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This study investigates a mediational model between legitimated elements, financial resource mobilisation and subsequent early firm growth among New Technology-Based Firms (NTBFs) using conformity and control perspectives of legitimacy.

To test the hypotheses, a longitudinal database of 303 NTBFs from Sweden, Finland and France is used. The ordinary least square regression analysis method is applied, and the proposed mediation relationships are studied by employing the four-step approach developed by Baron and Kenny (1986).

This study finds that based on the conformity principle, two out of three legitimated elements (business plan and incubator relationship, but not start-up experience) have an impact on financial resource mobilisation, which in turn, is associated with early growth in NTBFs based on the control principle. Thus, financial resource mobilisation positively mediates the relationships among the two legitimated elements and early growth in NTBFs.

This study has several limitations, which also generate promising pathways for future research. Future research should study the relationship between the three legitimacy elements and financial resource mobilisation and early growth across a wider range of firms and settings. The questionnaire was also based on a single point in time and could not capture the evolving nature of the legitimacy elements and fundraising. Hence, future research can examine the multidimensionality of these processes; longitudinal qualitative studies can be a complement, allowing for a better understanding of the impact of legitimacy on NTBFs.

The findings offer implications for managers of NTBFs because developing legitimacy is critical to NTBFs early growth and development. The findings indicate that NTBFs' founders must systematically develop business plans and that incubators help enhance legitimacy through a signalling.

It is believed that the study meaningfully contributes to the collective understanding of the role of legitimacy in driving the development of NTBFs. Given the importance of NTBFs in our economies, coupled with the lack of attention given to the role of mobilisation of external resources in explaining NTBF early growth, it is believed that the study is both timely and important.

The findings meaningfully contribute to the collective understanding of NTBF growth. While there are studies that have examined the antecedents of growth and finance separately, this study proposes a novel mediational model that integrates both and tests it empirically.

In this paper, we study a Cauchy-type problem for Hilfer fractional integrodifferential equations with boundary conditions. The existence of solutions for the given problem is proved by applying measure of noncompactness technique in an abstract weighted space. Moreover, we use generalized Gronwall inequality with singularity to establish continuous dependence and uniqueness of ϵ-approximate solutions.

The purpose of this paper is to provide an outline of the major contributions in the literature on the determination of the least distance in data envelopment analysis (DEA). The focus herein is primarily on methodological developments. Specifically, attention is mainly paid to modeling aspects, computational features, the satisfaction of properties and duality. Finally, some promising avenues of future research on this topic are stated.

DEA is a methodology based on mathematical programming for the assessment of relative efficiency of a set of decision-making units (DMUs) that use several inputs to produce several outputs. DEA is classified in the literature as a non-parametric method because it does not assume a particular functional form for the underlying production function and presents, in this sense, some outstanding properties: the efficiency of firms may be evaluated independently on the market prices of the inputs used and outputs produced; it may be easily used with multiple inputs and outputs; a single score of efficiency for each assessed organization is obtained; this technique ranks organizations based on relative efficiency; and finally, it yields benchmarking information. DEA models provide both benchmarking information and efficiency scores for each of the evaluated units when it is applied to a dataset of observations and variables (inputs and outputs). Without a doubt, this benchmarking information gives DEA a distinct advantage over other efficiency methodologies, such as stochastic frontier analysis (SFA). Technical inefficiency is typically measured in DEA as the distance between the observed unit and a “benchmarking” target on the estimated piece-wise linear efficient frontier. The choice of this target is critical for assessing the potential performance of each DMU in the sample, as well as for providing information on how to increase its performance. However, traditional DEA models yield targets that are determined by the “furthest” efficient projection to the evaluated DMU. The projected point on the efficient frontier obtained as such may not be a representative projection for the judged unit, and consequently, some authors in the literature have suggested determining closest targets instead. The general argument behind this idea is that closer targets suggest directions of enhancement for the inputs and outputs of the inefficient units that may lead them to the efficiency with less effort. Indeed, authors like Aparicio et al. (2007) have shown, in an application on airlines, that it is possible to find substantial differences between the targets provided by applying the criterion used by the traditional DEA models, and those obtained when the criterion of closeness is utilized for determining projection points on the efficient frontier. The determination of closest targets is connected to the calculation of the least distance from the evaluated unit to the efficient frontier of the reference technology. In fact, the former is usually computed through solving mathematical programming models associated with minimizing some type of distance (e.g. Euclidean). In this particular respect, the main contribution in the literature is the paper by Briec (1998) on Hölder distance functions, where formally technical inefficiency to the “weakly” efficient frontier is defined through mathematical distances.

All the interesting features of the determination of closest targets from a benchmarking point of view have generated, in recent times, the increasing interest of researchers in the calculation of the least distance to evaluate technical inefficiency (Aparicio et al., 2014a). So, in this paper, we present a general classification of published contributions, mainly from a methodological perspective, and additionally, we indicate avenues for further research on this topic. The approaches that we cite in this paper differ in the way that the idea of similarity is made operative. Similarity is, in this sense, implemented as the closeness between the values of the inputs and/or outputs of the assessed units and those of the obtained projections on the frontier of the reference production possibility set. Similarity may be measured through multiple distances and efficiency measures. In turn, the aim is to globally minimize DEA model slacks to determine the closest efficient targets. However, as we will show later in the text, minimizing a mathematical distance in DEA is not an easy task, as it is equivalent to minimizing the distance to the complement of a polyhedral set, which is not a convex set. This complexity will justify the existence of different alternatives for solving these types of models.

As we are aware, this is the first survey in this topic.

This paper attempts to develop a simple, static model of tax administration that is capable of explaining the widespread collusive petty tax administration corruption observed in developing countries.

This paper utilizes a positivist research framework and adopts a theoretical method of analysis, although secondary data will also be mentioned to support theoretical arguments whenever it is appropriate to do so.

A high rate of collusive tax corruption is inevitable in developing countries.

The model is static and needs to be extended into a dynamic model.

Traditional enforcement tools such as higher audits or a higher penalty regime against tax evasion do not work. Tax simplification can lessen the incidence of tax corruption.

Fighting tax corruption requires significant changes in the attitudes of taxpayers and tax auditors.

This paper combines the literature on Kantian economics and tax compliance in an innovative fashion.

The present study aims at analysing consumer preferences for the pomegranate fruit, focussing on the effect of ready-to-eat format (i.e. packaged arils) on the purchasing choice, together with several products’ attributes as the origin, the packaging typology and the price.

The paper presents a choice experiment (CE) among 626 Italian consumers from Veneto region through an online survey. The study estimates both a conditional logit (CL) and a latent class logit model (LCM).

By segmenting the sample based on the heterogeneous preferences of consumers, it can distinguish “eco-friendly consumers”, “time-saving lovers”, “nationalists” and “price sensitive” subjects. Interestingly, the marginal willingness to pay for ready-to-eat arils is positive for the “time-saving lovers” that are mainly young consumers. The Italian origin has always a positive effect on the choice, whereas a negative effect is found for the price. Finally, the eco-friendly package has both a negative and a positive effect.

The sample of this study is not representative of the population and the CE has a hypothetical nature. It follows that further research will link the economic analysis to a consumer test on a more representative sample.

This study can be useful for the pomegranate producers and the industry because it provides original evidence that could drive their business and marketing strategies, for instance, the preference for ready-to-eat arils.

This study is one of the first seeking to determine the factors that affect consumers' preferences for pomegranate arils.

In this paper a systematic and well-defined student participation assessment scheme for college courses is proposed. The scheme supports the involvement of students in a variety of areas of participation within and outside the classroom with the aim of improving their learning. The scheme addresses mostly the challenges related to the practicality of the structure and design of the assessment. It also addresses the subjectivity of grading student participations. Areas of participation are widened to allow the faculty more accurate information about the conduct of each individual student towards more objective assessment. In addition, it provides the faculty with the flexibility to select areas that best fit the learning outcomes, nature of the course, availability of time and resources, and class atmosphere. The proposed scheme is initiated and developed using feedback from the teaching staff of Nizwa College of Technology, (NCT) through a survey and open discussion. The results indicate that over two thirds of the surveyed staff show agreement with the concept of assessing participation and find the scheme design clear and systematic, while 82% of them perceive the scheme as effective in improving the motivation and learning of students.

The purpose of this paper is to propose a semiparametric estimator for the tail index of Pareto-type random truncated data that improves the existing ones in terms of mean square error. Moreover, we establish its consistency and asymptotic normality.

To construct a root mean squared error (RMSE)-reduced estimator of the tail index, the authors used the semiparametric estimator of the underlying distribution function given by Wang (1989). This allows us to define the corresponding tail process and provide a weak approximation to this one. By means of a functional representation of the given estimator of the tail index and by using this weak approximation, the authors establish the asymptotic normality of the aforementioned RMSE-reduced estimator.

In basis on a semiparametric estimator of the underlying distribution function, the authors proposed a new estimation method to the tail index of Pareto-type distributions for randomly right-truncated data. Compared with the existing ones, this estimator behaves well both in terms of bias and RMSE. A useful weak approximation of the corresponding tail empirical process allowed us to establish both the consistency and asymptotic normality of the proposed estimator.

A new tail semiparametric (empirical) process for truncated data is introduced, a new estimator for the tail index of Pareto-type truncated data is introduced and asymptotic normality of the proposed estimator is established.

Since the turn of the 21st century, various institutions of higher education have been established in the Gulf Cooperation Council region, several of which are branches of universities from North America, Europe, Australia, and other regions. Quality education is currently a required component in the models of collaboration between Universities; yet the literature suggests that challenges remain in how the quality education will be practiced in a region that lacked for long time private universities. In this paper, we present an exploratory investigation to determine what could be learned by studying the practicalities of collaboration and accreditation of a newly established institution in Oman, namely, Dhofar University. The case study focuses on the practicalities of DU’s external collaboration, national accreditation, and good practices University-wide and within the College of Engineering in particular. The paper aims to present and analyze challenges, good practices, faculty and staff experiences, and solutions that could be a useful pattern for similar institutions. The investigation builds on an internal University-wide self-study and an external review by an accreditation council.

Covid-19 pandemic is a unique and extraordinary situation for the globe, which has potentially disrupted almost all aspects of life. In this global crisis, the tourism and hospitality sector has collapsed in almost all parts of the world, and the same is true for India. Therefore, this paper aims to investigate the impact of Covid-19 on the Indian tourism industry.

This study develops an appropriate model to forecast the expected loss of foreign tourist arrivals (FTAs) in India for 10 months. Since the FTAs follow a seasonal trend, seasonal autoregressive integrated moving average (SARIMA) method has been employed to forecast the expected FTAs in India from March 2020 to December 2020. The results of the proposed model are then compared with the ones obtained by Holt-Winter's (H-W) model to check the robustness of the proposed model.

The SARIMA model seeks to manifest the monthly arrival of foreign tourists and also elaborates on the progressing expected loss of foreign tourists arrive for the next three quarters is approximately 2 million, 2.3 million and 3.2 million, respectively. Thus, in the next three quarters, there will be an enormous downfall of FTAs, and there is a need to adopt appropriate measures. The comparison demonstrates that SARIMA is a better model than H-W model.

Several studies have been reported on pandemic-affected tourism sectors using different techniques. The earlier pandemic outbreak was controlled and region-specific, but the Covid-19 eruption is a global threat having potential ramifications and strong spreading power. This work is one of the first attempts to study and analyse the impact of Covid-19 on FTAs in India.