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The purpose of this paper is to study the characteristics of the workers in the informal economy and explore the reasons for workers migrating from rural to urban area. The authors also explore and enumerate various reasons why the migrants choose to work informally and study whether internal migrants treat this sector as temporary or transitory before moving to the formal sector. The authors reconnoitre the issues in coverage of factors in unregistered service, this research is carried out at a smaller scale of operations of the service enterprises having a minimum of three (or more) employees, which poses significant issues in the enumeration. This work further emphasises on the reasons why people migrate and choose the informal sector (IS) and to estimate the contribution of technology towards productivity of this sector.

Building on empirical data collected through interviews with the migrants, who are now part of the informal service enterprises of Delhi and peripheral areas, this paper presents the results of a survey conducted in 2017. This research is based on appropriate scale driven by the instrument of choice by the sampling of units. Data were collected by conducting field survey using structured questionnaire. By performing the estimation at the unit rather than the industry level, the authors reduce difficulties of mis-measured output and inputs, thus, potentially obtaining a more accurate estimate of technologies contributions towards the firm productivity.

The small service enterprises are making poorer value addition towards measured productivity due to the factors such as lack of equipment or technical know-how. The authors find that marginalisation thesis holds true only partially and the rest are in this sector by choice, considering it as an opportunity. Maximum number of entrants had been attracted by opportunities in this sector itself; actual and potential mobility from the informality towards formalisation is quite low; education is one of the important determinants for entrepreneurs shifting from informality towards formalisation.

The research is limited only to informal service enterprises located in Delhi, the national capital of India and the peripheral areas.

By identifying the factors, proper policy measures can be designed which will be in a focused direction to reduce the size of the IS and to improve the working condition of the migrants who are part of this sector. The estimation is at the unit level using primary data.

The estimation is at the unit level using primary data, the research contributes to the literature on informal service sector, and this sector needs more intensive large-scale studies in order to design policies which can result in betterment of the society as a whole, benefiting the segment that needs immediate attention from government and society as well.

The purpose of this paper is to identify reasons as to why firms operate informally, and to explore the rationalisation of not moving towards formalisation.

Building on empirical data collected through interviews with the entrepreneurs of the informal service enterprises of Delhi and peripheral areas, this paper presents the results of the survey conducted in 2017. By using the analytical tool developed by I. Bross, the authors have identified the most significant contributing factors to informality.

In the research, the authors establish that competition and lack of awareness are the most dominant reasons due to which informal firms are hesitant in moving towards formalisation. For successful transition towards formalisation, a “new pact” between the workers, enterprises and governments needs to be developed, based on capacity building, productivity gains, enabling business environment, empowerment and entitlements to social and economic rights.

The research is limited only to informal service enterprises located in Delhi, the national capital of India, and the peripheral areas.

By identifying the most dominant factors, focussed steps can be taken to reduce the size of the informal sector.

The informal service enterprises are not a widely explored community by researchers and policy makers. This sector can employ more people with less investment, and hence requires intensive study. The use of RIDIT approach to rank the identified factors due to which the firms do not move towards formalisation is the novelty of this work.

This study aims to assess the effect of knowledge management (KM) development and emotional intelligence (EI) on the productivity of librarians regarding the mediating role of job motivation (JM) and job feedback (JF).

This study was carried out in two phases. First, the variables affecting the productivity of librarians were identified and selected through an explorative study and by surveying their opinions. Then, the theoretically designed model was administered to 312 librarians at Iranian public libraries. A questionnaire was used to collect data, and the structural equation modelling technique was used to analyse data.

The results of this study showed that KM and EI, mediated by JM and JF, had a positive and significant effect on developing the librarians’ productivity. The results also revealed that JF had a positive effect on JM and that JF was more effective on productivity than JM. This study marginally proved the direct effect of KM and EI on productivity where KM was more effective than EI on productivity. Knowing the effects of organizational and individual factors on the higher productivity of librarians in public libraries will help library managers make more efficient use of those factors in developing the capabilities of librarians and enhancing productivity.

This study is one of the few studies of its kind that facilitates the perception of the concept of productivity in public libraries and also the assessment of the effects of organizational and individual factors on the librarians’ productivity.

The occurrence and dissemination of hate videos in social media platform could pose serious harm to both society and individuals. However, the characteristics of the hate videos increase the difficulty of detection task. Hate content is usually presented in a relatively covert manner in videos, and textual content in videos plays an important role in hate video detection. In this work, we propose a textual context enhanced dynamic bimodal fusion (TCE-DBF) method for hate video detection.

The proposed method TCE-DBF introduces dynamic modality gate (DMG) and bimodal fusion transformer network to dynamically integrate multimodalities. Moreover, in order to enhance textual modality in videos, two types of textual context from the video are taken as the input of TCE-DBF. One is extracted from video frames in visual modality. The other is extracted from audio in acoustic modality. Specially, TCE-DBF splits the original audio and learns the sequence representation to capture acoustic temporal information.

Hate video detection has been one of the hotspots in recent works. However, it still faces two serious challenges. The first challenge is the hate content in videos presented in multimodalities. The second challenge is how to evaluate the importance of different modalities for multimodal fusion modeling. TCE-DBF aims to tackle these challenges. Experimental results on hate video dataset HateMM demonstrate that TCE-DBF outperforms the state-of-the-art methods, and the visualization results show that textual modality plays a more important role in hate video detection. Therefore, it is vital to consider the text in videos.

TCE-DBF can be utilized to effectively detect hate videos on social media. Besides transcript, TCE-DBF considers text in video frames, which makes detection more accurate. Meanwhile, to better achieve multimodal fusion, TCE-DBF uses DMG and bimodal fusion transformer network to dynamically assign different weights to three modalities and integrate them. The proposed TCE-DBF is novel in terms of capturing multimodal features, enhancing the textual modality and achieving high detection performance for hate video detection.