Edwin Lin, Tom M.Y. Lin and Bou‐Wen Lin
The purpose of this research is to explore, through the lens of a resource‐based view and dynamic capability theory, how new ventures in high‐technology industries accumulate…
Abstract
Purpose
The purpose of this research is to explore, through the lens of a resource‐based view and dynamic capability theory, how new ventures in high‐technology industries accumulate resources to survive and sustain competitive advantage.
Design/methodology/approach
This study used the multiple case study approach completed for three integrated circuit (IC) design companies in Taiwan by conducting in‐depth interviews with senior executives in each case. Through the aforementioned case studies, the paper was able to summarize and verify the key elements and steps to find the customer and achieve the firm growth.
Findings
It was found that three core elements, technology, networking and legitimacy are necessary. In addition, there are emerging and embedding steps adopted by each case in this study for new ventures to successfully penetrate the market and sustain the competitive advantage.
Research limitations/implications
The findings are focused on one country, and three cases of a specific industry in Taiwan. Future research can be conducted in different cultural contexts and different industries.
Practical implications
New ventures in high‐technology industries can follow the elements and steps suggested in this research paper to accumulate their initial resources. The strategy has been proven by the case studies therein and can be considered highly applicable.
Originality/value
The paper concludes that three key resources for sustaining a company's competitive advantages are necessary. Moreover, a well‐orchestrated management is especially essential for new ventures in high‐technology industries to succeed.
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Fan-Chen Tseng, Pei-Hsun Emma Liu, T.C. Edwin Cheng and Ching-I Teng
This study intended to identify and categorize the drivers of using online English learning resources (OELR) and to understand OELR's impacts.
Abstract
Purpose
This study intended to identify and categorize the drivers of using online English learning resources (OELR) and to understand OELR's impacts.
Design/methodology/approach
The authors conducted an online survey, obtained complete responses from 157 OELR users and used structural equation modeling (SEM) for hypothesis testing.
Findings
Most utilitarian and hedonic drivers lead to positive perceptions of OELR, which in turn positively contribute to continuance intention (CI). Two counterintuitive findings were obtained. First, functionality was negatively related to the perception of ease of use. Second, perceived ease of use (PEOU) was not related to CI to use OELR.
Practical implications
This study has implications as follows: (1) complexity of the functions of OELR may deter rather than attract users, (2) ease of use of OELR is not directly positively related to CIs and (3) users may seek practical benefits (utilitarian) and experiential learning processes (hedonic) when using OELR.
Originality/value
The authors' study has theoretical significance by being the first to caution that excessive functionality or complexity in assisting learning tools would likely hinder further use of OELR. The practical significance of this finding is that the finding highlights two factors (perceived usefulness (PU) and perceived enjoyment) that could effectively increase OELR use.
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José Arias-Pérez, Nelson Lozada and Edwin Henao-García
This paper aims to analyze the moderating effect of knowledge leakage on the relationship between absorptive capacity and co-innovation, which implies collaborative work and…
Abstract
Purpose
This paper aims to analyze the moderating effect of knowledge leakage on the relationship between absorptive capacity and co-innovation, which implies collaborative work and knowledge exchange with external actors on virtual innovation platforms.
Design/methodology/approach
The research model was tested in a sample of companies through the use of structural equations by the partial least squares method.
Findings
The results confirm that absorptive capacity is a prior condition for co-innovation. However, the most interesting and surprising result has to do with knowledge leakage, which actually has a negative moderating effect, but whose size is modest, which dismisses the great damages that such leakage could generate.
Originality/value
This study is pioneering in analyzing knowledge leakage in the context of virtual innovation platforms, which occurs in a different manner as compared to leakage in the context of collaborative research and development, widely analyzed in the literature. However, the main contribution of the paper lies in the fact that the results evidence the existence of an intermediate position between the traditional approach that insists on demonstrating the devastating consequences of the leakage and the emerging approach that dismisses these negative repercussions and conceives leakage as a positive organizational phenomenon, natural and inherent to the interaction of the firm with the environment. The results also contradict recent empirical evidence that completely dismisses the negative repercussions of knowledge leakage in contexts where incremental innovations prevail.
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Fuyong Lin and T.C. Edwin Cheng
Based on several new concepts, this paper mathematically deduces a new model of general systems, namely, the structural model of general systems. By its mathematical analysis, the…
Abstract
Based on several new concepts, this paper mathematically deduces a new model of general systems, namely, the structural model of general systems. By its mathematical analysis, the principles and laws of general systems can be mathematically achieved, which can not only help scientists achieve a better understanding and control of complex systems in nature and society but also be applied to solve particular scientific problems, and thus a problem‐oriented and mathematically expressed general systems theory, namely, the structural theory of general systems, would be achieved.
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Kuan Cheng Lin, Tien‐Chi Huang, Jason C. Hung, Neil Y. Yen and Szu Ju Chen
This study aims to introduce an affective computing‐based method of identifying student understanding throughout a distance learning course.
Abstract
Purpose
This study aims to introduce an affective computing‐based method of identifying student understanding throughout a distance learning course.
Design/methodology/approach
The study proposed a learning emotion recognition model that included three phases: feature extraction and generation, feature subset selection and emotion recognition. Features are extracted from facial images and transform a given measument of facial expressions to a new set of features defining and computing by eigenvectors. Feature subset selection uses the immune memory clone algorithms to optimize the feature selection. Emotion recognition uses a classifier to build the connection between facial expression and learning emotion.
Findings
Experimental results using the basic expression of facial expression recognition research database, JAFFE, show that the proposed facial expression recognition method has high classification performance. The experiment results also show that the recognition of spontaneous facial expressions is effective in the synchronous distance learning courses.
Originality/value
The study shows that identifying student comprehension based on facial expression recognition in synchronous distance learning courses is feasible. This can help instrutors understand the student comprehension real time. So instructors can adapt their teaching materials and strategy to fit with the learning status of students.
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Yuyan Wang, Fei Lin, T.C.E. Cheng, Fu Jia and Yulin Sun
The purpose of this study is to investigate which of the two carbon allowance allocation methods (CAAMs), i.e. grandfathered system carbon allowance allocation (GCAA) and baseline…
Abstract
Purpose
The purpose of this study is to investigate which of the two carbon allowance allocation methods (CAAMs), i.e. grandfathered system carbon allowance allocation (GCAA) and baseline system carbon allowance allocation (BCAA), is more beneficial to capital-constrained supply chains under the carbon emission allowance repurchase strategy (CEARS).
Design/methodology/approach
Adopting CEARS to ease the capital-constrained supply chains, this study develops two-period game models with manufacturers as leaders and retailers as followers from the perspective of profit and social welfare maximization under two CAAMs (GCAA and BCAA), where the first period produces normal products, and the second period produces low-carbon products.
Findings
First, higher carbon-saving can better use CEARS and achieve a higher supply chain profit under the two CAAMs. However, the higher the end-of-period carbon price is, the lower the social welfare is. Second, when carbon-saving is small, GCAA achieves both economic and environmental benefits; BCAA reduces carbon emissions at the expense of economic benefit. Third, the supply chain members gain higher profits and social welfare under GCAA, so the government and supply chain members are more inclined to choose GCAA.
Originality/value
By analyzing the profits and total carbon emissions of capital-constrained supply chains under GCAA and BCAA, this study provides theoretical references for retailers and capital-constrained manufacturers. In addition, by comparing the difference in social welfare under GCAA and BCAA, it provides a basis for the government to choose a reasonable CAAM.
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Edwin Omol, Paul Abuonji and Lucy Mburu
This study investigates the relationships among various dimensions influencing the digital maturity of small- and medium-sized enterprises (SMEs). A novel variable, namely SMEs'…
Abstract
Purpose
This study investigates the relationships among various dimensions influencing the digital maturity of small- and medium-sized enterprises (SMEs). A novel variable, namely SMEs' dependence level on environmental factors, is introduced to broaden the scope beyond traditional linear relationships, providing insights into the multifaceted nature of SME digital maturity.
Design/methodology/approach
The study employs correlation and regression analyses to unravel significant correlations and explore the impact of predictors on the dependent variable. The interconnectedness of Technology, Product, Organization, People, Strategy and Operations is scrutinized, revealing their collective influence on SMEs' digital maturity. Importantly, the absence of multicollinearity issues is confirmed, validating the reliability of the study’s results. The regression models demonstrate robust explanatory power, with the inclusion of a mediator significantly enhancing overall model performance.
Findings
The findings highlight the interconnected nature of key dimensions, emphasizing the collective influence of Technology, Product, Organization, People, Strategy and Operations on SMEs' digital maturity. Analysis of variance results further support the effectiveness of these predictors in capturing variability in the dependent variable. Beta values provide insight into the distinct contributions of each predictor, emphasizing their individual impacts on SMEs' digital maturity.
Originality/value
This study contributes to the field by emphasizing the need for more holistic models and methodological advancements to understand the complex dynamics that shape SMEs' digital maturity. By introducing the novel variable of SMEs' dependence level on environmental factors, the research expands the conceptual framework, offering a fresh perspective on the multifaceted nature of SME digital maturity. The study’s originality is underscored by robust statistical analyses and an exploration of relationships among key dimensions. The comparison and contrast of findings with existing literature further enhance the study’s unique contributions to the field.
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Edwin Juma Omol, Lucy Waruguru Mburu and Paul Anyango Abuonji
This study introduces the Digital Maturity Assessment Model (DMAM), a model tailored to assess the digital maturity of SMEs, tracing its development from addressing business…
Abstract
Purpose
This study introduces the Digital Maturity Assessment Model (DMAM), a model tailored to assess the digital maturity of SMEs, tracing its development from addressing business challenges to establishing a comparative analysis framework grounded in Resource Dependence Theory (RDT).
Design/methodology/approach
DMAM is based on positivist philosophy and objectivist epistemology, supported by Design Science Research (DSR) and Capability Maturity Model Integration (CMMI). The methodology involves iterative development, from problem identification to creating a practical solution for assessing SMEs' digital maturity and guiding digitalization efforts.
Findings
DMAM offers a clear and specific methodology, distinguishing itself by addressing the unique needs of SMEs, particularly resource-dependent ones. The model’s development fills critical gaps in existing literature and provides a practical artifact for SMEs' digitalization.
Originality/value
DMAM is original in its focus on the specific needs of resource-dependent SMEs, offering actionable recommendations and addressing shortcomings in existing models. It serves as a foundational framework for SMEs' digital transformation, making a significant contribution to the digital maturity assessment literature.
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Mu-Yen Chen, Edwin David Lughofer, Neil Y. Yen and Chia-Chen Chen