Destination Stakeholders' Perceptions of Volunteer Tourism: An Equity Theory Approach

This study explores destination stakeholders' perceptions of volunteer tourism (VT) using equity theory. In this paper, 26 semi‐structured interviews were conducted to understand individuals' needs, motivations, expectations and their assessments of inputs and outcomes. Equity theory sheds light on the micro‐level of interaction between residents and volunteers and demonstrates why and how residents of Cusco (Peru) with an active role in VT develop certain perceptions in direct encounters with volunteer tourists. The data reveal how perceptions differ according to the respondents' social roles within VT. Heterogeneity, dynamism and a fluctuation between materialities and affection are discussed as important outcomes of these interactions. Copyright © 2014 John Wiley & Sons, Ltd.     

Entrepreneurship and Independent Professionals: Social and Economic Logics

This study discusses stereotypes of entrepreneurship by looking at the overlapping areas of entrepreneurship, self-employment and professions. Professions are part of the category of self-employment and the study presents empirical findings drawn from a unique empirical dataset from Finland: a survey (N?=?733) including freelance journalists, translators, interpreters and artists at the blurred boundaries between waged work and entrepreneurship. Findings reveal that the professions are clearly different and the manifestations of entrepreneurship vary, reflecting the work and the labor market situation within the profession. Life and work situations of liberal professions cannot be interpreted in simple black-and-white schemes of winners and losers. Instead, many different socioeconomic situations can be found ‘in between,’ which are driven by different social logics. For entrepreneurship research, the study opens up new avenues by taking us beyond the push-pull dichotomy, which over-simplifies the decision to enter self-employment. The term entrepreneurship is often used in an undifferentiated way, and it easily generates myths and stereotypes which are challenged by the study. A narrower and more realistic view shows that there are diverse agents under the flag of entrepreneurship, who are usually not regarded as core entrepreneurs although they exist in everyday life.     

Large panels with common factors and spatial correlation

This paper considers methods for estimating the slope coefficients in large panel data models that are robust to the presence of various forms of error cross-section dependence. It introduces a general framework where error cross-section dependence may arise because of unobserved common effects and/or error spill-over effects due to spatial or other forms of local dependencies. Initially, this paper focuses on a panel regression model where the idiosyncratic errors are spatially dependent and possibly serially correlated, and derives the asymptotic distributions of the mean group and pooled estimators under heterogeneous and homogeneous slope coefficients, and for these estimators proposes non-parametric variance matrix estimators. The paper then considers the more general case of a panel data model with a multifactor error structure and spatial error correlations. Under this framework, the Common Correlated Effects (CCE) estimator, recently advanced by Pesaran (2006), continues to yield estimates of the slope coefficients that are consistent and asymptotically normal. Small sample properties of the estimators under various patterns of cross-section dependence, including spatial forms, are investigated by Monte Carlo experiments. Results show that the CCE approach works well in the presence of weak and/or strong cross-sectionally correlated errors.     

Enabling and inhibiting factors in adoption of Electronic-Reverse auctions: A longitudinal case study in grocery retailing

Abstract

The paper aims to explore the factors that enable or inhibit the use of Electronic-Reverse Auctions (E-RAs) in the buying process of a large food retail organization, through a category management perspective. Using a case-study analysis based on in-depth interviews, examination of internal documents, simulation and direct observation of some E-RAs, we studied the experience of an Italian-based retailer conducting E-RAs during a two-year period. This approach enabled us to propose an E-RAs development model in retail buying groups, discussing enabling and inhibiting factors such as product, market, organizational and strategic factors. Propositions are developed to stimulate thought and provide guidance for future research.     

Revising the Corporate Social Performance Model – Towards Knowledge Creation for Sustainable Development

The objective of this paper is to offer a revision of the corporate social performance (CSP) model. CSP exemplifies how corporate social responsibility translates into an organization's practice by focusing on three key features of performance: principles, processes and outcomes. However, the development of the model has not kept pace with the literature on social and environmental responsibility. This study builds on an argument that if corporate social responsibility in general – in which CSP plays an important role – is to respond to the challenges of sustainable development, the CSP of businesses could be more profoundly planned in order to design knowledge outcomes that contribute to meeting those challenges. The paper thus answers the recent call for the development of a CSP model by revising some of the key elements in the existing model and also by adding a knowledge creation dimension. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment     

Spatial stochastic frontier models: controlling spatial global and local heterogeneity

In the last decade special attention has been focused on estimating a firm’s efficiency and productivity; Stochastic Frontier Analysis (SFA) has been one of the most used techniques that allows the separation of inefficiency from stochastic noise, assuming homogeneous technology is available to all producers and that there is independence between observations. However, this second assumption is violated data are spatial auto-correlated, thus biasing statistical inference. Attention has, therefore, shifted to models that allow the controlling of heterogeneity introducing, in the model or in the error term, contextual variables correlated with inefficiency. In our paper we propose viewing the spatial external factors (natural or artificial) in a new way: instead of identifying ex-ante a multitude of determinants, often statistically and economically difficult to detect, we suggested using an original methodology that, following a classical SFA approach, splits efficiency into three components: the first one is linked to the spatial lag, the second one to the DMU’s specificities, and the third to the error term. Finally, we tested our method using simulated data and examined the Italian wine sector, testing the ability to control spatial, global and local heterogeneity.     

Option Pricing in Stochastic Volatility Models of the Ornstein-Uhlenbeck type

Stochastic volatility models of the Ornstein-Uhlenbeck type possess authentic capability of capturing some stylized features of financial time series. In this work we investigate this class of models from the viewpoint of derivative asset analysis. We discuss topics related to the incompleteness of this type of markets. In particular, for structure preserving martingale measures, we derive the price of simple European-style contracts in closed form. Furthermore, the range of viable prices is determined and an empirical application is presented.     

A multivariate jump-driven financial asset model

We discuss a Lévy multivariate model for financial assets which incorporates jumps, skewness, kurtosis and stochastic volatility. We use it to describe the behaviour of a series of stocks or indexes and to study a multi-firm, value-based default model. Starting from an independent Brownian world, we introduce jumps and other deviations from normality, including non-Gaussian dependence. We use a stochastic time-change technique and provide the details for a Gamma change. The main feature of the model is the fact that—opposite to other, non-jointly Gaussian settings—its risk-neutral dependence can be calibrated from univariate derivative prices, providing a surprisingly good fit.     

An integrated production–distribution model for the dynamic location and allocation problem with safety stock optimization

The design and management of a multi-stage production–distribution system is one of the most critical problems in logistics and in facility management. Companies need to be able to evaluate and design different configurations for their logistic networks as quickly as possible. This means coordinating the entire supply chain effectively in order to minimize costs and simultaneously optimize facilities location, the allocation of customer demand to production/distribution centers, the inbound and outbound transportation activities, the product flows between production and/or warehousing facilities, the reverse logistics activities, etc.Full optimization of supply chain is achieved by integrating strategic, tactical, and operational decision-making in terms of the design, management, and control of activities. The cost-based and mixed-integer programming model presented in this study has been developed to support management in making the following decisions: the number of facilities (e.g. warehousing systems, distribution centers), the choice of their locations and the assignment of customer demand to them, and also incorporate tactical decisions regarding inventory control, production rates, and service-level determination in a stochastic environment. This paper presents an original model for the dynamic location–allocation problem with control of customer service level and safety stock optimization. An experimental analysis identifies the most critical factors affecting the logistics cost, and to finish, an industrial application is illustrated demonstrating the effectiveness of the proposed optimization approach.