One of the most important issues is its relation to information-communication technologies. The purpose of this paper is to examine prior research and propose a model linking Organizational Learning construct (LO) to Information-communication technologies (ACT). Using structural equation modeling methodology, we tested this relationship based on the data from 220 questionnaires received from top managers of 867 Slovenian companies with more than 100 employees in the year 2003.
Our research demonstrates statistically significant positive correlation between LO and ‘CT. Key words: Organizational learning, Information-communication technologies, Slovenian companies, Structural equation modeling. . Introduction Highly turbulent business environment requires modern businesses to rapidly adapt to change. In this context, a thorough understanding of the process of organizational learning is vital. Organizational learning has emerged as one of the most promising concepts in strategic management in late asses.
As a premier researcher in the field of organizational learning stated: “the ability to learn faster than your competitors may be the only sustainable competitive advantage” (De Gees, 1988). At the same time Information-communication technologies became almost ubiquitous and are seen as a 1 23 Associate professor of the Faculty of Economics University of Lausanne Assistant of the Faculty of Economics University of Lausanne Article received: 13-07-2004; Article accepted: 11-10-2004 7 V Diamonds, M. Sarajevo: Organizational Learning and Intimation-communication…
CB. Radar. – save©. U Rig. , Keen. Fake. , god. 22. SF. 1 (Bibb star. 7-19 major facilitator of business activities in the modern world (Taproots and Castor, 1993; Gill, 1996) and the main catalyst of fundamental changes in structure, operation and management of organizations (Detours, 1997). From this origin stems the need to understand the relationship among organizational learning and information-communication technologies. For above reasons we intend to develop a conceptual model relating those two issues and provide an empirical test in this article.
In order to do so, we first systematize and present definitions and process of organizational learning and present the most often used taxonomy of information- communication technologies and introduce constructs Organizational Learning (LO) and Information-communication technologies (ACT) as well as their measurement variables. Second, previous research relating CIT to LO is outlined in order to develop a conceptual model. Third, we test our hypothesis empirically, using structural equation modeling (LISPER) and fourth, results are discussed.
We conclude by indicating some limitations of our work and providing future research propositions. 2. Organizational learning and information-communication technologies – a model conceptualization First section of this article focuses on the development of a conceptual model to test the relationship between organizational learning (LO) and information-communication technologies (ACT). We approached this task in two steps – first, conceptualization of structural sub-model and second, conceptualization of measurement sub-model. 2. 1 .
Information-communication technologies and organizational learning – constructs and relationship In order to develop a sound model, a structural framework needs to be developed. This phase consists of two steps: presentation of constructs, and examination of possible relationships among them. Two constructs of our concern are Organizational learning (LO) and Information-communication technologies (ACT). Former could well be the most ambiguous part of the model due to absence of common understanding of the concept and virtual non-existence of unique definition.
This statement can be supported with findings of Shirtwaists (1983) and Diamonds (1994). According to the first author, a vast majority of research in the area has been fragmentary and incomplete. The second author adds that research in the field of organizational learning resulted in numerous definitions and models (e. G. Monika and Attacked, 1996; Wall, 1998) that can be differentiated through criteria of inclusiveness, width and focus. Most definitions are only partial, because they deal with organizational learning from one theoretical perspective.
To present Just a few of them, Sense (1990) defines organizational learning as ‘a continuous testing of experience and its transformation into knowledge available to the whole organization and relevant to their mission’, while Huber (1991) sees it as a combination of four processes: information acquisition, information distribution, 8 information interpretation and organizational memory. Arises and Such¶n (1996) are even less restricting in their definition, declaring that organizational learning merges when organizations acquire information (knowledge, understandings, know- how, techniques and procedures) of any kind by any meaner.
Jones (2000) emphasizes the importance of organizational learning for organizational performance defining it as ‘a process through which managers try to increase organizational members’ capabilities in order to better understand and manage the organization and its environment to accept decisions that increase organizational performance on a continuous basis’. Diamonds (1994) provides an overview of previous research and identifies four perspectives on organizational learning.
His model manages to merge informational, interpretation, strategic and behavioral approach to organizational learning and defines it as a process of information acquisition, information interpretation and resulting behavioral and cognitive changes, which should in turn have an impact on organizational performance. The purpose of information acquisition is to decrease uncertainty (Daft and Lange, 1986), which is defined as a lack of information by Shannon and Weaver (1973). Meaning, uncertainty and quantity of information should be negatively correlated (Daft and Lange, 1986).
We could like to add that there is an optimal quantity of information. Namely, information overflow probably limits organizations’ capacity to interpret information at hand. Information acquisition is determined by two variables: data sources and intrusiveness of organization (Daft and Wick, 1984). Data sources can be internal or external (Daft and Lange, 1986), with external sources representing managers’ direct contacts with information source outside firm boundaries, and internal sources including employee data collection conveyed later (in the form of information) to managers using internal data channels.
Recently, in this context, a very important role has been taken by information-communication technologies (such as intranet, enterprise resource planning systems, and e-mail). Intrusiveness of organization is defined as an extent to which organization is capable of actively penetrating its environment with browsing and searching for desired data and information. By this criterion organizations can be clustered as active or passive. On the one hand, active organizations allocate resources to search for information (e. G. Hey have employees to deal with research activities, hire external experts, actively use the Internet in order to obtain information for decision support, use extranet or ERP II systems as a form of connecting to external partners – suppliers and major customers). On the other hand, passive organizations accept all information offered by its environment at a certain moment in time (King, 1980). We would like to think of the distinction between active and passive organizations as a continuum (rather than a dichotomy) – and will treat it as such in further research.
The purpose of information interpretation is to reduce ambiguity related to information. Ambiguity can be fined as existence of multiple, contradictory, 4 ERP II systems or extended enterprise resource planning systems are an extension of enterprise resource planning systems (ERP) and are aimed at incorporating major suppliers and customers of the company in its integrated information system (Garner Group, 2000). 9 explanations of situation at hand (Daft and Lange, 1986).
Two variables describe information interpretation: richness of media (Daft and Wick, 1984) and top-down’ processing (Marcello, 1993). Richness of media relates to capabilities of various forms of media to process information. The richest medium is personal contact, followed by telephone conversations, written memorandums and letters, special reports, and formal chain of command as the ‘poorest’ medium (Daft and Lange, 1986). Modern media for instance involve videoconferencing as a ‘richer’ media and electronic mail or intranet as ‘poorer’ forms of media for information interpretation.
The top-down’ concept of processing assumes that individuals past experiences, and the context in which they were obtained, reaffirm valid analytical framework to understand future developments. The purpose of top-down’ processing is to improve information understanding of employees at lower levels of organizational structure and it is dependent of the level of details (Marcello, 1993) and frequency of information cycles or information dissemination using various communication channels (Daft and Wick, 1984).
Organizational learning reflects in ‘accompanying changes’ (Carving, 1993). If no behavioral or cognitive changes occur, organizational learning has in fact not occurred and the only thing that remains is unused potential for improvements (Fill and Less, 1985; Carving, 1993). When discussing cognitive changes two levels of earning can be observed. Lower-level learning reflects changes within organizational structure, which are short-term and only partially influence organization. Higher-level learning reflects changes in general rules and norms (Fill and Less, 1985).
Arises and Such¶n (1978) classify learning similarly: single-loop and double-loop learning, Dodson (1991) discusses tactical and strategic learning, while Sense (1990) uses terms of adaptive and generative learning. By all meaner, at lower-level learning organization acts passively and only adapts to environment, while higher-level earning involves active influence on business environment. CIT have become a major facilitator of business activities in the modern world (Taproots in Castor, 1993; Gill, 1996) and are also a main catalyst of fundamental changes in structure, operation and management of organizations (Detours, 1997).
One of the most often used taxonomies for CIT for business is the one that differentiates among software, hardware and telecommunications (Turban et al. , 2001; Beyond-Davies, 2002). Main components of hardware do not involve only computers but also several attached cosmologies that take care of data (or information) flow into and from computer. Turban et al (2001) define hardware as physical equipment, applied for following activities of the computer system: input, process, output and storage of data.
Main components of hardware are central process unit (CAP]), memory (primary and secondary storage), input technologies, technologies to display results and communication technologies. What needs to be noted is that communication technologies play such a crucial role that they are very often regarded as an entity per SE and discussed in relation to networks. Central process unit performs actual computation within the computer. Interesting thinking is the one of Gordon Moore, Intel co-founder, who predicted in 1965 that complexity of microprocessors would double approximately every 18 months.
This prognosis proved to be very accurate and 10 was named Moore law. Consequentially, capability of hardware equipment is mounting and prices are diminishing. User value of most of hardware equals zero if not combined with software. Beyond-Davies (2002) divides application and system software and sees later as a link between hardware and application software. At this mint, we address enterprise resource planning (ERP) systems, which represent important development for modern businesses, because they integrate data and information from transaction-processing systems, decision support systems and executive information systems.
At present, their essence is business-level data and information integration. However, we can expect that this integration will exceed firm boundaries and will be used for inter-firm collaboration (I. E. Connection to firms’ main suppliers and customers). Not alike hardware, power of computer software doubles approximately every 8 years (Turban et al, 2001). Reason for that can be probably contributed to market structure of software providers that can be best described as monopoly or oligopoly at certain segments. It will be interesting to monitor future advances in this area in regard to open-source software.
In segments where there are open-source alternatives, quality of commercial products is rising and their prices declining. The third component of Information-communication technologies, which has allowed for expansion of various networks are communication technologies. Internet is by all meaner the most important network. It has had an impact to the birth of so called ‘new economy mainly due to its inter-connectivity of various systems. Robe et al. (2000) provide an overview of research related to the relationship between our two exogenous latent variables CIT and LO. They identify two main streams of research (I. . One is related to CIT as a facilitator or even disabler of LO and the other is aimed at LO concepts to help develop and implement CIT in companies). Especially within the first stream, mainly qualitative body of empirical research provides no common understanding of what the impact of CIT on organizational learning should be like. The majority of case studies show that CIT act as enablers and facilitators of better organizational learning. Nevertheless, there are some cases where CIT caused rigidity in the systems and acted in exactly the opposite direction as desired.
Despite this duality, stream that proposes positive relationship is prevailing. Based on this research following hypothesis can be put forward: HI: Correlation between CIT and LO is positive. 2. 2. Towards personalization of LO and CIT In Table 1 model personalization is presented through the inclusion to constructs, matching measurement variables, number to teems involved and sources for underlying theories and measurement instruments.