Unnati Narang and Venkatesh Shankar
Mobile marketing, the two- or multi-way communication and promotion of an offer between a firm and its customers using a mobile medium, device, platform, or technology, has made…
Abstract
Mobile marketing, the two- or multi-way communication and promotion of an offer between a firm and its customers using a mobile medium, device, platform, or technology, has made rapid strides in the past several years. Mobile marketing has entered its second phase or Mobile Marketing 2.0. The surpassing of desktop by mobile devices in digital media consumption, diffusion of wearable devices among customers, and an overall integration and interconnectedness of devices characterize this phase. Against this backdrop, we present a synthesis of the most recent literature in mobile marketing. We discuss three key advances in mobile marketing research relating to mobile targeting, personalization, and mobile-led cross-channel effects. We outline emerging industry trends in mobile marketing, including mobile app monetization, augmented reality, data and privacy, wearable devices, driverless vehicles, the Internet of Things, and artificial intelligence. Within each extant and emerging area, we delineate the future research opportunities in mobile marketing. Finally, we discuss the impact of mobile marketing on customer, firm, and societal outcomes.
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Vinoth Kumar M. and Balasubramanian V.
Super 304HCu super austenitic stainless steel tubes containing 2.3 to 3 (Wt.%) of copper (Cu) is used in superheaters and reheater tubings of nuclear power plants. In general…
Abstract
Purpose
Super 304HCu super austenitic stainless steel tubes containing 2.3 to 3 (Wt.%) of copper (Cu) is used in superheaters and reheater tubings of nuclear power plants. In general, austenitic stainless steels welded by conventional constant current gas tungsten arc welding (CC-GTAW) produce coarse columnar grains, alloy segregation and may result in inferior mechanical properties. Pulsed current gas tungsten arc welding (PC-GTAW) can control the solidification structure by altering the prevailing thermal gradients in the weld pool.
Design/methodology/approach
Super 304HCu tubes of Ø 57.1 mm and the wall thickness of 3.5 mm were autogenously welded using CC and PC-GTAW processes. Joints are characterized using optical microscopy, electron microscopy, energy dispersive spectroscopy and electron backscatter diffraction (EBSD) techniques. Hot tensile properties of the weld joints were evaluated and correlated with their microstructural features.
Findings
Current pulsing in GTAW has resulted in minimal eutectic film segregation, lower volume % of delta ferrite and appreciable improvement in tensile properties than CC-GTAW joints.
Originality/value
The EBSD boundary map and inverse pole orientation map of Super 304HCu weld joints evidence the grain refinement and much frequent high angle grain boundaries achieved using weld current pulsing.
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C. Rajendran, K. Srinivasan, V. Balasubramanian, H. Balaji and P. Selvaraj
Presently, the materials used in light combat aircraft structures are aluminium alloys and composites. These structures are joined together through riveted joints. The weight of…
Abstract
Purpose
Presently, the materials used in light combat aircraft structures are aluminium alloys and composites. These structures are joined together through riveted joints. The weight of these rivets for the entire aircraft is nearly one ton. In addition to weight, the riveted connection requires a lot of tools, equipments, fixtures and manpower, which makes it an expensive and time-consuming process. Moreover, Al alloy is also welded using tungsten inert gas (TIG) welding process by proper control of process parameters. This process has limitations such as porosity, alloy segregation and hot cracking. To overcome the above limitations, an alternative technology is required. One such technology is friction stir welding (FSW), which can be successfully applied for welding of aluminium alloy in LCA structures. Therefore, this paper aims to compare the load carrying capabilities of FSW joints with TIG welded and riveted joints.
Design/methodology/approach
FSW joints and TIG welded joints were fabricated using optimized process parameters, followed by riveted joints using standard shop floor practice in the butt and lap joint configurations.
Findings
The load-carrying capabilities of FSW joints are superior than those of other joints. FSW joints exhibited 75 per cent higher load-carrying capability compared to the riveted joints and TIG-welded joints.
Practical implications
From this investigation, it is inferred that the FSW joint is suitable for the replacement of riveted joints in LCA and TIG-welded joints.
Originality/value
Friction stir butt joints exhibited 75 per cent higher load-carrying capability than riveted butt joints. Friction stir welded lap joints showed 70 per cent higher load-carrying capability than the riveted lap joints. Friction stir butt joints yielded 41 per cent higher breaking load capabilities than the TIG-welded butt joints. Moreover, Friction stir lap weld joints have 57 per cent more load-carrying capabilities than the TIG-welded lap joints.
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A. Arun Negemiya, S. Rajakumar and V. Balasubramanian
The purpose of this paper is to develop an empirical relationship for predicting the strength of titanium to austenitic stainless steel fabricated by diffusion bonding (DB…
Abstract
Purpose
The purpose of this paper is to develop an empirical relationship for predicting the strength of titanium to austenitic stainless steel fabricated by diffusion bonding (DB) process. Process parameters such as bonding pressure, bonding temperature and holding time play the main role in deciding the joint strength.
Design/methodology/approach
In this study, three-factors, five-level central composite rotatable design was used to conduct the minimum number of experiments involving all the combinations of parameters.
Findings
An empirical relationship was developed to predict the lap shear strength (LSS) of the joints incorporating DB process parameters. The developed empirical relationship was optimized using particle swarm optimization (PSO). The optimized value discovered through PSO was compared with the response surface methodology (RSM). The joints produced using bonding pressure of 14 MPa, bonding temperature of 900°C and holding time of 70 min exhibited a maximum LSS of 150.51 MPa in comparison with other joints. This was confirmed by constructing response graphs and contour plots.
Originality/value
Optimizing the DB parameters using RSM and PSO, PSO gives an accurate result when compared with RSM. Also, a sensitivity analysis is carried out to identify the most influencing parameter for the DB process.
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M. Balasubramanian and R. Kumar
In friction welding of dissimilar joint method, few material compositions are not possible to weld effectively. For better dissimilar metal joining in friction welding, the…
Abstract
Purpose
In friction welding of dissimilar joint method, few material compositions are not possible to weld effectively. For better dissimilar metal joining in friction welding, the interlayer techniques are used by the third metal to increase the diffusion for suitable metal bonding. The interlayer metals are popularly held by coating, foils, sheet and solid rod form. The coating method needs more care for surface preparation with special coating equipment with high workmanship. In case of foil as intermediate metal, more care is neededfor holding between the metal; most of the time this technique has the possibility of failure by peeling off from the contact surface during high speed rotation with pressure during friction generation.
Design/methodology/approach
In this investigation, a copper coin was machined to a suitable size (transition fit) to suit the recess inside the SS rod. The mating surfaces of Cu coin, SS rod and Ti alloy were machined, polished to mirror finish and handled in friction welding machine. The purpose of the transition fit between the coin and SS rod is for holding the same intact before the beginning of the process.
Findings
Successful joint was achieved with good joint strength at less time. Empirical models were established to fin out the joint strength at any given parameter within the range of investigation
Research limitations/implications
The models developed can be used only within the range of investigation considered for experimentation.
Practical implications
The paper includes implications for the development of a method of joining any dissimilar joints
Originality/value
In this investigation, a copper coin was machined to a suitable size (transition fit) to suit the recess inside the SS rod. The mating surfaces of Cu coin, SS rod and Ti alloy were machined, polished to mirror finish and handled in friction welding machine. The purpose of the transition fit between the coin and SS rod is for holding the same intact before the beginning of the process.
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Sathyaraj R, Ramanathan L, Lavanya K, Balasubramanian V and Saira Banu J
The innovation in big data is increasing day by day in such a way that the conventional software tools face several problems in managing the big data. Moreover, the occurrence of…
Abstract
Purpose
The innovation in big data is increasing day by day in such a way that the conventional software tools face several problems in managing the big data. Moreover, the occurrence of the imbalance data in the massive data sets is a major constraint to the research industry.
Design/methodology/approach
The purpose of the paper is to introduce a big data classification technique using the MapReduce framework based on an optimization algorithm. The big data classification is enabled using the MapReduce framework, which utilizes the proposed optimization algorithm, named chicken-based bacterial foraging (CBF) algorithm. The proposed algorithm is generated by integrating the bacterial foraging optimization (BFO) algorithm with the cat swarm optimization (CSO) algorithm. The proposed model executes the process in two stages, namely, training and testing phases. In the training phase, the big data that is produced from different distributed sources is subjected to parallel processing using the mappers in the mapper phase, which perform the preprocessing and feature selection based on the proposed CBF algorithm. The preprocessing step eliminates the redundant and inconsistent data, whereas the feature section step is done on the preprocessed data for extracting the significant features from the data, to provide improved classification accuracy. The selected features are fed into the reducer for data classification using the deep belief network (DBN) classifier, which is trained using the proposed CBF algorithm such that the data are classified into various classes, and finally, at the end of the training process, the individual reducers present the trained models. Thus, the incremental data are handled effectively based on the training model in the training phase. In the testing phase, the incremental data are taken and split into different subsets and fed into the different mappers for the classification. Each mapper contains a trained model which is obtained from the training phase. The trained model is utilized for classifying the incremental data. After classification, the output obtained from each mapper is fused and fed into the reducer for the classification.
Findings
The maximum accuracy and Jaccard coefficient are obtained using the epileptic seizure recognition database. The proposed CBF-DBN produces a maximal accuracy value of 91.129%, whereas the accuracy values of the existing neural network (NN), DBN, naive Bayes classifier-term frequency–inverse document frequency (NBC-TFIDF) are 82.894%, 86.184% and 86.512%, respectively. The Jaccard coefficient of the proposed CBF-DBN produces a maximal Jaccard coefficient value of 88.928%, whereas the Jaccard coefficient values of the existing NN, DBN, NBC-TFIDF are 75.891%, 79.850% and 81.103%, respectively.
Originality/value
In this paper, a big data classification method is proposed for categorizing massive data sets for meeting the constraints of huge data. The big data classification is performed on the MapReduce framework based on training and testing phases in such a way that the data are handled in parallel at the same time. In the training phase, the big data is obtained and partitioned into different subsets of data and fed into the mapper. In the mapper, the features extraction step is performed for extracting the significant features. The obtained features are subjected to the reducers for classifying the data using the obtained features. The DBN classifier is utilized for the classification wherein the DBN is trained using the proposed CBF algorithm. The trained model is obtained as an output after the classification. In the testing phase, the incremental data are considered for the classification. New data are first split into subsets and fed into the mapper for classification. The trained models obtained from the training phase are used for the classification. The classified results from each mapper are fused and fed into the reducer for the classification of big data.
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This chapter describes the importance of marketing activities at airports. The link between marketing and airports has been reinforced by new technologies and digital marketing…
Abstract
This chapter describes the importance of marketing activities at airports. The link between marketing and airports has been reinforced by new technologies and digital marketing tools. This technological combination has had a high penetration in the user's smartphones and airport activities, particularly in non-aeronautical revenue. Moreover, this chapter introduces a new conceptualisation of airport marketing, a definition more updated and aligned with airports' business needs in the time of a pandemic crisis. The rest of the chapter shows the mobile marketing tool and its interaction with passengers, as well as how this helps airport operators design new products and services, and increase commercial revenue through digital channels.
Shopper marketing describes the planning and execution of all marketing activities that influence a shopper along – and beyond – the path-to-purchase, from shopping trigger to…
Abstract
Shopper marketing describes the planning and execution of all marketing activities that influence a shopper along – and beyond – the path-to-purchase, from shopping trigger to purchase, consumption, repurchase, and recommendation stages. Shopper marketing practices at manufacturers and retailers are growing at a tremendous pace and a rising portion of marketing budgets are now devoted to shopper marketing. The first phase of shopper marketing research and practice, Shopper Marketing 1.0, addressed interesting issues, primarily relating to in-store marketing. In the next phase, Shopper Marketing 2.0, will significantly extend to out-of-store marketing, including online and mobile marketing, resulting in an integrated practice. In this new environment, to formulate and execute effective shopper marketing strategies, managers need to better understand the complete picture of how online, offline, mobile and in-store marketing influence shoppers in the path-to-purchase-and-beyond cycle. In this chapter, we present the evolution of shopper marketing, summarize key learnings, outline important issues, and discuss the opportunities and challenges of Shopper Marketing 2.0.
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Kondapalli Siva Prasad, Chalamalasetti Srinivasa Rao and Damera Nageswara Rao
The purpose of this paper is to optimize the fusion zone grain size and hardness using Hooke and Jeeves Algorithm.
Abstract
Purpose
The purpose of this paper is to optimize the fusion zone grain size and hardness using Hooke and Jeeves Algorithm.
Design/methodology/approach
Experiments are conducted as per four factors, five levels response surface method based central composite design matrix. Empirical relations for predicting grain size and harness are developed. The effect of welding variables on grain size and hardness are studies. Grain size and hardness are optimised using Hooke and Jeeves Algorithm.
Findings
The developed empirical relations can be effectively used to predict grain size and hardness values of micro plasma arc welded Inconel 625 sheets. The values of grain size and hardness obtained by Hooke and Jeeves Algorithm matches with experimental values with great accuracy.
Research limitations/implications
The developed mathematical models are valid for 0.25 mm thick Inconel 625 sheets only.
Practical implications
In the present paper only four important factors namely peak current, back current, pulse rate and pulse width are considered, however one may consider other parameters like plasma gas flow rate, shielding gas flow rate, etc.
Originality/value
The present work is very much useful to sheet metal industries manufacturing metal bellows, diaphragms, etc.