Sage Journals: Discover world-class research

Abstract

The academic performance of faculty members, as reflected by their research productivity and quality, is a crucial factor in determining aninstitution’s reputation and ranking. However, research productivity varies across academic disciplines and is influenced by multiple factors. In this study we investigate the impact of the academic discipline on research productivity and quality among faculty members in the School of Arts and Sciences at the Lebanese American University, and explore potential factors that could affect their research productivity. We measure research productivity and quality using indicators such as publication count, publication pattern preferences, and average number of citations per publication. Additionally, we assess the effects of individual, institutional and occasional factors on research productivity through a questionnaire distributed to faculty members. Our findings indicate that faculty members in hard disciplines tend to be more productive and have more cited works than their counterparts in soft disciplines, but both groups target top journals at similar rates. Furthermore, international collaboration is a significant predictor of advanced research productivity in hard disciplines. Additionally, both groups agree that teaching loads can limit the time available for research and that the research funding and equipment should be improved. Finally, we note the COVID-19 lockdown and the economic crisis in Lebanon have decreased research activity among faculty members in hard disciplines.

Keywords

research productivity academic discipline hard disciplines soft disciplines individual factors institutional factors

Introduction

The productivity and quality of research serve as crucial indicators of academic performance for universities, and form a significant basis for university rankings. In order to make continuous progress at the national, regional and global levels, universities are increasingly focusing on building their capacities to improve the quantity and quality of research, and encouraging their faculty to maintain a constant level of activity (Brew et al., 2016). As a result, higher education institutions are implementing various measures to increase research productivity, such as offering incentives in the form of promotions, teaching relief, reward systems and research funding (Braxton et al., 2002; Edgar & Geare, 2013; Jung, 2012).

To assess the research productivity of an academic institution, a quantitative approach is commonly used that involves measuring the number of publications including peer-reviewed journal articles (Akbaritabar et al., 2018; Butler, 2003), books/book chapters and conference proceedings (Heng et al., 2020; Khuram et al., 2022). Bibliometrics, such as number of citations, average citations per publication (Agarwal et al., 2016; Carpenter et al., 2014; Leydesdorff & Shin, 2011) and the journal quartile indicators ranging from Q1 (highest) to Q4 (lowest) (Bornmann et al., 2013; Chinchilla-Rodríguez et al., 2016; Miranda & Garcia-Carpintero, 2019), are also used to assess the quality of research. In this study, we have adopted these criteria to evaluate the productivity and quality of research in our the academic institution.

Research productivity varies across academic disciplines, with hard disciplines such as natural sciences, computer science, mathematics and bioinformatics, exhibiting higher research output than soft disciplines such as social sciences, humanities, communication arts and languages (Heng et al., 2020; Jung, 2012; Kyvik, 2003). The publication pattern preferences also differ between disciplines, with researchers in hard disciplines publishing mainly in prestigious journals, while academics in soft disciplines prefer books (Nguyen, 2015). Collaboration and co-authorship are more prevalent in hard disciplines, and positively correlate with higher research productivity (Abramo et al., 2009; Jung, 2012; Kyvik, 2003). In addition, various factors can differentially influence research productivity across disciplines (Brew et al., 2016; Heng et al., 2020; Jung, 2012; Kwiek, 2018; Oancea, 2013; Opesanwo & Simisaye, 2017; Shin & Cummings, 2010), including individual and institutional factors (Armijos Valdivieso et al., 2022; Bland et al., 2006; Heng et al., 2020; Jung, 2012; Kwiek, 2016; Teodorescu, 2000). Individual factors include age, gender, academic rank, and self-efficacy (Heng et al., 2020; Nguyen, 2015), while institutional factors refers to the research policies and strategies that support academic research including reward systems, academic promotion, research funds and resources, post-graduate training, teaching load and relief, and opportunities for research collaboration (Nguyen, 2015; Quimbo & Sulabo, 2014).

For several decades, the assessment of research productivity and the factors that affect it in higher education institutions have been crucial for various reasons. One reason is the need for comparative rankings of academic institutions, which reflect their academic performance and reputation, and ultimately influence students’ choices of universities (Bowman & Bastedo, 2009). Moreover, it helps academic administrators identify gaps that may be hindering the institution’s research output and inspires them to develop more robust research infrastructure and strategies to promote institutional growth and evolution (Bastedo & Bowman, 2011; Jameel & Ahmad, 2020b). Therefore, numerous studies have investigated the productivity and quality of research in different higher education institutions worldwide, including schools in developed and developing countries, by examining the impact of academic discipline and other critical individual and institutional factors (Abouchedid & Abdelnour, 2015; Brew et al., 2016; Heng et al., 2020; Jameel & Ahmad, 2020a; Jung, 2012; Khalil & Khalil, 2019; Opesanwo & Simisaye, 2017; Quimbo & Sulabo, 2014; Shin & Cummings, 2010). In comparison to the rest of the world, the Arab region has low research productivity due to multiple socioeconomic and political crises that significantly affect the productivity and quality of research (Almansour, 2016). Additionally, only a few studies have been conducted to compare research productivity in Arab countries, including Lebanon (Abouchedid & Abdelnour, 2015; El Rassi et al., 2018; Gul et al., 2015), or to assess factors influencing research productivity in specific Arab academic institutions and schools (Dakik et al., 2006; Jameel & Ahmad, 2020a; Khalil & Khalil, 2019; Rachid et al., 2021).

In this present study, our objective is to evaluate the impact of the academic discipline on the productivity and the level of research, and to identify other variables that may influence research productivity across disciplines, specifically in the School of Arts and Sciences (SoAS) at the Lebanese American University (LAU) over a 2-year period (2020–2021). LAU is a private, not for profit American-chartered university located in a developing country, ranked in in the 501 to 600 bracket out of 1,800 universities worldwide, and is ranked as the second-best university in Lebanon according to the Times Higher Education (THE) World University Rankings 2023. The SoAS encompasses various fields belonging to both the hard disciplines in the natural sciences, computer science and mathematics departments, and the soft disciplines in the social sciences and education, communication arts, and languages departments. This study aims to identify factors that may positively or negatively affect research productivity in each discipline, thereby identifying areas of improvement and potential gaps, to enhance the quantity and quality of research output in the school and improve the university’s performance on a larger scale.

Theoretical Background and Goals of the Study

Numerous studies have explored the factors that impact the research productivity of academics as it serves as a key indicator of the overall academic performance of higher education systems. Individual factors such as age, gender, academic rank, and research activity status, as well as institutional characteristics such as the reward system, funding, time spent on research, local and international collaboration, and post-graduate training, have been identified as efficient predictors of research productivity. However, it should be noted that the impact of these factors varies by discipline, with research productivity differing depending on disciplinary background, particularly between hard and soft sciences (Becher & Trowler, 2001; Jung, 2012; Linton et al., 2012; Pepe & Kurtz, 2012). This variation in research productivity across disciplines can be attributed to academic reasons such as differences in theory and research methods, research topics, publication patterns, and the time needed to publish (Agnew, 2013; Becher & Trowler, 2001). Additionally, the possibility of collaboration and co-authorship may be more prevalent in hard sciences than in soft sciences disciplines is shown to be probably more frequent in hard sciences than in soft sciences disciplines (Abramo et al., 2009; Jung, 2012). The teaching load has also been shown to have both positive and negative effects on research productivity in both disciplines, as it can engage academics more in research in some cases, particularly in soft sciences, while reducing the time spent on research in others, particularly in hard sciences (Ramsden & Moses, 1992; Teodorescu, 2000). While numerous studies have evaluated the research productivity of universities as a whole or limited to certain disciplines, only a few have examined and compared predictors of research productivity across disciplines. This approach is crucial in assessing the influence of factors in each discipline (Wanner et al., 1981) nd developing specific measures to enhance research productivity across disciplines, thereby boosting it throughout the entire institution. Findings from different studies investigating the influence of factors on research productivity cannot be generalized due to several reasons, including location, institution size, university by-laws (Nguyen, 2015), different departments, and sample size (Almansour, 2016; Gul et al., 2015; Jameel & Ahmad, 2020a). Furthermore, the special circumstances of each case study, such as the security situation of the studied country and the relevant period of time, may affect research productivity. For instance, the economic crisis and the COVID-19 pandemic have had an impact on research productivity in various institutions (Nocco et al., 2021; Shehatta et al., 2023)

Based on the previous literature and to the best of our knowledge, we conclude that:

Only a few studies have assessed research productivity and its predictors in Arab countries, and these are limited to some disciplines (Abouchedid & Abdelnour, 2015; El Rassi et al., 2018; Jameel & Ahmad, 2020a; Khalil & Khalil, 2019; Rachid et al., 2021),

Despite the robust role of individual and institutional factors in predicting research productivity in higher academic institutions, the positive, negative, or neutral effect of each factor cannot be generalized to all disciplines and institutions. For example, while some studies indicated a positive effect of collaboration and co-authorship on research productivity(Abramo et al., 2011; Ductor, 2015; Kato & Ando, 2013), another study found that collaboration does not impact research output (Ynalvez & Shrum, 2011). n addition, one study indicated that research productivity is enhanced only by international collaboration but not with local collaboration (He et al., 2009), contradicting another finding that local collaboration positively impacted research productivity (Abramo et al., 2017).

The purpose of this study is to evaluate and compare the research productivity and quality of the hard and soft disciplines in the Faculty of Arts and Sciences at the Lebanese American University, a leading university in the Arab region. Additionally, we will investigate the impact of individual, institutional, and occasional factors on research productivity in both disciplines. The results of this study will be used to redirect the university’s research policy based on the effect of each of the studied factors. This study will address the following questions, and the study model is presented in Figure 1:

Q1: Do the research productivity and quality of research differ between the hard and soft disciplines in the School of Arts and Sciences at the Lebanese American University

Figure 1.

Model of the study.

To answer this question:

First, we will compare the number of publications in indexed journals, books, and conference proceedings, as research output is a reliable predictor of research productivity (Jung, 2012; Nguyen, 2015; Teodorescu, 2000).

Second, we will compare the number of publications in different publication patterns and classify them based on whether they were published in Q1, Q2, Q3, or Q4 journals, books, or conference proceedings, as this approach is commonly used to assess research quality (Alamah et al., 2023; Bornmann et al., 2013; Chinchilla-Rodríguez et al., 2016; Miranda & Garcia-Carpintero, 2019; Shehatta et al., 2023).

Third, we will compare the number of citations per publication and their source, including whether they were extracted from Q1, Q2, Q3, or Q4 journals, books, or conference proceedings, as citations are a robust indicator of research quality(Alamah et al., 2023; Linton et al., 2012; Miranda & Garcia-Carpintero, 2019; Mryglod et al., 2013; Pepe & Kurtz, 2012).

Q2: Since research output and citation counts differ between the two disciplines, we will investigate the influence of individual, institutional, and occasional factors on research productivity for each discipline.

To address this question, we administered a questionnaire to faculty members in the relevant disciplines. The questionnaire contains direct inquiries about academic affiliation, academic rank, age, and gender (individual factors), as well as collaboration, teaching load, other occupations, reward system, research funding, research equipment, post-graduate training, and post-doctoral research fellow involvement (institutional factors). We also included questions regarding the impact of the COVID-19 pandemic and the Lebanese economic crisis (occasional factors) during 2020 and 2021. Responses were anonymous and recorded separately for faculty members in each discipline. We collected the percentage for each answer and conducted a comparative descriptive analysis based on faculty responses, as well as a regression analysis.

Data and Methodology

Disciplines

In this study, we take the case of the Lebanese American University (LAU), and focused especially on the School of Arts and Sciences (SoAS), one of the leading schools in high research activity, including its four departments: natural sciences, computer science and mathematics, social sciences and education, and communication arts and languages. In order to investigate the impact of the academic discipline on the productivity and the quality of research in the SoAS, we adopted the classification of the different disciplines into two general categories: the hard disciplines and the soft disciplines (Jung, 2012; Kyvik, 2003). The hard disciplines include both departments of natural sciences and computer science and mathematics, including the following sub-disciplines; biology, chemistry, biochemistry, physics, nutrition and food sciences, environmental toxicology, mathematics, computer science and bioinformatics. The soft disciplines include both departments of social sciences and education, and communication arts and languages, including the following sub-disciplines; education, English, Arabic studies, psychology, journalism, multimedia, communication arts, political sciences, philosophy, gender studies, film, theater, dance, and performing arts.

Data

To conduct our study, we considered the publications collected from LAU database for the faculty members assigned to the SoAS. Among them 38 members are affiliated to the hard disciplines and 38 members are affiliated to the soft disciplines, during the 2 years 2020 and 2021. This period coincides with the outbreak of COVID-19 pandemic and coexists with the ongoing Lebanese economic crisis, witnessing the worst decline in the levels of the Lebanese pound against the US dollar. We concluded to exclude the ongoing year to remove any inconsistency factor in the results, as the study began in mid-2022 and is not yet finished, and data collection needs constant updating.

The concerned faculty are the assistant, associate, and full professors, excluding part-timers and lecturers, because altogether most of them are engaged in teaching with no or reduced research activity (Jung, 2012).

The types of publication and publication venues considered in this study include the indexed journals (Q1, Q2, Q3, and Q4), conference proceedings and books (Alamah et al., 2023; Bornmann et al., 2013; Chinchilla-Rodríguez et al., 2016; Miranda & Garcia-Carpintero, 2019; Shehatta et al., 2023).

Data Analysis

Comparison of the Research Output in Both Disciplines

Since the research output is a robust indicator of the research productivity, we compared the total number of publications in both disciplines during 2020 and 2021. To investigate the significance of the research productivity, we compared the average of publication/year between the two disciplines using the statistical unpaired/two-tailed t-test to determine if there was a significant difference between the two group means.

Comparison of the Research Quality in Both Disciplines

We compared the quality of research between the two disciplines at both terms; publication pattern preferences (publication venues), and the average number of citations along with the source of citations (their distribution across the different publication patterns). At the first level, we collected data about the publication patterns where the publications were released, and we categorized them as indexed journals and their respective quartiles; Q1, Q2, Q3, and Q4 (based on SCImago Journal Rank (SJR) and Scopus database), conference proceedings and books. We calculated the total percentage of publications in each venue for both disciplines and sub-disciplines, and we compared the average percentage of publications in each publication pattern per year, using the statistical unpaired/two-tailed t-test to determine if there was a significant difference between the two group means.

At the second level, we collected the updated number of citations (until July 2022 -Google Scholar) for each publication in both disciplines, and we collected the total number of citations for each quartile or venue. To compare the differences in quality in terms of citations per venue between the two disciplines, we showed first the difference in the number of citations estimated as average number of citation per publication in both years for each discipline, and we compared the percentage of citations distributed in each quartile or venue for each year, using the statistical unpaired/two-tailed t-test to determine if there was a significant difference between the two group means.

Questionnaire: Factors Influencing the Research Productivity in Both Disciplines

With the intention of investigating what other factors may influence research productivity in both disciplines; we sent a questionnaire reviewed and approved by LAU - Institutional Review Board (IRB) (IRB #: LAU.GSR.SS1.28/Jul/2022), to the relevant faculty members of both disciplines (76 members). The questionnaire was composed of multiple choice questions and was divided into three sections, each comprising different type of factors adopted in previous studies (Heng et al., 2020; Jung, 2012; Nguyen, 2015; Quimbo & Sulabo, 2014). Section 1 represents the individual factors including questions about the academic affiliation, the academic ranking, the age, the gender, the self-efficacy and the engagement in research. Section 2 represents the institutional factors including questions about the research collaboration, the teaching load, other occupations, reward system and the research funding, research equipment, post-graduate training and post-doctoral research fellow’s involvement. In section 3 we aim to add some specific occasional factors regarding the situation in Lebanon between years 2020 and 2021 that may affect research productivity at LAU. These include questions about the impact of the COVID-19 pandemic and the Lebanese economic crisis on the research outputs during the biennium. The answers were anonymous and recorded independently for the faculty members from the two different disciplines. We collected the total percentage for each answer and conducted comparative descriptive analysis based on the faculty responses. Besides, we also addressed a regression analysis where the independent variable was the research output of faculty members during the considered biennium and the independent variables were the followings: academic rank (continuous), age (continuous), gender (dummy with Female = 1 and Male = 0), research activity (continuous), collaboration (continuous), workload (dummy with No = 0 and Yes = 1), other occupation (continuous), reward and funding (continuous), research equipment (continuous), postgraduate training (continuous), postdoc (dummy with No = 0 and Yes = 1), COVID-19 (dummy with No = 0 and Yes = 1) and Lebanese economic crisis (dummy with No = 0 and Yes = 1).

Findings

The Impact of the Academic Discipline on the Productivity of Research

The total number of publications released in 2020 and 2021 was 195 for the hard disciplines (94 publications in 2020 and 101 publications in 2021) and 68 publications for the soft disciplines (43 publications in 2020 and 25 publications in 2021) (Figure 2A). In order to assess the significance of this difference, we compared the means ± SEM of publications in the 2 years (2020–2021) between the hard and the soft disciplines). As shown in Figure 2B, the number of publications/year for the hard disciplines (97.5 ± 3.5) was significantly higher (p = .02) than the number of publications/year for the soft disciplines (34 ± 9). These results showed that the academics in hard discipline were more productive than their colleagues in the soft disciplines. This result reflects the academic discipline direct impact on the research output at LAU-SoAS.

Figure 2.

The impact of the academic discipline on the productivity of research: (a) presentation of the total number of publications for the hard and soft disciplines and (b) average of publications per year (data are expressed as means ± SEM) .

We looked further to the distribution of these publications according to the different sub-disciplines that belong to the hard and the soft disciplines (Figure 3). Concerning the hard disciplines, the computer science major recorded the highest number of publications (n = 76) followed by the biology major (n = 58), the nutrition and food sciences (n = 20), mathematics (n = 12), chemistry (n = 9), bioinformatics (n = 7), biochemistry and physics (n = 5 for each) and the environmental toxicology (n = 3) (Figure 3A). For the soft disciplines, the education and English literature studies recorded the highest number of publications (n = 23), followed by the psychology major (n = 22), the journalism, multimedia and communication arts (19), the political sciences (n = 3) and the performing arts as Film, theater and dance (n = 1). However, no publications were recorded for the Arabic studies, philosophy and gender studies sub-disciplines (Figure 3B). These results showed that the number of publications may also differ according to the sub-disciplines in the same academic discipline.

Figure 3.

Distribution of publications between the different sub-disciplines of the hard disciplines (a) or the soft disciplines (b).

The Impact of the Academic Discipline on the Level of Research in Terms of Publication Patterns

Regardless the number of publications, we aim to investigate the impact of the academic discipline on the quality of research in terms of their distribution in different publication patterns including indexed journals classified into four quartiles (Q1, Q2, Q3, and Q4) previously used to evaluate the research quality for faculty publications (Alamah et al., 2023; El-Zahr, 2022a, 2022b), conference proceedings and books. To do so, data were expressed as percentages of publications distributed in the different publication patterns (Figure 4). According to Table 1, around the half of publications in the hard disciplines (48.2%) were published in Q1 journals, followed by 28.2% published in Q2 Journals, 11.8% published in conference proceedings, 8.7% in Q3 journals, 2.6% in Q4 journals, where only 0.5% were published in books as book chapters. Similarly to the hard disciplines, around the half of publications in the soft disciplines (42.6%) were also published in Q1 journals, followed by 27.9% published in Q2 Journals. However, publications in Q3 journals represent 19.1%, followed by 8.8% published as book chapters, and only 1.5% of publications were published in conference proceedings, and no publications were recorded in Q4 journals (Table 2). These data showed that in both disciplines, the majority of publications are published in Q1 and Q2 journals, with no significant difference between the two disciplines (Figure 4) (p = .58 and p = .98, respectively), along with absence or very low record in the Q4 journals, reflecting the high quality of publications from the LAU-SoAS, regardless of the academic discipline. In addition, conference proceedings clearly make up an important venue for the hard sciences, but not for the soft sciences (p = .09), and vice versa for books (p = .35). Finally, both disciplines published in Q3 journals but to varying degrees (p = .4).

Figure 4.

The impact of the academic discipline on the quality of research in terms of publication patterns. Distribution of publications on different venues; journals (Q1, Q2, Q3, and Q4), conference proceedings and books for the hard and the soft disciplines (data are expressed as the means ± SEM of percentages normalized to the total number of publications for each discipline per year).

Table 1.

Distribution of the Publications From Different Sub-Disciplines of the Hard Disciplines on Different Venues; Journals (Q1, Q2, Q3, and Q4), Conference Proceedings and Books.

Sub-disciplines	Q1	Q2	Q3	Q4	Conference proceedings	Books
Chemistry	2.1	2.1	0.5	0.0	0.0	0.0
Biochemistry	0.5	2.1	0.0	0.0	0.0	0.0
Biology	11.8	12.3	4.1	1.5	0.0	0.0
Nutrition and Food sciences	4.6	4.6	1.0	0.0	0.0	0.0
Environmental Toxicology	0.5	1.0	0.0	0.0	0.0	0.0
Physics	1.5	0.5	0.5	0.0	0.0	0.0
Mathematics	2.1	3.1	0.0	0.0	1.0	0.0
Bioinformatics	2.1	0.0	1.5	0.0	0.0	0.0
Computer Science	22.6	2.6	1.0	1.0	10.8	0.5
Total percentage	48.2	28.2	8.7	2.6	11.8	0.5

Data are expressed as total percentages (%) normalized to the total number of publications during the 2 years (2020 and 2021).

Table 2.

Distribution of the Publications From Different Sub-Disciplines of the Soft Disciplines on Different Venues; Journals (Q1, Q2, Q3, and Q4), Conference Proceedings and Books.

Sub-disciplines	Q1	Q2	Q3	Conference proceedings	Books
Education/English	11.8	4.4	11.8	1.5	4.4
Psychology	14.7	10.3	5.9	0.0	1.5
Journalism/Multimedia/Communication Arts	14.7	10.3	0.0	0.0	2.9
Political Sciences	0.0	2.9	1.5	0.0	0.0
Arabic Studies	0.0	0.0	0.0	0.0	0.0
Philosophy/Gender studies	0.0	0.0	0.0	0.0	0.0
Film, Theater, Dance and performing arts	1.5	0.0	0.0	0.0	0.0
Total percentage	42.6	27.9	19.1	1.5	8.8

Data are expressed as total percentages (%) normalized to the total number of publications during the 2 years (2020 and 2021).

According to Table 1, conference proceedings are strictly targeted by the computer science (10.8%) and mathematics (1%) sub-disciplines (total percentage for conference proceedings is 11.8%), where the books are only targeted by the computer science sub-discipline (0.5% = total percentage for books), and the Q4 journals are only targeted by the computer Science (1%) and the biology (1.5%) sub-disciplines (total percentage for Q4 journals is 2.5%). Q1, Q2, and Q3 journals are almost targeted by all the sub-disciplines (except for bioinformatics where no publication was recorded in Q2 journals and for biochemistry, environmental toxicology and mathematics where no publication was recorded in Q3 journals).

According to Table 2, conference proceedings are strictly targeted by the education and English sub-disciplines (1.5% = total percentage for conference proceedings), where the books are targeted by education and English (4.4%), psychology (1.5%) and journalism, multimedia and performing arts (2.9%), (total percentage for books is 8.8%). Q3 journals are targeted by education and English (11.8%), psychology (5.9%) and political Sciences (1.5%) (total percentage for Q3 journals is 19.1%). Q1 and Q2 journals are almost targeted by all the sub-disciplines (except for political sciences where no publication was recorded in Q1 journals and for film, theater, dance and performing arts where no publication was recorded in Q2 journals).

Overall, these results showed that academic discipline has no direct impact on research quality at LAU-SoAS with respect to the targeted quartiles of journals, but other publications patterns such as books and conference proceedings are more or less preferred depending on the academic discipline and sub-disciplines.

The Impact of the Academic Discipline on the Level of Research in Terms of Citations and Citation Resources

We aim to study the impact of the academic discipline on the quality of research in terms of citations. Regarding that the total number of publications vary widely between the hard (n = 105) and the soft disciplines (n = 68) during the 2 year period (2020 and 2021), we cannot directly compare the number of citations in both disciplines (2,084 citations for the hard disciplines vs. 324 citations for the soft disciplines). Instead, we estimated the number of citations per publication for each discipline by normalizing to the total number of publications for each discipline (Figure 5A). It recorded an average of 10.6 citations per publication for the hard disciplines versus 5.2 citations per publication for the soft disciplines (p = .21). Even if it seems statistically non-significant, these data obviously showed that the hard discipline publications are most probably more cited (>2 fold-factor) than those of the soft disciplines, thus the academic discipline could impact the number of citations at LAU-SoAS.

Figure 5.

The impact of the academic discipline on the quality of research in terms of citations: (a) average of citations per publication per year for the hard and the soft disciplines (data are expressed as the means ± SEM of citations normalized to the total number of publications for each discipline per year). (b) distribution of citations on different venues; journals (Q1, Q2, Q3, and Q4), conference proceedings (data are expressed as the means ± SEM of percentages normalized to the total number of publications for each discipline per year).

Then we aimed to investigate how these citations are distributed on different publication patterns and quartiles, in other words, we searched for the resources of these citations (Figure 5B); the results showed that more than 85% of citations refer to publications released in Q1 and Q2 journals for both the hard (80.8% and 12.4%, respectively) and the soft disciplines (74.1% and 13%, respectively) with no significant difference between both disciplines (p = .62 and p = .89). The rest of citations was distributed between Q3 (3.8%), Q4 (1.5%), conference proceedings (1.3%) and books (0.15%) for the hard disciplines, and between Q3 (11.8%) and books (1.2%) for the soft disciplines, but no citation was recorded for conference papers. These data showed once again that the academic discipline has no direct impact on the quality of research in terms of citation resources at LAU-SoAS.

Overall, these results lead to the conclusion that the academic discipline has a remarkable impact on the productivity of research and citations since we found that the hard disciplines are more productive and their publications are more cited than the soft disciplines at LAU-SoAS. However, the academic discipline has not a direct impact on the quality of research in terms of journal quartiles or the citation resources.

The Influence of Individual, Institutional, and Some Occasional Factors on the Productivity of Research in Both Disciplines

Beside the academic discipline, we investigated other potential factors influencing the research productivity in both disciplines by sending a questionnaire to the faculty members. The responsiveness rate to the questionnaire was 60% and descriptive statistics and regression analysis are summarized in Table 3. It is noteworthy that none of the regression coefficients was significant (p > .05) due to the small sample size but we still mentioned the presence of negative or positive correlation with research productivity in the considered biennium.

Table 3.

Individual, Institutional and Occasional Factors Influencing Research Productivity.

Factors		Hard disciplines		Soft disciplines
Individual factors		%		%
Academic Rank	Assistant professor	22.2	1.3	41.7	−1.3
	Associate professor	72.2		54.2
	Full professor	5.6		4.2
Age (y)	30–40	33.3	0.59	21.7	1.84
	40–50	38.9		21.7
	50–60	22.2		39.1
	>60	5.6		17.4
Gender	Male	55.6	−0.08	45.8	0.67
Gender	Female	44.4	−0.08	54.2	0.67
Research Activity	Research active	100	0	87.5	0.27
Research Activity	Not research active	0	0	12.5	0.27
Institutional factors
Collaboration	Internal and external local collaboration	44.5	0.62	37.5	−0.19
	International and local collaboration	55.6		45.8
	No collaboration	0		16.7
Teaching Load	Decrease time spent on research	72.2	−1.2	69.6	0.25
Teaching Load	Do not affect time spent on research	27.8	−1.2	30.4	0.25
Other Occupation	No occupation	38.9	−2.15	41.7	0.71
	Yes but does not affect time spent on research	27.8	−2.15	25
	Yes and affects time spent on research	33.3		33.3
Reward system and funding	Strongly Satisfied	11.1	−0.91	8.3	−1.08
	Satisfied but could be better	38.9		41.7
	Not satisfied	50		50
Research equipment	Satisfied	55.6	−0.14	54.2	0.38
Research equipment	Not satisfied	44.4	−0.14	45.8	0.38
Post-graduate training	No	27.8	0.21	45.8	−0.23
	Master Students	27.8		50
	PhD students	11.1		0
	Master and PhD students	33.3		4.2
Post-doctoral fellowship	Yes	38.9	−1.31	25	−0.007
Post-doctoral fellowship	No	61.1	−1.31	75	−0.007
Occasional factors
COVID-19 pandemic	Affects research productivity	72.2	−0.82	12.5	−0.37
COVID-19 pandemic	Does not affect research productivity	27.8	−0.82	87.5	−0.37
Lebanese economic crisis	Affects research productivity	88.9	−0.63	33.3	−1.03
Lebanese economic crisis	Does not affect research productivity	11.1	−0.63	66.7	−1.03
R squared			0.783		0.500

Data are represented as percentage of faculty members and regression statistics.

Individual Factors

Associate professors represent the majority of both the hard and the soft disciplines faculty members (∼72% vs. ∼54%, respectively), followed by the assistant professors (∼22% vs. ∼42%, respectively) and the full professors (∼6% vs. ∼4%, respectively). Associate professors are more numerous in the hard disciplines than in the soft disciplines and the opposite is true for the assistant professors and the academic rank is positively correlated with the research productivity in hard disciplines but negatively correlated in soft disciplines. Most of the hard discipline faculty members have an age range between 30 and50 years old (∼72%), whereas the majority of faculty members in soft disciplines were >50 years old (∼57%) where age is positively correlated with research productivity in both disciplines. Males and females are almost equally presented in both disciplines with a slight increase in favor of males in the hard disciplines (∼56%), but the opposite is true in the soft disciplines with females representing ∼54%. Finally, research activity is positively correlated in both disciplines, and all the faculty members in the hard disciplines were research active; however, 13% of the soft disciplines faculty members were not during the considered biennium.

Institutional Factors

All the hard discipline faculty members collaborate to publish either by exclusive local collaboration (∼44%) or by both international and local collaboration (∼56%) with a positive correlation with research productivity; however, around 17% of the soft discipline faculty members have no collaboration at all in research and the rest collaborate locally (∼37%) or both locally and internationally (∼46%) but the collaboration doesn’t show a positive correlation with the research productivity. In both disciplines, faculty members believed that time spent in research is negatively affected by the teaching load (at least 70% of the faculty members) and other administrative occupations (33% of both faculty members) but the regression analysis showed that teaching load and other occupations are negatively correlated with the research productivity in hard sciences only. As well, half of the faculty members agreed that the reward system and findings are not sufficient to enhance research productivity in both disciplines and show negative correlation with research productivity. In addition, almost the half of both faculty members is not satisfied with the research equipment. The contribution of master and PhD students in published works is recorded in 72% of hard discipline faculty members and 54 % of soft discipline faculty members. They are distributed as 28% for master students, 11 % for PhD students and 33 % for both master and PhD students for hard disciplines, and 50% for master students, and only 4.2% for both master and PhD students for soft disciplines. Overall, postgraduate training is positively correlated with the research productivity inn hard sciences only. Postdoctoral research fellows were involved in research activity of ∼ 39% of hard discipline faculty members and 25% of soft discipline faculty members, with negative correlation with research productivity.

Occasional Factors

COVID-19 pandemic and the Lebanese economic crisis strongly affected the research activity of the hard discipline faculty members; around 72% of faculty stated that their research work is experimental done in person and on site and that the imposed lockdown delayed their projects, whereas 28% were not affected since their work can be done remotely or they managed to publish reviews related to the COVID-19 pandemic. As well, around 89% stated that the shortage of materials and reagents due to the economic crisis and the dollar rate fluctuation slowed down the lab work progress and therefore their research productivity. In contrast, COVID-19 pandemic slightly affects the research productivity of the soft discipline faculty members (13% only), since their research work can be done remotely and that they could publish works related to the COVID-19 pandemic. Similarly, they were slightly affected by the economic crisis (33% only) since their discipline didn’t require extensive equipment. In addition, both factors were negatively correlated with the research productivity in both disciplines.

Discussion

Although many universities in the Arab region are currently facing socioeconomic and political crises that hinder their global recognition, they have recognized the importance of both of both individual and institutional factors in building a healthy environment and robust research infrastructure to enhance their research productivity (Abouchedid & Abdelnour, 2015; Almansour, 2016). Research productivity is now widely considered the primary criterion for evaluating universities’ academic performance and is a key indicator for international, regional and national rankings. In this study we aimed to explore the impact of academic discipline on research productivity and quality, and to evaluate the influence of various individual and institutional factors on research productivity trajectory during the years 2020 and 2021 in the School of Arts and Sciences at the Lebanese American University, one of the leading universities in the Arab region and Lebanon.

Our study revealed that the academic discipline had a significant impact, as evidenced by the number of publications produced. Faculty members in hard disciplines published approximatively three times (2.9 fold-factor) more than their counterparts in soft disciplines. These findings are consistent with previous research conducted by Brew et al. (2016) and Heng et al. (2020) (Brew et al., 2016; Heng et al., 2020), which demonstrated that academics in hard disciplines tend to be more productive than those in soft disciplines. Similar results were also found in universities in Hong Kong (Jung, 2012) and North Korea (Shin & Cummings, 2010). Furthermore, faculty members in STEM disciplines (Science, Technology, Engineering, and Mathematics) are more likely to publish than those in non-STEM disciplines in North American universities (Padilla-Gonzalez et al., 2011).

Our study also revealed that publication counts varied across different sub-disciplines within the same discipline. For instance computer science (n = 76), biology (n = 58), nutrition and food sciences (n = 20) were the top performers among hard disciplines, while education and English (n = 23), psychology (n = 22), and communication arts (n = 19) were the top performers among soft disciplines. Other sub-disciplines within the same discipline showed much lower publication counts, ranging from 0 to 12 publications. These results are consistent with another study by Linton et al. (2012) that also demonstrated a wide variance in publication counts within different fields of the same discipline. (Linton et al., 2012). Interestingly, we found that highest number of publications in a discipline was not always due to the highest number of research active faculty members. For example, the chemistry field recorded nine publications and five research active members (∼2 publications per member), while the biology field recorded 58 publications and six research active members (10 publications per member).

At the level of research quality, we found that both disciplines preferred peer-reviewed journals, with the majority of publications appearing in Q1 journals, followed by Q2 and Q3 journals, with few or no publications in Q4 journals. This suggests a high quality of LAU publications regardless of the academic discipline. However, we observed that faculty in hard disciplines, particularly in computer science and mathematics sub-disciplines, publish more in conference proceedings than the faculty in soft disciplines. Conversely, the faculty members in soft sciences, especially in education and English, psychology and communication arts sub-disciplines, tend to publish more book chapters than those in the hard disciplines. This is consistent with previous studies indicating that academics in soft disciplines are more likely to publish in books than those in other disciplines (Heng et al., 2020; Jung, 2012; Nguyen, 2015).

Furthermore, we assessed research quality in terms of citation counts, as citation indicators are considered one of the most important criteria used in research university rankings by the Times Higher Education (Nguyen, 2015). Our results showed that publications in hard disciplines were cited approximately twice as often (∼10 citations per publication) as in soft disciplines (∼5 citations per publication). This difference is not related to publication pattern preferences, as the majority of citations are attributed to papers published in Q1 and Q2 journals in both disciplines.

Research productivity across academic disciplines can be influenced by various factors. To explore this, a questionnaire was sent to faculty members addressing individual, institutional, and occasional factors, and descriptive statistics were analyzed. Regression analysis was conducted, but none of the coefficients showed a significant value (p > .05) due to the small sample size. However, we found that years of experience may play a role in the difference of research productivity between the two disciplines, as associate professors are more numerous in hard disciplines and the opposite is true for assistant professors, with a positive correlation with research productivity in hard disciplines and the opposite in soft disciplines. This may explain the higher research productivity in hard disciplines, where academic rank reflects more research productivity, as shown in other studies (Zhou & Volkwein, 2004). Additionally, experience is often accompanied by more funding for research and enrollment of more students engaged in research, contributing to higher research productivity. Age is positively correlated with research productivity in both disciplines, but faculty members in hard disciplines tend to be younger than those in soft disciplines. Gender disparity exists; with men believed to publish more than women (Aiston & Jung, 2015; Vabø et al., 2014). However, gender is not a major factor causing the difference in research output between the two disciplines, which may be due to other factors. Research status appears to play a major role in research productivity since all academics in hard disciplines stated that they are strongly engaged in research, whereas 13% of the soft discipline academics were either not interested in research or stated that the avenues of research are rare in their discipline. Working load, including teaching and other administrative occupations, decreased time spent on research, showing a negative correlation with research productivity in hard disciplines. Both populations consider that the university research policy, including research equipment and reward system, must be improved to enhance their research productivity. Collaboration is one of the most important factors enhancing research productivity in hard sciences (Abramo et al., 2009; Jung, 2012; Kyvik, 2003) due to the exchange of expertise and innovative ideas, as well as cooperation to achieve research tasks (Smeby & Try, 2005). Due to its remarkable importance, we collected in Appendix A1 (hard disciplines) and A2 (soft disciplines) all the papers published with international collaborations. The data showed that 36% of hard disciplines publications are co-authored with international collaborators versus only 14% recorded for soft disciplines. As well, the collaboration network in hard disciplines is wider than in the soft disciplines, and includes different institutes and universities worldwide located in United Arab Emirates, Iran, United Kingdom, France, Saudi Arabia, Germany, United States, Belgium, South Africa, Switzerland, Czech Republic, Canada, Portugal, Pakistan, India, Spain, Italy, Norway, China, Malaysia, Mexico, and Vietnam. Post-graduate training and post-doctoral research fellows, as well as contributions from master students and doctoral students, seem to be advantageous to the advanced research productivity of hard discipline academics, highlighting the importance of institutional and supervisor support to enhance doctoral students’ academic performance (Khuram et al., 2021). The COVID-19 pandemic and Lebanese economic crisis negatively affected the research productivity of academics in hard disciplines more than those in soft disciplines due to the experimental nature of hard discipline work requiring in-person laboratory work that was prohibited during lockdowns, and the Lebanese economic crisis delaying the acquisition of laboratory equipment and materials. Nonetheless, both occasional factors were negatively correlated with research productivity in both disciplines.

Conclusions

This study aimed to investigate the influence of academic discipline on research productivity and quality among LAU-SoAS academics in both hard and soft disciplines, while also exploring individual, institutional, and occasional factors that could affect research productivity. Our findings clearly indicate that academics in hard disciplines exhibit higher research productivity and citation rates, but both hard and soft disciplines demonstrate comparable quality of research in terms of targeted journal quartiles. We found that conference proceedings are a crucial venue for publishing research in hard disciplines, while books and book chapters are more popular among soft disciplines. In terms of individual factors, associate professors and those under the age of 50 in hard disciplines show more advanced research productivity than their counterparts in soft disciplines. Gender may also play a role in academic research productivity, despite a slight increase in men in hard disciplines and women in soft disciplines. Additionally, hard discipline academics’ absolute research engagement may account for their higher research activity than their colleagues in soft sciences. Regarding the institutional factors, post-graduate training, particularly involving PhD students, is advantageous for research productivity in hard disciplines, while international collaboration networks are one of the major predictors of advanced research productivity in hard disciplines. However, workload and institutional research policy have a negative impact on both hard and soft disciplines’ research engagement, leading to lower research productivity. The COVID-19 pandemic, coupled with the Lebanese economic crisis, has significantly affected hard discipline academics’ research productivity due to laboratory material shortages and lockdowns, while soft discipline academics have been less affected as their work can be done remotely. Although our study has some limitations, such as focusing only on one school and having a moderate response rate to the questionnaire (60%), we performed a comparative descriptive analysis based on the responses of the faculty members and the coefficients of correlation. Despite these limitations, our study identifies several factors positively correlated with department research productivity, such as international collaboration, and highlights that both hard and soft disciplines are affected by workload and dissatisfied with institutional research policy. These findings encourage officials to review research policies, initiate new strategies to lighten workload, and improve the reward system and funding, as well as enhance research equipment. We suggest that future follow-up studies include more schools at LAU and examine more variables that could impact the institution’s research productivity.

Footnotes

Appendices

Appendix A2.

Publications with International Collaboration in Soft Disciplines.

References	International collaborator	Academic affiliation
Hansson and Yacoubian (2021)	Kristianstad University, Sweden	Education
Bradley et al. (2022)	University of Gothenburg, Sweden	Education
Majdalani et al. (2021)	Grenoble Ecole de Management, France	Education
De Witte et al. (2021)	Thomas More University of Applied Sciences stockholm University, Sweden Amsterdam University, Netherlands Friedrich-Alexander University Erlangen-Nuremberg, Germany University of Bergen, Norway University of Cyprus, Cyprus Rouen University, France University Institute of Maia - ISMAI, Portugal Vilnius University, Lithuania University of Porto - CPUP, Portugal University of Graz, Austria	Pyschology
Desatnik et al. (2021)	University College London & The Anna Freud National Centre for Children and Families, UK	Psychology
Tohme et al. (2021)	Thomas More University of Applied Sciences, Belgium	Psychology
Shane-Simpson et al. (2020)	University of Wisconsin Stout, US Case Western Reserve University, US College of Staten Island, City University of New York, US Boston College, US	Psychology
Grey et al. (2020)	Zayed University, UAE	Psychology
Malaeb et al. (2022)	Sapienza University of Rome, Italy	Psychology
King and Bonin-Labelle (2023)	CÉGEP Heritage College, Canada	Multimedia journalism and communication

Acknowledgements

I would like to thank Dr. Mira Abboud (University of prince Edward Island, Cairo, Egypt) for her valuable advices in statistics test and Dr. Samer Saab (Lebanese American University) for his advices and ideas.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Katia Sayyed

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

Abdallah

Nagarajan

Martin

Tamer

Faour

W. H.

Bassil

Cuisinier

F. J. G.

Gergely

Varga

Pall

Miele

Balme

El Tahchi

Bechelany

(2020). Enhancement of podocyte attachment on polyacrylamide hydrogels with gelatin-based polymers. ACS applied bio materials, 3, 7531–7539.

Abd El-Wahab

M. M.

Abu-Khzam

F. N.

Wang

Shaw

(2020). Semi-exact exponential-time algorithms: An experimental study. In 2020 Second International Conference on Transdisciplinary AI (TransAI) (pp. 96–99). IEEE.

Abdulrahman

Tout

Mourad

Talhi

(2021). FedMCCS: Multicriteria client selection model for optimal IoT federated learning. IEEE Internet of Things Journal, 8, 4723–4735.

Abdulrahman

Tout

Ould-Slimane

Mourad

Talhi

Guizani

(2021). A survey on federated learning: The journey from centralized to distributed on-site learning and beyond. IEEE Internet of Things Journal, 8, 5476–5497.

Abouchedid

Abdelnour

(2015). Faculty research productivity in six Arab countries. International Review of Education, 61, 673–690.

Abramo

D’Angelo

A. C.

Murgia

(2017). The relationship among research productivity, research collaboration, and their determinants. Journal of Informetrics, 11, 1016–1030.

Abramo

D’Angelo

C. A.

Di Costa

(2009). Research collaboration and productivity: Is there correlation? Higher Education, 57, 155–171.

Abramo

D’Angelo

C. A.

Solazzi

(2011). The relationship between scientists’ research performance and the degree of internationalization of their research. Scientometrics, 86, 629–643.

Abu-Khzam

F. N.

Feghali

Heggernes

(2020). Partitioning a graph into degenerate subgraphs. European Journal of Combinatorics, 83, 103015.

10.

Abu-Khzam

F. N.

Bazgan

Fernau

(2020a). Parameterized dynamic variants of red-blue dominating set. In International conference on current trends in theory and practice of informatics (pp. 236–247). Springer.

11.

Abu-Khzam

F. N.

Barr

J. R.

Fakhereldine

Shaw

(2021). A greedy heuristic for cluster editing with vertex splitting. In 2021 4th International conference on artificial intelligence for industries (AI4I) (pp. 38–41). IEEE.

12.

Agarwal

Durairajanayagam

Tatagari

Esteves

S. C.

Harlev

Henkel

Roychoudhury

Homa

Puchalt

N. G.

Ramasamy

Majzoub

K. D.

Tvrda

Assidi

Kesari

Sharma

Banihani

Abu-Elmagd

… Bashiri

(2016). Bibliometrics: Tracking research impact by selecting the appropriate metrics. Asian journal of andrology, 18, 296–309.

13.

Agnew

(2013). Strategic planning: An examination of the role of disciplines in sustaining internationalization of the university. Journal of Studies in International Education, 17, 183–202.

14.

Aiston

S. J.

Jung

(2015). Women academics and research productivity: An international comparison. Gender and Education, 27, 205–220.

15.

Akbaritabar

Casnici

Squazzoni

(2018). The conundrum of research productivity: A study on sociologists in Italy. Scientometrics, 114, 859–882.

16.

Alamah

AlSoussy

Fakih

(2023). The role of international research collaboration and faculty related factors in publication citations: Evidence from Lebanon. Economies, 11, 90.

17.

Al Hageh

Rahy

Khazen

Brial

Khnayzer

R. S.

Gauguier

Zalloua

P. A.

(2020). Plasma and urine metabolomic analyses in aortic valve stenosis reveal shared and biofluid-specific changes in metabolite levels. PLos One, 15(11), p.e0242019.

18.

Almansour

(2016). The crisis of research and global recognition in Arab universities. Near and Middle Eastern Journal of Research in Education, 2016(1):1.

19.

Arafeh

Ceravolo

Mourad

Damiani

Bellini

(2021). Ontology based recommender system using social network data. Future Generation Computer Systems, 115, 769–779.

20.

Arisdakessian

Wahab

O. A.

Mourad

Otrok

Kara

(2020). FoGMatch: An intelligent multi-criteria IoT-Fog scheduling approach using game theory. IEEE/ACM Transactions on Networking, 28, 1779–1789.

21.

Armijos Valdivieso

Avolio Alecchi

Arévalo-Avecillas

(2022). Factors that influence the individual research output of university professors: The Case of Ecuador, Peru, and Colombia. Journal of Hispanic Higher Education, 21, 450–468.

22.

Atat

O. E.

Farzaneh

Pourhamzeh

Taki

Abi-Habib

Vosough

El-Sibai

(2022). 3D modeling in cancer studies. Human Cell, 35, 23–36.

23.

Baaklini

Issa

Fakhri

Brajard

Fifani

Menna

Taupier-Letage

Bosse

Mortier

(2021). Blending drifters and altimetric data to estimate surface currents: Application in the levantine Mediterranean and objective validation with different data types. Ocean Modelling, 166: 101850.

24.

Barr

J. R.

Shaw

Abu-Khzam

F. N.

Thatcher

(2020). Vulnerability rating of source code with token embedding and combinatorial algorithms. International Journal of Semantic Computing, 14, 501–516.

25.

Barr

J. R.

Shaw

Abu-Khzam

F. N.

(2020a). Optimally balanced orientation of graphs. In 2020 Second international conference on transdisciplinary AI (TransAI) (pp. 100–103). IEEE.

26.

Barr

J. R.

Shaw

Abu-Khzam

F. N.

Yin

Thatcher

(2020). Combinatorial code classification & vulnerability rating. In 2020 second international conference on transdisciplinary AI (TransAI) (pp. 80–83). IEEE.

27.

Bastedo

M. N.

Bowman

N. A.

(2011). College rankings as an interorganizational dependency: Establishing the foundation for strategic and institutional accounts. Research in Higher Education, 52, 3–23.

28.

Becher

Trowler

(2001). Academic tribes and territories. McGraw-Hill Education (UK.

29.

Bland

C. J.

Center

B. A. (. A.

Finstad

D. A.

Risbey

K. R.

Staples

(2006). The impact of appointment type on the productivity and commitment of full-time faculty in research and doctoral institutions. Journal of Higher Education, 77, 89–123.

30.

Bornmann

de Moya Anegón

Mutz

(2013). Do universities or research institutions with a specific subject profile have an advantage or a disadvantage in institutional rankings? Journal of the American Society for Information Science and Technology, 64, 2310–2316.

31.

Bowman

N. A.

Bastedo

M. N.

(2009). Getting on the front page: Organizational reputation, status signals, and the impact of US News and World Report on student decisions. Research in Higher Education, 50, 415–436.

32.

Bradley

Bahous

Albasha

(2022). Professional development of Syrian refugee women: Proceeding with a career within education. Studies in Continuing Education, 44, 155–172.

33.

Braxton

J. M.

Luckey

Helland

(2002). Institutionalizing a broader view of scholarship through Boyer’s four domains. ASHE-ERIC Higher Education Report. Jossey-Bass Higher and Adult Education Series.

34.

Brew

Boud

Namgung

S. U.

Lucas

Crawford

(2016). Research productivity and academics’ conceptions of research. Higher Education, 71, 681–697.

35.

Brogden

Shammas

Walters

Maalouf

Das

A. M.

Naim

H. Y.

Rizk

(2020). Different trafficking phenotypes of Niemann-pick C1 gene mutations correlate with various alterations in lipid storage, membrane composition and Miglustat amenability. International Journal of Molecular Sciences, 21, 2101.

36.

Butler

(2003). Explaining Australia’s increased share of ISI publications—the effects of a funding formula based on publication counts. Research Policy, 32, 143–155.

37.

Carpenter

C. R.

Cone

D. C.

Sarli

C. C.

(2014). Using publication metrics to highlight academic productivity and research impact. Academic Emergency Medicine, 21, 1160–1172.

38.

Chapelon

Barry

Hubert

Com-Ruelle

Duclos

Mattar

Falissard

Huas

Godart

(2021). Health in adulthood after severe anorexia nervosa in adolescence: A study of exposed and unexposed women. Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity, 26, 1389–1397.

39.

Chicha

Bouna

B. A.

Nassar

Chbeir

Haraty

R. A.

Oussalah

Benslimane

Alraja

M. N.

(2021). A user-centric mechanism for sequentially releasing graph datasets under blowfish privacy. ACM Transactions on Internet Technology, 21, 1–25.

40.

Chidiac

Daher

Boeckstaens

Poelvoorde

Badran

Marini

A. M.

Khalaf

Vanhamme

(2020). Human apolipoprotein L1 interferes with mitochondrial function in Saccharomyces cerevisiae. Molecular Medicine Reports, 22, 1910–1920.

41.

Chinchilla-Rodríguez

Zacca-González

Vargas-Quesada

de Moya-Anegón

(2016). Benchmarking scientific performance by decomposing leadership of Cuban and Latin American institutions in Public Health. Scientometrics, 106, 1239–1264.

42.

Coussa

Bassil

Gougeon

Marliss

E. B.

Morais

J. A.

(2020). Glucose and protein metabolic responses to an energy- but not protein- restricted diet in type 2 diabetes. Diabetes Obesity and Metabolism, 22, 1278–1285.

43.

Craveur

Narwani

T. J.

Srinivasan

Gelly

J.-C.

Rebehmed

de Brevern

A. G.

(2022). Shaking the β-Bulges. IEEE/ACM Transactions on Computational Biology and Bioinformatics/IEEE, ACM, 19, 14–18.

44.

Dakik

H. A.

Kaidbey

Sabra

(2006). Research productivity of the medical faculty at the American University of Beirut. Postgraduate Medical Journal, 82, 462–464.

45.

Desatnik

Jarvis

Hickin

Taylor

Trevatt

Tohme

Lorenzini

(2021). Preliminary real-world evaluation of an intervention for parents of adolescents: The Open Door Approach to parenting teenagers (APT). Journal of Child and Family Studies, 30, 38–50.

46.

De Witte

N. A. J.

Carlbring

Etzelmueller

Nordgreen

Karekla

Haddouk

Belmont

Øverland

Abi-Habib

Bernaerts

Brugnera

Compare

Duque

Ebert

D. D.

Eimontas

Kassianos

A. P.

Salgado

Schwerdtfeger

Tohme

… Van Daele

(2021). Online consultations in mental healthcare during the COVID-19 outbreak: An international survey study on professionals’ motivations and perceived barriers. Internet Interventions, 25: 100405.

47.

Dinh

Arfaoui

M. A.

Sharafeddine

Assi

C. M.

Ghrayeb

(2020). A low-complexity framework for joint user pairing and power control for cooperative NOMA in 5G and beyond cellular networks. IEEE Transactions on Communications, 68, 6737–6749.

48.

Dinh

Arfaoui

M. A.

Sharafeddine

Assi

Ghrayeb

(2020). A low-complexity approach for sum-rate maximization in cooperative NOMA enhanced cellular networks. In 2020 IEEE international conference on communications workshops (ICC Workshops) (pp. 1–7). IEEE.

49.

Ductor

(2015). Does co-authorship lead to higher academic productivity? Oxford Bulletin of Economics and Statistics, 77, 385–407.

50.

Ebrahimi

Sharafeddine

P.-H.

Assi

(2021). Autonomous UAV trajectory for localizing ground objects: A reinforcement learning approach. IEEE Transactions on Mobile Computing, 20, 1312–1324.

51.

Edgar

Geare

(2013). Factors influencing university research performance. Studies in Higher Education, 38, 774–792.

52.

El Haber

Elhattab

Assi

Sharafeddine

Nguyen

K. K.

(2021). Latency and reliability aware edge computation offloading via an intelligent reflecting surface. IEEE Communications Letters, 25, 3947–3951.

53.

El Rassi

Meho

L. I.

Nahlawi

Salameh

J. S.

Bazarbachi

Akl

E. A.

(2018). Medical research productivity in the Arab countries: 2007-2016 bibliometric analysis. Journal of Global Health, 8(2).

54.

El-Sibai

El Hajj

Al Haddad

El Baba

Al Saneh

Daoud Khatoun

Helaers

Vikkula

El Atat

Sabbagh

Abou Chebel

Ghassibe-Sabbagh

(2021). Dysregulation of rho GTPases in orofacial cleft patients-derived primary cells leads to impaired cell migration, a potential cause of cleft/lip palate development. Cells and development, 165: 203656.

55.

El-Zahr

(2022a). Impact of student research in engineering: Case study of a non-doctoral university in the Arab world. In 2022 IEEE Integrated STEM Education Conference (ISEC) (pp. 124–131). IEEE.

56.

El-Zahr

(2022b). Quality, quantity and impact in engineering research: Case study of a non-doctoral university in the Arab world. In 2022 IEEE integrated STEM education conference (ISEC) (pp. 132–137). IEEE.

57.

Ettinger

C. L.

Bryan

Tokajian

Jospin

Coil

Eisen

J. A.

(2021). Reconstruction of metagenome-assembled genomes from aquaria. Microbiology resource announcements, 10, e0055721–NaN00521.

58.

Feghali

Merhi

Kwasiborski

Hourdel

Ghosn

Tokajian

(2021). Genomic characterization and phylogenetic analysis of the first SARS-CoV-2 variants introduced in Lebanon. PeerJ, 9: e11015.

59.

Grey

Tohme

Thomas

Al Mazrouie

Abi-Habib

(2020). Preferred therapist characteristics of Muslim college women in the United Arab Emirates: Implications for psychotherapy. Mental Health Religion & Culture, 23, 745–755.

60.

Gul

Nisa

N. T.

Shah

T. A.

Gupta

Jan

Ahmad

(2015). Middle East: Research productivity and performance across nations. Scientometrics, 105, 1157–1166.

61.

Haderer

Venables

van Olmen

Orcutt

Ghassibe-Sabbagh

van Den Boogaard

(2021). “I try the one that they say is good.”– factors influencing choice of health care provider and pathways to diabetes care for Syrian refugees in Lebanon. Conflict and Health, 15(1), 45.

62.

Hammoud

Otrok

Mourad

Dziong

(2021). Stable federated fog formation: An evolutionary game theoretical approach. Future Generation Computer Systems, 124, 21–32.

63.

Hammud

H. H.

Kortz

Bhattacharya

Demirdjian

Hariri

Isber

Sang Choi

Mirtamizdoust

Mroueh

Daher

C. F.

(2020). Structure, DFT studies, magnetism and biological activity of bis[(µ-azido)-chloro-(1,10-phenanthroline)-copper(II)] complex. Inorganica Chimica Acta, 506: 119533.

64.

Hanna

E. M.

Zhang

Eide

Fallahi

Furmanek

Yadetie

Zielinski

D. C.

Goksøyr

Jonassen

(2020). ReCodLiver0.9: Overcoming challenges in genome-scale metabolic reconstruction of a non-model species. Frontiers in Molecular Biosciences, 7: 591406.

65.

Hansson

Yacoubian

H. A.

(2021). Correction to: Nature of Science for Social Justice: Why, What and how? In Nature of Science for Social Justice (pp. C1–C1). Springer.

66.

Haykal

Younes

El Khoury

Ammoury

Tannous

Hodroj

M. H.

Sarkis

Gasilova

Menin

Rizk

(2021). The pro-apoptotic properties of a phytonutrient rich infusion of A. Cherimola leaf extract on AML cells. Biomedicine & Pharmacotherapy, 140: 111592.

67.

Heng

Hamid

Khan

(2020). Factors influencing academics’ research engagement and productivity: A developing countries perspective. Issues in Educational Research, 30, 965–987.

68.

Z.-L.

Geng

X.-S.

Campbell-Hunt

(2009). Research collaboration and research output: A longitudinal study of 65 biomedical scientists in a New Zealand university. Research Policy, 38, 306–317.

69.

Hoteit

Abualnaja

Afzal

Ait-El-Fquih

Akylas

Antony

Dawson

Asfahani

Brewin

R. J.

Cavaleri

Cerovecki

Cornuelle

Desamsetti

Attada

Dasari

Sanchez-Garrido

Genevier

El Gharamti

Gittings

J. A.

… Zodiatis

(2021). Towards an end-to-end analysis and prediction system for weather, climate, and marine applications in the red sea. Bulletin of the American Meteorological Society, 102, E99–E122.

70.

Husni

Chrabieh

Dib

R. W.

Vazquez

Guimaraes

Fernández

Khoury

Asmar

Khazen

Samaha

Raad

Hachem

(2021). Timing for step-down therapy of candidemia in non-neutropenic patients: An international multi-center study. Mediterranean Journal of Hematology and Infectious Diseases, 13(1).

71.

Hussain

Kaassamani

Auguste

Boutu

Gauthier

Kholodtsova

Gomes

J.-T.

Lavoute

Gaponov

Ducros

Fevrier

Nicolas

Imran

Zeitoun

Williams

G. O.

Fajardo

Merdji

(2021). Spectral control of high order harmonics through non-linear propagation effects. Applied Physics Letters, 119, 071101.

72.

Hussain

Pires

Boutu

Franz

Nicolas

Imran

Merdji

Fajardo

Williams

G. O.

(2020). Controlling the non-linear optical properties of MgO by tailoring the electronic structure. Applied Physics B, 126, 1–7.

73.

Jaafar

Fix-Tailler

Mansour

Allain

Shebaby

W. N.

Faour

W. H.

Tokajian

El-Ghayoury

Naoufal

Bouchara

Larcher

Ibrahim

(2020). Synthesis, characterization, antifungal and antibacterial activities evaluation of copper (II), zinc (II) and cadmium (II) chloride and bromide complexes with new (E)-1-(3,4-dimethoxybenzylidene)-4-methylthiosemicarbazone ligand. Applied Organometallic Chemistry, 34: e5988.

74.

Jameel

A. S.

Ahmad

A. R.

(2020a). Factors impacting research productivity of academic staff at the Iraqi higher education system. International Business Education Journal, 13, 108–126.

75.

Jameel

A. S.

Ahmad

A. R.

(2020b). The mediating role of job satisfaction between leadership style and performance of academic staff. International Journal of Psychosocial Rehabilitation, 24, 2399–2414.

76.

Jayaraj

Raymond

Krishnan

Tzou

K. S.

Baxi

Ram

M. R.

Govind

S. K.

Chandramoorthy

H. C.

Abu-Khzam

F. N.

Shaw

(2020). Clinical theragnostic potential of diverse miRNA expressions in prostate cancer: A systematic review and meta-analysis. Cancers, 12, 1199.

77.

Jung

(2012). Faculty Research Productivity in Hong Kong across academic discipline. Higher Education Studies, 2, 1–13.

78.

Kanbar

Touma

Klingenberg

(2020). Well-balanced central schemes for the one and two-dimensional Euler systems with gravity. Applied Numerical Mathematics, 156, 608–626.

79.

Kato

Ando

(2013). The relationship between research performance and international collaboration in chemistry. Scientometrics, 97, 535–553.

80.

Kern

Morvan

Mattar

Molina

Tailhardat

Peguet

De Tournemire

Hirot

Rizk

Godart

Fautrelle

(2020). Development and evaluation of an adapted physical activity program in anorexia nervosa inpatients: A pilot study. European Eating Disorders Review, 28, 687–700.

81.

Khalaf

R. A.

Fattouh

Medvecky

Hrabak

(2021). Whole genome sequencing of a clinical drug resistant Candida albicans isolate reveals known and novel mutations in genes involved in resistance acquisition mechanisms. Journal of Medical Microbiology, 70(4).

82.

Khaled

Hundley

Bassil

Bazzi

Tsofliou

(2021). Validation of the European Prospective Investigation into cancer (EPIC) FFQ for use among adults in Lebanon. Public Health Nutrition, 24, 4007–4016.

83.

Khalil

O. E. M.

(2019). Business research productivity and barriers. International Journal of Productivity and Quality Management, 26, 34–57.

84.

Khuram

Wang

Anjum

M. A.

Khalid

(2022). Factors affecting academic performance of international students in China: A Theory of reasoned action approach / čimbenici koji utječu na akademsku uspješnost međunarodnih studenata u Kini: Teorija pristupa razumnoga djelovanja. Croatian Journal of Education: Hrvatski časopis za odgoj i obrazovanje, 24, 831–859.

85.

Khuram

Wang

Khan

Khalid

(2021). Academic attitude and subjective norms effects on international doctoral students’ academic performance self-perceptions: A moderated-mediation analysis of the influences of knowledge- seeking intentions and supervisor support. Journal of Psychology in Africa, 31, 145–152.

86.

King

Bonin-Labelle

(2023). Assessing assumptions: Surveying diversity within nonprofit radio stations in Canada. Journal of Radio & Audio Media, 30, 207–226.

87.

Kwiek

(2016). The European research elite: A cross-national study of highly productive academics in 11 countries. Higher Education, 71, 379–397.

88.

Kwiek

(2018). High research productivity in vertically undifferentiated higher education systems: Who are the top performers? Scientometrics, 115, 415–462.

89.

Kyvik

(2003). Changing trends in publishing behaviour among university faculty, 1980-2000. Scientometrics, 58, 35–48.

90.

Leydesdorff

Shin

J. C.

(2011). How to evaluate universities in terms of their relative citation impacts: Fractional counting of citations and the normalization of differences among disciplines. Journal of the American Society for Information Science and Technology, 62, 1146–1155.

91.

Linton

J. D.

Tierney

Walsh

S. T.

(2012). What are research expectations? A comparative study of different academic disciplines. Serials Review, 38, 228–234.

92.

Majdalani

M. G.

Mielly

Islam

G. I.

(2021). Recasting sustainable collaborations through postcolonial perspectives. In Academy of management proceedings, academy of management, Briarcliff Manor, NY (p. 13183).

93.

Makke

Bitar

Salloum

Panossian

Alousi

Arabaghian

Medvecky

Hrabak

Merheb-Ghoussoub

Tokajian

(2020). Whole-genome-sequence-based characterization of extensively drug-resistant Acinetobacter baumannii hospital outbreak. mSphere, 5, e00934–NaN00919.

94.

Malaeb

Bianchi

Pompili

Berro

Laghi

Azzi

Akel

Obeid

Hallit

(2022). Drunkorexia behaviors and motives, eating attitudes and mental health in lebanese alcohol drinkers: A path analysis model. Eating and Weight Disorders - Studies on Anorexia Bulimia and Obesity, 27, 1787–1797.

95.

Mansour

Bodman-Smith

Khnayzer

R. S.

Daher

C. F.

(2021). A photoactivatable Ru (II) complex bearing 2,9-diphenyl-1,10-phenanthroline: A potent chemotherapeutic drug inducing apoptosis in triple negative human breast adenocarcinoma cells. Chemico-Biological Interactions, 336: 109317.

96.

Mehanna

Bodman-Smith

Daher

C. F.

Khnayzer

R. S.

(2020). Rapid quantification of ruthenium(ii) polypyridyl anti-cancer drugs using a selective ligand dissociation LC-MS/MS method. Analytical Methods, 12, 4517–4525.

97.

Melissa

Lama

Laurence

Sylvie

Jeanne

Odile

Nathalie

(2020). Physical activity in eating disorders: A systematic review. Nutrients, 12, 183.

98.

Miranda

Garcia-Carpintero

(2019). Comparison of the share of documents and citations from different quartile journals in 25 research areas. Scientometrics, 121, 479–501.

99.

Mourad

Antaki

Bissonnette

Al Baini

Saadeh

Jamal

(2021). Evidence-based clinical prioritization of embryos with mosaic results: A systematic review and meta-analysis. Journal of Assisted Reproduction and Genetics, 38, 2849–2860.

100.

Mourad

Tout

Wahab

O. A.

Otrok

Dbouk

(2021). Ad hoc vehicular fog enabling cooperative low-latency intrusion detection. IEEE Internet of Things Journal, 8, 829–843.

101.

Mryglod

Kenna

Holovatch

Berche

(2013). Comparison of a citation-based indicator and peer review for absolute and specific measures of research-group excellence. Scientometrics, 97, 767–777.

102.

Narwani

T. J.

Craveur

Shinada

N. K.

Floch

Santuz

Vattekatte

A. M.

Srinivasan

Rebehmed

Gelly

J.-C.

Etchebest

de Brevern

A. G.

(2020). Discrete analyses of protein dynamics. Journal of Biomolecular Structure and Dynamics, 38, 2988–3002.

103.

Nefedova

V. E.

Fröhlich

Navarrete

Tancogne-Dejean

Franz

Hamdou

Kaassamani

Gauthier

Nicolas

Jargot

Hanna

Georges

Ciappina

M. F.

Thumm

Boutu

Merdji

(2021). Enhanced extreme ultraviolet high-harmonic generation from chromium-doped magnesium oxide. Applied Physics Letters, 118, 201103.

104.

Nguyen

(2015). Factors Influencing the research productivity of academics at the research-oriented university in Vietnam. Griffith University.

105.

Nicolas

Shi

Chanteau

Franz

Kholodstova

Ripault

Andrade

J. R. C.

Iwan

Boutu

Kovacev

Merdji

(2021). Plasmon-amplified third harmonic generation in metal/dielectric resonators. Plasmonics, 16, 1883–1889.

106.

Nocco

M. A.

McGill

B. M.

MacKenzie

C. M.

Tonietto

R. K.

Dudney

Bletz

M. C.

Young

Kuebbing

S. E.

(2021). Mentorship, equity, and research productivity: Lessons from a pandemic. Biological Conservation, 255: 108966.

107.

O’Toole Hill

Pybus

O. G

Watts

Bogoch

I. I

Khan

Messina

J. P

Tegally

Lessells

R. R

Giandhari

Pillay

Tumedi

K. A

Nyepetsi

Kebabonye

Matsheka

Mine

Tokajian

Hassan

Salloum

… Kraemer

M. U. G.

(2021). Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2 with grinch. Wellcome Open Research, 6, 121.

108.

Oancea

(2013). Interpretations of research impact in seven disciplines. European Educational Research Journal, 12, 242–250.

109.

Opesanwo

Simisaye

A. O.

(2017). Influence of gender, academic disciplines on research productivity of lecturers in two universities in south-west Nigeria. Nigerian Libraries, 50, 20–35.

110.

Padilla-Gonzalez

Metcalfe

A. S.

Galaz-Fontes

J. F.

Fisher

Snee

(2011). Gender gaps in North American research productivity: Examining faculty publication rates in Mexico, Canada, and the US. Compare, 41, 649–668.

111.

Pepe

Kurtz

M. J.

(2012). A measure of total research impact independent of time and discipline. PLoS One, 7: e46428

112.

Pleplé

Lalanne

Huas

Mattar

Hanachi

Flament

M. F.

Carchon

Jouen

Berthoz

Godart

(2021). Nutritional status and anxious and depressive symptoms in anorexia nervosa: A prospective study. Scientific Reports, 11(1), 771.

113.

Quimbo

M. A. T.

Sulabo

E. C.

(2014). Research productivity and its policy implications in higher education institutions. Studies in Higher Education, 39, 1955–1971.

114.

Rachid

Noureddine

Tamim

Makki

Naalbandian

Al-Haddad

(2021). Gender disparity in research productivity across departments in the faculty of medicine: A bibliometric analysis. Scientometrics, 126, 4715–4731.

115.

Ramsden

Moses

(1992). Associations between research and teaching in Australian higher education. Higher Education, 23, 273–295.

116.

Salloum

Moussa

Rahy

Al Deek

Khalifeh

El Hajj

Hall

Hirt

R. P.

Tokajian

(2020). Expanded genome-wide comparisons give novel insights into population structure and genetic heterogeneity of Leishmania tropica complex. Plos Neglected Tropical Diseases, 14: e0008684.[p.]

117.

Salloum

Panossian

Bitar

Hrabak

Araj

G. F.

Tokajian

(2020). First report of plasmid-mediated colistin resistance mcr-8.1 gene from a clinical Klebsiella pneumoniae isolate from Lebanon. Antimicrobial Resistance and Infection Control, 9(1), 7.

118.

Salloum

Tokajian

Hirt

R. P.

(2021). Advances in understanding Leishmania pathobiology: What does rna-seq tell us? Frontiers in Cell and Developmental Biology, 9: 702240.

119.

Samiee

Kharazi

Elaridi

Taravati Javad

Leili

(2020). An assessment of the occurrence and nutritional factors associated with aflatoxin M1, ochratoxin A, and zearalenone in the breast milk of nursing mothers in Hamadan, Iran. Toxicon, 187, 209–213.

120.

Sami

Otrok

Bentahar

Mourad

(2021b). AI-based resource provisioning of IoE services in 6G: A deep reinforcement learning approach. IEEE Transactions on Network and Service Management, 18, 3527–3540.

121.

Sami

Mourad

Otrok

Bentahar

(2020). Fscaler: Automatic resource scaling of containers in fog clusters using reinforcement learning. In 2020 international wireless communications and mobile computing (IWCMC) (pp. 1824–1829). IEEE.

122.

Sami

Mourad

Otrok

Bentahar

(2022). Demand-driven deep reinforcement learning for scalable fog and service placement. IEEE Transactions on Services Computing, 15, 2671–2684.

123.

Shamseddine

Nizam

Hammoud

Mourad

Otrok

Harmanani

Dziong

(2021). A novel federated fog architecture embedding intelligent formation. IEEE Network, 35, 198–204.

124.

Shane-Simpson

Schwartz

A. M.

Abi-Habib

Tohme

Obeid

(2020). I love my selfie! An investigation of overt and covert narcissism to understand selfie-posting behaviors within three geographic communities. Computers in Human Behavior, 104: 106158.

125.

Shehatta

Al-Rubaish

A. M.

Qureshi

I. U.

(2023). Coronavirus research performance across journal quartiles. Advantages of Q1 publications. Global Knowledge, Memory and Communication, 72, 537–553.

126.

Shin

J. C.

Cummings

W. K.

(2010). Multilevel analysis of academic publishing across disciplines: Research preference, collaboration, and time on research. Scientometrics, 85, 581–594.

127.

Singh

D. K.

Haraty

R. A.

Debnath

N. C.

Choudhury

(2020). An analysis of the dynamic community detection algorithms in complex networks. In 2020 IEEE international conference on industrial technology (ICIT) (pp. 989–994). IEEE.

128.

Slim

Al Yusuf

Abbas

Abdallah

C. T.

Heileman

G. L.

Slim

(2021). A Markov decision processes modeling for curricular analytics. In 2021 20th IEEE international conference on machine learning and applications (ICMLA) (pp. 415–421). IEEE.

129.

Smeby

J.-C.

Try

(2005). Departmental contexts and faculty research activity in Norway. Research in Higher Education, 46, 593–619.

130.

Sorkhoh

Assi

Ebrahimi

Sharafeddine

(2022). Optimizing information freshness for MEC-Enabled cooperative autonomous driving. IEEE Transactions on Intelligent Transportation Systems, 23, 13127–13140.

131.

Sorkhoh

Ebrahimi

Assi

Sharafeddine

Khabbaz

(2020). An infrastructure-assisted workload scheduling for computational resources exploitation in the fog-enabled vehicular network. IEEE Internet of Things Journal, 7, 5021–5032.

132.

Teodorescu

(2000). Correlates of faculty publication productivity: A cross-national analysis. Higher Education, 39, 201–222.

133.

Tohme

De Witte

N. A. J.

Van Daele

Abi-Habib

(2021). Telepsychotherapy during the COVID-19 pandemic: The experience of Lebanese Mental Health Professionals. Journal of Contemporary Psychotherapy, 51, 349–355.

134.

Tout

Mourad

Kara

Talhi

(2021). Multi-persona mobility: Joint cost-effective and resource-aware mobile-edge computation offloading. IEEE/ACM Transactions on Networking, 29, 1408–1421.

135.

Toutounji

Wanes

El-Harakeh

El-Sabban

Rizk

Naim

H. Y.

(2020). Dextran sodium sulfate-induced impairment of protein trafficking and alterations in membrane composition in intestinal caco-2 cell line. International Journal of Molecular Sciences, 21, 2726.

136.

Vabø

Padilla-González

L. E.

Waagene

Næss

(2014). Gender and faculty internationalization. The internationalization of the academy (pp. 183–205). Springer.

137.

Wahab

O. A.

Cohen

Bentahar

Otrok

Mourad

Rjoub

(2020). An endorsement-based trust bootstrapping approach for newcomer cloud services. Information Sciences, 527, 159–175.

138.

Wahab

O. A.

Mourad

Otrok

Taleb

(2021). Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems. IEEE Communications Surveys & Tutorials, 23, 1342–1397.

139.

Wanner

R. A.

Lewis

L. S.

Gregorio

D. I.

(1981). Research productivity in academia: A comparative study of the sciences, social sciences and humanities. Sociology of Education, 54, 238–253.

140.

Ynalvez

M. A.

Shrum

W. M.

(2011). Professional networks, scientific collaboration, and publication productivity in resource-constrained research institutions in a developing country. Research Policy, 40, 204–216.

141.

Zhou

Volkwein

J. F.

(2004). Examining the influences on faculty departure intentions: A comparison of tenured versus nontenured faculty at research universities using NSOPF-99. Research in Higher Education, 45, 139–176.

Assessing Research Productivity and Quality Across Disciplines in the School of Arts and Sciences at the Lebanese American University

Abstract

Keywords

Introduction

Theoretical Background and Goals of the Study

Data and Methodology

Disciplines

Data

Data Analysis

Comparison of the Research Output in Both Disciplines

Comparison of the Research Quality in Both Disciplines

Questionnaire: Factors Influencing the Research Productivity in Both Disciplines

Findings

The Impact of the Academic Discipline on the Productivity of Research

The Impact of the Academic Discipline on the Level of Research in Terms of Publication Patterns

The Impact of the Academic Discipline on the Level of Research in Terms of Citations and Citation Resources

The Influence of Individual, Institutional, and Some Occasional Factors on the Productivity of Research in Both Disciplines

Individual Factors

Institutional Factors

Occasional Factors

Discussion

Conclusions

Footnotes

Appendices

Acknowledgements

Declaration of Conflicting Interests

Funding

ORCID iD

Data Availability Statement

References