The Impact of Core Technological Capabilities of High-Tech Industry on Sustainable Competitive Advantage

Identifying and ranking key technological capabilities in supply chain sustainability using ISM approach: case of food industry in Iran

The food industry is one of the strategic industries in developing countries, such as Iran and plays a critical role in the economy, food security, and public health. The growing populations can only have food security when the food industry's supply chain is sustainable. Therefore, due to the sustainable food supply chain's great importance, having technological capabilities compared to others is considered a competitive advantage for the companies involved in the food industry, as it can distinguish them as pioneer actors. Although many technologies have been investigated and used in the sustainable supply chain recently, no study has focused on identifying and ranking key technological capabilities related to the food industry in sustainable supply chain management. Also, we have not found any study using the ISM-MICMAC method to identify, rank, and interdependence between key technology capabilities in supply chain sustainability. Accordingly, the present study sought to identify and rank key technological capabilities in the supply chain sustainability of food industry companies. In this study, after reviewing the relevant literature, eleven technological capabilities in supply chain sustainability were identified. Then using experts' opinions and Interpretive Structural Modelling (ISM), interdependence among the technological capabilities ranked. Finally, dependent and independent drivers were presented using the MICMAC analysis. The ISM analysis results indicated that communication and information technology infrastructure was the most significant driver for other technological capabilities in companies' supply chain sustainability. Moreover, logistic optimization is imperative for improving supply chain sustainability performance. Therefore, if logistic optimization is appropriately implemented, it can improve supply chain sustainability. The present study results can increase supply chain productivity and effectiveness in Iranian food industry companies.

Employee's performance and Kaizen events' success: does supervisor behaviour play a moderating role?

Purpose

The study's goal was to identify the factors contributing to the practical completion of Kaizen events (KEs). The effect of the work-study man's characteristics, the supervisor's conduct and the autonomy of the Kaizen team are analysed in this study.

Design/methodology/approach

Data were collected from 249 respondents working in the manufacturing sector in India, mainly those who had been involved in Kaizen projects. Three-step procedures, namely, exploratory factor analysis, confirmatory factor analysis and partial least squares, have been applied to test the research hypotheses through structural equational modelling.

Findings

The exploratory factor analysis extracted in-role performance, creative performance and human aspect as latent variables explaining work-study man's performance (eigenvalue = 1). The study's findings indicate that the performance of work-study man (in-role, creative and human) and supervisors' conduct is directly related to the success of KEs. It was shown that supervisors might influence the outcomes of KEs only by moderating the human aspects. Additionally, the degree of autonomy of the Kaizen team was found having a significant positive relationship with the success of KEs.

Practical implications

The current study suggests that in-role and creative performance are prime assets of a work-study man. At the same time, the human aspect is a delicate issue that can affect the supervisor's behaviour. Therefore, the study implies that work-study men have the tactics and abilities to work with other co-workers to make a Kaizen project successful.

Originality/value

Although the significance of Kaizen projects has been widely emphasised, past research has failed to establish what factors contribute to the success of Kaizen efforts. Similarly, the supervisor's critical role has been highlighted several times. However, it is unclear how their conduct influences the relationship between work-study man's performance and the effectiveness of Kaizen projects. This study contributes significantly to organisational culture and human resource management by answering these questions.

Entrepreneurship education of college students and entrepreneurial psychology of new entrepreneurs under causal attribution theory

With the rapid development of information technology, the society’s demand for innovative talents has become increasingly prominent. The purpose of this study is to optimize the teaching strategies of entrepreneurship education for college students, further cultivate college students’ entrepreneurial ideas, and promote the formation of entrepreneurial values. The problems existing in entrepreneurship education in colleges and universities are studied based on entrepreneurial psychology and attribution theory. A questionnaire survey is conducted on the problems with a high probability of entrepreneurial failure of college students. The heads of new ventures in Xi’an are selected. Then, 300 questionnaires are distributed, and 209 are returned. The survey results are analyzed using failure attribution and failure learning. Suggestions are provided for management strategies of new ventures. The results show that the Corrected Item-Total Correlation (CITC) value of R⁻¹ is 0.65, and the CITC value of R⁻² is 0.35. In addition, the Kaiser-Meyer-Olkin (KMO) values of entrepreneurial failure attribution and entrepreneurial failure mode are both greater than 0.7, which indicates that the scale of entrepreneurial failure attribution has good validity and can be used for factor analysis. However, the KMO values of entrepreneurial failure attribution and entrepreneurial failure learning model are both greater than 0.7, and the significance of Bartlett sphericity test is 0.00, which indicates that the survey has good validity. The research has practical application and reference value for the cultivation of college students’ innovative and entrepreneurial ability.

Financial Risk Early Warning Model of Listed Companies Under Rough Set Theory Using BPNN

In order to reduce the risk of enterprise management, the financial risk early warning methods of listed companies are mainly studied. The financial risk characteristics of listed companies are analysed. With the help of rough set theory, the financial risk indicators are selected, and the financial risk early warning index system is established. The financial risk early warning model is constructed by using back propagation neural network (BPNN) algorithm based on deep learning. Finally, the accuracy and feasibility of the constructed neural network model are verified. The results show that rough set theory can be used to screen financial risk indicators and select important indicators, which can simplify the data and reduce the complexity of calculation. BPNN can calculate the simplified data and identify and evaluate the financial risk. Empirical analysis shows that the proposed method can shorten the training time of the model to a certain extent, and improve the accuracy of financial risk prediction.

Core Technological Competence and Competitive Advantage: A Study on Chinese High-Tech SMEs

The purpose of this study was to examine the effect of core technology competence on the competitive advantage of high-tech SMEs (small- and mid-sized enterprises in China). Based on the 379 valid responses collected from a survey, structural equation modeling (SEM) was employed to examine the research model. Infrastructure and technology, state-of-the-art technology, innovative research and development (R&D) capability, and organizational flexibility all have a significant impact on the competitive advantage, while infrastructure and technology, state-of-the-art technology, and innovative R&D capability have a significant effect on organizational flexibility. Organizational flexibility plays a mediating role between innovative R&D capability's effect and competitive advantage. Under the continuous influence of COVID-19, we should promote development from the perspective of strengthening enterprise infrastructure and technology and improving organizational flexibility to gain a competitive advantage. This study reveals the internal relationship between core technology competence, organizational flexibility, and competitive advantage. The results of this study will help us to fully understand the survival status and competitive advantage of high-tech SMEs under COVID-19.

Identifying Dimensions of Dynamic Technological Capability: A Systematic Review of the Last two Decades of Research

Nowadays, technological innovation capabilities support competitive advantage, and the survival and development of modern organizations accordingly depend on the knowledge and applications of such innovations. Nevertheless, the link between various aspects of the dynamic technological capability of many organizations is not still clear. Meanwhile, the new trend of some research in the field of dynamic capabilities refers to its technological foundations, as a platform for strengthening and creating a competitive technological advantage in a scattered manner. In this regard, this paper systematically reviews the previous research on technological basis of dynamic capabilities using the systematic review approach, examining articles published during 2000–2021 in which the technological foundations of dynamic capabilities in terms of sensing, seizing, and deformation (i.e. cognitive, psychological and organizational) have been extracted. A framework for future research has also been presented. The recommended framework can partially bridge the gap in the literature on the technological foundations of dynamic capabilities in future studies and help the managers to identify the technological road map for gaining competitive technological advantages.

Application of Multi-Criteria Analytic Methods in the Assessment of the Technical Conditions of Small Hydraulic Structures

Increasing water demand, combined with unfavourable climate change, creates a need for well-thought-out water management. Such goals are realised thanks to appropriate hydrotechnical infrastructure, the efficiency and functionality of which depend on its technical condition. In the literature, there is no method for the assessment of the technical condition of small damming structures, including sluice gates. The aim of this article was to present the possibility of using the multi-criteria AHP decision support method to assess the technical condition of small damming structures. The assessment included both concrete elements (spillways, abutments, and apron) and steel elements (gates and hoisting equipment). The analyses considered the effects of growing vegetation, the condition of concrete surfaces (e.g., cracks, cavities, exposed rebar) and steel elements (corrosion, deterioration). A hybrid method was used to study the assessment of the technical condition of water structures. It consisted of a modified Zawadzki’s method and weights which were determined by different groups of respondents with industry backgrounds (university students and experts) using the AHP method. The obtained results show that the factors related to the holes and corrosion of the gate elements had the highest value of the matrix solution vector. The last level of the tree structure indicated that the condition of the spillway and gate is the most important factor in the technical condition assessment. As the assessment considers commonly available parameters, the proposed method is universal and can be used in the assessment of other structures of this type in different regions of the world, which is important in terms of their functioning, planned repairs, and optimal use in water resource management.

Relationship Analysis among Apparel Brand Image, Self-Congruity, and Consumers’ Purchase Intention

Brand image has been a crucial clue to making subjective judgment for consumers to determine the brand, which is critical to making a purchase decision. The influence mechanism from apparel brand images on consumers’ purchase intention was explored for theoretical and positive analysis based on the self-congruity theory. This research first constructed a hypothetical model of apparel brand images influencing consumers’ purchase intention with self-congruity and perceived quality as mediators, in which a questionnaire was designed and conducted to test the theoretical model. The research shows that apparel brand image and perceived quality can significantly influence consumers’ purchase intention. The consumer purchase intention is directly related to clothing brand image provided self-consistency and perceived quality play an intermediary with the regulatory effect of self-motivation and brand familiarity. A positive attitude toward apparel brand image will stimulate consumers to build cognitive clues and associations between the consumers and the brand and strengthen cognitive consistency with the apparel brand’s spirit. The research results are beneficial to textile fashion and clothing enterprises to improve brand building and marketing.

Applying Fuzzy Fault Tree Method to Evaluate the Reliability of College Classroom Teaching

The evaluation of classroom teaching quality is closely related to the development of higher education as a scientific and effective evaluation system that can provide a solid foundation for formulating educational policies. Therefore, an evaluation model of classroom teaching quality in colleges and universities is established based on the fuzzy fault tree theory with “classroom teaching failure” as the top event to effectively evaluate the reliability of college classroom teaching and optimize the teaching strategies. In consideration of the lack of availability and dynamics of classroom teaching data, fuzzy numbers are used to describe the probability of underlying events. In addition, the top event probability of the fuzzy fault tree is calculated by the double-layer Monte Carlo method (MCM), which analyzes the classroom teaching effect based on the fuzzy fault tree reasonable. In summary, the quantitative evaluation system of classroom teaching quality based on fuzzy fault trees can evaluate classroom teaching more comprehensively and dynamically and help to improve the teaching quality of higher education.

Construction of Innovation Behavior of College-Student Entrepreneurs Using Entrepreneurship and Innovation Theory Under Educational Psychology

The purpose is to analyze the entrepreneurship and innovation education of colleges from the perspective of educational psychology and optimize the teaching mode reform of entrepreneurship and innovation courses. In this study, the theoretical research and case studies are combined to explore the performance of college-student entrepreneurs during college and work and have provided data for targeted entrepreneurship and innovation education in the schools. Meanwhile, the specific manifestation of the entrepreneurial spirit during work is analyzed, and the impact of entrepreneurial spirit is discussed on the new venture performance. The case study shows that most of the surveyed college-student entrepreneurs have a higher educational background and short venture-creation time, and their ventures are mostly small and medium-sized enterprises (SMEs) with rapid development. Most entrepreneurs show a strong entrepreneurial spirit during college. Among them, the average score of honesty is 3.85. At work, the surveyed entrepreneurs have high innovation attitude and innovation intention. Most entrepreneurs use innovative methods to solve practical problems in their work, and innovation spirit plays an important role in improving venture performance. Innovation attitude and innovation performance have a significant positive impact on innovation behavior. The research is comprehensive, and the results have very important application value. The results can provide scientific and effective references for colleges to reform entrepreneurship and innovation education.

Influence of Cooperative Learning Intervention on the Intrinsic Motivation of Physical Education Students-A Meta-Analysis within a Limited Range

This study was conducted to explore physical education students' intrinsic motivation and clarify the influence mechanism of cooperative learning methods on learning intrinsic motivation through meta-analysis. In accordance with the Preferred Reporting Items for Systematic Reviews (PRISMA) criteria, we screened literature from the years 2000-2020. The included literature underwent bias analysis on the basis of the five criteria proposed herein. Data were extracted and summarized from the included literature to analyze the causality before and after cooperative learning intervention. Statistical analysis was conducted to determine principal factors affecting physical education students' learning intrinsic motivation. Simultaneously, the influencing mechanism of cooperative learning on physical education students' intrinsic motivation was clarified. Results revealed that intrinsic motivation had a high total effect amount. In the experimental group, only three documents determined the significant influence of cooperative learning on physical education students' intrinsic motivation. Moreover, the time and age differences needed to be considered thoroughly during the intervention. Therefore, cooperative learning intervention can improve physical education students' intrinsic motivation significantly, and meta-analysis provided a theoretical foundation for applying cooperative learning to the teaching of physical education majors.

AHP as a Useful Tool in the Assessment of the Technical Condition of Hydrotechnical Constructions

The key challenge for sustainable water management is to carry out a proper assessment of the technical condition of hydrotechnical constructions. Maintaining them in a good state is a prerequisite for ensuring the safety of objects, as well as adjacent areas. This paper compares the results of field research obtained by three methods to assess the technical condition of structures located on the Wełna River. The main objective is to determine the differences between the methods and to indicate the most important assessment elements and criteria. Moreover, it was checked if the Analytic Hierarchy Process (AHP) can be used to carry out the correct assessment of hydrotechnical construction. An assessment that will be based on the hierarchy of factors, which is not often used in other methods. The AHP was applied for the first time to assess the technical condition of hydrotechnical constructions. Based on AHP, three variants of different weights for factors, including exploitation problems and damage to construction elements, were selected. The new variants developed by the authors allow for a more accurate, multifactor assessment. The use of scales to determine the importance of individual elements contributes to the actual representation of the technical condition of the object, which is often over- or underestimated by other assessment methods. The analysis shows that the AHP method is a useful tool to support the assessment of the technical condition of hydrotechnical construction. The use of AHP as a universal assessment method will compare the technical condition of hydrotechnical constructions located all over the world.

Green Agricultural Development Based on Information Communication Technology and the Panel Space Measurement Model

This study was conducted to promote the construction of China’s ecological civilization; to reduce harm to the environment; to quantify the performance of agricultural green development (GD); and to truly achieve green, sustainable, and healthy agricultural development. From the perspectives of resources and the environment, first, information communication technology and the panel space measurement (PSM) model were adopted to analyze relevant indicator data from 2000 to 2019 in China’s 30 provinces. Second, China’s agriculture was measured to explore the overall characteristics, temporal changes, and regional differences of agricultural development. A panel data measurement model was constructed using the generalized least squares method, and the main factors affecting performance development were analyzed, which were verified by giving examples. Third, the governance countermeasures and improvement directors were proposed for agricultural GD in China. It is found that the driving force of performance of agricultural GD in China mainly depends on technological progress and that technological efficiency determines the speed of agricultural development. The regional differences in performance of agricultural GD are obvious in China. The growth in the performance of agricultural GD in the eastern region is much higher than that of the central, western, and northeast regions. In addition, the results show that the performance of agricultural GD is extremely positively correlated with the agricultural economic level, fiscal support for agriculture policy, and the industrialization process and that it is extremely negatively correlated with the level of opening-up, adjustment of agricultural structure, and the environmental regulatory capability of the government. As a result, this study can provide some ideas for the realization of agriculture GD in China.

The Psychological Expectation of New Project Income Under the Influence of the Entrepreneur's Sentiment From the Perspective of Information Asymmetry

The phenomenon of high first-day income and high break-up rate in China’s capital market has long attracted the attention of investors. Based on the disagreement model, in combination with the information asymmetry theory and behavioral finance, a mathematical model was put forward to analyze the reasons and mechanisms for the excess return of the initial public offering (IPO) on the first-day under the influence of investors’ sentiments. The analysis shows that the IPO first-day income is a function of the disagreement between investors, which generally presents an asymmetric U shape. Information asymmetry affects the degree of valuation deviation. The sentiment of investors reflects the psychological state of the investor at the time, which makes the income increase or decrease under the influence of investor sentiment and market sentiment. In turn, it leads to the emergence of excess returns or break-up rates on the first-day. The research results help deepen the understanding of the IPO pricing mechanism and explore the impact of investor psychology on its pricing, putting forward suggestions for the issue pricing mechanism of the Sci-Tech Innovation Board.

The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm

In the context of rapid urbanization, the spread of cities in the Yangtze River Economic Belt is intensifying, which has an impact on the green and sustainable development of these cities. It is necessary to establish an accurate urban sprawl measurement system. First, the regulation theory of urban sprawl is explained. According to the actual development situation of cities in the Yangtze River Economic Belt, smart growth theory is selected as the basic regulation method of urban sprawl. Second, the back propagation neural network (BPNN) algorithm under deep supervised learning is applied to construct a smart evaluation model of land use growth. Finally, based on the actual development of cities in the Yangtze River Economic Belt, the quantitative growth measurement method is selected to construct a measurement system of urban sprawl in the Yangtze River Economic Belt, and the empirical analysis is carried out. The training results show that the proposed BPNN smart growth evaluation model, based on deep supervised learning, has good evaluation accuracy, and the error is within the preset range. The analysis of the quantitative growth-based measurement system in the increase of urban construction land shows that the increase in urban construction land area of the Yangtze River Economic Belt from 2014 to 2019 was 78.67 km2. Meanwhile, the increases in urban construction land area in different years are different. The empirical results show that the population composition of the Yangtze River Economic Belt and the urban construction area between 2005 and 2019 show a trend of increasing annually; at the same time, urban sprawl development shows a staged characteristic. It is of great significance to apply deep learning fusion neural network algorithm in the construction of the urban sprawl measurement system, which provides a quantitative basis for the in-depth analysis and discussion of urban sprawl.