Research, 41(1), 1.
^ Jump up to: a b Sanders, Judith A. & Wiseman, Richard L., (1993) Uncertainty Reduction Among Ethnicities in the United States Intercultural Communication Studies III:1
^ Jump up to: a b Imahori, T. (1986). A COMPARISON OF VERBAL BEHAVIORS AND INTERPERSONAL PERCEPTIONS BETWEEN INITIAL INTRACULTURAL AND INTERCULTURAL INTERACTIONS (UNCERTAINTY REDUCTION, COMMUNICATION, INTIMACY, SIMILARITY, ATTRACTION) (Order No. 8617988). http://search.proquest.com/docview/303508884
^ Jump up to: a b Kim, B. (1990). Reexamination of uncertainty reduction theory in intercultural communication: A case study of korean-americans (Order No. 9120355). http://search.proquest.com/docview/303899142
^ Jump up to: a b c Gudykunst, William B., and Tsukasa Nishida. "Individual and cultural influences on uncertainty reduction." Communications Monographs 51.1 (1984): 23-36.
^ Jump up to: a b Kanbur, A. S. (2002). "The intercultural hiring interview: Applying uncertainty reduction theory to the study of nonverbal behavior between Indian applicants and united states interviewers".
Jump up ^ Ragan, S. L. (1983). A conversational analysis of alignment talk in job interviews. In R.N. Bostrom (Ed.), Communication yearbook 7. Beverly Hills, CA: Sage.
Jump up ^ Jablin, Fredric, and Linda Putnam. The New Handbook of Organizational Communication: Advances in Theory, Research, and Methods. Thousand Oaks, Calif.: Sage Publications, 2001
^ Jump up to: a b Wien, Shery L. "The Employment Interview: Applying Perspectives of Uncertainty Reduction and Anticipatory Socialization." (1997). Web. 6 Oct. 2014.
Jump up ^ Carr, C. T., & Walther, J. B. (2014). Increasing attribution certainty via social media: Learning about others one bit at a time. Journal of Computer‐Mediated Communication
Jump up ^ Chretien, K. C., Goldman, E. F., Beckman, L., & Kind, T. (2010). It's your own risk: Medical students' perspectives on online professionalism. Academic Medicine
Jump up ^ Hogg, Michael A., David K. Sherman, Joel Dierselhuis, Angela T. Maitner, and Graham Moffitt. "Uncertainty, Entitativity and Group Identification." Journal of Experimental Social Psychology (2006)
Jump up ^ Stephan, Walter G, Cookie White Stephan, and William B Gudykunst. "Anxiety in Intergroup Relations: A Comparison of Anxiety/uncertainty Management Theory and Integrated Threat Theory." International Journal of Intercultural Relations (1999).)
Jump up ^ Hogg, M. A. (2000). Subjective uncertainty reduction through self-categorization:A motivational theory of social identity processes.European Review of Social Psychology
Jump up ^ Hogg, M. A. (2001a). Self-categorization and subjective uncertainty resolution: Cognitive and motivational facets of social identity and group membership. In J. P. Forgas, K. D. Williams, & L.Wheeler (Eds.), The social mind: Cognitive and motivational aspects of interpersonal behavior. New York: Cambridge University Press.
Jump up ^ Reid, S. A. "Uncertainty Reduction, Self-Enhancement, and Ingroup Identification." Personality and Social Psychology Bulletin (2005): 804-17
Jump up ^ Pratt,L., Wiseman, R.L., Cody, M.J. & Wendt, P.M. (1999). Interrogative Strategies and Information Exchange in Computer-Mediated Communication. Communication Quarterly, 47 (1), 44-66
^ Jump up to: a b c Gibbs, J.L. , Ellison, N.B. & Lai, C. (2011). First Comes Love, Then Comes Google: An Investigation of Uncertainty Reduction Strategies and Self-Disclosure in Online Dating. Communication Research, 38 (1), 70-100
^ Jump up to: a b c Antheunis, Marjolijn L., et al. "Interactive uncertainty reduction strategies and verbal affection in computer-mediated communication." Communication Research 39.6 (2012): 757-780.
Jump up ^ Antheunis, M. L.; Valkenburg, P. M.; Peter, J. (2010). "Getting acquainted through social network sites: Testing a model of online uncertainty reduction and social attraction". Computers in Human Behavior. 26: 100. doi:10.1016/j.chb.2009.07.005.
Jump up ^ Flanagin, A. J. (2007). Commercial markets as communication markets: Uncertainty reduction through mediated information exchange in online auctions. New Media & Society.
Jump up ^ Bajari, P. and A. Hortacsu (2003) 'The Winner's Curse, Reserve Prices and Endogenous Entry: Empirical insights from eBay Auctions', Rand Journal of Economics.
Jump up ^ Resnick, P. and R. Zeckhauser (2002) 'Trust among Strangers in Internet Transactions:Empirical Analysis of eBay's Reputation System', in M.R. Baye (ed.) The Economics of the Internet and e-Commerce.
Jump up ^ Standifird, S.S. (2001) 'Reputation and e-Commerce: eBay Auctions and the Asymmetrical Impact of Positive and Negative Ratings', Journal of Management.
Jump up ^ Hyperpersonal Interaction', Communication Research 23(1):Yokoo, M. and S. Fujita (2001) 'Trends of Internet Auctions and Agent-mediated Web Commerce', New Generation Computing
Jump up ^ Ramirez, A., J.B.Walther, J.K. Burgoon and M. Sunnafrank (2002) 'Information-seeking Strategies, Uncertainty and Computer-mediated Communication', Human Communication Research.
Jump up ^ May, A. & Tenzek, K.E. (2011). Seeking Mrs. Right: Uncertainty Reduction in Online Surrogacy Ads. Qualitative Research Reports in Communication, 12 (1), 27-33
^ Jump up to: a b Brashers, Dale E. (2001-09-01). "Communication and Uncertainty Management". Journal of Communication. 51 (3): 477–497. ISSN 1460-2466. doi:10.1111/j.1460-2466.2001.tb02892.x.
^ Jump up to: a b c Planalp, S., & Honeycutt, J. (1985). "Events that increase uncertainty in personal relationships." Human Communication Research, 11, 593-604.
Jump up ^ Kellermann, Kathy; Reynolds, Rodney (1990-09-01). "When Ignorance Is Bliss The Role of Motivation to Reduce Uncertainty in Uncertainty Reduction Theory". Human Communication Research. 17 (1): 5–75. ISSN 1468-2958. doi:10.1111/j.1468-2958.1990.tb00226.x.
^ Jump up to: a b c d e f g h i Kramer, MW. 1999. Motivation To Reduce Uncertainty: A Reconceptualization of Uncertainty Reduction Theory., Management communication quarterly, 13(2), 305. (ISSN 0893-3189).
Jump up ^ Miller, V. D., & Jablin, F. M. (1991). Information seeking during organization entry: Influences, tactics, and a model of the process. Academy of Management Review, 16, 92-120.
Jump up ^ Knoblock, Leanne (2010). "New Directions in Interpersonal Communication Research." New York: Sage.
Jump up ^ Maguire, K.C. (2007). Will It Ever End?: A (Re)examination of Uncertainty in College Student Long-Distance Dating Relationships.Communication Quarterly, 55 (4), 415-432
Jump up ^ Gudykunst, W. B. (1985). "The Influence of Cultural Similarity, Type of Relationship, and Self-Monitoring on Uncertainty Reduction Processes". Communication Monographs, 52, 203–217.
Jump up ^ Hurley, R.J., Kosenko, K.A. & Brashers, D. (2011). Uncertain Terms: Message Features of Online Cancer News. Communication Monographs, 78 (3), 370-390
Jump up ^ Berger, C. R. (1986). Uncertain Outcome Values in Predicted Relationships: Uncertainty Reduction Theory Then and Now Human Communication Research, 13, 34-38
Further reading[edit]
Deyo, J., Price, W. & Davis, L. (2011). Rapidly Recognizing Relationships: Observing Speed Dating in the South. Qualitative Research Reports in Communication, 12 (1), 71-78
Koester, J., Booth-Butterfield, M. & Booth-Butterfield, S. (1988). The Function of Uncertainty Reduction in Alleviating Primary Tension in Small Groups. Communication Research Reports, 5(2), 146-153
Ramirez, A. (2009). The Effect of Interactivity on Initial Interactions: The Influence of Information Seeking Role on Computer-Mediated Interaction. Western Journal of Communication, 73 (3), 300-325
Witt, P.L. & Behnke, R.R. (2006). Anticipatory Speech Anxiety as a Function of Public Speaking Assignment Type. Communication Education, 55(2), 167-177
Gudykunst, W. B., Shapiro, R., "Communication in Everyday Interpersonal and Intergroup Encounters," International Journal of Intercultural Relations, Vol. 20, 1996, pp. 19–45.
Goldsmith, D, J. (2001). A Normative Approach to the Study of Uncertainty and Communication. Journal of Communication, 514- 533
Sunnafrank, M. (1986), Predicted Outcome Value During Initial Interactions A Reformulation of Uncertainty Reduction Theory. Human Communication Research, 13: 3–33
Gudykunst, W. B., Yang, S.-M. and Nishida, T. (1985), A Cross-Cultural Test of Uncertainty Reduction Theory. Human Communication Research, 11: 407–454
Bradac, J. J. (2001). Theory Comparison: Uncertainty Reduction, ProblematicIntegration, Uncertainty Management, and Other Curious Constructs. Journal Of Communication,51(3), 456
External links[edit]
Em Griffin, the author of A First Look at Communication Theory, conducted an interview with Charles Berger on uncertainty reduction theory. During the interview, Berger explains how the theory came to exist, how it has evolved throughout the years, why he used axioms and thermos to develop the theory and the connection of uncertainty reduction theory to his work on cognitive plans and strategic communication.
Griffin, Em. (2014). A First Look at Communication Theory. Retrieved 6 December 2014.
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List of rail tunnels in India by length
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This is a list of the longest rail tunnels in India. In considering tunnels for this section, tunnels of underground metro railways have not been counted. Only tunnels on the main Indian Railways network longer than 2,000 metres (6,600 ft) have been listed.
Contents
[hide]
1 Location
2 The list
3 See also
4 References
Location[edit]
Most of the tunnels listed below are located in the Western Ghats, the only mountain range in the country that has good railway connectivity. There are longer tunnels that are under construction in the Himalayas in Jammu & Kashmir, as part of the JUSBRL Project.Pir Panjal Railway Tunnel, the 11.2 km long railway tunnel, passes through the Pir Panjal Range of middle Himalayas in Jammu and Kashmir. It is a part of its Udhampur - Srinagar - Baramulla rail link project, India's longest railway tunnel and reduced the distance between Quazigund and Banihal .[1]
The list[edit]
Rank
Name
Track length
(km)
Station
Station
State
Railway Division
Year of Opening
Coordination
1. Pir Panjal Railway Tunnel 11,215 metres (36,795 ft) Banihal Hillar Shahabad Jammu and Kashmir Northern Railway 2013 33°33′42″N 75°11′56″E / 33.5617942°N 75.1988626°E / 33.5617942; 75.1988626
2. Rohtang pass 8,000 metres (26,000 ft) Manali unknown Jammu and Kashmir enter here enter here
3. Karbude (T-35) 6,506 metres (21,345 ft) Ukshi Bhoke Maharashtra Konkan Railway 1997 17°6′9″N 73°24′59″E / 17.10250°N 73.41639°E / 17.10250; 73.41639
4. Nathuwadi (T-6) 4,389 metres (14,400 ft) Karanjadi Diwan Khavati Maharashtra Konkan Railway 1997 17°53′37″N 73°23′14″E / 17.89361°N 73.38722°E / 17.89361; 73.38722
5. Tike (T-39) 4,077 metres (13,376 ft) Ratnagiri Nivasar Maharashtra Konkan Railway 1997 16°58′48″N 73°23′42″E / 16.98000°N 73.39500°E / 16.98000; 73.39500
6. Berdewadi (T-49) 4,000 metres (13,000 ft) Adavali Vilawade Maharashtra Konkan Railway 1997 16°53′43″N 73°36′22″E / 16.89528°N 73.60611°E / 16.89528; 73.60611
7. Savarde (T-17) 3,429 metres (11,250 ft) Kamathe Savarde Maharashtra Konkan Railway 1997 17°27′35″N 73°31′19″E / 17.45972°N 73.52194°E / 17.45972; 73.52194
8. Barcem (T-73) 3,343 metres (10,968 ft) Balli Canacona Goa Konkan Railway 1997 15°3′49″N 74°1′54″E / 15.06361°N 74.03167°E / 15.06361; 74.03167
9. Borail (T-10) 3,235 metres (10,614 ft) Jatinga lampur New Haflong Assam Northeast Frontier Railway 2015
10. Karwar (T-80) 2,950 metres (9,680 ft) Karwar Harwada Karnataka Konkan Railway 1997
11. Chowk (T-3) 2,830 metres (9,280 ft) Panvel Karjat Maharashtra Central Railway 2006 18°55′5″N 73°17′10″E / 18.91806°N 73.28611°E / 18.91806; 73.28611
12. Parchuri (T-27) 2,628 metres (8,622 ft) Sangameshwar Ukshi Maharashtra Konkan Railway 1997 17°9′30″N 73°28′57″E / 17.15833°N 73.48250°E / 17.15833; 73.48250
13. Khowai (T-2) 2,472 metres (8,110 ft) Mungiabari Teliamura Tripura Northeast Frontier Railway 2008
14. Sangar (T-4) 2,445 metres (8,022 ft) Sangar Manwal Jammu and Kashmir Northern Railway 2005
15. Monkey Hill (T-25C) 2,156 metres (7,073 ft) Karjat Khandala Maharashtra Central Railway 1982
16. Aravali (T-21) 2,100 metres (6,900 ft) Aravali Sangameshwar Maharashtra Konkan Railway 1997
17. Chiplun (T-16) 2,033 metres (6,670 ft) Chiplun Kamathe Maharashtra Konkan Railway 1997 17°29′45″N 73°31′50″E / 17.49583°N 73.53056°E / 17.49583; 73.53056
18. Saranda(T-1) 2,000 metres (6,600 ft) Goilkera Sarenda Halt Jharkhand South Eastern Railway 1900 25°00′00″N 85°30′45″E / 25.00000°N 85.51250°E / 25.00000; 85.51250
19. Parsik tunnel 1,618 metres (5,308 ft) Thane Diva Junction Maharashtra Central Railway 1916
See also[edit]
Wikimedia Commons has media related to Railway tunnels in India.
Indian Railways
List of tunnels
List of longest tunnels
Tunnel
References[edit]
Jump up ^ "India's longest railway tunnel unveiled in Jammu & Kashmir". The Times of India. October 14, 2011. Retrieved October 14, 2011. One of the oldest railway tunnel being Jamalpur Tunnel dates back to 1860's located in Bihar.
Retrieved from "https://en.wikipedia.org/w/index.php?title=List_of_rail_tunnels_in_India_by_length&oldid=818298482"
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Railway tunnels in India
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