Chetan Jalendra, B.K. Rout and Amol Marathe
Industrial robots are extensively used in the robotic assembly of rigid objects, whereas the assembly of flexible objects using the same robot becomes cumbersome and challenging…
Abstract
Purpose
Industrial robots are extensively used in the robotic assembly of rigid objects, whereas the assembly of flexible objects using the same robot becomes cumbersome and challenging due to transient disturbance. The transient disturbance causes vibration in the flexible object during robotic manipulation and assembly. This is an important problem as the quick suppression of undesired vibrations reduces the cycle time and increases the efficiency of the assembly process. Thus, this study aims to propose a contactless robot vision-based real-time active vibration suppression approach to handle such a scenario.
Design/methodology/approach
A robot-assisted camera calibration method is developed to determine the extrinsic camera parameters with respect to the robot position. Thereafter, an innovative robot vision method is proposed to identify a flexible beam grasped by the robot gripper using a virtual marker and obtain the dimension, tip deflection as well as velocity of the same. To model the dynamic behaviour of the flexible beam, finite element method (FEM) is used. The measured dimensions, tip deflection and velocity of a flexible beam are fed to the FEM model to predict the maximum deflection. The difference between the maximum deflection and static deflection of the beam is used to compute the maximum error. Subsequently, the maximum error is used in the proposed predictive maximum error-based second-stage controller to send the control signal for vibration suppression. The control signal in form of trajectory is communicated to the industrial robot controller that accommodates various types of delays present in the system.
Findings
The effectiveness and robustness of the proposed controller have been validated using simulation and experimental implementation on an Asea Brown Boveri make IRB 1410 industrial robot with a standard low frame rate camera sensor. In this experiment, two metallic flexible beams of different dimensions with the same material properties have been considered. The robot vision method measures the dimension within an acceptable error limit i.e. ±3%. The controller can suppress vibration amplitude up to approximately 97% in an average time of 4.2 s and reduces the stability time up to approximately 93% while comparing with control and without control suppression time. The vibration suppression performance is also compared with the results of classical control method and some recent results available in literature.
Originality/value
The important contributions of the current work are the following: an innovative robot-assisted camera calibration method is proposed to determine the extrinsic camera parameters that eliminate the need for any reference such as a checkerboard, robotic assembly, vibration suppression, second-stage controller, camera calibration, flexible beam and robot vision; an approach for robot vision method is developed to identify the object using a virtual marker and measure its dimension grasped by the robot gripper accommodating perspective view; the developed robot vision-based controller works along with FEM model of the flexible beam to predict the tip position and helps in handling different dimensions and material types; an approach has been proposed to handle different types of delays that are part of implementation for effective suppression of vibration; proposed method uses a low frame rate and low-cost camera for the second-stage controller and the controller does not interfere with the internal controller of the industrial robot.
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A simulation model conceived from the causal and interactive behaviour of various inter‐related activities is described, its aim being to aid study of the problems of the…
Abstract
A simulation model conceived from the causal and interactive behaviour of various inter‐related activities is described, its aim being to aid study of the problems of the procurement‐production‐distribution system of a manufacturing company engaged in the multi‐stage production of many products.
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Hsiang-Ming Lee, Ya-Hui Hsu, Tsai Chen, Wei-Yuan Lo and Wei-Chun Chien
The purpose of this study is to understand the effect of different brand positions (underdog vs top dog) and comparative advertising on consumers’ brand attitudes. Additionally…
Abstract
Purpose
The purpose of this study is to understand the effect of different brand positions (underdog vs top dog) and comparative advertising on consumers’ brand attitudes. Additionally, this study also aims to demonstrate the effects of inspiration, self-relevance and empathy on the relationship between brand positioning and comparative advertising.
Design/methodology/approach
A two-by-three factorial design was employed with brand positions (underdog vs top dog) and three types of comparative advertising (noncomparative, indirect comparative and direct comparative) as the independent variables. Inspiration serves as the mediator, while self-relevance and empathy act as moderators and brand attitude is the dependent variable.
Findings
The results show that different brand positions significantly affect brand attitudes, with respondents having a better brand attitude toward the underdog brand. Brand attitude is partially mediated by inspiration. Self-relevance moderates the relationship between brand positioning and brand attitude. However, brand positioning, comparative advertising and empathy do not have interaction effects.
Research limitations/implications
This study contributes to a better understanding of the effect of psychological variables on brand positioning and comparative advertising.
Practical implications
The results suggest that the underdog setting requires a real and honest story because consumers will spot a fake underdog story, which will damage consumer trust in the brand and harm the brand image.
Originality/value
There is a lack of research using psychological variables to demonstrate the effect of being the underdog brand. This study contributes to the literature by employing psychological variables to illustrate the effect of underdog positioning. These findings can help brands develop branding positioning strategies.
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The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed…
Abstract
Purpose
The COVID-19 outbreak reached a critical stage when it became imperative for public health systems to act decisively and design potential behavioral operational strategies aimed at containing the pandemic. Isolation through social distancing played a key role in achieving this objective. This research study examines the factors affecting the intention of individuals toward social distancing in India.
Design/methodology/approach
A correlation study was conducted on residents from across Indian states (N = 499). Online questionnaires were floated, consisting of health belief model and theory of planned behavior model, with respect to social distancing behavior initially. Finally, structural equation modeling was used to test the hypotheses.
Findings
The results show that perceived susceptibility (PS), facilitating conditions (FC) and subjective norms are the major predictors of attitude toward social distancing, with the effect size of 0.277, 0.132 and 0.551, respectively. The result also confirms that the attitude toward social distancing, perceived usefulness of social distancing and subjective norms significantly predict the Intention of individuals to use social distancing with the effect size of 0.355, 0.197 and 0.385, respectively. The nonsignificant association of PS with social distancing intention (IN) (H1b) is rendering the fact that attitude (AT) mediates the relationship between PS and IN; similarly, the nonsignificant association of FC with IN (H5) renders the fact that AT mediates the relationship between FC and IN.
Practical implications
The results of the study are helpful to policymakers to handle operations management of nudges like social distancing.
Originality/value
The research is one of its kind that explores the behavioral aspects of handling social nudges through FC.
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Peterson Owusu Junior and Ngo Thai Hung
This paper investigates the probable differential impact of the confirmed cases of COVID-19 on the equities markets of G7 and Nordic countries to ascertain possible…
Abstract
Purpose
This paper investigates the probable differential impact of the confirmed cases of COVID-19 on the equities markets of G7 and Nordic countries to ascertain possible interdependencies, diversification and safe haven prospects in the era of the COVID-19 pandemic over the short-, intermediate- and long-term horizons.
Design/methodology/approach
The authors apply a unique methodology in a denoised frequency-domain entropy paradigm to the selected equities markets (Li et al. 2020).
Findings
The authors’ findings reinforce the operability of the entrenched market dynamics in the COVID-19 pandemic era. The authors divulge that different approaches to fighting the pandemic do not necessarily drive a change in the deep-rooted fundamentals of the equities market, specifically for the studied markets. Except for an extreme case nearing the end (start) of the short-term (intermediate-term) between Iceland and either Denmark or the US equities, there exists no potential for diversification across the studied markets, which could be ascribed to the degree of integration between these markets.
Practical implications
The authors’ findings suggest that politicians should pay closer attention to stock market fluctuations as well as the count of confirmed COVID-19 cases in their respective countries since these could cause changes to market dynamics in the short-term through investor sentiments.
Originality/value
The authors measure the flow of information from COVID-19 to G7 and Nordic equities using the entropy methodology induced by the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), which is a data-driven technique. The authors employ a larger sample period as a result of this, which is required to better comprehend the subtleties of investor behaviour within and among economies – G7 and Nordic geographical blocs – which largely employed different approaches to fighting the COVID-19 pandemic. The authors’ focus is on diverging time horizons, and the ICEEMDAN-based entropy would enable us to measure the amount of information conveyed to account for large tails in these nations' equity returns. Furthermore, the authors use a unique type of entropy known as Rényi entropy, which uses suitable weights to discern tailed distributions. The Shannon entropy does not account for the fact that financial assets have fat tails. In a pandemic like COVID-19, these fat tails are very strong, and they must be accounted for.
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Power management in households has become the periodic issue for electric suppliers and household occupants. The number of electronic appliances is increasing day by day in every…
Abstract
Purpose
Power management in households has become the periodic issue for electric suppliers and household occupants. The number of electronic appliances is increasing day by day in every home with upcoming technology. So, it is becoming difficult for the energy suppliers to predict the power consumption for households at the appliance level. Power consumption in households depends on various factors such as building types, demographics, weather conditions and behavioral aspect. An uncertainty related to the usage of appliances in homes makes the prediction of power difficult. Hence, there is a need to study the usage patterns of the households appliances for predicting the power effectively.
Design/methodology/approach
Principal component analysis was performed for dimensionality reduction and for finding the hidden patterns to provide data in clusters. Then, these clusters were further being integrated with climate variables such as temperature, visibility and humidity. Finally, power has been predicted according to climate using regression-based machine learning models.
Findings
Power prediction was done based on different climatic conditions for electronic appliances in the residential sector. Different machine learning algorithms were implemented, and the result was compared with the existing work.
Social implications
This will benefit the society as a whole as it will help to reduce the power consumption and the electricity bills of the house. It will also be helpful in the reduction of the greenhouse gas emission.
Originality/value
The proposed work has been compared with the existing work to validate the current work. The work will be useful to energy suppliers as it will help them to predict the next day power supply to the households. It will be useful for the occupants of the households to complete their daily activities without any hindrance.
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Selin Türkel, Ebru Uzunoğlu and Sema Misci Kip
The purpose of this paper is to unearth common perceptions of non-profit organization (NPO) trust and reputation, with a specific focus in their overlaps and intersections…
Abstract
Purpose
The purpose of this paper is to unearth common perceptions of non-profit organization (NPO) trust and reputation, with a specific focus in their overlaps and intersections. Examining the two concepts in tandem allows a more comprehensive approach offering new insights.
Design/methodology/approach
This study is devoted to the analysis of the interplay of NPO trust and reputation combining semantic network analysis with a personification approach. The data are collected via semi-structured interviews with 482 individuals.
Findings
The present results reveal both common (e.g. charitable, credible) and unique (e.g. illuminating, nice) personality traits. Findings also demonstrate that reputation is a broader concept than trust, with more characteristics. Moreover, it is possible to state that NPOs deemed reputable have a 50% chance of being trusted.
Research limitations/implications
Clearly delineating the relationship between the concepts of NPO trust and reputation has certain conceptual significance and practical value. As traits are grouped in the existing taxonomy categories based on the analysis, it could contribute to improving understanding of these constructs, as well as a modification in the existing classification.
Practical implications
This study aims to assist NPO managers by providing a list of ideal traits for NPO reputation and trust. It can serve as a guide for managers to assess their own perceptions, for comparison with those of competitors.
Originality/value
To the authors' knowledge, this study is the first attempt to provide an interrelated perspective to the study of NPO trust and reputation through semantic network and personification approach.
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Amit Vishwakarma, G.S. Dangayach, M.L. Meena, Sumit Gupta and Sunil Luthra
The COVID-19 pandemic has had a significant and worldwide influence on healthcare delivery, and it has significantly increased the pace at which digital technology is being used…
Abstract
Purpose
The COVID-19 pandemic has had a significant and worldwide influence on healthcare delivery, and it has significantly increased the pace at which digital technology is being used. Blockchain, one of these developing digital technologies, is distinguished by a number of properties. This study focuses on a blockchain-enabled healthcare supply chain. The purpose of this work is to investigate how blockchain technology (BCT) benefits the performance of healthcare supply chain management (HSCM).
Design/methodology/approach
The present study is based on the empirical research. Blockchain Technology (BCT), Healthcare Sustainable Supply Chain Practices (HSSCP), Healthcare Supply Chain Performance (HSCP) and Stakeholders’ Involvement (SI) practices are identified from the literature review and hypotheses are framed to check their interrelationship. For testing of hypothesis, a questionnaire was developed. Data collection was done by healthcare professionals via Google docs. The IBM SPSS version 22.0 was used to analyze the data and IBM SPSS AMOS 22.0 software was used for the development of structural modal. The data was collected through the Google form from the stakeholders of healthcare sector and analyzed through Structural Equation Modelling.
Findings
This research is focused on adoption of BCT enabled Healthcare Sustainable Supply Chain to improve HSCP. From the result, it had been found that BCT is positively effecting the stakeholder's involvement (SI) and HSSCP practices. Cumulatively, they positively impact the performance of HSCP. From this study, it is found that adoption of BCT enabled Healthcare Sustainable Supply Chain succours to combat COVID-19 situation.
Originality/value
This study attempts to show the potential benefits of the adoption of BCT enabled HSSCP to improve HSCP.
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Varsha Jain, Rohit H Trivedi, Vikrant Joshi and Aarzoo Daswani
With increasing use of explicit comparative advertisement to get share of consumers’ mind and influence their purchase decision in western context, the same is now used…
Abstract
Purpose
With increasing use of explicit comparative advertisement to get share of consumers’ mind and influence their purchase decision in western context, the same is now used extensively in emerging markets like India. However, there has not been sufficient research to understand the effectiveness of explicit comparative advertisement in low and high-involvement product categories. Therefore, the purpose of this paper is to attempt to understand the effectiveness of explicit comparative advertising on consumers’ attitude and purchase intention (PI) towards high and low-involvement products.
Design/methodology/approach
The study carried out experimental treatments with 2 × 2 factorial design among 200 Indian young consumers who were in the age group 18-25. The independent variables were product categories and type of advertising (comparative and non-comparative) and dependent variables were consumer attitude and PIs.
Findings
It was found that the comparative form of advertisement developed favourable response towards the advertisement, rather than towards the brand or PI.
Research limitations/implications
The study found that comparative advertising is effective for high as well as low-involvement product category in changing the consumer’s attitude towards the advertisement. The research has used print media for conducting the experiment.
Practical implications
It can be inferred that comparisons should be supplemented with additional information in the form of the unique features and associated emotions and feeling of the product in order to develop favourable attitude towards the brand and PI.
Originality/value
Comparative advertising is a growing domain and there has been very little contribution by the researchers specially on high and low-involvement product categories.