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- The effect of corporate philanthropy on consumer behavior: open innovation in the operating mechanismPublication . Idrees, Ufera; Aftab, Hira; Qureshi, Hamza Ahmad; Mata, Mário Nuno; Moleiro Martins, José; Mata, Pedro; Martins, Jessica NunesThe aim of this study was to highlight the effect of corporate philanthropy (CP) on consumer patronage behavior. For this purpose, reciprocity was taken as the key mechanism which determines consumers’ willingness to participate in and buy goods or services of a company performing philanthropic activities. The moderating effect of trust and vicarious licensing was also studied. Considering the importance of CP to society and its residents, it is essential to recognize its effect on consumer patronage behavior. To accomplish this objective, data were collected from 340 respondents via a questionnaire. The results of this research revealed that reciprocity shows a statistically significantly positive association with both participation intention (R = 0.729, R2 = 0.531, p = 0.000, b = 0.740) and purchasing intention (R = 0.71, R2 = 0.534, p = 0.000, b = 0.878). Similarly, trust strengthens the relationship of reciprocity with both participation intention (b = 0.250) and purchasing intention (b = 0.310). However, vicarious licensing weakens the relationship of reciprocity with both participation intention (b = −0.175) and purchasing intention (b = −0.187). The mediation effect of participation intention was also examined in this study. The results of this research will contribute to the benefit of society, since philanthropy plays a vital role in society’s progress. The greater response of consumers towards companies performing philanthropic activities justifies the importance of CP.
- Impact of Financial Support on Textile Enterprises’ DevelopmentPublication . Бойченко, Катерина; Mata, Mário Nuno; Mata, Pedro; Martins, Jessica NunesThe purpose of this study is to determine the mutual influence of financial security on the textile enterprises development level. The proposed methodological approach is based on the formation of an integrated financial security indicator and its regression model. The study is based on 16 textile enterprises in the European Union. Integral indicators on capital structure, current financing sufficiency and financial efficiency of the investigated enterprises have been defined according to the rapid diagnostics of financial provision of the textile enterprises. The state of financial support for the studied companies’ development has been evaluated. It has been established that the development of textile enterprises depends to a large extent on their financial support as a whole. The change in the development level of companies depends substantially on the change in the integrated indicator of their financial provision. In particular, textile enterprises’ development is significantly affected by the capital structure and the predominance of equity in it, as well as current financing. The financial efficiency factors taken into account do not have a significant impact on the development of textile enterprises. This study proposes a financial security model, developed by partial integrated indicators. It enables visual comparison, collation of the capital structure state, current financing and financial efficiency of the studied enterprises with optimal value
- The role of self-esteem, optimism, deliberative thinking and self-control in shaping the financial behavior and financial well-being of young adultsPublication . Hashmi, Fatima; Aftab, Hira; Moleiro Martins, José; Mata, Mário Nuno; Qureshi, Hamza Ahmad; Abreu, António; Mata, PedroThe sustainable financial behavior and financial well-being have been a key concern among the developing societies; thereby encompassing the various psychological factors which play a role in influencing individual’s positive financial behavior and financial well-being, this study is conducted. Research focusing on the psychological aspect of human financial behavior and well-being is scarce, focusing more on the cognitive side such as financial literacy and numeracy. The aim of this research study is to find the role played by the non-cognitive factors such as self-esteem, self-control, optimism and deliberative thinking, in forming the financial behavior and financial well-being of the young adults. A sample of 429 university students from public and private sector was collected via an online and field survey using purposive sampling technique. The survey contained measures for demographics, self-esteem, optimism, deliberative thinking, self-control, general financial behavior and financial well-being. SPSS and PLS-SEM tools were used for the exploration of the relationships among dependent and independent variables. The results of PLS path analysis demonstrate that among the non-cognitive factors, self-control and deliberative thinking show a significant association with both financial behavior, and financial security. Self-esteem plays no significant role in forming the financial behavior of the young adults when all the variables are taken together but it exhibits a significant association with financial well-being (financial security and financial anxiety). Optimism on the other hand exhibits no significant association with both financial behavior and financial well-being (financial security and financial anxiety). The results of this study complement the previous studies and also put forth new outcomes. This research is unique as it is the first of its kind conducted in a consumption-oriented economy like Pakistan. In addition to the previous studies which have often established the link of self-esteem with general well-being, this study goes further by analyzing the association between self-esteem and financial well-being and by the identification of the role played by non-cognitive factors like self-esteem, optimism, deliberative thinking and self-control together on the financial behavior and financial well-being of the individuals using PLS-SEM approach.
- Systemic acquired critique of credit card deception exposure through machine learningPublication . Dantas, Rui; Firdaus, Raheela; Jaleel, Dr. Farrokh; Mata, Pedro; Mata, Mário Nuno; Li, GangA wide range of recent studies are focusing on current issues of financial fraud, especially concerning cybercrimes. The reason behind this is even with improved security, a great amount of money loss occurs every year due to credit card fraud. In recent days, ATM fraud has decreased, while credit card fraud has increased. This study examines articles from five foremost databases. The literature review is designed using extraction by database, keywords, year, articles, authors, and performance measures based on data used in previous research, future research directions and purpose of the article. This study identifies the crucial gaps which ultimately allow research opportunities in this fraud detection process by utilizing knowledge from the machine learning domain. Our findings prove that this research area has become most dominant in the last ten years. We accessed both supervised and unsupervised machine learning techniques to detect cybercrime and management techniques which provide evidence for the effectiveness of machine learning techniques to control cybercrime in the credit card industry. Results indicated that there is room for further research to obtain better results than existing ones on the basis of both quantitative and qualitative research analysis.
- Does Indian commodity futures markets exhibit price discovery? An empirical analysisPublication . Pani, Upananda; Gherghina, Ştefan Cristian; Mata, Mário Nuno; Ferrão, Joaquim; Mata, PedroPrice discovery function analyses the dynamics of futures and spot price behavior in an asset’s intertemporal dimensions. The present study examines the price discovery function of the bullion, metal, and energy commodity futures and spot prices through the Granger causality and Johansen–Juselius cointegration tests. The Granger causality test results show bidirectional causality between the spot and futures returns for gold, silver, aluminum, lead, nickel, and zinc. The Johansen cointegration test shows that spot and futures prices are in the long-run equilibrium path for silver, aluminum, lead, nickel, zinc, crude oil, and natural gas. The vector error correction model results suggest that both the spot and futures markets are equally efficient in price discovery for the nickel. The spot market leads the futures market in price discovery for copper and zinc. However, the futures market leads the spot market in price discovery for silver, aluminum, and lead. ,e findings of the study suggest the market participants for implementing hedging and arbitrage strategies. It also helps the market regulators to examine the stability of these rapidly growing commodity futures markets in India.
- Assessing the Impact of Green Hiring on Sustainable Performance: Mediating Role of Green Performance Management and CompensationPublication . Moleiro Martins, José; Aftab, Hira; Mata, Mário Nuno; Majeed, Muhammad Ussama; Aslam, Sumaira; BATISTA, Anabela; Mata, PedroThe global need to preserve ecology has propelled the green movement across the globe. An emerging managerial challenge for all organizations is to protect natural resources by reducing their negative impact on the environment and increase sustainable performance. Greening is the need of the age to conserve natural resources. This study investigates the impact of green human resource management practice—i.e., green hiring—on the sustainable performance of public and private healthcare organizations. A quantitative research approach was used for data collection. Scale survey of 160 responses was gathered from public and private healthcare organizations. Partial least square–structural equation modeling was used for data analysis. The study results suggest that green recruitment has a positive and significant impact on environmental performance, economic performance, and social performance. Path coefficients test also revealed that green performance management and compensation significantly mediate the relationship between green hiring and sustainable performance of public and private healthcare organizations. This study is helpful for organizations in adapting GHRM practices that will benefit the organizations in all ways. This study also provides a better understanding to policymakers on how to promote GHRM practices and increase sustainability in organizations
- Perceived Green Human Resource Management Practices and Corporate Sustainability: Multigroup Analysis and Major Industries PerspectivesPublication . Jamal, Tauseef; Zahid, Muhammad; Moleiro Martins, José; Mata, Mário Nuno; Ur Rahman, Haseeb; Mata, PedroThe substantial focus on achieving corporate sustainability has necessitated the implementation of green human resource management (GHRM) practices. The purpose of this paper is to reveal the industries’ perspective of the impact of GHRM practices (i.e., green recruitment and selection, green pay and rewards, and green employee involvement and green training) on corporate sustainability practices. Data were collected from 200 human resource professionals in major industrial sectors of a developing country. Partial least squares structural equation modelling was used to test the study hypotheses and multigroup analysis (MGA) between industrial sectors. The findings show a positive impact of three GHRM practices, i.e., green recruitment and selection, green pay and rewards, and green employee involvement on corporate sustainability. However, green training has no significant association with corporate sustainability, which is interesting. Furthermore, the multigroup analysis (MGA) revealed partial and significant differences among different sectors. The results provide more contextualized social, environmental, and economic implications to academics and practitioners interested in green initiatives. To date, limited research has been conducted to investigate whether GHRM practices can be an effective strategy in increasing corporate sustainability in a developing country context. Particularly, the industry’s perspective on the subject matter was rather absent in the existing literature. The present study fills this gap and contributes to the existing literature by providing the industry’s perspective on GHRM and corporate sustainability.
- Sustainable model: recommendations for water conservation strategies in a developing country through a psychosocial wellness programPublication . Aslam, Sumaira; Aftab, Hira; Moleiro Martins, José; Mata, Mário Nuno; Qureshi, Hamza Ahmad; Adriano, Ana Maria; Mata, PedroHuman industrial activities are bringing physiochemical changes to the land, air, and seas and leading towards more uncertain climate changes, like drought, thunderstorms, and heat waves. This has resulted in water scarcity because of overexploitation of water resources. It is therefore imperative to develop effective conservation programs that consider the factors that affect the decisions of people with regard to water conservation and sustainable activities. This study considered the perspective of a developing country and explored the impact of three psychosocial factors, i.e., subjective happiness, perceived stress, and personal well-being, on individuals’ current and future intentions to conserve water. A sample of 304 respondents was collected via a self-administered questionnaire containing measures of demographic characteristics, psychological factors, and current and future water conservation behavior. The data were collected online as well as through hard copies. Correlational analysis showed that the three psychosocial factors had significant associations with both current and future intentions to conserve water. Furthermore, the effect size (f2) demonstrated that personal well-being was a significant predictor of current and future water conservation behavior. Stress, however, did not serve as a significant predictor of either current or future water conservation behavior. In contrast, subjective happiness was a significant predictor of only future water conservation behavior.
- A machine learning framework towards bank telemarketing predictionPublication . KOUMETIO TEKOUABOU, Stéphane Cédric; Gherghina, Ştefan Cristian; TOULNI, Hamza; Mata, Pedro; Mata, Mário Nuno; Moleiro Martins, JoséThe use of machine learning (ML) methods has been widely discussed for over a decade. The search for the optimal model is still a challenge that researchers seek to address. Despite advances in current work that surpass the limitations of previous ones, research still faces new challenges in every field. For the automatic targeting of customers in a banking telemarketing campaign, the use of ML-based approaches in previous work has not been able to show transparency in the processing of heterogeneous data, achieve optimal performance or use minimal resources. In this paper, we introduce a class membership-based (CMB) classifier which is a transparent approach well adapted to heterogeneous data that exploits nominal variables in the decision function. These dummy variables are often either suppressed or coded in an arbitrary way in most works without really evaluating their impact on the final performance of the models. In many cases, their coding either favours or disfavours the learning model performance without necessarily reflecting reality, which leads to over-fitting or decreased performance. In this work, we applied the CMB approach to data from a bank telemarketing campaign to build an optimal model for predicting potential customers before launching a campaign. The results obtained suggest that the CMB approach can predict the success of future prospecting more accurately than previous work. Furthermore, in addition to its better performance in terms of accuracy (97.3%), the model also gives a very close score for the AUC (95.9%), showing its stability, which would be very unfavourable to over-fitting.
- Optimisation of time-varying asset pricing models with penetration of value at risk and expected shortfallPublication . Nasir, Adeel; Khan, Kanwal Iqbal; Mata, Mário Nuno; Mata, Pedro; Martins, Jéssica NunesThis study aims to apply value at risk (VaR) and expected shortfall (ES) as time-varying systematic and idiosyncratic risk factors to address the downside risk anomaly of various asset pricing models currently existing in the Pakistan stock exchange. The study analyses the significance of high minus low VaR and ES portfolios as a systematic risk factor in one factor, three-factor, and five-factor asset pricing model. Furthermore, the study introduced the six-factor model, deploying VaR and ES as the idiosyncratic risk factor. The theoretical and empirical alteration of traditional asset pricing models is the study’s contributions. This study reported a strong positive relationship of traditional market beta, value at risk, and expected shortfall. Market beta pertains its superiority in estimating the time-varying stock returns. Furthermore, value at risk and expected shortfall strengthen the effects of traditional beta impact on stock returns, signifying the proposed six-factor asset pricing model. Investment and profitability factors are redundant in conventional asset pricing models.