1
Communicating Organizational Change: Framing Messages using
Valence in order to reduce Resistance to Change
S. W. RIESKE University of Groningen Faculty of Economics and Business
Petrus Campersingel 147a 9713 AH Groningen
Tel: (06) 22750078
e-mail: s.w.rieske@student.rug.nl Supervisor: Tim Vriend
2
Communicating Organizational Change: Framing Messages
using Valance in order to reduce Resistance to Change
ABSTRACT
Resistance to change is a common issue for contemporary organizations. Adequate communication in the shape of change messages has been found to be an appropriate tool in managing resistance. However, the mechanisms behind this process remain vague. A model is tested which predicts the effectiveness of a change message by tailoring the message to an individual‟s regulatory focus using valance loaded statements on change goals and the current organizational state. In a laboratory study it was found that negative messages have a significant effect in the reduction of resistance to change by decreasing the perceived value of the current organizational state. For positive messages, no such effect was found. The effect of negative messages has not earlier been found in a change context, making them an innovative and practical tool for a change agent to manage resistance to change.
Keywords: Resistance to Change, Communication, Regulatory Focus, Valance, Messages, Experiment
INTRODUCTION
3 In attempts to understand resistance to change, various authors have uncovered a close link between communication and resistance to change (Reichers, Wanous, & Austin, 1997; Ford, Ford & D‟Amelio, 2008). Using communication, change agents can persuade the recipients to act on the change and thereby reducing resistance. Indeed, effective communication has been identified as one of the key predictors of successful organizational change (Lewin, 1951; Kotter, 1996; Goodman & Truss, 2004). However, little research is available on the mechanisms change agents can use to communicate aspects of these changes effectively (Goodman & Truss, 2004). As a consequence, ineffective communication is recognized as one of the main reasons for failure of change projects (Coulson-Thomas, 1997).
Understanding communication in a change setting can therefore be helpful for the agent in charge of the organizational change project (Goodman & Truss, 2004) and when done correctly, communication can be an effective strategy to alter the recipient‟s cognitions and emotions towards the change (Daly & Geyer, 1994). In a change project, the goal is to transform the organization from the current state (status quo) to the proposed state, which is the condition of the organization when the change goals are reached. The perceived value of either organizational state can be altered by using different communication styles which manipulate the relative value of each state. Following Fishbein and Ajzen‟s (1974) expectancy-value model, perceived value can be employed to get change recipients to act on the change. In order to do this, a high value towards the proposed state and a low value towards the current organizational state should be induced by the change communication.
In attempts to understand this process, various authors have developed frameworks on change communication which focus on communication content (Armenakis & Harris, 2002) and communication medium (Goodman & Truss, 2004). However, both frameworks do not answer how communication can persuade change recipients to act on a change and how it can influence the perceived value of both organizational states. A closer examination of change communication might provide the change agent with a practical tool to manage resistance.
4 situation. In contrast, prevention focused individuals are inherently aimed at means and outcomes which do not worsen their current situation. As a result, different focused individuals may interpret communication differently. Promotion focused individuals are aimed on improvements, so it can be expected that they are more sensitive to positive elements in communication. Prevention focused individuals are more aimed at avoidance, and are thus expected to be more sensitive to negative communicational elements (Brockner & Higgins, 2001).
Change agents can use this mechanism to increase the effectiveness of their communication by tailoring it to the recipient‟s regulatory focus (Spiegel et al., 2004). This can be done by adding positive or negative valence to change goals covered in the communication. Valence can load sentiments by using positive or negative phrasing and highlighting certain aspects of the change goals. The perceived value of those goals, and thus the proposed organizational state, is expected to be increased when portrayed positively. On the other hand, as the current organizational state is portrayed negatively, perceived value is expected to be reduced. Either option makes the change recipient want to move towards the proposed organizational state and thus reducing resistance.
The aim of this study is to develop and test a framework of communication in a change context, in order to increase the effectiveness of a change message. The valence of the change message influences the perceived value of the organizational state, depending on the change recipient‟s regulatory focus. The perceived value, in turn, impacts resistance to change.
5
THEORETICAL FRAMEWORK
Communication and message in a change context
Organizational change is an endeavor which intervenes in institutionalized organizational behavior and evokes participants to engage in new patterns. During a change project, numerous planned and emergent processes arise and bring up emotions such as ambiguity and insecurity for the persons affected (Mintzberg & Waters, 1985). Studies of change tend to have a „change agent-centric‟ view, in which those who attempt to execute a change are being thwarted by irrational behavior of change recipients (Ford, Ford & D‟Amelio, 2008). However, recent insights in the organizational change literature propose that change agents themselves play a distinctive role in the creation and stimulation of resistance to change. Their role as supervisor of the change project influences recipient‟s levels of resistance, involvement and uncertainty (Klein, 1996). Appropriate communication by the change agent is found to be able to handle these issues, and even to create readiness for change and other positive organizational outcomes (Daly and Geyer, 1994, Goodman & Truss, 2004). Proper communication in a change setting should fulfill the recipient‟s demand for information, which means that information provided by the change agent should include reasons to change and should attempt to mitigate the concerns of the recipient (Elving, 2005).
6 of this message shapes the „core sentiments‟ towards the change goals (Armenakis, Harris & Field, 1999, Armenakis & Harris, 2002).
The change process transforms the organization from the status quo to the proposed state, in which all change goals are attained. The proposed state is shaped by the change goals and targets covered in the change message and is the outcome of the change process. The change recipient awards a value towards either organizational state, based on his or her beliefs, supplemented with information from change agent‟s message (Fishbein, & Ajzen, 1974). It is expected that change recipients are more adoptive towards the organizational state with the highest value and want to move away from settings with a lower value.
The change agent has therefore the change message as a tool to manage the value of both organizational states. In order to do so, the change message should induce positive feelings towards the proposed state of the organization or negative feelings towards the current state. It has been found that an effective change message should address five domains in order to be effective (Armenakis, Harris & Field, 1999). One of these domains, valance, is where outcomes of the change for the change recipient are conceived. Phrasing in the message can load positive or negative valence to a specific outcome or goal and consequently the change recipient‟s levels of value towards both organizational states. This can be applied to the change message by portraying the proposed state in a positive way and the current state in a negative way.
The other content domains such as the justification for the change, the confidence in the ability to succeed in the change, the persuasion whether the change is appropriate and evidence of resources and commitment of the organization need to be addressed appropriately as well, but are not the focus of this study.
This results in the following hypotheses:
Hypothesis 1. A positive message on the proposed state is positively related to perceived value of the proposed state.
Hypothesis 2. A negative message on the current state is positively related to perceived value of the current situation.
Regulatory Focus
7 However, recent findings suggest that some individuals are more prone for positive elements in messages while others are more focused on negative elements. This effect makes the interpretation of message valence more profound. The interpretation process can be explained by Higgins‟ (1997) theory on regulatory focus. Regulatory focus comprises system which distinguishes two regulatory orientations: prevention focus and promotion focus. When in promotion focus, individuals are more sensitive to the presence and absence of gains and positive outcomes. In contrast, individuals in prevention focus are more sensitive to the presence and absence of losses and negative outcomes. Research on regulatory focus has shown that individuals have a chronic preference to either orientation (Higgins, 1998).
Regulatory focus finds its effects in various personal preferences (Gorman et al., 2012). Promotion focused individuals are concerned with growth, advancement and accomplishment and set their objectives based on goals, hopes, ideals, and aspirations. Promotion focused individuals are more concerned with responsibility, safety and security and set their objectives around duties, obligations, and necessities. These preferences are likely to make their appearance in a change setting. It has been confirmed that promotion focused individuals are generally more willing to adopt organizational change (Kark, & Van Dijk, 2007; Tseng & Kang, 2008).
In order to pick up on the recipient‟s regulatory focus, the message needs to fit with the regulatory preference. Altering the message valance could do so by conforming the phrasing of the organizational description to that preference. Promotion focused individuals are more focused on outcomes which improve their current situation. Therefore, they should be more sensitive to positive crafted messages. For prevention focused individuals, the sensitivity lies more on negatively crafted messages, as they are focused on avoiding worsening their current situation.
8 This results in the following hypotheses:
Hypothesis 1a. The effect of a positive message on value of the proposed state is stronger when the recipient has a promotion focus.
Hypothesis 2a. The effect of a negative message on fit with the current state is stronger when the recipient has a prevention focus.
Resistance to Change
Resistance is of frequent occurrence in the process of organizational change. Ansoff (1988) has defined resistance as a multifaceted phenomenon, which introduces unanticipated delays, costs and instabilities into the process of a strategic change. It is simply thought that such occurrences should be minimized as much as possible, as was proposed by early change scholars (Lewin, 1952; Daly & Geyer, 1994). However, recent insights have shown that resistance in the classic conception can be a source of utility as well (Piderit, 2000). Careful managed techniques used to cultivate resistance as a source of input for organizational effectiveness are increasingly popular among change scholars (Waddell & Sohal, 1998). Resistance to change therefore needs to be defined carefully.
Resistance in the classic sense may stem from the different approaches of agent and recipient have when engaging in organizational change. The change agent tries to determine “How will this get accomplished?” while the change recipient is more concerned by “What will happen to me?” (Gioia & Chittipeddi, 1991). This causes ambiguity and unexpected behavior on the side of the agent and the recipient‟s. This is usually interpreted by the change agent as resistance to change. In this case, it is not the resistance itself which needs to be reduced, but the behavior which intentionally or unintentionally hinders in the achievement of change targets and goals which, in turn, are there to increase organizational effectiveness. This counteractive behavior can be reduced when the agent-recipient relationship is managed effectively (Ford, Ford & D‟Amelio, 2008), in turn, input of change recipients can be cultivated to streamline the change targets and goals effectively.
9 this change is appropriate. This has shown to be able to increase the perceived value of the proposed organizational state and lower the perceived value of the current state.
The perceived value of an organizational state expected to precede the behavior of the change recipient towards that state (Fishbein, & Ajzen, 1974). High perceived value will induce adoptive behavior towards the organizational state, and thus low resistance to change. Consequently, low perceived value will induce resisting behavior towards an organizational state. As the goal of the change agent is to reduce resistance, two options can be distinguished; lowering the value of the current state or increasing the value of the proposed state. Increasing perceived value will use positive valence, while reducing perceived value will employ negative valence.
This results in the following hypotheses:
Hypothesis 3. The value of the proposed state mediates the relationship between change message and resistance to change.
Hypothesis 4. The value of the current state mediates the relationship between change message and resistance to change.
Valence Message Model
10
METHODOLOGY
Sample and data Collection
148 participants (73 female, 74 male, 1 unknown) were recruited from the faculty of Economics and Business of the University of Groningen. Participants were students who were mostly in the bachelor phase of their studies (N=116;78,4%). The average age of the sample was 20.97 years (SD=2.26). They were offered a monetary reward for participating in the study. Some participants partook as part of a course on research methodology and received course credits. The study took place in the research lab of the Faculty of Economics and Business at the University of Groningen, which boasts a controlled environment where the questionnaire could be administered. Participants were subjected to a one hour test which measured (i.a.) regulatory focus, regulatory fit, resistance righteousness and resistance to change. The test consisted of both a digital and a pen/paper section.
The study took place in a laboratory setting, in which one element (the change message) was conditional. The topic of resistance to change lends itself ideally to be measured in the field. However, the psychological elements of regulatory focus may very well be measured in a controlled setting such as a laboratory (For examples see Freitas et al. (2003) and Nolan & Harold (2010)) so confounds can be eliminated.
Scenario development
11 rated the sentiment of the positive message significantly more positive than the control message (t(8) = -2,2, p = 0.06) and the negative message significantly more negative compared to the control message (t(8)= -2,1, p = .07). This finding was confirmed with a manipulation check during the actual study, in which the participants indicated to what extent they found the message interesting, believable and informative. It was found that there were no significant differences in these variables between the conditions.
Measurements
Regulatory focus was measured by the 18-item General Regulatory Focus Measure (GRFM) developed by Lockwood, Jordan and Kunda (2002). The scale distinguishes between a promotion and prevention score, which was calculated by averaging 9 items on promotion (α = .86) and 9 items on prevention (α = .87). The scale has been found to have an average internal consistency estimate of .82 over 30 studies (Gorman et al., 2012). Items were formulated as: „In general, I am focused on preventing negative events in my life.‟ and „I often imagine myself experiencing good things that I hope will happen to me.‟, which were rated on a nine-item Likert scale.
Value was measured in two instances, for both the proposed and the current state. A direct measurement of perceived goal value was found to be most effective to assess the concept. The measurement instrument used a 1 (extremely worthless) to 5 (extremely valuable; Ajzen, 1991) scale in which the participant could rate the value of both situations. A multiple item scale, such as used by Latimer et al. (2008), was considered, but has not proven to yield valid measures.
Resistance to change was measured using a 17-item (α = .87) Resistance to Change (RTC) scale developed and validated by Oreg, 2003. Using a five-point Likert scale, statements such as „I‟m overwhelmed by all the things that need to be done because of the implementation of the XYZ system.‟ were rated by the participants. Oreg‟s instrument measures active and cognitive responses to the change, as well as the individuals functioning during the change.
Model testing
12 and Kenny (1986) was used, supplemented by a Sobel test (Sobel, 1982). To prove mediation, first, the relationship between predictor (change message) and outcome (resistance to change) was demonstrated. Second, the relationship between predictor and the hypnotized mediator (value) was analyzed for both organizational states, in combination with either promotion focus or prevention focus as a moderator. Third, the relationship between mediator and outcome was demonstrated. Finally, the last step to prove mediation was to find a significant effect in a Sobel test. For all mediation analyses, linear regression will be used. Statistical assumptions such as normal distribution, homoscedasticity and uncorrelated error terms were tested and found not to be violated. Independence among observations is ensured using the lab setting.
RESULTS Controls
The sample was controlled for age and gender effects. In a direct measurement of the variables, it was found that age had a significant impact on value of the current state (R2. = 044, B = .547, p = .01). As there is no theoretical evidence for such an effect, age is included as a covariate in model testing. Another notable finding showed that males scored significantly higher on prevention focus that females (F = 5,22, p = .024). This may have been caused by the GRFM-scale, which uses academic aspirations as an indicator. These aspirations are suggested to differ among gender (Mau & Bikos, 2000), which may have distorted the measurement. Gender is therefore also treated as a covariate in model analysis.
Direct Effect of Message on Resistance to change
In order to test the model, first the direct effect of independent variable (change message) on the main dependent variable (resistance to change) was established. Prior to this analysis, the scenarios were dummy coded from 1 to 3. In two separate linear regression tests, it was found that the positive message had an insignificant direct effect (β = -.20, p = .09) on resistance. The negative message also showed an insignificant effect (β = -.03, p = .71).
Moderating Effect of Regulatory Focus on Value
13 regression is believed to be appropriate to test the degree of moderation of regulatory focus. When testing the change message for value of the proposed state, the interaction with promotion focus was found to have no significant effect (β = .12, p = .43). For the current state, interaction with prevention focus was found to have a significant effect (β = -.30, p = .01). Hypothesis 1 is therefore not confirmed; hypothesis 2 is confirmed. Test results are displayed in table 1.
Table 1: Moderating effect of Regulatory Focus
Proposed State Current State
Variable β p R² β p R²
Model .12 .08 <.01 .56
Condition -.16 .83 -1.6 <.01
Promotion focus -.24 .32
Prevention focus -.57 <.01
Condition x Promotion focus .12 .43
Condition x Prevention focus .39 <.01
Age -.02 .46 -.09 <.01
Gender .17 .15 .10 .34
Note: n = 147.
Age was found as a significant covariate on value of the current state. (β = -.09, p < .01). This is an unexpected effect, which may be explained by an increasing level of inertia of older individuals. This effect has been identified by Hannan, & Freeman (1984) and makes older individuals more stringent on the current organizational state. It should however be noted, that the small distribution in age in the sample makes it improper to conclude that the effect found here is a confirmation of Hannan, & Freeman‟s (1984) findings.
Mediating effect of Value
14 (t = -2.00, p = .05) and the value of the current state (t= -3.51, p =<.01), therefore confirming the mediating effect of value in both cases. Therefore, hypothesis 3 and 4 are confirmed.
Table 2: Regression for integrated model
Positive Message Negative Message
Variable β p R² β p R² Model <.01 .25 <.01 .28 Condition -.20 .09 -.03 .71 Value (proposed/current) -.33 <.01 .28 <.01 Note: n = 147. DISCUSSION
The purpose of this study was to develop a framework for the potential manageability of change messages. The proposed framework employed regulatory focus, valance and value to influence resistance to change. So far, the topic of regulatory focus has not been applied to communication in a change context.
Theoretical Implications
For the effect on value, different results were found for the positive and the negative change message. The positive message was found not to alter a recipient‟s level of perceived value on the proposed situation. On the other hand, the negative message was able influence the level of value for the current state. This suggests that negative valance is more powerful to affect perceived value than positive valence. The stronger reaction towards negative valence has been found before in earlier studies on marketing messages (Bolls, Lang, & Potter, 2001) and may be explained by human‟s primal reaction towards negative emotions, including valence (Aggleton, & Young, 2000, p. 318). This effect has earlier not been found in a change communication context.
15 findings from other studies. There is evidence for moderating effects of both types of regulatory focus on similar concepts as perceived value, such as behavioral intent (Cesario et al, 2004; Latimer et al, 2005). This inconsistency of findings might be explained by the study‟s lab setting and sample, as these are both elements which are different for the target population of this study, and form a different set up than the before mentioned studies. Nevertheless, the negative „route‟ of the model proved to be significant, which increases the employment value of negative valence in a change setting.
The effect of value on resistance to change was proven to be significant for both organizational states. The perceived value change goal, or the proposed organizational state, is a predictor for behavior with regards to that goal. High perceived value will produce adoptive behavior, which is a low resistance to change. Low perceived value will produce the opposite effect. These findings are in line with expectancy-value theory.
Limitations
The generalizability of this study is limited because of the homogeneity in the student sample. Control factors such as education, age and gender may play a role a change context (as suggested by Abdulhamid, 2011), although the control covariates showed no extra indication of effect. In addition, tenure is also recognized as an important source of individual inertia (van Dam, Oreg, & Schyns, 2008) which was not included in this study due to the laboratory setting. Other confounds which appear in an organizational setting are likely to also play a role in the creation of resistance to change. Nevertheless, the internal and external validity of lab studies has proven to be at least equal to field studies (Andersn, Lindsay, & Bushman, 1999, making the findings not neglectable.
16 which in centered on the „value derived from fit‟ (Higgins, 2000) and naturally the concept of perceived value. Experiments with similar messages have shown significant result in a laboratory setting (Shah et al., 1998). Applying this method would have left valance and costs less open for interpretation of the participant and would therefore have increased the value of the experiment.
The measurement of value was partly inspired by earlier research (Latimer et al. 2008) but has not yet been validated. In addition, the construct was formed by a single measure which lowers the reliability of the measurement instrument and forms and important limitation. A multi- item instrument, such as developed by Sweeney & Soutar, (2001), would have improved this study.
Finally, another important confound which has not been dealt with in this study‟s set up is situational regulatory focus. Some studies (Higgins, 2001) showed that regulatory focus is not predispostional, but also context dependent. Messages have been found to induce a specific regulatory focus, which could have intervened with the GRFM measurement and made the regulatory focus measure unreliable. A repetition of this experiment should include situational regulatory focus in its design.
Managerial implications
Change agents need to be aware that their change messages play an important role in the change process. Messages can influence the perceived value of an organizational state and can, when used correctly, make change recipients want move away from the current organizational state. Remarkably enough, positive valence has no effect on how the change goals are valued. This is inconsistent with popular management schools such as appreciative inquiry which focus on positivity (Whitney & Trosten-Bloom, 2010). The employment of positive valence in a change setting should therefore be well considered by the change agent. In contrast, negative messages are found to have a negative effect on perceived value of the current state, which is increased when the change recipient has a prevention focus. The usability of negative messages may be underestimated. Change agents should therefore, perhaps counter intuitively, be aware of the effects of negative valence in a change setting.
17 proposed state and minimize the value of the current state. Tools to do so may be found beyond the scope of this study, although negative message valance forms a ready to use practicality.
Future research
For future research directions, three options come to mind. First, this study‟s most important finding on the effect of negative valance in messages needs to be examined further. A good addition to the model might be a combination of positive and negative valence in one message, in order to influence value on both organizational states. Other additions may be found around the concept of perceived value, which is expected to have various antecedents and consequents. A concept such as regulatory fit (Higgins, 2000) theoretically precedes perceived value and may be of importance in the light of regulatory focus. Second, for the experiment itself, it is self-evident that a repetition in an organizational setting relevant to test if similar effects occur. However, the measures have room for improvement, as well as sample diversity. Finally, the effect of negative valence and regulatory focus may be used in more applications beyond the scope of organizational behavior and other business related disciplines.
CONCLUSION
Resistance to change remains a complex phenomenon which can only be explained to a small amount by change communication. The black box of psychological processes surrounding resistance is yet to be fully opened, although effects of regulatory fit and valence will make their appearance there. Valence in a change communication context is a new approach to capture resistance and has proven to have an effect for negative messages. This can be a practical tool for the change agent, who may be able to use these findings in change projects. However, more antecedents of communication in a change setting may be discovered and it can be concluded this will remain a promising field of study.
REFERENCES
18
Aggleton, J.P., & Young, A.W. (2000). The enigma of the amygdala: On its contribution to human emotion. In R.D. Lane & L. Nadel (Eds.), Cognitive neuroscience of emotion. (p. 318) New York: Oxford University Press.
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211
Anderson, C. A., Lindsay, J. J., & Bushman, B. D. (1999) Research in the Psychological Laboratory: Truth or Triviality?. Current Directions in Psychological Science, 8(1): 3-9.
Ansoff, I.H. (1990), Implanting Strategic Management, Prentice Hall International Ltd, London.
Armenakis, A. A., Harris, S. G. (2002). Crafting a change message to create transformational readiness. Journal of Organizational Change Management, 15(2): 169-183.
Armenakis, A. A., Harris, S. G., Field, H. S. (1999). Making change permanent: a model for institutionalizing change. Journal of Change and Development, 12: 97-128.
Bolls, P. D., Lang, A., & Potter, R. F. (2001). The effects of message valence and listener arousal on attention, memory, and facial muscular responses to radio advertisements. Communication Research, 28(5), 627-651.
Brockner, J., & Higgins, E. T. (2001). Regulatory focus theory: Implications for the study of emotions at work. Organizational Behavior and Human Decision Processes, 86(1), 35-66.
Cesario, J., Grant, H., & Higgins, E.T. (2004). Regulatory fit and persuasion: Transfer from “feeling right”. Journal of Personality and Social Psychology. 86:388–404.
Coulson-Thomas, C., (1997). Strategic vision or strategic con? Rhetoric or reality?, in: C. A. Carnall (Ed.) Strategic Change.
Daly, J. P., & Geyer, P. D. (1994). The role of fairness in implementing large‐scale change: Employee evaluations of process and outcome in seven facility relocations. Journal of Organizational Behavior, 15(7): 623-638.
van Dam, K., Oreg, S., & Schyns, B. (2008). Daily Work Contexts and Resistance to Organisational Change: The Role of Leader–Member Exchange, Development Climate, and Change Process Characteristics. Applied Psychology: An International Review, 57(2): 313-334.
Dent, E., & Goldberg, S. (1999). Challenging “resistance to change.” Journal of Applied Behavioral Science, 35: 25-41.
Elving P., (2005). The role of communication in organisational change Corporate Communications 10(2): 129-138.
Goodman, J, Truss, C., (2004). The medium and the message: communicating effectively during a major change initiative. Journal of Change Management, 4(3): 217–228.
Gioia, D. A., Chittipeddi, K. 1991. Sensemaking and sensegiving in strategic change initiation. Strategic Management Journal, 12: 433–448.
Gorman, C. A., Meriac, J. P., Overstreet, B. L., Apodaca, S., McIntyre, A. L., Park, P., & Godbey, J. N. (2012). A meta-analysis of the regulatory focus nomological network: Work-related antecedents and consequences. Journal of Vocational Behavior, 80(1), 160-172.
Fishbein, M.. & Ajzen, 1. (1974). Attitudes toward objects as predictors of single and multiple behavioral Criteria. Psychological Review, 81.
Ford, J.D., Ford, L.W., D‟Amelio, A. (2008). Resistance to Change: The rest of the Story. Academy of Management Review, 33(2): 362–377.
Freitas, A. L., Higgins, E. T., Idson, L. C., Spiegel, S. & Molden, D. C. (2003) Transfer of Value From Fit. Journal of Personality and Social Psychology. 84(6): 1140-1153.
Hannan, M. T., & Freeman, J. (1984). Structural inertia and organizational change. American sociological review, 149-164.
19
Higgins, E. T. (1998). Promotion and prevention: Regulatory focus as a motivational principle. Advances in Experimental Social Psychology, 30: 1– 46.
Higgins, E. T. (2000). Making a good decision: Value from fit. American Psychologist, 55: 1217–1230.
Higgins, E. T., Friedman, R.S., Harlow, R. E., Idson, L. C., Ayduk, O. N., & Taylor, A. (2001). Achievement orientations from subjective histories of success: Promotion pride versus prevention pride. European Journal of Social Psychology. 31:3–23.
Hoag, B. G., Ritschard, H. V., & Cooper, C. L. (2002). Obstacles to effective organizational change: the underlying reasons. Leadership & Organization Development Journal, 23(1), 6-15.
Kirmani, A., & Zhu, R. (2007). Vigilant against manipulation: The effect of regulatory focus on the use of persuasion knowledge. Journal of Marketing Research, 688-701
Kark, R., & Van Dijk, D. (2007). Motivation to lead, motivation to follow: The role of the self-regulatory focus in leadership processes. Academy of Management Review, 32(2), 500-528.
Klein, S. M. (1996). A management communication strategy for change. Journal of Organizational Change Management, 9(2): 32-46.
Kotter, J. 1996. Leading change: Why transformation efforts fail. Harvard Business Review, 73(2): 59–67.
Latimer, A. E., Katulak, N. A., Mowad, L., & Salovey, P. (2005). Motivating cancer prevention and early detection behaviors using psychologically tailored messages. Journal of health communication, 10(1): 137-155. Latimer, A. E., Rivers, S. E., Rench, T. A., Katulak, N. A., Hicks, A., Hodorowski, J. K., ... & Salovey, P. (2008). A
field experiment testing the utility of regulatory fit messages for promoting physical activity. Journal of experimental social psychology, 44(3): 826-832.
Lewin, K. (1952). Field theory in social science: Selected theoretical papers. London: Tavistock. Lockwood, P., Jordan, C.H., Kunda, Z. 2002. Motivation by positive or negative role models: regulatory focus determines who will best inspire us, Journal of Personality and Social Psychology, 83: 854-64. Mau, W. C., & Bikos, L. H. (2000). Educational and vocational aspirations of minority and female students: A
longitudinal study. Journal of Counseling & Development, 78(2), 186-194.
Maurer, R. (1996). Beyond the wall of resistance: Unconventional strategies that build support for change. Bard. Mintzberg, H., & Waters, J. (1985). Of strategies, deliberate and emergent. Strategic Management Journal, 6:
257–272.
Nadler, D. A. (1981). Managing organizational change: An integrative perspective. The Journal of Applied
Behavioral Science, 17(2), 191-211.
Noland, K. P., & Harold, C.M. (2010) Fit with what? The influence of multiple self-concept images on organizational attraction. Journal of Occupational and Organizational Psychology. 83: 645–662. Oreg, S. 2003. Resistance to Change: Developing an Individual Differences Measure, Journal of Applied
Psychology, 88(4): 680–693.
Piderit, S. K. (2000). Rethinking resistance and recognizing ambivalence: A multidimensional view of attitudes toward an organizational change. Academy of management review, 25(4): 783-794.
Reichers, A. E., Wanous, J. P., & Austin, J. T. (1997). Understanding and managing cynicism about organizational change. The Academy of Management Executive, 11(1), 48-59.
Rothman, A.J., & Salovey, P. (1997) Shaping perceptions to motivate healthy behavior: The role of message framing. Psychological Bulletin.121:3–19.
Shah, J., Higgins, E.T., & Friedman, R.S. (1998) Performance incentives and means: How regulatory focus influences goal attainment. Journal of Personality and Social Psychology. 74:285–293.
Spiegel, S., Grant‐Pillow, H., & Higgins, E. T. (2004). How regulatory fit enhances motivational strength during goal pursuit. European Journal of Social Psychology, 34(1), 39-54.
Stone, E. F., & Hollenbeck, J. R. (1989). Clarifying some controversial issues surrounding statistical procedures for detecting moderator variables: Empirical evidence and related matters. Journal of Applied Psychology, 74(1), 3-10.
20 Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: the development of a multiple item
scale. Journal of retailing, 77(2), 203-220.
Tseng, H. C., & Kang, L. M. (2008). How does regulatory focus affect uncertainty towards organizational change?. Leadership & Organization Development Journal, 29(8), 713-731.
Waddell, D., & Sohal, A. S. (1998). Resistance: a constructive tool for change management. Management Decision, 36(8), 543-548.
21 APPENDIX 1
Example of scenario: current state and negative valance:
You work in the planning department of a large production firm. You work in a team which is responsible for the planning of the production lines, which means that you put orders into the planning system. Your team uses the ABC IT-system, which makes you able to plan orders so the production department can start producing the right order at the right time.
A few moments ago, you received the following message from your team leader. Dear …,
The company is planning to change the planning IT-system. As you know, we are currently working with the ABC IT-system. This system is known for its annoying errors, is not user friendly and is heavily outdated. The management has approved to abandon this system and has decided to implement the XYZ IT-system. This will change your work routine as the system has a different work procedure. However, the change should be manageable, since we are a great team and have faced greater challenges in the past. Best regards,
Michael Johnson
