Designing awareness campaigns to counter human trafficking: An analytic approach

Human trafficking – the trade of persons for the gain of others – is a pervasive societal issue. Ongoing trafficking recruitment calls for targeted prevention strategies for individuals and communities at risk. Awareness campaigns, arguably the most common form of trafficking prevention, are intended to alert individuals to the tactics used by traffickers and provide them with practical strategies to avoid deception and exploitation. However there is a shortage of technical solutions regarding the analysis, impact assessment, and evaluation of alternatives related to implementing awareness campaigns. We present a resource allocation model that can be used to determine the allocation of funds that maximizes increases in trafficking awareness among at-risk populations. We apply this model to determine the allocation of a limited budget among different types of prevention programs in at-risk populations in Nepal. For each awareness campaign, we estimate a production function that relates the amount invested to the associated change in awareness. When allocating limited resources, decision makers must balance competing interests, and we illustrate the impact of three allocation policies on trafficking awareness. The model presented in this article is a first attempt to help decision makers evaluate how to allocate funds in the context of trafficking awareness.     

Adverse selection,commitment and exhaustible resource taxation

This paper studies the contractual relationship between a government and a firm in charge of the extraction of an exhaustible resource. Governments design taxation scheme to capture resource rent and they usually propose contracts with limited duration and possess less information on resources than the extractive firms do. This article investigates how information asymmetry on costs and an inability to commit to long-term contracts affect tax revenue and the extraction path. This study gives several unconventional results. First, when information asymmetry exists, the inability to commit does not necessarily lower tax revenues. Second, under asymmetric information without commitment, an efficient firm may produce during the first period more or less than under symmetric information. Hence, the inability to commit has an ambiguous effect on the exhaustion date. Third, the modified Hotelling's rule is such that an increase in the discount factor does not necessarily reduce the first-period extraction.     

Travel deterrents to regional destinations

Travel motivation is prevalent in the tourism literature. Very few studies however have examined travel deterrents to visiting popular destinations. This study approaches from travel motivation understand why tourists do not visit regional destinations and from tourists’ background to identify who do not visit these destinations with a focus on well-known regional destinations in Australia. The results show that convenience to the destinations, timing, motivation and tourist attractions are the major deterrents, and the level of these deterrents is dependent upon some of the demographic background of tourists. The findings and implications conclude this paper.     

Using deep learning and visual analytics to explore hotel reviews and responses

This study aims to use computational linguistics, visual analytics, and deep learning techniques to analyze hotel reviews and responses collected on TripAdvisor and to identify response strategies. To this end, we collected and analyzed 113,685 hotel reviews and responses and their semantic and syntactic relations. We are among the first to use visual analytics and deep learning-based natural language processing to empirically identify managerial responses. The empirical results indicate that our proposed multi-feature fusion, convolutional neural network model can make different types of data complement each other, thereby outperforming the comparisons. The visualization results can also be used to improve the performance of the proposed model and provide insights into response strategies, which further shows the theoretical and technical contributions of this study.     

Development of a conflict management model as a tool for improved project outcomes in community based tourism

Community based tourism (CBT) offers many opportunities, however, conflict frequently occurs while developing CBT in communities around the world. Despite conflict limiting the potential of CBT, conflict management in CBT has not previously been systematically studied. To investigate conflict and conflict management during CBT, a linear model of conflict management was developed and subsequently tested through a three phase qualitative process: analysis of CBT literature, online international survey of 29 CBT stakeholders, and in-depth interviews of 23 CBT stakeholders. Results endorse the proposed linear model of ‘conflict themes’: an ‘instance’ of conflict, followed by a ‘response’, which results in an ‘impact’. The rich data highlights the complexity involved, which was incorporated into the expanded model with three additional scenarios: ‘new conflict develops’, ‘interrelated conflict themes’, and ‘simultaneous conflict themes’. The complete Conflict Management Model provides stakeholders with a tool to address conflict, thereby improving the outcomes of CBT.     

Seasonality and regional productivity in the Spanish accommodation sector

This study quantifies the impact of peak demand and seasonality on regional productivity in the Spanish accommodation sector. We then identify factors affecting seasonal fluctuations and their relative contributions to regional variations in seasonality. The results show that demand for accommodation in the peak season mainly determines productivity. Thus, improving a region's attractiveness as a tourist destination is most effective for tourism-based regional development. In addition, reducing seasonal variations has a non-negligible impact on productivity. A decomposition analysis reveals that providing climate-independent tourist attractions and attracting business travelers are effective in reducing seasonality.     

The effects of board structure on corporate performance: Evidence from East African frontier markets

The effectiveness of the well-known corporate governance practices may not be universal due to fundamental differences in the environments under which firms operate. By using hand-collected data from all the non-financial firms listed on the unexplored East African frontier markets (i.e., Kenya, Tanzania and Uganda), we examine the effect of board characteristics on the performance of firms. Our results show that board size has a negative and significant effect on firm performance. The presences of foreigners and civil servants on the board play positive roles on financial performance, where the agency and resource dependence theories apply. Further, we find that board members with higher education also contribute to firm performance. These findings still hold when we consider the 2008–2009 financial crisis period. Overall, we show that in a business climate where ownership is largely dominated by few shareholders, the conventional governance mechanisms do not work effectively.     

Intermediate units in multinational corporations: A resource dependency view on coordinative versus entrepreneurial roles

Due to the dispersion of headquarters’ activities across organizational and geographical boundaries, intermediate units (IUs) are emerging as a key actor of international business. IUs are intermediate structural layers between headquarters (HQ) and local subsidiaries with specific HQ responsibilities. Our study relies on original data of 67 IUs and, taking on a Resource Dependence approach, explores empirically the two HQ roles attributed to IUs: coordinative versus entrepreneurial. According to our results, the main differences between both roles relate to external network embeddedness, internal network position and autonomy. We argue that these differences arise from the dominant sources of power in each role. These findings have signi?cant relevance for theory development and managerial practice as we provide a starting point for understanding the dispersion of complex HQ systems as well as how those systems are discharged and add value.     

The effects of tourism on HSR: Spanish empirical evidence derived from a multi-criteria corridor selection methodology

The exorbitant cost of new High-Speed Rail (HSR) lines requires a selection methodology to define which HSR corridors within a network should be built first, and the most suitable evaluation tool appears to be the multi-criteria approach. In any corridor-ranking methodology, and especially in countries with high tourism attractiveness, tourism impacts on HSR should be considered as a variable.In addition to economic geography and destination choice models, the current literature on tourism demand is dominated by econometric models using a single-equation time-series based approach. However little research has been done so far on methodologies to rank HSR corridors taking into account the tourism variable. In 2014, a ranking methodology developed by Todorovich and Hagler was validated using the current Spanish HSR network. Twelve variables were used to create an index to assign scores to the city pairs, but tourism was not included as a variable. The findings showed the consistency of the model for ranking pairs mainly in the top O–D relations; however the tool failed to discriminate clearly between secondary groups of corridors.The aim of this paper is to assess empirically the positive effect of tourism on HSR and to enhance the abovementioned ranking tool with a tourism database. The new methodology is tested by application to 1176 city pairs in Spain, and the results clearly show that the implementation of a tourism variable helps discriminate between secondary groups of corridors and offers a more effective approach for determining the implications of tourism on HSR.     

A model for planning locations of temporary distribution facilities for emergency response

We propose a network flow model for dynamic selection of temporary distribution facilities and allocation of resources for emergency response planning. The model analyzes the transfer of excess resources between temporary facilities operating in different time periods in order to reduce deprivation. Numerical analysis shows that the location of temporary facilities is determined by the demand and supply points. This work contributes to the emergency response planning that requires a quick response for the supply of relief materials immediately after a disaster hits a particular area.