The global agreement on environmentally friendly policies puts pressure on businesses to implement good practices to increase legitimacy in a competitive environment. This research aims to examine business dynamic capabilities and value creation processes through the concept of green dynamic marketing capabilities. This concept addresses the ability of businesses to absorb, manage information and accumulate new knowledge that fuels innovative endeavors. The dynamic capability view and customer value theory are integrated to theoretically explain the value creation process of market-orientated innovative products. A total of 58 global companies in Clean200 were sampled. A quantitative approach was conducted to measure the effect of organizational learning (environment management team, environment management training, environment supply chain management) on green innovation (environmental innovation score, eco design product). The results showed that the contribution of Model-1 (0.473 or 47.3%) explained the effect of organizational learning on environmental innovation score, respectively on the variables of environment management team (2.859/0.005), environment management training (−2.971/0.003), and environment supply chain management (7.786/0.000). The contribution of Model-2 (0.448/44.8%) explains the effect of organizational learning on eco-design product, respectively on the variables of environment management team (4.280/0.000), environment management training (−6.401/0.000), and environment supply chain management (7.910/0.000). Model-3 tested the structural association variables in organizational learning and green innovation. A significant influence can be seen with a probability value smaller than 0.05. This research shows that the concept of green dynamic marketing capabilities can be used to explain the ability of businesses in response to the pressure of green global norms through the development of organizational learning towards creation of green innovation product that has impact on market performance. The implication of this research is the creation of new mindset in which green global norms challenge becomes an opportunity for businesses to improve competitiveness.
In recent years, the environment in the manufacturing industry has become strongly competitive, which is why companies have found it necessary to constantly adjust their strategies and take actions aimed at improving their performance and competitiveness in a sustainable way to grow and remain in the market. Therefore, this paper aims to present an analysis to explain the current situation in the manufacturing industry in Aguascalientes, Mexico, by means of a survey in which product eco-innovation (PEI), process eco-innovation (PrEI) and organizational eco-innovation (OEI) and its effect on environmental performance (EP) and sustainable competitive performance (SCP) were measured. The results show that (EP) is positively and significantly influenced by (PEI) and (PrEI), while no significant influence is found for (OE). Furthermore, it is confirmed that environmental performance positively and significantly influences (SCP). The findings obtained from this study point to the relevance of promoting eco-innovation activities in the manufacturing sector, as this will ensure sustainable competitiveness.
Many studies have called for more research and increased knowledge about Family Businesses (FB), notably their sustainability. This work aims to reduce this limitation through a narrative literature review and thus contribute to knowledge about FB’s compliance and sustainability design. The results suggest that interest in sustainability practices is growing but still low, and implementation is challenging. This work presents scientific contributions, notably to the Theories of Vision Based on Resources, Dynamic Capabilities, and Stewardship. At the same time, it contributes to the operationalization of FB, as they can design their sustainability practices and compliance strategies similar to those of others. The value of this work culminates in the original proposal of a framework identifying the leading information representative of the main challenges for the sustainability of FB.
The aviation industry is experiencing over and over again a technological revolution, nowadays with airports at the forefront of embracing smart technologies to enhance operational efficiency, security and passenger experience. This article comprehensively analyzes the benefits, challenges, and legal implications of adopting smart technologies in airport facilitation and security control. It examines the regulatory framework established by the International Civil Aviation Organization (ICAO) on an international level and by sovereign states on a national level. It explores using smart solutions such as automated systems, data and biometric verification, artificial intelligence (AI), and the Internet of Things (IoT) devices in airport operations. The authors’ purpose is to highlight the improvements in airport facilities and security measures brought about by these technologies, while addressing concerns over privacy, cost, technological limitations and human factors. By emphasizing the importance of a balanced approach and considering innovation alongside legal and operational imperatives, the article underscores the transformative potential of smart and integrated technologies in shaping the future of air travel.
Amidst an upsurge in the quantity of delinquent loans, the financial industry is experiencing a fundamental transformation in the approaches utilised for debt recovery. The debt collection process is presently undergoing automation and improvement through the utilisation of Artificial Intelligence (AI), an emergent technology that holds the potential to revolutionise this sector. By leveraging machine learning, natural language processing, and predictive analytics, automated debt recovery systems analyse vast quantities of data, generate forecasts regarding the likelihood of recovery, and streamline operational processes. Debt collection systems powered by AI are anticipated to be compliant, precise, and effective. On the other hand, conventional approaches are linked to increasing expenditures and inefficiencies in operations. These solutions facilitate efficient resource allocation, customised communication, and rapid data analysis, all while minimising the need for human intervention. Significant progress has been made in data analytics, predictive modelling, and decision-making through the application of artificial intelligence (AI) in debt recovery; this has the potential to revolutionize the financial sector’s approach to debt management. The findings of the research underscore the criticality of artificial intelligence (AI) in attaining efficacy and precision, in addition to the imperative of a data-centric framework to fundamentally reshape approaches to debt collection. In conclusion, artificial intelligence possesses the capacity to profoundly transform the existing approaches utilized in debt management, thereby guaranteeing financial institutions’ sustained profitability and efficacy. The application of machine learning methodologies, including predictive modelling and logistic regression, signifies the potential of the system.
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