The key purpose of the article is to analyze the effect of digital transformations, such as blockchain technology (BCT), the social internet of things (SIoT), and artificial intelligence (AI) techniques, on the supply chain (SC) for traceability and for creating transparency. The partial least squares (PSL) structural equation modeling (SEM) method was applied in combination with SmartPLS v3.3.6. The package was employed to obtain information through a survey of SC Pakistani professionals using the snowball sampling technique. Traceability plays a crucial role in enhancing transparency and ultimately the performance of SC through BCT, SIoT, and AI. Therefore, the study recommends starting the digital transformation of the SC because this is a complex process that involves a wide range of internal and external stakeholders. The study findings show the importance of technologies of traceability and transparency as an analytical multidisciplinary approach to enhance the SC sector, although with certain limitations this can be taken into account by stakeholders. This study will be useful for decision makers investing in technologies of traceability and transparency in the SC. The study raises the awareness of traceability and transparency in the SC process, and also reveals research gaps and provides opportunities for further research. Despite the prevalence of studies in supply-chain traceability (SCT) and transparency, there is a dearth of empirical proof on how the digital transformation of the SC could lead to transparency and ultimately performance.
Artificial Intelligence (AI) is generating new horizons in one of the biggest challenges in the world’s society—poverty. Our goal is to investigate utilities of AI in poverty prediction via finding answers to the following research questions: (1) How many papers on utilities of AI in poverty prediction were published up until March, 2022? (2) Which approach to poverty was applied when AI was used for poverty prediction? (3) Which AI methods were applied for predicting poverty? (4) What data were used for poverty prediction via AI? (5) What are the advantages and disadvantages of the created AI models for poverty prediction? In order to answer these questions, we selected twenty-two papers using appropriate keywords and the exclusion criteria and analyzed their content. The selection process identified that, since 2016, publications on AI applications in poverty prediction began. Results of our research illustrate that, during this relatively short period, the application of AI in predicting poverty experienced a significant progress. Overall, fifty-seven AI methods were applied during the analyzed span, among which the most popular one was random forest. It was revealed that with the adoption of AI tools, the process of poverty prediction has become, from one side, quicker and more accurate and, from another side, more advanced due to the creation and possibility of using different datasets. The originality of this work is that this is the first sophisticated survey of AI applications in poverty prediction.
The purpose of this paper is to test the role of trust in supervisors in mediating the link between paternalistic leadership styles and employee voice and to investigate the contingency role of self-efficacy on the relationship between trust in supervisors and employee voices. We designed the items using survey questionnaires that were assessed by prior studies and collected data from 485 highly skilled employees of manufacturing organizations. To assess the validity of the suggested hypotheses, we used a Baron and Kenny (1986) approach and conducted hierarchical regression analysis. The findings reveal that authoritarian leadership and moral leadership styles are significantly related to trust in supervisors, which explains the association between authoritarian leadership style, and moral leadership style and employee voice. However, the results suggest that trust in supervisors does not explain the association between benevolent leadership style and employee voice. Moreover, the findings reveal that self-efficacy moderates the link between trust in supervisors and employee voice. The originality of this work lies in the fact that this research is the first to test the mediating role of trust in supervisors in the relationship between paternalistic leadership styles and employee voice and the moderating role of self-efficacy on the association between trust in supervisors and employee voice.
Government's policy in financing social sphere is becoming more and more topical. In this regard, managing pension system effectively, conducting research basing on "income distribution through the time" principle in its financing is of particular significance. In this article the possibility of applying the experience of European Union countries in the level of coverage of population by the pension plan and its development in Uzbekistan.
This article investigates the expansion of organizational learning capabilities (OLC) and its growing utilization in the organization in order to identify whether OLC affects the relationship between training and development and organizational performance. This study further explores the correlation between organizational learning capabilities and organizational performance, offering insight into the different understandings of organizational triumph related to OLC. This research was conducted via survey method and data were collected from five service industries in Khyber Pakhtunkhwa (KP), Pakistan. A data sample of 300 employees was analyzed using quantitative approaches, such as descriptive statistics and partial least squares structural equation modeling (PLS-SEM). The results of the article addressed issues that are related to human capital regarding OLC, including training and development aspects which were not discussed by the literature in the past. The main findings of this paper are the formulation of an empirically and theoretically supported model related to the effect of OLC on the relationship between training and development and organizational performance. On the other hand, this study signifies that OLC is a better instrument for enhancing organizational performance, as well as in dealing with today’s indeterminate and continuously challenging economic atmosphere. This study is the first of its nature to shed light on training and development, organizational learning capabilities, and organizational performance in the service sector of KP, Pakistan.
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