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This study aims to develop a synthetic knowledge repository consisted of interrelated Web Ontology Language.

The ontology composes the main framework to categorize data of product life cycle with eco-design mode (PLC-EDM) and automatically infer specialists’ knowledge for data confirmation, eventually assisting the utilizations and generation of strategies toward decision-making

(i) utilization of a novel model with ontology mode for information reuse cross the different eco-design applications; (ii) generation of a sound platform toward life cycle evaluation; and (iii) implementation of the PLC-EDM model along the product generation process.

It cannot substitute an evaluation tool of life cycle. Certainly, this model does not predict the “target and range” and/or the depiction of the “utility module” that are basic activities in life cycle assessments as characterized through the international organization for standardization regulations.

As portion of this framework, a prototype Web application is presented which is applied to produce, reuse and verify knowledge of product life cycle.

By counting upon the ontology, the information conducted by the utilization is certainly semantically represented to promote the data sharing among various participants and tools. Besides, the data can be verified against possible faults by inferring over the ontology. Hence, a feasible way to a popular topic in the domain of eco-design applications extension in the industry.

The goals are: to lean on rigid modeling principles; and to promote the interoperability and diffusion of the ontology toward particular utilization demands.

With new hybrid working models in place post COVID-19, it is requisite that knowledge workers (KWs) stay agile. Knowledge-oriented leadership (KOL) can help employees with essential knowledge acquisition (KA) facilitating the journey toward hybrid work agility (HWA). This study, thus, aims to explore the impact of KOL and KA on HWA and reveal whether this effect stems uniformly from a single homogenous population or if there is unobserved heterogeneity leading to identifiable segments of agile KWs.

Data was collected through stratified sampling from 416 employees from 20 information technology enabled services companies involved in knowledge-intensive tasks. Partial least squares (PLS) structural equation modeling approach, using SMART PLS 4.0, has been applied to examine the effect of KOL and KA on HWA. Finite mixture PLS, PLS prediction-oriented segmentation and multigroup analysis have been used to identify segments, test segment-specific path models and analyze the significance of the differences in the path coefficients for unobserved heterogeneity. Predictive relevance of the model has been determined using PLS Predict.

Results indicate that KOL contributes to employees’ KA and HWA. A significant positive relationship is also reported between KA and HWA. The model has medium predictive relevance. A two-segment solution has been delineated, wherein independent agile KWs (who value autonomy and personal agency over leadership for KA) and dependent agile KWs (who depend on leaders for relational and structural support for KA) have been identified. Thus, KOL and KA play a differential role in determining HWA.

The authors’ major contribution to the knowledge body constitutes the determination of antecedents of HWA and a typology of agile KWs. Future researchers may conduct segment-wise qualitative analysis to delineate other variables that contribute to HWA.

Technological advances necessitate that knowledge-intensive industries foster agility in employees for strategic agility of the organization. For effecting agile adaption of an organization to the knowledge economy conditions, it is pertinent that the full potential of this human resource be used. By profiling HWA of KWs on the basis of dimensions of KOL and the level of their KA, organizations will be able to help employees adapt better to rapidly changing work conditions.

HWA is a novel concept and very germane in a hybrid working environment. To the best of the authors’ knowledge, this is the first study to examine the effects of the dimensions of KOL and KA in relation to HWA, along with an empirical examination of unobserved heterogeneity in the aforementioned relationship.

The case is based on the data collected from various secondary sources only.

Godi India, a lithium-ion cell manufacturing company in India, was working to design e-cell for electric vehicles (EV) which would be compatible with Indian conditions and reduce the cost of battery to the extent possible because e-cell contributes half of the electric vehicle’s price. Godi India was set up in January 2020 by Mahesh Godi. Looking for opportunities in India after having worked in the USA for 17 years, Mahesh found that even with the rise in EV the lithium-ion cell manufacturing in India was almost zero. Using innovation as its main strategy, the start-up started its operation with a team of 30 scientists. The start-up already registered 25 patents under its name with few awaiting. Most of the EV companies relied on Chinese lithium-ion cell. Local lithium-ion cell manufacturing was believed to be the key for EV industry growth in a country. Central government production linked schemes worth INR 18,100 crore were signed by major players like Ola electric, Reliance new energy and Rajesh exports to develop locally manufactured advance cells. The push from the government for locally manufacturing the cells was a major trigger for the rise in the EV industry. The case provides the analysis of the strategies applied by the company to grow in the lithium-ion cell manufacturing industry.

This case can be used in strategic management, entrepreneurship and general management courses/modules at the Undergraduate and Postgraduate level.