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An undergraduate civil engineering programme is assessed for its relevance to the building construction sector. Its contrast from the existing curriculum structure is also highlighted.

The curriculum is clustered into 15 groups based on disciplines. A pairwise comparison of groups is conducted by experts from the building construction sector. Expert judgements are analysed using Fuzzy Analytical Hierarchy Process (Fuzzy AHP) to determine the groups' order based on their importance in preparing students for a career in the building construction sector.

Concrete Technology, Structural Design and Analysis, and Building Technology and Town Planning emerged as the three most essential course groups, followed by Construction and Project Management, Surveying, and Geotechnical and Allied. Foundational Science and Math, Hydrology/Water Resource Engineering, and Computing and Programming came last in the order.

Relying on a curriculum from a specific region, generalizability to other geographical areas is limited. The perspective of building construction sector professionals excludes the views of other stakeholder groups within the sector.

The study allows universities in general to enhance students' job prospects in construction by calibrating course group priorities and aligning skills with industry needs, thereby potentially improving employability, and boosting the industry-academia relationship.

Fuzzy AHP has been utilized by building construction industry experts to assess the relevance of an undergraduate civil engineering curriculum. Findings serve as a valuable reference for implementing positive curriculum changes to potentially enhance student employability.

This paper aims to enlighten stakeholders about critical success factors (CSFs) in developing intelligent autonomous systems (IASs) by integrating artificial intelligence (AI) with robotics. It suggests a prioritization hierarchy model for building sustainable ecosystem for developing IASs.

This paper is based on the existing literature and on the opinion of 15 experts. All the experts have minimum of eight years of experience in AI and related technologies. The CSF theory is used as a theoretical lens and total interpretative structure modelling (TISM) is used for the prioritization of CSFs.

Developing countries like India could leverage IASs and associated technologies for solving different societal problems. Policymakers need to develop basic policies regarding data collection, standardized hardware, skilled manpower, funding and start-up culture that can act as building blocks in undertaking sustainable ecosystem for developing IASs and implementing national AI strategy. Clear-cut regulations need to be in place for the proper functioning of the ecosystem. Any technology that can function properly in India has better chances of working at the global level considering the size of the population.

This paper had all its experts from India only, and that makes the limitation of this paper, as there is a possibility that some of the factors identified may not hold same significance in other countries.

Stakeholders will understand the critical factors that are important in developing sustainable ecosystem for IASs and what should be the possible order of activities corresponding to each CSF.

The paper is the first of its kind that has used the CSF theory and TISM methodology for the identification and prioritization of CSFs in developing IASs. Further, eight significant factors, that is, emerging economy multinational enterprises (EMNEs), governance, utility, manpower, capital, software, data and hardware, have come up as the most important factors in integrating AI with robotics in India.

This study aims to introduce students to uncontrolled and unprecedented business scenarios and strategies to deal with them, to make students understand the importance of contingency planning and create what-if scenarios, to step by step guide students how to build a network contingency planning tool and to enable students to use tools such as solver to build up a dashboard with given information.

The case is about Godrej Commercial, a vertical of Godrej and Boyce that handles warehousing and transportation support to five verticals under the banner of Godrej operating pan India. How Godrej is trying to deal with COVID pandemic, what were their coping strategies and how contingency planning is done is what this case is all about. The main focus of this case is understanding how network contingency planning is done and what parameters should be considered. How a dashboard can be developed that can be used as a base for taking strategic decisions related to networking given the uncertainties due to COVID. The case gives hands on to students to use solver and build a dash board, plus gives a peep into Godrej and its operations.

This study is suitable for students of undergraduate or first year MBA level. Specifically, the case can be used in business strategies, operations and supply chain management courses.

Teaching notes are available for educators only.

CSS 9: Operations and Logistics.

This paper aims to provide a conceptual understanding of the drivers and outcomes of actor opportunism in the context of the three key actors of the sharing economy – the service provider, the platform and the consumer.

The research uses a conceptual approach by drawing on literature from within and outside of marketing.

The current research introduces a conceptual framework of opportunism in the sharing economy with seven underlying propositions. The framework posits a U-shaped moderating effect of social capital for the relationship between opportunism and its drivers, actor vulnerability and asset specificity. Furthermore, a 2 × 2 matrix consisting of two types of opportunistic behaviors (active and passive) and two coping strategies by other actors (defensive and nondefensive) suggests that passive opportunism tends to lead to value codestruction independently of the coping strategies employed by other actors. Counterintuitively, the combination of active opportunism and defensive coping strategy presents an opportunity for value cocreation due to its potential to break up older structures and generate new ones.

While our research provides a higher-level understanding of opportunism pertaining to platform, consumers and service providers in the sharing economy, future research could situate our framework within specific regulatory environments, incorporate the role of competitors and examine individual interaction effects between type of opportunism and coping strategies.

The framework enables service providers, platforms and consumers to identify drivers of opportunistic behaviors of their partners and discern instances in which opportunistic behaviors lead to value codestruction for all actors.

This research transcends prior work on the bright and dark sides of the sharing economy by identifying its dynamic nature and examining the contributing role of opportunism.

This research aims to identify and prioritize the circular economy (CE) benefits (CEBs) due to the adoption of CE enablers (CEEs) in the Indian manufacturing organization context.

This research proposes a hybrid framework of Pythagorean fuzzy analytic hierarchy process (PF-AHP) and Pythagorean fuzzy TODIM (an acronym in Portuguese for Interactive Multicriteria Decision-Making) techniques. It identifies the CEEs and CEBs based on literature review and validated through industrial experts. Further, this research conducts an empirical case study to demonstrate the applicability of the proposed framework.

The result shows that CE enabler SE1 (clear vision, support and commitment from top management for CE adoption) is the most critical enabler for CE implementation. The CE benefit CEB1 (improves the value chain of products and mitigating environmental damage during product life cycle phase) is the most significant benefit derived from the adoption of CEEs. The proposed framework will provide a more accurate, structural and systematic approach to the business organizations for achieving the CEBs in a stepwise manner through the effective adoption of CEEs.

The findings of this research are nation-specific and based on a case study of single manufacturing industry. Thus, the result obtained can vary from case to case and nation to nation.

A deep understanding of each CEEs and CEBs would help build confidence among decision-makers and industrial practitioners to eliminate the risks associated with CE implementation.

Individuals generate plenty of waste that is affecting the life while consumption of air and water at the base. The increasing industrialization, population and waste generation without proper measures of waste management are leading to major challenges to environmental sustainability. Considering these challenges, the present study focuses on the types and sources of waste generation and waste reduction by encouraging the reduction, recycling and reuse of waste products. The study aims to provide a well-functioning sustainable waste management system, that incorporates feedback loops, focuses on processes, embodies adaptability and diverts waste from disposal.

The university under study is situated at the central location of Pune City in India. The university has diverse units like academic and admin buildings, canteens and mess, hostels, a clinic, workshops and gardens. To fulfil the objective of this study a qualitative case study approach of research was adopted. A total of thirty-three representatives and waste management personnel from various units of the university were interviewed. The interviews were semi-structured and the duration of it was around 25–55 min. The interview transcripts were coded, and qualitative analysis was conducted.

This study proposes a strategic sustainable waste management model for environmental sustainability that brings circularity by closing the loops and focusing on sustainable development goals.

The findings of this research can guide universities to manage the waste generated through various sources and attain sustainable development goals and environmental sustainability at large by closing the loops. The study provides insights into waste management and environmental sustainability. The universities can make their resources more circular by following the strategies of reducing, reusing and recycling (3R). This study recommends customization according to the needs of specific universities and institutions. Researchers can take this study further by testing and customizing it as per requirement. Also, an effort can be extended to implement the model in other related areas.

This research is a unique attempt to advance knowledge of waste management practices for sustainable development by exploring different techniques opted by for individual entities from the university campus to understand the environmental impact.

In the process of industrial growth, when existing industries go for technology upgradation and new modernised industries emerge, both capital intensity and energy demand of overall industry tend to rise steadily. This poses a serious challenge for sustainable development objectives. Towards this end, enhancing energy efficiency of individual industries is the only remedy. Against this backdrop, the study aims to probe the trends in capital intensities and energy efficiencies of individual industries in India.

This study uses panel data regression analysis on data of two-digit industries from 1980/1981–2016/2017. The statistical analysis includes relevant macroeconomic variables derived from the literature to ascertain the drivers of energy efficiency in industries.

The results brought out that capital deepening due to technology upgradation and modernisation and capital productivity growth are the decisive determinants of energy efficiency growth. Furthermore, the ever-increasing fuel price motivated industries to conserve energy on a steady basis, supplemented by energy conservation-specific policy interventions.

This study recommends policy initiatives to ascertain and address technology gaps industry-wise, so that its subsequent efficient capital utilisation, and energy conservation measures of industries would result in energy efficiency growth in industry. The policy must focus on energy-efficient capital intensification in fabricated metals, leather, textile and wood industries that are found less-energy-efficient despite being less-capital-intensive.

This study empirically explores the capital efficiency of industries by investigating the interaction between capital intensity and energy efficiency at a two-digit industry level. It explores the determinants of energy efficiency and proposes industry-specific policies for energy-efficiency-enhancement of the overall industry.

Existing business model frameworks show weak conceptual unification, a paucity of measurement focus and limitations when applied in emerging economies. The study proposes a new business model framework – “Start-up Evaluation Calculus Using Research Evidence” (SECURE). The purpose of this study is to allow the measurement of the impact of business model design on start-up performance in emerging economies.

Data collected from 713 entrepreneurs in select cities of India, Oman and the United Arab Emirates is analyzed through structural equation modeling. The study uses measurement and structural models to examine the validity of measures and additionally tests the five hypothesized relationships proposed in the study.

The SECURE’s components comprising desirability, marketability, feasibility, scalability and viability showed validity and reliability. They synergistically demonstrated a statistically significant effect on a mix of financial and non-financial start-up performance outcomes. An alternative structural relationship that examined the impact of SECURE on only financial performance outcomes showed a weaker model fit. The findings indicate that a business model framework is useful when its ex ante measures show a positive causal effect on the desired performance outcomes.

The scores obtained by the SECURE framework serve as an evaluative tool that informs entrepreneurs and start-ups on the readiness of their proposed, incubated or existing start-ups.

Replacing subjective judgments with objective assessment criteria, SECURE is one of the first quantitative and performance-driven business model frameworks that contain measures from all functional domains of a start-up business. Start-ups can evaluate their business models against the SECURE model’s research-driven quantitative criteria and assess their impact on start-up performance.

This study reports the performance of thermally deteriorated concrete with and without fibres. Attempts have been made to find the suitable performance of steel polypropylene (PP) hybrid fibre combination that could significantly enhance the performance of mechanical properties at elevated temperatures.

In this experimental investigation, concrete cubes of 100 mm in size of various compositions were cast and water-cured for 28 days, and later exposed to elevated temperatures of either 200 or 400°C or 600 and or 800°C with a retention period of 2 h. The properties like change in colour and percentage weight loss were evaluated. Ultrasonic Pulse Velocity test was used to obtain qualitative information of strength variation. Residual strength of thermally deteriorated concrete specimen was measured by destructive testing.

Steel fibre volume fraction of 1 per cent improves the compressive strength of concrete in the temperature range of 400 to 800°C. The addition of steel fibre and PP fibre (Mix 3) improves the splitting strength of the concrete at elevated temperature range of 400 to 600°C.

Performance enhancement is observed with hybrid fibres for temperature endurance of concrete.