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The purpose of this study is to analyze the performance of indigenous innovation in developing countries in the era of trade liberalization. It analyzes indigenous innovation from research and development (R&D) investments to innovation output and its effect on economic growth.

The sample for this study includes 20 middle-income countries across five continents for the period between 1994 and 2018. The study employs the Crepon Duguet and Mairessec CDM model in a panel data setting to do a multistage analysis of the innovation process. A vector error correction model VECM is employed to test for Granger causality between the variables investigated.

The results show that imports and foreign direct investments (FDI) have generally have short-run and long-run causal effects on domestic R&D investments. In regions where imports and FDI do not have individual causal effects on innovation output, a joint increase in each of them and R&D have both short-run and long-run causal effects. Indigenous innovation is a significant contributor to economic growth when a country can produce and export novel products.

The sample is only limited to developing economies, and due to the unavailability of data, only 20 countries were captured.

Imported products and FDI are critical to the innovation drive when such activities are targeted at enhancing indigenous innovation from R&D to the production of new products. Hence, policy formulation should encourage the absorption of foreign technologies that serve as inputs to indigenous innovation.

This paper focuses specifically on indigenous innovation and analyses the influence of foreign technologies in this effort. It tests the moderating roles of imports and FDI in the relationship between R&D and innovation output, concluding that both variables enhance the effect of R&D on innovation output.

The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding and analyzing the significant changes, patterns and trends in the subject as they are represented in academic papers is the goal of this research.

Using bibliometric methodologies, this study gathered and examined a large corpus of research papers, conference papers and related material from several academic databases.

Starting with Artificial Intelligence (AI), the Internet of Things (IoT), Big Data (BD), Augmentation Reality/Virtual Reality and Blockchain Technology (BT), the study discusses the advent of new technologies and their effects on libraries. Using bibliometric analysis, this study looks at the evolution of publications over time, the geographic distribution of research and the most active institutions and writers in the area. A thematic analysis is also carried out to pinpoint the critical areas of study and trends in emerging technologies and smart libraries. Some emerging themes are information retrieval, personalized recommendations, intelligent data analytics, connected library spaces, real-time information access, augmented reality/virtual reality applications in libraries and strategies, digital literacy and inclusivity.

This study offers a thorough overview of the research environment by combining bibliometric and thematic analysis, illustrating the development of theories and concepts during the last ten years. The results of this study helps in understanding the trends and future research directions in emerging technologies and smart libraries. This study is an excellent source of information for academics, practitioners and policymakers involved in developing and applying cutting-edge technology in library environments.

The purpose of this paper is to examine the effects of perceived benefits, i.e. utilitarian value, hedonic value and social value, as well as perceived risk, on purchase intention in social commerce context.

To cast light on the factors motivating users’ intention to purchase in the context of social commerce, data of 277 users of social commerce in China were collected via an online survey.

Results show that satisfaction significantly and positively affects users’ purchase intention in social commerce context. In addition, utilitarian, hedonic and social values have significant and positive impacts on satisfaction and purchase intention; and utilitarian value is found to be the most salient factor influencing purchase intention, while hedonic value has the greatest effect on satisfaction. Moreover, perceived risk significantly and negatively affects satisfaction.

Extant research on social commerce has mainly focused on investigating how the general perceived value affects user behavior, but has less considered different dimensions of perceived value. Moreover, prior studies have explored the roles of utilitarian and hedonic values on user behavior; however, there is a lack of research on the effect of social value. The current study attempts to fill these research gaps.

By controlling the value of influencing factors of raglan sleeves, the authors can balance the comfort and aesthetics of raglan sleeves and get the best parameter value.

Under the condition that the slope of sleeve midline is 45 and the height of sleeve mountain is 15.00 cm, different armhole depth and connection point between the body and the sleeve are combined, and the influence of these two on the comfort and aesthetics of clothing is studied by CLO software.

The relationship between sleeve fat (Y), armhole depth drop (X₁) and the distance (X₂) between the connection point between the body and the sleeve and the center line is Y = 12.985 + 1.240·X₁ + 0.895·X₂. When the armhole drop is 5.00 cm and the connection point is 1 cm closer to the center line, the comfort and aesthetics can be better balanced.

These data can provide reference for future research on raglan sleeves.

This study examines the relationship between the emphasis on organic food in Afyonkarahisar's cuisine and the growing demand for healthier and sustainable options. This study aimed to understand the factors influencing the intention to consume organic foods.

This study uses a quantitative research method. It uses scales adapted from previous research to assess the health and safety of organic food's functional, hedonic, and social values. Data were collected using the purposive sampling method, and a sample size of 410 individuals was analyzed using the PLS-SEM method. Measurement and structural models were evaluated to assess validity, reliability, and model fit.

The results indicate that implementing health and safety practices significantly and positively affects perceptions of organic food's functional, hedonic, altruistic, and social values. Additionally, consumers' attitudes toward organic food are greatly influenced by their perceptions of functional and social value, whereas hedonic and altruistic values do not have a significant positive effect.

The results of this study have a beneficial impact on food industry practitioners and policymakers. Emphasizing health and safety practices in producing and promoting organic foods can improve consumer perceptions and attitudes toward organic products. Understanding the importance of practical benefits and social issues can help companies respond effectively to consumer preferences and market organic foods.

This study contributes significantly to the existing literature by investigating the relationship between organic food emphasis and consumer perceptions in the unique context of Afyonkarahisar, a city renowned for its gastronomy. While focusing on Afyonkarahisar provides valuable insights into the specific values that influence consumers' attitudes toward organic food, it is essential to highlight that this research extends beyond the local context to offer broader implications and significance.

In an emerging market, understanding shoppers' behavior in an online market is essential to developing online retail strategies. This research study examines the effects of intrinsic factors, namely, perceived utilitarian, hedonic value, materialism, fashion interest and enjoyment, on impulsive online shopping with mediating role of trust and online shopping attitude in the Indian emerging market.

Data are collected from 443 Indian respondents, using purposive and snowball sampling. The data were analyzed using the IBM Statistical Product and Service Solutions (SPSS) and Analysis of Moment Structures (AMOS) package using structural equation modeling.

The results showed that perceived utilitarian, hedonic value, materialism and enjoyment factors significantly impacted perceived trust and online shopping attitude, but fashion interest had no effect. Mediating factors positively impacted impulsive online shopping and showed a significant association between intrinsic factors and impulsive online shopping.

The geographical area of study was limited to only India. Consequently, the findings and conclusions of the study had their limits. The research used the information continuum with a purposive and snowball approach that does not necessarily generalize the findings of the analysis. This work looked at factors stimulating the impulsive online shopping pattern of Indian shoppers in an emerging market.

This research would help e-retailers develop new strategies and plans to increase sales volume and create strong relationships with online customers by providing trustworthiness and security in buying practices.

This study helps to understand the consumer impulsive buying during coronavirus disease 2019 (COVID-19), and it helps e-retailers to adopt a new online store to draw the attention of the consumers and enhance their online sales.

In this COVID-19 situation, this study explores the inherent factors influencing impulsive online shopping in the emerging Indian market. As a result, it contributes to visual identity literature by expanding the field of impulsive online shopping behavior.

The study focuses on drug safety regulation capture, reveals the inner mechanism and evolutionary characteristics of drug safety regulation capture and provides suggestions for effective regulation by pharmacovigilance.

The article introduces prospect theory into the game strategy analysis of drug safety events, constructs a benefit perception matrix based on psychological perception and analyzes the risk selection strategies and constraints on stable outcomes for both drug companies and drug regulatory authorities. Moreover, simulation was used to analyze the choice of results of different parameters on the game strategy.

The results found that the system does not have a stable equilibrium strategy under the role of cognitive psychology. The risk transfer coefficient, penalty cost, risk loss, regulatory benefit, regulatory success probability and risk discount coefficient directly acted in the direction of system evolution toward the system stable strategy. There is a critical effect on the behavioral strategies of drug manufacturers and drug supervisors, which exceeds a certain intensity before the behavioral strategies in repeated games tend to stabilize.

In this article, the authors constructed the perceived benefit matrix through the prospect value function to analyze the behavioral evolution game strategies of drug companies and FDA in the regulatory process, and to evaluate the evolution law of each factor.

System dynamics is a whole-system modelling and learning approach, useful for tackling non-linear problems, such as sustainable urban development. The purpose of this paper is to review system dynamics applications in the simulation of sustainable urban development over a period from 2005 to 2017.

The analysis reveals that the number of applications of system dynamics modelling in the area of urban sustainable development increased in the analysed period. Research has changed its focus from the modelling of environmental problems to more complex models, portraying the multidimensional socio-economic processes that have an impact on the sustainability of urban development. Analysed case studies most often use the behaviour reproduction test for model validation, but without a unified approach. In most cases, modelling has been done in China, Germany and the USA, while urban development in the Eastern European countries, Africa and Latin America has not often been investigated. This paper indicates the knowledge gaps and suggests future research directions.

Papers that report the use of system dynamics modelling reveal a wide range of applications in urban sustainability. The analysis shows significant emphasis on environmental problems, while the interest for modelling social problems has been increasing during the last several years. Most of the modelled problems examine the sustainability of resources (land, water) and waste management, which are used for insights into the reasons for the system behaviour, forecasting future behaviour and policy testing.

The presented models were developed in most cases for the purpose of understanding the phenomena examined, as well as the future use of the models in policy planning. This brings us back to the need for greater stakeholder involvement, not only in the initial phase, but also during the whole modelling process, which could increase understanding, use and ownership of the models in the future, and thus increase their practical application.

Devices for step estimation are body-worn devices used to compute steps taken and/or distance covered by the user. Even though textiles or clothing are foremost to come to mind in terms of articles meant to be worn, their prominence among devices and systems meant for cadence is overshadowed by electronic products such as accelerometers, wristbands and smart phones. Athletes and sports enthusiasts using knee sleeves should be able to track their performances and monitor workout progress without the need to carry other devices with no direct sport utility, such as wristbands and wearable accelerometers. The purpose of this study thus is to contribute to the broad area of wearable devices for cadence application by developing a cheap but effective and efficient stride measurement system based on a knee sleeve.

A textile strain sensor is designed by weft knitting silver-plated nylon yarn together with nylon DTY and covered elastic yarn using a 1 × 1 rib structure. The area occupied by the silver-plated yarn within the structure served as the strain sensor. It worked such that, upon being subjected to stress, the electrical resistance of the sensor increases and in turn, is restored when the stress is removed. The strip with the sensor is knitted separately and subsequently sewn to the knee sleeve. The knee sleeve is then connected to a custom-made signal acquisition and processing system. A volunteer was employed for a wearer trial.

Experimental results establish that the number of strides taken by the wearer can easily be correlated to the knee flexion and extension cycles of the wearer. The number of peaks computed by the signal acquisition and processing system is therefore counted to represent stride per minute. Therefore, the sensor is able to effectively count the number of strides taken by the user per minute. The coefficient of variation of over-ground test results yielded 0.03%, and stair climbing also obtained 0.14%, an indication of very high sensor repeatability.

The study was conducted using limited number of volunteers for the wearer trials.

By embedding textile piezoresistive sensors in some specific garments and or accessories, physical activity such as gait and its related data can be effectively measured.

To the best of our knowledge, this is the first application of piezoresistive sensing in the knee sleeve for stride estimation. Also, this study establishes that it is possible to attach (sew) already-knit textile strain sensors to apparel to effectuate smart functionality.