bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overconfidence bias and stock market volatility in Ghana: testing the rationality of investors in the Covid-19 era
Authors: Kuranchie-Pong Raphael , Forson Joseph Ato 
Published: December 2021

PurposeThe paper tests the overconfidence bias and volatility on the Ghana Stock Exchange (GSE) during the pre-Covid-19 pandemic and Covid-19 pandemic period.Design/methodology/approachThe study employs pairwise Granger causality to test the presence of overconfidence bias on the Ghana stock market as well as GARCH (1,1) and GJR-GARCH (1, 1) models to understand whether overconfidence bias contributed to volatility during pre-Covid-19 pandemic and Covid-19 pandemic period. The pre-Covid-19 pandemic period spans from January, 2019 to December, 2019, and Covid-19 pandemic period spans from January, 2020 to December, 2020.FindingsThe paper finds a unidirectional Granger causality running from weekly market returns to weekly trading volume during the Covid-19 pandemic period. These results indicate the presence of overconfidence bias on the Ghana stock market during the Covid-19 pandemic period. Finally, the conditional variance estimation results showed that excessive trading of overconfident market players significantly contributes to the weekly volatility observed during the Covid-19 pandemic period.Research limitations/implicationsThe empirical findings demonstrate that market participants on the GSE exhibit conditional irrationality in their investment decisions during the Covid-19 pandemic period. This implies investors overreact to private information and underreact to available public information and as a result become overconfident in their investment decisions.Practical implicationsFindings from this paper show that there is evidence of overconfidence bias among market players on the GSE. Therefore, investors, financial advisors and other market players should be educated on overconfidence bias and its negative effect on their investment decisions so as to minimize it, especially during the pandemic period.Originality/valueThis study is a maiden one that underscores investors’ overconfidence bias in the wake of a pandemic in the Ghanaian stock market. It is a precursor to the overconfidence bias discourse and encourages the testing of other behavioral biases aside what is understudied during the Covid-19 pandemic period in Ghana.
The effects of environmental consciousness and menu information on the perception of restaurant image
Authors: Remar Daniel , Sukhu Anupama , Bilgihan Anil 
Published: December 2021

PurposeThis research examines the influence of consumer environmental consciousness and perception of menu information in the formation of restaurant image. The concepts of mindfulness and mindful consumption were used as the theoretical background for the study.Design/methodology/approachUsing a quasi-experimental setting, data were collected from restaurant consumers dining at an upscale casual restaurant in the southeastern United States over a four-week time. Structural equation modeling, multi-group analysis and mediation analysis were used to test the hypothesized relationships between research constructs.FindingsResults suggested that consumer environmental consciousness does not have a direct effect on the formation of restaurant image. However, consumer environmental consciousness influenced consumers' perception of menu information, and the perception of menu information consequently influences the restaurant image.Practical implicationsFoodservice industry increasingly interested in sustainability practices. Consumers want to know the connections between food and its impact on their health and the environment. Findings reveal that environmentally conscious consumers actively sought out menu information, and that once the information they were seeking was perceived, it significantly strengthened the perception of restaurant image.Originality/valueTo the best of our knowledge, this is the first research that investigated the environmental consciousness construct in a live restaurant context.
Bayesian inference of multi-sensors impedance cardiography for detection of aortic dissection
Authors: Badeli Vahid , Ranftl Sascha , Melito Gian Marco , Reinbacher-Köstinger Alice , Von Der Linden Wolfgang , Ellermann Katrin , Biro Oszkar 
Published: December 2021

Purpose
This paper aims to introduce a non-invasive and convenient method to detect a life-threatening disease called aortic dissection. A Bayesian inference based on enhanced multi-sensors impedance cardiography (ICG) method has been applied to classify signals from healthy and sick patients.

Design/methodology/approach
A 3D numerical model consisting of simplified organ geometries is used to simulate the electrical impedance changes in the ICG-relevant domain of the human torso. The Bayesian probability theory is used for detecting an aortic dissection, which provides information about the probabilities for both cases, a dissected and a healthy aorta. Thus, the reliability and the uncertainty of the disease identification are found by this method and may indicate further diagnostic clarification.

Findings
The Bayesian classification shows that the enhanced multi-sensors ICG is more reliable in detecting aortic dissection than conventional ICG. Bayesian probability theory allows a rigorous quantification of all uncertainties to draw reliable conclusions for the medical treatment of aortic dissection.

Originality/value
This paper presents a non-invasive and reliable method based on a numerical simulation that could be beneficial for the medical management of aortic dissection patients. With this method, clinicians would be able to monitor the patient’s status and make better decisions in the treatment procedure of each patient.
Multiobjective optimization of compensation networks for wireless power transfer systems
Authors: Bertoluzzo Manuele , Di Barba Paolo , Forzan Michele , Mognaschi Maria Evelina , Sieni Elisabetta 
Published: December 2021

Purpose
The purpose of this paper is to show how the EStra-Many method works on optimization problems characterized by high-dimensionality of the objective space. Moreover, a comparison with a more classical approach (a constrained bi-objective problem solved by means of NSGA-II) is done.

Design/methodology/approach
The six reactances of a compensation network (CN) for a wireless power transfer system (WPTS) are synthesized by means of an automated optimal design. In particular, an evolutionary algorithm EStra-Many coupled with a sorting strategy has been applied to an optimization problem with four objective functions (OFs). To assess the obtained results, a classical genetic algorithm NSGA-II has been run on a bi-objective problem, constrained by two functions, and the solutions have been analyzed and compared with the ones obtained by EStra-Many.

Findings
The proposed EStra-Many method identified a solution (CN synthesis) that enhances the WPTS, considering all the four OFs. In particular, to assess the synthesized CN, the Bode diagram of the frequency response and a circuital simulation were evaluated a posteriori; they showed good performance of the CN, with smooth response and without unwanted oscillations when fed by a square wave signal with offset. The EStra-Many method has been able to find a good solution among all the feasible solutions, showing potentiality also for other fields of research, in fact, a solution nondominated with respect to the starting point has been identified. From the methodological viewpoint, the main finding is a new formulation of the many-objective optimization problem based on the concept of degree of conflict, which gives rise to an implementation free from hierarchical weights.

Originality/value
The new approach EStra-Many used in this paper showed to properly find an optimal solution, trading-off multiple objectives. The compensation network so synthesized by the proposed method showed good properties in terms of frequency response and robustness. The proposed method, able to deal effectively with four OFs, could be applied to solve problems with a higher number of OFs in a variety of applications because of its generality.
The mediating role of employee commitment between quality of work-life and job performance of the faculty
Authors: Singh Agyapal 
Published: December 2021

Purpose
This study aims to examine the mediating role of employee commitment between the quality of work-life (QWL) and job performance among the faculty of technical institutions established in the province of Punjab (India).

Design/methodology/approach
The data collected from 434 faculty members with a response rate of 72% is analyzed and the mediation effect of employee commitment between the QWL and job performance of the faculty is modeled through partial least square-structural equation modeling.

Findings
The results indicate that employee commitment partially mediates between QWL and job performance. To strengthen the result, mediation of employee commitment is also tested for each dimension of the QWL with job performance. All the factors of QWL also supported a partial mediation effect.

Practical implications
The findings of the study may help the policymakers to understand, frame and implement appropriate policies for improving the work-life quality and commitment among the faculty. This may further assist in augmenting the overall performance of the faculty amidst a crisis in the sector.

Originality/value
The study highlights the role of employee commitment as a mediator between the QWL and job performance of the faculty in the technical education sector which is one of its kind and possibly not yet explored. Besides, the study proposes some measures in improving the work-life quality and job performance of the faculty.
An experimental study on visual tracking based on deep learning
Authors: A Krishna Mohan , PVN Reddy , K Satya Prasad 
Published: December 2021

PurposeIn the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best performance. The main objective of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG & Harris are used for the process of feature extraction. The proposed method will give the best results when compared to other existing methods.Design/methodology/approachThis paper introduces the concept and research status of tracks; later the authors focus on the representative applications of deep learning in visual tracking.FindingsBetter tracking algorithms are not mentioned in the existing method.Research limitations/implicationsVisual tracking is the ability to control eye movements using the oculomotor system (vision and eye muscles working together). Visual tracking plays an important role when it comes to identifying an object and matching it with the database images. In visual tracking, deep learning has achieved great success.Practical implicationsThe authors implement the multiple tracking methods, for better tracking purpose.Originality/valueThe main theme of this paper is to review the state-of-the-art tracking methods depending on deep learning. First, we introduce the visual tracking that is carried out manually, and secondly, we studied different existing methods of visual tracking based on deep learning. For every paper, we explained the analysis and drawbacks of that tracking method. This paper introduces the concept and research status of tracks, later we focus on the representative applications of deep learning in visual tracking.
The actualization of maqāṣid al-Sharīʿah in Islamic finance: a conceptual framework
Authors: Monawer Abu Talib Mohammad , Abdul Rahman Noor Naemah , Qasem Al-‎Nahari Ameen Ahmed Abdullah , Haji Abdullah Luqman , Ali Abdul Karim , Meguellati Achour 
Published: December 2021

Purpose
This paper aims to formulate a conceptual framework that will facilitate the actualization of maqāṣid al-Sharīʿah in product design and consumption within Islamic financial institutions (IFIs).

Design/methodology/approach
This paper relies on the classical and contemporary literature on maqāṣid al-Sharīʿah and Islamic finance and adopts a qualitative content analysis method and an inductive approach to outline the constituent elements that formulate the framework.

Findings
This study determines six vital constituents of maqāṣid al-Sharīʿah, namely, parameters of maqāṣid, particular objectives, appropriate means, micro provisions, level of need and legal maxims to develop a conceptual framework of actualizing maqāṣid al-Sharīʿah in Islamic finance. The framework covers the following three stages: identification of maqāṣid, operationalization of maqāṣid in product design and consumption based on maqāṣid.

Research limitations/implications
This paper proposes a conceptual framework without investigating the practice of any particular industry or products. Further research would focus on formulating a practical framework based on a focus group discussion with industry experts, elaborating the parameters of maqāṣid, scrutinizing the maqāṣid available in the literature by the parameters of maqāṣid and assessing the IFIs’ products and services using the proposed framework.

Practical implications
This paper provides insights into the importance of maqāṣid elements and the effects of overlooking them on IFIs and customers’ product consumption. Furthermore, a major implication of the proposed framework is to learn how to use the maqāṣid approach as the baseline for designing new financial products.

Originality/value
The novelty of this paper lies in its pioneering attempt of harmonizing all essential maqāṣid elements and using them as constituents to formulate a comprehensive framework that actualizes maqāṣid al-Sharīʿah in the Islamic finance industry.
Warehouse robot market boosted by Covid pandemic and technological innovations
Authors: Bogue Robert 
Published: December 2021

Purpose
This paper aims to provide details of recent commercial and technological developments that are driving robotic warehouse automation.

Design/methodology/approach
Following a short introduction, this first provides a commercial background and identifies the factors driving the market growth. It then gives examples of robotics companies, products and applications that exploit innovations in artificial intelligence (AI). It then considers future prospects, and finally, brief conclusions are drawn.

Findings
Amazon’s acquisition of Kiva led to a community of new robot manufacturers and the realisation by major e-commerce companies that robotic automation would be required to maintain competitiveness. The Covid pandemic caused a surge in e-commerce and a critical shortage of labour, which further highlighted the need for automation and boosted robotic deployments. Recent advances in AI have resulted in a rapidly growing community of companies producing AI-powered robots which offer advanced capabilities such as mixed product picking, sorting and kitting. These are being deployed by a growing number of e-commerce and logistics companies and are paving the way towards ever-higher levels of warehouse automation. Full automation will soon become a reality.

Originality/value
This paper identifies the factors driving the rapidly developing warehouse robot business by considering the companies, products, technology and applications.
The impact of servitization on the environmental and social performance in manufacturing firms
Authors: Zhang Jingsi , Qi Liangqun , Wang Chengdong , Lyu Xichen 
Published: December 2021

PurposeThis study aims to examine how servitization affects the environmental and social performance of manufacturing firms.Design/methodology/approachThe hypotheses are tested using fixed-effect panel models based on secondary data of 1,413 manufacturing firms publicly listed in the USA.FindingsResults show that servitization is positively related to the social performance of manufacturing firms; this positive relationship is more prominent under high levels of human resource slack. However, the impact of servitization on environmental performance depends on the level of absorptive capacity and human resource slack. Servitization improves environmental performance under high levels of absorptive capacity and human resource slack, while this positive impact is insignificant under low levels of absorptive capacity and human resource slack.Research limitations/implicationsThe study focuses on the degree (depth) of servitization but ignores the scope of services provided by manufacturing firms (breadth of servitization).Practical implicationsThis research suggests that servitization is an effective way of achieving simultaneous improvements in environmental and social performance. However, high levels of absorptive capacity and human resource slack are needed to achieve this goal.Originality/valueThis study contributes to the servitization literature by demonstrating the environmental and social sustainability benefits of servitization. The findings also highlight the crucial role of absorptive capacity and human resource slack on improving environmental and social performance through servitization.
Blockchain in supply chain management: a grounded theory-based analysis
Authors: Rodrigues Eladian Batista , Lourenzani Wagner Luiz , Satolo Eduardo Guilherme , Braga Júnior Sergio Silva , Anholon Rosley , Rampasso Izabela Simon 
Published: December 2021

PurposeThis study aims to present consolidated information on blockchain, which seeks to better clarify the concept of blockchain and the associated implications and characteristics.Design/methodology/approachThe methodological procedure used was Grounded Theory, based on a Systematic Bibliographic Review on the adoption of blockchain in supply chain management. To add experts' opinion on the subject to the analyzed panorama, data from a survey were also considered in the analysis.FindingsThe Grounded Theory enabled the development of consolidated information on blockchain related knowledge, identifying benefits, fragilities and contributions of the concept for supply chain management.Originality/valueAn epistemological gap has been identified between the use of blockchain in supply chain management and a theoretical basis to support the application. The originality of this study lies in providing a proposition of this theoretical basis.
Statistical analysis used in LIS research produced by Pakistani authors
Authors: Ullah Ahsan , Ameen Kanwal 
Published: December 2021

PurposeStatistical methods are important for meaningful analysis, critique and interpretation of results. The current study aims to investigate the use of statistical methods used in LIS research articles produced by Pakistani authors during 2001–2016.Design/methodology/approachContent analysis method with both the qualitative and quantitative components was used. LIS articles published by Pakistani authors in national and international journals from 2001 to 2016 were selected. The descriptive and inferential statistics were used to analyze the usage of statistical techniques.FindingsThe findings show that use of descriptive statistics remained higher as compared to inferential statistics in the LIS research produced by Pakistani authors. However, a visible growth trend in the use of inferential statistical techniques is found. Males are two times more likely to use inferential statistics as compared to female authors. Articles published in foreign journals and impact factor journals used more inferential statistics as compared to local and nonimpact factor journals. Parametric inferential statistics is more popular among Pakistani authors as compared to nonparametric. Faculty was more inclined toward using parametric statistic. The percentage of collaboration was higher in the papers using parametric statistics. Few articles reported the tests to fulfill the assumptions of parametric and nonparametric statistics.Originality/valueThis study can be used to better understand the trends of statistical techniques used in LIS research and authors' orientation in this regard. It will be helpful for future researchers in the selection of appropriate statistical techniques to be used.
The liquidity, performance and investor preference of socially responsible investments
Authors: Brodmann Jennifer , Wuthisatian Phuvadon , Malladi Rama K. 
Published: December 2021

PurposeThe purpose of the paper is to analyze socially responsible investment (SRI) asset performance compared to traditional assets using the MSCI KLD 400 Index. The authors examine the required return that investors expect to maintain their holdings in SRI stock and whether SRI stocks can be used for diversification during financial crises.Design/methodology/approachThe authors examine SRI stocks' liquidity from the MSCI KLD 400 index, encompassing all environmental, social and governance (ESG) factor investments over 25 years, from 1990 until 2019. The authors test whether sorting portfolios based on their excess return, liquidity and volatility can explain the difference in SRI and non-SRI stocks' returns and then examine the global financial crisis' (GFC) impact on excess returns for SRI and non-SRI assets.FindingsThe authors find a significant difference in liquidity and volatility between SRI and non-SRI stocks and that SRI stocks perform better during financial crises. The results suggest a possible general investor preference to invest in non-SRI stocks despite our findings that SRI stocks tend to withstand financial risk better than non-SRI stocks. The authors find that long-term investors may be willing to forego short-term gains to reduce their overall risk exposure during crises.Originality/valueSRI is gaining international popularity as an alternative investment that includes ratings based on ESG factors. Previous studies provide mixed results of whether SRI stocks outperform conventional stocks. In addition, there is limited research examining the liquidity and volatility of SRI assets. The authors compare the differences between SRI and non-SRI stocks in terms of excess return, volatility and liquidity and compare the liquidity of SRI and non-SRI stocks during the financial crisis.
Gelation and microstructural properties of ternary composite gel of scallop (Patinopecten yessoensis) protein hydrolysates/κ‐carrageenan/xanthan gum
Authors: Du Yi‐Nan , Xue Shan , Yan Jia‐Nan , Jiang Xin‐Yu , Wu Hai‐Tao 
Published: December 2021

AbstractThe objective of this study was to investigate the properties of ternary composite gel of scallop (Patinopecten yessoensis) protein hydrolysates (SMGHs)/κ‐carrageenan (KC)/xanthan gum (XG). The rheological properties, moisture‐distribution, molecular structure, and microstructure of SMGNs/KC/XG gels were analyzed. The results showed that the G′ value, melting temperature, and water holding capacity of SMGHs/KC/XG were higher than those of SMGHs, SMGHs/KC, and SMGHs/XG. FTIR spectrum showed the generation of hydrogen bonds between SMGHs and KC/XG, and the carboxylic acid group of XG interacts with SMGHs. Moreover, the cryo‐SEM results showed that SMGHs/KC/XG exhibited a tighter, smoother, and more aggregated microstructure than those of SMGHs, SMGHs/KC, and SMGHs/XG. These results indicate that the gel and microstructural properties of SMGHs are significantly improved by addition of KC and XG, and SMGHs/KC/XG has potential to be used as functional hydrogels for food, pharmaceutical, and biomedical applications.Practical ApplicationScallop (Patinopecten yessoensis) male gonads are rich in protein and usually regarded as byproducts during adductor processing. Because of its gelation properties, scallop male gonads have potential to be used as functional hydrogels for food. The SMGHs/KC/XG ternary composite gel showed excellent gel properties, which would be potentially applied in delivery system in food and biological fields. Further study is undergoing to apply SMGHs/KC/XG to embed bioactive compounds, such as curcumin and β‐carotene.