Search results

The development of the digital age has made data and information more transparent, enhancing the strategic perspectives of both buyers (strategic waiting) and sellers (price fluctuations) in their decision-making. This research investigates the optimal dynamic pricing strategy of the content product developer in relation to their consideration of consumer fairness concerns to elucidate the impact of consumer fairness concerns on the dynamic pricing strategy of the developer.

This paper assumes that monopolistic content developers implement a dynamic pricing strategy for the content product. Through constructing a two-period dynamic pricing game model, this research investigates the optimal decisions of the content developer, contingent upon their consideration or disregard of consumer fairness concerns. In the extension section, the authors additionally account for the influence of myopic consumers on these optimal decisions.

Our findings reveal that the degree of consumer fairness concerns significantly influences the developer’s optimal dynamic pricing decision. When a developer offers content products with lower depth, there is a propensity for the developer to refrain from incorporating consumer fairness concerns into a dynamic pricing strategy. Conversely, in cases where the developer offers a high-depth content product, consumer fairness concerns benefit the developer. Furthermore, our analysis reveals a consistent benefit for the developer from the inclusion of myopic consumers.

Few studies have delved into the conjoined influence of consumer fairness concerns and strategic behavior on dynamic pricing strategy. Our findings indicate that consumer fairness concerns can enhance the efficiency of the value chain for content products under specific conditions. This paper not only enriches the existing literature on dynamic pricing by incorporating consumer fairness concerns theoretically but also offers practical insights. The outcomes of this research can guide content product developers in devising optimal dynamic pricing strategies.

The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.

This paper presents the phenomenographic analysis of students' approaches to learning in the first year architectural design coursework; thereby correlating contextualization in the architectural curriculum.

This paper reviews phenomenographic data of first year architecture students' learning experience through a comparative analysis of first- and fourth-year students' approaches to learning in the design studio; further co-relating this analysis to the final classification involving all five years of students' learning approaches in the architecture program.

Five meta-categories of the comparative analysis and nineteen meta-categories of the final classification are evaluated using first-year students' learning approaches – to understand the importance of contextualization in curriculums of architecture.

This phenomenographic analysis of first-year students' learning experience represents the onward journey from surface-to-deep approaches to learning that is encountered in their learning approaches, pertaining to the design process in the design coursework during five years of architectural education.

This paper systematically extends the discussion of first year architecture students' engagement in the design process that leads to deep learning; further delving into the static dimension of knowledge and its extension to the dynamic dimension of knowing architecture.

This paper aims to promote the higher quality development of high-tech enterprises in China. While science and technology have greatly promoted human civilization, resources have been excessively consumed and the environment has been sharply polluted. Therefore, it is particularly important for current enterprises to make use of scientific and technological innovation to maximize the benefits of mankind, minimize the loss of nature, and promote the sustainable development of our country.

By using DEA-Banker-Charnes-Cooper (BCC) model and DEA-Malmquist model, this paper comprehensively examines the innovation efficiency of high-tech enterprises from both static and dynamic perspectives, and conducts a provincial comparative study with the panel data of ten representative provinces from 2011 to 2020.

The research findings are as follows: the rapid number increase of high-tech enterprises in most provinces (cities) is accompanied by an ineffective input–output efficiency; the quality of high-tech enterprises needs to comprehensively examine both input–output efficiency and total factor productivity; and there is not a positive correlation between element investment and innovation performance.

Because the DEA model used in this paper assumes that the improvement direction of invalid units is to ensure that the input ratio of various production factors remains unchanged but sometimes the proportion of scientific and technological activities personnel and the total research and development investment is not constant. In the future, the nonradial DEA model can be considered for further research. Due to historical data statistics, more provinces, cities and longer panel data are difficult to obtain. The samples studied in this paper mainly refer to the provinces and cities that ranked first in the number of national high-tech enterprises in 2020. Limited by the number of samples, DEA analysis failed to select more input and output indicators. In the future, with the accumulation of statistical data, the existing efficiency analysis will be further optimized.

Aiming at the misunderstanding of emphasizing quantity and neglecting quality in the cultivation of high-tech enterprises, this paper comprehensively uses DEA-BCC model and DEA Malmquist index decomposition method to make a comprehensive comparative study on the development of high-tech enterprises in ten representative provinces (cities) from two aspects of static efficiency evaluation and dynamic efficiency evaluation.

The paper provides a detailed historical account of Douglass C. North's early intellectual contributions and analytical developments in pursuing a Grand Theory for why some countries are rich and others poor.

The author approaches the discussion using a theoretical and historical reconstruction based on published and unpublished materials.

The systematic, continuous and profound attempt to answer the Smithian social coordination problem shaped North's journey from being a young serious Marxist to becoming one of the founders of New Institutional Economics. In the process, he was converted in the early 1950s into a rigid neoclassical economist, being one of the leaders in promoting New Economic History. The success of the cliometric revolution exposed the frailties of the movement itself, namely, the limitations of neoclassical economic theory to explain economic growth and social change. Incorporating transaction costs, the institutional framework in which property rights and contracts are measured, defined and enforced assumes a prominent role in explaining economic performance.

In the early 1970s, North adopted a naive theory of institutions and property rights still grounded in neoclassical assumptions. Institutional and organizational analysis is modeled as a social maximizing efficient equilibrium outcome. However, the increasing tension between the neoclassical theoretical apparatus and its failure to account for contrasting political and institutional structures, diverging economic paths and social change propelled the modification of its assumptions and progressive conceptual innovation. In the later 1970s and early 1980s, North abandoned the efficiency view and gradually became more critical of the objective rationality postulate. In this intellectual movement, North's avant-garde research program contributed significantly to the creation of New Institutional Economics.

There are two purposes in this paper. The first one is to explore the impact mechanisms and paths of service-oriented manufacturing (SOM) on the sustainability performance of green manufacturing firms and to pay particular attention to the mediating role of enterprise costs in the relationship between the two. The second one is to reveal the dynamic process and laws of SOM influencing on the sustainability performance of green manufacturing enterprises.

This paper employs a combination of dynamic and static research from two aspects. On the one hand, based on 495 green manufacturing firms in China, the authors verify the SEM of SOM, enterprise cost and sustainability performance of green manufacturing firms through empirical research, analyze the path relationship and mediation effect, and demonstrate its complex impact mechanism. On the other hand, the authors use agent-based modeling and simulation to reveal the dynamic influence of SOM on the sustainability performance of green manufacturing enterprises and explore its dynamic laws and future development trends.

The study results indicate that (1) SOM has a direct positive effect on firm sustainability performance. (2) Reducing firm costs has a positive effect on firm sustainability performance, and firm costs play a partial mediating role in the mechanism by which SOM influences firm sustainability performance. (3) The dynamic impact of SOM on sustainability performance increases significantly over time. (4) Significant firm heterogeneity exists in the process by which SOM improves sustainability performance. (5) There are differences in the promotion of SOM for economic performance, environmental performance and social performance.

This paper makes two main contributions. First, compared with previous research on sustainability performance focusing on a certain dimension, this paper organically integrates the three dimensions of sustainability performance, regards them as a whole and considers the paths to improve sustainability performance. Second, this paper focuses on the complex relationship among SOM, enterprise costs and sustainability performance and reveals different sustainability performance improvement paths and dynamic impact processes, thereby expanding and deepening previous research on sustainability on the subject. These contributions lead to a better understanding of the driving forces and realization path for green manufacturing firms' sustainability performance from an integrated static and dynamic perspective.

This research paper aims to optimize the calibration process for an ABB IRB 120 robot, specifically for robotic orbital milling applications, by introducing and validating the use of the observability index and telescopic ballbar for accuracy enhancement.

The study uses the telescopic ballbar and an observability index for the calibration of an ABB IRB 120 robot, focusing on robotic orbital milling. Comparative simulation analysis selects the O₃ index. Experimental tests, both static and dynamic, evaluate the proposed calibration approach within the robot’s workspace.

The proposed calibration approach significantly reduces circularity errors, particularly in robotic orbital milling, showcasing effectiveness in both static and dynamic modes at various tool center point speeds.

The study focuses on a specific robot model and application (robotic orbital milling), limiting generalizability. Further research could explore diverse robot models and applications.

The findings offer practical benefits by enhancing the accuracy of robotic systems, particularly in precision tasks like orbital milling, providing a valuable calibration method.

While primarily technological, improved robotic precision can have social implications, potentially influencing fields where robotic applications are crucial, such as manufacturing and automation.

This study’s distinctiveness lies in advancing the accuracy and precision of industrial robots during circular motions, specifically tailored for orbital milling applications. The innovative approach synergistically uses the observability index and telescopic ballbar to achieve these objectives.

The purpose of this paper aims to design a robust wind turbine emulator (WTE) based on a three-phase induction motor (3PIM).

The 3PIM is driven by a soft voltage source inverter (VSI) controlled by a specific space vector modulation. By adjusting the appropriate vector sequence selection, the desired VSI output voltage allows a real wind turbine speed emulation in the laboratory, taking into account the wind profile, static and dynamic behaviors and parametric variations for theoretical and then experimental analysis. A Mexican hat profile and a sinusoidal profile are therefore used as the wind speed system input to highlight the electrical, mechanical and electromagnetic system response.

The simulation results, based on relative error data, show that the proposed reactive power control method effectively estimates the flux and the rotor time constant, thus ensuring an accurate trajectory tracking of the wind speed for the wind emulation application.

The proposed architecture achieves its results through the use of mathematical theory and WTE topology combine with an online adaptive estimator and Lyapunov stability adaptation control methods. These approaches are particularly relevant for low-cost or low-power alternative current (AC) motor drives in the field of renewable energy emulation. It has the advantage of eliminating the need for expensive and unreliable position transducers, thereby increasing the emulator drive life. A comparative analysis was also carried out to highlight the online adaptive estimator fast response time and accuracy.

Influenced by factors such as fluctuations in market supply and demand and the rapid development of new technologies, manufacturing companies are facing greater challenges to transform and upgrade. The existing relevant studies about sustainable innovation capabilities mostly focus on classification of innovation or from a static resource-based view and less on quantitative measurement from a dynamic perspective and inter-organizational relationships. This paper takes a dynamic capabilities and social capital theory, explore the concept and dimensions of sustainable innovation capabilities and then makes development of a new scale.

This paper uses a combination of qualitative and quantitative research methodologies to develop a measure of sustainable innovation capabilities in two studies. Grounded theory methodology is used to explore the concept definition and dimensions of sustainable innovation capabilities. Exploratory factor analysis and confirmatory factor analysis are conducted to refine and validate the factor structure, and then the authors developed the sustainable innovation capabilities scale.

The results show that sustainable innovation capabilities composed of ideation capabilities, opportunity capture capabilities, agile learning, creative inheritance and networking capabilities. The sustainable innovation capabilities that firms should possess are reflected at the firm level and inter-organizational relationship level, and the culture-specific dimension of creative inheritance reflects the influence of national and organizational culture.

The research reveals the internal driving force of the manufacturer's sustainable innovation capabilities, as well as the role and uniqueness embodied in the specific culture, providing a new perspective for improving the manufacturer's sustainable innovation capabilities.

This paper bridges the gap between the theory and practice by developing a life cycle sustainability tracker (LCST). The study is seeking to proffer solutions to an observed shortcoming of conventional life cycle sustainability assessment (LCSA) communication platforms. Notably, the static nature of the information provided on such platforms has made it difficult for them to be used for real-time decision-making and predictions. The main aim of this paper is to develop a LCST that facilitates a dynamic visualisation of life cycle sustainability results and allows for an integrated benchmark across the dimensions of sustainability.

The study leverages the model development capabilities of the design science research strategy in accomplishing a dynamic and novel communication platform. A life cycle thinking methodology and appropriate multicriteria decision approach (MCDA) is applied to accomplish a comprehensive, streamlined and replicable approach in mapping and tracking the progress of sustainable development goals (SDGs) in the National Infrastructure Pipeline (NIP) projects in India.

It was found that: (1) The use of the LCST tracker provides a dynamic and holistic insight into the key LCSA indicators with clearly defined benchmarks to assess the impact on the SDG 11, (2) The NIP projects achieve an upward trend across all the regions, and the percentage of opportunities ranges from 11 to 24%, with the South experiencing the highest growth and the North having the minimal increase in percentage and (3) The assessment score (52–58%) provides performance metrics that align well with the LCST – which ranges between “Fair” and “Average” for all the regions in India.

The novelty of this research is that the LCST provides a transparent and harmonised approach to reporting on the LCSA results. The LCST utilises heat maps and radial mapping to achieve an intuitive display of large amounts of highly heterogeneous data, thus allowing the synthesis of large sets of information compactly and with coherence. Progress towards the SDGs change on a yearly basis; hence, a dynamic LCSA tool provides a timely and the valuable context to map and track performance across different regions and contexts.