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The purpose of this paper is to find out the different types of business networks formed by firms with the stakeholders present in a cluster, i.e. how firms in a cluster interact with the cluster stakeholders?

To answer the research question, this study uses an exploratory research design, which is carried out in two stages, Stage 1 involves use of primary data, which was collected through semi-structured personal face-to-face interview mode and Stage 2 involves survey research method where data was collected through a survey questionnaire. Data for interviews and questionnaires were collected from managers and owners of firms operating in the cluster at their offices.

The study has identified four types of business networks between a firm and its buyers, only one type of business network with the suppliers and educational institutes, finally two types of business networks with government agencies and local associations. However, with respect to network with other stakeholders such as research institutes and competitors, the study shows that the interaction between a firm and these stakeholders is not strong i.e. the linkages between them remain largely unfilled.

The study has been limited to only one cluster thus it might not be appropriate to generalise the findings. Further research in this area needs to be done by taking other clusters to generalise the findings.

The study has tried to answer the research gap of lack of literature on types of business networks formed by firms with the stakeholders present in an industrial cluster, and thus, contributed to the existing literature of business networks. The identified business networks provide a much deeper understanding of how firms connect with its buyers, its suppliers, government agencies and educational institutes operating in an auto-component cluster.

The purpose of the present work is to improve the industry performance by identifying and quantifying the risks faced by the Indian pharmaceutical industry (IPI). The risk values for the prominent risks and overall industry are determined based on the four risk parameters, which would help determine the most contributive risks for mitigation.

An extensive literature survey was done to identify the risks, which were also validated by industry experts. The finalized risks were then evaluated using the fuzzy synthetic evaluation (FSE) method, which is the most suitable approach for the risk assessment with parameters having a set of different risk levels.

The three most contributive sub-risks are counterfeit drugs, demand fluctuations and loss of customers due to partners' poor service performance, while the main risks obtained are demand, financial and logistics. Also, the overall risk value indicates that the industry faces medium to high risk.

The study identifies the critical risks which need to be mitigated for an efficient industry. The industry is most vulnerable to the demand risk category. Therefore, the managers should minimize this risk by mitigating its sub-risks, like demand fluctuations, bullwhip effect, etc. Another critical sub-risk, the counterfeit risk, should be managed by adopting advanced technologies like blockchain, artificial intelligence, etc.

There is insufficient literature focusing on risk quantification. Therefore, this work addresses this gap and obtains the industry's most critical risks. It also discusses suitable mitigation strategies for better industry performance.

The purpose of this chapter is to analyze disaster exceptionalism in India, focusing on the case of Kosi river floods in the State of Bihar and their impact on Dalit communities. Data were gathered through document analysis and a qualitative approach based on interviews with national and local leaders and activists of NGOs and Dalit organizations. The main finding is that there are no second-generation social movements related to disasters in India, mainly in what concerns Dalit discrimination. The Disaster Management Act of 2005 reinforced the centralized and top-down nature of the Indian state concerning disasters. On the other hand, national Dalit organizations like National Confederation of Dalit and Adivasi Organisations (NACDAOR) and National Dalit Watch do not possess the expertise to alter the approach to disasters from a contingent and exceptional one to a more structured and long-term perspective.

The chapter shows how extreme events and permanent hazardous situations tend to increase the legitimacy of state intervention, often involving the suspension of social and economic norms, creating a state of exception, which indicates the inevitable presence of the state. The abyssal line that separates those individuals and groups that are integrated from those defined as disposable and invisible crosses through both the Global South and the little colonies of the North, reinforcing the logic of states that want to be bigger and stronger than their own citizens.

This paper proposes a new simultaneous optimization model of the industrial systems design and maintenance. This model aims to help the designer in searching for technical solutions and the product architecture by integrating the maintenance issues from the design stage. The goal is to reduce the life-cycle cost (LCC) of the studied system.

Literature indicates that the different approaches used in the design for maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and the maintainability of a multicomponent system as well as the modeling of the dynamic maintenance. This article proposes to go further in the optimization of the product, by simultaneously characterizing the design, in terms of reliability and maintainability, as well as the dynamic planning of the maintenance operations. This combinatorial characterization is performed by a two-level hybrid algorithm based on the genetic algorithms.

The proposed tool offers, depending on the life-cycle expectation, the desired availability, the desired business model (sales or rental), simulations in terms of the LCCs, and so an optimal product architecture.

In this article, the term “design” is limited to reliability properties, possible redundancies, component accessibility (maintainability), and levels of monitoring information.

This work is distinguished by the use of a hybrid optimization algorithm (two-level computation) using genetic algorithms. The first level is to identify an optimal design configuration that takes into account the LCC criterion. The second level consists in proposing a dynamic and optimal maintenance plan based on the maintenance-free operating period (MFOP) concept that takes into account certain criteria, such as replacement costs or the reliability of the system.

Crops are increasingly affected by drought; hence, the current study explored the potential role of three desert endophytic fungi, Aspergillus fumigatus, Aspergillus terreus and Talaromyces variabilis, in conferring drought tolerance in tomato plants.

Preserved endophytic fungi from a Rhazya stricta desert plant were adopted to obtain the required fungal treatment; tomatoes received fungal treatments directly in plastic trays and subsequently in pots. Drought was applied using 15% of PEG-6000 at two stages: flowering and fruiting. The following parameters were measured: pollen sterility, growth characteristics, morphological analysis and biochemical analysis, including proline, gibberellic acid (GA3) and chlorophyll measurements; thus, the data were analyzed statistically using SPSS software.

All applied endophytes significantly promoted pollen viability and tomato yield under stressed and nonstressed conditions. Interestingly, these endophytes significantly enhanced the number of trichomes under drought stress and promoted tomato fruit quality. The colonized tomato plants accumulated a high proline level under drought stress but lower than un-inoculated stressed plants. Also, a significant rise in growth characteristics was observed by A. fumigatus and A. terreus under normal conditions. Moreover, both raised GA3 levels under drought-stressed and nonstressed conditions. Also these two endophytes enhanced chlorophyll and carotenoid contents under drought stress. Fruit characteristics were enhanced by nonstressed T. variabilis and stressed A. fumigatus.

The present endophytic fungi provide impressive benefits to their host in normal and drought-stressed conditions. Consequently, they represent valuable sources as sustainable and environmentally friendly alternatives to mitigate drought stress.

In the final step, the trust model is applied to the on-demand federated multipath distance vector routing protocol (AOMDV) to introduce path trust as a foundation for routing selection in the route discovery phase, construct a trusted path, and implement a path warning mechanism to detect malicious nodes in the route maintenance phase, respectively.

A trust-based on-demand multipath distance vector routing protocol is being developed to address the problem of flying ad-hoc network being subjected to internal attacks and experiencing frequent connection interruptions. Following the construction of the node trust assessment model and the presentation of trust evaluation criteria, the data packet forwarding rate, trusted interaction degree and detection packet receipt rate are discussed. In the next step, the direct trust degree of the adaptive fuzzy trust aggregation network compute node is constructed. After then, rely on the indirect trust degree of neighbouring nodes to calculate the trust degree of the node in the network. Design a trust fluctuation penalty mechanism, as a second step, to defend against the switch attack in the trust model.

When compared to the lightweight trust-enhanced routing protocol (TEAOMDV), it significantly improves the data packet delivery rate and throughput of the network significantly.

Additionally, it reduces the amount of routing overhead and the average end-to-end delay.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

This research focuses on suggesting an optimized model for selecting best employees using advanced multi-criteria decision making method to a supply chain firm, who is planning to start a new cold chain business vertical.

Study has been conducted in a supply chain firm in North India, who wants to expand its business with the help of efficient team members. In total 38 applicants were considered for the study, as selected by the firm after initial screening from pool of talent. AHP-LP and TOPSIS-LP integrated approach were applied separately for evaluation and implementation of personnel selection model. Further, both the approaches were compared to find the best fit and optimized model.

As per the findings, both AHP and TOPSIS can be used to select the best candidate among the alternatives available. TOPSIS was found easier to implement as it involves ranking of applicants with respect to each skills required for respective job profile only once, whereas AHP involves pair-wise comparison among candidates with respect to each skills required for respective job profile and normalization of each comparison, resulting in the formation of number of comparison matrices. However, AHP is more reliable as it considers consistency check for each level of pair-wise comparison. Hence, there is a chance to avoid or revise the human judgment error. Integrated ranking and optimization approach minimizes the cost by suggesting the relevant positions to be filed to make an efficient team.

Group of interviewers are involved in the decision-making process, hence there are chances of biasness in ranking method which can influence the group decision. Research is limited to a particular geography of North India therefore needs to be tested for other regions also in order to generalize. The research will help the third party logistics (3PL) and other related firms in efficient team selection.

The researcher focuses on formalizing a method for potential candidate selection by considering the constraints of the organization. It has been observed that limited researches have been done on the application of AHP-LP or TOPSIS-LP integrated approach for selection process. Hence, this research proposes two integrated ranking-optimization method and suggests the best fit by comparing both the approaches.

This study aims to identify how ICT appeared as an emergent business strategy and to investigate the impact of ICT adoption factors on the perceived benefits of micro, small and medium enterprises (MSMEs).

A total of 393 responses from Indian small and mid-size enterprises (SMEs) were collected for the final analysis. The study presents the partial least-squares structural equation modeling with the Chi-square test and descriptive analysis as a methodology based on numerous independent variables and one dependent variable.

The findings indicate that ICT adoption during and following the COVID-19 pandemic is constant in nature of the enterprise. Moreover, the results indicate that different adoption of ICT factors influence on perceived benefits of organizational performance of Indian MSMEs that lent good support except for the regulatory framework.

The implications of the current research help Indian MSMEs to take investment decisions in various technologies that help the organization. Furthermore, managers and practitioners help the organization in deciding which technology adoption factors are more critical to the betterment of the organization.

The study found certain ICT adoption factors that have a significant role in organizational performance in Indian MSMEs. Moreover, during COVID-19, investigate ICTs' role as a business strategy.

The purpose of this paper is to demonstrate the acceptable performance by using the limited input range towards lower open-loop DC gain operational amplifier (op-amp) of an 8-bit pipelined analog-to-digital converter (ADC) for mobile communication application.

An op-amp with folded cascode configuration is designed to provide the maximum open-loop DC gain without any gain-boosting technique. The impact of low open-loop DC gain is observed and analysed through the results of pre-, post-layout simulations and measurement of the ADC. The fabrication process technology used is Silterra 0.18-µm CMOS process. The silicon area by the ADC is 1.08 mm².

Measured results show the differential non-linearity (DNL) error, integral non-linearity (INL) error, signal-to-noise ratio (SNR) and spurious-free dynamic range (SFDR) are within −0.2 to +0.2 LSB, −0.55 LSB for 0.4 Vpp input range, 22 and 27 dB, respectively, with 2 MHz input signal at the rate of 64 MS/s. The static power consumption is 40 mW with a supply voltage of 1.8 V.

The experimental results of ADC showed that by limiting the input range to ±0.2 V, this ADC is able to give a good reasonable performance. Open-loop DC gain of op-amp plays a critical role in ADC performance. Low open-loop DC gain results in stage-gain error of residue amplifier and, thus, leads to nonlinearity of output code. Nevertheless, lowering the input range enhances the linearity to ±0.2 LSB.