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Societal emergence and sustainability are results of human actions and practices which can either imbalance it with maximum exploitation or retain it through responsible utilization of resources. Based on theories on institutional and resource-based views, the study explores the enablers of green sustainable practices of procurement, logistics, product and process design and regulatory frameworks for low carbon performance .The study employs a Hybrid approach of step-by-step empirical process to examine the impact of sustainable practices on low carbon performance which further affects the sustainable manufacturing and societies. A theoretical model developed based on hypothesis is tested first using modified Dillman’s approach. Then it is tested in in the PLS-SEM package using 380 data responses collected from the various manufacturers. Further robustness of proposed model is validated using different ML (machine learning) followed by post hoc analysis using Item Response Theory to validate the scale and efficacy of the measurement model. The study validates the positive relationships of sustainable practices on the low carbon performance which eventually is responsible for sustainable societies. The area of sustainable manufacturing is found relatively lacking and requires further attention of leadership for better societal establishments. The study hopes to further enrich the literature with its unique Hybrid approach of SEM/PLS Machine Learning and IRT which is used to presents carbon performance as a central entity deriving from green practices and driving sustainable manufacturing and societies.

Novel coronavirus disease (COVID-19) and resulting lockdowns have contributed to major retail operational disturbances around the globe, forcing retail organizations to manage their operations effectively. The impact can be measured as a black swan event (BSE). Therefore, to understand its impact on retail operations and enhance operational performance, the study attempts to evaluate retail operations and develop a decision-making model for disruptive events in Morocco. The study develops a three-phase evaluation approach. The approach involves fuzzy logic (

As the business ecosystem is very becoming volatile with uncertainty accompanied with poor process centric practices leading to complexity and contributing to ambiguous decision making. Such a scenario constitutes a Volatile, Uncertain, Complex and Ambiguous world known as VUCA world. To manage the business in VUCA world, companies have started adopting emerging technologies such as Circular Economy (CE) and Internet of Things (IoT). These technologies combined with a proactive decision-making process promote Ethical Business Practices (EBP) that can lead a sustainable business operation in the market. Therefore, the present study assesses the impact of CE; IoT and EBP (CE-IoTEBP) in the food processing industry. Here, the factors that are influencing the company’s preference towards the CE-IoTEBP were analysed. Further to evaluate CE-IoTEBP, an evaluation model was developed. Using, Churchill approach, exhaustive list of factors (79 factors) relevant to the model were identified. Then, Ant colony optimisation was used to reduce the number of factors (39 factors) to make the model robust and apt for the evaluation of CE-IoTEBP. This was followed by using the Fuzzy ANN system for classifying the factors based on the level of contributions to assess the level of adoption intention of CE-IoTEBP in the industry. Through, fuzzy decoding (FANN) the final value for the CE-IoTEBP adoption intention was obtained. Additionally, this research proposes a deployment model for evaluating the CE-IoTEBP in the food processing industry to improve the low contributing factors. The use of Ant Colony Optimisation (ACO) method makes the decision making significantly robust and the ANN system improves its efficiency. The deployment model can be a reference for both academicians and practitioners to emulate in different industries.

Underwater wireless communication is a critical and challenging research area wherein acoustic signals are used to transfer data. The Underwater Wireless Sensor Network (UWSN) is used to transmit data sensed by the sensors in the sea bed to the surface sinks through intermediate nodes for seismic surveillance, border security and underwater environment monitoring applications. The nodes comprising of UWSN are battery operated and are subjected to failures leading to connectivity loss. And the propagation delay in sending the data in the form of acoustic signals is found to be high and as the depth increases the transmission delay also increases. Hence, routing in UWSN is a complex problem. The simulation experiments of the delay sensitive protocols are found to minimize the delay at the expense of network throughput which is not acceptable. The energy aware routing protocols on the other hand reduces energy consumption and routing overhead but has high delay involved in transmission. In this study, transmission delay and reliability estimation models are developed using which bi-objective routing model is proposed considering both delay and reliability in route selection. In the simulation studies, the bi-objective model reduced delay on an average by 9% and the reliability of the network is improved by 34% when compared to the delay sensitive and reliable routing strategies.

Routing in Mobile Ad-hoc NETwork (MANET) is a contemporary graph problem that is solved using various shortest path search techniques. The routing algorithms employed in modern routers use deterministic algorithms that extract an exact nondominated set of solutions from the search space. The search efficiency of these algorithms is found to have an exponential time complexity in the worst case. Moreover this problem is a multi-objective optimization problem in nature for MANET and it is required to consider changing topology layout. This study attempts to employ a formulation incorporating objectives viz., delay, hopdistance, load, cost and reliability that has significant impact on network performance. Simulation with different random topologies has been carried out to illustrate the implementation of an exhaustive search algorithm and it is observed that the algorithm could handle small-scale networks limited to 15 nodes. A random search meta-heuristic that adopts the nature of firefly swarm has been proposed for larger networks to yield an approximated non-dominated path set. Firefly Algorithm is found to perform better than the exact algorithm in terms of scalability and computational time.

The paper intends to analyse the impact of LSS in financial services through systematic literature review and identify current research gaps. It focuses more on exploring the different concepts in the area of financial services by performing a systematic literature review along with data visualisation techniques. The literature review of articles that are published in peer-reviewed scholarly journals from 1993 to 2017 was collected for performing the content analysis. Based, on the descriptive analysis performed on the collected materials, many results about the articles trend in the selected areas were found. Further, the content analysis revealed many research inferences like the role of e-banking, success factors, barriers in the context of LSS. Further, proposed work for future researchers in this field. The paper presents a systematic and unique application to detect the various opportunities for LSS in the financial domain.

In recent years, Mobile Ad-hoc NETwork (MANET), a flexible and rapidly deployable communication network is widely being used. The mobile nodes often create link changes that demand reconstruction of the already identified routes. The route discovery and the successive route maintenance is performed by the routing algorithm. In order to determine an efficient, robust and scalable routing in MANET, there is a need to develop a routing algorithm that is fully aware of the current network topology and available resources. A multi objective unicast MANET route optimization problem that uses network performance measures such as delay, hop distance, load, cost and reliability is addressed in this study. A multi-objective version of the traditional Ad hoc On-Demand Vector (AODV) routing protocol and an ant based routing algorithm is presented to solve this NP hard problem by employing this objective vector. Simulation is carried out in NS2 and the results revealed that the proposed algorithms yield good results in terms of delay, packet delivery ratio and throughput when compared with the AODV protocol.