Big data in smart tourism: challenges,issues and opportunities

In the era of digital transformation, Big Data have assumed a crucial role in changing the global travel and providing significant challenges and opportunities for established companies, as well as new entrants into the tourism industry. All these companies can get valuable information on Big Data for predicting tourist demand, enabling better decision-making, managing knowledge flows and interaction with customers, and providing the best service in a more efficient and effective way. This can result in improved productivity, increased customer satisfaction, personalized marketing campaigns, and more efficient operations. However, open research issues about the role of Big Data in the tourism industry can be still recognized. With these premises, this Editorial aims to present the articles included in the special issue of Current Issues in Tourism titled ‘Big data in smart tourism: challenges, issues and opportunities’, which has called for research contributing to the recent debates on the implications and challenges of the adoption of Big Data to improve the competitiveness of tourism destinations and companies. Main topics considered by the accepted articles include a literature review proposing a novel theoretical investigative frameworks, metrics and critical dimensions, and empirical investigations of the use of Big Data in different tourism contexts.     

Optimal farm size in an uncertain land market: the case of Kyrgyz Republic

This article applies a real options model to the problem of land development. Making use of the 1998–2001 Kyrgyz Household Budget Survey, we show that when the hypothesis of decreasing return to scale holds, the relation between the threshold value of revenue per hectare and the amount of land cultivated is positive. In addition, the relation between the threshold and the amount of land owned is positive in the case of continuous supply of land and negative when there is discontinuous supply of land. The direct consequence is that, in the first case, smaller farms will be more willing to rent land and exercise the option where, in the second case, larger farms will exercise first. The results suggest three main conclusions: (i) the combination of uncertainty and irreversibility is an important factor in land development decisions, (ii) farmer behavior is consistent with the continuous profit maximization model, and (iii) farming unit revenue tends to be positively related to farm size, once uncertainty is properly accounted for.     

Conic quantization: stochastic volatility and market implied liquidity

Market implied liquidity links the pricing of European options under stochastic volatility with the Conic Finance theory of two prices     

Systematic sampling and real exchange rates

Systematic Sampling and Real Exchange Rates. — Four major real bilateral exchange rates are shown to be well characterized by nonlinear stationary models over the recent float. Using Monte Carlo methods, this paper examines the effects of systematic sampling on the behaviour of real exchange rates and shows that: systematic sampling reduces significantly nonlinearity in real exchange rates and affects their lag structure; given a certain span, the frequency of the data set becomes crucial for detecting mean reversion in real exchange rates once the analysis is switched from a linear to a nonlinear model. Monte Carlo simulations also suggest that the parameter governing the speed of nonlinear mean reversion may be upward biased.     

Automobile replacement: a dynamic structural approach

This article specifies and estimates a structural dynamic model of consumer demand for new and used durable goods. Its primary contribution is to provide an explicit estimation procedure for transaction costs. Identification of transaction costs is achieved from the variation in the share of consumers choosing to hold a given car type each period, and from the share of consumers choosing to purchase the same car type that period. Specifically, I estimate a random‐coefficient discrete‐choice model that incorporates a dynamic optimal stopping problem. I apply this model to evaluate the impact of scrappage subsidies on the Italian automobile market.     

The changing pattern of foreign trade specialization in Indian manufacturing

This paper examines the pattern of international trade specializationin Indian manufacturing since the mid-1980s by using data ontrade flows. Low-technology sectors still dominate the categoriesfor which India exhibits the largest degree of trade specialization.By contrast, high-technology sectors are prevalent among thecategories for which India is import-dependent. Significantly,India has experienced an improvement in the degree of specializationin some of the most dynamic sectors of world trade.     

Followers' entry timing: evidence from the Spanish banking sector after deregulation

Much of the literature dedicated to the analysis of entry timing decisions has been devoted to the study of their consequences in terms of performance. However, only a limited amount of effort has been dedicated to analyzing the factors that determine these decisions. In addition, previous papers have centered their efforts on the product dimension, paying no attention to entry into new geographical markets. This paper departs from previous works in this respect and extends the entry timing literature through a consideration of the geographical side of entry. Our analysis shows that organizational size, organizational competence, and organizational experience appear as key factors when explaining the pattern of geographic diversification. Our results also indicate that diversification takes place sequentially, first proceeding to closer locations, then occupying markets further from the origin. Copyright © 2002 John Wiley & Sons, Ltd.     

Multipoint competition,strategic similarity and entry into geographic markets

The objective of this study is to integrate both multimarket contact and strategic similarity in the analysis of entry decisions. We also analyze the role of the reciprocity of contacts, market concentration, and coordination mechanisms at moderating the relationship. Our hypotheses are tested through the analysis of entry behavior into new geographical markets in the Spanish savings bank market. Interestingly, our results offer an opportunity of conciliating conflicting evidence in both the multimarket–mutual forbearance and the heterogeneity–rivalry literatures and offer further support to the U‐inverted influence of multimarket contact on entry. Given the coordination assumption implicit in the theory and the possible presence of unobservable variables, we also offer a method to cope with the common‐actor problem. Copyright © 2006 John Wiley & Sons, Ltd.     

PROPOSAL FOR A NEW MEASURE OF CORRUPTION, ILLUSTRATED WITH ITALIAN DATA

Standard cross-national measures of corruption are assembled through surveys. We propose a novel alternative objective measure that consists of the difference between a measure of the physical quantities of public infrastructure and the cumulative price government pays for public capital stocks. Where the difference is larger between the monies spent and the existing physical infrastructure, more money is being siphoned off to mismanagement, fraud, bribes, kickbacks, and embezzlement; that is, corruption is greater. We create this measure for Italy's 95 provinces and 20 regions as of the mid-1990s, controlling at the regional level for possible differences in the costs of public construction.     

Nonlinearity in Deviations from Uncovered Interest Parity: An Explanation of the Forward Bias Puzzle

We provide empirical evidence that deviations from the uncovered interest rate parity (UIP) condition display significant nonlinearities, consistent with theories based on transactions costs or limits to speculation. This evidence suggests that the forward bias documented in the literature may be less indicative of major market inefficiencies than previously thought. Monte Carlo experiments allow us to reconcile these results with the large empirical literature on the forward bias puzzle since we show that, if the true process of UIP deviations were of the nonlinear form we consider, estimation of conventional spot-forward regressions would generate the anomalies documented in previous research.This paper was partly written while Lucio Sarno was a Visiting Scholar at the International Monetary Fund. Financial support from the Economic and Social Research Council (Grant No. RES-000-22-0404) is gratefully acknowledged. The authors are indebted for useful conversations or constructive comments to Josef Zechner (editor), three anonymous referees, Ulf Axelson, Magnus Dahlquist, Paul De Grauwe, Hans Dewachter, John Driffill, Bob Flood, Gordon Gemmill, Campbell Harvey, Peter Kenen, Rich Lyons, Angelo Melino, Chris Neely, Anthony Neuberger, Carol Osler, David Peel, Dagfinn Rime, Piet Sercu, Per Str?mberg, Shinji Takagi, Gabriel Talmain, Mark Taylor, Timo Ter?svirta, Dan Thornton, Shang-Jin Wei, Mike Wickens and Mark Wohar, as well as to participants at the 2005 European Finance Association Annual Conference, Moscow; 2004 Society of Nonlinear Dynamics and Econometrics Annual Conference, Federal Reserve Bank of Atlanta; the 2004 European Financial Management Association Conference, Basel; and seminars at the International Monetary Fund, Swedish Institute for Financial Research, Central Bank of Norway, University of Oxford, Catholic University of Leuven, University ofWarwick, Chinese University of Hong Kong, York University, University of Exeter, University of Kent, and University of Edinburgh. The authors alone are responsible for any errors that may remain and for the views expressed in the paper.