GSBA: Dissertations
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- ItemThe role of customer voice in customer evaluation of service recovery(National Institute of Development Administration, 2018) Phimai Nuansi; Piya NgamcharoenmongkolThis dissertation builds upon a service recovery framework to establish new perspectives on customer voice in a service recovery context. Specifically, four studies were conducted to determine how to turn customer voice to opportunity in recovering from service failure. The first study provides an integrative review of the literature associated with service failure situations. This study combines two major research streams and proposes the “service failure management process model” to explain the end-to-end process of service failure in six sequential phases. The second study deals with the negative emotions that arise as a consequence of service failure by employing venting interaction as an emotion management strategy. The study tests how this strategy affects customer evaluation of service recovery, specifically in terms of perceived justice, post-recovery emotions and postrecovery satisfaction. Drawing on the role of initiation in the service recovery process, the third study explores how inviting customers to voice dissatisfaction enhances service recovery evaluations, specifically in terms of perceived justice, post-recovery satisfaction and negative word-of-mouth. Finally, the fourth study sheds light on the role of customer voice management in sustainable marketing by examining the interaction effect between compliant initiation and coping potential on service recovery evaluations, specifically in terms of perceived justice and post-recovery satisfaction. Three separate scenario-based experiments were carried out in a bank service setting. Partial least squares structural equation modeling was conducted to test the research hypotheses in study 2. Study 3 used multivariate analysis of covariance as a statistical technique. Analysis of variance was used to test the hypotheses in study 4. As hypothesized, this dissertation demonstrates that venting interaction and voice initiation can yield favorable recovery outcomes. Specifically, venting interaction plays an important role in lessening negative emotions and enhancing perceived justice and satisfaction. In addition, preferable outcomes of perceived justice, satisfaction and negative word-of-mouth intention were found when service recovery was provided based on voice invited by the service organization, and the effects on interactional justice and satisfaction were found to be stronger for low coping potential customer. These findings suggest that service managers should encourage customers to voice their complaints and should use the customers’ voice as an opportunity to enhance positive service recovery outcomes.
- ItemMobile commerce adoption of micro retailers in emercing economies(National Institute of Development Administration, 2018) Tanikan Pipitwanichakarn; Nittaya WongtadaIn this dissertation, the original Technology Acceptance Model (TAM) has been employed as the core theory across three studies in an attempt to establish a theoretical framework for determining the intention of street vendors to adopt a mobile commerce (m-commerce) application. The model has two tenets: perceived usefulness and perceived ease of use. Although the classical TAM is well known and well respected as a robust predictive framework, it seems to be situation specific and must be modified to accommodate other factors affecting the behavioral intentions of particular groups. No empirical study has used the TAM to investigate the perceptions and behaviors of street vendors. Therefore, to enhance our understanding of m-commerce adoption among micro vendors, the three studies that form the basis of this dissertation have examined the impact of external and internal factors on vendors as they embrace a new form of technology. The first study focused on the unique characteristics of vendors that affect their adoption of m-commerce. The features of trust in service providers, entrepreneurial orientation, and product differentiation were integrated into the TAM. Product differentiation was employed as a moderating variable on the effect of perceived usefulness on behavioral intention, whereas entrepreneurial orientation was assumed to affect a vendor’s trust in a service provider directly and to influence m-commerce adoption indirectly. A pen-and-paper survey was administered to 370 street vendors in Bangkok; 356 of the usable surveys were analyzed. Structural equation modeling was employed to analyze the data. This study contributes to the existing technology acceptance literature in the following ways: First, it shows that the predictive power of the TAM is strong and valid for street vendors. Second, it reveals that entrepreneurial orientation and technology adoption are related and that the connection continues throughout the decision-making process (i.e., these are trust and system characteristics that are otherwise known as usefulness and ease of use). Finally, it shows that the degree of product differentiation strengthens the positive relationship between perceived usefulness and the intention to use m-commerce. The first study found that not all street vendors were ready to adopt this new trading method. Vendors at various stages of adoption weighed different factors as they made decisions. Based on these findings, the second study tested how vendors at different stages approached m-commerce adoption. The vendors were classified as being in either the initial stage of adoption or the advanced stage of adoption. The role of trust and the perceived enjoyment were added to the TAM in this study. Face-to-face interviews using a structured questionnaire were conducted with 430 street vendors in Bangkok; 415 usable surveys were analyzed. By applying K-means cluster analysis, two segments were found, one with 200 initial adopters and one with 215 advanced adopters. A multi-group analysis was employed to investigate the difference in relationships between the two groups, and the findings revealed significant similarities and dissimilarities between them. Both initial and advanced adopters emphasized trust in the service provider. The first group relied more on perceived ease of use and perceived enjoyment in choosing m-commerce adoption but depended less on perceived usefulness. In the second group, the influence of perceived ease of use and perceived enjoyment significantly decreased but the effect of perceived usefulness significantly increased. In addition to perceived usefulness, perceived ease of use, and trust, online reviews are significant tools for promoting the adoption of a new technology. For instance, the integration of online reviews into the TAM can serve as an important predictor of the intention to use mobile banking. The impact of online reviews on behavioral intention and consumers’ decisions has indicated complex relationship patterns and has been context specific, which suggests the possibility of an interaction effect. For this reason, in the final study, an experiment was conducted to investigate the interaction of online reviews, perceived ease of use, and trust in enhancing the perceived usefulness and adoption of m-commerce. This study employed a 2 (perceived ease of use: high vs. low) x 2 (trust in the service provider: high vs. low) x 2 (online review: positive vs. negative) between-subjects design, resulting in eight experimental groups. A pen-and-paper survey was administered to street vendors in Bangkok. Of 280 cases, 16 cases were unusable and were deleted from the dataset; this left 264 cases for data analysis. The level of the online review was manipulated, whereas the degrees of perceived ease of use and trust were measured. The experiment revealed that the perceived usefulness was affected by online reviews when users found incongruent information in them (e.g., when reviewers reported that they found a high level of ease of use of the technology but had only a low level of trust in the service provider). In other words, users who read positive reviews were more likely to feel that m-commerce had a great deal of perceived usefulness. On the contrary, the perceived usefulness was not affected by online reviews if users found congruent information in them (e.g., when reviewers reported that they found a high level of ease of use and also had a high level of trust in the service provider). This dissertation has attempted to offer an alternative to the inadequate theoretical and managerial understanding of factors that drive m- commerce adoption for micro businesses, and in that regard, it is crucial for identifying predictors of the adoption of m- commerce applications. The results of this research should enable service providers and policy makers to continue to delve into the world of contemporary digital technology business and tailor its marketing strategies towards vendors.
- ItemThe impact of algorithmic trading on the market quality in the stock exchange of Thailand(National Institute of Development Administration, 2019) Pavinee Hassavayukul; Nattawut JenwittayarojeThis dissertation aims to study how the rising algorithmic trading activities in the Stock Exchange of Thailand affects the market quality. I conducted three researches to investigate the impact of algorithmic trading. One is on the impact of algorithmic trading on volatility. Second is on the effect of algorithmic trading on liquidity and third is on the relationship between algorithmic trading and price efficiency. Furthermore, I introduced two new algorithmic trading proxies, namely, algorithmic trading initiated by institutional and foreign investors to investigate the effect of algorithmic trading initiated by these two investors on the market quality. The first research demonstrates how algorithmic trading affects stock volatility in the Stock Exchange of Thailand. The study is based on SET100 stocks from March to December 2016. I implemented the OLS regression to establish the relationship between algorithmic trading and volatility and the two-stage least square regression and the Granger causality test to verify the causal relationship. I showed that on average, algorithmic trading proxy is associated and has a causal relationship with negative volatility. However, individually, algorithmic trading proxy is related to positive volatility. Similarly, algorithmic trading initiated by institutional and foreign investors lower realized and range-based volatility. During the volatile period, algorithmic trading decreases range-based volatility. There is no evidence that algorithmic trading affects realized volatility in the volatile period. The second research investigates the relationship between algorithmic trading and liquidity. In general, I found that algorithmic trading deteriorates liquidity by widening effective spread and lowering share turnover in the short run and reducing liquidity ratio in the long run. I confirmed the result by using the two-stage least square and showed that algorithmic trading causes liquidity to decrease by enlarging effective spread and shrinking share turnover. Information asymmetry is used to explain this phenomenon. An increase in algorithmic trading imposes adverse selection cost onto other investors, causing them to decrease their participation. Algorithmic trading initiated by foreign investors has more profound effect on deteriorating short-run liquidity while algorithmic trading initiated by institutional has more profound effect on decreasing long-run liquidity. During the volatile period, algorithmic trading also associates with lowering liquidity for all measures. The slope coefficient of algorithmic trading during volatile period is higher than during the whole sample except for the share turnover. Therefore, algorithmic traders have less effect on lowering share turnover during the volatile period than during the entire period. The third research determines whether the rise of algorithmic trading enhances price efficiency. There is no evidence that algorithmic trading influences price efficiency. However, when probing further, I found that algorithmic trading initiated by institutional and foreign investors and their interaction terms decrease pricing error, facilitating price efficiency. Furthermore, algorithmic trading initiated by foreign investors has a larger effect on augmenting price efficiency. During the volatile period, algorithmic trading, on the contrary, decreases price efficiency and enlarges price errors. Finally, this dissertation investigates the effect of algorithmic trading on market quality in detail and provides insightful conclusion for policymakers, regulators and investors in order to regulate or react to the increase in algorithmic trading strategies in the Stock Exchange of Thailand.
- ItemIn the race for sustainability and financial excellence: advancing firms' investment in knowledge assets and innovations(National Institute of Development Administration, 2021) Khalil, Muhammad Azhar; Kridsda NimmanuntaThis dissertation focuses on the firms’ investment management decisions regarding knowledge assets (intangible assets), innovation, sustainable investments, and other knowledge management practices through which firms generate both financial benefits and improved environmental outcomes. The previous title of this dissertation was ‘In the race for excellence: the role of knowledge assets and innovation’ (as appeared in the IRB document). The overall agenda is classified and decomposed into three major interrelated sections in an attempt to achieve the goals of this research. The main objective of the first study presented in Chapter 2 is the development and implementation of empirical models to examine the nonlinear impact of the key intangible assets and innovation formation through R&D on the firms’ financial performance of Asian countries. The difference between intangibles (knowledge-assets) and innovation and their combined impact on firm performance remains a puzzle since all types of knowledge assets are not of equal importance. Also, firms with higher spending on innovation can perform well. Integrating these two literature approaches, this study investigates how knowledge-assets and innovation impact firm performance by analyzing the sample of 2958 listed companies of Asian countries during 2015 – 2019. Using time fixed-effects panel regression with industry and country dummies, we observe that different sectors exhibit a strong heterogeneity in their investment level in knowledge assets and innovation. The study finds that more knowledge-assets negatively impact firm performance, but up to a point. The U-shaped relationship found suggests that learning and accumulating capabilities to exploit knowledge assets potential is essential to achieve higher firm value. We also find that firms' more spending on innovation positively impacts firm performance, but only up to a certain level. An inverted U-shaped relationship found suggests a balanced investment in innovation activities to attain improved firm performance. The main contribution of this study lies in identifying novel implications of these considerations, and offer novel evidence of their empirical relevance in four ways: (i) Difference between measures of internally generated and externally acquired knowledge-assets and measures of innovation; (ii) Theoretical and empirical justifications of U-shaped relationship between knowledge-intensity and firm performance; (iii) Support Schumpeterian theory of creative destruction by innovation; (iv) Theoretical and empirical explanations of inverted U-shaped relationship between innovation-intensity and firm performance. Next, we have extended this model in our second study to capture the environmental impacts of the investments in innovation by employing a set of Environmental, Social, and Governance (ESG) indicators presented in Chapter 3. Recently, the level of climate change has substantially been rising; relatively not much is known on ‘how’ companies alter the association between their environmental performance and financial performance within the context of specific elements of innovation: conventional innovation and green innovation. Drawing upon the stakeholder theory and the natural resource-based view of the firm, this research uses firm-level Environmental, Social, and Governance (ESG) data of 462 companies across 7 Asian countries for the period 2015 – 2019, and employs time fixed-effects panel regression with country and industry dummies. We find that measures of innovation (i.e., conventional innovation and green innovation) are beneficial to the firm value. However, the positive effect of conventional innovation on the firm valuation builds at the expense of the environment since it poses a significant threat to environmental quality by positively contributing to carbon emissions. Whilst firms’ investments in green innovation are advantageous to either type of firm performance. Further analysis shows that firms that focus on environmental practices generate significant outcomes, e.g., improved financial performance, suggesting that firms should prioritize their green investments to enhance the innovation outcomes so as to achieve superior financial value and to attract potential environmentally proactive stakeholders. The contributions of this study to the stream of sustainable finance, innovation, and environmental management literature are fourfold. First, firm-level studies on environmental performance have been scant, mainly due to the unavailability of the data. Those who studied this phenomenon primarily relied upon the data collected through survey questionnaires on a specific group of firms within a particular sector and country. Since the growing Asian economies are being successful when evaluated basis on their swift growth, however less effective in preservation of environmental damage compared to other regions. Thus, we conduct this study in the Asian region by using firm-level ESG performance data, which allows us to uncover this existing challenge in cross-sectoral across different countries. Second, previous studies solely emphasize the broader aspects of R&D-augmented innovation and its outcomes on a specific performance measure, instead; in this study, we filled this gap by decomposing innovation into two types in which firms invest simultaneously and investigate their joint impact on various performance measures – financial and environmental. Third, our findings offer insights on the importance of complying with the environmental policies by investing in green innovation with an awareness that bringing an essential change in redesigning products for environmental sustainability via employing non-toxic materials in the production processes, using eco-packaging, eco-friendly labeling, lower energy consumption, and improved recycling and decomposition designs would enable firms to achieve productivity. Productivity improvement in the resources would allow these firms to obtain higher financial and environmental performance. The findings also contribute to the sustainable investment literature by signifying the investments in green innovation, since green innovation serves as the vital component through which firms could obtain market related benefits from their environmental investments, introducing systematically the steady chains of sustainable products and services with improved functionality and layout i.e., better recycling design, reduced energy consumption level, lowered exploitation of natural resources and materials, and improved product/service’s functionality with the better lifecycle. These eco-friendly products/services are shown to be advantageous to the companies in terms of gaining green products’ market share, formation of green branding, and the likelihood of setting premium prices. These benefits are specifically crucial to those firms who longing to be competitive in the green industry and to enhance their revenues and returns on investment. Lastly, one of the limitations of the first study reported in Chapter 2 is that our investigation was limited to the analysis of knowledge assets which, though on a positive note, has been identified and codified in company statements – the objective data were accessible from public domains. However, we did not include intangible knowledge of certain other forms, such as managerial talent, practices, and tacit and explicit knowledge owned by employees which may meaningfully contribute to the firms’ entrepreneurial and innovation process. Against this backdrop, therefore, moving beyond the question of how innovation affects firms’ financial and environmental outcomes, to build theoretical insights and develop an approach that encourages us to estimate a firm-level model to quantify how firms’ innovative capabilities contribute to organizational learning (knowledge sharing) and corporate entrepreneurship. In particular, this study presented in Chapter 4 examines the role of organizational innovative capabilities on the relationship between knowledge sharing, corporate entrepreneurship, and firm performance. Specifically, this study uses the knowledge-based view (KBV) to develop a model that examines the mentioned relationship. Using survey data from 520 participants across 75 service sector companies in Thailand, measurement and structure models are tested through Structural Equation Modeling (SEM) to quantify the impact between constructs. The findings of this study show that knowledge sharing and corporate entrepreneurship positively affect organizational innovative capabilities and firm performance. A positive relationship is also found between knowledge sharing and corporate entrepreneurship. The mediating impact of organizational innovative capabilities strengthens the relationship between knowledge sharing and corporate entrepreneurship on firm performance. These findings contribute to the knowledge-based view, innovation management, and entrepreneurship literature by suggesting that to improve organizational learning and knowledge-based performance, commitment, and understanding of the employees in the entire organization is crucial. Knowledge sharing significantly contributes to developing innovative abilities because of its characteristics of providing firm-specific and socially complex advantages. The way a firm transforms and exploits its knowledge may ascertain its level of innovativeness, such as coming up with certain problem-solving procedures and new product development according to the rapid change in the market demand. We believe that the findings of this research are instrumental to management, practitioners, academics, and policymakers in offering key insights on optimal investment strategies concerning knowledge assets and innovation. This research offers ways to advance innovation such that to achieve higher firm value and better environmental prospects. Finally, this research instigates the tools to effectively organize knowledge as knowledge sharing boosts entrepreneurial practices and contributes towards innovativeness across individuals, groups, units, or the entire organization.
- ItemAnalytical integration and data-driven decision making in complementary and alternative medicine(National Institute of Development Administration, 2019) Kessara Kanchanapoom; Jongsawas ChongwatpolCustomer Lifetime Value (CLV) measures the success of an organization by estimating the net value its customers contribute to the business over the lifetime of the relationship. How can organizations assess their customers’ lifetime value and offer strategies to retain those prospects and profitable customers? The first part of this dissertation offers an integrated view of methods to calculate CLV considering scenarios ranging from finite-and-infinite customer lifetimes to customer migration and Monte Carlo simulation models. In addition to the CLV models, customer segmentation is considered the fundamental marketing activity assisting enterprises to gain a deeper understanding of their customers’ characteristics and needs and, consequently, develop appropriate strategies to strengthen the relationship between them and their customers. Many segmentation models proposed in the literature have been based on specific criteria or attributes such as psychology, demography, or behaviors. At present, the recency (R), frequency (F), and monetary values (M) and cluster analysis models are two popular methods used to create data-driven behavioral segmentation. One of the limitations of those two methods is that most studies focus on transaction-based data, that is, past customer behavior. Therefore, the second part of this dissertation presents a case for integrating CLV and the probability of customer migration, also called the probability that a customer will return in the future, in the segmentation models. The first scenario uses a slightly modified RFM model, replacing the monetary value (M) with CLV. The second scenario integrates recency, frequency, CLV, length of relationship (L), and the probability of migration in the k-means clustering technique. Both CLV, cluster analysis, and RFM models are validated in the context of the healthcare industry, particularly in the area of complementary and alternative medicine (CAM), which refers to practices for people or patients who seek alternative treatment or illness prevention along with or instead of conventional medicines. The results show that understanding CLV and improving customer segmentation models can help the organization develop strategies to retain valuable customers while maintaining profit margins. In addition, Appendix A illustrates a teaching case study on the application of business intelligence and marketing analytics to making proper decisions in a competitor-oriented pricing environment in Complementary and Alternative Medicine (CAM) Industry. This case study helps conceptualize the nature of the complementary and alternative medicine (CAM) Industry, understand the concept, pros, and cons of price wars, outline what factors/criteria are needed to get more insights about customers, utilize the RFM model and cluster analysis to segment customers based on their similar characteristics, illustrate how to calculate customer lifetime value (CLV), utilize the business intelligence framework to justify the decision choices, and finally, understand how to make decisions in competition-oriented pricing situations.
- ItemCapital structure and market power(National Institute of Development Administration, 2016) Prajya Ngamjan; Aekkachai NittayagasetwatEmploying a sample set of 289 Thai listed firms during 2005-2014, the research found that leverage leads to increasing market power as measured by Tobin’s Q and sales growth. The explanation is given by the limited liability theory; that is, a firm employs debt as a commitment tool to compete aggressively in product markets. The main finding remained robust through different leveraged firms/groups, different market concentration groups, different time periods, and in different industrial sectors. Additionally, leverage had stronger effects on market power: if the period was during economic expansion, if the firm was low leveraged, if the firm was in a low-leveraged sector, and if the firm was in an unconcentrated industrial sector. Furthermore, when using total debt instead of long-term debt as the independent variable, the explanatory powers captured by the adjusted 𝑅� s substantially increased. This suggests that the portion of short-term debt is an important source of finance and plays an important role in managing financial strategies, supporting the findings of previous research, that compared to developed countries, developing countries rely more on short-term finance.