ORGANIZATIONAL LEARNING CULTURE AS THE LINK BETWEEN BUSINESS PROCESS ORIENTATION

AND ORGANIZATIONAL PERFORMANCE

KULTURA ORGANIZACIJSKEGA UČENJA KOT POVEZAVA MED PROCESNO USMERJENOSTJO IN USPEŠNOSTJO POSLOVANJA

Vlado Dimovski, Miha Škerlavaj, Rok Škrinjar, Jurij Jaklič, Mojca Indihar Štemberger

Faculty of Economics, University of Ljubljana

{vlado.dimovski , miha.skerlavaj, rok.skrinjar , jurij.jaklic , mojca.stemberger}@ef.uni-lj.si

Abstract

The aim of this paper is to present a model for organizational performance improvement based on the joint impact of business process orientation and organizational learning. The concept of business process orientation (BPO) defines an organization that, in all its thinking, emphasizes a process as opposed to hierarchies with a special emphasis on the outcome and customer satisfaction. The concept organizational learning culture (OLC) is proposed and defined as a set of norms, values and underlying assumptions about the functioning of an organization that support more systematic, in-depth approaches aimed to achieve higher level organizational learning. By using the data obtained from 234 Slovenian companies employing more than 100 people a part of the structural model has been empirically tested. The results show that OLC has an impact on organizational performance.

Keywords: organizational learning, business process orientation, organizational performance, structural model, empirical investigation

Povzetek

Namen prispevka je prikazati model povečanja uspešnosti poslovanja na podlagi skupnega vpliva procesne usmerjenosti in organizacijskega učenja. Koncept procesne usmerjenosti (BPO) opisuje organiziranost, katere temeljni pogled poudarja procese namesto hierarhičnih struktur in daje poseben poudarek rezultatom poslovnih procesov ter zadovoljstvu strank. Koncept kulture organizacijskega učenja (OLC) je definiran kot množica pravil, vrednot in predpostavk o delovanju organizacije, ki podpirajo globlje in bolj sistematične pristope za doseganje višje stopnje organizacijskega učenja. Z uporabo podatkov, ki smo jih pridobili v raziskavi, v kateri je sodelovalo 234 slovenskih podjetij z več kot 100 zaposlenimi, je bil izdelan strukturnega modela, katerega del je bil empirično testiran. Rezultati kažejo, da ima kultura organizacijskega učenja vpliv na uspešnost poslovanja.

Ključne besede: organizacijsko učenje, procesna usmerjenost, uspešnost poslovanja, strukturni model, empirična raziskava

1. Introduction

Businesses around the globe are continually under pressure and forced to re-evaluate their business model and their very existence. Business and technological change threatens organizational sustainability, which depends on a balance between change and order. Few organizations can control the forces that affect them, but they can control the way in which they deal with those forces. Rigidity has been widely recognized by academicians and the practitioners as well. As a response many approaches have been developed and proposed to overcome this weakness. One of the focuses of the last two decades was on process improvement and redesign.

Operations management focuses on carefully managing internal processes and also processes it the supply chain, by improving their efficiency and effectiveness. Hammer (2004) is convinced that operational innovation is now needed more than ever, yet not enough attention is paid to this topic. It is well known that most of the problems regarding operations management are not technical but arise from inappropriate organizational culture or an organizational structure that may impede innovations to be implemented.

Business performance is the result of the sum total of all processes being implemented by the firm (Tenner, DeToro, 1997). Extensive literature about business process orientation (e.g. Davenport, 1993; Hammer, Champy, 1993; Harmon, 2003; McCormack, Johnson, 2000) suggests that organizations can enhance their overall performance by adopting a process view. McCormack and Johnson (2000) defined the concept of business process orientation (BPO) as an organization that, in all its thinking, emphasizes process as opposed to hierarchies with a special emphasis on the outcome and customer satisfaction. They investigated the relationship between BPO and enhanced business performance by conducting an empirical study. The research results showed that BPO is very important for encouraging greater connectedness within an organization, that it leads to more positive corporate climate and that process oriented companies have better overall performance.

Even though a wide range of approaches to establish or enhance BPO is available the expected results have not always been realized. During the 1990s many firms undertook business process reengineering (BPR) projects and despite its promising scheme the success rate was well below the desired one. Different studies report different failure rates of BPR project and span from 70% to almost 80% (Smith, 2003) failure rate. Such results fuelled new studies in order to identify the reasons for failure. Determination the critical success factors (CSF) of business process reengineering emerged as a response to low success rates of BPR projects. Many authors approached the subject and the list of CSFs appeared. As the list grew so did the need to synthesize the CSF framework. Guimaraes (1997) and Al-Mashari and Zairi (1999) made such synthesis. One of the common characteristics of any CSF framework seems to be the fact that organizational factors are highly neglected or entirely absent.

What the majority have overlooked or barely touched upon is to our opinion one of the key reasons for BPR project failures. The factors of organizational structure design are of paramount importance in delivering successful operational innovation

projects as well as sustaining the gains in business performance. Organizational design changes should go hand in hand with process redesign efforts. Implementation of new processes cannot occur in a rigid environment of a functional organizational structure. Instead, corresponding structural changes must reflect the new processes and support and enable their implementation.

Implementing radical innovation can be facilitated or hindered by an organizational structural design. As proved by empirical investigation (Nahm et al, 2003) some structural dimensions, like nature of formalization, the number of layers in the hierarchy, and the level of horizontal integration have significant, direct and positive effect on the locus of decision-making and level of communication. However, in their empirical study Sung and Gibson (1998) established that managers pay the least importance to organizational factors by introducing radical innovation. Furthermore, they are the least prepared for organizational changes needed to support such project and maintain the redesigned processes.

Moreover, the structural changes that must be implemented in order to support process change initiatives must be coupled with the corresponding cultural changes. If the attention is polarized around structural thinking, it can lead to a process described as empty restructuring (Bate 1995). In this case, regular and repeated restructuring takes precedence over the more challenging issue of realizing change in the management styles, organizational cultures and corporate processes which define, circumscribe and contextualize organizational life. After the brief shock of adjustment, life, culture and social process drift back into their original patterns, or into new, perverse and unintended forms: hence culture and structure can become misaligned. Gaps spring up between the way things are formally structured and the way they are really done (Bate, Khan, Pye, 2000).

If attention shifts to cultural thinking, the outcome is all too often one of endless organization development sessions and process consultation that eventually leads nowhere. It typically includes activities such as team development, culture workshops, counselling, training and an abundance of rhetoric on improving processes and relationships and transforming culture. Though valuable and necessary, such activities per se are not enough. They represent development without design, a positive process that often lacks a positive or lasting outcome, since it is not consolidated or institutionalized in hard design changes (Blunt 1997). Therefore structure and culture must both be considered when any change initiative is in progress.

De Geus (1988) argues that the ability to learn faster than your competitors may be the only sustainable competitive advantage and the way to superior performance. It is of utmost importance to nurture culture oriented towards higher-level organizational learning within the modern company. Organizational learning culture (OLC) is a set of norms, values and underlying assumptions about the functioning of an organization that support more systematic, in-depth approaches aimed to achieve deutero, strategic or generative organizational learning might be the missing link between business process orientation and organizational performance.

The paper presents the model for organizational performance improvement based on the joint impact of business process orientation and organizational learning culture.

The following section presents model conceptualization, its constituting constructs and the hypotheses stating the relationship between constructs. To test the hypotheses an empirical study was carried out. Methodology, measures and data analysis are the topic of the third section. In the final section the results of the empirical research are discussed and implications and limitations of the paper outlined.

2. Model conceptualization

Although the positive impact of business process orientation (BPO) on organizational performance had been proven by previous research (McCormack, Johnson, 2000), a lack of organizational culture in radical innovation project is still reported (e.g. Hammer, 2004). By the model developed in the paper we want to show that organizational learning culture (OLC) can enhance the success of such projects and contribute to the influence of BPO to organizational performance (Figure 1).

Figure 1: Research framework

Similarly, in (Lai, 2003) the relationships among market orientation, quality organization and organizational performance were investigated. The findings in (Lai, Cheng, 2005) reveal that quality orientation and market orientation are complementary and reinforce each other in enhancing organizational performance. The results suggest that a firm with a market orientation is likely to have favourable quality management implementation and performance results, which means that market orientation can be treated as a missing link between quality management and organizational performance.

In the paper the influence of organizational learning culture on organizational performance is investigated. The impact of business process orientation on organizational performance has already been researched previously (McCormack, Johnson, 2001). However, the relationships among all three constructs need to be further investigated. The authors of this paper plan to perform such investigation within a few months.

2.1 Business process orientation

Although many enterprises acknowledge the need to be quick and responsive in global economy and market that is constantly changing, many are not ready to do so. The organizations of today face increasing pressures to integrate their processes across disparate divisions and functional units in order to remove inefficiencies as well as to enhance manageability.

To overcome the deficiencies and to establish the flexibility and effectiveness required the organizations of nowadays need to adopt the process view and deploy corresponding organizational elements to support it. Many authors and researchers tackled the subject and developed their own understanding and management guidelines on the business process improvement and redesign. As a result there are many terms that describe the same general idea. O’Neil and Sohal (1999), reviewing the literature on the subject of business process change, found at least ten variations of the same general idea.

The concept of business process orientation (BPO) defines an organization that, in all its thinking, emphasizes process as opposed to hierarchies with a special emphasis on the outcome and customer satisfaction (McCormack, Johnson, 2001). It has five key dimensions of such organization: [1] process view, [2] structures that match these processes, [3] jobs that operate these processes, [4] management and measurement that direct and assess these processes and [5] customer-focused, empowerment- and continuous-improvement oriented values and beliefs (culture). The current position of an organization in becoming business process oriented can be measured by a process maturity model consisting of the following stages: ad hoc, defined, linked, and integrated.

A more detailed description (Figure 2) of a business process-oriented organization or a horizontal organization as the author refers to it is given by Ostroff (1999). The basic principles (Ostroff, 1999) of a process-oriented organization describe its fundamental characteristics and can broadly be divided in two groups.

Figure 2: Principles of a process-oriented organization

The first group is design principles. The central principle (1) is to organize work around cross-functional core processes, which create the value proposition – defined as a set of benefits a company offers at a price attractive to customers and consistent with its financial goals, not tasks or functions. The aim is to maximize the horizontal coordination of workers that take part in the core process, which results in better communication and coordination that in turn leads to performance improvements. New horizontal organizational structure emerges with the barriers that existed between functional silos removed.

The second (2) principle stresses the importance of process owners or managers. They take the responsibility for the core process in its entirety and thus have to be competent in different fields and areas in the organization and have a mixture of authority and persuasion skills. The next principle (3) of a process-oriented organization is teams. They are the cornerstone of organizational design and performance. Teamwork encourages creative solution seeking for the problems that an organization faces on a daily basis. The fourth (4) principle advocates decreasing hierarchy by eliminating non-value-added work and by giving team members who are not necessarily senior managers the authority to make decisions directly related to their activities within the value chain. (5) Integration with customers and suppliers for tighter and more effective relationships is the fifth design principle of a process-oriented organization.

Changing the organizational design is a daunting and complex undertaking. By following the implementation principles the plausibility of successful restructuring increases. These principles are: (1) empowerment of people by offering them tools, skills, motivation, and authority to make decisions essential to the team’s performance. (2) Use of information technology to help people reach performance objectives and deliver value proposition to the customer. (3) Emphasis of multiple competencies and training people to handle issues and work productively in cross-functional areas within the new organization. (4) Promotion of multi-skilling, the ability to think creatively and respond flexibly to new challenges that arise in the work that teams do. (5) Educating people trained primarily in specific functions or departments to work in partnership with others. (6) Measurement of end-of-process performance objectives (which are driven by the value proposition), as well as customer satisfaction, employee satisfaction, and financial contribution. And finally (7) Building a corporate culture of openness, cooperation, and collaboration, a culture that focuses on continuous performance improvement and values employee empowerment, responsibility, and well-being. 2.2 Organizational learning culture

The word ‘culture’ has been used by many different people to explain a variety of phenomena, and as each one tends to adopt a slightly different perspective there is no universally accepted definition (Rollinson and Broadfield, 2002). Ott (1989) identified over 70 different words or phrases used to define organizational culture. One of the first attempts was made by Jacques (1952) who claimed that organizational culture is the customary and traditional way of doing things, which is shared to a greater or lesser degree by all members, and which the new members must learn and at least partially accept in order to be accepted into the services of the firm. Harrison (1972) focuses more on culture itself rather than on its effects and defines it as ideologies, beliefs and deep-set values, which occur in all firms, and are prescriptions

for the ways in which people should work in these organizations. Consultants Peters and Waterman (1982) see it as a dominant and coherent set of shared values conveyed by such symbolic means as stories, myths, legends, slogans, anecdotes and fairy tales, while Deal and Kennedy (1982) articulate that organizational culture is the way we do things around here.

Currently, the most widely accepted definition is the one made by Schein (1992) that perceives organizational culture as a pattern of basic assumptions – invented, discovered or developed by a given group as it learns to cope with its problems of external adaptation and internal integration – that has worked well enough to be considered valuable and, therefore, to be taught to new members as the correct way to perceive, think and feel in relation to those problems.

Similarly to organizational culture, organizational learning is also a very elusive concept due to a variety of perspectives that come under scrutiny in academic literature. There have been numerous attempts to define organizational learning and its various aspects. Senge (1990) defines organizational learning as ‘a continuous testing of experience and its transformation into knowledge available to whole organization and relevant to their mission’, while Huber (1991) sees it as a combination of four processes: information acquisition, information distribution, information interpretation and organizational memory. Argyris and Schön (1996) are even less restricting in their definition declaring that organizational learning emerges when organizations acquire information (knowledge, understandings, know-how, techniques and procedures) of any kind by any means. While some of the premier researchers (Shrivastava, 1983; Dimovski, 1994) found that majority of research in the area has been fragmentized and incomplete and that research in the field of organizational learning resulted in numerous definitions and models (e.g. DiBella and Nevis, 1998; Wall, 1998), recent research (Easterby-Smith and Lyles, 2003) provided better understanding of the domain.

Jones (2000) emphasizes 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’. Dimovski (1994) provides an overview of previous research and identifies four various perspectives to organizational learning. His model manages to merge informational, interpretational, strategic and behavioural approach to organizational learning and defines it as a process of information acquisition, information interpretation and resulting behavioural and cognitive changes, which should in turn have impact on organizational performance.

We propose a new concept called organizational learning culture (OLC) and define it as a set of norms, values and underlying assumptions about the functioning of an organization that support more systematic, in-depth approaches aimed to achieve a higher level of organizational learning.

2.3 Organizational performance

Evaluating organizational performance cannot be done without taking organizational goals into consideration. Modern business environment demands multi-goal orientation. Profit theory (Cyert and March, 1963) is a no more valid measure of

organizational performance and neither are other approaches that take only interests of shareholders (owners) of a company into consideration. Modern business environment is characterized by increased importance and strength of customers, employees and society in general.

It has become quite obvious that within a modern company performance assessment, all stakeholders need to be taken into account. This is the main idea of Freeman’s Stakeholder theory (1984, 1994). Already behavioural theory of a company (Cyert and March, 1963) recognized company as a coalition of individuals or groups of individuals such as management, employees, customers, owners, government etc. but did nothing to introduce this affirmation to organizational performance assessment. Emerging management paradigms are emphasizing a stakeholder perspective (Atkinson et al., 1997).

Beside financial performance (FP) also non-financial performance (NFP) must be assessed in order to evaluate overall organizational performance of a modern company. There are two main reasons for such a requirement. First, several interest groups are involved in business and they all have their particular goals and expectations related to the company. They will remain in the coalition as long as their goals are satisfied in a sufficient manner. Second, strategic business areas are not necessarily financial in their nature.

There exist several approaches to non-financial indicators, of which Balanced Scorecard – BSC (Kaplan and Norton, 1992, 1993, 1996, 1996a) is the most established. The multi-model performance framework (MMPF) model by Weerakoon (1996) is also very interesting and consists of four dimensions including employee motivation, market performance, productivity performance, and societal impact, and covers satisfaction of various stakeholders, such as customers, investors, employees, suppliers, and society. 2.4 Hypothesis Development

After defining the constructs involved, the next logical step in the process is to examine relationships among them and to set the hypotheses to be tested afterward in the study. Given the confirmatory nature of our work, we will restrict ourselves empirically to relationship between organizational learning culture and organizational performance.

The research results in (McCormack, Johnson, 2001) showed that BPO can contribute to the overall performance of an organization and that it is critical in reducing conflict and encouraging greater connectedness within an organization. Moreover, companies with strong measures of BPO showed better overall business performance. The research also showed that high BPO levels within organizations led to a more positive corporate climate, illustrated through better organizational connectedness and less internal conflict.

Even though the relationship between BPO and OLC has not been previously empirically tested there is abundance of evidence in various strands of literature (organizational change, organizational development, business process reengineering, organizational culture etc.) that the two concepts presented in this paper are interdependent. As Bate, Khan and Pye (2000) argue they should not be considered in

isolation from one another in any organizational change initiative. It is our postulation that appropriate culture, learning culture being one such manifestation, enables and encourages hard changes in organizational structures and processes. In turn, a business process-oriented organization is a very suitable framework for achieving highly learning focused culture. Simultaneous consideration and alignment of the two concepts can provide higher performance improvements than any of the concepts alone.

Influence of OLC on both financial (FP) and non-financial performance (NFP) is examined. Dimovski (1994) demonstrated a positive impact of OL on both FP and NFP, using one-industry research design and stratified sample of 200 credit unions in Ohio. The study investigated determinants, process and outcomes of organizational learning, as well as relationship between organizational learning and performance. Sloan et al (2002), Lam (1998) and Figueireido (2003) also reached similar conclusions. Simonin (1997) found strong effects of learning on financial and non-financial performance in the context of strategic alliances. Specifically, he tests influence of collaborative know-how on tangible as well as intangible collaborative benefits. Tangible benefits are strategic and financial: generating additional profits, improving market share, and sustaining competitive advantage. Intangible benefits are learning or knowledge-based: learning specific skills and competencies (Kogut, 1988), learning about inter-firm cooperation (Lyles, 1988), and learning how to behave cooperatively (Lane and Beamish, 1990).

We have to be aware of the fact that various aspects of organizational learning contribute to performance. Pisano et al. (2001) examine learning curves in health care setting and determine that organizations achieve performance improvements (improve work processes – reduce procedure times, hence increase efficiency) from cumulative experience at different rates. Cohen and Levinthal (1990) argue that ability of a firm to recognize the value of new, external information, assimilate it, and apply it to commercial ends (named absorptive capacity) is critical to its innovative capabilities. On these bases hypotheses in Table 1 were set.

Table 1: Hypotheses

# Hypothesis Source

H1Culture oriented towards higher-level organizational learning (OLC) leads to better financial performance (FP).

Darr et al., 1995.Dimovski, 1994.Lam, 1998.Simonin, 1997.Sloan et al., 2002.

H2Culture oriented towards higher-level organizational learning (OLC) leads to better non-financial performance (NFP).

Cohen and Levinthal, 1990.

Dimovski, 1994.

Figueiredo, 2003.

Pisano et al., 2001.

Simonin, 1997.

3. Research Methodology

Methodology utilised to test our model is structural equation modelling (SEM). We used LISREL 8.53 software. Our model was found to be over-identified. Preceding data analysis and development of measures, sample and data collection processes are briefly presented.

3.1 Sample and data collection

Based on the model conceptualization, a measurement instrument – questionnaire was developed and sent in June 2003 to CEO’s or board members of all Slovenian companies employing more than 100 people, which accounted for 867 companies altogether. In the first three weeks 234 completed questionnaires were returned. Fourteen of them were excluded from further analysis due to missing values and the response rate accounted for 25.4%, which can be considered as success. That implies the fact that after 20 years of academic examination and scrutiny, organizational learning nowadays poses a very important issue for practitioners as well as academicians. Furthermore, no round of reminder was needed as we gathered enough data (in one month period) to allow for robust estimation of the model.

We aimed at the audience of top managers having in mind the idea to have a strategic and to some degree even interdisciplinary perspective of the company in question although there is some discrepancy between desired and actual structure of respondents. Figure 3 depicts the structure of respondents by their function. The structure of our sample by company size is a good representation of population of large Slovenian companies. Based on average-number-of-employees criterion in year 2002 51.4% of the companies had between 100 and 249 employees, followed by 24.6% of the companies with 250 to 499 employed persons, 11.8% had 500-999 and 12.2% of the companies had 1000 and more employees.

5.5 %

5.0 %

21.8 %

.9 %

1.8 %

16.8 % 6.4 %

9.1 %

10.9 %

21.8 %

Board advisory

Manufacturing director

N.a.

Marketing director

Sales director

CIO Personell Director

Accounting and finance director

Other: lower levels

CEO

Figure 3: Respondent structure by function within the company

Table 2: Structure of respondents – by industryIndustry (SIC) Frequency PercentA AGRICULTURE, HUNTING AND FORESTRY 8 3.6B FISHING 0 0C MINING AND QUARRYING 1 0.5D MANUFACTURING 107 48.6E ELECTRICITY, GAS AND WATER SUPPLY 14 6.4F CONSTRUCTION 23 10.5G WHOLESALE & RETAIL, REPAIR MOTOR

VEHICLES, PERSONAL & HOUSEHOLD GOODS

20 9.1

H HOTELS AND RESTAURANTS 6 2.7I TRANSPORT, STORAGE AND

COMMUNICATION12 5.5

J FINANCIAL MEDIATION 13 5.9K REAL ESTATE, RENTING AND BUSINESS

ACTIVITIES1 0.5

L PUBLIC ADMINISTRATION AND DEFENCE, COMPULSORY SOCIAL SECURITY

1 0.5

M EDUCATION 0 0N HEALTH AND SOCIAL WORK 1 0.5O OTHER COMMUNITY, SOCIAL AND

PERSONAL SERVICE ACTIVITIES13 5.9

Total 220 100.0

Table 2 serves to demonstrate industry structure of companies in question. Our respondents reported in almost half of all cases that their main industry was manufacturing, followed by 10.5% of companies in the construction business and 9.1% in trade and the repair of motor vehicles. Four out of fifteen industries only have one representative each, while there was no company stating fishery and education as their main industry. This is logical since non-profit and small businesses were excluded from our analysis.

3.2 Measures

Table 3 exhibits model operationalization. Three constructs (OLC, FP and NFP), matching measurement variables (indicators), number of items used in the questionnaire and sources for underlying theories are presented. The OLC construct will have 3 measurement variables: Information Acquisition (INFOACQ), Information Interpretation (INFOINT) and Behavioural and Cognitive Changes (BCC). When reporting on INFOACQ, the respondents were asked about the importance of different sources of information (such as employees, previous decisions, external experts, clipping, competition, external data sources etc.). Perceived importance of several ways to interpret information (personal contacts, teams, phone contacts, reports, memos etc.) will be used to measure INFOINT. Behavioural and cognitive changes (BCC) will be aggregated using 14 items asking about the changes in the past three years in several areas (adaptability to pressures from external environment, quality of products and services, general atmosphere in company, efficiency of team meetings, speed of business etc.).

Financial performance (FP) will be measured by two one-item measurement variables: Return on Assets (ROA) and Value Added per Employee (VAEMP) in the last three years relative to industry average, using bipolar scale. These results will reflect business performance from owners’ point of view, even though we are well aware of all the problems related to ROA (such as ‘creative accountancy’). The same approach will be used for non-financial performance (NFP) to capture perspectives of other stakeholders in a firm as a coalition of interests. Three single-item measurement variables utilized are Stability of Relationships with Suppliers (SUPPLY), Net Fluctuation of Employees (EMPLOY) and Customer Complaints (BUYER).

Table 3: Specification of constructs – latent variables, indicators, number of measurement items and their sources

Latent variables (constructs)

Measurement variables (indicators) Number of items aggregated into each

Sources

Organizational learning culture (OLC)

Information acquisition (INFOACQ) 12 Daft and Weick, 1984.

Daft and Lengel, 1986.Martello, 1993.Information interpretation (INTINF) 11

Behavioural and cognitive changes (BCC) 14Zahra and Covin, 1993.Dimovski, 1994.

Financial organizational performance (FP) – perspective of owners

Return on assets (ROA) 1Freeman, 1984, 1994: Stakeholder theory.Kaplan and Norton, 1992, 1993, 1996, 1996a: Balanced scorecard.Value added per employee (VAEMP) 1

Non-financial organizational performance (NFP) – perspective of other stakeholders

Stability of relationships with suppliers (SUPPLY) 1 Kaplan and Norton, 1992, 1993, 1996, 1996a: Balanced scorecard.Net fluctuation of employees (EMPLOY) 1

Customer complaints (BUYER) 1

3.3 Data analysis

Model fit was assessed from three perspectives: (1) at global level (using several fit indices such as , Root mean square of approximation etc.), (2) at the level of structural sub-model and (3) at the level of measurement sub-model (construct validity and construct and measurement variable reliability). Model fit relates to a degree to which a hypothesized model is consistent with the data at hand - degree to which the implied matrix of covariances (based on hypothesized model) and sample covariance matrix (based on data) fit (Bollen, 1989). The aim of global fit assessment is to determine the degree to which the model as a whole is consistent with the data gathered. Through years, numerous global fit indices have been developed. Unfortunately, none of them is superior to others. Different authors favour various measures. Diamantopoulos and Siguaw (2000) recommend using several measures and at the same time provide reference values for each of them as presented in Table 4.

Table 4: Fit indicesFit indices Model value Reference value Global model fit?

(level of significance p)

32.920 (0.0115) p 0.05 No

RMSEA 0.0628 < 0.100 Yes (Acceptable)Standardized RMR 0.0485 <0.05 YesGFI 0.965 0.90 YesAGFI 0.926 0.90 YesNFI 0.940 0.90 YesNNFI (TLI) 0.950 0.90 YesCFI 0.970 0.90 Yes

The most traditional value is statistics. Using this fit indicator we test hypothesis that implied covariance matrix equals sample covariance matrix. Our goal is not to reject this hypothesis. In our case this hypothesis must be rejected (at 5% level of significance) which might lead to (false) assumption that the model is not completely acceptable. Nevertheless, researchers are usually willing to accept approximately correct models with small misspecifications. Having established that the level of misfit is small, we can move on to an examination of the other fit indices. All other indices lead to a conclusion that the model is appropriate representation of reality. Root means square error of approximation (RMSEA) is the most wide spread measure of global fit and in our case points at acceptable model-fit. Standardized root mean square residual (Standardized RMR) is fit index calculated from standardized residuals (differences between elements of sample and implied covariance matrix). Goodness-of-fit (GFI) index and Adjusted goodness-of-fit (AGFI) index are absolute fit indices, which directly assess how well covariances based on parameter estimates reproduce sample covariances (Gebring and Anderson, 1993). Incremental fit indices (normed fit index – NFI, non-normed fit index – NNFI and comparative fit index – CFI) compare the statistics of the researcher’s model and a base model that assumes that all variables are uncorrelated (Bentler, 1990). The NNFI and CFI seem to be more independent of sample size and to better account for parsimony. NFI, NNFI (also called The Tucker and Lewis’ index - TLI) and Bentler’s (1990) CFI all satisfy criteria of model-fit. Those three and all other indices described above lead to a conclusion that the model can be regarded as an appropriate approximation of reality (at global level).

When assessing measurement sub-model fit, we focus on relationships between latent variables and their indicators (measurement, observed variables). The goal is to determine

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reliability and validity of measurement variables used to represent constructs of interest. Validity refers to degree to which an indicator actually measures what it was supposed to measure, while reliability deals with consistency of measurement (Tabachnick and Fidell, 2001). The data for construct validity measurement can be obtained from LAMBDA-Y and LAMBDA-X (Tables 5 and 6) matrices for non-standardized parameter estimates. All t-values are larger than 1.96, meaning that construct validity is achieved in our case. It is valid for completely standardized parameter estimates that the greater the weight the more valid certain indicator for certain construct measurement. In absolute terms the most valid indicator in our model is Value Added per Employee (VAEMP), while the least valid indicators are Information Acquisition (INFOACQ) and Information Interpretation (INFOINT). This might point out a necessity to invest further efforts in operationalization of Organizational Learning Culture (OLC) construct in future.

When reliability is an issue we need to address it in two steps: (1) reliability of individual indicators and (2) construct (composite) reliability. The former is measured by using R2 for every single individual indicator and presents a part of variance in an indicator explained by its latent variable. In our case, the most reliable indicator for OL is BCC, the most reliable indicator for FP is VAEMP and the most reliable measure of NFP is SUPPLY. The most reliable indicator in the model is VAEMP, while the least reliable measurement variable is INFOINT. For every single construct composite reliability can be calculated (in LISREL 8.53 still manually) by using the following formula:

where are indicator loadings and are variances of indicator errors (whether or ). The data were obtained from completely standardized solution. It is desired that exceeds 0.6 in order to be able to state that a certain construct as a whole is reliable. In our case = 0.62,

= 0.86 and = 0.63. Based on these three calculations it can be established that composite reliabilities in our case are adequate. Construct FP is the pre-eminently operationalised, which was expected given the objectivity of the indicators involved in the constructs (as opposed to potentially subjective measures included into OLC and also NFP and elusiveness of OL concept).

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Table 5: Lambda Y matrix (non-standardized values)LAMBDA-Y Fp NfpROA 0.873 - -

VAEMP 0.895(0.123)7.273

- -

SUPPLY - - 0.582EMPLOY - - 0.579

(0.092)6.298

BUYER - - 0.337(0.064)5.249

Table 6: Lambda X matrix (non-standardized values) LAMBDA-X OlcINFOACQ 3.443

(0.498)6.912

INTINF 2.386(0.409)5.827

BCC 5.499(0.550)10.001

R2 for FP equals 0.154, which is a relatively low value. We managed to explain the variance of NFP construct much better by using OL as an exogenous variable (R2 = 0.454). If nothing else, this discrepancy proves the fact that inclusion of non-financial performance indicators in the model (and their separation from financial performance) was a reasonable and correct thing to do.

4 Results and Implications

4.1 Hypothesis Testing

Maximum Likelihood (ML) method was used to estimate parameter values. In this phase, the hypotheses set in the conceptualization phase are tested. Even though several methods can be used for this purpose, ML is the most frequently used and has an advantage of being statistically efficient and at the same time specification error sensitive, because it demands only complete data and does not allow for missing values. All methods will, however, lead to similar parameter estimates under the circumstance that the sample is large enough and that the model is correct (Jöreskog and Sörbrom, 1993). In Figure 4 path diagram of our model (with completely standardized parameter estimates and corresponding t-values) is presented.

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Organizational learning culture construct (OLC) demonstrated statistically significant positive and strong impact on both Financial (FP) and Non-financial performance (NFP), which means that hypotheses 1 and 2 can be considered to have empirical support in data at hand. What is interesting is that performance implications of organizational learning tend to be even more expressed in terms of improved loyalty of customers, better relationships with suppliers and employees than purely in terms of increased return on assets and value added per employee comparable to those of competitor.

Figure 4: Research model (completely standardized parameter values and t-values)

4.2 Discussion and Implications

Traditional (vertical, functional) organizational structure is one of the hindrances impeding organizations in their quest for success. The vertical structure, a legacy from industrial revolution, means that companies are organized around functional units (departments or divisions), each with a highly specialized set of responsibilities. In such form of vertical organization units become centres of expertise that build up considerable bodies of knowledge in their own subjects, but even the simplest business tasks tend to cross functional units and require the co-ordination and co-operation of different parts of the organization (Giaglis, Paul, Hlupic, 1999; Blacker, 1995) which makes it rigid, inflexible and unresponsive, all of today’s requirements for a long-term prosperity.

The concepts of business process orientation and process maturity are becoming increasingly important as firms adopt a process view of organization (Lockamy, McCormack, 2004). As suggested by Hammer (1996), with increased process maturity, policies, standards and changes in organizational structures and culture are introduced. It is important to note that trying to skip maturity levels is counter-productive, since each level builds a foundation from which to achieve the subsequent level (Lockamy, McCormack, 2004). An organization must evolve through all levels to establish business process orientation principles. Organizational learning culture is certainly a way to accelerate maturing.

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We have shown that organizational learning culture does have an impact on organizational performance. As the values, behaviours, beliefs and other cultural artefacts shift toward a learning culture many benefits appear. This has important implications for managers striving for success. Clearly more attention has to be directed towards developing a learning culture in order to improve organizational performance, both financial and non-financial. By cultivating the environment in which employees can and should continually learn and share their knowledge, higher levels of satisfaction of all the stakeholders can be achieved.

Even though the relationship between BPO and OLC was not empirically tested in our study, researchers have emphasised they are complementary (see for example Bate, Khan, Pye, 2000). Radical structural changes cannot occur without adaptation of organizational culture. And some cultures, such as learning culture, are more willing to accept and even encourage these changes. This is another important implication for managers implementing concepts of business process orientation. They should not fail to remember the cultural aspect of change if they whish to maximize the yield of change.

5. Directions for Future Research

Our empirical research has shown the positive impact of organizational learning culture on organizational performance. However, the conceptualization of the model was wider, including business process orientation as well. Exclusion of this construct from our empirical analysis is one of the limitations of the paper and is left for future research. By empirically testing the whole model more precise statements can be made and conclusions drawn. The supposition that BPO and OLC together have higher influence on the overall organizational performance must therefore formally be tested.

Our study was only conducted in Slovenia. For wider applicability of the findings it should be expanded to a broader geographical context preferably in the countries at different development stages. Also longitudinal analysis of the relationship between constructs should be performed to determine if there is a time lag in construct correlation. Advancements to the model could come if other constructs were introduced, particularly information and communication technology as an enabler and contributor to BPO and OLC implementation.

To further validate our findings, a case study in a company should be performed. This would give us deeper understanding of the relationship of the constructs proposed in our model and would serve to further test its applicability and usefulness from the practical point of view.

References

Argyris, C., D. A. Schön, 1996, Organizational Learning II: Theory, Method and Practice. - Reading, MA: Addison-Wesley

Atkinson, A.A., Waterhouse, J.H., Wells, R.B., 1997, A stakeholder approach to strategic performance measurement. Sloan Management Review 38 (3), 25-37.

Al-Mashari, M., Zairi, M., 1999, BPR implementation process: an analysis of key success and failure factors Business. Process Management Journal. Bradford: Vol.5, Iss. 1; p. 87

18

Bate P., 1995, Strategies for Cultural Change. Butterworth-Heinemann, Oxford, UK.

Bate P., Khan R., Pye A., 2000, Towards a culturally sensitive approach to organization structuring: where organization design meets organization structuring. Organizational science, March/April 2000, 11, 2

Blacker, K., 1995, The basics of business process re-engineering. Birmingham: Edistone Books.

Blunt, P., 1997, Prisoners of the paradigm: Process consultants and 'clinical' development practitioners. Publ. Admin, and Development 17 341-349.

Bentler, P. M., 1990, Comparative Fit Indexes in Structural Models. Psychological Bulletin, Vol. 107, No. 2. – p. 238.

Carr, Nicholas G., 2003, IT Doesn't Matter. Harvard Business Review, 81 (5), 41-50.

Cohen, W. M., D. A. Levinthal, 1990, Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, – Vol. 35, No. 1. – pp. 128-152.

Cyert, R. M., March, J. G., 1963, Behavioural Theory of the Firm. - Englewood Cliffs: Prentice Hall.

Davenport, T. H., 1993, Process Innovation: Reengineering Work through Information Technology. Boston: Harvard Business School Press.

Deal T.E., Kennedy, A.A., 1982, Corporate Culture: The Rites and Rituals of Corporate Life. Reading, MA: Addison-Wesley.

De Geus, A. P., 1988, Planning as Learning. Harvard Business Review, 88, 2, pp. 70-74.

Diamantopoulos, A., J. A. Siguaw, 2000, Introducing LISREL. - London: SAGE Publications,

DiBella, A.J., Nevis, E.C., 1998, How organizations learn: an integrated strategy for building learning capability. San Francisco: Jossey Bass.

Dimovski, V., 1994, Organizational Learning and Competitive Advantage, PhD Thesis. – Cleveland

Easterby-Smith, M., M. Lyles, 2003, The Handbook of Organizational Learning and Knowledge Management. - London: Blackwell Publishing

Figueiredo, P. N. Learning Processes Features: How do They Influence Inter-firm Differences in Technological Capability - Accumulation Paths and Operational Performance Improvement? International Journal of Technology Management, 2003. – Vol. 26, No. 7. – pp. 655 - 689.

Freeman, E. R., 1984, Strategic Management – A Stakeholder Approach. - London: Pitman.

19

Freeman, E. R., 1994, Politics of Stakeholder Theory: Some Future Directions. Business Ethics Quarterly, No. 4. – pp. 409 – 422.

Giaglis, G. M., Paul, R. J., Hlupic. V., 1999, Integrating simulation in organizational design studies. International Journal of Information Management 19, pp. 219-236

Gebring, D. W., J. C. Anderson, 1993, Monte Carlo Evaluations of Goodness-of-fit Indices for Structural Equation Models. - K. Bollen and J. S. Long (eds.). Testing Structural Equation Models. Thousand Oaks, CA: Sage

Guimaraes, T., 1997, Empirically testing the antecedents of BPR success. International Journal of Production Economics 50: pp. 199-210

Hammer, M. H., Champy, J., 1993, Reengineering the Corporation: A manifesto for Business Revolution. New York: Harper Business. 223 p.

Hammer M., 1996, Beyond Reengineering: How the Proces-Centered Organization is Changing Our Lives. HarperBusiness, New York.

Hammer, M., 2004, Deep Change. Harvard Business Review 82 (4), pp. 84-93.

Harmon P., 2003, Business Process Change: A Manager’s Guide to Improving, Redesigning, and Automating Processes. Morgan Kaufmann Publishers, San Francisco.

Harrison, R., 1972, Understanding you organisation's character. Harvard business Review 5-6: pp. 119-28.

Huber, G. P., 1991, Organizational Learning: The Contributing Process and the Literatures. // Organization Science, No. 2. – pp. 88-115.

Jacques, E., 1952, The Changing Culture of a Company. London: Tavistock.

Jones, G. R., 2000, Organizational Theory, 3rd edition. New York: Prentice Hall,

Jöreskog, K. G., D. Sörbrom, 1993, LISREL 8: Structural Equation Modelling with the SIMPLIS Command Language. London: Lawrence Erlbaum Associates Publishers

Kaplan, R. S., D. P. Norton, 1992, Balanced Scorecard – Measures That Drive Performance. Harvard Business Review, No.1/2. – pp. 71-79.

Kaplan, R. S., D. P. Norton, 1993, Putting the Balanced Scorecard to Work. Harvard Business Review, No. 9/10. – pp. 134-147.

Kaplan, R. S., D. P. Norton, 1996, Using the Balanced Scorecard as Strategic Management System. Harvard Business Review, No.1/2. –pp. 75-85.

Kaplan, R. S., D. P. Norton, 1996a, The Balanced Scorecard. Boston: Harvard Business School

Kogut, B. Joint Ventures, 1988, Theoretical and Empirical Perspectives. // Strategic Management Journal, No. 9. – pp. 319-332.

20

Lai K.-H., 2003, Market orientation in quality-oriented organizations and its impact on their performance. International Journal of Production Economics 84, pp. 17-34.

Lai, K.-H., Cheng T.C.E., 2005, Effects of quality management and marketing on organizational performance. Journal of Business Research 58, pp. 446-456.

Lam, S. S. K., 1998, Organizational Performance and Learning Styles in Hong Kong. // Journal of Social Psychology, Vol . 138, No. 3. – pp. 401-403.

Lane, H. W., P. W. Beamish, 1990, Cross-cultural Cooperative behaviour in Joint ventures in LDCs. // Management International Review, No. 30. – pp. 87-102.

Lockamy, A., McCormack, K., 2004, The development of a supply chain management process maturity model using the concepts of business process orientation, Supply Chain Management: An International Journal, Volume 9, Number 4, pp. 272 – 278

Lyles, M., 1988, Learning among Joint Venture Sophisticated Firms. Management International Review, No. 28. – pp. 85-98.

Meiville N., Kraemer K. & Gurbaxani V., 2004, Information Technology and Organizational Performance: An Integrative Model of IT Business Value. MIS Quarterly, 28 (2), pp. 283-322.

McCormack, K. & Johnson, W., 2000, Business Process Orientation: Gaining the E-Business Competitive Advantage. St Lucie Press, Delray Beach, FL

McCormack, K.P., Johnson, W.C., 2001, Business Process Orientation: Gaining the E-business Competitive Advantage, CRC Press LLC, p. 194

Nahm, A.Y., Vonderembse, M.A., Koufteros, X.K., 2003, The impact of organizational structure on time-based manufacturing and plant performance. Journal of Operations Management 21, pp. 281-306.

O’Neill, P., Sohal, A.S., 1999, Business Process Reengineering: A review of recent literature. Technovation 19, pp. 571-581.

Ostroff, F., 1999, The Horizontal Organization. Oxford: Oxford University Press. p. 257

Ott, J.S., 1989, The Organizational Culture Perspective. Pacific Grove, CA: Brooks-Cole.

Peters, T.J., Waterman, R.H., 1982, In Search of Excellence: Lessons from America's Best-Run Companies. New York: Harper and Row.

Pisano, G.M., R. M. J. Bohmer, A. C. Edmondson, 2001, Organizational Differences in Rates of Learning: Evidence from the Adoption of Minimally Invasive Cardiac Surgery. Management Science, Vol. 47, No. 6. – pp. 752 – 768.

Rollinson, D., Broadfield, A., 2002, Organisational Behaviour and Analysis – an Integrated approach. 2nd ed. Pearson Education.

Senge, P. M., 1990, The Fifth Discipline: The Art and Practice of Learning Organization. New York: Currency Doubleday

21

Schein, E.H., 1992, Organizational Culture and Leadership. San Francisco, CA: Jossey-Bass.

Shrivastava, P., 1983, A Typology of Organizational Learning Systems. Journal of Management Studies, No. 20. – pp. 1-28.

Simonin, B. L., 1997, The Importance of Collaborative Know-how: An Empirical Test of the Learning Organization. Academy of Management Journal, Vol. 40, No. 5. – pp. 1150 – 1173.

Sloan, T. R., Hyland, P. W. B., Beckett, R. C., 2002, Learning as a Competitive Advantage: Innovative Training in the Australian Aerospace Industry. International Journal of Technology Management, Vol. 23, No. 4. – pp. 341-52.

Smith H. & Fingar P., 2003, IT Doesn’t Matter, Business Processes Do. Mergan-Kiffer Press, Tampa, Florida.

Smith, M., 2003, Business Process Design: Correlated of Success and Failure. The Quality Management Journal. Vol. 10, No. 2

Sung, T.K., Gibson, D.V., 1998, Critical Success Factors for Business Reengineering and Corporate Performance: The case of Korean Corporations. Technological Forecasting and Social Science 58, pp. 297-311

Tabachnick, B. G., Fidell, L. S., 2001, Using Multivariate Statistics, 4th ed. - Needham Heights, MA: Allyn and Bacon.

Tenner, A. R., DeToro, I. J., 1997, Process Redesign, The Implementation Guide for Mangers. Reading, MA: Addison-Wesley.

Wall, B., 1998, Measuring the Right Stuff: Identifying and Applying the Right Knowledge. Knowledge Management Review, Vol.1, No. 4. – pp. 20-24.

Weerakoon, T.S., 1996, Organizational performance - a stakeholder concept. International Research Conference on Quality Management Proceeding, pp. 80-90.

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