This study aimed to gain insights into the attitudes and strategies of top management regarding workplace happiness within a semi-government organization in the United Arab Emirates (UAE). Six senior managers at the organization were interviewed to explore their perspectives on employee happiness and the initiatives implemented to enhance it. Thematic analysis of the interview transcripts revealed several key findings. Top managers demonstrated strong commitment and willingness to prioritize employee well-being through long-term research-driven improvements. A variety of strategies incorporating personal, organizational, and Human Resources Management (HRM) factors known to impact happiness were utilized. Religious considerations and empowerment initiatives respect personal values while fostering intrinsic motivation. Top leaders modeled strategic priorities through their conduct, emphasizing visible support. The organization balanced individual needs with organizational goals respectfully. The findings provide practical implications for optimizing retention and performance outcomes through dedicated strategic happiness efforts guided by empirical research. However, more extensive research across diverse populations could further advance understanding in this field.

This study explores how Jordanian telecom companies can balance Internet of Things (IoT) driven automation with maintaining genuine consumer-brand connections. It seeks strategies that blend IoT automation with personalized engagement to foster lasting consumer loyalty. Employing qualitative research via semi-structured interviews with IT and customer service managers from Jordanian telecom companies. IoT-driven automation in Jordan’s telecom sector revolutionizes consumer-brand relationships by enabling data-driven personalization. It emphasizes the importance of IoT proficiency, transformed marketing strategies, and the need to balance personalization with consumer privacy. Interviews stress the significance of maintaining authentic human connections amidst automation. Strategies for Jordanian telecom firms include integrating IoT data into CRM systems, employing omnichannel marketing, balancing automation with human interaction, adopting a consumer-centric approach, mitigating security risks, and leveraging IoT insights for adaptive services. These approaches prioritize consumer trust, personalized engagement, and agile service adaptation to meet dynamic consumer preferences. This research provides actionable strategies for telecom firms on effective IoT integration, emphasizing the need to maintain genuine consumer relationships alongside technological advancements. It highlights IoT’s transformative potential while ensuring lasting consumer loyalty and business success. Future research avenues could explore longitudinal studies and the interplay between AI and IoT in telecom services.

Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.

The study has formulated the objective of synthesizing the extent to which technological barriers intervene in the transparency and effectiveness of public management (PM). Methodologically, the study was of a fundamental or basic nature, with a systematic review design, the databases of Scopus (369), SciELO (2), Web of Science (184) were explored, after the review process a set of 22 articles was available. The registration was made in an Excel table where the main data of the articles were included. 32% of the articles selected for the analysis of the evidence are from the period 2020, 27% were from 2022 and 18% from the year 2023; as far as origin is concerned, 14% of the articles come from Peru and 9% from Australia, Brazil, South Korea, Spain and Indonesia. In summary, the study points out that government institutions are making progress in digitizing and improving the citizen experience through electronic services, but they face challenges in areas such as resource management, the low adoption of advanced technologies such as blockchain and artificial intelligence, as well as the lack of transparency in PM. Despite this, it is highlighted that e-government improves citizen satisfaction, and the need to invest in digital innovation, training and overcoming technological barriers to achieve an effective transformation in state administration and promote a more inclusive and advanced society is emphasized.

Smallholder paprika farmers in Zimbabwe contribute to local economies and food security but face supply chain challenges like limited market access and poor infrastructure which lead to post harvest losses and unpredictable prices. To survive, these farmers must adopt sustainable value networks to reduce operational costs and improve performance. This study sought to establish the effect of sustainable value networks on the operational performance of smallholder paprika farming in Zimbabwe. This study, using a positivist research philosophy and a quantitative approach, surveyed 288 smallholder paprika farmers in Zimbabwe. Exploratory factor analysis and partial least squares structural equation modelling were used to validate the constructs and test the hypothesised relationships. Results demonstrate a moderate level of implementation of value networks in smallholder paprika farming characterised by successes and challenges. The findings illustrated resource sharing among smallholder farmers, facilitated by initiatives, such as recycled seed exchanges and financial support through village savings and loan associations. However, results show that challenges persist, particularly with market access and financial support. Results indicate that there is a significant awareness and implementation of green supply chain management practices among smallholder paprika farmers even though they do not have access to resources and live in rural areas. The findings demonstrate that value networks significantly influence the adoption of green supply chain management practices, which in turn positively impact operational performance, environmental performance, and social performance. Green supply chain management practices were found to mediate the relationship between value networks and environmental performance, social performance, and operational performance, underlining the critical role of sustainable practices in enhancing performance outcomes. While environmental performance showed a positive effect on operational performance, the direct influence of social performance on operational performance was found to be statistically insignificant, suggesting the need for further exploration of the factors linking social benefits to operational efficiency. The research contributes to both theory and practice by presenting a sustainable value network model for smallholder paprika farmers, integrating value network, green supply chain management practices and environmental performance to enhance operational performance. Practical implications include policy recommendations to strengthen collaboration between smallholder farmers and other stakeholdersand address power imbalances with intermediaries. Future research should extend the study to other agricultural sectors and incorporate more diverse stakeholder perspectives to validate and generalise the proposed sustainable value network model.