Ahmad Usman Shahid, Hafiza Sobia Tufail, Waqas Baig, Aimen Ismail and Jawad Shahid
This paper aims to contribute to the social aspect of corporate social responsibility literature by examining the influence of financial analysts’ spirituality on their socially…
Abstract
Purpose
This paper aims to contribute to the social aspect of corporate social responsibility literature by examining the influence of financial analysts’ spirituality on their socially responsible investing (SRI) decisions relating to a profitable organization, which is alleged by the media to employ children as laborers in hazardous works in Pakistan. This study also investigates whether analysts’ social consciousness mediates between their spirituality and investing decisions.
Design/methodology/approach
A scenario-based survey was administered to 124 financial analysts at leading financial institutions in Pakistan. Data were analyzed using regression, analysis of variance and mediation analysis on SPSS 26.
Findings
The findings demonstrate that financial analysts’ spirituality negatively influences their SRI decisions to invest in a profitable organization, which is alleged to employ children in hazardous work that may harm them physically and psychologically. The findings also express that analysts’ social consciousness intervenes in the association between analysts’ spirituality and SRI decisions.
Practical implications
The findings of this study may interest regulators, multinational firms and researchers in recognizing the importance of individuals’ values for increasing socially responsible investments and addressing social issues such as the exploitation of children.
Social implications
This study encourages firms to recognize the importance of spiritual and socially conscious corporate conviction while designing strategies and policies. For example, the financial industry may incorporate fundamental personal values such as stewardship, dignity and fairness into its investment plans.
Originality/value
This study provides rigorous insights and contributes to contemporary studies by providing empirical evidence that individuals’ intrinsic values and consciousness drive their judgments.
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Rizwan Ali, Jin Xu, Mushahid Hussain Baig, Hafiz Saif Ur Rehman, Muhammad Waqas Aslam and Kaleem Ullah Qasim
This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates…
Abstract
Purpose
This study aims to endeavour to decode artificial intelligence (AI)-based tokens' complex dynamics and predictability using a comprehensive multivariate framework that integrates technical and macroeconomic indicators.
Design/methodology/approach
In this study we used advance machine learning techniques, such as gradient boosting regression (GBR), random forest (RF) and notably long short-term memory (LSTM) networks, this research provides a nuanced understanding of the factors driving the performance of AI tokens. The study’s comparative analysis highlights the superior predictive capabilities of LSTM models, as evidenced by their performance across various AI digital tokens such as AGIX-singularity-NET, Cortex and numeraire NMR.
Findings
This study finding shows that through an intricate exploration of feature importance and the impact of speculative behaviour, the research elucidates the long-term patterns and resilience of AI-based tokens against economic shifts. The SHapley Additive exPlanations (SHAP) analysis results show that technical and some macroeconomic factors play a dominant role in price production. It also examines the potential of these models for strategic investment and hedging, underscoring their relevance in an increasingly digital economy.
Originality/value
According to our knowledge, the absence of AI research frameworks for forecasting and modelling current aria-leading AI tokens is apparent. Due to a lack of study on understanding the relationship between the AI token market and other factors, forecasting is outstandingly demanding. This study provides a robust predictive framework to accurately identify the changing trends of AI tokens within a multivariate context and fill the gaps in existing research. We can investigate detailed predictive analytics with the help of modern AI algorithms and correct model interpretation to elaborate on the behaviour patterns of developing decentralised digital AI-based token prices.
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Faisal Shahzad, Ijaz Ur Rehman, Waqas Hanif, Ghazanfar Ali Asim and Mushahid Hussain Baig
This study aims to empirically investigate the effect of financial reporting quality (FRQ) and audit quality (AQ) on the investment efficiency (IE) for the firms listed on the…
Abstract
Purpose
This study aims to empirically investigate the effect of financial reporting quality (FRQ) and audit quality (AQ) on the investment efficiency (IE) for the firms listed on the Pakistan Stock Exchange during the period 2007-2014.
Design/methodology
The authors use pooled ordinary least squares (OLS) regression which cluster at the firm and year level to test the hypotheses. For sensitivity check, the authors also account for reverse causality and cross-sectional dependence by using the GMM and FGLS regression methods. Furthermore, the authors built their theoretical arguments based on alignment hypothesis of the agency theory and resource-based view of the firm.
Findings
The findings suggest that higher FRQ and AQ are associated with higher IE. The results for these particular estimates are robust when tested using alternative estimation techniques. Overall, the outcomes of this study are in line with the arguments presented by the alignment hypothesis of the agency theory and resource-based view of the firm.
Practical implications
This study is fruitful for policymakers’ and investors. This study finds that the audit done by the Big 4 also reduces the information gap and, thus, reduces the moral hazard and adverse selection problems, thereby enhancing the IE.
Originality
The authors extend the debate on determinates of IE and highlight two monitoring mechanisms: FRQ and AQ. The authors further extend the literature on the economic consequences of AQ in terms of IE, as proposed by Francis (2011). For the first time, this study investigates the impact of AQ on IE in a setting where minority shareholder risk of exploitation is high relative to other markets in Asia.
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Attia Aman-Ullah, Anis Ali, Antonio Ariza-Montes, Waqas Mehmood and Ummi Naiemah Saraih
The present study aims to test the impact of workplace incivility and violence on doctors' turnover intentions. Besides, the present study also tested the mediating role of…
Abstract
Purpose
The present study aims to test the impact of workplace incivility and violence on doctors' turnover intentions. Besides, the present study also tested the mediating role of employees' burnout.
Design/methodology/approach
The population of the present study was doctors working in 20 public sector hospitals. Where 250 doctors working in emergency departments participated, the sample size was calculated through Krejcie and Morgan's table. The data analysis was conducted through SPSS and Smart-PLS.
Findings
Results of the present study supported all the relationships except the relationship between workplace violence and turnover intentions. More specifically, relationship between workplace incivility and turnover intentions was confirmed, and mediation effect of doctors' burnout was also confirmed.
Originality/value
This present study is novel in a way that this study framed the study model using conservative resource theory and social cognitive theory covering both employees cognitive and external factors. Further, the nexus “workplace incivility → workplace violence → job burnout → turnover intentions” was tested for the first time, hence making a valuable addition to the body of literature. Further this study is a contribution to healthcare literature in context of incivility, violence, burnout, and turnover. Burnout is first time explored as moderator with workplace incivility which is another contribution.
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Syed Faheem Hasan Bukhari, Frances M. Woodside, Rumman Hassan, Ayesha Latif Shaikh, Saima Hussain and Waqas Mazhar
This study aims to explore whether religiosity influences consumer purchase behavior among Muslim consumers in Pakistan.
Abstract
Purpose
This study aims to explore whether religiosity influences consumer purchase behavior among Muslim consumers in Pakistan.
Design/methodology/approach
An in-depth, semi-structured interview protocol was developed and administered to a sample of 90 participants, both male and female, across eight metropolitan cities of Pakistan. Professionals, university students and housewives were part of the sample. NVivo Version 11 was used for data analysis to answer the research questions raised in this study. Moreover, the purposive sampling method has been used in this research.
Findings
The behavior of consumers was found to vary with the degree of involvement and the degree of religiosity. Study findings are divided into three themes. Firstly, a high level of religiosity makes Muslim consumers follow the Islamic principles of food consumption, by evaluating the product ingredients, spending moderately and verifying a halal logo at the time of purchase. Secondly, a major theme is the view that religiosity has no influence on food consumption; it is more about individuals’ needs and priorities. Finally, the consumers’ overall perception of quality, product value, purity and health consciousness over-powers the concept of religiosity.
Research limitations/implications
Because of its qualitative and exploratory nature, the generalizability of this paper is limited. In addition to that, this research is just focused on one Muslim country.
Practical implications
This study suggests that western food exporters may use religiosity and other factors as probable segmentation variables to effectively position their brands. Religious images and other factors may be highlighted in product packaging and communication campaigns by marketers to gain recognition and usage of western food and consumption among religious, Pakistani Muslim consumers. The output of this research may support prospective entrants into the food business; those interested in exploring the Asian consumer market. Findings from this study may also be helpful for those in the west interested in exploring Pakistan as an emerging consumer market.
Social implications
The presence of western imported food may improve the quality of life by having more opportunities and healthier options for the nation. Western food products can also bring cultural convergence whereby the underdeveloped nation feels upgraded and modern. Moreover, if the western food products are certified halal, the product has a fair chance of adoption and penetration in the society. Also, the food products coming from the western world induces mindfulness, people are more aware about innovative and useful ingredients that can satisfy their taste buds, improve their health, increase their life expectancy and contented approach toward life.
Originality/value
Thus far, limited research has analyzed religiosity of an overwhelmingly Muslim population and its impact on consumer behavior. This study is a preliminary effort to provide a basic understanding of the behavior of Pakistani Muslims, who have been insufficiently investigated by marketing and consumer researchers. The intriguing results are to remind marketers that there are several factors that govern religiosity and lead to a purchase decision.
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Ismail Ismail, Muhammad Sohail, Hammad Gilani, Anwar Ali, Kiramat Hussain, Kamran Hussain, Bhaskar Singh Karky, Faisal Mueen Qamer, Waqas Qazi, Wu Ning and Rajan Kotru
The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate…
Abstract
Purpose
The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate the biomass per species and plot. Furthermore, it aims to measure forest biodiversity using established formulae for tree species diversity index, richness, evenness and accumulative curve.
Design/methodology/approach
Field data were collected, including stratification of forest sample plots. Statistical analysis of the data was carried out, and locally appropriate allometric equations were applied for biomass estimation.
Findings
Representative circular 556 forest sample plots of 1,000 m2 contained 13,135 trees belonging to nine tree species with a total aboveground biomass of 12,887 tonnes. Sixty-eight per cent of the trees were found between 2,600 and 3,400 masl; approximately 63 per cent had a diameter at breast height equal to 30 cm, and 45 per cent were less than 12 m in height. The Shannon diversity index was 1.82, and Simpson’s index of diversity was 0.813.
Research limitations/implications
Rough terrain, long distances, harsh weather conditions and location of forest in steep narrow valleys presented challenges for the field crews, and meant that fieldwork took longer than planned.
Practical implications
Estimating biomass in Gilgit-Baltistan’s forests using locally developed allometric equations will provide transparency in estimates of forest reference levels, National Forest Monitoring System in Pakistan and devising Reducing Emissions from Deforestation and Forest Degradation national strategies and for effective implementation.
Originality/value
This paper presents the first detailed forest inventory carried out for the dry temperate and semi-arid cold region of Gilgit-Baltistan, Pakistan.
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Rajesh Chidananda Reddy, Debasisha Mishra, D.P. Goyal and Nripendra P. Rana
The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their…
Abstract
Purpose
The study explores the potential barriers to data science (DS) implementation in organizations and identifies the key barriers. The identified barriers were explored for their interconnectedness and characteristics. This study aims to help organizations formulate apt DS strategies by providing a close-to-reality DS implementation framework of barriers, in conjunction with extant literature and practitioners' viewpoints.
Design/methodology/approach
The authors synthesized 100 distinct barriers through systematic literature review (SLR) under the individual, organizational and governmental taxonomies. In discussions with 48 industry experts through semi-structured interviews, 14 key barriers were identified. The selected barriers were explored for their pair-wise relationships using interpretive structural modeling (ISM) and fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analyses in formulating the hierarchical framework.
Findings
The lack of awareness and data-related challenges are identified as the most prominent barriers, followed by non-alignment with organizational strategy, lack of competency with vendors and premature governmental arrangements, and classified as independent variables. The non-commitment of top-management team (TMT), significant investment costs, lack of swiftness in change management and a low tolerance for complexity and initial failures are recognized as the linkage variables. Employee reluctance, mid-level managerial resistance, a dearth of adequate skills and knowledge and working in silos depend on the rest of the identified barriers. The perceived threat to society is classified as the autonomous variable.
Originality/value
The study augments theoretical understanding from the literature with the practical viewpoints of industry experts in enhancing the knowledge of the DS ecosystem. The research offers organizations a generic framework to combat hindrances to DS initiatives strategically.
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Wenjie Li, Idrees Waris and Muhammad Yaseen Bhutto
The current study examines the impact of big data analytics capabilities (BDAC) on supply chain performances of the manufacturing firms. Based on the underpinning of…
Abstract
Purpose
The current study examines the impact of big data analytics capabilities (BDAC) on supply chain performances of the manufacturing firms. Based on the underpinning of resource-based view (RBV) theory, the current study will highlight the significance of BDAC on green dynamic capabilities (GDC), supply chain agility (SCA) and green competitive advantage (GCA). Furthermore, the study examines the moderating effect of supply chain innovativeness (SCI) on the relationship between GCA and firm performance (FP).
Design/methodology/approach
Online survey method was employed for the data collection from the 331 managers employed in Pakistan Stock Exchange (PSX)-listed manufacturing firms. The hypothesized model was tested using partial least squares structural equation modeling (PLS-SEM) technique.
Findings
The study results indicate that BDAC has a positive influence on both GDC and SCA, leading to enhanced GCA. Furthermore, the results demonstrate that GCA significantly and positively impacts FP, and the relationship between them is positively moderated by SCI.
Originality/value
This study developed a novel theoretical perspective based on RBV theory and provided empirical evidence that manufacturing firms' performances are significantly influenced by BDAC, GDC and SCA. The study results provide valuable practical implications top management regarding the effectiveness of BDAC and SCA in the supply chain. The findings further highlight the significance of SCI strengthening relationship between GCA and FP.
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Paul Dung Gadi and Daisy Mui Hung Kee
Despite the concentrated study on turnover intention (TI), slightly is known on the subject in what manner work engagement intervenes the link connecting workplace bullying (WPB…
Abstract
Purpose
Despite the concentrated study on turnover intention (TI), slightly is known on the subject in what manner work engagement intervenes the link connecting workplace bullying (WPB) and TI is varied across sectors, and how WPB and TI implications are viewed among academicians of public universities in Nigeria. The aim of this article is to explore in what way the association between WPB and TI is mediated by work engagement (WE) in public universities in Nigeria.
Design/methodology/approach
The paper applied judgmental sampling to gather 400 data from academic staff that must have worked for a minimum of six months in the current university. The present study used SmartPLS software 3.2.9 for the estimation of the hypothesis.
Findings
The result confirmed that work engagement intervenes the outcome of WPB and HRM on TI.
Research limitations/implications
The current study presents validation for the mediating impact of work engagement on the relationships connecting WPB and HRM on TI in Nigeria universities. Outcomes from findings encompassing all employees in the universities and other service sectors would offer further significant and practical implications for administrators.
Originality/value
The research furthers our knowledge of the intervening effect of work engagement in the link among WPB and TI across academicians in public universities in Nigeria. To reduce turnover intention among academic staff, administrators must have a good insight into how WE mediates the correlation linking WPB and TI.
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Khalil Ahmad, Bhuvanesh Sharma, Ritesh Khatwani, Mahima Mishra and Pradip Kumar Mitra
This paper aims to explore the impact of metaverse technology on the hospitality and tourism industry. The introduction of metaverse technology has revolutionised the way the…
Abstract
Purpose
This paper aims to explore the impact of metaverse technology on the hospitality and tourism industry. The introduction of metaverse technology has revolutionised the way the hospitality and tourism industry works. In the present study, the authors have investigated the role of social media marketing in the adoption of metaverse technology in hotel booking in India.
Design/methodology/approach
An extended technology acceptance model was proposed for an empirical investigation in the Indian context. Sample of 344 respondents was collected across India using a purposive sampling technique for the purpose of data analysis. The structural model analysis is used to analyse the data collected from the respondents using the SmartPLS software to check the structural and the measurement fit of the model.
Findings
The adoption intentions were largely influenced by the utility, attitude (ATT) and ease of use of the technology, and social media marketing plays a major role in influencing the perceived usefulness (PU) and ease of use (PEU). The study finds positive ATTs of the customers for using metaverse technology for booking their hotels. PU and PEU significantly influence the ATT of the consumer indicating the traveller’s perception of the usefulness and ease of metaverse technology influence their ATTs towards adoption.
Originality/value
Influence of metaverse technology is at a nascent stage in India specifically for hotel booking and tourism. The authors have used discriminant validity by using the criteria for both the square root of the average variance extracted and heterotrait–monotrait ratio tests, and the results suggest that the constructs in the research are distinct from other.