Determination of indicators and standards for tourism impacts in protected Karaj River, Iran

This study was conducted with the main objective of determining the indicators and standards for the impact of tourism on the protected Karaj River in Tehran Province, Iran. The survey was carried out during the visitors’ peak season at several recreational areas along the protected Karaj River. Discriminative analysis was used to differentiate between the sites in terms of visitor satisfaction. The indicators were as follows: trash in the water, trash along the river banks, water quality, number of visitors, visitors’ distance to river, and visitors’ awareness of indicators. The following standards are suggested to improve the management of the site, including less than 12 percent of trash (both on the water surface and river banks), a family biotic index of less than five, less than 625 individuals per hectare, settlement points of more than 9 m from the river and a score of more than 32 on the scale of visitors’ awareness of potential impacts.     

Why do migrants remit?

This paper examines primary incentives of remitting. Using estimated bilateral data on remittances, this paper demonstrates that a rise in the home (remittance‐receiving) country's gross national income (GNI) per capita leads to fewer remittances and that a rise in the host (remittance‐sending) country's GNI per capita motivates migrants to remit more. Real exchange rates and real interest rates have no effect on remittances. These results indicate that altruism is an important and critical component of motivations behind remittances. However, altruism alone does not appear to be a sufficient explanation of the motivations behind remittances. Other incentives such as loan repayment and investment play a non‐negligible role in this regard as well. The degree of altruism is higher for migrants from developing countries in comparison with migrants from developed countries, and it is higher when we define remittances as “personal transfers” rather than “personal transfers and compensation of employees.” The results of the vector error correction model show if remittances deviate from the equilibrium relationship, they will eventually revert.     

Finding Donors by Relationship Fundraising

Our research utilizes revenue–business-based relationships and data to expand the donor bases of non-profit organizations. Fundraisers desire to predict who will donate and how much to allocate their marketing resources effectively. To answer both questions, we develop the Spatial Tobit Type 2 (ST2) model that integrates the auto-Logistic (AL) and auto-Gaussian (AG) models into the Tobit type 2 framework. The AL component is used to predict who is likely to donate by inferring inter-client similarities based on the clients' transaction information from the revenue businesses. Similarly, the AG component is used to predict how much based on a similar measure of inter-client similarities. The Tobit type 2 framework combines both components into the single framework of ST2. Our empirical application linking a veterinary school's medical treatment records to its donation records demonstrates that clients' relationships built through their medical treatments at the school hospital positively contribute to their donation decisions.     

What drives global B2B e-commerce usage: an analysis of the effect of the complexity of trading system and competition pressure

The purpose of this paper is to examine the conditions in which B2B e-commerce is most likely to diffuse widely at the country level. This paper examines the role of trading system complexity and pressure of competition on B2B EC diffusion by controlling Gross domestic product (GDP) per capita and Information and Communication Technology (ICT) infrastructure. Our sample comprises a pool of country-year dataset from 143 countries over a three-year period (2014–2016). The data were collected from Network Readiness Index Report and Global Competitiveness Report. The findings provide evidence that greater the complexity of trading relationships with the global economy and high level of pressure from the competition are the main forces for B2B use across countries. Consequently, the authors suggest that having a strong trade relationship with developed countries with matured B2B e-commerce practice is helpful in sustaining B2B e-commerce use across countries.     

Altruism: primary motivation of remittances

This article examines primary incentives of remittances. After controlling for host country’s GNI per capita, real exchange rates and real interest rates, a rise in home country’s GNI per capita leads to fewer remittances. A rise in host country’s GNI per capita motivates migrants to remit more. Real interest rates have no effect on remittances. These results indicate primary incentive of remittances is altruism.     

A National Governance Approach to the Political Nature and Role of Business: Case Study of the Mobile Telecommunications Industry in Afghanistan

Journal of Business Ethics - The study focuses on the mobile telecommunications industry in Afghanistan prior to the Taliban takeover of the country in 2021 and seeks to study how the mobile...     

Time-varying neural network for stock return prediction

We consider the problem of neural network training in a time-varying context. Machine learning algorithms have excelled in problems that do not change over time. However, problems encountered in financial markets are often time varying. We propose the online early stopping algorithm and show that a neural network trained using this algorithm can track a function changing with unknown dynamics. We compare the proposed algorithm to current approaches on predicting monthly US stock returns and show its superiority. We also show that prominent factors (such as the size and momentum effects) and industry indicators exhibit time-varying predictive power on stock returns. We find that during market distress, industry indicators experience an increase in importance at the expense of firm level features. This indicates that industries play a role in explaining stock returns during periods of heightened risk.     

Valuing organic farm volunteer tourists in Hawai'i: farm host perspectives

This article challenges conventional understandings of the benefits of farm volunteer tourism through a qualitative study of the perceived value of organic farm volunteer tourists participating in the World-Wide Opportunities on Organic Farms (WWOOF) network from the perspective of WWOOF farm hosts in Hawai'i. Through an ethnographic examination of farm hosts' perspectives, the economic and non-economic costs and benefits of hosting farm volunteer tourists are examined. It illustrates how the off-setting of labour costs are juxtaposed against the economic cost of lost productivity and accommodation expenses. Farm hosts also report non-economic benefits, including spiritual development, interpersonal exchange relationships and shared lifestyles, while non-economic costs pertained to loss of privacy, and the need to engage in the emotional labour associated with farm hosting.     

Learning outcomes of entrepreneurship education: Entrepreneurship education for knowing,doing, being,and living together

The authors try to identify the learning outcomes of entrepreneurship education at high schools. The statistical population of this research consists of vocational high school students in Tehran, Iran. The findings showed that learning outcomes for knowing are more than the aspects of doing, being, and living together. More specifically, 65 learning outcomes of entrepreneurship education have been identified in four pillars. This study presents a comprehensive framework for the philosophy of entrepreneurship education.     

A model for holding strategy in public transit systems with real-time information

Holding strategies are among the most commonly used operation-control strategies in public transit systems. These strategies are most effective when used to control services characterized by high frequency. In this paper, a mathematical model for a holding control strategy is developed. Particularly, this model uses real-time information of locations of buses along a specified route. The objective of the developed model is to minimize the waiting time of passengers at all stops on that route. Furthermore, the model developed in this paper is characterized by the flexibility of adopting situations where bus occupancy could be either high, or low. A heuristic is developed to circumvent the complexity of the solution for the problem described. Numerical examples and computational results are presented and discussed.