Academy of Strategic Management Journal (Print ISSN: 1544-1458; Online ISSN: 1939-6104)

Research Article: 2020 Vol: 19 Issue: 1

Digital Entrepreneurship as a Strategic Socioeconomical Enhancement Method for Communities

Zaleha Mohamad, Universiti Malaysia Terengganu

Muhammad Afiq Ahmad Khairuddin, Universiti Malaysia Terengganu

Mohd Nizam Lani, Universiti Malaysia Terengganu

Nur Munirah Zainuddin, Universiti Malaysia Terengganu

Ahmad Fadzil Ismail, International Islamic University

Rohana Ngah, Universiti Teknologi Mara

Azmah Che Abdullah, Usahanita Setiu

Abstract

Digital entrepreneurship has gotten its eyes around the globe with catalyst that consists of private and public relationships and global free market, the Digital Free Trade Zone (DFTZ) sets its base on Malaysia. Prior to this unique opportunity, this paper explains about the socioeconomic enhancement of the community in Kg. Telaga Papan, Setiu in the state of Terengganu with a test pilot questionnaire. From the data it is concluded by the linear regression model of the factors that taken account for, that the community shows particular interest of the strategic new market driven by digital entrepreneurs.

Keywords

Digital Entrepreneurship, Linear Regression Model, Strategic Management, Community-Based.

Introduction

Entrepreneurship is interpreted as a way of enhancing the business models through invention, vision and the power to evolve (Kuratko, 2003). Digital entrepreneur are defined as the person who brings a new horizon of the traditional business model via exploiting the fast paced information age (Zhao & Collier, 2016). In terms of global standings, Malaysia is given the privilege as the only Digital Free Trade Zone (DFTZ) outside the Republic of China as an initiative for amplifies Malaysia’s international e-commerce. This unique integration of SMEs with DFTZ and Royal Malaysian Customs Department as the stakeholder proved significantly well in their pilot program and Malaysian SMEs can now trade to United States of America for their traditional musical instruments, facilitating Malaysia’s 2025 goals (DFTZ, 2018).

Terengganu is a country in east coast Malaysia, rich in traditional and fisheries product, which gets to the state as a highly potential international market penetrate. Setiu selected as the district consists of 63,500 residents with the area covering 20,589.60 square hectare covering various of land, such as the beaches, farms and also wetlands (UPEN Terengganu, 2016). The focus of this paper is to determine whether the communities in Setiu are ready for digital changes in the entrepreneurial method for strategically enhance their socioeconomics in the near future.

Literature Review

Nonetheless, in postmodern business media, the concept digital revolution is becoming more and more universally used to symbolize the impactful or disruptive economic consequences of digital technologies for businesses (Boulton, 2018; De la Boutetière et al., 2018) and more broadly to reveal how existing companies may need to evolve massively in order to survive in the rapidly developing digital environment (McAfee & Brynjolfsson, 2017; Venkatraman, 2017; Salamzadeh & Kawamorita Kesim, 2015). Regarding this context, digital technologies are instigators of entrepreneurial activity (von Briel et al., 2018) and exist in multiple forms such as digital services or products (Lyytinen et al., 2016).

Basically, strategy can be interpret as a kind of consciously aware planned course of action or a collection of practical rules and guidelines for coping with a specific future situation or occurrence (Mintzberg, 1987). Entrepreneurship is often described as a contemporary feasible solution to worldwide socio-economic challenges such as wealth inequality (Bruton et al., 2013; Tedmanson et al., 2012). Strategic socioeconomical in digital entrepreneurship can be translating as a plan to improve the economic and social status of the individual by implement the digital entrepreneurship. In order to implement the digital, entrepreneur applies Maslow's Hierarchy of Needs which contributes to the foundation of the entrepreneurial drives. The model is focused on motivation to meet external and internal needs (Clark-Gill, 2016). Based on this theoretical, entrepreneur has motivation to fulfill in their desire in entrepreneurship, so that it comply the utilization of digital skill that need with expert by the entrepreneur despite their age barrier or status.

Methodology

31 pilot test respondents from Kampung Telaga Papan that includes in the territory of Chalok on the district of Setiu, Terengganu was given a questionnaire. The questionnaires constructed by 15 section that will focus on the relationship of demographical factor (age) as the dependent variable which influence the independent variable obtain new things on the internet and the increasing market impact of digital entrepreneurship (Figure 1). This research is needed in order to achieve how the digital entrepreneurship will be socioeconomical enhancement method for communities and entrepreneur.

Figure 1.Independent Variables And Dependent Variables For The Study.

One of the important aspects of the questionnaire is to prove that the hypothesis for the analysis is true or false. For our case, the hypothesis is described as below:

H1 There is a strong acceptance of digital entrepreneurship concept in the community of Kg. Telaga Papan.

H2 There are weak or no acceptance of digital entrepreneurship concept in the community of Kg. Telaga Papan.

If the first hypothesis, H1, accepted, and H2 rejected then we can conclude that the community in Telaga Papan, as representative of the Setiu district is already done or gone into changing state from traditional to digitalization entrepreneurship, where in other hand if H1 is rejected and H2 being accepted, it conclude the community of the district of Setiu is not yet ready for this new method of entrepreneurship.

For the descriptive analysis and inferential analysis part, we use Statistical Package for Social Science (SPSS) software as the medium to analyze the perception of the demographic by using F-test, ANOVA, correlations and regression analysis as a tool to prove the hypothesis above (Montgomery et al., 2012; Pallant, 2005).

Results and Discussion

For the result and discussion section, the presentation of the results will be in several sections that are the ANOVA Table 1, coefficient parameter and values and the linear regression model obtained.

The reason of ANOVA is used for this linear regression model, there are 2 types of model that can be deduced from the data that have the age of respondent is the dependent variable. For the analysis of variance Table 1 above we can see 2 possible outcomes of linear model, model 1 has significant level of 0.19 compared to 0.02 in model 2, rejecting model 2 due to the significant value is too low. Model 1 indicates that “OBTAIN NEW THINGS ON INTERNET” is the only factor that correlates highest between all other parameter. Thus model 1 is our best choice of model, and this is the proof to accept the H1 hypothesis.

Table 1: Anova Table Of Analysis
Model Sum of Squares Df Mean Square F Sig.
1 Regression 179.054 1 179.054 6.203 0.019a
Residual 865.914 30 28.864    
Total 1044.968 31      
2 Regression 370.167 2 185.083 7.954 0.002b
Residual 674.801 29 23.269    
Total 1044.968 31      
a. Predictors: (Constant), OBTAIN NEW THINGS ON INTERNET
b. Predictors: (Constant), OBTAIN NEW THINGS ON INTERNET, INCREASING MARKET IMPACT OF D.E
c. Dependent Variable: AGE OF RESPONDENT

Beta Coefficient (Constant and Excluded Variables) and Linear Regression

To construct the linear regression, we must first find the value of constant and variable coefficient first, and then compare the standardized coefficients to determine the importance of the variable to the dependent variable, in this case the age factor.

From the Table 2 above, we can conclude that there are 2 linear regression model is feasible with the current set of data, that is:

Table 2:  Beta Coefficient Determinaton Values
Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B
B Std. Error Beta Lower Bound Upper Bound
1 (Constant) 37.331 3.105   12.022 0.000 30.989 43.673
2 OBTAIN NEW THINGS ON INTERNET -1.902 0.764 -0.414 -2.491 0.019 -3.462 -0.342
3 (Constant) 32.240 3.306   9.752 0.000 25.478 39.001
4 OBTAIN NEW THINGS ON INTERNET -3.943 0.989 -0.858 -3.988 0.000 -5.965 -1.921
5 INCREASING MARKET IMPACT OF D.E 3.502 1.222 0.617 2.866 0.008 1.003 6.002

image

Where imageis the constant coefficient,image is the factor of obtaining new things on internet and imageis the factor of market increament impact of digital entrepreneurs to the society. The resultant model is as stated in equation below.

image

From the results above, there will be a negative valued trend on the first linear regression model as image andimage, and it is true that as the age is increases, there are more difficulties to the communites to search and obtain new findings on internet. In other hand the first linear regression shows rather high values of image terms in the first model rather than the second model. As for image there are an additional parameter that is being evaluated that is the increasing market impact perception effect of other digital entrepreneurs, it is shown as positive value and it shows that as the age of the community increases, they are more sensitive to market impact of the digital entrepreneurs have done, presumeably the global and fast moving marketing making the traditional entrepreneurs in Setiu felt the impact significantly.

Conclusion

As conclusion, for this pilot tests, there must be a significant impact of digital entrepreneurship, in a sense of marketing that the communities of Setiu felt the impact greatly, suppressing the other factors except the accessability of information on internet factor. The hypothesis is accepted that the socioeconomics of Setiu has high impact on strategic development in the future, and the factor is digital entrepreneurship. In other hand, the youth people tend to cope the digital entrepreneurship concept more thoroughly then the older people,that is the start of declining of 33 to 34 years old of age.

Acknowledgement

This paper is under the patronage of Knowledge Transfer Assimilation Grant (KTAG) of Universiti Malaysia Terengganu. Vote No:58901& 58902.

References