ISSN : 0976-531X
EISSN : 0976-5352
AMRAN AWANG1*, ZAINAL ARIFFIN AHMAD2, ABDUL RASHID SAID ASGHAR3, KHAIRUL ANWAR SUBARI4, SHAMSUL ANAZ KASSIM5
1Faculty of Business Management, Universiti Teknologi MARA (UiTM) Perlis, Arau, Malaysia
2College of Graduate Studies, Universiti Tenaga Nasional (UNITEN), Kuala Lumpur, Malaysia
3Faculty of Applied Science, Universiti Teknologi MARA (UiTM) Perlis, Arau, Malaysia
4Faculty of Business Management, Universiti Teknologi MARA (UiTM) Perlis, Arau, Malaysia
5Faculty of Business Management, Universiti Teknologi MARA (UiTM) Perlis, Arau, Malaysia
* Corresponding Author : amranawang@yahoo.com
Received : 05-08-2011 Accepted : 05-09-2011 Published : 05-12-2011
Volume : 2 Issue : 2 Pages : 79 - 91
Int J Econ Bus Model 2.2 (2011):79-91
Conflict of Interest : None declared
Small and medium agro-based enterprises (SMAEs) in Malaysia is progressing parallel with the developed nations’ direction in 2020. The progress in this sector could be enhanced with the support of strategic entrepreneurship variables. Entrepreneurial orientation, knowledge, business network, technology, strategy and perceived environmental factors showed significant impact on growth, efficiency and effectiveness of the SMAEs. A total of 615 observations were collected from owner or manager of multi sectoral SMAEs. The study substantiated specific EO patterns among SMAEs between regional growth corridors (RGCs) on the peninsular. EO among SMAEs in Malaysia shows some forms of strategic entrepreneurship. Knowledge, network and EO were important determinants for SMAEs’ growth, efficiency and effectiveness. Moreover, social network showed significant intervening effect for higher SMAEs effectiveness when EO was used. Presence of technology, strategy and perceived environment justified higher SMAEs’ growth, efficiency and effectiveness when knowledge, network and EO were utilized.
Knowledge; networking; entrepreneurial orientation; technology; strategy; perceived environment; performance; SMAEs.
Research in strategic entrepreneurship is at the embryonic stage [1] whereby creative and innovative inputs were crucial to develop variables and measurements towards formulating a model. The study explores the variables such as, knowledge, networking, entrepreneurial orientation, technology, strategy and perceived environment pertaining to the RGCs.
The study capitalizes on Malaysian agro-based industry performance especially among the SMAEs that found lacking, eventhough the sector had been targeted as the main contributor to the economy. On the other hand, in-depth study regards to agro-based entrepreneurship were found being left out compared to other imperatives in the economy. Consequently, strategic factors in agro-based industry need to be reviewed against their effectiveness, growth and efficiency.
The literature review reveals the overview of agro-based economics in Malaysia since the inception of our economic plans until the recent phenomena of regional growth corridors. Furthermore, the issues pertaining to the variables under study were discussed in term of the research gaps found in the methodology and findings of previous studies in Malaysia and other parts of the world.
A. Malaysian RGCs and EO
Under the ninth Malaysia plan (RMK9) where the goals of its socio-economic development to be materialized within 2006-2010. Among them were to revitalize the agro-based sectors as a powerful economic engine through the development of regional growth corridors (RGCs). They were the extention of our growth strategy focused at regional levels. The master plan was strategized through the New Economic Policy (NEP) in 1970-1990 continued with the New Development Policy in 1990-2000 and finally the Vision Development Policy in 2000-2020. However, Malaysia [2] reported that the economic distribution among major races as well as states’ wealth remain unbalanced. One of the key indicator was the economic participation achievement among races that showed the majority group achieved less than 19% and some states remained poor. Among the reasons of the under achievement was the entrepreneurial quality of the entrepreneurs and enterprises [2] . This has led to the 10th and 11th Malaysia Planning (2010-2020) that aimed to boost the development of new generation of entrepreneurial oriented human capital and firms capable to take part in global market. The plan also suggests that the focus will be concentrated on regional basis. Thus, we aim to explore to what extent does differences in EO explain whole SMAEs and SMAEs in the three RGCs on the Peninsular?
B. EO-The Concept and Strategic Relationships
EO refers to the behavior influences the process, decision-making styles and practices of a firm’s management and employees [3] that leads to superior firm performance. This section discusses the building blocks of EO concept and its operationalization approach. Consequently, the five dimensions of EO were elaborated individually and recapitulated with some concluding remarks.
Issues in EO measurement were argued by entrepreneurship scholars since the last three decades, dimensionality issue has spark numbers of studies. Dimension found in studies [4,5,6,7] , EO was operationalized using a 9-items construct. Issue in dimensionality hinges on unidimensional versus multidimensional argument, a study [7] concluded that multidimensionality was found justified, however unidimensional or aggregate dimension could be used for specific occassion but after careful consideration.
Final remark for this section refers to [8] who iterated that today’s enterprises will not be able to survive in this era of rapid ‘creative destruction’ and the ICT driven economy without entrepreneurship drivers. Entrepreneurs have to ensure that they behave as strategic leaders driving their firms with EO proficiency in this new competitive landscape. Therefore, embracing an entrepreneurial orientation, knowledge and networking capabilities in the entrepreneurs-led firms would secure survival and sustainability of enterprises [9,10] . A strategic entrepreneurship should be a compulsory option for firms’ adoption into themselves and their team [28] . Thus the study shall answer the question of to what extend do knowledge, network affect EO relationship with performance? And how do technology, strategy and perceived environment interact on those relationship?
A. Sample and data collection
Data for this study were collected from the SMAEs located in 11 states of peninsular Malaysia. Population frame was provided by six agro-based development agencies such as Malaysian Agriculture Department, Farmer’ Association Organization, Muda Development Authority (MADA), Kelantan Development Authority (KADA), Farmers’ Marketing Authority (FAMA) and Malaysian Agro Bank in every state under study. The list of SMAEs were then randomly selected, whereby the numbers of the firm in each state vary widely due to disproportionate random sampling. After scrutinizing about 850 returned responses 615 samples were usable.
For ease of control in data collection process the area was divided into three zones; northern, southern and eastern. Each zone was represented by a research assistant to supervise a group of 5-10 students to conduct a face-to-face interview. The students were trained to collect the data and provided with financial support to go back to their hometown and served as local interviewers.
B. Measures
The instrument was adopted from variety of sources such as Lumpkin and Dess [3] - EO (29 items) [11] - knowledge (11 items) [12] - networking (11 items) [13] – technology (7 items) [4] – strategy (12 items) [14] - perceived environment (19 items) [15] – efficiency (ROI) (objective measures) [16] - firm’s growth (4 items) [17] - firm’s effectiveness (4 items). EO, knowledge, networking, technology, strategy and perceived environment variables measured in 5-point Likert scale. The dependent variables utilized firms’ efficiency in objective mode, firm’s growth in 7-point interval scales, and firm’s effectiveness measured in 10-point percentages interval scales.
All variables proven to achieve normality observed in Kolmogorov-Smirnov (ks) test when the ks were non-significant proving non-normality to be rejected. Linearity of variable relationship utilized on P-P plot that showed all data fit on the plotted line.
Data internal consistency and reliability of most variables in the study assured by Cronbach’s alpha that showed the coefficient of more than .50 as suggested [18,19] . The items loaded in each variable compiled into composite score through mean score summated scale as suggested [20] .
C. Analytical Techniques
We controlled for firms’ type, size, legal form, firm cycle and agro dependency by recoding the dichotomous scale into dummy-coded scale. The control variables were analyzed in model 1 of the regression analysis followed by independent, mediator and interaction’s variables.
Prior to the regression analysis, some assumptions were assured, such as normality, linearity, multicollinearity free, error term free, homoscedasticity, and outlier free were ascertained [19] .
Factor anaysis were run on independent and mediator variables to ascertain their construct-convergent validity and underlying dimensions preceding the reliability analysis. In factor analysis, the principal component analysis utilizing varimax rotation were observed to detect the orthogonal rotated dimensions. Factor analysis proved the sample free from common method variance when independent and moderator variables did not produce a single-factor structure, suggesting that common method variance is not a threat to the sample [21] .
Mediating effect analysis was observed in a three-step regression analysis proposed in [22] . Mediator type was ascertain as suggested [23] . Estimation criteria suggested in equations as follows: (1) Y = i1 + cX, (2) M = i2 + aX, (3)Y = i3 + c’X + bM.
According to [22] , four conditions to be observed in determining the mediation effect. First condition as in equation (1), the effect of X on Y denotes the total effect c. Second condition as in equation (2) the effect of X on M denotes the total effect a. Third condition as in equation (3) the effect of M on Y denotes the total effect of b. And, fourth condition as in equation (3) the indirect effect of X on Y denotes the total effect of c’. When the effect of X on Y decreases to zero with the inclusion of M, full mediation is said to have occurred [24] . When the effect of X on Y decreases by a nontrivial amount, but not to zero, partial mediation is said to have occurred. Two further assumptions of mediation were observed, first, the measurement was combined in a mean score summated scale as a remedy. Second, moderator variable was ascertain did not cause the dependent variable [22] .
Moderating effect analysis follows [25] and [26] suggested that independent variable (IV) and moderators are suggested to be centered or standardized. The analysis is done in a four-step process, first step observes the effect of control variables, followed by the IV, moderators and in the fourth step, the interaction terms (IV x moderator). Aiken and West [25] claimed that beta coefficient of the interaction terms were arbitrary whereby positive and negative beta did not justify moderated relationship without a post-hoc analysis. The post-hoc justifies the interaction effect on a 2x2 curves’ graph (IV on x-axis, DV on y-axis) showed by moderator curves (high and low curves) [25] . Both IV and moderators will be split into two dichotomous dimensions of high and low. Decision for interaction effect can be observed on the slope steepness of the curves, steeper slope explains more interaction of the moderator on the relationship [25,26] .
A. Descriptives
Most firms were represented by owners at 95.3% and smaller firms’ size [27] . The gender was female represented by 59% more than male. The age brackets were dominated by older respondents who are more than 40 years old represented more than 70%. Education background showed most representations were those finishing lower level education represented more than 85% than the college graduates. SMAEs entrepreneurs’ profile resembled the global entrepreneurship monitor (GEM) survey in Asian regions noted similar findings prevailed in developing economies [27] .
Firms’ demographics divided into five categories. First, BSMAEs type of business mostly represented by 70% were the manufacturers and processors. Second, 78.9% were the sole proprietor. Third, firms’ size according to number of employees 77.9% were those firms categorized as micro business that employed less than 5 workers. Fourth, firms’ cycle influence, 71% were those influenced by the cycle and the rest free from cyclical influence. And fifth, agriculture dependence and non-dependence were about equally represented. Dummy-coded control variables among the firm’s demographics showed some interesting effect on all performance and growth measures of the SMAEs.
B. Item, Factor, ANOVA and Discriminant Analysis
The item analysis produced six items showed mean value more than 4.00 on scale of 5.00. Most of the items were on 3.0 scales, and five items showed mean value less than 2.5. Eleven items showed their standard deviation less than 1.0 indicating the items parameter tend to concentrate around the mean. Item analysis for 29 EO items based on the three regional corridors under the study showed twelve of them were significantly different at p<.05.
Five factors loadings of EO sub-dimensions’ eigenvalue (in parantheses) namely the competitive aggressiveness (2.12), risk taking (1.73), autonomy (1.98), innovativeness (1.55) and product market innovativeness (1.51) explained BSMAEs in Iskandar development region (IDR) (KMO=.68, Bartlett’s =905.27, p<.01) shown in [Table-1] . NCER states’ BSMAEs (KMO=.72, Bartlett’s
=1062.27, p<.01) were explained by six EO dimensions eigenvalue, risk taking (2.83), competitive aggressiveness (2.67), product innovativeness (2.56), autonomy (2.67), market innovativeness (1.75) and proactiveness (1.62) as shown in Table 2. And EO in eastern growth corridor (ECER) (KMO=.72, Bartlett’s
= 1062.27, p<.01) showed that five factors explained their EO eigenvalues, market innovativeness (2.03), autonomy (2.03), product innovativeness (1.63), participative innovativeness (1.38) and proactiveness dimensions (1.45) as shown in [Table-3] .
SMAEs EO’s differences between the economic regions in Malaysia proved in one-way ANOVA that showed significant different among EO dimensions except innovativeness dimension (p=.12) that proved otherwise as shown in [Table-4] . More in-depth interrogation then utilized stepwise DA that ascertained only two dimensions of EO i.e autonomy and proactiveness were the main contributor to the discriminant functions. Wilk’s lambda = .95 of the discriminant function ( = 29.79, df = 4, p<.000) held significance for the whole model. Autonomy dimension was found to be the most important variable in explaining the discriminant function at Wilk’s lambda = .97 (F = 10.3, p<.01), followed by proactiveness dimension with Wilk’s lambda =.95 (F=4.8, p<.01). The classification result of DA where prediction of group membership using classification function coefficient was at 56.6 percent.
C. Control, Direct, Mediation and Moderation Effect - Multiple regression analysis (MRA)
Some dummy-coded control variables, EO, network and human capital directly explained firms’ growth, efficiency and effectiveness showed in the lower order beta coefficients at p<.05. Mediation effect was detected in two level MRA showed social networking as a significant mediator. The four step process proved that social network managed to reduce competitive aggressiveness relationship to effectiveness to a certain degree but not to zero, which justified social network as a partial mediator [22] as shown in [Table-5] and [Table-6] .
Moderation effect were done in two separate analysis. First, technology and strategy were found moderate EO–knowledge–network relationship. Second, perceived environmental factors moderate knowledge-network-performance relationship showed in higher order coefficient beta significant at p<.05 as shown in [Table-7] to [Table-10] . The findings conclude that some of the moderators were found interacted significantly on both relationship showed in simple slope 2x2 curves [25] .
Entrepreneurs representation proved typical nature of agro-based industry in Malaysia with feminine, older and lower educated entrepreneurs’ domination, however Cowling [29] found those variables varied in explaining entrepreneurship across countries.
The study justified first research question as to what extent does EO explains overall SMAEs and SMAEs in specific RGCs. Multidimensionality of EO dimensions were justified as claimed in [30] when all factors in the whole peninsular and RGCs were found somewhat stable. The analysis of 615 observations manage to reconfigure all IVs pertaining to Malaysian SMAEs that address the applicability of the strategic entrepreneurship concept [31] . Some EO dimensions proved critical in explaining the variance among the Malaysian RGCs, whereby each region needs different approach of EO development.
Second question justified in the direct, mediating and moderating effects among the variables under study. EO, knowledge and network are crucial for SMAEs growth, efficiency and effectiveness. Social network is pertinent in enhancing effectiveness when SMAEs exercise competitive aggressiveness. Fine-grained technology and strategic capabilities enhance knowledge-network when EO was employed. Perceived environmental factors enhance growth, efficiency and effectiveness in the presence of knowledge and network capabilities.
The study implies that entrepreneurial development policy need some reviews in present entrepreneurship development protocols in Malaysian Agro-based authorities as found in [32,33] .
Limitation of the study pertains only to areas on the peninsular, thus generalization does not encompasses SMAEs in Sabah and Sarawak. The study focuses on firm level analysis whereby general Bumiputera SMAEs are the unit analyzed.
Future studies shall emphasize on more antecedents and outcomes of strategic entrepreneurship concept that fit and sustain the Malaysian entrepreneurial firms’ development and their outcomes respectively. The study also should emphasize on the growing ventures phenomenon such as the entrepreneurial leadership under the domain of strategic leadership [28] .
The research was funded by the FRGS, a research scheme under the Malaysian Ministry of Higher Education (MOHE).
[1] Ireland R.D. (2007) Strategic Entrepreneurship Journal, 1(1-2), 7-10.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[2] Malaysia (2006) Economic Report 2007, Kuala Lumpur: Malaysian National Printers Bhd.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[3] Lumpkin G.T. and Dess G. G. (1996) Academy of Management Review, 21, 135-172.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[4] Miller D. (1983) Management Science, 29(7), 770 791.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[5] Covin J.G. and Slevin D.P. (1989) Strategic Management Journal, 1(10), 75-87.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[6] Dess G.G., Lumpkin G.T. and Covin J. G. (1997) Strategic Management Journal, 18(9), 677-695.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[7] Kreiser P.M., Marino L. D. and Weaver K. M. (2002) Entrepreneurship Theory and Practice, 26, 71-92.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[8] Drucker P.F. (1985) Innovation and Entrepreneurship:Practices and Principles. New York: Harper and Row.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[9] Wilklund J. (1999) Frontiers of Entrepreneurship Research [Online] Available: http://www.babson.edu/entrep/fer/paper98/IX/IX_E/IX_E_text.htm (1999, March 12).
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[10] Wilklund J. and Shepherd D. (2003) Strategic Management Journal, 24, 1307-1314.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[11] Oliviera M.M. (1999). In M.A. Hitt, P.G. Clifford, R.D. Nixon, & K.P. Coyne, (Eds.). Dynamic Strategic Resources: Development, Diffusion and Integration (pp.17-41). Chichester: John Wiley & Sons Ltd,.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[12] Hitt M.A., Clifford P.G., Nixon R.D. and Coyne K.P. (1999) Dynamic Strategic Resources: Development, Diffusion and Integration. Chichester: John Wiley & Sons Ltd.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[13] Zahra S.A. and Bogner W.C. (2000) Journal of Business Venturing, 15(2), 135-173.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[14] Miller D. and Friesen P.H. (1982) Strategic Management Journal, 3(1), 1-25.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[15] Murphy G.B., Trailer J.W. and Hill R. C. (1996) Journal of Business Research, 36,15-23.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[16] Dess G.G. and Robinson R. (1984) Strategic Management Journal, 5(3), 265-273.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[17] Mahoney T.A. and Weitzel W. (1969) Administrative Science Quarterly, 14(3), 357-365.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[18] Hair J.F., Anderson R.E., Tatham R.L. and Black W.C. (1989) Multivariate Data Analysis, 5th ed. New Jersey: Prentice-Hall Inc.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[19] Nunnally J. C. (1978) Psychometric Theory, 2nd ed. New York: McGraw-Hill.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[20] Hair J.F., Black W.C., Babin B.J., Anderson R.E. and Tatham R.L. (2006) Multivariate Data Analysis, 6th ed. New Jersey: Prentice- Hall Inc.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[21] Podsakoff P.M. and Organ D.W. (1986) Journal of Management, 12(4), 531-543.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[22] Baron R.M. and Kenny D.A. (1986) Journal of Personality and Social Psychology, 51(6), 1173-1182.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[23] Preacher K.J. and Hayes A.F. (2004) Behavior Research Methods, Instruments, & Computers, 36 (4), 717-731.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[24] James L.R. and Brett J.M. (1984) Journal of Applied Psychology, 69, 307- 321.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[25] Aiken L.S. and West S.G. (1991) Multiple Regression: Testing and Interpreting Interactions, Newbury Park: Sage Publications.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[26] Cohen J., Cohen P., West S. G. and Aiken L. S. (2003) Applied Multiple Regression/ Correlation Analysis for the behavioral Sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates, Publishers.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[27] Frederick H.H., Kuratko D.F. and Hodgetts, R.M. (2006) Entrepreneurship: Theory, process and practice (Asia-Pacific Edition). Victoria, Australia: Cengage Learning Pty. Ltd.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[28] Kuratko D.F. and Audretsch D.B. (2009) Entrepreneurship Theory & Practices, 33(1), 1-18.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[29] Cowling M. (2000) Applied Economic Letters, 7(12), 785.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[30] Covin J.G., Green K.M. and Slevin D.P. (2006) Entrepreneurship Theory & Practice, 57-81.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[31] Covin J.G. and Miles M.P. (1999) Entrepreneurship Theory & Practice, 23(3), 47-63.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[32] Awang A. (2006) Firms’ entrepreneurial orientation and performance of SMEs in Malaysia: the study of the moderating impact of some perceived environmental factors. University Sains Malaysia: Unpublished Doctoral Thesis.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
[33] Awang A., Said Ashgar A.R., & Subari K. A. (2006) SMEs Global Entrepreneurship Conference, Monash University Malaysia.
» CrossRef » Google Scholar » PubMed » DOAJ » CAS » Scopus
 | Table 1- Entrepreneurial Orientation (EO) Factor Analysis (IDR): n = 135 |
 | Table 2- EO factor analysis (NCER): n = 349, communality is in parantheses. |
 | Table 3- EO factor analysis (ECER): n = 131 |
 | Table 4- Analysis of Variance (ANOVA) of EO based on Region: |
 | Table 5– Direct Relationship between EO, Social Network and Effectiveness *p<.05, **p<.01. |
 | Table 6– The Mediating Effect of Social Network between EO and Effectiveness *p<.05, **p<.01. |
 | Table 7- Multiple Hierarchical Regression Analysis (Moderating impact of technology and strategy on EO-Human capital development relationship): n = 402, *p<.05, **p<.01. |
 | Table 8- Multiple Hierarchical Regression Analysis (Moderating impact of technology and strategy on EO-Tacit Knowledge relationship): n = 417, *p<.05, **p<.01. |
 | Table 9- Multiple Hierarchical Regression Analysis (Moderating impact of technology and strategy on EO-Strategic alliance relationship): n = 394, *p<.05, **p<.01. |
 | Table 10- Multiple Hierarchical Regression Analysis (Moderating impact of technology and strategy on EO-Social network relationship): n = 512, *p<.05, **p<.01. |