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Family businesses are on the rise and facing severe sustainability challenges. The overall purpose of this thesis is to examine the moderating role of technological resources in the relationship between marketing innovation and family business sustainability.

From a post-positivist perspective, this study utilized a quantitative approach and causal research design. 204 family businesses within the Accra Metropolitan Assembly were sampled for this study. Structural Equation Modeling (SMART PLS 4) was utilized for data analysis after a closed-ended questionnaire was used to gather data.

It was evidenced that marketing innovation has a positive significant effect on family business sustainability. Technological resources have a negative significant moderating effect on the relationship between marketing innovation and family business sustainability.

The originality of this study lies in examining the moderating effect of technological resources on the relationship between marketing innovation and family business sustainability in Ghana, where this phenomenon is less explored.

Involvement plays a crucial role in understanding consumer behavior. In recent years, the concept of social innovation has gained momentum, resulting in the development of eco-friendly products and initiatives to tackle societal issues. This trend is driven by consumers, who are increasingly aware of the social benefits of the products they buy. The present study aims to investigate how socially innovative, environmentally conscious consumers can influence their engagement with eco-friendly products.

Researchers aimed to investigate the “impact of social innovation on involvement in environmentally friendly products.” They selected active members of various environmental organizations operating in the country to conduct the study. Convenience sampling was used to reach out to these members, and the managers of these organizations sent an electronic questionnaire to all members' email addresses.

The study found that socially innovative, environmentally conscious consumers tend to be more interested in the symbolic meaning and pleasure of products, leading to a decrease in perceived risk and risk importance.

There are limited studies examining the relationship between social innovation and product innovation. Therefore, the novelty of this research lies in its exploration of the relationship between these two concepts. Unlike previous studies, this research found a negative relationship between the dimensions of risk importance and risk probability. This result was interpreted as environmentally friendly products being sensitive to public welfare and not being perceived as risky by environmentalists.

To endure and cope in the rapidly changing environment, it is required of firms to gain a deeper acquisition of knowledge on market dynamics and subsequently concentrate on corporations' capacity to create, restructure and integrate their internal and external competences. Hence, the objective of this study is to investigate the influence of eco-dynamic capability (EDC) on the sustainability performance of small and medium-sized enterprises (SMEs).

Structured questionnaires were used to obtain primary data. The data were solicited from 500 employees and owner-managers of SMEs. The study’s hypotheses were tested using standard multiple regression through IBM SPSS Statistics (version 24).

The study revealed that EDC has a substantial positive effect on the economic, social and environmental sustainability performance dimensions.

The focus of this study is on EDC. Thus, although dynamic capability has been the subject of substantial study, little is known regarding the effect of EDC on the economic sustainability performance (ESP) (financial), environmental sustainability performance (ENSP) and social sustainability performance (SSP) of SMEs, predominantly amongst SMEs in emerging economies.

The environmental deterioration has become one of the most economically consequential and charged topics. Numerous scholars have examined the driving factors failing to consider the structural breaks. This study aims to explore sustainability using the per capita ecological footprints (EF) as an indicator of environmental adversities and controlling the resources rent [(natural resources (NR)], labor capital (LC), urbanization (UR) and per capita economic growth [gross domestic product (GDP)] of China.

Through the analysis of the long- and short-run effects with an autoregressive distributed lag model (ARDL), structural break based on BP test and Granger causality test based on vector error correction model (VECM), empirical evidence is provided for the policies formulation of sustainable development.

The long-run equilibrium between the EF and GDP, NR, UR and LC is proved. In the long run, an environmental Kuznets curve (EKC) relationship existed, but China is still in the rising stage of the curve; there is a positive relationship between the EF and NR, indicating a resource curse; the UR is also unsustainable. The LC is the most favorable factor for sustainable development. In the short term, only the lagged GDP has an inhibitory effect on the EF. Besides, all explanatory variables are Granger causes of the EF.

A novel attempt is made to examine the long-term equilibrium and short-term dynamics under the prerequisites that the structural break points with its time and frequencies were examined by BP test and ARDL and VECM framework and the validity of the EKC hypothesis is tested.

This paper aims to propose a novel adaptive Kalman filter (APRKF) designed to accommodate the operational environment of maglev pipeline trains, enhancing positioning accuracy by mitigating the impact of noise and sensor errors.

This approach is built upon the Kalman filtering algorithm, using a limited-memory weighted method to derive adaptive factors, while establishing judgment thresholds to constrain the range of their variation.

A comparative analysis with the traditional Kalman filter and the Sage-Husa adaptive filter reveals that APRKF offers superior speed estimation performance while effectively mitigating error accumulation caused by speed integration. The results indicate that APRKF excels in both speed and position estimation, demonstrating its effectiveness in improving estimation accuracy.

This study proposes an innovative method for the velocity and position estimation system of maglev tube-track trains.

This research aims to examine the effect of organisational culture on supply chain collaboration and firms’ competitive advantage in the garment industry in Vietnam.

Underpinned by the relational view and the organisational culture theories, the conceptual framework was proposed. This study obtained data from a survey of 192 managers in garment firms in Vietnam. A structural equation modelling was employed to examine the relationship between organisational culture, supply chain collaboration and competitive advantage.

There was a significant positive relationship between organisational culture in terms of group and development types and supply chain collaboration. Besides, the results revealed a significant positive relationship between supply chain collaboration and competitive advantage in terms of cost and differentiation. Furthermore, the cost competitive advantage was also found to have a significant positive effect on differentiation competitive advantage.

This study is perhaps one of the first empirical attempts to examine the relationship between organisational culture, supply chain collaboration and competitive advantage in the garment industry in Vietnam. Moreover, this study extends the application of the relational view and organisational culture theories in explaining these relationships in a new research context.

This study aims to explore the formation mechanism of aerodynamic noise of a high-speed maglev train and understand the characteristics of dipole and quadrupole sound sources of the maglev train at different speed levels.

Based on large eddy simulation (LES) method and Kirchhoff–Ffowcs Williams and Hawkings (K-FWH) equations, the characteristics of dipole and quadrupole sound sources of maglev trains at different speed levels were simulated and analyzed by constructing reasonable penetrable integral surface.

The spatial disturbance resulting from the separation of the boundary layer in the streamlined area of the tail car is the source of aerodynamic sound of the maglev train. The dipole sources of the train are mainly distributed around the radio terminals of the head and tail cars of the maglev train, the bottom of the arms of the streamlined parts of the head and tail cars and the nose tip area of the streamlined part of the tail car, and the quadrupole sources are mainly distributed in the wake area. When the train runs at three speed levels of 400, 500 and 600 km·h⁻¹, respectively, the radiated energy of quadrupole source is 62.4%, 63.3% and 71.7%, respectively, which exceeds that of dipole sources.

This study can help understand the aerodynamic noise characteristics generated by the high-speed maglev train and provide a reference for the optimization design of its aerodynamic shape.

Objectively evaluating the fairness of the algorithm, exploring in specific scenarios combined with scenario characteristics and constructing the algorithm fairness evaluation index system in specific scenarios.

This paper selects marketing scenarios, and in accordance with the idea of “theory construction-scene feature extraction-enterprise practice,” summarizes the definition and standard of fairness, combs the application link process of marketing algorithms and establishes the fairness evaluation index system of marketing equity allocation algorithms. Taking simulated marketing data as an example, the fairness performance of marketing algorithms in some feature areas is measured, and the effectiveness of the evaluation system proposed in this paper is verified.

The study reached the following conclusions: (1) Different fairness evaluation criteria have different emphases, and may produce different results. Therefore, different fairness definitions and standards should be selected in different fields according to the characteristics of the scene. (2) The fairness of the marketing equity distribution algorithm can be measured from three aspects: marketing coverage, marketing intensity and marketing frequency. Specifically, for the fairness of coverage, two standards of equal opportunity and different misjudgment rates are selected, and the standard of group fairness is selected for intensity and frequency. (3) For different characteristic fields, different degrees of fairness restrictions should be imposed, and the interpretation of their calculation results and the means of subsequent intervention should also be different according to the marketing objectives and industry characteristics.

First of all, the fairness sensitivity of different feature fields is different, but this paper does not classify the importance of feature fields. In the future, we can build a classification table of sensitive attributes according to the importance of sensitive attributes to give different evaluation and protection priorities. Second, in this paper, only one set of marketing data simulation data is selected to measure the overall algorithm fairness, after which multiple sets of marketing campaigns can be measured and compared to reflect the long-term performance of marketing algorithm fairness. Third, this paper does not continue to explore interventions and measures to improve algorithmic fairness. Different feature fields should be subject to different degrees of fairness constraints, and therefore their subsequent interventions should be different, which needs to be continued to be explored in future research.

This paper combines the specific features of marketing scenarios and selects appropriate fairness evaluation criteria to build an index system for fairness evaluation of marketing algorithms, which provides a reference for assessing and managing the fairness of marketing algorithms.

Algorithm governance and algorithmic fairness are very important issues in the era of artificial intelligence, and the construction of the algorithmic fairness evaluation index system in marketing scenarios in this paper lays a safe foundation for the application of AI algorithms and technologies in marketing scenarios, provides tools and means of algorithm governance and empowers the promotion of safe, efficient and orderly development of algorithms.

In this paper, firstly, the standards of fairness are comprehensively sorted out, and the difference between different standards and evaluation focuses is clarified, and secondly, focusing on the marketing scenario, combined with its characteristics, key fairness evaluation links are put forward, and different standards are innovatively selected to evaluate the fairness in the process of applying marketing algorithms and to build the corresponding index system, which forms the systematic fairness evaluation tool of marketing algorithms.

As a crucial institutional form established since the Chinese economic reform, the system of competitive local governments has been shaping the characteristics of China's socialist market economy to a considerable degree.

This study not only adopts the view of existing studies that attribute the economic motive of local governments to rent and consider land public finance as a means through which local governments carry out strategic investment but also attempts to further develop the view within a Marxist analytical framework.

As a result, the local governments have helped to maintain an incredibly high investment rate over a considerable period of time, facilitating the continuous, rapid growth of the Chinese economy.

This study concludes that China's local governments function as the productive allocator and user of rent in the strategic investment based on land public finance and thereby embed themselves in the relative surplus-value production initially arising from competition amongst enterprises, forming the dual structure of relative surplus-value production unique to China's economy.

This study purposes to study the influence of artificial freezing on the liquefaction characteristics of Nanjing sand, as well as its mechanism.

was studied through dynamic triaxial tests by means of the GDS dynamic triaxial system on Nanjing sand extensively discovered in the middle and lower reaches of the Yangtze River under seismic load and metro train vibration load, respectively, and potential hazards of the two loads to the freezing construction of Nanjing sand were also identified in the tests.

The results show that under both seismic load and metro train vibration load, freeze-thaw cycles will significantly reduce the stiffness and liquefaction resistance of Nanjing sand, especially in the first freeze-thaw cycle; the more freeze-thaw cycles, the worse structural behaviors of silty-fine sand, and the easier to liquefy; freeze-thaw cycles will increase the sensitivity of Nanjing sand's dynamic pore pressure to dynamic load response; the lower the freezing temperature and the effective confining pressure, the worse the liquefaction resistance of Nanjing sand after freeze-thaw cycles; compared to the metro train vibration load, the seismic load in Nanjing is potentially less dangerous to freezing construction of Nanjing sand.

The research results are helpful to the construction of the artificial ground freezing of the subway crossing passage in the lower reaches of the Yangtze River and to ensure the construction safety of the subway tunnel and its crossing passage.