Cytalist

50 Demographic Profile of Respondents Table 2 provides the demographic profile of respondents. Intentionally, the demographic profile section only highlights three items: gender, age, and education. The total number of respondents was two hundred. Among the respondents, there were more females (70.0%) than males. The top three age groups included those 21-30 years old (58.5%), 31-40 years old (29.0%), and 41-50 years old (7.5%). Finally, the top three education groups included undergraduate or equivalent (58.0%), senior high school (36.5%), and junior high school or below (3.5%). Table 2. Demographic Profile of Respondents Demographic Profile Frequency Percentage (%) Gender Male 60 30.0 Female 140 70.0 Total 200 Age (in years) < 21 8 4.0 21 – 30 117 58.5 31 – 40 58 29.0 41 – 50 15 7.5 > 50 2 1.0 Total 200 100 Education Junior high school or below 7 3.5 Senior high school 73 36.5 Undergraduate or equivalent 116 58.0 Above undergraduate 4 2.0 Total 200 100 Correlation Matrix The next stage in EFA is to develop a correlation matrix. Figure 2. Abridged Correlation Maxtrix among Variables (Question Items)

51 It is important to create a correlation matrix at an early stage of EFA. A correlation matrix could be simply defined as correlations among variables (items) of the study. According to Allen, Tisworth, and Hunt (2009), variables must be correlated to some extent to justify the use of EFA. They further recommend that correlations among variables should be at least 0.30. The original correlation matrix was too large due to a large number of variables (items). Thus, an abridged correlation matrix is presented above (Figure 2). In short, twenty-seven variables are significantly correlated. However, two items were deleted: Q 4.2 and Q 4.6, because they are not related with most other items. This left twenty-five items. Kaiser-Meyer-Olkin (KMO) Test and Bartlett’s Test of Sphericity The Kaiser-Meyer-Olkin (KMO) test is to check the sample’s adequacy for factor analysis. According to Williams, Onsman, and Brown (2010), if KMO ranges closer to 1 (0 being the lowest), it implies that the pattern correlations are compact. Given that the computed KMO value was 0.91, it could be concluded that the pattern correlations are adequately compact. Therefore, the sample data for this research is suitable for EFA. The null hypothesis for Bartlett’s Test of Sphericity proposes that variables are not correlated. The results obtained here led to the rejection of the hypothesis based on a Chi-square (χ 2 ) value of 1254.17 (df = 10, p-value (0.000) < 0.001). This implies that sample data was adequately correlated. This means the data are suitable for EFA, meaning that the questionnaire items are factorable. In short, both the KMO test and Bartlett’s Test of Sphericity indicated that EFA is appropriate. Thus, the analysis could realistically proceed to the next EFA stages. Very Simple Structure Analysis (VSS) Very simple structure (VSS) analysis is a function available on the psychology package (Revelle, 2017). The purpose of this analysis is to determine the number of factors that might be extracted. Based on Figure 3, the number factors that should be extracted was four. This solution will be compared against a parallel analysis in the next section. Figure 3. Number of Factors to Be Extracted, Recommended by VSS Parallel Analysis Scree Plot A parallel analysis scree plot is available in the R package. It produces three critical lines according to the legend of Figure 4: FA Actual Data, FA Simulated Data, and FA Resampled Data.

52 Figure 4. Scree Plot and Parallel Analysis The way to interpret Figure 4 is to count the number of small triangles from top to bottom before the FA actual data and FA simulated data lines are reached. Based on Figure 4, four small triangles could be counted before reaching the simulated and resampled lines. Thus, it could be concluded that the parallel analysis scree plots has extracted four factors. This is consistent with the analysis that was conducted by VSS above. Extraction and Rotation The extraction method used was Ordinary Least Squared, an extraction method in the R Package. The rotation method used was Oblimin, a default rotation method for the R Package. Factors Underlying the Decision to Rent Space (DTRS) Figure 5 and Table 3 (please see following pages) summarize factors extracted and retained, along with factor indicators. Figure 5 has four important components. From left to right, the first component notations (Q 1.1 to Q 4.8) includes indicators of the four individual factors. The second component includes factor loadings for all four factors, and the third component includes factors. Finally, the fourth component includes correlations among factors. The correlations among the factors are adequately correlated (all above 0.30). Table 3 summarizes the factor loadings and the variance percentages of individual factors contributing to the EFA model. Finally, SS or Sum Squared loadings (eigenvalues in other packages) are also included.

53 Indicators Loadings Factors Correlations Figure 5. Factors and Indicators Underlying the DTRS Construct Discussion As stated at the paper’s introduction, two problems were identified. First, few studies have investigated factors underlying decisions to rent shop space (construct). Secondly, these few studies employed descriptive statistics to analyse the data. This research began by proposing a conceptual model based upon the existing literature. Based on this model, a questionnaire was developed. To ensure the quality of the questionnaire, it went through recognized development procedures. This research proposed that there are four factors underlying rental decisions: SPAC, PRIC, MARK, and PHYS. These four factors are latent variables. This study used exploratory factor analysis available in the R Package to explore factors underlying the DTRS construct and identified their respective indicators. Four basic factors were identified, along with their appropriate indicators. Table 3. Indicators, Factors, Factor Loadings, Percent of Variance, SS Loadings Indicators Factors (1) SPAC (2) PRIC (3) MARK (4) PHYS Q 1.1 .678 Q 1.2 .717 Q 1.3 .646 Q 1.4 .705 Q 1.5 .604

54 Table 3. Indicators, Factors, Factor Loadings, Percent of Variance, SS Loadings (Cont.) Indicators Factors (1) SPAC (2) PRIC (3) MARK (4) PHYS Q 2.1 .673 Q 2.2 .793 Q 2.3 .790 Q 2.4 .603 Q 2.5 .696 Q 3.3 .821 Q 3.4 .794 Q 3.5 .737 Q 3.6 .653 Q 3.7 .645 Q 4.1 .566 Q 4.3 .542 Q 4.4 .752 Q 4.5 .748 Q 4.7 .576 Q 4.8 .606 Percent of Variance 11.100 11.200 13.400 11.800 SS Loadings 2.787 2.801 3.350 2.941 A correlation matrix was developed to ensure that variables (indicators) were adequately correlated. The KMO test and Bartlett’s Test of Sphericity were carried out to see whether EFA was suitable, and this was confirmed. The number of factors to be retained was assessed through the VSS function in R Package, and four factors were selected by the VSS function. A similar result was obtained by applying the parallel analysis scree plot available in the R Package. Hence, four factors along with their indicators were retained. Thus, the two major problems identified at the introduction were resolved. Conclusions The purpose of this research study was to explore the factors underlying the decision to rent space (DTRS), and this objective was achieved. Four factors (SPAC, PRIC, MARK, and PHYS) were identified along with their respective indicators. In terms of theoretical contributions, this research adds to a body of literature on the topic under study. In terms of practical contributions, this study helps the management of shopping centers to gain insights into the critical factors underlying decisions to rent. Thus, it is strongly recommended that they pay attention to the critical factors (SPACE, PRIC, MARK, and PHYS) because these play a significant role in shop tenants’ decisions to rent space. Of course, the decision to rent space is obviously related to shopping centers’ occupancy rate. In terms of pedagogy, this paper also contributes to a growing body of literature on the use of the R Package. In terms of further research, it is recommended that second-order confirmatory factor analysis (CFA) be carried out to ensure the robustness of the model discovered in this study.

55 Acknowledgements First of all, I would like to thank the shop tenants at Terminal 21 who provided useful information for this research. I would also like to thank the Management Research Unit, Mahasarakham Business School, Mahasarakham University, for enthusiastically supporting my research. About the Author Gamon Savatsomboon is a Lecturer at Mahasarakham Business School, Mahasarakham University, Thailand. Email: [email protected] References Allen, M., Titsworth, S., & Hunt, S. (2009). Quantitative research in communication. Hoboken, Thousand Oaks, California: Sage Publications, Inc. Becker, J., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: Guidelines for using reflective-formative type models. Long Range Planning, 45(5-6), 359-394. Bello, V. (2012). The determinants of shopping center rent in Akure, Nigeria. Paper presented at the meeting of the FIG Working Week 2012, Rome: Italy. Cohen, H. (2011). 72 marketing definitions. Actionable Marketing Guide. Retrieved from http://heidicohen.com/marketing-definition/. CBRE Thailand. (2016). Slow retail sales delay new retail project launches. Retrieved from https://www.cbre.co.th/en/ResearchCentre/Research/Bangkok-Retail-MarketView-Q1-2016. Hee, O. (2014). Validity and reliability of the customer-behavior scale in the health tourism hospitals in Malaysia. International Journal of Caring Sciences, 7(3), 771-775. Retrieved from http://www.internationaljournalofcaringsciences.org/docs/10.Hee%20ORIGINAL.pdf. Hollins, P. (2017). The science of intelligent decision making: how to think more clearly, save your time, and maximize your happiness. Destroy indecision! US: Create Space Independent Publishing Platform. Nasir, N., Jusoh, N., Ramin, A. & Yee, N. (2013). Determinants of tenants’ satisfaction: a case study in XXX Parade, Muar. In 2 nd International Conference on Technology Management, Business and Entrepreneurship, Melaka, Malaysia. Retrieved from http://eprints.uthm.edu.my/5085/1/ Determinants_of_Tenants%E2%80%99_Satisfation.pdf Kaluzny, J., Nitsche, R., & Roller, L.H. (2011). Defining product markets for shopping centers: Thoughts on methodological choices. ESMT White Paper No. WP-11-02. List of shopping malls in Thailand. (n.d.). Wikipedia. Retrieved May 31, 2018, from https://en.wikipedia.org/wiki/List_of_shopping_malls_in_Thailand Maenthong, N., & Tochaiwat, K. (2013). The factors affecting the decisions to rent shopping center areas of the Entrepreneurs. Paper presented at the Build Environment Research Associate Conference, BERAC 4, Faculty of Architecture and Planning, Thammasat University. Revelle, W. (2017). Psych: Procedures for personality and psychological research. Retrieved from https://www.scholars.northwestern.edu/en/publications/psych-procedures-for-personalityand-psychological-research. Sujatha, V., & Priya, B. (2015). Factors determining tenants’ satisfaction in shopping malls at Chennai City. Indian Journal of Research, 4(4), 4-6. Retrieved from https://www. worldwidejournals.com/paripex/file.php?val=April_2015_1430371171__120.pdf. Williams, B, Onsman, A., & Brown, T. (2010). Exploratory factor analysis: a five-step guide for novices. Journal of Emergency Primary Health Care, 8(3), 1-13. Retrieved from https://ajp.paramedics.org/index.php/ajp/article/viewFile/93/90.

Catalyst ISSN 2408-137X, Volume 18, 2018 56 Understanding Consumers’ Mobile Banking Adoption in Germany: An Integrated Technology Readiness and Acceptance Model (TRAM) Perspective Roshan Khadka and Phanasan Kohsuwan Abstract Today, more than a billion of the world’s population have access to mobile banking (KPMG, 2015). While people are embracing mobile banking services in their daily lives, the investigation of mobile banking from a behavioral perspective is a mystifying topic for research study. The purpose of this study is to propose and examine an integrated theoretical model to better understand consumer behavior regarding mobile banking adoption in Germany. This study integrates the multidimensional psychographic constructs of Technology Readiness Index (TRI) and the Technology Acceptance Model (TAM) with consequent consumer satisfaction and loyalty to provide a robust integrated framework of mobile banking adoption processes. Confirmatory factor analysis and structural equation modeling were employed to meticulously test the validation of constructs and their interrelationship with each other. The findings reveal that the Technology Readiness and Acceptance Model (TRAM) variables have a significant influence on adoption of mobile banking technology in Germany. The study concludes with a discussion on practical implications of the research across similar service providers, and suggests further research to improve their marketing and servicing strategies. Keywords: Mobile banking, Technology Readiness Index (TRI), Technology Acceptance Model (TAM), Technology Readiness and Acceptance Model (TRAM), Customer Satisfaction, and Customer Loyalty Introduction The development of virtual technology has challenged banking and financial institutions to shift their channels from conventional banking to digital banking. With advancements in the telecommunication industry, contemporary banking and financial organizations are leveraging from smartphones and internet connectivity. Smartphones and the internet have enabled consumers to efficiently manage tasks with simple clicks and communications, ultimately saving time and enabling consumers to devote more time for other activities. Mobile banking is a financial channel offered to consumers to access banking services using a mobile device with the aid of a telecommunication network. It evolved in Germany during the late 1990’s, when Deutsche Bank introduced the service in collaboration with a German tech company called Paybox (Shaikh & Karjaluoto, 2014). Today, millions of consumers simply login to the mobile banking site of banks or just send an instant text message to conduct a transaction. The 24/7 access to smart phones and improvement of internet connectivity in the telecommunication sector has supported the growing adoption of mobile banking services. According to a KPMG mobile banking report (2015), approximately 1.1 billion people in the world are using mobile banking services, and usage is increasing every year. Financial firms around the world are aiming to tap a growing market segment that provides promising opportunities for further advancement. The United States is the market leader in financial technologies, with a market size of 13.8 billion euros, followed by the United Kingdom and Germany, putting together a shared market size of 11.3 billion euros, or 8.9 billion euros and 2.4 billion euro respectively (EY, 2016). This study focusing on the world’s third largest mobile banking market, Germany, may provide a better understanding of this subject matter. It integrates multidimensional psychographic information regarding a construct known as the Technology Readiness Index (TRI) (i.e. Optimism, Innovativeness, Insecurity and Discomfort) and users' acceptance and usage of technology known as the Technology Acceptance Model (TAM) (i.e. Perceived Usefulness, Perceived Ease of Use, and Actual Usage) with consequent consumer satisfaction and loyalty to provide a robust integrated framework of mobile banking adoption processes.

57 Significance of the Study This study focused on the world’s third largest mobile banking market, Germany, and helps to provide a better understanding of this subject matter. The research investigation uses multiple dimensions of a modified Technology Readiness and Acceptance model (with the integration of satisfaction and loyalty) to assess mobile banking adoption behavior among actual adopters. It aims to bring holistic insights from consumers’ viewpoints precisely on the factors that influence the adoption of mobile banking in Germany. The objective of the study is to test and deliver an integrated model, which provides a better understanding of adoption of mobile banking, revealing existing barriers and drivers from a consumer’s perspective. Literature Review Background Mobile banking is a self-service technology application which has brought dramatic transformation in the way banks build and maintain relationships with their customers (Mols, 2000). Mobile banking allows consumers to connect to a financial organization and view account balances, transfer funds between accounts, pay bills, or receive accounting alerts. Payments commenced in physical or virtual worlds can be made via Short Message Service (SMS), Multimedia Messaging Service (MMS), mobile Internet, software application, or Near Field Communication (NFC) chips (McGuire & Crowe, 2008). Looking at the past two decades, technology has evolved by inclusion or replacement of other related technologies. The expansion of mobile banking has had a great impact on the banking industry. Banking services have gone through drastic changes starting from the early 1980s when telephone and computer banking became prominent and progressed towards automated teller machines (ATM) and internet banking facilities. Today, electronic banking is at its peak with the transformation brought by mobile technologies such as SMS, Wireless Application Protocol (WAP), Third Generation (3G) and Fourth Generation (4G) technologies (Laukanen, Sinkkonen, Laukkanen, & Kivijarvi, 2008). TAM (Technology Acceptance Model) The TAM model proposed by Davis (1989) is one of the most widely accepted models to describe and understand how end users make decisions to use technology products or services (Chau & Hu, 2001; Svendsen, Johnsen, Sorensen, & Vitterso, 2013). TAM has been applied to a wide range of research studies to understand consumer behavior and adoption of technology, including products such as internet banking (Al-Ajam & Nor, 2013), mobile financial services (Lee, Park, Chung, & Blakeney, 2012), mobile advertising (Zhang & Mao, 2008), e-commerce (McCloskey, 2004), 3G mobile value-added services (Kuo & Yen, 2009) and many more. According to TAM, two cognitive variables, perceived ease of use and perceived usefulness, are the critical factors that determine the consumers’ choice. Perceived usefulness can be explained as the extent to which an individual or organization believes that the application of technology will improve their performance (Davis, 1989). Perceived ease of use can be defined as the extent to which an individual or organization believes that application of technology will be effortless (Davis, 1989). Further, TAM hypothesizes that perceived ease of use contributes to perceived usefulness due to saved effort. According to Davis, the perceived characteristics are expected to influence intentions to use a system, which in turn influence actual system usage. Moreover, perceived ease of use is assumed to affect a user’s perception regarding perceived usefulness. This hypothesis follows from the logic that improvements in ease of use of a system contribute to increased usefulness due to saved effort (Davis, 1989). Technology Readiness Index (TRI) The Technology Readiness Index (TRI) was developed through a wide-ranging multiphase research program in the United States. Research has found a positive relationship between technology readiness (TR) scores and technology-related behavior pertaining to the ownership, usage, and desirability of using technology (Parasuraman, 2000). TRI replication in Great Britain has further strengthened the soundness of the index. According to Parasuraman (2000), Technology Readiness

58 refers to people's propensity to embrace and accept new technologies to realize goals in home life and at work. It is determined by the positive and negative technology-related beliefs of people. These beliefs of technology users can be characterized under four principle dimensions: optimism, innovativeness, discomfort, and insecurity (Parasuraman, 2000). Optimism is users’ confident view regarding a technology and a belief that it amplifies control, adaptability, and efficacy in their lives (Parasuraman & Colby, 2001). Innovativeness is the propensity of an individual to be a pioneer and thought leader in technology (Parasuraman & Colby, 2001). Discomfort is "a perceived lack of control over technology and a feeling of being overwhelmed by it" (Parasuraman & Colby, 2001, p. 41). Insecurity is "a distrust of technology and skepticism about its ability to work properly" (Parasuraman & Colby, 2001, p. 44). Research outcomes confirm that each of the four dimensions are independent and significantly influence the technological readiness of an individual. Technology Readiness and Acceptance Model (TRAM) The Technology Readiness and Acceptance Model (TRAM) is an integration of TRI and TAM. Lin, Shih, Sher & Wang (2005) initially presented TRAM, which incorporates the general dimensions of TRI with system specific dimensions of TAM to explain how these can influence individual interactions, experiences, and usage of the new technology. Initially when integrating TRI and TAM, the technology readiness index was tested as a predictor of TAM (Lin et al., 2005). In recent studies, dimensions of TRI are directly connected with the dimensions of TAM (perceived usefulness and perceived ease of use), resulting in a more detailed model (Walczuch, Lemmink, & Streukens, 2007). The optimism and innovativeness dimensions are assumed to increase perceived usefulness and ease of use of particular technology, while the insecurity and discomfort aspects limit the dimensions of TAM (Parasuraman & Colby, 2001) Satisfaction and Loyalty When a consumer accepts and uses an innovative product/service, the perception after consumption should drive the evaluation of product/service performance (Bailey & Pearson, 1983). Thus, satisfaction and loyalty has been integrated in the research study to observe performance of mobile banking services and its influence on behavior of mobile banking adopters in Germany. Satisfaction is the marketing concept that has been proven as a good indicator to measure and predict the future purchasing behavior of consumers (McQuitty, Finn, & Wiley, 2000). According to Kotler and Armstrong (1996), satisfaction is a sentiment derived from the evaluation process of what has been perceived against what was expected from the purchase decision itself, also considering needs and wants associated with the purchase. Previous studies have proven that consumer satisfaction safeguards future revenues (Fornell, 1992; Bolton, 1998), eases future transaction costs (Reichheld & Sasser, 1990), minimizes price elasticity (Anderson, 1996), and diminishes the probability of consumers discarding the product or service if quality falters (Anderson and Sullivan, 1993). On the other hand, Oliver (1987) and Nyer (1999) found that dissatisfied consumers are inclined to complain to organizations, and recall cognitive dissonance and bad consumption experiences with the product. According to Oliver (1999), loyalty is a deeply held commitment for consistent repurchase or to re-patronize a preferable product/service that repeatedly leads to purchase of the same brand despite any situational influence on marketing efforts. Satisfied consumers can be lost to competitors due to indifference which might arise from pure neglect (Clemes, Gan, Kao, & Choong, 2008). However, a loyal consumer base ensures continuity of sales and benefits for the organization. Today, banks and financial companies’ product offerings are evolving to satisfy and retain their consumers. Winning consumers with marketing campaigns is expensive, while retaining existing consumers and building a loyal consumer base allows them to reduce the customer acquirement cost. Relationship of Research Variables and Hypothesis – TRI and TAM Individuals who have an optimistic and innovative orientation to technology are supposed to embrace positive attitudes to new technology and technological use. Thus, it is reasonable to

59 hypothesize optimism and innovativeness as an enabler which has a positive influence on how individuals perceive and relate to new technology (Parasuraman & Colby, 2001; Tsikriktsis, 2004). On the contrary, emotions associated with insecurity towards technology lead to ambiguity and low usage of the technology (Parasuraman & Colby, 2001; Tsikriktsis, 2004). Hence, this study has assumed insecurity as the restraint, which induces lower levels of perceived usefulness and perceived ease of use. In addition, technology that creates unmanageable systems is not user-friendly, and hence discomfort is anticipated which would affect ease of use (Parasuraman & Colby, 2001; Tsikriktsis, 2004). Thus, based on above discussions, this study hypothesized that: H1A: The Optimism dimension of TRI has a positive influence on Perceived Usefulness of mobile banking service among consumers in Germany. H1B: The Innovativeness dimension of TRI has a positive influence on Perceived Usefulness of mobile banking service among consumers in Germany. H1C: The Insecurity dimension of TRI has a negative influence on Perceived Usefulness of mobile banking service among consumers in Germany. H1D: The Discomfort dimension of TRI has a negative influence on Perceived Usefulness of mobile banking service among consumers in Germany. H2A: The Optimism dimension of TRI has a positive influence on Perceived Ease of Use of mobile banking service among consumers in Germany. H2B: The Innovativeness dimension of TRI has a positive influence on Perceived Ease of Use of mobile banking service among consumers in Germany. H2C: The Insecurity dimension of TRI has a negative influence on Perceived Ease of Use of mobile banking service among consumers in Germany. H2D: The Discomfort dimension of TRI has a negative influence on Perceived Ease of Use of mobile banking service among consumers in Germany. Perceived Ease of Use and Perceived Usefulness of TAM Previous research studies have shown that higher perceived ease of use increases the perceived usefulness of applications (King & He, 2006; Lin et al., 2005; McFarland & Hamilton, 2006; Schepers & Wetzels, 2007; Venkatesh & Davis, 2000). Thus, based on these previous studies, the following statement is hypothesized: H3: Perceived Ease of Use has a positive influence on Perceived Usefulness of mobile banking service among consumers in Germany. Perceived Usefulness and Satisfaction According to Doll & Torkzadeh (1988), when users perceive ease of use of a computing system, users are most likely to feel satisfied. Similarly, Devaraj, Fan, & Kohli’s (2002) study on e-commerce concluded that both perceived usefulness and perceived ease of use have an influence on user satisfaction with e-commerce. In a study of an information system at a university, Rai, Lang, & Welker (2002) found that information quality, perceived ease of use, and perceived usefulness influenced user satisfaction. Thus, this study hypothesized that: H4A: The Perceived Usefulness dimension of TAM has a positive influence on Satisfaction among mobile banking consumers in Germany. H4B: The Perceived Ease of Use dimension of TAM has a positive influence on Satisfaction, among mobile banking consumers in Germany. Satisfaction and Loyalty Consumer loyalty is largely determined by consumer satisfaction (Anderson, Fornell, & Lehmann, 1994). When satisfaction among consumers increases, they are more likely to recommend

60 the product/service, are less likely to switch to substitutes, and are more likely to repurchase the product/service in the near future (Russell-Bennett & Rundle-Thiele, 2005: Sivadas & Baker Prewitt, 2000). Thus, this study hypothesized that: H5: Satisfaction among mobile banking consumers in Germany has a positive influence on Loyalty. Based upon the above discussion, a theoretical model (Figure 1) for the study is derived showing all the hypotheses. The model consists of eight variables to investigate the adoption process of mobile banking in Germany. Figure 1. Theoretical Framework (adapted from Parasuraman, 2000; Davis, 1989) Methodology Sample and Data Collection For the research purpose, respondents were selected from Germany – the world’s third largest mobile banking market; as such, investigation could provide better insights on the subject matter. The portion of the populace living in Germany were considered as the study’s population. The respondents for the study are actual mobile banking adopters rather than individuals who are intending to adopt the technology, as the information gained from non-adaptors could not be based upon their real experience. The minimum sample size of 400 was calculated by using Yamane’s (1973) formula with a 95 percent confidence level. However, to maintain the reliability of the data, the study’s sample size was increased to 412 persons. According to Sue and Ritter (2007), an online survey is an appropriate choice to conduct the study when sample population is large and widely dispersed geographically. Non-probability sampling – or more precisely – a web-based, self-selected online survey was used. In a self-selected online survey, questionnaire links are sent to target populations and respondents have a choice regarding their inclusion as part of the sample for a study (Callegaro, Manfreda, & Vehovar, 2015). It is a form of convenience sampling which facilitates access to information from people of the target group who are out of reach because of geographical and demographic challenges (Hughes, 2012). The online survey was organized through Google Docs survey tool, the Google Form. A questionnaire was developed and distributed in the English language. To ensure the survey was completed by the targeted group, firstly people were informed about the research with a short description in the questionnaire. They were instructed to proceed only if they have used German mobile banking services. Accessibility to the internet has created more prospects for large numbers of respondents

61 (White & McBurney, 2012). The questionnaire was distributed via the internet on Facebook groups and forums that specifically address people living in Germany. The data from online surveys was collected from December 2016 to January 2017. Measures The questionnaire for the study was separated into three sections: demographic information, technology readiness and acceptance, and user satisfaction and loyalty. The questionnaire consists of 16 questions. Eight constructs of the research model were measured with a total of 60 scale items (36 items for four dimensions of TRI, 12 items for two variables of TAM, 5 items for satisfaction, and 7 items for the loyalty construct). The items of each construct were measured using a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Analysis Techniques Firstly, a reliability analysis of the scale items was conducted using Cronbach’s alpha test. Secondly, the validity of the questionnaires was measured utilizing factor analysis. And finally, a Structural Equation Modeling (SEM) technique was applied to examine the theoretical framework and hypotheses of this study. Data Analysis The majority of respondents (41.75%) were 21-30 years old, followed by those who were between 31-40 years old (33.74%). Respondents under 21 years old accounted for 13.83 percent of the total, followed by those between 41-50 years old (9.95%) and those over 50 years old (0.73%). The majority of respondents (61.89%) were male, while 38.11 percent were female. The study utilized Cronbach’s alpha to test scale reliability. The Cronbach’s alpha value of all constructs were within the range of 0.714 to 0.839. To assure internal consistency of scales, Cronbach’s alpha value must be above 0.70 (Bagozzi, 1994; DeVellis, 2012; George & Mallery, 2003; Hair et. al, 2010; Kline, 2000). Hence, all constructs in the research framework are acceptable in terms of internal consistency. The Kaiser-Meyer-Oklin (KMO) Test was employed to assess the data’s suitability for factor analysis. For sampling adequacy, the KMO value should be either 0.6 or above, along with a significant result from Bartlett’s Test of Sphericity of less than 0.05. Both the KMO and Bartlett’s test results showed that the survey data obtained were both adequate and significant. Further, to ensure normal distribution, normalization testing was performed. According to George and Mallery (2010), values for asymmetry and kurtosis of between -2 and +2 are considered acceptable to prove the normal univariate distribution of data. The results of normality testing showed that out of 60 items, 56 data items had a skewness and kurtosis value between -2 and +2, and so further analysis was not performed. Utilizing Principal Component analysis with the Promax rotation method, Exploratory Factor Analysis was conducted with all related items. The analysis revealed three items with low factor loadings, which were carefully considered for further analysis. All other scale items ranged from between 0.536 to 0.99, which were above the recommended level of 0.5 (Hair et al., 2010). Finally, to assess the data’s convergent and composite validity, Average Variance Explained (AVE) and Composite Reliability (CR) were calculated utilizing the factor loadings of each item. According to Fornell and Larcker (1981), AVE should be above 0.50, and CR should be above 0.70 to assure convergent and composite validity of the data. Results from these criteria for AVE and CR were achieved for all constructs except for Innovativeness, which had an AVE value of 0.49 that was rounded up to a numerical value of 0.50. Confirmatory factor analysis (CFA) was conducted to test constructs of the proposed theoretical framework utilizing the maximum likelihood technique. CFA and SEM can be an iterative procedure when modifications are indicated in the initial results, and parameter constraints are altered to improve the fit of the model (Schreiber, Stage, King, Nora, & Barlow, 2006). Hence, a few original scale items were removed from the constructs to obtain acceptable results for the model. A

62 summary of the modified CFA results is shown in Table 1, which indicates that all constructs fit well within the measurement model, and was established as a critical precondition for the validity of following the Structural Model Estimations. Table 1. Summary of Refined Confirmatory Factor Analysis Developed for Research Study Variables χ2/df GFI NFI RFI IFI TLI CFI RMR RMSEA Criteria < 3 >.90 >.80 >.80 >.80 >.90 >.90 <.080 <.080 Optimism 0.00 1.00 1.00 _ 1.00 _ 1.00 0.00 0.73 Innovativeness 0.00 1.00 1.00 _ 1.00 _ 1.00 0.00 0.05 Discomfort 0.19 1.00 0.99 0.99 1.003 1.01 1.00 0.00 0.00 Insecurity 0.00 1.00 1.00 _ 1.00 _ 1.00 0.00 0.66 Perceived Usefulness 0.00 1.00 1.00 _ 1.00 _ 1.00 0.00 0.71 Perceived Ease of Use 0.89 0.99 0.99 0.99 1.00 1.00 1.00 0.005 0.00 Satisfaction 0.00 1.00 1.00 _ 1.00 _ 1.00 0.00 0.04 Loyalty 0.00 1.00 1.00 _ 1.00 _ 1.00 0.00 0.47 Note. Key to abbreviations: Degrees of Freedom (df), Goodness of Fit Index (GFI), Normed Fit Index (NFI), Relative Fit Index (RFI), Incremental Fit Index (IFI), Tucker-Lewis Index (TLI), Comparative Fit Index (CFI), Root Mean Residual (RMR), and Root Mean Square Error of Approximation (RMSEA) All constructs in the research framework of the study were tested to establish whether the proposed model can predict the adoption of mobile banking services in Germany. The Goodness of Fit (GOF) of the model was tested along with the hypothesized paths between research variables. The research framework generated a sufficient Chi-square to degree of freedom ratio (χ2/df) i.e. 2.62, which was below the threshold of 3.0. The model also generated acceptable values for GFI, Adjusted Goodness of Fit Index (AGFI), CFI, NFI, RMR and RMSEA measures, i.e., 0.906, 0.874, 0.913, 0.868, 0.016 and 0.063 respectively (Figure 2). According to Holye (1995), the GFI and CFI values should be at or above 0.90. Further, he mentioned that the value of AGFI and NFI for goodness of fit has to be just 0.80 or above. Similarly, the values of RMR and RMSEA are acceptable as a good fit up to 0.08 (Hair et al., 1998). Analyzing the result of goodness of fit indices, the theoretical model of the study can be considered as a good fit, which is a reasonable fit to the real-world data. Figure 2. Structural Model Developed from This Research Study

63 The standardized path coefficients and their critical ratios (t-values) were used to examine the hypothesized paths, and vice-versa. The cut-off level of more than 1.96, along with a p-value of less than 0.05, is recommended to achieve a statistically significant hypothesis (Chin, 1998). The results showed that the Optimism dimension of TRI had a positive influence on Perceived Usefulness (β=0.35, t-value=5.28, p<0.001), and the Discomfort dimension of TRI had a negative influence on Perceived Usefulness (β=-.22, t-value=-3.20, p<0.05). The Innovativeness dimension had a positive influence on Perceived Ease of Use (β=0.35, t-value=5.28, p<0.05), while the Perceived Ease of Use had a positive influence on Perceived Usefulness (β=0.13, t-value=5.28, p<0.001). The Perceived Usefulness dimension of TAM had a positive influence on Satisfaction (β=0.26, t-value=4.05, p<0.001), and it was also confirmed that satisfaction level of the mobile banking consumers in Germany had a positive influence on Loyalty (β=1, t-value=5.28, p<0.001). Thus, hypotheses H1A, H1D, H2, H3, H4A and H5 were supported. The results are portrayed in Table 2. Discussion The current study shows that there is a high level of relevancy among the TRI and TAM dimensions. Further, users’ personality dimensions from TRI like Optimism, Innovativeness, and Discomfort were found to have a significant indirect influence on satisfaction and loyalty levels among German mobile banking consumers. In the case of TAM, Perceived Usefulness had a direct – and Perceived Ease of Use had an indirect – influence upon the satisfaction and loyalty levels of German mobile banking consumers. Table 2. Summary of Hypotheses Tests Developed from SEM Analysis The assessment of relationships between TRI dimensions and Perceived Usefulness revealed that the Optimism and Discomfort dimensions of TRI have a significant influence on Perceived Usefulness. Although, the Innovativeness dimension of TRI did not have a significant influence on Perceived Usefulness of mobile banking, it had an indirect influence on Perceived Usefulness when mediated through Perceived Ease of Use of mobile banking services. Hypothesized Path Standardized Coefficients(β) C.R. (t-value) Results H1 A. Optimism → Perceived Usefulness B. Innovativeness → Perceived Usefulness C. Discomfort → Perceived Usefulness D. Insecurity → Perceived Usefulness 0.35 -0.37 -0.22 -0.07 5.28* -1.87 -3.20 -1.26 Supported Rejected Supported Rejected H2 A. Optimism → Perceived Ease of Use 0.27 1.309 Rejected B. Innovativeness → Perceived Ease of Use 0.35 5.28*** Supported C. Discomfort → Perceived Ease of Use 0.14 1.10 Rejected D. Insecurity → Perceived Ease of Use 0.03 0.35 Rejected H3 Perceived Ease of Use → Perceived Usefulness 0.13 5.28*** Supported H4 A. Perceived Usefulness → Satisfaction B. Perceived Ease of Use → Satisfaction H5 Satisfaction → Loyalty 0.26 -0.07 1 4.05*** -0.80 5.28*** Supported Rejected Supported Model Goodness-of-fit Statistics: χ2=410.862 (p < 0.000); df=157; χ2/df = 2.617; GFI=0.906; AGFI=0.874; CFI=0.913; NFI=0.866, RMR=0.063; RMSEA=0.016 Note. Cut off t-value is 1.96 (*p < 0.05, ***p<0.001)

64 The assessment of hypothesized relationships between TRI dimensions and Perceived Ease of Use reveals that only the Innovativeness dimension of TRI influenced Perceived Ease of Use. The result possibly implies that people living in Germany are highly exposed to advanced and new technologies, and such exposure to innovativeness has contributed to consumers’ ability to understand and use banking technology. Similarly, each small innovation applied by German service providers to improve mobile banking technology is expected to be user-friendly. Hence, Innovativeness had a positive influence on Perceived Ease of Use among mobile banking users in Germany. As hypothesized in H3, the Perceived Ease of Use has a positive influence on Perceived Usefulness of mobile banking among consumers in Germany. The result replicates similar findings from King & He (2006) , Lin et al. (2005), McFarland & Hamilton (2006), Schepers & Wetzels (2007) and Venkatesh & Davis (2000). As opposed to previous studies, the study found that only the Perceived Usefulness dimension of TAM had a significant influence on consumers’ satisfaction. The result showed that there is no direct relationship between Perceived Ease of Use and satisfaction among mobile banking users. However, Perceived Ease of Use had a significant and positive influence on Perceived Usefulness of mobile banking technology. Thus, the research concluded that Perceived Usefulness had a direct and positive influence on consumers’ satisfaction, and Perceived Ease of Use had an indirect influence on the satisfaction level among German mobile banking users. The satisfaction factor had a significant positive influence on consumer loyalty intentions for a wide variety of products and services, including telecommunication-related services (Fornell, 1992; Fornell, Johnson, Anderson, & Bryant, 1996). Satisfaction influence on loyalty is the strongest indicator in the whole model, with the β equal to 1, t-value equal to 3.71, and p-value less than 0.001. Conclusions and Recommendations This research provides an in-depth theoretical perspective pertaining to adoption behavior of mobile banking consumers in Germany. It offers a new approach to comprehend the adoption of mobile banking technology utilizing consumers’ psychographic dimensions (optimism, innovativeness, discomfort and insecurity), cognitive dimensions (perceived usefulness and perceived ease of use), and behavioural dimensions (satisfaction and loyalty) at the same time. The importance of creating satisfied and loyal consumers in the process of mobile banking adoption is emphasized; especially for new players in the market. The study demonstrated that consumers’ personality, cognitive and behavioural dimensions have significant impact on adoption of mobile banking service among German consumers. Thus, when a consumer opts to use a mobile banking service, the consumer’s personality needs to be explicitly taken into account, as personality forms the cognition/perception about the service, and perception determines satisfaction and loyalty towards mobile banking technology. Users’ optimism has a direct and positive impact on the perceived usefulness of mobile banking service. Managers should allocate their marketing resources and put forth an effort to create an optimistic veiw among consumers, with regard to mobile banking technology. This way they can positively influence the cognition of mobile banking users and increase their satisfaction and loyalty levels. The differential effects of innovativeness in the adoption process of mobile banking suggest that there is no one way to approach creating commercially viable innovations. Sometimes, innovativeness doesn’t make a difference on perceived usefulness of technology (possibly because targeted user groups are very innovative, so such innovations integrated in a product or service are percieved as too basic). Nevertheless, innovativeness in technology has a significant positive influence on the perceived ease of use. Hence, management and mobile banking developers have to meet the high standards of consumers and create user friendly innovations. The findings of a relationship between discomfort and percieved ease of use with respect to percieved usefulness of mobile banking technology suggests that mobile banking service providers need to understand and analyze each constituent of the whole service, and improve those fragments that are possibly creating inconvinence when a consumer uses the service. Thus, eliminate the discomfort and amplify the perceived ease of use when a service is consumed. This will increase the

65 percieved usefulness of mobile banking technology among consumers; hence, it will increase their satisfaction level. The fit analysis of this research study ascertained that understanding the adoption of mobile banking technolgy among users – including their satisfaction and loyalty levels – requires a holistic approach. Managers must consider multiple relevant variables and rationalize their association and impact on each other to gain insight into motives that influence consumers and persuade them to stay loyal. Therefore, organizations must develop an integrated strategy at a corporate as well as functional level – one that is aligned with the key influencing factors as noted above, to facilitate a positive mobile banking adoption process among users. Despite a large collection of sample data, the samples were possibly limited to a few regions of Germany beacause of the use of a self-selected online sampling method. Individuals participating anonymously in the survey may have possibly provided inaccurate information, hence creating biased and dishonest responses (Saunders, Lewis, & Thornhill, 2009). A longitudinal study to research the adoption of mobile banking is suggested over a longer period. The research study put forward possibilities for future research to explore other relevant variables that influence adoption of mobile banking. Additionally, the conceptual model that emerged from the research should be extended to understand the adoption of other technological products/services such as e-wallets, smart watches, smart keys, and so on. About the Authors Roshan Khadka is a Master of Business Administration candidate at International College, Panyapiwat Institute of Management, Thailand. Assistant Professor Dr. Phanasan Kohsuwan is a faculty member at International College, Panyapiwat Institute of Management, Thailand. References Al-Ajam, A., & Nor, K. (2013). Internet Banking Adoption: Integrating Technology Acceptance Model and Trust. European Journal of Business and Management, 5(3), 207-215. Anderson, E., & Sullivan, M. (1993). The Antecedents and Consequences of CustomerSatisfaction for Firms, Marketing Science, 12(2), 125-143 Anderson, E., Fornell, C., & Lehmann, R. (1994). Customer Satisfaction, Marketshare and Profitability: Findings from Sweden. Journal of Marketing, 58, 53-66. Anderson, Eugene W.; (1996). Customer Satisfaction and Price Tolerance. Marketing Letters 7(3): 265-274. Retrieved from http://dx.doi.org/10.1007/BF00435742 Bailey, J., & Pearson, S. (1983). Development of a Tool for Measuring and Analyzing Computer User Satisfaction. Management Science, 29(5), 530-545. Retrieved from https://doi:10.1287/mnsc.29.5.530 Bagozzi, R. (1994). Measurement in Marketing Research: Basic Principles of Questionnaire Design. Principles of marketing research. 1, 1-49 Bolton, R. (1998). A Dynamic Model of the Duration of the Customer’s Relationship with a Continuous Service Provider: The Role of Satisfaction. Marketing Science, 17(1), 45-65 Callegaro, M., Manfreda, K., & Vehovar, V. (2015). Web Survey Methodology. SAGE. Chau, P., & Hu, P. (2001). Information Technology Acceptance by Individual Professionals: A Model Comparison Approach*. Decision Sciences, 32(4), 699-719. Retrieved from https://doi:10.1111/j.1540- 5915.2001.tb00978.x Chin, W. (1998). Issues and Opinion on Structural Equation Modelling. Management Information Systems quarterly. 22(1), 1-8. Clemes, D., Gan, C., Kao, T., & Choong, M. (2008 ). An Empirical Analysis of Customer Satisfaction in International Air Travel. Innovative Marketing, 4(2), 49-62. Davis, F. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quaterly, 13(3), 319-340. Retrieved from https://doi:10.2307/249008 Devaraj, S., Fan, M., & Kohli, R. (2002). Antecedents of B2C Channel Satisfaction and Preference: Validating eCommerce Metrics. Information Systems Research, 13(3), 316-333. DeVellis, R. (2012). Scale Development: Theory and Applications (Vol. 26). Sage publications.

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Catalyst ISSN 2408-137X, Volume 18, 2018 68 A Study of Risk Factors Leading to Road Accidents: Chachoengsao Province, Thailand Thanasak Kulchamorin and Danai Pattaphongse Abstract The objectives of this research were to study: 1) personal factors of automobile drivers in Chachoengsao Province, Thailand in the target population; 2) their driving behavior; 3) risk factors influencing the chance of having an accident; 4) measures used to avoid or reduce the impact of an accident; and 5) their attitudes towards both controllable and uncontrollable driving risks based upon their personal factors. The sample consisted of 400 drivers; statistics used included both descriptive and inferential statistics. The majority of respondents were female, married, 36-40 years of age, bachelor degree graduates, and worked for private enterprises. They had non-permanent driver licenses in their possession for 3-5 years and had 10-20 years driving experience. Their overall attitudes towards controllable risk factors showed high scores on a given rating scale. Among controllable risk factors influencing the chance of having an accident, in descending order of magnitude, were violation of a traffic light, violation of a speed limit, texting while driving, and no signal given to other drivers. Uncontrollable risk factors influencing the chance of having an accident, in descending order of magnitude, were drunk driving, driving on damaged roads, driving when the rate of traffic is high, and driving on narrow roads. Keywords: Risk factors, road accidents Introduction Sivak and Schoettle (2014) studied mortality from road crashes in 193 countries, and found that Thailand ranked #2 in the world in terms of the number of people killed (44 deaths per 100,000 persons) in road accidents after Namibia (45 deaths per 100,000 persons). Road accidents caused premature deaths, injuries, and other social and economic problems after the incidents. According to a study conducted by the ThaiRoads Foundation and Thailand Accident Research Center, Asian Institute of Technology (2013), the average number of deaths from road accidents from 2012-2013 was 22,052 annually. That translated into an average of 60 deaths per day. The number of persons injured in accidents was several times as many. Translated into economic terms, the human and workforce losses, as well as medical expenses paid to cure the injured, yields a formidable cost to society. Toyota, the largest car manufacturer in the world and in Thailand, is concerned about the number of road accidents in Thailand. It aims to seek for guidelines that will help reduce road accidents, and has initiated a pilot study in Chachoengsao Province, east of Bangkok. The outcome of this pilot study will be used to develop a framework for a study that covers a larger area of the country. Research Objectives 1. To study personal factors of automobile drivers in Chachoengsao Province who were part of the target population being studied. 2. To study the driving behavior of this group. 3. To study risk factors leading to road accidents. 4. To study measures used to avoid or reduce the severity of accidents. 5. To study attitudes toward both controllable and uncontrollable risk factors based upon personal factors.

69 Literature Review Accident Causation Theory The study is based on Heinrich's Domino Theory (Heinrich, 1931). According to him, 88 percent of all accidents are caused by unsafe acts of people, 10 percent by unsafe mechanical or physical conditions, and 2 percent by "acts of God" which are unpreventable. He proposed a "five-factor accident sequence" in which each factor would actuate the next step, in the manner of toppling dominoes lined up in a row. The sequence of accident factors is as follows: 1. Ancestry and social environment 2. Human error 3. Unsafe acts, together with mechanical and physical hazards 4. Accidents 5. Damage or injury In the same way that the removal of a single domino in the row would interrupt the sequence of toppling, Heinrich suggested that removal of one of the factors would prevent accidents and resultant injuries, with the key domino to be removed from the sequence being number 3 (unsafe acts). However, unsafe acts are purely controllable factors, and many accidents may arise from uncontrollable factors. Multiple causation theory (Peterson, 1978), which is an outgrowth of Domino Theory, states that a single accident may arise from many contributory factors, causes, and subcauses. According to this theory, contributory factors can be grouped into the following two categories: 1. Behavioral: includes factors pertaining to the driver, such as improper attitudes, lack of knowledge, lack of skills, and inadequate physical and mental condition. 2. Environmental: includes improper guarding of other hazardous road elements, and degradation of vehicles through use and unsafe procedures. Other Related Articles An early study carried out by Knipling and Wang (1994) in the United States related to driver drowsiness/fatigue. The research attempted to summarize national statistics on the incidence and characteristics of crashes involving driver fatigue, drowsiness, or “asleep-at-the-wheel” situations during the five-year period from 1989 to 1993. During this period, an average of 40,000 non-fatal injuries annually were associated with police-reported driver drowsiness crashes, while drowsiness or fatigue were cited as a factor in an annual average of 1,357 passenger vehicle fatalities, and combination-crashes resulting in 1,544 fatalities. The statistics also indicated that drowsy driver crashes peaked in the early a.m. hours, with a second smaller peak in the afternoon. Fifty-five (55) percent occurred between midnight and 7:59 am, and another 18 percent occurred between 13:00 and 16:59 pm. Furthermore, male drivers had a drowsiness crash- involvement rate that was 1.8 times greater than that of females. The study also showed that the drowsiness crash-involvement rate for drivers under 30 was more than four times higher than that for drivers 30 or over. This statistical profile of U.S. police-cited drowsiness-related crashes is remarkably similar to the same category of crashes occurring in New South Wales, Australia (Fell, 1994). Thanadulburin (2011) conducted a study on awareness of accident occurrence on the part of youngsters’ parents and drivers in Chiang Mai Province, Thailand and identified two factors most influential to the rate of road accidents – carelessness and casualness. From the driver's point of view, controllable factors were responsible for road accidents. From the parents' point of view, uncontrollable factors were responsible for road accidents. A related study was carried out in China by Wang, Rau, and Salvendy (2011). The research indicated that drivers who were likely to engage in driving risks were also likely to take risks in the domains of ethics, gambling, investment, recreation, and abuse of/or ignoring health. Tongtua (2012) studied the process of instilling road safety culture in Thailand among Ubolrajthani University students and in surrounding communities. The study concluded that the two

70 major factors which could reduce the rate of road accidents were the behavior of drivers within the community themselves, and environmental factors such as road conditions that needed to be urgently reviewed. A further study in Thailand carried out by Karnjanaphen, Luethep, and Thaneerananont (2013), showed that major causes of road accidents, in descending order of magnitude, were driver errors (speeding, drowsy driving), bad road conditions (wet and slippery roads), poor visibility and unsafe vehicle. Some similar factors were found to apply to Russian drivers by Kudryavtsev (2012), who identified three major causes of road accidents: lack of safe driving skills, environmental conditions and bad traffic engineering, and lack of law reinforcement. The National Institutes of Health (2013) in Maryland, U.S.A., conducted a nationwide study of the risks that drivers faced. The research results revealed that inexperience was the most influential factor that caused crashes and deaths. Other risk factors included distractions while driving (using cell phones and texting), driving at excessive speeds, close following (“tailgating”), drinking and driving, and driving at night. The research also indicated that the estimated cost of injuries and fatalities from car crashes was $300 billion in 2009. Every year, more than 5.5 million car crashes are reported to police in the United States, with more than 30,000 fatalities and 2 million injuries. The Center for Statistics and Analysis (2016) reported that 9 percent of all drivers involved in fatal crashes were 15 to 20 years old. The rate of young male drivers involved in fatal crashes was about 2.3 times that of young female drivers. Twenty-six percent of young drivers 15 to 20 years old who were killed in crashes had blood alcohol concentrations (BACs) of 0.01 gram/decilitre or higher; 81 percent of those young drivers had BACs of 0.08 gram/deciliter or higher. The data also showed that for those young drivers who survived the fatal crash, 84 percent were restrained, compared to 90 percent of all drivers who survived. A study by the same agency in 2015 on road accidents indicated that a male driver’s risk of having a road accident was twice that faced by a female driver. This was due to the fact that men drove longer distances than women (an average man drives 24,000 kilometers annually, while an average woman drives 16,000 kilometers) and the tendency that men might drive while drunk. Finally, Stephens and Ohtsuka (2014) conducted a study on the cognitive biases shown by aggressive drivers, and tried to answer the question: does an illusion of control drive us off the road? The research findings revealed that road rage and illusion of control beliefs (feelings of control over the situation) accounted for 37 percent of the variance in hostile driving behavior scores. Thus, the literature review attempted to identify both controllable and uncontrollable factors affecting the rate of road accidents. Furthermore, practical measures designed to reduce the severity of accidents are urgently needed so that all people concerned can adopt and implement them. Scope of the Study Content Focuses on studying daily driving behavior and attitudes toward controllable and uncontrollable factors that may lead to a high probability of having accidents. Place Plaengyao District, Chachoengsao Province. Period August 2015 to January 2016 Population All automobile drivers living in Plaengyao District, Chachoengsao Province. Sampling Method Sampling was conducted using a multistage sampling method, whereby the areas were selected first using purposive sampling. There were four areas selected, namely, Hua Samrong

71 Municipality; the area supervised by Hua Samrong District Administrative Organization; Nong Tapao Village; and Gateway City Industrial Estate. Convenience sampling was then conducted using 80 persons as a quota for each area. Statistics Used in the Analysis This study uses both descriptive statistics (frequencies, percentages, means, and standard deviations) and inferential statistics (t-test, F-test). Independent Variables Dependent Variables Figure 1. Research Framework Research Findings The findings revealed that the majority of respondents were female (52.5 percent), married (55.9 percent), 36-40 years of age (19.4 percent), bachelor degree graduates (25.6 percent), working for private companies (46.9 percent), having temporary driver license (56.6 percent), possessing licenses for between 3-5 years (31.9 percent), and having 10-20 years of driving experience (29.4 percent). Controllable risk factors affecting the chance of accidents, according to them, are failing to obey traffic signals, violating speed limits, texting while driving, speaking on the phone while driving, and not signaling other drivers. Table 1 indicates that driving without obeying traffic signals, driving at speeds higher than those allowed by law, driving while having chatting online, driving while talking on the phone, and driving without signaling other drivers are among the controllable risk factors that are highly influence the chance of having a road accident. Personal Factors - Sex - Age - Education - Social and economic status - Type of driver license* - Length of possession - Driving experience * Note: Permanent driver licenses (not granted anymore) are lifelong with no expiry date, while temporary driver licenses are valid for 5 years and must be renewed. Opinion on both controllable and uncontrollable risk factors tending to increase the probability of having an accident Opinion on measures desired to reduce the severity of accidents Opinion on measures desired to reduce the chance of having an accident Driving behavior

72 Table 1. Attitudes toward Controllable Risk Factors that May Lead to Accidents Controllable Risk Factors x̅ S.D Interpretation Driving at speeds higher than those allowed by law 3.75 1.38 Highly Influential Driving without obeying traffic signals 3.76 1.52 Highly Influential Driving when visibility is poor (e.g. at night/during heavy downpours) 3.41 1.30 Moderately Influential Driving while talking on the phone 3.51 1.43 Highly Influential Driving while chatting online 3.58 1.52 Highly Influential Driving while watching portable television 3.27 1.46 Moderately Influential Driving without signaling other drivers 3.51 1.41 Highly Influential Driving on unfamiliar roads 3.32 1.30 Moderately Influential Driving when weary or suffering from fatigue 3.33 1.44 Moderately Influential Values and interpretation of x:̅1.00-1.50 (least influential) 3.51-4.50 (highly influential) 1.51-2.50 (somewhat influential) 4.51-5.00 (most highly influential) 2.51-3.50 (moderately influential) When these risk factors were weighted, with a weight of two assigned to the risk factor most likely to cause an accident and a weight of one assigned to the second most likely risk factor, we derived the weighted scores shown in Table 2. Table 2. Weighted Scores of Controllable Risk Factors Tending to Cause Accidents Controllable Risk Factors That Cause Accidents Assigned as Rank No. 1 Assigned as Rank No. 2 Weighted Scores Driving while doing something at the same time 62 55 179 Driving when visibility is poor 37 35 109 Driving without obeying traffic rules 141 51 333 Driving at speeds higher than those allowed by law 44 123 211 Driving on unfamiliar roads 21 31 73 Driving when weary or suffering from fatigue 15 25 55 Table 2 indicates that the top-three controllable risk factors tending to cause accidents, in descending order of magnitude, are driving without obeying traffic rules, driving that exceeds the speed limit, and driving while doing something at the same time. Table 3 indicates that uncontrollable risk factors that highly influence and increase the chance of having a road accident are driving under the influence of alcohol, driving on damaged roads, driving when traffic is heavy, and driving on narrow roads. Table 3. Attitudes toward Uncontrollable Risk Factors that May Lead to Accidents Uncontrollable Risk Factors x̅ S.D Interpretation Driving under the influence of alcohol 4.08 1.26 Highly Influential Damaged roads 3.73 1.06 Highly Influential Narrow roads 3.53 1.11 Highly Influential Heavy traffic 3.65 1.16 Highly Influential Carelessness due to moral hazards 3.31 1.44 Moderately Influential Values and interpretation of x:̅1.00-1.50 (least influential) 3.51-4.50 (highly influential) 1.51-2.50 (somewhat influential) 4.51-5.00 (most highly influential) 2.51-3.50 (moderately influential)

73 Table 4 indicates that a large number of respondents still exposed themselves to the risk of being seriously injured, or, if they are unfortunate enough, losing their lives or those of their loved ones. Table 4. Measures Taken to Alleviate the Impact of Accidents Attitudes toward Measures Deemed Most Effective in Reducing Accidents When measures deemed likely to reduce the number of accidents were weighted, the figures shown in Table 5 were generated. The measure viewed as most effective was given a weight of two, and the second most effective measure was given a weight of one. Table 5. Weighted Scores of Most Effective Measures to Reduce the Number of Accidents Measures Assigned Rank of No. 1 Assigned Rank of No. 2 Weighted Scores More police, more radar devices to measure speed 60 47 167 More levels of penalties (higher traffic fines, temporary suspension of driver’s license, permanent cancellation of driver’s license) 89 98 276 Unwavering strictness by the traffic police 140 97 377 Warning words with given in a sterner tone 31 78 140 Table 5 indicates that the three most effective measures used to reduce the number of accidents, in descending order of magnitude, are how strictly the traffic police enforce the law, more levels of penalties, and more traffic police, including more speed measuring devices. Most Effective Measures to be Taken to Reduce Accidents during Festivals or Long-holiday Periods Table 6 shows that, according to the respondents, the two most effective measures to reduce the number of road accidents during festivals or long-holiday periods are prevention of drunk driving and strict enforcement of speed limits. Table 6. Attitudes on Measures to Reduce Road Accidents during Festivals or Long-Holiday Periods Measures to be Implemented by the Government as Top Priorities to Reduce Road Accidents Table 7 indicates that respondents’ believe that two of the most important measures that might be taken by the government to cope with the problem of a high rate of road accidents are to reduce the problem of drinking and driving, and to impose high penalties on any violation of traffic laws. Measures Taken Always Practiced Sometimes Practiced Rarely Practiced Wearing seat belts 55.6 42.2 2.2 Stop driving during heavy downpours or poor visibility 45.3 52.2 2.5 Sleeping or resting when feeling drowsy 45.3 52.2 2.5 During long holiday periods, travel and return early 48.4 41.6 10.0 Stop driving when feeling weary 66.2 23.8 10.0 Measure(s) Considered Most Effective Percentage Enforcing speed limits 25.0 Preventing drunk people from driving 35.9 Adding more rest areas 17.8 Restricting access to alcoholic drinks 15.3 Others 6.0

74 Table 7. Measures to be Taken by Government as to Cope with the High Rate of Road Accidents Attitudes toward both Controllable and Uncontrollable Factors Based upon Personal Characteristics Table 8 shows the respondent attitudes toward controllable risk factors based upon their personal characteristics. Table 8. Attitudes toward Controllable Risk Factors Based upon Personal Characteristics Factors Sex1 Age2 Education2 Occupation2 Income2 Driving at speeds higher than allowed by law 0.069 0.004* 0.000* 0.000* 0.005* Driving without obeying traffic signals 0.027* 0.023* 0.000* 0.000* 0.004* Driving when visibility is poor 0.002* 0.001* 0.000* 0.000* 0.000* Driving while talking on the phone 0.041* 0.000* 0.000* 0.000* 0.000* Driving while chatting online 0.010* 0.000* 0.000* 0.000* 0.000* Driving while watching portable television 0.000* 0.018* 0.000* 0.000* 0.000* Driving without signaling other drivers 0.061 0.005* 0.005* 0.000* 0.030* Driving in unfamiliar roads 0.000* 0.003* 0.000* 0.000* 0.004* Driving when weary or fatigued 0.000* 0.001* 0.000* 0.000* 0.000* Notes. 1 = t-test conducted; 2 = F-test conducted Respondents of different genders differ in their attitudes towards most controllable risk factors. Respondents of different ages, education levels, occupations, and income levels differ in their attitudes regarding all controllable factors. It is of interest to note that the majority of controllable factors investigated were related to personal factors at the 0.05 level of significance. Post-hoc analysis may be used to identify certain type of persons who have attitudes that are liable to cause accidents. Table 9. Attitudes toward Uncontrollable Factors Based upon Personal Characteristics Notes. 1 = t-test conducted; 2 = F-test conducted Table 9 shows respondents of different ages, educational levels, and occupations differ in their attitudes toward all uncontrollable risk factors, while respondents of different genders and income levels differ in one of the uncontrollable risk factors. Discussion The findings of this research study pinpoint both controllable and uncontrollable risk factors that can cause road accidents. Thus, it supports as well as complements the studies conducted by Knipling and Wang. (1994), Thanadulburin (2011), and Karnjanaphen et al. (2013). These authors may not use the word controllable and uncontrollable risks, but the factors identified fall within both categories. Measure(s) Recommended Percentage The problem of drinking and driving 45.3 Speedy driving 17.5 Violation of traffic laws 32.8 Others 4.4 Factors Sex1 Age2 Education2 Occupation2 Income2 Driving under the influence of alcohol 0.470 0.003* 0.022* 0.033* 0.120 Damaged roads 0.442 0.011* 0.003* 0.000* 0.417 Narrow roads 0.016* 0.001* 0.000* 0.000* 0.125 Heavy traffic 0.056 0.004* 0.000* 0.000* 0.096 Carelessness due to moral hazards 0.188 0.006* 0.009* 0.000* 0.000*

75 It should be noted that it is too easy for one to blame uncontrollable risk factors as the culprits that tend to cause road accidents and ignore what may be done to reduce these factors. Some supposedly “uncontrollable” factors can be controlled and coped with; for example, one who handles the wheel should never drink even if the chance of getting drunk is slim. Driving with utmost care on damaged roads, narrow roads, or roads with heavy traffic will undoubtedly lower or eliminate the chance of having road accidents. If your car is fully insured, it won’t be worth it to drive carelessly, because when an accident occurs, every driver faces the loss of time, inconvenience while his/her car is in the repair shop, and the chance that the driver or family members may be injured, perhaps seriously. Suggestions and Recommendations The findings of this study have revealed that a large number of respondents do not take good care of themselves - they do not wear seat belts, they keep on driving even when they are drowsy or when their bodies are not in proper condition, and they drive even in situations where their visibility is poor. Measures to be taken must therefore be both psychological and instrumental. Psychologists may be able to help in devising measure that can change peoples’ behavior. As an example, police, pedestrian representatives, and psychologists may work together to design road warning signs using stronger words that can effectively deter speeding drivers from their illicit behavior, while at the same time not agitating social critics. A study by World Health Organization (2015) reported that Thailand’s roads were the seconddeadliest in the world (a rate surpassed only by Libya). Thus, all individuals and parties concerned, both public and private, have to admit that road accidents are a big problem for Thailand that is not going to disappear any time soon. It is now time for Thai authorities and those groups responsible for the betterment of the Thai people to ponder and ask themselves what variable(s) have been left out of the equation. Addressing these variables is necessary if there is to be a dramatic reduction in the rate of road accidents in Thailand. Suggestions for Further Study It should be noted that road accidents caused by motor vehicles are only part of the story. Motorbikes or motorcycles also play a large part in the number of road accidents in Thailand. Therefore, another study that aims to tackle the problem of accidents caused by motorcycle riders is also urgently needed. About the Authors Thanasak Kulchamorin is Assistant Manager of the Planning Department, Toyota Motor Thailand Co., Ltd. Dr. Danai Pattaphongse is a Lecturer and Director of the Master of Business Administration Program, Nation University, Bangna, Thailand. References Center for Statistics and Analysis. (2016). Young drivers: 2014 data. (Traffic Safety Facts. Report No.DOT HS 812 278). Washington, DC: National Highway Traffic Safety Administration. Retrieved from https:// crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812278. Fell, D. (1994). Safety Update: Problem definition and countermeasure summary: fatigue. New South Wales Road Safety Bureau, RUS No. 5. Heinrich, H.W. (1931). Industrial accident prevention: a scientific approach. New York: McGraw-Hill. Karnjanaphen, E., Luethep, P., & Thaneerananont, P. (2013). Crash investigation of public vans and buses: A case study of Southern Thailand. Paper presented in 18th National Conference on Civil Engineering (NCCE). The Empress Hotel, Chiang Mai. Retrieved from http://trsl.thairoads.org/FileUpLoad/ 1502/141004001502.pdf Knipling, R. and Wang, J. (1994). Crashes and fatalities related to driver drowsiness/fatigue. U.S. Department of Transportation. National Highway Traffic Safety Administration. Retrieved from https://trid.trb.org/ view/ 415055.

76 Kudryavtsev, A. (2012). Road traffic crashes in Arkhangelsk, Russia in 2005-2010. A Dissertation for the Degree of Philosophiae Doctor, University of Tromso, Faculty of Health Sciences, Department of Community Medicine. Retrieved from https://munin.uit.no/bitstream/handle/ 10037/4786/ thesis.pdf? sequence =2. National Institute of Health (n.d.). What risk factors do all drivers face? Eunice Kennedy Shriver National Institute of Child Health and Human Development. Retrieved from https://www.nichd.nih.gov/health/ topics/ driving/conditioninfo/risk-factors. Peterson, D. (1978). Techniques of safety management, 2nd Edition, McGraw Hill. Sivak, M. & Schoettle, B. (2014). Mortality from road crashes in 193 countries: A comparison with other leading causes of death. Transportation Research Institute, University of Michigan, Ann Arbor. Report No. UMTRI-2014-6. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/ download?doi= 10.1.1.650.4951 &rep=rep1& type=pdf. Stephens, N., & Ohtsuka, K. (2014). Cognitive biases in aggressive drivers: Does illusion of control drive us off the road? Personality and Individual Differences 68, 124-129. Retrieved from http://isiarticles.com /bundles/ Article/pre/pdf/77516.pdf. Suriyawongpaisal, P. (Ed.) (2015). Key facts on road safety situations in Thailand: 2012-2013. ThaiRoads Foundation & Thailand Accident Research Center, Asian Institute of Technology. Retrieved from http://www.roadsafetythai.org/uploads/ userfiles/file_20151224095849.pdf. Thanadulburin,T. (2011). Evaluation of awareness in accidents on the part of parents and car drivers. (Master’s Thesis). Chiang Mai University, Faculty of Economics. Tongtua, K.(2012). The creation of road safety culture on the part of students and people living in the vicinity of Ubolrajthani University. Thai Health Organization. Retrieved from http://roadsafetythai.org/uploads/ userfiles/ACC_54008.pdf. Wang, P., Rau, P.P. and Salvendy, G. (2011). Chinese drivers’ risky driving and risk taking in other life situations. International Journal of Occupational Safety and Ergonomics (JOSE), Vol. 17 (2), 155–164. Retrieved from https://doi.org/10.1080/10803548.2011.11076886. World Health Organization (2015). Global status report on road safety 2015. WHO Press. World Health Organization, Geneva, Switzerland. Retrieved from http://www.who.int/violence_ injury_ prevention / road_safety_ status/2015/en/

Catalyst ISSN 2408-137X, Volume 18, 2018 77 Time Management Capabilities of Undergraduate Students at a Private Thai University Anchalee Chanpisut Abstract This research study examined the self-described time management capabilities of undergraduate students at a small private university in Thailand. Since completing a university degree requires taking many classes as well as participating in extracurricular activities, students need good time management skills to be successful. Developing such skills while they are still students will also help them to manage time effectively after they graduate and begin their professional lives. The research instrument used for collecting data was a five-rating scale questionnaire with 58 items. The sample consisted of 320 undergraduate students during the 2015/2016 academic year. These were classified by gender, age, program of study, year of study, cumulative grade point average (CGPA), residence accommodations, and means of financial support. The results show that students reported moderate levels of overall time management capabilities. In regards to planning time usage, female students reported a higher level of capability than male students did. In terms of formation of life objectives, students with government loans had higher scores than students who were self-financed. Keywords: Time management capabilities, undergraduate students Introduction In a university, there are so many activities inside and outside of the classroom. Students need to manage their time to accomplish all their study tasks as well as to participate in required activities. In order to be successful, students need to plan their time wisely. Poser (2003) stated that “you need to manage time effectively if you’re going to be successful. All other things being held constant, better time management skills can improve your grades, help you keep stress in check, and help you be competitive in the career you undertake following your university education.” While many students achieve excellent academic results, many others receive low grades or fail courses and are not able to graduate due largely to their inability to manage their time well. Time management skills are a major criterion that affects student achievement. Previous research studies have shown that positive time management behaviors boost students’ CGPAs, whereas negative time management behaviors decrease academic performance (Britton and Tesser, 1991; Mpofu, D'Amico, & Cleghorn, 1996; Saketi & Taheri, 2010; Sevari & Kandy, 2011; Tanriogen & Iscan, 2009). It is generally assumed that students with good time management skills are able to manage time effectively even after they graduate and enter professional life. According to Persky, Alford, and Kyle (2013), time management skills are a significant predictor of first-year performance of college students. Students who have no self-discipline and have never been trained to use time efficiently before entering university tend to find it difficult to engage in activities and yet get all the academic tasks done on time. The consequences are stress and failure in academic life. Satija and Satija (2013) believe that people choose to work on tasks that yield the highest utility. They found that people think about what they will gain by working on task (a) or task (b), and so if task (a) has a higher utility, then they are more likely to work on task (a) than on task (b). In other words, people maximize the expected utility. Statement of the Problem A private university located in Central Thailand had an enrolment of 1,134 students (both Thai and International) for the 2015/2016 academic year. In that same academic year, there were 78 students categorized as on either warning or probation status, which means that these students had achieved a GPA or CGPA lower than 2.00. In regardsto poor academic achievement, previous research

78 studies have found that the ability to manage time affects academic achievement. This study was limited to the six time management steps suggested by Lokam (2007) as follows: (1) Analysis of Problems Related to Time Usage How to make the most use of time may be analyzed by evaluating problems that interfere with effective time management. Some problems that distract students from managing time are talking with friends, using the telephone, or waiting for something. These can be ascertained by keeping a record of all activities that happen each day. When students realize their weaknesses, then they will be able to plan for solutions to use their time more effectively. (2) Formation of Life Objectives Setting life objectives is to establish short-term and a long-term life plan. Having clear objectives helps a person to overcome obstacles in order to attain the set objectives. Setting longterm life objectives begins with self-examination regarding what students like. What are their abilities or skills? What makes students the happiest? By searching for information or consulting with experienced people like parents and teachers, students can establish their highest objectives in life. The long-term life objectives should be clear, practical, and realistic. Setting short-term objectives is secondary and should lead to the long-term life objectives. (3) Planning of Time Usage As time is limited, students need to plan how to use their time by prioritizing the most important activities that have to be done and leaving out the unimportant ones. The importance can be evaluated according to the value of work to the long-term objectives, and concern for the urgency and responsibility that have been assigned to it. (4) Implementation of Projected Plans In this step, a student establishes a timetable for the whole week, in divisions of 24 hours, in order to have a clear picture of all activities that have to be done each day. The most important activities should be scheduled in the timetable first. Then evaluate whether the timetable is appropriate and practical. Most of all, one needs to have self-discipline to follow the timetable. (5) Assessment of Time Usage At this step, students should honestly assess their time usage to know how well they have been able to follow the timetable, and if there are any obstacles at each step. Assessment of time usage should be done regularly to follow up progress and success in work, along with the amount of time used. (6) Improvement of Projected Time Usage Plan and Revision of Wasted Time Activities This final step is to search for the best method to improve time usage in order to increase work efficiency. There are causes of time wasting such as procrastination, unclear objectives, work not prioritized, no daily or weekly plan for time usage, spending a lot of time talking on the phone, waking up late, and spending a lot of time eating. Students have to examine their time usage and eliminate those activities that waste time in order to improve time usage. Finally, the results will mean that they have more time to work on important activities and achieve the objectives they have set for successful lives. Purpose of the Study The purpose of this study is to examine time management capabilities of undergraduate students and to generate helpful guidelines, especially for students with low academic achievement (probation and warning status). This may then be done by analyzing problems related to time usage, setting objectives, planning time usage, implementing plans, assessing time usage, improving projected time usage plans, and revising time-wasting activities. The researcher believes that this will eventually help students to improve their academic achievements, as well as succeed in their personal lives, while studying at university.

79 Literature Review Many studies have been conducted at colleges and universities to examine the relationship between students’ time management and their academic achievements. The results of several such studies related to this topic are summarized below. Britton and Tesser’s (1991) study showed that time management practices were a significant predictor of CGPA. In addition, time management attitudes and skills had a positive effect on academic achievement. Similar results were also found in the later studies of: Mpofu, D'Amico, and Cleghorn (1996), who found that students’ perceived control of their time accounted for a significant proportion of variance in CGPAs. Tanriogen and Iscan (2009) also found that time management skills affected students’ academic achievement at a significant level. Sevari and Kandy (2011) found that training in time management skills increased students’ academic performance. In addition, several studies compared time management skills by gender, and discovered interesting results. Misra and McKean (2000) investigated the interrelationship between academic stress, anxiety, time management, and leisure satisfaction. The results showed that female students possessed more effective time management skills than male students. Similar results emerged from a study in Thailand by Lokam (2007), which showed that females possessed higher time management abilities than males. A study by Saketi and Taheri (2010) showed no difference between genders in terms of time management skills, but in terms of academic achievement, female students once again outscored male students. While Misra and McKean (2000) found that female students have more effective time management skills than males, yet they also experienced greater levels of academic stress and anxiety. These result seem to conflict with those of Macan, Shahani, Dipboye, and Phillips (1990), who found that students who had control of their time reported significantly higher evaluations of their performance, greater work and life satisfaction, less role ambiguity, less role overload, and less jobinduced and somatic tension. However, Macan et al. (1990) end with a thoughtful message suggesting that the dynamics of time management are more complex than previously believed. This may be because of rapid changes in the environment, social media, cultures, and transportation that influence today’s students differently than in previous years. Lokam’s (2007) study of the steps of time management found a statistically significant difference in the overall time management capabilities of males and females. In addition, females possessed higher time management capabilities in the formation of life objectives, the improvement of projected time usage, and the revision of time wasting activities than males. A comparison of students by year of study showed that juniors had higher scores than seniors in the area of assessment of time usage. This was because in their last year of study, senior students were planning to pursue their careers, and therefore may focus on preparing to search for jobs, while juniors took responsibility for leading university activities for the younger students. Juniors were also taking core and major courses that required more effort. In spite of these additional duties, which caused junior to carry heavier overall study and activity workloads, they felt a sense of satisfaction and accomplishment that is shown in higher assessment of time usage scores. In terms of academic achievement, Lokam found that students with lower grades reported higher time management scores than students with medium and higher grades. These students tended to be involved in many activities with friends, such as listening to music, watching television, exercising, helping parents with household chores, and playing games. In general, they seemed to have better relationships with others, balanced lifestyles, and better overall quality of life. However, students with higher grades focused most of their time on academic assignments and paid little attention to other activities.

80 Sattayawaksakul, Maidom, and Cheewaprakobkit (2016) studied time management capabilities in an industrial workplace, using Lokam’s questionnaire as the research instrument. The results showed that female workers reported slightly higher levels of overall time management capabilities, as well as for each individual step. This may be because many female employees s feel more pressure in juggling career and family responsibilities (Worthley, MacNab, Brislin, Ito, & Rose, 2009). As a result, they learn to manage their time so that they can balance their professional and family life. These findings seem to indicate that gender differences in time management persist even after formal education is completed. Methodology This study adapted Lokam’s (2007) questionnaire as the research instrument to examine the self-described time management capabilities of 320 undergraduate student samples at a private university. A questionnaire using a 5-level Likert rating scale was comprised of 2 sections: Section 1: Student’s Demographic Information. This part asked for information about personal factors including gender, age, Faculty of study, CGPA, student accommodations, and sources of financial support. Section 2: Student’s Personal Time Management Capabilities. This part was divided into six aspects and consisted of 58 questions, which were both positive and negative. The questionnaires were distributed to all levels of undergraduate student on campus. They were distributed to freshmen students during the evening Study Hall time. For sophomores, juniors, and seniors, the researcher received permission to use 10-15 minutes of lecture time from selected instructors, and distributed and collected questionnaires in their classrooms. Study Results The personal information of sampled undergraduate students for the 2015/2016 academic year regarding gender, age, Faculty of study, year of study, CGPA, student accommodations, and source of financial support is shown below as follows: Table 1. Biographical Information Variable Sample (320) Percentage Variable Sample (320) Percentage Gender CGPA Male 98 30.6 Lower than 2.00 3 0.9 Female 222 69.4 2.01 – 2.50 60 18.8 Age 2.51 - 3.00 96 30.0 18 years 35 10.9 3.01 – 3.50 90 28.1 19 years 49 15.3 More than 3.50 71 22.2 20 years 43 13.4 Accommodation 21 years 69 21.6 Dormitory/Residence 288 90.0 Over 22 years 124 38.8 Own house 20 6.3 Faculty of Study Off campus 12 3.7 Art and Humanities 76 23.8 Financial Support Business Administration 84 26.3 Private Scholarship 34 10.6 Education and Psychology 27 8.4 Government Loan 157 49.1 Nursing 110 34.4 Family 101 31.6 Religious Studies 14 4.4 Other 28 8.8 Science 9 2.8 Year of Study Freshmen 65 20.3 Sophomore 73 22.8 Junior 63 19.7 Senior 119 37.2

81 Biographical Information Table 1 shows that most participants were female (69.4%) and 20 years of age or older. Large numbers of respondents were majoring in Nursing (34.4%), Business Administration (26.3%), and Arts and Humanities (23.8%). The highest number of participants were seniors (37.2%), followed by sophomore level (22.8). The most common range of cumulative grade point average (CGPA) was between 2.51 to 3.00 (30.0%), followed by a range of 3.01 to 3.50 (28.1%). Most participants lived in university dormitories or residences (90.0%), and the largest number of supported their studies with government loans (49.1%), or were supported by their families (31.6%). Overall Level of Time Management Capabilities The results of the study in Table 2 show that students reported a moderate level of capability in all time management steps (X = 3.36, SD = 0.39). Table 2. Overall Level of Time Management Capabilities Time Management Capabilities x̅ S.D. Capability Level Analysis of problems related to time usage 3.08 0.42 Moderate The formation of life objectives 3.47 0.53 Moderate The planning of time usage 3.48 0.62 Moderate The implementation of projected plans 3.45 0.54 Moderate The assessment of time usage 3.34 0.48 Moderate The improvement of projected time usage plan and revision of wasted time activities 3.37 0.61 Moderate Average 3.36 0.39 Moderate Time Management Capabilities Compared by Gender Table 3 shows a comparison of time management capabilities between male and female students in both overall time management and the six related steps. The results for the t-test indicate no statistically significant difference between male and female students in overall time management capabilities (p < 0.05). However, there was a statistically significant difference in the planning of time usage among students by gender (p = 0.03). Female students possessed higher time management capabilities in the area of planning time usage. Male and female students show no differences in the other five aspects. Table 3. Time Management Capabilities Compared by Gender Female (n = 222) Male (n = 98) Time Management Capabilities x̅ S.D. x̅ S.D. t p Analyses of problems related to time usage 3.07 0.42 3.11 0.43 0.66 0.51 The formation of life objectives 3.48 0.52 3.45 0.54 -0.53 0.60 The planning of time usage 3.53 0.58 3.36 0.69 -2.20 0.03 The implementation of projected plans 3.47 0.50 3.40 0.61 -1.01 0.32 The assessment of time usage 3.36 0.44 3.30 0.57 -1.04 0.30 The improvement of projected time usage plan and the revision of time-wasting time activities 3.35 0.61 3.42 0.61 1.00 0.32 Average 3.38 0.38 3.34 0.43 -0.76 0.45 Time Management Capabilities Compared by Age The results of a One-Way Analysis of Variance (ANOVA) showed no statistically significant differences in overall time management capabilities among students of different ages. However, there was a statistically significant difference in the implementation of a projected plan (p = 0.01). Table 4 shows the level of time management capabilities by age.

82 Table 4. Time Management Capabilities Compared by Age Variance F P The analyses of problems related to time usage 1.49 0.21 The formation of life objectives 1.12 0.35 The planning of time usage 2.20 0.07 The implementation of projected plans 3.74 0.01 The assessment of time usage 1.42 0.23 The improvement of projected time usage plans and revision of time-wasting activities 1.65 0.16 Overall Capabilities 2.33 0.06 The results from Scheffe’s method shows that there were statistically significant differences between two pairs of groups: students who were 18 and 20 years of age, and those who were 20 and 21 years. In both cases, students who were 18 and 21 years old possessed better time management capabilities than those who were 20 years old. In other words, students who were 20 years old reported weaker time management capabilities than those who were younger or older (p < 0.05). Time Management Capabilities Compared by Faculty of Study The results of a One-Way ANOVA test showed statistically significant differences in the overall time management capabilities among students from different Faculties of Study. In addition, there were also statistically significant differences in several time management steps, including formation of life objectives, planning of time usage, and implementation of projected plans among students from different Faculties (p < 0.05). Table 5 shows student levels of time management capabilities by Faculty of Study. Table 5. Time Management Capabilities Compared by Faculty of Study Variance F P The analyses of problems related to time usage 2.29 0.05 The formation of life objectives 7.05 0.00 The planning of time usage 4.32 0.00 The implementation of projected plans 2.72 0.02 The assessment of time usage 0.66 0.65 The improvement of projected time usage plans and revision of time-wasting activities 1.13 0.35 Overall Capabilities 3.09 0.01 The overall capabilities and the three steps that were statistically significant were further testedby Scheffe’s method. The findings showed (Table 5) that firstly, three pairs that included nursing students showed statistically significant differences in the formation of life objectives. These pairs consisted of Nursing and Arts and Humanities students, Nursing and Business Administration students, and Nursing and Education and Psychology (p < 0.05) students. In each case, nursing student scores for the formation of life objectives were higher than for the other three Faculties. Secondly, nursing students also showed a statistically significant difference in the planning of time usage when compared with Arts and Humanities students. Time Management Capabilities Compared by Year of Study The results (Table 6) of a One-Way ANOVA showed statistically significant differences in overall time management capabilities among students in different years of study. Significant differences were found in several steps, including analysis of problems related to time usage (p = 0.01), formation of life objectives (p = 0.01), implementation of projected plans (p = 0.03), and improvement of projected time usage/revision of wasted time activities (p = 0.00).

83 Table 6. Time Management Capabilities Compared by Year of Study Variance F P The analyses of problems related to time usage 4.31 0.01 The formation of life objectives 4.31 0.01 The planning of time usage 2.23 0.09 The implementation of projected plans 3.04 0.03 The assessment of time usage 1.00 0.39 The improvement of projected time usage plans and revision of time-wasting activities 4.91 0.00 Overall Capabilities 3.71 0.01 In Table 6, use of Scheffe’s test method revealed a statistically significant difference in overall capabilities in the pairs of freshmen and juniors, with freshmen reporting higher time management capabilities than juniors. Furthermore, statistically significant differences were found for three of the time management steps: (1) Analysis of problems related to time usage, with sophomores reporting better time management capabilities than did juniors; (2) Implementation of projected plans, with freshmen showing better abilities to implement projected plans than juniors; and (3) Improvement in projected time usage and revision of wasted time activities, with seniors rating higher than did juniors in improving time usage plans. Time Management Capabilities Compared by CGPA The results of a One-Way ANOVA test showed statistically significant differences in overall time management capabilities among students with different CGPAs. In addition, statistically significant differences were found for all of the time management steps among students with different CGPAs. Table 7. Time Management Capabilities Compared by CGPA Variance F P The analyses of problems related to time usage 2.42 0.05 The formation of life objectives 4.57 0.00 The planning of time usage 5.18 0.00 The implementation of projected plans 3.63 0.01 The assessment of time usage 2.62 0.04 The improvement of projected time usage plans and revision of time-wasting activities 4.43 0.00 Overall Capabilities 5.76 0.00 Students’ overall time management capabilities and each of the six aspects were further tested by Scheffe’s method to determine which ranges of CGPAs were significantly different from the others (see Table 7). The results showed statistically significant differences in overall time management capabilities by two pairs of student groups: 1) those with CGPAs below 2.00 had lower scores than those with CGPAs from 2.01-2.50. 2) those with CGPAs above 3.50 had lower scores those with CGPAs from 2.01-2.50. In terms of the individual time management steps, students with CGPAs below 2.00 were less proficient in the planning time usage step than groups with higher CGPAs; these differences were statistically significant at the 0.05 level. This finding is not surprising, and low CGPAs are probably the result of poor time planning usage skills. For the implementation of projected plansstep, however, students with CGPAs from 2.01-2.50 outperformed those with CGPAs above 3.50. The same was true for the improvement of projected time usage plans and revision of wasted time activitiesstep; students with modest CGPAs (2.51 – 3.00, and 3.01 – 3.50) outperformed those with CGPAs above 3.50 at statistically significant levels. These results may indicate that weaker or average students must put more effort into the time management process than do very bright students in order to achieve acceptable results.

84 Time Management Capabilities Compared by Student Accommodations A One-Way ANOVA test showed no statistically significant differences in overall time management capabilities among students with different accommodation arrangements. Time Management Capabilities Compared by Source of Financial Support The results of One-Way ANOVA show a statistically significant difference in the ability of students to formulate life objectives among students with different financial support (p < 0.05). Formation of life objectives was further tested by Scheffe’s method (please see Table 8 on following page) to determine which mean scores for financial support were significantly different from the others. Statistically significant differences were found for the pair of students receiving government loans and those who were supported by their families. Students with government loans reported better time management skills than students whose education was financed by their families. Table 8. Time Management Capabilities Compared by Source of Financial Support Variance F P The analyses of problems related to time usage 0.09 0.91 The formation of life objectives 6.35 0.00 The planning of time usage 3.11 0.05 The implementation of projected plans 1.20 0.30 The assessment of time usage 0.44 0.64 The improvement of projected time usage plans and revision of time-wasting activities 1.14 0.32 Overall Capabilities 2.94 0.06 Results and Discussion This study examined both overall time management capabilities and the six steps identified in the time management process. The results are discussed as follows. Analysis of Overall Time Management Capabilities Undergraduate students’ time management capabilities were measured using Lokam’s (2007) questionnaire in a small Thai university, with a similar sample and setting. Results were similar to Lokam’s; most respondents reported a moderate level of overall time management ability. In contrast, a study by Sattayawaksakul et al. (2016) in an industrial company found higher overall levels of time management capabilities among educated, experienced adult employees. Thus, adults’ time management capabilities appear to be better developed than those of university students, which is not a surprising result. An analysis of significant factors that influenced these findings is shown below. Relationships between Demographic Factors and Time Management Capabilities 1. Gender: Gender differences in the planning of time usage step were statistically significant. Female students displayed a higher level of time management abilities than did males. This result is similar to Lokam’s (2007) findings. This may be because brain connections are streamlined at an earlier age in females than in males of the same age, according to a recent study by scientists at Newcastle University in the United Kingdom (Lim, Han, Uhlhaas, & Kaiser, 2015). The researchers concluded that this may explain why females generally mature faster in certain cognitive and emotional areas than males during childhood and adolescence. Another reason may be that females spend more time on their studies, while many male students spend more time on sports and leisure activities. A Residence Hall Dean who works closely with dormitory students was interviewed. His observation was that girls are more responsible, thorough, pay attention, and have better motivation to get things done. On the other hand, males simply agree to do things, but do not take them seriously and are easily distracted. They also engage in more outside class activities such as sports, hanging out with friends, and playing computer games. Many of these students could not prioritize the most important things they were required to do.

85 2. Age: Age differences were statistically significant in the implementation of projected plans. Students aged 18 and 21 displayed higher time management capabilities than did 20-year olds. This may be because most 20-year olds were in their junior year, taking more difficult core and major courses that required more effort. Though these students should be already familiar with the university schedule and environment, they may relax too much and not manage their time as well as before. A Dean expressed his opinion that 18-year old freshmen need to adjust to the university regulations and a new environment. In addition, most of them come right after high school, where rules and regulations are part of school programs. Therefore, it is easier for them to follow rules and adjust to the university’s class schedule. In addition, 21-year old seniors were more mature and better at managing and taking responsibility for their duties, unlike the 20-year olds, who were mostly sophomore and junior students. Though seniors are better prepared to accept responsibility for balancing their studies with other duties, many of them still struggle to do a good job of managing their time well. Many are involved in more extracurricular activities. They face situations where they must choose and make decisions. In addition, they begin to question why so many rules, restrictions, and requirements must be followed. Some choose to break the rules, and so this is a challenging time for them to manage their studies as well as other aspects of their lives. The Dean emphasized that at this time in their lives, this is natural behavior for young people. 3. Faculty of Study: Students in the Faculty of Nursing reported statistically significant differences in scores for the formation of life objectives step and higher scores for the planning of time usage step than students from other Faculties. This may be because nursing students must display higher levels of self-discipline and self-preparedness because they are aware that their profession deals with patients’ lives and health. A study by Park (2015) also showed high levels of career preparation behavior among Korean nursing students. 4. CGPA: Students with low but passing CGPAs (2.01 – 2.50) reported higher time management scores than either students with very high (3.50 or higher) or very low CGPAs (below 2.00). These results were statistically significant for overall time management, as well as for several steps in the process including planning of time usage, implementation of projected plans, and improvement of projected time usage plans and revision of time-wasting activities(CGPAs of 2.51 – 3.00). This indicates that weak or average students often find it necessary to put more effort into managing their time effectively than do either very bright or very weak students in order to achieve acceptable academic results. It also implies that good time management skills may help to compensate for lack of innate scholastic ability, enabling diligent but ordinary students to achieve academic success. 5. Student’s Financial Support: The formation of life objectives step showed statistically significant differences among student groups. Students with government loans displayed better time management skills than students who were supported by their families. This maybe because students with government loans realized their debt burden; therefore, they paid more attention to planning their academic activities. The university’s student finance officer expressed some thoughts regarding this finding. She felt that students who face financial uncertainty often struggle to do their best in the hope of a better life in the future. In addition, government loans do not cover all educational expenses for the entire semester; thus, parents must pay the remaining balances. Government loans are given only to students whose parents have a total income of not more than 200,000 Baht per year. Therefore, many students choose to work in order to lighten their family’s financial burden. Students endeavor to make the best use of their time by balancing study requirements and part-time jobs at the same time. In addition, working helps them to understand the value of money, because they realize how difficult it is to earn. Also, if students owe a large debt, it motivates them to seriously study in order to graduate on time and find a good job. Then they can earn enough to pay back the government loan. Another reason that motivated them to repay their loans was that loan contracts require their parents to be their guarantors, and so they did not want their parents to be in trouble if they did not repay them.

86 Conclusion In conclusion, the students of a private Thai University reported moderate levels of overall time management skills in all steps of a time management process, showing that there is still room for further improvement. Students may improve their time management practices by examining time usage, establishing a timetable or daily schedule, examining the causes for wasted time, and honestly and consistently assessing their time usage. This study’s scope was limited to only six timemanagement steps, but more aspects of time management could be investigated in a future study. About the Author At the time that this article was written, Anchalee Chanpisut was a candidate in the Master of Business Administration Program at Asia-Pacific International University, Muak Lek, Thailand. References Britton, B., & Tesser, A. (1991). Effects of time-management practices on college grades. Journal of Educational Psychology, 83(3), 405-410. Retrieved from http://search.proquest.com/docview/62904688?account id=39909 Lim, S., Han, C., Uhlhaas, P., & Kaiser, M. (2015). Preferential detachment during human brain development: Age- and sex-specific structural connectivity in Diffusion Tensor Imaging (DTI) Data. Cerebral Cortex 25(6), 1477–1489. Retrieved from https://doi.org/10.1093/cercor/bht333 Lokam, P. (2007). Time management capabilities of undergraduate students at Srinakharinwirot University (Master’s thesis). Retrieved from http://thesis.swu.ac.th/swuthesis/Hi_Ed/Pim_L.pdf Macan, T., Shahani, C., Dipboye, R., & Phillips, A. (1990). College students’ time management: Correlations with academic performance and stress. Journal of Educational Psychology, 82(4), 760-768. Retrieved from https://pdfs.semanticscholar.org/ea72/13c01261e9e172f1c362be3781df30f6f5b7.pdf Misra, R., & Mckean, M. (2000). College students’ academic stress and its relation to their anxiety, time management, and leisure satisfaction. American Journal of Health Studies, 16(1), 41-51. Retrieved from https://www.researchgate.net/publication/209835950_College_students'academic_stress_and_its_r elation_to_their_anxiety_time_management_and_leisure_satisfaction Mpofu, E., D'Amico, M., and Cleghorn, A. (1996). Time management practices in an African culture: Correlates with college academic grades. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 28(2), 102-112. Retrieved from http://dx.doi.org/10.1037/0008-400X.28.2.102 Park, S. (2015). Effects of discipline-based career course on nursing students' career search self-efficacy, career preparation behavior, and perceptions of career barriers. Asian Nursing Research 9(3), 259-264. Retrieved from https://www.sciencedirect.com/science/article/pii/S1976131715000626#! Persky, A., Alford, E., & Kyle, J. (2013). Not all hard work leads to learning. American Journal of Pharmaceutical Education, 77(5), 89. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3687122/ Poser, B. (2003). Time management for students. Retrieved from Counselling and Development Centre, York University. Website: http://www.aui.ma/personal/~A.Cads/1201x/read/crm1/Rdg3.pdf Saketi, P., & Taheri, A. (2010). The relationship between time management and academic achievements among bachelor and master students of Shiraz University and Shiraz University of Medical Sciences. Iranian Journal of Medical Education, 10(3): 293-300. Retrieved from http://ijme.mui.ac.ir/article-1-1422- en.pdf Satija, S, & Satija, P. (2013). Time management: An insight with Indian perspective. SMS Varanasi, 5(2), 115-134. Retrieved from https://slidex.tips/download/time-management-an-insight-with-indian-perspective Sattayawaksakul, D., Maidom, R., Cheewaprakobkit, P. (2016). Time management capabilities: A Case of the industrial workers of the Gulf Cogeneration Company Limited’s Clients. Journal of International Scholars’ Conference, 1(3), 243-255. Retrieved from http://jurnal.unai.edu/index.php/JISCBG/article/ view/411/309 Sevari, K., and Kandy, M. (2011). Time management skills impact on self-efficacy and academic performance. Journal of American Sciences, 7(12), 720-726. Retrieved from http://jofamericanscience.org/journals/ am-sci/am0712/093_7696am0712_720_726.pdf Tanriogen, A., and Iscan, S. (2009). Time management skills of Pamukkale University students and their effects on academic achievement. Eurasian Journal of Education Research, 35, 93-108. Retrieved from http://www.ejer.com.tr/0DOWNLOAD/pdfler/eng/377153884.pdf

87 Worthley, R., MacNab, B., Brislin, R., Ito, K., & Rose, E. (2009). Workforce motivation in Japan: an examination of gender differences and management perceptions. The International Journal of Human Resource Management 20(7), 1503-1520. Retrieved from https://doi.org/10.1080/09585190902983421

Catalyst ISSN 2408-137X, Volume 18, 2018 88 Geographical Location and Internationalization: Small and Medium Enterprise Entry into Cambodia, Laos, Myanmar, and Vietnam Suwaree Tantanawat Abstract Porter (2000) proposed the notion of location as a competitive advantage, a way to generate advantages for regions, nations, and even firms. Small and Medium Enterprises (SMEs) are one factor in the quest to pursue national prosperity. SMEs may create competitive advantages for countries as well as at the regional level, a point that is understood by the Association of Southeast Asian Nations (ASEAN) even though public sector support for SMEs is very limited, especially in the internationalization process. Lack of consistent policy initiation and implementation has led to uncertainty for business firms. The CLMV region consisting of Cambodia, Laos, Myanmar, and Vietnam is an area that other ASEAN members may explore to find opportunities for international market expansion. This paper highlights factors that influence the internationalization process in respect to the competitiveness of location. The proposed model identifies factors that influence international market expansion, which include product competitive advantage and firm characteristics. These influences are moderated by market accessibility, financial resources, innovation, and networking. The paper also suggests several propositions intended to increase the effectiveness of the internationalization process for SMEs that are interested in regional expansion. Keywords: Small and Medium Enterprises, Internationalization, CLMV, competitive location Introduction The process of internationalization involves not only firms, but also economic activities that take place in more than one country. Internationalization refers to firm economic activities that take place outside of home country borders. The external expansion of firms leads to growth in both national economies and the world economy (Ruzzier, Hisrich, & Antoncic, 2006). Internationalization developed through multinational firms or large corporations that were ready for cross-border expansion. Axinn and Matthyssens (2002) stated that every step in the internationalization process remains significant due to rapid environmental changes. Multiple types of economies – e.g. global economy, service economy, new economy, value economy, and the connected knowledge/ network economy – remain integral components in managerial decision making. Many previous researchers and practitioners have focused on the factors that determine the internationalization process. When firms enter international markets, they must consider various entry modes. Internationalization enriches firm capacities in terms of managerial skills and risk mitigation in business practices (Pinho, 2007; Cort, Griffith, & White, 2007; Marchi, Vignola, Facchinetti, & Mastroleo, 2014). Porter (2000) mentioned internationalization’s relevance in the context of competitiveness. This is because competitiveness has become a core issue for generating advantages across nations, regions, and even firms. Snowdon and Stoehouse (2006) explored this idea from Porter’s viewpoint. Delgado, Ketels, Porter, and Stern (2012) conducted research in microeconomic perspectives with funding granted by the US National Bureau of Economic Research. This research study aimed to define the foundation of competitiveness by identifying both macroeconomic and microeconomic factors that influence the prosperity of nations. Porter tried to fill the gap in microeconomics that he had found. The Competitive Advantage of Nations (1990) provided a framework to integrate relevant factors that influence the prosperity of nations. Figure 1 shows the determinants of National Competitive Advantage. The diagram presents associations in the form of a diamond-shaped framework. Each factor is a determinant that leads to success in the internationalization process. The advantage of clusters of firms in a single geographical location increases competitiveness. The geographical concentration of firms allows more efficient

89 access to specialized suppliers, information, and workforces. However, even Porter’s well-known diamond theory has been scrutinized and not seen as a new trade theory (Smit, 2010). Comparative advantage is not similar to country specific advantages; thus, cluster and competition are not a trade pattern. Moreover, factor conditions such as labor productivity and labor mobilization are able to generate prosperity for nations. Figure 1. Competitive Advantage of Nations (Porter, 1990) Porter’s perspective emphasized the performance of small and medium sized enterprises (SMEs). The significance of SMEs in the global economy is not less than that of large multinational corporations (Ruzzier, Hisrich, & Antoncic, 2006). The cost of production always plays a significant role in firms’ decision making processes, which require accurate and timely information. Marchi et al. (2014) suggested that a recent problem affecting SMEs is their entry into markets, especially when SMEs attempt to venture into international markets, where they often experience a fluctuating rate of success. In addition, limitations affecting SMEs’ international expansion occur not only in developed countries, but also in developing countries. SMEs in the ASEAN region also face similar problems. The process of internationalization in member countries still needs more support and guidance. The countries of Cambodia, Laos, Myanmar and Vietnam (CLMV) are often desired destinations. SMEs in Thailand especially are still exploring opportunities for international expansion. Therefore, managerial decision practices and research findings pertaining to large corporations must be modified to provide guidelines and implementation models for SMEs (Fernhaber, Gilbert, & McDougall, 2008; Fornes, Cardoza, & Xu, 2012). The goal of this article is to explore SMEs’ opportunities and constraints in the internationalization process, because their success will lead to prosperity and long term competitive advantages. The expansion of foreign SMEs from neighboring countries into the Cambodia, Laos, Myanmar, and Vietnam (CLMV) region is one of this article’s main contributions, and will be discussed accordingly. In addition, regional competitiveness plays a significant role in defining the overall quality of a country as a place to do business. Country specific priorities are important factors in upgrading overall competitiveness (Snowdon & Stoehouse, 2006; Delgado et al., 2012). Regional economic integration among Cambodia, Laos, and Vietnam may lead to bargaining power. Economic reforms in

90 these three countries have taken place slowly due to socialist economic systems. Industrial manufacturing output differs due to dissimilar levels of technological development (Chheang & Wong, 2012). An optimistic outlook for this region shows there are more opportunities for entrepreneurs who are trained and ready for international expansion. Most internationalization processes monitored for this study highlight the importance of factors that determine success. These factors include network development by top management, internal commitment, orientation, positioning and time, and recruiting the right staff to provide services that meet the needs of multicultural customers. Finally, top executives require appropriate recommendations from experts with experience in monitoring and identifying the key attributes necessary for internationalization. The countries in the CLMV region, which consist of Cambodia, Laos, Myanmar and Vietnam, require more studies regarding their readiness for expansion from the perspectives of both researchers and practitioners. Hall (2003) determined SME policy and framework in Association of Southeast Asian Nations (ASEAN) countries has created employment and industrial competitiveness, since SMEs stimulated a wide range of jobs, which lead to competitive advantages (Hall, 2003; Pinho, 2007). The major contributions still focused on the readiness and awareness of SMEs. Innovation is a key factor that influences SME competitiveness and international expansion (Ruzzier et al., 2006). However, while limited availability of research in the CLMV region remains a major constraint, theories developed from studies of multinational corporations can be modified and applied in practice. Most researchers have focused on large corporations, and conceptual research is more common than empirical studies (Wyatt, Pathak, & Zibarras, 2010). Collaboration between SMEs and large firms that pursued internationalization expansion was undertaken in particular contexts (Ruzzier et al., 2006; Wyatt et al., 2010). The SMEs normally considered how to enter markets. Ruzzier et al. (2006) affirmed that collaboration remains a significant aspect in market entry approaches. The mitigation of market risk was also a significant aspect. An expected outcome of this study is that SMEs operating in CLMV countries will gain knowledge about current market situations. The overall region can hopefully gain from the benefits of economic integration as well. Hall (2003) confirmed that business environments should be taken into consideration when formulating SME support policies. Encouragement of a policy framework throughout the region may enhance national, regional, and global competiveness respectively (Snowdon & Stoehouse, 2006). Moreover, strengthening cooperation between governments and regional parties may increase supportive interventions to support the fundamental needs of SMEs that wish to pursue international expansion. This article aims to identify significant attributes in SME development in the CLMV countries. Hlaing (2014) highlighted the important roles of SMEs in CLMV countries, but obstacles, both tangible and intangible, were identified. These include market accessibility, financial assistance, and technological innovation as challenges to SME development. Lim and Kimura (2009) found that international production/distribution networks in the CLMV region are quite sophisticated. SMEs in neighboring countries that have tried to enter CLMV markets have endeavored to be competitive by designing and marketing new products. Therefore, the objectives of this study are the following: a. To explore factors influencing international expansion by nearby SMEs in the CLMV region. b. To investigate essential policy framework requirements for SMEs such as market access, financial availability and human capital. Literature Review International Expansion of SMEs Political, economic, social, and technological issues must be considered SMEs’ market entry decisions. There are many factors to be considered before selecting an appropriate market. Yiu and Makino (2002) pointed out that transaction costs, which determine the cost of business operations and influence the choice of entry mode, are an important factor that should be considered.

91 In addition, a cross-national cultural framework was proposed by Hofstede (2003). His four measures of culture are power distance, uncertainty avoidance, individualism, and masculinity; all of these are major factors affecting internationalization (Berry, Guillen, & Zhou, 2010). Consequently, Berry et al. (2010) extended the measurement of cultural factors as part of their theoretical attributes and integrated them with the institutional approach. Meanwhile, a recent paper by Hitt (2016) compared the institutional approach to theories of culture and institutional distance. The author categorized these factors by national institutions, and explored the relationship between specific institutions and strategies. This is a classical problem faced by small firms that wish to expand internationally, but don’t know which places are appropriate for them. For these reasons, international market selection has become an important consideration. Especially when venturing abroad for the first time, market selection is an essential issue. Market situations must be evaluated first to mitigate risk and avoid failure (Marchi, Vignol, Facchinetti, & Mastroleo, 2014). Competitive Location Decision Making A strategic location can support firm competitive advantages with respect to production capacity, additional profit, business expansion, better service to customers, and cost reduction (Mazzarol & Choo, 2003). Competitive advantage will not only determine a firm’s productivity, but also its prosperity in a suitable location for competing with regional rivals. Intensive technological advancement is able to generate superior productivity for firms. Firms with advanced technology can make progress within their industry as they integrate their knowledge. Mazzarol and Choo (2003) suggested that owners of small firms should normally seek a location, and especially a manufacturing site, that is close to their home base, rather than struggle with complicated logistical transportation arrangements. This study takes a broad view of small and medium enterprises in terms of governmental support. Table 1. Internationalization and Focus Source SME Internationalization Focus Pinho (2007) Ownership-specific advantage Location-specific advantage Managerial-specific advantage Ownership structure Ruzzier et al. (2006) Human capital Social capital Firm characteristics (Number of employees, sales) Environment characteristics (Domestic environment, International environment) Process Wyatt et al. (2010) Consultancy selection process (human resources) Indrawati (2012) Product competitive advantage Market attractiveness Technology and human resources Minai & Lucky (2011) Lucky (2012) Individual determinants External determinants Firm characteristics Moderating effects of location and culture Fornes et al. (2012) The need to catch up Government roles Possible institutional dependence Culture Marchi et al. (2014) Market/Perceived Accessibility Market/Perceived Attraction

92 SME research approaches are often adapted from multinational firm concepts and theories. Many researchers have attempted to prove similarity among the constraints and problems that small firms face as compared with those of large firms (Boter & Lundström, 2005). Table 1 shows that firm performance is the key success measurement identified by all authors in the internationalization process. The key factors that influence firm internationalization are as follows. Hitt (2016) reviewed the motives in multinational enterprise (MNE) decision making to prepare their international strategies. Smit (2010) also elaborated on the diamond theory or competitiveness of nations to compare trade theories and economic perspectives. These theories are still being monitored as to how well this framework can explain the concept of international trade among countries. Meanwhile, the US National Bureau of Economic Research constructed a working paper by extending Porter’s theoretical framework to define the ultimate foundation of competitiveness of nations (Delgado et al., 2012). The generic approach that is used presently might not be appropriate in competitive markets. Therefore, the author aimed to examine and refine the generic approach to use resources to support strategic management decision making (Parnell, 2006). International Expansion of SMEs in CLMV Region Hall (2003) noticed that the ASEAN economies have generally adopted the Japanese development pattern approach to establish SME policy, which can be seen in a policy framework. ASEAN generally provides information access to SMEs regarding market accessibility, which is highlighted as a priority task. Market research and intelligence have been initiated to support SME accessibility to markets. The concept of one-stop service, if implemented as in developed countries, represents an appreciated outcome for ASEAN economies, but slow development policy implementation by governments can still pose a handicap. The lack of consistent policy implementation and initiation leads to uncertainty in business firms (Hall, 2003; Chheang & Wong, 2012; Hlaing, 2014; Sisounonth & Kongmanila, 2014). Table 2 shows the proportion of economic activity accounted for by domestic SMEs in the CLMV region; it is evident that these businesses represent a large percentage of economic activity in many sectors across the region. Table 2. SMEs Participation in Economic Sectors in CLMV Countries* Cambodia Laos PDR Myanmar Vietnam 93% of economic sector, processing primary products for the domestic market 99% of of economic sector, engaged in retail, wholesale trade, and services, and semiprocessing businesses (SMEPDO, 2010) 96% of economic sectors in both rural and urban areas; (92% of manufacturing sector) 99% represented as SMEs, accounting for 77% of workforce, 80% of retail market *Adapted from Hlaing, 2014 Hlaing (2014) highlighted that in CLMV countries, insufficient sources of financing remains a challenge. SMEs have difficulty in obtaining loans from public and privately-owned banks due to high collateral requirements and delays in processing loans and transactions, as well as administrative barriers. They are discouraged from taking loans from informal banking sectors because of high interest rates. All of the surveyed enterprises have loans, though use of formal banking services is very limited because of institutional policies and procedures, although they are willing to take loans from government. The government opened an SME bank recently, but they find it difficult to lend to the SME sector due to improper records and lack of information. They need to develop transparency so that short-term loans for enterprises will no longer be a problem, and their financial needs can be met. Nearly all surveyed enterprises started with their own investment capital, and borrowed from informal banking sources with high interest rates.

93 Table 3 outlines constraints in CLMV countries. Fundamental needs can be classified into 4 categories: market accessibility, sources of finance, technological advancement, and management of companies themselves. Some small enterprises specifically referred to the need for managerial capability and skills in rapidly changing environments. Table 3. SME Constraints in CLMV Countries* Market Access Financial Resources Technology Management - Lack of market information and market access - Opportunity to expand in new markets - Global and regional competitiveness increase - Limited credit and sources of financing - Collateral required; often issued at very high interest rates - Inadequate access to financing - Limited sources of investment in SME sector - Product need to meet international standards - Connectivity, information, & IT - Limited access to resources, technology, and government support policies - Lack of management skill *Sources: Hall, 2003; Chheang & Wong, 2012; Hlaing, 2014; Sisounonth & Kongmanila, 2014 International Expansion of SMEs in Thailand Lim and Kimura (2009) concluded that Southeast Asian economies face the usual problems of level of entrepreneurial skill, expertise, networking and financial accessibility. Thailand is one of the countries that is still struggling to overcome these limitations. Empirical research confirms that multinational corporations in heavy industries have received significant support when they expand internationally. Some essential technology and knowledge may be transferred to SMEs (Hitt, 2016) from these corporations. However, other industries still struggle with conventional constraints. Research Approach As a result of this review of SME internationalization, a conceptual framework for countries in the CLMV region was created from key literature sources. The literature from both empirical and conceptual research has influenced development of an approach to determine SME performance when expanding internationally. Figure 1. Proposed Conceptual Framework Product Competitiveness Firm Characteristics - Experience (International) - Human Capital Firm Performance SMEs Policy - Market Access - Financial Availability - Innovation

94 Research Propositions This research proposes a conceptual framework as follows. Factors Influencing SMEs International Expansion 1) Product Competitive Advantage Indrawati (2012) divided a product’s competitive image into three elements: product character, competitive product value (price and quality), and product fulfilment when compared to competitors. The product/customer focus is important as the enterprise ascertains if it is able to produce the right product to meet customer needs (Sisounonth & Kongmanila, 2014). Proposition 1: Product competitiveness has a direct impact on firm performance when an SME is considering international expansion in the CLMV region. 2) Firm Characteristics Minai and Lucky (2011) considered the need for firms’ employees to possess particular sets of professional skills. The nature of a firm is largely determined by the owner-managerial skill that can enhance a firm’s overall performance. Wyatt et al. (2010) wrote of the overwhelming need for job analysis in the context of consultancy. The right person who is able to operate a business or give appropriate recommendations will be a beneficial person for the firm. Human capital is a crucial issue that SMEs face not less than large corporate firms. In addition, the best practice of selecting someone suitable to be the best advisor should be considered based on experience gained from international expansion. SMEs need more support from management teams in the decision-making process. The owners and management should be directly involved in other processes as well (Mazzarol & Choo, 2003). Proposition 2a: Firm characteristics (international experience) has a positive influence on firm performance in international expansion in the CLMV region. Proposition 2b: Firm characteristics (human capital) has a positive influence on firm performance in international expansion in the CLMV region. Moderating Factors Influencing SMEs’ International Expansion 3) Market Accessibility Small firms need to be supported with information to use in selecting markets in which to participate given highly competitive environments (Marchi et al., 2014). Delgado et al. (2012) defined the foundation of competitiveness as well as the factors that influence the prosperity of nations, which include both macroeconomic and microeconomic factors. Furthermore, even Porter’s well-known diamond theory is still being scrutinized. Parnell (2006) stated that to enter competitive markets, it is necessary to adopt plans that are in line with the current situation. The generic approach that is still presently used might not be appropriate in competitive markets. The generic approach shows how to use resources to support strategic management decision making. The real value of the topic is intended to define the up-to-date generic approach that can continue being used for a long period. Proposition 3a: Product competitiveness has a positive influence on SME performance in international expansion to the CLMV region when moderated by policies that support market access. Proposition 3b: Firm characteristics (international experience) has a positive influence on SME performance in international expansion to the CLMV region when moderated by policies that support market access. Proposition 3c: Firm characteristics (human capital) has a positive influence on SME performance in international expansion to the CLMV region when moderated by policies that support market access. 4) Financial Resources Hall (2003) pinpointed accessibility to financial resources as a major factor affecting the growth and success of SMEs. There is an urgent case for building up efficient financial markets and regulatory infrastructure. Unaffordable interest rates are also an important issue that can be a barrier

95 to SME access to finance resources. Financial problems are normal and common problems in SMEs. Their limited accessibility to financial resources and obvious lack of experience in complicated lending processes can also prove to be a barrier (Sisounont & Kongmanila, 2014). The promotion of financial accessibility is also limited in particular cities and regions. Inequality is also a big problem for SMEs that have inadequate information and knowledge, particularly in less developed areas (Fornes, Cardoza, & Xu, 2012). Proposition 4a: Product competitiveness has a positive influence on SME performance in international expansion to the CLMV region when moderated by policies that support availability of financial resources. Proposition 4b: Firm characteristics (international experience) has a positive influence on SME performance in international expansion to the CLMV region when moderated by policies that support availability of financial resources. Proposition 4c: Firm characteristics (human capital) has a positive influence on SME performance in international expansion to the CLMV region when moderated by policies that support availability of financial resources. 5) Technology and Innovation The most important factor for SMEs in attaining success is innovation. Successful SMEs not only justify the innovation they create, but they need to bring innovation to an international level and let markets recognize it. To be competitive, innovation requires flexibility suitable for market situations, and the time for launching new products in the market is important. Technology is the key economic driving force, and technological advancement may also enhance scientific know-how, leading to rapid changes in market context as well as in demand. Therefore, technical capacity needs to be monitored since it is a key factor. Flexibility in production processes helps firms adapt to significant market changes. More flexibility can minimize risks and uncertainties in firm operations (Axinn & Matthyssens, 2002; Hall, 2003; Ruzzier et al., 2006; Indrawati, 2012). In many industries, SMEs have received helpful technology transfers. ASEAN recognizes the importance of encouraging governments of member countries to continue their support of innovation and technology transfer (Hall, 2003). Proposition 5a: Product competitiveness has a positive influence on a firm’s performance in international expansion to the CLMV region when moderated by policies supporting innovation. Proposition 5b: Firm characteristics (international experience) has a positive influence on performance in international expansion to the CLMV region when moderated by policies supporting innovation. Proposition 5c: Firm characteristics (human capital) has a positive influence on performance in international expansion to the CLMV region when moderated by policies supporting innovation. 6) Network Approach to Internationalization Network-based business research focuses on international relationships among members. Long-term relationships can be enhanced by sharing knowledge regarding technological innovation, financial accessibility to markets, and access to the international environment. Evidence can be found that knowledge sharing, networking, and cooperation among members enhanced awareness of opportunities (Ruzzier et al., 2006; Basly, 2007) Proposition 6a: Product competitiveness has a positive influence on a firm’s performance in international expansion to the CLMV region when moderated by policies supporting international networking. Proposition 6b: Firm characteristics (international experience) has a positive influence on a firm’s performance in international expansion to the CLMV region when moderated by policies supporting international networking.

96 Proposition 6c: Firm characteristics (human capital) has a positive influence on a firm‘s performance in international expansion to the CLMV region when moderated by policies supporting international networking. Firm Performance This study of SMEs takes into account the performance of small businesses, as well as their entrepreneurial performance. However, within the context of this study, the term “firm performance” is used in order to align with general context. Furthermore, small business performance measurement has been viewed in two major dimensions: financial and non-financial measures. Firm performance may be related to human capital, financial capital, and social capital. Thus, researchers are divided on which of these measurements provide the best way to measure small firm performance (Minai & Lucky, 2011; Sisounonth & Kongmanila, 2014) Discussion and Conclusions This proposed conceptual framework seeks to define the major factors that influence SME performance in international expansion to the CLMV region. Product competitiveness and firm characteristics have been empirically shown to be associated with successful international expansion by SMEs (Lucky & Minai, 2001; Mazzarol & Choo, 2003; Indrawati, 2012, and Sissounonth & Kongmanila, 2014). Appropriate market accessibility, financial availability and support, and technological innovation determine the successful level of international expansions (Axinn & Matthyssens, 2002; Hall, 2003; Parnell, 2006; Ruzzier et al., 2006; Indrawati, 2012). Nevertheless, Lim and Kimura (2009) pointed out the importance of regional networking cooperation. Southeast Asian countries face many challenges if they wish for such cooperation to become a reality. Therefore, the conceptual model suggests that networks that accelerate product competiveness are an important factor in achieving success (Ruzzier et al., 2006; Basly, 2007). In some countries, SMEs in certain industries have received special attention from the public and private sectors, while those in other industries are still hoping for similar opportunities. The classical constraint remains financial resource availability. Cooperation between the government sector and private sector is also one of the key areas that might help SMEs counteract the obstacle of financial limitations. Innovations that enable financial institutions to offer assistance in a variety of packages and encourage repayment by SMEs (Lim & Kimura, 2009) enhance their chances of success. This study not only highlighted a conceptual model for SME development in the CLMV region, but also offered a significant contribution to SME practitioners. It provides guidance to facilitate both academic research and real managerial practice in small and medium enterprise firms. Academic research and real industrial experience are expected to enhance the goal of SME internationalization. Attainment of success will not only affect the business firms themselves, but also contribute overwhelmingly to development of national and regional industries and societies. Pinho (2007) discussed the importance of international expansion by firms if they have the ability to innovate and create market capacity, as well as to select the right markets for themselves. International expansion by SMEs will tend to be successful in the long run because of low cost operations and preparation that allows avoidance of risks. Research about the internationalization process of SMEs and multinationals – especially in the CLMV region – is still insufficient (Boter & Lundström, 2005). Research and practices by large corporations needs to be adapted by SME participants in the context of the CLMV region. Both qualitative and quantitative research in this area will be needed in the future. Empirical research in the region is also insufficient for both academic researchers and practitioners. More research about startups may provide opportunities for network cooperation to become stronger as these fledgling businesses encounter an increasingly competitive business world.

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Catalyst ISSN 2408-137X, Volume 18, 2018 99 How Young Consumers in Thailand Respond to Global Sporting Apparel Brands: The Mediation Effect of Self-Identification Lokweetpun Suprawan Abstract Competition in global markets is not only fierce, with rivalry among various brands in the same industry, but also because of the threat of an increasing number of counterfeit products. The concept of brand equity studies how brands may become more prominent in the marketplace. Thus, this study investigates the causal relationships of (i) brand awareness and brand image and; (ii) brand image and self-identification with global consumer culture. This study also examined the mediation effect of self-identification with global consumer culture on the relationship of brand image and loyalty. The research was conducted on 276 young Thai consumers asking about global sporting apparel brands. The statistical analysis used for hypothesis testing was regression analysis, with mediation testing included. The findings suggest that the relationship of brand awareness and brand image is a causal relationship, indicating that stronger brand awareness will lead to stronger brand image. It was also found that brand image will influence consumer self-identification with global consumer culture for global sporting apparel brands. Finally, the mediation effect of self-identification with global consumer culture on the relationship between brand image and brand loyalty was found to be fully mediated. Keywords: Global Brand Awareness, Brand Image, Self-Identification, Brand Loyalty, Global Brand Introduction The existence of globalisation has increased competition among brands all around the world. With lower barriers to globalisation, a number of products have expanded their markets in the AsiaPacific Region. Global brands can be defined as brands that offer standardised positioning and image in most countries, with well recognized consumer perceptions towards their products (Frank & Watchravesringkan, 2016). Sporting goods is one industry that has experienced global growth, and which now includes sport events, sport sponsorship, and sports media as well as the tangible sport product categories—apparel, athletic shoes, and sporting equipment (Gerke, Chanavat, & BensonRea, 2014). Just like many other product categories, it has encountered counterfeit products, and it turns out that sporting goods face a relatively high level , compared with other product categories (Chiu, Lee, & Won, 2014). In other words, sporting good brands are not only competing with other genuine brands in the same categories, but they also have to fight against counterfeit products in the market. According to the study of (Weisheng & Keat, 2016), evidence was found that Singaporian and Taiwanese consumers are more than likely to buy counterfeit sporting good brands if they have positive attitudes towards counterfeit products, positive affirmation from their friends, and the ability to control the purchase of counterfeit products. However, the relationship between brand consciousness and intention to purchase counterfeit sporting goods was found to be negative. This suggests that if consumers have more knowledge about brands, they will be more likely not to buy counterfeit products. For this reason, creating strong brand equity is essential for protection from the threat of counterfeit products and achievement of firm financial goals. (Frank & Watchravesringkan, 2016). Moreover, for brands to survive globally, consumer responses towards the brands play an important part in this process. The challenge is to generate brand equity among customers across national borders, as customer-based brand equity will lead to favorable marketing outcomes for the brands (Keller, 1993). Specifically, young consumers are an important segment in this market, with much interest from practitioners and academia (Frank & Watchravesringkan, 2016). Thus, this research is