bluuebunny/crossref_metadata_2025_split huggingface dataset:
Determinants of positive mental health during organizational change: role of continuous learning, mindfulness and change-efficacy
Authors: Budhiraja Sunil , Rathi Neerpal 
Published: April 2022

Purpose
By integrating job demands-resource (JD-R) theory and organizational change approach, the paper investigates determinants of positive mental health (PMH) of employees experiencing unpredictable organizational change (i.e. transition from physical work to remote work and other associated changes during the Covid-19 pandemic). The paper aims to examine the direct and indirect effects of continuous learning (CL) and mindfulness (MF) on PMH of employees via their perceived change-efficacy (CE).

Design/methodology/approach
Time-lagged primary data were collected from a cohort of information technology employees experiencing organizational change in the past one year. During the first stage, data was collected on variables, including CF, MF and CE, whereas response on PMH of employees was collected after one month. AMOS-24 has been used to assess the measurement model and perform the analysis.

Findings
At the outset, the study affirms that CL, MF and CE significantly contribute toward PMH of employees. The mediation analysis suggests that CE significantly mediates both relationships (i.e. CL-PMH and MF-PMH).

Practical implications
First, CL and MF are key to recovering from a crisis and enhancing PMH of employees. Second, employees’ CE is an essential ingredient for organizations to successfully implement organizational changes while amplifying the PMH of employees.

Originality/value
The study is one of its kind which examines the antecedents of employees’ mental health during organizational change while examining the mediating role of their CE. The findings contribute substantially to the literature of organizational change and JD-R theory by integrating and extending it to organizational change context.
Multisensory prosumption: how cooking classes shape perceptions of destinations
Authors: Aksenova Diana , Cai Wenjie , Gebbels Maria 
Published: April 2022

Purpose
This study aims to examine the multisensory experiences of participating in a cooking class and how they shape perceptions of destinations in the pre-trip stage. Performance theory and prosumption provide a theoretical lens to investigate how a cooking class influences the pre-trip destination sensescape.

Design/methodology/approach
This study used participatory action research consisting of an immersive Tatarstan cooking class experience with the supporting materials of music and videos, focus group discussions and participant observations.

Findings
Cooking class participants prosume local culture and (re)construct the perceptions of Tatarstan by partaking in cooking classes through a multisensory experience. The pre-trip destination sensescape formation in the cooking class is dynamic, stimulating and memorable. With active engagement in co-creating in the process, such experience significantly strengthens and reshapes the perceptions of a destination.

Practical implications
Cooking classes can be leveraged in pre-trip marketing as a tool to enhance the competitiveness of tourism destinations and contribute to accessible tourism, such as engaging visually impaired tourists’ other heightened senses in experience design and marketing.

Originality/value
This study revealed that participation in cooking classes involves active, embodied and multisensory engagement, which acts as a vehicle of the destination perception change.
Effects of history, location and size of ethnic enclaves and ethnic restaurants on authentic cultural gastronomic experiences
Authors: Song Hanqun , Kim Jong-Hyeong 
Published: April 2022

Purpose
The extant gastronomy literature has rarely examined a connection between authentic gastronomic experiences and destinations. Specifically, ethnic enclaves, which are unique gastronomic and cultural destinations providing ethnic cuisine and cultural experiences to visitors, have been under-researched. Thus, this study aims to address this knowledge gap.

Design/methodology/approach
Using a 2 (history: long vs short) × 2 (location: Central Business District vs rural; main street vs alleyway) × 2 size/ownership type (big vs small; chain vs independent) between-subjects design, two experiments were conducted using a sample of 557 British consumers to test the effect of history, location and size of ethnic enclaves and ethnic restaurants on consumers’ authentic cultural and gastronomic experiences in a UK context.

Findings
In Study 1, ethnic enclave’s size affected consumers’ authentic cultural experiences. In Study 2, restaurants’ history and ownership type positively influenced consumers’ authentic gastronomic experiences. Both studies consistently reported the positive relationship between authentic experiences and behavioural intentions.

Practical implications
For ethnic enclaves, the management team may consider expanding the size of ethnic enclaves to increase consumers’ authentic cultural experience. For those ethnic restaurants within the ethnic enclave, any independent or old ethnic restaurants should actively promote both characteristics in their marketing materials to create a feeling of offering authentic gastronomic experiences to customers.

Originality/value
This study identified important ethnic enclave-related factors and ethnic restaurant-related factors forming consumers’ authentic cultural and gastronomic experiences.
STEM vs non-STEM differences in university teaching and research during the COVID-19 pandemic: the case of Sri Lanka
Authors: de Silva Tiloka , Wickramasinghe Vathsala 
Published: April 2022

PurposeThis study aims to explore the differences between science, technology, engineering and mathematics (STEM) and non-STEM disciplines in terms of the changes to teaching and research practices caused by the COVID-19 pandemic.Design/methodology/approachThe paper analyses survey responses collected between July and November 2020 from 241 academics (excluding library staff) from the five oldest state universities in Sri Lanka. The analysis focuses on the differences between STEM and non-STEM faculty using multiple linear regression to control for demographic characteristics such as age, gender and designation as well as university-specific factors.FindingsThe paper finds significant differences in the teaching practices of STEM and non-STEM academics, both in terms of preparation time for teaching and tools used for online delivery. Significant differences are also observed in research practices, with STEM faculty being significantly more likely to engage in research collaborations, obtain research funding and be involved in more research projects. The authors do not find any evidence of the pandemic having differential impacts on research productivity between the broad disciplines.Originality/valueThis research provides insights into the differences between STEM and non-STEM disciplines in online teaching and research practices adopted since the onset of the pandemic, which are important for formulating appropriate policy responses to mitigate the impact of the pandemic on both students and staff. The contribution is particularly significant for developing countries where the creation of a skilled workforce is a key driver of the development process.
Longitudinal modelling of housing prices with machine learning and temporal regression
Authors: Zhang Yu , Rahman Arnab , Miller Eric 
Published: April 2022

Purpose
The purpose of this paper is to model housing price temporal variations and to predict price trends within the context of land use–transportation interactions using machine learning methods based on longitudinal observation of housing transaction prices.

Design/methodology/approach
This paper examines three machine learning algorithms (linear regression machine learning (ML), random forest and decision trees) applied to housing price trends from 2001 to 2016 in the Greater Toronto and Hamilton Area, with particular interests in the role of accessibility in modelling housing price. It compares the performance of the ML algorithms with traditional temporal lagged regression models.

Findings
The empirical results show that the ML algorithms achieve good accuracy (R2 of 0.873 after cross-validation), and the temporal regression produces competitive results (R2 of 0.876). Temporal lag effects are found to play a key role in housing price modelling, along with physical conditions and socio-economic factors. Differences in accessibility effects on housing prices differ by mode and activity type.

Originality/value
Housing prices have been extensively modelled through hedonic-based spatio-temporal regression and ML approaches. However, the mutually dependent relationship between transportation and land use makes price determination a complex process, and the comparison of different longitudinal analysis methods is rarely considered. The finding presents the longitudinal dynamics of housing market variation to housing planners.
Predicting arrhythmia, atrial fibrillation from electrocardiogram signals using Pivot Range Fitness Scale-Based Machine Learning Model
Authors: Jyothi Sreedhar , Nelloru Geetanjali 
Published: April 2022

PurposePatients having ventricular arrhythmias and atrial fibrillation, that are early markers of stroke and sudden cardiac death, as well as benign subjects are all studied using the electrocardiogram (ECG). In order to identify cardiac anomalies, ECG signals analyse the heart's electrical activity and show output in the form of waveforms. Patients with these disorders must be identified as soon as possible. ECG signals can be difficult, time-consuming and subject to inter-observer variability when inspected manually.Design/methodology/approachThere are various forms of arrhythmias that are difficult to distinguish in complicated non-linear ECG data. It may be beneficial to use computer-aided decision support systems (CAD). It is possible to classify arrhythmias in a rapid, accurate, repeatable and objective manner using the CAD, which use machine learning algorithms to identify the tiny changes in cardiac rhythms. Cardiac infractions can be classified and detected using this method. The authors want to categorize the arrhythmia with better accurate findings in even less computational time as the primary objective. Using signal and axis characteristics and their association n-grams as features, this paper makes a significant addition to the field. Using a benchmark dataset as input to multi-label multi-fold cross-validation, an experimental investigation was conducted.FindingsThis dataset was used as input for cross-validation on contemporary models and the resulting cross-validation metrics have been weighed against the performance metrics of other contemporary models. There have been few false alarms with the suggested model's high sensitivity and specificity.Originality/valueThe results of cross validation are significant. In terms of specificity, sensitivity, and decision accuracy, the proposed model outperforms other contemporary models.
Are Industry 4.0 technologies enablers of lean? Evidence from manufacturing industries
Authors: Narula Sanjiv , Puppala Harish , Kumar Anil , Luthra Sunil , Dwivedy Maheshwar , Prakash Surya , Talwar Vishal 
Published: April 2022

Purpose
This study aims to propose a conceptual model indicating the impact of Industry 4.0 (I4.0) technologies on lean tools. Additionally, it prioritizes I4.0 technologies for the digital transformation of lean plants.

Design/methodology/approach
The authors conducted a questionnaire-based survey to capture the perception of 115 experts of manufacturing industries from Germany, India, Taiwan and China. The impact of I4.0 on lean tools, using analysis of variance (ANOVA). Further, the authors drew a prioritization map of I4.0 on the employment of lean tools in manufacturing, using the Best–Worst Method (BWM).

Findings
The findings indicate that cloud manufacturing, simulation, industrial internet of things, horizontal and vertical integration impact 100% of the lean tools, while both cyber-security, big data analytics impact 93% of the lean tools and advanced robotics impact 74% of the lean tools. On the other hand, it is observed that augmented reality and additive manufacturing will impact 21% and 14% of the lean tools, respectively.

Practical implications
The results of this study would help practitioners draw up a strategic plan and roadmap for implementing lean 4.0. The amalgamation of lean with I4.0 technologies in the right combination would enhance speed productivity and facilitate autonomous operations.

Originality/value
Studies exploring the influence of I4.0 on lean manufacturing lack comprehensiveness, testing and validation. Importantly, no studies in the recent past have explored mapping and prioritizing I4.0 technologies in the “lean” context. This study thereby attempts to establish a conceptual model, indicating the influence of I4.0 technologies on lean tools and presents the hierarchy of all digital technologies.
Domain-based ambidexterity for managing a dual business model in the hospitality industry in the midst of COVID-19 pandemic: an exploratory study
Authors: Yassiva Vergine Virsta , Priyono Anjar , Wibowo Wisnu Pambudi 
Published: April 2022

Purpose
This study aims to analyse how a hotel company manages ambidexterity when operating different business models in different markets located in the same country.

Design/methodology/approach
This research was conducted using a qualitative case study, and the subjects were selected using the theoretical sampling technique. A corporation managing two hotel business units located in the same city but operating different business models – a premium and a low-cost business model – were selected as subjects.

Findings
The empirical evidence revealed that an ambidextrous business model can be realized through integration or separation of appropriate domains of business activities. The empirical findings further showed that exploitations are easier to integrate than explorations.

Practical implications
The authors found that firms using structural separation for managing premium and low-cost business models can avoid market cannibalism and achieve synergies between different business models if business model ambidexterity is well managed.

Originality/value
This study extends research in the area of ambidexterity and business models. It responds to calls to examine how firms using structural separation implement business model ambidexterity in practice, particularly in service sectors. By analysing the details of activities within the business model, the authors advance the understanding of which domains are suitable for an integration or separation approach.
The relationship between sustainable supply chain management and enterprise economic performance: does firm size matter?
Authors: Yang Xiaoyue , Wang Jing 
Published: April 2022

Purpose
Based on the extended resource-based view (ERBV), this paper aims to investigate the relationship between sustainable supply chain management (SSCM), dynamic capabilities (DCs) and enterprise economic performance (EEP). Both the direct effects of SSCM on economic performance and the mediation effect of DCs are investigated. This empirical study also examines the moderating role of firm size.

Design/methodology/approach
This study applies hierarchical regression analyses to test our hypotheses, and then the mediation test was performed using the macro PROCESS. Data were collected from 178 Chinese manufacturing firms.

Findings
The findings show that SSCM practices significantly and positively influence both economic performance and DCs. The results indicate that DCs partially mediate the relationship between SSCM practices and EEP. Moreover, firm size has a moderating effect on external SSCM practices that influence EEP, but the moderating effect was not found to be significant for the effects of internal SSCM practices on economic performance and SSCM practices on DCs.

Practical implications
This study reveals insights into the potential benefits for large enterprises and SMEs related to the utilization of SSCM practices in China and puts forward differentiated suggestions for SSCM practices in large enterprises and SMEs.

Originality/value
Drawing on the ERBV, this study provides a deeper perspective on the relationship between SSCM and EEP by regarding DCs as a mediating variable and firm size as a moderating variable.
Can Shari’ah supervisory board and Islamic bank characteristics reduce tax avoidance? Evidence in Indonesia and Malaysia
Authors: Taufik Muhammad 
Published: April 2022

Purpose
This study aims to shed light on Shari’ah supervisory boards (SSBs) and the possibilities of Islamic banks to reduce the tax avoidance. Performance and Shari’ah compliance have been extensively studied; however, tax avoidance remains a challenge.

Design/methodology/approach
SSB characteristics, based on resource dependence theory, influence tax avoidance, including SSB size, educational level, expertise, reputation, remuneration and turnover. The samples were obtained from Islamic banks in Indonesia and Malaysia (2010–2020) using the data panel method.

Findings
Islamic banks avoid taxes through the effective tax rate and book tax difference. SSBs who have more expertise play a role in investigating the complexity of tax avoidance, and SSB reputation, who is a member of the Islamic bank regulator, understands immorality, resulting in reduced tax avoidance. Moreover, the recruitment system has been effective, as SSBs with more expertise have become more prevalent. Meanwhile, SSB from a Shari’ah background works only in regulated areas, simplifying Shari’ah compliance, in particular, attestation of financial reporting. A heavy workload is created by cross-membership, resulting in the neglect of the immoral value of tax avoidance. The calculation of tax avoidance also includes remuneration and bank assets.

Practical implications
Given the uniqueness of Islamic banks contributing to social welfare, tax regulators need to review the appropriateness of fees that can be treated as taxes. Tax regulators can join hands with Islamic bank regulators on this review.

Originality/value
To the best of the authors’ knowledge, this study is one of the first to examine the characteristics of SSBs and Islamic banks on tax avoidance. Separating Islamic banks by country enriches the analysis.
Reducing occupational fraud through reforms in public sector audit: evidence from Ghana
Authors: Agyemang Samuel Kojo , Ohalehi Paschal , Mgbame Oscar Chijoke , Alo Kolawole 
Published: April 2022

Purpose
This paper aims to explore the contributions that public sector audit through reforms can make in dealing with the issues of occupational fraud in Ghana.

Design/methodology/approach
The issues surrounding the Ghana Audit Service (GAS) reports issued to parliament were reviewed using socio-legal methodology. The discussion as well as the theoretical contribution is informed by stakeholder theory.

Findings
The findings show matching of irregularities as reported by regular audit reports to schemes of occupational fraud and abuse as well as how the power to surcharge and disallow would serve as a deterrence mechanism in the fight against occupational fraud.

Practical implications
This paper concludes with discussions on specific requirements including the use of fraud investigators and modern forensic techniques in a collaborative effort with guidelines from the Supreme Audit Institution to minimise fraud.

Originality/value
This study, to the best of the authors’ knowledge, is the first to explore the role of GAS in minimising occupational fraud.
The effect of intellectual capital on firm performance: the mediating role of family management
Authors: Bataineh Hanady , Abbadi Sinan Suleiman , Alabood Enas , Alkurdi Amneh 
Published: April 2022

PurposeThis study aims to investigate the effect of intellectual capital components on firms’ performance, and also examines the influence of the mediating role of family management on such a relationship.Design/methodology/approachThe hypotheses are tested using structural equation modeling for a sample of 46 Jordanian service listed firms during 2014–2019.FindingsThe results indicate that intellectual capital efficiency is a key factor that enables firms to achieve higher financial performance and higher market value. Human capital efficiency has a significant positive effect on firms’ profitability as measured by return on assets and earnings per share. No evidence is shown to support that family management has a mediating role on the relationship between intellectual capital and firms’ performance.Practical implicationsThe results indicate strong evidence of the important role of intellectual capital on firm performance. Accordingly, this study recommends that the managers of service firms should continue to enhance and improve the components of intellectual capital, especially investing more in the competencies and capabilities of employees, including their skills, education and training programs to achieve competitive advantage and ensure continued success in the future, and investors to pay special attention to the components of intellectual capital to predict the performance of the firm and be able to choose the best investment opportunities.Originality/valueThis study provides additional insights into the literature of both intellectual capital and family businesses by analyzing data from an emerging market.
Saddling effect of underlying contracts on sales performance: a multi-group analysis in the takaful industry
Authors: Shamsudheen Shinaj Valangattil , Mahomed Ziyaad , Muneeza Aishath 
Published: April 2022

Purpose
This study aims to examine the impact of information overload (referred to as the saddling effect in this study) of underlying contracts on the sales performance of the salesforce at takaful institutions with special reference to addressing the heterogeneous effect among distribution channels.

Design/methodology/approach
A total of 311 samples were collected from the sales professionals of the takaful industry in Malaysia using a purposive sampling technique and the empirical analysis was conducted with the measures of model fit and bootstrapping technique using partial least square structural equation modeling and multi-group analysis.

Findings
Empirical results indicate that the saddling effect of the underlying contracts is evident among salesforce and the magnitude of the impact was found to be heterogeneous between the groups of salesforces in different distribution channels.

Practical implications
Findings recommend respective authorities of takaful institutions to intensify capacity building for their salesforce, particularly in the area of shariah knowledge and nature of underlying Islamic contracts used in the takaful products. A significant heterogeneous effect between distribution channels suggests that the actions and policy formulations should be diverse between the salesforce at different distribution channels and higher attention should be catered for the salesforce at the direct selling channel.

Originality/value
The increased information expectation (i.e. underlying contract knowledge) on takaful salesforce and its impact on their sales performance have not been documented before. The increase in information may create a burdening effect or what is referred to in this study as the information or knowledge “saddling effect.” If a saddling effect is identified, this may be a formidable reason for the slowing growth of the takaful industry in the respective market. It is expected that the outcome of this study would assist not only to fill the gap in the literature of personnel selling in the takaful industry but also will assist the takaful institutions in formulating appropriate policies for tackling the issue of the saddling effect of underlying contracts.