Endogeneity bias can lead to inconsistent estimates and incorrect inferences, which may provide misleading conclusions and inappropriate theoretical interpretations. Sometimes, such bias can even ...lead to coefficients having the wrong sign. Although this is a long-standing issue, it is now emerging in marketing and management science, with high-ranked journals increasingly exploring the issue. In this paper, we methodologically demonstrate how to detect and deal with endogeneity issues in panel data. For illustration purposes, we used a dataset consisting of observations over a 15-year period (i.e., 2002 to 2016) from 101 UK listed companies and examined the direct effect of R&D expenditures, corporate governance, and firms' characteristics on performance. Due to endogeneity bias, the result of our analyses indicates significant differences in findings reported under the ordinary least square (OLS) approach, fixed effects and the generalized method of moments (GMM) estimations. We also provide generic STATA commands that can be utilized by marketing researchers in implementing a GMM model that better controls for the three sources of endogeneity, namely, unobserved heterogeneity, simultaneity and dynamic endogeneity.
•This article emphasizes endogeneity bias can lead to inconsistent estimates and incorrect inferences.•We methodologically demonstrate how to detect and deal with endogeneity issues in panel data.•We provide generic STATA commands that can be utilized by marketing researchers in implementing a GMM model.
This paper examines the relationship between sustainability targets and their impacts on corporate environmental innovation. Using data over the period 2009-2018 on 202 companies from BRICS ...countries, covering firm-level governance, social responsibility and sustainability this paper examines firm-level sustainability targets, and incentives encourage managers to engage in more environmentally friendly activities. Using panel data probit regression, and after controlling for country-level governance and institutional factors, the study finds that embedding environmental targets in corporate strategy does encourage corporate managers to design and develop eco-friendly products and services, and such firm-level commitments at the top motivates managers to promote, market, and label environmentally friendly products. The findings call for greater emphasis on aligning executive compensation with sustainability targets rather than focusing too much on short-term accounting and market-based measures of firm performance.
•We explore how sustainability related target impacts on corporate environmental innovation.•202 companies' data is collected for BRICS countries between 2009 and 2018.•Panel data Probit estimation was employed to assess likelihood of environmental innovation.•Environmental targets in corporate strategy does encourage corporate managers in developing eco-friendly products.•More companies should be encouraged to include environmental targets in executive compensation.
Trojan Detection—the process of understanding the behaviour of a suspicious file has been the talk of the town these days. Existing approaches, e.g., signature-based, have not been able to classify ...them accurately as Trojans. This paper proposes TrojanDetector—a simple yet effective multi-layer hybrid approach for Trojan detection. TrojanDetector analyses every downloaded application and extracts and correlates its features on three layers (i.e., application-, user-, and package layer) to identify it as either a benign application or a Trojan. TrojanDetector adopts a hybrid approach, combining static and dynamic analysis characteristics, for feature extraction from any downloaded application. We have evaluated our scheme on three publicly available datasets, namely (i) CCCS- CIC-AndMal-2020, (ii) Cantagio-Mobile, and (iii) Virus share, by using simple yet state-of-the-art classifiers, namely, random forest (RF), decision tree (DT), support vector machine (SVM), and logistic regression (LR) in binary—class settings. SVM outperformed its counterparts and attained the highest accuracy of 96.64%. Extensive experimentation shows the effectiveness of our proposed Trojan detection scheme.
Smart cities assure the masses a higher quality of life through digital interconnectivity, leading to increased efficiency and accessibility in cities. In addition, a huge amount of data is being ...exchanged through smart devices, networks, cloud infrastructure, big data analysis and Internet of Things (IoT) applications in the various private and public sectors, such as critical infrastructures, financial sectors, healthcare, and Small and Medium Enterprises (SMEs). However, these sectors require maintaining certain security mechanisms to ensure the confidentiality and integrity of personal and critical information. However, unfortunately, organizations fail to maintain their security posture in terms of security mechanisms and controls, which leads to data breach incidents either intentionally or inadvertently due to the vulnerabilities in their information management systems that either malicious insiders or attackers exploit. In this paper, we highlight the importance of data breaches and issues related to information leakage incidents. In particular, the impact of data breaching incidents and the reasons contributing to such incidents affect the citizens' well-being. In addition, this paper also discusses various preventive measures such as security mechanisms, laws, standards, procedures, and best practices, including follow-up mitigation strategies.
ABSTRACT
BACKGROUND & OBJECTIVE: Students reading strategies strongly influence their academic performance. Our study aimed to determine medical students' metacognitive awareness during reading ...strategies and its relation with their academic scores.
METHODOLOGY: Study was done among third year MBBS students of Aziz Fatima Medical College Faisalabad. Students previous years academic achievement information was collected and they also filled questionnaire on metacognition regulation by the Metacognitive Awareness Reading Strategies Inventory. Convenient sampling was used for this study. The data were analyzed in SPSS 20. In our study the independent variable was metacognitive score while previous professional examination marks were taken as the dependent variable.Standard deviation and mean were used for the descriptive data. For categorical data, percentage and frequencies were used.
RESULTS:
Different reading strategies employed by medical students in relation to metacognition were our main focus in the study. Metacognition was taken as score measured by a 30 item MARSI scale and their academic performance measured in terms of total marks obtained in the last professional examination held by the University. Total 101 out of 110 students from 3rd year MBBS class were enrolled in the study and the response rate was 92%. Forty one (41) respondents were females and sixty (60) respondents were male the mean± SD age of students was 21.05±0.74.
CONCLUSION: All dimensions of metacognition are positive and strongly correlated with each other’s. Higher the score in one dimension will cause positive change in other dimension score and vice versa.
Cryptojacking is a type of computer piracy in which a hacker uses a victim’s computer resources, without their knowledge or consent, to mine for cryptocurrency. This is made possible by new ...memory-based cryptomining techniques and the growth of new web technologies such as WebAssembly, allowing mining to occur within a browser. Most of the research in the field of cryptojacking has focused on detection methods rather than prevention methods. Some of the detection methods proposed in the literature include using static and dynamic features of in-browser cryptojacking malware, along with machine learning algorithms such as Support Vector Machine (SVM), Random Forest (RF), and others. However, these methods can be effective in detecting known cryptojacking malware, but they may not be able to detect new or unknown variants. The existing prevention methods are shown to be effective only against web-assembly (WASM)-based cryptojacking malware and cannot handle mining service-providing scripts that use non-WASM modules. This paper proposes a novel hybrid approach for detecting and preventing web-based cryptojacking. The proposed approach performs the real-time detection and prevention of in-browser cryptojacking malware, using the blacklisting technique and statistical code analysis to identify unique features of non-WASM cryptojacking malware. The experimental results show positive performances in the ease of use and efficiency, with the detection accuracy improved from 97% to 99.6%. Moreover, the time required to prevent already known malware in real time can be decreased by 99.8%.
The exponential growth of the Internet of Things (IoT) has led to the rapid expansion of interconnected systems, which has also increased the vulnerability of IoT devices to security threats such as ...distributed denial-of-service (DDoS) attacks. In this paper, we propose a machine learning pipeline that specifically addresses the issue of DDoS attack detection in IoT networks. Our approach comprises of (i) a processing module to prepare the data for further analysis, (ii) a dynamic attribute selection module that selects the most adaptive and productive features and reduces the training time, and (iii) a classification module to detect DDoS attacks. We evaluate the effectiveness of our approach using the CICI-IDS-2018 dataset and five powerful yet simple machine learning classifiers-Decision Tree (DT), Gaussian Naive Bayes, Logistic Regression (LR), K-Nearest Neighbor (KNN), and Random Forest (RF). Our results demonstrate that DT outperforms its counterparts and achieves up to 99.98% accuracy in just 0.18 s of CPU time. Our approach is simple, lightweight, and accurate for detecting DDoS attacks in IoT networks.
This paper explores the relationship between corporate social responsibility, corporate innovation, and corporate performance in developing countries. Firm level governance and corporate social ...responsibility data for 150 companies from 12 developing countries were collected from Datastream and Bloomberg for 2014–2019. The results show that in the context of developing countries there is no significant relationship between corporate social responsibility and corporate innovation. Our findings raise concerns about the level of R&D investments and commitment to corporate social responsibilities in developing economies.
In developing countries, like Pakistan, the pursuit of urbanization and economic development disrupts the delicate ecosystem, resulting in additional biogeochemical emissions of heavy metals into the ...human habitat and posing significant health risks. The levels of these trace elements in humans remain unknown in areas at higher risk of pollution in Pakistan. In this investigation, selected trace metals including Copper (Cu), Chromium (Cr), Lead (Pb) Cadmium (Cd), Cobalt (Co), Nickel (Ni), and Arsenic (As) were examined in human hair, urine, and nail samples of different age groups from three major cities (Muzaffargarh, Multan, and Vehari) in Punjab province, Pakistan. The results revealed that the mean concentrations (ppm) of Cr (1.1) and Cu (9.1) in hair was highest in Muzaffargarh. In urine samples, the mean concentrations (μg/L) of Co (93), As (79), Cu (69), Cr (56), Ni (49), Cd (45), and Pb (35) were highest in the Multan region, while As (34) and Cr (26) were highest in Vehari. The mean concentrations (ppm) of Ni (9.2), Cr (5.6), and Pb (2.8), in nail samples were highest in Vehari; however, Multan had the highest Cu (28) concentration (ppm). In urine samples, the concentrations of all the studied metals were within permissible limits except for As (34 µg/L) and Cr (26 µg/L) in Vehari. However, in nail samples, the concentrations of Ni in Multan (8.1 ppm), Muzaffargarh (9 ppm), Vehari (9.2 ppm), and Cd (3.69 ppm) in Muzaffargarh exceeded permissible limits. Overall, the concentrations of metals in urine, nail, and hair samples were higher in adults (39-45 age group). Cr, Cu, and Ni revealed significantly higher concentrations of metals in hair and water in Multan, whereas As in water was significantly (
< 0.001) correlated with urinary As in Multan, indicating that the exposure source was region-specific.
Motivated by recent inconclusive debates on the natural resource ‘curse’ phenomenon, this paper reviews studies that have explored the causes and implications of natural resource endowments ‘curse’ ...within oil-rich developing countries (ODCs). Most of these studies find corruption, transparency, accountability, weak institutions and poor governance as causes of developing countries’ natural resource ‘curse’. However, recent studies identify a strong association between oil and gas multinational corporations (MNCs) as agents of globalisation and the resource-curse. First, we consider the international dimensions of this relationship and how MNCs have an influence on the resources of ODCs. Second, we link the impact of MNCs and their natural resource nexus to broaden debates on strategic organisational practices. We show that globalisation creates the platform for the natural resource ‘curse’ phenomenon. Our findings offer new insights into the natural resource ‘curse’ debates. We expand knowledge on the traditional focus of the resource-curse literature to include globalisation and how ethical practices of MNCs could avert the ‘curse’ or allow ODCs to experience the advantages of their natural resource wealth.
•We review literature on causes and implications of the natural resource curse (NRC).•We show that MNCs create the platform for the NRC.•Key determinants include corruption, transparency, accountability, weak institutions and poor governance.
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