Investigating the key drivers of traveler loyalty in the airport lounge setting

This study intended to examine the structural relationships among functional congruity factors, delight, well-being perception, brand identification, and traveler satisfaction in the formation of air traveler loyalty for airline lounges. The survey sample consisted of 394 air travelers who visited an airline lounge in airport in the U.S. during the past six months. Structural equation modeling was used to test the conceptual model. Results of the structural equation modeling indicated that functional congruity of the physical environments and facilities were significantly and positively associated with delight, which in turn, affected air travelers’ perceived well-being and satisfaction level in the lounge. It was also found that well-being perception significantly and positively affected brand identification and satisfaction, and loyalty was a positive and significant function of satisfaction. The mediation test showed that delight and well-being perception were significant mediators in the proposed theoretical framework. Practical and theoretical implications are discussed.     

Capital City Museums and Tourism Flows: an Empirical Study of the Museum of New Zealand Te Papa Tongarewa

This study uses time series analysis to explore the extent to which the opening of the Museum of New Zealand in 1998 contributed to tourism growth in the nation's capital, Wellington. With the use of a series of different measures for tourism and major events in the city, econometric regressions are undertaken to better understand the relationship between visitors to the museum and tourism growth in the city's short‐term commercial accommodation sector. The findings are consistent with the museum having a positive impact on tourist arrivals and overnight stays. These results contribute valuable empirical evidence of the positive role of museums in attracting tourists to urban centres. Copyright © 2012 John Wiley & Sons, Ltd.     

Delta Boosting Machine with Application to General Insurance

In this article, we introduce Delta Boosting (DB) as a new member of the boosting family. Similar to the popular Gradient Boosting (GB), this new member is presented as a forward stagewise additive model that attempts to reduce the loss at each iteration by sequentially fitting a simple base learner to complement the running predictions. Instead of relying on the negative gradient, as is the case for GB, DB adopts a new measure called delta as the basis. Delta is defined as the loss minimizer at an observation level. We also show that DB is the optimal boosting member for a wide range of loss functions. The optimality is a consequence of DB solving for the split and adjustment simultaneously to maximize loss reduction at each iteration. In addition, we introduce an asymptotic version of DB that works well for all twice-differentiable strictly convex loss functions. This asymptotic behavior does not depend on the number of observations, but rather on a high number of iterations that can be augmented through common regularization techniques. We show that the basis in the asymptotic extension differs from the basis in GB only by a multiple of the second derivative of the log-likelihood. The multiple is considered to be a correction factor, one that corrects the bias toward the observations with high second derivatives in GB. When negative log-likelihood is used as the loss function, this correction can be interpreted as a credibility adjustment for the process variance. Simulation studies and real data application we conducted suggest that DB is a significant improvement over GB. The performance of the asymptotic version is less dramatic, but the improvement is still compelling. Like GB, DB provides a high transparency to users, and we can review the marginal influence of variables through relative importance charts and the partial dependence plots. We can also assess the overall model performance through evaluating the losses, lifts, and double lifts on the holdout sample.     

Statistically based quarterly earnings expectation models for nonseasonal firms

We present empirical evidence on the relative predictive power of statistically based quarterly earnings expectation models for firms that are characterized as nonseasonal in nature. We are particularly interested in nonseasonal firms for two reasons. First, it appears that a sizable and growing percentage of firms exhibit quarterly earnings patterns that are clearly nonseasonal in nature. We present new evidence that is consistent with this trend. Specifically, 36% of our sample firms (n = 296) are nonseasonal compared to 12% reported in Lorek and Bathke (J Acc Res 22:369–379, 1984) (n = 29); 17% in Brown and Han (J Acc Res 38:149–164, 2000) (n = 155); and 28.2% in Bathke et al. (J Business Inquiry 5:39–49, 2006) (n = 167). Second, we also find that 43.6% of the nonseasonal firms in our sample have no analyst coverage. Therefore, interest in the predictive ability of statistically based models for such firms is greatly enhanced. Our predictive findings indicate that the random walk model provides significantly more accurate pooled, one-step ahead quarterly earnings predictions across 40 quarters in the 1994–2003 holdout period than the first-order autoregressive model popularized in the literature. We attribute the superior performance of the random walk model to at least three contributing factors: (1) its parsimonious nature; (2) the reduced levels of autocorrelation observed in our quarterly earnings data relative to previous work; and (3) a significantly greater frequency of loss quarters evidenced by nonseasonal versus seasonal firms.

Ethical challenges in corporate-shareholder and investor relations: Using the Value Exchange Model to analyze and respond

Shareholder and investor relations, and the closely related area of corporate governance have been the arenas of much dispute, much of which has not been confined to practical financial matters. Ethical challenges have come as well from persons and groups with widely differing value systems. This paper presents the Corporate Value Exchange Model (CVE) as a framework for analyzing the corporate-shareholder and corporate-investor relationships, and for formulating decisions that can respond ethically to these groups without subordinating the interests of other constituents.Richard Lee Miller is Associate Professor of Management and Graduate Faculty at the University of Dayton. He has numerous articles published in journals and proceedings, the most recent of which have been on various applications of the value exchange theory.     

Residential energy consumption: Models of consumer behavior and their implications for rate design

This article illustrates the use of bounded rationality concepts in policy analysis. Specifically, we discuss reasons why we expect residential energy consumption to deviate from the utility-maximizing level when multiple-tier rate structures are in use. Then we construct a simple, predictive model of boundedly-rational household behavior which can be tested against a conventional utility-maximization model. Our model predicts that households will over-consume when facing increasing tier rates and under-consume when facing decreasing tier rates.We then discuss some of the policy consequences of this behavior. One consequence, given the kind of increasing tier structures that are common in the United States, is that the magnitude of the overconsumption for a household is plausibly 10 percent in the short-run and 50 percent in the long-run. Another consequence, if policy is constrained to increasing tier rates with constant total consumer subsidy, is that the most efficient of these is likely to have a lower first-tier price and quantity than would be the case without bounded rationality. Finally, we note that both the bounded-rationality model and the utility-maximizing model support the use of a two-part tariff rate structure over tiered rate structures for residential consumers.

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Energieverbrauch privater Haushalte: Modelle des Verbraucherverhaltens und ihre Implikationen für die Tarifgestaltung

Zusammenfassung Der vorliegende Beitrag wendet das Konzept eingeschränkter Rationalität auf energiepolitische Zusammenhänge an. Es wird insbesondere erörtert, wie sich der Energieverbrauch privater Haushalte unter der Annahme eingeschränkter Rationalität von dem unterscheidet, wie er sich bei vollständiger Rationalität (Nutzenmaximierung) ergeben würde — vorausgesetzt, es gilt ein mehrfach gestaffelter Tarif. Die Autoren stellen ein einfaches Vorhersagemodell beschränkt rationalen Haushaltsverhaltens vor, das gegen ein konventionelles Nutzen-Maximierungsmodell getestet werden kann. Nach diesem Modell werden Haushalte bei progressiv gestaffelten Tarifen zu Überkonsum und bei degressiv gestaffelten Tarifen zu Unterkonsum tendieren.Anschließend werden einige politische Konsequenzen dieses Verhaltens diskutiert. Bei der Form progressiv gestaffelter Tarife, die in den USA üblich ist, ist eine Konsequenz, daß die Größenordnung des Mehrverbrauchs eines Haushaltes bei kurzfristiger Betrachtung bei 10%, bei längerfristiger Betrachtung bei 50% liegt. Wenn sich die Tarifpolitik auf progressiv gestaffelte Stufentarife mit konstanter Gesamtversorgung beschränkt, ist eine andere Konsequenz, daß die wirkungsvollste Tarifgestaltung bei beschränkter Rationalität einen niedrigeren Eingangstarif und eine niedrige Eingangsmenge fordert. Schließlich wird ausgeführt, daß sowohl das Modell eingeschränkter Rationalität wie auch das Nutzen-Maximierungs-Modell für einen zweistufigen Tarif anstelle eines mehrfach gestaffelten Tarifs spricht.

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Lee S. Friedman is Professor of Public Policy in the Graduate School of Public Policy, University of California at Berkeley, Berkeley, CA 94720, USA. Karl Hausker is a staff Economist at the U.S. Senate Energy and Natural Resources Committee, Dirksen Senate Office Building, Room 358, Washington, D.C. 20510, USA.The authors are grateful to the University of California Energy Research Group for its support of this research. They would like to thank Suzanne Scotchmer, the Editors, and two anonymous referees for their helpful comments.     

The relationship among competitive advantage,catch-up,and linkage effects: a comparative study on ICT industry between South Korea and India

Service Business - This study examined the relationship among competitive advantage, catch-up, and linkage effects using Input–Output (IO) data of the information and communications...     

Anti-consumption and brand avoidance

This article focuses on a particular form of anti-consumption; brand avoidance. Specifically, it explores why people may avoid some brands, even when their financial circumstances allow them the option to purchase. The authors use qualitative data to develop a conceptual framework that helps clarify why consumers avoid certain brands. This study reveals three types of brand avoidance: experiential, identity and moral brand avoidance. Experiential brand avoidance occurs because of negative first hand consumption experiences that lead to unmet expectations. Identity avoidance develops when the brand image is symbolically incongruent with the individual's identity. Moral avoidance arises when the consumer's ideological beliefs clash with certain brand values or associations, particularly when the consumer is concerned about the negative impact of a brand on society. Finally, this study highlights potential strategies that managers could implement to deal with brand avoidance.