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Beaudry & Pinsonneault/User Responses to IT

MIS Quarterly Vol. 29 No. 3, pp. 493-524/September 2005 493

RESEARCH ARTICLE

UNDERSTANDING USER RESPONSES TOINFORMATION TECHNOLOGY: A COPINGMODEL OF USER ADAPTATION1

By: Anne BeaudryJohn Molson School of BusinessConcordia University1455 de Maisonneuve Boulevard WestMontréal, QC H3G [email protected]

Alain PinsonneaultFaculty of ManagementMcGill University1001 Sherbrooke Street WestMontréal, QC H3A [email protected]

Abstract

This paper defines user adaptation as the cogni-tive and behavioral efforts performed by users tocope with significant information technology eventsthat occur in their work environment. Drawing oncoping theory, we posit that users choose differentadaptation strategies based on a combination ofprimary appraisal (i.e., a user’s assessment of the

1Ritu Agarwal was the accepting senior editor for thispaper. Susan Brown was the associate editor. BradleyWheeler, Pamela Carter, and Julie Rennecker served asreviewers.

expected consequences of an IT event) andsecondary appraisal (i.e., a user’s assessment ofhis/her control over the situation). On that basis,we identify four adaptation strategies (benefitsmaximizing, benefits satisficing, disturbancehandling, and self-preservation) which are hypo-thesized to result in three different individual-leveloutcomes: restoring emotional stability, minimizingthe perceived threats of the technology, andimproving user effectiveness and efficiency. Astudy of the adaptation behaviors of six accountmanagers in two large North American banksprovides preliminary support for our model. Byexplaining adaptation patterns based on users’initial appraisal and subsequent responses to an ITevent, our model offers predictive power whileretaining an agency view of user adaptation. Also,by focusing on user cognitive and behavioraladaptation responses related to the technology,the work system, and the self, our model accountsfor a wide range of user behaviors such as tech-nology appropriation, avoidance, and resistance.

Keywords: Coping theory, user adaptation, ITappropriation, individual performance

Introduction

The introduction of a new information technologygenerates a multitude of expected and unexpected


494 MIS Quarterly Vol. 29 No. 3/September 2005

consequences in the users’ environment (Griffith1999; Weick 1990). These consequences areinterpreted and understood in a variety of ways byusers, triggering equally plentiful, varied, andcomplex user responses (Griffith 1999; Pinson-neault and Rivard 1998). Researchers, managers,and information systems professionals face thecritical but daunting task of explaining why, andtrying to predict how, users will react to newtechnologies. To date, two main streams ofresearch have addressed this complex phenom-enon. The first stream, which has applied avariance approach, has mainly focused on theantecedents of adoption and usage of newtechnologies and has yielded numerous models ofuser acceptance (Venkatesh et al. 2003). Fourmodels have identified factors that can influenceuser adaptation (e.g., performance expectancy,social influence, task-technology fit, and com-patibility) and are particularly relevant to thispaper, namely the technology acceptance model/unified theory of acceptance and use of technology(TAM/UTAUT) (Davis 1989; Davis et al. 1989;Venkatesh et al. 2003), innovation diffusion theory(IDT) (Rogers 1983), decomposed theory ofplanned behavior (DTPB) (Taylor and Todd1995b), and task-technology fit (TTF) (Dishaw andStrong 1999; Dishaw et al. 2002; Goodhue 1995;Goodhue and Thompson 1995; Zigurs andBuckland 1998; Zigurs et al. 1999).

The second stream of research has mainly reliedupon a process approach and has focused onuser adaptation (Orlikowski 1996; Tyre and Orli-kowski 1994, 1996) and its effects on outcomessuch as group performance (DeSanctis and Poole1994; Majchrzak et al. 2000). This stream showedthe rich and complex nature of user adaptation anddescribed how users change their skills, knowl-edge, beliefs, attitudes, aspirations, and workcommitment (Majchrzak and Cotton 1988; Tyreand Orlikowski 1994), modify their work proce-dures and communication patterns (Leonard-Barton 1988; Poole and DeSanctis 1988, 1990),and adapt/use the technology in unanticipatedways (Griffith 1999; Kraut et al. 1989).

While these two streams of research haveprovided significant insights into different aspectsrelated to user adaptation, the extant research is

fragmented and has evolved over the years in afairly nonintegrated way. There is a need to pro-gress toward a framework that integrates bothapproaches and allows studying the antecedents,behaviors, and outcomes of user adaptationtogether. This paper takes the study of user adap-tation a step further in that direction by proposingan integrative model, the coping model of useradaptation (CMUA). The fundamental premise ofCMUA is that the introduction of a new technologyor the modification of an exiting one can bringabout changes that are perceived as novel (Louisand Sutton 1991) and can constitute a disruptionin organizations (Lyytinen and Rose 2003).Adaptation behaviors are, in fact, acts that usersperform in order to cope with the perceivedconsequences of the technological event. Bydefining user adaptation as coping, we can studya wide range of user responses including howusers restore emotional stability, modify theirtasks, reinvent and adapt the technology, or evenresist it. We can also understand the antecedentsand effects of these user behaviors. Consideringuser adaptation as coping also allows us to studyuser behaviors that occur before, during, and afterthe implementation of a new technology.

The paper is organized into five sections. The firstsection presents the coping theory and describesthe coping process. The second section sum-marizes the extant literature on user adaptation,conceptualizes user adaptation as coping, andpresents the coping model of user adaptation(CMUA) and our research propositions. The thirdsection describes the research method and thefourth section presents the results of our study.The last section discusses the contributions andimplications of our paper and suggests an agendafor future research.

Coping Theory

Coping: An Overview

Coping deals with the adaptational acts that anindividual performs in response to disruptiveevents that occur in his/her environment. In the


MIS Quarterly Vol. 29 No. 3/September 2005 495

contextual model, identified as the one most widelyused and accepted in psychology (Lazarus 2000),2

coping is defined as “the cognitive and behavioralefforts exerted to manage specific external and/orinternal demands that are appraised as taxing orexceeding the resources of the person” (Lazarusand Folkman 1984, p. 141). Cognitive efforts suchas acceptance, distancing, and escaping aim ataltering the subjective meaning of the event whilebehavioral efforts, which include activities such asseeking additional information and evidence andconfronting individuals, aim at altering the situationitself (Folkman and Lazarus 1985; Lazarus andFolkman 1984). Internal demands are personaldesires or requirements that the environment mustmeet, for example, an individual’s desire to getchallenging work versus the challenges that aspecific job effectively carries (French et al. 1974).External demands emanate from the contextual orsocial environment and must be met by indi-viduals. They are related to the roles one has toplay in a given environment, for example, a secre-tarial position requiring a typing speed of 50 wordsper minutes versus the effective typing ability of acandidate. Finally, the ways in which people copedepend upon the resources (financial, material,physical, psychological, cognitive, and social) thatare available to them (Lazarus and Folkman1984).

The Coping Process

Individuals cope with disruptions by using two keysubprocesses that continuously influence eachother (Lazarus 1966; Lazarus and Folkman 1984).First, individuals evaluate the potential conse-quences of an event (appraisal). They assess thenature of the particular event and its personalimportance and relevance (primary appraisal). Inother words, when a disruption occurs, one firstasks: “What is at stake for me in this situation?”The paramount issue is to determine what are the

likely consequences (specific internal/externaldemands) of this event and what is the personalsignificance of the disruption (Folkman 1992). Inmanagement, disruptive events have been cate-gorized into two main types: challenges, which areevents perceived as having positive conse-quences, or threats, defined as events perceivedas having negative consequences (Carpenter1992; McCrae 1989). Events are multifaceted andthey are usually perceived as comprising bothchallenges and threats (Lazarus and Folkman1984). In addition to assessing the importance ofan event, individuals also evaluate the copingoptions available to them (secondary appraisal).They determine the level of control they exert overthe situation and what they feel they can do aboutit given the coping resources available to them(Lazarus and Folkman 1984).

Second, individuals perform different actions todeal with the situation at hand (coping efforts).They rely on a combination of cognitive andbehavioral efforts, both of which have beencategorized as either problem- or emotion-focused(Folkman 1992; Lazarus and Folkman 1984; Stoneet al. 1992). Problem-focused coping aims atmanaging the disruptive issue itself. It is orientedtoward dealing with the specific aspects of thesituation by changing the environment (e.g.,altering or alleviating environmental pressures,barriers, resources, or procedures) or changingone’s self (e.g., developing new standards ofbehavior, shifting levels of aspiration, finding newchannels of gratification, and learning new skills orprocedures) (Lazarus and Folkman 1984).Emotion-focused coping changes one’s perceptionof the situation, but does not alter the situationitself. It aims at regulating personal emotions andtensions, restoring or maintaining a sense ofstability, and reducing emotional distress (Lazarusand Folkman 1984). Emotion-focused coping isoriented only toward one’s self and includesminimizing the consequences of threats (e.g.,maintaining hope and optimism, refusing toacknowledge the negative side of an event), posi-tive comparison (e.g., comparing one’s situationwith other situations that are worse off), situationredefinition and passive acceptance, avoidance(e.g., escaping the situation), denial (e.g., denying

2Space limitation does not allow us to discuss the otherperspectives used to study coping behaviors. Readerscan consult Folkman (1992) and Lazarus and Folkman(1984) for an extensive discussion of the topic.



the facts and their implications and acting as if theevent never happened), selective attention,venting anger, and seeking psychological oremotional support (Folkman et al. 1986; Lazarusand Folkman 1984; McCrae 1989; Stone et al.1992).

The specific combination of problem- and emotion-focused coping efforts depends upon one’sappraisals of a given situation (Lazarus and Folk-man 1984). Individuals tend to choose the copingstrategy that promises the greater chance ofsuccess and the restoration of a sense of wellbeing (Begley 1998). Consequently, emotion-focused coping occurs mainly when individuals feelthat they have limited control over the situation(Folkman 1992; Folkman et al. 1986; Folkman andMoskowitz 2000; Lazarus and Folkman 1984).Over-relying on problem-focused coping in such asituation leads to frustration and distress, whilehaving little effect on the issue at hand (Begley1998; Cohen et al. 1986; Folkman 1992). Alter-natively, problem-focused coping occurs primarilywhen individuals feel that they are in control of thesituation (Folkman 1992; Folkman et al. 1986;Folkman and Moskowitz 2000; Lazarus andFolkman 1984). In this case, relying heavily onemotion-focused coping rather than handling thesituation is likely to result in frustration (Begley1998; Folkman 1992). Coping theory indicatesthat in extreme cases, when the expected con-sequences of an event are threatening and thesituation is perceived as being insurmountable ortoo demanding, individuals might withdraw fromthe situation and consciously escape from it, forexample, by asking for a transfer, quitting a job, orretiring (Begley 1998).

The entire coping process can occur in whatpsychologists call the anticipation period, beforethe event actually occurs, the impact period, as theevent happens, or the post-impact period, after theevent has taken place (Folkman 1992). Becauseit explains individuals’ adaptation behaviors con-ducted in response to changes that occur in theirenvironment, coping theory offers a new lensthrough which to study how and why users adaptto IT in organizations. It also provides theconceptual foundation to enable the development

of an integrative model that allows a richerunderstanding of this complex organizationalphenomenon.

The Coping Model of UserAdaptation (CMUA)

User adaptation has been diversely understoodand defined in Information Systems. As shown inTable 1, different labels are used by Clark (1987),Ives and Olson (1984), Leonard-Barton (1988),Poole and DeSanctis (1988), and Rice and Rogers(1980) to describe the modifications made to atechnology by users. Furthermore, similar con-cepts are defined differently across studies. See,for example, the competing definitions of “adapta-tion” in Leonard-Barton (1988), Sokol (1994), andTyre and Orlikowski (1996). However, Table 1indicates that the studies all fundamentally focuson a key phenomenon: the way users respond tochanges or disruptions induced by IT (Clark 1987;Leonard-Barton 1988; Tyre and Orlikowski 1994).In essence, user adaptation is very similar to theconcept of coping. Therefore, we define useradaptation as the cognitive and behavioral effortsexerted by users to manage specific conse-quences3 associated with a significant IT event4

that occurs in their work environment. This defi-nition reconciles and integrates the various dimen-sions studied in prior research (see Table 1). Assuch, the process of user adaptation can thus beunderstood in light of coping theory.

3Consequences and demands are used interchangeablyin the literature on coping. To avoid confusion, we onlyuse the term consequences.

4Modifications made to an existing IT can sometimes beperceived as significant enough to stimulate similar userresponses as with the implementation of a new IT(Griffith 1999; Louis and Sutton 1991). We use “ITevent” to refer to both the implementation of a new IT aswell as significant modifications made to an existing IT.



Table 1. User Adaptation

Authors Concept Working Definition Focus

Rice and Rogers(1980)

Reinvention The extent to which an innovation is changedduring its adoption and implementation.

Technology

Ives and Olson(1984)

Adaptation Alignment or alteration of the technology in sucha way that it meets users’ needs.

Technology

Clark (1987) Appropriation A situation where the user starts by recognizingthe potential value of a particular IT and managesto narrow the absorption gap between therequirements of the IT and its own limited capa-cities, then begins to creatively modify, refine,and use it in such a way that it will meet his/herneeds. Appropriation implies the continuous,cumulative, and incremental modification of aninnovation in all its aspects (p. 156).

Technology

Leonard-Barton(1988)

Reinvention The alteration of the initial innovation as userschange it to suit their needs or use it in waysunforeseen by developers (p. 253).

Technology

Leonard-Barton(1988)

Adaptation The reinvention of the technology and the simul-taneous adaptation occurring at multiple levelswithin the organization (p. 253).

Technology,Work system

Majchrzak and Cotton (1988)

Adjustment Has four different aspects: changes in job satis-factions, work commitment, psychological andstress problems, and perceived quality of life (p.48).

User

Poole andDeSanctis (1988)

Appropriation Concerns alterations brought by users to thetechnology while using it (p. 9).

Technology

Poole andDeSanctis (1990)

Appropriation The way a group uses, adapts, and reproducesthe structures of a technology.


DeSanctis andPoole (1994)

Appropriation Is visible through acts that reveal a deepstructuration process of IT use.


Sokol (1994) Adaptation The modifications brought to the technology, theenvironment, social protocols, others expecta-tions, and the development of contingency plans.


Tyre andOrlikowski (1994)

Adaptation Refers to the adjustments and changes followingthe new IT implementation. The adaptations mayconcern the physical aspects of the technologyas well as the procedures, beliefs, knowledge, orrelationships of the users (p. 99).

Technology,Work system,

User

Orlikowski (1996) Appropriation The continuous, progressive, and mutual adjust-ments, accommodations, and improvisationsbetween the technology and the users (p. 69).

Technology,User

Tyre andOrlikowski (1996)

Adaptation Modifications brought to the technology, workingprocedures, and users’ beliefs (p. 791).

Technology,Work system,

User



Assessing an IT Event: Appraisal

As discussed in the section on coping theory, theassessment of an IT event starts with primaryappraisal. At this stage, the user determines theexpected consequences of the IT event and howthey are likely to affect him/her both personally andprofessionally. For example, a user might thinkthat a new system will make her job less tediousand more interesting and that she will need tolearn new skills and to adapt her working proce-dures. Another user might be afraid of losing hisjob and think that he does not have the necessaryskills to obtain a new and interesting job.Consequences can be categorized as eitherthreats or opportunities (Chattopadhyay et al.2001; Dutton and Jackson 1987; Jackson andDutton 1988; Milburn et al. 1983). However, dueto the fact that most IT events are multifaceted,they are likely to be assessed as containing bothtypes of expected consequences (Beaudry andPinsonneault 2001; Cartwright and Cooper 1996;Louis and Sutton 1991) and it is their relativeimportance that influences what adaptation effortswill occur (Lazarus and Folkman 1984).

As shown in Figure 1, user adaptation in CMUA istriggered by a significant IT event that disrupts thework environment of users. More specifically, useradaptation starts when a user gains an awarenessof the potential consequences of a significant ITevent and evaluates them to be of personal and/orprofessional relevance and importance (i.e., anopportunity or a threat) (Folkman 1992; Griffith1999; McCrae 1984). Because individual usersare likely to have asymmetrical information aboutthe IT event and because they synthesizeinformation differently (Fiske and Taylor 1991;Griffith 1999; Lewis et al. 2003; Louis and Sutton1991), users are likely to begin the adaptationprocess at different points. Some users mightbegin adapting when they first hear of theforthcoming IT event, while others might beginadapting when the IT event occurs, and still othersmight adapt later, only after they have startedinteracting with the technology. The triggering ofthe adaptation process is also likely to beinfluenced by a number of individual charac-

teristics (Griffith 1999; Louis and Sutton 1991).For example, personal innovativeness, whichrepresents the degree to which users are willing totry out new IT (Agarwal and Prasad 1998, Lewis etal. 2003) might influence the point at which usersbegin their adaptation process. Similarly, Rotter(1966) suggests that an individual with a strongbelief about his ability to control his destiny(internal locus of control) is likely to be more alertto environmental stimuli, suggesting that userswith high internal locus of control might startadapting sooner (Louis and Sutton 1991).

While coping theory is mute regarding whatelements of a disruption are used in primaryappraisal, the IS literature provides some insightson this issue. Numerous authors have suggestedthat users’ beliefs are mainly developed basedupon their understanding of certain key aspects ofa technology (Davis 1989; Griffith 1999; Mooreand Benbasat 1991; Rogers 1983; Venkatesh etal. 2003). For example, Griffith (1999) argued thata new or adapted feature of a technology that isseen as concrete, meaning that it can be directlyand specifically observed and described (asopposed to abstract), or core, referring to a dimen-sion that is critical to the functionality, or the goalof a technology (as opposed to tangential) is morelikely to be experienced as novel and discrepantand to generate more individual sensemaking.The perceived or expected fit between a tech-nology and a task (Dishaw and Strong 1999;Zigurs and Buckland 1998) and the perceivedcompatibility of the technology with users’ values,needs, and past experiences (Karahanna et al.1999; Moore and Benbasat 1991) might alsoinfluence user appraisal. For instance, the per-ceived inability of an IT to support the user’s task(task-technology misfit) might lead one to assessan IT event as threatening, whereas a strong task-technology fit might be considered an opportunityto improve one’s performance. In addition, perfor-mance expectancy has been found to influenceusers’ behavior (Venkatesh et al. 2003) and mightaffect whether one considers an IT event to be anopportunity or not (i.e., a technology associatedwith high performance expectancy is likely to beassessed positively).



Awareness of anIT event

Opportunity

ThreatSelf PreservationEmotion-focused acts

Benefits MaximizingProblem-Focused acts

(Task, Technology, Self)

Disturbance HandlingEmotion and

Problem- focused acts(Task, Technology, Self)

Benefits SatisficingLimited Problem and

Emotion-Focused acts

Adaptation StrategiesAppraisal

High Control

High Control

LowControl

LowControl

Outcomes

individual efficiency and effectiveness

Restoring personal emotional stability

Minimization of the negative consequences of the IT Event

Exit

Primary Appraisal Secondary Appraisal

To simplify the illustration, we present pure forms of appraisal, I.e., where an IT event is monolithically appraised as constituting either a threat or an opportunity.

Awareness of anIT event

Opportunity

ThreatSelf PreservationEmotion-focused acts

Benefits MaximizingProblem-Focused acts

(Task, Technology, Self)

Disturbance HandlingEmotion and

Problem- focused acts(Task, Technology, Self)

Benefits SatisficingLimited Problem and

Emotion-Focused acts

Adaptation StrategiesAppraisal

High Control

High Control

LowControl

LowControl

Outcomes

individual efficiency and effectiveness

Restoring personal emotional stability

Minimization of the negative consequences of the IT Event

Exit

Primary Appraisal Secondary Appraisal

To simplify the illustration, we present pure forms of appraisal, I.e., where an IT event is monolithically appraised as constituting either a threat or an opportunity.

Figure 1. Coping Model of User Adaptation (CMUA)

Some factors relating to the individuals themselvesare also likely to affect users’ primary appraisal.For instance, it has been shown that an indivi-dual’s anxiety with regard to a specific situationtends to generate further anxiety throughanticipatory self-arousal (Bandura 1977; Rosen etal. 1987). In an IT appraisal context, this cycle ofanxiety can negatively influence beliefs about thetechnology (Venkatesh 2000) and engender fear(Weil and Wugalter 1990). Similarly, individualswith higher personal innovativeness have beenfound to exhibit more positive beliefs about atarget technology (Agarwal et al. 2000; Lewis et al.2003). Users’ prior experience with a technologyhas also been found to shape how they perceive anew technology (Agarwal and Prasad 1999;Agarwal et al. 2000; Taylor and Todd 1995a;Venkatesh 2000).

Primary appraisal occurs in a specific context andit is, therefore, likely to be influenced by somesocial and institutional factors such as what peersand superiors think of the technology (Lewis et al.

2003; Taylor and Todd 1995b; Venkatesh et al.2003). Top management’s commitment and sup-port for a technology has been found to positivelyinfluence users’ beliefs about the usefulness andease of use of a technology (Lewis et al. 2003).The organizational and group subjective normsassociated with technology acceptance and use aswell as the culture of an organization are also likelyto shape user appraisal (Ajzen 1985; Davis et al.1989; Taylor and Todd 1995b; Thompson et al.1991; Venkatesh et al. 2003).

In secondary appraisal, users assess how muchcontrol they have over the IT event and what theiradaptation options are given the resources avail-able to them (Lazarus and Folkman 1984). In thecontext of IT, secondary appraisal will be done withrespect to three main components: work, self, andtechnology (see Table 1). As outlined in Shaw andBarrett-Power (1997), control over the work refersto the degree to which users feel they havesufficient autonomy over their jobs and are able tomodify their tasks in response to an IT event.



Control over the self refers to whether users feelthey can adapt themselves to the new environment(Lazarus and Folkman 1984). Finally, control overtechnology refers to how much influence users feelthey have over the features and functionalities ofthe IT (Beaudry 2002) during its development orusage (Clark 1987; Orlikowski 1996; Poole andDeSanctis 1988; Tyre and Orlikowski 1994 ).

The Focus of Adaptation Efforts

Adaptation follows appraisal and, similar to coping,can be emotion- and/or problem-focused. Emot-ion-focused adaptation is oriented toward one’sself and aims at changing one’s perception of theconsequences of the IT event or at reducingemotional distress. Emotion-focused adaptationincludes self-deception and avoidance (e.g.,denying that the IT affects one, acting as if the ITevent had not occurred; Zuboff 1988), minimizationof the consequences of the IT event, selectiveattention (e.g., removing thoughts of the event),positive comparison (e.g., comparing oneself toother users who are more badly affected by theevent; Lazarus and Folkman 1984), and passiveacceptance (e.g., accepting the IT event as a factof life by changing beliefs and attitudes; Tyre andOrlikowski 1994, 1996). Problem-focused adap-tation aims at managing the issues associated withthe IT event directly by (1) adapting one’s self suchas adjusting personal habits to fit the requirementsof the technology (Orlikowski 1996; Tyre andOrlikowski 1994), learning new skills (Tyre andOrlikowski 1994), and adjusting work commitment(Majchrzak and Cotton 1988); (2) adapting thework by modifying procedures and routines (Sokol1994; Tyre and Orlikowski 1996); and/or(3) adapting the technology by changing its func-tionalities and features (Clark 1987; Leonard-Barton 1988; Rice and Rogers 1980).

As most significant IT events are complex, userswill rely on both types of adaptation efforts (forexample, in Table 1, see Majchrzak and Cotton1988, Tyre and Orlikowski 1994, 1996). However,the relative emphasis on emotion- and problem-focused adaptation will depend upon the user’s

appraisal of the IT event (i.e., the combination ofprimary and secondary appraisals; Folkman 1992;Folkman and Lazarus 1985; Lazarus and Folkman1984; McCrae 1984; Oakland and Ostell 1996;Patterson et al. 1990; Stone et al. 1992).

Four Principal Adaptation Strategies

Primary and secondary appraisals, being con-tinuous rather than dichotomous constructs, canbe expected to result in various forms of useradaptation strategies. However, for the purpose ofsimplicity, we present here the four “pure” forms ofadaptation which we derived by combining the twoextreme cases of both types of appraisal (oppor-tunity and threat; high or low control). The fouradaptation stategies (benefits maximizing, benefitssatisficing, disturbance handling, and self-preser-vation) are presented in Figure 2 and describednext.

Benefits Maximizing Strategy

In an instance where the expected consequencesof an IT event are appraised as an opportunity andusers feel that they have control over the situation(IT, work, self), adaptation efforts will be mainlyproblem-focused (Folkman 1992; Folkman et al.1986; Folkman and Moskowitz 2000; Lazarus andFolkman 1984) and oriented to take full advantageof the opportunities offered by the IT event andmaximize personal benefits. As the IS literatureindicates (Majchrzak and Cotton 1988; Poole andDeSanctis 1988 1990), users can achieve thisobjective by adapting the work system (e.g.,modify operational procedures, focus users’ timeon the most important and productive activities),the technology (e.g., modify, add, delete screens;personalize the IT; change its functionalities),and/or themselves (e.g., develop new standards ofbehavior by extensively using the IT, shift levels ofaspiration and channels of gratification such asbecoming the renowned “expert” user, seektraining). Since most adaptation efforts areoriented toward reaping the benefits associatedwith the IT event, they are likely to result in perfor-



BenefitsSatisficing

Self-Preservation

DisturbanceHandling

BenefitsMaximizing

HighControl

LowControl

Threat

Opportunity

PrimaryAppraisal

SecondaryAppraisal

BenefitsSatisficing

Self-Preservation

DisturbanceHandling

BenefitsMaximizing

HighControl

LowControl

Threat

Opportunity

PrimaryAppraisal

SecondaryAppraisal

Figure 2. User Adaptation Strategies

mance improvements such as reducing errors,doing the work faster, and increasing revenues(Goodhue and Thompson 1995; Pentland 1989;Vessey and Galletta 1991). Majchrzak et al.(2000) illustrate this adaptation strategy well bydocumenting how the members of a team, in asituation similar to the one described above,extensively adapted their work system and theirnew technology (problem-focused adaptation) andsubsequently significantly improved their perfor-mance. Thus, our first proposition is as follows:

Proposition 1: When the perceivedconsequences of an IT event are ap-praised as an opportunity and users feelthat they have control over the situation,they will engage in a benefits maximizingstrategy, which will increase theirindividual efficiency and effectiveness.

Benefits Satisficing Strategy

In a situation where the perceived consequencesof an IT event are appraised as an opportunity butusers feel that they have limited control over thesituation, adaptation efforts are likely to be

minimal. Emotion-focused efforts will be limitedbecause users do not feel the need to reducetensions emanating from the IT event (Lazarusand Folkman 1984) and problem-focused effortswill be limited because users feel they cannot domuch to further exploit the IT and reap its benefits(Folkman 1992; Folkman et al. 1986; Folkman andMoskowitz 2000; Lazarus and Folkman 1984).Therefore, users will satisfy themselves with thebenefits the IT offers, which, in absence ofindividual adaptation, are likely to be limited(Pinsonneault and Rivard 1998). Zuboff (1988, pp.90-91) documented a situation in both the CedarBluff and Pine Wood paper mills that resemblesthis strategy. Operators felt that the new auto-mated control system offered interesting oppor-tunities to improve their work, but felt that they hadvery little autonomy to change their work and thetechnology. Minimal adaptation was carried outand the new system generated few benefits otherthan allowing the operators to relax and enjoy life.Thus our second proposition.

Proposition 2: When the perceived con-sequences of an IT event are appraisedas an opportunity and users feel that theyhave limited control over the situation,



they will engage in a benefits satisficingstrategy, which will have limited effectson their individual efficiency and effec-tiveness.

Disturbance Handling Strategy

When one appraises an IT event as a threat andfeels that she has some control over the situation,she is likely to rely on problem-focused adaptationto manage the situation and on emotion-focusedadaptation to minimize the expected negativeconsequences and restore emotional stability(Folkman 1992; Folkman et al. 1986; Folkman andMoskowitz 2000). Adaptation efforts are likely tobe oriented toward one’s self (e.g., seekingtraining), the technology (e.g., reducing the nega-tive aspects of the new system, changing thefeatures of the IT), and the task (e.g., adjustingwork procedures so that they better fit with thetechnology) (Majchrzak et al. 2000; Tyre and Orli-kowski 1996). Because the IT event is threat-ening, emotion-focused adaptation is also likely tobe used and might include positive comparison,threat minimization, and positive reappraisal(Folkman 1992; Folkman and Lazarus 1985;McCrae 1984; Stone et al. 1992).

The adaptation, if successful, will lead to therestoration of personal emotional stability and tothe minimization of the perceived negative conse-quences associated with the IT event. Kraut et al.(1989) presented a case that demonstrates thisstrategy. They described how service represen-tatives responded to a new record system thateliminated their ability to perform several taskssimultaneously, which was once the hallmark oftheir competence. In an effort to minimize thenegative consequences of the new IT, therepresentatives quickly discovered ways to per-form tasks simultaneously and to work on tworecords in parallel by logging into the databasetwice. They also feared that the new system wouldeliminate some existing social ties by limiting thepossibilities to exchange information and, there-fore, created a clandestine note-passing systemwithin the record system. Service representativesresponded by modifying the technology and their

work habits (problem-focused adaptation) and, indoing so, were able to minimize the negativeconsequences of the IT event.

It is also possible that users are able to turn an ITevent around and improve their individual effi-ciency and effectiveness by relying on adaptationefforts such as benefit-finding and benefit-appraisal (i.e., trying to find a positive aspect ofany situation, even those first assessed asnegative) and growth-oriented functioning (i.e.,trying to find ways to grow and improve in allsituations) (Folkman and Moskowitz 2000;Holahan et al. 1996; Lazarus 1999; Somerfield andMcCrae 2000; Tennen and Affleck 1999).

Proposition 3: When the perceived con-sequences of an IT event are appraisedas a threat and users feel that they havecontrol over the situation, they will en-gage in a disturbance handling strategy,which will restore their emotional stabilityand minimize the perceived negativeconsequences of the event. It can alsoincrease their individual efficiency andeffectiveness.

Self-Preservation Strategy

In a situation where the expected consequences ofan IT event are perceived as a threat and usersfeel that they have only limited control over thesituation, their adaptation efforts will be mainlyemotion-focused and aimed at restoring emotionalstability and reducing the tensions emanating fromthe IT event (Folkman 1992; Folkman et al. 1986;Folkman and Moskowitz 2000; Lazarus andFolkman 1984). Users will try to change theirperception of the IT event by minimizing the per-ceived negative consequences (e.g., maintaininghope that the expected negative consequenceswill not materialize), positive comparison (e.g.,comparing themselves to other users who areworse off), self-deception and avoidance, selectiveattention, and distancing (e.g., reducing theirinvolvement in their work) (Lazarus and Folkman1984; Zuboff 1988). This strategy, if successful,will restore emotional stability but will have little or



no impact on users’ performance at work.Patrickson’s (1986) study of newspaper composi-tors’ reactions to the implementation of an elec-tronic production system illustrates this strategy.Because they expected that the new technologywould deskill and/or eliminate their jobs andreduce their prestige and influence, newspapercompositors avoided the system, using it as littleas possible, and distanced themselves from theirwork. Our fourth proposition is as follows:

Proposition 4: When the perceived con-sequences of an IT event are appraisedas a threat and users feel that they havelimited control the situation, they willengage in a self-preservation strategy,which will restore their emotional stability.It can also minimize the perceived nega-tive consequences of the event.

As illustrated in CMUA (Figure 1), in cases whereusers perceive the circumstances as too de-manding and overwhelming in light of theresources available and where they feel option-less, users might totally withdraw from the situation(Begley 1998; Lazarus and Folkman 1984). Here,emotional adjustments and modifications of thesituation are simply insufficient to allow users toadapt to the IT event; users are thus likely toemotionally disengage themselves from it and exitthe situation altogether (Begley 1998).

User Adaptation Processas a Whole

As illustrated in Figure 1, the adaptation process ishighly iterative and continually evolves as a func-tion of the ongoing changes that occur in theuser/environment relationship. Appraisal andadaptation constantly influence each other. Shiftsmay be due to the adaptation efforts that changedthe technology, the work, or the individual; tochanges in the environment that might haveoccurred independently of the person; or tochanges in the meaning and subjective under-standing one has of the situation (Folkman andLazarus 1985). In other words, appraisal influ-

ences the adaptation efforts that are likely to beperformed, which in turn lead to the reappraisal ofthe situation (Folkman 1992; Stone et al. 1992).This is illustrated in Figure 1 by the feedback loopthat goes from adaptation strategies back toappraisal.

Further, the outcomes of the adaptation process(i.e., restoring emotional stability, improvingindividual performance, minimizing the negativeconsequences of an IT event) are likely to changethe user’s perception of the IT event, which canlead to a reappraisal of the situation and cantrigger a new adaptation efforts sequence. This isillustrated in CMUA by the feedback arrow thatgoes from outcomes back to appraisal. This loopis particularly important because it helps accountfor both the negative and positive recursive spiralsof appraisal–adaptation–outcomes. For instance,it is possible that a user appraised the expectedconsequences of an IT event as threatening, butthat her adaptation efforts minimized the negativeconsequences and that, in light of this, she reap-praises the new technology more positively andengages in a new and different adaptationsequence. Alternatively, an IT event appraised asan opportunity might end-up having negativeconsequences for a user, which may, in turn,change her prior appraisal and trigger a new seriesof adaptation efforts. CMUA allows for both rein-forcement loops (positive and negative) as well asfor reversal loops (i.e., negative assessmentbecoming positive and positive assessmentbecoming negative). Thus our fifth proposition.

Proposition 5: The adaptation efforts andoutcomes lead to the reappraisal of theIT event, which can trigger a newsequence of adaptation efforts.

Research Method

Research Sites

In order to provide a preliminary test of our model,case studies were conducted in two NorthAmerican banks. There were three main reasons



for this choice. First, both banks had implementeda new account management system two yearsbefore, just past the 18-month window duringwhich user adaptation behaviors have beenobserved to occur (Tyre and Orlikowski 1994,1996). Second, the two systems were customiz-able and their usage was strongly encouraged inboth banks. This was important in order to studyhow appraisal of the perceived consequences ofthe new technology might have influenced howusers adapted. Third, users at both banks hadwide-ranging latitude and autonomy in their workand in the way they used the system, which wasimportant for studying adaptation efforts related towork routines and to the technology. Users’control in the pre-implementation phases of thesystems was, however, very limited in both banksas they were company-wide systems that weredeveloped with minimal user involvement.

Bank A

Bank A has over $15 billion in assets, employs3,200 people, and serves over one million clientsthrough 204 branches. Account managers at BankA are entrepreneurs who have their own clientsand are responsible for generating new businessand managing their portfolio of accounts. Theirperformance and remuneration are based on thegrowth and profitability of their portfolio. Prior tothe implementation of the new account manage-ment system, account managers met their clientsat the branch and used a terminal to access thebank’s centralized database in order to print acopy of the client’s record. That record, in additionto providing the client’s name, address, phonenumber, and employment information, listed theclient’s account numbers with their balances andall transactions from the previous two weeks. Italso listed all loans and investment products alongwith their balances, terms, and interest rates. Ineach branch, an administrative assistant waspresent to help account managers with paperwork.Any discussion about an investment or a requestfor a loan would result in a two-page paper form tobe completed and signed both by the accountmanager and the client. Investment forms wouldthen be sent by internal mail to the head office

where the database would be updated, whereasloan request forms would be dispatched to thebranch manager for approval before being sent tothe head office.

Link, as the new system is called, was developedin-house and is a Windows-based platform con-sisting of a transactional application and an expertsystem called “Personal Investment Profile” (PIP).The transactional application allows accountmanagers to write documents, open and closeaccounts, assign credit lines, register deposits andloans, buy mutual funds, link with the creditbureau, and register mortgages. PIP, which iscomplementary to the transactional system, usesthe client’s financial situation, demographics, riskaversion information, and personal financial goals.It determines one’s risk propensity, draws aninvestment profile, and suggests an ideal-typepersonalized portfolio. At the time of the imple-mentation, all account managers attended a four-hour training session, which used PowerPointslides and handouts. No hands-on activity waspart of the formal training. Users were invited totry the new system and to rely on the onlinetutorial, help function, and help desk for anyquestions with regard to its use.

It was hoped that Link would help accountmanagers better understand their clients’ needsand allow them to offer more personalized pro-ducts, services, and investment strategies. Linkwas also expected to improve the quality of theirwork, their efficiency and effectiveness, and theprofitability of their portfolio, as well as to increaseclients’ satisfaction. Ultimately, reaching thesegoals was expected to allow the bank to abolishthe position of administrative assistant and toincrease its revenues.

Bank B

Bank B’s assets are worth $69 billion. It operates655 branches and employs 200 account managerswho share the responsibility for managing theaccounts of corporate clients. At Bank B, theaccount manager position is prestigious. As inBank A, although very detailed working procedures



exist, account managers benefit from significantlatitude in terms of the way they fulfill their jobs.Account managers’ performance appraisal andpay are, as in Bank A, based on the value of theirportfolio and on growth in sales. There are 125administrative assistants who help account man-agers with their administrative and clerical tasks.

Before the new system was implemented, accountmanagers had prepared for meetings with clientsusing a printout of the client’s record that theadministrative assistant obtained from the centra-lized database. Account managers met with theirclients either at the bank, at the clients’ premises,at a restaurant for lunch, or even on the golfcourse. If a decision was made to grant a loan,the account manager would write the details on apiece of paper, sometimes a paper napkin, andgive it to his/her assistant who would enter thedata in the system and print the required forms forthe client to sign. The clients could either sign thedocuments at the bank or, alternatively, the ac-count manager would go to the client’s office. Thisprocess drastically changed when the Windows-based platform called Reach was implementedand account managers were provided with laptops.

Reach was developed in-house and comprisesmany applications to support account managers intheir work. The main application is the clientsdatabase management system. It provides theaccount manager with the client’s profile, credithistory, incidents, and portfolio of products. Otherapplications include an agenda, e-mail, MSOffice,a Web browser, a financial analysis module, and asimulation tool; the latter two were also developedin-house. Reach was installed on laptops to allowaccount managers to carry it when meeting theirclients outside of the bank’s premises. It washoped that Reach would increase the accountmanagers’ efficiency and effectiveness by stream-lining their job, providing them with faster accessto better information, and increasing their ability tomeet the clients’ needs, all while minimizing theneed for administrative assistants. Since theintroduction of Reach, account managers’ officialworking procedures have changed significantly.Account managers now directly access and updateclient files online and use the system interactivelyduring meetings with their clients.

Data Collection

Our study examined the relationships among thefour main constructs of our model: primary ap-praisal, secondary appraisal, adaptation strategies,and outcomes. An additional objective was todevelop a sense of how the systems werereappraised after two years of usage to give anindication of the feedback loops that could lead tonew series of adaptation efforts. Finally, theorganizational context (e.g., structure, culture,account managers’ job, autonomy, and remunera-tion) and IT context (e.g., how the system wasdeveloped and implemented, training, support, andfunctionalities of the system) were also studied asthey have the potential to influence useradaptation. Data sources included interviews,annual reports of each bank, training and usermanuals, and account managers’ job descriptions.Using multiple sources of data allowed thetriangulation of the data and provided an appro-priate level of internal validity (Kirk and Miller 1986;Miles and Huberman 1994). Table 2 summarizesthe data collection process for each construct.

As shown in Table 2, nine semi-structured inter-views were conducted in Bank A and eight in BankB. Interviews lasted on average two hours andwere tape-recorded and transcribed. In eachbank, we followed the same procedure. First, wegathered information on the organizational and ITcontexts through interviews with two seniormanagers (vice president IS and project director inBank A; CIO and director of operations in Bank B).Additional information specific to the branch inwhich the account managers of Bank A workedwas obtained by interviewing the branch manager.The annual reports were consulted to obtaininformation on the banks and on the performanceof the account managers (e.g., historical data onportfolio profitability and growth). The projectmanagers of the two banks were interviewed toexplain how the systems had been developed andimplemented and to get their impressions abouthow account managers were using them. In orderto familiarize ourselves with the systems, the firstauthor attended a three-hour training session ateach bank and studied the user manuals. Finally,we obtained a good preliminary understanding of

Table 2. Data Collection

Bank A Bank B

V-P

IS

Pro

ject

Dire

ctor

Bra

nch

Man

ager

Pro

ject

Man

ager

Pet

er, A

ccou

nt M

anag

er

Mic

hele

, Acc

ount

Man

ager

John

, Acc

ount

Man

ager

Hel

p D

esk

Em

ploy

ee

Acc

ount

Man

ager

Tra

iner

Trai

ning

Ses

sion

and

Man

uals

Ann

ual R

epor

ts

Acc

ount

Man

ager

s’ J

obD

escr

iptio

n (In

tern

al D

ocum

ent)

CIO

Dire

ctor

of

Ope

ratio

ns a

ndFo

rmer

Bra

nch

Man

ager

Pro

ject

Man

ager

Bill

, Acc

ount

Man

ager

Mar

k, A

ccou

nt M

anag

er

Dav

e, A

ccou

nt M

anag

er

IT T

rain

er

Adm

inis

trativ

e A

ssis

tant

Trai

ning

Ses

sion

and

Man

ual

Ann

ual R

epor

ts

Acc

ount

Man

ager

s’ J

obD

escr

iptio

n (In

tern

al D

ocum

ent)

Organizational Context X X X X X X X

Account Managers’ Job Description X X X X X X X X X X X X X X X X X X X X

IT Context X X X X X X X X X X

Primary Appraisal X X X X X X X X X X X X X X X X X

Secondary Appraisal X X X X X X X X X X X X X

Adaptation Efforts X X X X X X X X X X X X

Outcomes X X X X X X X X X X X X

Reappraisal X X X X X X X X X X X X



an account manager’s job through interviews withthe senior managers and the project managers ofeach bank and by consulting detailed job descri-ptions. Although it was not the primary purpose ofthese interviews, we also benefitted from theirperspective to gain a preliminary understanding ofaccount managers’ reactions to the new systemsand of how they adapted.

The second step consisted of studying theadaptation process of three account managers inBank A and three account managers in Bank B.Following Miles and Huberman (1994), we tried tomaximize variation by selecting respondents whowere known to hold different views and opinionsabout the systems and to have different usagepatterns. In addition, in an effort to triangulate theinformation obtained directly from the accountmanagers, we interviewed an IT trainer and onehelp desk support specialist in Bank A, and oneadministrative assistant and an IT trainer in BankB. These individuals were chosen because theyhad close professional relationships with theaccount managers and they had worked with themduring the two years covered by the study. Theywere thus asked to describe how, to their knowl-edge, each account manager had initially ap-praised the consequences of the new system, howthey had adapted, how the IT had affected theirperformance, and how the account managers hadreappraised the system at the time of the study.

The interviews with the six account managersaimed at understanding how each originallyappraised the consequences of the technology(primary appraisal); what control they felt they hadover the technology, their work, and themselves(secondary appraisal); how they adapted (adapta-tion strategy); and what effects they perceived thenew system had on them personally and on theirperformance at work (outcomes). The accountmanagers were asked to provide a detailed nar-rative description of the implementation process,all the related major events, and their individualreactions. In order to minimize recall biases, wefollowed Collopy’s (1996) and Hufnagel andConca’s (1994) recommendations and anchoredquestions with significant event flags, for example,questions such as “Do you recall the moment

when you were first made aware that a new ITwould soon be introduced?” and “What was yourreaction when you saw the computer on your deskfor the very first time?” In addition, in an attempt toexplore the notion of reappraisal, all interviewsended with an open discussion of how the accountmanagers perceived their system at the time of theinterview.

Data Analysis

The unit of analysis of the model is the adaptationstrategy (i.e., patterns in streams of adaptationacts of users). In order to discover these patterns,we had to document the different adaptation effortsand acts used by account managers and groupthem into adaptation strategies. To do this, thedata analysis was conducted in two main steps:coding and construction of the chains of evidence.Coding was done in two phases. First, the dataobtained in interviews about the adaptation pro-cess of account managers was coded into broadcategories (primary appraisal, secondary ap-praisal, adaptation efforts, and outcomes) by thetwo authors independently. As suggested by Milesand Huberman, the researchers compared theirclassifications after having coded two interviews.No significant differences were identified at thatpoint and the coding thus proceeded for theremaining interviews. Second, a finer-grainedcoding was performed. Quotes relating to primaryappraisal were further categorized into perceivedopportunity or threat. Those related to secondaryappraisal were categorized into perceived high orlow control with regard to the technology, the work,and the individual. Adaptation efforts were furthercategorized into problem- or emotion-focused andoutcomes were categorized into improving indivi-dual effectiveness and efficiency, minimizingthreat, or restoring emotional stability. The entirecoding process yielded a total of 247 codedquotes. Inter-coder agreement between the tworesearchers was above 90 percent.5 An agree-

5The code given to each quote by both researchers wascompared. Both researchers had assigned the samecode to 226 quotes, leaving 21 coding discrepancies tobe resolved.



ment was reached between the two researchersafter discussing the 21 discrepant quotes.

The second step in the data analysis was theconstruction of the chains of evidence thatgrouped quotes from each account manager aboutprimary and secondary appraisals and adaptationefforts into patterns of actions, thereby identifyingadaptation strategies. The data gathered in theinterviews with the two IT trainers, the adminis-trative assistant, and the help desk supportemployee were used to provide additional insightinto the adaptation process of the accountmanagers. A table was constructed for eachaccount manager organizing all the data related tohis/her adaptation process into patterns allowingus to identify the four main strategies under study.Finally, account managers with similar adaptationstrategies were grouped into separate tables whichinclude relevant quotes to illustrate the givenstrategy. This process yielded the four tablespresented in the next section.

Results

The reactions and responses of account managerswith regard to the new systems varied extensivelywithin each bank.

Link was perceived by most accountmanagers as an improvement to theirtool kit. Generally speaking, accountmanagers received it very well. Obvi-ously, there were a few very bad reac-tions to its introduction. It’s easy tounderstand; we were introducing a majorchange in their work process.…a certainnumber of account managers still utilizethe paper-based version that has been inuse at the Bank since 1995. (IS VicePresident, Bank A)

I’ve seen everything: from an accountmanager who tried to open his laptopusing a screwdriver, to one who was madbecause they were not provided with anInternet access. [The Internet access

was provided to account managers onlya year after the initial implementation.]One even left slamming the door. Hecame back two days later only to packup: he retired. (Director of Operations,Bank A)

We thought all account managers wouldwelcome the system, it is such a goodsystem, but we were mistaken. Severalwere mad at us for implementing it; wealmost had a revolution.…Nowadays, it’swhen the system is down that we hearthem. Some expect it to be up andrunning 24/7! (Project Manager, Bank B)

At first, several account managerswelcomed the laptop but some wereunhappy. Obviously, the new system didnot please everyone; many accountmanagers felt they were demoted tosecretarial positions while many adminis-trative assistants felt they were doing theaccount managers’ job without being paidfor it.…I wonder how many accountmanagers really use it as it should.(Chief Information Officer, Bank B)

The data provided evidence for our four adaptationstrategies and their link with appraisal and out-comes. We present and discuss chains of evi-dence relating to the four strategies below:benefits maximizing (Peter, Bank A; Mark, BankB); benefits satisficing (Dave, Bank B); disturbancehandling (John, Bank A; Bill, Bank B); and self-preservation (Michele, Bank A).

Benefits Maximizing

Peter welcomed the new system (quote Q1,Table 3)6 and saw it as an opportunity to improve

6Quotes in each of Tables 3 to 6 have been numberedsequentially in order to facilitate referencing.

Pet

er (B

ank

A)

Mar

k (B

ank

B)

Table 3. Chains of Evidence: Benefits MaximizingAppraisal

Adaptation Efforts OutcomesPrimary SecondaryQ1 “I felt happy andrelieved. It was about timefor us to be equipped withsuch a tool.”Q2 “I was confident thatthis system would give mean opportunity to do thingsdifferently and better andto be much faster, to domuch fewer errors and toimprove the quality ofservice I give to my client.”

Q3 “I wasconvinced that Iwould becomeproficient using it inno time and that Iwould use it toimprove the way Iwork.”

Q4 “I spent numerous hours trying new things on the system. Iquickly learned how to use the system and found creative usesfor it.…I used the help function and called the help desk manytimes over the first few weeks after which I discovered new usesmostly by trial and error.”Q5 “Peter is one of those who used to call us many times a dayduring the weeks following the implementation. He wanted toknow how to do everything and even things the system hasn’tbeen developed for.” (Help Desk Employee)Q6 “The system allowed me to completely change the way I wasused to work and interact with my clients. It brought me to forgetabout my favorite stocks or funds, those that I was used torecommend to everyone, and to explore new personal avenueswith each customer.”Q7 “I can benchmark my services against competitors and I canget information on my clients.”

Q8 “This system really helpedme improve my performance. Itis easier to convince clients totransfer their accounts with me.Also, I am much more efficient. Iam faster and I make fewererrors. My profit and my salaryincreased since I have it.”

Q9 “I felt so relieved whenthey gave it to us. I wouldnot have to fill piles ofpaper forms anymore. Ifelt like I was working inthe old age era using apen and paper all the timeand not having up-to-dateinformation about myclients.”Q10 “That was goodnews.”Q11 “Mark not onlywelcomed the system buthe also quickly became astrong proponent of it.Since day one, he hasbeen helping hiscolleagues a lot.” (Directorof Operations)

Q12 “Our work isflexible and I havea lot of autonomyin the way I do myjob.”Q13 “We are prettyfree to use thesystem how andwhen we want.There are somestandard forms thatwe need to fill onthe system, buthow and when Iuse it is my deci-sion. I don’t think management reallycares how we useit. As long as thejob is done.”

Q14 “At first, I really played with it, trying out everything up to thelast command in each menu. I discovered that I could use thesystem to do many more things than what they said during thetraining session.”Q15 “I created links to import data from the financial module intoExcel to analyze my clients’ sales forecasts and to create graphsto show to my clients.”Q16 “At first, we did not have access to the internet, but there isvery useful information on the net for account managers. You canfind information on your clients, you can compare your clients toindustry standards, and you can even find information on yourcompetitors. So, I found a way to use Reach to access theInternet.”Q17 “As I was learning how it worked and what it could do, I wasintegrating various functionalities in my working procedures. Ichanged about everything in the way I do my job.” Q18 “When he was provided with the laptop, Mark started to doeverything by himself, he would only let me answer the phone!After a few weeks, he started to give me back some work to do, themost boring tasks, like typing letters.” (Administrative Assistant)

Q19 “The reports that I produceusing Reach make me save a lotof time. After having spent 5 min-utes analyzing this report forinstance (showing an 8½ by 11inches sheet loaded withfigures), I have a pretty goodidea of my client’s situation. Itused to take me hours before.”Q20 “It doesn’t only save metime, it shortens the responsetime to my clients”.Q21 “It’s obvious. Before Reach,we didn’t have a good risk eval-uation tool. Now it’s much easierto evaluate risk and I have amuch better overall picture and Imake better decisions”.Q22 “I doubled my bonusessince we have this system.”



his efficiency (e.g., reducing time and effort),effectiveness (e.g., improving the quality ofservices), and overall performance (Q2). As Q3indicates, Peter felt he had control over thesituation, in particular with regard to his ability tolearn and use the system (control over self andtechnology) and to change the way he worked(control over the work system). In the interview,he stressed that since he had always beensuccessful in that job, he thought this new toolcould help him in becoming even better.

Peter’s adaptation efforts were almost exclusivelyproblem-focused and oriented toward enhancingthe benefits of Link. He wanted to make sure thathe would rapidly master Link so that he could takeadvantage of it as soon as possible and use it toincrease his performance. His adaptation effortswere quite extensive and addressed himself, thework system, and the technology. Throughtraining and discovery by trial and error, he quicklylearned how to exploit the new system (Q4). Heoften called the help desk during the first fewweeks in an effort to learn as many functionalitiesas possible (Q5). Peter’s adaptation efforts alsofocused on the work system and his working habitsand procedures. He changed his interactions withhis clients and used the new system to exploredifferent financial alternatives and analyze newstocks and funds with his clients, something hehad never done before (Q6). Peter’s adaptationefforts were also oriented toward the technology.Although Link was not originally designed as such,Peter found ways to use it to gather information oncompetitors’ products and services and to bench-mark his own service level against that of hiscompetitors (Q7). As Q8 indicates, according toPeter, the system allowed him to improve hisefficiency (work faster, make fewer errors) and hiseffectiveness (convince clients to transfer theiraccounts with him), which improved his overallperformance and his salary. Peter concluded bystating how good the system was and how happyhe was.

Mark, from Bank B, positively appraised Reachand saw it as an opportunity to eliminate thetedious and low-value tasks of his job, an oppor-tunity that could improve his performance (Q9,

Table 3). For him, Reach’s implementation wasgood news (Q10, Q11). Mark also felt he hadextensive control over his job as well as over thenew system. As an account manager, he hadgreat autonomy in his job and felt that his super-visor was interested in his results, but not in theway he did his job (Q12). Similarly, while the Bankpromoted Reach, Mark felt its usage wasvoluntary. He could decide how and when hewould use it (Q13).

Mark’s adaptation efforts were problem-focusedand directed at himself and at the environment(adapting Reach and modifying his work system)so that he could maximize the benefits of Reach.During the first weeks, Mark learned how to usethe system rapidly in order to quickly reap thebenefits he thought Reach could bring (Q14). Hetried every single application, clicking on everysingle icon (Q14). Mark also adapted the newtechnology to his work routines and preferences bycreating new applications using MS Excel andimporting data into his financial analysis appli-cation (Q15). He also connected Reach to theInternet to gather important information about hisclients and to benchmark his services againstcompetitors (Q16). Finally, Mark modified his worksystem quite substantially (Q17). He indicated thatReach allowed him to focus on the most importantactivities of his job and to delegate the rest to hisassistant (Q18).

Mark felt that the system provided very significantimprovements in his performance. He indicatedthat Reach helped him improve his efficiency(saving time, faster response to client Q19, Q20)and effectiveness (better risk assessment, betterdecisions Q21), which increased his overallperformance and contributed to increasing hisbonuses (Q22). Mark concluded by saying that hewas very satisfied with this system: “I would neverwant to go back to the old way of doing things.”

The adaptation processes used by both Peter andMark illustrate the benefits maximizing strategydescribed in our model (Figure 2) and supportProposition 1. Peter and Mark appraised the newIT as an opportunity to improve their work andproductivity and felt that they had control over the

Dav

e (B

ank

B)

Table 4. Chain of Evidence: Benefits SatisficingAppraisal

Adaptation Efforts OutcomesPrimary SecondaryQ1 “It was obvious rightfrom the start that thiswould help us. One couldsee that it had greatpotential.”Q2 “Most of us were veryhappy.”

Q3 “We don’t havemuch control overthings here. Topmanagement decides and wefollow.”Q4 “Like it or not,the system wasgoing to beimplemented. Ithought that thesystem would notbe flexible. It was astandard tool thatwas developed andimplementedacross the bank.”

Q5 “We helped each other a lot. It took time but we succeeded.”Q6 “Management really insisted and after a while, the only thingwe could do was to learn how to use it.”Q7 “So I learned how to use it. Hey, it was not that easy, it was amajor change for us.”Q8 “Apart from learning how to use it, I didn’t do much about thissystem.”

Q9 “All the documents thataccount managers produce havea much better look.”Q10 “The system prevents a lotof errors, so we loose less time.”Q11 “After all, it did not change alot of things in my work.”



situation at all three levels: the technology, theirworking system, and themselves. They both per-formed extensive problem-focused adaptationefforts, which resulted in significant improvementsin their efficiency and effectiveness.

Benefits Satisficing

Like Mark, Dave positively appraised Reach andwas very happy when Bank B implemented it (Q1,Q2, Table 4). He was convinced that the newsystem was good and that it had a great potentialto improve his job. Contrary to Mark, however,Dave felt he had very little control over the situa-tion in general (Q3). He felt that he had no controlover the new system and that, being a standardtool implemented across the bank, Reach was notvery flexible. So he felt he could not really modifynor adapt it (Q4).

Dave’s adaptation efforts were minimal. We foundno evidence that he performed any emotion-focused adaptation efforts and his problem-focused efforts were strictly limited to learning howto use the minimum number of functionalities heneeded to perform his job (Q5, Q6, and Q7). Infact, as he stated in the interview, he adopted alaissez faire approach and, contrary to Mark, Davedid not modify his work routines or the technology(Q8). His adaptation was limited to learning howto use Reach.

Dave considers the benefits associated withReach to be relatively limited, consisting ofmarginal improvements in the quality of the docu-ments and in his efficiency in producing them (Q9,Q10). He concluded that the system did notchange much after all (Q11). This is consistentwith our model and supports Proposition 2. Dave’spositive appraisal of the technology and hisperceived lack of control over the situation led himto perform minimal adaptation efforts, whichresulted in limited benefits.

Disturbance Handling

Table 5 presents quotes from interviews with John(Bank A) and Bill (Bank B), both of whom adapted

in ways that are similar to what was described inthe disturbance handling strategy of our model.

At first, John was discouraged and afraid thatBank A might use the new system to cut his job(Q1, Q2, Table 5). He was preoccupied by the factthat Link might cause him to make errors and tolose data (Q3). However, John felt that he hadsome control over the situation (Q4), especiallywith regard to his ability to learn the system (Q5)and his ability to control the way he performed hisjob (Q6).

John performed both emotion- and problem-focused adaptation efforts. John’s emotion-focused efforts were threefold. By comparinglearning to use Link to learning to play the piano (anonthreatening situation), he minimized the threatsassociated with the new technology (Q7). He alsoconvinced himself that since Link had beendesigned by experts like him, it must be a goodsystem that was probably not as threatening as hehad initially believed (Q8). This resembles positivecomparison and positive reappraisal emotion-focused adaptation as they were previouslydiscussed. Also, similarly to passive acceptanceas described in psychology, he convinced himselfthat using the system and learning to use it werepart of his job and his responsibilities (Q9). John’sproblem-focused efforts were oriented towardhimself and consisted mainly of obtaining trainingto learn to use the new system (Q10, Q11).

It is interesting to note that, contrary to hispreliminary expectations, John felt, in the end, thatLink did not affect him negatively. As indicated inour model and in Proposition 3, through hisadaptation efforts, John was able to minimize theperceived negative consequences of Link andeven to increase his efficiency, although not to thesame extent that Peter did. John thought that thesystem helped to improve the satisfaction of hisclients (Q12) and made him look more profes-sional, while also enabling him to make fewererrors (Q13). At the end of the interview, Johnindicated that Link was a good system after all,suggesting that two years after the implemen-tation, he reappraised Link positively.

John

(Ban

k A

)

Table 5. Chains of Evidence: Disturbance HandlingAppraisal

Adaptation Efforts OutcomesPrimary SecondaryQ1 “We were all afraid that theBank would use the technologyto cut jobs.”Q2 “It was not an easy period.John was frightened andfrustrated. I understand that.When you have beensuccessful at doing somethingfor many years, it’s difficult toaccept that you have tochange.” (Branch Manager)Q3 “Along with others, I wasafraid of it and I thought that itwould lead us to make errorsand that we would loosedata.…This is really not good,especially when you dealdirectly with clients and yoursalary directly depends on yourperformance.....At first, I wasreally afraid for my job.”

Q4 “I was confident thatwith enough good will andefforts, I would be able toface this challenge.”Q5 “I was convinced thatwith enough time andpractice, I would learn thesystem and I wouldbecome more efficientand effective in my job.”Q6 “We control our joband this is part of our job,we need to be able to useit.”

Q7 “At first, I did not want to use this system. Then, I keptsaying to myself: you have to use computers to learn it. Thereare no other ways. The more you use it, the better you are atusing it…. In fact, it is like learning to play the piano. Youdon’t learn to play the piano by reading about it. You need totry it and play. You have to get hands on experience.”Q8 “I told myself: you know it is not the computer that makesthe decision, it is me. Plus, how do you think that thecomputer can make a decision? It is because it wasprogrammed to do so by aggregating the expertise of accountmanagers, like me, so it must be good.”Q9 “And, after all, it is our responsibility to learn new tools.”Q10 “I decided to take some additional training thinking itmight help. It helped me a lot to learn how to use thesoftware, it made me realize that the only way to learn to useLink was to use it”. Q11 “John was reluctant to use the system at first but a fewweeks after the implementation, User Services offered one toone special training sessions. John enrolled and attendedone of these sessions.” (Branch Manager)

Q12 “Generallyspeaking, my clientslike to see the compu-ter’s results… it helpsme suggest invest-ment products withthe objective ofreaching the “ideal”portfolio as suggestedby the system.”Q13 “I make fewererrors and I look moreprofessional.”

Bill

(Ban

k B

)Table 5. Chains of Evidence: Disturbance Handling (Continued)

AppraisalAdaptation Efforts OutcomesPrimary Secondary

Q14 “I was afraid to lookignorant in front of mycolleagues. I had never workedwith a computer before.” Q15 “I thought this systemwould make me do my assis-tant’s job.”Q16 “I was afraid of losing myjob. After all, the bank has usedtechnology to eliminate jobs inthe past.”Q17 “Bill was really afraid atfirst.” (Director of Operations)

Q18 “If I had enough timeI know that I could learnthe technology.”Q19 “They tried to imposeit on us but I’ve been herefor many years, and Icontrol my job and theway I do it. I knew theywouldn’t kick me outbecause I did not use it.So, I told Karen: with orwithout it, it’s business asusual.”

Q20 “Bill is one of the many who resisted a lot in thebeginning”. (Director of Operations)Q21 “I didn’t use it at first. I didn’t want to.”Q22 “At the beginning, Bill didn’t do anything. He was actingas if no system had been implemented. He used to say thatthe computer was my job (pointing to her).…It really took hima lot of time before he started to use it”. (AdministrativeAssistant)Q23 “At first, I was really angry that they wanted us to usethat system and I voiced my opinion about this. I felt that wehad enough work, we did not need to do our secretary’s jobon top of it.”

Q24 “After a while, I decided that I should try to learn the newsystem. I’m grateful to Mark, he is a nerd and he helped me alot to learn how to use the system. I always ask him when Ihave a problem.”Q25 “Bill is always in Mark’s office to ask for help on how todo this and that.” (Administrative Assistant)Q26 “I brought it at home a few times at the beginning to try itand to learn how to use it.”Q27 “Now, I use it all the time. It is completely integrated inmy job. I changed a couple of things about the system thatbogged me and also, I changed my job a little bit. I think Ispend more time using the system than with my clients.”

Q28 “After a couple ofmonths, I quieteddown and calmed my-self. I think I hadrealized that the sys-tem was not that bad.”Q29 “After a while,and with the help ofMark, Bill came toaccept it. He was OKwith it.” (Director ofOperations)

Q30 “It produces veryprofessional lookingletters for my clients.”Q31 “No, it doesn’thelp me be moreproductive. It doesn’thelp me find newclients but thedocuments I producehave a much betterand professionallook.”



Bill (Bank B) initially negatively appraised thesystem and felt personally and professionallythreatened because he was afraid that Reachwould reduce his credibility and deskill his job(Q14, Q15, Table 5). He was also afraid that thesystem could be used to eliminate his job (Q16,Q17). Bill felt, however, that he had some controlover the situation, especially regarding how he didhis job and the extent to which he would useReach (Q18, Q19).

Bill’s adaptation process is quite interesting as theinterview allowed us to clearly delineate twophases (identified by vertical arrows in Table 5).The first phase transpired from the implementationof Reach until about six months later and thesecond phase afterward. These two phases pro-vide support for our Proposition 5, which suggeststhat adaptation efforts and outcomes may lead oneto reappraise the situation and trigger a new seriesof adaptation efforts. In the initial phase, Bill’sadaptation efforts were mostly oriented towardrestoring emotional stability. At first, Bill resistedthe implementation of the new system (Q20). AsQ21 and Q22 indicate, he did not use it, ignored itspresence, and acted as if Reach had not beenimplemented (self-deception and avoidance). Healso expressed his anger to colleagues (Q23),which is similar to the “venting anger” coping actdocumented in psychology (Lazarus and Folkman1984). These efforts seemed successful inrestoring his emotional stability. For instance, Billindicated that after two or three months, he had“calmed down” and started to see the systemdifferently and not as negatively (Q28). This wascorroborated by the Director of Operations, whoindicated that after a while, “Bill came to accept it.He was OK with it.” (Q29).

Bill’s interview clearly indicates that another seriesof adaptation efforts occurred approximately sixmonths after the implementation of Reach. At thattime, most adaptation efforts were problem-focused and oriented toward himself and, to alesser degree, toward the technology and the worksystem. With the help of Mark, Bill decided tolearn how to use the system (Q24, Q25) and heeven brought it home to practice in what was aless threatening environment, one where his

mistakes would go unnoticed (Q26). Bill indicatedin the interview that only when he had reached acertain level of expertise did he start to use itovertly at the office. He also slightly modified hiswork and the technology so that they would betterfit together (Q27). Bill indicated that, in the end,although Reach did not improve his efficiency, itallowed him to write professional looking docu-ments, improve his credibility, and increase thesatisfaction of his clients (Q30, Q31).

Bill’s adaptation strategy was successful as he wasable to restore emotional stability and integrateReach into his work. He was able to turn the situa-tion around from originally perceiving the newtechnology as a threat to finally using it to improvehis performance. In fact, our data indicates that, atthe time of the interview, he had positively reap-praised the technology: “Today, I like that system.It makes me look very smart and up to date withtechnology, but don’t get me wrong, it will neverreplace the account manager.”

The cases of John and Bill illustrate the distur-bance handling strategy of our model and providesupport for Propositions 3 and 5. Both accountmanagers initially perceived the new systems asconstituting a threat and both felt that they hadcontrol over the way they performed their job andover how they would integrate the new IT in it.Through a series of emotion- and problem-focusedadaptation efforts, they were able to restoreemotional stability and even improve their perfor-mance, thus leading to a positive reappraisal of thesystems and, in Bill’s case, to a new sequence ofadaptation efforts.

Self-Preservation

Michele, like John, initially negatively appraisedLink. She felt that the new system would increaseher workload, reduce her productivity, and de-crease her commission-based salary (Q1, Q2,Table 6). She perceived the system as a threat,thinking that it might replace her (Q3). Contrary toJohn, however, Michele felt that she had littlecontrol over the technology and its usage (Q4, Q5)and had insufficient time to learn the new system

Mic

hele

(Ban

k A

)Table 6. Chain of Evidence: Self-Preservation

AppraisalAdaptation Efforts OutcomesPrimary Secondary

Q1 “I did not see how thesystem could improveclients’ satisfaction, growmy portfolio, or help bemore productive.”Q2 “I knew that it wouldonly add steps in my job. Ihad enough to do like that;I did not need that aboveeverything else. I thought itcould not help me be moreproductive anyway.” Q3 “I was really hesitant atfirst. I think I was afraid. Itwas very frustrating and Iwas afraid that the systemmight actually replace me.I was afraid that I wouldloose my job.”

Q4 “We had nochoice, really….Therewas nothing I coulddo about it.”Q5 “The system ishere, that’s it!”Q6 “I have so muchto do in my job that Idon’t even have thetime to think aboutimproving it.”Q7 “If I had the time,maybe I would try toget some training, butI don’t.”

Q8 “Anyway, after a while, I decided to stop complaining.After all, there are more important things in life!”Q9 “I came to the conclusion that since the system decideseverything, I would simply accept it and do whatever thesystem recommends.”Q10 “Moreover, I’m convinced that my clients would hate tosee me using a computer; they trust my judgment and me, notthe computer. Actually, if I were to use the computer to makeinvestment decisions, I think several of my clients would closetheir accounts and go to another bank. In anyway, that’s whatI’d do if I were the client, I trust people, not computers.”Q11 “Fortunately, the help desk people are very nice andknowledgeable. Sometimes, they ask me to use thecontextual help menu or to refer to the manual but I keep oncalling them every time I encounter a problem, it’s much fasterthan looking for the answer myself…” Q12 “Michele is one of those who still call us on a weeklybasis…most of the time for the same basic questions....Someaccount managers just don’t get it. It’s like she doesn’t want tolearn it.” (Help Desk Employee)Q13 “others, (referring to Michele) do not use it a lot, nor asthey should, and when they do, they rely on their colleaguesand on the help desk.” (Branch Manager)Q14 “Although I tried to convince my colleagues who refusedto use it, some of them postponed its use for many monthsand some still do not use it.” (John, Account Manager)

Q15 “The system does not allowme to better manage my work, toorganize my work better or tomanage my accounts moreefficiently.” Q16 “I know some say that thesystem helps us but I disagree.The system does not help meincrease my portfolio or my clientbase. It simply reduced some ofthe paperwork.”Q17 “I’m much faster usingpaper and pencil.”



or to try to adapt her work routines to make themfit together (Q6, Q7).

Michele’s reactions resemble those described inthe self-preservation strategy of our model and inour Proposition 4. Michele relied essentially onemotion-focused adaptation efforts. At somepoint, she decided to stop complaining about thenew system and convinced herself that there weremore important things to care about, thus mini-mizing the perceived threat of Link (Q8). Shesimply accepted the new system as a fact of life(Q9). She was also convinced that her clientswould not accept seeing her use a computer, thusredefining the situation by using someone else’sperspective (Q10). Finally, she avoided the sys-tem and tried to escape the situation not only bytrying not to learn it (Q11, Q12, Q13), but also bynot using it (Q14).

Overall, it seems that although Michele still thinksthat Link does not help her to be more productive,she was able to minimize the perceived threats ofthe system. She indicated that although Link hadsome positive effects on her job (e.g., reducingpaper work Q16), she felt it did not improve herperformance and did not allow her to be a betteraccount manager (Q15, Q16, Q17). In fact,Michele’s reappraisal of the system is still quitenegative as she felt that Link had reduced herautonomy and her pride and gratification asso-ciated with making decisions about loans:

We have lost all autonomy and controlover our job. The system decides for us.There are very limited opportunities tomake a decision. It is automated 100percent. We don’t even have to thinkanymore. The system does it for you.Before, I was proud of making decisionsabout loans. It was gratifying. Now, thesystem decides everything. The onlything left is to decide the interest rate thatwe will charge for the loan.

Michele’s situation contrasts with that of John andBill. While the three of them started with a nega-tive appraisal of the systems, John and Bill wereable to turn the situation around and derive

benefits from it, which led them to reappraise thesystem more positively. Interestingly, John andMichele work for the same Bank and thus ap-praised the same technology. However, Michele’sadaptation efforts did not help improve herproductivity. Rather, they seemed to have rein-forced her initial appraisal and led to a negativereappraisal.

Discussion and Contributions

The case studies provide preliminary support forCMUA and our five propositions. Convergent withthe sensemaking literature (Griffith 1999; Weick1990), a given technology was appraised differ-ently by different account managers who adopteddifferent adaptation strategies.

Our research shows that the four strategies aredifferent patterns in streams of actions that areinitiated by different appraisals and lead to dif-ferent outcomes. What strategy one uses de-pends on one’s assessment of an IT and on abroader contingent of organizational factors. Froman individual point of view, all of the strategies canbe effective in helping to address personallyrelevant issues raised by an IT event. For some,restoring emotional stability and reducing thestress associated with the IT event is a significantoutcome that allows them to continue to work andfunction properly in an environment they hadinitially perceived as threatening. For others,pushing their limits further by learning to use a newIT will constitute a major achievement. Still otherswill grasp an opportunity to increase their produc-tivity and overall performance. From an organi-zational point of view, the benefits satisficing andself-preservation strategies might at first appearsuboptimal because individuals are not trying tomaximize the potential benefits of an IT event. Insome situations, however, inducing individuals totry to maximize IT benefits might require substan-tial organizational changes and investments (e.g.,increasing job autonomy, decentralizing decision-making authority, extensive user training, or em-powering users) that might outweigh the benefitsan organization can achieve in doing so. On the



other hand, although employees’ ability to restoreemotional stability is not an end in itself, it shouldnot be overlooked. For some, it might be arequired step before they can perform problem-focused adaptation efforts which will eventuallyincrease operational efficiency and effectiveness.

Implications for Practiceand Research

The fundamental contribution of this research topractice is to highlight the importance of an indivi-dual user’s perception of an IT event in managingadaptation efforts. Hence, this research demon-strates the need for managers to understand howusers appraise an IT event and to appreciate theimportance of providing users with adequateresources so that they can adapt to it. By doingso, managers can promote adaptation strategiesthat are likely to improve users’ performance andminimize negative emotions associated with an ITevent. This study indicates that while users’ re-sponses vary from one individual to another, theycan be grouped into four broad adaptation stra-tegies, which can be used by managers to chooseappropriate management approaches.

Further, CMUA can help managers to proactivelymanage IT-induced changes, in anticipationperiods, even before an IT event occurs. It alsoprovides managers with tools that can help thembetter understand the components of user adapta-tion, better predict users’ reactions, and hencemanage them more efficiently. For example, usingCMUA, managers could identify future proponentsand opponents of a new IT, more judiciously selectlocal champions, and assist employees who needhelp adapting to the situation. Depending onusers’ appraisal of the situation, this can include,for example, providing additional training, com-municating additional information about the newsystem so that users have a better understandingof its consequences, increasing the supportprovided by colleagues, mentoring, or temporarilyreducing performance or productivity targets. Inan adaptation context, a key role of managers is tocreate an environment in which appraisal is openlydiscussed with individuals and adaptation effortsare welcomed.

This study makes four contributions to research.First, CMUA provides a rich understanding of abroad variety of user behaviors. Prior models,(e.g., TAM, IDT, TTF) help in predicting adoptionand use of a given technology. CMUA helpsexplain and predict how and why users will adaptthe technology, the work, and themselves.Grounding the predictions in the users’ appraisalsof the technology allows for variations to occuramong individuals facing a given IT event, and forvariations within individuals over time, affording adynamism that is unavailable in factor models suchas personality characteristics or in single-cyclemodels. It also offers predictive power whileretaining an agency view of IT-related behaviors,allowing for and explaining a myriad of responsepatterns such as technological adjustment andreinvention, changes in individual habits, andresistance to IT-induced changes.

Second, by integrating antecedents, adaptationefforts, and outcomes, by focusing on both positiveand negative emotions associated with an ITevent, and by taking into account what objectivesusers seek to achieve when adapting, CMUAoffers a complementary perspective to thevariance and process approaches to the study ofuser adaptation.

Third, this research might help shed some light onthe relationship between IT and individual perfor-mance at work. Despite significant research ef-forts, the empirical evidence to date is inconclusiveand even seems contradictory (Pinsonneault andRivard 1998). While several hypotheses can beproposed to explain this state of empirical evi-dence, the possibility that an intervening variableacts upon the relationship between IT use andindividual performance seems plausible. It maywell be that users’ appraisal and adaptationinfluence how they use the technology and how itwill affect their performance. This study suggeststhat when individuals appraise an IT event as athreat, their efforts will be mostly oriented towardeither diminishing emotional distress associatedwith the technology or reducing the perceivednegative consequences associated with it. Whilethese strategies can be successful and allow theindividual to restore emotional stability, they are



not likely to quickly lead to any significantimprovements in the performance of the individual.On the other hand, adaptation efforts associatedwith positive appraisals can lead to actions aimedat improving operational and functional efficiencyand effectiveness, which are likely to positivelyaffect user performance.

Fourth, this research provides a contribution topsychology by adapting and extending copingtheory (Lazarus 1966). To our knowledge, this isthe first time that coping theory has been appliedto understanding how individuals react to theintroduction of a tangible artifact as opposed toabstract events such as mergers, losing a job, orgetting divorced. This can lead to a differentappraisal process. Users can rely on both theabstract and concrete features of the IT event toassess its potential consequences. This may alsotrigger a wider range of adaptation efforts. Forinstance, users can act directly on the object thatis perceived as being the source of the disruptionand try to physically eliminate it (e.g., sabotage,theft). A second contribution of CMUA to psychol-ogy is that it shows how coping can be applied topositive events. It is known that coping theory canbe used to assess positively appraised events(Folkman and Moskowitz 2000), but to ourknowledge it has never been used in that context.Finally, coping theory is relatively vague in definingand describing the coping strategies and linkingthem to antecedents. Our research identified fourprecise strategies and the contingent situations inwhich they are likely to occur. It also providespreliminary evidence of their validity.

Study Limitations andFuture Research

This study has limitations that should be acknowl-edged. First, the retrospective nature of ourempirical study might have left room for a recallbias from our respondents. Despite careful atten-tion to this issue, it is possible that some respon-dents have reported weaker or distorted storiesabout their appraisal and adaptation process.Additionally, it was not possible to interviewindividuals who either retired or were transferred

since the IT events had occurred in the two banks.Such interviews might have provided us with adifferent perspective from respondents who mayhave appraised the situation as too demandingand who may have decided to withdraw from thesituation. Finally, because our two research sitesoffered very similar characteristics, the generali-zability of our model to other contexts needs to befurther investigated.

This research suggests five main avenues forfuture study. First, more research is needed tofurther explore, test, and refine CMUA. While ourstudy was conducted with knowledge workersadapting to flexible technologies, it seems thatCMUA has a broader scope and can explain theadaptation behavior of various types of usersdealing with other technologies. More research isneeded to test the model with different users andtechnologies. In particular, large-scale studiesinvolving numerous users would help assess themodel’s generalizability. Also, more work needs tobe done to further understand the effects of somesocial factors (e.g., group norms, top managementinfluence, organizational culture, and colleagues’attitude) on user adaptation. To do so, one couldstudy the adaptation behaviors of comparableusers who face a similar IT-induced disruption indifferent organizational or group contexts.

Second, the sequencing and interplay of problem-and emotion-focused adaptation efforts should bestudied. For example, because some individualsneed to feel worse before they can feel better(Lazarus and Folkman 1984), it is possible that, forsome users, emotion-focused efforts that tempo-rarily increase emotional distress (e.g., self-blame)are necessary to induce problem-focused adapta-tion and mobilize individuals to adapt to an ITevent. Longitudinal studies are thus required toexamine the user adaptation process in depth.

Third, this research proposes four principal useradaptation strategies related to IT events inorganizations. More research is needed to docu-ment and build a comprehensive inventory of IT-related adaptation efforts and develop a typologyof adaptation strategies. For instance, it would beinteresting to apply CMUA to understand extreme



user responses such as sabotage. Using CMUA,it could be argued that sabotage occurs when anIT event is assessed as extremely threatening,when users feel they lack control over the situa-tion, when the resources available are insufficientto handle the situation, and when they cannotwithdraw from the situation. In such a situation,users might be forced to stay in the threateningsituation and they might see no other alternativesexcept to try to manage the situation at hand andrestore emotional stability by rendering the ITinoffensive.

Fourth, one’s self-efficacy (one’s belief in his/herability to adapt to a specific situation) has beenfound to moderate the appraisal–coping rela-tionship (Jerusalem and Mittag 1995; Jex andBliese 1999; Jex and Gudanowski 1992; Schau-broeck et al. 2000). Research is needed toexamine the notion of self-efficacy in the context ofuser adaptation (e.g., as a belief about one’scapability to adapt the IT, the self, and the job) anddetermine what effect it has on appraisal andadaptation. Moderating effects of other knownantecedents of IT acceptance and use (e.g., userinnovativeness, computer anxiety, perceived easeof use, and perceived usefulness) should also beinvestigated.

Finally, the timing of appraisal and adaptationefforts should be studied. The coping process hasbeen found to occur at different points in time forvarious individuals (Folkman 1992). The wholeprocess can occur in the anticipation period (whichwe would call pre-implementation) or in whatpsychologists call the impact and post-impactperiods (implementation and post-implementationperiods). When adaptation occurs in the antici-pation period, users can modify their work andthemselves based on the expected consequencesand features of the future IT event. Modificationsto the technology are also possible when it is beingdesigned (e.g., users participating in a project caninfluence the functionalities and features of thenew IT or adjust their requirements; Orlikowski1996). During the post-implementation period,users can modify their work, themselves, and thetechnology while using it. Future studies couldshed some light on how adaptation strategies

unfold at different points in time and acrossperiods.

Despite the fact that user adaptation behaviors arewidely accepted as key to understanding severalimportant issues related to the development,implementation, usage, and effects of IT inorganizations, little is known on the topic. Whilethe framework proposed in this paper constitutesa step toward a better understanding of useradaptation, it raises as many questions as itprovides answers. It is hoped that this study willstimulate research in this domain.

Acknowledgements

The authors are grateful for the insightful com-ments and suggestions received from the senioreditor, associate editor, and three reviewers. Thepaper has benefitted from comments of the parti-cipants of the research seminar of the MarshallBusiness School of University of SouthernCalifornia. We thank the Social Sciences andHumanities Research Council of Canada (SSHRC)for providing support for this research and theCenter for Research on Information Technologyand Organization at the University of California,Irvine.

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About the Authors

Anne Beaudry is an assistant professor at theJohn Molson School of Business, ConcordiaUniversity. She obtained her Ph.D. from HEC-Montréal. Her research has been presented at theAcademy of Management, Americas’ Conferenceon Information Systems, the AdministrativeSciences Association of Canada, and the Inter-national Conference on Information Systems. Herresearch interests focus on IT-induced behaviorsand on individual and organizational impacts of ITimplementation and use.

Alain Pinsonneault is the Imasco Chair of IS andJames McGill Professor in the Faculty of Manage-ment at McGill University. He obtained his Ph.D.at the University of California, Irvine. His currentresearch interests include the business value of IT,organizational and individual impacts of IT, ERP,health informatics, electronic commerce, and man-agement of IT departments. He has publishedpapers in Management Science, MIS Quarterly,Information Systems Research, The Journal ofManagement Information Systems, OrganizationScience, Decision Support Systems, and the Euro-pean Journal of Operational Research.

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