Search results

This study aims to investigate the relationship between intrinsic motivators and the transfer of knowledge/skills gained during training to work. The intrinsic motivators considered for the study were self-efficacy and motivation to transfer the training knowledge. The study also examined how work conditions mediate the association of intrinsic motivators and training transfer. The working conditions considered in the study were autonomy and the opportunity to perform in the job.

A cross-sectional study was conducted among 426 participants from microfinance institutions in Karnataka, India, who had received a three-week job training six months earlier. Data were collected using a questionnaire and structural equation modelling was performed for the analysis of the data.

The study found positive significant relationships between motivation motivators and training transfer of learning. Positive relationships were also seen between work conditions and training transfer of learning acquired via training. The study also established the role of intrinsic motivators in predicting training transfer through work conditions.

This study stands among the pioneering works to investigate the influence of intrinsic motivators on training transfer, while also examining the mediating role of work conditions. It focuses on an emerging economy, specifically India, thereby contributing valuable insights to the field.

To describe the Pragathi Bandhu Groups (PBG) Model and portray the performance of PBG farmers encouraged by their financial and decision-making participation in micro financing and labor sharing, as well as to analyze the factors that influenced participation of small farmers in PBG.

The empirical study is confined to the small farmers and laborers of PBG functioning in the coastal districts of Karnataka State in India. The study is conducted in Belthangady and Bantwal Taluks of Dakshina Kannada (DK) Districts-Udupi taluk of Udupi District in the State of Karnataka. Primary data from 100 farmer members, selected at random in each of the Taluks, is collected through personal interview by administering semi-structured interview schedules and open discussion. In addition, the data on the functions and the performance of PBG in the State of Karnataka in India are also collected from the official records of Shri Kshetra Dharmasthala Rural Development Project (SKDRDP) and their field-level functionaries through informal discussions. Factor analysis is performed with principal component analysis followed by Varimax rotation to analyze the factors that influenced participation of small farmers in PBG.

Results show that the implementation of PBG Model, through the collective participation of small farmers in micro financing, free labor sharing, financial and decision-making activities underlying the functions of PBG Model, has helped them to achieve robust performance in terms of increased savings mobilization, loan utilization, and value of free labor sharing and acres of land brought under cultivation with the help of irrigation facilities created by them. The factor analysis has derived four factors that influenced the participation of farmers in PBG (agriculture development, financial participation, capacity building, and other benefits) which explain 63.701 of total factor variance.

The findings of this paper can benefit the small farmers and laborers in replicating the PBG Model and its initiatives that address shortages of labor and credit, as well as the high cost of labor, particularly in the unorganized sector in the agrarian economy.

The insights offered are likely to be beneficial to the distressed small farmers, development agencies, and agriculture policy makers to solve the agrarian crisis caused due to shortages of labor and farm credit.

The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their interconnectedness and characteristics. This study aims to help organizations formulate apt DS strategies by providing a close-to-reality DS implementation framework of barriers, in conjunction with extant literature and practitioners' viewpoints.

The authors synthesized 100 distinct barriers through systematic literature review (SLR) under the individual, organizational and governmental taxonomies. In discussions with 48 industry experts through semi-structured interviews, 14 key barriers were identified. The selected barriers were explored for their pair-wise relationships using interpretive structural modeling (ISM) and fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses in formulating the hierarchical framework.

The lack of awareness and data-related challenges are identified as the most prominent barriers, followed by non-alignment with organizational strategy, lack of competency with vendors and premature governmental arrangements, and classified as independent variables. The non-commitment of top-management team (TMT), significant investment costs, lack of swiftness in change management and a low tolerance for complexity and initial failures are recognized as the linkage variables. Employee reluctance, mid-level managerial resistance, a dearth of adequate skills and knowledge and working in silos depend on the rest of the identified barriers. The perceived threat to society is classified as the autonomous variable.

The study augments theoretical understanding from the literature with the practical viewpoints of industry experts in enhancing the knowledge of the DS ecosystem. The research offers organizations a generic framework to combat hindrances to DS initiatives strategically.

Sentiment analysis has observed a nascent interest over the past decade in the field of social media analytics. With major advances in the volume, rationality and veracity of social networking data, the misunderstanding, uncertainty and inaccuracy within the data have multiplied. In the textual data, the location of sarcasm is a challenging task. It is a different way of expressing sentiments, in which people write or says something different than what they actually intended to. So, the researchers are showing interest to develop various techniques for the detection of sarcasm in the texts to boost the performance of sentiment analysis. This paper aims to overview the sentiment analysis, sarcasm and related work for sarcasm detection. Further, this paper provides training to health-care professionals to make the decision on the patient’s sentiments.

This paper has compared the performance of five different classifiers – support vector machine, naïve Bayes classifier, decision tree classifier, AdaBoost classifier and K-nearest neighbour on the Twitter data set.

This paper has observed that naïve Bayes has performed the best having the highest accuracy of 61.18%, and decision tree performed the worst with an accuracy of 54.27%. Accuracy of AdaBoost, K-nearest neighbour and support vector machine measured were 56.13%, 54.81% and 59.55%, respectively.

This research work is original.

The purpose of this paper is to study and develop supply chain structure of traditional Indian agri-fresh food supply chain (AFSC). This paper proposes a mathematical model to design a traditional Indian AFSC to minimize total distribution cost and post-harvest losses in the chain.

This paper formulates two mathematical models to structure and represent the flow of products in the existing chain. First, a three-echelon, multi-period, multi-product, mixed-integer linear programming (MILP) model is formulated to minimize the total distribution cost incurred in the chain. Further, the developed formulation is extended by considering the perishability of products in the second model.

A real case study problem of Mandsaur district (India) is solved in LINGO 17.0 package to check the validity of the formulated models. The perishable (second) model of AFSC reports better results in terms of costs and post-harvest losses minimization. The results revealed that 92% of the total distribution cost incurred in the transportation of products from farmers to the hubs.

This paper includes implications for redesigning an existing supply chain network by incorporating an appropriate transportation strategy from farmers to hubs to minimize transportation inefficiency and enhance the profitability of farmers.

The formulated AFSC model would help managers and policymakers to identify optimal locations for hubs where required infrastructure would be developed.

According to the author's best knowledge, this paper is the first to design traditional Indian AFSC by considering the perishability of products.