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This study aims to examine the effectiveness of the Central Board of Secondary Education (CBSE)-based English textbooks and question papers in developing second-language higher-order thinking skills (HOTS).

Descriptive analysis establishes a causal relationship between learning objectives and second language (L2) writing proficiency. Content analysis is used to compare and analyze tabulated data for textbooks and question papers for the English language by the National Council of Educational Research and Training (NCERT) and CBSE. This method categorizes the materials and their assessments under HOTS and lower-order thinking skills to ascertain the relationship between learning objectives and L2 writing proficiency.

The study highlights teaching material and assessment shortcomings and their alignment with learning outcomes to enhance students' writing skills. It underscores the need for HOTS-focused materials, discussing their impact on writing skills. The study also explores how textbook–question paper mismatch hampers Bloom's taxonomy-based cognitive skills.

This research illuminates the efficacy of teaching and learning English as a second language (ESL) writing skills to improve the quality of education, which has real-world implications. The study highlights flaws in the educational system in India and suggests curricular and pedagogical changes.

The research examines NCERT and CBSE ESL textbooks and question papers to align teaching and assessment methods. The results aim to improve education through ESL writers' HOTS.

The decision-making to outsource and select the most suitable global manufacturing outsourcing partner (MOP) is complex and uncertain due to multiple conflicting qualitative and quantitative criteria as well as multiple alternatives. Vagueness and variability exist in ratings of criteria and alternatives by group of decision-makers (DMs). The paper provides a novel Stochastic Fuzzy (SF) method for evaluation and selection of agile and sustainable global MOP in uncertain and volatile business environment.

Four main selection criteria for global MOP selection were identified such as economic, agile, environmental and social criteria. Total 16 sub-criteria were selected. To consider the vagueness and variability in ratings by group of DMs, SF method using t-distribution or z-distribution was adopted. The criteria weights were determined using the Stochastic Fuzzy-CRiteria Importance Through Intercriteria Correlation (SF-CRITIC), while MOP selection was carried out using Stochastic Fuzzy-VIseKriterijumskaOptimizacija I KompromisnoResenje (SF-VIKOR) in the case study of footwear industry. Sensitivity analysis was performed to test the robustness of the proposed model. A comparative analysis of SF-VIKOR and VIKOR was made.

The worker’s wages and welfare, product price, product quality, green manufacturing process and collaboration with partners are the most important criteria for MOP selection. The MOP3 was found to be the best agile and sustainable global MOP for the footwear company. In sensitivity analysis, significance level is found to have important role in MOP ranking. Hence, the study concluded that integrated SF-CRITIC and SF-VIKOR is an improved method for MOP selection problem.

In a group decision-making, ambiguity, impreciseness and variability are found in relative ratings. Fuzzy variant Multi-Criteria Decision-Making methods cover impreciseness in ratings but not the variability. On the other hand, deterministic models do not cover either. Hence, the stochastic method based on the probability theory combining fuzzy theory is proposed to deal with decision-making problems in imprecise and uncertain environments. Most notably, the proposed model has novelty as it captures and reveals both the stochastic perspective and the fuzziness perspective in rating by group of DMs.

The proposed multi-criteria group decision-making model contributes to the sustainable and agile footwear supply chain management and will help the policymakers in selecting the best global MOP.

To the best of the authors’ knowledge, SF method has not been used to select MOP in the existing literature. For the first time, integrated SF-CRITIC and SF-VIKOR method were applied to select the best agile and sustainable MOP under uncertainty. Unlike other studies, this study considered agile criteria along with triple bottom line sustainable criteria for MOP selection. The novel method of SF assessment contributes to the literature and put forward the managerial implication for improving agility and sustainability of global manufacturing outsourcing in footwear industry.

System dynamics has several applications in the built environment, and few studies indicate that it has potential in evaluating sustainability. Sustainability in the built environment involves numerous entities and multiple trade-offs. Hence, a Multi-Criteria Decision-Making (MCDM) method is ideal for promoting sustainability-based decision-making in the built environment. Therefore, this study integrates system dynamics with an MCDM method to enable the sustainability assessment by capturing the time-induced dynamic changes affecting long time sustainability performance of buildings.

Conventional sustainability assessment tools in the built environment lack a comprehensive evaluation that balances the needs of the society, economy and environment. This study develops a system dynamics-based framework to enable sustainability-conscious decision-making and policy analysis in the built environment.

Various material, technology and water-related policies specific to the buildings are investigated for a case study building. It is found that the effect of penetration of renewable energy technology to the tune of 80% and above in the energy mix is a much superior policy in sustainability improvement in comparison to material and water-related policies. The study also demonstrates the effect of weights assigned for the different indicators on sustainability-based decisions.

The study provides a methodological framework for a sustainability-based decision support system for the built environment that enables dynamic performance evaluation by coupling system dynamics with the MCDM. This coupling further strengthens system dynamics as a decision-making and policy analysis for sustainability evaluation in the built environment.

This paper aims to investigate the influence of picking sequence, weave design and weft yarn material on the thermal conductivity of the woven fabrics.

This work includes the development of 36 woven samples with two weave designs (1/1 plain and 3/1 twill), three picking sequences (single, double and three pick insertion) and six different weft yarn materials (cotton, polyester having 48 filaments, polyester with 144 filaments, spun coolmax having Lycra in core and coolmax in sheath, filament coolmax and polypropylene). The thermal conductivity was measured using ALAMBETA tester.

The results showed that weft yarn material, weave design and picking sequence have a meaningful impact on the thermal conductivity of woven fabric. The value of thermal conductivity was lowest for the fabrics with three pick insertion and 3/1 twill weave in all weft yarn materials.

Plain woven fabric with single pick insertion is feasible for summer wear to enhance the comfort of wearer. By changing the warp yarn grouping and material, improved thermal conductivity/resistance can also be achieved.

The authors have studied the combined effect of different weft yarn materials with different picking sequences and different weave designs on thermal conductivity of the woven fabrics.

The regular occurrence of natural disasters elevates the need for an effective method to measure organizational preparedness in responding to the adverse impact of disasters. In this context, this paper presents a new decision support model to assess organizational disaster preparedness using both subjective and objective disaster preparedness criteria in a multi-criteria decision-making context.

The statistical variance method is integrated with the proximity value index (PVI) technique to determine priority scores in order to rank organizational disaster readiness.

The results of applying the integrated model developed herein enable decision-makers to make informed decisions for assigning priority ranking of organizational disaster preparedness in a simpler and more efficient way.

Human resource is the most impacting criterion affecting hospital preparedness in undertaking action to cure disaster victims.

This paper offers an exemplar of a simple and efficient decision-making process considering the subjectivity associated with decision-making as well as the objectivity of data used for determining the priority ranking of organizational disaster preparedness.

Integrating statistical variance method with the PVI technique is novel and it has not been presented in previous studies. In fact, this study is the first to integrate both methods for selecting the priority ranking of organizational disaster preparedness.

This study aims to unravel the role of teams’ job crafting in translating responsible leadership into their customer relationship performance.

The data were gathered from 87 managers and 608 employees from tour companies. The data analysis was performed via multilevel structural equation modeling.

The results demonstrated that crafting of team tasks played a mediating role for the link of responsible leadership to the team’s customer relationship performance. Task interdependence, outcome interdependence and their interaction attenuated the influence of responsible leadership on collective job crafting.

The results suggest that tourism managers can enhance customer relationship performance of their team through training and development of responsible leadership, encouraging team members’ crafting of team tasks, as well as enhancing outcome and task interdependence.

This research expands the literature by identifying how and when responsible leadership promotes team customer relationship performance in tourism companies.

This research intends to analyse the trend in educational technology (EdTech) over the last 20 years using systematic scientific mapping and bibliometric analysis and how it relates to the Indian context. Considering the anticipated growth in this field over the previous three years post-pandemic, an existing literature analysis is required. This study aims to map the existing intellectual structure in EdTech applications to extend the knowledge base further in this field. This study also intends to research how the Indian education sector compares in terms of the research output for the EdTech sector, considering the increased government focus on online learning as per the education policy in 2020. The study's findings will pave the way for sustainable research that will be extended in the future.

Bibliometric analysis is conducted on the manuscripts extracted from Web of Science databases for the last 20 years (from 2003 to 2023). This study uses a descriptive research approach for bibliometric analysis as, by nature, this is an exploratory investigation, and no physical or existing experiment can be performed on the quantification, characteristic or productivity of EdTech applications. VoS Viewer and R software are extensively considered for a detailed bibliometric analysis.

E-learning, blended learning and distance education emerged as the most frequently used keywords. The results reveal that technology adoption, higher education, technology and modelling are the most researched topics in this field.

This research is limited to the last 20 years' database obtained from the Web of Science database and limited to educational, management and operation databases only.

The paper intends to analyse the global scenario of EdTech research and ensures that the paper will effectively connect with researchers, educators, policymakers and practitioners from different parts of the world. The results derived from the bibliometric analysis, cluster analysis and identification of key authors, journals and countries can contribute towards the improved contribution in this area.

The paper discusses the research in EdTech over the last two decades and effectively tries to bridge the gap in global research. Integrating systematic scientific mapping and bibliometric analysis is an innovative way to assess the growth and impact of EdTech. Considering the post-pandemic scenario and the government's emphasis on online learning, these are consistent with current developments.

This paper aims to develop bilayer woven fabrics with different picking sequences with enhanced comfort without any change in the constituent materials.

Six bilayer woven fabrics were produced on Dobby loom with 3/1 twill weave using micro-polyester yarn. Three different picking sequences, i.e. single pick insertion (SPI), double pick insertion (DPI) and three pick insertion (3PI), were used in both face and back layers. The effect of picking sequence on air permeability (AP), volume porosity, thermal resistance and overall moisture management capability (OMMC) of the samples were analyzed.

The results showed that 3PI–3PI picking sequence gives the highest OMMC, AP and thermal resistance in bilayer woven fabrics and the least results exhibited by SPI–SPI picking sequence.

This research uses a bilayer woven system that develops channels and trapes the air causing higher thermal resistance; therefore, applicable for winter sports clothing rather than for summer wear. Developed bilayer woven fabrics can be used in winter sportswear to improve the comfort of the wearer and reduce fatigue during activity.

Authors have developed bilayer fabrics by changing the picking sequences, i.e. SPI, DPI and 3PI of weft yarns in both layers and compared their thermo-physiological comfort properties.

The Internet is used as a tool to seek health information by individuals. Mental health concerns are the high prevalence of the novel coronavirus disease 2019 (COVID-19) and preventive steps are required to curb the illness. Therefore, to gain more insight into health concerns, it is now a common practice to seek health information on the Internet. This study propose an integrated theoretical model to explore the relationship between COVID-19 protocols and perceived online trust with online health information seeking intention (OHISI) and a moderating effect of perceived severity and perceived urgency.

Data are collected from 325 athletes in the category of individual and team sports through an online survey in a Likert-scale questionnaire. The analysis is performed with a quantitative methodology.

The study reveals the bright side of online health information (OHI), which brings athletes together and has played out with virtual happy hours, meetings and events. The bright side of OHI reflects social, cultural, technological and economic benefits. An OHI chatbot offers bright personalised side information to the individual seeker, which is more convenient and efficient than human capabilities.

The pivotal contribution is the integrated theoretical framework that is derived from multidisciplinary literature to capture the complexity of OHI. Also, it conceptualises the constructs in the context of OHI and COVID-19.

The British East India Company (EIC) made connections between the Malay Archipelago and Bengal and established a penal settlement at Bencoolen, followed by the Straits Settlements for the Indian convicts. The convicts from different parts of South Asia today were generally described as “Indian”, such generalisation often hides the identity of specific convicts from South Asia. Among the Indian convicts, the Bengalis were transported to Bencoolen and the Straits Settlements. However, the generic term has made it difficult to reconstruct the history of Bengali convicts’ experiences and pathos. Therefore, this paper attempts to “rediscover” the afterlife of transportation of Bengali felons in the Malay Peninsula.

By examining a range of archival records and current scholarships, this article shows the inclusivity, diversity and accessibility of convict labourers with mainstream society. This study will open up a new avenue of convict histories and subaltern studies on Asia.

The Bengali convicts in the Straits Settlements, one of the oldest migrant sections, have largely been ignored in historical literature. Though the Bengalis, among other South Asian convicts, constituted a significant portion, they were categorised under the generic term “Indian” (Rai, 2014). Their manual labour was invaluable for the colonial economy and the development of the Straits Settlements.

Researcher faced difficulties to get the descendant of Bengali convicts.

This article is a research paper based on mostly archival records; therefore, it is an original contribution to the existing knowledge on the convict history.