Introduction
It is obvious that the software industry is sustaining its continuous growth worldwide. Therefore, the growth and evolution of software industry has been the interest of theorists and practitioners in terms of strategic management, industrial economics, organization theory and psychology (Nambisan, 2002). There are various researches to evaluate internal and external environmental factors of software industry, such as organizational resources and qualifications, innovation, organizational learning and organizational structure (Lee et al., 2008; Nambisan, 2002; Koc, 2007; Mehra and Dhawan, 2003; Therin, 2003; Ajila, 2006). Besides, some studies have provided descriptive analysis of software services industry (Arora et al, 2001; Mohamed et al, 2009; Iyidogan et al, 2006). The Israeli and Irish software industries have major roles in the world wide software industry, together with the Indian software industry being a major competitor to them (Arora et al, 2001).
Literature Review and Hypotheses
Organizational Effectiveness
Since organizational effectiveness is a complex concept, there are a number of approaches to explain what it means. Various organizational theories are structured based on the different conditions and organizational factors while effectiveness is one of the most used criteria (Baker et al., 1997; Ajila, 2006). The strategic-constituencies approach is a theory that evaluates the organizational effectiveness according to the identified common aims and strategies of organizations (Papadimitriou and Taylor, 2000). According to Kushner and Poole (1996) the effectiveness of an organization can be evaluated using four components which are resource acquisitions, efficiency, goal attainment, and customer satisfaction. Parhizgari and Gilbert (2004) assume that a domain including effective factors can be defined with its constraints due to feasibility considerations for each company, or each industry, or each sector and the measurement of organizational effectiveness could be done based on this domain of effective factors using the views of the employees and/or the customers.
Organizational structure has an important part in determining organizational effectiveness, and practices of organizational structure are context specific (Zheng et al., 2010). A successful organizational structure facilitates managerial issues, provides great potential for improving organization’s competitive power, innovation capability and labor force relations while lowering expenses. McDermott and Stock (1999) analyze the relationship between organizational factors and innovation considering the operational benefits such as improvements in productivity and flexibility, advantages in business processes, information exchange, coordination of tasks, managerial control and competitive success characterized by increase in sales, market share and profits.
When the organization is a software firm, the organizational performance may also be evaluated using four impact items such as impact on software development, overall performance, cost and customer satisfaction (Ajila, 2006).
Organizational Structural Determinants
Age
Although there are a large number of studies for exploring the relationships between organizational context and various independent variables like innovativeness, organizational climate and organizational performance, organizational age has received less attention from scholars of organization theory (Nystrom et al, 2002).
Some arguments in support of a positive association between organizational age and organizational effectiveness can be developed by considering that older organizations tend to be larger and wealthier. However, Nystrom and Starbuck (1984) highlighted that not all organizations prolong to grow larger and healthier as they age. Only some of them can survive over time and others fail to adapt to rapidly changing environmental conditions. Besides, some researchers utilize age as the representative of the experience of a company in a specific industry. Audrestch (1995) explains organizational performance as positively related with the age of a company given that, the company is eligible based on the years of activity.
According to Durand and Coeurderoy (2001) the age of a company causes a decrease in company performance and therefore, young companies produce better results than older ones. Older organizations become isolated and slow down with the trap of repeated tasks, they do not try and learn new ways of doing things, they do not innovate and therefore, their effectiveness weakens and deteriorates (Dunne and Hughes, 1994).
In the context of this study, organizational age is tested to see whether or not it affects the organizational effectiveness in the software industry:
Hypothesis 1: The Organizational age affects the organizational effectiveness of a software company.
Size
There is a long-standing research area for the relationship between organizational size and organizational structure (Pfeffer and Leblebici, 1973; Scott, 1975; Mileti et al, 1977; Hsu et al, 1983). The size of a software company can be a good evidence of an achieved reputation (Ajila, 2006). Blau (1970) proposed generalizations and propositions about the influence of size on structural differentiation in organizations. Besides, Hsu et al. (1983) made an analysis to discover the linkages among organizational context, organizational complexity and bureaucratic control and found that specialization, organizational size and formalization are interrelated. Additionally, it is emphasized that there are positive correlations between the size and the number of departments, the number of hierarchical positions and the financial resources, that department managers are allowed to use without taking approval of their super ordinates (Pfeffer and Leblebici, 1973).
Although the size is an essential variable for organization theory, there are not enough findings at empirical level. Hal et al. (1967) claimed that no consistent linkage exists between size and other structural variables, and the findings indicated the irrelevance of size in determining organizational structure. These claims suggest that organization size does not have a close relation with formalization and complexity. Therefore, the organization size should be taken as a questionable variable about its deterministic role on organizational structure. Additionally, there is no significant connection between size and decision making, and reporting procedures (Pfeffer and Leblebici, 1973). Although the general perception for large organizations is connected to high goal achievement and performance, it is reported that small software companies have higher performances (Alija, 2006). According to Hal et al. (1967) larger organizations have a slight tendency for being more formalized even though the relationship between organizational size and formalization is very weak.
In the context of this study, organization size is represented with the number of employees in the company and the following hypotheses were developed:
Hypothesis 2: Organization size affects the organizational effectiveness of a software company.
Hypothesis 3: As software company gets larger in size, its degree of formalization increases.
Hypothesis 4: A relationship exists between the organization size and the degree of centralization of a software company
Formalization
The “formalization” indicates the amount of written principles, policies, procedures, rules for managing business processes and relations among employees (Pertusa-Ortega et al., 2010). In other words, when the degree of formalization is high in an organization, the duties and rights of labor force, ways of doing things at all levels are clearly described and written (Willem and Buelens, 2009).
If an organization has a formalized structure, the attitudes of its employees are organized, frequent and effective (Pertusa-Ortega et al., 2010). Besides, formalization improves and facilitates the cooperation and collaboration among the members of the organization. These advantages will increase the quality of all activities in the firm. Beckmann et al. (2007) claim that formalization has a positive correlation with the quality of the products and services which is an essential part of the organizational performance.
Schminke et al. (2002) emphasizes that the broad rules and procedures can increase the individuals’ confidence for acting similarly in equivalent situations. Employees can be anticipated to carry out the same input in exactly the same way, and finalize the task with a consistent and uniform output. Dunford et al (2007) investigated the coexistence of “old organizational forms” and “new organizational forms” in dynamic business environments like formalization together with speed, flexibility and innovation. The study explains that formalization may have advantages for some business processes. When routine tasks are highly formalized and non-routine tasks are not, it is possible to observe rising organizational performances (Baum and Wally, 2003). Nahm et al. (2003) analyzed the interactions between organizational structure, production time and manufacturing performance and concluded that formalization and the degree of hierarchy influences decision making and communication significantly and positively in the firm. Based on these literature findings the following hypothesis was developed:
Hypothesis 5: As the degree of formalization increases in a software company, its organizational effectiveness increases.
Centralization
The “centralization” is the degree which indicates the concentration of decision making authority by a person, department or a level in the organization (Schminke et al, 2002). When the degree of decentralization is high, authority is delegated to all levels, and employees have enough rights to execute their activities in a fast and competent manner without waiting the approval of an upper level manager (Andrews et al, 2008). Literature contains findings showing that organizational effectiveness is influenced positively by centralization (Ruekert et al, 1985). However, some other findings in the literature claim that organizational effectiveness may be influenced positively by decentralization (Burns and Stalker, 1961; Dewar and Werbel, 1979; Schminke et al, 2002). It is demonstrated that decentralization fosters communication in the organization and creates a workplace with more satisfied and motivated employees (Burns and Stalker, 1961; Dewar and Werbel, 1979). Free flow of communication is conducive, decision-making heavily depends on the specialists rather than the managers (Burns and Stalker, 1961) and faster response to changing market requirements is possible (Schminke et al, 2002). Contrary to many studies that claimed existence of a negative correlation between formalization and centralization, a higher degree of formalization cannot mean being more decentralized because of two reasons: a well-combined, advanced information system and an intend to be more defensive in uncertain environments (Wang, 2003). Besides, when the organizational environment is not stable, the top level of an organization may prefer to arrange decision making processes with a centralized approach while decentralizing operational level. Another important point for software companies is that there is a negative relationship between centralization and innovation.
Wang (2003) emphasizes that although formalization and centralization are usually considered as solid structural characteristics which can restrain the firm effectiveness, the rigid organizational structures classically defined in the organizational literature may in fact enhance the organizational effectiveness. Therefore, the following hypotheses will be tested:
Hypothesis 6: Centralization affects organizational effectiveness of a software company.
Hypothesis 7: A relationship exists between the degree of formalization and centralization in a software company.
Specialization
The “specialization” is the degree of dividing organizational assignments into smaller pieces of work, and employees are held responsible for only one or a small number of these tiny tasks (Mintzberg, 1989). Therefore, only one person or a group of people gain special expertise on a specified part of a job (Grant, 1996). Specialization is extended to knowledge complexity, unit differences, interdependency and different specialties found in an organization (Willem and Buelens, 2009). In order to evaluate knowledge complexity there are two variables taken into consideration: One of them is occupational specialty, and the other variable is the time necessary to acquire a special skill or expertise (Hal et al, 1967). Interdependency is another concept explaining the degree of necessity for departments to work together. Interdependency and differences among units can both be developed in the decentralized organizations. While studying the impact of formalization, centralization, and specialization on knowledge sharing among the departments of an organization, Willem and Buelens (2009) found that specialization has an essential effect on the organizational communication especially considering interdependency and knowledge complexity. However, it is suggested that an optimum in the formalization should be an advantage to enhance the knowledge sharing and organizational performance. The following hypotheses will test two of the relationships mentioned in the literature for the software industry:
Hypothesis 8: As the degree of specialization increases in a software company, its organizational effectiveness increases.
Hypothesis 9: A relationship exists between specialization and formalization in a software company.
Hypothesis 10: The influence of age, size, formalization, centralization and specialization on determining organizational effectiveness level can be expressed with a linear equation.
Methodology
The research model consists of six dimensions which are organizational age, organizational size, formalization, centralization, specialization and organizational effectiveness. As shown in Figure 1 organizational effectiveness is dependent dimension of the model. The variables used in determination of organizational effectiveness level are customer satisfaction, quality, time management, employee resources management, employee satisfaction, internal communication, management ability, long-term support after project releases and additional employee assignment during the project releases. Organizational structure factors such as organizational age, organizational size, formalization, centralization and specialization are the independent dimensions of the model. The model aims to investigate the impact of organizational structure dimensions on organizational effectiveness. The relationships of organizational structure dimensions among each other will be second degree findings of the research.
As the survey instrument, a web-based questionnaire has been designed based on the literature study. The survey aims to capture all essential key points of organizational structure variables, and organizational effectiveness of software firms in the sample.
The draft questionnaire has been applied to some employees working in the software industry and then, the survey questions have been revised considering the feedback obtained from the participants. The questionnaire has been finalized by adding questions about organizational age, organizational size, and firm services for comparing the sample with those of previous works focusing on the software industry.
The questionnaire and/or survey link has been sent to employees working for software industry. From the electronic version and face-to-face visits, 127 responses were collected. The rule was “one survey for each software company”. Duplicate responses detected by IP address controls and by reviewing specific questions in the questionnaire and then, the average values of the duplicate answers were used as of one questionnaire in data entry. After the elimination of 5 invalid responses the sample included 120 responses of which 117 fully and 3 partially are completed. The data are checked and transformed to the appropriate format and then, analyzed by using SPSS 18.0.
Table 1: Organizational size of the companies
Table 2: Establishment dates of the companies
Table 3: Hierarchy levels in the companies
Results
In the sample 51.7% of the companies have more than 50 employees as it can be seen in Table 1. Table 2, illustrates that 64.2% of the companies are established after 1996. 41.7% of the organizations in the sample have 4 or more hierarchy levels. Mean values for all variables can be seen in Table 4.
Software companies provide services on software, hardware and consultancy. 85% of the companies in the sample offer software services by more than 50% of their activities. In the sample, 54 % of the software companies are subject to regular audit for a certificate. In the study done by Iyidogan (2006), it is seen that the ratio of software companies having regular audit is 48% for a similar sample. When two ratios are compared although there is an increase, the tendency for having regular audit is still low. Low audit ratio indicates that formalization is not high. The high costs of application and evaluation phases, insufficient attention to apply a certificate and “no need” perception are the main reasons of not having a quality certificate (Iyidogan, 2006).
Table4: Mean values of responses for variables
Reliabilities of each scale of the survey instrument were tested using Cronbach’s alpha coefficient. Higher Cronbach’s alpha coefficients indicate greater reliability among the indicators (Zhu et al., 2002) which is true for organizational effectiveness, formalization and centralization. As shown in Table 5, specialization has a relatively moderate level of reliability indicating lower internal consistency among the questions of this dimension. Age and size are not in Table 5 due to the nature of these questions, and the related data can be seen in Table 1 and Table 2.
Table 6 shows correlation analyses among dimensions. Pearson correlation coefficients indicate that organizational age has significant positive correlations with organizational size and centralization. However, a negative significant correlation with a low Pearson coefficient of -0.277 exists between organizational age and organizational effectiveness which supports H1 just like the literature does. Organizational size also has a significant negative correlation with organizational effectiveness (-0.390) which proves H2. There is no significant correlation between organizational size and formalization, so H3 is not supported. The significant Pearson correlation coefficient of 0.318 indicates that organizational size and centralization are correlated and H4 has a proof. Formalization has a moderate and significant Pearson correlation coefficient of (0.435) with organizational effectiveness and H5 is supported. The significant correlation coefficient of -0.39 between centralization and organizational effectiveness suggests the same as H6. Formalization and centralization are related with a negative Pearson correlation coefficient 0f -0.229 which displays H7 may be right. Specialization is correlated with organizational effectiveness which strengthens H8 with a Pearson correlation coefficient of 0.298(sign≤0.01). The significant Pearson correlation coefficient of 0.234 between specialization and formalization proves H9.
In regression analysis, organizational effectiveness is taken as dependent variable by evaluating the mean value of ten effectiveness variables which are Long-term support, Additional employee, Customer complaints, Customer satisfaction, Quality, Time management, Employee resource management, Employee satisfaction, Communication in firm and Management ability. Organization Age, Organization Size, Formalization, Centralization and Specialization are considered as independent variables. The regression model is estimated as below:
of the regression model is 0.427 (adjusted = 0.402), indicating that 43 % of the variance in the dependent variable can be explained by the independent variables of the model. The level of significance of the equation for F test is 0.000, demonstrating that the model is meaningful. However, only coefficients of organization size, formalization and specialization have been calculated statistically significant at 0.05 level, while organization age and centralization are not found to be statistically significant for influencing organizational effectiveness linearly. A stepwise regression has been applied in order to consider only the significant variables in the regression model. Revised model is the following:
of the revised regression is 0.413 (adjusted = 0.398). This model explains that 41% of the variance in the dependent variable. The level of significance of the equation for F test is 0.004 which is significant at 0.05 level. Besides, Durbin Watson is calculated as 1.874 indicating that multicollinearity statistics for the second regression are within the acceptable limits. T test values for coefficients indicate that coefficients for all variables including constant are statistically significant at 0.05 level. Therefore, the final model can be explained as below:
Y = organizational effectiveness
X2= organizational size
X3= formalization
X5= specialization
The regression analysis brought a significant model of a linear relationship although, H10 is not fully supported. The regression model proves that organizational size, formalization and specialization are the factors influencing organizational effectiveness. However, organizational size has a negative impact on organizational effectiveness. The regression model explains that while formalization and specialization increase the organizational effectiveness of a software company, higher company size decreases the company effectiveness. Formalization is the most dominant determinant among organizational structural factors. Even though centralization is subject to various literature searches, the affect of centralization on organizational performance is not distinctive for software organizations in the sample.
Conclusion
The main goal of this research was to determine the structural determinants of the organizational effectiveness in the software companies. The research points out the most influential structural dimensions so that, software companies may focus on them for increasing their organizational success. Having the right priorities when controlling the structural issues, may bring higher organizational effectiveness levels.
The organizational structure dimensions such as age, size, formalization, centralization and specialization are included in the study. Among these dimensions, an organization has no control on age. Therefore, a decrease in organizational effectiveness due to the increasing age of organization is unavoidable. Additionally, as the company finds or creates new business opportunities, new employees will be hired, which will increase the size of the organization while decreasing the organizational effectiveness level. However, an organization’s levels of formalization, centralization and specialization depend on managerial decisions. Therefore, having priorities and controlling the degrees of formalization, centralization and specialization contributes to managerial control of organizational effectiveness.
The research clarifies that when a software company gets more formalized, its organizational effectiveness increases. As a company establishes formal rules, standard policies and procedures and improves them for reaching excellence in time, the quality of all activities increase together with organizational performance (Bechmann et al., 2007).
While controlling specialization dimension for increasing organizational effectiveness, managers have to keep in mind that some individuals or groups will become the sole owner of some specific knowledge. As the knowledge complexity increases, the organization will need better communication processes to keep the positive effect on the organizational effectiveness. Improved communication may refer to more policies, procedures and rules which in turn will increase for formalization.
Since centralization has a negative correlation to organizational effectiveness, software companies need to avoid centralization. However, it may be difficult for companies not to get more centralized while they continuously hire new employees.
As a company gets older, if it keeps its size and if it does not centralize, it may better stand the drop in organizational effectiveness. However, as years go by and the organization hires more and more employees, it should focus on holding centralization at minimum level in order to keep its level of organizational effectiveness. If the organization gets more formalized it can decrease its degree of centralization.
The negative impact of organizational size, the positive influences of formalization and specialization on organizational effectiveness have been verified when all factors are tested together with a regression analysis.
This study can serve managers of software organizations for reaching higher organizational effectiveness levels while they make various decisions concerning size, formalization, specialization and centralization. Findings of the study will also serve researchers of organizational issues, although its sample is small and limited to software industry.
References
1. Ajila, S. (2006), ‘The Impact of Firm Size on Knowledge Reuse and Exploration during Software Product Development: an Empirical Study,’ Information Reuse and Integration, 2006 IEEE International Conference, September 16-18, pp. 160-165
2. Arora , A., Arunachalam, V. S., Asundi, J., and Fernandes, R. (2001), ‘ The Indian software services industry,’ Research Policy, 30 (8), 1267-1287.
Publisher – Google Scholar
3. Audrestch, D. B. (1995), Innovation and industry evolution, Cambridge, MA: MIT Press.
Google Scholar
4. Baker, C.M., Reising, D.L., Johnson, D.R., Stewart, R.L., and Day Baker, S. (1997), ‘Organizational Effectiveness: Toward an Integrated Model for Schools of Nursing,’ Journal of Professional Nursing, 13 (4), 246–255.
Publisher – Google Scholar
5. Baum, J.R., and Wally, S. (2003), ‘Strategic decision speed and firm performance,’ Strategic Management Journal, 24 (11), 1107-1129.
Publisher – Google Scholar
6. Beckmann, C., Otto, H.U., Schaarschuch A., and Shrödter, M. (2007), ‘Quality management and formalization in social service organizations. A survey on home-based family intervention services,’ Social Work and Society, 5 (1), 78–93.
Google Scholar
7. Blau, P. (1970), ‘A Formal Theory of Differentiation in Organizations,’ American Sociological Review, 35 (2), 201-218.
Publisher – Google Scholar
8. Burns, T., and Stalker, G. (1961), The management innovation, London: Tavistock.
9. Dewar, R., and Werbel, J. (1979), ‘Universalistic and contingency predictions of employee satisfaction and conflict,’ Administrative Science Quarterly, 24 (3), 426–448.
Publisher – Google Scholar
10. Dunford, R., Palmer, I., Benveniste, J., and Crawford, J. (2007), ‘Coexistence of ‘old’ and ‘new’ organizational practices: Transitory phenomenon or enduring feature?’ Asia Pacific Journal of Human Resources, 45 (1), 24-43.
Publisher – Google Scholar
11. Dunne, P., and Hughes, A. (1994), ‘Age, Size, Growth and Survival: UK Companies in the 1980s,’ the Journal of Industrial Economics, 42 (2), 115-140.
Google Scholar
12. Durand, R., and Coeurderoy, R. (2001), ‘Age, order of entry, strategic orientation and organizational performance,‘Journal of Business Venturing, 16 (5), 471-494.
Publisher – Google Scholar
13. Grant, R. M. (1996), ‘Toward a knowledge-based theory of the firm,’ Strategic Management Journal, 17 (Winter Special Issue), 109-122.
Google Scholar
14. Hal, R.H., Johnson, N.J., and Haas, J.E. (1967), ‘Organizational Size, Complexity and Formalization,’ American Sociological Review, 32 (6), 903-912.
15. Hsu, C., Marsh, R.M., and Mannari, H. (1983), ‘An Examination of the Determinants of Organizational Structure,’The American Journal of Sociology, 88 (5), 975-996.
Publisher – Google Scholar
16. Iyidogan, S., Gürbüz, Y., and Zeyneloglu, I. (2006), Türkiye’de Yazılım Endüstrisinin Yapısı ve Gelişimi, Istanbul Ticaret Odası, Yayın No: 2006-31
17. Koc, T. (2007), ‘Organizational determinants of innovation capacity in software companies,’ Computers & Industrial Engineering, 53 (3), 373 -385.
Publisher – Google Scholar
18. Kushner, R.J., and Poole, P.P. (1996), ‘Exploring Structure-Effectiveness Relationships in Nonprofit Arts Organizations,’ Nonprofit Management and Leadership, 7 (2), 119-136.
19. Lee, B.R., Lee, S.H., and Leem, C.S. (2008), ‘A Competitive-Perspective Evaluation Framework of Software Firms,’ Networked Computing and Advanced Information Management, NCM ’08, Fourth International Conference, September 2-4, Vol. 2, pp. 13 – 20. DOI 10.1109/NCM.2008.136
Publisher – Google Scholar
20. McDermott, C.M., and Stock, G.N. (1999), ‘Organizational culture and advanced manufacturing technology implementation,’ Journal of Operations Management, 17 (5), 521-533.
Publisher – Google Scholar
21. Mehra, K., and Dhawan, S. K. (2003), ‘Study of the process of organisational learning in software firms in India,’ Technovation, 23 (2), 121-129.
Publisher – Google Scholar
22. Mileti, D.S., Gillespie, D.F., and Haas, J.E. (1977), ‘Size and Structure in Complex Organizations,’ Social Forces, 56 (1), 208-217.
Google Scholar
23. Mintzberg, H. (1989), Mintzberg on management: Inside our strange world of organizations, (1st ed.), Newyork: The Free Press.
Google Scholar
24. Mohamed, N., Hussein, R., Ahlan, A.R., and Hazza, Z.M. (2009), ‘A descriptive analysis of IT adoption in Malaysian small software firms,’ Computer Science and Information Technology, ICCSIT 2009, 2nd IEEE International Conference, August 8-11, pp. 275 – 278. DOI: 10.1109/ICCSIT.2009.5234397
Publisher – Google Scholar
25. Nahm, A.Y.,Vonderembse, M.A., and Koufteros, X.A. (2003), ‘The impact of organizational structure on time-based manufacturing and plant performance.,’ Journal of Operations Management, 21 (3), 281-306.
Publisher – Google Scholar
26. Nambisan, S. (2002), ‘Software firm evolution and innovation–orientation.,’ Journal of Engineering and Technology Management, 19 (2), 141-165.
Publisher – Google Scholar
27. Nystrom, P.C., and Starbuck, W.H. (1984), ‘To avoid organizational crises, unlearn,’ Organizational Dynamics, 12 (4), 53–65.
Google Scholar
28. Nystrom, P.C., Ramamurthy, K., and Wilson, A. (2002), ‘Organizational context, climate and innovativeness: adoption of imaging technology,’ Journal of Engineering and Technology Management, 19 (3-4), 221-247.
Publisher – Google Scholar
29. Papadimitriou, D., and Taylor, P. (2000), ‘Organisational Effectiveness of Hellenic National Sports Organisations: A Multiple Constituency Approach,’ Sport Management Review, 3 (1), 23-46.
Publisher – Google Scholar
30. Parhizgari, A.M., and Gilbert, G.R. (2004), ‘ Measures of organizational effectiveness: private and public sector performance,’ Omega, 32(3), 221-229.
Publisher – Google Scholar
31. Pertusa-Ortega, E.M., Zaragoza-Sáez, P., and Claver-Cortés, E. (2010), ‘ Can formalization, complexity, and centralization influence knowledge performance? ‘ Journal of Business Research, 63 (3), 310-320.
Publisher – Google Scholar
32. Pfeffer, J., Leblebici, H. (1973), ‘ The Effect of Competition on Some Dimensions of Organizational Structure, ‘Social Forces, 52 (2), 268-279.
Publisher – Google Scholar
33. Scott, W.R. (1975), ‘Organizational Structure,‘ Annual Review of Sociology, 1, 1-20. DOI: 10.1146/annurev.so.01.080175.000245
34. Schminke, M., Cropanzano, R., and Rupp D.E. (2002), ‘Organization structure and fairness perceptions: The moderating effects of organizational level,’ Organizational Behavior and Human Decision Processes, 89 (1), 881-905.
Publisher – Google Scholar
35. Therin, F. (2003), ‘ Organizational learning and innovation in high-tech small firms,’ System Sciences, 2003, Proceedings of the 36th Annual Hawaii International Conference, January 6-9. DOI: 10.1109/HICSS.2003.1174262
Publisher – Google Scholar
36. Wang, E.T.G., and Tai, J.C.F. (2003), ‘ Factors affecting information systems planning effectiveness: organizational contexts and planning systems dimensions,’ Information & Management, 40, 287-303. DOI: 10.1016/S0378-7206(02)00011-3
Publisher – Google Scholar
37. Willem, A. and Buelens, M. (2009), ‘ Knowledge sharing in inter-unit cooperative episodes: The impact of organizational structure dimensions,’ International Journal of Information Management, 29 (2), 151-160.
Publisher – Google Scholar
38. Zheng, W., Yang, B., and McLean, G.N.(2010), ‘ Linking organizational culture, structure, strategy, and organizational effectiveness: Mediating role of knowledge management,’ Journal of Business Research, 63(2010), 763-771.
Publisher – Google Scholar
39. Zhu, K., Kraemer, K. L., and Xu, S. (2002), A Cross-Country Study of Electronic Business Adoption Using the Technology-Organization-Environment Framework, Center for Research on Information Technology and Organizations, University of California, Irvine.
Google Scholar
