bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virtual grocery shopping intention: an application of the model of goal-directed behaviour
Authors: Thomas-Francois Kimberly , Jo WooMi , Somogyi Simon , Li Qianya , Nixon Andrew 
Published: February 2023

PurposeVirtual grocery shopping (VGS), or online grocery shopping, traditionally has seen slow adoption in Canada; however, the COVID-19 pandemic has forced consumers to seek safer ways to shop. Retailers have invested in building new infrastructure to meet the current consumer demands for VGS. However, the main driver for VGS behaviour has not been yet clearly identified. Additionally, it is also not unknown whether the shopping modalities will continue VGS after the pandemic. This study provides insights into consumer intentions to use VGS by extending the model of goal-directed behaviour (MGB) to incorporate consumer technological readiness.Design/methodology/approachThe study collected 935 valid survey responses from an online survey panel of Canadian consumers. A two-step approach was applied to analyse the data, comprising confirmatory factor analysis (CFA) and structural equation modelling (SEM). The data quality and model fit were tested before testing the proposed relationships among the constructs: attitude, subjective norm, perceived behavioural control, positive and negative anticipated emotions, as well as technological readiness, desire and behaviour intentions. The mediation role of desire between frequency of past online grocery shopping behaviours and the future behavioural intention was also tested using SPSS PROCESS.FindingsThe study results showed that attitudes, subjective norms, perceived behavioural control, positive and negative emotions, technological readiness and frequency of past VGS have a major impact on consumers' desire to embrace VGS in the future. Consumer desire also played a significant mediating role between frequency of past VGS behaviours and future shopping intention online. In addition, the frequency of past VGS showed an even stronger impact on behavioural intention among female consumers than among male consumers.Originality/valueThe findings of this study provide an original insight into the social, cultural and psychological factors that impact consumers' use of VGS, particularly the impacts of gender.
Forecasting demand in the residential construction industry using machine learning algorithms in Jordan
Authors: Sammour Farouq , Alkailani Heba , Sweis Ghaleb J. , Sweis Rateb J. , Maaitah Wasan , Alashkar Abdulla 
Published: February 2023

Purpose
Demand forecasts are a key component of planning efforts and are crucial for managing core operations. This study aims to evaluate the use of several machine learning (ML) algorithms to forecast demand for residential construction in Jordan.

Design/methodology/approach
The identification and selection of variables and ML algorithms that are related to the demand for residential construction are indicated using a literature review. Feature selection was done by using a stepwise backward elimination. The developed algorithm’s accuracy has been demonstrated by comparing the ML predictions with real residual values and compared based on the coefficient of determination.

Findings
Nine economic indicators were selected to develop the demand models. Elastic-Net showed the highest accuracy of (0.838) versus artificial neural networkwith an accuracy of (0.727), followed by Eureqa with an accuracy of (0.715) and the Extra Trees with an accuracy of (0.703). According to the results of the best-performing model forecast, Jordan’s 2023 first-quarter demand for residential construction is anticipated to rise by 11.5% from the same quarter of the year 2022.

Originality/value
The results of this study extend to the existing body of knowledge through the identification of the most influential variables in the Jordanian residential construction industry. In addition, the models developed will enable users in the fields of construction engineering to make reliable demand forecasts while also assisting in effective financial decision-making.
Power density improvement of axial flux permanent magnet synchronous motor by using different magnetic materials
Authors: Hebri Mohamed Amine , Rebhaoui Abderrahmane , Bauw Gregory , Lecointe Jean-Philippe , Duchesne Stéphane , Zito Gianluca , Abdenour Abdelli , Mediavilla Santos Victor , Mallard Vincent , Maier Adrien 
Published: February 2023

Purpose
The purpose of this paper is to exploit the optimal performances of each magnetic material in terms of low iron losses and high saturation flux density to improve the efficiency and the power density of the selected motor.

Design/methodology/approach
This paper presents a study to improve the power density and efficiency of e-motors for electric traction applications with high operating speed. The studied machine is a yokeless-stator axial flux permanent magnet synchronous motor with a dual rotor. The methodology consists in using different magnetic materials for an optimal design of the stator and rotor magnetic circuits to improve the motor performance. The candidate magnetic materials, adapted to the constraints of e-mobility, are made of thin laminations of Si-Fe nonoriented grain electrical steel, Si-Fe grain-oriented electrical steel (GOES) and iron-cobalt Permendur electrical steel (Co-Fe).

Findings
The mixed GOES-Co-Fe structure allows to reach 10 kW/kg in rated power density and a high efficiency in city driving conditions. This structure allows to make the powertrain less energy consuming in the battery electric vehicles and to reduce CO2 emissions in hybrid electric vehicles.

Originality/value
The originality of this study lies in the improvement of both power density and efficiency of the electric motor in automotive application by using different magnetic materials through a multiobjective optimization.
Where are your ideas going? Idea adoption in online user innovation communities
Authors: Qin Min , Li Shuqin , Cai Fangtong , Zhu Wei , Qiu Shanshan 
Published: February 2023

PurposeWith the proliferation of ideas submitted by users in firm-built online user innovation communities, community managers are faced with the problem of user idea overload. The purpose of this paper is to explore the influencing factors on the idea adoption to identify high quality ideas, and then propose a method to quickly filter high value ideas.Design/methodology/approachThe authors collected more than 110,000 data submitted by Xiaomi community users and analyzed the factors affecting idea adoption using a multinomial logistic regression model. In addition, the authors also used BP neural network to predict the idea adoption process.FindingsThe empirical results show that idea semantics, number of likes, number of comments, number of related posts, the existence of pictures and self-presentation have positive impact on idea adoption, while idea length and idea timeliness had negative impact on idea adoption. In addition, this paper calculates the idea evaluation value through the idea adoption process predicted by neural network and the mean value of idea term frequency inverse document frequency (TF-IDF).Originality/valueThis empirical study expands the theoretical perspective of idea adoption research by using dual-process theory and enriches the research methods in the field of idea adoption research through the multinomial logistic regression method. Based on our findings, firms can quickly identify valuable ideas and effectively alleviate the information overload problem of online user innovation communities.
A modified UTAUT framework to predict students' intention to adopt online learning: moderating role of openness to change
Authors: Tewari Alok , Singh Ram , Mathur Smriti , Pande Sushil 
Published: February 2023

PurposeThe current study employs a modified framework of the unified theory of acceptance and use of technology (UTAUT) to predict students' intention to adopt online learning in India. The moderating role of openness to change in influencing the proposed relationships is also assessed.Design/methodology/approachA structured questionnaire was emailed to 650 students enrolled in various courses in public and private universities in India. In total 424 responses were considered for analysis using structural equation modeling (SEM). Moderation analysis was carried out with multi-group SEM and chi-square difference tests.FindingsThe results reveal that there is a significant impact of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FS) and perceived security (PS) on students' intention to adopt online learning. Further, openness to change moderates the impact of PE, FS and PS on intention of students to opt for online learning.Originality/valueThis study is one of the initial efforts to examine the factors affecting students' intention to adopt online learning at the onset of third wave of coronavirus disease 2019 (COVID-19) pandemic in India. Besides the factors of the UTAUT model, this study highlights the importance of PS and openness to change in influencing students' intention to opt for online learning.
Does country risk moderates the financial market development and shadow economy nexus? Evidence from fast-emerging countries analysis
Authors: Ur Rahman Sami , Faisal Faisal , Sami Fariha , Schneider Friedrich 
Published: February 2023

PurposeThe shadow economy (SE) has been a serious issue with varied dimensions in all countries that significantly affect economic growth. Therefore, all countries have made an effort to tackle the SE by pursuing several measures. This study aims to investigate the impact of financial markets (stock and bond) in reducing the SE while considering the role of country risk (political, economic and financial) in N-11 countries.Design/methodology/approachThe study employed first-generation methodological techniques, including a unit root test to identify stationarity in the series, a panel cointegration test and panel autoregressive distributive lag (ARDL) to estimate long-run and short-run relationships. Finally, the Granger causality is applied to determine the direction of the causal relationship.FindingsThe study explored that country risk factors are crucial in reducing the size of the SE. Moreover, the significant moderating role of country risk factors in the financial market development and SE nexus suggests that by controlling the country's risk, financial market development can negatively affect the SE.Research limitations/implicationsDue to the availability of data, the study used data, ranging from 1995 to 2015, because the tax burden data is available from 1995 while the maximum data for the SE is available till 2015, using Medina and Schneider's (2019) data estimates for the SE.Originality/valueThe previous studies have focused explicitly on the role of financial institutions' development in the SE. To the best of the author's knowledge, no previous study is attempted to investigate the role of financial markets (bonds and stock) in the size of the SE. Furthermore, previous studies have ignored the important role of country risk factors in the size of the SE. This study investigates the impact of country risk on the SE and the moderating role of country risk in the development of financial markets and the SE nexus.
Heterogeneity of investor sentiment, geopolitical risk and economic policy uncertainty: do Islamic banks differ during COVID-19 pandemic?
Authors: Albaity Mohamed , Saadaoui Mallek Ray , Mustafa Hasan 
Published: February 2023

PurposeThis study examined the impact of; COVID-19 investor sentiment, COVID-19 cases, geopolitical risk (GPR), economic policy uncertainty (EPU), oil returns and Islamic banking on bank stock returns. In addition, it examined whether Islamic bank stock returns differed from conventional banks when interacting with selected variables.Design/methodology/approachThis study consisted of 137 conventional and Islamic stock market listed banks in 16 Middle East and North Africa (MENA) countries from February 2020 to July 2021. Monthly data were used for bank stock returns, number of COVID-19 cases, COVID-19 investor sentiment, oil price and EPU, while GPR data were obtained annually. This paper used unconditional quantile regression (UQR) in its analysis.FindingsCOVID-19 investor sentiment and EPU negatively influenced bank stock returns. However, oil returns were only positive and significant in first quantile. Conversely, GPR negatively impacted bank returns up to the median quantile, while the impact was positive in upper quantiles. Islamic banks outperformed conventional banks in all quantiles. Additionally, GPR negatively influenced Islamic bank returns up to 75th quantile, while oil returns negatively impacted Islamic bank returns up to 95th quantile. Ultimately, COVID-19 investor sentiment and EPU positively influenced Islamic bank returns up to 95th quantile.Practical implicationsMarket conditions must be considered when implementing investment decisions and policies, as the effects of market shocks are mostly asymmetrical. For example, it is important for international investors to take into consideration asymmetric factors, such as market uncertainty in oil market. Especially in bearish Islamic markets, bad news concerning uncertainty can be perceived as riskier than good news.Social implicationsA change in health sentiment, such as COVID-19 cases and COVID-19 investor sentiment, can be used to determine future direction of conventional and Islamic stock markets. Asymmetric effects associated with market news can make portfolio management more effective. COVID-19 investor sentiment states can be used to predict Islamic market index dynamics in MENA region.Originality/valueThis paper offered insight into heterogeneity of market conditions and dependencies of Islamic banks' stock market returns on COVID-19 investor sentiment and uncertainty, among others that should be considered when implementing investment decisions and policies.
Spillovers and tail dependence between oil and US sectoral stock markets before and during COVID-19 pandemic
Authors: Mensi Walid , Hanif Waqas , Bouri Elie , Vo Xuan Vinh 
Published: February 2023

PurposeThis paper examines the extreme dependence and asymmetric risk spillovers between crude oil futures and ten US stock sector indices (consumer discretionary, consumer staples, energy, financials, health care, industrials, information technology, materials, telecommunication and utilities) before and during COVID-19 outbreak. This study is based on the rationale that stock sectors exhibit heterogeneity in their response to oil prices depending on whether they are classified as oil-intensive or non-oil-intensive sectors and the possible time variation in the dependence and risk spillover effects.Design/methodology/approachThe authors employ static and dynamic symmetric and asymmetric copula models as well as Conditional Value at Risk (VaR) (CoVaR). Finally, they use robustness tests to validate their results.FindingsBefore the COVID-19 pandemic, crude oil returns showed an asymmetric tail dependence with all stock sector returns, except health care and industrials (materials), where an average (symmetric tail) dependence is identified. During the COVID-19 pandemic, crude oil returns exhibit a lower tail dependency with the returns of all stock sectors, except financials and consumer discretionary. Furthermore, there is evidence of downside and upside risk asymmetric spillovers from crude oil to stock sectors and vice versa. Finally, the risk spillovers from stock sectors to crude oil are higher than those from crude oil to stock sectors, and they significantly increase during the pandemic.Originality/valueThere is heterogeneity in the linkages and the asymmetric bidirectional systemic risk between crude oil and US economic sectors during bearish and bullish market conditions; this study is the first to investigate the average and extreme tail dependence and asymmetric spillovers between crude oil and US stock sectors.
Sustainability in higher education in Ecuador- Universidad Técnica del Norte case study
Authors: Aguirre Patricia , Villota Freddy Hernán , Mera Silvia 
Published: February 2023

Purpose
According to the importance of higher education institutions (HEIs) in meeting sustainable development goals (SDGs), the purpose of this study is to analyze how sustainability was implemented in Ecuadorian higher education. The case study of the Universidad Técnica del Norte (UTN) process was analyzed to show the advantages of implementing projects with SD approaches.

Design/methodology/approach
This study includes an analytic-synthetic method. In the case study, a longitudinal-documentary method was used to analyze the projects implemented in the UTN. The primary source of information corresponds to reports, minutes, publications, interviews and surveys from the academic staff of UTN, which can be found in the Postgraduate Institute of the UTN archives.

Findings
Projects implemented at UTN facilitated the development of skills in the participating university community and influenced the general organizational development of the university. Likewise, the potential benefits of the projects in each of the components are highlighted, so that social learning and the development of skills in students and teachers have been facilitated, focusing on internationalization.

Research limitations/implications
The population analyzed corresponds to Ecuadorian universities and technical institutes, however, access to information from all HEIs is limited, due to processing time and economic resources.

Practical implications
This study presents implications for representatives of higher education and policymakers at the national level since the positive aspects can be rescued to promote the sustainable performance of HEIs.

Social implications
HEIs train ethical professionals capable of transforming the world. The study shows successful experiences that can be used by other HEIs to have a positive impact on society, providing a sustainable future. In addition, UTN has prioritized the initiative of the students in several activities.

Originality/value
The primary information for the case study comes from the experiences obtained during the international cooperation projects of the UTN. Positive findings and limitations have been identified, which are published with the purpose of contributing to the scientific community.
Digital transformation of supply chain: a study on additive manufacturing practice in medical device in Australia
Authors: Chowdhury Md Maruf Hossan , Scerri Moira , Shahriar Sajib , Skellern Katrina 
Published: February 2023

PurposeDrawing on a dynamic capability view, this study develops a decision support model that determines the most suitable configuration of strategies and challenges to adopt additive manufacturing (AM) to expedite digital transformation and performance improvement of the surgical and medical device (SMD) supply chain.Design/methodology/approachTo investigate the research objective, a multi-method and multi-study research design was deployed using quality function deployment and fuzzy set qualitative comparative analysis.FindingsThe study finds that only resilience strategies or negation (i.e. minimisation) of challenges are not enough; instead, a configuration of resilience strategies and negation of challenges is highly significant in enhancing performance.Practical implicationsSMD supply chain decision-makers will find the decision support model presented in this study as beneficial to be resilient against various challenges in the digital transformation of service delivery process.Originality/valueThis study builds new knowledge of the adoption of AM technology in the SMD supply chain. The decision support model developed in this study is unique and highly effective for fostering digital transformation and enhancing SMD supply chain performance.
Growing older and growing apart? Population age structure and trade
Authors: Kopecky Joseph 
Published: February 2023

PurposeThis paper explores the empirical relationship between population age structure and bilateral trade.Design/methodology/approachThe author includes age structure in both log and Poisson pseudo-maximum likelihood (PPML) formulations of the gravity equation of trade. The author studies relative age effects, using differences in the demographic structure of each country-pair.FindingsThe author finds that a relatively larger share of population in working age increases bilateral exports. This is robust to various estimation models, as well as to changes in the method of specifying the demographic controls. Old-age shares have a negative, but less robustly estimated impact on trade. Estimating instead the balance of trade between trading partners produces similar results, with positive effects of age structure peaking later in working life.Practical implicationsGlobal populations are poised to undergo a massive transition. Trade a crucial way that the demographic deficits of one country may be offset by the dividends of another as comparative advantages shift along with the size and strength of their underlying workforce.Originality/valueThe author’s work is among the first to quantify the effect of relative age structure between two countries and their bilateral trade flows. Focusing on the aggregate flows, relative age shares and PPML estimates of the trade relationship, this paper provides the most comprehensive picture to date on how age structure affects trade.
Exploring empowerment as an enabler of effective knowledge management
Authors: Ozpamuk Mustafa , Bolatan Gulin Idil , VanDerSchaaf Hans , Daim Tugrul 
Published: February 2023

Purpose
This study aims to investigate the degree to which trust influences job satisfaction and job performance by building on research in the organizational sciences about the relationships between interpersonal trust relationships, cognitive empowerment, job performance and job satisfaction. This study's primary research question is: What factors contribute to job satisfaction and job performance?

Design/methodology/approach
Data are collected through a field survey. The data set has 738 responses from employees who work in the financial sector in Turkey. Structural equation modelling was used to validate the hypotheses.

Findings
This study's main findings are that when considering job satisfaction and job performance, cognition-based trust (CBT) has a strong influence on both constructs, whereas affect-based faith has a medium effect on job satisfaction and no significant effect on job performance.

Originality/value
In an organization where trust is established, knowledge exchange will be facilitated and knowledge management will be done correctly. Therefore, trust is a critical factor for knowledge management. On the other hand, knowledge is an important key factor for job performance. Trust has two parts: affect-based trust and CBT. Psychological empowerment has four variables: impact, competence, meaningfulness and self-determination. This study aims to investigate the relationships between psychological empowerment, trust, job satisfaction and job performance.