Search results

The study has identified the factors among students that can enable or inhibit students from using online learning platforms. Students enrolled at different levels, diversified streams and separate courses were surveyed for the investigation. The study also highlights the significant hitches faced in using or adopting e-learning.

Responses were collected from Indian students on a seven-point Likert-type scale using a structured questionnaire around the updated Technology Readiness Index's four dimensions. Adapted dimensions were evolved to identify the people's propensity to accept and reject the new technology.

The result of the survey highlights the students' positive attitude towards the e-learning approach. The diffusion of e-learning platforms occupies them with a feeling of optimism and innovativeness. However, discomfort in using the newly penetrated e-learning platforms was also found. Furthermore, no significant variances concerning the different demographics were detected.

The cross-sectional research approach was used for the investigation. However, it is evident that with the use and experience of technology, an increase in its acceptance follows. Thus, a longitudinal research approach should explore the differences between students' earlier and later involvement after experiencing the platform. A cross-country investigation is also needed to measure the technological biases among students.

With advancements in technology, the chances of diffusion of e-learning in traditional classrooms have risen. However, to encourage the student's engagement towards e-learning, the platform needs to be student and teacher-friendly. This study serves the purpose of exploring the determinants that will guide educational institutes and developers of online platforms in achieving excellence in enhancement and engagement among students.

The investigation adds to recognize the acceptance of e-learning among students by exploring its determinants using the Technology Readiness Index 2.0. The study has also explored the differences in readiness to use e-learning on differences in enrolment level, institute type and courses.

Forecasting product returns plays an important role in the operations of reverse logistics (RL). However, their contribution to sustainability performance is yet to be explored. The purpose of this paper is to explore the product returns in Indian electronics industry and examine the relationship of forecasting product returns with triple bottom line performance of RL.

In this study, based on past literature review, four hypotheses, relating to forecasting of product returns and its association with performance, were developed. A questionnaire was sent to 700 respondents from the Indian electronics industry. Overall, 208 received responses were found suitable for the research. The necessary statistical analysis was carried out to ensure the reliability and validity of the questionnaire. In order to test different hypotheses, partial least square path modelling (PLSPM) technique of structural equation modeling was utilized.

Measurement model had shown sufficient data fit for the modeling. PLSPM results reveal that the accuracy in forecasting product returns is positively associated with operational performance of RL. It also plays an important role in the sustainability efforts of an organization.

Managers can utilize results of study for exploring and emphasizing issues of product returns for improving RL performance. One of the limitations is that data are collected only from Indian electronics industry. Another limitation is that only product returns are considered for the operational and TBL performance of RL. In future, study may be carried out considering different factors in other sectors and countries.

The intent of forecasting product returns is considered to be operational efficiency. It can make significant contributions to the sustainability efforts of an organization. Review of the past literature indicates that research in the field of RL is in developing stage, and issues related to forecasting product returns are under-represented. The paper adds value to the few available articles on product returns.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

The paper aims to incorporate the relationship of reverse logistics into the economic, environmental, and social sustainability, known as triple bottom line and developed a framework for reverse logistics performance evaluation.

The performance measures, based on triple bottom line approach, were selected, and fuzzy analytical hierarchy process and extent analysis approach was applied for estimating the weights, global weights of performance measures and hence, the reverse logistics performance index. Reverse logistics performance of three electronic companies were evaluated and compared for the demonstration of the methodology.

The results show that economic performance has highest performance index followed by environmental performance and social performance. “Recapturing value” and “return on investment” from economic, “minimum energy consumption” and “optimum use of raw material” from environmental and “community complaints” and “customer health and safety” from social perspective have higher performance indexes. Over all, “reduced packaging”, “use of recycled material” and “employee benefits” show very poor performance indexes.

The study will provide useful guidance to the academicians and practitioners for evaluating, improving and benchmarking the reverse logistics performance.

The analysis adds to the very few studies on triple bottom line aspects of reverse logistics and its performance evaluation. Also, fuzzy analytical hierarchy process and extent analysis is used first time being an efficient tool to tackle the fuzziness of the data involved in performance evaluation.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

There are a lack of recourses for substance abuse (SA) treatment for forensic clients with intellectual disabilities (ID). Many complexities arise when treating this population, calling for the creation of comprehensive resources which not only address the SA, but also account for the risk and offending issues. The purpose of this paper is to detail a pilot programme which aims to provide treatment for forensic ID clients with substance abuse issues as well as a significant risk of reoffending.

Six participants completed a 27-week SA treatment programme (the Alcohol and Substance Abuse Programme-Intellectual Disability) which incorporated the use of dialectical behavioural therapy (DBT) and the Good Lives Model concepts. Pre- and post-measures aimed to assess readiness for change and confidence in ability to stay clean and sober.

Preliminary findings showed a marked improvement in confidence of the participants’ ability to stay clean and sober in risk-related situations as well as an increase in overall readiness for change.

This research paper addresses a gap in the current forensic ID research and clinical treatment options pertaining to SA, by focussing on supporting forensic ID clients in their recovery journey from SA. Being at the forefront of SA treatment for forensic ID, further research in this domain should attempt to consolidate the findings of this programme.

The purpose of this paper is to measure the impact of financial inclusion on rural development through cooperatives.

The primary data were collected from 540 beneficiaries of Cooperatives banks operating in three northern states of India, i.e., J&K, Himachal Pradesh and Punjab using purposive sampling during January to June 2016. Exploratory factor analysis, confirmatory factor analysis, ANOVA, t-test and structural equation modelling were used for scale purification and data analysis.

The findings of the study revealed that financial inclusion through cooperatives has direct and significant impact on rural development. Further, the results support the notion that financial inclusion is a strategy of inclusive growth, but inclusive growth itself is a subset of a larger set of inclusive development which means that the benefit must reach the all, particularly the women and the children, minority groups, the extremely poor and those pushed below the poverty line by natural and human-made disasters.

The research has certain inescapable limitations. First, the in-depth analysis of the study is restricted to three northern states of India only because of time and resource constraints. Second, the study is confined to the perception of financial inclusion beneficiaries only, which in future could be carried further on the perception of other stakeholders such as SHGs, banking correspondents, etc. Third, possibility of subjective interpretation in some cases cannot be ruled out.

The study makes contribution towards financial inclusion literature relating to sustainable rural development and fulfils the research gap to some extent by assessing the impact of financial inclusion on rural development through cooperatives.

Under the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.

This paper uses the Stackelberg game theory to obtain the optimal wholesale prices, retail prices, sales quantities and carbon emissions in different cases, and investigates the effect of the carbon tax policy.

This study’s main results are as follows: (1) the optimal retail price of the centralized supply chain is the lowest, while that of the decentralized supply chain where the manufacturer undertakes the carbon emission reduction (CER) responsibility and the corporate social responsibility (CSR) is the highest under certain conditions. (2) The sales quantity when the retailer undertakes the CER responsibility and the CSR is the largest. (3) The supply chain obtains the highest profits when the retailer undertakes the CER responsibility and the CSR. (4) The environmental performance impact decreases with the carbon tax.

The results of this study can provide decision-making suggestions for low-carbon supply chains. Besides, this paper provides implications for the government to promote the low-carbon market.

Most of the existing studies only consider economic responsibility and social responsibility or only consider economic responsibility and environmental responsibility. This paper is the first study that examines the operational decisions of low-carbon supply chains with the triple bottom line under the carbon tax policy.

The purpose of this study is to explore how social entrepreneurship empowers women and how it influences the existing gender based intersectionalities in the society. This paper is based on a single case study of a social entrepreneurial startup called “Pahal,” which used social entrepreneurial strategies to encourage women to engage in economic activities, which helped them in gaining economic empowerment.

The researcher alongside the social entrepreneur visited the field for eight months from August 2016 to March 2017 and interviewed multiple stakeholder-employees (as partners) of the social enterprise. This study was done by conducting interviews with all the stakeholders in all the three social entrepreneurial phases, i.e. pre-Pahal, during-Pahal and after-Pahal. The interviews and observations were recorded and analysed using social entrepreneurial lens and intersectionality.

“Pahal Initiative” – is a social entrepreneurial intervention that helped the women in the household to start a food delivery business with the support of the social entrepreneur. Consequently, women gained confidence and self-respect. The attitude of men in the household changed when the women in the household generated additional income. It impacted their position and status which led to an increase in their participation in decision-making in the household and economic independence. The women become more interactive and expressive in a predominantly patriarchal household. Within one year, the entrepreneur had to stop the Pahal initiative. Then, this study observed and recorded that this event curtailed the economic activities undertaken by the women in their village and their social status reverted to what it was before the initiative.

First, social entrepreneurial strategies lead to economic value creation and lead overall socio-economic gains. Second, social entrepreneurial strategies address the problems of patriarchy and gender discrimination. Third, economic activities undertaken by women changed the social perceptions of the family members towards women in the families.

From this case study, one observes that social entrepreneurship has a strong potential to bring about social and economic change. This study helps policymakers and non-governmental organisations to solve poverty and gender discrimination related problems using social entrepreneurial strategies.

This study uses social entrepreneurial intervention to understand and bring about change in the socio-economic status of women in rural India. This study uses an intersectionality lens to make sense of the data, reality and reflects on how intersectional positions are altered when women are economically empowered either through training or through a proper organisation or both.

Industries have been the most significant contributor to carbon emissions since the beginning of the Industrial Revolution. The transition to Industry 5.0 (I5.0) marks a pivotal moment in the industrial revolution, which aims to reconcile productivity with environmental responsibility. As concerns about the decline of environmental quality increase and the demand for sustainable industrial methods intensifies, experts recognize the shift toward the I5.0 transition as a crucial turning point.

This review study explores the convergence of green technological advancements with the evolving landscape of I5.0, thereby presenting a roadmap toward carbon neutrality. Through an extensive analysis of literature spanning from 2012 to 2024, sourced from the Scopus database, the research study unravels the transformative potential of green technological innovations, artificial intelligence, green supply chain management and the metaverse.

The findings underscore the urgent imperative of integrating green technologies into the fabric of I5.0, highlighting the opportunities and challenges inherent in this endeavor. Furthermore, the study provides insights tailored for policymakers, regulators, researchers and environmental stakeholders, fostering informed decision-making toward a carbon-neutral future.

This review serves as a call to action, urging collective efforts to harness innovation for the betterment of industry and the environment.