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Construction industry is one of the worst affected sectors due to the impact of the current coronavirus disease 2019 (COVID-19) outbreak. Therefore, the purpose of this study was to identify the key competencies that should be demonstrated by the contractors in the post-COVID-19 scenario to make them resilient to the adverse impact of pandemic outbreaks.

A survey instrument was developed using an extensive literature review and was tested using a pilot study. It was then administered online using survey monkey to 900 respondents, out of which 324 complete responses were obtained. The data analysis was performed using exploratory factor analysis and second-order confirmatory factor analysis.

After analyzing the data, it was identified that the most critical competence was managing site safety (standard factor loading (SFL) = 0.91), followed by leadership skills (SFL = 0.88), technical competence (SFL = 0.81), managing supply chain disruption (SFL = 0.73) and financial stability (SFL = 0.48) that were found to be less essential from the respondents’ point of view.

The study is first of its kind to identify the core competencies that should be demonstrated by the contractors to cope with COVID-19-induced disruptions. The findings of this article can be used by the practitioners to develop policies and procedures for selection of contractors.

Research on strategic procurement was mostly focussed on the clients' and main contractors' perspectives, while limited work had been done from a subcontractor's perspective. The paper hypothesises that “strategic capability” influences the latent constructs of power, dependence and collaboration in the main contractor–subcontractor relationship. Therefore, the purpose of this study is to investigate the influence of a subcontractor's strategic capabilities on power, dependence and collaboration.

A survey questionnaire was developed and distributed amongst the subcontractors in Australia, and 212 complete responses were received. Then second order confirmatory factor analysis and partial least square structure equation modelling (PLS-SEM) analysis were performed to test the hypothesised relationships.

The findings support “strategic capabilities” as a construct expressive of a subcontractor's unique market position and good business reputation. The findings also suggest that strategically capable subcontractors enhance their potential for forming partnerships with main contractors through dependence (StratC. → Dep., β = 0.84; Effect Size (ES) = 0.713; p < 0.01), collaboration (StratC. → Collab., β = 0.84; ES = 0.697; p < 0.01) and bargaining power (StratC. → Pow., β = 0.83; ES = 0.672; p < 0.01).

The study is one of its kind to explore the impact of a subcontractor's strategic capability on their bargaining power, dependability and ability to form collaborations. Furthermore, results indicate that the “strategic capabilities” of subcontractors can strongly influence their ability to create “dependence”, foster “collaboration” and exert “power” over a main contractor. The findings can help improve the strategic procurement decision-making processes of both subcontractors and main contractors to build better business relationships.

Electric vehicles are well known for a silent and smooth drive; however, their presence on the road is difficult to identify for road users who may be subjected to certain incidences. Although electric vehicles are free from exhaust emission gases, the wear particles coming out from disc brakes are still unresolved issues. Therefore, the purpose of the present paper is to introduce a smart eco-friendly braking system that uses signal processing and integrated technologies to eventually build a comprehensive driver assistance system.

The parameters obstacle identification, driver drowsiness, driver alcohol situation and heart rate were all taken into account. A contactless brake blending system has been designed while upgrading a rapid response. The implemented state flow rule-based decision strategy validated with the outcomes of a novel experimental setup.

The drowsiness state of drivers was successfully identified for the proposed control map and set up vindicated with the improvement in stopping time, atmospheric environment and increase in vehicle active safety regime.

The present study adopted a unique approach and obtained a brake blending system for improved braking performance as well as overall safety enhancement with rapid control of the vehicle.

Entrepreneurship, innovation, marketing and strategy.

Master’s, postgraduate and executive level programs.

The fashion industry has evolved over the generations. Fashion is what defines any person. Your style and quotient statement gives you an edge. In a world which is getting smaller and smaller with evolving mobile and computer technology connectivity, there has been a rise in new startups in personalized fashion. This sector of personal styling has seen an investment of over US$220m in the past two years. Social media is connecting billions of people around the globe. Roposo is the brand of Relevant E-solutions and was launched in 2012. It is the brainchild idea of Avinash Saxena, Kaushal Shubhank and Mayank Bhangadia. It has created a buzz in the fashion and social media industry. This case illustrates the connective power of social media and personalized fashion. Roposo has over 2 million active users which includes a number of Bollywood stars. These users are creating their own stories related to styling and fashion tips and inspiring millions worldwide. The case explores the journey of how Roposo has changed the style statement of millions of people.

The expected learning outcomes are as follows: to identify the new business opportunity in the fashion industry with the use of a social media platform; to understand the evolution of fashion with the boom in social media and mobile communications; to learn how the brand grows and how celebrities are also motivated to be a part of it to connect to their fans for free; to provide inspiration for students to start up an entrepreneurial venture; to find out how the use of recommendation engines should be done to keep users engaged; and to discuss threats of competitors.

Teaching Notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 3: Entrepreneurship.

Investment decisions hold immense significance for investors and eventually affect their portfolio performance. Investors are advised to weigh the costs and benefits associated with every decision in order to make rational investment decisions. However, behavioral finance research reveals that investors' choices often stem from a blend of economic, psychological and sociological factors, leading to irrationality. Moreover, environmental, social and corporate governance (ESG) factors, aligned with behavioral finance hypotheses, also sway opinions and stock prices. Hence, this study aims to identify how individual equity investors prioritize key determinants of investment decisions in the Indian stock market.

The current research gathered data from 391 individual equity investors through a structured questionnaire. Thereafter, a fuzzy analytic hierarchy process (F-AHP) was used to meet the purpose of the research.

Information availability, representative heuristics belonging to psychological factors and macroeconomic indicators falling under economic factors were discovered to be the three most prioritized criteria, whereas environmental issues within the realm of ESG factors, recommendations of brokers or investment consultants of sociological factors, and social issues belonging to ESG factors were found to be the least prioritized criteria, respectively.

Only active and experienced individual equity investors were surveyed in this study. Furthermore, with a sample size of 391 participants, the study was confined to individual equity investors in one nation, India.

This research has implications for individual investors, institutional investors, market regulators, corporations, financial advisors, portfolio managers, policymakers and society as a whole.

To the best of the authors' knowledge, no real attempt has been made to comprehend how active and experienced individual investors prioritize critical determinants of investment decisions by taking economic, psychological, sociological and ESG factors collectively under consideration.

The purpose of this paper is to focus on the technical know‐how required for digitisation of manuscripts. It aims to discuss the digitisation process of manuscripts adopted in the Jayakar Library, University of Pune in India and also to evaluate the digitisation software used in this project.

The paper explains different steps of the digitisation process. It also explains the process for creating metadata fields for easy retrieval of manuscripts and evaluates the digitisation software.

Digitisation of manuscripts is a difficult process because of the fragility and discolouration (yellowishness) of manuscripts. Creation of metadata and especially subject headings for manuscripts is difficult and time consuming. QuickScan software is good for image capturing and DSpace is good for providing access to digital contents.

The project details and use of different software in this project may be useful for others carrying out digitisation projects.

This paper aims to describe and evaluate JCCC@UGC‐INFONET and the document supply service at the University of Pune.

The approach takes the form of a brief overview of JCCC@UGC‐INFONET and the document supply service provided by the University library. Problems encountered while using the JCCC@UGC‐INFONET user interface and the administrative interface in providing ILL service are identified and some recommendations made.

The document supply service provided by Pune University library is satisfactory but the overall objective of INFLIBNET for starting this service is far from satisfactory. The JCCC@UGC‐INFONET database and software have some very good features but also some deficiencies that need to be rectified.

The paper provides details of the new service initiated by INFLIBNET and also evaluates the JCCC software from both the user's and the administrative point‐of‐view. These inputs will be useful for the development and improvement of both the service and the software.

As the global financial ecosystem grapples with the complexities of modernization, blockchain technology emerges as a pivotal catalyst, offering the banking, financial services, and insurance (BFSI) industry unprecedented opportunities for secured digital transformation and enhanced customer trust. To gain a comprehensive understanding of blockchain technology adoption, this study aims to identify the factors and establish the contextual interrelationships among them.

The authors have identified the factors affecting blockchain technology adoption in BFSI industry through extensive literature review and experts’ interviews. After identification of factors, contextual relationship has been established based on experts’ opinion and total interpretive structural modeling (TISM) approach. Furthermore, factors are categorized into autonomous, dependent, linkage and driving variables using cross-impact matrix multiplication applied to classification analysis.

The TISM-based structural model is divided into eight different hierarchal levels in which Government support is placed on the lower most layer (level 8) which indicates that this is the most crucial factor in blockchain adoption. Further social influence and security are placed on seventh and sixth level in the hierarchy.

The results of this study will help the policymakers to direct the resources from the most crucial factor to other factors in the hierarchy as per their relevance. In essence, this study serves as a guiding compass, steering the course of blockchain technology adoption in the BFSI sector toward a more secure and digitally transformed future.

In the current landscape, blockchain technology remains in its nascent stage, leaving ample room for exploration and innovation. This study stands as the pioneering effort to comprehensively identify and establish the contextual relationships among the adoption factors of blockchain technology within BFSI industry. Through rigorous TISM analysis, this paper enriches the existing body of knowledge on blockchain technology adoption.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

The purpose of this paper is to establish correlations among the input variables of production within themselves and input variables of consumption within themselves and to forecast the production and consumption of the rice.

The production and consumption of rice crop is governed by diverse variables. In the present study five key input variables for production of rice based on literature review and the authenticated data available from agricultural sources have been selected. These variables are area sown, agricultural workers (AW), area irrigated, growth rate and yield per hectare. On similar basis four key input variables responsible for consumption of rice are considered, namely, price of rice, population, poverty ratio and per capita net national product (NNP).

Correlation analysis showed that priority wise production of rice depends upon yield per hectare, percentage irrigation, AW and area sown. The growth rate is found to be having insignificant correlation with other variables of production and hence was omitted from subsequent study. Correlation analysis also showed that priority wise consumption depends upon whole sale price per ton, population and the per capita NNP. The poverty ratio is found to be having insignificant correlation with other variables of consumption and hence was omitted from subsequent study. The outcomes of the correlation analysis are utilized for designing rule base for fuzzy inference system (FIS) to forecast the production and consumption of the rice. Subsequently Bayesian technique is used to forecast production and consumption and its results are compared with the results of fuzzy inference analysis.

There are many techniques used for forecasting purpose but FIS and Bayesian technique outperform others. In the present study, the authors therefore focussed on these two techniques. Bayesian technique takes into account the expert opinion at the current conditions whereas FIS uses previously designed rule base. Besides discussing the appropriateness of these two techniques for forecasting production and consumption of rice, their forecasting outcomes will help in logistical and operational planning of the resources at national level, farmers’ level and traders’ level.