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Theory Development in EnterpriseSystems and Organizational LearningM. Shane Tomblin aa Marshall University , Huntington, WV, USAPublished online: 23 Oct 2010.

To cite this article: M. Shane Tomblin (2010) Theory Development in Enterprise Systems andOrganizational Learning, Journal of Organizational Computing and Electronic Commerce, 20:4,398-416, DOI: 10.1080/10919392.2010.516647

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THEORY DEVELOPMENT IN ENTERPRISE SYSTEMSAND ORGANIZATIONAL LEARNING

M. Shane Tomblin

Marshall University, Huntington, WV, USA

Despite the wide-spread attention focused on Enterprise Resource Planning (ERP) systems

by both researchers and practitioners, there remain gaps in understanding their

implementation and impacts. The majority of ERP research concerns either critical success

factors or ERP effects. Very little has been done with regard to the relationship between ERP

and organizational learning (OL). Much of the existing literature in this area focuses on

learning during system implementation with a small amount of additional literature focusing

on learning resulting from or connected to ERP use. The work of integrating research on ERP

implementation and post-implementation effects is begun by identifying the use of OL as a

lens for understanding these two phenomena. The paper makes two unique contributions to

the existing literature. First, a case is built for ERP support of OL by emphasizing ERP

decision-support capabilities. Second, a set of existing theoretical constructs is put forward as

a possible basis for investigating the relationship between ERP implementation learning and

post-implementation support of OL. Finally, the paper outlines areas for future investigation

and provides a basic investigative framework to be pursued. Given that this research identifies

connections between the two forms of learning, it is possible that what is represented is a

lifecycle of OL within the ERP implementation/post-implementation chain of events.

Keywords: decision support systems; enterprise resource planning; organizational learning;

system implementation; technology support

1. INTRODUCTION

With the increased use of integrated information systems—Enterprise Resource

Planning (ERP) systems in particular [1]—it is necessary to advance current under-

standing of the implementation, use, and organizational impact aspects of cross-

functional and process-focused systems. This is due, in no small part, to their large

IT budget share and key role in organizational IT infrastructure [2] in addition to their

risky payoff and the desire of adopters to reap rewards in the form of increased

productivity [3], operational performance [4], and customer satisfaction [5]. ERP

systems pose multiple challenges to adopters, both in implementation [6–11] and

post-adoption use [12, 13].Robey et al. [14] described two major groupings of ERP research. They noted

that the majority of ERP research concerns either critical success factors or ERP

Journal of Organizational Computing and Electronic Commerce, 20: 398–416, 2010

Copyright # Taylor & Francis Group, LLC

ISSN: 1091-9392 print / 1532-7744 online

DOI: 10.1080/10919392.2010.516647

Address correspondence to M. Shane Tomblin, Marshall University, Division of Management,

Marketing, and Management Information Systems, One JohnMarshall Drive, Huntington, WV 25755, USA.

E-mail: shane.tomblin@marshall.edu

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effects. With regard to the former, success for ERP is often defined in terms of projectmanagement measures, such as meeting deadlines and staying within budgets, orbusiness benefits, such as decreased inventory or labor costs. These studies generallyshow that factors associated with project success are top management support, effec-tive project teams, and organization-wide commitment. Value-generating criticalsuccess factors include metrics that clarify managerial objectives for ERP, develop-ment of processes and structures for managing cross-functionality, and investment inorganizational change. With regard to ERP effects, research has revealed a mixed bagof results. Although ERP packages and systems are sold on their assumed positiveattributes, both positive and negative effects arise. While some firms see positiveresults almost immediately, others take asmuch as a year to experience positive results.ERP can increase individual job flexibility, but the systems themselves were noted forbeing less flexible than the legacy systems that they replaced. The authors alsosummarize research concerned with identifying process models of ERP implementa-tion. In this type of research, implementation is described as a series of stages, withanywhere from three to six stages. Despite the number of stages, each seems to follow alife-cycle process, with stages proceeding in a necessary sequence. For each groupingof research, the authors noted that most efforts are largely descriptive, with very littlecompelling theoretical explanation. An exception to this is [15], which provides evi-dence of the importance of considering decision support objectives in ERP plans.

Al-Mashari [16] provided a more fine-grained description of ERP research. TheERP research taxonomy lists 24 areas, several of which can be associated broadly withimplementation issues and ongoing use and effects. Those associated with implementa-tion issues include deployment strategies, change management, technical aspects ofimplementation, successful and failed implementation, managing various scales ofchanges, role of IS function in implementation, critical success factors, project manage-ment infrastructure, and benchmarking best implementations. Research areas that canbe associated with ongoing use and effects are business process management, trainingand teaching ERP, supply chain reengineering, ERP and E-commerce applications,knowledge management, investment evaluation, and performance measurement.

There is, understandably, also great interest in the impacts of ERP implementa-tions among practitioners. Kennerly andNeely [17] provided summary outcomes froma case study conducted at a multi-site European organization. Financial performancedata gathered at the four sites showed no direct impact on return on sales. However,corporate level managers identified other positive impacts including commonality ofoperating systems and procedures, standardization of reporting systems, improvedefficiency and control, rationalization of inventories, increased leverage on suppliers,and improved planning. Results at the plant, functional, and individual level are moremixed. Immediate frustrations gave way, over time, to improvements in system use tothe point that users were able to advantageously leverage the system to analyze dataand improve supplier relations. Given the factor of improvement over time, animportant underlying theme identified in this article is that of learning.

It is with respect to learning that research has begun to appear that maycollectively offer a way to integrate research on ERP implementation and post-implementation effects. Shehab et al. [6] provided a comprehensive review of theERP research literature and mentioned organizational learning (OL) in their assess-ment of areas for future research. Determining the connection between ERP and OL isdesirable by implication, because the competitive business environments in which ERP

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can be exploited as a tool [18] are the same environments in which OL can provide acompetitive advantage [19]. It is the connection between ERP and OL that this paperinvestigates. The body of literature linking ERP and OL is currently small andunfocused; however, it is rich enough to provide a foundation for the current study.Using OL as an integrative foundation, it is possible to connect ERP implementationissues and post-implementation effects.

This paper anticipates that the outcome of such an investigation will be thebeginning of a conceptual foundation, with subsequent investigations refining andadding to current conceptual findings. It is believed that the stated research goal willadd significantly to the current and future understanding of ERP implementations andsubsequent impacts, with the paper’s particular contribution being a synthesis of theoryconcerning implementation learning and post-implementation learning. The remainderof the paper is, therefore, organized, as follows. Section II presents appropriate con-ceptualizations of OL. Section III reviews current literature relating ERP implementa-tion and learning. Section IV builds a case for ERP support of organizational learning.Section V identifies and discusses connections between ERP implementation learningand ERP support of OL. Section VI concludes the paper with an agenda of areasdeserving investigation and potential practical impacts of such investigation.

2. CONCEPTUALIZING OL

Many OL frameworks and conceptualizations exist in the abundant literature onOL and in the rather broad literature on the relationship between OL and informationtechnology. At the particular stage of conceptual development of this study, it seemsreasonable to use definitional descriptions of OL that are broad, thus providing roomfor refinement. Furthermore, it is noteworthy that characterizations of OL that rely onthe concept of knowledge are particularly relevant for our purposes. With this in mind,three particular conceptualizations of OL are adopted here. First, Argyris and Schon[20] identified two types of learning. Single loop learning (SLL) is defined as thedetection and correction of error. Basically, an individual or organization identifies adiscrepancy between performance and some desired goals, with corrective action thenbeing taken. SLL can be seen as that limited type of learning that maintains anorganization relative to its environment. Double loop learning (DLL) is that kind oflearning in which there is a questioning of the underlying assumptions and goals with aresultant change in both. DLL is of critical importance to organizations and individualsbecause it enables further learning and the potential of changing informal and formalroutines and processes, sometimes yielding radical change in organizational design.

For those researchers seeking to understand certain ERP phenomena, includingits relationship to OL, an oft-cited OL framework is that of Huber [21]. Four con-structs are related to OL. Knowledge acquisition is a broad term for processes thatinclude knowledge arrived at through experiment or experience, knowledge absorbedthrough observing the experiences of others, and knowledge acquired through internaland environmental search activity. Information distribution concerns the creation ofadditional information by integrating existing items of information by entities withinthe organization and increasing the sources of existing information within the organi-zation.Organizational memory refers to the retention of knowledge and information inthe minds of individuals and that which is stored in standard operating procedures,routines, and information, systems. Information interpretation refers to the process of

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giving meaning to information, as well as to the translation of events and the devel-opment of shared understandings and conceptual schemes. Learning is tied to action.Thus, an increase in the variety of interpretations of an item of information impliesthat more learning has occurred because of an increase in the range of possiblebehaviors. Also, more learning has occurred when units understand the interpretationsheld by other units because this understanding promotes or inhibits cooperation,which, in turn, changes the range of potential behaviors.

Ching et al. [22] posited that OL subsumes learning by entities. Human or non-human entities learn when they adjust the contents of their knowledge systems. A knowl-edge system may consist of various types of knowledge, such as descriptive, procedural,and reasoning knowledge [23]. Because a knowledge system can be adjusted in differentways, the authors contend that there exist different modes of learning. Because OL alsoinvolves trans-entity learning, the knowledge system of the organization is more than asimple union of the knowledge systems of its respective entities. This can be explained bythe presence of various repositories, as well as communication channels. Repositoriesserve as storehouses of various kinds of knowledge, separate from the organization’sentities, which can be made accessible for review and use. Communication channels areimportant fororganizational learningbecause theopeningand shiftingof communicationchannels, if used effectively, can create new knowledge. Finally, this characterization ofOL is important because the patterns of interaction through communication and coordi-nation give rise to organizational-level knowledge.

3. ERP IMPLEMENTATION AND LEARNING

Arguably, if an ERP implementation fails, or simply does not live up to expecta-tions, it would be reasonable to anticipate that learning during implementation wasinhibited. This kind of statement, however, is currently unclear from a researchperspective. First, what does the phrase ‘‘implementation learning’’ really mean?This paper posits that Implementation Learning (IL) is comprised of three types oflearning: learning to implement, learning from implementation, and organizationalmemory. Furthermore, IL sets the stage, not only for effective ERP system use, but foruse supporting post-implementation organizational learning.

The strategic value of organizational learning (OL) during phased ERP imple-mentation has been studied from the perspective of compound real options [2]. OL isimportant due to the requirement of learning about the interactions of people duringERP implementation. Understanding the interactions reduces the complexity and deci-sion ambiguity of the process. Phased ERP implementation helps OL by adjusting staffeducation and organizational design, reducing hostility to the system, and enhancinguser involvement. Subsequently, the firm can gain further project knowledge for full-scale investment and better respond to uncertainties during further implementation.

Case studies of ERP implementation at two affiliate companies at two differentpoints in time reveal that even unsuccessful ERP implementation can provide learningbenefits that can be directed toward later implementations [24]. The first unsuccessfulimplementation permitted OL to occur around certain critical success factors, whichwere carried to the second implementation and allowed the proper configuration of theimplementation process. Tsai and Hung [25] regarded ERP implementation as an OLbehavior. They contended that problems with education and training and vendor

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support are impediments to successful ERP implementation and that implementationwill improve when users are appropriately familiarized with the system.

The idea of purposefully learning from failures during ERP implementation hasbeen investigated [26]. In comparative case studies of different firms, a firm’s learningresults from implementation of ERP depended on project characteristics (require-ments) that are influenced by the firm’s focus on implementation as a process and itsorganizational culture. The successful implementation had project characteristics thatwere defined by a set of well-planned implementation actions, lowered implementationoutcome uncertainty, smoother implementation through lower-scale expectations,and rigorous monitoring and feedback during implementation progress. While appro-priate internal skill sets and task-technology fit were further components of theassumed model, neither implementation had an appropriate task-technology fit.Given the focus is on learning from ‘‘small,’’ expected failures, achieving appropriatelevels of each characteristic is theorized to permit a firm to recover from small failuresalong the way to full implementation.

A critical factor affecting the implementation of ERP is that of knowledgetransfer during implementation [27]. Especially in the case of the use of vendors andconsultants, it is important that knowledge flow from the consultant to the client.Consultant competence, seen as a stock of knowledge, can flow to the client firm,provided that the client firm’s absorptive capacity, i.e. its own knowledge stock, issufficient to absorb the consultant knowledge. Together, these two variables influenceERP implementation knowledge transfer. Ultimately, the transfer of knowledgeaffects the organization’s process fit with the ERP system.

Necessary ERP knowledge does not come exclusively from the ERP vendor norcan vendor, ERP knowledge simply be transferred into the adopting organization [28].Rather, needed ERP knowledge, that which is appropriate to the adopting firm, issynthesized from knowledge that resides with the vendor and that which is dispersedwithin the firm (e.g., across functional divisions and work teams). A large percentageof ERP knowledge is tacit [29] in nature. This knowledge must be surfaced duringimplementation and combined with explicit, ERP system-specific knowledge duringthe implementation process. This process is facilitated by project teams comprised of avariety of organizational members, which analyze and model the current state ofexisting processes, identify gaps between the current state and the desired state asprovided in the new system, and oversee the installation of the new system and systemtraining. This process of implementation promotes convergence of cross-functionalinformation and knowledge at the organizational level. It also alleviates the divergencethat exists at the individual level by allowing users to understand how their tasks fitinto the overall process and how organizational objectives are achieved by thatprocess. This is in agreement with research that asserts that ERP end-users mustreceive immediate education on the process focus of ERP within the organization [30].

Organizational processes can be regarded as organizational memory [28] giventheir form and distribution across members’ cognitions. ERP systems potentiallyembed many, if not all, of the processes necessary for adopting organizations. Anorganization may choose to adopt the entire process knowledge of the ERP orreconfigure aspects of the ERP to match the necessities of the organization. Robeyet al. [14] cited knowledge of existing business processes (i.e., organizational memory)as one of the main impediments to ERP implementation. Two types of barriers haveexisted: configuration knowledge barriers and assimilation knowledge barriers.

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Configuration knowledge barriers have been overcome by appropriately establishedcore teams and consultants. Assimilation knowledge barriers have been overcomethrough choices of training, incremental implementation, or concerted change efforts.

From the foregoing discussion, it is possible to categorize implementation out-comes according to the three proposed components of ERP implementation learning.Table 1 lists each IL learning component and potential outcomes. ‘‘Learning toimplement’’ can be loosely defined as those outcomes that enable the organization toconduct an implementation. This would apply to current and possible future imple-mentation efforts. Selection of implementation strategy, knowledge of implementa-tion activities, and determination of critical success factors fall into this category.‘‘Learning from implementation’’ encompasses derived knowledge and informationthat increases understanding of the cross-functional and process orientation of theorganization. Identification of general and individual-level process knowledge as wellas convergence of cross-functional information and knowledge belongs to this cate-gory. ‘‘Organizational memory’’ refers to the embedding of process knowledge. Thecreation of tacit process knowledge, through training and core team creation andsystem-embedding of organizational processes and routines, belongs to this category.

4. ERP SUPPORT OF OL

Here, it must be noted that the literature connecting ERP and its support of OL isquite limited. A search for relevant articles identified few investigations that arguably linkERP and post-implementation OL. While not explicitly indicative of ERP support forOL, evidence of the existence of ongoing learning effects in the form of order lead-timeimprovements over time following ERP deployment is found in [31]. ERP is able to serveas ongoing support for OL, particularly at the organizational level, by serving as organi-zational memory [32]. Upon implementation, ERP systems contain much of the knowl-edge of the organization related to strategy, structures, processes, and so forth. ERP arethus able to carry out the organizational memory process of acquisition, retention,maintenance, and retrieval [33]. This can support OL at the level of the organization byembedding and retaining newknowledge,maintaining stocks of knowledge, and allowingusers to access and use existing knowledge, possibly creating new knowledge.

Caremust be taken to balance any claims, such as those made above, of the realityor potential of ERP systems to support OL by considering the cautions raised in [34].

Table 1 Type of implementation learning and potential outcomes.

Type of learning Outcomes

Learning to implement l Use of phased implementationl Knowledge of interactions during implementationl ERP implementation knowledge transferl Determination of critical success factors

Learning from implementation l Identification of internal process knowledgel Identification of individual-level process rolesl Convergence of cross-functional information and knowledge

Organizational memory l System-embedding of organizational processes and routinesl Creation of tacit process knowledge through training and

creation of core teams

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In short, ERP systems arrive with ready-made plans of action and thus ‘‘help institutepatterns of action and communication and shape human agency in organizations’’ (p.21). Consequently, while it may be possible that ERP can be shown to support OL, it isalso possible that ERP could constrain users to the point of inhibiting OL. The authorindicated that ERP systems break the link between framing and action. Once this link isbroken or disrupted, the capacity is lost to decide which pieces of procedural knowledgeapply in particular situations, andbehavioral innovation is stifled.Wemight extend thesethoughts by appealing to the notionof double-loop learning definedpreviously.Once theinherent procedures of the ERP system are enacted, it is possible that theymay be simplytaken as-is without, over time, calling them into question with possible subsequentchange. This notion of the inhibition of OL by ERP is reflected in the cautions providedin [35] on the possible trade-offs between exploitation, the use and maintenance ofexisting capabilities, and exploration, the search for alternate capabilities, that could beexperienced by multi-national enterprises after ERP implementation. Exploitation canbe seen as similar or related to SLL, while exploration is similar in effect to DLL.

Despite the assertion [34] that there are very real differences between ERP anddecision support systems (DSS) (i.e., that ERP prescribes and/or enacts organizationalprocedures whereas DSS use built-in knowledge to support the selection of courses ofaction), it is the current paper’s contention that the OL-supporting capabilities of ERP canbe investigated via their decision-support characteristics. Bhatt and Zaveri [36] suggestednine general DSS attributes that enable OL. They relied on the single- and double-looplearning components in [20] and Huber’s [21] information acquisition, information distri-bution, information interpretation, and organizational memory constructs to understandOL. The set of attributes include efficient access of data, experimentation with variables,generation of alternate models, trend analysis, exploratory and confirmatory models,simulation, justification of solutions, exploration and exploitation of stored data, andidea generation. The decision-support characteristics of ERP should enable OL by helpingto ‘‘facilitate an understanding among different decision-making participants’’ [36, p. 304].

Holsapple and Sena [37] measured the perceived existence and importance ofmulti-participant DSS (MDSS) characteristics in ERP. Findings reveal that MDSScharacteristics are perceived to exist at relatively significant levels and to be relativelyimportant to users. These characteristics are reproduced in Table 2. The list of attributesis arrived at by building on the Group Decision Support System (GDSS) capabilities in[38] and extending them to MDSS, which support more complex organizational deci-sion-makers, and to DSS that support individual decision-makers. Thus, it is importantto note that a multi-level support perspective is embedded in possible sets of impactsarising from the listed attributes. The applicability of this perspective is bolstered by theidentification of ERP as a multi-channel IT [39]. Although not all users may have directaccess to or interaction with all others, users may be dependent on all others through acomplex, intra-organizational network based on the flow of knowledge [40].

We now add a complementary extension from another GDSS classification in[41]. The primary types of support provided by GDSS can be divided into contentsupport and process support. Content support is described as the extent to which acomputer-based system is capable of providing support in addressing the substance ofa task, problem, or decision in a particular domain. Content support is provided indata, information, and knowledge processing without regard to the participation orinvolvement of the groupmembers. Process support is described as the extent to whicha system is able to support or influence the proceedings of interacting participants.

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This support is seen in changes made to verbal or non-verbal exchanges of informa-tion, attitudes, beliefs, or procedures. This type of support, coming from the commu-

nication hardware and software, is designed to positively impact participation andinformation exchange. We contend here that content and process support can also beextended to MDSS. It is not difficult, then, to see these types of support as inherent inERP, especially if we regard ERP as a specialized type of MDSS. Returning to theprevious list of MDSS characteristics, it is possible to divide these along the contentand process support dimensions. Table 3 provides the resulting list. While it is believedthat this is a rather parsimonious categorization, some characteristics may not fitexclusively within either the content or process support categories.

What remains, then, is to conceptually connect the categorized attributes to OL.Recalling the selected OL descriptions and definitions, a preliminary list of OL outcomescan be created. Table 4 lists potential outcomes according to OL definition or description.First, content support is related toOLinallowingMDSSusers access to stored information.Having access to stored information during tasks or decision-making sessions can actgenerally to aid understanding of a problem domain. Confirmation of current understand-ing of the problem or process at hand, thus reinforcing existing mental structures, can alsoresult from access to stored information. Conversely, information accessed as a result ofsearchandretrieval canact to call existingknowledge,procedures,or routines intoquestion.Content support can allow users to synthesize mentally stored knowledge with repositoryknowledge to create newknowledge or to integrate different itemsof repository knowledge.Lastly, task structuring provided in MDSS can affect problem analysis and decisionmaking.These capabilities have been observed and studied in the use of groupDSS [42–44].

Process support can also generally be related to OL in its ability to influence interac-tion and information exchange. Process support can create shared understanding, as well asenhanced problemunderstanding as implied in the study of groupDSS [45, 46]. This type ofsupport can create connections between decision participants, leading to the exchange of

Table 2 MDSS characteristics (adapted from [37]).

Selects and delivers knowledge to meet unanticipated needs.

Presents results in formats customized to suit the tastes or needs of decision participants.

Derives new knowledge via automated calculation, analysis, or reasoning.

Provides mechanisms to facilitate communication among decision participants

across the organization’s boundaries.

Accepts requests in styles that suit the tastes or needs of decision participants.

Provides mechanisms to structure and regulate the making of interrelated decisions.

Provides mechanisms to structure and regulate tasks performed in decision making that crosses

organizational boundaries.

Includes a repository of knowledge used to define, document, or regulate the actions of decision participants.

Includes a repository of knowledge about decision participants used to facilitate interactions among decision

participants.

Includes a repository of knowledge used to identify and/or solve problems encountered in decision making.

Provides mechanisms to facilitate communication among decision participants within the organization.

Gives users flexibility in determining the timing of requests—from spur-of-the-moment to scheduled

requests.

Provides mechanisms to structure and regulate tasks performed by multiple participants jointly making a

decision.

Allows public repositories of organizational knowledge with shared access.

Provides mechanisms to structure and regulate tasks performed by an individual decision maker.

Allows private knowledge repositories under the access control of individuals.

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information and knowledge. It can also be argued that the sets of connections thus createdand maintained, in and of themselves, constitute a form of knowledge. Thus, as commu-nication links amongusers are created, destroyed, ormodified, learning canbe said tooccur.

Considering the numbered items in Tables 3 and 4, it is possible to argue forpotential positive relationships between the grouped content and process support char-acteristics and the items in the grouped lists of OL outcomes. Some examples will serve toillustrate the claim.Content support items (5), (7), and (9) inTable 3 dealwith repositoriesof knowledge for individuals and multiple users. These could be connected to the orga-nizationalmemory items (6), (7), and (8) listedunder theOL-RelatedConstructs groupingin Table 4, or item (5) under the Knowledge System Adjustment grouping. Being able toderive new knowledge via calculation, analysis, or reasoning (item (3) under contentsupport) could be related to items (1)–(5) under OL-Related Constructs grouping inTable 4. Process support items may find similar relationships. For example, item (4)under process support could aid users in understanding the responsibilities and/or tasks ofothers acrossdepartments.Wewould thus expect this item tobepotentially related to item(13) under the OL-Related Constructs grouping in Table 4.

However, it is entirely possible, given cautions covered earlier, that ERP char-acteristics inhibit or have a negative relationship to potential OL outcomes. Forexample, items (1), (2), (4), (8), and (9) under content support may be negativelyrelated to items (5) and (6) under the SLL and DLL grouping in Table 4. Havinginformation provided in a customized format may serve to continually reinforce theexistence of knowledge, procedures, routines, etc. upheld by the ERP so that these

Table 3 Content and process support classification of ERP MDSS characteristics.

Content Support Characteristics:

(1) Selects and delivers knowledge to meet unanticipated needs.

(2) Presents results in formats customized to suit the tastes or needs of decision participants.

(3) Derives new knowledge via automated calculation, analysis, or reasoning.

(4) Accepts requests in styles that suit the tastes or needs of decision participants.

(5) Includes a repository of knowledge used to identify and/or solve problems encountered in decision

making.

(6) Gives users flexibility in determining the timing of requests—from spur-of-the-moment

to scheduled requests.

(7) Allows public repositories of organizational knowledge with shared access.

(8) Provides mechanisms to structure and regulate tasks performed by an individual decision maker.

(9) Allows private knowledge repositories under the access control of individuals.

Process Support Characteristics:

(1) Provides mechanisms to facilitate communication among decision participants across the

organization’s boundaries.

(2) Provides mechanisms to structure and regulate the making of interrelated decisions.

(3) Provides mechanisms to structure and regulate tasks performed in decision making that crosses

organizational boundaries.

(4) Includes a repository of knowledge used to define, document, or regulate the actions of decision

participants.

(5) Includes a repository of knowledge about decision participants used to facilitate

interactions among decision participants.

(6) Provides mechanisms to facilitate communication among decision participants within the

organization.

(7) Providesmechanisms to structure and regulate tasks performed bymultiple participants jointlymaking

a decision.

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remain unquestioned. Item (4) under process support, if rigid enough, may also proveto be an inhibitor of, or be negatively associated with, desired learning outcomes if useof the repository excludes beneficial communication channels or relationships, orinhibits the diversity of contacts or communication channels.

By parsing ERP attributes along the lines of their decision support capabilities orcharacteristics, we have established system use patterns of content and process supportthat have testable relationships to OL outcomes. The lens of decision making andsupport is useful for a couple of reasons. Decision making is an information and knowl-edge intensive activity. Knowledge, through its creation and use, is inextricably linked tolearning. Learning occurs when new knowledge is created. A decision is, arguably, a newpiece of knowledge [47]. Decisions are also tied to actionwithin organizations.Decisionsare oftenmade in the context of ERPwith regard to internal operations and processes, aswell as how the organizationwill continue to act or react within its external environment.It is this knowledge-decision-action chain in which organizational learning often occurs.

5. ERP IMPLEMENTATION LEARNING AND POST-IMPLEMENTATION OL

Thus far, this paper has introduced two partial frameworks for understanding therelationships between ERP and organizational learning. First, we now have a structurefor learning in ERP implementation. Second, we have established a perspective of

Table 4 Potential OL outcomes by definition or description.

Knowledge System Adjustment [22]:

(1) Changes to/creation of descriptive knowledge.

(2) Changes to/creation of procedural knowledge.

(3) Changes to/creation of presentation knowledge.

(4) Changes to/creation of linguistic knowledge.

(5) Changes to/access of/synthesis from knowledge repositories.

(6) Changes to/creation of communication channels.

OL-Related Constructs [21]:

(1) Acquire knowledge through experiment/experience.

(2) Acquire knowledge through internal search activity.

(3) Acquire knowledge though environmental search activity.

(4) Creation of new knowledge/information through synthesis of existing information.

(5) Increase in stock of knowledge/information.

(6) Act as a repository of data/information.

(7) Act as a repository of procedural knowledge.

(8) Act as a locus of organizational routines.

(9) Aid in giving meaning to data and information.

(10) Aid in giving meaning to events.

(11) Aid in developing shared understanding.

(12) Aid in developing shared conceptual schemes.

(13) Increase in cross-departmental understanding.

SLL and DLL [20]:

(1) Ongoing detection and correction of error.

(2) Maintenance of organizational routines.

(3) Maintenance of organizational procedures.

(4) Identification of confirmatory information.

(5) Questioning of existing routines.

(6) Questioning of existing procedures.

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decision-support as a means of understanding the relationship of post-implementationERP use to OL. Separately, either provides a basis for further investigation. The parti-cular contribution of the current work is to begin to determine how these two phenomenaare related. Given that the theoretical basis for a relationship is not clearly in evidence inthe extant literature, we must either identify some conceptual or theoretical basis that isimmediately adaptable or piece together a foundation from candidate concepts.

To this end, the question must be asked as to why we would expect the two typesof learning to be related in the first place. It is possible that a particular ERPimplementation might be situated in one of several possible scenarios. First, anorganization might successfully implement ERP and subsequently use it, intentionallyor otherwise, to produce learning outcomes. Second, a successful ERP implementationmight not be followed by any significant learning outcomes. Third, an ERP imple-mentation could fail. Its failure could manifest as abandonment of the project, or itsfailure could be evident (at least from the organization’s estimation) in its failure to beappropriately adopted by its intended users. We would not expect to connect imple-mentation learning and post-implementation OL in this last scenario. It seems reason-able, then, to expect the two types of learning to be connected through post-implementation use. Furthermore, the activities that lead to implementation and usemust be grounded in the assimilation of organizationally relevant knowledge. Thus, ifthe two phenomena are significantly related, ERP implementation learning outcomesshould establish necessary or sufficient conditions under which post-implementationOL is promoted or made possible.

An initial candidate concept is the intensity of organizational learning [48]. Theintensity of organizational learning is an organizational capability and is related toabsorptive capacity [49]. This construct can be defined as the ability to capture,assimilate, and apply knowledge efficiently. The quality of an organization’s ITinfrastructure and its IT business experience are found to be positively and significantlyaffected by the intensity of organizational learning. Implementation of ERP places thesystem squarely at the core of an organization’s IT infrastructure. IT infrastructure [50]is seen as a potentially value-adding capability that can permit firms to share informa-tion across functions, innovate, exploit business opportunities, and respond tochanges in business opportunities [51]. IT business experience is argued to allow anorganization to integrate IT strategy and business strategy, as well as anticipate theneeds of customers in a timely and competitive manner [52]. Development of both ITbusiness experience and a quality IT infrastructure are, arguably, desirable for theimplementation of ERP. Thus, given that the intensity of OL is positively related to thetwo aforementioned constructs, it reasonably follows that it could be a precursor to theactivities and outcomes that lead to proper ERP implementation.

Additional theoretical underpinning can be found by extending work addressinguser innovation in information technology [53]. To innovatively utilize a new informa-tion technology, users need to know what the technology is capable of providing andhow to make use of it within the particular organizational environment and workprocesses. Their emphasis is on the innovative use of technologies in the form of newapplications of existing IT rather than passive adoption. Here, we regard the use ofERP technology to acquire, create, distribute, or store knowledge as ‘‘innovative’’ useof the implemented technology. Such use can potentially improve the standing of thefirm with respect to the customer or supplier, improve decision making, improveinternal operations, or create other innovations that can be regarded as learning.

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The propensity to innovatively use a technology is positively affected by threeantecedents: technology cognizance, intention to explore, and ability to explore.Technology cognizance relates to a user’s knowledge about the capabilities of a tech-nology, features, potential use, and benefits and costs. This relates to what is called‘‘awareness knowledge’’ (context-free or general knowledge about an application andits uses). This last type of knowledge is considered a critical antecedent of anothernecessary component, ‘‘how-to’’ knowledge (contextual, or firm-based, knowledgeabout the technology within a user’s firm), which is necessary for deploying a technol-ogy. Ability to explore refers to a user’s perceived competence in bringing together thephysical and cognitive resources needed for technology exploration. It is the result ofthe reinterpretation of a technology within a user’s given work context and representsthe aforementioned ‘‘how-to’’ knowledge. Intention to explore reflects a user’s will-ingness and purpose to explore a new technology and to find potential use based on theperception of derived benefits of use within the work context.

Nambisan et al. [53] found that organizations can positively affect users’ pro-pensity to innovate through the establishment of organizational mechanisms thatinfluence the development of the foregoing antecedents. Table 5 lists the mechanismsrelated to each of the three antecedents. While not expecting to find these exactmechanisms in evidence in a firm implementing ERP, it is useful to consider the effectsof each mechanism so that similar mechanisms can be discovered in an ERP imple-mentation. For example, with regard to technology cognizance, the first two listedmechanisms can provide factual, non-contextual knowledge about an application. Theother two mechanisms can provide industry-wide knowledge concerning an applica-tion. Steering committees and strategic planning teams influence the intention toexplore a technology by providing guidelines for the key business areas where ITshould be applied. IT task groups can influence this same construct by enablingusers to understand the benefits obtainable by applying the IT within certain businessareas or a specific work context. Considering ability to explore, relationship managersand customer support units provide personal help to users in identifying and evolvingnew application ideas. User groups can provide formal or informal means for users toexchange ideas and user experiences.

We should expect to find analogs to these mechanisms in an actual firm intendingor attempting to implement ERP. In fact, there may be a variety of both ‘‘standard’’ and

Table 5 Mechanisms influencing the propensity to innovate (adapted from [53]).

Antecedent Mechanisms

Technology cognizance l Attending IT conferencesl IT journal subscriptionsl Joint venturesl Vendor demonstrations

Ability to explore l User groupsl Customer support unitl User labl Relationship manager

Intention to explore l IT steering committeel Strategic IT planning teaml IT task group

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novel mechanisms employed by firms and other organizations that could impact each ofthe foregoing constructs. As an example, consider the results recorded in [54]. In thatstudy, top management in a firm conceived the need to implement an enterprise systemdue to impairment of decision making from information support failures. Top manage-ment created a vision of transformation thatwas communicated ‘‘downstream’’ to upperand middle managers and then further to subordinates. Early in the process, posters,flyers, and other communications were distributed to members across the organization.Employee fears of job loss were mitigated by management, aiding in the receptivity ofthe employees and aiding in knowledge transfer. The company hired an outside con-sultant, whose teammembers were included on a consulting group set up by the firm. Inaddition to the consulting group, the firm also established a steering committee, aworking committee, an IT Group, and various project function groups. Functiongroups met often and were in charge of analyzing and redesigning the firm’s businessprocesses. Further, employee training was rigorous, with the firm only allowing employ-ees to take up jobs using the system after they passed required system skills tests.Additionally, consultants taught process-oriented methodology to appropriate firmmembers. Finally, power users were assigned to each business unit.

Some of the recorded outcomes [54] of this effort are listed below.

l Firm managers learned to evaluate different business practices by analyzing theeffectiveness and efficiency of business processes.

l Group and committee members learned process-orientedmethodology, resulting inthe ability to make changes in business processes without the aid of consultantsafter the project went live.

l End users and power users mastered system knowledge.l Power users became able to reconfigure the system when needed.l Trust was created as problem solving was conducted jointly.l Relationship and business practice knowledge made interdepartmental coordina-

tion more effective and efficient.l Swifter responses tomarket changes andmore informed decisions were enabled as a

result of real-time, centralized operational data.l There was a wide-spread embedding of organizational memory.

This example is consistent with the selection of the constructs of intensity oforganizational learning and propensity to innovatively use a technology as potentialtheoretical underpinning to the examination and understanding of the relationshipbetween implementation learning and post-implementation organizational learning.The firm was able, to a high degree, to capture, assimilate, and apply knowledge.Awareness was created by top management. Knowledge transfer and the developmentof organizationally relevant knowledge was created and managed through the imple-mentation process by the creation of various groups, teams, and system experts. Userswere adequately trained on the system, enhancing post implementation use.Organizational members were better able to deal with post-implementation changesas a result of the training and knowledge transfer. Organizational memory was createdin the users and the system. Consistent with the identification of the inherent decisionsupport characteristics of ERP, decision making within the organization wasenhanced. Finally, this example reinforces the assertion that ERP implementationlearning outcomes should establish necessary or sufficient conditions under which

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post-implementation OL is promoted or made possible. Thus, implementation learn-ing and post-implementation learning are expected to be related through conditionssurrounding system use.

6. DISCUSSION AND FUTURE RESEARCH

We can now summarize the major contributions of this work. We have arguedthat it is desirable to integrate research on ERP implementation and post-implementa-tion effects. This paper has begun to do so in both implicit and overt ways. First,although not a goal of the current work, it is clear that learning can be used as a lens tounderstand both ERP implementation and post-implementation use. Each one of thechosen OL characterizations can, in fact, function in this manner. This is most obviousin the literature herein reviewed that deals with ERP implementation. The work ofHuber [21] and related researchers is cited extensively. This is justified given its knowl-edge-based character. Implementation of ERP is not an appropriate point in time foran organization to rely on self-discovery and self-directed learning. ERP is implemen-ted because it addresses an immediate need for the organization. Therefore, transfer ofknowledge from external sources is a rational choice for attaining needed know-how.The organization acquires needed ERP and ERP-implementation knowledge fromexternal sources. The knowledge and information is subsequently distributed through-out the organization through various mechanisms. Along the way, members engage inthe interpretation of the acquired and distributed knowledge and information intoorganizationally relevant knowledge. As a result of the foregoing, it may be thatrelevant and useful information and knowledge is embedded in the organizationalmemory, where it can be accessed when needed.

Knowledge system adjustment [22] and the creation of communication channelsalso serve as a theoretical underpinning. Knowledge system adjustment during ERPimplementation is most strikingly realized in the modeling and understanding of as-isand to-be business processes. The organization’s members and, by extension, the orga-nization, come to understand processes and their roles in them through modelingcurrent processes and possibly coming to the understanding of why change is desired.Through modeling of to-be processes, knowledge and understanding is further refinedto fit post-implementation processes. As indicated and implicit in the previous example,lines of communication are created between the organization and its members andbetween the various members as the implementation process is continued and facilitatesthe exchange of information and the creation of organizationally relevant knowledge.

Finally, although not as concrete and obvious as the foregoing, SLL and DLLcan also serve as a lens for understanding ERP implementation [26]. ERP implementa-tion can be characterized by SLL if the implementation results in the reinforcement ormaintenance of the existing processes in the organization. The implementation can becharacterized by DLL if the implementation results in the questioning of existing waysof operating and creation of new ways of operating.

On the post-implementation side, use of ERP is conditioned on organizationalmemory in the form of system-enacted procedures and processes, while also being usedto create organizational memory as use and processes adjust over time. Informationcreated and channeled via ERP use can be distributed and can be the subject ofinterpretation in pursuit of organizational problem solving. It is possible that ongoingERP use can be understood from the perspective of knowledge system adjustment.

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Information and knowledge created during use could serve to create new ways of

thinking, analyzing, or understanding. Finally, changes that tend to reinforce pro-

cesses or procedures during prolonged use can be understood as either SLL or DLL.The second means of integration identified by this paper is in beginning to

understand learning as an object of interest and result of ERP implementation and

post-implementation use. The standpoint of learning as lensmasks, to some degree, the

benefits to be derived from ERP. Learning to implement ERP is useful not only for the

sake of the current implementation effort. Organizations that succeed in implementa-

tion can port that learning to similar efforts in the future, either in the implementation

of other enterprise-level systems or in the implementation of other aspects of ERP

(modules, legacy integration, etc.). What is learned from implementation, (for exam-

ple, cross-functional convergence of information and knowledge) is important to the

organization and its members because it provides a knowledge base for further learn-

ing and success. What is learned is also important during ongoing use. Discoveries

about suppliers and customers provide a basis for questioning the organization’s

performance and processes. Discoveries about internal process performance can also

be a point of learning.Finally, this paper has laid the groundwork for future investigation of the relation-

ship between implementation learning and post-implementation OL. It is consistent

with other research that indicates that learning happens both during implementation

and subsequent to implementation. In their model of the relationship between IT

implementations and organizational learning, Scott andVessey [26] posited that business

OL and technological OL result from adaptations to business change (e.g., business

process reengineering) and technological change (e.g., architectural or software

changes), respectively. That distinction has not been pursued in the current paper but

could be of interest as an outcome of implementation learning. The authors further posit

that post implementation use results in adaptations by the users, with the extent of any

experienced changes depending on whether single-loop or double-loop learning was

involved. The learning that happens during implementation can be called learning by

doing. The learning that occurs after implementation can be called learning by using [55].The basic investigative framework to be pursued in further research is depicted in

Figure 1. Given that this research identifies connections between the two forms of

learning, it is possible that what is represented is a lifecycle of OL within the ERP

implementation/post-implementation chain of events. Several things must be estab-

lished before a true model of ERP-OL can be revealed. First, what are the mechanisms

(formal versus informal, standard versus novel) that are employed by organizations as

they implement ERP? Once this is known, we will be positioned to be able to discover

the exact relationship these bear to implementation learning. Given the reviewed

literature and preliminary theoretical development, we should also be able to deter-

mine that organizational mechanisms will also impact members’ propensity to inno-

vatively use the technology. What is not clear, but conceivably possible, is that

Implementation Learning outcomes also impact the propensity to innovatively use

ERP. Given the nature of Intensity of Organizational Learning, with its underlying

connection to absorptive capacity, it might be anticipated that it would have a positive

impact on all three constructs indicated in the lifecycle framework. If the intensity is at

an appropriate level, this may lead organizations to establish needed mechanisms,

increase the tendency to realize the implementation learning outcomes, and facilitate

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users’ propensity to innovate in their use. The exact nature of these relationships, if

they exist, must be discovered empirically.We must also establish in what way, and to what degree, the components of the

propensity to innovatively use ERP set the stage for actual ERP use. The main

contribution of this work will be realized if it can be determined how this propensity

increases or affects the likelihood of achieving OL results. Further investigation may

also be able to establish the presence and nature of any feedback effect that may exist

between OL and the uses made of the system.All of this is much to be expected and will require some time. An ideal situation

would be to conduct a case or longitudinal study to investigate the proposed framework.

Action research could prove to be invaluable in this case. Another approach, although

less revealing, would be to conduct questionnaire-based research. To be useful, the

various implementations would have to be recent. A less informative approach would

be to study each phase (implementation vs. post-implementation) separately and infer

the relationship. Study of each phase separately will contribute to further understanding

of organizational learning in ERP environments. However, until some comprehensive

study is conducted we will be left with the relationship in theoretical limbo.Finally, the study findings in [14] emphasized OL at the organization level

because respondents indicated learning that transcended individuals. Given the pre-

sence of IOL, associated with individual, team, and organizational improvement (and

thus learning), in the present framework, we are left to wonder if OL resulting from or

associated with ERP is entirely an organization-level phenomenon. Future research

should determine the nature and intensity of OL on the individual, collective, and

organizational levels.

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AUTHOR BIO

M. Shane Tomblin is an Associate Professor at Marshall University in Huntington,WV, USA. He holds a Ph.D. in Business Administration (emphasizing MIS) from theUniversity of Kentucky. His areas of research interest include organizational learningand its technological support, knowledge management, health care informatics, ISfoundations, and organizational semiotics. Dr. Tomblin has published articles onknowledge management and its intersection with organizational learning and techno-logical support of organizational learning.

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